Interactions between temperature and nutrients across levels of ecological organization.

PubMed

Cross, Wyatt F; Hood, James M; Benstead, Jonathan P; Huryn, Alexander D; Nelson, Daniel

2015-03-01

Temperature and nutrient availability play key roles in controlling the pathways and rates at which energy and materials move through ecosystems. These factors have also changed dramatically on Earth over the past century as human activities have intensified. Although significant effort has been devoted to understanding the role of temperature and nutrients in isolation, less is known about how these two factors interact to influence ecological processes. Recent advances in ecological stoichiometry and metabolic ecology provide a useful framework for making progress in this area, but conceptual synthesis and review are needed to help catalyze additional research. Here, we examine known and potential interactions between temperature and nutrients from a variety of physiological, community, and ecosystem perspectives. We first review patterns at the level of the individual, focusing on four traits--growth, respiration, body size, and elemental content--that should theoretically govern how temperature and nutrients interact to influence higher levels of biological organization. We next explore the interactive effects of temperature and nutrients on populations, communities, and food webs by synthesizing information related to community size spectra, biomass distributions, and elemental composition. We use metabolic theory to make predictions about how population-level secondary production should respond to interactions between temperature and resource supply, setting up qualitative predictions about the flows of energy and materials through metazoan food webs. Last, we examine how temperature-nutrient interactions influence processes at the whole-ecosystem level, focusing on apparent vs. intrinsic activation energies of ecosystem processes, how to represent temperature-nutrient interactions in ecosystem models, and patterns with respect to nutrient uptake and organic matter decomposition. We conclude that a better understanding of interactions between temperature and nutrients will be critical for developing realistic predictions about ecological responses to multiple, simultaneous drivers of global change, including climate warming and elevated nutrient supply. © 2014 John Wiley & Sons Ltd.

Theoretical branching ratios for the 5I7 to 5I7 levels of Ho(3+) in the garnets A3B2C3O12 (A = Y,La,Lu,Gd; B = Al,Lu,Sc,Ga; C = Al,Ga)

NASA Technical Reports Server (NTRS)

Filer, Elizabeth D.; Morrison, Clyde A.; Turner, Gregory A.; Barnes, Norman P.

1991-01-01

Results are reported from an experimental study investigating triply ionized holmium in 10 garnets using the point-change model to predict theoretical energy levels and temperature-dependent branching ratios for the 5I7 to 5I8 manifolds for temperatures between 50 and 400 K. Plots were made for the largest lines at 300 K. YScAG was plotted twice, once for each set of X-ray data available. Energy levels are predicted based on theoretical crystal-field parameters, and good agreement to experiment is found. It is suggested that the present set of theoretical crystal-field parameters provides good estimates of the energy levels for the other hosts on which there are no experimental optical data. X-ray and index-of-refraction data are used to evaluate the performance of 10 lasers via a quantum mechanical model to predict the position of the energy levels and the temperature-dependent branching rations of the 5I7 to 5I8 levels of holmium. The fractional population inversion required for threshold is also evaluated.

Experimental Analysis of Steel Beams Subjected to Fire Enhanced by Brillouin Scattering-Based Fiber Optic Sensor Data.

PubMed

Bao, Yi; Chen, Yizheng; Hoehler, Matthew S; Smith, Christopher M; Bundy, Matthew; Chen, Genda

2017-01-01

This paper presents high temperature measurements using a Brillouin scattering-based fiber optic sensor and the application of the measured temperatures and building code recommended material parameters into enhanced thermomechanical analysis of simply supported steel beams subjected to combined thermal and mechanical loading. The distributed temperature sensor captures detailed, nonuniform temperature distributions that are compared locally with thermocouple measurements with less than 4.7% average difference at 95% confidence level. The simulated strains and deflections are validated using measurements from a second distributed fiber optic (strain) sensor and two linear potentiometers, respectively. The results demonstrate that the temperature-dependent material properties specified in the four investigated building codes lead to strain predictions with less than 13% average error at 95% confidence level and that the Europe building code provided the best predictions. However, the implicit consideration of creep in Europe is insufficient when the beam temperature exceeds 800°C.

Exploring the importance of within-canopy spatial temperature variation on transpiration predictions

PubMed Central

Bauerle, William L.; Bowden, Joseph D.; Wang, G. Geoff; Shahba, Mohamed A.

2009-01-01

Models seldom consider the effect of leaf-level biochemical acclimation to temperature when scaling forest water use. Therefore, the dependence of transpiration on temperature acclimation was investigated at the within-crown scale in climatically contrasting genotypes of Acer rubrum L., cv. October Glory (OG) and Summer Red (SR). The effects of temperature acclimation on intracanopy gradients in transpiration over a range of realistic forest growth temperatures were also assessed by simulation. Physiological parameters were applied, with or without adjustment for temperature acclimation, to account for transpiration responses to growth temperature. Both types of parameterization were scaled up to stand transpiration (expressed per unit leaf area) with an individual tree model (MAESTRA) to assess how transpiration might be affected by spatial and temporal distributions of foliage properties. The MAESTRA model performed well, but its reproducibility was dependent on physiological parameters acclimated to daytime temperature. Concordance correlation coefficients between measured and predicted transpiration were higher (0.95 and 0.98 versus 0.87 and 0.96) when model parameters reflected acclimated growth temperature. In response to temperature increases, the southern genotype (SR) transpiration responded more than the northern (OG). Conditions of elevated long-term temperature acclimation further separate their transpiration differences. Results demonstrate the importance of accounting for leaf-level physiological adjustments that are sensitive to microclimate changes and the use of provenance-, ecotype-, and/or genotype-specific parameter sets, two components likely to improve the accuracy of site-level and ecosystem-level estimates of transpiration flux. PMID:19561047

Climate warming causes life-history evolution in a model for Atlantic cod (Gadus morhua).

PubMed

Holt, Rebecca E; Jørgensen, Christian

2014-01-01

Climate change influences the marine environment, with ocean warming being the foremost driving factor governing changes in the physiology and ecology of fish. At the individual level, increasing temperature influences bioenergetics and numerous physiological and life-history processes, which have consequences for the population level and beyond. We provide a state-dependent energy allocation model that predicts temperature-induced adaptations for life histories and behaviour for the North-East Arctic stock (NEA) of Atlantic cod (Gadus morhua) in response to climate warming. The key constraint is temperature-dependent respiratory physiology, and the model includes a number of trade-offs that reflect key physiological and ecological processes. Dynamic programming is used to find an evolutionarily optimal strategy of foraging and energy allocation that maximizes expected lifetime reproductive output given constraints from physiology and ecology. The optimal strategy is then simulated in a population, where survival, foraging behaviour, growth, maturation and reproduction emerge. Using current forcing, the model reproduces patterns of growth, size-at-age, maturation, gonad production and natural mortality for NEA cod. The predicted climate responses are positive for this stock; under a 2°C warming, the model predicted increased growth rates and a larger asymptotic size. Maturation age was unaffected, but gonad weight was predicted to more than double. Predictions for a wider range of temperatures, from 2 to 7°C, show that temperature responses were gradual; fish were predicted to grow faster and increase reproductive investment at higher temperatures. An emergent pattern of higher risk acceptance and increased foraging behaviour was also predicted. Our results provide important insight into the effects of climate warming on NEA cod by revealing the underlying mechanisms and drivers of change. We show how temperature-induced adaptations of behaviour and several life-history traits are not only mediated by physiology but also by trade-offs with survival, which has consequences for conservation physiology.

Climate warming causes life-history evolution in a model for Atlantic cod (Gadus morhua)

PubMed Central

Holt, Rebecca E.; Jørgensen, Christian

2014-01-01

Climate change influences the marine environment, with ocean warming being the foremost driving factor governing changes in the physiology and ecology of fish. At the individual level, increasing temperature influences bioenergetics and numerous physiological and life-history processes, which have consequences for the population level and beyond. We provide a state-dependent energy allocation model that predicts temperature-induced adaptations for life histories and behaviour for the North-East Arctic stock (NEA) of Atlantic cod (Gadus morhua) in response to climate warming. The key constraint is temperature-dependent respiratory physiology, and the model includes a number of trade-offs that reflect key physiological and ecological processes. Dynamic programming is used to find an evolutionarily optimal strategy of foraging and energy allocation that maximizes expected lifetime reproductive output given constraints from physiology and ecology. The optimal strategy is then simulated in a population, where survival, foraging behaviour, growth, maturation and reproduction emerge. Using current forcing, the model reproduces patterns of growth, size-at-age, maturation, gonad production and natural mortality for NEA cod. The predicted climate responses are positive for this stock; under a 2°C warming, the model predicted increased growth rates and a larger asymptotic size. Maturation age was unaffected, but gonad weight was predicted to more than double. Predictions for a wider range of temperatures, from 2 to 7°C, show that temperature responses were gradual; fish were predicted to grow faster and increase reproductive investment at higher temperatures. An emergent pattern of higher risk acceptance and increased foraging behaviour was also predicted. Our results provide important insight into the effects of climate warming on NEA cod by revealing the underlying mechanisms and drivers of change. We show how temperature-induced adaptations of behaviour and several life-history traits are not only mediated by physiology but also by trade-offs with survival, which has consequences for conservation physiology. PMID:27293671

Comparing exposure metrics for classifying ‘dangerous heat’ in heat wave and health warning systems

PubMed Central

Zhang, Kai; Rood, Richard B.; Michailidis, George; Oswald, Evan M.; Schwartz, Joel D.; Zanobetti, Antonella; Ebi, Kristie L.; O’Neill, Marie S.

2012-01-01

Heat waves have been linked to excess mortality and morbidity, and are projected to increase in frequency and intensity with a warming climate. This study compares exposure metrics to trigger heat wave and health warning systems (HHWS), and introduces a novel multi-level hybrid clustering method to identify potential dangerously hot days. Two-level and three-level hybrid clustering analysis as well as common indices used to trigger HHWS, including spatial synoptic classification (SSC); and 90th, 95th, and 99th percentiles of minimum and relative minimum temperature (using a 10 day reference period), were calculated using a summertime weather dataset in Detroit from 1976 to 2006. The days classified as ‘hot’ with hybrid clustering analysis, SSC, minimum and relative minimum temperature methods differed by method type. SSC tended to include the days with, on average, 2.6 °C lower daily minimum temperature and 5.3 °C lower dew point than days identified by other methods. These metrics were evaluated by comparing their performance in predicting excess daily mortality. The 99th percentile of minimum temperature was generally the most predictive, followed by the three-level hybrid clustering method, the 95th percentile of minimum temperature, SSC and others. Our proposed clustering framework has more flexibility and requires less substantial meteorological prior information than the synoptic classification methods. Comparison of these metrics in predicting excess daily mortality suggests that metrics thought to better characterize physiological heat stress by considering several weather conditions simultaneously may not be the same metrics that are better at predicting heat-related mortality, which has significant implications in HHWSs. PMID:22673187

Groundwater-level prediction using multiple linear regression and artificial neural network techniques: a comparative assessment

NASA Astrophysics Data System (ADS)

Sahoo, Sasmita; Jha, Madan K.

2013-12-01

The potential of multiple linear regression (MLR) and artificial neural network (ANN) techniques in predicting transient water levels over a groundwater basin were compared. MLR and ANN modeling was carried out at 17 sites in Japan, considering all significant inputs: rainfall, ambient temperature, river stage, 11 seasonal dummy variables, and influential lags of rainfall, ambient temperature, river stage and groundwater level. Seventeen site-specific ANN models were developed, using multi-layer feed-forward neural networks trained with Levenberg-Marquardt backpropagation algorithms. The performance of the models was evaluated using statistical and graphical indicators. Comparison of the goodness-of-fit statistics of the MLR models with those of the ANN models indicated that there is better agreement between the ANN-predicted groundwater levels and the observed groundwater levels at all the sites, compared to the MLR. This finding was supported by the graphical indicators and the residual analysis. Thus, it is concluded that the ANN technique is superior to the MLR technique in predicting spatio-temporal distribution of groundwater levels in a basin. However, considering the practical advantages of the MLR technique, it is recommended as an alternative and cost-effective groundwater modeling tool.

Analysis of turbulence and surface growth models on the estimation of soot level in ethylene non-premixed flames

NASA Astrophysics Data System (ADS)

Yunardi, Y.; Munawar, Edi; Rinaldi, Wahyu; Razali, Asbar; Iskandar, Elwina; Fairweather, M.

2018-02-01

Soot prediction in a combustion system has become a subject of attention, as many factors influence its accuracy. An accurate temperature prediction will likely yield better soot predictions, since the inception, growth and destruction of the soot are affected by the temperature. This paper reported the study on the influences of turbulence closure and surface growth models on the prediction of soot levels in turbulent flames. The results demonstrated that a substantial distinction was observed in terms of temperature predictions derived using the k-ɛ and the Reynolds stress models, for the two ethylene flames studied here amongst the four types of surface growth rate model investigated, the assumption of the soot surface growth rate proportional to the particle number density, but independent on the surface area of soot particles, f ( A s ) = ρ N s , yields in closest agreement with the radial data. Without any adjustment to the constants in the surface growth term, other approaches where the surface growth directly proportional to the surface area and square root of surface area, f ( A s ) = A s and f ( A s ) = √ A s , result in an under- prediction of soot volume fraction. These results suggest that predictions of soot volume fraction are sensitive to the modelling of surface growth.

An evaluation of the use of remotely sensed parameters for prediction of incidence and risk associated with Vibrio parahaemolyticus in Gulf Coast oysters (Crassostrea virginica).

PubMed

Phillips, A M B; Depaola, A; Bowers, J; Ladner, S; Grimes, D J

2007-04-01

The U.S. Food and Drug Administration recently published a Vibrio parahaemolyticus risk assessment for consumption of raw oysters that predicts V. parahaemolyticus densities at harvest based on water temperature. We retrospectively compared archived remotely sensed measurements (sea surface temperature, chlorophyll, and turbidity) with previously published data from an environmental study of V. parahaemolyticus in Alabama oysters to assess the utility of the former data for predicting V. parahaemolyticus densities in oysters. Remotely sensed sea surface temperature correlated well with previous in situ measurements (R(2) = 0.86) of bottom water temperature, supporting the notion that remotely sensed sea surface temperature data are a sufficiently accurate substitute for direct measurement. Turbidity and chlorophyll levels were not determined in the previous study, but in comparison with the V. parahaemolyticus data, remotely sensed values for these parameters may explain some of the variation in V. parahaemolyticus levels. More accurate determination of these effects and the temporal and spatial variability of these parameters may further improve the accuracy of prediction models. To illustrate the utility of remotely sensed data as a basis for risk management, predictions based on the U.S. Food and Drug Administration V. parahaemolyticus risk assessment model were integrated with remotely sensed sea surface temperature data to display graphically variations in V. parahaemolyticus density in oysters associated with spatial variations in water temperature. We believe images such as these could be posted in near real time, and that the availability of such information in a user-friendly format could be the basis for timely and informed risk management decisions.

Experimental Analysis of Steel Beams Subjected to Fire Enhanced by Brillouin Scattering-Based Fiber Optic Sensor Data

PubMed Central

Bao, Yi; Chen, Yizheng; Hoehler, Matthew S.; Smith, Christopher M.; Bundy, Matthew; Chen, Genda

2016-01-01

This paper presents high temperature measurements using a Brillouin scattering-based fiber optic sensor and the application of the measured temperatures and building code recommended material parameters into enhanced thermomechanical analysis of simply supported steel beams subjected to combined thermal and mechanical loading. The distributed temperature sensor captures detailed, nonuniform temperature distributions that are compared locally with thermocouple measurements with less than 4.7% average difference at 95% confidence level. The simulated strains and deflections are validated using measurements from a second distributed fiber optic (strain) sensor and two linear potentiometers, respectively. The results demonstrate that the temperature-dependent material properties specified in the four investigated building codes lead to strain predictions with less than 13% average error at 95% confidence level and that the Europe building code provided the best predictions. However, the implicit consideration of creep in Europe is insufficient when the beam temperature exceeds 800°C. PMID:28239230

Predicting body temperature and activity of adult Polyommatus icarus using neural network models under current and projected climate scenarios.

PubMed

Howe, P D; Bryant, S R; Shreeve, T G

2007-10-01

We use field observations in two geographic regions within the British Isles and regression and neural network models to examine the relationship between microhabitat use, thoracic temperatures and activity in a widespread lycaenid butterfly, Polyommatus icarus. We also make predictions for future activity under climate change scenarios. Individuals from a univoltine northern population initiated flight with significantly lower thoracic temperatures than individuals from a bivoltine southern population. Activity is dependent on body temperature and neural network models of body temperature are better at predicting body temperature than generalized linear models. Neural network models of activity with a sole input of predicted body temperature (using weather and microclimate variables) are good predictors of observed activity and were better predictors than generalized linear models. By modelling activity under climate change scenarios for 2080 we predict differences in activity in relation to both regional differences of climate change and differing body temperature requirements for activity in different populations. Under average conditions for low-emission scenarios there will be little change in the activity of individuals from central-southern Britain and a reduction in northwest Scotland from 2003 activity levels. Under high-emission scenarios, flight-dependent activity in northwest Scotland will increase the greatest, despite smaller predicted increases in temperature and decreases in cloud cover. We suggest that neural network models are an effective way of predicting future activity in changing climates for microhabitat-specialist butterflies and that regional differences in the thermoregulatory response of populations will have profound effects on how they respond to climate change.

Comparison of adaptive neuro-fuzzy inference system (ANFIS) and Gaussian processes for machine learning (GPML) algorithms for the prediction of skin temperature in lower limb prostheses.

PubMed

Mathur, Neha; Glesk, Ivan; Buis, Arjan

2016-10-01

Monitoring of the interface temperature at skin level in lower-limb prosthesis is notoriously complicated. This is due to the flexible nature of the interface liners used impeding the required consistent positioning of the temperature sensors during donning and doffing. Predicting the in-socket residual limb temperature by monitoring the temperature between socket and liner rather than skin and liner could be an important step in alleviating complaints on increased temperature and perspiration in prosthetic sockets. In this work, we propose to implement an adaptive neuro fuzzy inference strategy (ANFIS) to predict the in-socket residual limb temperature. ANFIS belongs to the family of fused neuro fuzzy system in which the fuzzy system is incorporated in a framework which is adaptive in nature. The proposed method is compared to our earlier work using Gaussian processes for machine learning. By comparing the predicted and actual data, results indicate that both the modeling techniques have comparable performance metrics and can be efficiently used for non-invasive temperature monitoring. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Improving Simulations of Precipitation Phase and Snowpack at a Site Subject to Cold Air Intrusions: Snoqualmie Pass, WA

NASA Astrophysics Data System (ADS)

Wayand, N. E.; Stimberis, J.; Zagrodnik, J.; Mass, C.; Lundquist, J. D.

2016-12-01

Low-level cold air from eastern Washington state often flows westward through mountain passes in the Washington Cascades, creating localized inversions and locally reducing climatological temperatures. The persistence of this inversion during a frontal passage can result in complex patterns of snow and rain that are difficult to predict. Yet, these predictions are critical to support highway avalanche control, ski resort operations, and modeling of headwater snowpack storage. In this study we used observations of precipitation phase from a disdrometer and snow depth sensors across Snoqualmie Pass, WA, to evaluate surface-air-temperature-based and mesoscale-model-based predictions of precipitation phase during the anomalously warm 2014-2015 winter. The skill of surface-based methods was greatly improved by using air temperature from a nearby higher-elevation station, which was less impacted by low-level inversions. Alternatively, we found a hybrid method that combines surface-based predictions with output from the Weather Research and Forecasting mesoscale model to have improved skill over both parent models. These results suggest that prediction of precipitation phase in mountain passes can be improved by incorporating observations or models from above the surface layer.

Temperature distribution analysis of tissue water vaporization during microwave ablation: experiments and simulations.

PubMed

Ai, Haiming; Wu, Shuicai; Gao, Hongjian; Zhao, Lei; Yang, Chunlan; Zeng, Yi

2012-01-01

The temperature distribution in the region near a microwave antenna is a critical factor that affects the entire temperature field during microwave ablation of tissue. It is challenging to predict this distribution precisely, because the temperature in the near-antenna region varies greatly. The effects of water vaporisation and subsequent tissue carbonisation in an ex vivo porcine liver were therefore studied experimentally and in simulations. The enthalpy and high-temperature specific absorption rate (SAR) of liver tissues were calculated and incorporated into the simulation process. The accuracy of predictions for near-field temperatures in our simulations has reached the level where the average maximum error is less than 5°C. In addition, a modified thermal model that accounts for water vaporisation and the change in the SAR distribution pattern is proposed and validated with experiment. The results from this study may be useful in the clinical practice of microwave ablation and can be applied to predict the temperature field in surgical planning.

Simulations of surface winds at the Viking Lander sites using a one-level model

NASA Technical Reports Server (NTRS)

Bridger, Alison F. C.; Haberle, Robert M.

1992-01-01

The one-level model developed by Mass and Dempsey for use in predicting surface flows in regions of complex terrain was adapted to simulate surface flows at the Viking lander sites on Mars. In the one-level model, prediction equations for surface winds and temperatures are formulated and solved. Surface temperatures change with time in response to diabatic heating, horizontal advection, adiabatic heating and cooling effects, and horizontal diffusion. Surface winds can change in response to horizontal advection, pressure gradient forces, Coriolis forces, surface drag, and horizontal diffusion. Surface pressures are determined by integration of the hydrostatic equation from the surface to some reference level. The model has successfully simulated surface flows under a variety of conditions in complex-terrain regions on Earth.

Warming and Resource Availability Shift Food Web Structure and Metabolism

PubMed Central

O'Connor, Mary I.; Piehler, Michael F.; Leech, Dina M.; Anton, Andrea; Bruno, John F.

2009-01-01

Climate change disrupts ecological systems in many ways. Many documented responses depend on species' life histories, contributing to the view that climate change effects are important but difficult to characterize generally. However, systematic variation in metabolic effects of temperature across trophic levels suggests that warming may lead to predictable shifts in food web structure and productivity. We experimentally tested the effects of warming on food web structure and productivity under two resource supply scenarios. Consistent with predictions based on universal metabolic responses to temperature, we found that warming strengthened consumer control of primary production when resources were augmented. Warming shifted food web structure and reduced total biomass despite increases in primary productivity in a marine food web. In contrast, at lower resource levels, food web production was constrained at all temperatures. These results demonstrate that small temperature changes could dramatically shift food web dynamics and provide a general, species-independent mechanism for ecological response to environmental temperature change. PMID:19707271

Synergistic Effects of Temperature, Oxidation and Stress Level on Fatigue Damage Evolution and Lifetime Prediction of Cross-Ply SiC/CAS Ceramic-Matrix Composites Through Hysteresis-Based Parameters

NASA Astrophysics Data System (ADS)

Li, Longbiao

2017-12-01

The damage development and cyclic fatigue lifetime of cross-ply SiC/CAS ceramic-matrix composites have been investigated at different testing temperatures in air atmosphere. The relationships between the fatigue hysteresis-based damage parameters, i.e., fatigue hysteresis dissipated energy, fatigue hysteresis modulus and fatigue peak strain and the damage mechanisms of matrix multicracking, fiber/matrix interface debonding, interface sliding and fibers failure, have been established. With the increase in the cycle number, the evolution of the fatigue hysteresis modulus, fatigue peak strain and fatigue hysteresis dissipated energy depends upon the fatigue peak stress levels, interface and fibers oxidation and testing temperature. The fatigue life S-N curves of cross-ply SiC/CAS composite at room and elevated temperatures have been predicted, and the fatigue limit stresses at room temperature, 750 and 850 °C, are 50, 36 and 30% of the tensile strength, respectively.

Comparison of eight logger layouts for monitoring animal-level temperature and humidity during commercial feeder cattle transport.

PubMed

Goldhawk, C; Crowe, T; González, L A; Janzen, E; Kastelic, J; Pajor, E; Schwartzkopf-Genswein, K

2014-09-01

Measuring animal-level conditions during transit provides information regarding the true risk of environmental challenges to cattle welfare during transportation. However, due to constraints on placing loggers at the animal level, there is a need to identify appropriate proxy locations. The objective was to evaluate 8 distributions of ceiling-level loggers in the deck and belly compartments of pot-belly trailers for assessing animal-level temperature and humidity during 5 to 18 h commercial transportation of feeder cattle. Ambient conditions during transportation ranged from 3.6 to 45.2°C (20.3 ± 7.61°C, mean ± SD). When considering the entire journey, average differences between ceiling and animal-level temperatures were similar among logger layouts (P > 0.05). The uncertainty in the difference in temperature and humidity between locations was high relative to the magnitude of the difference between animal- and ceiling-level conditions. Single-logger layouts required larger adjustments to predict animal-level conditions within either compartment, during either the entire journey or when the trailer was stationary (P < 0.05). Within certain logger layouts, there were small but significant differences in the ability of regression equations to predict animal-level conditions that were associated with cattle weight and available space relative to body size. Furthermore, evaluation of logger layouts based solely on the entire journey without consideration of stationary periods did not adequately capture variability in layout performance. In conclusion, to adequately monitor animal-level temperature and humidity, 10 loggers distributed throughout the compartment was recommended over single-logger layouts within both the deck and belly compartments of pot-belly trailers transporting feeder cattle in warm weather.

Thermal time constant: optimising the skin temperature predictive modelling in lower limb prostheses using Gaussian processes

PubMed Central

Buis, Arjan

2016-01-01

Elevated skin temperature at the body/device interface of lower-limb prostheses is one of the major factors that affect tissue health. The heat dissipation in prosthetic sockets is greatly influenced by the thermal conductive properties of the hard socket and liner material employed. However, monitoring of the interface temperature at skin level in lower-limb prosthesis is notoriously complicated. This is due to the flexible nature of the interface liners used which requires consistent positioning of sensors during donning and doffing. Predicting the residual limb temperature by monitoring the temperature between socket and liner rather than skin and liner could be an important step in alleviating complaints on increased temperature and perspiration in prosthetic sockets. To predict the residual limb temperature, a machine learning algorithm – Gaussian processes is employed, which utilizes the thermal time constant values of commonly used socket and liner materials. This Letter highlights the relevance of thermal time constant of prosthetic materials in Gaussian processes technique which would be useful in addressing the challenge of non-invasively monitoring the residual limb skin temperature. With the introduction of thermal time constant, the model can be optimised and generalised for a given prosthetic setup, thereby making the predictions more reliable. PMID:27695626

Thermal time constant: optimising the skin temperature predictive modelling in lower limb prostheses using Gaussian processes.

PubMed

Mathur, Neha; Glesk, Ivan; Buis, Arjan

2016-06-01

Elevated skin temperature at the body/device interface of lower-limb prostheses is one of the major factors that affect tissue health. The heat dissipation in prosthetic sockets is greatly influenced by the thermal conductive properties of the hard socket and liner material employed. However, monitoring of the interface temperature at skin level in lower-limb prosthesis is notoriously complicated. This is due to the flexible nature of the interface liners used which requires consistent positioning of sensors during donning and doffing. Predicting the residual limb temperature by monitoring the temperature between socket and liner rather than skin and liner could be an important step in alleviating complaints on increased temperature and perspiration in prosthetic sockets. To predict the residual limb temperature, a machine learning algorithm - Gaussian processes is employed, which utilizes the thermal time constant values of commonly used socket and liner materials. This Letter highlights the relevance of thermal time constant of prosthetic materials in Gaussian processes technique which would be useful in addressing the challenge of non-invasively monitoring the residual limb skin temperature. With the introduction of thermal time constant, the model can be optimised and generalised for a given prosthetic setup, thereby making the predictions more reliable.

The energetic and carbon economic origins of leaf thermoregulation.

PubMed

Michaletz, Sean T; Weiser, Michael D; McDowell, Nate G; Zhou, Jizhong; Kaspari, Michael; Helliker, Brent R; Enquist, Brian J

2016-08-22

Leaf thermoregulation has been documented in a handful of studies, but the generality and origins of this pattern are unclear. We suggest that leaf thermoregulation is widespread in both space and time, and originates from the optimization of leaf traits to maximize leaf carbon gain across and within variable environments. Here we use global data for leaf temperatures, traits and photosynthesis to evaluate predictions from a novel theory of thermoregulation that synthesizes energy budget and carbon economics theories. Our results reveal that variation in leaf temperatures and physiological performance are tightly linked to leaf traits and carbon economics. The theory, parameterized with global averaged leaf traits and microclimate, predicts a moderate level of leaf thermoregulation across a broad air temperature gradient. These predictions are supported by independent data for diverse taxa spanning a global air temperature range of ∼60 °C. Moreover, our theory predicts that net carbon assimilation can be maximized by means of a trade-off between leaf thermal stability and photosynthetic stability. This prediction is supported by globally distributed data for leaf thermal and photosynthetic traits. Our results demonstrate that the temperatures of plant tissues, and not just air, are vital to developing more accurate Earth system models.

Integrating a human thermoregulatory model with a clothing model to predict core and skin temperatures.

PubMed

Yang, Jie; Weng, Wenguo; Wang, Faming; Song, Guowen

2017-05-01

This paper aims to integrate a human thermoregulatory model with a clothing model to predict core and skin temperatures. The human thermoregulatory model, consisting of an active system and a passive system, was used to determine the thermoregulation and heat exchanges within the body. The clothing model simulated heat and moisture transfer from the human skin to the environment through the microenvironment and fabric. In this clothing model, the air gap between skin and clothing, as well as clothing properties such as thickness, thermal conductivity, density, porosity, and tortuosity were taken into consideration. The simulated core and mean skin temperatures were compared to the published experimental results of subject tests at three levels of ambient temperatures of 20 °C, 30 °C, and 40 °C. Although lower signal-to-noise-ratio was observed, the developed model demonstrated positive performance at predicting core temperatures with a maximum difference between the simulations and measurements of no more than 0.43 °C. Generally, the current model predicted the mean skin temperatures with reasonable accuracy. It could be applied to predict human physiological responses and assess thermal comfort and heat stress. Copyright © 2017 Elsevier Ltd. All rights reserved.

Modeling of NiTiHf using finite difference method

NASA Astrophysics Data System (ADS)

Farjam, Nazanin; Mehrabi, Reza; Karaca, Haluk; Mirzaeifar, Reza; Elahinia, Mohammad

2018-03-01

NiTiHf is a high temperature and high strength shape memory alloy with transformation temperatures above 100oC. A constitutive model based on Gibbs free energy is developed to predict the behavior of this material. Two different irrecoverable strains including transformation induced plastic strain (TRIP) and viscoplastic strain (VP) are considered when using high temperature shape memory alloys (HTSMAs). The first one happens during transformation at high levels of stress and the second one is related to the creep which is rate-dependent. The developed model is implemented for NiTiHf under uniaxial loading. Finite difference method is utilized to solve the proposed equations. The material parameters in the equations are calibrated from experimental data. Simulation results are captured to investigate the superelastic behavior of NiTiHf. The extracted results are compared with experimental tests of isobaric heating and cooling at different levels of stress and also superelastic tests at different levels of temperature. More results are generated to investigate the capability of the proposed model in the prediction of the irrecoverable strain after full transformation in HTSMAs.

Integrated CFD modeling of gas turbine combustors

NASA Technical Reports Server (NTRS)

Fuller, E. J.; Smith, C. E.

1993-01-01

3D, curvilinear, multi-domain CFD analysis is becoming a valuable tool in gas turbine combustor design. Used as a supplement to experimental testing. CFD analysis can provide improved understanding of combustor aerodynamics and used to qualitatively assess new combustor designs. This paper discusses recent advancements in CFD combustor methodology, including the timely integration of the design (i.e. CAD) and analysis (i.e. CFD) processes. Allied Signal's F124 combustor was analyzed at maximum power conditions. The assumption of turbulence levels at the nozzle/swirler inlet was shown to be very important in the prediction of combustor exit temperatures. Predicted exit temperatures were compared to experimental rake data, and good overall agreement was seen. Exit radial temperature profiles were well predicted, while the predicted pattern factor was 25 percent higher than the harmonic-averaged experimental pattern factor.

Analytical Predictions of Thermal Stress in the Stardust PICA Heatshield Under Reentry Flight Conditions

NASA Technical Reports Server (NTRS)

Squire, Thomas; Milos, Frank; Agrawal, Parul

2009-01-01

We performed finite element analyses on a model of the Phenolic Impregnated Carbon Ablator (PICA) heatshield from the Stardust sample return capsule (SRC) to predict the thermal stresses in the PICA material during reentry. The heatshield on the Stardust SRC was a 0.83 m sphere cone, fabricated from a single piece of 5.82 cm-thick PICA. The heatshield performed successfully during Earth reentry of the SRC in January 2006. Material response analyses of the full, axisymmetric PICA heatshield were run using the Two-Dimensional Implicit Ablation, Pyrolysis, and Thermal Response Program (TITAN). Peak surface temperatures were predicted to be 3385K, while the temperature at the PICA backface remained at the estimated initial cold-soak temperature of 278K. Surface recession and temperature distribution results from TITAN, at several points in the reentry trajectory, were mapped onto an axisymmetric finite element model of the heatshield. We used the finite element model to predict the thermal stresses in the PICA from differential thermal expansion. The predicted peak compressive stress in the PICA heatshield was 1.38 MPa. Although this level of stress exceeded the chosen design limit for compressive stresses in PICA tiles for the design of the Orion crew exploration vehicle heatshield, the Stardust heatshield exhibited no obvious mechanical failures from thermal stress. The analyses of the Stardust heatshield were used to assess and adjust the level of conservatism in the finite element analyses in support of the Orion heatshield design.

Body Temperature Regulation in Hot Environments.

PubMed

Nilsson, Jan-Åke; Molokwu, Mary Ngozi; Olsson, Ola

2016-01-01

Organisms in hot environments will not be able to passively dissipate metabolically generated heat. Instead, they have to revert to evaporative cooling, a process that is energetically expensive and promotes excessive water loss. To alleviate these costs, birds in captivity let their body temperature increase, thereby entering a state of hyperthermia. Here we explore the use of hyperthermia in wild birds captured during the hot and dry season in central Nigeria. We found pronounced hyperthermia in several species with the highest body temperatures close to predicted lethal levels. Furthermore, birds let their body temperature increase in direct relation to ambient temperatures, increasing body temperature by 0.22°C for each degree of increased ambient temperature. Thus to offset the costs of thermoregulation in ambient temperatures above the upper critical temperature, birds are willing to let their body temperatures increase by up to 5°C above normal temperatures. This flexibility in body temperature may be an important mechanism for birds to adjust to predicted increasing ambient temperatures in the future.

Body Temperature Regulation in Hot Environments

PubMed Central

Nilsson, Jan-Åke; Molokwu, Mary Ngozi; Olsson, Ola

2016-01-01

Organisms in hot environments will not be able to passively dissipate metabolically generated heat. Instead, they have to revert to evaporative cooling, a process that is energetically expensive and promotes excessive water loss. To alleviate these costs, birds in captivity let their body temperature increase, thereby entering a state of hyperthermia. Here we explore the use of hyperthermia in wild birds captured during the hot and dry season in central Nigeria. We found pronounced hyperthermia in several species with the highest body temperatures close to predicted lethal levels. Furthermore, birds let their body temperature increase in direct relation to ambient temperatures, increasing body temperature by 0.22°C for each degree of increased ambient temperature. Thus to offset the costs of thermoregulation in ambient temperatures above the upper critical temperature, birds are willing to let their body temperatures increase by up to 5°C above normal temperatures. This flexibility in body temperature may be an important mechanism for birds to adjust to predicted increasing ambient temperatures in the future. PMID:27548758

Temperature-dependence of biomass accumulation rates during secondary succession.

PubMed

Anderson, Kristina J; Allen, Andrew P; Gillooly, James F; Brown, James H

2006-06-01

Rates of ecosystem recovery following disturbance affect many ecological processes, including carbon cycling in the biosphere. Here, we present a model that predicts the temperature dependence of the biomass accumulation rate following disturbances in forests. Model predictions are derived based on allometric and biochemical principles that govern plant energetics and are tested using a global database of 91 studies of secondary succession compiled from the literature. The rate of biomass accumulation during secondary succession increases with average growing season temperature as predicted based on the biochemical kinetics of photosynthesis in chloroplasts. In addition, the rate of biomass accumulation is greater in angiosperm-dominated communities than in gymnosperm-dominated ones and greater in plantations than in naturally regenerating stands. By linking the temperature-dependence of photosynthesis to the rate of whole-ecosystem biomass accumulation during secondary succession, our model and results provide one example of how emergent, ecosystem-level rate processes can be predicted based on the kinetics of individual metabolic rate.

Predicting East African spring droughts using Pacific and Indian Ocean sea surface temperature indices

USGS Publications Warehouse

Funk, Christopher C.; Hoell, Andrew; Shukla, Shraddhanand; Blade, Ileana; Liebmann, Brant; Roberts, Jason B.; Robertson, Franklin R.

2014-01-01

In southern Ethiopia, Eastern Kenya, and southern Somalia poor boreal spring rains in 1999, 2000, 2004, 2007, 2008, 2009 and 2011 contributed to severe food insecurity and high levels of malnutrition. Predicting rainfall deficits in this region on seasonal and decadal time frames can help decision makers support disaster risk reduction while guiding climate-smart adaptation and agricultural development. Building on recent research that links more frequent droughts to a stronger Walker Circulation, warming in the Indo-Pacific warm pool, and an increased western Pacific sea surface temperature (SST) gradient, we explore the dominant modes of East African rainfall variability, links between these modes and sea surface temperatures, and a simple index-based monitoring-prediction system suitable for drought early warning.

Predicted thermal response of a cryogenic fuel tank exposed to simulated aerodynamic heating profiles with different cryogens and fill levels

NASA Technical Reports Server (NTRS)

Hanna, Gregory J.; Stephens, Craig A.

1991-01-01

A two dimensional finite difference thermal model was developed to predict the effects of heating profile, fill level, and cryogen type prior to experimental testing the Generic Research Cryogenic Tank (GRCT). These numerical predictions will assist in defining test scenarios, sensor locations, and venting requirements for the GRCT experimental tests. Boiloff rates, tank-wall and fluid temperatures, and wall heat fluxes were determined for 20 computational test cases. The test cases spanned three discrete fill levels and three heating profiles for hydrogen and nitrogen.

A new predictive dynamic model describing the effect of the ambient temperature and the convective heat transfer coefficient on bacterial growth.

PubMed

Ben Yaghlene, H; Leguerinel, I; Hamdi, M; Mafart, P

2009-07-31

In this study, predictive microbiology and food engineering were combined in order to develop a new analytical model predicting the bacterial growth under dynamic temperature conditions. The proposed model associates a simplified primary bacterial growth model without lag, the secondary Ratkowsky "square root" model and a simplified two-parameter heat transfer model regarding an infinite slab. The model takes into consideration the product thickness, its thermal properties, the ambient air temperature, the convective heat transfer coefficient and the growth parameters of the micro organism of concern. For the validation of the overall model, five different combinations of ambient air temperature (ranging from 8 degrees C to 12 degrees C), product thickness (ranging from 1 cm to 6 cm) and convective heat transfer coefficient (ranging from 8 W/(m(2) K) to 60 W/(m(2) K)) were tested during a cooling procedure. Moreover, three different ambient air temperature scenarios assuming alternated cooling and heating stages, drawn from real refrigerated food processes, were tested. General agreement between predicted and observed bacterial growth was obtained and less than 5% of the experimental data fell outside the 95% confidence bands estimated by the bootstrap percentile method, at all the tested conditions. Accordingly, the overall model was successfully validated for isothermal and dynamic refrigeration cycles allowing for temperature dynamic changes at the centre and at the surface of the product. The major impact of the convective heat transfer coefficient and the product thickness on bacterial growth during the product cooling was demonstrated. For instance, the time needed for the same level of bacterial growth to be reached at the product's half thickness was estimated to be 5 and 16.5 h at low and high convection level, respectively. Moreover, simulation results demonstrated that the predicted bacterial growth at the air ambient temperature cannot be assumed to be equivalent to the bacterial growth occurring at the product's surface or centre when convection heat transfer is taken into account. Our results indicate that combining food engineering and predictive microbiology models is an interesting approach providing very useful tools for food safety and process optimisation.

Forced synchronization of large-scale circulation to increase predictability of surface states

NASA Astrophysics Data System (ADS)

Shen, Mao-Lin; Keenlyside, Noel; Selten, Frank; Wiegerinck, Wim; Duane, Gregory

2016-04-01

Numerical models are key tools in the projection of the future climate change. The lack of perfect initial condition and perfect knowledge of the laws of physics, as well as inherent chaotic behavior limit predictions. Conceptually, the atmospheric variables can be decomposed into a predictable component (signal) and an unpredictable component (noise). In ensemble prediction the anomaly of ensemble mean is regarded as the signal and the ensemble spread the noise. Naturally the prediction skill will be higher if the signal-to-noise ratio (SNR) is larger in the initial conditions. We run two ensemble experiments in order to explore a way to reduce the SNR of surface winds and temperature. One ensemble experiment is AGCM with prescribing sea surface temperature (SST); the other is AGCM with both prescribing SST and nudging the high-level temperature and winds to ERA-Interim. Each ensemble has 30 members. Larger SNR is expected and found over the tropical ocean in the first experiment because the tropical circulation is associated with the convection and the associated surface wind convergence as these are to a large extent driven by the SST. However, small SNR is found over high latitude ocean and land surface due to the chaotic and non-synchronized atmosphere states. In the second experiment the higher level temperature and winds are forced to be synchronized (nudged to reanalysis) and hence a larger SNR of surface winds and temperature is expected. Furthermore, different nudging coefficients are also tested in order to understand the limitation of both synchronization of large-scale circulation and the surface states. These experiments will be useful for the developing strategies to synchronize the 3-D states of atmospheric models that can be later used to build a super model.

“Skin-Core-Skin” Structure of Polymer Crystallization Investigated by Multiscale Simulation

PubMed Central

Ruan, Chunlei

2018-01-01

“Skin-core-skin” structure is a typical crystal morphology in injection products. Previous numerical works have rarely focused on crystal evolution; rather, they have mostly been based on the prediction of temperature distribution or crystallization kinetics. The aim of this work was to achieve the “skin-core-skin” structure and investigate the role of external flow and temperature fields on crystal morphology. Therefore, the multiscale algorithm was extended to the simulation of polymer crystallization in a pipe flow. The multiscale algorithm contains two parts: a collocated finite volume method at the macroscopic level and a morphological Monte Carlo method at the microscopic level. The SIMPLE (semi-implicit method for pressure linked equations) algorithm was used to calculate the polymeric model at the macroscopic level, while the Monte Carlo method with stochastic birth-growth process of spherulites and shish-kebabs was used at the microscopic level. Results show that our algorithm is valid to predict “skin-core-skin” structure, and the initial melt temperature and the maximum velocity of melt at the inlet mainly affects the morphology of shish-kebabs. PMID:29659516

Diagnostics of seeded RF plasmas: An experimental study related to the gaseous core reactor

NASA Technical Reports Server (NTRS)

Thompson, S. D.; Clement, J. D.; Williams, J. R.

1974-01-01

Measurements of the temperature profiles in an RF argon plasma were made over magnetic field intensities ranging from 20 amp turns/cm to 80 amp turns/cm. The results were compared with a one-dimensional numerical treatment of the governing equations and with an approximate closed form analytical solution that neglected radiation losses. The average measured temperatures in the plasma compared well with the numerical treatment, though the experimental profile showed less of an off center temperature peak than predicted by theory. This may be a result of the complex turbulent flow pattern present in the experimental torch and not modeled in the numerical treatment. The radiation term cannot be neglected for argon at the power levels investigated. The closed form analytical approximation that neglected radiation led to temperature predictions on the order of 1000 K to 2000 K higher than measured or predicted by the numerical treatment which considered radiation losses.

Studies on thermo-elastic heating of horns used in ultrasonic plastic welding.

PubMed

Roopa Rani, M; Prakasan, K; Rudramoorthy, R

2015-01-01

Ultrasonic welding horn is half wavelength section or tool used to focus the ultrasonic vibrations to the components being welded. The horn is designed in such a way that it maximizes the amplitude of the sound wave passing through it. The ends of the horn represent the displacement anti-nodes and the center the 'node' of the wave. As the horns perform 20,000 cycles of expansion and contraction per second, they are highly stressed at the nodes and are heated owing to thermo-elastic effects. Considerable temperature rise may be observed in the horn, at the nodal region when working at high amplitudes indicating high stress levels leading to failure of horns due to cyclic loading. The limits for amplitude must therefore be evaluated for the safe working of the horn. Horns made of different materials have different thermo-elastic behaviors and hence different temperatures at the nodes and antinodes. This temperature field can be used as a control mechanism for setting the amplitude/weld parameters. Safe stress levels can be predicted using modal and harmonic analyses followed by a stress analysis to study the effect of cyclic loads. These are achieved using 'Ansys'. The maximum amplitude level obtained from the stress analysis is used as input for 'Comsol' to predict the temperature field. The actual temperature developed in the horn during operation is measured using infrared camera and compared with the simulated temperature. From experiments, it is observed that horn made of titanium had the lowest temperature rise at the critical region and can be expected to operate at amplitudes up to 77 μm without suffering failure due to cyclic loading. The method of predicting thermo-elastic stresses and temperature may be adopted by the industry for operating the horn within the safe stress limits thereby extending the life of the horn. Copyright © 2014 Elsevier B.V. All rights reserved.

Evaluation of potential impacts on Great Lakes water resources based on climate scenarios of two GCMs

USGS Publications Warehouse

Lofgren, B.M.; Quinn, F.H.; Clites, A.H.; Assel, R.A.; Eberhardt, A.J.; Luukkonen, C.L.

2002-01-01

The results of general circulation model predictions of the effects of climate change from the Canadian Centre for Climate Modeling and Analysis (model CGCM1) and the United Kingdom Meteorological Office's Hadley Centre (model HadCM2) have been used to derive potential impacts on the water resources of the Great Lakes basin. These impacts can influence the levels of the Great Lakes and the volumes of channel flow among them, thus affecting their value for interests such as riparians, shippers, recreational boaters, and natural ecosystems. On one hand, a hydrological modeling suite using input data from the CGCM1 predicts large drops in lake levels, up to a maximum of 1.38 m on Lakes Michigan and Huron by 2090. This is due to a combination of a decrease in precipitation and an increase in air temperature that leads to an increase in evaporation. On the other hand, using input from HadCM2, rises in lake levels are predicted, up to a maximum of 0.35 m on Lakes Michigan and Huron by 2090, due to increased precipitation and a reduced increase in air temperature. An interest satisfaction model shows sharp decreases in the satisfaction of the interests of commercial navigation, recreational boating, riparians, and hydropower due to lake level decreases. Most interest satisfaction scores are also reduced by lake level increases. Drastic reductions in ice cover also result from the temperature increases such that under the CGCM1 predictions, most of Lake Erie has 96% of its winters ice-free by 2090. Assessment is also made of impacts on the groundwater-dependent region of Lansing, Michigan.

Empirical evidence that metabolic theory describes the temperature dependency of within-host parasite dynamics.

PubMed

Kirk, Devin; Jones, Natalie; Peacock, Stephanie; Phillips, Jessica; Molnár, Péter K; Krkošek, Martin; Luijckx, Pepijn

2018-02-01

The complexity of host-parasite interactions makes it difficult to predict how host-parasite systems will respond to climate change. In particular, host and parasite traits such as survival and virulence may have distinct temperature dependencies that must be integrated into models of disease dynamics. Using experimental data from Daphnia magna and a microsporidian parasite, we fitted a mechanistic model of the within-host parasite population dynamics. Model parameters comprising host aging and mortality, as well as parasite growth, virulence, and equilibrium abundance, were specified by relationships arising from the metabolic theory of ecology. The model effectively predicts host survival, parasite growth, and the cost of infection across temperature while using less than half the parameters compared to modeling temperatures discretely. Our results serve as a proof of concept that linking simple metabolic models with a mechanistic host-parasite framework can be used to predict temperature responses of parasite population dynamics at the within-host level.

Empirical evidence that metabolic theory describes the temperature dependency of within-host parasite dynamics

PubMed Central

Jones, Natalie; Peacock, Stephanie; Phillips, Jessica; Molnár, Péter K.; Krkošek, Martin; Luijckx, Pepijn

2018-01-01

The complexity of host–parasite interactions makes it difficult to predict how host–parasite systems will respond to climate change. In particular, host and parasite traits such as survival and virulence may have distinct temperature dependencies that must be integrated into models of disease dynamics. Using experimental data from Daphnia magna and a microsporidian parasite, we fitted a mechanistic model of the within-host parasite population dynamics. Model parameters comprising host aging and mortality, as well as parasite growth, virulence, and equilibrium abundance, were specified by relationships arising from the metabolic theory of ecology. The model effectively predicts host survival, parasite growth, and the cost of infection across temperature while using less than half the parameters compared to modeling temperatures discretely. Our results serve as a proof of concept that linking simple metabolic models with a mechanistic host–parasite framework can be used to predict temperature responses of parasite population dynamics at the within-host level. PMID:29415043

Research on the time-temperature-damage superposition principle of NEPE propellant

NASA Astrophysics Data System (ADS)

Han, Long; Chen, Xiong; Xu, Jin-sheng; Zhou, Chang-sheng; Yu, Jia-quan

2015-11-01

To describe the relaxation behavior of NEPE (Nitrate Ester Plasticized Polyether) propellant, we analyzed the equivalent relationships between time, temperature, and damage. We conducted a series of uniaxial tensile tests and employed a cumulative damage model to calculate the damage values for relaxation tests at different strain levels. The damage evolution curve of the tensile test at 100 mm/min was obtained through numerical analysis. Relaxation tests were conducted over a range of temperature and strain levels, and the equivalent relationship between time, temperature, and damage was deduced based on free volume theory. The equivalent relationship was then used to generate predictions of the long-term relaxation behavior of the NEPE propellant. Subsequently, the equivalent relationship between time and damage was introduced into the linear viscoelastic model to establish a nonlinear model which is capable of describing the mechanical behavior of composite propellants under a uniaxial tensile load. The comparison between model prediction and experimental data shows that the presented model provides a reliable forecast of the mechanical behavior of propellants.

Prediction of Turbulent Temperature Fluctuations in Hot Jets

NASA Technical Reports Server (NTRS)

DeBonis, James R.

2017-01-01

Large-eddy simulations (LES) were used to investigate turbulent temperature fluctuations and turbulent heat flux in hot jets. A high-resolution finite-difference Navier-Stokes solver was used to compute the flow from a 2-inch round nozzle. Three different flow conditions of varying jet Mach numbers and temperature ratios were examined. The LES results showed that the temperature field behaves similar to the velocity field, but with a more rapidly spreading mixing layer. Predictions of mean, mu-bar(sub i), and fluctuating, mu'(sub i), velocities were compared to particle image velocimetry data. Predictions of mean, T-bar, and fluctuating, T', temperature were compared to data obtained using Rayleigh scattering and Raman spectroscopy. Very good agreement with experimental data was demonstrated for the mean and fluctuating velocities. The LES correctly predicts the behavior of the turbulent temperature field, but over-predicts the levels of the fluctuations. The turbulent heat flux was examined and compared to Reynolds-averaged Navier-Stokes (RANS) results. The LES and RANS simulations produced very similar results for the radial heat flux. However, the axial heat flux obtained from the LES differed significantly from the RANS result in both structure and magnitude, indicating that the gradient diffusion type model in RANS is inadequate. Finally, the LES data was used to compute the turbulent Prandtl number and verify that a constant value of 0.7 used in the RANS models is a reasonable assumption.

Comparison of ArcGIS and SAS Geostatistical Analyst to Estimate Population-Weighted Monthly Temperature for US Counties.

PubMed

Xiaopeng, Q I; Liang, Wei; Barker, Laurie; Lekiachvili, Akaki; Xingyou, Zhang

Temperature changes are known to have significant impacts on human health. Accurate estimates of population-weighted average monthly air temperature for US counties are needed to evaluate temperature's association with health behaviours and disease, which are sampled or reported at the county level and measured on a monthly-or 30-day-basis. Most reported temperature estimates were calculated using ArcGIS, relatively few used SAS. We compared the performance of geostatistical models to estimate population-weighted average temperature in each month for counties in 48 states using ArcGIS v9.3 and SAS v 9.2 on a CITGO platform. Monthly average temperature for Jan-Dec 2007 and elevation from 5435 weather stations were used to estimate the temperature at county population centroids. County estimates were produced with elevation as a covariate. Performance of models was assessed by comparing adjusted R 2 , mean squared error, root mean squared error, and processing time. Prediction accuracy for split validation was above 90% for 11 months in ArcGIS and all 12 months in SAS. Cokriging in SAS achieved higher prediction accuracy and lower estimation bias as compared to cokriging in ArcGIS. County-level estimates produced by both packages were positively correlated (adjusted R 2 range=0.95 to 0.99); accuracy and precision improved with elevation as a covariate. Both methods from ArcGIS and SAS are reliable for U.S. county-level temperature estimates; However, ArcGIS's merits in spatial data pre-processing and processing time may be important considerations for software selection, especially for multi-year or multi-state projects.

Stability of procalcitonin at room temperature.

PubMed

Milcent, Karen; Poulalhon, Claire; Fellous, Christelle Vauloup; Petit, François; Bouyer, Jean; Gajdos, Vincent

2014-01-01

The aim was to assess procalcitonin (PCT) stability after two days of storage at room temperature. Samples were collected from febrile children aged 7 to 92 days and were rapidly frozen after sampling. PCT levels were measured twice after thawing: immediately (named y) and 48 hours later after storage at room temperature (named x). PCT values were described with medians and interquartile ranges or by categorizing them into classes with thresholds 0.25, 0.5, and 2 ng/mL. The relationship between x and y PCT levels was analyzed using fractional polynomials in order to predict the PCT value immediately after thawing (named y') from x. A significant decrease in PCT values was observed after 48 hours of storage at room temperature, either in median, 30% lowering (p < 0.001), or as categorical variable (p < 0.001). The relationship between x and y can be accurately modeled with a simple linear model: y = 1.37 x (R2 = 0.99). The median of the predicted PCT values y' was quantitatively very close to the median of y and the distributions of y and y' across categories were very similar and not statistically different. PCT levels noticeably decrease after 48 hours of storage at room temperature. It is possible to pre- dict accurately effective PCT values from the values after 48 hours of storage at room temperature with a simple statistical model.

Time series modelling of increased soil temperature anomalies during long period

NASA Astrophysics Data System (ADS)

Shirvani, Amin; Moradi, Farzad; Moosavi, Ali Akbar

2015-10-01

Soil temperature just beneath the soil surface is highly dynamic and has a direct impact on plant seed germination and is probably the most distinct and recognisable factor governing emergence. Autoregressive integrated moving average as a stochastic model was developed to predict the weekly soil temperature anomalies at 10 cm depth, one of the most important soil parameters. The weekly soil temperature anomalies for the periods of January1986-December 2011 and January 2012-December 2013 were taken into consideration to construct and test autoregressive integrated moving average models. The proposed model autoregressive integrated moving average (2,1,1) had a minimum value of Akaike information criterion and its estimated coefficients were different from zero at 5% significance level. The prediction of the weekly soil temperature anomalies during the test period using this proposed model indicated a high correlation coefficient between the observed and predicted data - that was 0.99 for lead time 1 week. Linear trend analysis indicated that the soil temperature anomalies warmed up significantly by 1.8°C during the period of 1986-2011.

Ordering transition in salt-doped diblock copolymers

DOE PAGES

Qin, Jian; de Pablo, Juan J.

2016-04-26

Lithium salt-doped block copolymers offer promise for applications as solid electrolytes in lithium ion batteries. Control of the conductivity and mechanical properties of these materials, for membrane applications relies critically on the ability to predict and manipulate their microphase separation temperature. Past attempts to predict the so-called "order-disorder transition temperature" of copolymer electrolytes have relied on approximate treatments of electrostatic interactions. In this work, we introduce a coarse-grained simulation model that treats Coulomb interactions explicitly, and we use it to investigate the ordering transition of charged block copolymers. The order-disorder transition temperature is determined from the ordering free energy, whichmore » we calculate with a high level of precision using a density-of-states approach. Our calculations allow us to discern a delicate competition between two physical effects: ion association, which raises the transition temperature, and solvent dilution, which lowers the transition temperature. Lastly, in the intermediate salt concentration regime, our results predict that the order-disorder transition temperature increases with salt content, in agreement with available experimental data.« less

Advanced error-prediction LDPC with temperature compensation for highly reliable SSDs

NASA Astrophysics Data System (ADS)

Tokutomi, Tsukasa; Tanakamaru, Shuhei; Iwasaki, Tomoko Ogura; Takeuchi, Ken

2015-09-01

To improve the reliability of NAND Flash memory based solid-state drives (SSDs), error-prediction LDPC (EP-LDPC) has been proposed for multi-level-cell (MLC) NAND Flash memory (Tanakamaru et al., 2012, 2013), which is effective for long retention times. However, EP-LDPC is not as effective for triple-level cell (TLC) NAND Flash memory, because TLC NAND Flash has higher error rates and is more sensitive to program-disturb error. Therefore, advanced error-prediction LDPC (AEP-LDPC) has been proposed for TLC NAND Flash memory (Tokutomi et al., 2014). AEP-LDPC can correct errors more accurately by precisely describing the error phenomena. In this paper, the effects of AEP-LDPC are investigated in a 2×nm TLC NAND Flash memory with temperature characterization. Compared with LDPC-with-BER-only, the SSD's data-retention time is increased by 3.4× and 9.5× at room-temperature (RT) and 85 °C, respectively. Similarly, the acceptable BER is increased by 1.8× and 2.3×, respectively. Moreover, AEP-LDPC can correct errors with pre-determined tables made at higher temperatures to shorten the measurement time before shipping. Furthermore, it is found that one table can cover behavior over a range of temperatures in AEP-LDPC. As a result, the total table size can be reduced to 777 kBytes, which makes this approach more practical.

Limitations of predicting in vivo biostability of multiphase polyurethane elastomers using temperature-accelerated degradation testing.

PubMed

Padsalgikar, Ajay; Cosgriff-Hernandez, Elizabeth; Gallagher, Genevieve; Touchet, Tyler; Iacob, Ciprian; Mellin, Lisa; Norlin-Weissenrieder, Anna; Runt, James

2015-01-01

Polyurethane biostability has been the subject of intense research since the failure of polyether polyurethane pacemaker leads in the 1980s. Accelerated in vitro testing has been used to isolate degradation mechanisms and predict clinical performance of biomaterials. However, validation that in vitro methods reproduce in vivo degradation is critical to the selection of appropriate tests. High temperature has been proposed as a method to accelerate degradation. However, correlation of such data to in vivo performance is poor for polyurethanes due to the impact of temperature on microstructure. In this study, we characterize the lack of correlation between hydrolytic degradation predicted using a high temperature aging model of a polydimethylsiloxane-based polyurethane and its in vivo performance. Most notably, the predicted molecular weight and tensile property changes from the accelerated aging study did not correlate with clinical explants subjected to human biological stresses in real time through 5 years. Further, DMTA, ATR-FTIR, and SAXS experiments on samples aged for 2 weeks in PBS indicated greater phase separation in samples aged at 85°C compared to those aged at 37°C and unaged controls. These results confirm that microstructural changes occur at high temperatures that do not occur at in vivo temperatures. In addition, water absorption studies demonstrated that water saturation levels increased significantly with temperature. This study highlights that the multiphase morphology of polyurethane precludes the use of temperature accelerated biodegradation for the prediction of clinical performance and provides critical information in designing appropriate in vitro tests for this class of materials. © 2014 Wiley Periodicals, Inc.

Modeling and optimization of trihalomethanes formation potential of surface water (a drinking water source) using Box-Behnken design.

PubMed

Singh, Kunwar P; Rai, Premanjali; Pandey, Priyanka; Sinha, Sarita

2012-01-01

The present research aims to investigate the individual and interactive effects of chlorine dose/dissolved organic carbon ratio, pH, temperature, bromide concentration, and reaction time on trihalomethanes (THMs) formation in surface water (a drinking water source) during disinfection by chlorination in a prototype laboratory-scale simulation and to develop a model for the prediction and optimization of THMs levels in chlorinated water for their effective control. A five-factor Box-Behnken experimental design combined with response surface and optimization modeling was used for predicting the THMs levels in chlorinated water. The adequacy of the selected model and statistical significance of the regression coefficients, independent variables, and their interactions were tested by the analysis of variance and t test statistics. The THMs levels predicted by the model were very close to the experimental values (R(2) = 0.95). Optimization modeling predicted maximum (192 μg/l) TMHs formation (highest risk) level in water during chlorination was very close to the experimental value (186.8 ± 1.72 μg/l) determined in laboratory experiments. The pH of water followed by reaction time and temperature were the most significant factors that affect the THMs formation during chlorination. The developed model can be used to determine the optimum characteristics of raw water and chlorination conditions for maintaining the THMs levels within the safe limit.

Improving simulations of precipitation phase and snowpack at a site subject to cold air intrusions: Snoqualmie Pass, WA

NASA Astrophysics Data System (ADS)

Wayand, Nicholas E.; Stimberis, John; Zagrodnik, Joseph P.; Mass, Clifford F.; Lundquist, Jessica D.

2016-09-01

Low-level cold air from eastern Washington often flows westward through mountain passes in the Washington Cascades, creating localized inversions and locally reducing climatological temperatures. The persistence of this inversion during a frontal passage can result in complex patterns of snow and rain that are difficult to predict. Yet these predictions are critical to support highway avalanche control, ski resort operations, and modeling of headwater snowpack storage. In this study we used observations of precipitation phase from a disdrometer and snow depth sensors across Snoqualmie Pass, WA, to evaluate surface-air-temperature-based and mesoscale-model-based predictions of precipitation phase during the anomalously warm 2014-2015 winter. Correlations of phase between surface-based methods and observations were greatly improved (r2 from 0.45 to 0.66) and frozen precipitation biases reduced (+36% to -6% of accumulated snow water equivalent) by using air temperature from a nearby higher-elevation station, which was less impacted by low-level inversions. Alternatively, we found a hybrid method that combines surface-based predictions with output from the Weather Research and Forecasting mesoscale model to have improved skill (r2 = 0.61) over both parent models (r2 = 0.42 and 0.55). These results suggest that prediction of precipitation phase in mountain passes can be improved by incorporating observations or models from above the surface layer.

Toxin production and growth of pathogens subjected to temperature fluctuations simulating consumer handling of cold cuts.

PubMed

Røssvoll, Elin; Rønning, Helene Thorsen; Granum, Per Einar; Møretrø, Trond; Hjerpekjøn, Marianne Røine; Langsrud, Solveig

2014-08-18

It is crucial for the quality and safety of ready-to-eat (RTE) foods to maintain the cold chain from production to consumption. The effect of temperature abuse related to daily meals and elevated refrigerator temperatures on the growth and toxin production of Bacillus cereus, Bacillus weihenstephanensis and Staphylococcus aureus and the growth of Listeria monocytogenes and Yersinia enterocolitica was studied. A case study with temperature loggings in the domestic environment during Easter and Christmas holidays was performed to select relevant time and temperature courses. A model for bacterial surface growth on food using nutrient agar plates exposed to variations in temperatures was used to simulate food stored at different temperatures and exposed to room temperature for short periods of time. The results were compared with predicted growth using the modeling tool ComBase Predictor. The consumers exposed their cold cuts to room temperatures as high as 26.5°C with an average duration of meals was 47 min daily for breakfast/brunch during the vacations. Short (≤ 2 h) daily intervals at 25°C nearly halved the time the different pathogens needed to reach levels corresponding to the levels associated with human infection or intoxication, compared with the controls continuously stored at refrigerator temperature. Although the temperature fluctuations affected growth of both B. weihenstephanensis and S. aureus, toxin production was only detected at much higher cell concentrations than what has been associated with human intoxications. Therefore, growth of L. monocytogenes and Y. enterocolitica was found to be the limiting factor for safety. In combination with data on temperature abuse in the domestic environment, modeling programs such as ComBase Predictor can be efficient tools to predict growth of some pathogens but will not predict toxin production. Copyright © 2014 Elsevier B.V. All rights reserved.

Analysis tool and methodology design for electronic vibration stress understanding and prediction

NASA Astrophysics Data System (ADS)

Hsieh, Sheng-Jen; Crane, Robert L.; Sathish, Shamachary

2005-03-01

The objectives of this research were to (1) understand the impact of vibration on electronic components under ultrasound excitation; (2) model the thermal profile presented under vibration stress; and (3) predict stress level given a thermal profile of an electronic component. Research tasks included: (1) retrofit of current ultrasonic/infrared nondestructive testing system with sensory devices for temperature readings; (2) design of software tool to process images acquired from the ultrasonic/infrared system; (3) developing hypotheses and conducting experiments; and (4) modeling and evaluation of electronic vibration stress levels using a neural network model. Results suggest that (1) an ultrasonic/infrared system can be used to mimic short burst high vibration loads for electronics components; (2) temperature readings for electronic components under vibration stress are consistent and repeatable; (3) as stress load and excitation time increase, temperature differences also increase; (4) components that are subjected to a relatively high pre-stress load, followed by a normal operating load, have a higher heating rate and lower cooling rate. These findings are based on grayscale changes in images captured during experimentation. Discriminating variables and a neural network model were designed to predict stress levels given temperature and/or grayscale readings. Preliminary results suggest a 15.3% error when using grayscale change rate and 12.8% error when using average heating rate within the neural network model. Data were obtained from a high stress point (the corner) of the chip.

Scaling the metabolic balance of the oceans.

PubMed

López-Urrutia, Angel; San Martin, Elena; Harris, Roger P; Irigoien, Xabier

2006-06-06

Oceanic communities are sources or sinks of CO2, depending on the balance between primary production and community respiration. The prediction of how global climate change will modify this metabolic balance of the oceans is limited by the lack of a comprehensive underlying theory. Here, we show that the balance between production and respiration is profoundly affected by environmental temperature. We extend the general metabolic theory of ecology to the production and respiration of oceanic communities and show that ecosystem rates can be reliably scaled from theoretical knowledge of organism physiology and measurement of population abundance. Our theory predicts that the differential temperature-dependence of respiration and photosynthesis at the organism level determines the response of the metabolic balance of the epipelagic ocean to changes in ambient temperature, a prediction that we support with empirical data over the global ocean. Furthermore, our model predicts that there will be a negative feedback of ocean communities to climate warming because they will capture less CO2 with a future increase in ocean temperature. This feedback of marine biota will further aggravate the anthropogenic effects on global warming.

Identifying the microbial taxa that consistently respond to soil warming across time and space.

PubMed

Oliverio, Angela M; Bradford, Mark A; Fierer, Noah

2017-05-01

Soil microbial communities are the key drivers of many terrestrial biogeochemical processes. However, we currently lack a generalizable understanding of how these soil communities will change in response to predicted increases in global temperatures and which microbial lineages will be most impacted. Here, using high-throughput marker gene sequencing of soils collected from 18 sites throughout North America included in a 100-day laboratory incubation experiment, we identified a core group of abundant and nearly ubiquitous soil microbes that shift in relative abundance with elevated soil temperatures. We then validated and narrowed our list of temperature-sensitive microbes by comparing the results from this laboratory experiment with data compiled from 210 soils representing multiple, independent global field studies sampled across spatial gradients with a wide range in mean annual temperatures. Our results reveal predictable and consistent responses to temperature for a core group of 189 ubiquitous soil bacterial and archaeal taxa, with these taxa exhibiting similar temperature responses across a broad range of soil types. These microbial 'bioindicators' are useful for understanding how soil microbial communities respond to warming and to discriminate between the direct and indirect effects of soil warming on microbial communities. Those taxa that were found to be sensitive to temperature represented a wide range of lineages and the direction of the temperature responses were not predictable from phylogeny alone, indicating that temperature responses are difficult to predict from simply describing soil microbial communities at broad taxonomic or phylogenetic levels of resolution. Together, these results lay the foundation for a more predictive understanding of how soil microbial communities respond to soil warming and how warming may ultimately lead to changes in soil biogeochemical processes. © 2016 John Wiley & Sons Ltd.

Impact of the 3 °C temperature rise on bacterial growth and carbon transfer towards higher trophic levels: Empirical models for the Adriatic Sea

NASA Astrophysics Data System (ADS)

Šolić, Mladen; Krstulović, Nada; Šantić, Danijela; Šestanović, Stefanija; Kušpilić, Grozdan; Bojanić, Natalia; Ordulj, Marin; Jozić, Slaven; Vrdoljak, Ana

2017-09-01

The Mediterranean Sea (including the Adriatic Sea) has been identified as a 'hotspot' for climate change, with the prediction of the increase in water temperature of 2-4 °C over the next few decades. Being mainly oligotrophic, and strongly phosphorus limited, the Adriatic Sea is characterized by the important role of the microbial food web in production and transfer of biomass and energy towards higher trophic levels. We hypothesized that predicted 3 °C temperature rise in the near future might cause an increase of bacterial production and bacterial losses to grazers, which could significantly enlarge the trophic base for metazoans. This empirical study is based on a combined 'space-for-time substitution' analysis (which is performed on 3583 data sets) and on an experimental approach (36 in situ grazing experiments performed at different temperatures). It showed that the predicted 3 °C temperature increase (which is a result of global warming) in the near future could cause a significant increase in bacterial growth at temperatures lower than 16 °C (during the colder winter-spring period, as well as in the deeper layers). The effect of temperature on bacterial growth could be additionally doubled in conditions without phosphorus limitation. Furthermore, a 3 °C increase in temperature could double the grazing on bacteria by heterotrophic nanoflagellate (HNF) and ciliate predators and it could increase the proportion of bacterial production transferred to the metazoan food web by 42%. Therefore, it is expected that global warming may further strengthen the role of the microbial food web in a carbon cycle in the Adriatic Sea.

Conventional and simplified canopy temperature indices predict water stress in sunflower

USDA-ARS?s Scientific Manuscript database

Two indicators based on remotely-sensed canopy temperature were used in northern Colorado to monitor water stress in sunflower under six levels of regulated deficit irrigation. The two indicators included the widely-used Crop Water Stress Index (CWSI) and the new Degrees Above Non-stressed Canopy at...

Closed-form solution of temperature and heat flux in embedded cooling channels

NASA Astrophysics Data System (ADS)

Griggs, Steven Craig

1997-11-01

An analytical method is discussed for predicting temperature in a layered composite material with embedded cooling channels. The cooling channels are embedded in the material to maintain its temperature at acceptable levels. Problems of this type are encountered in the aerospace industry and include high-temperature or high-heat-flux protection for advanced composite-material skins of high-speed air vehicles; thermal boundary-layer flow control on supersonic transports; or infrared signature suppression on military vehicles. A Green's function solution of the diffusion equation is used to simultaneously predict the global and localized effects of temperature in the material and in the embedded cooling channels. The integral method is used to solve the energy equation with fluid flow to find the solution of temperature and heat flux in the cooling fluid and material simultaneously. This method of calculation preserves the three-dimensional nature of this problem.

An attempt to model the probability of growth and aflatoxin B1 production of Aspergillus flavus under non-isothermal conditions in pistachio nuts.

PubMed

Aldars-García, Laila; Ramos, Antonio J; Sanchis, Vicente; Marín, Sonia

2015-10-01

Human exposure to aflatoxins in foods is of great concern. The aim of this work was to use predictive mycology as a strategy to mitigate the aflatoxin burden in pistachio nuts postharvest. The probability of growth and aflatoxin B1 (AFB1) production of aflatoxigenic Aspergillus flavus, isolated from pistachio nuts, under static and non-isothermal conditions was studied. Four theoretical temperature scenarios, including temperature levels observed in pistachio nuts during shipping and storage, were used. Two types of inoculum were included: a cocktail of 25 A. flavus isolates and a single isolate inoculum. Initial water activity was adjusted to 0.87. Logistic models, with temperature and time as explanatory variables, were fitted to the probability of growth and AFB1 production under a constant temperature. Subsequently, they were used to predict probabilities under non-isothermal scenarios, with levels of concordance from 90 to 100% in most of the cases. Furthermore, the presence of AFB1 in pistachio nuts could be correctly predicted in 70-81 % of the cases from a growth model developed in pistachio nuts, and in 67-81% of the cases from an AFB1 model developed in pistachio agar. The information obtained in the present work could be used by producers and processors to predict the time for AFB1 production by A. flavus on pistachio nuts during transport and storage. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Statistical Model-Based Decision Support System for Managing Summer Stream Temperatures with Quantified Confidence Analysis

NASA Astrophysics Data System (ADS)

Neumann, D. W.; Zagona, E. A.; Rajagopalan, B.

2005-12-01

Warm summer stream temperatures due to low flows and high air temperatures are a critical water quality problem in many western U.S. river basins because they impact threatened fish species' habitat. Releases from storage reservoirs and river diversions are typically driven by human demands such as irrigation, municipal and industrial uses and hydropower production. Historically, fish needs have not been formally incorporated in the operating procedures, which do not supply adequate flows for fish in the warmest, driest periods. One way to address this problem is for local and federal organizations to purchase water rights to be used to increase flows, hence decrease temperatures. A statistical model-predictive technique for efficient and effective use of a limited supply of fish water has been developed and incorporated in a Decision Support System (DSS) that can be used in an operations mode to effectively use water acquired to mitigate warm stream temperatures. The DSS is a rule-based system that uses the empirical, statistical predictive model to predict maximum daily stream temperatures based on flows that meet the non-fish operating criteria, and to compute reservoir releases of allocated fish water when predicted temperatures exceed fish habitat temperature targets with a user specified confidence of the temperature predictions. The empirical model is developed using a step-wise linear regression procedure to select significant predictors, and includes the computation of a prediction confidence interval to quantify the uncertainty of the prediction. The DSS also includes a strategy for managing a limited amount of water throughout the season based on degree-days in which temperatures are allowed to exceed the preferred targets for a limited number of days that can be tolerated by the fish. The DSS is demonstrated by an example application to the Truckee River near Reno, Nevada using historical flows from 1988 through 1994. In this case, the statistical model predicts maximum daily Truckee River stream temperatures in June, July, and August using predicted maximum daily air temperature and modeled average daily flow. The empirical relationship was created using a step-wise linear regression selection process using 1993 and 1994 data. The adjusted R2 value for this relationship is 0.91. The model is validated using historic data and demonstrated in a predictive mode with a prediction confidence interval to quantify the uncertainty. Results indicate that the DSS could substantially reduce the number of target temperature violations, i.e., stream temperatures exceeding the target temperature levels detrimental to fish habitat. The results show that large volumes of water are necessary to meet a temperature target with a high degree of certainty and violations may still occur if all of the stored water is depleted. A lower degree of certainty requires less water but there is a higher probability that the temperature targets will be exceeded. Addition of the rules that consider degree-days resulted in a reduction of the number of temperature violations without increasing the amount of water used. This work is described in detail in publications referenced in the URL below.

Review of temperature dependence of thermal properties, dielectric properties, and perfusion of biological tissues at hyperthermic and ablation temperatures.

PubMed

Rossmanna, Christian; Haemmerich, Dieter

2014-01-01

The application of supraphysiological temperatures (>40°C) to biological tissues causes changes at the molecular, cellular, and structural level, with corresponding changes in tissue function and in thermal, mechanical and dielectric tissue properties. This is particularly relevant for image-guided thermal treatments (e.g. hyperthermia and thermal ablation) delivering heat via focused ultrasound (FUS), radiofrequency (RF), microwave (MW), or laser energy; temperature induced changes in tissue properties are of relevance in relation to predicting tissue temperature profile, monitoring during treatment, and evaluation of treatment results. This paper presents a literature survey of temperature dependence of electrical (electrical conductivity, resistivity, permittivity) and thermal tissue properties (thermal conductivity, specific heat, diffusivity). Data of soft tissues (liver, prostate, muscle, kidney, uterus, collagen, myocardium and spleen) for temperatures between 5 to 90°C, and dielectric properties in the frequency range between 460 kHz and 3 GHz are reported. Furthermore, perfusion changes in tumors including carcinomas, sarcomas, rhabdomyosarcoma, adenocarcinoma and ependymoblastoma in response to hyperthmic temperatures up to 46°C are presented. Where appropriate, mathematical models to describe temperature dependence of properties are presented. The presented data is valuable for mathematical models that predict tissue temperature during thermal therapies (e.g. hyperthermia or thermal ablation), as well as for applications related to prediction and monitoring of temperature induced tissue changes.

Review of temperature dependence of thermal properties, dielectric properties, and perfusion of biological tissues at hyperthermic and ablation temperatures

PubMed Central

Rossmann, Christian; Haemmerich, Dieter

2016-01-01

The application of supraphysiological temperatures (>40°C) to biological tissues causes changes at the molecular, cellular, and structural level, with corresponding changes in tissue function and in thermal, mechanical and dielectric tissue properties. This is particularly relevant for image-guided thermal treatments (e.g. hyperthermia and thermal ablation) delivering heat via focused ultrasound (FUS), radiofrequency (RF), microwave (MW), or laser energy; temperature induced changes in tissue properties are of relevance in relation to predicting tissue temperature profile, monitoring during treatment, and evaluation of treatment results. This paper presents a literature survey of temperature dependence of electrical (electrical conductivity, resistivity, permittivity) and thermal tissue properties (thermal conductivity, specific heat, diffusivity). Data of soft tissues (liver, prostate, muscle, kidney, uterus, collagen, myocardium and spleen) for temperatures between 5 to 90°C, and dielectric properties in the frequency range between 460 kHz and 3 GHz are reported. Furthermore, perfusion changes in tumors including carcinomas, sarcomas, rhabdomyosarcoma, adenocarcinoma and ependymoblastoma in response to hyperthmic temperatures up to 46°C are presented. Where appropriate, mathematical models to describe temperature dependence of properties are presented. The presented data is valuable for mathematical models that predict tissue temperature during thermal therapies (e.g. hyperthermia or thermal ablation), as well as for applications related to prediction and monitoring of temperature induced tissue changes. PMID:25955712

Leuconostoc mesenteroides growth in food products: prediction and sensitivity analysis by adaptive-network-based fuzzy inference systems.

PubMed

Wang, Hue-Yu; Wen, Ching-Feng; Chiu, Yu-Hsien; Lee, I-Nong; Kao, Hao-Yun; Lee, I-Chen; Ho, Wen-Hsien

2013-01-01

An adaptive-network-based fuzzy inference system (ANFIS) was compared with an artificial neural network (ANN) in terms of accuracy in predicting the combined effects of temperature (10.5 to 24.5°C), pH level (5.5 to 7.5), sodium chloride level (0.25% to 6.25%) and sodium nitrite level (0 to 200 ppm) on the growth rate of Leuconostoc mesenteroides under aerobic and anaerobic conditions. THE ANFIS AND ANN MODELS WERE COMPARED IN TERMS OF SIX STATISTICAL INDICES CALCULATED BY COMPARING THEIR PREDICTION RESULTS WITH ACTUAL DATA: mean absolute percentage error (MAPE), root mean square error (RMSE), standard error of prediction percentage (SEP), bias factor (Bf), accuracy factor (Af), and absolute fraction of variance (R (2)). Graphical plots were also used for model comparison. The learning-based systems obtained encouraging prediction results. Sensitivity analyses of the four environmental factors showed that temperature and, to a lesser extent, NaCl had the most influence on accuracy in predicting the growth rate of Leuconostoc mesenteroides under aerobic and anaerobic conditions. The observed effectiveness of ANFIS for modeling microbial kinetic parameters confirms its potential use as a supplemental tool in predictive mycology. Comparisons between growth rates predicted by ANFIS and actual experimental data also confirmed the high accuracy of the Gaussian membership function in ANFIS. Comparisons of the six statistical indices under both aerobic and anaerobic conditions also showed that the ANFIS model was better than all ANN models in predicting the four kinetic parameters. Therefore, the ANFIS model is a valuable tool for quickly predicting the growth rate of Leuconostoc mesenteroides under aerobic and anaerobic conditions.

Leuconostoc Mesenteroides Growth in Food Products: Prediction and Sensitivity Analysis by Adaptive-Network-Based Fuzzy Inference Systems

PubMed Central

Wang, Hue-Yu; Wen, Ching-Feng; Chiu, Yu-Hsien; Lee, I-Nong; Kao, Hao-Yun; Lee, I-Chen; Ho, Wen-Hsien

2013-01-01

Background An adaptive-network-based fuzzy inference system (ANFIS) was compared with an artificial neural network (ANN) in terms of accuracy in predicting the combined effects of temperature (10.5 to 24.5°C), pH level (5.5 to 7.5), sodium chloride level (0.25% to 6.25%) and sodium nitrite level (0 to 200 ppm) on the growth rate of Leuconostoc mesenteroides under aerobic and anaerobic conditions. Methods The ANFIS and ANN models were compared in terms of six statistical indices calculated by comparing their prediction results with actual data: mean absolute percentage error (MAPE), root mean square error (RMSE), standard error of prediction percentage (SEP), bias factor (Bf), accuracy factor (Af), and absolute fraction of variance (R 2). Graphical plots were also used for model comparison. Conclusions The learning-based systems obtained encouraging prediction results. Sensitivity analyses of the four environmental factors showed that temperature and, to a lesser extent, NaCl had the most influence on accuracy in predicting the growth rate of Leuconostoc mesenteroides under aerobic and anaerobic conditions. The observed effectiveness of ANFIS for modeling microbial kinetic parameters confirms its potential use as a supplemental tool in predictive mycology. Comparisons between growth rates predicted by ANFIS and actual experimental data also confirmed the high accuracy of the Gaussian membership function in ANFIS. Comparisons of the six statistical indices under both aerobic and anaerobic conditions also showed that the ANFIS model was better than all ANN models in predicting the four kinetic parameters. Therefore, the ANFIS model is a valuable tool for quickly predicting the growth rate of Leuconostoc mesenteroides under aerobic and anaerobic conditions. PMID:23705023

Macroalgal response to a warmer ocean with higher CO2 concentration.

PubMed

Hernández, Celso A; Sangil, Carlos; Fanai, Alessandra; Hernández, José Carlos

2018-05-01

Primary production and respiration rates were studied for six seaweed species (Cystoseira abies-marina, Lobophora variegata, Pterocladiella capillacea, Canistrocarpus cervicornis, Padina pavonica and Corallina caespitosa) from Subtropical North-East Atlantic, to estimate the combined effects of different pH and temperature levels. Macroalgal samples were cultured at temperature and pH combinations ranging from current levels to those predicted for the next century (19, 21, 23, 25 °C, pH: 8.1, 7.7 and 7.4). Decreased pH had a positive effect on short-term production of the studied species. Raised temperatures had a more varied and species dependent effect on short term primary production. Thermophilic algae increased their production at higher temperatures, while temperate species were more productive at lower or present temperature conditions. Temperature also affected algal respiration rates, which were higher at low temperature levels. The results suggest that biomass and productivity of the more tropical species in coastal ecosystems would be enhanced by future ocean conditions. Copyright © 2018 Elsevier Ltd. All rights reserved.

A neighborhood statistics model for predicting stream pathogen indicator levels.

PubMed

Pandey, Pramod K; Pasternack, Gregory B; Majumder, Mahbubul; Soupir, Michelle L; Kaiser, Mark S

2015-03-01

Because elevated levels of water-borne Escherichia coli in streams are a leading cause of water quality impairments in the U.S., water-quality managers need tools for predicting aqueous E. coli levels. Presently, E. coli levels may be predicted using complex mechanistic models that have a high degree of unchecked uncertainty or simpler statistical models. To assess spatio-temporal patterns of instream E. coli levels, herein we measured E. coli, a pathogen indicator, at 16 sites (at four different times) within the Squaw Creek watershed, Iowa, and subsequently, the Markov Random Field model was exploited to develop a neighborhood statistics model for predicting instream E. coli levels. Two observed covariates, local water temperature (degrees Celsius) and mean cross-sectional depth (meters), were used as inputs to the model. Predictions of E. coli levels in the water column were compared with independent observational data collected from 16 in-stream locations. The results revealed that spatio-temporal averages of predicted and observed E. coli levels were extremely close. Approximately 66 % of individual predicted E. coli concentrations were within a factor of 2 of the observed values. In only one event, the difference between prediction and observation was beyond one order of magnitude. The mean of all predicted values at 16 locations was approximately 1 % higher than the mean of the observed values. The approach presented here will be useful while assessing instream contaminations such as pathogen/pathogen indicator levels at the watershed scale.

Integrated Advance Microwave Sounding Unit-A (AMSU-A). Performance Verification Report: EOS AMSU-A1 and AMSU-A2 Receivers Assemblies

NASA Technical Reports Server (NTRS)

2000-01-01

This test report presents the test data of the EOS AMSU-A Flight Model No.1 (FM-1) receiver subsystem. The tests are performed per the Acceptance Test Procedure for the AMSU-A Reseiver Subsystem, AE-26002/6A. The functional performance tests are conducted either at the component or subsystem level. While the component-level tests are performed over the entire operating temperature range predicted by thermal analysis, the subsystem-level test are conducted at ambient temperature only.

Sleep and Predicted Cognitive Performance of New Cadets during Cadet Basic Training at the United States Military Academy

DTIC Science & Technology

2005-09-01

7 B. SLEEP ARCHITECTURE..................................7 1. Circadian Rhythm and Human Sleep Drive...body temperature. Van Dongen & Dinges, 2000 ....10 Figure 2. EEG of Human Brain Activity During Sleep. http://ist-socrates.berkeley.edu/~jmp...the predicted levels of human performance based on circadian rhythms , amount and quality of sleep, and combines cognitive performance 5 predictions

Relationship between the humidity and temperature of inspired gas and the function of the airway mucosa.

PubMed

Williams, R; Rankin, N; Smith, T; Galler, D; Seakins, P

1996-11-01

To review the available literature on the relationship between the humidity and temperature of inspired gas and airway mucosal function. International computerized databases and published indices, experts in the field, conference proceedings, bibliographies. Two hundred articles/texts on respiratory tract physiology and humidification were reviewed. Seventeen articles were selected from 40 articles for inclusion in the published data verification of the model. Selection was by independent reviewers. Extraction was by consensus, and was based on finding sufficient data. A relationship exists between inspired gas humidity and temperature, exposure time to a given humidity level, and mucosal function. This relationship can be modeled and represented as an inspired humidity magnitude vs. exposure time map. The model is predictive of mucosal function and can be partially verified by the available literature. It predicts that if inspired humidity deviates from an optimal level, a progressive mucosal dysfunction begins. The greater the humidity deviation, the faster the mucosal dysfunction progresses. A model for the relationship between airway mucosal dysfunction and the combination of the humidity of inspired gas and the duration over which the airway mucosa is exposed to that humidity is proposed. This model suggests that there is an optimal temperature and humidity above which, and below which, there is impaired mucosal function. This optimal level of temperature and humidity is core temperature and 100% relative humidity. However, existing data are only sufficient to test this model for gas conditions below core temperature and 100% relative humidity. These data concur with the model in that region. No studies have yet looked at this relationship beyond 24 hrs. Longer exposure times to any given level of inspired humidity and inspired gas temperatures and humidities above core temperature and 100% relative humidity need to be studied to fully verify the proposed model.

Linking the Response of Annual Grasslands to Warming and Altered Rainfall Across Scales of Gene Expression, Species, and Ecosystem

NASA Astrophysics Data System (ADS)

Torn, M. S.; Bernard, S. M.; Castanha, C.; Fischer, M. L.; Hopkins, F. M.; Placella, S. A.; St. Clair, S. B.; Salve, R.; Sudderth, E.; Herman, D.; Ackerly, D.; Firestone, M. K.

2007-12-01

Climate change can influence terrestrial ecosystems at multiple biological levels: gene expression, species, and ecosystem. We are studying California grassland mesocosms with seven annual species (five grasses, two forbs) that were started in 2005. In the 2006-2007 growing season, they were exposed to three rainfall treatments (297, 552, and 867 mm y-1) and soil and air temperature (ambient and elevated +4oC) in replicated greenhouses. This presentation will combine plant and ecosystem level results with transcript level analyses associated with key enzymes, such as rubisco and glutamine synthetase (GS). Because rainfall is the dominant climate variable for most processes in this Mediterranean ecosystem, the effect of warming was strongly mediated by rainfall. In fact, we saw significant interactions between temperature and rainfall treatments at all three biological levels. For example, at the ecosystem level, warming led to a decrease in aboveground and total NPP under low rainfall, and an increase under high rainfall. For the dominant species, Avena barbata, warming had no effect under high rainfall, but suppressed Avena NPP in low rainfall. At the same time, warmer, wetter conditions accelerated Avena flowering by almost 15 days. This shift in phenology was presaged by observations at the transcript level. Specifically, in the high temperature, high rainfall treatment, the levels of mRNAs for RbcS and GS2 (encoding the small subunit of rubisco and the chloroplastic isoform of GS, respectively) declined while GS1 (encoding the cytosolic isoform of GS) was upregulated several weeks before heading. The transcript level response (along with soil and plant nitrogen data) indicated the leaf had switched from a carbon and nitrogen sink to a source - consistent with more mature plant function and earlier flowering. Soil CO2 respiration also showed strong rain-by-temperature interactions that were due mainly to changes in root response (respiration and/or exudates) rather than in microbial respiration. Overall, the pervasive rain-by-temperature interactions mean that it may be very difficult to predict the effect of warming alone, without accounting for changes in precipitation (in our Mediterranean system). While predictions of warming of 3-6°C in the next 100 years are fairly certain, changes in precipitation are much more uncertain, with some forecasts drier and others wetter for a given location. We suggest that uncertainty about future precipitation and the interacting influences of temperature and moisture on ecosystems are currently key limitations in predicting ecosystem response to climate change, particularly in Mediterranean ecosystems such as the one studied here.

Effects of soil temperature and depth to ground water on first-year growth of a dryland riparian phreatophyte, Glycyrrhiza lepidota (American licorice)

USGS Publications Warehouse

Andersen, Douglas C.; Nelson, S. Mark

2014-01-01

We investigated the effects of soil temperature and depth to ground water on first-year growth of a facultative floodplain phreatophyte, Glycyrrhiza lepidota, in a 2-×-2 factorial greenhouse experiment. We grew plants in mesocosms subirrigated with water low in dissolved oxygen, mimicking natural systems, and set depth of ground water at 63 or 100 cm and soil temperature at cold (ambient) or warm (≤2.7°C above ambient). We hypothesized the moister (63 cm) and warmer soil would be most favorable and predicted faster growth of shoots and roots and greater nitrogen-fixation (thus, less uptake of mineral nitrogen) under those conditions. Growth in height was significantly faster in the moister treatment but was not affected by soil temperature. Final biomass of shoots and of roots, total biomass of plants, and root:shoot ratio indicated a significant effect only from depth of ground water. Final levels of soil mineral-nitrogen were as predicted, with level of nitrate in the moister treatment more than twice that in the drier treatment. No effect from soil temperature on level of soil-mineral nitrogen was detected. Our results suggest that establishment of G. lepidotarequires strict conditions of soil moisture, which may explain the patchy distribution of the species along southwestern dryland rivers.

Species and temperature measurement in H2/O2 rocket flow fields by means of Raman scattering diagnostics

NASA Technical Reports Server (NTRS)

De Groot, Wim A.; Weiss, Jonathan M.

1992-01-01

Validation of CFD codes developed for prediction and evaluation of rocket performance is hampered by a lack of experimental data. Nonintrusive laser based diagnostics are needed to provide spatially and temporally resolved gas dynamic and fluid dynamic measurements. This paper reports the first nonintrusive temperature and species measurements in the plume of a 110 N gaseous hydrogen/oxygen thruster at and below ambient pressures, obtained with spontaneous Raman spectroscopy. Measurements at 10 mm downstream of the exit plane are compared with predictions from a numerical solution of the axisymmetric Navier-Stokes and species transport equations with chemical kinetics, which fully model the combustor-nozzle-plume flowfield. The experimentally determined oxygen number density at the centerline at 10 mm downstream of the exit plane is four times that predicted by the model. The experimental number density data fall between those numerically predicted for the exit and 10 mm downstream planes in both magnitude and radial gradient. The predicted temperature levels are within 10 to 15 percent of measured values.

Loggerhead sea turtle environmental sex determination: implications of moisture and temperature for climate change based predictions for species survival.

PubMed

Wyneken, Jeanette; Lolavar, Alexandra

2015-05-01

It has been proposed that because marine turtles have environmentally determined sex by incubation temperature, elevated temperatures might skew sex ratios to unsustainable levels, leading to extinction. Elevated temperatures may also reduce availability of suitable nesting sites via sea level rise. Increased tropical storm activity can directly affect nest site moisture, embryonic development, and the probability that nests will survive. Here, we question some of these assumptions and review the limits of sex ratio estimates. Sea turtles may be more resilient to climate change than previously thought, in part because of hitherto unappreciated mechanisms for coping with variable incubation conditions. © 2015 Wiley Periodicals, Inc.

Probabilistic micromechanics for metal matrix composites

NASA Astrophysics Data System (ADS)

Engelstad, S. P.; Reddy, J. N.; Hopkins, Dale A.

A probabilistic micromechanics-based nonlinear analysis procedure is developed to predict and quantify the variability in the properties of high temperature metal matrix composites. Monte Carlo simulation is used to model the probabilistic distributions of the constituent level properties including fiber, matrix, and interphase properties, volume and void ratios, strengths, fiber misalignment, and nonlinear empirical parameters. The procedure predicts the resultant ply properties and quantifies their statistical scatter. Graphite copper and Silicon Carbide Titanlum Aluminide (SCS-6 TI15) unidirectional plies are considered to demonstrate the predictive capabilities. The procedure is believed to have a high potential for use in material characterization and selection to precede and assist in experimental studies of new high temperature metal matrix composites.

Effects of winter temperatures on gypsy moth egg masses in the Great Lakes region of the United States.

Treesearch

J.A. Andresen; D.G. McCullough; B.E. Potter; C.N. Koller; L.S. Bauer; C. W. Ramm

2001-01-01

Accurate prediction of winter survival of gypsy moth (Lymantria dispar L.) eggs and phenology of egg hatch in spring are strongly dependent on temperature and are critical aspects of gypsy moth management programs. We monitored internal temperatures of egg masses at three heights aboveground level and at the four cardinal aspects on oak tree stems at two different...

Prediction of summer maximum and minimum temperature over the central and western United States: the roles of soil moisture and sea surface temperature

USGS Publications Warehouse

Alfaro, Eric J.; Gershunov, Alexander; Cayan, Daniel R.

2006-01-01

A statistical model based on canonical correlation analysis (CCA) was used to explore climatic associations and predictability of June–August (JJA) maximum and minimum surface air temperatures (Tmax and Tmin) as well as the frequency of Tmax daily extremes (Tmax90) in the central and western United States (west of 90°W). Explanatory variables are monthly and seasonal Pacific Ocean SST (PSST) and the Climate Division Palmer Drought Severity Index (PDSI) during 1950–2001. Although there is a positive correlation between Tmax and Tmin, the two variables exhibit somewhat different patterns and dynamics. Both exhibit their lowest levels of variability in summer, but that of Tmax is greater than Tmin. The predictability of Tmax is mainly associated with local effects related to previous soil moisture conditions at short range (one month to one season), with PSST providing a secondary influence. Predictability of Tmin is more strongly influenced by large-scale (PSST) patterns, with PDSI acting as a short-range predictive influence. For both predictand variables (Tmax and Tmin), the PDSI influence falls off markedly at time leads beyond a few months, but a PSST influence remains for at least two seasons. The maximum predictive skill for JJA Tmin, Tmax, and Tmax90 is from May PSST and PDSI. Importantly, skills evaluated for various seasons and time leads undergo a seasonal cycle that has maximum levels in summer. At the seasonal time frame, summer Tmax prediction skills are greatest in the Midwest, northern and central California, Arizona, and Utah. Similar results were found for Tmax90. In contrast, Tmin skill is spread over most of the western region, except for clusters of low skill in the northern Midwest and southern Montana, Idaho, and northern Arizona.

Prediction of Human Performance Using Electroencephalography under Different Indoor Room Temperatures

PubMed Central

Zhang, Tinghe; Mao, Zijing; Xu, Xiaojing; Zhang, Lin; Pack, Daniel J.; Dong, Bing; Huang, Yufei

2018-01-01

Varying indoor environmental conditions is known to affect office worker’s performance; wherein past research studies have reported the effects of unfavorable indoor temperature and air quality causing sick building syndrome (SBS) among office workers. Thus, investigating factors that can predict performance in changing indoor environments have become a highly important research topic bearing significant impact in our society. While past research studies have attempted to determine predictors for performance, they do not provide satisfactory prediction ability. Therefore, in this preliminary study, we attempt to predict performance during office-work tasks triggered by different indoor room temperatures (22.2 °C and 30 °C) from human brain signals recorded using electroencephalography (EEG). Seven participants were recruited, from whom EEG, skin temperature, heart rate and thermal survey questionnaires were collected. Regression analyses were carried out to investigate the effectiveness of using EEG power spectral densities (PSD) as predictors of performance. Our results indicate EEG PSDs as predictors provide the highest R2 (> 0.70), that is 17 times higher than using other physiological signals as predictors and is more robust. Finally, the paper provides insight on the selected predictors based on brain activity patterns for low- and high-performance levels under different indoor-temperatures. PMID:29690601

Prediction of Human Performance Using Electroencephalography under Different Indoor Room Temperatures.

PubMed

Nayak, Tapsya; Zhang, Tinghe; Mao, Zijing; Xu, Xiaojing; Zhang, Lin; Pack, Daniel J; Dong, Bing; Huang, Yufei

2018-04-23

Varying indoor environmental conditions is known to affect office worker’s performance; wherein past research studies have reported the effects of unfavorable indoor temperature and air quality causing sick building syndrome (SBS) among office workers. Thus, investigating factors that can predict performance in changing indoor environments have become a highly important research topic bearing significant impact in our society. While past research studies have attempted to determine predictors for performance, they do not provide satisfactory prediction ability. Therefore, in this preliminary study, we attempt to predict performance during office-work tasks triggered by different indoor room temperatures (22.2 °C and 30 °C) from human brain signals recorded using electroencephalography (EEG). Seven participants were recruited, from whom EEG, skin temperature, heart rate and thermal survey questionnaires were collected. Regression analyses were carried out to investigate the effectiveness of using EEG power spectral densities (PSD) as predictors of performance. Our results indicate EEG PSDs as predictors provide the highest R ² (> 0.70), that is 17 times higher than using other physiological signals as predictors and is more robust. Finally, the paper provides insight on the selected predictors based on brain activity patterns for low- and high-performance levels under different indoor-temperatures.

Comparison of ArcGIS and SAS Geostatistical Analyst to Estimate Population-Weighted Monthly Temperature for US Counties

PubMed Central

Xiaopeng, QI; Liang, WEI; BARKER, Laurie; LEKIACHVILI, Akaki; Xingyou, ZHANG

2015-01-01

Temperature changes are known to have significant impacts on human health. Accurate estimates of population-weighted average monthly air temperature for US counties are needed to evaluate temperature’s association with health behaviours and disease, which are sampled or reported at the county level and measured on a monthly—or 30-day—basis. Most reported temperature estimates were calculated using ArcGIS, relatively few used SAS. We compared the performance of geostatistical models to estimate population-weighted average temperature in each month for counties in 48 states using ArcGIS v9.3 and SAS v 9.2 on a CITGO platform. Monthly average temperature for Jan-Dec 2007 and elevation from 5435 weather stations were used to estimate the temperature at county population centroids. County estimates were produced with elevation as a covariate. Performance of models was assessed by comparing adjusted R2, mean squared error, root mean squared error, and processing time. Prediction accuracy for split validation was above 90% for 11 months in ArcGIS and all 12 months in SAS. Cokriging in SAS achieved higher prediction accuracy and lower estimation bias as compared to cokriging in ArcGIS. County-level estimates produced by both packages were positively correlated (adjusted R2 range=0.95 to 0.99); accuracy and precision improved with elevation as a covariate. Both methods from ArcGIS and SAS are reliable for U.S. county-level temperature estimates; However, ArcGIS’s merits in spatial data pre-processing and processing time may be important considerations for software selection, especially for multi-year or multi-state projects. PMID:26167169

The Effects of Temperature on Political Violence: Global Evidence at the Subnational Level

PubMed Central

Bollfrass, Alexander; Shaver, Andrew

2015-01-01

A number of studies have demonstrated an empirical relationship between higher ambient temperatures and substate violence, which have been extrapolated to make predictions about the security implications of climate change. This literature rests on the untested assumption that the mechanism behind the temperature-conflict link is that disruption of agricultural production provokes local violence. Using a subnational-level dataset, this paper demonstrates that the relationship: (1) obtains globally, (2) exists at the substate level — provinces that experience positive temperature deviations see increased conflict; and (3) occurs even in regions without significant agricultural production. Diminished local farm output resulting from elevated temperatures is unlikely to account for the entire increase in substate violence. The findings encourage future research to identify additional mechanisms, including the possibility that a substantial portion of the variation is brought about by the well-documented direct effects of temperature on individuals' propensity for violence or through macroeconomic mechanisms such as food price shocks. PMID:25992616

Predictions of avian Plasmodium expansion under climate change.

PubMed

Loiseau, Claire; Harrigan, Ryan J; Bichet, Coraline; Julliard, Romain; Garnier, Stéphane; Lendvai, Adám Z; Chastel, Olivier; Sorci, Gabriele

2013-01-01

Vector-borne diseases are particularly responsive to changing environmental conditions. Diurnal temperature variation has been identified as a particularly important factor for the development of malaria parasites within vectors. Here, we conducted a survey across France, screening populations of the house sparrow (Passer domesticus) for malaria (Plasmodium relictum). We investigated whether variation in remotely-sensed environmental variables accounted for the spatial variation observed in prevalence and parasitemia. While prevalence was highly correlated to diurnal temperature range and other measures of temperature variation, environmental conditions could not predict spatial variation in parasitemia. Based on our empirical data, we mapped malaria distribution under climate change scenarios and predicted that Plasmodium occurrence will spread to regions in northern France, and that prevalence levels are likely to increase in locations where transmission already occurs. Our findings, based on remote sensing tools coupled with empirical data suggest that climatic change will significantly alter transmission of malaria parasites.

Creep behavior of bone cement: a method for time extrapolation using time-temperature equivalence.

PubMed

Morgan, R L; Farrar, D F; Rose, J; Forster, H; Morgan, I

2003-04-01

The clinical lifetime of poly(methyl methacrylate) (PMMA) bone cement is considerably longer than the time over which it is convenient to perform creep testing. Consequently, it is desirable to be able to predict the long term creep behavior of bone cement from the results of short term testing. A simple method is described for prediction of long term creep using the principle of time-temperature equivalence in polymers. The use of the method is illustrated using a commercial acrylic bone cement. A creep strain of approximately 0.6% is predicted after 400 days under a constant flexural stress of 2 MPa. The temperature range and stress levels over which it is appropriate to perform testing are described. Finally, the effects of physical aging on the accuracy of the method are discussed and creep data from aged cement are reported.

Re-analysis of the association of temperature or sunshine with hyperthymic temperament using lithium levels of drinking water.

PubMed

Matsuzaki, Hideki; Terao, Takeshi; Inoue, Takeshi; Takaesu, Yoshikazu; Ishii, Nobuyoshi; Kohno, Kentaro; Takeshima, Minoru; Baba, Hajime; Honma, Hiroshi

2017-12-01

The Japanese archipelago stretches over 4000km from north to south and has four large islands: Hokkaido, Honshu, Shikoku, and Kyushu. Previously, using the Temperament Evaluation of Memphis, Pisa, Paris and San Diego-auto questionnaire version (TEMPS-A), we compared the hyperthymic scores of residents in Sapporo, Obihiro, Takaoka, Koshigaya, and Oita cities (which are located at latitudes of 43°N, 42°N, 36°N, 36°N and 33°N with various combinations of ambient temperament and sunshine in Japan, respectively). We found that latitude predicted significant variance in hyperthymic temperament, and that ambient temperature, but not sunshine, significantly affected hyperthymic temperament scores. However, the analysis failed to consider the effects of naturally occurring low-dose lithium on temperament. In addition to the TEMPS-A data previously collected, we measured lithium levels of the five cities. The effect of temperature, sunshine, and lithium levels on hyperthymic temperament was analyzed for the five cities. A stepwise multiple regression analysis revealed that lithium levels as well as latitude, but not temperature or sunshine, predicted significant variance in hyperthymic temperament scores. Hyperthymic temperament scores were significantly and positively associated with lithium levels whereas they were significantly and negatively associated with latitude. The light, temperature, lithium exposure that residents actually received was not measured. The number of regions studied was limited. The findings might not be generalized to residents across Japan or other countries. The present findings suggest that lithium in drinking water may positively maintain hyperthymic temperament, and that latitude may negatively maintain it. Copyright © 2017 Elsevier B.V. All rights reserved.

Specialist-generalist model of body temperature regulation can be applied at the intraspecific level.

PubMed

Przybylska, Anna S; Boratyński, Jan S; Wojciechowski, Michał S; Jefimow, Małgorzata

2017-07-01

According to theoretical predictions, endothermic homeotherms can be classified as either thermal specialists or thermal generalists. In high cost environments, thermal specialists are supposed to be more prone to using facultative heterothermy than generalists. We tested this hypothesis at the intraspecific level using male laboratory mice (C57BL/cmdb) fasted under different thermal conditions (20 and 10°C) and for different time periods (12-48 h). We predicted that variability of body temperature ( T b ) and time spent with T b below normothermy would increase with the increase of environmental demands (duration of fasting and cold). To verify the above prediction, we measured T b and energy expenditure of fasted mice. We did not record torpor bouts but we found that variations in T b and time spent in hypothermia increased with environmental demands. In response to fasting, mice also decreased their energy expenditure. Moreover, animals that showed more precise thermoregulation when fed had more variable T b when fasted. We postulate that the prediction of the thermoregulatory generalist-specialist trade-off can be applied at the intraspecific level, offering a valid tool for identifying mechanistic explanations of the differences in animal responses to variations in energy supply. © 2017. Published by The Company of Biologists Ltd.

Skilful multi-year predictions of tropical trans-basin climate variability

PubMed Central

Chikamoto, Yoshimitsu; Timmermann, Axel; Luo, Jing-Jia; Mochizuki, Takashi; Kimoto, Masahide; Watanabe, Masahiro; Ishii, Masayoshi; Xie, Shang-Ping; Jin, Fei-Fei

2015-01-01

Tropical Pacific sea surface temperature anomalies influence the atmospheric circulation, impacting climate far beyond the tropics. The predictability of the corresponding atmospheric signals is typically limited to less than 1 year lead time. Here we present observational and modelling evidence for multi-year predictability of coherent trans-basin climate variations that are characterized by a zonal seesaw in tropical sea surface temperature and sea-level pressure between the Pacific and the other two ocean basins. State-of-the-art climate model forecasts initialized from a realistic ocean state show that the low-frequency trans-basin climate variability, which explains part of the El Niño Southern Oscillation flavours, can be predicted up to 3 years ahead, thus exceeding the predictive skill of current tropical climate forecasts for natural variability. This low-frequency variability emerges from the synchronization of ocean anomalies in all basins via global reorganizations of the atmospheric Walker Circulation. PMID:25897996

Skilful multi-year predictions of tropical trans-basin climate variability.

PubMed

Chikamoto, Yoshimitsu; Timmermann, Axel; Luo, Jing-Jia; Mochizuki, Takashi; Kimoto, Masahide; Watanabe, Masahiro; Ishii, Masayoshi; Xie, Shang-Ping; Jin, Fei-Fei

2015-04-21

Tropical Pacific sea surface temperature anomalies influence the atmospheric circulation, impacting climate far beyond the tropics. The predictability of the corresponding atmospheric signals is typically limited to less than 1 year lead time. Here we present observational and modelling evidence for multi-year predictability of coherent trans-basin climate variations that are characterized by a zonal seesaw in tropical sea surface temperature and sea-level pressure between the Pacific and the other two ocean basins. State-of-the-art climate model forecasts initialized from a realistic ocean state show that the low-frequency trans-basin climate variability, which explains part of the El Niño Southern Oscillation flavours, can be predicted up to 3 years ahead, thus exceeding the predictive skill of current tropical climate forecasts for natural variability. This low-frequency variability emerges from the synchronization of ocean anomalies in all basins via global reorganizations of the atmospheric Walker Circulation.

A basin-scale approach to estimating stream temperatures of tributaries to the lower Klamath River, California

USGS Publications Warehouse

Flint, L.E.; Flint, A.L.

2008-01-01

Stream temperature is an important component of salmonid habitat and is often above levels suitable for fish survival in the Lower Klamath River in northern California. The objective of this study was to provide boundary conditions for models that are assessing stream temperature on the main stem for the purpose of developing strategies to manage stream conditions using Total Maximum Daily Loads. For model input, hourly stream temperatures for 36 tributaries were estimated for 1 Jan. 2001 through 31 Oct. 2004. A basin-scale approach incorporating spatially distributed energy balance data was used to estimate the stream temperatures with measured air temperature and relative humidity data and simulated solar radiation, including topographic shading and corrections for cloudiness. Regression models were developed on the basis of available stream temperature data to predict temperatures for unmeasured periods of time and for unmeasured streams. The most significant factor in matching measured minimum and maximum stream temperatures was the seasonality of the estimate. Adding minimum and maximum air temperature to the regression model improved the estimate, and air temperature data over the region are available and easily distributed spatially. The addition of simulated solar radiation and vapor saturation deficit to the regression model significantly improved predictions of maximum stream temperature but was not required to predict minimum stream temperature. The average SE in estimated maximum daily stream temperature for the individual basins was 0.9 ?? 0.6??C at the 95% confidence interval. Copyright ?? 2008 by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America. All rights reserved.

Waning habitats due to climate change: the effects of changes in streamflow and temperature at the rear edge of the distribution of a cold-water fish

NASA Astrophysics Data System (ADS)

María Santiago, José; Muñoz-Mas, Rafael; Solana-Gutiérrez, Joaquín; García de Jalón, Diego; Alonso, Carlos; Martínez-Capel, Francisco; Pórtoles, Javier; Monjo, Robert; Ribalaygua, Jaime

2017-08-01

Climate changes affect aquatic ecosystems by altering temperatures and precipitation patterns, and the rear edges of the distributions of cold-water species are especially sensitive to these effects. The main goal of this study was to predict in detail how changes in air temperature and precipitation will affect streamflow, the thermal habitat of a cold-water fish (the brown trout, Salmo trutta), and the synergistic relationships among these variables at the rear edge of the natural distribution of brown trout. Thirty-one sites in 14 mountain rivers and streams were studied in central Spain. Models of streamflow were built for several of these sites using M5 model trees, and a non-linear regression method was used to estimate stream temperatures. Nine global climate models simulations for Representative Concentration Pathways RCP4.5 and RCP8.5 scenarios were downscaled to the local level. Significant reductions in streamflow were predicted to occur in all of the basins (max. -49 %) by the year 2099, and seasonal differences were noted between the basins. The stream temperature models showed relationships between the model parameters, geology and hydrologic responses. Temperature was sensitive to streamflow in one set of streams, and summer reductions in streamflow contributed to additional stream temperature increases (max. 3.6 °C), although the sites that are most dependent on deep aquifers will likely resist warming to a greater degree. The predicted increases in water temperatures were as high as 4.0 °C. Temperature and streamflow changes will cause a shift in the rear edge of the distribution of this species. However, geology will affect the extent of this shift. Approaches like the one used herein have proven to be useful in planning the prevention and mitigation of the negative effects of climate change by differentiating areas based on the risk level and viability of fish populations.

Use of differential scanning calorimetry to detect canola oil (Brassica napus L.) adulterated with lard stearin.

PubMed

Marikkar, Jalaldeen Mohammed Nazrim; Rana, Sohel

2014-01-01

A study was conducted to detect and quantify lard stearin (LS) content in canola oil (CaO) using differential scanning calorimetry (DSC). Authentic samples of CaO were obtained from a reliable supplier and the adulterant LS were obtained through a fractional crystallization procedure as reported previously. Pure CaO samples spiked with LS in levels ranging from 5 to 15% (w/w) were analyzed using DSC to obtain their cooling and heating profiles. The results showed that samples contaminated with LS at 5% (w/w) level can be detected using characteristic contaminant peaks appearing in the higher temperature regions (0 to 70°C) of the cooling and heating curves. Pearson correlation analysis of LS content against individual DSC parameters of the adulterant peak namely peak temperature, peak area, peak onset temperature indicated that there were strong correlations between these with the LS content of the CaO admixtures. When these three parameters were engaged as variables in the execution of the stepwise regression procedure, predictive models for determination of LS content in CaO were obtained. The predictive models obtained with single DSC parameter had relatively lower coefficient of determination (R(2) value) and higher standard error than the models obtained using two DSC parameters in combination. This study concluded that the predictive models obtained with peak area and peak onset temperature of the adulteration peak would be more accurate for prediction of LS content in CaO based on the highest coefficient of determination (R(2) value) and smallest standard error.

Comparison of primary zone combustor liner wall temperatures with calculated predictions

NASA Technical Reports Server (NTRS)

Norgren, C. T.

1973-01-01

Calculated liner temperatures based on a steady-state radiative and convective heat balance at the liner wall were compared with experimental values. Calculated liner temperatures were approximately 8 percent higher than experimental values. A radiometer was used to experimentally determine values of flame temperature and flame emissivity. Film cooling effectiveness was calculated from an empirical turbulent mixing expression assuming a turbulent mixing level of 2 percent. Liner wall temperatures were measured in a rectangular combustor segment 6 by 12 in. and tested at pressures up to 26.7 atm and inlet temperatures up to 922 K.

Matematical modeling of galophytic plants productivity taking into account the temperature factor and soil salinity level

NASA Astrophysics Data System (ADS)

Natalia, Slyusar; Pisman, Tamara; Pechurkin, Nikolai S.

Among the most challenging tasks faced by contemporary ecology is modeling of biological production process in different plant communities. The difficulty of the task is determined by the complexity of the study material. Models showing the influence of climate and climate change on plant growth, which would also involve soil site parameters, could be of both practical and theoretical interest. In this work a mathematical model has been constructed to describe the growth dynamics of different plant communities of halophytic meadows as dependent upon the temperature factor and soil salinity level, which could be further used to predict yields of these plant communities. The study was performed on plants of halophytic meadows in the coastal area of Lake of the Republic of Khakasia in 2004 - 2006. Every plant community grew on the soil of a different level of salinity - the amount of the solid residue of the saline soil aqueous extract. The mathematical model was analyzed using field data of 2004 and 2006, the years of contrasting air temperatures. Results of model investigations show that there is a correlation between plant growth and the temperature of the air for plant communities growing on soils containing the lowest (0.1Thus, results of our study, in which we used a mathematical model describing the development of plant communities of halophytic meadows and field measurements, suggest that both climate conditions (temperature) and ecological factors of the plants' habitat (soil salinity level) should be taken into account when constructing models for predicting crop yields.

Detection of polarization in the cosmic microwave background using DASI. Degree Angular Scale Interferometer.

PubMed

Kovac, J M; Leitch, E M; Pryke, C; Carlstrom, J E; Halverson, N W; Holzapfel, W L

The past several years have seen the emergence of a standard cosmological model, in which small temperature differences in the cosmic microwave background (CMB) radiation on angular scales of the order of a degree are understood to arise from acoustic oscillations in the hot plasma of the early Universe, arising from primordial density fluctuations. Within the context of this model, recent measurements of the temperature fluctuations have led to profound conclusions about the origin, evolution and composition of the Universe. Using the measured temperature fluctuations, the theoretical framework predicts the level of polarization of the CMB with essentially no free parameters. Therefore, a measurement of the polarization is a critical test of the theory and thus of the validity of the cosmological parameters derived from the CMB measurements. Here we report the detection of polarization of the CMB with the Degree Angular Scale Interferometer (DASI). The polarization is deteced with high confidence, and its level and spatial distribution are in excellent agreement with the predictions of the standard theory.

Climate change: overview of data sources, observed and predicted temperature changes, and impacts on public and environmental health

Treesearch

David H. Levinson; Christopher J. Fettig

2014-01-01

This chapter addresses the societal and the environmental impacts of climate change related to increasing surface temperatures on air quality and forest health. Increasing temperatures at and near the earth’s surface, due to both a warming climate and urban heat island effects, have been shown to increase ground-level ozone concentrations in cities across the U.S. In...

Long-memory and the sea level-temperature relationship: a fractional cointegration approach.

PubMed

Ventosa-Santaulària, Daniel; Heres, David R; Martínez-Hernández, L Catalina

2014-01-01

Through thermal expansion of oceans and melting of land-based ice, global warming is very likely contributing to the sea level rise observed during the 20th century. The amount by which further increases in global average temperature could affect sea level is only known with large uncertainties due to the limited capacity of physics-based models to predict sea levels from global surface temperatures. Semi-empirical approaches have been implemented to estimate the statistical relationship between these two variables providing an alternative measure on which to base potentially disrupting impacts on coastal communities and ecosystems. However, only a few of these semi-empirical applications had addressed the spurious inference that is likely to be drawn when one nonstationary process is regressed on another. Furthermore, it has been shown that spurious effects are not eliminated by stationary processes when these possess strong long memory. Our results indicate that both global temperature and sea level indeed present the characteristics of long memory processes. Nevertheless, we find that these variables are fractionally cointegrated when sea-ice extent is incorporated as an instrumental variable for temperature which in our estimations has a statistically significant positive impact on global sea level.

Artificial neural network modeling of DDGS flowability with varying process and storage parameters

USDA-ARS?s Scientific Manuscript database

Neural Network (NN) modeling techniques were used to predict flowability behavior in distillers dried grains with solubles (DDGS) prepared with varying CDS (10, 15, and 20%, wb), drying temperature (100, 200, and 300°C), cooling temperature (-12, 0, and 35°C) and cooling time (0 and 1 month) levels....

Sudden temperature changes in the Sydney Basin: climatology and case studies during the Olympic months of September and October

NASA Astrophysics Data System (ADS)

Buckley, Bruce W.; Leslie, Lance M.

2000-03-01

The accurate prediction of sudden large changes in the maximum temperature from one day to the next remains one of the major challenges for operational forecasters. It is probably the meteorological parameter most commonly verified and used as a measure of the skill of a meteorological service and one that is immediately evident to the general public. Marked temperature changes over a short period of time have widespread social, economic, health and safety effects on the community. The first part of this paper describes a 40-year climatology for Sydney, Australia, of sudden temperature rises and falls, defined as maximum temperature changes of 5°C or more from one day to the next, for the months of September and October. The nature of the forecasting challenge during the period of the Olympic and Paralympic Games to be held in Sydney in the year 2000 will be described as a special application. The international importance of the accurate prediction of all types of significant weather phenomena during this period has been recognized by the World Meteorological Organisation's Commission for Atmospheric Science. The first World Weather Research Program forecast demonstration project is to be established in the Sydney Office of the Bureau of Meteorology over this period in order to test the ability of existing systems to predict such phenomena. The second part of this study investigates two case studies from the Olympic months in which there were both abrupt temperature rises and falls over a 4-day interval. Currently available high resolution numerical weather prediction systems are found to have significant skill several days ahead in predicting a large amount of the detail of these events, provided they are run at an appropriate resolution. The limitations of these systems are also discussed, with areas requiring further development being identified if the desired levels of accuracy of predictions are to be reliably delivered. Differences between the predictability of sudden temperature rises and sudden temperature falls are also explored.

Larval connectivity across temperature gradients and its potential effect on heat tolerance in coral populations.

PubMed

Kleypas, Joan A; Thompson, Diane M; Castruccio, Frederic S; Curchitser, Enrique N; Pinsky, Malin; Watson, James R

2016-11-01

Coral reefs are increasingly exposed to elevated temperatures that can cause coral bleaching and high levels of mortality of corals and associated organisms. The temperature threshold for coral bleaching depends on the acclimation and adaptation of corals to the local maximum temperature regime. However, because of larval dispersal, coral populations can receive larvae from corals that are adapted to very different temperature regimes. We combine an offline particle tracking routine with output from a high-resolution physical oceanographic model to investigate whether connectivity of coral larvae between reefs of different thermal regimes could alter the thermal stress threshold of corals. Our results suggest that larval transport between reefs of widely varying temperatures is likely in the Coral Triangle and that accounting for this connectivity may be important in bleaching predictions. This has important implications in conservation planning, because connectivity may allow some reefs to have an inherited heat tolerance that is higher or lower than predicted based on local conditions alone. © 2016 John Wiley & Sons Ltd.

Relative mass distributions of neutron-rich thermally fissile nuclei within a statistical model

NASA Astrophysics Data System (ADS)

Kumar, Bharat; Kannan, M. T. Senthil; Balasubramaniam, M.; Agrawal, B. K.; Patra, S. K.

2017-09-01

We study the binary mass distribution for the recently predicted thermally fissile neutron-rich uranium and thorium nuclei using a statistical model. The level density parameters needed for the study are evaluated from the excitation energies of the temperature-dependent relativistic mean field formalism. The excitation energy and the level density parameter for a given temperature are employed in the convolution integral method to obtain the probability of the particular fragmentation. As representative cases, we present the results for the binary yields of 250U and 254Th. The relative yields are presented for three different temperatures: T =1 , 2, and 3 MeV.

Does the growth response of woody plants to elevated CO2 increase with temperature? A model-oriented meta-analysis.

PubMed

Baig, Sofia; Medlyn, Belinda E; Mercado, Lina M; Zaehle, Sönke

2015-12-01

The temperature dependence of the reaction kinetics of the Rubisco enzyme implies that, at the level of a chloroplast, the response of photosynthesis to rising atmospheric CO2 concentration (Ca ) will increase with increasing air temperature. Vegetation models incorporating this interaction predict that the response of net primary productivity (NPP) to elevated CO2 (eCa ) will increase with rising temperature and will be substantially larger in warm tropical forests than in cold boreal forests. We tested these model predictions against evidence from eCa experiments by carrying out two meta-analyses. Firstly, we tested for an interaction effect on growth responses in factorial eCa  × temperature experiments. This analysis showed a positive, but nonsignificant interaction effect (95% CI for above-ground biomass response = -0.8, 18.0%) between eCa and temperature. Secondly, we tested field-based eCa experiments on woody plants across the globe for a relationship between the eCa effect on plant biomass and mean annual temperature (MAT). This second analysis showed a positive but nonsignificant correlation between the eCa response and MAT. The magnitude of the interactions between CO2 and temperature found in both meta-analyses were consistent with model predictions, even though both analyses gave nonsignificant results. Thus, we conclude that it is not possible to distinguish between the competing hypotheses of no interaction vs. an interaction based on Rubisco kinetics from the available experimental database. Experiments in a wider range of temperature zones are required. Until such experimental data are available, model predictions should aim to incorporate uncertainty about this interaction. © 2015 John Wiley & Sons Ltd.

Boosted food web productivity through ocean acidification collapses under warming.

PubMed

Goldenberg, Silvan U; Nagelkerken, Ivan; Ferreira, Camilo M; Ullah, Hadayet; Connell, Sean D

2017-10-01

Future climate is forecast to drive bottom-up (resource driven) and top-down (consumer driven) change to food web dynamics and community structure. Yet, our predictive understanding of these changes is hampered by an over-reliance on simplified laboratory systems centred on single trophic levels. Using a large mesocosm experiment, we reveal how future ocean acidification and warming modify trophic linkages across a three-level food web: that is, primary (algae), secondary (herbivorous invertebrates) and tertiary (predatory fish) producers. Both elevated CO 2 and elevated temperature boosted primary production. Under elevated CO 2 , the enhanced bottom-up forcing propagated through all trophic levels. Elevated temperature, however, negated the benefits of elevated CO 2 by stalling secondary production. This imbalance caused secondary producer populations to decline as elevated temperature drove predators to consume their prey more rapidly in the face of higher metabolic demand. Our findings demonstrate how anthropogenic CO 2 can function as a resource that boosts productivity throughout food webs, and how warming can reverse this effect by acting as a stressor to trophic interactions. Understanding the shifting balance between the propagation of resource enrichment and its consumption across trophic levels provides a predictive understanding of future dynamics of stability and collapse in food webs and fisheries production. © 2017 John Wiley & Sons Ltd.

Human health risk assessment due to global warming--a case study of the Gulf countries.

PubMed

Husain, Tahir; Chaudhary, Junaid Rafi

2008-12-01

Accelerated global warming is predicted by the Intergovernmental Panel on Climatic Change (IPCC) due to increasing anthropogenic greenhouse gas emissions. The climate changes are anticipated to have a long-term impact on human health, marine and terrestrial ecosystems, water resources and vegetation. Due to rising sea levels, low lying coastal regions will be flooded, farmlands will be threatened and scarcity of fresh water resources will be aggravated. This will in turn cause increased human suffering in different parts of the world. Spread of disease vectors will contribute towards high mortality, along with the heat related deaths. Arid and hot climatic regions will face devastating effects risking survival of the fragile plant species, wild animals, and other desert ecosystems. The paper presents future changes in temperature, precipitation and humidity and their direct and indirect potential impacts on human health in the coastal regions of the Gulf countries including Yemen, Oman, United Arab Emirates, Qatar, and Bahrain. The analysis is based on the long-term changes in the values of temperature, precipitation and humidity as predicted by the global climatic simulation models under different scenarios of GHG emission levels. Monthly data on temperature, precipitation, and humidity were retrieved from IPCC databases for longitude 41.25 degrees E to 61.875 degrees E and latitude 9.278 degrees N to 27.833 degrees N. Using an average of 1970 to 2000 values as baseline, the changes in the humidity, temperature and precipitation were predicted for the period 2020 to 2050 and 2070 to 2099. Based on epidemiological studies on various diseases associated with the change in temperature, humidity and precipitation in arid and hot regions, empirical models were developed to assess human health risk in the Gulf region to predict elevated levels of diseases and mortality rates under different emission scenarios as developed by the IPCC.The preliminary assessment indicates increased mortality rates due to cardiovascular and respiratory illnesses, thermal stress, and increased frequency of infectious vector borne diseases in the region between 2070 and 2099.

Ab Initio Reaction Kinetics of CH 3 O$$\\dot{C}$$(=O) and $$\\dot{C}$$H 2 OC(=O)H Radicals

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tan, Ting; Yang, Xueliang; Ju, Yiguang

The dissociation and isomerization kinetics of the methyl ester combustion intermediates methoxycarbonyl radical (CH3Omore » $$\\dot{C}$$(=O)) and (formyloxy)methyl radical ($$\\dot{C}$$H2OC(=O)H) are investigated theoretically using high-level ab initio methods and Rice–Ramsperger–Kassel–Marcus (RRKM)/master equation (ME) theory. Geometries obtained at the hybrid density functional theory (DFT) and coupled cluster singles and doubles with perturbative triples correction (CCSD(T)) levels of theory are found to be similar. We employ high-level ab initio wave function methods to refine the potential energy surface: CCSD(T), multireference singles and doubles configuration interaction (MRSDCI) with the Davidson–Silver (DS) correction, and multireference averaged coupled-pair functional (MRACPF2) theory. MRSDCI+DS and MRACPF2 capture the multiconfigurational character of transition states (TSs) and predict lower barrier heights than CCSD(T). The temperature- and pressure-dependent rate coefficients are computed using RRKM/ME theory in the temperature range 300–2500 K and a pressure range of 0.01 atm to the high-pressure limit, which are then fitted to modified Arrhenius expressions. Dissociation of CH3O$$\\dot{C}$$(=O) to $$\\dot{C}$$H3 and CO2 is predicted to be much faster than dissociating to CH3$$\\dot{O}$$ and CO, consistent with its greater exothermicity. Isomerization between CH3O$$\\dot{C}$$(=O) and $$\\dot{C}$$H2OC(=O)H is predicted to be the slowest among the studied reactions and rarely happens even at high temperature and high pressure, suggesting the decomposition pathways of the two radicals are not strongly coupled. The predicted rate coefficients and branching fractions at finite pressures differ significantly from the corresponding high-pressure-limit results, especially at relatively high temperatures. Finally, because it is one of the most important CH3$$\\dot{O}$$ removal mechanisms under atmospheric conditions, the reaction kinetics of CH3$$\\dot{O}$$ + CO was also studied along the PES of CH3O$$\\dot{C}$$(=O); the resulting kinetics predictions are in remarkable agreement with experiments.« less

Core Body and Skin Temperature in Type 1 Narcolepsy in Daily Life; Effects of Sodium Oxybate and Prediction of Sleep Attacks.

PubMed

van der Heide, Astrid; Werth, Esther; Donjacour, Claire E H M; Reijntjes, Robert H A M; Lammers, Gert Jan; Van Someren, Eus J W; Baumann, Christian R; Fronczek, Rolf

2016-11-01

Previous laboratory studies in narcolepsy patients showed altered core body and skin temperatures, which are hypothesised to be related to a disturbed sleep wake regulation. In this ambulatory study we assessed temperature profiles in normal daily life, and whether sleep attacks are heralded by changes in skin temperature. Furthermore, the effects of three months of treatment with sodium oxybate (SXB) were investigated. Twenty-five narcolepsy patients and 15 healthy controls were included. Core body, proximal and distal skin temperatures, and sleep-wake state were measured simultaneously for 24 hours in ambulatory patients. This procedure was repeated in 16 narcolepsy patients after at least 3 months of stable treatment with SXB. Increases in distal skin temperature and distal-to-proximal temperature gradient (DPG) strongly predicted daytime sleep attacks (P < 0.001). As compared to controls, patients had a higher proximal and distal skin temperature in the morning, and a lower distal skin temperature during the night (all P < 0.05). Furthermore, they had a higher core body temperature during the first part of the night (P < 0.05), which SXB decreased (F = 4.99, df = 1, P = 0.03) to a level similar to controls. SXB did not affect skin temperature. This ambulatory study demonstrates that daytime sleep attacks were preceded by clear changes in distal skin temperature and DPG. Furthermore, changes in core body and skin temperature in narcolepsy, previously only studied in laboratory settings, were partially confirmed. Treatment with SXB resulted in a normalisation of the core body temperature profile. Future studies should explore whether predictive temperature changes can be used to signal or even prevent sleep attacks. © 2016 Associated Professional Sleep Societies, LLC.

Thermal/Pyrolysis Gas Flow Analysis of Carbon Phenolic Material

NASA Technical Reports Server (NTRS)

Clayton, J. Louie

2001-01-01

Provided in this study are predicted in-depth temperature and pyrolysis gas pressure distributions for carbon phenolic materials that are externally heated with a laser source. Governing equations, numerical techniques and comparisons to measured temperature data are also presented. Surface thermochemical conditions were determined using the Aerotherm Chemical Equilibrium (ACE) program. Surface heating simulation used facility calibrated radiative and convective flux levels. Temperatures and pyrolysis gas pressures are predicted using an upgraded form of the SINDA/CMA program that was developed by NASA during the Solid Propulsion Integrity Program (SPIP). Multispecie mass balance, tracking of condensable vapors, high heat rate kinetics, real gas compressibility and reduced mixture viscosity's have been added to the algorithm. In general, surface and in-depth temperature comparisons are very good. Specie partial pressures calculations show that a saturated water-vapor mixture is the main contributor to peak in-depth total pressure. Further, for most of the cases studied, the water-vapor mixture is driven near the critical point and is believed to significantly increase the local heat capacity of the composite material. This phenomenon if not accounted for in analysis models may lead to an over prediction in temperature response in charring regions of the material.

Assessment of daytime outdoor comfort levels in and outside the urban area of Glasgow, UK.

PubMed

Krüger, Eduardo; Drach, Patricia; Emmanuel, Rohinton; Corbella, Oscar

2013-07-01

To understand thermal preferences and to define a preliminary outdoor comfort range for the local population of Glasgow, UK, an extensive series of measurements and surveys was carried out during 19 monitoring campaigns from winter through summer 2011 at six different monitoring points in pedestrian areas of downtown Glasgow. For data collection, a Davis Vantage Pro2 weather station equipped with temperature and humidity sensors, cup anemometer with wind vane, silicon pyranometer and globe thermometer was employed. Predictions of the outdoor thermal index PET (physiologically equivalent temperature) correlated closely to the actual thermal votes of respondents. Using concurrent measurements from a second Davis Vantage Pro2 weather station placed in a rural setting approximately 15 km from the urban area, comparisons were drawn with regard to daytime thermal comfort levels and urban-rural temperature differences (∆T(u-r)) for the various sites. The urban sites exhibited a consistent lower level of thermal discomfort during daytime. No discernible effect of urban form attributes in terms of the sky-view factor were observed on ∆Tu-r or on the relative difference of the adjusted predicted percentage of dissatisfied (PPD*).

Human impacts and changes in the coastal waters of south China.

PubMed

Wang, Linlin; Li, Qiang; Bi, Hongsheng; Mao, Xian-Zhong

2016-08-15

Human impact on the environment remains at the center of the debate on global environmental change. Using the Hong Kong-Shenzhen corridor in south China as an example, we present evidence that rapid urbanization and economic development in coastal areas were the dominant factors causing rapid changes in coastal waters. From 1990 to 2012, coastal seawater temperature increased ~0.060°C per year, sea level rose 4.4mm per year and pH decreased from 8.2 to 7.7, much faster than global averages. In the same period, there were exponential increases in the local population, gross domestic product and land fill area. Empirical analyses suggest that the large increase in the population affected local temperature, and economic development had a major impact on local pH. Results also show that pH and temperature were significantly correlated with local sea level rise, but pH had more predictive power, suggesting it could be considered a predictor for changes in local sea level. We conclude that human activities could significantly exacerbate local environmental changes which should be considered in predictive models and future development plans in coastal areas. Copyright © 2016 Elsevier B.V. All rights reserved.

Prediction-Market-Based Quantification of Climate Change Consensus and Uncertainty

NASA Astrophysics Data System (ADS)

Boslough, M.

2012-12-01

Intrade is an online trading exchange that includes climate prediction markets. One such family of contracts can be described as "Global temperature anomaly for 2012 to be greater than x °C or more," where the figure x ranges in increments of .05 from .30 to 1.10 (relative to the 1951-1980 base period), based on data published by NASA GISS. Each market will settle at 10.00 if the published global temperature anomaly for 2012 is equal to or greater than x, and will otherwise settle at 0.00. Similar contracts will be available for 2013. Global warming hypotheses can be cast as probabilistic predictions for future temperatures. The first modern such climate prediction is that of Broecker (1975), whose temperatures are easily separable from his CO2 growth scenario—which he overestimated—by interpolating his table of temperature as a function of CO2 concentration and projecting the current trend into the near future. For the current concentration of 395 ppm, Broecker's equilibrium temperature anomaly prediction relative to pre-industrial is 1.05 °C, or about 0.75 °C relative to the GISS base period. His neglect of lag in response to the changes in radiative forcing was partially compensated by his low sensitivity of 2.4 °C, leading to a slight overestimate. Simple linear extrapolation of the current trend since 1975 yields an estimate of .65 ± .09 °C (net warming of .95 °C) for anthropogenic global warming with a normal distribution of random natural variability. To evaluate an extreme case, we can estimate the prediction Broecker would have made if he had used the Lindzen & Choi (2009) climate sensitivity of 0.5 °C. The net post-industrial warming by 2012 would have been 0.21 °C, for an expected change of -0.09 from the GISS base period. This is the temperature to which the Earth would be expected to revert if the observed warming since the 19th century was merely due to random natural variability that coincidentally mimicked Broecker's anthropogenic change prediction for the past 36 years. Assertions made outside the scientific literature can also be cast into predictions for 2012 temperatures, for example Carter's (2006) argument for a lack of warming since 1998 can be extrapolated to a 2012 value of 0.56 °C (net warming of .86 °C), and Easterbrook's (2010) claim of global cooling can be extrapolated to a 2012 value of .42 °C (net warming of .72 °C). All contracts in the current market ensembles are consistent with net warming from pre-industrial temperatures. They are also capable of distinguishing the level of acceptance of the various global warming hypotheses, even by their respective proponents. Moreover, they can be used as a market-based consensus estimate of future warming and climate variability that is weighted according to level of risk taken on by those providing the estimates, while filtering out the opinions of individuals unwilling to accept any financial risk associated with being wrong.

Shifting the Arctic Carbon Balance: Effects of a Long-Term Fertilization Experiment and Anomalously Warm Temperatures on Net Ecosystem Exchange in the Alaskan Tundra

NASA Astrophysics Data System (ADS)

Ludwig, S.; Natali, S.; Rastetter, E. B.; Shaver, G. R.; Graham, L. M.; Jastrow, J. D.

2017-12-01

The arctic is warming at an accelerated rate relative to the globe. Among the predicted consequences of warming temperatures in the arctic are increased gross primary productivity (GPP), ecosystem respiration (ER), and nutrient availability. The net effect of these changes on the carbon (C) cycle and resulting C balance and feedback to climate change remain unclear. Historically the Arctic has been a C sink, but evidence from recent years suggests some regions in the Arctic are becoming C sources. To predict the role of the Arctic in global C cycling, the mechanisms affecting arctic C balances need to be better resolved. We measured net ecosystem exchange (NEE) in a long-term, multi-level, fertilization experiment at Toolik Lake, AK during an anomalously warm summer. We modeled NEE, ER, and GPP using a Bayesian network model. The best-fit model included Q10 temperature functions and linear fertilization functions for both ER and GPP. ER was more strongly affected by temperature and GPP was driven more by fertilization level. As a result, fertilization increased the C sink capacity, but only at moderate and low temperatures. At high temperatures (>28 °C) the NEE modeled for the highest level of fertilization was not significantly different from zero. In contrast, at ambient nutrient levels modeled NEE was significantly below zero (net uptake) until 35 °C, when it becomes neutral. Regardless of the level of fertilization, NEE never decreased with warming. Temperature in low ranges (5-15°C) had no net effect on NEE, whereas NEE began to increase exponentially with temperature after a threshold of 15°C until becoming a net source to the atmosphere at 37°C. Our results indicate that the C sink strength of tundra ecosystems can be increased with small increases in nutrient availability, but that large increase in nutrient availability can switch tundra ecosystems into C sources under warm conditions. Warming temperatures in tundra ecosystems will only decrease C sink strength, and the continued increase in days with anomalously high summer temperatures could lead to the Arctic tundra becoming a source of C and a positive feed back to climate change.

Some coolness concerning global warming

NASA Technical Reports Server (NTRS)

Lindzen, Richard S.

1990-01-01

The greenhouse effect hypothesis is discussed. The effects of increasing CO2 levels in the atmosphere on global temperature changes are analyzed. The problems with models currently used to predict climatic changes are examined.

Correlations among body temperature, plasma progesterone, cortisol and prostaglandin F2alpha of the periparturient bitch.

PubMed

Veronesi, M C; Battocchio, M; Marinelli, L; Faustini, M; Kindahl, H; Cairoli, F

2002-06-01

The results of this study suggest that, besides the irrelevant role of body temperature measurement to predict the impending parturition in the bitch, progesterone and 15-ketodihydroprostaglandin F2alpha plasma level records could be more suitable to detect the approaching whelping in this species. More interesting was the statistically significant substantial increase in body temperature beginning 12 h after the onset of parturition. Therefore, if any significant increase in body temperature is recorded at the end of pregnancy without the beginning of the expulsion of fetuses, it could indicate problems at parturition. In this study, cortisol levels increased significantly at the time of delivery and remained high 12 h after the beginning of parturition, decreasing within 36 h after the onset of whelping. 15-ketodihydro-prostaglandin F2alpha levels increased significantly 24 h before parturition and again at the onset of whelping. Progesterone levels decreased significantly, starting 24 h before the onset of whelping and remained low after delivery.

Growth and food consumption by tiger muskellunge: Effects of temperature and ration level on bioenergetic model predictions

USGS Publications Warehouse

Chipps, S.R.; Einfalt, L.M.; Wahl, David H.

2000-01-01

We measured growth of age-0 tiger muskellunge as a function of ration size (25, 50, 75, and 100% C(max))and water temperature (7.5-25??C) and compared experimental results with those predicted from a bioenergetic model. Discrepancies between actual and predicted values varied appreciably with water temperature and growth rate. On average, model output overestimated winter consumption rates at 10 and 7.5??C by 113 to 328%, respectively, whereas model predictions in summer and autumn (20-25??C) were in better agreement with actual values (4 to 58%). We postulate that variation in model performance was related to seasonal changes in esocid metabolic rate, which were not accounted for in the bioenergetic model. Moreover, accuracy of model output varied with feeding and growth rate of tiger muskellunge. The model performed poorly for fish fed low rations compared with estimates based on fish fed ad libitum rations and was attributed, in part, to the influence of growth rate on the accuracy of bioenergetic predictions. Based on modeling simulations, we found that errors associated with bioenergetic parameters had more influence on model output when growth rate was low, which is consistent with our observations. In addition, reduced conversion efficiency at high ration levels may contribute to variable model performance, thereby implying that waste losses should be modeled as a function of ration size for esocids. Our findings support earlier field tests of the esocid bioenergetic model and indicate that food consumption is generally overestimated by the model, particularly in winter months and for fish exhibiting low feeding and growth rates.

Validating computational predictions of night-time ventilation in Stanford's Y2E2 building

NASA Astrophysics Data System (ADS)

Chen, Chen; Lamberti, Giacomo; Gorle, Catherine

2017-11-01

Natural ventilation can significantly reduce building energy consumption, but robust design is a challenging task. We previously presented predictions of natural ventilation performance in Stanford's Y2E2 building using two models with different levels of fidelity, embedded in an uncertainty quantification framework to identify the dominant uncertain parameters and predict quantified confidence intervals. The results showed a slightly high cooling rate for the volume-averaged temperature, and the initial thermal mass temperature and window discharge coefficients were found to have an important influence on the results. To further investigate the potential role of these parameters on the observed discrepancies, the current study is performing additional measurements in the Y2E2 building. Wall temperatures are recorded throughout the nightflush using thermocouples; flow rates through windows are measured using hotwires; and spatial variability in the air temperature is explored. The measured wall temperatures are found the be within the range of our model assumptions, and the measured velocities agree reasonably well with our CFD predications. Considerable local variations in the indoor air temperature have been recorded, largely explaining the discrepancies in our earlier validation study. Future work will therefore focus on a local validation of the CFD results with the measurements. Center for Integrated Facility Engineering (CIFE).

Predictive model for the growth of spoilage bacteria on modified atmosphere packaged Atlantic salmon produced in Australia.

PubMed

Powell, S M; Ratkowsky, D A; Tamplin, M L

2015-05-01

Most existing models for the spoilage of modified atmosphere packed Atlantic salmon are based on the growth of the spoilage organism Photobacterium phosphoreum. However, there is evidence that this organism is not the specific spoilage organism on salmon produced and packaged in Australia. We developed a predictive model for the growth of bacteria in Australian-produced Atlantic salmon stored under modified atmosphere conditions (30-98% carbon dioxide in nitrogen) at refrigeration temperatures (0-10 °C). As expected, both higher levels of carbon dioxide and lower temperatures decreased the observed growth rates of the total population. A Bělehrádek-type model for growth rate fitted the data best with an acceptably low root mean square error. At low temperatures (∼0 °C) the growth rates in this study were similar to those predicted by other models but at higher temperatures (∼10 °C) the growth rates were significantly lower in the current study. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

Unravelling the magnetism, high spin polarization and thermoelectric efficiency of ZrFeSi half-Heusler

NASA Astrophysics Data System (ADS)

Yousuf, Saleem; Gupta, D. C.

2018-04-01

We report the systematic investigation of structural properties, occupancy of density of states, nature of bonding and thermoelectric efficiency of half-Heusler ZrFeSi. The band structure analysis predicts the hybridization of Zr-d and Fe-d metal atoms resulting in occupation of density of states above the Fermi level (EF) while Fe-p and Si-p occupy the lower energy states below the EF. Thermoelectric transport coefficients are predicted using the Boltzmann transport theory under constant relaxation approximation, where Seebeck coefficient (S), total thermal conductivity and figure of merit are calculated. The negative value of total S as -14.02 μV/K predicts the material as n-type with thermoelectric figure of merit (zT) of 0.5 at 800 K. The lattice thermal conductivity decreases with increasing temperature with room temperature value of 4.18 W/mK and shows a significant reduction towards higher temperatures. In view of above elements, structural stability, high zT, ZrFeSi alloy have the capabilities to stimulate experimental verification as a promising materials for high temperature power generation and spintronic device fabrications.

Spin-lattice relaxation and the calculation of gain, pump power, and noise temperature in ruby

NASA Technical Reports Server (NTRS)

Lyons, J. R.

1989-01-01

The use of a quantitative analysis of the dominant source of relaxation in ruby spin systems to make predictions of key maser amplifier parameters is described. The spin-lattice Hamiltonian which describes the interaction of the electron spins with the thermal vibrations of the surrounding lattice is obtained from the literature. Taking into account the vibrational anisotropy of ruby, Fermi's rule is used to calculate the spin transition rates between the maser energy levels. The spin population rate equations are solved for the spin transition relaxation times, and a comparison with previous calculations is made. Predictions of ruby gain, inversion ratio, and noise temperature as a function of physical temperature are made for 8.4-GHz and 32-GHz maser pumping schemes. The theory predicts that ruby oriented at 90 deg will have approximately 50 percent higher gain in dB and slightly lower noise temperature than a 54.7-deg ruby at 32 GHz (assuming pump saturation). A specific calculation relating pump power to inversion ratio is given for a single channel of the 32-GHz reflected wave maser.

Improved protocol and data analysis for accelerated shelf-life estimation of solid dosage forms.

PubMed

Waterman, Kenneth C; Carella, Anthony J; Gumkowski, Michael J; Lukulay, Patrick; MacDonald, Bruce C; Roy, Michael C; Shamblin, Sheri L

2007-04-01

To propose and test a new accelerated aging protocol for solid-state, small molecule pharmaceuticals which provides faster predictions for drug substance and drug product shelf-life. The concept of an isoconversion paradigm, where times in different temperature and humidity-controlled stability chambers are set to provide a critical degradant level, is introduced for solid-state pharmaceuticals. Reliable estimates for temperature and relative humidity effects are handled using a humidity-corrected Arrhenius equation, where temperature and relative humidity are assumed to be orthogonal. Imprecision is incorporated into a Monte-Carlo simulation to propagate the variations inherent in the experiment. In early development phases, greater imprecision in predictions is tolerated to allow faster screening with reduced sampling. Early development data are then used to design appropriate test conditions for more reliable later stability estimations. Examples are reported showing that predicted shelf-life values for lower temperatures and different relative humidities are consistent with the measured shelf-life values at those conditions. The new protocols and analyses provide accurate and precise shelf-life estimations in a reduced time from current state of the art.

Winter temperatures over the Korean Peninsula and East Asia: development of a new index and its application to seasonal forecast

NASA Astrophysics Data System (ADS)

Kim, Seon Tae; Sohn, Soo-Jin; Kug, Jong-Seong

2017-09-01

This study proposes a new index for monitoring and predicting winter temperatures of the Korean Peninsula based on the dominant atmospheric winter teleconnection patterns. The utilization of this index is further extended to the East Asian Winter Monsoon (EAWM) index because the new index is found to well represent the main feature of the EAWM circulation. Among the teleconnection patterns, the East Atlantic (EA) and Western Pacific (WP) patterns are found to be most strongly correlated with winter temperatures via their partial association with changes in sea level pressure (SLP) around the Korean Peninsula, i.e., the EA and WP patterns are associated with SLP variation over the Siberian High region and the Kuroshio extension region to the east of Japan, respectively. On the basis of this relationship, the two regions representing the northwest-to-southeast SLP gradients are determined to define the new index. It is found that the new index can represent the Korean winter temperatures consistently well regardless of their considerable decadal changes. When compared with the existing SLP-based EAWM indices, the new index shows the best performance in delineating winter air temperatures, not only in the Korean Peninsula but also in the entire East Asian region. We also assess the prediction skill of the new index with seasonal coupled forecast models of the APEC Climate Center of Korea and its capability to predict winter temperatures. This assessment shows that the new index has potential for operationally predicting and monitoring winter temperatures in Korea and the whole of East Asia.

Neuro-genetic non-invasive temperature estimation: intensity and spatial prediction.

PubMed

Teixeira, César A; Ruano, M Graça; Ruano, António E; Pereira, Wagner C A

2008-06-01

The existence of proper non-invasive temperature estimators is an essential aspect when thermal therapy applications are envisaged. These estimators must be good predictors to enable temperature estimation at different operational situations, providing better control of the therapeutic instrumentation. In this work, radial basis functions artificial neural networks were constructed to access temperature evolution on an ultrasound insonated medium. The employed models were radial basis functions neural networks with external dynamics induced by their inputs. Both the most suited set of model inputs and number of neurons in the network were found using the multi-objective genetic algorithm. The neural models were validated in two situations: the operating ones, as used in the construction of the network; and in 11 unseen situations. The new data addressed two new spatial locations and a new intensity level, assessing the intensity and space prediction capacity of the proposed model. Good performance was obtained during the validation process both in terms of the spatial points considered and whenever the new intensity level was within the range of applied intensities. A maximum absolute error of 0.5 degrees C+/-10% (0.5 degrees C is the gold-standard threshold in hyperthermia/diathermia) was attained with low computationally complex models. The results confirm that the proposed neuro-genetic approach enables foreseeing temperature propagation, in connection to intensity and space parameters, thus enabling the assessment of different operating situations with proper temperature resolution.

Acute dim light at night increases body mass, alters metabolism, and shifts core body temperature circadian rhythms.

PubMed

Borniger, Jeremy C; Maurya, Santosh K; Periasamy, Muthu; Nelson, Randy J

2014-10-01

The circadian system is primarily entrained by the ambient light environment and is fundamentally linked to metabolism. Mounting evidence suggests a causal relationship among aberrant light exposure, shift work, and metabolic disease. Previous research has demonstrated deleterious metabolic phenotypes elicited by chronic (>4 weeks) exposure to dim light at night (DLAN) (∼ 5 lux). However, the metabolic effects of short-term (<2 weeks) exposure to DLAN are unspecified. We hypothesized that metabolic alterations would arise in response to just 2 weeks of DLAN. Specifically, we predicted that mice exposed to dim light would gain more body mass, alter whole body metabolism, and display altered body temperature (Tb) and activity rhythms compared to mice maintained in dark nights. Our data largely support these predictions; DLAN mice gained significantly more mass, reduced whole body energy expenditure, increased carbohydrate over fat oxidation, and altered temperature circadian rhythms. Importantly, these alterations occurred despite similar activity locomotor levels (and rhythms) and total food intake between groups. Peripheral clocks are potently entrained by body temperature rhythms, and the deregulation of body temperature we observed may contribute to metabolic problems due to "internal desynchrony" between the central circadian oscillator and temperature sensitive peripheral clocks. We conclude that even relatively short-term exposure to low levels of nighttime light can influence metabolism to increase mass gain.

Validation and Inter-comparison Against Observations of GODAE Ocean View Ocean Prediction Systems

NASA Astrophysics Data System (ADS)

Xu, J.; Davidson, F. J. M.; Smith, G. C.; Lu, Y.; Hernandez, F.; Regnier, C.; Drevillon, M.; Ryan, A.; Martin, M.; Spindler, T. D.; Brassington, G. B.; Oke, P. R.

2016-02-01

For weather forecasts, validation of forecast performance is done at the end user level as well as by the meteorological forecast centers. In the development of Ocean Prediction Capacity, the same level of care for ocean forecast performance and validation is needed. Herein we present results from a validation against observations of 6 Global Ocean Forecast Systems under the GODAE OceanView International Collaboration Network. These systems include the Global Ocean Ice Forecast System (GIOPS) developed by the Government of Canada, two systems PSY3 and PSY4 from the French Mercator-Ocean Ocean Forecasting Group, the FOAM system from UK met office, HYCOM-RTOFS from NOAA/NCEP/NWA of USA, and the Australian Bluelink-OceanMAPS system from the CSIRO, the Australian Meteorological Bureau and the Australian Navy.The observation data used in the comparison are sea surface temperature, sub-surface temperature, sub-surface salinity, sea level anomaly, and sea ice total concentration data. Results of the inter-comparison demonstrate forecast performance limits, strengths and weaknesses of each of the six systems. This work establishes validation protocols and routines by which all new prediction systems developed under the CONCEPTS Collaborative Network will be benchmarked prior to approval for operations. This includes anticipated delivery of CONCEPTS regional prediction systems over the next two years including a pan Canadian 1/12th degree resolution ice ocean prediction system and limited area 1/36th degree resolution prediction systems. The validation approach of comparing forecasts to observations at the time and location of the observation is called Class 4 metrics. It has been adopted by major international ocean prediction centers, and will be recommended to JCOMM-WMO as routine validation approach for operational oceanography worldwide.

Species and temperature measurement in H2/O2 rocket flow fields by means of Raman scattering diagnostics

NASA Technical Reports Server (NTRS)

Degroot, Wim A.; Weiss, Jonathan M.

1992-01-01

Validation of Computational Fluid Dynamics (CFD) codes developed for prediction and evaluation of rocket performance is hampered by a lack of experimental data. Non-intrusive laser based diagnostics are needed to provide spatially and temporally resolved gas dynamic and fluid dynamic measurements. This paper reports the first non-intrusive temperature and species measurements in the plume of a 110 N gaseous hydrogen/oxygen thruster at and below ambient pressures, obtained with spontaneous Raman spectroscopy. Measurements at 10 mm downstream of the exit plane are compared with predictions from a numerical solution of the axisymmetric Navier-Stokes and species transport equations with chemical kinetics, which fully model the combustor-nozzle-plume flowfield. The experimentally determined oxygen number density at the centerline at 10 mm downstream of the exit plane is four times that predicted by the model. The experimental number density data fall between those numerically predicted for the exit and 10 mm downstream planes in both magnitude and radial gradient. The predicted temperature levels are within 10 to 15 percent of measured values. Some of the discrepancies between experimental data and predictions result from not modeling the three dimensional core flow injection mixing process, facility back pressure effects, and possible diffuser-thruster interactions.

Effect of Climate Change on Water Temperature and Attainment of Water Temperature Criteria in the Yaquina Estuary, Oregon (USA)

EPA Science Inventory

There is increasing evidence that our planet is warming and this warming is also resulting in rising sea levels. Estuaries which are located at the interface between land and ocean are impacted by these changes. We used CE-QUAL-W2 water quality model to predict changes in water...

Upper-Level Mediterranean Oscillation index and seasonal variability of rainfall and temperature

NASA Astrophysics Data System (ADS)

Redolat, Dario; Monjo, Robert; Lopez-Bustins, Joan A.; Martin-Vide, Javier

2018-02-01

The need for early seasonal forecasts stimulates continuous research in climate teleconnections. The large variability of the Mediterranean climate presents a greater difficulty in predicting climate anomalies. This article reviews teleconnection indices commonly used for the Mediterranean basin and explores possible extensions of one of them, the Mediterranean Oscillation index (MOi). In particular, the anomalies of the geopotential height field at 500 hPa are analyzed using segmentation of the Mediterranean basin in seven spatial windows: three at eastern and four at western. That is, different versions of an Upper-Level Mediterranean Oscillation index (ULMOi) were calculated, and monthly and annual variability of precipitation and temperature were analyzed for 53 observatories from 1951 to 2015. Best versions were selected according to the Pearson correlation, its related p value, and two measures of standardized error. The combination of the Balearic Sea and Libya/Egypt windows was the best for precipitation and temperature, respectively. The ULMOi showed the highest predictive ability in combination with the Atlantic Multidecadal Oscillation index (AMOi) for the annual temperature throughout the Mediterranean basin. The best model built from the indices presented a final mean error between 15 and 25% in annual precipitation for most of the studied area.

On the organization and thermal behavior of functional groups on Ti3C2 MXene surfaces in vacuum

NASA Astrophysics Data System (ADS)

Persson, Ingemar; Näslund, Lars-Åke; Halim, Joseph; Barsoum, Michel W.; Darakchieva, Vanya; Palisaitis, Justinas; Rosen, Johanna; Persson, Per O. Å.

2018-03-01

The two-dimensional (2D) MXene Ti3C2T x is functionalized by surface groups (T x ) that determine its surface properties for, e.g. electrochemical applications. The coordination and thermal properties of these surface groups has, to date, not been investigated at the atomic level, despite strong variations in the MXene properties that are predicted from different coordinations and from the identity of the functional groups. To alleviate this deficiency, and to characterize the functionalized surfaces of single MXene sheets, the present investigation combines atomically resolved in situ heating in a scanning transmission electron microscope (STEM) and STEM simulations with temperature-programmed x-ray photoelectron spectroscopy (TP-XPS) in the room temperature to 750 °C range. Using these techniques, we follow the surface group coordination at the atomic level. It is concluded that the F and O atoms compete for the DFT-predicted thermodynamically preferred site and that at room temperature that site is mostly occupied by F. At higher temperatures, F desorbs and is replaced by O. Depending on the O/F ratio, the surface bare MXene is exposed as F desorbs, which enables a route for tailored surface functionalization.

Three-dimensional laser cooling at the Doppler limit

NASA Astrophysics Data System (ADS)

Chang, R.; Hoendervanger, A. L.; Bouton, Q.; Fang, Y.; Klafka, T.; Audo, K.; Aspect, A.; Westbrook, C. I.; Clément, D.

2014-12-01

Many predictions of Doppler-cooling theory of two-level atoms have never been verified in a three-dimensional geometry, including the celebrated minimum achievable temperature ℏ Γ /2 kB , where Γ is the transition linewidth. Here we show that, despite their degenerate level structure, we can use helium-4 atoms to achieve a situation in which these predictions can be verified. We make measurements of atomic temperatures, magneto-optical trap sizes, and the sensitivity of optical molasses to a power imbalance in the laser beams, finding excellent agreement with Doppler theory. We show that the special properties of helium, particularly its small mass and narrow transition linewidth, prevent effective sub-Doppler cooling with red-detuned optical molasses. This discussion can be generalized to identify when a given species is likely to be subject to the same limitation.

New methodology for the heat flow prediction for different construction materials

NASA Astrophysics Data System (ADS)

Benachour, Elhadj; Draoui, Belkacem; Imine, Bachir; Asnoune, Khadidja; Boumediene, Allaoua; Mebarki, Brahim

2018-06-01

Among the ways of energy transfer by conduction is that of molecular interaction, in which the greater motion of a molecule at a higher energy level (temperature) imparts energy to adjacent molecules at lower energy levels. This type of transfer is present, to some degree, in all systems in which a temperature gradient exists and in which molecules of a solid, liquid, or gas are present. So, in heat transfer, the thermal conductivity of a substance is an intensive property that indicates its ability to conduct heat In particular in the building sector. The thermal flux is often measured with a mathematical analysis but for the same material, on the other hand the estimate will be disruptive and sometimes very difficult when the material changes. In this paper, a single equation for predicting heat flux of different materials is given.

Annual temperature variation as a time machine to understand the effects of long-term climate change on a poleward range shift.

PubMed

Crickenberger, Sam; Wethey, David S

2018-05-10

Range shifts due to annual variation in temperature are more tractable than range shifts linked to decadal to century long temperature changes due to climate change, providing natural experiments to determine the mechanisms responsible for driving long-term distributional shifts. In this study we couple physiologically grounded mechanistic models with biogeographic surveys in 2 years with high levels of annual temperature variation to disentangle the drivers of a historical range shift driven by climate change. The distribution of the barnacle Semibalanus balanoides has shifted 350 km poleward in the past half century along the east coast of the United States. Recruits were present throughout the historical range following the 2015 reproductive season, when temperatures were similar to those in the past century, and absent following the 2016 reproductive season when temperatures were warmer than they have been since 1870, the earliest date for temperature records. Our dispersal dependent mechanistic models of reproductive success were highly accurate and predicted patterns of reproduction success documented in field surveys throughout the historical range in 2015 and 2016. Our mechanistic models of reproductive success not only predicted recruitment dynamics near the range edge but also predicted interior range fragmentation in a number of years between 1870 and 2016. All recruits monitored within the historical range following the 2015 colonization died before 2016 suggesting juvenile survival was likely the primary driver of the historical range retraction. However, if 2016 is indicative of future temperatures mechanisms of range limitation will shift and reproductive failure will lead to further range retraction in the future. Mechanistic models are necessary for accurately predicting the effects of climate change on ranges of species. © 2018 John Wiley & Sons Ltd.

Autumn temperature and carbon balance of a boreal Scots pine forest in Southern Finland

NASA Astrophysics Data System (ADS)

Vesala, T.; Launiainen, S.; Kolari, P.; Pumpanen, J.; Sevanto, S.; Hari, P.; Nikinmaa, E.; Kaski, P.; Mannila, H.; Ukkonen, E.; Piao, S. L.; Ciais, P.

2010-01-01

We analyzed the dynamics of carbon balance components: gross primary production (GPP) and total ecosystem respiration (TER), of a boreal Scots pine forest in Southern Finland. The main focus is on investigations of environmental drivers of GPP and TER and how they affect the inter-annual variation in the carbon balance in autumn (September-December). We used standard climate data and CO2 exchange measurements collected by the eddy covariance (EC) technique over 11 years. EC data revealed that increasing autumn temperature significantly enhances TER: the temperature sensitivity was 9.5 gC m-2 °C-1 for the period September-October (early autumn when high radiation levels still occur) and 3.8 gC m-2 °C-1 for November-December (late autumn with suppressed radiation level). The cumulative GPP was practically independent of the temperature in early autumn. In late autumn, air temperature could explain part of the variation in GPP but the temperature sensitivity was very weak, less than 1 gC m-2 °C-1. Two models, a stand photosynthesis model (COCA) and a global vegetation model (ORCHIDEE), were used for estimating stand GPP and its sensitivity to the temperature. The ORCHIDEE model was tested against the observations of GPP derived from EC data. The stand photosynthesis model COCA predicted that under a predescribed 3-6 °C temperature increase, the temperature sensitivity of 4-5 gC m-2 °C-1 in GPP may appear in early autumn. The analysis by the ORCHIDEE model revealed the model sensitivity to the temporal treatment of meteorological forcing. The model predictions were similar to observed ones when the site level 1/2-hourly time step was applied, but the results calculated by using daily meteorological forcing, interpolated to 1/2-hourly time step, were biased. This is due to the nonlinear relationship between the processes and the environmental factors.

Core Body and Skin Temperature in Type 1 Narcolepsy in Daily Life; Effects of Sodium Oxybate and Prediction of Sleep Attacks

PubMed Central

van der Heide, Astrid; Werth, Esther; Donjacour, Claire E.H.M.; Reijntjes, Robert H.A.M.; Lammers, Gert Jan; Van Someren, Eus J.W.; Baumann, Christian R.; Fronczek, Rolf

2016-01-01

Study Objectives: Previous laboratory studies in narcolepsy patients showed altered core body and skin temperatures, which are hypothesised to be related to a disturbed sleep wake regulation. In this ambulatory study we assessed temperature profiles in normal daily life, and whether sleep attacks are heralded by changes in skin temperature. Furthermore, the effects of three months of treatment with sodium oxybate (SXB) were investigated. Methods: Twenty-five narcolepsy patients and 15 healthy controls were included. Core body, proximal and distal skin temperatures, and sleep-wake state were measured simultaneously for 24 hours in ambulatory patients. This procedure was repeated in 16 narcolepsy patients after at least 3 months of stable treatment with SXB. Results: Increases in distal skin temperature and distal-to-proximal temperature gradient (DPG) strongly predicted daytime sleep attacks (P < 0.001). As compared to controls, patients had a higher proximal and distal skin temperature in the morning, and a lower distal skin temperature during the night (all P < 0.05). Furthermore, they had a higher core body temperature during the first part of the night (P < 0.05), which SXB decreased (F = 4.99, df = 1, P = 0.03) to a level similar to controls. SXB did not affect skin temperature. Conclusions: This ambulatory study demonstrates that daytime sleep attacks were preceded by clear changes in distal skin temperature and DPG. Furthermore, changes in core body and skin temperature in narcolepsy, previously only studied in laboratory settings, were partially confirmed. Treatment with SXB resulted in a normalisation of the core body temperature profile. Future studies should explore whether predictive temperature changes can be used to signal or even prevent sleep attacks. Citation: van der Heide A, Werth E, Donjacour CE, Reijntjes RH, Lammers GJ, Van Someren EJ, Baumann CR, Fronczek R. Core body and skin temperature in type 1 narcolepsy in daily life; effects of sodium oxybate and prediction of sleep attacks. SLEEP 2016;39(11):1941–1949. PMID:27568803

Significance of Landsat-7 Spacecraft Level Thermal Balance and Thermal Test for ETM+Instrument

NASA Technical Reports Server (NTRS)

Choi, Michael K.

1999-01-01

The thermal design and the instrument thermal vacuum (T/V) test of the Landsat-7 Enhanced Thematic Mapper Plus (ETM+) instrument were based on the Landsat-4, 5 and 6 heritage. The ETM+ scanner thermal model was also inherited from Landsat-4, 5 and 6. The temperature predictions of many scanner components in the original thermal model had poor agreement with the spacecraft and instrument integrated sun-pointing safehold (SPSH) thermal balance (T/B) test results. The spacecraft and instrument integrated T/B test led to a change of the Full Aperture Calibrator (FAC) motor stack "solar shield" coating from MIL-C-5541 to multi-layer insulation (MLI) thermal blanket. The temperature predictions of the Auxiliary Electronics Module (AEM) in the thermal model also had poor agreement with the T/B test results. Modifications to the scanner and AEM thermal models were performed to give good agreement between the temperature predictions and the test results. The correlated ETM+ thermal model was used to obtain flight temperature predictions. The flight temperature predictions in the nominal 15-orbit mission profile, plus margins, were used as the yellow limits for most of the ETM+ components. The spacecraft and instrument integrated T/B and TN test also revealed that the standby heater capacity on the Scan Mirror Assembly (SMA) was insufficient when the Earth Background Simulator (EBS) was 1 50C or colder, and the baffle heater possibly caused the coherent noise in the narrow band data when it was on. Also, the cooler cool-down was significantly faster than that in the instrument T/V test, and the coldest Cold Focal Plane Array (CFPA) temperature achieved was colder.

Investigation of energy transport in DIII-D high- β P EAST-demonstration discharges with the TGLF turbulent and NEO neoclassical transport models [Investigation of energy transport in DIII-D high- β P EAST-demonstration discharges with turbulent and neoclassical transport models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pan, Chengkang; Staebler, Gary M.; Lao, Lang L.

Here, energy transport analyses of DIII-D high-β P EAST-demonstration discharges have been performed using the TGYRO transport package with TGLF turbulent and NEO neoclassical transport models under the OMFIT integrated modeling framework. Ion energy transport is shown to be dominated by neoclassical transport and ion temperature profiles predicted by TGYRO agree closely with the experimental measured profiles for these high-β P discharges. Ion energy transport is largely insensitive to reductions in the E × B flow shear stabilization. The Shafranov shift is shown to play a role in the suppression of the ion turbulent energy transport below the neoclassical level.more » Electron turbulent energy transport is under-predicted by TGLF and a significant shortfall in the electron energy transport over the whole core plasma is found with TGLF predictions for these high-β P discharges. TGYRO can successfully predict the experimental ion and electron temperature profiles by artificially increasing the saturated turbulence level for ETG driven modes used in TGLF.« less

Investigation of energy transport in DIII-D high- β P EAST-demonstration discharges with the TGLF turbulent and NEO neoclassical transport models [Investigation of energy transport in DIII-D high- β P EAST-demonstration discharges with turbulent and neoclassical transport models

DOE PAGES

Pan, Chengkang; Staebler, Gary M.; Lao, Lang L.; ...

2017-01-11

Here, energy transport analyses of DIII-D high-β P EAST-demonstration discharges have been performed using the TGYRO transport package with TGLF turbulent and NEO neoclassical transport models under the OMFIT integrated modeling framework. Ion energy transport is shown to be dominated by neoclassical transport and ion temperature profiles predicted by TGYRO agree closely with the experimental measured profiles for these high-β P discharges. Ion energy transport is largely insensitive to reductions in the E × B flow shear stabilization. The Shafranov shift is shown to play a role in the suppression of the ion turbulent energy transport below the neoclassical level.more » Electron turbulent energy transport is under-predicted by TGLF and a significant shortfall in the electron energy transport over the whole core plasma is found with TGLF predictions for these high-β P discharges. TGYRO can successfully predict the experimental ion and electron temperature profiles by artificially increasing the saturated turbulence level for ETG driven modes used in TGLF.« less

Probing for suitable climatology to estimate the predictability of monsoon onset over Kerala (MOK), India

NASA Astrophysics Data System (ADS)

Pal, J.; Chaudhuri, S.; Mukherjee, S.; Chowdhury, A. Roy

2017-10-01

Inter-annual variability in the onset of monsoon over Kerala (MOK), India, is investigated using daily temperature; mean sea level pressure; winds at 850, 500 and 200 hPa pressure levels; outgoing longwave radiation (OLR); sea surface temperature (SST) and vertically integrated moisture content anomaly with 32 years (1981-2013) observation. The MOK is classified as early, delayed, or normal by considering the mean monsoon onset date over Kerala to be the 1st of June with a standard deviation of 8 days. The objective of the study is to identify the synoptic setup during MOK and comparison with climatology to estimate the predictability of the onset type (early, normal, or delayed) with 5, 10, and 15 days lead time. The study reveals that an enhanced convection observed over the Bay of Bengal during early MOK is found to shift over the Arabian Sea during delayed MOK. An intense high-pressure zone observed over the western south Indian Ocean during early MOK shifts to the east during delayed MOK. Higher tropospheric temperature (TT) over the western Equatorial Ocean during early MOK and lower TT over the Indian subcontinent intensify the land-ocean thermal contrast that leads to early MOK. The sea surface temperature (SST) over the Arabian Sea is observed to be warmer during delayed than early MOK. During early MOK, the source of 850 hPa southwesterly wind shifts to the west equatorial zone while a COL region has been found during delayed MOK at that level. The study further reveals that the wind speed anomaly at the 200-hPa pressure level coincides inversely with the anomaly of tropospheric temperature.

Phase Stability of a Powder Metallurgy Disk Superalloy

NASA Technical Reports Server (NTRS)

Gabb, Timothy P.; Gayda, John; Kantzos, P.; Telesman, Jack; Gang, Anita

2006-01-01

Advanced powder metallurgy superalloy disks in aerospace turbine engines now entering service can be exposed to temperatures approaching 700 C, higher than those previously encountered. They also have higher levels of refractory elements, which can increase mechanical properties at these temperatures but can also encourage phase instabilities during service. Microstructural changes including precipitation of topological close pack phase precipitation and coarsening of existing gamma' precipitates can be slow at these temperatures, yet potentially significant for anticipated disk service times exceeding 1,000 h. The ability to quantify and predict such potential phase instabilities and degradation of capabilities is needed to insure structural integrity and air worthiness of propulsion systems over the full life cycle. A prototypical advanced disk superalloy was subjected to high temperature exposures, and then evaluated. Microstructural changes and corresponding changes in mechanical properties were quantified. The results will be compared to predictions of microstructure modeling software.

A Stab in the Dark?: A Research Note on Temporal Patterns of Street Robbery.

PubMed

Tompson, Lisa; Bowers, Kate

2013-11-01

Test the influence of darkness in the street robbery crime event alongside temperature. Negative binomial regression models tested darkness and temperature as predictors of street robbery. Units of analysis were four 6-hr time intervals in two U.K. study areas that have different levels of darkness and variations of temperature throughout the year. Darkness is a key factor related to robbery events in both study areas. Traversing from full daylight to full darkness increased the predicted volume of robbery by a multiple of 2.6 in London and 1.2 in Glasgow. Temperature was significant only in the London study area. Interaction terms did not enhance the predictive power of the models. Darkness is an important driving factor in seasonal variation of street robbery. A further implication of the research is that time of the day patterns are crucial to understanding seasonal trends in crime data.

The Effect of Temperature and Host Plant Resistance on Population Growth of the Soybean Aphid Biotype 1 (Hemiptera: Aphididae).

PubMed

Hough, Ashley R; Nechols, James R; McCornack, Brian P; Margolies, David C; Sandercock, Brett K; Yan, Donglin; Murray, Leigh

2017-02-01

A laboratory experiment was conducted to evaluate direct and indirect effects of temperature on demographic traits and population growth of biotype 1 of the soybean aphid, Aphis glycines Matsumura. Our objectives were to better understand how temperature influences the expression of host plant resistance, quantify the individual and interactive effects of plant resistance and temperature on soybean aphid population growth, and generate thermal constants for predicting temperature-dependent development on both susceptible and resistant soybeans. To assess indirect (plant-mediated) effects, soybean aphids were reared under a range of temperatures (15-30 °C) on soybean seedlings from a line expressing a Rag1 gene for resistance, and life history traits were quantified and compared to those obtained for soybean aphids on a susceptible soybean line. Direct effects of temperature were obtained by comparing relative differences in the magnitude of life-history traits among temperatures on susceptible soybeans. We predicted that temperature and host plant resistance would have a combined, but asymmetrical, effect on soybean aphid fitness and population growth. Results showed that temperature and plant resistance influenced preimaginal development and survival, progeny produced, and adult longevity. There also appeared to be a complex interaction between temperature and plant resistance for survival and developmental rate. Evidence suggested that the level of plant resistance increased at higher, but not lower, temperature. Soybean aphids required about the same number of degree-days to develop on resistant and susceptible plants. Our results will be useful for making predictions of soybean aphid population growth on resistant plants under different seasonal temperatures. © The Authors 2016. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Global predictability of temperature extremes

NASA Astrophysics Data System (ADS)

Coughlan de Perez, Erin; van Aalst, Maarten; Bischiniotis, Konstantinos; Mason, Simon; Nissan, Hannah; Pappenberger, Florian; Stephens, Elisabeth; Zsoter, Ervin; van den Hurk, Bart

2018-05-01

Extreme temperatures are one of the leading causes of death and disease in both developed and developing countries, and heat extremes are projected to rise in many regions. To reduce risk, heatwave plans and cold weather plans have been effectively implemented around the world. However, much of the world’s population is not yet protected by such systems, including many data-scarce but also highly vulnerable regions. In this study, we assess at a global level where such systems have the potential to be effective at reducing risk from temperature extremes, characterizing (1) long-term average occurrence of heatwaves and coldwaves, (2) seasonality of these extremes, and (3) short-term predictability of these extreme events three to ten days in advance. Using both the NOAA and ECMWF weather forecast models, we develop global maps indicating a first approximation of the locations that are likely to benefit from the development of seasonal preparedness plans and/or short-term early warning systems for extreme temperature. The extratropics generally show both short-term skill as well as strong seasonality; in the tropics, most locations do also demonstrate one or both. In fact, almost 5 billion people live in regions that have seasonality and predictability of heatwaves and/or coldwaves. Climate adaptation investments in these regions can take advantage of seasonality and predictability to reduce risks to vulnerable populations.

Stark parameter dependence of the rest core charge of the emitters for multiply charged ions spectral lines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Šćepanović, M., E-mail: mara.scepanovic@gmail.com; Purić, J.

2016-03-25

Stark width and shift simultaneous dependence on the upper level ionization potential and rest core charge of the emitter has been evaluated and discussed. It has been verified that the found relations, connecting Stark broadening parameters with upper level ionization potential and rest core charge of the emitters for particular electron temperature and density, can be used for prediction of Stark line width and shift data in case of ions for which observed data, or more detailed calculations, are not yet available. Stark widths and shifts published data are used to demonstrate the existence of other kinds of regularities withinmore » similar spectra of different elements and their ionization stages. The emphasis is on the Stark parameter dependence on the upper level ionization potential and on the rest core charge for the lines from similar spectra of multiply charged ions. The found relations connecting Stark widths and shift parameters with upper level ionization potential, rest core charge and electron temperature were used for a prediction of new Stark broadening data, thus avoiding much more complicated procedures.« less

A primary exploration to quasi-two-dimensional rare-earth ferromagnetic particles: holmium-doped MoS2 sheet as room-temperature magnetic semiconductor

NASA Astrophysics Data System (ADS)

Chen, Xi; Lin, Zheng-Zhe

2018-05-01

Recently, two-dimensional materials and nanoparticles with robust ferromagnetism are even of great interest to explore basic physics in nanoscale spintronics. More importantly, room-temperature magnetic semiconducting materials with high Curie temperature is essential for developing next-generation spintronic and quantum computing devices. Here, we develop a theoretical model on the basis of density functional theory calculations and the Ruderman-Kittel-Kasuya-Yoshida theory to predict the thermal stability of two-dimensional magnetic materials. Compared with other rare-earth (dysprosium (Dy) and erbium (Er)) and 3 d (copper (Cu)) impurities, holmium-doped (Ho-doped) single-layer 1H-MoS2 is proposed as promising semiconductor with robust magnetism. The calculations at the level of hybrid HSE06 functional predict a Curie temperature much higher than room temperature. Ho-doped MoS2 sheet possesses fully spin-polarized valence and conduction bands, which is a prerequisite for flexible spintronic applications.

An Interactive Tool For Semi-automated Statistical Prediction Using Earth Observations and Models

NASA Astrophysics Data System (ADS)

Zaitchik, B. F.; Berhane, F.; Tadesse, T.

2015-12-01

We developed a semi-automated statistical prediction tool applicable to concurrent analysis or seasonal prediction of any time series variable in any geographic location. The tool was developed using Shiny, JavaScript, HTML and CSS. A user can extract a predictand by drawing a polygon over a region of interest on the provided user interface (global map). The user can select the Climatic Research Unit (CRU) precipitation or Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) as predictand. They can also upload their own predictand time series. Predictors can be extracted from sea surface temperature, sea level pressure, winds at different pressure levels, air temperature at various pressure levels, and geopotential height at different pressure levels. By default, reanalysis fields are applied as predictors, but the user can also upload their own predictors, including a wide range of compatible satellite-derived datasets. The package generates correlations of the variables selected with the predictand. The user also has the option to generate composites of the variables based on the predictand. Next, the user can extract predictors by drawing polygons over the regions that show strong correlations (composites). Then, the user can select some or all of the statistical prediction models provided. Provided models include Linear Regression models (GLM, SGLM), Tree-based models (bagging, random forest, boosting), Artificial Neural Network, and other non-linear models such as Generalized Additive Model (GAM) and Multivariate Adaptive Regression Splines (MARS). Finally, the user can download the analysis steps they used, such as the region they selected, the time period they specified, the predictand and predictors they chose and preprocessing options they used, and the model results in PDF or HTML format. Key words: Semi-automated prediction, Shiny, R, GLM, ANN, RF, GAM, MARS

Prediction of soot and thermal radiation in a model gas turbine combustor burning kerosene fuel spray at different swirl levels

NASA Astrophysics Data System (ADS)

Ghose, Prakash; Patra, Jitendra; Datta, Amitava; Mukhopadhyay, Achintya

2016-05-01

Combustion of kerosene fuel spray has been numerically simulated in a laboratory scale combustor geometry to predict soot and the effects of thermal radiation at different swirl levels of primary air flow. The two-phase motion in the combustor is simulated using an Eulerian-Lagragian formulation considering the stochastic separated flow model. The Favre-averaged governing equations are solved for the gas phase with the turbulent quantities simulated by realisable k-ɛ model. The injection of the fuel is considered through a pressure swirl atomiser and the combustion is simulated by a laminar flamelet model with detailed kinetics of kerosene combustion. Soot formation in the flame is predicted using an empirical model with the model parameters adjusted for kerosene fuel. Contributions of gas phase and soot towards thermal radiation have been considered to predict the incident heat flux on the combustor wall and fuel injector. Swirl in the primary flow significantly influences the flow and flame structures in the combustor. The stronger recirculation at high swirl draws more air into the flame region, reduces the flame length and peak flame temperature and also brings the soot laden zone closer to the inlet plane. As a result, the radiative heat flux on the peripheral wall decreases at high swirl and also shifts closer to the inlet plane. However, increased swirl increases the combustor wall temperature due to radial spreading of the flame. The high incident radiative heat flux and the high surface temperature make the fuel injector a critical item in the combustor. The injector peak temperature increases with the increase in swirl flow mainly because the flame is located closer to the inlet plane. On the other hand, a more uniform temperature distribution in the exhaust gas can be attained at the combustor exit at high swirl condition.

Owens-Illinois liquid solar collector materials assessment

NASA Technical Reports Server (NTRS)

Nichols, R. L.

1978-01-01

From the beginning, it was noted that the baseline drawings for the liquid solar collector exhibited a distinct weakness concerning materials specification where elastomers, plastics, and foam insulation materials were utilized. A relatively small effort by a competent design organization would alleviate this deficiency. Based on results obtained from boilout and stagnation tests on the solar simulator, it was concluded that proof testing of the collector tubes prior to use helps to predict their performance for limited service life. Fracture mechanics data are desirable for predicting extended service life and establishing a minimum proof pressure level requirement. The temperature capability of this collector system was increased as the design matured and the coating efficiency improved. This higher temperature demands the use of higher temperature materials at critical locations in the collector.

Temperature sensor based on ladder-level assisted thermal coupling and thermal-enhanced luminescence in NaYF4: Nd³⁺.

PubMed

Tian, Xiuna; Wei, Xiantao; Chen, Yonghu; Duan, Changkui; Yin, Min

2014-12-01

NaYF4: Nd³⁺ microprisms were synthesized by a hydrothermal method. The bands of near-infrared (NIR) luminescence originating from the 4F3/2, 4F5/2 and 4F7/2 levels of Nd³⁺ ions in NaYF4: Nd³⁺ microcrystals were measured under 574.8 nm excitation at various temperatures from 323 to 673 K. The fluorescence intensity ratios (FIRs) between any two of the three bands change monotonically with temperature and agree with the prediction assuming thermal couplings. A large relative temperature sensitivity of 1.12% K⁻¹ at 500K is reached with the FIR of 4F7/2 to 4F3/2 levels. In addition, anti-Stokes fluorescence from 4F5/2 level (740 nm) and 4F5/2,7/2 levels (740 nm and 803 nm) of Nd³⁺ ions was studied meticulously under 793.8 nm and 864.2 nm excitations, respectively. The intensities were shown to be greatly enhanced as temperature increases, and the 740 nm band from 4F7/2 level at 458 K increases in intensity by 170 fold relative to that at 298 K under the 793.8 nm excitation.

Cyclic stress analysis of an air-cooled turbine vane

NASA Technical Reports Server (NTRS)

Kaufman, A.; Gauntner, D. J.; Gauntner, J. W.

1975-01-01

The effects of gas pressure level, coolant temperature, and coolant flow rate on the stress-strain history and life of an air-cooled vane were analyzed using measured and calculated transient metal temperatures and a turbine blade stress analysis program. Predicted failure locations were compared to results from cyclic tests in a static cascade and engine. The results indicate that a high gas pressure was detrimental, a high coolant flow rate somewhat beneficial, and a low coolant temperature the most beneficial to vane life.

Idiosyncratic species effects confound size-based predictions of responses to climate change.

PubMed

Twomey, Marion; Brodte, Eva; Jacob, Ute; Brose, Ulrich; Crowe, Tasman P; Emmerson, Mark C

2012-11-05

Understanding and predicting the consequences of warming for complex ecosystems and indeed individual species remains a major ecological challenge. Here, we investigated the effect of increased seawater temperatures on the metabolic and consumption rates of five distinct marine species. The experimental species reflected different trophic positions within a typical benthic East Atlantic food web, and included a herbivorous gastropod, a scavenging decapod, a predatory echinoderm, a decapod and a benthic-feeding fish. We examined the metabolism-body mass and consumption-body mass scaling for each species, and assessed changes in their consumption efficiencies. Our results indicate that body mass and temperature effects on metabolism were inconsistent across species and that some species were unable to meet metabolic demand at higher temperatures, thus highlighting the vulnerability of individual species to warming. While body size explains a large proportion of the variation in species' physiological responses to warming, it is clear that idiosyncratic species responses, irrespective of body size, complicate predictions of population and ecosystem level response to future scenarios of climate change.

Effects of ambient ozone on respiratory function and symptoms in Mexico City schoolchildren

DOE Office of Scientific and Technical Information (OSTI.GOV)

Castillejos, M.; Gold, D.R.; Dockery, D.

1992-02-01

The effects of ambient ozone (O3) on respiratory function and acute respiratory symptoms were evaluated in 143 7- to 9-yr-old schoolchildren followed longitudinally at 1- to 2-wk intervals over a period of 6 months at three schools in Pedregal, Mexico City. The maximum O3 level exceeded the World Health Organization guideline of 80 ppb and the U.S. standard of 120 ppb in every week. For an increase from lowest to highest in the mean O3 level during the 48 hr before spirometry (53 ppb), logistic regression estimated relative odds of 1.7 for a child reporting cough/phlegm on the day ofmore » spirometry. For the full population, the mean O3 level during the hour before spirometry, not adjusted for temperature and humidity, predicted a significant decrement in FVC but not in FEV1 or FEF25-75. In contrast, the mean O3 level during the previous 24-, 48-, and 168-h periods predicted significant decrements in FEV1 and FEF25-75 but not in FVC. Ozone was consistently associated with a greater decrement in lung function for the 15 children with chronic phlegm as compared with the children without chronic cough, chronic phlegm, or wheeze. Ozone in the previous 24-, 48-, and 168-h periods predicted decrements in FEV1 for children of mothers who were current or former smokers, but not for children of mothers who were never smokers. Many of these effects were reduced in multiple regression analyses including temperature and humidity, as temperature and O3 were highly correlated.« less

Development of a Climate Prediction Market

NASA Astrophysics Data System (ADS)

Roulston, M. S.

2017-12-01

Winton, a global investment firm, is planning to establish a prediction market for climate. This prediction market will allow participants to place bets on global climate up to several decades in the future. Winton is pursuing this endeavour as part of its philanthropy that funds scientific research and the communication of scientific ideas. The Winton Climate Prediction Market will be based in the U.K. It will be structured as an online gambling site subject to the regulation of the Gambling Commission. Unlike existing betting sites, the Climate Prediction Market will be subsidized: a central market maker will inject money into the market. This is in contrast to traditional bookmakers or betting exchanges who set odds in their favour or charge commissions to make a profit. The philosophy of a subsidized prediction market is that the party seeking information should fund the market, rather than the participants who provide the information. The initial market will allow bets to be placed on the atmospheric concentration of carbon dioxide and the global mean temperature anomaly. It will thus produce implied forecasts of carbon dioxide concentration as well as global temperatures. If the initial market is successful, additional markets could be added which target other climate variables, such as regional temperatures or sea-level rise. These markets could be sponsored by organizations that are interested in predictions of the specific climate variables. An online platform for the Climate Prediction Market has been developed and has been tested internally at Winton.

Plant molecular responses to the elevated ambient temperatures expected under global climate change.

PubMed

Fei, Qionghui; Li, Jingjing; Luo, Yunhe; Ma, Kun; Niu, Bingtao; Mu, Changjun; Gao, Huanhuan; Li, Xiaofeng

2018-01-02

Environmental temperatures affect plant distribution, growth, and development. The Intergovernmental Panel on Climate Change (IPCC) predicts that global temperatures will rise by at least 1.5°C by the end of this century. Global temperature changes have already had a discernable impact on agriculture, phenology, and ecosystems. At the molecular level, extensive literature exists on the mechanism controlling plant responses to high temperature stress. However, few studies have focused on the molecular mechanisms behind plant responses to mild increases in ambient temperature. Previous research has found that moderately higher ambient temperatures can induce hypocotyl elongation and early flowering. Recent evidence demonstrates roles for the phytohormones auxin and ethylene in adaptive growth of plant roots to slightly higher ambient temperatures.

Climate change and freshwater ecosystems: impacts across multiple levels of organization

PubMed Central

Woodward, Guy; Perkins, Daniel M.; Brown, Lee E.

2010-01-01

Fresh waters are particularly vulnerable to climate change because (i) many species within these fragmented habitats have limited abilities to disperse as the environment changes; (ii) water temperature and availability are climate-dependent; and (iii) many systems are already exposed to numerous anthropogenic stressors. Most climate change studies to date have focused on individuals or species populations, rather than the higher levels of organization (i.e. communities, food webs, ecosystems). We propose that an understanding of the connections between these different levels, which are all ultimately based on individuals, can help to develop a more coherent theoretical framework based on metabolic scaling, foraging theory and ecological stoichiometry, to predict the ecological consequences of climate change. For instance, individual basal metabolic rate scales with body size (which also constrains food web structure and dynamics) and temperature (which determines many ecosystem processes and key aspects of foraging behaviour). In addition, increasing atmospheric CO2 is predicted to alter molar CNP ratios of detrital inputs, which could lead to profound shifts in the stoichiometry of elemental fluxes between consumers and resources at the base of the food web. The different components of climate change (e.g. temperature, hydrology and atmospheric composition) not only affect multiple levels of biological organization, but they may also interact with the many other stressors to which fresh waters are exposed, and future research needs to address these potentially important synergies. PMID:20513717

Further experimentation on bubble generation during transformer overload

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oommen, T.V.

1992-03-01

This report covers additional work done during 1990 and 1991 on gas bubble generation under overload conditions. To improve visual bubble detection, a single disc coil was used. To further improve detection, a corona device was also used which signaled the onset of corona activity in the early stages of bubble formation. A total of fourteen model tests were conducted, half of which used the Inertaire system, and the remaining, a conservator (COPS). Moisture content of paper in the coil varied from 1.0% to 8.0%; gas (nitrogen) content varied from 1.0% to 8.8%. The results confirmed earlier observations that themore » mathematical bubble prediction model was not valid for high gas content model with relatively low moisture levels in the coil. An empirical relationship was formulated to accurately predict bubble evolution temperatures from known moisture and gas content values. For low moisture content models (below 2%), the simple Piper relationship was sufficient to predict bubble evolution temperatures, regardless of gas content. Moisture in the coil appears to be the key factor in bubble generation. Gas blanketed (Inertaire) systems do not appear to be prone to premature bubble generation from overloads as previously thought. The new bubble prediction model reveals that for a coil with 2% moisture, the bubble evolution temperature would be about 140{degrees}C. Since old transformers in service may have as much as 2% moisture in paper, the 140{degrees}C bubble evolution temperature may be taken as the lower limit of bubble evolution temperature under overload conditions for operating transformers. Drier insulation would raise the bubble evolution temperature.« less

Perceived exertion is as effective as the perceptual strain index in predicting physiological strain when wearing personal protective clothing.

PubMed

Borg, David N; Costello, Joseph T; Bach, Aaron J; Stewart, Ian B

2017-02-01

The perceptual strain index (PeSI) has been shown to overcome the limitations associated with the assessment of the physiological strain index (PSI), primarily the need to obtain a core body temperature measurement. The PeSI uses the subjective scales of thermal sensation and perceived exertion (RPE) to provide surrogate measures of core temperature and heart rate, respectively. Unfortunately, thermal sensation has shown large variability in providing an estimation of core body temperature. Therefore, the primary aim of this study was to determine if thermal comfort improved the ability of the PeSI to predict the PSI during exertional-heat stress. Eighteen healthy males (age: 23.5years; body mass: 79.4kg; maximal aerobic capacity: 57.2ml·kg -1 ·min -1 ) wore four different chemical/biological protective garments while walking on treadmill at a low (<325W) or moderate (326-499W) metabolic workload in environmental conditions equivalent to wet bulb globe temperatures 21, 30 or 37°C. Trials were terminated when heart rate exceeded 90% of maximum, when core body temperature reached 39°C, at 120min or due to volitional fatigue. Core body temperature, heart rate, thermal sensation, thermal comfort and RPE were recorded at 15min intervals and at termination. Multiple statistical methods were used to determine the most accurate perceptual predictor. Significant moderate relationships were observed between the PeSI (r=0.74; p<0.001), the modified PeSI (r=0.73; p<0.001) and unexpectedly RPE (r=0.71; p<0.001) with the PSI, respectively. The PeSI (mean bias: -0.8±1.5 based on a 0-10 scale; area under the curve: 0.887), modified PeSI (mean bias: -0.5±1.4 based on 0-10 scale; area under the curve: 0.886) and RPE (mean bias: -0.7±1.4 based on a 0-10 scale; area under the curve: 0.883) displayed similar predictive performance when participants experienced high-to-very high levels of physiological strain. Modifying the PeSI did not improve the subjective prediction of physiological strain. However, RPE provided an equally accurate prediction of physiological strain, particularly when high-to-very high levels of strain were observed. Therefore, given its predictive performance and user-friendliness, the evidence suggests that RPE in isolation is a practical and cost-effective tool able to estimate physiological strain during exertional-heat stress under these work conditions. Copyright © 2016 Elsevier Inc. All rights reserved.

Electro-thermal analysis of contact resistance

NASA Astrophysics Data System (ADS)

Pandey, Nitin; Jain, Ishant; Reddy, Sudhakar; Gulhane, Nitin P.

2018-05-01

Electro-Mechanical characterization over copper samples are performed at the macroscopic level to understand the dependence of electrical contact resistance and temperature on surface roughness and contact pressure. For two different surface roughness levels of samples, six levels of load are selected and varied to capture the bulk temperature rise and electrical contact resistance. Accordingly, the copper samples are modelled and analysed using COMSOLTM as a simulation package and the results are validated by the experiments. The interface temperature during simulation is obtained using Mikic-Elastic correlation and by directly entering experimental contact resistance value. The load values are varied and then reversed in a similar fashion to capture the hysteresis losses. The governing equations & assumptions underlying these models and their significance are examined & possible justification for the observed variations are discussed. Equivalent Greenwood model is also predicted by mapping the results of the experiment.

The predicted influence of climate change on lesser prairie-chicken reproductive parameters

USGS Publications Warehouse

Grisham, Blake A.; Boal, Clint W.; Haukos, David A.; Davis, D.; Boydston, Kathy K.; Dixon, Charles; Heck, Willard R.

2013-01-01

The Southern High Plains is anticipated to experience significant changes in temperature and precipitation due to climate change. These changes may influence the lesser prairie-chicken (Tympanuchus pallidicinctus) in positive or negative ways. We assessed the potential changes in clutch size, incubation start date, and nest survival for lesser prairie-chickens for the years 2050 and 2080 based on modeled predictions of climate change and reproductive data for lesser prairie-chickens from 2001-2011 on the Southern High Plains of Texas and New Mexico. We developed 9 a priori models to assess the relationship between reproductive parameters and biologically relevant weather conditions. We selected weather variable(s) with the most model support and then obtained future predicted values from climatewizard.org. We conducted 1,000 simulations using each reproductive parameter's linear equation obtained from regression calculations, and the future predicted value for each weather variable to predict future reproductive parameter values for lesser prairie-chickens. There was a high degree of model uncertainty for each reproductive value. Winter temperature had the greatest effect size for all three parameters, suggesting a negative relationship between above-average winter temperature and reproductive output. The above-average winter temperatures are correlated to La Nina events, which negatively affect lesser prairie-chickens through resulting drought conditions. By 2050 and 2080, nest survival was predicted to be below levels considered viable for population persistence; however, our assessment did not consider annual survival of adults, chick survival, or the positive benefit of habitat management and conservation, which may ultimately offset the potentially negative effect of drought on nest survival.

Locust displacing winds in eastern Australia reassessed with observations from an insect monitoring radar

NASA Astrophysics Data System (ADS)

Hao, Zhenhua; Drake, V. Alistair; Sidhu, Leesa; Taylor, John R.

2017-12-01

Based on previous investigations, adult Australian plague locusts are believed to migrate on warm nights (with evening temperatures >25 °C), provided daytime flight is suppressed by surface winds greater than the locusts' flight speed, which has been shown to be 3.1 m s-1. Moreover, adult locusts are believed to undertake briefer `dispersal' flights on nights with evening temperature >20 °C. To reassess the utility of these conditions for forecasting locust flight, contingency tests were conducted comparing the nights selected on these bases (predicted nights) for the months of November, January, and March and the nights when locust migration were detected with an insect monitoring radar (actual nights) over a 7-year period. In addition, the wind direction distributions and mean wind directions on all predicted nights and actual nights were compared. Observations at around 395 m above ground level (AGL), the height at which radar observations have shown that the greatest number of locusts fly, were used to determine the actual nights. Tests and comparisons were also made for a second height, 990 m AGL, as this was used in the previous investigation. Our analysis shows that the proposed criteria are successful from predicting migratory flight only in March, when the surface temperature is effective as a predicting factor. Surface wind speed has no predicting power. It is suggested that a strong daytime surface wind speed requirement should not be considered and other meteorological variables need to be added to the requirement of a warm surface temperature around dusk for the predictions to have much utility.

The predicted influence of climate change on lesser prairie-chicken reproductive parameters.

PubMed

Grisham, Blake A; Boal, Clint W; Haukos, David A; Davis, Dawn M; Boydston, Kathy K; Dixon, Charles; Heck, Willard R

2013-01-01

The Southern High Plains is anticipated to experience significant changes in temperature and precipitation due to climate change. These changes may influence the lesser prairie-chicken (Tympanuchus pallidicinctus) in positive or negative ways. We assessed the potential changes in clutch size, incubation start date, and nest survival for lesser prairie-chickens for the years 2050 and 2080 based on modeled predictions of climate change and reproductive data for lesser prairie-chickens from 2001-2011 on the Southern High Plains of Texas and New Mexico. We developed 9 a priori models to assess the relationship between reproductive parameters and biologically relevant weather conditions. We selected weather variable(s) with the most model support and then obtained future predicted values from climatewizard.org. We conducted 1,000 simulations using each reproductive parameter's linear equation obtained from regression calculations, and the future predicted value for each weather variable to predict future reproductive parameter values for lesser prairie-chickens. There was a high degree of model uncertainty for each reproductive value. Winter temperature had the greatest effect size for all three parameters, suggesting a negative relationship between above-average winter temperature and reproductive output. The above-average winter temperatures are correlated to La Niña events, which negatively affect lesser prairie-chickens through resulting drought conditions. By 2050 and 2080, nest survival was predicted to be below levels considered viable for population persistence; however, our assessment did not consider annual survival of adults, chick survival, or the positive benefit of habitat management and conservation, which may ultimately offset the potentially negative effect of drought on nest survival.

Modeling conductive heat transfer during high-pressure thawing processes: determination of latent heat as a function of pressure.

PubMed

Denys, S; Van Loey, A M; Hendrickx, M E

2000-01-01

A numerical heat transfer model for predicting product temperature profiles during high-pressure thawing processes was recently proposed by the authors. In the present work, the predictive capacity of the model was considerably improved by taking into account the pressure dependence of the latent heat of the product that was used (Tylose). The effect of pressure on the latent heat of Tylose was experimentally determined by a series of freezing experiments conducted at different pressure levels. By combining a numerical heat transfer model for freezing processes with a least sum of squares optimization procedure, the corresponding latent heat at each pressure level was estimated, and the obtained pressure relation was incorporated in the original high-pressure thawing model. Excellent agreement with the experimental temperature profiles for both high-pressure freezing and thawing was observed.

Predictability of the 2012 Great Arctic Cyclone on medium-range timescales

NASA Astrophysics Data System (ADS)

Yamagami, Akio; Matsueda, Mio; Tanaka, Hiroshi L.

2018-03-01

Arctic Cyclones (ACs) can have a significant impact on the Arctic region. Therefore, the accurate prediction of ACs is important in anticipating their associated environmental and societal costs. This study investigates the predictability of the 2012 Great Arctic Cyclone (AC12) that exhibited a minimum central pressure of 964 hPa on 6 August 2012, using five medium-range ensemble forecasts. We show that the development and position of AC12 were better predicted in forecasts initialized on and after 4 August 2012. In addition, the position of AC12 was more predictable than its development. A comparison of ensemble members, classified by the error in predictability of the development and position of AC12, revealed that an accurate prediction of upper-level fields, particularly temperature, was important for the prediction of this event. The predicted position of AC12 was influenced mainly by the prediction of the polar vortex, whereas the predicted development of AC12 was dependent primarily on the prediction of the merging of upper-level warm cores. Consequently, an accurate prediction of the polar vortex position and the development of the warm core through merging resulted in better prediction of AC12.

Can spatial statistical river temperature models be transferred between catchments?

NASA Astrophysics Data System (ADS)

Jackson, Faye L.; Fryer, Robert J.; Hannah, David M.; Malcolm, Iain A.

2017-09-01

There has been increasing use of spatial statistical models to understand and predict river temperature (Tw) from landscape covariates. However, it is not financially or logistically feasible to monitor all rivers and the transferability of such models has not been explored. This paper uses Tw data from four river catchments collected in August 2015 to assess how well spatial regression models predict the maximum 7-day rolling mean of daily maximum Tw (Twmax) within and between catchments. Models were fitted for each catchment separately using (1) landscape covariates only (LS models) and (2) landscape covariates and an air temperature (Ta) metric (LS_Ta models). All the LS models included upstream catchment area and three included a river network smoother (RNS) that accounted for unexplained spatial structure. The LS models transferred reasonably to other catchments, at least when predicting relative levels of Twmax. However, the predictions were biased when mean Twmax differed between catchments. The RNS was needed to characterise and predict finer-scale spatially correlated variation. Because the RNS was unique to each catchment and thus non-transferable, predictions were better within catchments than between catchments. A single model fitted to all catchments found no interactions between the landscape covariates and catchment, suggesting that the landscape relationships were transferable. The LS_Ta models transferred less well, with particularly poor performance when the relationship with the Ta metric was physically implausible or required extrapolation outside the range of the data. A single model fitted to all catchments found catchment-specific relationships between Twmax and the Ta metric, indicating that the Ta metric was not transferable. These findings improve our understanding of the transferability of spatial statistical river temperature models and provide a foundation for developing new approaches for predicting Tw at unmonitored locations across multiple catchments and larger spatial scales.

Climate Response of Direct Radiative Forcing of Anthropogenic Black Carbon

NASA Technical Reports Server (NTRS)

Chung, Serena H.; Seinfeld,John H.

2008-01-01

The equilibrium climate effect of direct radiative forcing of anthropogenic black carbon (BC) is examined by 100-year simulations in the Goddard Institute for Space Studies General Circulation Model II-prime coupled to a mixed-layer ocean model. Anthropogenic BC is predicted to raise globally and annually averaged equilibrium surface air temperature by 0.20 K if BC is assumed to be externally mixed. The predicted increase is significantly greater in the Northern Hemisphere (0.29 K) than in the Southern Hemisphere (0.11 K). If BC is assumed to be internally mixed with the present day level of sulfate aerosol, the predicted annual mean surface temperature increase rises to 0.37 K globally, 0.54 K for the Northern Hemisphere, and 0.20 K for the Southern Hemisphere. The climate sensitivity of BC direct radiative forcing is calculated to be 0.6 K W (sup -1) square meters, which is about 70% of that of CO2, independent of the assumption of BC mixing state. The largest surface temperature response occurs over the northern high latitudes during winter and early spring. In the tropics and midlatitudes, the largest temperature increase is predicted to occur in the upper troposphere. Direct radiative forcing of anthropogenic BC is also predicted to lead to a change of precipitation patterns in the tropics; precipitation is predicted to increase between 0 and 20 N and decrease between 0 and 20 S, shifting the intertropical convergence zone northward. If BC is assumed to be internally mixed with sulfate instead of externally mixed, the change in precipitation pattern is enhanced. The change in precipitation pattern is not predicted to alter the global burden of BC significantly because the change occurs predominantly in regions removed from BC sources.

Surface Temperature Variation Prediction Model Using Real-Time Weather Forecasts

NASA Astrophysics Data System (ADS)

Karimi, M.; Vant-Hull, B.; Nazari, R.; Khanbilvardi, R.

2015-12-01

Combination of climate change and urbanization are heating up cities and putting the lives of millions of people in danger. More than half of the world's total population resides in cities and urban centers. Cities are experiencing urban Heat Island (UHI) effect. Hotter days are associated with serious health impacts, heart attaches and respiratory and cardiovascular diseases. Densely populated cities like Manhattan, New York can be affected by UHI impact much more than less populated cities. Even though many studies have been focused on the impact of UHI and temperature changes between urban and rural air temperature, not many look at the temperature variations within a city. These studies mostly use remote sensing data or typical measurements collected by local meteorological station networks. Local meteorological measurements only have local coverage and cannot be used to study the impact of UHI in a city and remote sensing data such as MODIS, LANDSAT and ASTER have with very low resolution which cannot be used for the purpose of this study. Therefore, predicting surface temperature in urban cities using weather data can be useful.Three months of Field campaign in Manhattan were used to measure spatial and temporal temperature variations within an urban setting by placing 10 fixed sensors deployed to measure temperature, relative humidity and sunlight. Fixed instrument shelters containing relative humidity, temperature and illumination sensors were mounted on lampposts in ten different locations in Manhattan (Vant-Hull et al, 2014). The shelters were fixed 3-4 meters above the ground for the period of three months from June 23 to September 20th of 2013 making measurements with the interval of 3 minutes. These high resolution temperature measurements and three months of weather data were used to predict temperature variability from weather forecasts. This study shows that the amplitude of spatial and temporal variation in temperature for each day can be predicted by regression of weather variables. In addition amplitude of spatial variations were most dependent on temperature, north winds, and high level lapse rate and the temporal variations were most dependent on temperature and lapse rates.

Prediction model for peninsular Indian summer monsoon rainfall using data mining and statistical approaches

NASA Astrophysics Data System (ADS)

Vathsala, H.; Koolagudi, Shashidhar G.

2017-01-01

In this paper we discuss a data mining application for predicting peninsular Indian summer monsoon rainfall, and propose an algorithm that combine data mining and statistical techniques. We select likely predictors based on association rules that have the highest confidence levels. We then cluster the selected predictors to reduce their dimensions and use cluster membership values for classification. We derive the predictors from local conditions in southern India, including mean sea level pressure, wind speed, and maximum and minimum temperatures. The global condition variables include southern oscillation and Indian Ocean dipole conditions. The algorithm predicts rainfall in five categories: Flood, Excess, Normal, Deficit and Drought. We use closed itemset mining, cluster membership calculations and a multilayer perceptron function in the algorithm to predict monsoon rainfall in peninsular India. Using Indian Institute of Tropical Meteorology data, we found the prediction accuracy of our proposed approach to be exceptionally good.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lv, Q.; Kraus, A.; Hu, R.

CFD analysis has been focused on important component-level phenomena using STARCCM+ to supplement the system analysis of integral system behavior. A notable area of interest was the cavity region. This area is of particular interest for CFD analysis due to the multi-dimensional flow and complex heat transfer (thermal radiation heat transfer and natural convection), which are not simulated directly by RELAP5. CFD simulations allow for the estimation of the boundary heat flux distribution along the riser tubes, which is needed in the RELAP5 simulations. The CFD results can also provide additional data to help establish what level of modeling detailmore » is necessary in RELAP5. It was found that the flow profiles in the cavity region are simpler for the water-based concept than for the air-cooled concept. The local heat flux noticeably increases axially, and is higher in the fins than in the riser tubes. These results were utilized in RELAP5 simulations as boundary conditions, to provide better temperature predictions in the system level analyses. It was also determined that temperatures were higher in the fins than the riser tubes, but within design limits for thermal stresses. Higher temperature predictions were identified in the edge fins, in part due to additional thermal radiation from the side cavity walls.« less

Predicting the size and elevation of future mountain forests: Scaling macroclimate to microclimate

NASA Astrophysics Data System (ADS)

Cory, S. T.; Smith, W. K.

2017-12-01

Global climate change is predicted to alter continental scale macroclimate and regional mesoclimate. Yet, it is at the microclimate scale that organisms interact with their physiochemical environments. Thus, to predict future changes in the biota such as biodiversity and distribution patterns, a quantitative coupling between macro-, meso-, and microclimatic parameters must be developed. We are evaluating the impact of climate change on the size and elevational distribution of conifer mountain forests by determining the microclimate necessary for new seedling survival at the elevational boundaries of the forest. This initial life stage, only a few centimeters away from the soil surface, appears to be the bottleneck to treeline migration and the expansion or contraction of a conifer mountain forest. For example, survival at the alpine treeline is extremely rare and appears to be limited to facilitated microsites with low sky exposure. Yet, abundant mesoclimate data from standard weather stations have rarely been scaled to the microclimate level. Our research is focusing on an empirical downscaling approach linking microclimate measurements at favorable seedling microsites to the meso- and macro-climate levels. Specifically, mesoclimate values of air temperature, relative humidity, incident sunlight, and wind speed from NOAA NCEI weather stations can be extrapolated to the microsite level that is physiologically relevant for seedling survival. Data will be presented showing a strong correlation between incident sunlight measured at 2-m and seedling microclimate, despite large differences from seedling/microsite temperatures. Our downscaling approach will ultimately enable predictions of microclimate from the much more abundant mesoclimate data available from a variety of sources. Thus, scaling from macro- to meso- to microclimate will be possible, enabling predictions of climate change models to be translated to the microsite level. This linkage between measurement scales will enable a more precise prediction of the effects of climate change on the future extent and elevational distribution of our mountain forests and an accompanying array of critical ecosystem services.

Elements of a predictive model for determining beach closures on a real time basis: the case of 63rd Street Beach Chicago

USGS Publications Warehouse

Olyphant, Greg A.; Whitman, Richard L.

2004-01-01

Data on hydrometeorological conditions and E. coli concentration were simultaneously collected on 57 occasions during the summer of 2000 at 63rd Street Beach, Chicago, Illinois. The data were used to identify and calibrate a statistical regression model aimed at predicting when the bacterial concentration of the beach water was above or below the level considered safe for full body contact. A wide range of hydrological, meteorological, and water quality variables were evaluated as possible predictive variables. These included wind speed and direction, incoming solar radiation (insolation), various time frames of rainfall, air temperature, lake stage and wave height, and water temperature, specific conductance, dissolved oxygen, pH, and turbidity. The best-fit model combined real-time measurements of wind direction and speed (onshore component of resultant wind vector), rainfall, insolation, lake stage, water temperature and turbidity to predict the geometric mean E.coliconcentration in the swimming zone of the beach. The model, which contained both additive and multiplicative (interaction) terms, accounted for 71% of the observed variability in the log E. coliconcentrations. A comparison between model predictions of when the beach should be closed and when the actualbacterial concentrations were above or below the 235 cfu 100 ml-1 threshold value, indicated that the model accurately predicted openingsversus closures 88% of the time.

A Physics-Based Temperature Stabilization Criterion for Thermal Testing

NASA Technical Reports Server (NTRS)

Rickman, Steven L.; Ungar, Eugene K.

2009-01-01

Spacecraft testing specifications differ greatly in the criteria they specify for stability in thermal balance tests. Some specify a required temperature stabilization rate (the change in temperature per unit time, dT/dt), some specify that the final steady-state temperature be approached to within a specified difference, delta T , and some specify a combination of the two. The particular values for temperature stabilization rate and final temperature difference also vary greatly between specification documents. A one-size-fits-all temperature stabilization rate requirement does not yield consistent results for all test configurations because of differences in thermal mass and heat transfer to the environment. Applying a steady-state temperature difference requirement is problematic because the final test temperature is not accurately known a priori, especially for powered configurations. In the present work, a simplified, lumped-mass analysis has been used to explore the applicability of these criteria. A new, user-friendly, physics-based approach is developed that allows the thermal engineer to determine when an acceptable level of temperature stabilization has been achieved. The stabilization criterion can be predicted pre-test but must be refined during test to allow verification that the defined level of temperature stabilization has been achieved.

Enrichment of wheat chips with omega-3 fatty acid by flaxseed addition: textural and some physicochemical properties.

PubMed

Yuksel, Ferhat; Karaman, Safa; Kayacier, Ahmed

2014-02-15

In the present study, wheat chips enriched with flaxseed flour were produced and response surface methodology was used for the studying the simultaneous effects of flaxseed level (10-20%), frying temperature (160-180 °C) and frying time (40-60 s) on some physicochemical, textural and sensorial properties and fatty acid composition of wheat chips. Ridge analysis was conducted to determine the optimum levels of processing variables. Predictive regression equations with adequate coefficients of determination (R² ≥ 0.705) to explain the effect of processing variables were constructed. Addition of flaxseed flour increased the dry matter and protein content of samples and increase of frying temperature decreased the hardness values of wheat chips samples. Increment in flaxseed level provided an increase in unsaturated fatty acid content namely omega-3 fatty acids of wheat chips samples. Overall acceptability of chips increased with the increase of frying temperature. Ridge analysis showed that maximum taste score would be at flaxseed level = 10%, frying temperature = 180 °C and frying time = 50 s. Copyright © 2013 Elsevier Ltd. All rights reserved.

Nest temperatures in a loggerhead nesting beach in Turkey is more determined by sea surface than air temperature.

PubMed

Girondot, Marc; Kaska, Yakup

2015-01-01

While climate change is now fully recognised as a reality, its impact on biodiversity is still not completely understood. To predict its impact, proxies coherent with the studied ecosystem or species are thus required. Marine turtles are threatened worldwide (though some populations are recovering) as they are particularly sensitive to temperature throughout their entire life cycle. This is especially true at the embryo stage when temperature affects both growth rates and sex determination. Nest temperature is thus of prime importance to understand the persistence of populations in the context of climate change. We analysed the nest temperature of 21 loggerheads (Caretta caretta) originating from Dalyan Beach in Turkey using day-lagged generalised mixed models with autocorrelation. Surprisingly, the selected model for nest temperature includes an effect for sea surface temperature 4-times higher than for air temperature. We also detected a very significant effect of metabolic heating during development compatible with what is already known about marine turtle nests. Our new methodology allows the prediction of marine turtle nest temperatures with good precision based on a combination of air temperature measured at beach level and sea surface temperature in front of the beach. These data are available in public databases for most of the beaches worldwide. Copyright © 2014 Elsevier Ltd. All rights reserved.

A two-scale model of radio-frequency electrosurgical tissue ablation

NASA Astrophysics Data System (ADS)

Karaki, Wafaa; Rahul; Lopez, Carlos A.; Borca-Tasciuc, Diana-Andra; De, Suvranu

2017-12-01

Radio-frequency electrosurgical procedures are widely used to simultaneously dissect and coagulate tissue. Experiments suggest that evaporation of cellular and intra-cellular water plays a significant role in the evolution of the temperature field at the tissue level, which is not adequately captured in a single scale energy balance equation. Here, we propose a two-scale model to study the effects of microscale phase change and heat dissipation in response to radiofrequency heating on the tissue level in electrosurgical ablation procedures. At the microscale, the conservation of mass along with thermodynamic and mechanical equilibrium is applied to obtain an equation-of-state relating vapor mass fraction to temperature and pressure. The evaporation losses are incorporated in the macro-level energy conservation and results are validated with mean experimental temperature distributions measured from electrosurgical ablation testing on ex vivo porcine liver at different power settings of the electrosurgical instrument. Model prediction of water loss and its effect on the temperature along with the effect of the mechanical properties on results are evaluated and discussed.

Experimental study of magnetocaloric effect in the two-level quantum system KTm(MoO4)2

NASA Astrophysics Data System (ADS)

Tarasenko, R.; Tkáč, V.; Orendáčová, A.; Orendáč, M.; Valenta, J.; Sechovský, V.; Feher, A.

2018-05-01

KTm(MoO4)2 belongs to the family of binary alkaline rare-earth molybdates. This compound can be considered to be an almost ideal quantum two-level system at low temperatures. Magnetocaloric properties of KTm(MoO4)2 single crystals were investigated using specific heat and magnetization measurement in the magnetic field applied along the easy axis. Large conventional magnetocaloric effect (-ΔSM ≈ 10.3 J/(kg K)) was observed in the magnetic field of 5 T in a relatively wide temperature interval. The isothermal magnetic entropy change of about 8 J/(kgK) has been achieved already for the magnetic field of 2 T. Temperature dependence of the isothermal entropy change under different magnetic fields is in good agreement with theoretical predictions for a quantum two-level system with Δ ≈ 2.82 cm-1. Investigation of magnetocaloric properties of KTm(MoO4)2 suggests that the studied system can be considered as a good material for magnetic cooling at low temperatures.

Negative impacts of climate change on cereal yields: statistical evidence from France

NASA Astrophysics Data System (ADS)

Gammans, Matthew; Mérel, Pierre; Ortiz-Bobea, Ariel

2017-05-01

In several world regions, climate change is predicted to negatively affect crop productivity. The recent statistical yield literature emphasizes the importance of flexibly accounting for the distribution of growing-season temperature to better represent the effects of warming on crop yields. We estimate a flexible statistical yield model using a long panel from France to investigate the impacts of temperature and precipitation changes on wheat and barley yields. Winter varieties appear sensitive to extreme cold after planting. All yields respond negatively to an increase in spring-summer temperatures and are a decreasing function of precipitation about historical precipitation levels. Crop yields are predicted to be negatively affected by climate change under a wide range of climate models and emissions scenarios. Under warming scenario RCP8.5 and holding growing areas and technology constant, our model ensemble predicts a 21.0% decline in winter wheat yield, a 17.3% decline in winter barley yield, and a 33.6% decline in spring barley yield by the end of the century. Uncertainty from climate projections dominates uncertainty from the statistical model. Finally, our model predicts that continuing technology trends would counterbalance most of the effects of climate change.

Temperature-driven regime shifts in the dynamics of size-structured populations.

PubMed

Ohlberger, Jan; Edeline, Eric; Vøllestad, Leif Asbjørn; Stenseth, Nils C; Claessen, David

2011-02-01

Global warming impacts virtually all biota and ecosystems. Many of these impacts are mediated through direct effects of temperature on individual vital rates. Yet how this translates from the individual to the population level is still poorly understood, hampering the assessment of global warming impacts on population structure and dynamics. Here, we study the effects of temperature on intraspecific competition and cannibalism and the population dynamical consequences in a size-structured fish population. We use a physiologically structured consumer-resource model in which we explicitly model the temperature dependencies of the consumer vital rates and the resource population growth rate. Our model predicts that increased temperature decreases resource density despite higher resource growth rates, reflecting stronger intraspecific competition among consumers. At a critical temperature, the consumer population dynamics destabilize and shift from a stable equilibrium to competition-driven generation cycles that are dominated by recruits. As a consequence, maximum age decreases and the proportion of younger and smaller-sized fish increases. These model predictions support the hypothesis of decreasing mean body sizes due to increased temperatures. We conclude that in size-structured fish populations, global warming may increase competition, favor smaller size classes, and induce regime shifts that destabilize population and community dynamics.

Material Damping Experiments at Cryogenic Temperatures

NASA Technical Reports Server (NTRS)

Levine, Marie; White, Christopher

2003-01-01

A unique experimental facility has been designed to measure damping of materials at cryogenic temperatures. The test facility pays special attention to removing other sources of damping in the measurement by avoiding frictional interfaces, decoupling the test specimen from the support system, and by using a non-contacting measurement device; Damping data is obtained for materials (AI, GrEp, Be, Fused Quartz), strain amplitudes (less than 10-6 ppm), frequencies (20Hz-330Hz) and temperatures (20K-293K) relevant to future precision optical space missions. The test data shows a significant decrease in viscous damping at cryogenic temperatures and can be as low as 10-4%, but the amount of the damping decrease is a function of frequency and material. Contrary to the other materials whose damping monotonically decreased with temperature, damping of Fused Quartz increased substantially at cryo, after reaching a minimum at around l50 K. The damping is also shown to be insensitive to strain for low strain levels. At room temperatures, the test data correlates well to the analytical predictions of the Zener damping model. Discrepancies at cryogenic temperatures between the model predictions and the test data are observed.

Predicting the hand, foot, and mouth disease incidence using search engine query data and climate variables: an ecological study in Guangdong, China.

PubMed

Du, Zhicheng; Xu, Lin; Zhang, Wangjian; Zhang, Dingmei; Yu, Shicheng; Hao, Yuantao

2017-10-06

Hand, foot, and mouth disease (HFMD) has caused a substantial burden in China, especially in Guangdong Province. Based on the enhanced surveillance system, we aimed to explore whether the addition of temperate and search engine query data improves the risk prediction of HFMD. Ecological study. Information on the confirmed cases of HFMD, climate parameters and search engine query logs was collected. A total of 1.36 million HFMD cases were identified from the surveillance system during 2011-2014. Analyses were conducted at aggregate level and no confidential information was involved. A seasonal autoregressive integrated moving average (ARIMA) model with external variables (ARIMAX) was used to predict the HFMD incidence from 2011 to 2014, taking into account temperature and search engine query data (Baidu Index, BDI). Statistics of goodness-of-fit and precision of prediction were used to compare models (1) based on surveillance data only, and with the addition of (2) temperature, (3) BDI, and (4) both temperature and BDI. A high correlation between HFMD incidence and BDI ( r =0.794, p<0.001) or temperature ( r =0.657, p<0.001) was observed using both time series plot and correlation matrix. A linear effect of BDI (without lag) and non-linear effect of temperature (1 week lag) on HFMD incidence were found in a distributed lag non-linear model. Compared with the model based on surveillance data only, the ARIMAX model including BDI reached the best goodness-of-fit with an Akaike information criterion (AIC) value of -345.332, whereas the model including both BDI and temperature had the most accurate prediction in terms of the mean absolute percentage error (MAPE) of 101.745%. An ARIMAX model incorporating search engine query data significantly improved the prediction of HFMD. Further studies are warranted to examine whether including search engine query data also improves the prediction of other infectious diseases in other settings. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Predicting the hand, foot, and mouth disease incidence using search engine query data and climate variables: an ecological study in Guangdong, China

PubMed Central

Du, Zhicheng; Xu, Lin; Zhang, Wangjian; Zhang, Dingmei; Yu, Shicheng; Hao, Yuantao

2017-01-01

Objectives Hand, foot, and mouth disease (HFMD) has caused a substantial burden in China, especially in Guangdong Province. Based on the enhanced surveillance system, we aimed to explore whether the addition of temperate and search engine query data improves the risk prediction of HFMD. Design Ecological study. Setting and participants Information on the confirmed cases of HFMD, climate parameters and search engine query logs was collected. A total of 1.36 million HFMD cases were identified from the surveillance system during 2011–2014. Analyses were conducted at aggregate level and no confidential information was involved. Outcome measures A seasonal autoregressive integrated moving average (ARIMA) model with external variables (ARIMAX) was used to predict the HFMD incidence from 2011 to 2014, taking into account temperature and search engine query data (Baidu Index, BDI). Statistics of goodness-of-fit and precision of prediction were used to compare models (1) based on surveillance data only, and with the addition of (2) temperature, (3) BDI, and (4) both temperature and BDI. Results A high correlation between HFMD incidence and BDI (r=0.794, p<0.001) or temperature (r=0.657, p<0.001) was observed using both time series plot and correlation matrix. A linear effect of BDI (without lag) and non-linear effect of temperature (1 week lag) on HFMD incidence were found in a distributed lag non-linear model. Compared with the model based on surveillance data only, the ARIMAX model including BDI reached the best goodness-of-fit with an Akaike information criterion (AIC) value of −345.332, whereas the model including both BDI and temperature had the most accurate prediction in terms of the mean absolute percentage error (MAPE) of 101.745%. Conclusions An ARIMAX model incorporating search engine query data significantly improved the prediction of HFMD. Further studies are warranted to examine whether including search engine query data also improves the prediction of other infectious diseases in other settings. PMID:28988169

Testing a bioenergetics-based habitat choice model: bluegill (Lepomis macrochirus) responses to food availability and temperature

USGS Publications Warehouse

2011-01-01

Using an automated shuttlebox system, we conducted patch choice experiments with 32, 8–12 g bluegill sunfish (Lepomis macrochirus) to test a behavioral energetics hypothesis of habitat choice. When patch temperature and food levels were held constant within patches but different between patches, we expected bluegill to choose patches that maximized growth based on the bioenergetic integration of food and temperature as predicted by a bioenergetics model. Alternative hypotheses were that bluegill may choose patches based only on food (optimal foraging) or temperature (behavioral thermoregulation). The behavioral energetics hypothesis was not a good predictor of short-term (from minutes to weeks) patch choice by bluegill; the behavioral thermoregulation hypothesis was the best predictor. In the short-term, food and temperature appeared to affect patch choice hierarchically; temperature was more important, although food can alter temperature preference during feeding periods. Over a 19-d experiment, mean temperatures occupied by fish offered low rations did decline as predicted by the behavioral energetics hypothesis, but the decline was less than 1.0 °C as opposed to a possible 5 °C decline. A short-term, bioenergetic response to food and temperature may be precluded by physiological costs of acclimation not considered explicitly in the behavioral energetics hypothesis.

Application of a Physics-Based Stabilization Criterion to Flight System Thermal Testing

NASA Technical Reports Server (NTRS)

Baker, Charles; Garrison, Matthew; Cottingham, Christine; Peabody, Sharon

2010-01-01

The theory shown here can provide thermal stability criteria based on physics and a goal steady state error rather than on an arbitrary "X% Q/mC(sub P)" method. The ability to accurately predict steady-state temperatures well before thermal balance is reached could be very useful during testing. This holds true for systems where components are changing temperature at different rates, although it works better for the components closest to the sink. However, the application to these test cases shows some significant limitations: This theory quickly falls apart if the thermal control system in question is tightly coupled to a large mass not accounted for in the calculations, so it is more useful in subsystem-level testing than full orbiter tests. Tight couplings to a fluctuating sink causes noise in the steady state temperature predictions.

Temperature characteristics of silicon space solar cells and underlying parameters

NASA Technical Reports Server (NTRS)

Anspaugh, B. E.; Kachare, Ram; Garlick, G. F. J.

1987-01-01

Silicon space cells, 2 cm x 2 cm, with 10 ohm-cm p-base resistivity, 8-mil base thickness, and no back-surface fields have been investigated over the temperature range from 301 to 223 K by measurements of dark forward and reverse current-voltage characteristics and current-voltage relations under illumination. From dark forward bias data, the first and second diode saturation currents, I01 and I02, are determined and hence the base diffusion length and lifetime of minority carriers as functions of temperature. Lifetime increases exponentially with temperature and is explained by a Shockley-Read-Hall model with deep recombination levels 0.245 eV above the valence band. The I02 variation with temperature follows the Sah-Noyce-Shockley-Choo model except at low temperature where extra transitions raise the value above the predicted level. Reverse bias current at low voltage is a thermally assisted tunneling process via deep levels which are observed in base recombination at higher temperatures. The tunneling effects tend to become independent of temperature in the low-temperature region. These results demonstrate the ability to deduce basic parameters such as lifetime from simple measurements and show that back-surface fields offer no advantage at temperatures below 230 K. The analysis also explains the fall in lifetimes observed as the base conductivity increases, attributing it to native defects (perhaps carbon-oxygen-vacancy complexes) rather than the concentration of base dopant.

Thermoviscoplastic nonlinear constitutive relationships for structural analysis of high temperature metal matrix composites

NASA Technical Reports Server (NTRS)

Chamis, C. C.; Hopkins, D. A.

1985-01-01

A set of thermoviscoplastic nonlinear constitutive relationships (1VP-NCR) is presented. The set was developed for application to high temperature metal matrix composites (HT-MMC) and is applicable to thermal and mechanical properties. Formulation of the TVP-NCR is based at the micromechanics level. The TVP-NCR are of simple form and readily integrated into nonlinear composite structural analysis. It is shown that the set of TVP-NCR is computationally effective. The set directly predicts complex materials behavior at all levels of the composite simulation, from the constituent materials, through the several levels of composite mechanics, and up to the global response of complex HT-MMC structural components.

Correlation of Apollo oxygen tank thermodynamic performance predictions

NASA Technical Reports Server (NTRS)

Patterson, H. W.

1971-01-01

Parameters necessary to analyze the stratified performance of the Apollo oxygen tanks include g levels, tank elasticity, flow rates and pressurized volumes. Methods for estimating g levels and flow rates from flight plans prior to flight, and from quidance and system data for use in the post flight analysis are described. Equilibrium thermodynamic equations are developed for the effects of tank elasticity and pressurized volumes on the tank pressure response and their relative magnitudes are discussed. Correlations of tank pressures and heater temperatures from flight data with the results of a stratification model are shown. Heater temperatures were also estimated with empirical heat transfer agreement with flight data when fluid properties were averaged rather than evaluated at the mean film temperature.

Aerobic scope does not predict the performance of a tropical eurythermal fish at elevated temperatures.

PubMed

Norin, Tommy; Malte, Hans; Clark, Timothy D

2014-01-15

Climate warming is predicted to negatively impact fish populations through impairment of oxygen transport systems when temperatures exceed those which are optimal for aerobic scope (AS). This concept of oxygen- and capacity-limited thermal tolerance (OCLTT) is rapidly gaining popularity within climate change research and has been applied to several fish species. Here, we evaluated the relevance of aerobic performance of juvenile barramundi (Lates calcarifer) in the context of thermal preference and tolerance by (1) measuring standard and maximum metabolic rates (SMR and MMR, respectively) and AS of fish acclimated to 29°C and acutely exposed to temperatures from 23 to 38°C, (2) allowing the fish to behaviourally select a preferred temperature between 29 and 38°C, and (3) quantifying alterations to AS after 5 weeks of acclimation to 29 and 38°C. SMR and MMR both increased continuously with temperature in acutely exposed fish, but the increase was greater for MMR such that AS was highest at 38°C, a temperature approaching the upper lethal limit (40-41°C). Despite 38°C eliciting maximum AS, when given the opportunity the fish selected a median temperature of 31.7 ± 0.5°C and spent only 10 ± 3% of their time at temperatures >36°C. Following acclimation to 38°C, AS measured at 38°C was decreased to the same level as 29°C-acclimated fish measured at 29°C, suggesting that AS may be dynamically modulated independent of temperature to accommodate the requirements of daily life. Together, these results reveal limited power of the OCLTT hypothesis in predicting optimal temperatures and effects of climate warming on juvenile barramundi.

A mechanistic model to study the thermal ecology of a southeastern pacific dominant intertidal mussel and implications for climate change.

PubMed

Finke, G R; Bozinovic, F; Navarrete, S A

2009-01-01

Developing mechanistic models to predict an organism's body temperature facilitates the study of physiological stresses caused by extreme climatic conditions the species might have faced in the past or making predictions about changes to come in the near future. Because the models combine empirical observation of different climatic variables with essential morphological attributes of the species, it is possible to examine specific aspects of predicted climatic changes. Here, we develop a model for the competitively dominant intertidal mussel Perumytilus purpuratus that estimates body temperature on the basis of meteorological and tidal data with an average difference (+/-SE) of 0.410 degrees +/- 0.0315 degrees C in comparison with a field-deployed temperature logger. Modeled body temperatures of P. purpuratus in central Chile regularly exceeded 30 degrees C in summer months, and values as high as 38 degrees C were found. These results suggest that the temperatures reached by mussels in the intertidal zone in central Chile are not sufficiently high to induce significant mortality on adults of this species; however, because body temperatures >40 degrees C can be lethal for this species, sublethal effects on physiological performance warrant further investigation. Body temperatures of mussels increased sigmoidally with increasing tidal height. Body temperatures of individuals from approximately 70% of the tidal range leveled off and did not increase any further with increasing tidal height. Finally, body size played an important role in determining body temperature. A hypothetical 5-cm-long mussel (only 1 cm longer than mussels found in nature) did reach potentially lethal body temperatures, suggesting that the biophysical environment may play a role in limiting the size of this small species.

Agricultural losses related to frost events: use of the 850 hPa level temperature as an explanatory variable of the damage cost

NASA Astrophysics Data System (ADS)

Papagiannaki, K.; Lagouvardos, K.; Kotroni, V.; Papagiannakis, G.

2014-01-01

The objective of this study is to analyze frost damaging events in agriculture, by examining the relationship between the daily minimum temperature at the lower atmosphere (at the pressure level of 850 hPa) and crop production losses. Furthermore, the study suggests a methodological approach for estimating agriculture risk due to frost events, with the aim to estimate the short-term probability and magnitude of frost-related financial losses for different levels of 850 hPa temperature. Compared with near surface temperature forecasts, temperature forecast at the level of 850 hPa is less influenced by varying weather conditions, as well as by local topographical features, thus it constitutes a more consistent indicator of the forthcoming weather conditions. The analysis of the daily monetary compensations for insured crop losses caused by weather events in Greece, during the period 1999-2011, shows that frost is the major meteorological phenomenon with adverse effects on crop productivity in the largest part of the country. Two regions of different geographical latitude are further examined, to account for the differences in the temperature ranges developed within their ecological environment. Using a series of linear and logistic regressions, we found that minimum temperature (at 850 hPa level), grouped in three categories according to its magnitude, and seasonality are significant variables when trying to explain crop damage costs, as well as to predict and quantify the likelihood and magnitude of frost damaging events.

Agricultural losses related to frost events: use of the 850 hPa level temperature as an explanatory variable of the damage cost

NASA Astrophysics Data System (ADS)

Papagiannaki, K.; Lagouvardos, K.; Kotroni, V.; Papagiannakis, G.

2014-09-01

The objective of this study is the analysis of damaging frost events in agriculture, by examining the relationship between the daily minimum temperature in the lower atmosphere (at an isobaric level of 850 hPa) and crop production losses. Furthermore, the study suggests a methodological approach for estimating agriculture risk due to frost events, with the aim of estimating the short-term probability and magnitude of frost-related financial losses for different levels of 850 hPa temperature. Compared with near-surface temperature forecasts, temperature forecasts at the level of 850 hPa are less influenced by varying weather conditions or by local topographical features; thus, they constitute a more consistent indicator of the forthcoming weather conditions. The analysis of the daily monetary compensations for insured crop losses caused by weather events in Greece shows that, during the period 1999-2011, frost caused more damage to crop production than any other meteorological phenomenon. Two regions of different geographical latitudes are examined further, to account for the differences in the temperature ranges developed within their ecological environment. Using a series of linear and logistic regressions, we found that minimum temperature (at an 850 hPa level), grouped into three categories according to its magnitude, and seasonality, are significant variables when trying to explain crop damage costs, as well as to predict and quantify the likelihood and magnitude of damaging frost events.

Modelling the Relationship Between Land Surface Temperature and Landscape Patterns of Land Use Land Cover Classification Using Multi Linear Regression Models

NASA Astrophysics Data System (ADS)

Bernales, A. M.; Antolihao, J. A.; Samonte, C.; Campomanes, F.; Rojas, R. J.; dela Serna, A. M.; Silapan, J.

2016-06-01

The threat of the ailments related to urbanization like heat stress is very prevalent. There are a lot of things that can be done to lessen the effect of urbanization to the surface temperature of the area like using green roofs or planting trees in the area. So land use really matters in both increasing and decreasing surface temperature. It is known that there is a relationship between land use land cover (LULC) and land surface temperature (LST). Quantifying this relationship in terms of a mathematical model is very important so as to provide a way to predict LST based on the LULC alone. This study aims to examine the relationship between LST and LULC as well as to create a model that can predict LST using class-level spatial metrics from LULC. LST was derived from a Landsat 8 image and LULC classification was derived from LiDAR and Orthophoto datasets. Class-level spatial metrics were created in FRAGSTATS with the LULC and LST as inputs and these metrics were analysed using a statistical framework. Multi linear regression was done to create models that would predict LST for each class and it was found that the spatial metric "Effective mesh size" was a top predictor for LST in 6 out of 7 classes. The model created can still be refined by adding a temporal aspect by analysing the LST of another farming period (for rural areas) and looking for common predictors between LSTs of these two different farming periods.

Thermal Pairing in Nuclei

NASA Astrophysics Data System (ADS)

Dang, Nguyen Dinh

2008-04-01

The modified Hartree-Fock-Bogoliubov (MHFB) theory at finite temperature is derived for finite nuclei.1 In the limit of constant pairing parameter, the MHFB theory yields the modified BCS (MBCS) theory.2 These are the microscopic theories that can describe the crossover region at temperature T around the critical value Tc of the BCS superfluid-normal (SN) phase transition. By requiring the unitarity conservation of the particle-density matrix, the derivation of these theories is achieved by constructing a modified quasiparticle density matrix, where the fluctuation of the quasiparticle number is microscopically built in. This matrix can be directly obtained from the usual quasiparticle-density matrix by applying the secondary Bogoliubov transformation, which includes the quasiparticle occupation number. The calculations of the thermal pairing gap, total energy, heat capacity, quasiparticle and pairing correlation functions were carried out within MBCS theory for the Richardson model3 as well as realistic single-particle spectra. The Richardson model under consideration has varying Ω equidistant levels and N particles with a level distant equal to 1 MeV. It is shown that the limitation of the configuration space sets a limiting temperature TM up to which the MBCS theory can be applied. Enlarging the space in the half-filled case (Ω = N) by one valence level (Ω = N + 1) extends TM to a much higher temperature so that the predictions by the MBCS theory can be compared directly with the exact results up to T ~ 4 - 5 MeV even for small N. The MBCS gap does not collapse, but decreases monotonously with increasing T. The total energy and heat capacity predicted by the MBCS theory are closer to the exact results than those predicted by the BCS theory, especially in the region of the SN phase transition predicted within the BCS theory. The discontinuity in the BCS heat capacity at the critical temperature Tc is smoothed out within the MBCS theory, especially for small N, showing the disappearance of SN phase transition in very light systems. With increasing N the peak at Tc in the heat capacity becomes more pronounced, showing a phase-transition-like behavior in heavy systems. The effect of approximated particle-number projection using the Lipkin-Nogami method is also discussed. An application of the MBCS theory to the description of the damping of giant dipole resonances (GDR) in hot nuclei shows that, because of the existence of the pseudo gap, the GDR width remains nearly constant at temperatures up to around 1 MeV in tin isotopes in good agreement with the recent experimental systematic.4

Use of Ground-water Temperature Patterns to Determine the Hydraulic Conductance of the Streambed Along the Middle Reaches of the Russian River, CA

NASA Astrophysics Data System (ADS)

Su, G. W.; Constantz, J.; Jasperse, J.; Seymour, D.

2002-12-01

Along the Russian River in Sonoma County, the alluvial aquifer is the preferred source of drinking water because sediments and other constituents in the river water would require additional treatment. From late spring to early winter, an inflatable dam is erected to raise the river stage and passively recharge the alluvial aquifer. The raised stage also permits diversion of river water to a series of recharge ponds located near the dam along the river. Improved understanding of stream exchanges with ground water is needed to better manage available water resources. Heat is used as a tracer of shallow ground-water movement for detailed hydraulic parameter estimation along the middle reaches of the river. Water-levels and ground-water temperatures were measured in a series of observations wells and compared to the river stage and surface-water temperatures. Hydraulic conductivities were predicted by optimizing simulated ground-water temperatures using VS2DHI, a heat and water transport model, to observed temperatures in the aquifer. These conductivity values will be used in a stream/ground-water model of this region being developed using MODFLOW. Temperature-based estimates of streambed conductance will be inserted in the STREAM package of the model to constrain this parameter. Although temperature-based predictions of hydraulic conductivity vary significantly along the reach, the results generally suggest that an anisotropy of 5 to 1 (horizontal to vertical) provides the best hydraulic conductivity matches for predicted versus observed ground-water temperatures.

Modeling of detachment experiments at DIII-D

DOE PAGES

Canik, John M.; Briesemeister, Alexis R.; Lasnier, C. J.; ...

2014-11-26

Edge fluid–plasma/kinetic–neutral modeling of well-diagnosed DIII-D experiments is performed in order to document in detail how well certain aspects of experimental measurements are reproduced within the model as the transition to detachment is approached. Results indicate, that at high densities near detachment onset, the poloidal temperature profile produced in the simulations agrees well with that measured in experiment. However, matching the heat flux in the model requires a significant increase in the radiated power compared to what is predicted using standard chemical sputtering rates. Lastly, these results suggest that the model is adequate to predict the divertor temperature, provided thatmore » the discrepancy in radiated power level can be resolved.« less

Axion dark matter and the Lattice

NASA Astrophysics Data System (ADS)

Moore, Guy

2018-03-01

First I will review the QCD theta problem and the Peccei-Quinn solution, with its new particle, the axion. I will review the possibility of the axion as dark matter. If PQ symmetry was restored at some point in the hot early Universe, it should be possible to make a definite prediction for the axion mass if it constitutes the Dark Matter. I will describe progress on one issue needed to make this prediction - the dynamics of axionic string-wall networks and how they produce axions. Then I will discuss the sensitivity of the calculation to the high temperature QCD topological susceptibility. My emphasis is on what temperature range is important, and what level of precision is needed.

Ductility normalized-strainrange partitioning life relations for creep-fatigue life predictions

NASA Technical Reports Server (NTRS)

Halford, G. R.; Saltsman, J. F.; Hirschberg, M. H.

1977-01-01

Procedures based on Strainrange Partitioning (SRP) are presented for estimating the effects of environment and other influences on the high temperature, low cycle, creep fatigue resistance of alloys. It is proposed that the plastic and creep, ductilities determined from conventional tensile and creep rupture tests conducted in the environment of interest be used in a set of ductility normalized equations for making a first order approximation of the four SRP inelastic strainrange life relations. Different levels of sophistication in the application of the procedures are presented by means of illustrative examples with several high temperature alloys. Predictions of cyclic lives generally agree with observed lives within factors of three.

Real-time control of focused ultrasound heating based on rapid MR thermometry.

PubMed

Vimeux, F C; De Zwart, J A; Palussiére, J; Fawaz, R; Delalande, C; Canioni, P; Grenier, N; Moonen, C T

1999-03-01

Real-time control of the heating procedure is essential for hyperthermia applications of focused ultrasound (FUS). The objective of this study is to demonstrate the feasibility of MRI-controlled FUS. An automatic control system was developed using a dedicated interface between the MR system control computer and the FUS wave generator. Two algorithms were used to regulate FUS power to maintain the focal point temperature at a desired level. Automatic control of FUS power level was demonstrated ex vivo at three target temperature levels (increase of 5 degrees C, 10 degrees C, and 30 degrees C above room temperature) during 30-minute hyperthermic periods. Preliminary in vivo results on rat leg muscle confirm that necrosis estimate, calculated on-line during FUS sonication, allows prediction of tissue damage. CONCLUSIONS. The feasibility of fully automatic FUS control based on MRI thermometry has been demonstrated.

Temperature-dependent phenology of Plutella xylostella (Lepidoptera: Plutellidae): Simulation and visualization of current and future distributions along the Eastern Afromontane.

PubMed

Ngowi, Benignus V; Tonnang, Henri E Z; Mwangi, Evans M; Johansson, Tino; Ambale, Janet; Ndegwa, Paul N; Subramanian, Sevgan

2017-01-01

There is a scarcity of laboratory and field-based results showing the movement of the diamondback moth (DBM) Plutella xylostella (L.) across a spatial scale. We studied the population growth of the diamondback moth (DBM) Plutella xylostella (L.) under six constant temperatures, to understand and predict population changes along altitudinal gradients and under climate change scenarios. Non-linear functions were fitted to continuously model DBM development, mortality, longevity and oviposition. We compiled the best-fitted functions for each life stage to yield a phenology model, which we stochastically simulated to estimate the life table parameters. Three temperature-dependent indices (establishment, generation and activity) were derived from a logistic population growth model and then coupled to collected current (2013) and downscaled temperature data from AFRICLIM (2055) for geospatial mapping. To measure and predict the impacts of temperature change on the pest's biology, we mapped the indices along the altitudinal gradients of Mt. Kilimanjaro (Tanzania) and Taita Hills (Kenya) and assessed the differences between 2013 and 2055 climate scenarios. The optimal temperatures for development of DBM were 32.5, 33.5 and 33°C for eggs, larvae and pupae, respectively. Mortality rates increased due to extreme temperatures to 53.3, 70.0 and 52.4% for egg, larvae and pupae, respectively. The net reproduction rate reached a peak of 87.4 female offspring/female/generation at 20°C. Spatial simulations indicated that survival and establishment of DBM increased with a decrease in temperature, from low to high altitude. However, we observed a higher number of DBM generations at low altitude. The model predicted DBM population growth reduction in the low and medium altitudes by 2055. At higher altitude, it predicted an increase in the level of suitability for establishment with a decrease in the number of generations per year. If climate change occurs as per the selected scenario, DBM infestation may reduce in the selected region. The study highlights the need to validate these predictions with other interacting factors such as cropping practices, host plants and natural enemies.

Photoacoustic Non-Destructive Evaluation and Imaging of Caries in Dental Samples

NASA Astrophysics Data System (ADS)

Li, T.; Dewhurst, R. J.

2010-02-01

Dental caries is a disease wherein bacterial processes damage hard tooth structure. Traditional dental radiography has its limitations for detecting early stage caries. In this study, a photoacoustic (PA) imaging system with the near-infrared light source has been applied to postmortem dental samples to obtain 2-D and 3-D images. Imaging results showed that the PA technique can be used to image human teeth caries. For non-destructive photoacoustic evaluation and imaging, the induced temperature and pressure rises within biotissues should not cause physical damage to the tissue. For example, temperature rises above 5 °C within live human teeth will cause pulpal necrosis. Therefore, several simulations based on the thermoelastic effect have been applied to predict temperature and pressure fields within samples. Predicted temperature levels are below corresponding safety limits, but care is required to avoid nonlinear absorption phenomena. Furthermore, PA imaging results from the phantom provide evidence for high sensitivity, which shows the imaging potential of the PA technique for detecting early stage disease.

Reassessing Pliocene temperature gradients

NASA Astrophysics Data System (ADS)

Tierney, J. E.

2017-12-01

With CO2 levels similar to present, the Pliocene Warm Period (PWP) is one of our best analogs for climate change in the near future. Temperature proxy data from the PWP describe dramatically reduced zonal and meridional temperature gradients that have proved difficult to reproduce with climate model simulations. Recently, debate has emerged regarding the interpretation of the proxies used to infer Pliocene temperature gradients; these interpretations affect the magnitude of inferred change and the degree of inconsistency with existing climate model simulations of the PWP. Here, I revisit the issue using Bayesian proxy forward modeling and prediction that propagates known uncertainties in the Mg/Ca, UK'37, and TEX86 proxy systems. These new spatiotemporal predictions are quantitatively compared to PWP simulations to assess probabilistic agreement. Results show generally good agreement between existing Pliocene simulations from the PlioMIP ensemble and SST proxy data, suggesting that exotic changes in the ocean-atmosphere are not needed to explain the Pliocene climate state. Rather, the spatial changes in SST during the Pliocene are largely consistent with elevated CO2 forcing.

Identification and management of microbial contaminations in a surface drinking water source.

PubMed

Aström, J; Pettersson, T J R; Stenström, T A

2007-01-01

Microbial contamination of surface waters constitutes a health risk for drinking water consumers which may be lowered by closing the raw water intake. We have evaluated microbial discharge events reported in the river Göta älv, which is used for raw water supply to the city of Göteborg. Elevated levels of faecal indicator bacteria were observed during periods of closed raw water intake. High bacteria levels were, however, also occasionally detected during periods of open intake, probably as a result of microbial discharge far upstream in the river which may be difficult to predict and manage by closing the intake. Accumulated upstream precipitations, resulting in surface runoff and wastewater contaminations in the catchment, correlated positively with the levels of total coliforms, E. coli, intestinal enterococci and sulfite-reducing clostridia. Levels of faecal indicator organisms were negatively correlated to the water temperature due to enhanced survival at lower temperatures. Wastewater discharges from a municipality located just upstream of the water intake resulted in elevated E. coli concentrations downstream at the raw water intake for Göteborg. To improve the prediction of microbial contaminations within the river Göta älv, monitoring data on turbidity and upstream precipitation are of particular importance.

Further experimentation on bubble generation during transformer overload. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oommen, T.V.

1992-03-01

This report covers additional work done during 1990 and 1991 on gas bubble generation under overload conditions. To improve visual bubble detection, a single disc coil was used. To further improve detection, a corona device was also used which signaled the onset of corona activity in the early stages of bubble formation. A total of fourteen model tests were conducted, half of which used the Inertaire system, and the remaining, a conservator (COPS). Moisture content of paper in the coil varied from 1.0% to 8.0%; gas (nitrogen) content varied from 1.0% to 8.8%. The results confirmed earlier observations that themore » mathematical bubble prediction model was not valid for high gas content model with relatively low moisture levels in the coil. An empirical relationship was formulated to accurately predict bubble evolution temperatures from known moisture and gas content values. For low moisture content models (below 2%), the simple Piper relationship was sufficient to predict bubble evolution temperatures, regardless of gas content. Moisture in the coil appears to be the key factor in bubble generation. Gas blanketed (Inertaire) systems do not appear to be prone to premature bubble generation from overloads as previously thought. The new bubble prediction model reveals that for a coil with 2% moisture, the bubble evolution temperature would be about 140{degrees}C. Since old transformers in service may have as much as 2% moisture in paper, the 140{degrees}C bubble evolution temperature may be taken as the lower limit of bubble evolution temperature under overload conditions for operating transformers. Drier insulation would raise the bubble evolution temperature.« less

Climatic Factors Driving Invasion of the Tiger Mosquito (Aedes albopictus) into New Areas of Trentino, Northern Italy

PubMed Central

Castellani, Cristina; Arnoldi, Daniele; Rizzoli, Annapaola

2011-01-01

Background The tiger mosquito (Aedes albopictus), vector of several emerging diseases, is expanding into more northerly latitudes as well as into higher altitudes in northern Italy. Changes in the pattern of distribution of the tiger mosquito may affect the potential spread of infectious diseases transmitted by this species in Europe. Therefore, predicting suitable areas of future establishment and spread is essential for planning early prevention and control strategies. Methodology/Principal Findings To identify the areas currently most suitable for the occurrence of the tiger mosquito in the Province of Trento, we combined field entomological observations with analyses of satellite temperature data (MODIS Land Surface Temperature: LST) and human population data. We determine threshold conditions for the survival of overwintering eggs and for adult survival using both January mean temperatures and annual mean temperatures. We show that the 0°C LST threshold for January mean temperatures and the 11°C threshold for annual mean temperatures provide the best predictors for identifying the areas that could potentially support populations of this mosquito. In fact, human population density and distance to human settlements appear to be less important variables affecting mosquito distribution in this area. Finally, we evaluated the future establishment and spread of this species in relation to predicted climate warming by considering the A2 scenario for 2050 statistically downscaled at regional level in which winter and annual temperatures increase by 1.5 and 1°C, respectively. Conclusions/Significance MODIS satellite LST data are useful for accurately predicting potential areas of tiger mosquito distribution and for revealing the range limits of this species in mountainous areas, predictions which could be extended to an European scale. We show that the observed trend of increasing temperatures due to climate change could facilitate further invasion of Ae. albopictus into new areas. PMID:21525991

A time-dependent radiative model of HD 209458b

NASA Astrophysics Data System (ADS)

Iro, N.; Bézard, B.; Guillot, T.

2005-06-01

We present a time-dependent radiative model of the atmosphere of HD 209458b and investigate its thermal structure and chemical composition. In a first step, the stellar heating profile and radiative timescales were calculated under planet-averaged insolation conditions. We find that 99.99% of the incoming stellar flux has been absorbed before reaching the 7 bar level. Stellar photons cannot therefore penetrate deeply enough to explain the large radius of the planet. We derive a radiative time constant which increases with depth and reaches about 8 h at 0.1 bar and 2.3 days at 1 bar. Time-dependent temperature profiles were also calculated, in the limit of a zonal wind that is independent of height (i.e. solid-body rotation) and constant absorption coefficients. We predict day-night variations of the effective temperature of ~600 K, for an equatorial rotation rate of 1 km s-1, in good agreement with the predictions by Showmann & Guillot (2002). This rotation rate yields day-to-night temperature variations in excess of 600 K above the 0.1-bar level. These variations rapidly decrease with depth below the 1-bar level and become negligible below the ~5-bar level for rotation rates of at least 0.5 km s-1. At high altitudes (mbar pressures or less), the night temperatures are low enough to allow sodium to condense into Na2S. Synthetic transit spectra of the visible Na doublet show a much weaker sodium absorption on the morning limb than on the evening limb. The calculated dimming of the sodium feature during planetary transites agrees with the value reported by Charbonneau et al. (2002).

The Predicted Influence of Climate Change on Lesser Prairie-Chicken Reproductive Parameters

PubMed Central

Grisham, Blake A.; Boal, Clint W.; Haukos, David A.; Davis, Dawn M.; Boydston, Kathy K.; Dixon, Charles; Heck, Willard R.

2013-01-01

The Southern High Plains is anticipated to experience significant changes in temperature and precipitation due to climate change. These changes may influence the lesser prairie-chicken (Tympanuchus pallidicinctus) in positive or negative ways. We assessed the potential changes in clutch size, incubation start date, and nest survival for lesser prairie-chickens for the years 2050 and 2080 based on modeled predictions of climate change and reproductive data for lesser prairie-chickens from 2001–2011 on the Southern High Plains of Texas and New Mexico. We developed 9 a priori models to assess the relationship between reproductive parameters and biologically relevant weather conditions. We selected weather variable(s) with the most model support and then obtained future predicted values from climatewizard.org. We conducted 1,000 simulations using each reproductive parameter’s linear equation obtained from regression calculations, and the future predicted value for each weather variable to predict future reproductive parameter values for lesser prairie-chickens. There was a high degree of model uncertainty for each reproductive value. Winter temperature had the greatest effect size for all three parameters, suggesting a negative relationship between above-average winter temperature and reproductive output. The above-average winter temperatures are correlated to La Niña events, which negatively affect lesser prairie-chickens through resulting drought conditions. By 2050 and 2080, nest survival was predicted to be below levels considered viable for population persistence; however, our assessment did not consider annual survival of adults, chick survival, or the positive benefit of habitat management and conservation, which may ultimately offset the potentially negative effect of drought on nest survival. PMID:23874549

Temperature variations at nano-scale level in phase transformed nanocrystalline NiTi shape memory alloys adjacent to graphene layers.

PubMed

Amini, Abbas; Cheng, Chun; Naebe, Minoo; Church, Jeffrey S; Hameed, Nishar; Asgari, Alireza; Will, Frank

2013-07-21

The detection and control of the temperature variation at the nano-scale level of thermo-mechanical materials during a compression process have been challenging issues. In this paper, an empirical method is proposed to predict the temperature at the nano-scale level during the solid-state phase transition phenomenon in NiTi shape memory alloys. Isothermal data was used as a reference to determine the temperature change at different loading rates. The temperature of the phase transformed zone underneath the tip increased by ∼3 to 40 °C as the loading rate increased. The temperature approached a constant with further increase in indentation depth. A few layers of graphene were used to enhance the cooling process at different loading rates. Due to the presence of graphene layers the temperature beneath the tip decreased by a further ∼3 to 10 °C depending on the loading rate. Compared with highly polished NiTi, deeper indentation depths were also observed during the solid-state phase transition, especially at the rate dependent zones. Larger superelastic deformations confirmed that the latent heat transfer through the deposited graphene layers allowed a larger phase transition volume and, therefore, more stress relaxation and penetration depth.

Equivalent circuit-level model of quantum cascade lasers with integrated hot-electron and hot-phonon effects

NASA Astrophysics Data System (ADS)

Yousefvand, H. R.

2017-12-01

We report a study of the effects of hot-electron and hot-phonon dynamics on the output characteristics of quantum cascade lasers (QCLs) using an equivalent circuit-level model. The model is developed from the energy balance equation to adopt the electron temperature in the active region levels, the heat transfer equation to include the lattice temperature, the nonequilibrium phonon rate to account for the hot phonon dynamics and simplified two-level rate equations to incorporate the carrier and photon dynamics in the active region. This technique simplifies the description of the electron-phonon interaction in QCLs far from the equilibrium condition. Using the presented model, the steady and transient responses of the QCLs for a wide range of sink temperatures (80 to 320 K) are investigated and analysed. The model enables us to explain the operating characteristics found in QCLs. This predictive model is expected to be applicable to all QCL material systems operating in pulsed and cw regimes.

Keep up or drown: adjustment of western Pacific coral reefs to sea-level rise in the 21st century

PubMed Central

van Woesik, R.; Golbuu, Y.; Roff, G.

2015-01-01

Since the Mid-Holocene, some 5000 years ago, coral reefs in the Pacific Ocean have been vertically constrained by sea level. Contemporary sea-level rise is releasing these constraints, providing accommodation space for vertical reef expansion. Here, we show that Porites microatolls, from reef-flat environments in Palau (western Pacific Ocean), are ‘keeping up’ with contemporary sea-level rise. Measurements of 570 reef-flat Porites microatolls at 10 locations around Palau revealed recent vertical skeletal extension (78±13 mm) over the last 6–8 years, which is consistent with the timing of the recent increase in sea level. We modelled whether microatoll growth rates will potentially ‘keep up’ with predicted sea-level rise in the near future, based upon average growth, and assuming a decline in growth for every 1°C increase in temperature. We then compared these estimated extension rates with rates of sea-level rise under four Representative Concentration Pathways (RCPs). Our model suggests that under low–mid RCP scenarios, reef-coral growth will keep up with sea-level rise, but if greenhouse gas concentrations exceed 670 ppm atmospheric CO2 levels and with +2.2°C sea-surface temperature by 2100 (RCP 6.0 W m−2), our predictions indicate that Porites microatolls will be unable to keep up with projected rates of sea-level rise in the twenty-first century. PMID:26587277

Using RNA-seq to Profile Gene Expression of Spikelet Development in Response to Temperature and Nitrogen during Meiosis in Rice (Oryza sativa L.).

PubMed

Yang, Jun; Chen, Xiaorong; Zhu, Changlan; Peng, Xiaosong; He, Xiaopeng; Fu, Junru; Ouyang, Linjuan; Bian, Jianmin; Hu, Lifang; Sun, Xiaotang; Xu, Jie; He, Haohua

2015-01-01

Rice reproductive development is sensitive to high temperature and soil nitrogen supply, both of which are predicted to be increased threats to rice crop yield. Rice spikelet development is a critical process that determines yield, yet little is known about the transcriptional regulation of rice spikelet development in response to the combination of heat stress and low nitrogen availability. Here, we profiled gene expression of rice spikelet development during meiosis under heat stress and different nitrogen levels using RNA-seq. We subjected plants to four treatments: 1) NN: normal nitrogen level (165 kg ha-1) with normal temperature (30°C); 2) HH: high nitrogen level (264 kg ha-1) with high temperature (37°C); 3) NH: normal nitrogen level and high temperature; and 4) HN: high nitrogen level and normal temperature. The de novo transcriptome assembly resulted in 52,250,482 clean reads aligned with 76,103 unigenes, which were then used to compare differentially expressed genes (DEGs) in the different treatments. Comparing gene expression in samples with the same nitrogen levels but different temperatures, we identified 70 temperature-responsive DEGs in normal nitrogen levels (NN vs NH) and 135 DEGs in high nitrogen levels (HN vs HH), with 27 overlapping DEGs. We identified 17 and seven nitrogen-responsive DEGs by comparing changes in nitrogen levels in lower temperature (NN vs HN) and higher temperature (NH vs HH), with one common DEG. The temperature-responsive genes were principally associated with cytochrome, heat shock protein, peroxidase, and ubiquitin, while the nitrogen-responsive genes were mainly involved in glutamine synthetase, amino acid transporter, pollen development, and plant hormone. Rice spikelet fertility was significantly reduced under high temperature, but less reduced under high-nitrogen treatment. In the high temperature treatments, we observed downregulation of genes involved in spikelet development, such as pollen tube growth, pollen maturation, especially sporopollenin biosynthetic process, and pollen exine formation. Moreover, we observed higher expression levels of the co-expressed DEGs in HN vs HH compared to NN vs NH. These included the six downregulated genes (one pollen maturation and five pollen exine formation genes), as well as the four upregulated DEGs in response to heat. This suggests that high-nitrogen treatment may enhance the gene expression levels to mitigate aspects of heat-stress. The spikelet genes identified in this study may play important roles in response to the combined effects of high temperature and high nitrogen, and may serve as candidates for crop improvement.

An Assessment of the Predictability of Northern Winter Seasonal Means with the NSIPP 1 AGCM

NASA Technical Reports Server (NTRS)

Suarez, Max J. (Editor); Pegion, Philip J.; Schubert, Siegfried D.

2000-01-01

This atlas assesses the predictability of January-February-March (JFM) means using version 1 of the NASA Seasonal-to-Interannual Prediction Project Atmospheric General Circulation Model (the NSIPP 1 AGCM). The AGCM is part of the NSIPP coupled atmosphere-land-ocean model. For these results, the atmosphere was run uncoupled from the ocean, but coupled with an interactive land model. The results are based on 20 ensembles of nine JFM hindcasts for the period 1980-1999, with sea surface temperature (SST) and sea ice specified from observations. The model integrations were started from initial atmospheric conditions (taken from NCEP/NCAR reanalyses) centered on December 15. The analysis focuses on 200 mb height, precipitation, surface temperature, and sea-level pressure. The results address issues of both predictability and forecast skill. Various signal-to-noise measures are computed to demonstrate the potential for skillful prediction on seasonal time scales under the assumption of a perfect model and perfectly known oceanic boundary forcings. The results show that the model produces a realistic ENSO response in both the tropics and extratropics.

Measuring Moisture Levels in Graphite Epoxy Composite Sandwich Structures

NASA Technical Reports Server (NTRS)

Nurge, Mark; Youngquist, Robert; Starr, Stanley

2011-01-01

Graphite epoxy composite (GEC) materials are used in the construction of rocket fairings, nose cones, interstage adapters, and heat shields due to their high strength and light weight. However, they absorb moisture depending on the environmental conditions they are exposed to prior to launch. Too much moisture absorption can become a problem when temperature and pressure changes experienced during launch cause the water to vaporize. The rapid state change of the water can result in structural failure of the material. In addition, heat and moisture combine to weaken GEC structures. Diffusion models that predict the total accumulated moisture content based on the environmental conditions are one accepted method of determining if the material strength has been reduced to an unacceptable level. However, there currently doesn t exist any field measurement technique to estimate the actual moisture content of a composite structure. A multi-layer diffusion model was constructed with Mathematica to predict moisture absorption and desorption from the GEC sandwich structure. This model is used in conjunction with relative humidity/temperature sensors both on the inside and outside of the material to determine the moisture levels in the structure. Because the core materials have much higher diffusivity than the face sheets, a single relative humidity measurement will accurately reflect the moisture levels in the core. When combined with an external relative humidity measurement, the model can be used to determine the moisture levels in the face sheets. Since diffusion is temperaturedependent, the temperature measurements are used to determine the diffusivity of the face sheets for the model computations.

The impact of wet flue gas desulfurization scrubbing on mercury emissions from coal-fired power stations.

PubMed

Niksa, Stephen; Fujiwara, Naoki

2005-07-01

This article introduces a predictive capability for Hg retention in any Ca-based wet flue gas desulfurization (FGD) scrubber, given mercury (Hg) speciation at the FGD inlet, the flue gas composition, and the sulphur dioxide (SO2) capture efficiency. A preliminary statistical analysis of data from 17 full-scale wet FGDs connects flue gas compositions, the extents of Hg oxidation at FGD inlets, and Hg retention efficiencies. These connections clearly signal that solution chemistry within the FGD determines Hg retention. A more thorough analysis based on thermochemical equilibrium yields highly accurate predictions for total Hg retention with no parameter adjustments. For the most reliable data, the predictions were within measurement uncertainties for both limestone and Mg/lime systems operating in both forced and natural oxidation mode. With the U.S. Environmental Protection Agency's (EPA) Information Collection Request (ICR) database, the quantitative performance was almost as good for the most modern FGDs, which probably conform to the very high SO2 absorption efficiencies assumed in the calculations. The large discrepancies for older FGDs are tentatively attributed to the unspecified SO2 capture efficiencies and operating temperatures and to the possible elimination of HCl in prescrubbers. The equilibrium calculations suggest that Hg retention is most sensitive to inlet HCl and O2 levels and the FGD temperature; weakly dependent on SO2 capture efficiency; and insensitive to HgCl2, NO, CA:S ratio, slurry dilution level in limestone FGDs, and MgSO3 levels in Mg/lime systems. Consequently, systems with prescrubbers to eliminate HCl probably retain less Hg than fully integrated FGDs. The analysis also predicts re-emission of Hg(O) but only for inlet O2 levels that are much lower than those in full-scale FGDs.

Ecological covariates based predictive model of malaria risk in the state of Chhattisgarh, India.

PubMed

Kumar, Rajesh; Dash, Chinmaya; Rani, Khushbu

2017-09-01

Malaria being an endemic disease in the state of Chhattisgarh and ecologically dependent mosquito-borne disease, the study is intended to identify the ecological covariates of malaria risk in districts of the state and to build a suitable predictive model based on those predictors which could assist developing a weather based early warning system. This secondary data based analysis used one month lagged district level malaria positive cases as response variable and ecological covariates as independent variables which were tested with fixed effect panelled negative binomial regression models. Interactions among the covariates were explored using two way factorial interaction in the model. Although malaria risk in the state possesses perennial characteristics, higher parasitic incidence was observed during the rainy and winter seasons. The univariate analysis indicated that the malaria incidence risk was statistically significant associated with rainfall, maximum humidity, minimum temperature, wind speed, and forest cover ( p  < 0.05). The efficient predictive model include the forest cover [IRR-1.033 (1.024-1.042)], maximum humidity [IRR-1.016 (1.013-1.018)], and two-way factorial interactions between district specific averaged monthly minimum temperature and monthly minimum temperature, monthly minimum temperature was statistically significant [IRR-1.44 (1.231-1.695)] whereas the interaction term has a protective effect [IRR-0.982 (0.974-0.990)] against malaria infections. Forest cover, maximum humidity, minimum temperature and wind speed emerged as potential covariates to be used in predictive models for modelling the malaria risk in the state which could be efficiently used for early warning systems in the state.

Temperature Sensitivity of an Atomic Vapor Cell-Based Dispersion-Enhanced Optical Cavity

NASA Technical Reports Server (NTRS)

Myneni, K.; Smith, D. D.; Chang, H.; Luckay, H. A.

2015-01-01

Enhancement of the response of an optical cavity to a change in optical path length, through the use of an intracavity fast-light medium, has previously been demonstrated experimentally and described theoretically for an atomic vapor cell as the intracavity resonant absorber. This phenomenon may be used to enhance both the scale factor and sensitivity of an optical cavity mode to the change in path length, e.g. in gyroscopic applications. We study the temperature sensitivity of the on-resonant scale factor enhancement, S(sub o), due to the thermal sensitivity of the lower-level atom density in an atomic vapor cell, specifically for the case of the Rb-87 D(sub 2) transition. A semi-empirical model of the temperature-dependence of the absorption profile, characterized by two parameters, a(sub o)(T) and gamma(sub a)(T) allows the temperature-dependence of the cavity response, S(sub o)(T) and dS(sub o)/dT to be predicted over a range of temperature. We compare the predictions to experiment. Our model will be useful in determining the useful range for S(sub o), given the practical constraints on temperature stability for an atomic vapor cell.

Effect of creep in titanium alloy Ti-6Al-4V at elevated temperature on aircraft design and flight test

NASA Technical Reports Server (NTRS)

Jenkins, J. M.

1984-01-01

Short-term compressive creep tests were conducted on three titanium alloy Ti-6Al-4V coupons at three different stress levels at a temperature of 714 K (825 F). The test data were compared to several creep laws developed from tensile creep tests of available literature. The short-term creep test data did not correlate well with any of the creep laws obtained from available literature. The creep laws themselves did not correlate well with each other. Short-term creep does not appear to be very predictable for titanium alloy Ti-6Al-4V. Aircraft events that result in extreme, but short-term temperature and stress excursions for this alloy should be approached cautiously. Extrapolations of test data and creep laws suggest a convergence toward predictability in the longer-term situation.

Improvement of the modeling of the low-temperature oxidation of n-butane: study of the primary reactions.

PubMed

Cord, Maximilien; Sirjean, Baptiste; Fournet, René; Tomlin, Alison; Ruiz-Lopez, Manuel; Battin-Leclerc, Frédérique

2012-06-21

This paper revisits the primary reactions involved in the oxidation of n-butane from low to intermediate temperatures (550-800 K) including the negative temperature coefficient (NTC) zone. A model that was automatically generated is used as a starting point and a large number of thermochemical and kinetic data are then re-estimated. The kinetic data of the isomerization of alkylperoxy radicals giving (•)QOOH radicals and the subsequent decomposition to give cyclic ethers has been calculated at the CBS-QB3 level of theory. The newly obtained model allows a satisfactory prediction of experimental data recently obtained in a jet-stirred reactor and in rapid compression machines. A considerable improvement of the prediction of the selectivity of cyclic ethers is especially obtained compared to previous models. Linear and global sensitivity analyses have been performed to better understand which reactions are of influence in the NTC zone.

Statistical Modeling of Zr/Hf Extraction using TBP-D2EHPA Mixtures

NASA Astrophysics Data System (ADS)

Rezaeinejhad Jirandehi, Vahid; Haghshenas Fatmehsari, Davoud; Firoozi, Sadegh; Taghizadeh, Mohammad; Keshavarz Alamdari, Eskandar

2012-12-01

In the present work, response surface methodology was employed for the study and prediction of Zr/Hf extraction curves in a solvent extraction system using D2EHPA-TBP mixtures. The effect of change in the levels of temperature, nitric acid concentration, and TBP/D2EHPA ratio (T/D) on the Zr/Hf extraction/separation was studied by the use of central composite design. The results showed a statistically significant effect of T/D, nitric acid concentration, and temperature on the extraction percentage of Zr and Hf. In the case of Zr, a statistically significant interaction was found between T/D and nitric acid, whereas for Hf, both interactive terms between temperature and T/D and nitric acid were significant. Additionally, the extraction curves were profitably predicted applying the developed statistical regression equations; this approach is faster and more economical compared with experimentally obtained curves.

High Temperature Chemistry of Rare Earth Compounds: Dramatic Examples of Periodicity.

ERIC Educational Resources Information Center

Cater, E. David

1978-01-01

Reports that energy required to promote a 4f electron to the 5d level has a profound and predictable influence on the systematics of reactions involving conversion of rare earth atoms from combined to free states. (Author/MA)

Climate-soil Interactions: Global Change, Local Properties, and Ecological Sites

USDA-ARS?s Scientific Manuscript database

Global climate change is predicted to alter historic patterns of precipitation and temperature in rangelands globally. Vegetation community response to altered weather patterns will be mediated at the site level by local-scale properties that govern ecological potential, including geology, topograph...

Bubble nuclei within the self-consistent Hartree-Fock mean field plus pairing approach

NASA Astrophysics Data System (ADS)

Phuc, L. Tan; Hung, N. Quang; Dang, N. Dinh

2018-02-01

The depletion of the nuclear density at its center, called the nuclear bubble, is studied within the Skyrme Hartree-Fock mean field consistently incorporating the superfluid pairing. The latter is obtained within the finite-temperature Bardeen-Cooper-Schrieffer theory and within the approach using the exact pairing. The numerical calculations are carried out for 22O and 34Si nuclei, whose bubble structures, caused by a very low occupancy of the 2 s1 /2 level, were previously predicted at T =0 . Among 24 Skyrme interactions under consideration, the MSk3 is the only one which reproduces the experimentally measured occupancy of the 2 s1 /2 proton level as well as the binding energy, and consequently produces the most pronounced bubble structure in 34Si. As compared to the approaches employing the same BSk14 interaction, our approach with exact pairing predicts a pairing effect which is stronger in 22O and weaker in 34Si. The increase in temperature depletes the bubble structure and completely washes it out when the temperature reaches a critical value, at which the factor measuring the depletion of the nucleon density vanishes.

A Short Guide to the Climatic Variables of the Last Glacial Maximum for Biogeographers.

PubMed

Varela, Sara; Lima-Ribeiro, Matheus S; Terribile, Levi Carina

2015-01-01

Ecological niche models are widely used for mapping the distribution of species during the last glacial maximum (LGM). Although the selection of the variables and General Circulation Models (GCMs) used for constructing those maps determine the model predictions, we still lack a discussion about which variables and which GCM should be included in the analysis and why. Here, we analyzed the climatic predictions for the LGM of 9 different GCMs in order to help biogeographers to select their GCMs and climatic layers for mapping the species ranges in the LGM. We 1) map the discrepancies between the climatic predictions of the nine GCMs available for the LGM, 2) analyze the similarities and differences between the GCMs and group them to help researchers choose the appropriate GCMs for calibrating and projecting their ecological niche models (ENM) during the LGM, and 3) quantify the agreement of the predictions for each bioclimatic variable to help researchers avoid the environmental variables with a poor consensus between models. Our results indicate that, in absolute values, GCMs have a strong disagreement in their temperature predictions for temperate areas, while the uncertainties for the precipitation variables are in the tropics. In spite of the discrepancies between model predictions, temperature variables (BIO1-BIO11) are highly correlated between models. Precipitation variables (BIO12-BIO19) show no correlation between models, and specifically, BIO14 (precipitation of the driest month) and BIO15 (Precipitation Seasonality (Coefficient of Variation)) show the highest level of discrepancy between GCMs. Following our results, we strongly recommend the use of different GCMs for constructing or projecting ENMs, particularly when predicting the distribution of species that inhabit the tropics and the temperate areas of the Northern and Southern Hemispheres, because climatic predictions for those areas vary greatly among GCMs. We also recommend the exclusion of BIO14 and BIO15 from ENMs because those variables show a high level of discrepancy between GCMs. Thus, by excluding them, we decrease the level of uncertainty of our predictions. All the climatic layers produced for this paper are freely available in http://ecoclimate.org/.

A Short Guide to the Climatic Variables of the Last Glacial Maximum for Biogeographers

PubMed Central

Varela, Sara; Lima-Ribeiro, Matheus S.; Terribile, Levi Carina

2015-01-01

Ecological niche models are widely used for mapping the distribution of species during the last glacial maximum (LGM). Although the selection of the variables and General Circulation Models (GCMs) used for constructing those maps determine the model predictions, we still lack a discussion about which variables and which GCM should be included in the analysis and why. Here, we analyzed the climatic predictions for the LGM of 9 different GCMs in order to help biogeographers to select their GCMs and climatic layers for mapping the species ranges in the LGM. We 1) map the discrepancies between the climatic predictions of the nine GCMs available for the LGM, 2) analyze the similarities and differences between the GCMs and group them to help researchers choose the appropriate GCMs for calibrating and projecting their ecological niche models (ENM) during the LGM, and 3) quantify the agreement of the predictions for each bioclimatic variable to help researchers avoid the environmental variables with a poor consensus between models. Our results indicate that, in absolute values, GCMs have a strong disagreement in their temperature predictions for temperate areas, while the uncertainties for the precipitation variables are in the tropics. In spite of the discrepancies between model predictions, temperature variables (BIO1-BIO11) are highly correlated between models. Precipitation variables (BIO12- BIO19) show no correlation between models, and specifically, BIO14 (precipitation of the driest month) and BIO15 (Precipitation Seasonality (Coefficient of Variation)) show the highest level of discrepancy between GCMs. Following our results, we strongly recommend the use of different GCMs for constructing or projecting ENMs, particularly when predicting the distribution of species that inhabit the tropics and the temperate areas of the Northern and Southern Hemispheres, because climatic predictions for those areas vary greatly among GCMs. We also recommend the exclusion of BIO14 and BIO15 from ENMs because those variables show a high level of discrepancy between GCMs. Thus, by excluding them, we decrease the level of uncertainty of our predictions. All the climatic layers produced for this paper are freely available in http://ecoclimate.org/. PMID:26068930

Organismal climatology: analyzing environmental variability at scales relevant to physiological stress.

PubMed

Helmuth, Brian; Broitman, Bernardo R; Yamane, Lauren; Gilman, Sarah E; Mach, Katharine; Mislan, K A S; Denny, Mark W

2010-03-15

Predicting when, where and with what magnitude climate change is likely to affect the fitness, abundance and distribution of organisms and the functioning of ecosystems has emerged as a high priority for scientists and resource managers. However, even in cases where we have detailed knowledge of current species' range boundaries, we often do not understand what, if any, aspects of weather and climate act to set these limits. This shortcoming significantly curtails our capacity to predict potential future range shifts in response to climate change, especially since the factors that set range boundaries under those novel conditions may be different from those that set limits today. We quantitatively examine a nine-year time series of temperature records relevant to the body temperatures of intertidal mussels as measured using biomimetic sensors. Specifically, we explore how a 'climatology' of body temperatures, as opposed to long-term records of habitat-level parameters such as air and water temperatures, can be used to extrapolate meaningful spatial and temporal patterns of physiological stress. Using different metrics that correspond to various aspects of physiological stress (seasonal means, cumulative temperature and the return time of extremes) we show that these potential environmental stressors do not always occur in synchrony with one another. Our analysis also shows that patterns of animal temperature are not well correlated with simple, commonly used metrics such as air temperature. Detailed physiological studies can provide guidance to predicting the effects of global climate change on natural ecosystems but only if we concomitantly record, archive and model environmental signals at appropriate scales.

Boundary Layer Transition Flight Experiment Overview and In-Situ Measurements

NASA Technical Reports Server (NTRS)

Berger, Karen T.; Anderson, Brian P.; Campbell, Charles H.; Garske, Michael T.; Saucedo, Luis A.; Kinder, Gerald R.

2010-01-01

In support of the Boundary Layer Transition Flight Experiment (BLT FE) Project, a manufactured protuberance tile was installed on the port wing of Space Shuttle Orbiter Discovery for the flights of STS-119, STS-128 and STS-131. Additional instrumentation was installed in order to obtain more spatially resolved measurements downstream of the protuberance. This paper provides an overview of the BLT FE Project. Significant efforts were made to place the protuberance at an appropriate location on the Orbiter and to design the protuberance to withstand the expected environments. A high-level overview of the in-situ flight data is presented, along with a summary of the comparisons between pre- and post-flight analysis predictions and flight data. Comparisons show that predictions for boundary layer transition onset time closely match the flight data, while predicted temperatures were significantly higher than observed flight temperatures.

Guiding Empirical and Theoretical Explorations of Organic Matter Decay By Synthesizing Temperature Responses of Enzyme Kinetics, Microbes, and Isotope Fluxes

NASA Astrophysics Data System (ADS)

Billings, S. A.; Ballantyne, F.; Lehmeier, C.; Min, K.

2014-12-01

Soil organic matter (SOM) transformation rates generally increase with temperature, but whether this is realized depends on soil-specific features. To develop predictive models applicable to all soils, we must understand two key, ubiquitous features of SOM transformation: the temperature sensitivity of myriad enzyme-substrate combinations and temperature responses of microbial physiology and metabolism, in isolation from soil-specific conditions. Predicting temperature responses of production of CO2 vs. biomass is also difficult due to soil-specific features: we cannot know the identity of active microbes nor the substrates they employ. We highlight how recent empirical advances describing SOM decay can help develop theoretical tools relevant across diverse spatial and temporal scales. At a molecular level, temperature effects on purified enzyme kinetics reveal distinct temperature sensitivities of decay of diverse SOM substrates. Such data help quantify the influence of microbial adaptations and edaphic conditions on decay, have permitted computation of the relative availability of carbon (C) and nitrogen (N) liberated upon decay, and can be used with recent theoretical advances to predict changes in mass specific respiration rates as microbes maintain biomass C:N with changing temperature. Enhancing system complexity, we can subject microbes to temperature changes while controlling growth rate and without altering substrate availability or identity of the active population, permitting calculation of variables typically inferred in soils: microbial C use efficiency (CUE) and isotopic discrimination during C transformations. Quantified declines in CUE with rising temperature are critical for constraining model CUE estimates, and known changes in δ13C of respired CO2 with temperature is useful for interpreting δ13C-CO2 at diverse scales. We suggest empirical studies important for advancing knowledge of how microbes respond to temperature, and ideas for theoretical work to enhance the relevance of such work to the world's soils.

Online Adaptive Hyperthermia Treatment Planning During Locoregional Heating to Suppress Treatment-Limiting Hot Spots.

PubMed

Kok, H Petra; Korshuize-van Straten, Linda; Bakker, Akke; de Kroon-Oldenhof, Rianne; Geijsen, Elisabeth D; Stalpers, Lukas J A; Crezee, Johannes

2017-11-15

Adequate tumor temperatures during hyperthermia are essential for good clinical response, but excessive heating of normal tissue should be avoided. This makes locoregional heating using phased array systems technically challenging. Online application of hyperthermia treatment planning could help to improve the heating quality. The aim of this study was to evaluate the clinical benefit of online treatment planning during treatment of pelvic tumors heated with the AMC-8 locoregional hyperthermia system. For online adaptive hyperthermia treatment planning, a graphical user interface was developed. Electric fields were calculated in a preprocessing step using our in-house-developed finite-difference-based treatment planning system. This allows instant calculation of the temperature distribution for user-selected phase-amplitude settings during treatment and projection onto the patient's computed tomographic scan for online visualization. Online treatment planning was used for 14 treatment sessions in 8 patients to reduce the patients' reports of hot spots while maintaining the same level of tumor heating. The predicted decrease in hot spot temperature should be at least 0.5°C, and the tumor temperature should decrease less than 0.2°C. These predictions were compared with clinical data: patient feedback about the hot spot and temperature measurements in the tumor region. In total, 17 hot spot reports occurred during the 14 sessions, and the alternative settings predicted the hot spot temperature to decrease by at least 0.5°C, which was confirmed by the disappearance of all 17 hot spot reports. At the same time, the average tumor temperature was predicted to change on average -0.01°C (range, -0.19°C to 0.34°C). The measured tumor temperature change was on average only -0.02°C (range, -0.26°C to 0.31°C). In only 2 cases the temperature decrease was slightly larger than 0.2°C, but at most it was 0.26°C. Online application of hyperthermia treatment planning is reliable and very useful to reduce hot spots without affecting tumor temperatures. Copyright © 2017 Elsevier Inc. All rights reserved.

Identify the dominant variables to predict stream water temperature

NASA Astrophysics Data System (ADS)

Chien, H.; Flagler, J.

2016-12-01

Stream water temperature is a critical variable controlling water quality and the health of aquatic ecosystems. Accurate prediction of water temperature and the assessment of the impacts of environmental variables on water temperature variation are critical for water resources management, particularly in the context of water quality and aquatic ecosystem sustainability. The objective of this study is to measure stream water temperature and air temperature and to examine the importance of streamflow on stream water temperature prediction. The measured stream water temperature and air temperature will be used to test two hypotheses: 1) streamflow is a relatively more important factor than air temperature in regulating water temperature, and 2) by combining air temperature and streamflow data stream water temperature can be more accurately estimated. Water and air temperature data loggers are placed at two USGS stream gauge stations #01362357and #01362370, located in the upper Esopus Creek watershed in Phonecia, NY. The ARIMA (autoregressive integrated moving average) time series model is used to analyze the measured water temperature data, identify the dominant environmental variables, and predict the water temperature with identified dominant variable. The preliminary results show that streamflow is not a significant variable in predicting stream water temperature at both USGS gauge stations. Daily mean air temperature is sufficient to predict stream water temperature at this site scale.

Prediction Model for Predicting Powdery Mildew using ANN for Medicinal Plant— Picrorhiza kurrooa

NASA Astrophysics Data System (ADS)

Shivling, V. D.; Ghanshyam, C.; Kumar, Rakesh; Kumar, Sanjay; Sharma, Radhika; Kumar, Dinesh; Sharma, Atul; Sharma, Sudhir Kumar

2017-02-01

Plant disease fore casting system is an important system as it can be used for prediction of disease, further it can be used as an alert system to warn the farmers in advance so as to protect their crop from being getting infected. Fore casting system will predict the risk of infection for crop by using the environmental factors that favor in germination of disease. In this study an artificial neural network based system for predicting the risk of powdery mildew in Picrorhiza kurrooa was developed. For development, Levenberg-Marquardt backpropagation algorithm was used having a single hidden layer of ten nodes. Temperature and duration of wetness are the major environmental factors that favor infection. Experimental data was used as a training set and some percentage of data was used for testing and validation. The performance of the system was measured in the form of the coefficient of correlation (R), coefficient of determination (R2), mean square error and root mean square error. For simulating the network an inter face was developed. Using this interface the network was simulated by putting temperature and wetness duration so as to predict the level of risk at that particular value of the input data.

Prediction modeling of physiological responses and human performance in the heat with application to space operations

NASA Technical Reports Server (NTRS)

Pandolf, Kent B.; Stroschein, Leander A.; Gonzalez, Richard R.; Sawka, Michael N.

1994-01-01

This institute has developed a comprehensive USARIEM heat strain model for predicting physiological responses and soldier performance in the heat which has been programmed for use by hand-held calculators, personal computers, and incorporated into the development of a heat strain decision aid. This model deals directly with five major inputs: the clothing worn, the physical work intensity, the state of heat acclimation, the ambient environment (air temperature, relative humidity, wind speed, and solar load), and the accepted heat casualty level. In addition to predicting rectal temperature, heart rate, and sweat loss given the above inputs, our model predicts the expected physical work/rest cycle, the maximum safe physical work time, the estimated recovery time from maximal physical work, and the drinking water requirements associated with each of these situations. This model provides heat injury risk management guidance based on thermal strain predictions from the user specified environmental conditions, soldier characteristics, clothing worn, and the physical work intensity. If heat transfer values for space operations' clothing are known, NASA can use this prediction model to help avoid undue heat strain in astronauts during space flight.

Quantitative assessment of the microbial risk of leafy greens from farm to consumption: preliminary framework, data, and risk estimates.

PubMed

Danyluk, Michelle D; Schaffner, Donald W

2011-05-01

This project was undertaken to relate what is known about the behavior of Escherichia coli O157:H7 under laboratory conditions and integrate this information to what is known regarding the 2006 E. coli O157:H7 spinach outbreak in the context of a quantitative microbial risk assessment. The risk model explicitly assumes that all contamination arises from exposure in the field. Extracted data, models, and user inputs were entered into an Excel spreadsheet, and the modeling software @RISK was used to perform Monte Carlo simulations. The model predicts that cut leafy greens that are temperature abused will support the growth of E. coli O157:H7, and populations of the organism may increase by as much a 1 log CFU/day under optimal temperature conditions. When the risk model used a starting level of -1 log CFU/g, with 0.1% of incoming servings contaminated, the predicted numbers of cells per serving were within the range of best available estimates of pathogen levels during the outbreak. The model predicts that levels in the field of -1 log CFU/g and 0.1% prevalence could have resulted in an outbreak approximately the size of the 2006 E. coli O157:H7 outbreak. This quantitative microbial risk assessment model represents a preliminary framework that identifies available data and provides initial risk estimates for pathogenic E. coli in leafy greens. Data gaps include retail storage times, correlations between storage time and temperature, determining the importance of E. coli O157:H7 in leafy greens lag time models, and validation of the importance of cross-contamination during the washing process.

Gradient augmented level set method for phase change simulations

NASA Astrophysics Data System (ADS)

Anumolu, Lakshman; Trujillo, Mario F.

2018-01-01

A numerical method for the simulation of two-phase flow with phase change based on the Gradient-Augmented-Level-set (GALS) strategy is presented. Sharp capturing of the vaporization process is enabled by: i) identification of the vapor-liquid interface, Γ (t), at the subgrid level, ii) discontinuous treatment of thermal physical properties (except for μ), and iii) enforcement of mass, momentum, and energy jump conditions, where the gradients of the dependent variables are obtained at Γ (t) and are consistent with their analytical expression, i.e. no local averaging is applied. Treatment of the jump in velocity and pressure at Γ (t) is achieved using the Ghost Fluid Method. The solution of the energy equation employs the sub-grid knowledge of Γ (t) to discretize the temperature Laplacian using second-order one-sided differences, i.e. the numerical stencil completely resides within each respective phase. To carefully evaluate the benefits or disadvantages of the GALS approach, the standard level set method is implemented and compared against the GALS predictions. The results show the expected trend that interface identification and transport are predicted noticeably better with GALS over the standard level set. This benefit carries over to the prediction of the Laplacian and temperature gradients in the neighborhood of the interface, which are directly linked to the calculation of the vaporization rate. However, when combining the calculation of interface transport and reinitialization with two-phase momentum and energy, the benefits of GALS are to some extent neutralized, and the causes for this behavior are identified and analyzed. Overall the additional computational costs associated with GALS are almost the same as those using the standard level set technique.

Sensitivity of two dispersion models (AERMOD and ISCST3) to input parameters for a rural ground-level area source.

PubMed

Faulkner, William B; Shaw, Bryan W; Grosch, Tom

2008-10-01

As of December 2006, the American Meteorological Society/U.S. Environmental Protection Agency (EPA) Regulatory Model with Plume Rise Model Enhancements (AERMOD-PRIME; hereafter AERMOD) replaced the Industrial Source Complex Short Term Version 3 (ISCST3) as the EPA-preferred regulatory model. The change from ISCST3 to AERMOD will affect Prevention of Significant Deterioration (PSD) increment consumption as well as permit compliance in states where regulatory agencies limit property line concentrations using modeling analysis. Because of differences in model formulation and the treatment of terrain features, one cannot predict a priori whether ISCST3 or AERMOD will predict higher or lower pollutant concentrations downwind of a source. The objectives of this paper were to determine the sensitivity of AERMOD to various inputs and compare the highest downwind concentrations from a ground-level area source (GLAS) predicted by AERMOD to those predicted by ISCST3. Concentrations predicted using ISCST3 were sensitive to changes in wind speed, temperature, solar radiation (as it affects stability class), and mixing heights below 160 m. Surface roughness also affected downwind concentrations predicted by ISCST3. AERMOD was sensitive to changes in albedo, surface roughness, wind speed, temperature, and cloud cover. Bowen ratio did not affect the results from AERMOD. These results demonstrate AERMOD's sensitivity to small changes in wind speed and surface roughness. When AERMOD is used to determine property line concentrations, small changes in these variables may affect the distance within which concentration limits are exceeded by several hundred meters.

Evaluating the Impact of Global Warming on Water Balance of Maize by High-precision Controlled Experiment and MLCan model

NASA Astrophysics Data System (ADS)

Ma, Y.; Song, X.; Kumar, P.; Wu, Y.; Woo, D.; Le, P. V.; Ma, C.

2016-12-01

Increased temperature affects the agricultural hydrologic cycle not only by changing precipitation levels, evapotranspiration and the magnitude and timing of run-off, but also by impacting water flows and soil water dynamics. Accurate prediction of hydrologic change under global warming requires high-precision experiment and mathematical model to determine water interaction between interfaces in the soil-plant-atmosphere continuum. In this study, the weighting lysimeter and chamber were coupled to monitor water balance component dynamics of maize under controlled ambient temperature and elevated temperature of 2°C conditions. A mechanistic multilayer canopy-soil-root system model (MLCan) was used to predict hydrologic fluxes variation under different elevated temperature scenarios after calibration with experimental results. The results showed that maize growth period reduced 8 days under increased temperature of 2°C. The mean daily evapotranspiration, soil water storage change, and drainage was 2.66 mm, -2.75 mm, and 0.22 mm under controlled temperature condition, respectively. When temperature was elevated by 2°C, the average daily ET for maize significantly increased about 6.7% (p<0.05). However, there were non-significant impacts of increased temperature on the daily soil water storage change and drainage (p>0.05). Quantification of changes in water balance components induced by temperature increase for maize is critical for optimizing irrigation water management practices and improving water use efficiency.

Temperature-Dependent Kinetic Model for Nitrogen-Limited Wine Fermentations▿

PubMed Central

Coleman, Matthew C.; Fish, Russell; Block, David E.

2007-01-01

A physical and mathematical model for wine fermentation kinetics was adapted to include the influence of temperature, perhaps the most critical factor influencing fermentation kinetics. The model was based on flask-scale white wine fermentations at different temperatures (11 to 35°C) and different initial concentrations of sugar (265 to 300 g/liter) and nitrogen (70 to 350 mg N/liter). The results show that fermentation temperature and inadequate levels of nitrogen will cause stuck or sluggish fermentations. Model parameters representing cell growth rate, sugar utilization rate, and the inactivation rate of cells in the presence of ethanol are highly temperature dependent. All other variables (yield coefficient of cell mass to utilized nitrogen, yield coefficient of ethanol to utilized sugar, Monod constant for nitrogen-limited growth, and Michaelis-Menten-type constant for sugar transport) were determined to vary insignificantly with temperature. The resulting mathematical model accurately predicts the observed wine fermentation kinetics with respect to different temperatures and different initial conditions, including data from fermentations not used for model development. This is the first wine fermentation model that accurately predicts a transition from sluggish to normal to stuck fermentations as temperature increases from 11 to 35°C. Furthermore, this comprehensive model provides insight into combined effects of time, temperature, and ethanol concentration on yeast (Saccharomyces cerevisiae) activity and physiology. PMID:17616615

Temperature variations in a parked vehicle.

PubMed

Dadour, I R; Almanjahie, I; Fowkes, N D; Keady, G; Vijayan, K

2011-04-15

There were two reasons why this work was conducted. The first was to help determine the time of death of suicide and homicide victims inside vehicles. The second was to investigate the serious threat to life of children or pets left in stationary vehicles on a hot summers day. This paper demonstrates that when a vehicle is parked in the sun, temperature levels in the cabin of the vehicle can be more than 20°C above the ambient temperature. A simple 'greenhouse' model for predicting the daily internal vehicle temperatures, using readily available local meteorological data, was developed. This statistical model was calibrated using meteorological data and temperature data collected on parked vehicles over several summer seasons. The model uses environmental temperature and radiation data as input, and is shown to predict cabin temperatures to within about 1°C. Both the data collected and the model developed show that the temperature inside the cabin of a black vehicle is typically 5°C higher than that inside a white vehicle on a hot summer day. Also lowering the driver's window of the vehicle by 2.5 cm typically reduces cabin temperatures by about 3°C, which is not sufficient to reduce significantly the safety concerns for children or pets left in parked vehicles. Crown Copyright © 2010. Published by Elsevier Ireland Ltd. All rights reserved.

Suitability of different comfort indices for the prediction of thermal conditions in tree-covered outdoor spaces in arid cities

NASA Astrophysics Data System (ADS)

Ruiz, María Angélica; Correa, Erica Norma

2015-10-01

Outdoor thermal comfort is one of the most influential factors in the habitability of a space. Thermal level is defined not only by climate variables but also by the adaptation of people to the environment. This study presents a comparison between inductive and deductive thermal comfort models, contrasted with subjective reports, in order to identify which of the models can be used to most correctly predict thermal comfort in tree-covered outdoor spaces of the Mendoza Metropolitan Area, an intensely forested and open city located in an arid zone. Interviews and microclimatic measurements were carried out in winter 2010 and in summer 2011. Six widely used indices were selected according to different levels of complexity: the Temperature-Humidity Index (THI), Vinje's Comfort Index (PE), Thermal Sensation Index (TS), the Predicted Mean Vote (PMV), the COMFA model's energy balance (S), and the Physiological Equivalent Temperature (PET). The results show that the predictive models evaluated show percentages of predictive ability lower than 25 %. Despite this low indicator, inductive methods are adequate for obtaining a diagnosis of the degree and frequency in which a space is comfortable or not whereas deductive methods are recommended to influence urban design strategies. In addition, it is necessary to develop local models to evaluate perceived thermal comfort more adequately. This type of tool is very useful in the design and evaluation of the thermal conditions in outdoor spaces, based not only to climatic criteria but also subjective sensations.

A scale model wind tunnel study of dispersion in the Cleveland area. Laboratory simulation of lake breeze effects on diffusion from ground level emissions

NASA Technical Reports Server (NTRS)

Hoydysh, W. G.

1974-01-01

A wind tunnel simulation of the diffusion patterns in a sea breeze was attempted. The results indicate that the low level onshore flow was well simulated for neutral, stable, unstable, and elevated inversion conditions. Velocity, turbulence, shear stress, and temperature data were taken, and the spread of emissions from ground level sources was investigated. Comparison is made with theoretical predictions by E. Inoue and with the open, homogeneous plane field results of Pasquill. Agreement with the predictions by Inoue is good, and the comparison with Pasquill's results shows that the wind tunnel flows are shifted two categories towards more stable. The discrepancy may be explained as a matter of averaging time.

Identification of the significant factors in food safety using global sensitivity analysis and the accept-and-reject algorithm: application to the cold chain of ham.

PubMed

Duret, Steven; Guillier, Laurent; Hoang, Hong-Minh; Flick, Denis; Laguerre, Onrawee

2014-06-16

Deterministic models describing heat transfer and microbial growth in the cold chain are widely studied. However, it is difficult to apply them in practice because of several variable parameters in the logistic supply chain (e.g., ambient temperature varying due to season and product residence time in refrigeration equipment), the product's characteristics (e.g., pH and water activity) and the microbial characteristics (e.g., initial microbial load and lag time). This variability can lead to different bacterial growth rates in food products and has to be considered to properly predict the consumer's exposure and identify the key parameters of the cold chain. This study proposes a new approach that combines deterministic (heat transfer) and stochastic (Monte Carlo) modeling to account for the variability in the logistic supply chain and the product's characteristics. The model generates a realistic time-temperature product history , contrary to existing modeling whose describe time-temperature profile Contrary to existing approaches that use directly a time-temperature profile, the proposed model predicts product temperature evolution from the thermostat setting and the ambient temperature. The developed methodology was applied to the cold chain of cooked ham including, the display cabinet, transport by the consumer and the domestic refrigerator, to predict the evolution of state variables, such as the temperature and the growth of Listeria monocytogenes. The impacts of the input factors were calculated and ranked. It was found that the product's time-temperature history and the initial contamination level are the main causes of consumers' exposure. Then, a refined analysis was applied, revealing the importance of consumer behaviors on Listeria monocytogenes exposure. Copyright © 2014. Published by Elsevier B.V.

A global model for steady state and transient S.I. engine heat transfer studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bohac, S.V.; Assanis, D.N.; Baker, D.M.

1996-09-01

A global, systems-level model which characterizes the thermal behavior of internal combustion engines is described in this paper. Based on resistor-capacitor thermal networks, either steady-state or transient thermal simulations can be performed. A two-zone, quasi-dimensional spark-ignition engine simulation is used to determine in-cylinder gas temperature and convection coefficients. Engine heat fluxes and component temperatures can subsequently be predicted from specification of general engine dimensions, materials, and operating conditions. Emphasis has been placed on minimizing the number of model inputs and keeping them as simple as possible to make the model practical and useful as an early design tool. The successmore » of the global model depends on properly scaling the general engine inputs to accurately model engine heat flow paths across families of engine designs. The development and validation of suitable, scalable submodels is described in detail in this paper. Simulation sub-models and overall system predictions are validated with data from two spark ignition engines. Several sensitivity studies are performed to determine the most significant heat transfer paths within the engine and exhaust system. Overall, it has been shown that the model is a powerful tool in predicting steady-state heat rejection and component temperatures, as well as transient component temperatures.« less

Effects of Genotype and Growth Temperature on the Contents of Tannin, Phytate and In Vitro Iron Availability of Sorghum Grains

PubMed Central

Wu, Gangcheng; Johnson, Stuart K.; Bornman, Janet F.; Bennett, Sarita J.; Singh, Vijaya; Simic, Azra; Fang, Zhongxiang

2016-01-01

Background It has been predicted that the global temperature will rise in the future, which means crops including sorghum will likely be grown under higher temperatures, and consequently may affect the nutritional properties. Methods The effects of two growth temperatures (OT, day/night 32/21°C; HT 38/21°C) on tannin, phytate, mineral, and in vitro iron availability of raw and cooked grains (as porridge) of six sorghum genotypes were investigated. Results Tannin content significantly decreased across all sorghum genotypes under high growth temperature (P ≤0.05), while the phytate and mineral contents maintained the same level, increased or decreased significantly, depending on the genotype. The in vitro iron availability in most sorghum genotypes was also significantly reduced under high temperature, except for Ai4, which showed a pronounced increase (P ≤0.05). The cooking process significantly reduced tannin content in all sorghum genotypes (P ≤0.05), while the phytate content and in vitro iron availability were not significantly affected. Conclusions This research provides some new information on sorghum grain nutritional properties when grown under predicted future higher temperatures, which could be important for humans where sorghum grains are consumed as staple food. PMID:26859483

Why "suboptimal" is optimal: Jensen's inequality and ectotherm thermal preferences.

PubMed

Martin, Tara Laine; Huey, Raymond B

2008-03-01

Body temperature (T(b)) profoundly affects the fitness of ectotherms. Many ectotherms use behavior to control T(b) within narrow levels. These temperatures are assumed to be optimal and therefore to match body temperatures (Trmax) that maximize fitness (r). We develop an optimality model and find that optimal body temperature (T(o)) should not be centered at Trmax but shifted to a lower temperature. This finding seems paradoxical but results from two considerations relating to Jensen's inequality, which deals with how variance and skew influence integrals of nonlinear functions. First, ectotherms are not perfect thermoregulators and so experience a range of T(b). Second, temperature-fitness curves are asymmetric, such that a T(b) higher than Trmax depresses fitness more than will a T(b) displaced an equivalent amount below Trmax. Our model makes several predictions. The magnitude of the optimal shift (Trmax - To) should increase with the degree of asymmetry of temperature-fitness curves and with T(b) variance. Deviations should be relatively large for thermal specialists but insensitive to whether fitness increases with Trmax ("hotter is better"). Asymmetric (left-skewed) T(b) distributions reduce the magnitude of the optimal shift but do not eliminate it. Comparative data (insects, lizards) support key predictions. Thus, "suboptimal" is optimal.

Net superoxide levels: steeper increase with activity in cooler female and hotter male lizards.

PubMed

Ballen, Cissy; Healey, Mo; Wilson, Mark; Tobler, Michael; Wapstra, Erik; Olsson, Mats

2012-03-01

Ectotherms increase their body temperature in response to ambient heat, thereby elevating their metabolic rate. An often inferred consequence of this is an overall upregulation of gene expression and energetic expenditure, and a concomitant increased production of reactive oxygen species (e.g. superoxide) and, perhaps, a shortened lifespan. However, recent work shows that this may be a superficial interpretation. For example, sometimes a reduced temperature may in fact trigger up-regulation of gene expression. We studied temperature and associated activity effects in male and female Australian painted dragon lizards (Ctenophorus pictus) by allowing the lizards to bask for 4 h versus 12 h, and scoring their associated activity (inactive versus active basking and foraging). As predicted, long-basking lizards (hereafter 'hot') showed heightened activity in both sexes, with a more pronounced effect in females. We then tested for sex-specific effects of basking treatment and activity levels on the increase in net levels of superoxide. In males, short-baskers (hereafter 'cold') had significantly more rapidly decreasing levels of superoxide per unit increasing activity than hot males. In females, however, superoxide levels increased faster with increasing activity in the cold than in the hot basking treatment, and females earlier in the ovarian cycle had lower superoxide levels than females closer to ovulation. In short, males and females differ in how their levels of reactive oxygen species change with temperature-triggered activity.

Experimental confirmation of the predicted shallow donor hydrogen state in zinc oxide.

PubMed

Cox, S F; Davis, E A; Cottrell, S P; King, P J; Lord, J S; Gil, J M; Alberto, H V; Vilão, R C; Piroto Duarte, J; Ayres de Campos, N; Weidinger, A; Lichti, R L; Irvine, S J

2001-03-19

We confirm the recent prediction that interstitial protium may act as a shallow donor in zinc oxide, by direct spectroscopic observation of its muonium counterpart. On implantation into ZnO, positive muons--chemically analogous to protons in this context--form paramagnetic centers below about 40 K. The muon-electron contact hyperfine interaction, as well as the temperature and activation energy for ionization, imply a shallow level. Similar results for the cadmium chalcogenides suggest that such shallow donor states are generic to the II-VI compounds. The donor level depths should serve as a guide for the electrical activity of interstitial hydrogen.

Influence of predicted climage change elements on Z. japonica distribution in Washington State

EPA Science Inventory

Global climate change (GCC) is expected to have pronounced impacts on estuarine and marine habitats including sea level rise, increased storm intensity, increased air and water temperatures, changes in upwelling dynamics and ocean acidification. All of these elements are likely ...

Predicting the relatiave vulnerability of near-coastal species to climate change using a rule-based ecoinformatics approach

EPA Science Inventory

Background/Questions/Methods Near-coastal species are threatened by multiple climate change drivers, including temperature increases, ocean acidification, and sea level rise. To identify vulnerable habitats, geographic regions, and species, we developed a sequential, rule-based...

Shelf-life prediction models for ready-to-eat fresh cut salads: Testing in real cold chain.

PubMed

Tsironi, Theofania; Dermesonlouoglou, Efimia; Giannoglou, Marianna; Gogou, Eleni; Katsaros, George; Taoukis, Petros

2017-01-02

The aim of the study was to develop and test the applicability of predictive models for shelf-life estimation of ready-to-eat (RTE) fresh cut salads in realistic distribution temperature conditions in the food supply chain. A systematic kinetic study of quality loss of RTE mixed salad (lollo rosso lettuce-40%, lollo verde lettuce-45%, rocket-15%) packed under modified atmospheres (3% O 2 , 10% CO 2 , 87% N 2 ) was conducted. Microbial population (total viable count, Pseudomonas spp., lactic acid bacteria), vitamin C, colour and texture were the measured quality parameters. Kinetic models for these indices were developed to determine the quality loss and calculate product remaining shelf-life (SL R ). Storage experiments were conducted at isothermal (2.5-15°C) and non-isothermal temperature conditions (T eff =7.8°C defined as the constant temperature that results in the same quality value as the variable temperature distribution) for validation purposes. Pseudomonas dominated spoilage, followed by browning and chemical changes. The end of shelf-life correlated with a Pseudomonas spp. level of 8 log(cfu/g), and 20% loss of the initial vitamin C content. The effect of temperature on these quality parameters was expressed by the Arrhenius equation; activation energy (E a ) value was 69.1 and 122.6kJ/mol for Pseudomonas spp. growth and vitamin C loss rates, respectively. Shelf-life prediction models were also validated in real cold chain conditions (including the stages of transport to and storage at retail distribution center, transport to and display at 7 retail stores, transport to and storage in domestic refrigerators). The quality level and SL R estimated after 2-3days of domestic storage (time of consumption) ranged between 1 and 8days at 4°C and was predicted within satisfactory statistical error by the kinetic models. T eff in the cold chain ranged between 3.7 and 8.3°C. Using the validated models, SL R of RTE fresh cut salad can be estimated at any point of the cold chain if the temperature history is known. Shelf-life models of validated applicability can serve as an effective tool for shelf-life assessment and the development of new products in the fresh produce food sector. Copyright © 2016. Published by Elsevier B.V.

Development and validation of a mathematical model for growth of pathogens in cut melons.

PubMed

Li, Di; Friedrich, Loretta M; Danyluk, Michelle D; Harris, Linda J; Schaffner, Donald W

2013-06-01

Many outbreaks of foodborne illness associated with the consumption of fresh-cut melons have been reported. The objective of our research was to develop a mathematical model that predicts the growth rate of Salmonella on fresh-cut cantaloupe over a range of storage temperatures and to validate that model by using Salmonella and Escherichia coli O157:H7 on cantaloupe, honeydew, and watermelon, using both new data and data from the published studies. The growth of Salmonella on honeydew and watermelon and E. coli O157:H7 on cantaloupe, honeydew, and watermelon was monitored at temperatures of 4 to 25°C. The Ratkowsky (or square-root model) was used to describe Salmonella growth on cantaloupe as a function of storage temperature. Our results show that the levels of Salmonella on fresh-cut cantaloupe with an initial load of 3 log CFU/g can reach over 7 log CFU/g at 25°C within 24 h. No growth was observed at 4°C. A linear correlation was observed between the square root of Salmonella growth rate and temperature, such that √growth rate = 0.026 × (T - 5.613), R(2) = 0.9779. The model was generally suitable for predicting the growth of both Salmonella and E. coli O157:H7 on cantaloupe, honeydew, and watermelon, for both new data and data from the published literature. When compared with existing models for growth of Salmonella, the new model predicts a theoretic minimum growth temperature similar to the ComBase Predictive Models and Pathogen Modeling Program models but lower than other food-specific models. The ComBase Prediction Models results are very similar to the model developed in this study. Our research confirms that Salmonella can grow quickly and reach high concentrations when cut cantaloupe is stored at ambient temperatures, without visual signs of spoilage. Our model provides a fast and cost-effective method to estimate the effects of storage temperature on fresh-cut melon safety and could also be used in subsequent quantitative microbial risk assessments.

Land-Breeze Forecasting

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Wheeler, Mark M.; Merceret, Francis J. (Technical Monitor)

2002-01-01

The nocturnal land breeze at the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) is both operationally significant and challenging to forecast. The occurrence and timing of land breezes impact low-level winds, atmospheric stability, low temperatures, and fog development. Accurate predictions of the land breeze are critical for toxic material dispersion forecasts associated with space launch missions, since wind direction and low-level stability can change noticeably with the onset of a land breeze. This report presents a seven-year observational study of land breezes over east-central Florida from 1995 to 2001. This comprehensive analysis was enabled by the high-resolution tower observations over KSC/CCAFS. Five-minute observations of winds, temperature, and moisture along with 9 15-MHz Doppler Radar Wind Profiler data were used to analyze specific land-breeze cases, while the tower data were used to construct a composite climatology. Utilities derived from this climatology were developed to assist forecasters in determining the land-breeze occurrence, timing, and movement based on predicted meteorological conditions.

Sand lizard (Lacerta agilis) phenology in a warming world.

PubMed

Ljungström, Gabriella; Wapstra, Erik; Olsson, Mats

2015-10-08

Present-day climate change has altered the phenology (the timing of periodic life cycle events) of many plant and animal populations worldwide. Some of these changes have been adaptive, leading to an increase in population fitness, whereas others have been associated with fitness decline. Representing short-term responses to an altered weather regime, hitherto observed changes are largely explained by phenotypic plasticity. However, to track climatically induced shifts in optimal phenotype as climate change proceeds, evolutionary capacity in key limiting climate- and fitness-related traits is likely to be crucial. In order to produce realistic predictions about the effects of climate change on species and populations, a main target for conservation biologists is thus to assess the potential of natural populations to respond by these two mechanisms. In this study we use a large 15-year dataset on an ectotherm model, the Swedish sand lizard (Lacerta agilis), to investigate how higher spring temperature is likely to affect oviposition timing in a high latitude population, a trait strongly linked to offspring fitness and survival. With an interest in both the short- and potential long-term effect of rising temperatures, we applied a random regression model, which yields estimates of population-level plasticity and among-individual variation in the average, as well as the plastic, response to temperature. Population plasticity represents capacity for short-term adjustments whereas variation among individuals in a fitness-related trait indicates an opportunity for natural selection and hence for evolutionary adaptation. The analysis revealed both population-level plasticity and individual-level variation in average laying date. In contrast, we found no evidence for variation among females in their plastic responses to spring temperature, which could demonstrate a similarity in responses amongst females, but may also be due to a lack of statistical power to detect such an effect. Our findings indicate that climate warming may have positive fitness effects in this lizard population through an advancement of oviposition date. This prediction is consistent over shorter and potentially also longer time scales as the analysis revealed both population-level plasticity and individual-level variation in average laying date. However, the genetic basis for this variation would have to be examined in order to predict an evolutionary response.

A dynamic growth model of macroalgae: Application in an estuary recovering from treated wastewater and earthquake-driven eutrophication

NASA Astrophysics Data System (ADS)

Ren, Jeffrey S.; Barr, Neill G.; Scheuer, Kristin; Schiel, David R.; Zeldis, John

2014-07-01

A dynamic growth model of macroalgae was developed to predict growth of the green macroalga Ulva sp. in response to changes in environmental variables. The model is based on common physiological behaviour of macroalgae and hence has general applicability to macroalgae. Three state variables (nitrogen, carbon and phosphorus) were used to describe physiological processes and functional differences between nutrient and carbon uptakes. Carbon uptake is modelled as a function of temperature, light, algal internal state and water current, while nutrient uptake depends on internal state, temperature and environmental nutrient level. Growth can only occur when nutrients in the environment and in the internal storage pools (N-quota and P-quota) reach threshold levels. Physiological rates follow the Arrhenius relationship and increase exponentially with increasing temperature within the temperature tolerance range of a species. When parameterised and applied to Ulva sp. in the eutrophic Avon-Heathcote Estuary, New Zealand, the model generally reproduced field observations of Ulva sp. growth and abundance. Growth followed a clear seasonal cycle with biomass increasing from early-middle summer, reaching peak values in early autumn and then decreasing. Conversely, N-quotient levels were maximal during the winter months, declining during summer peak growth. These seasonal patterns were collectively driven by temperature, light intensity and nutrients. The model captured the N-quota and growth responses of Ulva sp. to the N-reduction arising from diversion of treated wastewater from the Avon-Heathcote Estuary to an offshore outfall in 2010, and of raw sewage N-discharges resulting from wastewater infrastructure damage caused by the Canterbury earthquakes in 2011. Sensitivity analyses revealed that temperature-related parameters and maximum uptake rate of C were among the most sensitive parameters in predicting biomass. In addition, the earthquake-derived changes in reduction of immersion time and decrease in the start biomass prior to summer blooms were shown to drive considerable declines in summer growth and biomass of Ulva sp.

Combined effects of temperature and avermectins on life history and stress response of the western flower thrips, Frankliniella occidentalis.

PubMed

Li, Hong-Bo; Zheng, Yu-Tao; Sun, Dan-Dan; Wang, Jian-Jun; Du, Yu-Zhou

2014-01-01

Temperature and pesticide are two important factors that affect survival, reproduction and other physiological processes of insects. To determine interactions of elevated temperature and avermectins treatment on the western flower thrips, Frankliniella occidentalis, newly emerged adults were exposed to combinations of three temperatures (21, 26 and 33 °C) and two avermectins concentrations (0, 45 ppm), and survival rate, reproduction, longevity, antioxidant enzymes activities and heat shock proteins (hsps) induction were analyzed. The results showed that the survival, longevity and reproduction of F. occidentalis decreased with increased temperature and avermectins treatment. While elevated temperature and avermectins treatment significantly decreased activity of SOD, activities of POD and GST significantly increased after exposure to elevated temperature, avermectins or their combination. Elevated temperature had no effect on activity of CAT, but it was obviously improved by the combination of temperature and avermectins treatment. Expression analysis of hsps showed that four heat shock proteins (hsp90, hsc702, hsp60 and hop) were up-regulated by the induction of elevated temperature with small fold changes. After treatment with avermectins, expression levels of hsp90, hsc701, hsc702 and hop were significantly up-regulated with increased temperature and higher than those of their respective control at higher temperature. Surprisingly, expression level of hps60 was down-regulated with increased temperature, but the expression level at 21 or 26 °C remained higher than that of control. Overall, our studies suggest that elevated temperature enhance toxicity of avermectins and their combination induced acute oxidative damage to F. occidentalis. Therefore, consideration of temperature in evaluating avermectins toxicity is necessary to make accurate prediction of its effect on F. occidentalis and other insects. Copyright © 2014 Elsevier Inc. All rights reserved.

Biological modulation of the earth's atmosphere

NASA Technical Reports Server (NTRS)

Margulis, L.; Lovelock, J. E.

1974-01-01

Review of the evidence that the earth's atmosphere is regulated by life on the surface so that the probability of growth of the entire biosphere is maximized. Acidity, gas composition including oxygen level, and ambient temperature are enormously important determinants for the distribution of life. The earth's atmosphere deviates greatly from that of the other terrestrial planets in particular with respect to acidity, composition, redox potential and temperature history as predicted from solar luminosity. These deviations from predicted steady state conditions have apparently persisted over millions of years. These anomalies may be evidence for a complex planet-wide homeostasis that is the product of natural selection. Possible homeostatic mechanisms that may be further investigated by both theoretical and experimental methods are suggested.

Kinetic mechanism of molecular energy transfer and chemical reactions in low-temperature air-fuel plasmas.

PubMed

Adamovich, Igor V; Li, Ting; Lempert, Walter R

2015-08-13

This work describes the kinetic mechanism of coupled molecular energy transfer and chemical reactions in low-temperature air, H2-air and hydrocarbon-air plasmas sustained by nanosecond pulse discharges (single-pulse or repetitive pulse burst). The model incorporates electron impact processes, state-specific N(2) vibrational energy transfer, reactions of excited electronic species of N(2), O(2), N and O, and 'conventional' chemical reactions (Konnov mechanism). Effects of diffusion and conduction heat transfer, energy coupled to the cathode layer and gasdynamic compression/expansion are incorporated as quasi-zero-dimensional corrections. The model is exercised using a combination of freeware (Bolsig+) and commercial software (ChemKin-Pro). The model predictions are validated using time-resolved measurements of temperature and N(2) vibrational level populations in nanosecond pulse discharges in air in plane-to-plane and sphere-to-sphere geometry; temperature and OH number density after nanosecond pulse burst discharges in lean H(2)-air, CH(4)-air and C(2)H(4)-air mixtures; and temperature after the nanosecond pulse discharge burst during plasma-assisted ignition of lean H2-mixtures, showing good agreement with the data. The model predictions for OH number density in lean C(3)H(8)-air mixtures differ from the experimental results, over-predicting its absolute value and failing to predict transient OH rise and decay after the discharge burst. The agreement with the data for C(3)H(8)-air is improved considerably if a different conventional hydrocarbon chemistry reaction set (LLNL methane-n-butane flame mechanism) is used. The results of mechanism validation demonstrate its applicability for analysis of plasma chemical oxidation and ignition of low-temperature H(2)-air, CH(4)-air and C(2)H(4)-air mixtures using nanosecond pulse discharges. Kinetic modelling of low-temperature plasma excited propane-air mixtures demonstrates the need for development of a more accurate 'conventional' chemistry mechanism. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Association Between Air Temperature and Cancer Death Rates in Florida: An Ecological Study.

PubMed

Hart, John

2015-01-01

Proponents of global warming predict adverse events due to a slight warming of the planet in the last 100 years. This ecological study tests one of the possible arguments that might support the global warming theory - that it may increase cancer death rates. Thus, average daily air temperature is compared to cancer death rates at the county level in a U.S. state, while controlling for variables of smoking, race, and land elevation. The study revealed that lower cancer death rates were associated with warmer temperatures. Further study is indicated to verify these findings.

Association Between Air Temperature and Cancer Death Rates in Florida

PubMed Central

2015-01-01

Proponents of global warming predict adverse events due to a slight warming of the planet in the last 100 years. This ecological study tests one of the possible arguments that might support the global warming theory – that it may increase cancer death rates. Thus, average daily air temperature is compared to cancer death rates at the county level in a U.S. state, while controlling for variables of smoking, race, and land elevation. The study revealed that lower cancer death rates were associated with warmer temperatures. Further study is indicated to verify these findings. PMID:26674418

Fitness Effects of Chlorpyrifos in the Damselfly Enallagma cyathigerum Strongly Depend upon Temperature and Food Level and Can Bridge Metamorphosis

PubMed Central

Janssens, Lizanne; Stoks, Robby

2013-01-01

Interactions between pollutants and suboptimal environmental conditions can have severe consequences for the toxicity of pollutants, yet are still poorly understood. To identify patterns across environmental conditions and across fitness-related variables we exposed Enallagma cyathigerum damselfly larvae to the pesticide chlorpyrifos at two food levels or at two temperatures and quantified four fitness-related variables (larval survival, development time, mass at emergence and adult cold resistance). Food level and temperature did not affect survival in the absence of the pesticide, yet the pesticide reduced survival only at the high temperature. Animals reacted to the pesticide by accelerating their development but only at the high food level and at the low temperature; at the low food level, however, pesticide exposure resulted in a slower development. Chlorpyrifos exposure resulted in smaller adults except in animals reared at the high food level. Animals reared at the low food level and at the low temperature had a higher cold resistance which was not affected by the pesticide. In summary our study highlight that combined effects of exposure to chlorpyrifos and the two environmental conditions (i) were mostly interactive and sometimes even reversed in comparison with the effect of the environmental condition in isolation, (ii) strongly differed depending on the fitness-related variable under study, (iii) were not always predictable based on the effect of the environmental condition in isolation, and (iv) bridged metamorphosis depending on which environmental condition was combined with the pesticide thereby potentially carrying over from aquatic to terrestrial ecosystems. These findings are relevant when extrapolating results of laboratory tests done under ideal environmental conditions to natural communities. PMID:23840819

A Comparative study between MPC and PI controller to control vacuum distillation unit for producing LVGO, MVGO, and HVGO

NASA Astrophysics Data System (ADS)

Wahid, A.; Prasetyo, A. P.

2018-03-01

This study describes the selection of controllers in the vacuum distillation unit (VDU) between a model predictive control (MPC) and a proportional-integral (PI) controller by comparing the integral square error (ISE) values. Design of VDU in this simulation is based on modified Metso Automation Inc. scheme. Controlled variables in this study are feed flow rate, feed temperature, top stage pressure, condenser level, bottom stage temperature, LVGO (light vacuum gas oil), MVGO (medium vacuum gas oil), and HVGO (heavy vacuum gas oil) flow rate. As a result, control performance improvements occurred as using MPC compared to PI controllers, when testing a set-point change, of feed flow rate control, feed temperature, top-stage pressure, bottom-stage temperature and flow rate of LVGO, MVGO, and HVGO, respectively, 36%, 6%, 92%, 53%, 90%, 96% and 88%. Only on condenser level control PI performs much better than the MPC. So PI controller is used for level condenser control. While for the test of disturbance rejection, by changing feed flow rate by 10%, there is improvement of control performance using MPC compared to PI controller on feed temperature control, top-stage pressure, bottom-stage temperature and flow rate LVGO, MVGO and HVGO 0.3%, 0.7%, 14%, 2.7%, 10.6% and 4.3%, respectively.

Lethal and sub-lethal responses of the biogenic reef forming polychaete Sabellaria alveolata to aqueous chlorine and temperature.

PubMed

Last, K S; Hendrick, V J; Beveridge, C M; Roberts, D A; Wilding, T A

2016-06-01

Sabellaria alveolata, a reef-forming marine polychaete, was exposed to aqueous chlorine which is routinely used as an anti-fouling agent in power station cooling water. Worms were treated to a range of chlorination levels (0, 0.02, 0.1 and 0.5 mg l(-1) Total Residual Oxidant referred to as control, low, intermediate and high TRO) at mean and maximum summer temperatures (18 and 23 °C respectively). Overall mortality was relatively low, however a combination of high temperature and intermediate and high TRO resulted in a significant increase in mortality compared to the control and low TRO treatments. In contrast the extension of dwelling tubes was reduced at high TRO, but increased at low and intermediate TRO levels relative to the controls independent of temperature. Finally, tube strength was found to decrease with increasing TRO, again independent of temperature. On the basis of these findings, S. alveolata can be considered tolerant of one month exposures to low TRO at water temperatures up to and including the summer maxima for southern UK waters. However, at higher TRO levels and during warm weather, high mortality would be predicted. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Electronic clinical predictive thermometer using logarithm for temperature prediction

NASA Technical Reports Server (NTRS)

Cambridge, Vivien J. (Inventor); Koger, Thomas L. (Inventor); Nail, William L. (Inventor); Diaz, Patrick (Inventor)

1998-01-01

A thermometer that rapidly predicts body temperature based on the temperature signals received from a temperature sensing probe when it comes into contact with the body. The logarithms of the differences between the temperature signals in a selected time frame are determined. A line is fit through the logarithms and the slope of the line is used as a system time constant in predicting the final temperature of the body. The time constant in conjunction with predetermined additional constants are used to compute the predicted temperature. Data quality in the time frame is monitored and if unacceptable, a different time frame of temperature signals is selected for use in prediction. The processor switches to a monitor mode if data quality over a limited number of time frames is unacceptable. Determining the start time on which the measurement time frame for prediction is based is performed by summing the second derivatives of temperature signals over time frames. When the sum of second derivatives in a particular time frame exceeds a threshold, the start time is established.

Predicting future thermal habitat suitability of competing native and invasive fish species: from metabolic scope to oceanographic modelling.

PubMed

Marras, Stefano; Cucco, Andrea; Antognarelli, Fabio; Azzurro, Ernesto; Milazzo, Marco; Bariche, Michel; Butenschön, Momme; Kay, Susan; Di Bitetto, Massimiliano; Quattrocchi, Giovanni; Sinerchia, Matteo; Domenici, Paolo

2015-01-01

Global increase in sea temperatures has been suggested to facilitate the incoming and spread of tropical invaders. The increasing success of these species may be related to their higher physiological performance compared with indigenous ones. Here, we determined the effect of temperature on the aerobic metabolic scope (MS) of two herbivorous fish species that occupy a similar ecological niche in the Mediterranean Sea: the native salema (Sarpa salpa) and the invasive marbled spinefoot (Siganus rivulatus). Our results demonstrate a large difference in the optimal temperature for aerobic scope between the salema (21.8°C) and the marbled spinefoot (29.1°C), highlighting the importance of temperature in determining the energy availability and, potentially, the distribution patterns of the two species. A modelling approach based on a present-day projection and a future scenario for oceanographic conditions was used to make predictions about the thermal habitat suitability (THS, an index based on the relationship between MS and temperature) of the two species, both at the basin level (the whole Mediterranean Sea) and at the regional level (the Sicilian Channel, a key area for the inflow of invasive species from the Eastern to the Western Mediterranean Sea). For the present-day projection, our basin-scale model shows higher THS of the marbled spinefoot than the salema in the Eastern compared with the Western Mediterranean Sea. However, by 2050, the THS of the marbled spinefoot is predicted to increase throughout the whole Mediterranean Sea, causing its westward expansion. Nevertheless, the regional-scale model suggests that the future thermal conditions of Western Sicily will remain relatively unsuitable for the invasive species and could act as a barrier for its spread westward. We suggest that metabolic scope can be used as a tool to evaluate the potential invasiveness of alien species and the resilience to global warming of native species.

Prediction of brain tissue temperature using near-infrared spectroscopy.

PubMed

Holper, Lisa; Mitra, Subhabrata; Bale, Gemma; Robertson, Nicola; Tachtsidis, Ilias

2017-04-01

Broadband near-infrared spectroscopy (NIRS) can provide an endogenous indicator of tissue temperature based on the temperature dependence of the water absorption spectrum. We describe a first evaluation of the calibration and prediction of brain tissue temperature obtained during hypothermia in newborn piglets (animal dataset) and rewarming in newborn infants (human dataset) based on measured body (rectal) temperature. The calibration using partial least squares regression proved to be a reliable method to predict brain tissue temperature with respect to core body temperature in the wavelength interval of 720 to 880 nm with a strong mean predictive power of [Formula: see text] (animal dataset) and [Formula: see text] (human dataset). In addition, we applied regression receiver operating characteristic curves for the first time to evaluate the temperature prediction, which provided an overall mean error bias between NIRS predicted brain temperature and body temperature of [Formula: see text] (animal dataset) and [Formula: see text] (human dataset). We discuss main methodological aspects, particularly the well-known aspect of over- versus underestimation between brain and body temperature, which is relevant for potential clinical applications.

Ecosystem response to climatic variables - air temperature and precipitation: How can these variables alter plant productions in C4-grass dominant ecosystem?

NASA Astrophysics Data System (ADS)

Jung, C. G.; Jiang, L.; Luo, Y.

2017-12-01

Understanding net primary production (NPP) response to the key climatic variables, temperature and precipitation, is essential since the response could be represented by one of future consequences from ecosystem responses. Under future climatic warming, fluctuating precipitation is expected. In addition, NPP solely could not explain whole ecosystem response; therefore, not only NPP, but also above- and below-ground NPP (ANPP and BNPP, respectively) need to be examined. This examination needs to include how the plant productions response along temperature and precipitation gradients. Several studies have examined the response of NPP against each of single climatic variable, but understanding the response of ANPP and BNPP to the multiple variables is notably poor. In this study, we used the plant productions data (NPP, ANPP, and BNPP) with climatic variables, i.e., air temperature and precipitation, from 1999 to 2015 under warming and clipping treatments (mimicking hay-harvesting) in C4-grass dominant ecosystem located in central Oklahoma, United States. Firstly, we examined the nonlinear relationships with the climatic variables for NPP, ANPP and BNPP; and then predicted possible responses in the temperature - precipitation space by using a linear mixed effect model. Nonlinearities of NPP, ANPP and BNPP to the climatic variables have been found to show unimodal curves, and nonlinear models have better goodness of fit as shown lower Akaike information criterion (AIC) than linear models. Optimum condition for NPP is represented at high temperature and precipitation level whereas BNPP is maximized at moderate precipitation levels while ANPP has same range of NPP's optimum condition. Clipping significantly reduced ANPP while there was no clipping effect on NPP and BNPP. Furthermore, inclining NPP and ANPP have shown in a range from moderate to high precipitation level with increasing temperature while inclining pattern for BNPP was observed in moderate precipitation level. Overall, the C4-grass dominant ecosystem has a potential for considerable increases in NPP in hotter and wetter conditions as shown a range from moderate to high temperature and precipitation levels; ANPP has peaked at the high temperature and precipitation level, but maximum BNPP needs moderate precipitation level and high temperature.

77 FR 21721 - Sierra National Forest, Bass Lake Ranger District, California, Whisky Ecosystem Restoration Project

Federal Register 2010, 2011, 2012, 2013, 2014

2012-04-11

... to predicted warmer temperatures and longer periods of depleted soil moisture. Stocking levels (stand... ecological processes, biodiversity, wildlife habitat, and structural heterogeneity. The impacts of past... culturally gathered plant material; Protect the historic values and characteristics of archaeological and...

Improving groundwater predictions utilizing seasonal precipitation forecasts from general circulation models forced with sea surface temperature forecasts

USGS Publications Warehouse

Almanaseer, Naser; Sankarasubramanian, A.; Bales, Jerad

2014-01-01

Recent studies have found a significant association between climatic variability and basin hydroclimatology, particularly groundwater levels, over the southeast United States. The research reported in this paper evaluates the potential in developing 6-month-ahead groundwater-level forecasts based on the precipitation forecasts from ECHAM 4.5 General Circulation Model Forced with Sea Surface Temperature forecasts. Ten groundwater wells and nine streamgauges from the USGS Groundwater Climate Response Network and Hydro-Climatic Data Network were selected to represent groundwater and surface water flows, respectively, having minimal anthropogenic influences within the Flint River Basin in Georgia, United States. The writers employ two low-dimensional models [principle component regression (PCR) and canonical correlation analysis (CCA)] for predicting groundwater and streamflow at both seasonal and monthly timescales. Three modeling schemes are considered at the beginning of January to predict winter (January, February, and March) and spring (April, May, and June) streamflow and groundwater for the selected sites within the Flint River Basin. The first scheme (model 1) is a null model and is developed using PCR for every streamflow and groundwater site using previous 3-month observations (October, November, and December) available at that particular site as predictors. Modeling schemes 2 and 3 are developed using PCR and CCA, respectively, to evaluate the role of precipitation forecasts in improving monthly and seasonal groundwater predictions. Modeling scheme 3, which employs a CCA approach, is developed for each site by considering observed groundwater levels from nearby sites as predictands. The performance of these three schemes is evaluated using two metrics (correlation coefficient and relative RMS error) by developing groundwater-level forecasts based on leave-five-out cross-validation. Results from the research reported in this paper show that using precipitation forecasts in climate models improves the ability to predict the interannual variability of winter and spring streamflow and groundwater levels over the basin. However, significant conditional bias exists in all the three modeling schemes, which indicates the need to consider improved modeling schemes as well as the availability of longer time-series of observed hydroclimatic information over the basin.

A creep cavity growth model for creep-fatigue life prediction of a unidirectional W/Cu composite

NASA Astrophysics Data System (ADS)

Kim, Young-Suk; Verrilli, Michael J.; Halford, Gary R.

1992-05-01

A microstructural model was developed to predict creep-fatigue life in a (0)(sub 4), 9 volume percent tungsten fiber-reinforced copper matrix composite at the temperature of 833 K. The mechanism of failure of the composite is assumed to be governed by the growth of quasi-equilibrium cavities in the copper matrix of the composite, based on the microscopically observed failure mechanisms. The methodology uses a cavity growth model developed for prediction of creep fracture. Instantaneous values of strain rate and stress in the copper matrix during fatigue cycles were calculated and incorporated in the model to predict cyclic life. The stress in the copper matrix was determined by use of a simple two-bar model for the fiber and matrix during cyclic loading. The model successfully predicted the composite creep-fatigue life under tension-tension cyclic loading through the use of this instantaneous matrix stress level. Inclusion of additional mechanisms such as cavity nucleation, grain boundary sliding, and the effect of fibers on matrix-stress level would result in more generalized predictions of creep-fatigue life.

A creep cavity growth model for creep-fatigue life prediction of a unidirectional W/Cu composite

NASA Technical Reports Server (NTRS)

Kim, Young-Suk; Verrilli, Michael J.; Halford, Gary R.

1992-01-01

A microstructural model was developed to predict creep-fatigue life in a (0)(sub 4), 9 volume percent tungsten fiber-reinforced copper matrix composite at the temperature of 833 K. The mechanism of failure of the composite is assumed to be governed by the growth of quasi-equilibrium cavities in the copper matrix of the composite, based on the microscopically observed failure mechanisms. The methodology uses a cavity growth model developed for prediction of creep fracture. Instantaneous values of strain rate and stress in the copper matrix during fatigue cycles were calculated and incorporated in the model to predict cyclic life. The stress in the copper matrix was determined by use of a simple two-bar model for the fiber and matrix during cyclic loading. The model successfully predicted the composite creep-fatigue life under tension-tension cyclic loading through the use of this instantaneous matrix stress level. Inclusion of additional mechanisms such as cavity nucleation, grain boundary sliding, and the effect of fibers on matrix-stress level would result in more generalized predictions of creep-fatigue life.

Formability analysis of aluminum alloy sheets at elevated temperatures with numerical simulation based on the M-K method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bagheriasl, Reza; Ghavam, Kamyar; Worswick, Michael

2011-05-04

The effect of temperature on formability of aluminum alloy sheet is studied by developing the Forming Limit Diagrams, FLD, for aluminum alloy 3000-series using the Marciniak and Kuczynski technique by numerical simulation. The numerical model is conducted in LS-DYNA and incorporates the Barlat's YLD2000 anisotropic yield function and the temperature dependant Bergstrom hardening law. Three different temperatures; room temperature, 250 deg. C and 300 deg. C, are studied. For each temperature case, various loading conditions are applied to the M-K defect model. The effect of the material anisotropy is considered by varying the defect angle. A simplified failure criterion ismore » used to predict the onset of necking. Minor and major strains are obtained from the simulations and plotted for each temperature level. It is demonstrated that temperature improves the forming limit of aluminum 3000-series alloy sheet.« less

Modeling the growth of Salmonella in raw poultry stored under aerobic conditions.

PubMed

Dominguez, Silvia A; Schaffner, Donald W

2008-12-01

The presence of Salmonella in raw poultry is a well-recognized risk factor for foodborne illness. The objective of this study was to develop and validate a mathematical model that predicts the growth of Salmonella in raw poultry stored under aerobic conditions at a variety of temperatures. One hundred twelve Salmonella growth rates were extracted from 12 previously published studies. These growth rates were used to develop a square-root model relating the growth rate of Salmonella to storage temperature. Model predictions were compared to growth rate measurements collected in our laboratory for four poultry-specific Salmonella strains (two antibiotic-resistant and two nonresistant strains) inoculated onto raw chicken tenderloins. Chicken was inoculated at two levels (10(3) CFU/cm2 and < or = 10 CFU/cm2) and incubated at temperatures ranging from 10 to 37 degrees C. Visual inspection of the data, bias and accuracy factors, and comparison with two other published models were used to analyze the performance of the new model. Neither antibiotic resistance nor inoculum size affected Salmonella growth rates. The presence of spoilage microflora did not appear to slow the growth of Salmonella. Our model provided intermediate predicted growth rates when compared with the two other published models. Our model predicted slightly faster growth rates than those observed in inoculated chicken in the temperature range of 10 to 28 degrees C but slightly slower growth rates than those observed between 30 and 37 degrees C. Slightly negative bias factors were obtained in every case (-5 to -3%); however, application of the model may be considered fail-safe for storage temperatures below 28 degrees C.

Lethal Temperature for Pinewood Nematode, Bursaphelenchus xylophilus, in Infested Wood Using Microwave Energy

PubMed Central

Hoover, Kelli; Uzunovic, Adnan; Gething, Brad; Dale, Angela; Leung, Karen; Ostiguy, Nancy; Janowiak, John J.

2010-01-01

To reduce the risks associated with global transport of wood infested with pinewood nematode Bursaphelenchus xylophilus, microwave irradiation was tested at 14 temperatures in replicated wood samples to determine the temperature that would kill 99.9968% of nematodes in a sample of ≥ 100,000 organisms, meeting a level of efficacy of Probit 9. Treatment of these heavily infested wood samples (mean of > 1,000 nematodes/g of sapwood) produced 100% mortality at 56 °C and above, held for 1 min. Because this “brute force” approach to Probit 9 treats individual nematodes as the observational unit regardless of the number of wood samples it takes to treat this number of organisms, we also used a modeling approach. The best fit was to a Probit function, which estimated lethal temperature at 62.2 (95% confidence interval 59.0-70.0) °C. This discrepancy between the observed and predicted temperature to achieve Probit 9 efficacy may have been the result of an inherently limited sample size when predicting the true mean from the total population. The rate of temperature increase in the small wood samples (rise time) did not affect final nematode mortality at 56 °C. In addition, microwave treatment of industrial size, infested wood blocks killed 100% of > 200,000 nematodes at ≥ 56 °C held for 1 min in replicated wood samples. The 3rd-stage juvenile (J3) of the nematode, that is resistant to cold temperatures and desiccation, was abundant in our wood samples and did not show any resistance to microwave treatment. Regression analysis of internal wood temperatures as a function of surface temperature produced a regression equation that could be used with a relatively high degree of accuracy to predict internal wood temperatures, under the conditions of this study. These results provide strong evidence of the ability of microwave treatment to successfully eradicate B. xylophilus in infested wood at or above 56 °C held for 1 min. PMID:22736846

A Study of Pattern Prediction in the Monitoring Data of Earthen Ruins with the Internet of Things.

PubMed

Xiao, Yun; Wang, Xin; Eshragh, Faezeh; Wang, Xuanhong; Chen, Xiaojiang; Fang, Dingyi

2017-05-11

An understanding of the changes of the rammed earth temperature of earthen ruins is important for protection of such ruins. To predict the rammed earth temperature pattern using the air temperature pattern of the monitoring data of earthen ruins, a pattern prediction method based on interesting pattern mining and correlation, called PPER, is proposed in this paper. PPER first finds the interesting patterns in the air temperature sequence and the rammed earth temperature sequence. To reduce the processing time, two pruning rules and a new data structure based on an R-tree are also proposed. Correlation rules between the air temperature patterns and the rammed earth temperature patterns are then mined. The correlation rules are merged into predictive rules for the rammed earth temperature pattern. Experiments were conducted to show the accuracy of the presented method and the power of the pruning rules. Moreover, the Ming Dynasty Great Wall dataset was used to examine the algorithm, and six predictive rules from the air temperature to rammed earth temperature based on the interesting patterns were obtained, with the average hit rate reaching 89.8%. The PPER and predictive rules will be useful for rammed earth temperature prediction in protection of earthen ruins.

A general strategy for performing temperature-programming in high performance liquid chromatography--prediction of segmented temperature gradients.

PubMed

Wiese, Steffen; Teutenberg, Thorsten; Schmidt, Torsten C

2011-09-28

In the present work it is shown that the linear elution strength (LES) model which was adapted from temperature-programming gas chromatography (GC) can also be employed to predict retention times for segmented-temperature gradients based on temperature-gradient input data in liquid chromatography (LC) with high accuracy. The LES model assumes that retention times for isothermal separations can be predicted based on two temperature gradients and is employed to calculate the retention factor of an analyte when changing the start temperature of the temperature gradient. In this study it was investigated whether this approach can also be employed in LC. It was shown that this approximation cannot be transferred to temperature-programmed LC where a temperature range from 60°C up to 180°C is investigated. Major relative errors up to 169.6% were observed for isothermal retention factor predictions. In order to predict retention times for temperature gradients with different start temperatures in LC, another relationship is required to describe the influence of temperature on retention. Therefore, retention times for isothermal separations based on isothermal input runs were predicted using a plot of the natural logarithm of the retention factor vs. the inverse temperature and a plot of the natural logarithm of the retention factor vs. temperature. It could be shown that a plot of lnk vs. T yields more reliable isothermal/isocratic retention time predictions than a plot of lnk vs. 1/T which is usually employed. Hence, in order to predict retention times for temperature-gradients with different start temperatures in LC, two temperature gradient and two isothermal measurements have been employed. In this case, retention times can be predicted with a maximal relative error of 5.5% (average relative error: 2.9%). In comparison, if the start temperature of the simulated temperature gradient is equal to the start temperature of the input data, only two temperature-gradient measurements are required. Under these conditions, retention times can be predicted with a maximal relative error of 4.3% (average relative error: 2.2%). As an example, the systematic method development for an isothermal as well as a temperature gradient separation of selected sulfonamides by means of the adapted LES model is demonstrated using a pure water mobile phase. Both methods are compared and it is shown that the temperature-gradient separation provides some advantages over the isothermal separation in terms of limits of detection and analysis time. Copyright © 2011 Elsevier B.V. All rights reserved.

Indirect downscaling of global circulation model data based on atmospheric circulation and temperature for projections of future precipitation in hourly resolution

NASA Astrophysics Data System (ADS)

Beck, F.; Bárdossy, A.

2013-07-01

Many hydraulic applications like the design of urban sewage systems require projections of future precipitation in high temporal resolution. We developed a method to predict the regional distribution of hourly precipitation sums based on daily mean sea level pressure and temperature data from a Global Circulation Model. It is an indirect downscaling method avoiding uncertain precipitation data from the model. It is based on a fuzzy-logic classification of atmospheric circulation patterns (CPs) that is further subdivided by means of the average daily temperature. The observed empirical distributions at 30 rain gauges to each CP-temperature class are assumed as constant and used for projections of the hourly precipitation sums in the future. The method was applied to the CP-temperature sequence derived from the 20th century run and the scenario A1B run of ECHAM5. According to ECHAM5, the summers in southwest Germany will become progressively drier. Nevertheless, the frequency of the highest hourly precipitation sums will increase. According to the predictions, estival water stress and the risk of extreme hourly precipitation will both increase simultaneously during the next decades.

An Improved Model of Cryogenic Propellant Stratification in a Rotating, Reduced Gravity Environment

NASA Technical Reports Server (NTRS)

Oliveira, Justin; Kirk, Daniel R.; Schallhorn, Paul A.; Piquero, Jorge L.; Campbell, Mike; Chase, Sukhdeep

2007-01-01

This paper builds on a series of analytical literature models used to predict thermal stratification within rocket propellant tanks. The primary contribution to the literature is to add the effect of tank rotation and to demonstrate the influence of rotation on stratification times and temperatures. This work also looks levels of thermal stratification for generic propellant tanks (cylindrical shapes) over a parametric range of upper-stage coast times, heating levels, rotation rates, and gravity levels.

Robustness of larval development of intertidal sea urchin species to simulated ocean warming and acidification.

PubMed

García, Eliseba; Hernández, José Carlos; Clemente, Sabrina

2018-08-01

Ocean warming and acidification are the two most significant side effects of carbone dioxide emissions in the world's oceans. By changing water, temperature and pH are the main environmental factors controlling the distribution, physiology, morphology and behaviour of marine invertebrates. This study evaluated the combined effects of predicted high temperature levels, and predicted low pH values, on fertilization and early development stages of the sea urchins Arbacia lixula, Paracentrotus lividus, Sphaerechinus granularis and Diadema africanum. Twelve treatments, combining different temperatures (19, 21, 23 and 25 °C) and pH values (8.1, 7.7 and 7.4 units), were tested in laboratory experiments. All of the tested temperatures and pH values were within the open coast seawater range expected within the next century. We examined fertilization rate, cleavage rate, 3-day larvae survival, and development of the different sea urchin species at set time intervals after insemination. Our results highlight the susceptibility of subtidal species to environmental changes, and the robustness of intertidal species to ocean warming and acidification. Copyright © 2018 Elsevier Ltd. All rights reserved.

PHOTOACOUSTIC NON-DESTRUCTIVE EVALUATION AND IMAGING OF CARIES IN DENTAL SAMPLES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, T.; Dewhurst, R. J.

Dental caries is a disease wherein bacterial processes damage hard tooth structure. Traditional dental radiography has its limitations for detecting early stage caries. In this study, a photoacoustic (PA) imaging system with the near-infrared light source has been applied to postmortem dental samples to obtain 2-D and 3-D images. Imaging results showed that the PA technique can be used to image human teeth caries. For non-destructive photoacoustic evaluation and imaging, the induced temperature and pressure rises within biotissues should not cause physical damage to the tissue. For example, temperature rises above 5 deg. C within live human teeth will causemore » pulpal necrosis. Therefore, several simulations based on the thermoelastic effect have been applied to predict temperature and pressure fields within samples. Predicted temperature levels are below corresponding safety limits, but care is required to avoid nonlinear absorption phenomena. Furthermore, PA imaging results from the phantom provide evidence for high sensitivity, which shows the imaging potential of the PA technique for detecting early stage disease.« less

Coulomb thermal properties and stability of the Io plasma torus

NASA Technical Reports Server (NTRS)

Barbosa, D. D.; Coroniti, F. V.; Eviatar, A.

1983-01-01

Coulomb collisional energy exchange rates are computed for a model of the Io plasma torus consisting of newly created pickup ions, a background of thermally degraded intermediary ions, and a population of cooler electrons. The electrons are collisionally heated by both the pickup ions and background ions and are cooled by electron impact excitation of plasma ions which radiate in the EUV. It is found that a relative concentration of S III pickup ions forbidden S III/electrons = 0.1 with a temperature of 340 eV can deliver energy to the electrons at a rate of 3 x 10 to the -13th erg/cu cm per sec, sufficient to power the EUV emissions in the Io torus. The model predicts a background ion temperature Ti of about 53 eV and an electron temperature Te of about 5.5 eV on the basis of steady-state energy balance relations at Coulomb rates. The model also predicts electron temperature fluctuations at the 30 percent level on a time scale of less than 11 hours, consistent with recent observations of this phenomenon.

Detailed predictions of climate induced changes in the thermal and flow regimes in mountain streams of the Iberian Peninsula

NASA Astrophysics Data System (ADS)

Santiago, José M.; Muñoz-Mas, Rafael; García de Jalón, Diego; Solana, Joaquín; Alonso, Carlos; Martínez-Capel, Francisco; Ribalaygua, Jaime; Pórtoles, Javier; Monjo, Robert

2016-04-01

Streamflow and temperature regimes are well-known to influence on the availability of suitable physical habitat for instream biological communities. General Circulation Models (GCMs) have predicted significant changes in timing and geographic distribution of precipitation and atmospheric temperature for the ongoing century. However, differences in these predictions may arise when focusing on different spatial and temporal scales. Therefore, to perform substantiated mitigation and management actions detailed scales are necessary to adequately forecast the consequent thermal and flow regimes. Regional predictions are relatively abundant but detailed ones, both spatially and temporally, are still scarce. The present study aimed at predicting the effects of climate change on the thermal and flow regime in the Iberian Peninsula, refining the resolution of previous studies. For this purpose, the study encompassed 28 sites at eight different mountain rivers and streams in the central part of the Iberian Peninsula (Spain). The daily flow was modelled using different daily, monthly and quarterly lags of the historical precipitation and temperature time series. These precipitation-runoff models were developed by means of M5 model trees. On the other hand water temperature was modelled at similar time scale by means of nonlinear regression from dedicated site-specific data. The developed models were used to simulate the temperature and flow regime under two Representative Concentration Pathway (RCPs) climate change scenarios (RCP 4.5 and RCP 8.5) until the end of the present century by considering nine different GCMs, which were pertinently downscaled. The precipitation-runoff models achieved high accuracy (NSE>0.7), especially in regards of the low flows of the historical series. Results concomitantly forecasted flow reductions between 7 and 17 % (RCP4.5) and between 8 and 49% (RCP8.5) of the annual average in the most cases, being variable the magnitude and timing at each site. The largest predicted changes will occur in summer and the complete depletion of some river segments was forecasted. Winter was the only season predicted flows to remain mostly unaffected by climate change. Mean annual stream temperature was predicted to experience heavy increases, especially during the second half of the century, varying from 0.3 to 1.6°C (RCP4.5), and 0.8 to 4.0°C (RCP8.5). Annual maximum and minimum average temperature increases were predicted to be between 0.1 and 1.5°C (RCP4.5) and between 0.2 and 3.0°C (RCP8.5), and between 0.4 and 1.8°C (RCP4.5) and between 1.1 and 4.5°C (RCP8.5), respectively. The most important increases were predicted to occur in summer while winter will experience the lesser ones. Geology attributable differences on thermal regime were observed between rivers. These results suggested the exacerbation of the principal characteristics of the Mediterranean climate-induced flow regimes with increased summer water temperatures and reduced low flows. Consequently, the synergistic effects of these climate induced changes may significantly impacts instream communities. Predictions of this study will be useful for designing habitat managing strategies for climate change adaptation at the local level. The revealed particularities reinforce the convenience of refining local predictions to design effective management policies.

Validation of standard ASTM F2732 and comparison with ISO 11079 with respect to comfort temperature ratings for cold protective clothing.

PubMed

Gao, Chuansi; Lin, Li-Yen; Halder, Amitava; Kuklane, Kalev; Holmér, Ingvar

2015-01-01

American standard ASTM F2732 estimates the lowest environmental temperature for thermal comfort for cold weather protective clothing. International standard ISO 11079 serves the same purpose but expresses cold stress in terms of required clothing insulation for a given cold climate. The objective of this study was to validate and compare the temperature ratings using human subject tests at two levels of metabolic rates (2 and 4 MET corresponding to 116.4 and 232.8 W/m(2)). Nine young and healthy male subjects participated in the cold exposure at 3.4 and -30.6 °C. The results showed that both standards predict similar temperature ratings for an intrinsic clothing insulation of 1.89 clo and for 2 MET activity. The predicted temperature rating for 2 MET activity is consistent with test subjects' thermophysiological responses, perceived thermal sensation and thermal comfort. For 4 MET activity, however, the whole body responses were on the cold side, particularly the responses of the extremities. ASTM F2732 is also limited due to its omission and simplification of three climatic variables (air velocity, radiant temperature and relative humidity) and exposure time in the cold which are of practical importance. Copyright © 2014 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Survival, growth and reproduction of non-indigenous Nile tilapia, Oreochromis niloticus (Linnaeus 1758). I. Physiological capabilities in various temperatures and salinities

USGS Publications Warehouse

Schofield, Pamela J.; Peterson, Mark S.; Lowe, Michael R.; Brown-Peterson, Nancy J.; Slack, William T.

2011-01-01

The physiological tolerances of non-native fishes is an integral component of assessing potential invasive risk. Salinity and temperature are environmental variables that limit the spread of many non-native fishes. We hypothesised that combinations of temperature and salinity will interact to affect survival, growth, and reproduction of Nile tilapia, Oreochromis niloticus, introduced into Mississippi, USA. Tilapia withstood acute transfer from fresh water up to a salinity of 20 and survived gradual transfer up to 60 at typical summertime (30°C) temperatures. However, cold temperature (14°C) reduced survival of fish in saline waters ≥10 and increased the incidence of disease in freshwater controls. Although fish were able to equilibrate to saline waters in warm temperatures, reproductive parameters were reduced at salinities ≥30. These integrated responses suggest that Nile tilapia can invade coastal areas beyond their point of introduction. However, successful invasion is subject to two caveats: (1) wintertime survival depends on finding thermal refugia, and (2) reproduction is hampered in regions where salinities are ≥30. These data are vital to predicting the invasion of non-native fishes into coastal watersheds. This is particularly important given the predicted changes in coastal landscapes due to global climate change and sea-level rise.

Links between type E botulism outbreaks, lake levels, and surface water temperatures in Lake Michigan, 1963-2008

USGS Publications Warehouse

Lafrancois, Brenda Moraska; Riley, Stephen C.; Blehert, David S.; Ballmann, Anne E.

2011-01-01

Relationships between large-scale environmental factors and the incidence of type E avian botulism outbreaks in Lake Michigan were examined from 1963 to 2008. Avian botulism outbreaks most frequently occurred in years with low mean annual water levels, and lake levels were significantly lower in outbreak years than in non-outbreak years. Mean surface water temperatures in northern Lake Michigan during the period when type E outbreaks tend to occur (July through September) were significantly higher in outbreak years than in non-outbreak years. Trends in fish populations did not strongly correlate with botulism outbreaks, although botulism outbreaks in the 1960s coincided with high alewife abundance, and recent botulism outbreaks coincided with rapidly increasing round goby abundance. Botulism outbreaks occurred cyclically, and the frequency of outbreaks did not increase over the period of record. Climate change scenarios for the Great Lakes predict lower water levels and warmer water temperatures. As a consequence, the frequency and magnitude of type E botulism outbreaks in the Great Lakes may increase.

Evaluating penalized logistic regression models to predict Heat-Related Electric grid stress days

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bramer, Lisa M.; Rounds, J.; Burleyson, C. D.

Understanding the conditions associated with stress on the electricity grid is important in the development of contingency plans for maintaining reliability during periods when the grid is stressed. In this paper, heat-related grid stress and the relationship with weather conditions were examined using data from the eastern United States. Penalized logistic regression models were developed and applied to predict stress on the electric grid using weather data. The inclusion of other weather variables, such as precipitation, in addition to temperature improved model performance. Several candidate models and combinations of predictive variables were examined. A penalized logistic regression model which wasmore » fit at the operation-zone level was found to provide predictive value and interpretability. Additionally, the importance of different weather variables observed at various time scales were examined. Maximum temperature and precipitation were identified as important across all zones while the importance of other weather variables was zone specific. In conclusion, the methods presented in this work are extensible to other regions and can be used to aid in planning and development of the electrical grid.« less

Evaluating penalized logistic regression models to predict Heat-Related Electric grid stress days

DOE PAGES

Bramer, Lisa M.; Rounds, J.; Burleyson, C. D.; ...

2017-09-22

Understanding the conditions associated with stress on the electricity grid is important in the development of contingency plans for maintaining reliability during periods when the grid is stressed. In this paper, heat-related grid stress and the relationship with weather conditions were examined using data from the eastern United States. Penalized logistic regression models were developed and applied to predict stress on the electric grid using weather data. The inclusion of other weather variables, such as precipitation, in addition to temperature improved model performance. Several candidate models and combinations of predictive variables were examined. A penalized logistic regression model which wasmore » fit at the operation-zone level was found to provide predictive value and interpretability. Additionally, the importance of different weather variables observed at various time scales were examined. Maximum temperature and precipitation were identified as important across all zones while the importance of other weather variables was zone specific. In conclusion, the methods presented in this work are extensible to other regions and can be used to aid in planning and development of the electrical grid.« less

Transient and residual stresses in large castings, taking time effects into account

NASA Astrophysics Data System (ADS)

Thorborg, J.; Klinkhammer, J.; Heitzer, M.

2012-07-01

Casting of large scale steel and iron parts leads to long solidification and cooling times. Solid mechanical calculations for these castings have to take the time scale of the process into account, in order to predict the transient and residual stress levels with a reasonable accuracy. This paper presents a study on the modelling of the thermo-mechanical conditions in the cast material using a unified approach to describe the constitutive behaviour. This means a classical splitting of the mechanical strain into an elastic and an inelastic contribution, where the inelastic strain is only formulated in the deviatoric space in terms of the J2 invariant. At high temperatures, creep is pronounced. Since the cooling time is long, the model includes a type of Norton's power law to integrate the significant contribution of creep to the inelastic strains. At these temperature levels, annealing effects are also dominant and hence no hardening is modelled. However, at intermediate and lower temperature levels, hardening is more pronounced and isotropic hardening is considered. Different hardening models have been studied and selected based on their ability to describe the behaviour at the different temperature levels. At the lower temperature levels, time effects decrease and the formulation reduces to a time independent formulation, like classical J2-flow theory. Several tensile and creep experiments have been made at different temperature levels to provide input data for selecting the appropriate contributions to the material model. The measurements have furthermore been used as input for extracting material data for the model. The numerical model is applied on different industrial examples to verify the agreement between measured and calculated deformations.

Skill of real-time operational forecasts with the APCC multi-model ensemble prediction system during the period 2008-2015

NASA Astrophysics Data System (ADS)

Min, Young-Mi; Kryjov, Vladimir N.; Oh, Sang Myeong; Lee, Hyun-Ju

2017-12-01

This paper assesses the real-time 1-month lead forecasts of 3-month (seasonal) mean temperature and precipitation on a monthly basis issued by the Asia-Pacific Economic Cooperation Climate Center (APCC) for 2008-2015 (8 years, 96 forecasts). It shows the current level of the APCC operational multi-model prediction system performance. The skill of the APCC forecasts strongly depends on seasons and regions that it is higher for the tropics and boreal winter than for the extratropics and boreal summer due to direct effects and remote teleconnections from boundary forcings. There is a negative relationship between the forecast skill and its interseasonal variability for both variables and the forecast skill for precipitation is more seasonally and regionally dependent than that for temperature. The APCC operational probabilistic forecasts during this period show a cold bias (underforecasting of above-normal temperature and overforecasting of below-normal temperature) underestimating a long-term warming trend. A wet bias is evident for precipitation, particularly in the extratropical regions. The skill of both temperature and precipitation forecasts strongly depends upon the ENSO strength. Particularly, the highest forecast skill noted in 2015/2016 boreal winter is associated with the strong forcing of an extreme El Nino event. Meanwhile, the relatively low skill is associated with the transition and/or continuous ENSO-neutral phases of 2012-2014. As a result the skill of real-time forecast for boreal winter season is higher than that of hindcast. However, on average, the level of forecast skill during the period 2008-2015 is similar to that of hindcast.

Development of Design Analysis Methods for C/SiC Composite Structures

NASA Technical Reports Server (NTRS)

Sullivan, Roy M.; Mital, Subodh K.; Murthy, Pappu L. N.; Palko, Joseph L.; Cueno, Jacques C.; Koenig, John R.

2006-01-01

The stress-strain behavior at room temperature and at 1100 C (2000 F) was measured for two carbon-fiber-reinforced silicon carbide (C/SiC) composite materials: a two-dimensional plain-weave quasi-isotropic laminate and a three-dimensional angle-interlock woven composite. Micromechanics-based material models were developed for predicting the response properties of these two materials. The micromechanics based material models were calibrated by correlating the predicted material property values with the measured values. Four-point beam bending sub-element specimens were fabricated with these two fiber architectures and four-point bending tests were performed at room temperature and at 1100 C. Displacements and strains were measured at various locations along the beam and recorded as a function of load magnitude. The calibrated material models were used in concert with a nonlinear finite element solution to simulate the structural response of these two materials in the four-point beam bending tests. The structural response predicted by the nonlinear analysis method compares favorably with the measured response for both materials and for both test temperatures. Results show that the material models scale up fairly well from coupon to subcomponent level.

Reducing Uncertainty in Chemistry Climate Model Predictions of Stratospheric Ozone

NASA Technical Reports Server (NTRS)

Douglass, A. R.; Strahan, S. E.; Oman, L. D.; Stolarski, R. S.

2014-01-01

Chemistry climate models (CCMs) are used to predict the future evolution of stratospheric ozone as ozone-depleting substances decrease and greenhouse gases increase, cooling the stratosphere. CCM predictions exhibit many common features, but also a broad range of values for quantities such as year of ozone-return-to-1980 and global ozone level at the end of the 21st century. Multiple linear regression is applied to each of 14 CCMs to separate ozone response to chlorine change from that due to climate change. We show that the sensitivity of lower atmosphere ozone to chlorine change deltaO3/deltaCly is a near linear function of partitioning of total inorganic chlorine (Cly) into its reservoirs; both Cly and its partitioning are controlled by lower atmospheric transport. CCMs with realistic transport agree with observations for chlorine reservoirs and produce similar ozone responses to chlorine change. After 2035 differences in response to chlorine contribute little to the spread in CCM results as the anthropogenic contribution to Cly becomes unimportant. Differences among upper stratospheric ozone increases due to temperature decreases are explained by differences in ozone sensitivity to temperature change deltaO3/deltaT due to different contributions from various ozone loss processes, each with their own temperature dependence. In the lower atmosphere, tropical ozone decreases caused by a predicted speed-up in the Brewer-Dobson circulation may or may not be balanced by middle and high latitude increases, contributing most to the spread in late 21st century predictions.

Predicting patterns of vulnerability to climate change in near coastal species using an algorithm-based risk assessment framework

EPA Science Inventory

Near-coastal (0-200 depth) ecosystems and species are under threat from increasing temperatures, ocean acidification, and sea level rise. However, species vary in their vulnerability to specific climatic changes and climate impacts will vary geographically. For management to resp...

Mapping Environmental Suitability for Malaria Transmission, Greece

PubMed Central

Sudre, Bertrand; Rossi, Massimiliano; Van Bortel, Wim; Danis, Kostas; Baka, Agoritsa; Vakalis, Nikos

2013-01-01

During 2009–2012, Greece experienced a resurgence of domestic malaria transmission. To help guide malaria response efforts, we used spatial modeling to characterize environmental signatures of areas suitable for transmission. Nonlinear discriminant analysis indicated that sea-level altitude and land-surface temperature parameters are predictive in this regard. PMID:23697370

Environmental interactions that influence secondary metabolism and development in the saprophytic crop pathogen Aspergillus flavus

USDA-ARS?s Scientific Manuscript database

Aspergillus flavus is a pathogenic and opportunistic fungus that can infect several crops of agricultural importance and has the potential to produce carcinogenic mycotoxins such as aflatoxin. Predicted changes in global temperatures, precipitation patterns and carbon dioxide levels are expected to ...

The Icarus challenge - Predicting vulnerability to climate change using an algorithm-based species’ trait approach

EPA Science Inventory

Like Icarus, the world’s ecological resources are “flying too close” to the sun, and climate change will impact near-coastal species through temperature, sea-level rise, and ocean acidification and indirectly through changes in invasive species and land-use patt...

TRAIT-BASED FRAMEWORK TO PREDICTING RELATIVE VULNERABILITY TO CLIMATE CHANGE IN NEAR-COASTAL SPECIES AND HABITAT

EPA Science Inventory

Like Icarus, near-coastal species are “flying too close” to the sun, and are being impacted by climate-induced changes in air and ocean temperature, precipitation, salinity, ocean pH, sea level rise, and nonindigenous species. Sound management requires knowledge of wh...

Temperature sensing in Yersinia pestis: translation of the LcrF activator protein is thermally regulated.

PubMed Central

Hoe, N P; Goguen, J D

1993-01-01

The lcrF gene of Yersinia pestis encodes a transcription activator responsible for inducing expression of several virulence-related proteins in response to temperature. The mechanism of this thermoregulation was investigated. An lcrF clone was found to produce much lower levels of LcrF protein at 26 than at 37 degrees C in Y. pestis, although it was transcribed at similar levels at both temperatures. High-level T7 polymerase-directed transcription of the lcrF gene in Escherichia coli also resulted in temperature-dependent production of the LcrF protein. Pulse-chase experiments showed that the LcrF protein was stable at 26 and 37 degrees C, suggesting that translation rate or message degradation is thermally controlled. The lcrF mRNA appears to be highly unstable and could not be reliably detected in Y. pestis. Insertion of the lcrF gene into plasmid pET4a, which produces high levels of plasmid-length RNA, aided detection of lcrF-specific message in E. coli. Comparison of the amount of LcrF protein produced per unit of message at 26 and 37 degrees C indicated that the efficiency of translation of lcrF message increased with temperature. mRNA secondary structure predictions suggest that the lcrF Shine-Dalgarno sequence is sequestered in a stem-loop. A model in which decreased stability of this stem-loop with increasing temperature leads to increased efficiency of translation initiation of lcrF message is presented. Images PMID:7504666

Reconciling the temperature dependence of respiration across timescales and ecosystem types.

PubMed

Yvon-Durocher, Gabriel; Caffrey, Jane M; Cescatti, Alessandro; Dossena, Matteo; del Giorgio, Paul; Gasol, Josep M; Montoya, José M; Pumpanen, Jukka; Staehr, Peter A; Trimmer, Mark; Woodward, Guy; Allen, Andrew P

2012-07-26

Ecosystem respiration is the biotic conversion of organic carbon to carbon dioxide by all of the organisms in an ecosystem, including both consumers and primary producers. Respiration exhibits an exponential temperature dependence at the subcellular and individual levels, but at the ecosystem level respiration can be modified by many variables including community abundance and biomass, which vary substantially among ecosystems. Despite its importance for predicting the responses of the biosphere to climate change, it is as yet unknown whether the temperature dependence of ecosystem respiration varies systematically between aquatic and terrestrial environments. Here we use the largest database of respiratory measurements yet compiled to show that the sensitivity of ecosystem respiration to seasonal changes in temperature is remarkably similar for diverse environments encompassing lakes, rivers, estuaries, the open ocean and forested and non-forested terrestrial ecosystems, with an average activation energy similar to that of the respiratory complex (approximately 0.65 electronvolts (eV)). By contrast, annual ecosystem respiration shows a substantially greater temperature dependence across aquatic (approximately 0.65 eV) versus terrestrial ecosystems (approximately 0.32 eV) that span broad geographic gradients in temperature. Using a model derived from metabolic theory, these findings can be reconciled by similarities in the biochemical kinetics of metabolism at the subcellular level, and fundamental differences in the importance of other variables besides temperature—such as primary productivity and allochthonous carbon inputs—on the structure of aquatic and terrestrial biota at the community level.

Sensitivity of decomposition rates of soil organic matter with respect to simultaneous changes in temperature and moisture

NASA Astrophysics Data System (ADS)

Sierra, Carlos A.; Trumbore, Susan E.; Davidson, Eric A.; Vicca, Sara; Janssens, I.

2015-03-01

The sensitivity of soil organic matter decomposition to global environmental change is a topic of prominent relevance for the global carbon cycle. Decomposition depends on multiple factors that are being altered simultaneously as a result of global environmental change; therefore, it is important to study the sensitivity of the rates of soil organic matter decomposition with respect to multiple and interacting drivers. In this manuscript, we present an analysis of the potential response of decomposition rates to simultaneous changes in temperature and moisture. To address this problem, we first present a theoretical framework to study the sensitivity of soil organic matter decomposition when multiple driving factors change simultaneously. We then apply this framework to models and data at different levels of abstraction: (1) to a mechanistic model that addresses the limitation of enzyme activity by simultaneous effects of temperature and soil water content, the latter controlling substrate supply and oxygen concentration for microbial activity; (2) to different mathematical functions used to represent temperature and moisture effects on decomposition in biogeochemical models. To contrast model predictions at these two levels of organization, we compiled different data sets of observed responses in field and laboratory studies. Then we applied our conceptual framework to: (3) observations of heterotrophic respiration at the ecosystem level; (4) laboratory experiments looking at the response of heterotrophic respiration to independent changes in moisture and temperature; and (5) ecosystem-level experiments manipulating soil temperature and water content simultaneously.

Analysis of uncertainties in turbine metal temperature predictions

NASA Technical Reports Server (NTRS)

Stepka, F. S.

1980-01-01

An analysis was conducted to examine the extent to which various factors influence the accuracy of analytically predicting turbine blade metal temperatures and to determine the uncertainties in these predictions for several accuracies of the influence factors. The advanced turbofan engine gas conditions of 1700 K and 40 atmospheres were considered along with those of a highly instrumented high temperature turbine test rig and a low temperature turbine rig that simulated the engine conditions. The analysis showed that the uncertainty in analytically predicting local blade temperature was as much as 98 K, or 7.6 percent of the metal absolute temperature, with current knowledge of the influence factors. The expected reductions in uncertainties in the influence factors with additional knowledge and tests should reduce the uncertainty in predicting blade metal temperature to 28 K, or 2.1 percent of the metal absolute temperature.

Prediction of brain tissue temperature using near-infrared spectroscopy

PubMed Central

Holper, Lisa; Mitra, Subhabrata; Bale, Gemma; Robertson, Nicola; Tachtsidis, Ilias

2017-01-01

Abstract. Broadband near-infrared spectroscopy (NIRS) can provide an endogenous indicator of tissue temperature based on the temperature dependence of the water absorption spectrum. We describe a first evaluation of the calibration and prediction of brain tissue temperature obtained during hypothermia in newborn piglets (animal dataset) and rewarming in newborn infants (human dataset) based on measured body (rectal) temperature. The calibration using partial least squares regression proved to be a reliable method to predict brain tissue temperature with respect to core body temperature in the wavelength interval of 720 to 880 nm with a strong mean predictive power of R2=0.713±0.157 (animal dataset) and R2=0.798±0.087 (human dataset). In addition, we applied regression receiver operating characteristic curves for the first time to evaluate the temperature prediction, which provided an overall mean error bias between NIRS predicted brain temperature and body temperature of 0.436±0.283°C (animal dataset) and 0.162±0.149°C (human dataset). We discuss main methodological aspects, particularly the well-known aspect of over- versus underestimation between brain and body temperature, which is relevant for potential clinical applications. PMID:28630878

A transported probability density function/photon Monte Carlo method for high-temperature oxy-natural gas combustion with spectral gas and wall radiation

NASA Astrophysics Data System (ADS)

Zhao, X. Y.; Haworth, D. C.; Ren, T.; Modest, M. F.

2013-04-01

A computational fluid dynamics model for high-temperature oxy-natural gas combustion is developed and exercised. The model features detailed gas-phase chemistry and radiation treatments (a photon Monte Carlo method with line-by-line spectral resolution for gas and wall radiation - PMC/LBL) and a transported probability density function (PDF) method to account for turbulent fluctuations in composition and temperature. The model is first validated for a 0.8 MW oxy-natural gas furnace, and the level of agreement between model and experiment is found to be at least as good as any that has been published earlier. Next, simulations are performed with systematic model variations to provide insight into the roles of individual physical processes and their interplay in high-temperature oxy-fuel combustion. This includes variations in the chemical mechanism and the radiation model, and comparisons of results obtained with versus without the PDF method to isolate and quantify the effects of turbulence-chemistry interactions and turbulence-radiation interactions. In this combustion environment, it is found to be important to account for the interconversion of CO and CO2, and radiation plays a dominant role. The PMC/LBL model allows the effects of molecular gas radiation and wall radiation to be clearly separated and quantified. Radiation and chemistry are tightly coupled through the temperature, and correct temperature prediction is required for correct prediction of the CO/CO2 ratio. Turbulence-chemistry interactions influence the computed flame structure and mean CO levels. Strong local effects of turbulence-radiation interactions are found in the flame, but the net influence of TRI on computed mean temperature and species profiles is small. The ultimate goal of this research is to simulate high-temperature oxy-coal combustion, where accurate treatments of chemistry, radiation and turbulence-chemistry-particle-radiation interactions will be even more important.

Behavioral responses of Atlantic cod to sea temperature changes.

PubMed

Freitas, Carla; Olsen, Esben Moland; Moland, Even; Ciannelli, Lorenzo; Knutsen, Halvor

2015-05-01

Understanding responses of marine species to temperature variability is essential to predict impacts of future climate change in the oceans. Most ectotherms are expected to adjust their behavior to avoid extreme temperatures and minimize acute changes in body temperature. However, measuring such behavioral plasticity in the wild is challenging. Combining 4 years of telemetry-derived behavioral data on juvenile and adult (30-80 cm) Atlantic cod (Gadus morhua), and in situ ocean temperature measurements, we found a significant effect of sea temperature on cod depth use and activity level in coastal Skagerrak. During summer, cod were found in deeper waters when sea surface temperature increased. Further, this effect of temperature was stronger on larger cod. Diel vertical migration, which consists in a nighttime rise to shallow feeding habitats, was stronger among smaller cod. As surface temperature increased beyond ∼15°C, their vertical migration was limited to deeper waters. In addition to larger diel vertical migrations, smaller cod were more active and travelled larger distances compared to larger specimens. Cold temperatures during winter tended, however, to reduce the magnitude of diel vertical migrations, as well as the activity level and distance moved by those smaller individuals. Our findings suggest that future and ongoing rises in sea surface temperature may increasingly deprive cod in this region from shallow feeding areas during summer, which may be detrimental for local populations of the species.

Behavioral responses of Atlantic cod to sea temperature changes

PubMed Central

Freitas, Carla; Olsen, Esben Moland; Moland, Even; Ciannelli, Lorenzo; Knutsen, Halvor

2015-01-01

Understanding responses of marine species to temperature variability is essential to predict impacts of future climate change in the oceans. Most ectotherms are expected to adjust their behavior to avoid extreme temperatures and minimize acute changes in body temperature. However, measuring such behavioral plasticity in the wild is challenging. Combining 4 years of telemetry-derived behavioral data on juvenile and adult (30–80 cm) Atlantic cod (Gadus morhua), and in situ ocean temperature measurements, we found a significant effect of sea temperature on cod depth use and activity level in coastal Skagerrak. During summer, cod were found in deeper waters when sea surface temperature increased. Further, this effect of temperature was stronger on larger cod. Diel vertical migration, which consists in a nighttime rise to shallow feeding habitats, was stronger among smaller cod. As surface temperature increased beyond ∼15°C, their vertical migration was limited to deeper waters. In addition to larger diel vertical migrations, smaller cod were more active and travelled larger distances compared to larger specimens. Cold temperatures during winter tended, however, to reduce the magnitude of diel vertical migrations, as well as the activity level and distance moved by those smaller individuals. Our findings suggest that future and ongoing rises in sea surface temperature may increasingly deprive cod in this region from shallow feeding areas during summer, which may be detrimental for local populations of the species. PMID:26045957

Marshall N. Rosenbluth Outstanding Doctoral Thesis Award Talk: Simultaneous Measurement of Electron Temperature and Density Fluctuations in the Core of DIII-D Plasmas

NASA Astrophysics Data System (ADS)

White, A. E.

2009-11-01

Multi-field fluctuation measurements provide opportunities for rigorous comparison between experiment and nonlinear gyrokinetic turbulence simulations. A unique set of diagnostics on DIII-D allows for simultaneous study of local, long-wavelength (0 < kθρs< 0.5) electron temperature and density fluctuations in the core plasma (0.4 < ρ< 0.8). Previous experiments in L-mode indicate that normalized electron temperature fluctuation levels (40 < f < 400,kHz) increase with radius from ˜0.4% at ρ= 0.5 to ˜2% at ρ=0.8, similar to simultaneously measured density fluctuations. Electron cyclotron heating (ECH) is used to increase Te, which increases electron temperature fluctuation levels and electron heat transport in the experiments. In contrast, long wavelength density fluctuation levels change very little. The different responses are consistent with increased TEM drive relative to ITG-mode drive. A new capability at DIII-D is the measurement of phase angle between electron temperature and density fluctuations using coupled correlation electron cyclotron emission radiometer and reflectometer diagnostics. Linear and nonlinear GYRO runs have been used to design validation experiments that focus on measurements of the phase angle. GYRO shows that if Te and ∇Te increase 50% in a beam-heated L-mode plasma (ρ=0.5), then the phase angle between electron temperature and density fluctuations decreases 30%-50% and electron temperature fluctuation levels increase a factor of two more than density fluctuations. Comparisons between these predictions and experimental results will be presented.

Convergence in the temperature response of leaf respiration across biomes and plant functional types

PubMed Central

Heskel, Mary A.; O’Sullivan, Odhran S.; Reich, Peter B.; Tjoelker, Mark G.; Weerasinghe, Lasantha K.; Penillard, Aurore; Egerton, John J. G.; Creek, Danielle; Bloomfield, Keith J.; Xiang, Jen; Sinca, Felipe; Stangl, Zsofia R.; Martinez-de la Torre, Alberto; Griffin, Kevin L.; Huntingford, Chris; Hurry, Vaughan; Meir, Patrick; Turnbull, Matthew H.; Atkin, Owen K.

2016-01-01

Plant respiration constitutes a massive carbon flux to the atmosphere, and a major control on the evolution of the global carbon cycle. It therefore has the potential to modulate levels of climate change due to the human burning of fossil fuels. Neither current physiological nor terrestrial biosphere models adequately describe its short-term temperature response, and even minor differences in the shape of the response curve can significantly impact estimates of ecosystem carbon release and/or storage. Given this, it is critical to establish whether there are predictable patterns in the shape of the respiration–temperature response curve, and thus in the intrinsic temperature sensitivity of respiration across the globe. Analyzing measurements in a comprehensive database for 231 species spanning 7 biomes, we demonstrate that temperature-dependent increases in leaf respiration do not follow a commonly used exponential function. Instead, we find a decelerating function as leaves warm, reflecting a declining sensitivity to higher temperatures that is remarkably uniform across all biomes and plant functional types. Such convergence in the temperature sensitivity of leaf respiration suggests that there are universally applicable controls on the temperature response of plant energy metabolism, such that a single new function can predict the temperature dependence of leaf respiration for global vegetation. This simple function enables straightforward description of plant respiration in the land-surface components of coupled earth system models. Our cross-biome analyses shows significant implications for such fluxes in cold climates, generally projecting lower values compared with previous estimates. PMID:27001849

Convergence in the temperature response of leaf respiration across biomes and plant functional types.

PubMed

Heskel, Mary A; O'Sullivan, Odhran S; Reich, Peter B; Tjoelker, Mark G; Weerasinghe, Lasantha K; Penillard, Aurore; Egerton, John J G; Creek, Danielle; Bloomfield, Keith J; Xiang, Jen; Sinca, Felipe; Stangl, Zsofia R; Martinez-de la Torre, Alberto; Griffin, Kevin L; Huntingford, Chris; Hurry, Vaughan; Meir, Patrick; Turnbull, Matthew H; Atkin, Owen K

2016-04-05

Plant respiration constitutes a massive carbon flux to the atmosphere, and a major control on the evolution of the global carbon cycle. It therefore has the potential to modulate levels of climate change due to the human burning of fossil fuels. Neither current physiological nor terrestrial biosphere models adequately describe its short-term temperature response, and even minor differences in the shape of the response curve can significantly impact estimates of ecosystem carbon release and/or storage. Given this, it is critical to establish whether there are predictable patterns in the shape of the respiration-temperature response curve, and thus in the intrinsic temperature sensitivity of respiration across the globe. Analyzing measurements in a comprehensive database for 231 species spanning 7 biomes, we demonstrate that temperature-dependent increases in leaf respiration do not follow a commonly used exponential function. Instead, we find a decelerating function as leaves warm, reflecting a declining sensitivity to higher temperatures that is remarkably uniform across all biomes and plant functional types. Such convergence in the temperature sensitivity of leaf respiration suggests that there are universally applicable controls on the temperature response of plant energy metabolism, such that a single new function can predict the temperature dependence of leaf respiration for global vegetation. This simple function enables straightforward description of plant respiration in the land-surface components of coupled earth system models. Our cross-biome analyses shows significant implications for such fluxes in cold climates, generally projecting lower values compared with previous estimates.

Impact Assessment of Global Temperature Perturbations on Urban and Regional Ozone Levels in South Texas

NASA Astrophysics Data System (ADS)

Biswas, Jhumoor; John, Kuruvilla; Farooqui, Zuber

The recent Intergovernmental Panel on Climate Change report predicts significant temperature increases over the century which constitutes the pulse of climate variability in a region. A modeling study was performed to identify the potential impact of temperature perturbations on tropospheric ozone concentrations in South Texas. A future case modeling scenario which incorporates appropriate emission reduction strategies without accounting for climatic inconsistencies was used in this study. The photochemical modeling was undertaken for a high ozone episode of 13-20 September 1999, and a future modeling scenario was projected for ozone episode days in 2007 utilizing the meteorological conditions prevalent in the base year. The temperatures were increased uniformly throughout the simulation domain and through the vertical layers by 2°C, 3°C, 4°C, 5°C, and 6°C, respectively in the future year modeling case. These temperature perturbations represented the outcome of extreme climate change within the study region. Significantly large changes in peak ozone concentrations were predicted by the photochemical model. For the 6°C temperature perturbation, the greatest amplification in the maximum 8-h ozone concentrations within urban areas of the modeling domain was approximately 12 ppb. In addition, transboundary flux from major industrialized urban areas played a major role in supplementing the high ozone concentrations during the perturbed temperature scenarios. The Unites States Environmental Protection Agency (USEPA) is currently proposing stricter 8-h ozone standards. The effect of temperature perturbations on ozone exceedances based on current and potential stringent future National Ambient Air Quality Standards (NAAQS) was also studied. Temperatures had an appreciable spatial impact on the 8-h ozone exceedances with a considerable increase in spatial area exceeding the NAAQS for the 8-h ozone levels within the study region for each successive augmentation in temperature. The number of exceedances of the 8-h ozone standard increased significantly with each degree rise of temperature with the problem becoming even more acute in light of stricter future proposed standards of ozone.

Increased resource use efficiency amplifies positive response of aquatic primary production to experimental warming.

PubMed

Hood, James M; Benstead, Jonathan P; Cross, Wyatt F; Huryn, Alexander D; Johnson, Philip W; Gíslason, Gísli M; Junker, James R; Nelson, Daniel; Ólafsson, Jón S; Tran, Chau

2018-03-01

Climate warming is affecting the structure and function of river ecosystems, including their role in transforming and transporting carbon (C), nitrogen (N), and phosphorus (P). Predicting how river ecosystems respond to warming has been hindered by a dearth of information about how otherwise well-studied physiological responses to temperature scale from organismal to ecosystem levels. We conducted an ecosystem-level temperature manipulation to quantify how coupling of stream ecosystem metabolism and nutrient uptake responded to a realistic warming scenario. A ~3.3°C increase in mean water temperature altered coupling of C, N, and P fluxes in ways inconsistent with single-species laboratory experiments. Net primary production tripled during the year of experimental warming, while whole-stream N and P uptake rates did not change, resulting in 289% and 281% increases in autotrophic dissolved inorganic N and P use efficiency (UE), respectively. Increased ecosystem production was a product of unexpectedly large increases in mass-specific net primary production and autotroph biomass, supported by (i) combined increases in resource availability (via N mineralization and N 2 fixation) and (ii) elevated resource use efficiency, the latter associated with changes in community structure. These large changes in C and nutrient cycling could not have been predicted from the physiological effects of temperature alone. Our experiment provides clear ecosystem-level evidence that warming can shift the balance between C and nutrient cycling in rivers, demonstrating that warming will alter the important role of in-stream processes in C, N, and P transformations. Moreover, our results reveal a key role for nutrient supply and use efficiency in mediating responses of primary producers to climate warming. © 2017 John Wiley & Sons Ltd.

Thyroid hormone modulates offspring sex ratio in a turtle with temperature-dependent sex determination

PubMed Central

Li, Teng; Mu, Yi; McGlashan, Jessica K.; Georges, Arthur

2016-01-01

The adaptive significance of temperature-dependent sex determination (TSD) has attracted a great deal of research, but the underlying mechanisms by which temperature determines the sex of a developing embryo remain poorly understood. Here, we manipulated the level of a thyroid hormone (TH), triiodothyronine (T3), during embryonic development (by adding excess T3 to the eggs of the red-eared slider turtle Trachemys scripta, a reptile with TSD), to test two competing hypotheses on the proximate basis for TSD: the developmental rate hypothesis versus the hormone hypothesis. Exogenous TH accelerated embryonic heart rate (and hence metabolic rate), developmental rate, and rates of early post-hatching growth. More importantly, hyperthyroid conditions depressed expression of Cyp19a1 (the gene encoding for aromatase) and levels of oestradiol, and induced more male offspring. This result is contrary to the direction of sex-ratio shift predicted by the developmental rate hypothesis, but consistent with that predicted by the hormone hypothesis. Our results suggest an important role for THs in regulating sex steroid hormones, and therefore, in affecting gonadal sex differentiation in TSD reptiles. Our study has implications for the conservation of TSD reptiles in the context of global change because environmental contaminants may disrupt the activity of THs, and thereby affect offspring sex in TSD reptiles. PMID:27798296

Characterization of a large biogenic secondary organic aerosol event from eastern Canadian forests

NASA Astrophysics Data System (ADS)

Slowik, J. G.; Stroud, C.; Bottenheim, J. W.; Brickell, P. C.; Chang, R. Y.-W.; Liggio, J.; Makar, P. A.; Martin, R. V.; Moran, M. D.; Shantz, N. C.; Sjostedt, S. J.; van Donkelaar, A.; Vlasenko, A.; Wiebe, H. A.; Xia, A. G.; Zhang, J.; Leaitch, W. R.; Abbatt, J. P. D.

2010-03-01

Measurements of aerosol composition, volatile organic compounds, and CO are used to determine biogenic secondary organic aerosol (SOA) concentrations at a rural site 70 km north of Toronto. These biogenic SOA levels are many times higher than past observations and occur during a period of increasing temperatures and outflow from Northern Ontario and Quebec forests in early summer. A regional chemical transport model approximately predicts the event timing and accurately predicts the aerosol loading, identifying the precursors as monoterpene emissions from the coniferous forest. The agreement between the measured and modeled biogenic aerosol concentrations contrasts with model underpredictions for polluted regions. Correlations of the oxygenated organic aerosol mass with tracers such as CO support a secondary aerosol source and distinguish biogenic, pollution, and biomass burning periods during the field campaign. Using the Master Chemical Mechanism, it is shown that the levels of CO observed during the biogenic event are consistent with a photochemical source arising from monoterpene oxidation. The biogenic aerosol mass correlates with satellite measurements of regional aerosol optical depth, indicating that the event extends across the eastern Canadian forest. This regional event correlates with increased temperatures, indicating that temperature-dependent forest emissions can significantly affect climate through enhanced direct optical scattering and higher cloud condensation nuclei numbers.

Long-Term Creep and Creep Rupture Behavior of Woven Ceramic Matrix Composites

NASA Technical Reports Server (NTRS)

Haque, A.; Rahman, M.; Mach, A.; Jeelani, S.; Verrilli, Michael J. (Technical Monitor)

2001-01-01

Tensile creep behavior of SiC/SiNC ceramic matrix composites at elevated temperatures and at various stress levels have been investigated for turbine engine applications. The objective of this research is to present creep behavior of SiC/SiCN composites at stress levels above and below the monotonic proportional limit strength and predict the life at creep rupture conditions. Tensile creep-rupture tests were performed on an Instron 8502 servohydraulic testing machine at constant load conditions up to a temperature limit of 1000 C. Individual creep curves indicate three stages such as primary, secondary, and tertiary. The creep rate increased linearly at an early stage and then gradually became exponential at higher strains. The stress exponent and activation energy were also obtained at 700 and 1000 C. The specimen lifetime was observed to be 55 hrs at 121 MPa and at 700 C. The life span reduced to 35 hrs at 143 MPa and at 1000 C. Scanning electron microscopy observations revealed significant changes in the crystalline phases and creep damage development. Creep failures were accompanied by extensive fiber pullout, matrix cracking, and debonding along with fiber fracture. The creep data was applied to Time-Temperature-Stress superposition model and the Manson-Haferd parametric model for long-time life prediction.

The impacts of climate change in coastal marine systems.

PubMed

Harley, Christopher D G; Randall Hughes, A; Hultgren, Kristin M; Miner, Benjamin G; Sorte, Cascade J B; Thornber, Carol S; Rodriguez, Laura F; Tomanek, Lars; Williams, Susan L

2006-02-01

Anthropogenically induced global climate change has profound implications for marine ecosystems and the economic and social systems that depend upon them. The relationship between temperature and individual performance is reasonably well understood, and much climate-related research has focused on potential shifts in distribution and abundance driven directly by temperature. However, recent work has revealed that both abiotic changes and biological responses in the ocean will be substantially more complex. For example, changes in ocean chemistry may be more important than changes in temperature for the performance and survival of many organisms. Ocean circulation, which drives larval transport, will also change, with important consequences for population dynamics. Furthermore, climatic impacts on one or a few 'leverage species' may result in sweeping community-level changes. Finally, synergistic effects between climate and other anthropogenic variables, particularly fishing pressure, will likely exacerbate climate-induced changes. Efforts to manage and conserve living marine systems in the face of climate change will require improvements to the existing predictive framework. Key directions for future research include identifying key demographic transitions that influence population dynamics, predicting changes in the community-level impacts of ecologically dominant species, incorporating populations' ability to evolve (adapt), and understanding the scales over which climate will change and living systems will respond.

NaK Plugging Meter Design for the Feasibility Test Loops

NASA Technical Reports Server (NTRS)

Pearson, J. Boise; Godfroy, Thomas J.; Reid, Robert S.; Polzin, Kurt A.

2008-01-01

The design and predicted performance of a plugging meter for use in the measurement of NaK impurity levels are presented. The plugging meter is incorporated into a Feasibility Test Loop (FTL), which is a small pumped-NaK loop designed to enable the rapid, small-scale evaluation of techniques such as in situ purification methods and to permit the measurement of bulk material transport effects (not mechanisms) under flow conditions that are representative of a fission surface power reactor. The FTL operates at temperatures similar to those found in a reactor, with a maximum hot side temperature of 900 K and a corresponding cold side temperature of 860 K. In the plugging meter a low flow rate bypass loop is cooled until various impurities (primarily oxides) precipitate out of solution. The temperatures at which these impurities precipitate are indicative of the level of impurities in the NaK. The precipitates incrementally plug a small orifice in the bypass loop, which is detected by monitoring changes in the liquid metal flow rate.

Thermal Plasticity of Photosynthesis: the Role of Acclimation in Forest Responses to a Warming Climate

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gunderson, Carla A; O'Hara, Keiran H; Campion, Christina M

2010-01-01

The increasing air temperatures central to climate change predictions have the potential to alter forest ecosystem function and structure by exceeding temperatures optimal for carbon gain. Such changes are projected to threaten survival of sensitive species, leading to local extinctions, range migrations, and altered forest composition. This study investigated photosynthetic sensitivity to temperature and the potential for acclimation in relation to the climatic provenance of five species of deciduous trees, Liquidambar styraciflua, Quercus rubra, Quercus falcata, Betula alleghaniensis, and Populus grandidentata. Open-top chambers supplied three levels of warming (+0, +2, and +4 C above ambient) over 3 years, tracking naturalmore » temperature variability. Optimal temperature for CO2 assimilation was strongly correlated with daytime temperature in all treatments, but assimilation rates at those optima were comparable. Adjustment of thermal optima was confirmed in all species, whether temperatures varied with season or treatment, and regardless of climate in the species' range or provenance of the plant material. Temperature optima from 17 to 34 were observed. Across species, acclimation potentials varied from 0.55 C to 1.07 C per degree change in daytime temperature. Responses to the temperature manipulation were not different from the seasonal acclimation observed in mature indigenous trees, suggesting that photosynthetic responses should not be modeled using static temperature functions, but should incorporate an adjustment to account for acclimation. The high degree of homeostasis observed indicates that direct impacts of climatic warming on forest productivity, species survival, and range limits may be less than predicted by existing models.« less

A general strategy for performing temperature-programming in high performance liquid chromatography--further improvements in the accuracy of retention time predictions of segmented temperature gradients.

PubMed

Wiese, Steffen; Teutenberg, Thorsten; Schmidt, Torsten C

2012-01-27

In the present work it is shown that the linear elution strength (LES) model which was adapted from temperature-programming gas chromatography (GC) can also be employed for systematic method development in high-temperature liquid chromatography (HT-HPLC). The ability to predict isothermal retention times based on temperature-gradient as well as isothermal input data was investigated. For a small temperature interval of ΔT=40°C, both approaches result in very similar predictions. Average relative errors of predicted retention times of 2.7% and 1.9% were observed for simulations based on isothermal and temperature-gradient measurements, respectively. Concurrently, it was investigated whether the accuracy of retention time predictions of segmented temperature gradients can be further improved by temperature dependent calculation of the parameter S(T) of the LES relationship. It was found that the accuracy of retention time predictions of multi-step temperature gradients can be improved to around 1.5%, if S(T) was also calculated temperature dependent. The adjusted experimental design making use of four temperature-gradient measurements was applied for systematic method development of selected food additives by high-temperature liquid chromatography. Method development was performed within a temperature interval from 40°C to 180°C using water as mobile phase. Two separation methods were established where selected food additives were baseline separated. In addition, a good agreement between simulation and experiment was observed, because an average relative error of predicted retention times of complex segmented temperature gradients less than 5% was observed. Finally, a schedule of recommendations to assist the practitioner during systematic method development in high-temperature liquid chromatography was established. Copyright © 2011 Elsevier B.V. All rights reserved.

Can air temperature be used to project influences of climate change on stream temperature?

USGS Publications Warehouse

Arismendi, Ivan; Safeeq, Mohammad; Dunham, Jason B.; Johnson, Sherri L.

2014-01-01

Worldwide, lack of data on stream temperature has motivated the use of regression-based statistical models to predict stream temperatures based on more widely available data on air temperatures. Such models have been widely applied to project responses of stream temperatures under climate change, but the performance of these models has not been fully evaluated. To address this knowledge gap, we examined the performance of two widely used linear and nonlinear regression models that predict stream temperatures based on air temperatures. We evaluated model performance and temporal stability of model parameters in a suite of regulated and unregulated streams with 11–44 years of stream temperature data. Although such models may have validity when predicting stream temperatures within the span of time that corresponds to the data used to develop them, model predictions did not transfer well to other time periods. Validation of model predictions of most recent stream temperatures, based on air temperature–stream temperature relationships from previous time periods often showed poor performance when compared with observed stream temperatures. Overall, model predictions were less robust in regulated streams and they frequently failed in detecting the coldest and warmest temperatures within all sites. In many cases, the magnitude of errors in these predictions falls within a range that equals or exceeds the magnitude of future projections of climate-related changes in stream temperatures reported for the region we studied (between 0.5 and 3.0 °C by 2080). The limited ability of regression-based statistical models to accurately project stream temperatures over time likely stems from the fact that underlying processes at play, namely the heat budgets of air and water, are distinctive in each medium and vary among localities and through time.

Mismatch in microbial food webs: predators but not prey perform better in their local biotic and abiotic conditions.

PubMed

Parain, Elodie C; Gravel, Dominique; Rohr, Rudolf P; Bersier, Louis-Félix; Gray, Sarah M

2016-07-01

Understanding how trophic levels respond to changes in abiotic and biotic conditions is key for predicting how food webs will react to environmental perturbations. Different trophic levels may respond disproportionately to change, with lower levels more likely to react faster, as they typically consist of smaller-bodied species with higher reproductive rates. This response could cause a mismatch between trophic levels, in which predators and prey will respond differently to changing abiotic or biotic conditions. This mismatch between trophic levels could result in altered top-down and bottom-up control and changes in interaction strength. To determine the possibility of a mismatch, we conducted a reciprocal-transplant experiment involving Sarracenia purpurea food webs consisting of bacterial communities as prey and a subset of six morphologically similar protozoans as predators. We used a factorial design with four temperatures, four bacteria and protozoan biogeographic origins, replicated four times. This design allowed us to determine how predator and prey dynamics were altered by abiotic (temperature) conditions and biotic (predators paired with prey from either their local or non-local biogeographic origin) conditions. We found that prey reached higher densities in warmer temperature regardless of their temperature of origin. Conversely, predators achieved higher densities in the temperature condition and with the prey from their origin. These results confirm that predators perform better in abiotic and biotic conditions of their origin while their prey do not. This mismatch between trophic levels may be especially significant under climate change, potentially disrupting ecosystem functioning by disproportionately affecting top-down and bottom-up control.

Predicting and Modelling the Growth of Potentially Pathogenic Bacteria in Coalho Cheese.

PubMed

de Araújo, Valdenice Gomes; de Oliveira Arruda, Maria Digian; Dantas Duarte, Francisca Nayara; de Sousa, Janaína Maria Batista; da Costa Lima, Maiara; da Conceição, Maria Lúcia; Schaffner, Donald W; de Souza, Evandro Leite

2017-07-01

Coalho is a semihard medium- to high-moisture cheese produced in various states in the northeastern region of Brazil. This study was conducted to predict the growth kinetics (maximum growth rate, Grmax) of Escherichia coli, Listeria monocytogenes, Salmonella, and Staphylococcus aureus using the ComBase predictor with various combinations of temperature, pH, and water activity (a w ) in commercial Coalho cheese samples. The growth of two antibiotic-resistant derivative strains of L. monocytogenes (parental strains ATCC 19115 and ATCC 7644) and S. aureus (parental strains ATCC 13565 and ATCC 19095) was measured in commercial Coalho cheese samples during 14 days of storage as a function of the initial contamination level (3 and 5 log CFU/g) and storage temperature (7.5 and 12°C). The highest Grmax values predicted by ComBase under the various conditions of temperature, pH, and a w were for L. monocytogenes (0.006 to 0.065 log CFU/g/h) and S. aureus (0.003 to 0.048 log CFU/g/h). The Grmax values predicted by ComBase for E. coli and Salmonella were 0.007 to 0.026 and 0.008 to 0.041 log CFU/g/h, respectively. An experimental challenge in Coalho cheese revealed that the populations of all tested antibiotic-resistant derivative strains of L. monocytogenes and S. aureus increased (>0.5 log CFU/g) by day 14 of storage at 7.5 or 12°C. L. monocytogenes and S. aureus had higher Grmax values in cheese samples stored at 12°C than those stored at 7.5°C. The ComBase growth predictions under the temperature, pH, and a w conditions in commercial Coalho cheese samples were generally fail-safe for predicting the growth of L. monocytogenes and S. aureus in the actual product. These results indicate that Coalho cheese has pH and a w characteristics that allow the growth of E. coli, L. monocytogenes, Salmonella, and S. aureus. These cheeses are typically stored at temperatures that do not prevent the growth of these bacteria.

SST-Forced Seasonal Simulation and Prediction Skill for Versions of the NCEP/MRF Model.

NASA Astrophysics Data System (ADS)

Livezey, Robert E.; Masutani, Michiko; Jil, Ming

1996-03-01

The feasibility of using a two-tier approach to provide guidance to operational long-lead seasonal prediction is explored. The approach includes first a forecast of global sea surface temperatures (SSTs) using a coupled general circulation model, followed by an atmospheric forecast using an atmospheric general circulation model (AGCM). For this exploration, ensembles of decade-long integrations of the AGCM driven by observed SSTs and ensembles of integrations of select cases driven by forecast SSTs have been conducted. The ability of the model in these sets of runs to reproduce observed atmospheric conditions has been evaluated with a multiparameter performance analysis.Results have identified performance and skill levels in the specified SST runs, for winters and springs over the Pacific/North America region, that are sufficient to impact operational seasonal predictions in years with major El Niño-Southern Oscillation (ENSO) episodes. Further, these levels were substantially reproduced in the forecast SST runs for 1-month leads and in many instances for up to one-season leads. In fact, overall the 0- and 1-month-lead forecasts of seasonal temperature over the United States for three falls and winters with major ENSO episodes were substantially better than corresponding official forecasts. Thus, there is considerable reason to develop a dynamical component for the official seasonal forecast process.

An evaluation of a coupled microstructural approach for the analysis of functionally graded composites via the finite-element method

NASA Technical Reports Server (NTRS)

Pindera, Marek-Jerzy; Dunn, Patrick

1995-01-01

A comparison is presented between the predictions of the finite-element analysis and a recently developed higher-order theory for functionally graded materials subjected to a thorough-thickness temperature gradient. In contrast to existing micromechanical theories that utilize classical (i.e., uncoupled) homogenization schemes to calculate micro-level and macro-level stress and displacement fields in materials with uniform or nonuniform fiber spacing (i.e., functionally graded materials), the new theory explicitly couples the microstructural details with the macrostructure of the composite. Previous thermo-elastic analysis has demonstrated that such coupling is necessary when: the temperature gradient is large with respect to the dimension of the reinforcement; the characteristic dimension of the reinforcement is large relative to the global dimensions of the composite and the number of reinforcing fibers or inclusions is small. In these circumstances, the standard micromechanical analyses based on the concept of the representative volume element used to determine average composite properties produce questionable results. The comparison between the predictions of the finite-element method and the higher-order theory presented herein establish the theory's accuracy in predicting thermal and stress fields within composites with a finite number of fibers in the thickness direction subjected to a thorough-thickness thermal gradient.

Diagnosing sea ice from the north american multi model ensemble and implications on mid-latitude winter climate

NASA Astrophysics Data System (ADS)

Elders, Akiko; Pegion, Kathy

2017-12-01

Arctic sea ice plays an important role in the climate system, moderating the exchange of energy and moisture between the ocean and the atmosphere. An emerging area of research investigates how changes, particularly declines, in sea ice extent (SIE) impact climate in regions local to and remote from the Arctic. Therefore, both observations and model estimates of sea ice become important. This study investigates the skill of sea ice predictions from models participating in the North American Multi-Model Ensemble (NMME) project. Three of the models in this project provide sea-ice predictions. The ensemble average of these models is used to determine seasonal climate impacts on surface air temperature (SAT) and sea level pressure (SLP) in remote regions such as the mid-latitudes. It is found that declines in fall SIE are associated with cold temperatures in the mid-latitudes and pressure patterns across the Arctic and mid-latitudes similar to the negative phase of the Arctic Oscillation (AO). These findings are consistent with other studies that have investigated the relationship between declines in SIE and mid-latitude weather and climate. In an attempt to include additional NMME models for sea-ice predictions, a proxy for SIE is used to estimate ice extent in the remaining models, using sea surface temperature (SST). It is found that SST is a reasonable proxy for SIE estimation when compared to model SIE forecasts and observations. The proxy sea-ice estimates also show similar relationships to mid-latitude temperature and pressure as the actual sea-ice predictions.

Validation of an individualised model of human thermoregulation for predicting responses to cold air

NASA Astrophysics Data System (ADS)

van Marken Lichtenbelt, Wouter D.; Frijns, Arjan J. H.; van Ooijen, Marieke J.; Fiala, Dusan; Kester, Arnold M.; van Steenhoven, Anton A.

2007-01-01

Most computer models of human thermoregulation are population based. Here, we individualised the Fiala model [Fiala et al. (2001) Int J Biometeorol 45:143 159] with respect to anthropometrics, body fat, and metabolic rate. The predictions of the adapted multisegmental thermoregulatory model were compared with measured skin temperatures of individuals. Data from two experiments, in which reclining subjects were suddenly exposed to mild to moderate cold environmental conditions, were used to study the effect on dynamic skin temperature responses. Body fat was measured by the three-compartment method combining underwater weighing and deuterium dilution. Metabolic rate was determined by indirect calorimetry. In experiment 1, the bias (mean difference) between predicted and measured mean skin temperature decreased from 1.8°C to -0.15°C during cold exposure. The standard deviation of the mean difference remained of the same magnitude (from 0.7°C to 0.9°C). In experiment 2 the bias of the skin temperature changed from 2.0±1.09°C using the standard model to 1.3±0.93°C using individual characteristics in the model. The inclusion of individual characteristics thus improved the predictions for an individual and led to a significantly smaller systematic error. However, a large part of the discrepancies in individual response to cold remained unexplained. Possible further improvements to the model accomplished by inclusion of more subject characteristics (i.e. body fat distribution, body shape) and model refinements on the level of (skin) blood perfusion, and control functions, are discussed.

Influence of the Sampling Rate and Noise Characteristics on Prediction of the Maximal Safe Laser Exposure in Human Skin Using Pulsed Photothermal Radiometry

NASA Astrophysics Data System (ADS)

Vidovič, L.; Milanič, M.; Majaron, B.

2013-09-01

Pulsed photothermal radiometry (PPTR) allows for noninvasive determination of the laser-induced temperature depth profile in strongly scattering samples, including human skin. In a recent experimental study, we have demonstrated that such information can be used to derive rather accurate predictions of the maximal safe radiant exposure on an individual patient basis. This has important implications for efficacy and safety of several laser applications in dermatology and aesthetic surgery, which are often compromised by risk of adverse side effects (e.g., scarring, and dyspigmentation) resulting from nonselective absorption of strong laser light in epidermal melanin. In this study, the differences between the individual maximal safe radiant exposure values as predicted from PPTR temperature depth profiling performed using a commercial mid-IR thermal camera (as used to acquire the original patient data) and our customized PPTR setup are analyzed. To this end, the latter has been used to acquire 17 PPTR records from three healthy volunteers, using 1 ms laser irradiation at 532 nm and a signal sampling rate of 20 000 . The laser-induced temperature profiles are reconstructed first from the intact PPTR signals, and then by binning the data to imitate the lower sampling rate of the IR camera (1000 fps). Using either the initial temperature profile in a dedicated numerical model of heat transfer or protein denaturation dynamics, the predicted levels of epidermal thermal damage and the corresponding are compared. A similar analysis is performed also with regard to the differences between noise characteristics of the two PPTR setups.

Estimating non-isothermal bacterial growth in foods from isothermal experimental data.

PubMed

Corradini, M G; Peleg, M

2005-01-01

To develop a mathematical method to estimate non-isothermal microbial growth curves in foods from experiments performed under isothermal conditions and demonstrate the method's applicability with published growth data. Published isothermal growth curves of Pseudomonas spp. in refrigerated fish at 0-8 degrees C and Escherichia coli 1952 in a nutritional broth at 27.6-36 degrees C were fitted with two different three-parameter 'primary models' and the temperature dependence of their parameters was fitted by ad hoc empirical 'secondary models'. These were used to generate non-isothermal growth curves by solving, numerically, a differential equation derived on the premise that the momentary non-isothermal growth rate is the isothermal rate at the momentary temperature, at a time that corresponds to the momentary growth level of the population. The predicted non-isothermal growth curves were in agreement with the reported experimental ones and, as expected, the quality of the predictions did not depend on the 'primary model' chosen for the calculation. A common type of sigmoid growth curve can be adequately described by three-parameter 'primary models'. At least in the two systems examined, these could be used to predict growth patterns under a variety of continuous and discontinuous non-isothermal temperature profiles. The described mathematical method whenever validated experimentally will enable the simulation of the microbial quality of stored and transported foods under a large variety of existing or contemplated commercial temperature histories.

Gauging climate change effects at local scales: weather-based indices to monitor insect harassment in caribou.

PubMed

Witter, Leslie A; Johnson, Chris J; Croft, Bruno; Gunn, Anne; Poirier, Lisa M

2012-09-01

Climate change is occurring at an accelerated rate in the Arctic. Insect harassment may be an important link between increased summer temperature and reduced body condition in caribou and reindeer (both Rangifer tarandus). To examine the effects of climate change at a scale relevant to Rangifer herds, we developed monitoring indices using weather to predict activity of parasitic insects across the central Arctic. During 2007-2009, we recorded weather conditions and used carbon dioxide baited traps to monitor activity of mosquitoes (Culicidae), black flies (Simuliidae), and oestrid flies (Oestridae) on the post-calving and summer range of the Bathurst barren-ground caribou (Rangifer tarandus groenlandicus) herd in Northwest Territories and Nunavut, Canada. We developed statistical models representing hypotheses about effects of weather, habitat, location, and temporal variables on insect activity. We used multinomial logistic regression to model mosquito and black fly activity, and logistic regression to model oestrid fly presence. We used information theory to select models to predict activity levels of insects. Using historical weather data, we used hindcasting to develop a chronology of insect activity on the Bathurst range from 1957 to 2008. Oestrid presence and mosquito and black fly activity levels were explained by temperature. Wind speed, light intensity, barometric pressure, relative humidity, vegetation, topography, location, time of day, and growing degree-days also affected mosquito and black fly levels. High predictive ability of all models justified the use of weather to index insect activity. Retrospective analyses indicated conditions favoring mosquito activity declined since the late 1950s, while predicted black fly and oestrid activity increased. Our indices can be used as monitoring tools to gauge potential changes in insect harassment due to climate change at scales relevant to caribou herds.

Development and application of Geobacillus stearothermophilus growth model for predicting spoilage of evaporated milk.

PubMed

Kakagianni, Myrsini; Gougouli, Maria; Koutsoumanis, Konstantinos P

2016-08-01

The presence of Geobacillus stearothermophilus spores in evaporated milk constitutes an important quality problem for the milk industry. This study was undertaken to provide an approach in modelling the effect of temperature on G. stearothermophilus ATCC 7953 growth and in predicting spoilage of evaporated milk. The growth of G. stearothermophilus was monitored in tryptone soy broth at isothermal conditions (35-67 °C). The data derived were used to model the effect of temperature on G. stearothermophilus growth with a cardinal type model. The cardinal values of the model for the maximum specific growth rate were Tmin = 33.76 °C, Tmax = 68.14 °C, Topt = 61.82 °C and μopt = 2.068/h. The growth of G. stearothermophilus was assessed in evaporated milk at Topt in order to adjust the model to milk. The efficiency of the model in predicting G. stearothermophilus growth at non-isothermal conditions was evaluated by comparing predictions with observed growth under dynamic conditions and the results showed a good performance of the model. The model was further used to predict the time-to-spoilage (tts) of evaporated milk. The spoilage of this product caused by acid coagulation when the pH approached a level around 5.2, eight generations after G. stearothermophilus reached the maximum population density (Nmax). Based on the above, the tts was predicted from the growth model as the sum of the time required for the microorganism to multiply from the initial to the maximum level ( [Formula: see text] ), plus the time required after the [Formula: see text] to complete eight generations. The observed tts was very close to the predicted one indicating that the model is able to describe satisfactorily the growth of G. stearothermophilus and to provide realistic predictions for evaporated milk spoilage. Copyright © 2016 Elsevier Ltd. All rights reserved.

Modelling climate change responses in tropical forests: similar productivity estimates across five models, but different mechanisms and responses

NASA Astrophysics Data System (ADS)

Rowland, L.; Harper, A.; Christoffersen, B. O.; Galbraith, D. R.; Imbuzeiro, H. M. A.; Powell, T. L.; Doughty, C.; Levine, N. M.; Malhi, Y.; Saleska, S. R.; Moorcroft, P. R.; Meir, P.; Williams, M.

2015-04-01

Accurately predicting the response of Amazonia to climate change is important for predicting climate change across the globe. Changes in multiple climatic factors simultaneously result in complex non-linear ecosystem responses, which are difficult to predict using vegetation models. Using leaf- and canopy-scale observations, this study evaluated the capability of five vegetation models (Community Land Model version 3.5 coupled to the Dynamic Global Vegetation model - CLM3.5-DGVM; Ecosystem Demography model version 2 - ED2; the Joint UK Land Environment Simulator version 2.1 - JULES; Simple Biosphere model version 3 - SiB3; and the soil-plant-atmosphere model - SPA) to simulate the responses of leaf- and canopy-scale productivity to changes in temperature and drought in an Amazonian forest. The models did not agree as to whether gross primary productivity (GPP) was more sensitive to changes in temperature or precipitation, but all the models were consistent with the prediction that GPP would be higher if tropical forests were 5 °C cooler than current ambient temperatures. There was greater model-data consistency in the response of net ecosystem exchange (NEE) to changes in temperature than in the response to temperature by net photosynthesis (An), stomatal conductance (gs) and leaf area index (LAI). Modelled canopy-scale fluxes are calculated by scaling leaf-scale fluxes using LAI. At the leaf-scale, the models did not agree on the temperature or magnitude of the optimum points of An, Vcmax or gs, and model variation in these parameters was compensated for by variations in the absolute magnitude of simulated LAI and how it altered with temperature. Across the models, there was, however, consistency in two leaf-scale responses: (1) change in An with temperature was more closely linked to stomatal behaviour than biochemical processes; and (2) intrinsic water use efficiency (IWUE) increased with temperature, especially when combined with drought. These results suggest that even up to fairly extreme temperature increases from ambient levels (+6 °C), simulated photosynthesis becomes increasingly sensitive to gs and remains less sensitive to biochemical changes. To improve the reliability of simulations of the response of Amazonian rainforest to climate change, the mechanistic underpinnings of vegetation models need to be validated at both leaf- and canopy-scales to improve accuracy and consistency in the quantification of processes within and across an ecosystem.

Controls on SOC across space and time: Models with different acclimation schemes make similar spatial predictions but divergent warming predictions

NASA Astrophysics Data System (ADS)

Abramoff, R. Z.; Torn, M. S.; Georgiou, K.; Tang, J.; Riley, W. J.

2017-12-01

Researchers use spatial gradients to estimate long-term ecosystem responses to perturbations. This approach is commonly applied to soil organic carbon (SOC) stocks which change slowly but store the majority of terrestrial carbon. Climate warming may reduce SOC stocks if higher temperatures increase decomposition rates. Yet, it is uncertain how vulnerable SOC is to warming, and whether the same factors - such as organo-mineral associations, climate, or plant inputs - determine SOC stocks across space and time. In order to test the "space for time" concept, we developed two versions of the Substrate-Mineral-Microbe Soil (SuMMS) model - one with microbial temperature acclimation and one without - to analyze observed SOC stocks at 24 sites spanning a wide range of soil types and climate. Both model predictions of SOC were strongly correlated with observations (R2 > 0.9), because mineral sorption capacity was the dominant control over steady-state SOC stock as determined by a Random Forest model. However, the two model versions made fundamentally different predictions of the change in SOC following 5°C soil warming from 2016 to 2100 because the initial mean annual temperature (MAT) was the dominant control over the SOC response. The model with microbial acclimation predicted that SOC would decline 10% at all sites along the transect, while the model with no acclimation predicted large surface SOC losses at high latitude sites and SOC gains at low latitude sites where microbial exoenzymes were already at or near their temperature optimum. These simulations suggest that gradient studies cannot be used to infer site-level responses to warming, because the dominant controls on SOC at steady state (i.e., mineral sorption capacity) are different than the dominant controls on the SOC response to a warming perturbation (i.e., initial MAT, capacity for acclimation).

IMPROVEMENT OF THE MODELLING OF THE LOW-TEMPERATURE OXIDATON OF N-BUTANE - STUDY OF THE PRIMARY REACTIONS

PubMed Central

CORD, Maximilien; SIRJEAN, Baptiste; FOURNET, René; TOMLIN, Alison; RUIZ-LOPEZ, Manuel; BATTIN-LECLERC, Frédérique

2013-01-01

This paper revisits the primary reactions involved in the oxidation of n-butane from low to intermediate temperatures (550-800 K) including the negative temperature coefficient (NTC) zone. A model which was automatically generated is used as a starting point and a large number of thermochemical and kinetic data are then re-estimated. The kinetic data of the isomerization of alkylperoxy radicals giving ·QOOH radicals and the subsequent decomposition to give cyclic ethers has been calculated at the CBS-QB3 level of theory. The newly obtained model allows a satisfactory prediction of experimental data recently obtained in a jet-stirred reactor and in rapid compression machines. A considerable improvement of the prediction of the selectivity of cyclic ethers is especially obtained compared to previous models. Linear and global sensitivity analyses have been performed in order to better understand which reactions are of influence in the NTC zone. PMID:22257166

Development of an Accelerated Test Design for Predicting the Service Life of the Solar Array at Mead, Nebraska

NASA Technical Reports Server (NTRS)

Gaines, G. B.; Thomas, R. E.; Noel, G. T.; Shilliday, T. S.; Wood, V. E.; Carmichael, D. C.

1979-01-01

An accelerated life test is described which was developed to predict the life of the 25 kW photovoltaic array installed near Mead, Nebraska. A quantitative model for accelerating testing using multiple environmental stresses was used to develop the test design. The model accounts for the effects of thermal stress by a relation of the Arrhenius form. This relation was then corrected for the effects of nonthermal environmental stresses, such as relative humidity, atmospheric pollutants, and ultraviolet radiation. The correction factors for the nonthermal stresses included temperature-dependent exponents to account for the effects of interactions between thermal and nonthermal stresses on the rate of degradation of power output. The test conditions, measurements, and data analyses for the accelerated tests are presented. Constant-temperature, cyclic-temperature, and UV types of tests are specified, incorporating selected levels of relative humidity and chemical contamination and an imposed forward-bias current and static electric field.

A non-LTE model for the Jovian methane infrared emissions at high spectral resolution

NASA Technical Reports Server (NTRS)

Halthore, Rangasayi N.; Allen, J. E., Jr.; Decola, Philip L.

1994-01-01

High resolution spectra of Jupiter in the 3.3 micrometer region have so far failed to reveal either the continuum or the line emissions that can be unambiguously attributed to the nu(sub 3) band of methane (Drossart et al. 1993; Kim et al. 1991). Nu(sub 3) line intensities predicted with the help of two simple non-Local Thermodynamic Equilibrium (LTE) models -- a two-level model and a three-level model, using experimentally determined relaxation coefficients, are shown to be one to three orders of magnitude respectively below the 3-sigma noise level of these observations. Predicted nu(sub 4) emission intensities are consistent with observed values. If the methane mixing ratio below the homopause is assumed as 2 x 10(exp -3), a value of about 300 K is derived as an upper limit to the temperature of the high stratosphere at microbar levels.

Background Noise Analysis in a Few-Photon-Level Qubit Memory

NASA Astrophysics Data System (ADS)

Mittiga, Thomas; Kupchak, Connor; Jordaan, Bertus; Namazi, Mehdi; Nolleke, Christian; Figeroa, Eden

2014-05-01

We have developed an Electromagnetically Induced Transparency based polarization qubit memory. The device is composed of a dual-rail probe field polarization setup colinear with an intense control field to store and retrieve any arbitrary polarization state by addressing a Λ-type energy level scheme in a 87Rb vapor cell. To achieve a signal-to-background ratio at the few photon level sufficient for polarization tomography of the retrieved state, the intense control field is filtered out through an etalon filtrating system. We have developed an analytical model predicting the influence of the signal-to-background ratio on the fidelities and compared it to experimental data. Experimentally measured global fidelities have been found to follow closely the theoretical prediction as signal-to-background decreases. These results suggest the plausibility of employing room temperature memories to store photonic qubits at the single photon level and for future applications in long distance quantum communication schemes.

Chesapeake Bay Forecast System: Oxygen Prediction for the Sustainable Ecosystem Management

NASA Astrophysics Data System (ADS)

Mathukumalli, B.; Long, W.; Zhang, X.; Wood, R.; Murtugudde, R. G.

2010-12-01

The Chesapeake Bay Forecast System (CBFS) is a flexible, end-to-end expert prediction tool for decision makers that will provide customizable, user-specified predictions and projections of the region’s climate, air and water quality, local chemistry, and ecosystems at days to decades. As a part of CBFS, the long-term water quality data were collected and assembled to develop ecological models for the sustainable management of the Chesapeake Bay. Cultural eutrophication depletes oxygen levels in this ecosystem particularly in summer which has several negative implications on the structure and function of ecosystem. In order to understand dynamics and prediction of spatially-explicit oxygen levels in the Bay, an empirical process based ecological model is developed with long-term control variables (water temperature, salinity, nitrogen and phosphorus). Statistical validation methods were employed to demonstrate usability of predictions for management purposes and the predicted oxygen levels are quite faithful to observations. The predicted oxygen values and other physical outputs from downscaling of regional weather and climate predictions, or forecasts from hydrodynamic models can be used to forecast various ecological components. Such forecasts would be useful for both recreational and commercial users of the bay (for example, bass fishing). Furthermore, this work can also be used to predict extent of hypoxia/anoxia not only from anthropogenic nutrient pollution, but also from global warming. Some hindcasts and forecasts are discussed along with the ongoing efforts at a mechanistic ecosystem model to provide prognostic oxygen predictions and projections and upper trophic modeling using an energetics approach.

Extreme value modeling for the analysis and prediction of time series of extreme tropospheric ozone levels: a case study.

PubMed

Escarela, Gabriel

2012-06-01

The occurrence of high concentrations of tropospheric ozone is considered as one of the most important issues of air management programs. The prediction of dangerous ozone levels for the public health and the environment, along with the assessment of air quality control programs aimed at reducing their severity, is of considerable interest to the scientific community and to policy makers. The chemical mechanisms of tropospheric ozone formation are complex, and highly variable meteorological conditions contribute additionally to difficulties in accurate study and prediction of high levels of ozone. Statistical methods offer an effective approach to understand the problem and eventually improve the ability to predict maximum levels of ozone. In this paper an extreme value model is developed to study data sets that consist of periodically collected maxima of tropospheric ozone concentrations and meteorological variables. The methods are applied to daily tropospheric ozone maxima in Guadalajara City, Mexico, for the period January 1997 to December 2006. The model adjusts the daily rate of change in ozone for concurrent impacts of seasonality and present and past meteorological conditions, which include surface temperature, wind speed, wind direction, relative humidity, and ozone. The results indicate that trend, annual effects, and key meteorological variables along with some interactions explain the variation in daily ozone maxima. Prediction performance assessments yield reasonably good results.

Fuel droplet burning rates at high pressures

NASA Technical Reports Server (NTRS)

Canada, G. S.; Faeth, G. M.

1972-01-01

Combustion of methanol, ethanol, propanol -1, n - pentane, n - heptane and n - decane was observed in air under natural convection conditions at pressures up to 100 atm. The droplets were simulated by porous spheres with diameters in the range 0.63 - 1.90 cm. The pressure levels of the tests were high enough so that near critical combustion was observed for methanol and ethanol. Measurements were made of the burning rate and liquid surface temperatures of the fuels. The data were compared with variable property analysis of the combustion process, including a correction for natural convection. The burning rate predictions of the various theories were similar and in fair agreement with the data. The high pressure theory gave the best prediction for the liquid surface temperatures of ethanol and propanol -1 at high pressure. The experiments indicated the approach of critical burning conditions for methanol and ethanol at pressures on the order of 80 - 100 atm, which was in good agreement with the predictions of both the low and high pressure analysis.

Predicting Salmonella populations from biological, chemical, and physical indicators in Florida surface waters.

PubMed

McEgan, Rachel; Mootian, Gabriel; Goodridge, Lawrence D; Schaffner, Donald W; Danyluk, Michelle D

2013-07-01

Coliforms, Escherichia coli, and various physicochemical water characteristics have been suggested as indicators of microbial water quality or index organisms for pathogen populations. The relationship between the presence and/or concentration of Salmonella and biological, physical, or chemical indicators in Central Florida surface water samples over 12 consecutive months was explored. Samples were taken monthly for 12 months from 18 locations throughout Central Florida (n = 202). Air and water temperature, pH, oxidation-reduction potential (ORP), turbidity, and conductivity were measured. Weather data were obtained from nearby weather stations. Aerobic plate counts and most probable numbers (MPN) for Salmonella, E. coli, and coliforms were performed. Weak linear relationships existed between biological indicators (E. coli/coliforms) and Salmonella levels (R(2) < 0.1) and between physicochemical indicators and Salmonella levels (R(2) < 0.1). The average rainfall (previous day, week, and month) before sampling did not correlate well with bacterial levels. Logistic regression analysis showed that E. coli concentration can predict the probability of enumerating selected Salmonella levels. The lack of good correlations between biological indicators and Salmonella levels and between physicochemical indicators and Salmonella levels shows that the relationship between pathogens and indicators is complex. However, Escherichia coli provides a reasonable way to predict Salmonella levels in Central Florida surface water through logistic regression.

Predicting Salmonella Populations from Biological, Chemical, and Physical Indicators in Florida Surface Waters

PubMed Central

McEgan, Rachel; Mootian, Gabriel; Goodridge, Lawrence D.; Schaffner, Donald W.

2013-01-01

Coliforms, Escherichia coli, and various physicochemical water characteristics have been suggested as indicators of microbial water quality or index organisms for pathogen populations. The relationship between the presence and/or concentration of Salmonella and biological, physical, or chemical indicators in Central Florida surface water samples over 12 consecutive months was explored. Samples were taken monthly for 12 months from 18 locations throughout Central Florida (n = 202). Air and water temperature, pH, oxidation-reduction potential (ORP), turbidity, and conductivity were measured. Weather data were obtained from nearby weather stations. Aerobic plate counts and most probable numbers (MPN) for Salmonella, E. coli, and coliforms were performed. Weak linear relationships existed between biological indicators (E. coli/coliforms) and Salmonella levels (R2 < 0.1) and between physicochemical indicators and Salmonella levels (R2 < 0.1). The average rainfall (previous day, week, and month) before sampling did not correlate well with bacterial levels. Logistic regression analysis showed that E. coli concentration can predict the probability of enumerating selected Salmonella levels. The lack of good correlations between biological indicators and Salmonella levels and between physicochemical indicators and Salmonella levels shows that the relationship between pathogens and indicators is complex. However, Escherichia coli provides a reasonable way to predict Salmonella levels in Central Florida surface water through logistic regression. PMID:23624476

Utility of NCEP Operational and Emerging Meteorological Models for Driving Air Quality Prediction

NASA Astrophysics Data System (ADS)

McQueen, J.; Huang, J.; Huang, H. C.; Shafran, P.; Lee, P.; Pan, L.; Sleinkofer, A. M.; Stajner, I.; Upadhayay, S.; Tallapragada, V.

2017-12-01

Operational air quality predictions for the United States (U. S.) are provided at NOAA by the National Air Quality Forecasting Capability (NAQFC). NAQFC provides nationwide operational predictions of ozone and particulate matter twice per day (at 06 and 12 UTC cycles) at 12 km resolution and 1 hour time intervals through 48 hours and distributed at http://airquality.weather.gov. The NOAA National Centers for Environmental Prediction (NCEP) operational North American Mesoscale (NAM) 12 km weather prediction is used to drive the Community Multiscale Air Quality (CMAQ) model. In 2017, the NAM was upgraded in part to reduce a warm 2m temperature bias in Summer (V4). At the same time CMAQ was updated to V5.0.2. Both versions of the models were run in parallel for several months. Therefore the impact of improvements from the atmospheric chemistry model versus upgrades with the weather prediction model could be assessed. . Improvements to CMAQ were related to improvements to improvements in NAM 2 m temperature bias through increasing the opacity of clouds and reducing downward shortwave radiation resulted in reduced ozone photolysis. Higher resolution operational NWP models have recently been introduced as part of the NCEP modeling suite. These include the NAM CONUS Nest (3 km horizontal resolution) run four times per day through 60 hours and the High Resolution Rapid Refresh (HRRR, 3 km) run hourly out to 18 hours. In addition, NCEP with other NOAA labs has begun to develop and test the Next Generation Global Prediction System (NGGPS) based on the FV3 global model. This presentation also overviews recent developments with operational numerical weather prediction and evaluates the ability of these models for predicting low level temperatures, clouds and capturing boundary layer processes important for driving air quality prediction in complex terrain. The assessed meteorological model errors could help determine the magnitude of possible pollutant errors from CMAQ if used for driving meteorology. The NWP models will be evaluated against standard and mesonet fields averaged for various regions during the summer 2017. An evaluation of meteorological fields important to air quality modeling (eg: near surface winds, temperatures, moisture and boundary layer heights, cloud cover) will be reported on.

Fourier and non-Fourier bio-heat transfer models to predict ex vivo temperature response to focused ultrasound heating

NASA Astrophysics Data System (ADS)

Li, Chenghai; Miao, Jiaming; Yang, Kexin; Guo, Xiasheng; Tu, Juan; Huang, Pintong; Zhang, Dong

2018-05-01

Although predicting temperature variation is important for designing treatment plans for thermal therapies, research in this area is yet to investigate the applicability of prevalent thermal conduction models, such as the Pennes equation, the thermal wave model of bio-heat transfer, and the dual phase lag (DPL) model. To address this shortcoming, we heated a tissue phantom and ex vivo bovine liver tissues with focused ultrasound (FU), measured the temperature response, and compared the results with those predicted by these models. The findings show that, for a homogeneous-tissue phantom, the initial temperature increase is accurately predicted by the Pennes equation at the onset of FU irradiation, although the prediction deviates from the measured temperature with increasing FU irradiation time. For heterogeneous liver tissues, the predicted response is closer to the measured temperature for the non-Fourier models, especially the DPL model. Furthermore, the DPL model accurately predicts the temperature response in biological tissues because it increases the phase lag, which characterizes microstructural thermal interactions. These findings should help to establish more precise clinical treatment plans for thermal therapies.

Convection equation modeling: A non-iterative direct matrix solution algorithm for use with SINDA

NASA Technical Reports Server (NTRS)

Schrage, Dean S.

1993-01-01

The determination of the boundary conditions for a component-level analysis, applying discrete finite element and finite difference modeling techniques often requires an analysis of complex coupled phenomenon that cannot be described algebraically. For example, an analysis of the temperature field of a coldplate surface with an integral fluid loop requires a solution to the parabolic heat equation and also requires the boundary conditions that describe the local fluid temperature. However, the local fluid temperature is described by a convection equation that can only be solved with the knowledge of the locally-coupled coldplate temperatures. Generally speaking, it is not computationally efficient, and sometimes, not even possible to perform a direct, coupled phenomenon analysis of the component-level and boundary condition models within a single analysis code. An alternative is to perform a disjoint analysis, but transmit the necessary information between models during the simulation to provide an indirect coupling. For this approach to be effective, the component-level model retains full detail while the boundary condition model is simplified to provide a fast, first-order prediction of the phenomenon in question. Specifically for the present study, the coldplate structure is analyzed with a discrete, numerical model (SINDA) while the fluid loop convection equation is analyzed with a discrete, analytical model (direct matrix solution). This indirect coupling allows a satisfactory prediction of the boundary condition, while not subjugating the overall computational efficiency of the component-level analysis. In the present study a discussion of the complete analysis of the derivation and direct matrix solution algorithm of the convection equation is presented. Discretization is analyzed and discussed to extend of solution accuracy, stability and computation speed. Case studies considering a pulsed and harmonic inlet disturbance to the fluid loop are analyzed to assist in the discussion of numerical dissipation and accuracy. In addition, the issues of code melding or integration with standard class solvers such as SINDA are discussed to advise the user of the potential problems to be encountered.

Statistical validation of predictive TRANSP simulations of baseline discharges in preparation for extrapolation to JET D-T

NASA Astrophysics Data System (ADS)

Kim, Hyun-Tae; Romanelli, M.; Yuan, X.; Kaye, S.; Sips, A. C. C.; Frassinetti, L.; Buchanan, J.; Contributors, JET

2017-06-01

This paper presents for the first time a statistical validation of predictive TRANSP simulations of plasma temperature using two transport models, GLF23 and TGLF, over a database of 80 baseline H-mode discharges in JET-ILW. While the accuracy of the predicted T e with TRANSP-GLF23 is affected by plasma collisionality, the dependency of predictions on collisionality is less significant when using TRANSP-TGLF, indicating that the latter model has a broader applicability across plasma regimes. TRANSP-TGLF also shows a good matching of predicted T i with experimental measurements allowing for a more accurate prediction of the neutron yields. The impact of input data and assumptions prescribed in the simulations are also investigated in this paper. The statistical validation and the assessment of uncertainty level in predictive TRANSP simulations for JET-ILW-DD will constitute the basis for the extrapolation to JET-ILW-DT experiments.

Identification of structural motifs as tunneling two-level systems in amorphous alumina at low temperatures

NASA Astrophysics Data System (ADS)

Paz, Alejandro Pérez; Lebedeva, Irina V.; Tokatly, Ilya V.; Rubio, Angel

2014-12-01

One of the most accepted models that describe the anomalous thermal behavior of amorphous materials at temperatures below 1 K relies on the quantum mechanical tunneling of atoms between two nearly equivalent potential energy wells forming a two-level system (TLS). Indirect evidence for TLSs is widely available. However, the atomistic structure of these TLSs remains an unsolved topic in the physics of amorphous materials. Here, using classical molecular dynamics, we found several hitherto unknown bistable structural motifs that may be key to understanding the anomalous thermal properties of amorphous alumina at low temperatures. We show through free energy profiles that the complex potential energy surface can be reduced to canonical TLSs. The tunnel splitting predicted from instanton theory, the number density, dipole moment, and coupling to external strain of the discovered motifs are consistent with experiments.

Analytical fuel property effects: Small combustors, phase 2

NASA Technical Reports Server (NTRS)

Hill, T. G.; Monty, J. D.; Morton, H. L.

1985-01-01

The effects of non-standard aviation fuels on a typical small gas turbine combustor were studied and the effectiveness of design changes intended to counter the effects of these fuels was evaluated. The T700/CT7 turboprop engine family was chosen as being representative of the class of aircraft power plants desired for this study. Fuel properties, as specified by NASA, are characterized by low hydrogen content and high aromatics levels. No. 2 diesel fuel was also evaluated in this program. Results demonstrated the anticipated higher than normal smoke output and flame radiation intensity with resulting increased metal temperatures on the baseline T700 combustor. Three new designs were evaluated using the non standard fuels. The three designs incorporated enhanced cooling features and smoke reduction features. All three designs, when burning the broad specification fuels, exhibited metal temperatures at or below the baseline combustor temperatures on JP-5. Smoke levels were acceptable but higher than predicted.

Annual Corn Yield Estimation through Multi-temporal MODIS Data

NASA Astrophysics Data System (ADS)

Shao, Y.; Zheng, B.; Campbell, J. B.

2013-12-01

This research employed 13 years of the Moderate Resolution Imaging Spectroradiometer (MODIS) to estimate annual corn yield for the Midwest of the United States. The overall objective of this study was to examine if annual corn yield could be accurately predicted using MODIS time-series NDVI (Normalized Difference Vegetation Index) and ancillary data such monthly precipitation and temperature. MODIS-NDVI 16-Day composite images were acquired from the USGS EROS Data Center for calendar years 2000 to 2012. For the same time-period, county level corn yield statistics were obtained from the National Agricultural Statistics Service (NASS). The monthly precipitation and temperature measures were derived from Precipitation-Elevation Regressions on Independent Slopes Model (PRISM) climate data. A cropland mask was derived using 2006 National Land Cover Database. For each county and within the cropland mask, the MODIS-NDVI time-series data and PRISM climate data were spatially averaged, at their respective time steps. We developed a random forest predictive model with the MODIS-NDVI and climate data as predictors and corn yield as response. To assess the model accuracy, we used twelve years of data as training and the remaining year as hold-out testing set. The training and testing procedures were repeated 13 times. The R2 ranged from 0.72 to 0.83 for testing years. It was also found that the inclusion of climate data did not improve the model predictive performance. MODIS-NDVI time-series data alone might provide sufficient information for county level corn yield prediction.

Cold Spots in Neonatal Incubators Are Hot Spots for Microbial Contamination▿

PubMed Central

de Goffau, Marcus C.; Bergman, Klasien A.; de Vries, Hendrik J.; Meessen, Nico E. L.; Degener, John E.; van Dijl, Jan Maarten; Harmsen, Hermie J. M.

2011-01-01

Thermal stability is essential for the survival and well-being of preterm neonates. This is achieved in neonatal incubators by raising the ambient temperature and humidity to sufficiently high levels. However, potentially pathogenic microorganisms also can thrive in such warm and humid environments. We therefore investigated whether the level of microbial contamination (i.e., the bacterial load) inside neonatal incubators can be predicted on the basis of their average temperature and relative humidity settings, paying special attention to local temperature differences. Swab samples were taken from the warmest and coldest spots found within Caleo incubators, and these were plated to determine the number of microbial CFU per location. In incubators with high average temperature (≥34°C) and relative humidity (≥60%) values, the level of microbial contamination was significantly higher at cold spots than at hot spots. This relates to the fact that the local equilibrium relative humidity at cold spots is sufficiently high to sustain microbial growth. The abundance of staphylococci, which are the main causative agents of late-onset sepsis in preterm neonates, was found to be elevated significantly in cold areas. These findings can be used to improve basic incubator hygiene. PMID:22003021

Effects of temperature, total dissolved solids, and total suspended solids on survival and development rate of larval Arkansas River Shiner

USGS Publications Warehouse

Mueller, Julia S.; Grabowski, Timothy B.; Brewer, Shannon K.; Worthington, Thomas A.

2017-01-01

Decreases in the abundance and diversity of stream fishes in the North American Great Plains have been attributed to habitat fragmentation, altered hydrological and temperature regimes, and elevated levels of total dissolved solids and total suspended solids. Pelagic-broadcast spawning cyprinids, such as the Arkansas River Shiner Notropis girardi, may be particularly vulnerable to these changing conditions because of their reproductive strategy. Our objectives were to assess the effects of temperature, total dissolved solids, and total suspended solids on the developmental and survival rates of Arkansas River Shiner larvae. Results suggest temperature had the greatest influence on the developmental rate of Arkansas River Shiner larvae. However, embryos exposed to the higher levels of total dissolved solids and total suspended solids reached developmental stages earlier than counterparts at equivalent temperatures. Although this rapid development may be beneficial in fragmented waters, our data suggest it may be associated with lower survival rates. Furthermore, those embryos incubating at high temperatures, or in high levels of total dissolved solids and total suspended solids resulted in less viable embryos and larvae than those incubating in all other temperature, total dissolved solid, and total suspended solid treatment groups. As the Great Plains ecoregion continues to change, these results may assist in understanding reasons for past extirpations and future extirpation threats as well as predict stream reaches capable of sustaining Arkansas River Shiners and other species with similar early life-history strategies.

Response of salt marsh and mangrove wetlands to changes in atmospheric CO2, climate, and sea-level

USGS Publications Warehouse

Mckee, Karen L.; Rogers, Kerrylee; Saintilan, Neil; Middleton, Beth A.

2012-01-01

Coastal salt marsh and mangrove ecosystems are particularly vulnerable to changes in atmospheric CO2 concentrations and associated climate and climate-induced changes. We provide a review of the literature detailing theoretical predictions and observed responses of coastal wetlands to a range of climate change stressors, including CO2, temperature, rainfall, and sea-level rise. This review incorporates a discussion of key processes controlling responses in different settings and thresholds of resilience derived from experimental and observational studies. We specifically consider the potential and observed effects on salt marsh and mangrove vegetation of changes in (1) elevated [CO2] on physiology, growth, and distribution; (2) temperature on distribution and diversity; (3) rainfall and salinity regimes on growth and competitive interactions; and (4) sea level on geomorphological, hydrological, and biological processes.

Crop Yield Predictions - High Resolution Statistical Model for Intra-season Forecasts Applied to Corn in the US

NASA Astrophysics Data System (ADS)

Cai, Y.

2017-12-01

Accurately forecasting crop yields has broad implications for economic trading, food production monitoring, and global food security. However, the variation of environmental variables presents challenges to model yields accurately, especially when the lack of highly accurate measurements creates difficulties in creating models that can succeed across space and time. In 2016, we developed a sequence of machine-learning based models forecasting end-of-season corn yields for the US at both the county and national levels. We combined machine learning algorithms in a hierarchical way, and used an understanding of physiological processes in temporal feature selection, to achieve high precision in our intra-season forecasts, including in very anomalous seasons. During the live run, we predicted the national corn yield within 1.40% of the final USDA number as early as August. In the backtesting of the 2000-2015 period, our model predicts national yield within 2.69% of the actual yield on average already by mid-August. At the county level, our model predicts 77% of the variation in final yield using data through the beginning of August and improves to 80% by the beginning of October, with the percentage of counties predicted within 10% of the average yield increasing from 68% to 73%. Further, the lowest errors are in the most significant producing regions, resulting in very high precision national-level forecasts. In addition, we identify the changes of important variables throughout the season, specifically early-season land surface temperature, and mid-season land surface temperature and vegetation index. For the 2017 season, we feed 2016 data to the training set, together with additional geospatial data sources, aiming to make the current model even more precise. We will show how our 2017 US corn yield forecasts converges in time, which factors affect the yield the most, as well as present our plans for 2018 model adjustments.

Effects of climate change on forest insect and disease outbreaks

Treesearch

David W. Williams; Robert P. Long; Philip M. Wargo; Andrew M. Liebhold

2000-01-01

General circulation models (GCMs) predict dramatic future changes in climate for the northeastern and north central United States under doubled carbon dioxide (CO2) levels (Hansen et al., 1984; Manabe and Wetherald, 1987; Wilson and Mitchell, 1987; Cubasch and Cess, 1990; Mitchell et al., 1990). January temperatures are projected to rise as much...

Understanding the science of climate change: Talking points - Impacts to the Gulf Coast

Treesearch

Rachel Loehman; Greer Anderson

2010-01-01

Predicted climate changes in the Gulf Coast bioregion include increased air and sea surface temperatures, altered fire regimes and rainfall patterns, increased frequency of extreme weather events, rising sea levels, increased hurricane intensity, and potential destruction of coastal wetlands and the species that reside within them. Prolonged drought conditions, storm...

Using Nitrogen Stable Isotope Tracers to Track Climate Change Impacts on Coastal Salt Marshes

EPA Science Inventory

Climate change impacts on coastal salt marshes are predicted to be complex and multi-faceted. In addition to rising sea level and warmer water temperatures, regional precipitation patterns are also expected to change. At least in the Northeast and Mid-Atlantic U.S., more severe s...

On the Dielectric Constant for Acetanilide: Experimental Measurements and Effect on Energy Transport

NASA Astrophysics Data System (ADS)

Careri, G.; Compatangelo, E.; Christiansen, P. L.; Halding, J.; Skovgaard, O.

1987-01-01

Experimental measurements of the dielectric constant for crystalline acetanilide powder for temperatures ranging from - 140°C to 20°C and for different hydration levels are presented. A Davydov-soliton computer model predicts dramatic changes in the energy transport and storage for typically increased values of the dielectric constant.

Trait-based framework to predict relative vulnerability of near-coastal species and habitats to climate change

EPA Science Inventory

Like Icarus, near-coastal species are “flying too close” to the sun, and are being impacted by climate-induced changes in air and ocean temperature, precipitation, salinity, ocean pH, and sea level rise. Sound management requires knowledge of what species and habitats...

Global performance enhancements via pedestal optimisation on ASDEX Upgrade

NASA Astrophysics Data System (ADS)

Dunne, M. G.; Frassinetti, L.; Beurskens, M. N. A.; Cavedon, M.; Fietz, S.; Fischer, R.; Giannone, L.; Huijsmans, G. T. A.; Kurzan, B.; Laggner, F.; McCarthy, P. J.; McDermott, R. M.; Tardini, G.; Viezzer, E.; Willensdorfer, M.; Wolfrum, E.; The EUROfusion MST1 Team; The ASDEX Upgrade Team

2017-02-01

Results of experimental scans of heating power, plasma shape, and nitrogen content are presented, with a focus on global performance and pedestal alteration. In detailed scans at low triangularity, it is shown that the increase in stored energy due to nitrogen seeding stems from the pedestal. It is also shown that the confinement increase is driven through the temperature pedestal at the three heating power levels studied. In a triangularity scan, an orthogonal effect of shaping and seeding is observed, where increased plasma triangularity increases the pedestal density, while impurity seeding (carbon and nitrogen) increases the pedestal temperature in addition to this effect. Modelling of these effects was also undertaken, with interpretive and predictive models being employed. The interpretive analysis shows a general agreement of the experimental pedestals in separate power, shaping, and seeding scans with peeling-ballooning theory. Predictive analysis was used to isolate the individual effects, showing that the trends of additional heating power and increased triangularity can be recoverd. However, a simple change of the effective charge in the plasma cannot explain the observed levels of confinement improvement in the present models.

Prognosis for a sick planet.

PubMed

Maslin, Mark

2008-12-01

Global warming is the most important science issue of the 21st century, challenging the very structure of our global society. The study of past climate has shown that the current global climate system is extremely sensitive to human-induced climate change. The burning of fossil fuels since the beginning of the industrial revolution has already caused changes with clear evidence for a 0.75 degrees C rise in global temperatures and 22 cm rise in sea level during the 20th century. The Intergovernmental Panel on Climate Change synthesis report (2007) predicts that global temperatures by 2100 could rise by between 1.1 degrees C and 6.4 degrees C. Sea level could rise by between 28 cm and 79 cm, more if the melting of the polar ice caps accelerates. In addition, weather patterns will become less predictable and the occurrence of extreme climate events, such as storms, floods, heat waves and droughts, will increase. The potential effects of global warming on human society are devastating. We do, however, already have many of the technological solutions to cure our sick planet.

Symbiont diversity may help coral reefs survive moderate climate change.

PubMed

Baskett, Marissa L; Gaines, Steven D; Nisbet, Roger M

2009-01-01

Given climate change, thermal stress-related mass coral-bleaching events present one of the greatest anthropogenic threats to coral reefs. While corals and their symbiotic algae may respond to future temperatures through genetic adaptation and shifts in community compositions, the climate may change too rapidly for coral response. To test this potential for response, here we develop a model of coral and symbiont ecological dynamics and symbiont evolutionary dynamics. Model results without variation in symbiont thermal tolerance predict coral reef collapse within decades under multiple future climate scenarios, consistent with previous threshold-based predictions. However, model results with genetic or community-level variation in symbiont thermal tolerance can predict coral reef persistence into the next century, provided low enough greenhouse gas emissions occur. Therefore, the level of greenhouse gas emissions will have a significant effect on the future of coral reefs, and accounting for biodiversity and biological dynamics is vital to estimating the size of this effect.

Explaining and modeling the concentration and loading of Escherichia coli in a stream-A case study.

PubMed

Wang, Chaozi; Schneider, Rebecca L; Parlange, Jean-Yves; Dahlke, Helen E; Walter, M Todd

2018-09-01

Escherichia coli (E. coli) level in streams is a public health indicator. Therefore, being able to explain why E. coli levels are sometimes high and sometimes low is important. Using citizen science data from Fall Creek in central NY we found that complementarily using principal component analysis (PCA) and partial least squares (PLS) regression provided insights into the drivers of E. coli and a mechanism for predicting E. coli levels, respectively. We found that stormwater, temperature/season and shallow subsurface flow are the three dominant processes driving the fate and transport of E. coli. PLS regression modeling provided very good predictions under stormwater conditions (R 2  = 0.85 for log (E. coli concentration) and R 2  = 0.90 for log (E. coli loading)); predictions under baseflow conditions were less robust. But, in our case, both E. coli concentration and E. coli loading were significantly higher under stormwater condition, so it is probably more important to predict high-flow E. coli hazards than low-flow conditions. Besides previously reported good indicators of in-stream E. coli level, nitrate-/nitrite-nitrogen and soluble reactive phosphorus were also found to be good indicators of in-stream E. coli levels. These findings suggest management practices to reduce E. coli concentrations and loads in-streams and, eventually, reduce the risk of waterborne disease outbreak. Copyright © 2018. Published by Elsevier B.V.

Prediction of microstructure, residual stress, and deformation in laser powder bed fusion process

NASA Astrophysics Data System (ADS)

Yang, Y. P.; Jamshidinia, M.; Boulware, P.; Kelly, S. M.

2018-05-01

Laser powder bed fusion (L-PBF) process has been investigated significantly to build production parts with a complex shape. Modeling tools, which can be used in a part level, are essential to allow engineers to fine tune the shape design and process parameters for additive manufacturing. This study focuses on developing modeling methods to predict microstructure, hardness, residual stress, and deformation in large L-PBF built parts. A transient sequentially coupled thermal and metallurgical analysis method was developed to predict microstructure and hardness on L-PBF built high-strength, low-alloy steel parts. A moving heat-source model was used in this analysis to accurately predict the temperature history. A kinetics based model which was developed to predict microstructure in the heat-affected zone of a welded joint was extended to predict the microstructure and hardness in an L-PBF build by inputting the predicted temperature history. The tempering effect resulting from the following built layers on the current-layer microstructural phases were modeled, which is the key to predict the final hardness correctly. It was also found that the top layers of a build part have higher hardness because of the lack of the tempering effect. A sequentially coupled thermal and mechanical analysis method was developed to predict residual stress and deformation for an L-PBF build part. It was found that a line-heating model is not suitable for analyzing a large L-PBF built part. The layer heating method is a potential method for analyzing a large L-PBF built part. The experiment was conducted to validate the model predictions.

Prediction of microstructure, residual stress, and deformation in laser powder bed fusion process

NASA Astrophysics Data System (ADS)

Yang, Y. P.; Jamshidinia, M.; Boulware, P.; Kelly, S. M.

2017-12-01

Laser powder bed fusion (L-PBF) process has been investigated significantly to build production parts with a complex shape. Modeling tools, which can be used in a part level, are essential to allow engineers to fine tune the shape design and process parameters for additive manufacturing. This study focuses on developing modeling methods to predict microstructure, hardness, residual stress, and deformation in large L-PBF built parts. A transient sequentially coupled thermal and metallurgical analysis method was developed to predict microstructure and hardness on L-PBF built high-strength, low-alloy steel parts. A moving heat-source model was used in this analysis to accurately predict the temperature history. A kinetics based model which was developed to predict microstructure in the heat-affected zone of a welded joint was extended to predict the microstructure and hardness in an L-PBF build by inputting the predicted temperature history. The tempering effect resulting from the following built layers on the current-layer microstructural phases were modeled, which is the key to predict the final hardness correctly. It was also found that the top layers of a build part have higher hardness because of the lack of the tempering effect. A sequentially coupled thermal and mechanical analysis method was developed to predict residual stress and deformation for an L-PBF build part. It was found that a line-heating model is not suitable for analyzing a large L-PBF built part. The layer heating method is a potential method for analyzing a large L-PBF built part. The experiment was conducted to validate the model predictions.

Level density inputs in nuclear reaction codes and the role of the spin cutoff parameter

DOE PAGES

Voinov, A. V.; Grimes, S. M.; Brune, C. R.; ...

2014-09-03

Here, the proton spectrum from the 57Fe(α,p) reaction has been measured and analyzed with the Hauser-Feshbach model of nuclear reactions. Different input level density models have been tested. It was found that the best description is achieved with either Fermi-gas or constant temperature model functions obtained by fitting them to neutron resonance spacing and to discrete levels and using the spin cutoff parameter with much weaker excitation energy dependence than it is predicted by the Fermi-gas model.

Analysis of Two-Phase Flow in Damper Seals for Cryogenic Turbopumps

NASA Technical Reports Server (NTRS)

Arauz, Grigory L.; SanAndres, Luis

1996-01-01

Cryogenic damper seals operating close to the liquid-vapor region (near the critical point or slightly su-cooled) are likely to present two-phase flow conditions. Under single phase flow conditions the mechanical energy conveyed to the fluid increases its temperature and causes a phase change when the fluid temperature reaches the saturation value. A bulk-flow analysis for the prediction of the dynamic force response of damper seals operating under two-phase conditions is presented as: all-liquid, liquid-vapor, and all-vapor, i.e. a 'continuous vaporization' model. The two phase region is considered as a homogeneous saturated mixture in thermodynamic equilibrium. Th flow in each region is described by continuity, momentum and energy transport equations. The interdependency of fluid temperatures and pressure in the two-phase region (saturated mixture) does not allow the use of an energy equation in terms of fluid temperature. Instead, the energy transport is expressed in terms of fluid enthalpy. Temperature in the single phase regions, or mixture composition in the two phase region are determined based on the fluid enthalpy. The flow is also regarded as adiabatic since the large axial velocities typical of the seal application determine small levels of heat conduction to the walls as compared to the heat carried by fluid advection. Static and dynamic force characteristics for the seal are obtained from a perturbation analysis of the governing equations. The solution expressed in terms of zeroth and first order fields provide the static (leakage, torque, velocity, pressure, temperature, and mixture composition fields) and dynamic (rotordynamic force coefficients) seal parameters. Theoretical predictions show good agreement with experimental leakage pressure profiles, available from a Nitrogen at cryogenic temperatures. Force coefficient predictions for two phase flow conditions show significant fluid compressibility effects, particularly for mixtures with low mass content of vapor. Under these conditions, an increase on direct stiffness and reduction of whirl frequency ratio are shown to occur. Prediction of such important effects will motivate experimental studies as well as a more judicious selection of the operating conditions for seals used in cryogenic turbomachinery.

DWPF STARTUP FRIT VISCOSITY MEASUREMENT ROUND ROBIN RESULTS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Crum, Jarrod V.; Edwards, Tommy B.; Russell, Renee L.

2012-07-31

A viscosity standard is needed to replace the National Institute of Standards and Technology (NIST) glasses currently being used to calibrate viscosity measurement equipment. The current NIST glasses are either unavailable or less than ideal for calibrating equipment to measure the viscosity of high-level waste glasses. This report documents the results of a viscosity round robin study conducted on the Defense Waste Processing Facility (DWPF) startup frit. DWPF startup frit was selected because its viscosity-temperature relationship is similar to most DWPF and Hanford high-level waste glass compositions. The glass underwent grinding and blending to homogenize the large (100 lb) batch.more » Portions of the batch were supplied to the laboratories (named A through H) for viscosity measurements following a specified temperature schedule with a temperature range of 1150 C to 950 C and with an option to measure viscosity at lower temperatures if their equipment was capable of measuring at the higher viscosities. Results were used to fit the Vogel-Tamman-Fulcher and Arrhenius equations to viscosity as a function of temperature for the entire temperature range of 460 C through 1250 C as well as the limited temperature interval of approximately 950 C through 1250 C. The standard errors for confidence and prediction were determined for the fitted models.« less

Type 2 diabetes, but not obesity, prevalence is positively associated with ambient temperature.

PubMed

Speakman, John R; Heidari-Bakavoli, Sahar

2016-08-01

Cold exposure stimulates energy expenditure and glucose disposal. If these factors play a significant role in whole body energy balance, and glucose homeostasis, it is predicted that both obesity and type 2 diabetes prevalence would be lower where it is colder. Previous studies have noted connections between ambient temperature and obesity, but the direction of the effect is confused. No previous studies have explored the link of type 2 diabetes to ambient temperature. We used county level data for obesity and diabetes prevalence across the mainland USA and matched this to county level ambient temperature data. Average ambient temperature explained 5.7% of the spatial variation in obesity and 29.6% of the spatial variation in type 2 diabetes prevalence. Correcting the type 2 diabetes data for the effect of obesity reduced the explained variation to 26.8%. Even when correcting for obesity, poverty and race, ambient temperature explained 12.4% of the variation in the prevalence of type 2 diabetes, and this significant effect remained when latitude was entered into the model as a predictor. When obesity prevalence was corrected for poverty and race the significant effect of temperature disappeared. Enhancing energy expenditure by cold exposure will likely not impact obesity significantly, but may be useful to combat type 2 diabetes.

Boron-tuning transition temperature of vanadium dioxide from rutile to monoclinic phase

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, J. J.; He, H. Y.; Xie, Y.

2014-11-21

The effect of the doped boron on the phase transition temperature between the monoclinic phase and the rutile phase of VO{sub 2} has been studied by performing first-principles calculations. It is found that the phase transition temperature decreases linearly with increasing the doping level of B in each system, no matter where the B atom is in the crystal. More importantly, the descent of the transition temperature is predicted to be as large as 83 K/at. % B, indicating that the boron concentration of only 0.5% can cause the phase transition at room temperature. These findings provide a new routinemore » of modulating the phase transition of VO{sub 2} and pave a way for the practicality of VO{sub 2} as an energy-efficient green material.« less

Effects of elevated pCO2 on physiological performance of marine microalgae Dunaliella salina (Chlorophyta, Chlorophyceae

NASA Astrophysics Data System (ADS)

Hu, Shunxin; Wang, You; Wang, Ying; Zhao, Yan; Zhang, Xinxin; Zhang, Yongsheng; Jiang, Ming; Tang, Xuexi

2018-03-01

The present study was conducted to determine the effects of elevated pCO2 on growth, photosynthesis, dark respiration and inorganic carbon acquisition in the marine microalga Dunaliella salina. To accomplish this, D. salina was incubated in semi-continuous cultures under present-day CO2 levels (390 μatm, pHNBS: 8.10), predicted year 2100 CO2 levels (1 000 μatm, pHNBS: 7.78) and predicted year 2300 CO2 levels (2 000 μatm, pHNBS: 7.49). Elevated pCO2 significantly enhanced photosynthesis (in terms of gross photosynthetic O2 evolution, effective quantum yield (Δ F/ F' m ), photosynthetic efficiency ( α), maximum relative electron transport rate (rETRmax) and ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) activity) and dark respiration of D. salina, but had insignificant effects on growth. The photosynthetic O2 evolution of D. salina was significantly inhibited by the inhibitors acetazolamide (AZ), ethoxyzolamide (EZ) and 4,4'-diisothiocyanostilbene-2,2'-disulfonate (DIDS), indicating that D. salina is capable of acquiring HCOˉ 3 via extracellular carbonic anhydrase and anion-exchange proteins. Furthermore, the lower inhibition of the photosynthetic O2 evolution at high pCO2 levels by AZ, EZ and DIDS and the decreased carbonic anhydrase showed that carbon concentrating mechanisms were down-regulated at high pCO2. In conclusion, our results show that photosynthesis, dark respiration and CCMs will be affected by the increased pCO2/low pH conditions predicted for the future, but that the responses of D. salina to high pCO2/low pH might be modulated by other environmental factors such as light, nutrients and temperature. Therefore, further studies are needed to determine the interactive effects of pCO2, temperature, light and nutrients on marine microalgae.

Effects of elevated pCO2 on physiological performance of marine microalgae Dunaliella salina (Chlorophyta, Chlorophyceae)

NASA Astrophysics Data System (ADS)

Hu, Shunxin; Wang, You; Wang, Ying; Zhao, Yan; Zhang, Xinxin; Zhang, Yongsheng; Jiang, Ming; Tang, Xuexi

2017-06-01

The present study was conducted to determine the effects of elevated pCO2 on growth, photosynthesis, dark respiration and inorganic carbon acquisition in the marine microalga Dunaliella salina. To accomplish this, D. salina was incubated in semi-continuous cultures under present-day CO2 levels (390 μatm, pHNBS: 8.10), predicted year 2100 CO2 levels (1 000 μatm, pHNBS: 7.78) and predicted year 2300 CO2 levels (2 000 μatm, pHNBS: 7.49). Elevated pCO2 significantly enhanced photosynthesis (in terms of gross photosynthetic O2 evolution, effective quantum yield (ΔF/F' m ), photosynthetic efficiency (α), maximum relative electron transport rate (rETRmax) and ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) activity) and dark respiration of D. salina, but had insignificant effects on growth. The photosynthetic O2 evolution of D. salina was significantly inhibited by the inhibitors acetazolamide (AZ), ethoxyzolamide (EZ) and 4,4'-diisothiocyanostilbene-2,2'-disulfonate (DIDS), indicating that D. salina is capable of acquiring HCO3 - via extracellular carbonic anhydrase and anion-exchange proteins. Furthermore, the lower inhibition of the photosynthetic O2 evolution at high pCO2 levels by AZ, EZ and DIDS and the decreased carbonic anhydrase showed that carbon concentrating mechanisms were down-regulated at high pCO2. In conclusion, our results show that photosynthesis, dark respiration and CCMs will be affected by the increased pCO2/low pH conditions predicted for the future, but that the responses of D. salina to high pCO2/low pH might be modulated by other environmental factors such as light, nutrients and temperature. Therefore, further studies are needed to determine the interactive effects of pCO2, temperature, light and nutrients on marine microalgae.

A regional neural network model for predicting mean daily river water temperature

USGS Publications Warehouse

Wagner, Tyler; DeWeber, Jefferson Tyrell

2014-01-01

Water temperature is a fundamental property of river habitat and often a key aspect of river resource management, but measurements to characterize thermal regimes are not available for most streams and rivers. As such, we developed an artificial neural network (ANN) ensemble model to predict mean daily water temperature in 197,402 individual stream reaches during the warm season (May–October) throughout the native range of brook trout Salvelinus fontinalis in the eastern U.S. We compared four models with different groups of predictors to determine how well water temperature could be predicted by climatic, landform, and land cover attributes, and used the median prediction from an ensemble of 100 ANNs as our final prediction for each model. The final model included air temperature, landform attributes and forested land cover and predicted mean daily water temperatures with moderate accuracy as determined by root mean squared error (RMSE) at 886 training sites with data from 1980 to 2009 (RMSE = 1.91 °C). Based on validation at 96 sites (RMSE = 1.82) and separately for data from 2010 (RMSE = 1.93), a year with relatively warmer conditions, the model was able to generalize to new stream reaches and years. The most important predictors were mean daily air temperature, prior 7 day mean air temperature, and network catchment area according to sensitivity analyses. Forest land cover at both riparian and catchment extents had relatively weak but clear negative effects. Predicted daily water temperature averaged for the month of July matched expected spatial trends with cooler temperatures in headwaters and at higher elevations and latitudes. Our ANN ensemble is unique in predicting daily temperatures throughout a large region, while other regional efforts have predicted at relatively coarse time steps. The model may prove a useful tool for predicting water temperatures in sampled and unsampled rivers under current conditions and future projections of climate and land use changes, thereby providing information that is valuable to management of river ecosystems and biota such as brook trout.

Estimation of cold stress effect on dairy cows

NASA Astrophysics Data System (ADS)

Brouček, J.; Letkovičová, M.; Kovalčuj, K.

1991-03-01

Twelve crossbred heifers (Slovak Spotted x Holstein-Friesian) were housed in an open, uninsulated barn with straw bedding and a concrete-floored yard. Minimum temperatures inside the barn were as low as -19°C. The average milk yield decreased as the temperatures approached these minima. Compared with the temperate conditions, the feed intake and blood levels of glucose and free fatty acids increased. The level of sodium declined significantly during the second cold period. Correlations and regressions between milk yield and biochemical parameters were calculated, and the results indicate that the concentrations of free fatty acids, cholesterol, and triiodothyronine and the haematocrit values may serve to predict milk production during periods of cold stress, or in lactations of 305 days.

Toward a Predictive Model of Arctic Coastal Retreat in a Warming Climate, Beaufort Sea, Alaska

DTIC Science & Technology

2012-09-30

Water level is modulated of the water level by waves and surge and tide. Melt rate is governed by an empirically based iceberg melting algorithm that...examination of enviornmental conditions, modified iceberg melting rules, and energy fluxes to the coast establish that water depth, water temperature and...photography, Arctic Alpine Antarctic Research 43(3): 474-484. (includes cover photo of this issue) Matell, N., R. S. Anderson, I. Overeem, C. Wobus

Study of degradation processes kinetics in ohmic contacts of resonant tunneling diodes based on nanoscale AlAs/GaAs heterostructures under influence of temperature

NASA Astrophysics Data System (ADS)

Makeev, M. O.; Meshkov, S. A.

2017-07-01

The artificial aging of resonant tunneling diodes based on nanoscale AlAs/GaAs heterostructures was conducted. As a result of the thermal influence resonant tunneling diodes IV curves degrade firstly due to ohmic contacts' degradation. To assess AlAs/GaAs resonant tunneling diodes degradation level and to predict their reliability, a functional dependence of the contact resistance of resonant tunneling diode AuGeNi ohmic contacts on time and temperature was offered.

The Climate Response to Stratospheric Aerosol Geoengineering Can Be Tailored Using Multiple Injection Locations

DOE Office of Scientific and Technical Information (OSTI.GOV)

MacMartin, Douglas G.; Kravitz, Ben; Tilmes, Simone

The climate response to geoengineering with stratospheric aerosols has the potential to be designed to achieve some chosen objectives. By injecting different amounts of SO2 at multiple different latitudes, the spatial pattern of aerosol optical depth (AOD) can be partially controlled. We use simulations from the fully-coupled whole-atmosphere chemistry-climate model CESM1(WACCM), to demonstrate that three spatial degrees of freedom of AOD can be achieved by appropriately combining injection at different locations: an approximately spatially-uniform AOD distribution, the relative difference in AOD between Northern and Southern hemispheres, and the relative AOD in high versus low latitudes. For forcing levels that yieldmore » 1–2°C cooling, the AOD and surface temperature response are sufficiently linear in this model so that many climate effects can be predicted from single-latitude injection simulations. Optimized injection at multiple locations is predicted to improve compensation of CO2-forced climate change, relative to a case using only equatorial aerosol injection. The additional degrees of freedom can be used, for example, to balance interhemispheric temperature differences and the equator to pole temperature difference in addition to the global mean temperature; this is projected in this model to reduce the mean-square error in temperature compensation by 30%.« less

Assimilation of Quality Controlled AIRS Temperature Profiles using the NCEP GFS

NASA Technical Reports Server (NTRS)

Susskind, Joel; Reale, Oreste; Iredell, Lena; Rosenberg, Robert

2013-01-01

We have previously conducted a number of data assimilation experiments using AIRS Version-5 quality controlled temperature profiles as a step toward finding an optimum balance of spatial coverage and sounding accuracy with regard to improving forecast skill. The data assimilation and forecast system we used was the Goddard Earth Observing System Model , Version-5 (GEOS-5) Data Assimilation System (DAS), which represents a combination of the NASA GEOS-5 forecast model with the National Centers for Environmental Prediction (NCEP) operational Grid Point Statistical Interpolation (GSI) global analysis scheme. All analyses and forecasts were run at a 0.5deg x 0.625deg spatial resolution. Data assimilation experiments were conducted in four different seasons, each in a different year. Three different sets of data assimilation experiments were run during each time period: Control; AIRS T(p); and AIRS Radiance. In the "Control" analysis, all the data used operationally by NCEP was assimilated, but no AIRS data was assimilated. Radiances from the Aqua AMSU-A instrument were also assimilated operationally by NCEP and are included in the "Control". The AIRS Radiance assimilation adds AIRS observed radiance observations for a select set of channels to the data set being assimilated, as done operationally by NCEP. In the AIRS T(p) assimilation, all information used in the Control was assimilated as well as Quality Controlled AIRS Version-5 temperature profiles, i.e., AIRS T(p) information was substituted for AIRS radiance information. The AIRS Version-5 temperature profiles were presented to the GSI analysis as rawinsonde profiles, assimilated down to a case-by-case appropriate pressure level p(sub best) determined using the Quality Control procedure. Version-5 also determines case-by-case, level-by-level error estimates of the temperature profiles, which were used as the uncertainty of each temperature measurement. These experiments using GEOS-5 have shown that forecasts resulting from analyses using the AIRS T(p) assimilation system were superior to those from the Radiance assimilation system, both with regard to global 7 day forecast skill and also the ability to predict storm tracks and intensity.

Prey size and availability limits maximum size of rainbow trout in a large tailwater: insights from a drift-foraging bioenergetics model

USGS Publications Warehouse

Dodrill, Michael J.; Yackulic, Charles B.; Kennedy, Theodore A.; Haye, John W

2016-01-01

The cold and clear water conditions present below many large dams create ideal conditions for the development of economically important salmonid fisheries. Many of these tailwater fisheries have experienced declines in the abundance and condition of large trout species, yet the causes of these declines remain uncertain. Here, we develop, assess, and apply a drift-foraging bioenergetics model to identify the factors limiting rainbow trout (Oncorhynchus mykiss) growth in a large tailwater. We explored the relative importance of temperature, prey quantity, and prey size by constructing scenarios where these variables, both singly and in combination, were altered. Predicted growth matched empirical mass-at-age estimates, particularly for younger ages, demonstrating that the model accurately describes how current temperature and prey conditions interact to determine rainbow trout growth. Modeling scenarios that artificially inflated prey size and abundance demonstrate that rainbow trout growth is limited by the scarcity of large prey items and overall prey availability. For example, shifting 10% of the prey biomass to the 13 mm (large) length class, without increasing overall prey biomass, increased lifetime maximum mass of rainbow trout by 88%. Additionally, warmer temperatures resulted in lower predicted growth at current and lower levels of prey availability; however, growth was similar across all temperatures at higher levels of prey availability. Climate change will likely alter flow and temperature regimes in large rivers with corresponding changes to invertebrate prey resources used by fish. Broader application of drift-foraging bioenergetics models to build a mechanistic understanding of how changes to habitat conditions and prey resources affect growth of salmonids will benefit management of tailwater fisheries.

Quantitative comparison of electron temperature fluctuations to nonlinear gyrokinetic simulations in C-Mod Ohmic L-mode discharges

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sung, C., E-mail: csung@physics.ucla.edu; White, A. E.; Greenwald, M.

2016-04-15

Long wavelength turbulent electron temperature fluctuations (k{sub y}ρ{sub s} < 0.3) are measured in the outer core region (r/a > 0.8) of Ohmic L-mode plasmas at Alcator C-Mod [E. S. Marmar et al., Nucl. Fusion 49, 104014 (2009)] with a correlation electron cyclotron emission diagnostic. The relative amplitude and frequency spectrum of the fluctuations are compared quantitatively with nonlinear gyrokinetic simulations using the GYRO code [J. Candy and R. E. Waltz, J. Comput. Phys. 186, 545 (2003)] in two different confinement regimes: linear Ohmic confinement (LOC) regime and saturated Ohmic confinement (SOC) regime. When comparing experiment with nonlinear simulations, it is found that local,more » electrostatic ion-scale simulations (k{sub y}ρ{sub s} ≲ 1.7) performed at r/a ∼ 0.85 reproduce the experimental ion heat flux levels, electron temperature fluctuation levels, and frequency spectra within experimental error bars. In contrast, the electron heat flux is robustly under-predicted and cannot be recovered by using scans of the simulation inputs within error bars or by using global simulations. If both the ion heat flux and the measured temperature fluctuations are attributed predominantly to long-wavelength turbulence, then under-prediction of electron heat flux strongly suggests that electron scale turbulence is important for transport in C-Mod Ohmic L-mode discharges. In addition, no evidence is found from linear or nonlinear simulations for a clear transition from trapped electron mode to ion temperature gradient turbulence across the LOC/SOC transition, and also there is no evidence in these Ohmic L-mode plasmas of the “Transport Shortfall” [C. Holland et al., Phys. Plasmas 16, 052301 (2009)].« less

Modeling of temperature-induced near-infrared and low-field time-domain nuclear magnetic resonance spectral variation: chemometric prediction of limonene and water content in spray-dried delivery systems.

PubMed

Andrade, Letícia; Farhat, Imad A; Aeberhardt, Kasia; Bro, Rasmus; Engelsen, Søren Balling

2009-02-01

The influence of temperature on near-infrared (NIR) and nuclear magnetic resonance (NMR) spectroscopy complicates the industrial applications of both spectroscopic methods. The focus of this study is to analyze and model the effect of temperature variation on NIR spectra and NMR relaxation data. Different multivariate methods were tested for constructing robust prediction models based on NIR and NMR data acquired at various temperatures. Data were acquired on model spray-dried limonene systems at five temperatures in the range from 20 degrees C to 60 degrees C and partial least squares (PLS) regression models were computed for limonene and water predictions. The predictive ability of the models computed on the NIR spectra (acquired at various temperatures) improved significantly when data were preprocessed using extended inverted signal correction (EISC). The average PLS regression prediction error was reduced to 0.2%, corresponding to 1.9% and 3.4% of the full range of limonene and water reference values, respectively. The removal of variation induced by temperature prior to calibration, by direct orthogonalization (DO), slightly enhanced the predictive ability of the models based on NMR data. Bilinear PLS models, with implicit inclusion of the temperature, enabled limonene and water predictions by NMR with an error of 0.3% (corresponding to 2.8% and 7.0% of the full range of limonene and water). For NMR, and in contrast to the NIR results, modeling the data using multi-way N-PLS improved the models' performance. N-PLS models, in which temperature was included as an extra variable, enabled more accurate prediction, especially for limonene (prediction error was reduced to 0.2%). Overall, this study proved that it is possible to develop models for limonene and water content prediction based on NIR and NMR data, independent of the measurement temperature.

Prediction of pathogen growth on iceberg lettuce under real temperature history during distribution from farm to table.

PubMed

Koseki, Shigenobu; Isobe, Seiichiro

2005-10-25

The growth of pathogenic bacteria Escherichia coli O157:H7, Salmonella spp., and Listeria monocytogenes on iceberg lettuce under constant and fluctuating temperatures was modelled in order to estimate the microbial safety of this vegetable during distribution from the farm to the table. Firstly, we examined pathogen growth on lettuce at constant temperatures, ranging from 5 to 25 degrees C, and then we obtained the growth kinetic parameters (lag time, maximum growth rate (micro(max)), and maximum population density (MPD)) using the Baranyi primary growth model. The parameters were similar to those predicted by the pathogen modelling program (PMP), with the exception of MPD. The MPD of each pathogen on lettuce was 2-4 log(10) CFU/g lower than that predicted by PMP. Furthermore, the MPD of pathogens decreased with decreasing temperature. The relationship between mu(max) and temperature was linear in accordance with Ratkowsky secondary model as was the relationship between the MPD and temperature. Predictions of pathogen growth under fluctuating temperature used the Baranyi primary microbial growth model along with the Ratkowsky secondary model and MPD equation. The fluctuating temperature profile used in this study was the real temperature history measured during distribution from the field at harvesting to the retail store. Overall predictions for each pathogen agreed well with observed viable counts in most cases. The bias and root mean square error (RMSE) of the prediction were small. The prediction in which mu(max) was based on PMP showed a trend of overestimation relative to prediction based on lettuce. However, the prediction concerning E. coli O157:H7 and Salmonella spp. on lettuce greatly overestimated growth in the case of a temperature history starting relatively high, such as 25 degrees C for 5 h. In contrast, the overall prediction of L. monocytogenes under the same circumstances agreed with the observed data.

An enhanced hydrogen adsorption enthalpy for fluoride intercalated graphite compounds.

PubMed

Cheng, Hansong; Sha, Xianwei; Chen, Liang; Cooper, Alan C; Foo, Maw-Lin; Lau, Garret C; Bailey, Wade H; Pez, Guido P

2009-12-16

We present a combined theoretical and experimental study on H(2) physisorption in partially fluorinated graphite. This material, first predicted computationally using ab initio molecular dynamics simulation and subsequently synthesized and characterized experimentally, represents a novel class of "acceptor type" graphite intercalated compounds that exhibit significantly higher isosteric heat of adsorption for H(2) at near ambient temperatures than previously demonstrated for commonly available porous carbon-based materials. The unusually strong interaction arises from the semi-ionic nature of the C-F bonds. Although a high H(2) storage capacity (>4 wt %) at room temperature is predicted not to be feasible due to the low heat of adsorption, enhanced storage properties can be envisaged by doping the graphitic host with appropriate species to promote higher levels of charge transfer from graphene to F(-) anions.

Numerical and experimental investigation of turbine blade film cooling

NASA Astrophysics Data System (ADS)

Berkache, Amar; Dizene, Rabah

2017-12-01

The blades in a gas turbine engine are exposed to extreme temperature levels that exceed the melting temperature of the material. Therefore, efficient cooling is a requirement for high performance of the gas turbine engine. The present study investigates film cooling by means of 3D numerical simulations using a commercial code: Fluent. Three numerical models, namely k-ɛ, RSM and SST turbulence models; are applied and then prediction results are compared to experimental measurements conducted by PIV technique. The experimental model realized in the ENSEMA laboratory uses a flat plate with several rows of staggered holes. The performance of the injected flow into the mainstream is analyzed. The comparison shows that the RANS closure models improve the over-predictions of center-line film cooling velocities that is caused by the limitations of the RANS method due to its isotropy eddy diffusivity.

A modified artificial neural network based prediction technique for tropospheric radio refractivity

PubMed Central

Javeed, Shumaila; Javed, Wajahat; Atif, M.; Uddin, Mueen

2018-01-01

Radio refractivity plays a significant role in the development and design of radio systems for attaining the best level of performance. Refractivity in the troposphere is one of the features affecting electromagnetic waves, and hence the communication system interrupts. In this work, a modified artificial neural network (ANN) based model is applied to predict the refractivity. The suggested ANN model comprises three modules: the data preparation module, the feature selection module, and the forecast module. The first module applies pre-processing to make the data compatible for the feature selection module. The second module discards irrelevant and redundant data from the input set. The third module uses ANN for prediction. The ANN model applies a sigmoid activation function and a multi-variate auto regressive model to update the weights during the training process. In this work, the refractivity is predicted and estimated based on ten years (2002–2011) of meteorological data, such as the temperature, pressure, and humidity, obtained from the Pakistan Meteorological Department (PMD), Islamabad. The refractivity is estimated using the method suggested by the International Telecommunication Union (ITU). The refractivity is predicted for the year 2012 using the database of the previous ten years, with the help of ANN. The ANN model is implemented in MATLAB. Next, the estimated and predicted refractivity levels are validated against each other. The predicted and actual values (PMD data) of the atmospheric parameters agree with each other well, and demonstrate the accuracy of the proposed ANN method. It was further found that all parameters have a strong relationship with refractivity, in particular the temperature and humidity. The refractivity values are higher during the rainy season owing to a strong association with the relative humidity. Therefore, it is important to properly cater the signal communication system during hot and humid weather. Based on the results, the proposed ANN method can be used to develop a refractivity database, which is highly important in a radio communication system. PMID:29494609

Temperatures in Excess of Critical Thresholds Threaten Nestling Growth and Survival in A Rapidly-Warming Arid Savanna: A Study of Common Fiscals

PubMed Central

Cunningham, Susan J.; Martin, Rowan O.; Hojem, Carryn L.

2013-01-01

Frequency, duration, and intensity of hot-weather events are all predicted to increase with climate warming. Despite this, mechanisms by which temperature increases affect individual fitness and drive population-level changes are poorly understood. We investigated the link between daily maximum air temperature (tmax) and breeding success of Kalahari common fiscals (Lanius collaris) in terms of the daily effect on nestling body-mass gain, and the cumulative effect on size and age of fledglings. High tmax reduced mass gain of younger, but not older nestlings and average nestling-period tmax did not affect fledgling size. Instead, the frequency with which tmax exceeded critical thresholds (tcrits) significantly reduced fledging body mass (tcrit = 33°C) and tarsus length (tcrit = 37°C), as well as delaying fledging (tcrit = 35°C). Nest failure risk was 4.2% per day therefore delays reduced fledging probability. Smaller size at fledging often correlates with reduced lifetime fitness and might also underlie documented adult body-size reductions in desert birds in relation to climate warming. Temperature thresholds above which organisms incur fitness costs are probably common, as physiological responses to temperature are non-linear. Understanding the shape of the relationship between temperature and fitness has implications for our ability to predict species’ responses to climate change. PMID:24040296

Temperature dependence of the hydrated electron's excited-state relaxation. I. Simulation predictions of resonance Raman and pump-probe transient absorption spectra of cavity and non-cavity models

NASA Astrophysics Data System (ADS)

Zho, Chen-Chen; Farr, Erik P.; Glover, William J.; Schwartz, Benjamin J.

2017-08-01

We use one-electron non-adiabatic mixed quantum/classical simulations to explore the temperature dependence of both the ground-state structure and the excited-state relaxation dynamics of the hydrated electron. We compare the results for both the traditional cavity picture and a more recent non-cavity model of the hydrated electron and make definite predictions for distinguishing between the different possible structural models in future experiments. We find that the traditional cavity model shows no temperature-dependent change in structure at constant density, leading to a predicted resonance Raman spectrum that is essentially temperature-independent. In contrast, the non-cavity model predicts a blue-shift in the hydrated electron's resonance Raman O-H stretch with increasing temperature. The lack of a temperature-dependent ground-state structural change of the cavity model also leads to a prediction of little change with temperature of both the excited-state lifetime and hot ground-state cooling time of the hydrated electron following photoexcitation. This is in sharp contrast to the predictions of the non-cavity model, where both the excited-state lifetime and hot ground-state cooling time are expected to decrease significantly with increasing temperature. These simulation-based predictions should be directly testable by the results of future time-resolved photoelectron spectroscopy experiments. Finally, the temperature-dependent differences in predicted excited-state lifetime and hot ground-state cooling time of the two models also lead to different predicted pump-probe transient absorption spectroscopy of the hydrated electron as a function of temperature. We perform such experiments and describe them in Paper II [E. P. Farr et al., J. Chem. Phys. 147, 074504 (2017)], and find changes in the excited-state lifetime and hot ground-state cooling time with temperature that match well with the predictions of the non-cavity model. In particular, the experiments reveal stimulated emission from the excited state with an amplitude and lifetime that decreases with increasing temperature, a result in contrast to the lack of stimulated emission predicted by the cavity model but in good agreement with the non-cavity model. Overall, until ab initio calculations describing the non-adiabatic excited-state dynamics of an excess electron with hundreds of water molecules at a variety of temperatures become computationally feasible, the simulations presented here provide a definitive route for connecting the predictions of cavity and non-cavity models of the hydrated electron with future experiments.

Met Éireann high resolution reanalysis for Ireland

NASA Astrophysics Data System (ADS)

Gleeson, Emily; Whelan, Eoin; Hanley, John

2017-03-01

The Irish Meteorological Service, Met Éireann, has carried out a 35-year very high resolution (2.5 km horizontal grid) regional climate reanalysis for Ireland using the ALADIN-HIRLAM numerical weather prediction system. This article provides an overview of the reanalysis, called MÉRA, as well as a preliminary analysis of surface parameters including screen level temperature, 10 m wind speeds, mean sea-level pressure (MSLP), soil temperatures, soil moisture and 24 h rainfall accumulations. The quality of the 3-D variational data assimilation used in the reanalysis is also assessed. Preliminary analysis shows that it takes almost 12 months to spin up the deep soil in terms of moisture, justifying the choice of running year-long spin up periods. Overall, the model performed consistently over the time period. Small biases were found in screen-level temperatures (less than -0.5 °C), MSLP (within 0.5 hPa) and 10 m wind speed (up to 0.5 m s-1) Soil temperatures are well represented by the model. 24 h accumulations of precipitation generally exhibit a small positive bias of ˜ 1 mm per day and negative biases over mountains due to a mismatch between the model orography and the geography of the region. MÉRA outperforms the ERA-Interim reanalysis, particularly in terms of standard deviations in screen-level temperatures and surface winds. This dataset is the first of its kind for Ireland that will be made publically available during spring 2017.

Thermal decomposition of ethanol. 4. Ab initio chemical kinetics for reactions of H atoms with CH3CH2O and CH3CHOH radicals.

PubMed

Xu, Z F; Xu, Kun; Lin, M C

2011-04-21

The potential energy surfaces of H-atom reactions with CH(3)CH(2)O and CH(3)CHOH, two major radicals in the decomposition and oxidation of ethanol, have been studied at the CCSD(T)/6-311+G(3df,2p) level of theory with geometric optimization carried out at the BH&HLYP/6-311+G(3df,2p) level. The direct hydrogen abstraction channels and the indirect association/decomposition channels from the chemically activated ethanol molecule have been considered for both reactions. The rate constants for both reactions have been calculated at 100-3000 K and 10(-4) Torr to 10(3) atm Ar pressure by microcanonical VTST/RRKM theory with master equation solution for all accessible product channels. The results show that the major product channel of the CH(3)CH(2)O + H reaction is CH(3) + CH(2)OH under atmospheric pressure conditions. Only at high pressure and low temperature, the rate constant for CH(3)CH(2)OH formation by collisonal deactivation becomes dominant. For CH(3)CHOH + H, there are three major product channels; at high temperatures, CH(3)+CH(2)OH production predominates at low pressures (P < 100 Torr), while the formation of CH(3)CH(2)OH by collisional deactivation becomes competitive at high pressures and low temperatures (T < 500 K). At high temperatures, the direct hydrogen abstraction reaction producing CH(2)CHOH + H(2) becomes dominant. Rate constants for all accessible product channels in both systems have been predicted and tabulated for modeling applications. The predicted value for CH(3)CHOH + H at 295 K and 1 Torr pressure agrees closely with available experimental data. For practical modeling applications, the rate constants for the thermal unimolecular decomposition of ethanol giving key accessible products have been predicted; those for the two major product channels taking place by dehydration and C-C breaking agree closely with available literature data.

Idiosyncratic Responses of High Arctic Plants to Changing Snow Regimes

PubMed Central

Rumpf, Sabine B.; Semenchuk, Philipp R.; Dullinger, Stefan; Cooper, Elisabeth J.

2014-01-01

The Arctic is one of the ecosystems most affected by climate change; in particular, winter temperatures and precipitation are predicted to increase with consequent changes to snow cover depth and duration. Whether the snow-free period will be shortened or prolonged depends on the extent and temporal patterns of the temperature and precipitation rise; resulting changes will likely affect plant growth with cascading effects throughout the ecosystem. We experimentally manipulated snow regimes using snow fences and shoveling and assessed aboveground size of eight common high arctic plant species weekly throughout the summer. We demonstrated that plant growth responded to snow regime, and that air temperature sum during the snow free period was the best predictor for plant size. The majority of our studied species showed periodic growth; increases in plant size stopped after certain cumulative temperatures were obtained. Plants in early snow-free treatments without additional spring warming were smaller than controls. Response to deeper snow with later melt-out varied between species and categorizing responses by growth forms or habitat associations did not reveal generic trends. We therefore stress the importance of examining responses at the species level, since generalized predictions of aboveground growth responses to changing snow regimes cannot be made. PMID:24523859

Idiosyncratic responses of high Arctic plants to changing snow regimes.

PubMed

Rumpf, Sabine B; Semenchuk, Philipp R; Dullinger, Stefan; Cooper, Elisabeth J

2014-01-01

The Arctic is one of the ecosystems most affected by climate change; in particular, winter temperatures and precipitation are predicted to increase with consequent changes to snow cover depth and duration. Whether the snow-free period will be shortened or prolonged depends on the extent and temporal patterns of the temperature and precipitation rise; resulting changes will likely affect plant growth with cascading effects throughout the ecosystem. We experimentally manipulated snow regimes using snow fences and shoveling and assessed aboveground size of eight common high arctic plant species weekly throughout the summer. We demonstrated that plant growth responded to snow regime, and that air temperature sum during the snow free period was the best predictor for plant size. The majority of our studied species showed periodic growth; increases in plant size stopped after certain cumulative temperatures were obtained. Plants in early snow-free treatments without additional spring warming were smaller than controls. Response to deeper snow with later melt-out varied between species and categorizing responses by growth forms or habitat associations did not reveal generic trends. We therefore stress the importance of examining responses at the species level, since generalized predictions of aboveground growth responses to changing snow regimes cannot be made.

Temperature-driven Topological Phase Transition in MoTe2

NASA Astrophysics Data System (ADS)

Notis Berger, Ayelet; Andrade, Erick; Kerelsky, Alex; Cheong, Sang-Wook; Li, Jian; Bernevig, B. Andrei; Pasupathy, Abhay

The discovery of several candidates predicted to be weyl semimetals has made it possible to experimentally study weyl fermions and their exotic properties. One example is MoTe2, a transition metal dichalcogenide. At temperatures below 240 K it is predicted to be a type II Weyl semimetal with four Weyl points close to the fermi level. As with most weyl semimetals, the complicated band structure causes difficulty in distinguishing features related to bulk states and those related to topological fermi arc surface states characteristic of weyl semimetals. MoTe2 is unique because of its temperature-driven phase change. At high temperatures, MoTe2 is monoclinic, with trivial surface states. When cooled below 240K, it undergoes a first order phase transition to become an orthorhombic weyl semimetal with topologically protected fermi arc surface states. We present STM and STS measurements on MoTe2 crystals in both states. In the orthorhombic phase, we observe scattering that is consistent with the presence of the Fermi-arc surface states. Upon warming into the monoclinic phase, these features disappear in the observed interference patterns, providing direct evidence of the topological nature of the fermi arcs in the Weyl phase

Investigation of detailed kinetic scheme performance on modelling of turbulent non-premixed sooting flames

NASA Astrophysics Data System (ADS)

Yunardi, Y.; Darmadi, D.; Hisbullah, H.; Fairweather, M.

2011-12-01

This paper presents the results of an application of a first-order conditional moment closure (CMC) approach coupled with a semi-empirical soot model to investigate the effect of various detailed combustion chemistry schemes on soot formation and destruction in turbulent non-premixed flames. A two-equation soot model representing soot particle nucleation, growth, coagulation and oxidation, was incorporated into the CMC model. The turbulent flow-field of both flames is described using the Favre-averaged fluid-flow equations, applying a standard k-ɛ turbulence model. A number of five reaction kinetic mechanisms having 50-100 species and 200-1000 elementary reactions called ABF, Miller-Bowman, GRI-Mech3.0, Warnatz, and Qin were employed to study the effect of combustion chemistry schemes on soot predictions. The results showed that of various kinetic schemes being studied, each yields similar accuracy in temperature prediction when compared with experimental data. With respect to soot prediction, the kinetic scheme containing benzene elementary reactions tends to result in a better prediction on soot concentrations in comparison to those contain no benzene elementary reactions. Among five kinetic mechanisms being studied, the Qin combustion scheme mechanism turned to yield the best prediction on both flame temperature and soot levels.

Modulation of Bjerknes feedback on the decadal variations in ENSO predictability

NASA Astrophysics Data System (ADS)

Zheng, Fei; Fang, Xiang-Hui; Zhu, Jiang; Yu, Jin-Yi; Li, Xi-Chen

2016-12-01

Clear decadal variations exist in the predictability of the El Niño-Southern Oscillation (ENSO), with the most recent decade having the lowest ENSO predictability in the past six decades. The Bjerknes Feedback (BF) intensity, which dominates the development of ENSO, has been proposed to determine ENSO predictability. Here we demonstrate that decadal variations in BF intensity are largely a result of the sensitivity of the zonal winds to the zonal sea level pressure (SLP) gradient in the equatorial Pacific. Furthermore, the results show that during low-ENSO predictability decades, zonal wind anomalies over the equatorial Pacific are more linked to SLP variations in the off-equatorial Pacific, which can then transfer this information into surface temperature and precipitation fields through the BF, suggesting a weakening in the ocean-atmosphere coupling in the tropical Pacific. This result indicates that more attention should be paid to off-equatorial processes in the prediction of ENSO.

Using GRACE and climate model simulations to predict mass loss of Alaskan glaciers through 2100

DOE PAGES

Wahr, John; Burgess, Evan; Swenson, Sean

2016-05-30

Glaciers in Alaska are currently losing mass at a rate of ~–50 Gt a –1, one of the largest ice loss rates of any regional collection of mountain glaciers on Earth. Existing projections of Alaska's future sea-level contributions tend to be divergent and are not tied directly to regional observations. Here we develop a simple, regional observation-based projection of Alaska's future sea-level contribution. We compute a time series of recent Alaska glacier mass variability using monthly GRACE gravity fields from August 2002 through December 2014. We also construct a three-parameter model of Alaska glacier mass variability based on monthly ERA-Interimmore » snowfall and temperature fields. When these three model parameters are fitted to the GRACE time series, the model explains 94% of the variance of the GRACE data. Using these parameter values, we then apply the model to simulated fields of monthly temperature and snowfall from the Community Earth System Model, to obtain predictions of mass variations through 2100. Here, we conclude that mass loss rates may increase between –80 and –110 Gt a –1by 2100, with a total sea-level rise contribution of 19 ± 4 mm during the 21st century.« less

Predicting low-temperature free energy landscapes with flat-histogram Monte Carlo methods

NASA Astrophysics Data System (ADS)

Mahynski, Nathan A.; Blanco, Marco A.; Errington, Jeffrey R.; Shen, Vincent K.

2017-02-01

We present a method for predicting the free energy landscape of fluids at low temperatures from flat-histogram grand canonical Monte Carlo simulations performed at higher ones. We illustrate our approach for both pure and multicomponent systems using two different sampling methods as a demonstration. This allows us to predict the thermodynamic behavior of systems which undergo both first order and continuous phase transitions upon cooling using simulations performed only at higher temperatures. After surveying a variety of different systems, we identify a range of temperature differences over which the extrapolation of high temperature simulations tends to quantitatively predict the thermodynamic properties of fluids at lower ones. Beyond this range, extrapolation still provides a reasonably well-informed estimate of the free energy landscape; this prediction then requires less computational effort to refine with an additional simulation at the desired temperature than reconstruction of the surface without any initial estimate. In either case, this method significantly increases the computational efficiency of these flat-histogram methods when investigating thermodynamic properties of fluids over a wide range of temperatures. For example, we demonstrate how a binary fluid phase diagram may be quantitatively predicted for many temperatures using only information obtained from a single supercritical state.

How Much Global Burned Area Can Be Forecast on Seasonal Time Scales Using Sea Surface Temperatures?

NASA Technical Reports Server (NTRS)

Chen, Yang; Morton, Douglas C.; Andela, Niels; Giglio, Louis; Randerson, James T.

2016-01-01

Large-scale sea surface temperature (SST) patterns influence the interannual variability of burned area in many regions by means of climate controls on fuel continuity, amount, and moisture content. Some of the variability in burned area is predictable on seasonal timescales because fuel characteristics respond to the cumulative effects of climate prior to the onset of the fire season. Here we systematically evaluated the degree to which annual burned area from the Global Fire Emissions Database version 4 with small fires (GFED4s) can be predicted using SSTs from 14 different ocean regions. We found that about 48 of global burned area can be forecast with a correlation coefficient that is significant at a p < 0.01 level using a single ocean climate index (OCI) 3 or more months prior to the month of peak burning. Continental regions where burned area had a higher degree of predictability included equatorial Asia, where 92% of the burned area exceeded the correlation threshold, and Central America, where 86% of the burned area exceeded this threshold. Pacific Ocean indices describing the El Nino-Southern Oscillation were more important than indices from other ocean basins, accounting for about 1/3 of the total predictable global burned area. A model that combined two indices from different oceans considerably improved model performance, suggesting that fires in many regions respond to forcing from more than one ocean basin. Using OCI-burned area relationships and a clustering algorithm, we identified 12 hotspot regions in which fires had a consistent response to SST patterns. Annual burned area in these regions can be predicted with moderate confidence levels, suggesting operational forecasts may be possible with the aim of improving ecosystem management.

Integrated Application of Random Forest and Artificial Neural Network Algorithms to Predict Viral Contamination in Coastal Waters

NASA Astrophysics Data System (ADS)

Shamkhali Chenar, S.; Deng, Z.

2017-12-01

Pathogenic viruses pose a significant public health threat and economic losses to shellfish industry in the coastal environment. Norovirus is a contagious virus and the leading cause of epidemic gastroenteritis following consumption of oysters harvested from sewage-contaminated waters. While it is challenging to detect noroviruses in coastal waters due to the lack of sensitive and routine diagnostic methods, machine learning techniques are allowing us to prevent or at least reduce the risks by developing effective predictive models. This study attempts to develop an algorithm between historical norovirus outbreak reports and environmental parameters including water temperature, solar radiation, water level, salinity, precipitation, and wind. For this purpose, the Random Forests statistical technique was utilized to select relevant environmental parameters and their various combinations with different time lags controlling the virus distribution in oyster harvesting areas along the Louisiana Coast. An Artificial Neural Networks (ANN) approach was then presented to predict the outbreaks using a final set of input variables. Finally, a sensitivity analysis was conducted to evaluate relative importance and contribution of the input variables to the model output. Findings demonstrated that the developed model was capable of reproducing historical oyster norovirus outbreaks along the Louisiana Coast with the overall accuracy of than 99.83%, demonstrating the efficacy of the model. Moreover, the increase in water temperature, solar radiation, water level, and salinity, and the decrease in wind and rainfall are associated with the reduction in the model-predicted risk of norovirus outbreak according to sensitivity analysis results. In conclusion, the presented machine learning approach provided reliable tools for predicting potential norovirus outbreaks and could be used for early detection of possible outbreaks and reduce the risk of norovirus to public health and the seafood industry.

Evaluation and Application of Gridded Snow Water Equivalent Products for Improving Snowmelt Flood Predictions in the Red River Basin of the North

NASA Astrophysics Data System (ADS)

Schroeder, R.; Jacobs, J. M.; Vuyovich, C.; Cho, E.; Tuttle, S. E.

2017-12-01

Each spring the Red River basin (RRB) of the North, located between the states of Minnesota and North Dakota and southern Manitoba, is vulnerable to dangerous spring snowmelt floods. Flat terrain, low permeability soils and a lack of satisfactory ground observations of snow pack conditions make accurate predictions of the onset and magnitude of major spring flood events in the RRB very challenging. This study investigated the potential benefit of using gridded snow water equivalent (SWE) products from passive microwave satellite missions and model output simulations to improve snowmelt flood predictions in the RRB using NOAA's operational Community Hydrologic Prediction System (CHPS). Level-3 satellite SWE products from AMSR-E, AMSR2 and SSM/I, as well as SWE computed from Level-2 brightness temperatures (Tb) measurements, including model output simulations of SWE from SNODAS and GlobSnow-2 were chosen to support the snowmelt modeling exercises. SWE observations were aggregated spatially (i.e. to the NOAA North Central River Forecast Center forecast basins) and temporally (i.e. by obtaining daily screened and weekly unscreened maximum SWE composites) to assess the value of daily satellite SWE observations relative to weekly maximums. Data screening methods removed the impacts of snow melt and cloud contamination on SWE and consisted of diurnal SWE differences and a temperature-insensitive polarization difference ratio, respectively. We examined the ability of the satellite and model output simulations to capture peak SWE and investigated temporal accuracies of screened and unscreened satellite and model output SWE. The resulting SWE observations were employed to update the SNOW-17 snow accumulation and ablation model of CHPS to assess the benefit of using temporally and spatially consistent SWE observations for snow melt predictions in two test basins in the RRB.

Application of the Systems Impact Assessment Model (SIAM) to Fishery Resource Issues in the Klamath River, California

USGS Publications Warehouse

Campbell, Sharon G.; Bartholow, John M.; Heasley, John

2010-01-01

At the request of two offices of the U.S. Fish and Wildlife Service (FWS) located in Yreka and Arcata, Calif., we applied the Systems Impact Assessment Model (SIAM) to analyze a variety of water management concerns associated with the Federal Energy Regulatory Commission (FERC) relicensing of the Klamath hydropower projects or with ongoing management of anadromous fish stocks in the mainstem Klamath River, Oregon and California. Requested SIAM analyses include predicted effects of reservoir withdrawal elevations, use of full active storage in Copco and Iron Gate Reservoirs to augment spring flows, and predicted spawning and juvenile outmigration timing of fall Chinook salmon. In an effort to further refine the analysis of spring flow effects on predicted fall Chinook production, additional SIAM analyses were performed for predicted response to spring flow release variability from Iron Gate Dam, high and low pulse flow releases, the predicted effects of operational constraints for both Upper Klamath Lake water surface elevations, and projected flow releases specified in the Klamath Project 2006 Operations Plan (April 10, 2006). Results of SIAM simulations to determine flow and water temperature relationships indicate that up to 4 degrees C of thermal variability can be attributed to flow variations, but the effect is seasonal. Much more of thermal variability can be attributed to air temperature variations, up to 6 degrees C. Reservoirs affect the annual thermal signature by delaying spring warming by about 3 weeks and fall cooling by about 2 weeks. Multi-level release outlets on Iron Gate Dam would have limited utility; however, if releases are small (700 cfs) and a near-surface and bottom-level outlet could be blended, then water temperature may be reduced by 2-4 degrees C for a 4-week period during September. Using the full active storage in Copco and Iron Gate Reservoir, although feasible, had undesirable ramifications such as earlier spring warming, loss of hydropower production, and inability to re-fill the reservoirs without causing shortages elsewhere in the system. Altering spawning and outmigration timing may be important management objectives for the salmon fishery, but difficult to implement. SIAM predicted benefits that might occur if water temperature was cooler in fall and spring emergence was advanced; however, model simulations were based on purely arbitrary thermal reductions. Spring flow variability did indicate that juvenile fall Chinook rearing habitat was the major biological 'bottleneck' for year class success. Rearing habitat is maximal in a range between 4,500 and 5,500 cfs below Iron Gate Dam. These flow levels are not typically provided by Klamath River system operations, except in very wet years. The incremental spring flow analysis provided insight into when and how long a pulse flow should occur to provide predicted fall Chinook salmon production increases. In general, March 15th - April 30th of any year was the period for pulse flows and 4000 cfs was the target flow release that provided near-optimal juvenile rearing habitat. Again, competition for water resources in the Klamath River Basin may make implementation of pulsed flows difficult.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blijderveen, Maarten van; University of Twente, Department of Thermal Engineering, Drienerlolaan 5, 7522 NB Enschede; Bramer, Eddy A.

Highlights: Black-Right-Pointing-Pointer We model piloted ignition times of wood and plastics. Black-Right-Pointing-Pointer The model is applied on a packed bed. Black-Right-Pointing-Pointer When the air flow is above a critical level, no ignition can take place. - Abstract: To gain insight in the startup of an incinerator, this article deals with piloted ignition. A newly developed model is described to predict the piloted ignition times of wood, PMMA and PVC. The model is based on the lower flammability limit and the adiabatic flame temperature at this limit. The incoming radiative heat flux, sample thickness and moisture content are some of themore » used variables. Not only the ignition time can be calculated with the model, but also the mass flux and surface temperature at ignition. The ignition times for softwoods and PMMA are mainly under-predicted. For hardwoods and PVC the predicted ignition times agree well with experimental results. Due to a significant scatter in the experimental data the mass flux and surface temperature calculated with the model are hard to validate. The model is applied on the startup of a municipal waste incineration plant. For this process a maximum allowable primary air flow is derived. When the primary air flow is above this maximum air flow, no ignition can be obtained.« less

Predicting bioactive glass properties from the molecular chemical composition: glass transition temperature.

PubMed

O'Donnell, Matthew D

2011-05-01

The glass transition temperature (T(g)) of inorganic glasses is an important parameter than can be used to correlate with other glass properties, such as dissolution rate, which governs in vitro and in vivo bioactivity. Seven bioactive glass compositional series reported in the literature (77 in total) were analysed here with T(g) values obtained by a number of different methods: differential thermal analysis, differential scanning calorimetry and dilatometry. An iterative least-squares fitting method was used to correlate T(g) from thermal analysis of these compositions with the levels of individual oxide and fluoride components in the glasses. When all seven series were fitted a reasonable correlation was found between calculated and experimental values (R(2)=0.89). When the two compositional series that were designed in weight percentages (the remaining five were designed in molar percentage) were removed from the model an improved fit was achieved (R(2)=0.97). This study shows that T(g) for a wide range in compositions (e.g. SiO(2) content of 37.3-68.4 mol.%) can be predicted to reasonable accuracy enabling processing parameters to be predicted such as annealing, fibre-drawing and sintering temperatures. Copyright © 2011 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Thermal behavior of crumb-rubber modified asphalt concrete mixtures

NASA Astrophysics Data System (ADS)

Epps, Amy Louise

Thermal cracking is one of the primary forms of distress in asphalt concrete pavements, resulting from either a single drop in temperature to an extreme low or from multiple temperature cycles above the fracture temperature of the asphalt-aggregate mixture. The first mode described is low temperature cracking; the second is thermal fatigue. The addition of crumb-rubber, manufactured from scrap tires, to the binder in asphalt concrete pavements has been suggested to minimize both types of thermal cracking. Four experiments were designed and completed to evaluate the thermal behavior of crumb-rubber modified (CRM) asphalt-aggregate mixtures. Modified and unmodified mixture response to thermal stresses was measured in four laboratory tests. The Thermal Stress Restrained Specimen Test (TSRST) and the Indirect Tensile Test (IDT) were used to compare mixture resistance to low temperature cracking. Modified mixtures showed improved performance, and cooling rate did not affect mixture resistance according to the statistical analysis. Therefore results from tests with faster rates can predict performance under slower field rates. In comparison, predicted fracture temperatures and stresses (IDT) were generally higher than measured values (TSRST). In addition, predicted fracture temperatures from binder test results demonstrated that binder testing alone is not sufficient to evaluate CRM mixtures. Thermal fatigue was explored in the third experiment using conventional load-induced fatigue tests with conditions selected to simulate daily temperature fluctuations. Test results indicated that thermal fatigue may contribute to transverse cracking in asphalt pavements. Both unmodified and modified mixtures had a finite capacity to withstand daily temperature fluctuations coupled with cold temperatures. Modified mixtures again exhibited improved performance. The fourth experiment examined fracture properties of modified and unmodified mixtures using a common fracture toughness test. Results showed no effect from modification, but the small experiment size may have masked this effect. Reliability concepts were introduced to include risk and uncertainty in a comparison of mixture response measured in the laboratory and estimated environmental conditions. This comparison provided evidence that CRM mixtures exhibit improved resistance to both types of thermal cracking at high levels of reliability. In conclusion, a mix design and analysis framework for evaluating thermal behavior was recommended.

Chemical indicators of subsurface temperature applied to hot spring waters of Yellowstone National Park, Wyoming, U.S.A.

USGS Publications Warehouse

Fournier, R.O.; Truesdell, A.H.

1970-01-01

Under favorable conditions the chemistry of hot springs may give reliable indications of subsurface temperatures and circulation patterns. These chemical indicators can be classified by the type of process involved: {A table is presented}. All these indicators have certain limitations. The silica geothermometer gives results independent of the local mineral suite and gas partial pressures, but may be affected by dilution. Alkali ratios are strongly affected by the local mineral suite and the formation of complex ions. Carbonate-chloride ratios are strongly affected by subsurface PCO2. The relative concentration of volatiles can be very misleading in high-pressure liquid systems. In Yellowstone National Park most thermal waters issue from hot, shallow aquifers with pressures in excess of hydrostatic by 2 to 6 bars and with large flows (the flow of hot spring water from the Park is greater than 4000 liters per second). These conditions should be ideal for the use of chemical indicators to estimate aquifer temperatures. In five drill holes aquifer temperatures were within 2??C of that predicted from the silica content of nearby hot springs; the temperature level off at a lower value than predicted in only one hole, and in four other holes drilling was terminated before the predicted aquifer temperature was reached. The temperature-Na/K ratio relationship does not follow any published experimental or empirical curve for water-feldspar or water-clay reactions. We suspect that ion exchange reactions involving zeolites in the Yellowstone rocks result in higher Na/K ratios at given temperatures than result from feldspar or clay reactions. Comparison of SiO2 and Cl/(HCO3 + CO3) suggest that because of higher subsurface PCO2 in Upper Geyser Basin a given Cl/(HCO3 + CO3) ratio there means a higher temperature than in Lower Geyser Basin. No correlation was found in Yellowstone Park between the subsurface regions of highest temperature and the relative concentration of volatile components such as boron and ammonia. ?? 1971.

Development of self-powered wireless high temperature electrochemical sensor for in situ corrosion monitoring of coal-fired power plant.

PubMed

Aung, Naing Naing; Crowe, Edward; Liu, Xingbo

2015-03-01

Reliable wireless high temperature electrochemical sensor technology is needed to provide in situ corrosion information for optimal predictive maintenance to ensure a high level of operational effectiveness under the harsh conditions present in coal-fired power generation systems. This research highlights the effectiveness of our novel high temperature electrochemical sensor for in situ coal ash hot corrosion monitoring in combination with the application of wireless communication and an energy harvesting thermoelectric generator (TEG). This self-powered sensor demonstrates the successful wireless transmission of both corrosion potential and corrosion current signals to a simulated control room environment. Copyright © 2014 ISA. All rights reserved.

Fundamental studies on the nature and properties of ceramic fiber insulation

NASA Technical Reports Server (NTRS)

Mueller, J. I.; Whittemore, O. J., Jr.; Scott, W. D.; Miller, A. D.; Smiser, L. W.; Leiser, D. B.

1975-01-01

Silica and mullite fibers used to fabricate reusable surface insulation (RSI) for the space shuttle orbiter may devitrify/recrystallize within the temperature range anticipated upon reentry. This is shown to be dependent upon impurity level, temperature, and time at temperature. It is determined that the effects of the material improvement and optimization program are positive. The degree of crystallinity is shown to have a predominant effect upon the strength of fabricated RSI tile, and limits are determined. Models are developed to predict tensile strengths and shrinkage rates of silica tile based upon readily measurable parameters. Thermal cycling which simulates reentry results in an increase in the crystallinity and in the porosity of tile coatings.

An energy balance climate model with cloud feedbacks

NASA Technical Reports Server (NTRS)

Roads, J. O.; Vallis, G. K.

1984-01-01

The present two-level global climate model, which is based on the atmosphere-surface energy balance, includes physically based parameterizations for the exchange of heat and moisture across latitude belts and between the surface and the atmosphere, precipitation and cloud formation, and solar and IR radiation. The model field predictions obtained encompass surface and atmospheric temperature, precipitation, relative humidity, and cloudiness. In the model integrations presented, it is noted that cloudiness is generally constant with changing temperature at low latitudes. High altitude cloudiness increases with temperature, although the cloud feedback effect on the radiation field remains small because of compensating effects on thermal and solar radiation. The net global feedback by the cloud field is negative, but small.

Biomass-C specific temperature responses of microbial C transformations reveal consistency regardless of microbial community structure across diverse timescales of inquiry

NASA Astrophysics Data System (ADS)

Min, K.; Buckeridge, K. M.; Ziegler, S. E.; Edwards, K. A.; Bagchi, S.; Billings, S. A.

2016-12-01

The responses of heterotrophic microbial process rates to temperature in soils are often investigated in the short-term (hours to months), making it difficult to predict longer-term temperature responses. Here, we integrate the temperature sensitivity obtained from the Arrhenius model with the concepts of microbial resistance, resilience, and susceptibility to assess temporal dynamics of microbial temperature responses. We collected soils along a boreal forest climate gradient (long-term effect), and quantified exo-enzyme activities and CO2 respiration at 5, 15, and 25°C for 84 days (relatively short-term effect). Microbial process rates were examined at two levels (per g microbial biomass-C; and per g dry soil) along with community structure, to characterize driving mechanisms for temporal patterns (e.g., size of biomass, physiological plasticity, community composition). Although temperature sensitivity of exo-enzyme activities on a per g dry soil basis showed both resistance and resilience depending on the types of exo-enzyme, biomass -C-specific responses always exhibited resistance regardless of distinct community composition. Temperature sensitivity of CO2 respiration was constant across time and different communities at both units. This study advances our knowledge in two ways. First, resistant temperature sensitivity of exo-enzymes and respiration at biomass-C specific level across distinct communities and diverse timescales indicates a common relationship between microbial physiology and temperature at a fundamental level, a useful feature allowing microbial process models to be reasonably simplified. Second, different temporal responses of exo-enzymes depending on the unit selected provide a cautionary tale for those projecting future microbial behaviors, because interpretation of ecosystem process rates may vary with the unit of observation.

Predicting East African spring droughts using Pacific and Indian Ocean sea surface temperature indices

NASA Astrophysics Data System (ADS)

Funk, C.; Hoell, A.; Shukla, S.; Bladé, I.; Liebmann, B.; Roberts, J. B.; Robertson, F. R.; Husak, G.

2014-03-01

In southern Ethiopia, Eastern Kenya, and southern Somalia, poor boreal spring rains in 1999, 2000, 2004, 2007, 2008, 2009, and 2011 contributed to severe food insecurity and high levels of malnutrition. Predicting rainfall deficits in this region on seasonal and decadal time frames can help decision makers implement disaster risk reduction measures while guiding climate-smart adaptation and agricultural development. Building on recent research that links more frequent droughts in that region to a stronger Walker Circulation, warming in the Indo-Pacific warm pool, and an increased western Pacific sea surface temperature (SST) gradient, we show that the two dominant modes of East African boreal spring rainfall variability are tied, respectively, to western-central Pacific and central Indian Ocean SST. Variations in these rainfall modes can be predicted using two previously defined SST indices - the West Pacific Gradient (WPG) and Central Indian Ocean index (CIO), with the WPG and CIO being used, respectively, to predict the first and second rainfall modes. These simple indices can be used in concert with more sophisticated coupled modeling systems and land surface data assimilations to help inform early warning and guide climate outlooks.

Simulated GOLD Observations of Atmospheric Waves

NASA Astrophysics Data System (ADS)

Correira, J.; Evans, J. S.; Lumpe, J. D.; Rusch, D. W.; Chandran, A.; Eastes, R.; Codrescu, M.

2016-12-01

The Global-scale Observations of the Limb and Disk (GOLD) mission will measure structures in the Earth's airglow layer due to dynamical forcing by vertically and horizontally propagating waves. These measurements focus on global-scale structures, including compositional and temperature responses resulting from dynamical forcing. Daytime observations of far-UV emissions by GOLD will be used to generate two-dimensional maps of the ratio of atomic oxygen and molecular nitrogen column densities (ΣO/N2 ) as well as neutral temperature that provide signatures of large-scale spatial structure. In this presentation, we use simulations to demonstrate GOLD's capability to deduce periodicities and spatial dimensions of large-scale waves from the spatial and temporal evolution observed in composition and temperature maps. Our simulations include sophisticated forward modeling of the upper atmospheric airglow that properly accounts for anisotropy in neutral and ion composition, temperature, and solar illumination. Neutral densities and temperatures used in the simulations are obtained from global circulation and climatology models that have been perturbed by propagating waves with a range of amplitudes, periods, and sources of excitation. Modeling of airglow emission and predictions of ΣO/N2 and neutral temperatures are performed with the Atmospheric Ultraviolet Radiance Integrated Code (AURIC) and associated derived product algorithms. Predicted structure in ΣO/N2 and neutral temperature due to dynamical forcing by propagating waves is compared to existing observations. Realistic GOLD Level 2 data products are generated from simulated airglow emission using algorithm code that will be implemented operationally at the GOLD Science Data Center.

Improved management of small pelagic fisheries through seasonal climate prediction.

PubMed

Tommasi, Désirée; Stock, Charles A; Pegion, Kathleen; Vecchi, Gabriel A; Methot, Richard D; Alexander, Michael A; Checkley, David M

2017-03-01

Populations of small pelagic fish are strongly influenced by climate. The inability of managers to anticipate environment-driven fluctuations in stock productivity or distribution can lead to overfishing and stock collapses, inflexible management regulations inducing shifts in the functional response to human predators, lost opportunities to harvest populations, bankruptcies in the fishing industry, and loss of resilience in the human food supply. Recent advances in dynamical global climate prediction systems allow for sea surface temperature (SST) anomaly predictions at a seasonal scale over many shelf ecosystems. Here we assess the utility of SST predictions at this "fishery relevant" scale to inform management, using Pacific sardine as a case study. The value of SST anomaly predictions to management was quantified under four harvest guidelines (HGs) differing in their level of integration of SST data and predictions. The HG that incorporated stock biomass forecasts informed by skillful SST predictions led to increases in stock biomass and yield, and reductions in the probability of yield and biomass falling below socioeconomic or ecologically acceptable levels. However, to mitigate the risk of collapse in the event of an erroneous forecast, it was important to combine such forecast-informed harvest controls with additional harvest restrictions at low biomass. © 2016 by the Ecological Society of America.

Eutrophication effects on greenhouse gas fluxes from shallow-lake mesocosms override those of climate warming.

PubMed

Davidson, Thomas A; Audet, Joachim; Svenning, Jens-Christian; Lauridsen, Torben L; Søndergaard, Martin; Landkildehus, Frank; Larsen, Søren E; Jeppesen, Erik

2015-12-01

Fresh waters make a disproportionately large contribution to greenhouse gas (GHG) emissions, with shallow lakes being particular hot spots. Given their global prevalence, how GHG fluxes from shallow lakes are altered by climate change may have profound implications for the global carbon cycle. Empirical evidence for the temperature dependence of the processes controlling GHG production in natural systems is largely based on the correlation between seasonal temperature variation and seasonal change in GHG fluxes. However, ecosystem-level GHG fluxes could be influenced by factors, which while varying seasonally with temperature are actually either indirectly related (e.g. primary producer biomass) or largely unrelated to temperature, for instance nutrient loading. Here, we present results from the longest running shallow-lake mesocosm experiment which demonstrate that nutrient concentrations override temperature as a control of both the total and individual GHG flux. Furthermore, testing for temperature treatment effects at low and high nutrient levels separately showed only one, rather weak, positive effect of temperature (CH4 flux at high nutrients). In contrast, at low nutrients, the CO2 efflux was lower in the elevated temperature treatments, with no significant effect on CH4 or N2 O fluxes. Further analysis identified possible indirect effects of temperature treatment. For example, at low nutrient levels, increased macrophyte abundance was associated with significantly reduced fluxes of both CH4 and CO2 for both total annual flux and monthly observation data. As macrophyte abundance was positively related to temperature treatment, this suggests the possibility of indirect temperature effects, via macrophyte abundance, on CH4 and CO2 flux. These findings indicate that fluxes of GHGs from shallow lakes may be controlled more by factors indirectly related to temperature, in this case nutrient concentration and the abundance of primary producers. Thus, at ecosystem scale, response to climate change may not follow predictions based on the temperature dependence of metabolic processes. © 2015 John Wiley & Sons Ltd.

Age-stage, two-sex life table of Parapoynx crisonalis (Lepidoptera: Pyralidae) at different temperatures

PubMed Central

Chen, Qi; Li, Ni; Wang, Xing; Ma, Li; Huang, Jian-Bin; Huang, Guo-Hua

2017-01-01

Parapoynx crisonalis is an important pest of many aquatic vegetables including water chestnuts. Understanding the relationship between temperature variations and the population growth rates of P. crisonalis is essential to predicting its population dynamics in water chestnuts ponds. These relationships were examined in this study based on the age-stage, two-sex life table of P. crisonalis developed in the laboratory at 21, 24, 27, 30, 33 and 36°C. The results showed that the values of Sxj (age-stage–specific survival rate), fxj (age-stage-specific fecundity), lx (age specific survival rate) and mx (age-specific fecundity) increased as the temperature rose from 21 to 27°C, then decreased from 30 to 36°C. Temperature also had a significant effect on the net reproductive rate (R0), gross reproductive rate (GRR), intrinsic rate of increase (r) and finite rate of increase (λ). The value of these parameters were at low levels at 21, 33, and 36°C. Further, the r value decreased as the temperature rose from 24 to 30°C, while the GRR reached its highest level at 27°C. The results indicated that optimal growth and development of P. crisonalis occurred at temperatures between 24°C to 30°C when compared to the lowest temperature (21°C) and higher temperatures of 33°C and 36°C. PMID:28264022

Prediction of L70 lumen maintenance and chromaticity for LEDs using extended Kalman filter models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lall, Pradeep; Wei, Junchao; Davis, Lynn

2013-09-30

Solid-state lighting (SSL) luminaires containing light emitting diodes (LEDs) have the potential of seeing excessive temperatures when being transported across country or being stored in non-climate controlled warehouses. They are also being used in outdoor applications in desert environments that see little or no humidity but will experience extremely high temperatures during the day. This makes it important to increase our understanding of what effects high temperature exposure for a prolonged period of time will have on the usability and survivability of these devices. Traditional light sources “burn out” at end-of-life. For an incandescent bulb, the lamp life is definedmore » by B50 life. However, the LEDs have no filament to “burn”. The LEDs continually degrade and the light output decreases eventually below useful levels causing failure. Presently, the TM-21 test standard is used to predict the L70 life of LEDs from LM-80 test data. Several failure mechanisms may be active in a LED at a single time causing lumen depreciation. The underlying TM-21 Model may not capture the failure physics in presence of multiple failure mechanisms. Correlation of lumen maintenance with underlying physics of degradation at system-level is needed. In this paper, Kalman Filter (KF) and Extended Kalman Filters (EKF) have been used to develop a 70-percent Lumen Maintenance Life Prediction Model for LEDs used in SSL luminaires. Ten-thousand hour LM-80 test data for various LEDs have been used for model development. System state at each future time has been computed based on the state space at preceding time step, system dynamics matrix, control vector, control matrix, measurement matrix, measured vector, process noise and measurement noise. The future state of the lumen depreciation has been estimated based on a second order Kalman Filter model and a Bayesian Framework. The measured state variable has been related to the underlying damage using physics-based models. Life prediction of L70 life for the LEDs used in SSL luminaires from KF and EKF based models have been compared with the TM-21 model predictions and experimental data.« less

L70 life prediction for solid state lighting using Kalman Filter and Extended Kalman Filter based models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lall, Pradeep; Wei, Junchao; Davis, Lynn

2013-08-08

Solid-state lighting (SSL) luminaires containing light emitting diodes (LEDs) have the potential of seeing excessive temperatures when being transported across country or being stored in non-climate controlled warehouses. They are also being used in outdoor applications in desert environments that see little or no humidity but will experience extremely high temperatures during the day. This makes it important to increase our understanding of what effects high temperature exposure for a prolonged period of time will have on the usability and survivability of these devices. Traditional light sources “burn out” at end-of-life. For an incandescent bulb, the lamp life is definedmore » by B50 life. However, the LEDs have no filament to “burn”. The LEDs continually degrade and the light output decreases eventually below useful levels causing failure. Presently, the TM-21 test standard is used to predict the L70 life of LEDs from LM-80 test data. Several failure mechanisms may be active in a LED at a single time causing lumen depreciation. The underlying TM-21 Model may not capture the failure physics in presence of multiple failure mechanisms. Correlation of lumen maintenance with underlying physics of degradation at system-level is needed. In this paper, Kalman Filter (KF) and Extended Kalman Filters (EKF) have been used to develop a 70-percent Lumen Maintenance Life Prediction Model for LEDs used in SSL luminaires. Ten-thousand hour LM-80 test data for various LEDs have been used for model development. System state at each future time has been computed based on the state space at preceding time step, system dynamics matrix, control vector, control matrix, measurement matrix, measured vector, process noise and measurement noise. The future state of the lumen depreciation has been estimated based on a second order Kalman Filter model and a Bayesian Framework. The measured state variable has been related to the underlying damage using physics-based models. Life prediction of L70 life for the LEDs used in SSL luminaires from KF and EKF based models have been compared with the TM-21 model predictions and experimental data.« less

Prediction of Lumen Output and Chromaticity Shift in LEDs Using Kalman Filter and Extended Kalman Filter Based Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lall, Pradeep; Wei, Junchao; Davis, J Lynn

2014-06-24

Abstract— Solid-state lighting (SSL) luminaires containing light emitting diodes (LEDs) have the potential of seeing excessive temperatures when being transported across country or being stored in non-climate controlled warehouses. They are also being used in outdoor applications in desert environments that see little or no humidity but will experience extremely high temperatures during the day. This makes it important to increase our understanding of what effects high temperature exposure for a prolonged period of time will have on the usability and survivability of these devices. Traditional light sources “burn out” at end-of-life. For an incandescent bulb, the lamp life ismore » defined by B50 life. However, the LEDs have no filament to “burn”. The LEDs continually degrade and the light output decreases eventually below useful levels causing failure. Presently, the TM-21 test standard is used to predict the L70 life of LEDs from LM-80 test data. Several failure mechanisms may be active in a LED at a single time causing lumen depreciation. The underlying TM-21 Model may not capture the failure physics in presence of multiple failure mechanisms. Correlation of lumen maintenance with underlying physics of degradation at system-level is needed. In this paper, Kalman Filter (KF) and Extended Kalman Filters (EKF) have been used to develop a 70-percent Lumen Maintenance Life Prediction Model for LEDs used in SSL luminaires. Ten-thousand hour LM-80 test data for various LEDs have been used for model development. System state at each future time has been computed based on the state space at preceding time step, system dynamics matrix, control vector, control matrix, measurement matrix, measured vector, process noise and measurement noise. The future state of the lumen depreciation has been estimated based on a second order Kalman Filter model and a Bayesian Framework. Life prediction of L70 life for the LEDs used in SSL luminaires from KF and EKF based models have been compared with the TM-21 model predictions and experimental data.« less

The Coastal Ocean Prediction Systems program: Understanding and managing our coastal ocean

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eden, H.F.; Mooers, C.N.K.

1990-06-01

The goal of COPS is to couple a program of regular observations to numerical models, through techniques of data assimilation, in order to provide a predictive capability for the US coastal ocean including the Great Lakes, estuaries, and the entire Exclusive Economic Zone (EEZ). The objectives of the program include: determining the predictability of the coastal ocean and the processes that govern the predictability; developing efficient prediction systems for the coastal ocean based on the assimilation of real-time observations into numerical models; and coupling the predictive systems for the physical behavior of the coastal ocean to predictive systems for biological,more » chemical, and geological processes to achieve an interdisciplinary capability. COPS will provide the basis for effective monitoring and prediction of coastal ocean conditions by optimizing the use of increased scientific understanding, improved observations, advanced computer models, and computer graphics to make the best possible estimates of sea level, currents, temperatures, salinities, and other properties of entire coastal regions.« less

Assessing Confidence in Pliocene Sea Surface Temperatures to Evaluate Predictive Models

NASA Technical Reports Server (NTRS)

Dowsett, Harry J.; Robinson, Marci M.; Haywood, Alan M.; Hill, Daniel J.; Dolan, Aisling. M.; Chan, Wing-Le; Abe-Ouchi, Ayako; Chandler, Mark A.; Rosenbloom, Nan A.; Otto-Bliesner, Bette L.;

Assessing confidence in Pliocene sea surface temperatures to evaluate predictive models

USGS Publications Warehouse

Dowsett, Harry J.; Robinson, Marci M.; Haywood, Alan M.; Hill, Daniel J.; Dolan, Aisling M.; Stoll, Danielle K.; Chan, Wing-Le; Abe-Ouchi, Ayako; Chandler, Mark A.; Rosenbloom, Nan A.; Otto-Bliesner, Bette L.; Bragg, Fran J.; Lunt, Daniel J.; Foley, Kevin M.; Riesselman, Christina R.

2012-01-01

In light of mounting empirical evidence that planetary warming is well underway, the climate research community looks to palaeoclimate research for a ground-truthing measure with which to test the accuracy of future climate simulations. Model experiments that attempt to simulate climates of the past serve to identify both similarities and differences between two climate states and, when compared with simulations run by other models and with geological data, to identify model-specific biases. Uncertainties associated with both the data and the models must be considered in such an exercise. The most recent period of sustained global warmth similar to what is projected for the near future occurred about 3.3–3.0 million years ago, during the Pliocene epoch. Here, we present Pliocene sea surface temperature data, newly characterized in terms of level of confidence, along with initial experimental results from four climate models. We conclude that, in terms of sea surface temperature, models are in good agreement with estimates of Pliocene sea surface temperature in most regions except the North Atlantic. Our analysis indicates that the discrepancy between the Pliocene proxy data and model simulations in the mid-latitudes of the North Atlantic, where models underestimate warming shown by our highest-confidence data, may provide a new perspective and insight into the predictive abilities of these models in simulating a past warm interval in Earth history. This is important because the Pliocene has a number of parallels to present predictions of late twenty-first century climate.

Effects of radiation on crack-initiation and crack-arrest toughness for SA508 Cl. 3 steel

DOE Office of Scientific and Technical Information (OSTI.GOV)

Milella, P.P.; Pini, A.; Iskander, S.K.

1995-11-01

An investigation was carried out to determine the effects of neutron irradiation, conducted in several different test-reactors at approximately 280 C, on the mechanical properties of an SA508 Class 3 carbon steel ring forging produced in Italy as a prototype of a pressurized water reactor vessel. The research had two primary objectives: (1) to investigate the effect of a various levels of neutron irradiation (fluences from 1 to 5.5 10{sup 19} n/cm{sup 2} [E>1 MeV]) on the strength, initiation and arrest toughness and ductile-to-brittle transition temperature, and (2) to determine if Charpy data and empirical prediction equations provide conservative estimatesmore » of irradiation effects on the K{sub Ic} and K{sub Ia} transition curves. The paper reports results from tension, Charpy V-notch (CVN) fracture toughness, and crack-arrest tests performed on both unirradiated and irradiated material. It was found that both Charpy V-notch transition temperature shifts and two prediction equations provided conservative estimates of shifts in fracture initiation and fracture arrest transition temperatures for the steel investigated. The 54 C shift of the Charpy V-notch transition curves at a fluence level of 5.5 10{sup 19} n/cm{sup 2} suggests the possibility of extending the component life beyond the common 40 year design life.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burnham, A K; Weese, R K; Andrzejewski, W J

Decomposition kinetics are determined for HMX (nitramine octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine) and CP (2-(5-cyanotetrazalato) pentaammine cobalt (III) perchlorate) separately and together. For high levels of thermal stress, the two materials decompose faster as a mixture than individually. This effect is observed both in high-temperature thermal analysis experiments and in long-term thermal aging experiments. An Arrhenius plot of the 10% level of HMX decomposition by itself from a diverse set of experiments is linear from 120 to 260 C, with an apparent activation energy of 165 kJ/mol. Similar but less extensive thermal analysis data for the mixture suggests a slightly lower activation energy formore » the mixture, and an analogous extrapolation is consistent with the amount of gas observed in the long-term detonator aging experiments, which is about 30 times greater than expected from HMX by itself for 50 months at 100 C. Even with this acceleration, however, it would take {approx}10,000 years to achieve 10% decomposition at {approx}30 C. Correspondingly, negligible decomposition is predicted by this kinetic model for a few decades aging at temperatures slightly above ambient. This prediction is consistent with additional sealed-tube aging experiments at 100-120 C, which are estimated to have an effective thermal dose greater than that from decades of exposure to temperatures slightly above ambient.« less

The Icarus challenge - Predicting geographical and taxonomic patterns of vulnerability to climate change in near-coastal species

EPA Science Inventory

Like Icarus, the world's oceans are "flying too close" to the sun. Increases in temperature and sea level and reductions in pH will affect many, if not most, near-coastal species. The type and severity of the effects will vary both by species and regionally due to geogr...

The Oxidation of Ascorbic Acid by Hexacyanoferrate(III) Ion in Acidic Aqueous Media.

ERIC Educational Resources Information Center

Martins, Luis J. A.; da Costa, J. Barbosa

1988-01-01

Describes a kinetic and mechanistic investigation of ascorbic acid by a substitution-inert complex in acidic medium suitable for the undergraduate level. Discusses obtaining the second order rate constant for the rate determining step at a given temperature and comparison with the value predicted on the basis of the Marcus cross-relation. (CW)

Improving the spectral measurement accuracy based on temperature distribution and spectra-temperature relationship

NASA Astrophysics Data System (ADS)

Li, Zhe; Feng, Jinchao; Liu, Pengyu; Sun, Zhonghua; Li, Gang; Jia, Kebin

2018-05-01

Temperature is usually considered as a fluctuation in near-infrared spectral measurement. Chemometric methods were extensively studied to correct the effect of temperature variations. However, temperature can be considered as a constructive parameter that provides detailed chemical information when systematically changed during the measurement. Our group has researched the relationship between temperature-induced spectral variation (TSVC) and normalized squared temperature. In this study, we focused on the influence of temperature distribution in calibration set. Multi-temperature calibration set selection (MTCS) method was proposed to improve the prediction accuracy by considering the temperature distribution of calibration samples. Furthermore, double-temperature calibration set selection (DTCS) method was proposed based on MTCS method and the relationship between TSVC and normalized squared temperature. We compare the prediction performance of PLS models based on random sampling method and proposed methods. The results from experimental studies showed that the prediction performance was improved by using proposed methods. Therefore, MTCS method and DTCS method will be the alternative methods to improve prediction accuracy in near-infrared spectral measurement.

When Will the Antarctic Ozone Hole Recover?

NASA Technical Reports Server (NTRS)

Newman, Paul A.

2006-01-01

The Antarctic ozone hole demonstrates large-scale, man-made affects on our atmosphere. Surface observations now show that human produced ozone depleting substances (ODSs) are declining. The ozone hole should soon start to diminish because of this decline. In this talk we will demonstrate an ozone hole parametric model. This model is based upon: 1) a new algorithm for estimating 61 and Br levels over Antarctica and 2) late-spring Antarctic stratospheric temperatures. This parametric model explains 95% of the ozone hole area's variance. We use future ODS levels to predict ozone hole recovery. Full recovery to 1980 levels will occur in approximately 2068. The ozone hole area will very slowly decline over the next 2 decades. Detection of a statistically significant decrease of area will not occur until approximately 2024. We further show that nominal Antarctic stratospheric greenhouse gas forced temperature change should have a small impact on the ozone hole.

When Will the Antarctic Ozone Hole Recover?

NASA Technical Reports Server (NTRS)

Newman, Paul A.; Nash, Eric R.; Kawa, S. Randolph; Montzka, Stephen A.; Schauffler, Sue

2006-01-01

The Antarctic ozone hole demonstrates large-scale, man-made affects on our atmosphere. Surface observations now show that human produced ozone depleting substances (ODSs) are declining. The ozone hole should soon start to diminish because of this decline. Herein we demonstrate an ozone hole parametric model. This model is based upon: 1) a new algorithm for estimating C1 and Br levels over Antarctica and 2) late-spring Antarctic stratospheric temperatures. This parametric model explains 95% of the ozone hole area s variance. We use future ODS levels to predict ozone hole recovery. Full recovery to 1980 levels will occur in approximately 2068. The ozone hole area will very slowly decline over the next 2 decades. Detection of a statistically significant decrease of area will not occur until approximately 2024. We further show that nominal Antarctic stratospheric greenhouse gas forced temperature change should have a small impact on the ozone hole.

Activity affects intraspecific body-size scaling of metabolic rate in ectothermic animals.

PubMed

Glazier, Douglas Stewart

2009-10-01

Metabolic rate is commonly thought to scale with body mass (M) to the 3/4 power. However, the metabolic scaling exponent (b) may vary with activity state, as has been shown chiefly for interspecific relationships. Here I use a meta-analysis of literature data to test whether b changes with activity level within species of ectothermic animals. Data for 19 species show that b is usually higher during active exercise (mean +/- 95% confidence limits = 0.918 +/- 0.038) than during rest (0.768 +/- 0.069). This significant upward shift in b to near 1 is consistent with the metabolic level boundaries hypothesis, which predicts that maximal metabolic rate during exercise should be chiefly influenced by volume-related muscular power production (scaling as M (1)). This dependence of b on activity level does not appear to be a simple temperature effect because body temperature in ectotherms changes very little during exercise.

Theoretical and experimental studies of the deposition of Na2So4 from seeded combustion gases

NASA Technical Reports Server (NTRS)

Kohl, F. J.; Santoro, G. J.; Stearns, C. A.; Fryburg, G. C.; Rosner, D. E.

1977-01-01

Flames in a Mach 0.3 atmospheric pressure laboratory burner rig were doped with sea salt, NaS04, and NaCl, respectively, in an effort to validate theoretical dew point predictions made by a local thermochemical equilibrium (LTCE) method of predicting condensation temperatures of sodium sulfate in flame environments. Deposits were collected on cylindrical platinum targets placed in the combustion products, and the deposition was studied as a function of collector temperature. Experimental deposition onset temperatures checked within experimental error with LTCE-predicted temperatures. A multicomponent mass transfer equation was developed to predict the rate of deposition of Na2SO4(c) via vapor transport at temperatures below the deposition onset temperature. Agreement between maximum deposition rates predicted by this chemically frozen boundary layer (CFBL) theory and those obtained in the seeded laboratory burner experiments is good.

Temperature Sensitivity Conferred by ligA Alleles from Psychrophilic Bacteria upon Substitution in Mesophilic Bacteria and a Yeast Species

PubMed Central

Pankowski, Jarosław A.; Puckett, Stephanie M.

2016-01-01

We have assembled a collection of 13 psychrophilic ligA alleles that can serve as genetic elements for engineering mesophiles to a temperature-sensitive (TS) phenotype. When these ligA alleles were substituted into Francisella novicida, they conferred a TS phenotype with restrictive temperatures between 33 and 39°C. When the F. novicida ligA hybrid strains were plated above their restrictive temperatures, eight of them generated temperature-resistant variants. For two alleles, the mutations that led to temperature resistance clustered near the 5′ end of the gene, and the mutations increased the predicted strength of the ribosome binding site at least 3-fold. Four F. novicida ligA hybrid strains generated no temperature-resistant variants at a detectable level. These results suggest that multiple mutations are needed to create temperature-resistant variants of these ligA gene products. One ligA allele was isolated from a Colwellia species that has a maximal growth temperature of 12°C, and this allele supported growth of F. novicida only as a hybrid between the psychrophilic and the F. novicida ligA genes. However, the full psychrophilic gene alone supported the growth of Salmonella enterica, imparting a restrictive temperature of 27°C. We also tested two ligA alleles from two Pseudoalteromonas strains for their ability to support the viability of a Saccharomyces cerevisiae strain that lacked its essential gene, CDC9, encoding an ATP-dependent DNA ligase. In both cases, the psychrophilic bacterial alleles supported yeast viability and their expression generated TS phenotypes. This collection of ligA alleles should be useful in engineering bacteria, and possibly eukaryotic microbes, to predictable TS phenotypes. PMID:26773080

A Comparison of Five Numerical Weather Prediction Analysis Climatologies in Southern High Latitudes.

NASA Astrophysics Data System (ADS)

Connolley, William M.; Harangozo, Stephen A.

2001-01-01

In this paper, numerical weather prediction analyses from four major centers are compared-the Australian Bureau of Meteorology (ABM), the European Centre for Medium-Range Weather Forecasts (ECMWF), the U.S. National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR), and The Met. Office (UKMO). Two of the series-ECMWF reanalysis (ERA) and NCEP-NCAR reanalysis (NNR)-are `reanalyses'; that is, the data have recently been processed through a consistent, modern analysis system. The other three-ABM, ECMWF operational (EOP), and UKMO-are archived from operational analyses.The primary focus in this paper is on the period of 1979-93, the period used for the reanalyses, and on climatology. However, ABM and NNR are also compared for the period before 1979, for which the evidence tends to favor NNR. The authors are concerned with basic variables-mean sea level pressure, height of the 500-hPa surface, and near-surface temperature-that are available from the basic analysis step, rather than more derived quantities (such as precipitation), which are available only from the forecast step.Direct comparisons against station observations, intercomparisons of the spatial pattern of the analyses, and intercomparisons of the temporal variation indicate that ERA, EOP, and UKMO are best for sea level pressure;that UKMO and EOP are best for 500-hPa height; and that none of the analyses perform well for near-surface temperature.

Plant physiological models of heat, water and photoinhibition stress for climate change modelling and agricultural prediction

NASA Astrophysics Data System (ADS)

Nicolas, B.; Gilbert, M. E.; Paw U, K. T.

2015-12-01

Soil-Vegetation-Atmosphere Transfer (SVAT) models are based upon well understood steady state photosynthetic physiology - the Farquhar-von Caemmerer-Berry model (FvCB). However, representations of physiological stress and damage have not been successfully integrated into SVAT models. Generally, it has been assumed that plants will strive to conserve water at higher temperatures by reducing stomatal conductance or adjusting osmotic balance, until potentially damaging temperatures and the need for evaporative cooling become more important than water conservation. A key point is that damage is the result of combined stresses: drought leads to stomatal closure, less evaporative cooling, high leaf temperature, less photosynthetic dissipation of absorbed energy, all coupled with high light (photosynthetic photon flux density; PPFD). This leads to excess absorbed energy by Photosystem II (PSII) and results in photoinhibition and damage, neither are included in SVAT models. Current representations of photoinhibition are treated as a function of PPFD, not as a function of constrained photosynthesis under heat or water. Thus, it seems unlikely that current models can predict responses of vegetation to climate variability and change. We propose a dynamic model of damage to Rubisco and RuBP-regeneration that accounts, mechanistically, for the interactions between high temperature, light, and constrained photosynthesis under drought. Further, these predictions are illustrated by key experiments allowing model validation. We also integrated this new framework within the Advanced Canopy-Atmosphere-Soil Algorithm (ACASA). Preliminary results show that our approach can be used to predict reasonable photosynthetic dynamics. For instances, a leaf undergoing one day of drought stress will quickly decrease its maximum quantum yield of PSII (Fv/Fm), but it won't recover to unstressed levels for several days. Consequently, cumulative effect of photoinhibition on photosynthesis can cause a decrease of about 35% of CO2 uptake. As a result, the incorporation of stress and damage into SVAT models could considerably improve our ability to predict global responses to climate change.

Process Setting through General Linear Model and Response Surface Method

NASA Astrophysics Data System (ADS)

Senjuntichai, Angsumalin

2010-10-01

The objective of this study is to improve the efficiency of the flow-wrap packaging process in soap industry through the reduction of defectives. At the 95% confidence level, with the regression analysis, the sealing temperature, temperatures of upper and lower crimper are found to be the significant factors for the flow-wrap process with respect to the number/percentage of defectives. Twenty seven experiments have been designed and performed according to three levels of each controllable factor. With the general linear model (GLM), the suggested values for the sealing temperature, temperatures of upper and lower crimpers are 185, 85 and 85° C, respectively while the response surface method (RSM) provides the optimal process conditions at 186, 89 and 88° C. Due to different assumptions between percentage of defective and all three temperature parameters, the suggested conditions from the two methods are then slightly different. Fortunately, the estimated percentage of defectives at 5.51% under GLM process condition and the predicted percentage of defectives at 4.62% under RSM process condition are not significant different. But at 95% confidence level, the percentage of defectives under RSM condition can be much lower approximately 2.16% than those under GLM condition in accordance with wider variation. Lastly, the percentages of defectives under the conditions suggested by GLM and RSM are reduced by 55.81% and 62.95%, respectively.

Predicting Bacillus coagulans spores inactivation in tomato pulp under nonisothermal heat treatments.

PubMed

Zimmermann, Morgana; Longhi, Daniel A; Schaffner, Donald W; Aragão, Gláucia M F

2014-05-01

The knowledge and understanding of Bacillus coagulans inactivation during a thermal treatment in tomato pulp, as well as the influence of temperature variation during thermal processes are essential for design, calculation, and optimization of the process. The aims of this work were to predict B. coagulans spores inactivation in tomato pulp under varying time-temperature profiles with Gompertz-inspired inactivation model and to validate the model's predictions by comparing the predicted values with experimental data. B. coagulans spores in pH 4.3 tomato pulp at 4 °Brix were sealed in capillary glass tubes and heated in thermostatically controlled circulating oil baths. Seven different nonisothermal profiles in the range from 95 to 105 °C were studied. Predicted inactivation kinetics showed similar behavior to experimentally observed inactivation curves when the samples were exposed to temperatures in the upper range of this study (99 to 105 °C). Profiles that resulted in less accurate predictions were those where the range of temperatures analyzed were comparatively lower (inactivation profiles starting at 95 °C). The link between fail prediction and both lower starting temperature and magnitude of the temperature shift suggests some chemical or biological mechanism at work. Statistical analysis showed that overall model predictions were acceptable, with bias factors from 0.781 to 1.012, and accuracy factors from 1.049 to 1.351, and confirm that the models used were adequate to estimate B. coagulans spores inactivation under fluctuating temperature conditions in the range from 95 to 105 °C. How can we estimate Bacillus coagulans inactivation during sudden temperature shifts in heat processing? This article provides a validated model that can be used to predict B. coagulans under changing temperature conditions. B. coagulans is a spore-forming bacillus that spoils acidified food products. The mathematical model developed here can be used to predict the spoilage risk following thermal process deviations for tomato products. © 2014 Institute of Food Technologists®

IONSIV(R) IE-911 Performance in Savannah River Site Radioactive Waste

DOE Office of Scientific and Technical Information (OSTI.GOV)

Walker, D.D.

2001-06-04

This report describes cesium sorption from high-level radioactive waste solutions onto IONSIV(R) IE-911 at ambient temperature. Researchers characterized six radioactive waste samples from five high-level waste tanks in the Savannah River Site tank farm, diluted the wastes to 5.6 M Na+, and made equilibrium and kinetic measurements of cesium sorption. The equilibrium measurements were compared to ZAM (Zheng, Anthony, and Martin) model predictions. The kinetic measurements were compared to simulant solutions whose column performance has been measured.

Determination of thermal contact conductance in vacuum-bagged thermoplastic prepreg stacks using infrared thermography

NASA Astrophysics Data System (ADS)

Baumard, Théo; De Almeida, Olivier; Menary, Gary; Le Maoult, Yannick; Schmidt, Fabrice; Bikard, Jérôme

2016-10-01

The infrared heating of a vacuum-bagged, thermoplastic prepreg stack of glass/PA66 was studied to investigate the influence of vacuum level on thermal contact resistance between plies. A higher vacuum level was shown experimentally to decrease the transverse heat transfer efficiency, indicating that considering only the effect of heat conduction at the plies interfaces is not sufficient to predict the temperature distribution. An inverse analysis was used to retrieve the contact resistance coefficients as a function of vacuum pressure.

Superconductivity in dense carbon-based materials

DOE PAGES

Lu, Siyu; Liu, Hanyu; Naumov, Ivan I.; ...

2016-03-08

Guided by a simple strategy in searching of new superconducting materials we predict that high temperature superconductivity can be realized in classes of high-density materials having strong sp 3 chemical bonding and high lattice symmetry. Here, we examine in detail sodalite carbon frameworks doped with simple metals such as Li, Na, and Al. Though such materials share some common features with doped diamond, their doping level is not limited and the density of states at the Fermi level in them can be as high as that in the renowned MgB 2. Altogether, with other factors, this boosts the superconducting temperaturemore » (T c) in the materials investigated to higher levels compared to doped diamond. For example, the superconducting T c of sodalite-like NaC 6 is predicted to be above 100 K. This phase and a series of other sodalite-based superconductors are predicted to be metastable phases but are dynamically stable. In owing to the rigid carbon framework of these and related dense carbon-materials, these doped sodalite-based structures could be recoverable as potentially useful superconductors.« less

Trailer microclimate and calf welfare during fall-run transportation of beef calves in Alberta.

PubMed

Goldhawk, C; Janzen, E; González, L A; Crowe, T; Kastelic, J; Pajor, E; Schwartzkopf-Genswein, K S

2014-11-01

Twenty-four commercial loads of beef calves (BW 300 ± 52 kg, mean ± SD) were evaluated for associations among transportation factors, in-transit microclimate, and calf welfare. Transport factors evaluated included vehicle speed, space allowance, compartment within trailer, and transit duration. Calves were transported for 7 h 44 min ± 4 h 15 min, with space allowances ranging from 0.56 to 1.17 m(2)/animal. Compartment within trailer, space allowance, and vehicle speed did not affect the difference between compartment ceiling-level and ambient temperatures during a 30-min period of steady-state microclimate. During the steady-state period, a 1°C increase in ambient temperature above the mean of 5.6°C was associated with a 0.62°C decrease in the difference between ceiling-level and ambient temperature (P < 0.01). Ceiling-level temperature and humidity during the first 400 min of transport could be predicted by ambient conditions and vehicle speed (pseudo-r(2) of 0.91 and 0.82 for temperature and humidity ratio; P < 0.01). Events when animal-level temperature-humidity index (THI) was classified as above the "danger" level lasted for 10.2 ± 4.1 consecutive minutes. Ambient and ceiling-level THI values were not classified as above "danger" for 90.0 and 84.9% of animal-level events. Ambient and ceiling-level THI were 5.0 ± 2.1 and 4.7 ± 2.0° Flower than animal-level THI during periods of disagreement, respectively. The majority of calves arrived in good condition and biochemical indicators of calf welfare were within reference ranges for healthy cattle. Within the study population, high pre-transport cortisol and hematocrit were associated with elevated post-transport values (P < 0.01). A 1% increase in shrink during the weaning to loading interval (24 or 48 h) decreased transportation shrink by 0.26 ± 0.04% when average animal-level temperature was greater than 5°C and decreased transportation shrink by 0.11 ± 0.04% when average animal-level temperature was less than 5°C (P < 0.01). We inferred that the study results support future investigation of the extension of in-transit microclimate as a risk factor for post-transport treatment for disease. The study also provided correction factors for estimating in-transit microclimate that could assist in evaluation of transportation management and decisions affecting profitability and calf welfare.

A Predictive Framework for Thermomechanical Fatigue Life of High Silicon Molybdenum Ductile Cast Iron Based on Considerations of Strain Energy Dissipation

NASA Astrophysics Data System (ADS)

Avery, Katherine R.

Isothermal low cycle fatigue (LCF) and anisothermal thermomechanical fatigue (TMF) tests were conducted on a high silicon molybdenum (HiSiMo) cast iron for temperatures up to 1073K. LCF and out-of-phase (OP) TMF lives were significantly reduced when the temperature was near 673K due to an embrittlement phenomenon which decreases the ductility of HiSiMo at this temperature. In this case, intergranular fracture was predominant, and magnesium was observed at the fracture surface. When the thermal cycle did not include 673K, the failure mode was predominantly transgranular, and magnesium was not present on the fracture surface. The in-phase (IP) TMF lives were unaffected when the thermal cycle included 673K, and the predominant failure mode was found to be transgranular fracture, regardless of the temperature. No magnesium was present on the IP TMF fracture surfaces. Thus, the embrittlement phenomenon was found to contribute to fatigue damage only when the temperature was near 673K and a tensile stress was present. To account for the temperature- and stress-dependence of the embrittlement phenomenon on the TMF life of HiSiMo cast iron, an original model based on the cyclic inelastic energy dissipation is proposed which accounts for temperature-dependent differences in the rate of fatigue damage accumulation in tension and compression. The proposed model has few empirical parameters. Despite the simplicity of the model, the predicted fatigue life shows good agreement with more than 130 uniaxial low cycle and thermomechanical fatigue tests, cyclic creep tests, and tests conducted at slow strain rates and with hold times. The proposed model was implemented in a multiaxial formulation and applied to the fatigue life prediction of an exhaust manifold subjected to severe thermal cycles. The simulation results show good agreement with the failure locations and number of cycles to failure observed in a component-level experiment.

Comparing stream-specific to generalized temperature models to guide salmonid management in a changing climate

USGS Publications Warehouse

Andrew K. Carlson,; William W. Taylor,; Hartikainen, Kelsey M.; Dana M. Infante,; Beard, Douglas; Lynch, Abigail

2017-01-01

Global climate change is predicted to increase air and stream temperatures and alter thermal habitat suitability for growth and survival of coldwater fishes, including brook charr (Salvelinus fontinalis), brown trout (Salmo trutta), and rainbow trout (Oncorhynchus mykiss). In a changing climate, accurate stream temperature modeling is increasingly important for sustainable salmonid management throughout the world. However, finite resource availability (e.g. funding, personnel) drives a tradeoff between thermal model accuracy and efficiency (i.e. cost-effective applicability at management-relevant spatial extents). Using different projected climate change scenarios, we compared the accuracy and efficiency of stream-specific and generalized (i.e. region-specific) temperature models for coldwater salmonids within and outside the State of Michigan, USA, a region with long-term stream temperature data and productive coldwater fisheries. Projected stream temperature warming between 2016 and 2056 ranged from 0.1 to 3.8 °C in groundwater-dominated streams and 0.2–6.8 °C in surface-runoff dominated systems in the State of Michigan. Despite their generally lower accuracy in predicting exact stream temperatures, generalized models accurately projected salmonid thermal habitat suitability in 82% of groundwater-dominated streams, including those with brook charr (80% accuracy), brown trout (89% accuracy), and rainbow trout (75% accuracy). In contrast, generalized models predicted thermal habitat suitability in runoff-dominated streams with much lower accuracy (54%). These results suggest that, amidst climate change and constraints in resource availability, generalized models are appropriate to forecast thermal conditions in groundwater-dominated streams within and outside Michigan and inform regional-level salmonid management strategies that are practical for coldwater fisheries managers, policy makers, and the public. We recommend fisheries professionals reserve resource-intensive stream-specific models for runoff-dominated systems containing high-priority fisheries resources (e.g. trophy individuals, endangered species) that will be directly impacted by projected stream warming.

The Effect of Elevated CO2 and Temperature on the Hatch Rate and Survival of Estuarine Forage Fish

NASA Astrophysics Data System (ADS)

Merlo, L. R.; Gobler, C.

2016-02-01

The World Oceans are acidifying and warming, yet little is known regarding how these processes will combine to impact fish populations. In estuaries, microbial respiration of eutrophication-enhanced organic matter can create elevated CO2 levels during late spring and summer seasons when thermal extremes can occur and temperate fish spawn. Here, we report on experiments that exposed fish embryos (e.g. Menidia beryllina, inland silverside) to normal and elevated CO2 (400 and 2,000 ppm) and the range of temperatures experienced within temperate estuaries during the spawning season (16 - 30C). Fish survival and growth rates were quantified from hatching through early life, larval stages. Temperature controlled egg hatching times, with elevated temperatures leading to more rapid hatch rates. Elevated levels of CO2 significantly depressed post-hatch survival of fish. Survival rates of fish exposed to elevated CO2 at lower than ideal temperatures were significantly lower than predicted by either variable individually indicating the ability of these stressors to synergistically interact. Since embryonic stages have been identified as being highly sensitive to acidification, this finding may be associated with the extended exposure of eggs to high CO2 at lower temperatures. The physiological mechanisms driving experimental trends and broader ecological implications of the study will be discussed.

Monthly mean forecast experiments with the GISS model

NASA Technical Reports Server (NTRS)

Spar, J.; Atlas, R. M.; Kuo, E.

1976-01-01

The GISS general circulation model was used to compute global monthly mean forecasts for January 1973, 1974, and 1975 from initial conditions on the first day of each month and constant sea surface temperatures. Forecasts were evaluated in terms of global and hemispheric energetics, zonally averaged meridional and vertical profiles, forecast error statistics, and monthly mean synoptic fields. Although it generated a realistic mean meridional structure, the model did not adequately reproduce the observed interannual variations in the large scale monthly mean energetics and zonally averaged circulation. The monthly mean sea level pressure field was not predicted satisfactorily, but annual changes in the Icelandic low were simulated. The impact of temporal sea surface temperature variations on the forecasts was investigated by comparing two parallel forecasts for January 1974, one using climatological ocean temperatures and the other observed daily ocean temperatures. The use of daily updated sea surface temperatures produced no discernible beneficial effect.

Visualization techniques to experimentally model flow and heat transfer in turbine and aircraft flow passages

NASA Technical Reports Server (NTRS)

Russell, Louis M.; Hippensteele, Steven A.

1991-01-01

Increased attention to fuel economy and increased thrust requirements have increased the demand for higher aircraft gas turbine engine efficiency through the use of higher turbine inlet temperatures. These higher temperatures increase the importance of understanding the heat transfer patterns which occur throughout the turbine passages. It is often necessary to use a special coating or some form of cooling to maintain metal temperatures at a level which the metal can withstand for long periods of time. Effective cooling schemes can result in significant fuel savings through higher allowable turbine inlet temperatures and can increase engine life. Before proceeding with the development of any new turbine it is economically desirable to create both mathematical and experimental models to study and predict flow characteristics and temperature distributions. Some of the methods are described used to physically model heat transfer patterns, cooling schemes, and other complex flow patterns associated with turbine and aircraft passages.

Predicting Stream Temperature After Riparian Vegetation Removal

Treesearch

Bruce J. McGurk

1989-01-01

Removal of stream channel shading during timber harvest operations may raise the stream temperature and adversely affect desirable aquatic populations. Field work in California at one clearcut and one mature fir site demonstrated diurnal water temperature cycles and provided data to evaluate two stream temperature prediction techniques. Larger diurnal temperature...

Spectrocopic measurements of water vapor plasmas at high resolution: The optical transition probabilities for OH (A 2 Sigma - X 2 Pi)

NASA Technical Reports Server (NTRS)

Klein, L.

1972-01-01

Emission and absorption spectra of water vapor plasmas generated in a wall-stabilized arc at atmospheric pressure and 4 current, and at 0.03 atm and 15 to 50 A, were measured at high spatial and spectral resolution. The gas temperature was determined from the shape of Doppler-broadened rotational lines of OH. The observed nonequilibrium population distributions over the energy levels of atoms are interpreted in terms of a theoretical state model for diffusion-controlled arc plasmas. Excellent correlation is achieved between measured and predicted occupation of hydrogen energy levels. It is shown that the population distribution over the nonpredissociating rotational-vibrational levels of the A 2 Sigma state of OH is close to an equilibrium distribution at the gas temperature, although the total density of this state is much higher than its equilibrium density. The reduced intensities of the rotational lines originating in these levels yielded Boltzmann plots that were strictly linear.

Calcification persists with CO2-induced ocean acidification but decreases with warming for the Caribbean coral Siderastrea siderea

NASA Astrophysics Data System (ADS)

Castillo, K. D.; Ries, J. B.; Westfield, I. T.; Weiss, J. M.; Bruno, J. F.

2012-12-01

Atmospheric carbon dioxide (pCO2) induced ocean acidification and rising seawater temperatures are identified as two of the greatest threats to modern coral reefs. Within this century, surface seawater pH is expected to decrease by at least 0.3 units, and sea surface temperature is predicted to rise by 1 to 3 °C. However, uncertainty remains as to whether ocean acidification or ocean warming will have a more deleterious impact on coral reefs by the end of the century. Here, we present results of 95-day laboratory experiments in which we investigated the impact of CO2-induced ocean acidification and temperature on the calcification rate of the tropical reef-building zooxanthellate scleractinian coral Siderastrea siderea. We found that calcification rates for S. siderea, estimated from buoyant weighing, increased as pCO2 increased from a pre-industrial value of 324 ppm to a near-present-day value of 477 ppm, remained unchanged as pCO2 increased from 477 ppm to the predicted end-of-century value of 604 ppm, and only declined at 6-times the modern pCO2 value of 2553 ppm. Corals reared at average pCO2 of 488 ppm and at temperatures of 25 and 32 °C, approximately the lower and upper temperature extremes for this species, calcified at lower rates relative to corals reared at 28 °C under equivalent pCO2. These results support the existing evidence that scleractinian corals such as S. siderea are able to manipulate the carbonate chemistry at their calcification site, enabling them to maintain their calcification rates under elevated pCO2 levels predicted for the end of this century. However, exposure of S. siderea corals to sea surface temperatures predicted for tropical waters for the end of this century grossly impaired their rate of calcification. These findings suggest that ocean warming poses a more immediate threat to the coral S. siderea than does ocean acidification, at least under scenarios (B1, A1T, and B2) predicted by the Intergovernmental Panel on Climate Change for the end of the 21st century. We are presently investigating the calcification responses of S. siderea to the combined effects of ocean acidification and warming, in order to better constrain how corals will respond to global CO2-induced changes that are predicted for the near future.

Freezing temperatures as a limit to forest recruitment above tropical Andean treelines.

PubMed

Rehm, Evan M; Feeley, Kenneth J

2015-07-01

The elevation of altitudinal treelines is generally believed to occur where low mean temperatures during the growing season limit growth and prevent trees from establishing at higher elevations. Accordingly, treelines should move upslope with increasing global temperatures. Contrary to this prediction, tropical treelines have remained stable over the past several decades despite increasing mean temperatures. The observed stability of tropical treelines, coupled with the drastically different temperature profiles between temperate and tropical treelines, suggests that using mean measures of temperature to predict tropical treeline movements during climate change may be overly simplistic. We hypothesize that frost events at tropical treelines may slow climate driven treeline movement by preventing tree recruitment beyond the established forest canopy. To assess this hypothesis, we measured freezing resistance of four canopy-forming treeline species (Weinmannia fagaroides, Polylepis pauta, Clethra cuneata, and Gynoxys nitida) at two life stages (juvenile and adult) and during two seasons (warm-wet and cold-dry). Freezing resistances were then compared to microclimatic data to determine if freezing events in the grassland matrix above treeline are too harsh for these forest species. Freezing resistance varied among species and life stages from -5.7 degrees C for juveniles of P. pauta to -11.1 degrees C for juveniles of W. fagaroides. Over a four-year period, the lowest temperatures recorded at 10 cm above ground level in the grasslands above treeline and at treeline itself were -8.9 degrees C and -6.8 degrees C, respectively. Juveniles maintained freezing resistances similar to adults during the coldest parts of the year and ontogenetic differences in freezing resistance were only present during the warm season when temperatures did not represent a significant threat to active plant tissue. These findings support the hypothesis that rare extreme freezing events at and above tropical treelines can prevent recruitment outside of closed canopy forest for some tree species and may significantly slow treeline advancement despite warming mean temperatures. Predictions of treeline shifts under climate change should be reevaluated to include species-specific' climatic tolerances and measures of climatic variability.

Metal flow and temperature in direct extrusion of large-size aluminum billets

NASA Astrophysics Data System (ADS)

Valberg, Henry; Costa, André L. M.

2018-05-01

FEM-analysis is used to study thermo-mechanical conditions in aluminum rod extrusion for billets with large size corresponding to that used in industrial production. In the analysis, focus is on how the metal flow and the temperature conditions in the extrusion material is affected by the extrusion velocity in terms of the ram speed used in the extrusion process. In the study, metal flow is characterized by the deformations in extrusion subjected to a perfect grid pattern, consisting of orthogonal crossing lines, added into the longitudinal mid-plane of the initial billet. The analysis shows that metal flow in extrusion conducted at a low ram speed of 1 mms-1, is predicted significantly different from that at a high speed of 5 mms-1, or above. As regards the thermal conditions in the extrusion material, they are also predicted significantly different, at the low and the high ram speed level. A likely explanation why metal flow is different at low and high ram speeds may be that flow is altered because of the concurrent change in the temperature field within the billet.

Fall field crickets did not acclimate to simulated seasonal changes in temperature.

PubMed

Niehaus, Amanda C; Wilson, Robbie S; Storm, Jonathan J; Angilletta, Michael J

2012-02-01

In nature, many organisms alter their developmental trajectory in response to environmental variation. However, studies of thermal acclimation have historically involved stable, unrealistic thermal treatments. In our study, we incorporated ecologically relevant treatments to examine the effects of environmental stochasticity on the thermal acclimation of the fall field cricket (Gryllus pennsylvanicus). We raised crickets for 5 weeks at either a constant temperature (25°C) or at one of three thermal regimes mimicking a seasonal decline in temperature (from 25 to 12°C). The latter three treatments differed in their level of thermal stochasticity: crickets experienced either no diel cycle, a predictable diel cycle, or an unpredictable diel cycle. Following these treatments, we measured several traits considered relevant to survival or reproduction, including growth rate, jumping velocity, feeding rate, metabolic rate, and cold tolerance. Contrary to our predictions, the acclimatory responses of crickets were unrelated to the magnitude or type of thermal variation. Furthermore, acclimation of performance was not ubiquitous among traits. We recommend additional studies of acclimation in fluctuating environments to assess the generality of these findings.

Individual differences in normal body temperature: longitudinal big data analysis of patient records.

PubMed

Obermeyer, Ziad; Samra, Jasmeet K; Mullainathan, Sendhil

2017-12-13

To estimate individual level body temperature and to correlate it with other measures of physiology and health. Observational cohort study. Outpatient clinics of a large academic hospital, 2009-14. 35 488 patients who neither received a diagnosis for infections nor were prescribed antibiotics, in whom temperature was expected to be within normal limits. Baseline temperatures at individual level, estimated using random effects regression and controlling for ambient conditions at the time of measurement, body site, and time factors. Baseline temperatures were correlated with demographics, medical comorbidities, vital signs, and subsequent one year mortality. In a diverse cohort of 35 488 patients (mean age 52.9 years, 64% women, 41% non-white race) with 243 506 temperature measurements, mean temperature was 36.6°C (95% range 35.7-37.3°C, 99% range 35.3-37.7°C). Several demographic factors were linked to individual level temperature, with older people the coolest (-0.021°C for every decade, P<0.001) and African-American women the hottest (versus white men: 0.052°C, P<0.001). Several comorbidities were linked to lower temperature (eg, hypothyroidism: -0.013°C, P=0.01) or higher temperature (eg, cancer: 0.020, P<0.001), as were physiological measurements (eg, body mass index: 0.002 per m/kg 2 , P<0.001). Overall, measured factors collectively explained only 8.2% of individual temperature variation. Despite this, unexplained temperature variation was a significant predictor of subsequent mortality: controlling for all measured factors, an increase of 0.149°C (1 SD of individual temperature in the data) was linked to 8.4% higher one year mortality (P=0.014). Individuals' baseline temperatures showed meaningful variation that was not due solely to measurement error or environmental factors. Baseline temperatures correlated with demographics, comorbid conditions, and physiology, but these factors explained only a small part of individual temperature variation. Unexplained variation in baseline temperature, however, strongly predicted mortality. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Individual differences in normal body temperature: longitudinal big data analysis of patient records

PubMed Central

Samra, Jasmeet K; Mullainathan, Sendhil

2017-01-01

Abstract Objective To estimate individual level body temperature and to correlate it with other measures of physiology and health. Design Observational cohort study. Setting Outpatient clinics of a large academic hospital, 2009-14. Participants 35 488 patients who neither received a diagnosis for infections nor were prescribed antibiotics, in whom temperature was expected to be within normal limits. Main outcome measures Baseline temperatures at individual level, estimated using random effects regression and controlling for ambient conditions at the time of measurement, body site, and time factors. Baseline temperatures were correlated with demographics, medical comorbidities, vital signs, and subsequent one year mortality. Results In a diverse cohort of 35 488 patients (mean age 52.9 years, 64% women, 41% non-white race) with 243 506 temperature measurements, mean temperature was 36.6°C (95% range 35.7-37.3°C, 99% range 35.3-37.7°C). Several demographic factors were linked to individual level temperature, with older people the coolest (–0.021°C for every decade, P<0.001) and African-American women the hottest (versus white men: 0.052°C, P<0.001). Several comorbidities were linked to lower temperature (eg, hypothyroidism: –0.013°C, P=0.01) or higher temperature (eg, cancer: 0.020, P<0.001), as were physiological measurements (eg, body mass index: 0.002 per m/kg2, P<0.001). Overall, measured factors collectively explained only 8.2% of individual temperature variation. Despite this, unexplained temperature variation was a significant predictor of subsequent mortality: controlling for all measured factors, an increase of 0.149°C (1 SD of individual temperature in the data) was linked to 8.4% higher one year mortality (P=0.014). Conclusions Individuals’ baseline temperatures showed meaningful variation that was not due solely to measurement error or environmental factors. Baseline temperatures correlated with demographics, comorbid conditions, and physiology, but these factors explained only a small part of individual temperature variation. Unexplained variation in baseline temperature, however, strongly predicted mortality. PMID:29237616

The interacting effects of temperature and food chain length on trophic abundance and ecosystem function.

PubMed

Beveridge, Oliver S; Humphries, Stuart; Petchey, Owen L

2010-05-01

1. While much is known about the independent effects of trophic structure and temperature on density and ecosystem processes, less is known about the interaction(s) between the two. 2. We manipulated the temperature of laboratory-based bacteria-protist communities that contained communities with one, two, or three trophic levels, and recorded species' densities and bacterial decomposition. 3. Temperature, food chain length and their interaction produced significant responses in microbial density and bacterial decomposition. Prey and resource density expressed different patterns of temperature dependency during different phases of population dynamics. The addition of a predator altered the temperature-density relationship of prey, from a unimodal trend to a negative one. Bacterial decomposition was greatest in the presence of consumers at higher temperatures. 4. These results are qualitatively consistent with a recent model of direct and indirect temperature effects on resource-consumer population dynamics. Results highlight and reinforce the importance of indirect effects of temperature mediated through trophic interactions. Understanding and predicting the consequences of environmental change will require that indirect effects, trophic structure, and individual species' tolerances be incorporated into theory and models.

Parametric study of irradiation effects on the ductile damage and flow stress behavior in ferritic-martensitic steels

NASA Astrophysics Data System (ADS)

Chakraborty, Pritam; Biner, S. Bulent

2015-10-01

Ferritic-martensitic steels are currently being considered as structural materials in fusion and Gen-IV nuclear reactors. These materials are expected to experience high dose radiation, which can increase their ductile to brittle transition temperature and susceptibility to failure during operation. Hence, to estimate the safe operational life of the reactors, precise evaluation of the ductile to brittle transition temperatures of ferritic-martensitic steels is necessary. Owing to the scarcity of irradiated samples, particularly at high dose levels, micro-mechanistic models are being employed to predict the shifts in the ductile to brittle transition temperatures. These models consider the ductile damage evolution, in the form of nucleation, growth and coalescence of voids; and the brittle fracture, in the form of probabilistic cleavage initiation, to estimate the influence of irradiation on the ductile to brittle transition temperature. However, the assessment of irradiation dependent material parameters is challenging and influences the accuracy of these models. In the present study, the effects of irradiation on the overall flow stress and ductile damage behavior of two ferritic-martensitic steels is parametrically investigated. The results indicate that the ductile damage model parameters are mostly insensitive to irradiation levels at higher dose levels though the resulting flow stress behavior varies significantly.

Elevated temperature causes metabolic trade-offs at the whole-organism level in the Antarctic fish Trematomus bernacchii.

PubMed

Sandersfeld, Tina; Davison, William; Lamare, Miles D; Knust, Rainer; Richter, Claudio

2015-08-01

As a response to ocean warming, shifts in fish species distribution and changes in production have been reported that have been partly attributed to temperature effects on the physiology of animals. The Southern Ocean hosts some of the most rapidly warming regions on earth and Antarctic organisms are reported to be especially temperature sensitive. While cellular and molecular organismic levels appear, at least partially, to compensate for elevated temperatures, the consequences of acclimation to elevated temperature for the whole organism are often less clear. Growth and reproduction are the driving factors for population structure and abundance. The aim of this study was to assess the effect of long-term acclimation to elevated temperature on energy budget parameters in the high-Antarctic fish Trematomus bernacchii. Our results show a complete temperature compensation for routine metabolic costs after 9 weeks of acclimation to 4°C. However, an up to 84% reduction in mass growth was measured at 2 and 4°C compared with the control group at 0°C, which is best explained by reduced food assimilation rates at warmer temperatures. With regard to a predicted temperature increase of up to 1.4°C in the Ross Sea by 2200, such a significant reduction in growth is likely to affect population structures in nature, for example by delaying sexual maturity and reducing production, with severe impacts on Antarctic fish communities and ecosystems. © 2015. Published by The Company of Biologists Ltd.

Intensity dependence of focused ultrasound lesion position

NASA Astrophysics Data System (ADS)

Meaney, Paul M.; Cahill, Mark D.; ter Haar, Gail R.

1998-04-01

Knowledge of the spatial distribution of intensity loss from an ultrasonic beam is critical to predicting lesion formation in focused ultrasound surgery. To date most models have used linear propagation models to predict the intensity profiles needed to compute the temporally varying temperature distributions. These can be used to compute thermal dose contours that can in turn be used to predict the extent of thermal damage. However, these simulations fail to adequately describe the abnormal lesion formation behavior observed for in vitro experiments in cases where the transducer drive levels are varied over a wide range. For these experiments, the extent of thermal damage has been observed to move significantly closer to the transducer with increasing transducer drive levels than would be predicted using linear propagation models. The simulations described herein, utilize the KZK (Khokhlov-Zabolotskaya-Kuznetsov) nonlinear propagation model with the parabolic approximation for highly focused ultrasound waves, to demonstrate that the positions of the peak intensity and the lesion do indeed move closer to the transducer. This illustrates that for accurate modeling of heating during FUS, nonlinear effects must be considered.

Effects of fluctuating temperature and food availability on reproduction and lifespan.

PubMed

Schwartz, Tonia S; Pearson, Phillip; Dawson, John; Allison, David B; Gohlke, Julia M

2016-12-15

Experimental studies on energetics and aging often remove two major factors that in part regulate the energy budget in a normal healthy individual: reproduction and fluctuating environmental conditions that challenge homeostasis. Here we use the cyclical parthenogenetic Daphnia pulex to evaluate the role of a fluctuating thermal environment on both reproduction and lifespan across six food concentrations. We test the hypotheses that (1) caloric restriction extends lifespan; (2) maximal reproduction will come with a cost of shortened lifespan; and (3) at a given food concentration, relative to a metabolically equivalent constant temperature environment a diel fluctuating thermal environment will alter the allocation of energy to reproduction and lifespan to maintain homeostasis. We did not identify a level of food concentration that extended lifespan in response to caloric restriction, and we found no cost of reproduction in terms of lifespan. Rather, the individuals at the highest food levels generally had the highest reproductive output and the longest lifespans, the individuals at the intermediate food level decreased reproduction and maintained lifespan, and the individuals at the three lower food concentrations had a decrease in reproduction and lifespan as would be predicted with increasing levels of starvation. Fluctuating temperature had no effect on lifespan at any food concentration, but delayed time to reproductive maturity and decreased early reproductive output at all food concentrations. This suggests that a fluctuating temperature regimen activates molecular pathways that alter energy allocation. The costs of fluctuating temperature on reproduction were not consistent across the lifespan. Statistical interactions for age of peak reproduction and lifetime fecundity suggest that senescence of the reproductive system may vary between temperature regimens at the different food concentrations. Copyright © 2016 Elsevier Inc. All rights reserved.

Effects of fluctuating temperature and food availability on reproduction and lifespan

PubMed Central

Schwartz, Tonia S.; Pearson, Phillip; Dawson, John; Allison, David B.; Gohlke, Julia M.

2016-01-01

Experimental studies on energetics and aging often remove two major factors that in part regulate the energy budget in a normal healthy individual: reproduction and fluctuating environmental conditions that challenge homeostasis. Here we use the cyclical parthenogenetic Daphnia pulex to evaluate the role of a fluctuating thermal environment on both reproduction and lifespan across six food concentrations. We test the hypotheses that (1) caloric restriction extends lifespan; (2) maximal reproduction will come with a cost of shortened lifespan; and (3) at a given food concentration, relative to a metabolically equivalent constant temperature environment a diel fluctuating thermal environment will alter the allocation of energy to reproduction and lifespan to maintain homeostasis. We did not identify a level of food concentration that extended lifespan in response to caloric restriction, and we found no cost of reproduction in terms of lifespan. Rather, the individuals at the highest food levels generally had the highest reproductive output and the longest lifespans, the individuals at the intermediate food level decreased reproduction and maintained lifespan, and the individuals at the three lower food concentrations had a decrease in reproduction and lifespan as would be predicted with increasing levels of starvation. Fluctuating temperature had no effect on lifespan at any food concentration, but delayed time to reproductive maturity and decreased early reproductive output at all food concentrations. This suggests that a fluctuating temperature regimen activates molecular pathways that alter energy allocation. The costs of fluctuating temperature on reproduction were not consistent across the lifespan. Statistical interactions for age of peak reproduction and lifetime fecundity suggest that senescence of the reproductive system may vary between temperature regimens at the different food concentrations. PMID:27364192

Experimental clean combustor program: Noise study

NASA Technical Reports Server (NTRS)

Sofrin, T. G.; Riloff, N., Jr.

1976-01-01

Under a Noise Addendum to the NASA Experimental Clean Combustor Program (ECCP) internal pressure fluctuations were measured during tests of JT9D combustor designs conducted in a burner test rig. Measurements were correlated with burner operating parameters using an expression relating farfield noise to these parameters. For a given combustor, variation of internal noise with operating parameters was reasonably well predicted by this expression but the levels were higher than farfield predictions and differed significantly among several combustors. For two burners, discharge stream temperature fluctuations were obtained with fast-response thermocouples to allow calculation of indirect combustion noise which would be generated by passage of the temperature inhomogeneities through the high pressure turbine stages of a JT9D turbofan engine. Using a previously developed analysis, the computed indirect combustion noise was significantly lower than total low frequency core noise observed on this and several other engines.

Development of a Polarizable Force Field for Molecular Dynamics Simulations of Poly (Ethylene Oxide) in Aqueous Solution.

PubMed

Starovoytov, Oleg N; Borodin, Oleg; Bedrov, Dmitry; Smith, Grant D

2011-06-14

We have developed a quantum chemistry-based polarizable potential for poly(ethylene oxide) (PEO) in aqueous solution based on the APPLE&P polarizable ether and the SWM4-DP polarizable water models. Ether-water interactions were parametrized to reproduce the binding energy of water with 1,2-dimethoxyethane (DME) determined from high-level quantum chemistry calculations. Simulations of DME-water and PEO-water solutions at room temperature using the new polarizable potentials yielded thermodynamic properties in good agreement with experimental results. The predicted miscibility of PEO and water as a function of the temperature was found to be strongly correlated with the predicted free energy of solvation of DME. The developed nonbonded force field parameters were found to be transferrable to poly(propylene oxide) (PPO), as confirmed by capturing, at least qualitatively, the miscibility of PPO in water as a function of the molecular weight.

Winds from T Tauri stars. I - Spherically symmetric models

NASA Technical Reports Server (NTRS)

Hartmann, Lee; Avrett, Eugene H.; Loeser, Rudolf; Calvet, Nuria

1990-01-01

Line fluxes and profiles are computed for a sequence of spherically symmetric T Tauri wind models. The calculations indicate that the H-alpha emission of T Tauri stars arises in an extended and probably turbulent circumstellar envelope at temperatures above about 8000 K. The models predict that Mg II resonance line emission should be strongly correlated with H-alpha fluxes; observed Mg II/H-alpha ratios are inconsistent with the models unless extinction corrections have been underestimated. The models predict that most of the Ca II resonance line and IR triplet emission arises in dense layers close to the star rather than in the wind. H-alpha emission levels suggest mass loss rates of about 10 to the -8th solar mass/yr for most T Tauri stars, in reasonable agreement with independent analysis of forbidden emission lines. These results should be useful for interpreting observed line profiles in terms of wind densities, temperatures, and velocity fields.

A trait-based framework for predicting when and where microbial adaptation to climate change will affect ecosystem functioning

USGS Publications Warehouse

Wallenstein, Matthew D.; Hall, Edward K.

2012-01-01

As the earth system changes in response to human activities, a critical objective is to predict how biogeochemical process rates (e.g. nitrification, decomposition) and ecosystem function (e.g. net ecosystem productivity) will change under future conditions. A particular challenge is that the microbial communities that drive many of these processes are capable of adapting to environmental change in ways that alter ecosystem functioning. Despite evidence that microbes can adapt to temperature, precipitation regimes, and redox fluctuations, microbial communities are typically not optimally adapted to their local environment. For example, temperature optima for growth and enzyme activity are often greater than in situ temperatures in their environment. Here we discuss fundamental constraints on microbial adaptation and suggest specific environments where microbial adaptation to climate change (or lack thereof) is most likely to alter ecosystem functioning. Our framework is based on two principal assumptions. First, there are fundamental ecological trade-offs in microbial community traits that occur across environmental gradients (in time and space). These trade-offs result in shifting of microbial function (e.g. ability to take up resources at low temperature) in response to adaptation of another trait (e.g. limiting maintenance respiration at high temperature). Second, the mechanism and level of microbial community adaptation to changing environmental parameters is a function of the potential rate of change in community composition relative to the rate of environmental change. Together, this framework provides a basis for developing testable predictions about how the rate and degree of microbial adaptation to climate change will alter biogeochemical processes in aquatic and terrestrial ecosystems across the planet.

Ocean warming ameliorates the negative effects of ocean acidification on Paracentrotus lividus larval development and settlement.

PubMed

García, Eliseba; Clemente, Sabrina; Hernández, José Carlos

2015-09-01

Ocean warming and acidification both impact marine ecosystems. All organisms have a limited body temperature range, outside of which they become functionally constrained. Beyond the absolute extremes of this range, they cannot survive. It is hypothesized that some stressors can present effects that interact with other environmental variables, such as ocean acidification (OA) that have the potential to narrow the thermal range where marine species are functional. An organism's response to ocean acidification can therefore be highly dependent on thermal conditions. This study evaluated the combined effects of predicted ocean warming conditions and acidification, on survival, development, and settlement, of the sea urchin Paracentrotus lividus. Nine combined treatments of temperature (19.0, 20.5 and 22.5 °C) and pH (8.1, 7.7 and 7.4 units) were carried out. All of the conditions tested were either within the current natural ranges of seawater pH and temperature or are within the ranges that have been predicted for the end of the century, in the sampling region (Canary Islands). Our results indicated that the negative effects of low pH on P. lividus larval development and settlement will be mitigated by a rise in seawater temperature, up to a thermotolerance threshold. Larval development and settlement performance of the sea urchin P. lividus was enhanced by a slight increase in temperature, even under lowered pH conditions. However, the species did show negative responses to the levels of ocean warming and acidification that have been predicted for the turn of the century. Copyright © 2015 Elsevier Ltd. All rights reserved.

Tracer Gas Transport under Mixed Convection Conditions in anExperimental Atrium: Comparison Between Experiments and CFDPredictions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jayaraman, Buvaneswari; Finlayson, Elizabeth U.; Sohn, MichaelD.

We compare computational fluid dynamics (CFD) predictions using a steady-state Reynolds Averaged Navier-Stokes (RANS) model with experimental data on airflow and pollutant dispersion under mixed-convection conditions in a 7 x 9 x 11m high experimental facility. The Rayleigh number, based on height, was O(10{sup 11}) and the atrium was mechanically ventilated. We released tracer gas in the atrium and measured the spatial distribution of concentrations; we then modeled the experiment using four different levels of modeling detail. The four computational models differ in the choice of temperature boundary conditions and the choice of turbulence model. Predictions from a low-Reynolds-number k-{var_epsilon}more » model with detailed boundary conditions agreed well with the data using three different model-measurement comparison metrics. Results from the same model with a single temperature prescribed for each wall also agreed well with the data. Predictions of a standard k-{var_epsilon} model were about the same as those of an isothermal model; neither performed well. Implications of the results for practical applications are discussed.« less

Nonlinear viscoelastic characterization of polymer materials using a dynamic-mechanical methodology

NASA Technical Reports Server (NTRS)

Strganac, Thomas W.; Payne, Debbie Flowers; Biskup, Bruce A.; Letton, Alan

1995-01-01

Polymer materials retrieved from LDEF exhibit nonlinear constitutive behavior; thus the authors present a method to characterize nonlinear viscoelastic behavior using measurements from dynamic (oscillatory) mechanical tests. Frequency-derived measurements are transformed into time-domain properties providing the capability to predict long term material performance without a lengthy experimentation program. Results are presented for thin-film high-performance polymer materials used in the fabrication of high-altitude scientific balloons. Predictions based upon a linear test and analysis approach are shown to deteriorate for moderate to high stress levels expected for extended applications. Tests verify that nonlinear viscoelastic response is induced by large stresses. Hence, an approach is developed in which the stress-dependent behavior is examined in a manner analogous to modeling temperature-dependent behavior with time-temperature correspondence and superposition principles. The development leads to time-stress correspondence and superposition of measurements obtained through dynamic mechanical tests. Predictions of material behavior using measurements based upon linear and nonlinear approaches are compared with experimental results obtained from traditional creep tests. Excellent agreement is shown for the nonlinear model.

Boundary Layer Transition Flight Experiment Overview

NASA Technical Reports Server (NTRS)

Berger, Karen T.; Anderson, Brian P.; Campbell, Charles H.; Garske, Michael T.; Saucedo, Luis A.; Kinder, Gerald R.; Micklos, Ann M.

2011-01-01

In support of the Boundary Layer Transition Flight Experiment (BLT FE) Project, a manufactured protuberance tile was installed on the port wing of Space Shuttle Orbiter Discovery for STS-119, STS-128, STS-131 and STS-133 as well as Space Shuttle Endeavour for STS-134. Additional instrumentation was installed in order to obtain more spatially resolved measurements downstream of the protuberance. This paper provides an overview of the BLT FE Project with emphasis on the STS-131 and STS-133 results. A high-level overview of the in-situ flight data is presented, along with a summary of the comparisons between pre- and post-flight analysis predictions and flight data. Comparisons show that empirically correlated predictions for boundary layer transition onset time closely match the flight data, while predicted surface temperatures were significantly higher than observed flight temperatures. A thermocouple anomaly observed on a number of the missions is discussed as are a number of the mitigation actions that will be taken on the final flight, STS-134, including potential alterations of the flight trajectory and changes to the flight instrumentation.

Boundary Layer Transition Flight Experiment Overview and In-Situ Measurements

NASA Technical Reports Server (NTRS)

Anderson, Brian P.; Campbell, Charles H.; Saucedo, Luis A.; Kinder, Gerald R.; Berger, Karen T.

2010-01-01

In support of the Boundary Layer Transition Flight Experiment (BLTFE) Project, a manufactured protuberance tile was installed on the port wing of Space Shuttle Orbiter Discovery for the flights of STS-119 and STS-128. Additional instrumentation was also installed in order to obtain more spatially resolved measurements downstream of the protuberance. This paper provides an overview of the BLTFE Project, including the project history, organizations involved, and motivations for the flight experiment. Significant efforts were made to place the protuberance at an appropriate location on the Orbiter and to design the protuberance to withstand the expected environments. Efforts were also extended to understand the as-fabricated shape of the protuberance and the thermal protection system tile configuration surrounding the protuberance. A high-level overview of the in-situ flight data is presented, along with a summary of the comparisons between pre- and post-flight analysis predictions and flight data. Comparisons show that predictions for boundary layer transition onset time closely match the flight data, while predicted temperatures were significantly higher than observed flight temperatures.

Assimilating a decade of hydrometeorological ship measurements across the North American Great Lakes

NASA Astrophysics Data System (ADS)

Fries, K. J.; Kerkez, B.

2015-12-01

We use a decade of measurements made by the Volunteer Observing Ships (VOS) program on the North American Great Lakes to derive spatial estimates of over-lake air temperature, sea surface temperature, dewpoint, and wind speed. This Lagrangian data set, which annually comprises over 200,000 point observations from over 80,000 ship reports across a 244,000 square kilometer study area, is assimilated using a Gaussian Process machine learning algorithm. This algorithm classifies a model for each hydrometeorological variable using a combination of latitudes, longitudes, seasons of the year, as well as predictions made by the National Digital Forecast Database (NDFD) and Great Lakes Coastal Forecasting System (GLCFS) operational models. We show that our data-driven method significantly improves the spatial and temporal estimation of overlake hydrometeorological variables, while simultaneously providing uncertainty estimates that can be used to improve historical and future predictions on dense spatial and temporal scales. This method stands to improve the prediction of water levels on the Great Lakes, which comprise over 90% of America's surface fresh water, and impact the lives of millions of people living in the basin.

Low temperature delays timing and enhances the cost of nitrogen fixation in the unicellular cyanobacterium Cyanothece

PubMed Central

Brauer, Verena S; Stomp, Maayke; Rosso, Camillo; van Beusekom, Sebastiaan AM; Emmerich, Barbara; Stal, Lucas J; Huisman, Jef

2013-01-01

Marine nitrogen-fixing cyanobacteria are largely confined to the tropical and subtropical ocean. It has been argued that their global biogeographical distribution reflects the physiologically feasible temperature range at which they can perform nitrogen fixation. In this study we refine this line of argumentation for the globally important group of unicellular diazotrophic cyanobacteria, and pose the following two hypotheses: (i) nitrogen fixation is limited by nitrogenase activity at low temperature and by oxygen diffusion at high temperature, which is manifested by a shift from strong to weak temperature dependence of nitrogenase activity, and (ii) high respiration rates are required to maintain very low levels of oxygen for nitrogenase, which results in enhanced respiratory cost per molecule of fixed nitrogen at low temperature. We tested these hypotheses in laboratory experiments with the unicellular cyanobacterium Cyanothece sp. BG043511. In line with the first hypothesis, the specific growth rate increased strongly with temperature from 18 to 30 °C, but leveled off at higher temperature under nitrogen-fixing conditions. As predicted by the second hypothesis, the respiratory cost of nitrogen fixation and also the cellular C:N ratio rose sharply at temperatures below 21 °C. In addition, we found that low temperature caused a strong delay in the onset of the nocturnal nitrogenase activity, which shortened the remaining nighttime available for nitrogen fixation. Together, these results point at a lower temperature limit for unicellular nitrogen-fixing cyanobacteria, which offers an explanation for their (sub)tropical distribution and suggests expansion of their biogeographical range by global warming. PMID:23823493

Space Shuttle Main Engine performance analysis

NASA Technical Reports Server (NTRS)

Santi, L. Michael

1993-01-01

For a number of years, NASA has relied primarily upon periodically updated versions of Rocketdyne's power balance model (PBM) to provide space shuttle main engine (SSME) steady-state performance prediction. A recent computational study indicated that PBM predictions do not satisfy fundamental energy conservation principles. More recently, SSME test results provided by the Technology Test Bed (TTB) program have indicated significant discrepancies between PBM flow and temperature predictions and TTB observations. Results of these investigations have diminished confidence in the predictions provided by PBM, and motivated the development of new computational tools for supporting SSME performance analysis. A multivariate least squares regression algorithm was developed and implemented during this effort in order to efficiently characterize TTB data. This procedure, called the 'gains model,' was used to approximate the variation of SSME performance parameters such as flow rate, pressure, temperature, speed, and assorted hardware characteristics in terms of six assumed independent influences. These six influences were engine power level, mixture ratio, fuel inlet pressure and temperature, and oxidizer inlet pressure and temperature. A BFGS optimization algorithm provided the base procedure for determining regression coefficients for both linear and full quadratic approximations of parameter variation. Statistical information relative to data deviation from regression derived relations was also computed. A new strategy for integrating test data with theoretical performance prediction was also investigated. The current integration procedure employed by PBM treats test data as pristine and adjusts hardware characteristics in a heuristic manner to achieve engine balance. Within PBM, this integration procedure is called 'data reduction.' By contrast, the new data integration procedure, termed 'reconciliation,' uses mathematical optimization techniques, and requires both measurement and balance uncertainty estimates. The reconciler attempts to select operational parameters that minimize the difference between theoretical prediction and observation. Selected values are further constrained to fall within measurement uncertainty limits and to satisfy fundamental physical relations (mass conservation, energy conservation, pressure drop relations, etc.) within uncertainty estimates for all SSME subsystems. The parameter selection problem described above is a traditional nonlinear programming problem. The reconciler employs a mixed penalty method to determine optimum values of SSME operating parameters associated with this problem formulation.

Climate relationships to fecal bacterial densities in Maryland shellfish harvest waters.

PubMed

Leight, A K; Hood, R; Wood, R; Brohawn, K

2016-02-01

Coastal states of the United States (US) routinely monitor shellfish harvest waters for types of bacteria that indicate the potential presence of fecal pollution. The densities of these indicator bacteria in natural waters may be related to climate in several ways, including through runoff from precipitation and survival related to water temperatures. The relationship between interannual precipitation and air temperature patterns and the densities of fecal indicator bacteria in shellfish harvest waters in Maryland's portion of the Chesapeake Bay was quantified using 34 years of data (1979-2013). Annual and seasonal precipitation totals had a strong positive relationship with average fecal coliform levels (R(2) = 0.69) and the proportion of samples with bacterial densities above the FDA regulatory criteria (R(2) = 0.77). Fecal coliform levels were also significantly and negatively related to average annual air temperature (R(2) = -0.43) and the average air temperature of the warmest month (R(2) = -0.57), while average seasonal air temperature was only significantly related to fecal coliform levels in the summer. River and regional fecal coliform levels displayed a wide range of relationships with precipitation and air temperature patterns, with stronger relationships in rural areas and mainstem Bay stations. Fecal coliform levels tended to be higher in years when the bulk of precipitation occurred throughout the summer and/or fall (August to September). Fecal coliform levels often peaked in late fall and winter, with precipitation peaking in summer and early fall. Continental-scale sea level pressure (SLP) analysis revealed an association between atmospheric patterns that influence both extratropical and tropical storm tracks and very high fecal coliform years, while regional precipitation was found to be significantly correlated with the Atlantic Multidecadal Oscillation and the Pacific North American Pattern. These findings indicate that management of shellfish harvest waters should account for changes in climate conditions and that SLP patterns may be particularly important for predicting years with extremely high levels of fecal coliforms. Published by Elsevier Ltd.

Temperature effects on stocks and stability of a phytoplankton-zooplankton model and the dependence on light and nutrients

USGS Publications Warehouse

Norberg, J.; DeAngelis, D.L.

1997-01-01

A model of a closed phytoplankton—zooplankton ecosystem was analyzed for effects of temperature on stocks and stability and the dependence of these effects on light and total nutrient concentration of the system. An analysis of the steady state equations showed that the effect of temperature on zooplankton and POM biomass was levelled when primary production is nutrient limited. Temperature increase had a generally negative effect on all biomasses at high nutrient levels due to increased maintenance costs. Nutrient limitation of net primary production is the main factor governing the effect of stocks and flows as well as the stability of the system. All components of the system, except for phytoplankton biomass, are proportional to net production and thus to the net effect of light on photosynthesis. However, temperature determines the slope of that relationship. The resilience of the system was measured by calculating the eigenvalues of the steady state. Under oligotrophic conditions, the system can be stable, but an increase in temperature can cause instability or a decrease in resilience. This conclusion is discussed in the face of recent models that take spatial heterogeneity into account and display far more stable behavior, in better agreement to empirical data. Using simulations, we found that the amplitude of fluctuations of the herbivore stock increases with temperature while the mean biomass and minimum values decrease in comparison with steady state predictions

An Intercomparison of Lidar Ozone and Temperature Measurements From the SOLVE Mission With Predicted Model Values

NASA Technical Reports Server (NTRS)

Burris, John; McGee, Thomas J.; Hoegy, Walt; Lait, Leslie; Sumnicht, Grant; Twigg, Larry; Heaps, William

2000-01-01

Temperature profiles acquired by Goddard Space Flight Center's AROTEL lidar during the SOLVE mission onboard NASA's DC-8 are compared with predicted values from several atmospheric models (DAO, NCEP and UKMO). The variability in the differences between measured and calculated temperature fields was approximately 5 K. Retrieved temperatures within the polar vortex showed large regions that were significantly colder than predicted by the atmospheric models.

Thickness dependences of solar cell performance

NASA Technical Reports Server (NTRS)

Sah, C. T.

1982-01-01

The significance of including factors such as the base resistivity loss for solar cells thicker than 100 microns and emitter and BSF layer recombination for thin cells in predicting the fill factor and efficiency of solar cells is demonstrated analytically. A model for a solar cell is devised with the inclusion of the dopant impurity concentration profile, variation of the electron and hole mobility with dopant concentration, the concentration and thermal capture and emission rates of the recombination center, device temperature, the AM1 spectra and the Si absorption coefficient. Device equations were solved by means of the transmission line technique. The analytical results were compared with those of low-level theory for cell performance. Significant differences in predictions of the fill factor resulted, and inaccuracies in the low-level approximations are discussed.

Predicted optical performance of the high-altitude balloon experiment (HABE) telescope in an adverse thermal environment

NASA Astrophysics Data System (ADS)

Akau, Ronald L.; Givler, Richard C.; Eastman, Daniel R.

1994-07-01

The High-Altitude Balloon Experiment telescope was designed to operate at an ambient temperature of -55 degree(s)C and an altitude of 26 km, using a precooled primary mirror. Although at this altitude the air density is only 1.4 percent of the value at sea level, the temperature gradients within the telescope are high enough to deform the optical wavefront. This problem is considerably lessened by precooling the primary mirror to -35 degree(s)C. This paper describes the application of several codes to determine the range of wavefront deformation during a mission.

Evaluation of nickel-hydrogen battery for space application

NASA Technical Reports Server (NTRS)

Billard, J. M.; Dupont, D.

1983-01-01

Results of electrical space qualification tests of nickel-hydrogen battery type HR 23S are presented. The results obtained for the nickel-cadmium battery type VO 23S are similar except that the voltage level and the charge conservation characteristics vary significantly. The electrical and thermal characteristics permit predictions of the following optimal applications: charge coefficient in the order of 1.3 to 1.4 at 20C; charge current density higher than C/10 at 20C; discharge current density from C/10 to C/3 at 20C; maximum discharge temperature: OC; storage temperature: -20C.

A spatiotemporal land-use regression model of winter fine particulate levels in residential neighbourhoods.

PubMed

Smargiassi, Audrey; Brand, Allan; Fournier, Michel; Tessier, François; Goudreau, Sophie; Rousseau, Jacques; Benjamin, Mario

2012-07-01

Residential wood burning can be a significant wintertime source of ambient fine particles in urban and suburban areas. We developed a statistical model to predict minute (min) levels of particles with median diameter of <1 μm (PM1) from mobile monitoring on evenings of winter weekends at different residential locations in Quebec, Canada, considering wood burning emissions. The 6 s PM1 levels were concurrently measured on 10 preselected routes travelled 3 to 24 times during the winters of 2008-2009 and 2009-2010 by vehicles equipped with a GRIMM or a dataRAM sampler and a Global Positioning System device. Route-specific and global land-use regression (LUR) models were developed using the following spatial and temporal covariates to predict 1-min-averaged PM1 levels: chimney density from property assessment data at sampling locations, PM2.5 "regional background" levels of particles with median diameter of <2.5 μm (PM2.5) and temperature and wind speed at hour of sampling, elevation at sampling locations and day of the week. In the various routes travelled, between 49% and 94% of the variability in PM1 levels was explained by the selected covariates. The effect of chimney density was not negligible in "cottage areas." The R(2) for the global model including all routes was 0.40. This LUR is the first to predict PM1 levels in both space and time with consideration of the effects of wood burning emissions. We show that the influence of chimney density, a proxy for wood burning emissions, varies by regions and that a global model cannot be used to predict PM in regions that were not measured. Future work should consider using both survey data on wood burning intensity and information from numerical air quality forecast models, in LUR models, to improve the generalisation of the prediction of fine particulate levels.

A simple method to predict body temperature of small reptiles from environmental temperature.

PubMed

Vickers, Mathew; Schwarzkopf, Lin

2016-05-01

To study behavioral thermoregulation, it is useful to use thermal sensors and physical models to collect environmental temperatures that are used to predict organism body temperature. Many techniques involve expensive or numerous types of sensors (cast copper models, or temperature, humidity, radiation, and wind speed sensors) to collect the microhabitat data necessary to predict body temperatures. Expense and diversity of requisite sensors can limit sampling resolution and accessibility of these methods. We compare body temperature predictions of small lizards from iButtons, DS18B20 sensors, and simple copper models, in both laboratory and natural conditions. Our aim was to develop an inexpensive yet accurate method for body temperature prediction. Either method was applicable given appropriate parameterization of the heat transfer equation used. The simplest and cheapest method was DS18B20 sensors attached to a small recording computer. There was little if any deficit in precision or accuracy compared to other published methods. We show how the heat transfer equation can be parameterized, and it can also be used to predict body temperature from historically collected data, allowing strong comparisons between current and previous environmental temperatures using the most modern techniques. Our simple method uses very cheap sensors and loggers to extensively sample habitat temperature, improving our understanding of microhabitat structure and thermal variability with respect to small ectotherms. While our method was quite precise, we feel any potential loss in accuracy is offset by the increase in sample resolution, important as it is increasingly apparent that, particularly for small ectotherms, habitat thermal heterogeneity is the strongest influence on transient body temperature.

Skin temperature reveals the intensity of acute stress

PubMed Central

Herborn, Katherine A.; Graves, James L.; Jerem, Paul; Evans, Neil P.; Nager, Ruedi; McCafferty, Dominic J.; McKeegan, Dorothy E.F.

2015-01-01

Acute stress triggers peripheral vasoconstriction, causing a rapid, short-term drop in skin temperature in homeotherms. We tested, for the first time, whether this response has the potential to quantify stress, by exhibiting proportionality with stressor intensity. We used established behavioural and hormonal markers: activity level and corticosterone level, to validate a mild and more severe form of an acute restraint stressor in hens (Gallus gallus domesticus). We then used infrared thermography (IRT) to non-invasively collect continuous temperature measurements following exposure to these two intensities of acute handling stress. In the comb and wattle, two skin regions with a known thermoregulatory role, stressor intensity predicted the extent of initial skin cooling, and also the occurrence of a more delayed skin warming, providing two opportunities to quantify stress. With the present, cost-effective availability of IRT technology, this non-invasive and continuous method of stress assessment in unrestrained animals has the potential to become common practice in pure and applied research. PMID:26434785

Skin temperature reveals the intensity of acute stress.

PubMed

Herborn, Katherine A; Graves, James L; Jerem, Paul; Evans, Neil P; Nager, Ruedi; McCafferty, Dominic J; McKeegan, Dorothy E F

2015-12-01

Acute stress triggers peripheral vasoconstriction, causing a rapid, short-term drop in skin temperature in homeotherms. We tested, for the first time, whether this response has the potential to quantify stress, by exhibiting proportionality with stressor intensity. We used established behavioural and hormonal markers: activity level and corticosterone level, to validate a mild and more severe form of an acute restraint stressor in hens (Gallus gallus domesticus). We then used infrared thermography (IRT) to non-invasively collect continuous temperature measurements following exposure to these two intensities of acute handling stress. In the comb and wattle, two skin regions with a known thermoregulatory role, stressor intensity predicted the extent of initial skin cooling, and also the occurrence of a more delayed skin warming, providing two opportunities to quantify stress. With the present, cost-effective availability of IRT technology, this non-invasive and continuous method of stress assessment in unrestrained animals has the potential to become common practice in pure and applied research. Copyright © 2015 Elsevier Inc. All rights reserved.

An investigation of satellite sounding products for the remote sensing of the surface energy balance and soil moisture

NASA Technical Reports Server (NTRS)

Diak, George R.

1989-01-01

Improved techniques for the remote sensing of the land surface energy balance (SEB) and soil moisture would greatly improve prediction of climate and weather as well as be of benefit to agriculture, hydrology and many associated fields. Most of the satellite remote sensing methods which were researched to date rely upon satellite-measured infrared surface temperatures or their time changes as a remote sensing signal. Optimistically, only four or five levels of information (wet to dry) in surface heating/evaporation are discernable by surface temperature methods and a good understanding of atmospheric conditions is necessary to bring them to this accuracy level. Skin temperature methods were researched as well as begun work on several new methods for the remote sensing of the SEB, some elements of which are applicable to current and retrospective data sources and some which will rely on instrumentation from the Earth Observing System (EOS) program in the 1990s.

Mitigating the Impacts of Climate Nonstationarity on Seasonal Streamflow Predictability in the U.S. Southwest

NASA Astrophysics Data System (ADS)

Lehner, Flavio; Wood, Andrew W.; Llewellyn, Dagmar; Blatchford, Douglas B.; Goodbody, Angus G.; Pappenberger, Florian

2017-12-01

Seasonal streamflow predictions provide a critical management tool for water managers in the American Southwest. In recent decades, persistent prediction errors for spring and summer runoff volumes have been observed in a number of watersheds in the American Southwest. While mostly driven by decadal precipitation trends, these errors also relate to the influence of increasing temperature on streamflow in these basins. Here we show that incorporating seasonal temperature forecasts from operational global climate prediction models into streamflow forecasting models adds prediction skill for watersheds in the headwaters of the Colorado and Rio Grande River basins. Current dynamical seasonal temperature forecasts now show sufficient skill to reduce streamflow forecast errors in snowmelt-driven regions. Such predictions can increase the resilience of streamflow forecasting and water management systems in the face of continuing warming as well as decadal-scale temperature variability and thus help to mitigate the impacts of climate nonstationarity on streamflow predictability.

A new criterion for predicting rolling-element fatigue lives of through-hardened steels

NASA Technical Reports Server (NTRS)

Chevalier, J. L.; Zaretsky, E. V.; Parker, R. J.

1972-01-01

A carbide factor was derived based upon a statistical analysis which related rolling-element fatigue life to the total number of residual carbide particles per unit area, median residual carbide size, and percent residual carbide area. An equation was experimentally determined which predicts material hardness as a function of temperature. The limiting temperatures of all of the materials studied were dependent on initial room temperature hardness and tempering temperature. An equation was derived combining the effects of material hardness, carbide factor, and bearing temperature to predict rolling-element bearing life.

Contribution of air conditioning adoption to future energy use under global warming.

PubMed

Davis, Lucas W; Gertler, Paul J

2015-05-12

As household incomes rise around the world and global temperatures go up, the use of air conditioning is poised to increase dramatically. Air conditioning growth is expected to be particularly strong in middle-income countries, but direct empirical evidence is scarce. In this paper we use high-quality microdata from Mexico to describe the relationship between temperature, income, and air conditioning. We describe both how electricity consumption increases with temperature given current levels of air conditioning, and how climate and income drive air conditioning adoption decisions. We then combine these estimates with predicted end-of-century temperature changes to forecast future energy consumption. Under conservative assumptions about household income, our model predicts near-universal saturation of air conditioning in all warm areas within just a few decades. Temperature increases contribute to this surge in adoption, but income growth by itself explains most of the increase. What this will mean for electricity consumption and carbon dioxide emissions depends on the pace of technological change. Continued advances in energy efficiency or the development of new cooling technologies could reduce the energy consumption impacts. Similarly, growth in low-carbon electricity generation could mitigate the increases in carbon dioxide emissions. However, the paper illustrates the enormous potential impacts in this sector, highlighting the importance of future research on adaptation and underscoring the urgent need for global action on climate change.

Contribution of air conditioning adoption to future energy use under global warming

PubMed Central

Davis, Lucas W.; Gertler, Paul J.

2015-01-01

As household incomes rise around the world and global temperatures go up, the use of air conditioning is poised to increase dramatically. Air conditioning growth is expected to be particularly strong in middle-income countries, but direct empirical evidence is scarce. In this paper we use high-quality microdata from Mexico to describe the relationship between temperature, income, and air conditioning. We describe both how electricity consumption increases with temperature given current levels of air conditioning, and how climate and income drive air conditioning adoption decisions. We then combine these estimates with predicted end-of-century temperature changes to forecast future energy consumption. Under conservative assumptions about household income, our model predicts near-universal saturation of air conditioning in all warm areas within just a few decades. Temperature increases contribute to this surge in adoption, but income growth by itself explains most of the increase. What this will mean for electricity consumption and carbon dioxide emissions depends on the pace of technological change. Continued advances in energy efficiency or the development of new cooling technologies could reduce the energy consumption impacts. Similarly, growth in low-carbon electricity generation could mitigate the increases in carbon dioxide emissions. However, the paper illustrates the enormous potential impacts in this sector, highlighting the importance of future research on adaptation and underscoring the urgent need for global action on climate change. PMID:25918391

Sensitivity of salmonid freshwater life history in western US streams to future climate conditions.

PubMed

Beer, W Nicholas; Anderson, James J

2013-08-01

We projected effects of mid-21st century climate on the early life growth of Chinook salmon (Oncorhynchus tshawytscha) and steelhead (O. mykiss) in western United States streams. Air temperature and snowpack trends projected from observed 20th century trends were used to predict future seasonal stream temperatures. Fish growth from winter to summer was projected with temperature-dependent models of egg development and juvenile growth. Based on temperature data from 115 sites, by mid-21st century, the effects of climate change are projected to be mixed. Fish in warm-region streams that are currently cooled by snow melt will grow less, and fish in suboptimally cool streams will grow more. Relative to 20th century conditions, by mid-21st century juvenile salmonids' weights are expected to be lower in the Columbia Basin and California Central Valley, but unchanged or greater in coastal and mountain streams. Because fish weight affects fish survival, the predicted changes in weight could impact population fitness depending on other factors such as density effects, food quality and quantity changes, habitat alterations, etc. The level of year-to-year variability in stream temperatures is high and our analysis suggests that identifying effects of climate change over the natural variability will be difficult except in a few streams. © 2013 John Wiley & Sons Ltd.

High temperature, oxygen, and performance: Insights from reptiles and amphibians.

PubMed

Gangloff, Eric J; Telemeco, Rory S

2018-04-25

Much recent theoretical and empirical work has sought to describe the physiological mechanisms underlying thermal tolerance in animals. Leading hypotheses can be broadly divided into two categories that primarily differ in organizational scale: 1) high temperature directly reduces the function of subcellular machinery, such as enzymes and cell membranes, or 2) high temperature disrupts system-level interactions, such as mismatches in the supply and demand of oxygen, prior to having any direct negative effect on the subcellular machinery. Nonetheless, a general framework describing the contexts under which either subcellular component or organ system failure limits organisms at high temperatures remains elusive. With this commentary, we leverage decades of research on the physiology of ectothermic tetrapods (amphibians and non-avian reptiles) to address these hypotheses. Available data suggest both mechanisms are important. Thus, we expand previous work and propose the Hierarchical Mechanisms of Thermal Limitation (HMTL) hypothesis, which explains how subcellular and organ system failures interact to limit performance and set tolerance limits at high temperatures. We further integrate this framework with the thermal performance curve paradigm commonly used to predict the effects of thermal environments on performance and fitness. The HMTL framework appears to successfully explain diverse observations in reptiles and amphibians and makes numerous predictions that remain untested. We hope that this framework spurs further research in diverse taxa and facilitates mechanistic forecasts of biological responses to climate change.

Configuration of the Hemoglobin Oxygen Dissociation Curve Demystified: A Basic Mathematical Proof for Medical and Biological Sciences Undergraduates

ERIC Educational Resources Information Center

Leow, Melvin Khee-Shing

2007-01-01

The oxygen dissociation curve (ODC) of hemoglobin (Hb) has been widely studied and mathematically described for nearly a century. Numerous mathematical models have been designed to predict with ever-increasing accuracy the behavior of oxygen transport by Hb in differing conditions of pH, carbon dioxide, temperature, Hb levels, and…

Correleation of the SAGE III on ISS Thermal Models in Thermal Desktop

NASA Technical Reports Server (NTRS)

Amundsen, Ruth M.; Davis, Warren T.; Liles, Kaitlin, A. K.; McLeod, Shawn C.

2017-01-01

The Stratospheric Aerosol and Gas Experiment III (SAGE III) instrument is the fifth in a series of instruments developed for monitoring aerosols and gaseous constituents in the stratosphere and troposphere. SAGE III was launched on February 19, 2017 and mounted to the International Space Station (ISS) to begin its three-year mission. A detailed thermal model of the SAGE III payload, which consists of multiple subsystems, has been developed in Thermal Desktop (TD). Correlation of the thermal model is important since the payload will be expected to survive a three-year mission on ISS under varying thermal environments. Three major thermal vacuum (TVAC) tests were completed during the development of the SAGE III Instrument Payload (IP); two subsystem-level tests and a payload-level test. Additionally, a characterization TVAC test was performed in order to verify performance of a system of heater plates that was designed to allow the IP to achieve the required temperatures during payload-level testing; model correlation was performed for this test configuration as well as those including the SAGE III flight hardware. This document presents the methods that were used to correlate the SAGE III models to TVAC at the subsystem and IP level, including the approach for modeling the parts of the payload in the thermal chamber, generating pre-test predictions, and making adjustments to the model to align predictions with temperatures observed during testing. Model correlation quality will be presented and discussed, and lessons learned during the correlation process will be shared.

A complete Holocene record of trematode-bivalve infection and implications for the response of parasitism to climate change

NASA Astrophysics Data System (ADS)

Huntley, John Warren; Fürsich, Franz T.; Alberti, Matthias; Hethke, Manja; Liu, Chunlian

2014-12-01

Increasing global temperature and sea-level rise have led to concern about expansions in the distribution and prevalence of complex-lifecycle parasites (CLPs). Indeed, numerous environmental variables can influence the infectivity and reproductive output of many pathogens. Digenean trematodes are CLPs with intermediate invertebrate and definitive vertebrate hosts. Global warming and sea level rise may affect these hosts to varying degrees, and the effect of increasing temperature on parasite prevalence has proven to be nonlinear and difficult to predict. Projecting the response of parasites to anthropogenic climate change is vital for human health, and a longer term perspective (104 y) offered by the subfossil record is necessary to complement the experimental and historical approaches of shorter temporal duration (10-1 to 103 y). We demonstrate, using a high-resolution 9,600-y record of trematode parasite traces in bivalve hosts from the Holocene Pearl River Delta, that prevalence was significantly higher during the earliest stages of sea level rise, significantly lower during the maximum transgression, and statistically indistinguishable in the other stages of sea-level rise and delta progradation. This stratigraphic paleobiological pattern represents the only long-term high-resolution record of pathogen response to global change, is consistent with fossil and recent data from other marine basins, and is instructive regarding the future of disease. We predict an increase in trematode prevalence concurrent with anthropogenic warming and marine transgression, with negative implications for estuarine macrobenthos, marine fisheries, and human health.

Computational prediction of Mg-isotope fractionation between aqueous [Mg(OH2)6]2+ and brucite

NASA Astrophysics Data System (ADS)

Colla, Christopher A.; Casey, William H.; Ohlin, C. André

2018-04-01

The fractionation factor in the magnesium-isotope fractionation between aqueous solutions of magnesium and brucite changes sign with increasing temperature, as uncovered by recent experiments. To understand this behavior, the Reduced Partition Function Ratios and isotopic fractionation factors (Δ26/24Mgbrucite-Mg(aq)) are calculated using molecular models of aqueous [Mg(OH2)6]2+ and the mineral brucite at increasing levels of density functional theory. The calculations were carried out on the [Mg(OH2)6]2+·12H2O cluster, along with different Pauling-bond-strength-conserving models of the mineral lattice of brucite. Three conclusions were reached: (i) all levels of theory overestimate bond distances in the aqua ion complex relative to Tutton's salts; (ii) the calculations predict that brucite at 298.15 K is always enriched in the heavy isotope, in contrast with experimental observations; (iii) the temperature dependencies of Wimpenny et al. (2014) and Li et al. (2014) could only be achieved by fixing the bond distances in the [Mg(OH2)6]2+·12H2O cluster to values close to those observed in crystals that trap the hydrated ion.

Mechanical-Electrochemical-Thermal Simulation of Lithium-Ion Cells

DOE Office of Scientific and Technical Information (OSTI.GOV)

Santhanagopalan, Shriram; Zhang, Chao; Sprague, Michael A.

2016-06-01

Models capture the force response for single-cell and cell-string levels to within 15%-20% accuracy and predict the location for the origin of failure based on the deformation data from the experiments. At the module level, there is some discrepancy due to poor mechanical characterization of the packaging material between the cells. The thermal response (location and value of maximum temperature) agrees qualitatively with experimental data. In general, the X-plane results agree with model predictions to within 20% (pending faulty thermocouples, etc.); the Z-plane results show a bigger variability both between the models and test-results, as well as among multiple repeatsmore » of the tests. The models are able to capture the timing and sequence in voltage drop observed in the multi-cell experiments; the shapes of the current and temperature profiles need more work to better characterize propagation. The cells within packaging experience about 60% less force under identical impact test conditions, so the packaging on the test articles is robust. However, under slow-crush simulations, the maximum deformation of the cell strings with packaging is about twice that of cell strings without packaging.« less

Gradient Augmented Level Set Method for Two Phase Flow Simulations with Phase Change

NASA Astrophysics Data System (ADS)

Anumolu, C. R. Lakshman; Trujillo, Mario F.

2016-11-01

A sharp interface capturing approach is presented for two-phase flow simulations with phase change. The Gradient Augmented Levelset method is coupled with the two-phase momentum and energy equations to advect the liquid-gas interface and predict heat transfer with phase change. The Ghost Fluid Method (GFM) is adopted for velocity to discretize the advection and diffusion terms in the interfacial region. Furthermore, the GFM is employed to treat the discontinuity in the stress tensor, velocity, and temperature gradient yielding an accurate treatment in handling jump conditions. Thermal convection and diffusion terms are approximated by explicitly identifying the interface location, resulting in a sharp treatment for the energy solution. This sharp treatment is extended to estimate the interfacial mass transfer rate. At the computational cell, a d-cubic Hermite interpolating polynomial is employed to describe the interface location, which is locally fourth-order accurate. This extent of subgrid level description provides an accurate methodology for treating various interfacial processes with a high degree of sharpness. The ability to predict the interface and temperature evolutions accurately is illustrated by comparing numerical results with existing 1D to 3D analytical solutions.

Fuzzy logic, artificial neural network and mathematical model for prediction of white mulberry drying kinetics

NASA Astrophysics Data System (ADS)

Jahedi Rad, Shahpour; Kaveh, Mohammad; Sharabiani, Vali Rasooli; Taghinezhad, Ebrahim

2018-05-01

The thin-layer convective- infrared drying behavior of white mulberry was experimentally studied at infrared power levels of 500, 1000 and 1500 W, drying air temperatures of 40, 55 and 70 °C and inlet drying air speeds of 0.4, 1 and 1.6 m/s. Drying rate raised with the rise of infrared power levels at a distinct air temperature and velocity and thus decreased the drying time. Five mathematical models describing thin-layer drying have been fitted to the drying data. Midlli et al. model could satisfactorily describe the convective-infrared drying of white mulberry fruit with the values of the correlation coefficient (R 2=0.9986) and root mean square error of (RMSE= 0.04795). Artificial neural network (ANN) and fuzzy logic methods was desirably utilized for modeling output parameters (moisture ratio (MR)) regarding input parameters. Results showed that output parameters were more accurately predicted by fuzzy model than by the ANN and mathematical models. Correlation coefficient (R 2) and RMSE generated by the fuzzy model (respectively 0.9996 and 0.01095) were higher than referred values for the ANN model (0.9990 and 0.01988 respectively).

Test Data Analysis of a Spray Bar Zero-Gravity Liquid Hydrogen Vent System for Upper Stages

NASA Technical Reports Server (NTRS)

Hedayat, A.; Bailey, J. W.; Hastings, L. J.; Flachbart, R. H.

2003-01-01

To support development of a zero-gravity pressure control capability for liquid hydrogen (LH2), a series of thermodynamic venting system (TVS) tests was conducted in 1996 and 1998 using the Marshall Space Flight Center (MSFC) multipurpose hydrogen test bed (MHTB). These tests were performed with ambient heat leaks =20 and 50 W for tank fill levels of 90%, 50%, and 25%. TVS performance testing revealed that the spray bar was highly effective in providing tank pressure control within a 7-kPa band (131-138 Wa), and complete destratification of the liquid and the ullage was achieved with all test conditions. Seven of the MHTB tests were correlated with the TVS performance analytical model. The tests were selected to encompass the range of tank fill levels, ambient heat leaks, operational modes, and ullage pressurants. The TVS model predicted ullage pressure and temperature and bulk liquid saturation pressure and temperature obtained from the TVS model were compared with the test data. During extended self-pressurization periods, following tank lockup, the model predicted faster pressure rise rates than were measured. However, once the system entered the cyclic mixing/venting operational mode, the modeled and measured data were quite similar.

Neural networks to predict exosphere temperature corrections

NASA Astrophysics Data System (ADS)

Choury, Anna; Bruinsma, Sean; Schaeffer, Philippe

2013-10-01

Precise orbit prediction requires a forecast of the atmospheric drag force with a high degree of accuracy. Artificial neural networks are universal approximators derived from artificial intelligence and are widely used for prediction. This paper presents a method of artificial neural networking for prediction of the thermosphere density by forecasting exospheric temperature, which will be used by the semiempirical thermosphere Drag Temperature Model (DTM) currently developed. Artificial neural network has shown to be an effective and robust forecasting model for temperature prediction. The proposed model can be used for any mission from which temperature can be deduced accurately, i.e., it does not require specific training. Although the primary goal of the study was to create a model for 1 day ahead forecast, the proposed architecture has been generalized to 2 and 3 days prediction as well. The impact of artificial neural network predictions has been quantified for the low-orbiting satellite Gravity Field and Steady-State Ocean Circulation Explorer in 2011, and an order of magnitude smaller orbit errors were found when compared with orbits propagated using the thermosphere model DTM2009.

Evaluation of Computational Fluid Dynamics and Coupled Fluid-Solid Modeling for a Direct Transfer Preswirl System.

PubMed

Javiya, Umesh; Chew, John; Hills, Nick; Dullenkopf, Klaus; Scanlon, Timothy

2013-05-01

The prediction of the preswirl cooling air delivery and disk metal temperature are important for the cooling system performance and the rotor disk thermal stresses and life assessment. In this paper, standalone 3D steady and unsteady computation fluid dynamics (CFD), and coupled FE-CFD calculations are presented for prediction of these temperatures. CFD results are compared with previous measurements from a direct transfer preswirl test rig. The predicted cooling air temperatures agree well with the measurement, but the nozzle discharge coefficients are under predicted. Results from the coupled FE-CFD analyses are compared directly with thermocouple temperature measurements and with heat transfer coefficients on the rotor disk previously obtained from a rotor disk heat conduction solution. Considering the modeling limitations, the coupled approach predicted the solid metal temperatures well. Heat transfer coefficients on the rotor disk from CFD show some effect of the temperature variations on the heat transfer coefficients. Reasonable agreement is obtained with values deduced from the previous heat conduction solution.

Roughness induced transition and heat transfer augmentation in hypersonic environments

NASA Astrophysics Data System (ADS)

Wassel, A. T.; Shih, W. C. L.; Courtney, J. F.

Boundary layer transition and surface heating distributions on graphite, fine weave carbon-carbon, and metallic nosetip materials were derived from surface temperature responses measured in nitrogen environments during both free-flight and track-guided testing in hypersonic environments. Innovative test procedures were developed, and heat transfer results were validated against established theory through experiments using a super-smooth tungsten model. Quantitative definitions of mean transition front locations were established by deriving heat flux distributions from measured temperatures, and comparisons made with existing nosetip transition correlations. Qualitative transition locations were inferred directly from temperature distributions to investigate preferred orientations on fine weave nosetips. Levels of roughness augmented heat transfer were generally shown to be below values predicted by state-of-the-art methods.

Temperature distributions and thermal stresses in a graded zirconia/metal gas path seal system for aircraft gas turbine engines

NASA Technical Reports Server (NTRS)

Taylor, C. M.; Bill, R. C.

1978-01-01

A ceramic/metallic aircraft gas turbine outer gas path seal designed for improved engine performance was studied. Transient temperature and stress profiles in a test seal geometry were determined by numerical analysis. During a simulated engine deceleration cycle from sea-level takeoff to idle conditions, the maximum seal temperature occurred below the seal surface, therefore the top layer of the seal was probably subjected to tensile stresses exceeding the modulus of rupture. In the stress analysis both two- and three-dimensional finite element computer programs were used. Predicted trends of the simpler and more easily usable two-dimensional element programs were borne out by the three-dimensional finite element program results.

Charge Yield at Low Electric Fields: Considerations for Bipolar Integrated Circuits

NASA Technical Reports Server (NTRS)

Johnston, A. H.; Swimm, R. T.; Thorbourn, D. O.

2013-01-01

A significant reduction in total dose damage is observed when bipolar integrated circuits are irradiated at low temperature. This can be partially explained by the Onsager theory of recombination, which predicts a strong temperature dependence for charge yield under low-field conditions. Reduced damage occurs for biased as well as unbiased devices because the weak fringing field in thick bipolar oxides only affects charge yield near the Si/SiO2 interface, a relatively small fraction of the total oxide thickness. Lowering the temperature of bipolar ICs - either continuously, or for time periods when they are exposed to high radiation levels - provides an additional degree of freedom to improve total dose performance of bipolar circuits, particularly in space applications.

Insects in fluctuating thermal environments.

PubMed

Colinet, Hervé; Sinclair, Brent J; Vernon, Philippe; Renault, David

2015-01-07

All climate change scenarios predict an increase in both global temperature means and the magnitude of seasonal and diel temperature variation. The nonlinear relationship between temperature and biological processes means that fluctuating temperatures lead to physiological, life history, and ecological consequences for ectothermic insects that diverge from those predicted from constant temperatures. Fluctuating temperatures that remain within permissive temperature ranges generally improve performance. By contrast, those which extend to stressful temperatures may have either positive impacts, allowing repair of damage accrued during exposure to thermal extremes, or negative impacts from cumulative damage during successive exposures. We discuss the mechanisms underlying these differing effects. Fluctuating temperatures could be used to enhance or weaken insects in applied rearing programs, and any prediction of insect performance in the field-including models of climate change or population performance-must account for the effect of fluctuating temperatures.