Thermal analysis of combinatorial solid geometry models using SINDA

NASA Technical Reports Server (NTRS)

Gerencser, Diane; Radke, George; Introne, Rob; Klosterman, John; Miklosovic, Dave

1993-01-01

Algorithms have been developed using Monte Carlo techniques to determine the thermal network parameters necessary to perform a finite difference analysis on Combinatorial Solid Geometry (CSG) models. Orbital and laser fluxes as well as internal heat generation are modeled to facilitate satellite modeling. The results of the thermal calculations are used to model the infrared (IR) images of targets and assess target vulnerability. Sample analyses and validation are presented which demonstrate code products.

Insights to Engineered Geothermal System Performance Using Gringarten-Witherspoon-Ohnishi Analytical Solutions and Fracture Network Models

NASA Astrophysics Data System (ADS)

Doe, T.; McLaren, R.; Finilla, A.

2017-12-01

An enduring legacy of Paul Witherspoon and his students and colleagues has been both the development of geothermal energy and the bases of modern fractured-rock hydrogeology. One of the seminal contributions to the geothermal field was Gringarten, Witherspoon, and Ohnishi's analytical models for enhanced geothermal systems. Although discrete fracture network (DFN) modeling developed somewhat independently in the late 1970s, Paul Witherspoon's foresight in promoting underground in situ testing at the Stripa Mine in Sweden was a major driver in Lawrence Berkeley Laboratory's contributions to its development.This presentation looks extensions of Gringarten's analytical model into discrete fracture network modeling as a basis for providing further insights into the challenges and opportunities of engineered geothermal systems. The analytical solution itself has many insightful applications beyond those presented in the original paper. The definition of dimensionless time by itself shows that thermal breakthrough has a second power dependence on surface area and on flow rate. The fracture intensity also plays a strong role, as it both increases the surface area and decrease his flow rate per fracture. The improvement of EGS performance with fracture intensity reaches a limit where thermal depletion of the rock lags only slightly behind the thermal breakthrough of cold water in the fracture network.Simple network models, which couple a DFN generator (FracMan) with a hydrothermally coupled flow solver (HydroGeoSphere) expand on Gringarten's concepts to show that realistic heterogeneity of spacing and transmissivity significantly degrades EGS performance. EGS production in networks of stimulated fractures initially follows Gringarten's type curves, with a later deviation is the smaller rock blocks thermally deplete and the entire stimulated volume acts as a single sink. Three-dimensional models of EGS performance show the critical importance of the relative magnitudes of fluid pressure and stress gradients, preferential growth and aperture enhancement may change with depth creating preferential pathways through rock this cooler than the injection depth.

Numerical Simulation and Artificial Neural Network Modeling for Predicting Welding-Induced Distortion in Butt-Welded 304L Stainless Steel Plates

NASA Astrophysics Data System (ADS)

Narayanareddy, V. V.; Chandrasekhar, N.; Vasudevan, M.; Muthukumaran, S.; Vasantharaja, P.

2016-02-01

In the present study, artificial neural network modeling has been employed for predicting welding-induced angular distortions in autogenous butt-welded 304L stainless steel plates. The input data for the neural network have been obtained from a series of three-dimensional finite element simulations of TIG welding for a wide range of plate dimensions. Thermo-elasto-plastic analysis was carried out for 304L stainless steel plates during autogenous TIG welding employing double ellipsoidal heat source. The simulated thermal cycles were validated by measuring thermal cycles using thermocouples at predetermined positions, and the simulated distortion values were validated by measuring distortion using vertical height gauge for three cases. There was a good agreement between the model predictions and the measured values. Then, a multilayer feed-forward back propagation neural network has been developed using the numerically simulated data. Artificial neural network model developed in the present study predicted the angular distortion accurately.

Neural Network approach to assess the thermal affected zone around the injection well in a groundwater heat pump system

NASA Astrophysics Data System (ADS)

Lo Russo, Stefano; Taddia, Glenda; Verda, Vittorio

2014-05-01

The common use of well doublets for groundwater-sourced heating or cooling results in a thermal plume of colder or warmer re-injected groundwater known as the Thermal Affected Zone(TAZ). The plumes may be regarded either as a potential anthropogenic geothermal resource or as pollution, depending on downstream aquifer usage. A fundamental aspect in groundwater heat pump (GWHP) plant design is the correct evaluation of the thermally affected zone that develops around the injection well. Temperature anomalies are detected through numerical methods. Crucial elements in the process of thermal impact assessment are the sizes of installations, their position, the heating/cooling load of the building, and the temperature drop/increase imposed on the re-injected water flow. For multiple-well schemes, heterogeneous aquifers, or variable heating and cooling loads, numerical models that simulate groundwater and heat transport are needed. These tools should consider numerous scenarios obtained considering different heating/cooling loads, positions, and operating modes. Computational fluid dynamic (CFD) models are widely used in this field because they offer the opportunity to calculate the time evolution of the thermal plume produced by a heat pump, depending on the characteristics of the subsurface and the heat pump. Nevertheless, these models require large computational efforts, and therefore their use may be limited to a reasonable number of scenarios. Neural networks could represent an alternative to CFD for assessing the TAZ under different scenarios referring to a specific site. The use of neural networks is proposed to determine the time evolution of the groundwater temperature downstream of an installation as a function of the possible utilization profiles of the heat pump. The main advantage of neural network modeling is the possibility of evaluating a large number of scenarios in a very short time, which is very useful for the preliminary analysis of future multiple installations. The neural network is trained using the results from a CFD model (FEFLOW) applied to the installation at Politecnico di Torino (Italy) under several operating conditions.

[Spectral quantitative analysis by nonlinear partial least squares based on neural network internal model for flue gas of thermal power plant].

PubMed

Cao, Hui; Li, Yao-Jiang; Zhou, Yan; Wang, Yan-Xia

2014-11-01

To deal with nonlinear characteristics of spectra data for the thermal power plant flue, a nonlinear partial least square (PLS) analysis method with internal model based on neural network is adopted in the paper. The latent variables of the independent variables and the dependent variables are extracted by PLS regression firstly, and then they are used as the inputs and outputs of neural network respectively to build the nonlinear internal model by train process. For spectra data of flue gases of the thermal power plant, PLS, the nonlinear PLS with the internal model of back propagation neural network (BP-NPLS), the non-linear PLS with the internal model of radial basis function neural network (RBF-NPLS) and the nonlinear PLS with the internal model of adaptive fuzzy inference system (ANFIS-NPLS) are compared. The root mean square error of prediction (RMSEP) of sulfur dioxide of BP-NPLS, RBF-NPLS and ANFIS-NPLS are reduced by 16.96%, 16.60% and 19.55% than that of PLS, respectively. The RMSEP of nitric oxide of BP-NPLS, RBF-NPLS and ANFIS-NPLS are reduced by 8.60%, 8.47% and 10.09% than that of PLS, respectively. The RMSEP of nitrogen dioxide of BP-NPLS, RBF-NPLS and ANFIS-NPLS are reduced by 2.11%, 3.91% and 3.97% than that of PLS, respectively. Experimental results show that the nonlinear PLS is more suitable for the quantitative analysis of glue gas than PLS. Moreover, by using neural network function which can realize high approximation of nonlinear characteristics, the nonlinear partial least squares method with internal model mentioned in this paper have well predictive capabilities and robustness, and could deal with the limitations of nonlinear partial least squares method with other internal model such as polynomial and spline functions themselves under a certain extent. ANFIS-NPLS has the best performance with the internal model of adaptive fuzzy inference system having ability to learn more and reduce the residuals effectively. Hence, ANFIS-NPLS is an accurate and useful quantitative thermal power plant flue gas analysis method.

Generation, Analysis and Characterization of Anisotropic Engineered Meta Materials

NASA Astrophysics Data System (ADS)

Trifale, Ninad T.

A methodology for a systematic generation of highly anisotropic micro-lattice structures was investigated. Multiple algorithms for generation and validation of engineered structures are developed and evaluated. Set of all possible permutations of structures for an 8-node cubic unit cell were considered and the degree of anisotropy of meta-properties in heat transport and mechanical elasticity were evaluated. Feasibility checks were performed to ensure that the generated unit cell network was repeatable and a continuous lattice structure. Four different strategies for generating permutations of the structures are discussed. Analytical models were developed to predict effective thermal, mechanical and permeability characteristics of these cellular structures.Experimentation and numerical modeling techniques were used to validate the models that are developed. A self-consistent mechanical elasticity model was developed which connects the meso-scale properties to stiffness of individual struts. A three dimensional thermal resistance network analogy was used to evaluate the effective thermal conductivity of the structures. The struts were modeled as a network of one dimensional thermal resistive elements and effective conductivity evaluated. Models were validated against numerical simulations and experimental measurements on 3D printed samples. Model was developed to predict effective permeability of these engineered structures based on Darcy's law. Drag coefficients were evaluated for individual connections in transverse and longitudinal directions and an interaction term was calibrated from the experimental data in literature in order to predict permeability. Generic optimization framework coupled to finite element solver is developed for analyzing any application involving use of porous structures. An objective functions were generated structure to address frequently observed trade-off between the stiffness, thermal conductivity, permeability and porosity. Three application were analyzed for potential use of engineered materials. Heat spreader application involving thermal and mechanical constraints, artificial bone grafts application involving mechanical and permeability constraints and structural materials applications involving mechanical, thermal and porosity constraints is analyzed. Recommendations for optimum topologies for specific operating conditions are provided.

Research on optimization of combustion efficiency of thermal power unit based on genetic algorithm

NASA Astrophysics Data System (ADS)

Zhou, Qiongyang

2018-04-01

In order to improve the economic performance and reduce pollutant emissions of thermal power units, the characteristics of neural network in establishing boiler combustion model are analyzed based on the analysis of the main factors affecting boiler efficiency by using orthogonal method. In addition, on the basis of this model, the genetic algorithm is used to find the best control amount of the furnace combustion in a certain working condition. Through the genetic algorithm based on real number encoding and roulette selection is concluded: the best control quantity at a condition of furnace combustion can be combined with the boiler combustion system model for neural network training. The precision of the neural network model is further improved, and the basic work is laid for the research of the whole boiler combustion optimization system.

Thermal management methods for compact high power LED arrays

NASA Astrophysics Data System (ADS)

Christensen, Adam; Ha, Minseok; Graham, Samuel

2007-09-01

The package and system level temperature distributions of a high power (>1W) light emitting diode (LED) array has been investigated using numerical heat flow models. For this analysis, a thermal resistor network model was combined with a 3D finite element submodel of an LED structure to predict system and die level temperatures. The impact of LED array density, LED power density, and active versus passive cooling methods on device operation were calculated. In order to help understand the role of various thermal resistances in cooling such compact arrays, the thermal resistance network was analyzed in order to estimate the contributions from materials as well as active and passive cooling schemes. An analysis of thermal stresses and residual stresses in the die are also calculated based on power dissipation and convection heat transfer coefficients. Results show that the thermal stress in the GaN layer are compressive which can impact the band gap and performance of the LEDs.

Incorporating Retention Time to Refine Models Predicting Thermal Regimes of Stream Networks Across New England

EPA Science Inventory

Thermal regimes are a critical factor in models predicting effects of watershed management activities on fish habitat suitability. We have assembled a database of lotic temperature time series across New England (> 7000 station-year combinations) from state and Federal data s...

Atmospheric cloud physics thermal systems analysis

NASA Technical Reports Server (NTRS)

1977-01-01

Engineering analyses performed on the Atmospheric Cloud Physics (ACPL) Science Simulator expansion chamber and associated thermal control/conditioning system are reported. Analyses were made to develop a verified thermal model and to perform parametric thermal investigations to evaluate systems performance characteristics. Thermal network representations of solid components and the complete fluid conditioning system were solved simultaneously using the Systems Improved Numerical Differencing Analyzer (SINDA) computer program.

Elastic and thermal expansion asymmetry in dense molecular materials.

PubMed

Burg, Joseph A; Dauskardt, Reinhold H

2016-09-01

The elastic modulus and coefficient of thermal expansion are fundamental properties of elastically stiff molecular materials and are assumed to be the same (symmetric) under both tension and compression loading. We show that molecular materials can have a marked asymmetric elastic modulus and coefficient of thermal expansion that are inherently related to terminal chemical groups that limit molecular network connectivity. In compression, terminal groups sterically interact to stiffen the network, whereas in tension they interact less and disconnect the network. The existence of asymmetric elastic and thermal expansion behaviour has fundamental implications for computational approaches to molecular materials modelling and practical implications on the thermomechanical strains and associated elastic stresses. We develop a design space to control the degree of elastic asymmetry in molecular materials, a vital step towards understanding their integration into device technologies.

Thermal Error Test and Intelligent Modeling Research on the Spindle of High Speed CNC Machine Tools

NASA Astrophysics Data System (ADS)

Luo, Zhonghui; Peng, Bin; Xiao, Qijun; Bai, Lu

2018-03-01

Thermal error is the main factor affecting the accuracy of precision machining. Through experiments, this paper studies the thermal error test and intelligent modeling for the spindle of vertical high speed CNC machine tools in respect of current research focuses on thermal error of machine tool. Several testing devices for thermal error are designed, of which 7 temperature sensors are used to measure the temperature of machine tool spindle system and 2 displacement sensors are used to detect the thermal error displacement. A thermal error compensation model, which has a good ability in inversion prediction, is established by applying the principal component analysis technology, optimizing the temperature measuring points, extracting the characteristic values closely associated with the thermal error displacement, and using the artificial neural network technology.

Evolution of cosmic string networks

NASA Technical Reports Server (NTRS)

Albrecht, Andreas; Turok, Neil

1989-01-01

A discussion of the evolution and observable consequences of a network of cosmic strings is given. A simple model for the evolution of the string network is presented, and related to the statistical mechanics of string networks. The model predicts the long string density throughout the history of the universe from a single parameter, which researchers calculate in radiation era simulations. The statistical mechanics arguments indicate a particular thermal form for the spectrum of loops chopped off the network. Detailed numerical simulations of string networks in expanding backgrounds are performed to test the model. Consequences for large scale structure, the microwave and gravity wave backgrounds, nucleosynthesis and gravitational lensing are calculated.

Thermal Network Modelling Handbook

NASA Technical Reports Server (NTRS)

1972-01-01

Thermal mathematical modelling is discussed in detail. A three-fold purpose was established: (1) to acquaint the new user with the terminology and concepts used in thermal mathematical modelling, (2) to present the more experienced and occasional user with quick formulas and methods for solving everyday problems, coupled with study cases which lend insight into the relationships that exist among the various solution techniques and parameters, and (3) to begin to catalog in an orderly fashion the common formulas which may be applied to automated conversational language techniques.

Applications of a New England stream temperature model to evaluate distribution of thermal regimes and sensitivity to change in riparian condition

EPA Science Inventory

We have applied a statistical stream network (SSN) model to predict stream thermal metrics (summer monthly medians, growing season maximum magnitude and timing, and daily rates of change) across New England nontidal streams and rivers, excluding northern Maine watersheds that ext...

Mathematical modeling of the process of determining the standards for process losses in the transfer of thermal energy of the coolant

NASA Astrophysics Data System (ADS)

Akhmetova, I. G.; Chichirova, N. D.

2017-11-01

Currently the actual problem is a precise definition of the normative and actual heat loss. Existing methods - experimental, on metering devices, on the basis of mathematical modeling methods are not without drawbacks. Heat losses establishing during the heat carrier transport has an impact on the tariff structure of heat supply organizations. This quantity determination also promotes proper choice of main and auxiliary equipment power, temperature chart of heat supply networks, as well as the heating system structure choice with the decentralization. Calculation of actual heat loss and their comparison with standard values justifies the performance of works on improvement of the heat networks with the replacement of piping or its insulation. To determine the cause of discrepancies between normative and actual heat losses thermal tests on the magnitude of the actual heat losses in the 124 sections of heat networks in Kazan. As were carried out the result mathematical model of the regulatory definition of heat losses is developed and tested. This model differ from differs the existing according the piping insulation type. The application of this factor will bring the value of calculative normative losses heat energy to their actual value. It is of great importance for enterprises operating distribution networks and because of the conditions of their configuration and extensions do not have the technical ability to produce thermal testing.

Evaluation of thermal conductivity of MgO-MWCNTs/EG hybrid nanofluids based on experimental data by selecting optimal artificial neural networks

NASA Astrophysics Data System (ADS)

Vafaei, Masoud; Afrand, Masoud; Sina, Nima; Kalbasi, Rasool; Sourani, Forough; Teimouri, Hamid

2017-01-01

In this paper, the thermal conductivity ratio of MgO-MWCNTs/EG hybrid nanofluids has been predicted by an optimal artificial neural network at solid volume fractions of 0.05%, 0.1%, 0.15%, 0.2%, 0.4% and 0.6% in the temperature range of 25-50 °C. In this way, at the first, thirty six experimental data was presented to determine the thermal conductivity ratio of the hybrid nanofluid. Then, four optimal artificial neural networks with 6, 8, 10 and 12 neurons in hidden layer were designed to predict the thermal conductivity ratio of the nanofluid. The comparison between four optimal ANN results and experimental showed that the ANN with 12 neurons in hidden layer was the best model. Moreover, the results obtained from the best ANN indicated the maximum deviation margin of 0.8%.

Thermal Modeling and Testing of the Edison Demonstration of Smallsat Networks Project

NASA Technical Reports Server (NTRS)

Coker, Robert

2014-01-01

NASA's Edison program is intending to launch the Edison Demonstration of Smallsat Networks (EDSN) project, a swarm of 8 1.5U cubesats in the fall of 2014 to demonstrate intra-swarm communications and multi-point in situ space physics data acquisition. Due to late changes in the duty cycles of various components, potential overheating issues appeared. In addition, it was determined that capacity loss due to the coldness of the batteries was unacceptable, so mitigation was required. This paper will discuss the thermal modeling, testing, and results of the EDSN mission.

Modelled spatiotemporal variability of outdoor thermal comfort in local climate zones of the city of Brno, Czech Republic.

PubMed

Geletič, Jan; Lehnert, Michal; Savić, Stevan; Milošević, Dragan

2018-05-15

This study uses the MUKLIMO_3 urban climate model (in German, Mikroskaliges Urbanes KLImaMOdell in 3-Dimensionen) and measurements from an urban climate network in order to simulate, validate and analyse the spatiotemporal pattern of human thermal comfort outdoors in the city of Brno (Czech Republic) during a heat-wave period. HUMIDEX, a heat index designed to quantify human heat exposure, was employed to assess thermal comfort, employing air temperature and relative humidity data. The city was divided into local climate zones (LCZs) in order to access differences in intra-urban thermal comfort. Validation of the model results, based on the measurement dates within the urban monitoring network, confirmed that the MUKLIMO_3 micro-scale model had the capacity to simulate the main spatiotemporal patterns of thermal comfort in an urban area and its vicinity. The results suggested that statistically significant differences in outdoor thermal comfort exist in the majority of cases between different LCZs. The most built-up LCZ types (LCZs 2, 3, 5, 8 and 10) were disclosed as the most uncomfortable areas of the city. Hence, conditions of great discomfort (HUMIDEX >40) were recorded in these areas, mainly in the afternoon hours (from 13.00 to 18.00 CEST), while some thermal discomfort continued overnight. In contrast, HUMIDEX values in sparsely built-up LCZ 9 and non-urban LCZs were substantially lower and indicated better thermal conditions for the urban population. Interestingly, the model captured a local increase of HUMIDEX values arising out of air humidity in LCZs with the presence of more vegetation (LCZs A and B) and in the vicinity of larger bodies of water (LCZ G). Copyright © 2017 Elsevier B.V. All rights reserved.

Thermal Texture Generation and 3d Model Reconstruction Using SFM and Gan

NASA Astrophysics Data System (ADS)

Kniaz, V. V.; Mizginov, V. A.

2018-05-01

Realistic 3D models with textures representing thermal emission of the object are widely used in such fields as dynamic scene analysis, autonomous driving, and video surveillance. Structure from Motion (SfM) methods provide a robust approach for the generation of textured 3D models in the visible range. Still, automatic generation of 3D models from the infrared imagery is challenging due to an absence of the feature points and low sensor resolution. Recent advances in Generative Adversarial Networks (GAN) have proved that they can perform complex image-to-image transformations such as a transformation of day to night and generation of imagery in a different spectral range. In this paper, we propose a novel method for generation of realistic 3D models with thermal textures using the SfM pipeline and GAN. The proposed method uses visible range images as an input. The images are processed in two ways. Firstly, they are used for point matching and dense point cloud generation. Secondly, the images are fed into a GAN that performs the transformation from the visible range to the thermal range. We evaluate the proposed method using real infrared imagery captured with a FLIR ONE PRO camera. We generated a dataset with 2000 pairs of real images captured in thermal and visible range. The dataset is used to train the GAN network and to generate 3D models using SfM. The evaluation of the generated 3D models and infrared textures proved that they are similar to the ground truth model in both thermal emissivity and geometrical shape.

Neural network model for thermal inactivation of Salmonella Typhimurium to elimination in ground chicken: Acquisition of data by whole sample enrichment, miniature most-probable-number method

USDA-ARS?s Scientific Manuscript database

Predictive models are valuable tools for assessing food safety. Existing thermal inactivation models for Salmonella and ground chicken do not provide predictions above 71 degrees C, which is below the recommended final cooked temperature of 73.9 degrees C. They also do not predict when all Salmone...

Thermal Modeling in Support of the Edison Demonstration of Smallsat Networks Project

NASA Technical Reports Server (NTRS)

Coker, Robert

2013-01-01

NASA's Edison program is intending to launch a swarm of at least 8 small satellites in 2013. This swarm of 1.5U Cubesats, the Edison Demonstration of Smallsat Networks (EDSN) project, will demonstrate intra-swarm communications and multi-point in-situ space physics data acquisition. In support of the design and testing of the EDSN satellites, a geometrically accurate thermal model has been constructed. Due to the low duty cycle of most components, no significant overheating issues were found. The predicted mininum temperatures of the external antennas are low enough, however, that some mitigation may be in order. The development and application of the model will be discussed in detail.

El Niño, Sea Surface Temperature Anomaly and Coral Bleaching in the South Atlantic: A Chain of Events Modeled With a Bayesian Approach

NASA Astrophysics Data System (ADS)

Lisboa, D. S.; Kikuchi, R. K. P.; Leão, Zelinda M. A. N.

2018-04-01

Coral bleaching represents one of the main climate-change related threats to reef ecosystems. This research represents a methodological alternative for modeling this phenomenon, focused on assessing uncertainties and complexities with a low number of observations. To develop this model, intermittent reef monitoring data from the largest reef complex in the South Atlantic collected over nine summers between 2000 and 2014 were used with remote sensing data to construct and train a bleaching seasonal prediction model. The Bayesian approach was used to construct the network as it is suitable for hierarchically organizing local thermal variables and combining them with El Niño indicators from the preceding winter to generate accurate bleaching predictions for the coming season. Network count information from six environmental indicators was used to calculate the probability of bleaching, which is mainly influenced by the combined information of two thermal indices; one thermal index is designed to track short period anomalies in the early summer that are capable of triggering bleaching (SST of five consecutive days), and the other index is responsible for tracking the accumulation of thermal stress over time, an index called degree heating trimester (DHT). In addition to developing the network, this study conducted the three tests of applicability proposed for model: 1- Perform the forecast of coral bleaching for the summer of 2016; 2- Investigate the role of turbidity during the bleaching episodes; and 3- Use the model information to identify areas with a lower predisposition to bleaching events.

Interfacial welding of dynamic covalent network polymers

NASA Astrophysics Data System (ADS)

Yu, Kai; Shi, Qian; Li, Hao; Jabour, John; Yang, Hua; Dunn, Martin L.; Wang, Tiejun; Qi, H. Jerry

2016-09-01

Dynamic covalent network (or covalent adaptable network) polymers can rearrange their macromolecular chain network by bond exchange reactions (BERs) where an active unit replaces a unit in an existing bond to form a new bond. Such macromolecular events, when they occur in large amounts, can attribute to unusual properties that are not seen in conventional covalent network polymers, such as shape reforming and surface welding; the latter further enables the important attributes of material malleability and powder-based reprocessing. In this paper, a multiscale modeling framework is developed to study the surface welding of thermally induced dynamic covalent network polymers. At the macromolecular network level, a lattice model is developed to describe the chain density evolution across the interface and its connection to bulk stress relaxation due to BERs. The chain density evolution rule is then fed into a continuum level interfacial model that takes into account surface roughness and applied pressure to predict the effective elastic modulus and interfacial fracture energy of welded polymers. The model yields particularly accessible results where the moduli and interfacial strength of the welded samples as a function of temperature and pressure can be predicted with four parameters, three of which can be measured directly. The model identifies the dependency of surface welding efficiency on the applied thermal and mechanical fields: the pressure will affect the real contact area under the consideration of surface roughness of dynamic covalent network polymers; the chain density increment on the real contact area of interface is only dependent on the welding time and temperature. The modeling approach shows good agreement with experiments and can be extended to other types of dynamic covalent network polymers using different stimuli for BERs, such as light and moisture etc.

Validation of the thermal challenge problem using Bayesian Belief Networks.

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

McFarland, John; Swiler, Laura Painton

The thermal challenge problem has been developed at Sandia National Laboratories as a testbed for demonstrating various types of validation approaches and prediction methods. This report discusses one particular methodology to assess the validity of a computational model given experimental data. This methodology is based on Bayesian Belief Networks (BBNs) and can incorporate uncertainty in experimental measurements, in physical quantities, and model uncertainties. The approach uses the prior and posterior distributions of model output to compute a validation metric based on Bayesian hypothesis testing (a Bayes' factor). This report discusses various aspects of the BBN, specifically in the context ofmore » the thermal challenge problem. A BBN is developed for a given set of experimental data in a particular experimental configuration. The development of the BBN and the method for ''solving'' the BBN to develop the posterior distribution of model output through Monte Carlo Markov Chain sampling is discussed in detail. The use of the BBN to compute a Bayes' factor is demonstrated.« less

Investigation of transient thermal dissipation in thinned LSI for advanced packaging

NASA Astrophysics Data System (ADS)

Araga, Yuuki; Shimamoto, Haruo; Melamed, Samson; Kikuchi, Katsuya; Aoyagi, Masahiro

2018-04-01

Thinning of LSI is necessary for superior form factor and performance in dense cutting-edge packaging technologies. At the same time, degradation of thermal characteristics caused by the steep thermal gradient on LSIs with thinned base silicon is a concern. To manage a thermal environment in advanced packages, thermal characteristics of the thinned LSIs must be clarified. In this study, static and dynamic thermal dissipations were analyzed before and after thinning silicon to determine variations of thermal characteristics in thinned LSI. Measurement results revealed that silicon thinning affects dynamic thermal characteristics as well as static one. The transient variations of thermal characteristics of thinned LSI are precisely verified by analysis using an equivalent model based on the thermal network method. The results of analysis suggest that transient thermal characteristics can be easily estimated by employing the equivalent model.

Thermal design and TDM test of the ETS-VI

NASA Astrophysics Data System (ADS)

Yoshinaka, T.; Kanamori, K.; Takenaka, N.; Kawashima, J.; Ido, Y.; Kuriyama, Y.

The Engineering Test Satellite-VI (ETS-VI) thermal design, thermal development model (TDM) test, and evaluation results are described. The allocation of the thermal control materials on the spacecraft is illustrated. The principal design approach is to minimize the interactions between the antenna tower module and the main body, and between the main body and the liquid apogee propulsion system by means of multilayer insulation blankets and low conductance graphite epoxy support structures. The TDM test shows that the thermal control subsystem is capable of maintaining the on-board components within specified temperature limits. The heat pipe network is confirmed to operate properly, and a uniform panel temperature distribution is accomplished. The thermal analytical model is experimentally verified. The validity of the thermal control subsystem design is confirmed by the modified on-orbit analytical model.

Neural network modelling of thermal stratification in a solar DHW storage

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

Geczy-Vig, P.; Farkas, I.

2010-05-15

In this study an artificial neural network (ANN) model is introduced for modelling the layer temperatures in a storage tank of a solar thermal system. The model is based on the measured data of a domestic hot water system. The temperatures distribution in the storage tank divided in 8 equal parts in vertical direction were calculated every 5 min using the average 5 min data of solar radiation, ambient temperature, mass flow rate of collector loop, load and the temperature of the layers in previous time steps. The introduced ANN model consists of two parts describing the load periods andmore » the periods between the loads. The identified model gives acceptable results inside the training interval as the average deviation was 0.22 C during the training and 0.24 C during the validation. (author)« less

Modelling thermal comfort of visitors at urban squares in hot and arid climate using NN-ARX soft computing method

NASA Astrophysics Data System (ADS)

Kariminia, Shahab; Motamedi, Shervin; Shamshirband, Shahaboddin; Piri, Jamshid; Mohammadi, Kasra; Hashim, Roslan; Roy, Chandrabhushan; Petković, Dalibor; Bonakdari, Hossein

2016-05-01

Visitors utilize the urban space based on their thermal perception and thermal environment. The thermal adaptation engages the user's behavioural, physiological and psychological aspects. These aspects play critical roles in user's ability to assess the thermal environments. Previous studies have rarely addressed the effects of identified factors such as gender, age and locality on outdoor thermal comfort, particularly in hot, dry climate. This study investigated the thermal comfort of visitors at two city squares in Iran based on their demographics as well as the role of thermal environment. Assessing the thermal comfort required taking physical measurement and questionnaire survey. In this study, a non-linear model known as the neural network autoregressive with exogenous input (NN-ARX) was employed. Five indices of physiological equivalent temperature (PET), predicted mean vote (PMV), standard effective temperature (SET), thermal sensation votes (TSVs) and mean radiant temperature ( T mrt) were trained and tested using the NN-ARX. Then, the results were compared to the artificial neural network (ANN) and the adaptive neuro-fuzzy inference system (ANFIS). The findings showed the superiority of the NN-ARX over the ANN and the ANFIS. For the NN-ARX model, the statistical indicators of the root mean square error (RMSE) and the mean absolute error (MAE) were 0.53 and 0.36 for the PET, 1.28 and 0.71 for the PMV, 2.59 and 1.99 for the SET, 0.29 and 0.08 for the TSV and finally 0.19 and 0.04 for the T mrt.

Network-based Prediction of Lotic Thermal Regimes Across New England

EPA Science Inventory

Thermal regimes are a critical factor in models predicting effects of watershed management activities on fish habitat suitability. We have assembled a database of lotic temperature time series across New England (> 7000 station-year combinations) from state and Federal data sour...

WSN system design by using an innovative neural network model to perform thermals forecasting in a urban canyon scenario

NASA Astrophysics Data System (ADS)

Giuseppina, Nicolosi; Salvatore, Tirrito

2015-12-01

Wireless Sensor Networks (WSNs) were studied by researchers in order to manage Heating, Ventilating and Air-Conditioning (HVAC) indoor systems. WSN can be useful specially to regulate indoor confort in a urban canyon scenario, where the thermal parameters vary rapidly, influenced by outdoor climate changing. This paper shows an innovative neural network approach, by using WSN data collected, in order to forecast the indoor temperature to varying the outdoor conditions based on climate parameters and boundary conditions typically of urban canyon. In this work more attention will be done to influence of traffic jam and number of vehicles in queue.

Prediction of the Thermal Conductivity of Refrigerants by Computational Methods and Artificial Neural Network.

PubMed

Ghaderi, Forouzan; Ghaderi, Amir H; Ghaderi, Noushin; Najafi, Bijan

2017-01-01

Background: The thermal conductivity of fluids can be calculated by several computational methods. However, these methods are reliable only at the confined levels of density, and there is no specific computational method for calculating thermal conductivity in the wide ranges of density. Methods: In this paper, two methods, an Artificial Neural Network (ANN) approach and a computational method established upon the Rainwater-Friend theory, were used to predict the value of thermal conductivity in all ranges of density. The thermal conductivity of six refrigerants, R12, R14, R32, R115, R143, and R152 was predicted by these methods and the effectiveness of models was specified and compared. Results: The results show that the computational method is a usable method for predicting thermal conductivity at low levels of density. However, the efficiency of this model is considerably reduced in the mid-range of density. It means that this model cannot be used at density levels which are higher than 6. On the other hand, the ANN approach is a reliable method for thermal conductivity prediction in all ranges of density. The best accuracy of ANN is achieved when the number of units is increased in the hidden layer. Conclusion: The results of the computational method indicate that the regular dependence between thermal conductivity and density at higher densities is eliminated. It can develop a nonlinear problem. Therefore, analytical approaches are not able to predict thermal conductivity in wide ranges of density. Instead, a nonlinear approach such as, ANN is a valuable method for this purpose.

Prediction of the Thermal Conductivity of Refrigerants by Computational Methods and Artificial Neural Network

PubMed Central

Ghaderi, Forouzan; Ghaderi, Amir H.; Ghaderi, Noushin; Najafi, Bijan

2017-01-01

Background: The thermal conductivity of fluids can be calculated by several computational methods. However, these methods are reliable only at the confined levels of density, and there is no specific computational method for calculating thermal conductivity in the wide ranges of density. Methods: In this paper, two methods, an Artificial Neural Network (ANN) approach and a computational method established upon the Rainwater-Friend theory, were used to predict the value of thermal conductivity in all ranges of density. The thermal conductivity of six refrigerants, R12, R14, R32, R115, R143, and R152 was predicted by these methods and the effectiveness of models was specified and compared. Results: The results show that the computational method is a usable method for predicting thermal conductivity at low levels of density. However, the efficiency of this model is considerably reduced in the mid-range of density. It means that this model cannot be used at density levels which are higher than 6. On the other hand, the ANN approach is a reliable method for thermal conductivity prediction in all ranges of density. The best accuracy of ANN is achieved when the number of units is increased in the hidden layer. Conclusion: The results of the computational method indicate that the regular dependence between thermal conductivity and density at higher densities is eliminated. It can develop a nonlinear problem. Therefore, analytical approaches are not able to predict thermal conductivity in wide ranges of density. Instead, a nonlinear approach such as, ANN is a valuable method for this purpose. PMID:29188217

Predicting Thermal Regimes of Stream Networks Across New England: Natural and Anthropogenic Influences

EPA Science Inventory

Thermal regime is a critical factor in models predicting joint effects of watershed management activities and climate change on habitat suitability for fish. We used a database of lotic temperature time series across New England (> 7000 station-year combinations) from state a...

Integrated Modeling Tools for Thermal Analysis and Applications

NASA Technical Reports Server (NTRS)

Milman, Mark H.; Needels, Laura; Papalexandris, Miltiadis

1999-01-01

Integrated modeling of spacecraft systems is a rapidly evolving area in which multidisciplinary models are developed to design and analyze spacecraft configurations. These models are especially important in the early design stages where rapid trades between subsystems can substantially impact design decisions. Integrated modeling is one of the cornerstones of two of NASA's planned missions in the Origins Program -- the Next Generation Space Telescope (NGST) and the Space Interferometry Mission (SIM). Common modeling tools for control design and opto-mechanical analysis have recently emerged and are becoming increasingly widely used. A discipline that has been somewhat less integrated, but is nevertheless of critical concern for high precision optical instruments, is thermal analysis and design. A major factor contributing to this mild estrangement is that the modeling philosophies and objectives for structural and thermal systems typically do not coincide. Consequently the tools that are used in these discplines suffer a degree of incompatibility, each having developed along their own evolutionary path. Although standard thermal tools have worked relatively well in the past. integration with other disciplines requires revisiting modeling assumptions and solution methods. Over the past several years we have been developing a MATLAB based integrated modeling tool called IMOS (Integrated Modeling of Optical Systems) which integrates many aspects of structural, optical, control and dynamical analysis disciplines. Recent efforts have included developing a thermal modeling and analysis capability, which is the subject of this article. Currently, the IMOS thermal suite contains steady state and transient heat equation solvers, and the ability to set up the linear conduction network from an IMOS finite element model. The IMOS code generates linear conduction elements associated with plates and beams/rods of the thermal network directly from the finite element structural model. Conductances for temperature varying materials are accommodated. This capability both streamlines the process of developing the thermal model from the finite element model, and also makes the structural and thermal models compatible in the sense that each structural node is associated with a thermal node. This is particularly useful when the purpose of the analysis is to predict structural deformations due to thermal loads. The steady state solver uses a restricted step size Newton method, and the transient solver is an adaptive step size implicit method applicable to general differential algebraic systems. Temperature dependent conductances and capacitances are accommodated by the solvers. In addition to discussing the modeling and solution methods. applications where the thermal modeling is "in the loop" with sensitivity analysis, optimization and optical performance drawn from our experiences with the Space Interferometry Mission (SIM), and the Next Generation Space Telescope (NGST) are presented.

Predicting thermal regimes of stream networks across the Chesapeake Bay Watershed: Natural and anthropogenic influences

EPA Science Inventory

Thermal regimes are a critical factor in models predicting joint effects of watershed management activities and climate change on fish habitat suitability. We have compiled a database of lotic temperature time series across the Chesapeake Bay Watershed (725 station-year combinat...

Thermal Runaway in Jammed Networks

NASA Astrophysics Data System (ADS)

Lechman, Jeremy; Yarrington, Cole; Bolintineanu, Dan

2017-06-01

The study of thermal explosion has a long history. Names such as Semenov and Frank-Kamenetskii are associated with classical model descriptions under particular assumptions. In this talk we revisit this problem with particular focus on the latter's model for conduction dominated thermal transport and Arrenhius-type reaction chemistry. We extend this description to the case of inhomogeneous microstructure generated by packing mono-sized spheres via a well-defined ``Jamming'' protocol. With these material structures in hand, we recast the Frank-Kamenetskii problem into a reduced-order network form for conduction in particle packs. With this model we can efficiently investigate the variability of the time to ignition due to the random microstructure. Additionally, we propose a modal decomposition and stability analysis of the model akin to stability of linear systems. We highlight the physical insights this approach can give with respect to questions of material dependent performance variability. Sandia National Laboratories is a multiprogram laboratory managed and operated by Sandia Corporation, a Lockheed-Martin Company, for the U. S. Department of Energy's National Nuclear Security Administration under Contract No. DE-AC04-94AL85000.

An Integrated Solution for Performing Thermo-fluid Conjugate Analysis

NASA Technical Reports Server (NTRS)

Kornberg, Oren

2009-01-01

A method has been developed which integrates a fluid flow analyzer and a thermal analyzer to produce both steady state and transient results of 1-D, 2-D, and 3-D analysis models. The Generalized Fluid System Simulation Program (GFSSP) is a one dimensional, general purpose fluid analysis code which computes pressures and flow distributions in complex fluid networks. The MSC Systems Improved Numerical Differencing Analyzer (MSC.SINDA) is a one dimensional general purpose thermal analyzer that solves network representations of thermal systems. Both GFSSP and MSC.SINDA have graphical user interfaces which are used to build the respective model and prepare it for analysis. The SINDA/GFSSP Conjugate Integrator (SGCI) is a formbase graphical integration program used to set input parameters for the conjugate analyses and run the models. The contents of this paper describes SGCI and its thermo-fluids conjugate analysis techniques and capabilities by presenting results from some example models including the cryogenic chill down of a copper pipe, a bar between two walls in a fluid stream, and a solid plate creating a phase change in a flowing fluid.

Interfacing a General Purpose Fluid Network Flow Program with the SINDA/G Thermal Analysis Program

NASA Technical Reports Server (NTRS)

Schallhorn, Paul; Popok, Daniel

1999-01-01

A general purpose, one dimensional fluid flow code is currently being interfaced with the thermal analysis program Systems Improved Numerical Differencing Analyzer/Gaski (SINDA/G). The flow code, Generalized Fluid System Simulation Program (GFSSP), is capable of analyzing steady state and transient flow in a complex network. The flow code is capable of modeling several physical phenomena including compressibility effects, phase changes, body forces (such as gravity and centrifugal) and mixture thermodynamics for multiple species. The addition of GFSSP to SINDA/G provides a significant improvement in convective heat transfer modeling for SINDA/G. The interface development is conducted in multiple phases. This paper describes the first phase of the interface which allows for steady and quasi-steady (unsteady solid, steady fluid) conjugate heat transfer modeling.

Thermal and Fluid Modeling of the CRYogenic Orbital TEstbed (CRYOTE) Ground Test Article (GTA)

NASA Technical Reports Server (NTRS)

Piryk, David; Schallhorn, Paul; Walls, Laurie; Stopnitzky, Benny; Rhys, Noah; Wollen, Mark

2012-01-01

The purpose of this study was to anchor thermal and fluid system models to data acquired from a ground test article (GTA) for the CRYogenic Orbital TEstbed - CRYOTE. To accomplish this analysis, it was broken into four primary tasks. These included model development, pre-test predictions, testing support at Marshall Space Flight Center (MSFC} and post-test correlations. Information from MSFC facilitated the task of refining and correlating the initial models. The primary goal of the modeling/testing/correlating efforts was to characterize heat loads throughout the ground test article. Significant factors impacting the heat loads included radiative environments, multi-layer insulation (MLI) performance, tank fill levels, tank pressures, and even contact conductance coefficients. This paper demonstrates how analytical thermal/fluid networks were established, and it includes supporting rationale for specific thermal responses seen during testing.

Modelling reverse characteristics of power LEDs with thermal phenomena taken into account

NASA Astrophysics Data System (ADS)

Ptak, Przemysław; Górecki, Krzysztof

2016-01-01

This paper refers to modelling characteristics of power LEDs with a particular reference to thermal phenomena. Special attention is paid to modelling characteristics of the circuit protecting the considered device against the excessive value of the reverse voltage and to the description of the temperature influence on optical power. The network form of the worked out model is presented and some results of experimental verification of this model for the selected diodes operating at different cooling conditions are described. The very good agreement between the calculated and measured characteristics is obtained.

Toward Improved Fidelity of Thermal Explosion Simulations

NASA Astrophysics Data System (ADS)

Nichols, Albert; Becker, Richard; Burnham, Alan; Howard, W. Michael; Knap, Jarek; Wemhoff, Aaron

2009-06-01

We present results of an improved thermal/chemical/mechanical model of HMX based explosives like LX04 and LX10 for thermal cook-off. The original HMX model and analysis scheme were developed by Yoh et.al. for use in the ALE3D modeling framework. The improvements were concentrated in four areas. First, we added porosity to the chemical material model framework in ALE3D used to model HMX explosive formulations to handle the roughly 2% porosity in solid explosives. Second, we improved the HMX reaction network, which included the addition of a reactive phase change model base on work by Henson et.al. Third, we added early decomposition gas species to the CHEETAH material database to improve equations of state for gaseous intermediates and products. Finally, we improved the implicit mechanics module in ALE3D to more naturally handle the long time scales associated with thermal cookoff. The application of the resulting framework to the analysis of the Scaled Thermal Explosion (STEX) experiments will be discussed.

Predicting thermal regimes of stream networks across the northeast United States: Natural and anthropogenic influences

EPA Science Inventory

We used STARS (Spatial Tools for the Analysis of River Systems), an ArcGIS geoprocessing toolbox, to create spatial stream networks. We then developed and assessed spatial statistical models for each of these metrics, incorporating spatial autocorrelation based on both distance...

A chemical model for the interstellar medium in galaxies

NASA Astrophysics Data System (ADS)

Bovino, S.; Grassi, T.; Capelo, Pedro R.; Schleicher, D. R. G.; Banerjee, R.

2016-05-01

Aims: We present and test chemical models for three-dimensional hydrodynamical simulations of galaxies. We explore the effect of changing key parameters such as metallicity, radiation, and non-equilibrium versus equilibrium metal cooling approximations on the transition between the gas phases in the interstellar medium. Methods: The microphysics was modelled by employing the public chemistry package KROME, and the chemical networks were tested to work in a wide range of densities and temperatures. We describe a simple H/He network following the formation of H2 and a more sophisticated network that includes metals. Photochemistry, thermal processes, and different prescriptions for the H2 catalysis on dust are presented and tested within a one-zone framework. The resulting network is made publicly available on the KROME webpage. Results: We find that employing an accurate treatment of the dust-related processes induces a faster HI-H2 transition. In addition, we show when the equilibrium assumption for metal cooling holds and how a non-equilibrium approach affects the thermal evolution of the gas and the HII-HI transition. Conclusions: These models can be employed in any hydrodynamical code via an interface to KROME and can be applied to different problems including isolated galaxies, cosmological simulations of galaxy formation and evolution, supernova explosions in molecular clouds, and the modelling of star-forming regions. The metal network can be used for a comparison with observational data of CII 158 μm emission both for high-redshift and for local galaxies.

Neural network approach to prediction of temperatures around groundwater heat pump systems

NASA Astrophysics Data System (ADS)

Lo Russo, Stefano; Taddia, Glenda; Gnavi, Loretta; Verda, Vittorio

2014-01-01

A fundamental aspect in groundwater heat pump (GWHP) plant design is the correct evaluation of the thermally affected zone that develops around the injection well. This is particularly important to avoid interference with previously existing groundwater uses (wells) and underground structures. Temperature anomalies are detected through numerical methods. Computational fluid dynamic (CFD) models are widely used in this field because they offer the opportunity to calculate the time evolution of the thermal plume produced by a heat pump. The use of neural networks is proposed to determine the time evolution of the groundwater temperature downstream of an installation as a function of the possible utilization profiles of the heat pump. The main advantage of neural network modeling is the possibility of evaluating a large number of scenarios in a very short time, which is very useful for the preliminary analysis of future multiple installations. The neural network is trained using the results from a CFD model (FEFLOW) applied to the installation at Politecnico di Torino (Italy) under several operating conditions. The final results appeared to be reliable and the temperature anomalies around the injection well appeared to be well predicted.

Super-Joule heating in graphene and silver nanowire network

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

Maize, Kerry; Das, Suprem R.; Sadeque, Sajia

Transistors, sensors, and transparent conductors based on randomly assembled nanowire networks rely on multi-component percolation for unique and distinctive applications in flexible electronics, biochemical sensing, and solar cells. While conduction models for 1-D and 1-D/2-D networks have been developed, typically assuming linear electronic transport and self-heating, the model has not been validated by direct high-resolution characterization of coupled electronic pathways and thermal response. In this letter, we show the occurrence of nonlinear “super-Joule” self-heating at the transport bottlenecks in networks of silver nanowires and silver nanowire/single layer graphene hybrid using high resolution thermoreflectance (TR) imaging. TR images at the microscopicmore » self-heating hotspots within nanowire network and nanowire/graphene hybrid network devices with submicron spatial resolution are used to infer electrical current pathways. The results encourage a fundamental reevaluation of transport models for network-based percolating conductors.« less

An empirical analysis of thermal protective performance of fabrics used in protective clothing.

PubMed

Mandal, Sumit; Song, Guowen

2014-10-01

Fabric-based protective clothing is widely used for occupational safety of firefighters/industrial workers. The aim of this paper is to study thermal protective performance provided by fabric systems and to propose an effective model for predicting the thermal protective performance under various thermal exposures. Different fabric systems that are commonly used to manufacture thermal protective clothing were selected. Laboratory simulations of the various thermal exposures were created to evaluate the protective performance of the selected fabric systems in terms of time required to generate second-degree burns. Through the characterization of selected fabric systems in a particular thermal exposure, various factors affecting the performances were statistically analyzed. The key factors for a particular thermal exposure were recognized based on the t-test analysis. Using these key factors, the performance predictive multiple linear regression and artificial neural network (ANN) models were developed and compared. The identified best-fit ANN models provide a basic tool to study thermal protective performance of a fabric. © The Author 2014. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

Parameter Estimation of the Thermal Network Model of a Machine Tool Spindle by Self-made Bluetooth Temperature Sensor Module

PubMed Central

Lo, Yuan-Chieh; Hu, Yuh-Chung; Chang, Pei-Zen

2018-01-01

Thermal characteristic analysis is essential for machine tool spindles because sudden failures may occur due to unexpected thermal issue. This article presents a lumped-parameter Thermal Network Model (TNM) and its parameter estimation scheme, including hardware and software, in order to characterize both the steady-state and transient thermal behavior of machine tool spindles. For the hardware, the authors develop a Bluetooth Temperature Sensor Module (BTSM) which accompanying with three types of temperature-sensing probes (magnetic, screw, and probe). Its specification, through experimental test, achieves to the precision ±(0.1 + 0.0029|t|) °C, resolution 0.00489 °C, power consumption 7 mW, and size Ø40 mm × 27 mm. For the software, the heat transfer characteristics of the machine tool spindle correlative to rotating speed are derived based on the theory of heat transfer and empirical formula. The predictive TNM of spindles was developed by grey-box estimation and experimental results. Even under such complicated operating conditions as various speeds and different initial conditions, the experiments validate that the present modeling methodology provides a robust and reliable tool for the temperature prediction with normalized mean square error of 99.5% agreement, and the present approach is transferable to the other spindles with a similar structure. For realizing the edge computing in smart manufacturing, a reduced-order TNM is constructed by Model Order Reduction (MOR) technique and implemented into the real-time embedded system. PMID:29473877

Parameter Estimation of the Thermal Network Model of a Machine Tool Spindle by Self-made Bluetooth Temperature Sensor Module.

PubMed

Lo, Yuan-Chieh; Hu, Yuh-Chung; Chang, Pei-Zen

2018-02-23

Thermal characteristic analysis is essential for machine tool spindles because sudden failures may occur due to unexpected thermal issue. This article presents a lumped-parameter Thermal Network Model (TNM) and its parameter estimation scheme, including hardware and software, in order to characterize both the steady-state and transient thermal behavior of machine tool spindles. For the hardware, the authors develop a Bluetooth Temperature Sensor Module (BTSM) which accompanying with three types of temperature-sensing probes (magnetic, screw, and probe). Its specification, through experimental test, achieves to the precision ±(0.1 + 0.0029|t|) °C, resolution 0.00489 °C, power consumption 7 mW, and size Ø40 mm × 27 mm. For the software, the heat transfer characteristics of the machine tool spindle correlative to rotating speed are derived based on the theory of heat transfer and empirical formula. The predictive TNM of spindles was developed by grey-box estimation and experimental results. Even under such complicated operating conditions as various speeds and different initial conditions, the experiments validate that the present modeling methodology provides a robust and reliable tool for the temperature prediction with normalized mean square error of 99.5% agreement, and the present approach is transferable to the other spindles with a similar structure. For realizing the edge computing in smart manufacturing, a reduced-order TNM is constructed by Model Order Reduction (MOR) technique and implemented into the real-time embedded system.

The small community solar thermal power experiment. Parabolic dish technology for industrial process heat application

NASA Technical Reports Server (NTRS)

Polzien, R. E.; Rodriguez, D.

1981-01-01

Aspects of incorporating a thermal energy transport system (ETS) into a field of parabolic dish collectors for industrial process heat (IPH) applications were investigated. Specific objectives are to: (1) verify the mathematical optimization of pipe diameters and insulation thicknesses calculated by a computer code; (2) verify the cost model for pipe network costs using conventional pipe network construction; (3) develop a design and the associated production costs for incorporating risers and downcomers on a low cost concentrator (LCC); (4) investigate the cost reduction of using unconventional pipe construction technology. The pipe network design and costs for a particular IPH application, specifically solar thermally enhanced oil recovery (STEOR) are analyzed. The application involves the hybrid operation of a solar powered steam generator in conjunction with a steam generator using fossil fuels to generate STEOR steam for wells. It is concluded that the STEOR application provides a baseline pipe network geometry used for optimization studies of pipe diameter and insulation thickness, and for development of comparative cost data, and operating parameters for the design of riser/downcomer modifications to the low cost concentrator.

Slow crack growth: Models and experiments

NASA Astrophysics Data System (ADS)

Santucci, S.; Vanel, L.; Ciliberto, S.

2007-07-01

The properties of slow crack growth in brittle materials are analyzed both theoretically and experimentally. We propose a model based on a thermally activated rupture process. Considering a 2D spring network submitted to an external load and to thermal noise, we show that a preexisting crack in the network may slowly grow because of stress fluctuations. An analytical solution is found for the evolution of the crack length as a function of time, the time to rupture and the statistics of the crack jumps. These theoretical predictions are verified by studying experimentally the subcritical growth of a single crack in thin sheets of paper. A good agreement between the theoretical predictions and the experimental results is found. In particular, our model suggests that the statistical stress fluctuations trigger rupture events at a nanometric scale corresponding to the diameter of cellulose microfibrils.

Characterization of an Isolated Kidney's Vasculature for Use in Bio-Thermal Modeling

NASA Astrophysics Data System (ADS)

Payne, Allison H.; Parker, Dennis L.; Moellmer, Jeff; Roemer, Robert B.; Clifford, Sarah

2007-05-01

Accurate bio-thermal modeling requires site-specific modeling of discrete vascular anatomy. Presented herewith are several steps that have been developed to describe the vessel network of isolated canine and bovine kidneys. These perfused, isolated kidneys provide an environment to repeatedly test and improve acquisition methods to visualize the vascular anatomy, as well as providing a method to experimentally validate discrete vasculature thermal models. The organs are preserved using a previously developed methodology that keeps the vasculature intact, allowing for the organ to be perfused. It also allows for the repeated fixation and re-hydration of the same organ, permitting the comparison of various methods and models. The organ extraction, alcohol preservation, and perfusion of the organ are described. The vessel locations were obtained through a high-resolution time-of-flight (TOF) magnetic resonance angiography (MRA) technique. Sequential improvements of both the experimental setup used for this acquisition, as well as MR sequence development are presented. The improvements in MR acquisition and experimental setup improved the number of vessels seen in both the raw data and segmented images by 50%. An automatic vessel centerline extraction algorithm describes both vessel location and genealogy. Centerline descriptions also allows for vessel diameter and flow rate determination, providing valuable input parameters for the discrete vascular thermal model. Characterized vessels networks of both canine and bovine kidneys are presented. While these tools have been developed in an ex vivo environment, all steps can be applied to in vivo applications.

Coupling Network Computing Applications in Air-cooled Turbine Blades Optimization

NASA Astrophysics Data System (ADS)

Shi, Liang; Yan, Peigang; Xie, Ming; Han, Wanjin

2018-05-01

Through establishing control parameters from blade outside to inside, the parametric design of air-cooled turbine blade based on airfoil has been implemented. On the basis of fast updating structure features and generating solid model, a complex cooling system has been created. Different flow units are modeled into a complex network topology with parallel and serial connection. Applying one-dimensional flow theory, programs have been composed to get pipeline network physical quantities along flow path, including flow rate, pressure, temperature and other parameters. These inner units parameters set as inner boundary conditions for external flow field calculation program HIT-3D by interpolation, thus to achieve full field thermal coupling simulation. Referring the studies in literatures to verify the effectiveness of pipeline network program and coupling algorithm. After that, on the basis of a modified design, and with the help of iSIGHT-FD, an optimization platform had been established. Through MIGA mechanism, the target of enhancing cooling efficiency has been reached, and the thermal stress has been effectively reduced. Research work in this paper has significance for rapid deploying the cooling structure design.

Thermal conductivity of tubrostratic carbon nanofiber networks

DOE PAGES

Bauer, Matthew L.; Saltonstall, Chris B.; Leseman, Zayd C.; ...

2016-01-01

Composite material systems composed of a matrix of nano materials can achieve combinations of mechanical and thermophysical properties outside the range of traditional systems. While many reports have studied the intrinsic thermal properties of individual carbon fibers, to be useful in applications in which thermal stability is critical, an understanding of heat transport in composite materials is required. In this work, air/ carbon nano fiber networks are studied to elucidate the system parameters influencing thermal transport. Sample thermal properties are measured with varying initial carbon fiber fill fraction, environment pressure, loading pressure, and heat treatment temperature through a bidirectional modificationmore » of the 3ω technique. The nanostructures of the individual fibers are characterized with small angle x-ray scattering and Raman spectroscopy providing insight to individual fiber thermal conductivity. Measured thermal conductivity varied from 0.010 W/(m K) to 0.070 W/(m K). An understanding of the intrinsic properties of the individual fibers and the interactions of the two phase composite is used to reconcile low measured thermal conductivities with predictive modeling. This methodology can be more generally applied to a wide range of fiber composite materials and their applications.« less

Chrysler improved numerical differencing analyzer for third generation computers CINDA-3G

NASA Technical Reports Server (NTRS)

Gaski, J. D.; Lewis, D. R.; Thompson, L. R.

1972-01-01

New and versatile method has been developed to supplement or replace use of original CINDA thermal analyzer program in order to take advantage of improved systems software and machine speeds of third generation computers. CINDA-3G program options offer variety of methods for solution of thermal analog models presented in network format.

Parametric study of closed wet cooling tower thermal performance

NASA Astrophysics Data System (ADS)

Qasim, S. M.; Hayder, M. J.

2017-08-01

The present study involves experimental and theoretical analysis to evaluate the thermal performance of modified Closed Wet Cooling Tower (CWCT). The experimental study includes: design, manufacture and testing prototype of a modified counter flow forced draft CWCT. The modification based on addition packing to the conventional CWCT. A series of experiments was carried out at different operational parameters. In view of energy analysis, the thermal performance parameters of the tower are: cooling range, tower approach, cooling capacity, thermal efficiency, heat and mass transfer coefficients. The theoretical study included develops Artificial Neural Network (ANN) models to predicting various thermal performance parameters of the tower. Utilizing experimental data for training and testing, the models simulated by multi-layer back propagation algorithm for varying all operational parameters stated in experimental test.

An improved theoretical electrochemical-thermal modelling of lithium-ion battery packs in electric vehicles

NASA Astrophysics Data System (ADS)

Amiribavandpour, Parisa; Shen, Weixiang; Mu, Daobin; Kapoor, Ajay

2015-06-01

A theoretical electrochemical thermal model combined with a thermal resistive network is proposed to investigate thermal behaviours of a battery pack. The combined model is used to study heat generation and heat dissipation as well as their influences on the temperatures of the battery pack with and without a fan under constant current discharge and variable current discharge based on electric vehicle (EV) driving cycles. The comparison results indicate that the proposed model improves the accuracy in the temperature predication of the battery pack by 2.6 times. Furthermore, a large battery pack with four of the investigated battery packs in series is simulated in the presence of different ambient temperatures. The simulation results show that the temperature of the large battery pack at the end of EV driving cycles can reach to 50 °C or 60 °C in high ambient temperatures. Therefore, thermal management system in EVs is required to maintain the battery pack within the safe temperature range.

Predictive modelling-based design and experiments for synthesis and spinning of bioinspired silk fibres

PubMed Central

Gronau, Greta; Jacobsen, Matthew M.; Huang, Wenwen; Rizzo, Daniel J.; Li, David; Staii, Cristian; Pugno, Nicola M.; Wong, Joyce Y.; Kaplan, David L.; Buehler, Markus J.

2016-01-01

Scalable computational modelling tools are required to guide the rational design of complex hierarchical materials with predictable functions. Here, we utilize mesoscopic modelling, integrated with genetic block copolymer synthesis and bioinspired spinning process, to demonstrate de novo materials design that incorporates chemistry, processing and material characterization. We find that intermediate hydrophobic/hydrophilic block ratios observed in natural spider silks and longer chain lengths lead to outstanding silk fibre formation. This design by nature is based on the optimal combination of protein solubility, self-assembled aggregate size and polymer network topology. The original homogeneous network structure becomes heterogeneous after spinning, enhancing the anisotropic network connectivity along the shear flow direction. Extending beyond the classical polymer theory, with insights from the percolation network model, we illustrate the direct proportionality between network conductance and fibre Young's modulus. This integrated approach provides a general path towards de novo functional network materials with enhanced mechanical properties and beyond (optical, electrical or thermal) as we have experimentally verified. PMID:26017575

Predictive modelling-based design and experiments for synthesis and spinning of bioinspired silk fibres.

PubMed

Lin, Shangchao; Ryu, Seunghwa; Tokareva, Olena; Gronau, Greta; Jacobsen, Matthew M; Huang, Wenwen; Rizzo, Daniel J; Li, David; Staii, Cristian; Pugno, Nicola M; Wong, Joyce Y; Kaplan, David L; Buehler, Markus J

2015-05-28

Scalable computational modelling tools are required to guide the rational design of complex hierarchical materials with predictable functions. Here, we utilize mesoscopic modelling, integrated with genetic block copolymer synthesis and bioinspired spinning process, to demonstrate de novo materials design that incorporates chemistry, processing and material characterization. We find that intermediate hydrophobic/hydrophilic block ratios observed in natural spider silks and longer chain lengths lead to outstanding silk fibre formation. This design by nature is based on the optimal combination of protein solubility, self-assembled aggregate size and polymer network topology. The original homogeneous network structure becomes heterogeneous after spinning, enhancing the anisotropic network connectivity along the shear flow direction. Extending beyond the classical polymer theory, with insights from the percolation network model, we illustrate the direct proportionality between network conductance and fibre Young's modulus. This integrated approach provides a general path towards de novo functional network materials with enhanced mechanical properties and beyond (optical, electrical or thermal) as we have experimentally verified.

Formation of metallic cation-oxygen network for anomalous thermal expansion coefficients in binary phosphate glass

NASA Astrophysics Data System (ADS)

Onodera, Yohei; Kohara, Shinji; Masai, Hirokazu; Koreeda, Akitoshi; Okamura, Shun; Ohkubo, Takahiro

2017-05-01

Understanding glass structure is still challenging due to the result of disorder, although novel materials design on the basis of atomistic structure has been strongly demanded. Here we report on the atomic structures of the zinc phosphate glass determined by reverse Monte Carlo modelling based on diffraction and spectroscopic data. The zinc-rich glass exhibits the network formed by ZnOx (averaged x<4) polyhedra. Although the elastic modulus, refractive index and glass transition temperature of the zinc phosphate glass monotonically increase with the amount of ZnO, we find for the first time that the thermal expansion coefficient is very sensitive to the substitution of the phosphate chain network by a network consisting of Zn-O units in zinc-rich glass. Our results imply that the control of the structure of intermediate groups may enable new functionalities in the design of oxide glass materials.

Formation of metallic cation-oxygen network for anomalous thermal expansion coefficients in binary phosphate glass.

PubMed

Onodera, Yohei; Kohara, Shinji; Masai, Hirokazu; Koreeda, Akitoshi; Okamura, Shun; Ohkubo, Takahiro

2017-05-31

Understanding glass structure is still challenging due to the result of disorder, although novel materials design on the basis of atomistic structure has been strongly demanded. Here we report on the atomic structures of the zinc phosphate glass determined by reverse Monte Carlo modelling based on diffraction and spectroscopic data. The zinc-rich glass exhibits the network formed by ZnO x (averaged x<4) polyhedra. Although the elastic modulus, refractive index and glass transition temperature of the zinc phosphate glass monotonically increase with the amount of ZnO, we find for the first time that the thermal expansion coefficient is very sensitive to the substitution of the phosphate chain network by a network consisting of Zn-O units in zinc-rich glass. Our results imply that the control of the structure of intermediate groups may enable new functionalities in the design of oxide glass materials.

Poly(Capro-Lactone) Networks as Actively Moving Polymers

NASA Astrophysics Data System (ADS)

Meng, Yuan

Shape-memory polymers (SMPs), as a subset of actively moving polymers, form an exciting class of materials that can store and recover elastic deformation energy upon application of an external stimulus. Although engineering of SMPs nowadays has lead to robust materials that can memorize multiple temporary shapes, and can be triggered by various stimuli such as heat, light, moisture, or applied magnetic fields, further commercialization of SMPs is still constrained by the material's incapability to store large elastic energy, as well as its inherent one-way shape-change nature. This thesis develops a series of model semi-crystalline shape-memory networks that exhibit ultra-high energy storage capacity, with accurately tunable triggering temperature; by introducing a second competing network, or reconfiguring the existing network under strained state, configurational chain bias can be effectively locked-in, and give rise to two-way shape-actuators that, in the absence of an external load, elongates upon cooling and reversibly contracts upon heating. We found that well-defined network architecture plays essential role on strain-induced crystallization and on the performance of cold-drawn shape-memory polymers. Model networks with uniform molecular weight between crosslinks, and specified functionality of each net-point, results in tougher, more elastic materials with a high degree of crystallinity and outstanding shape-memory properties. The thermal behavior of the model networks can be finely modified by introducing non-crystalline small molecule linkers that effectively frustrates the crystallization of the network strands. This resulted in shape-memory networks that are ultra-sensitive to heat, as deformed materials can be efficiently triggered to revert to its permanent state upon only exposure to body temperature. We also coupled the same reaction adopted to create the model network with conventional free-radical polymerization to prepare a dual-cure "double network" that behaves as a real thermal "actuator". This approach places sub-chains under different degrees of configurational bias within the network to utilize the material's propensity to undergo stress-induced crystallization. Reconfiguration of model shape-memory networks containing photo-sensitive linkages can also be employed to program two-way actuator. Chain reshuffling of a partially reconfigurable network is initiated upon exposure to light under specific strains. Interesting photo-induced creep and stress relaxation behaviors were demonstrated and understood based on a novel transient network model we derived. In summary, delicate manipulation of shape-memory network architectures addressed critical issues constraining the application of this type of functional polymer material. Strategies developed in this thesis may provide new opportunity to the field of shape-memory polymers.

Grain growth in nanocrystalline iron and Fe-Al alloys

NASA Astrophysics Data System (ADS)

Mirzadeh, Hamed; Zomorodian, Amir

2010-02-01

The effects of the annealing temperature and time, cryomilling in liquid nitrogen, and the addition of aluminum powder on the thermal stability and grain growth behavior of nanocrystalline iron were modeled using the Artificial Neural Network (ANN) technique. The developed model can be used as a guide for the quantification of the grain growth by considering the effects of annealing temperature and time. The model also quantified the effect of Al on the thermal stability of cryomilled nanocrystalline Fe. The model results showed that the cryomilling of Fe has a tangible effect on the stabilization of the nanostructure.

The General-Use Nodal Network Solver (GUNNS) Modeling Package for Space Vehicle Flow System Simulation

NASA Technical Reports Server (NTRS)

Harvey, Jason; Moore, Michael

2013-01-01

The General-Use Nodal Network Solver (GUNNS) is a modeling software package that combines nodal analysis and the hydraulic-electric analogy to simulate fluid, electrical, and thermal flow systems. GUNNS is developed by L-3 Communications under the TS21 (Training Systems for the 21st Century) project for NASA Johnson Space Center (JSC), primarily for use in space vehicle training simulators at JSC. It has sufficient compactness and fidelity to model the fluid, electrical, and thermal aspects of space vehicles in real-time simulations running on commodity workstations, for vehicle crew and flight controller training. It has a reusable and flexible component and system design, and a Graphical User Interface (GUI), providing capability for rapid GUI-based simulator development, ease of maintenance, and associated cost savings. GUNNS is optimized for NASA's Trick simulation environment, but can be run independently of Trick.

Temperature control simulation for a microwave transmitter cooling system. [deep space network

NASA Technical Reports Server (NTRS)

Yung, C. S.

1980-01-01

The thermal performance of a temperature control system for the antenna microwave transmitter (klystron tube) of the Deep Space Network antenna tracking system is discussed. In particular the mathematical model is presented along with the details of a computer program which is written for the system simulation and the performance parameterization. Analytical expressions are presented.

Simulation of a steady-state integrated human thermal system.

NASA Technical Reports Server (NTRS)

Hsu, F. T.; Fan, L. T.; Hwang, C. L.

1972-01-01

The mathematical model of an integrated human thermal system is formulated. The system consists of an external thermal regulation device on the human body. The purpose of the device (a network of cooling tubes held in contact with the surface of the skin) is to maintain the human body in a state of thermoneutrality. The device is controlled by varying the inlet coolant temperature and coolant mass flow rate. The differential equations of the model are approximated by a set of algebraic equations which result from the application of the explicit forward finite difference method to the differential equations. The integrated human thermal system is simulated for a variety of combinations of the inlet coolant temperature, coolant mass flow rate, and metabolic rates.

Use of a Hybrid Edge Node-Centroid Node Approach to Thermal Modeling

NASA Technical Reports Server (NTRS)

Peabody, Hume L.

2010-01-01

A recent proposal submitted for an ESA mission required that models be delivered in ESARAD/ESAT AN formats. ThermalDesktop was the preferable analysis code to be used for model development with a conversion done as the final step before delivery. However, due to some differences between the capabilities of the two codes, a unique approach was developed to take advantage of the edge node capability of ThermalDesktop while maintaining the centroid node approach used by ESARAD. In essence, two separate meshes were used: one for conduction and one for radiation. The conduction calculations were eliminated from the radiation surfaces and the capacitance and radiative calculations were eliminated from the conduction surfaces. The resulting conduction surface nodes were coincident with all nodes of the radiation surface and were subsequently merged, while the nodes along the edges remained free. Merging of nodes on the edges of adjacent surfaces provided the conductive links between surfaces. Lastly, all nodes along edges were placed into the subnetwork and the resulting supernetwork included only the nodes associated with radiation surfaces. This approach had both benefits and disadvantages. The use of centroid, surface based radiation reduces the overall size of the radiation network, which is often the most computationally intensive part of the modeling process. Furthermore, using the conduction surfaces and allowing ThermalDesktop to calculate the conduction network can save significant time by not having to manually generate the couplings. Lastly, the resulting GMM/TMM models can be exported to formats which do not support edge nodes. One drawback, however, is the necessity to maintain two sets of surfaces. This requires additional care on the part of the analyst to ensure communication between the conductive and radiative surfaces in the resulting overall network. However, with more frequent use of this technique, the benefits of this approach can far outweigh the additional effort.

Use of a Hybrid Edge Node-Centroid Node Approach to Thermal Modeling

NASA Technical Reports Server (NTRS)

Peabody, Hume L.

2010-01-01

A recent proposal submitted for an ESA mission required that models be delivered in ESARAD/ESATAN formats. ThermalDesktop was the preferable analysis code to be used for model development with a conversion done as the final step before delivery. However, due to some differences between the capabilities of the two codes, a unique approach was developed to take advantage of the edge node capability of ThermalDesktop while maintaining the centroid node approach used by ESARAD. In essence, two separate meshes were used: one for conduction and one for radiation. The conduction calculations were eliminated from the radiation surfaces and the capacitance and radiative calculations were eliminated from the conduction surfaces. The resulting conduction surface nodes were coincident with all nodes of the radiation surface and were subsequently merged, while the nodes along the edges remained free. Merging of nodes on the edges of adjacent surfaces provided the conductive links between surfaces. Lastly, all nodes along edges were placed into the subnetwork and the resulting supernetwork included only the nodes associated with radiation surfaces. This approach had both benefits and disadvantages. The use of centroid, surface based radiation reduces the overall size of the radiation network, which is often the most computationally intensive part of the modeling process. Furthermore, using the conduction surfaces and allowing ThermalDesktop to calculate the conduction network can save significant time by not having to manually generate the couplings. Lastly, the resulting GMM/TMM models can be exported to formats which do not support edge nodes. One drawback, however, is the necessity to maintain two sets of surfaces. This requires additional care on the part of the analyst to ensure communication between the conductive and radiative surfaces in the resulting overall network. However, with more frequent use of this technique, the benefits of this approach can far outweigh the additional effort.

Thermal/vacuum measurements of the Herschel space telescope by close-range photogrammetry

NASA Astrophysics Data System (ADS)

Parian, J. Amiri; Cozzani, A.; Appolloni, M.; Casarosa, G.

2017-11-01

In the frame of the development of a videogrammetric system to be used in thermal vacuum chambers at the European Space Research and Technology Centre (ESTEC) and other sites across Europe, the design of a network using micro-cameras was specified by the European Space agency (ESA)-ESTEC. The selected test set-up is the photogrammetric test of the Herschel Satellite Flight Model in the ESTEC Large Space Simulator. The photogrammetric system will be used to verify the Herschel Telescope alignment and Telescope positioning with respect to the Cryostat Vacuum Vessel (CVV) inside the Large Space Simulator during Thermal-Vacuum/Thermal-Balance test phases. We designed a close-range photogrammetric network by heuristic simulation and a videogrammetric system with an overall accuracy of 1:100,000. A semi-automated image acquisition system, which is able to work at low temperatures (-170°C) in order to acquire images according to the designed network has been constructed by ESA-ESTEC. In this paper we will present the videogrammetric system and sub-systems and the results of real measurements with a representative setup similar to the set-up of Herschel spacecraft which was realized in ESTEC Test Centre.

PLS Road surface temperature forecast for susceptibility of ice occurrence

NASA Astrophysics Data System (ADS)

Marchetti, Mario; Khalifa, Abderrhamen; Bues, Michel

2014-05-01

Winter maintenance relies on many operational tools consisting in monitoring atmospheric and pavement physical parameters. Among them, road weather information systems (RWIS) and thermal mapping are mostly used by service in charge of managing infrastructure networks. The Data from RWIS and thermal mapping are considered as inputs for forecasting physical numerical models, commonly in place since the 80s. These numerical models do need an accurate description of the infrastructure, such as pavement layers and sub-layers, along with many meteorological parameters, such as air temperature and global and infrared radiation. The description is sometimes partially known, and meteorological data is only monitored on specific spot. On the other hand, thermal mapping is now an easy, reliable and cost effective way to monitor road surface temperature (RST), and many meteorological parameters all along routes of infrastructure networks, including with a whole fleet of vehicles in the specific cases of roads, or airports. The technique uses infrared thermometry to measure RST and an atmospheric probes for air temperature, relative humidity, wind speed and global radiation, both at a high resolution interval, to identify sections of the road network prone to ice occurrence. However, measurements are time-consuming, and the data from thermal mapping is one input among others to establish the forecast. The idea was to build a reliable forecast on the sole data from thermal mapping. Previous work has established the interest to use principal component analysis (PCA) on the basis of a reduced number of thermal fingerprints. The work presented here is a focus on the use of partial least-square regression (PLS) to build a RST forecast with air temperature measurements. Roads with various environments, weather conditions (clear, cloudy mainly) and seasons were monitored over several months to generate an appropriate number of samples. The study was conducted to determine the minimum number of samples to get a reliable forecast, considering inputs for numerical models do not exceed five thermal fingerprints. Results of PLS have shown that the PLS model could have a R² of 0.9562, a RMSEP of 1.34 and a bias of -0.66. The same model applied to establish a forecast on past event indicates an average difference between measurements and forecasts of 0.20 °C. The advantage of such approach is its potential application not only to winter events, but also the extreme summer ones for urban heat island.

Orion Active Thermal Control System Dynamic Modeling Using Simulink/MATLAB

NASA Technical Reports Server (NTRS)

Wang, Xiao-Yen J.; Yuko, James

2010-01-01

This paper presents dynamic modeling of the crew exploration vehicle (Orion) active thermal control system (ATCS) using Simulink (Simulink, developed by The MathWorks). The model includes major components in ATCS, such as heat exchangers and radiator panels. The mathematical models of the heat exchanger and radiator are described first. Four different orbits were used to validate the radiator model. The current model results were compared with an independent Thermal Desktop (TD) (Thermal Desktop, PC/CAD-based thermal model builder, developed in Cullimore & Ring (C&R) Technologies) model results and showed good agreement for all orbits. In addition, the Orion ATCS performance was presented for three orbits and the current model results were compared with three sets of solutions- FloCAD (FloCAD, PC/CAD-based thermal/fluid model builder, developed in C&R Technologies) model results, SINDA/FLUINT (SINDA/FLUINT, a generalized thermal/fluid network-style solver ) model results, and independent Simulink model results. For each case, the fluid temperatures at every component on both the crew module and service module sides were plotted and compared. The overall agreement is reasonable for all orbits, with similar behavior and trends for the system. Some discrepancies exist because the control algorithm might vary from model to model. Finally, the ATCS performance for a 45-hr nominal mission timeline was simulated to demonstrate the capability of the model. The results show that the ATCS performs as expected and approximately 2.3 lb water was consumed in the sublimator within the 45 hr timeline before Orion docked at the International Space Station.

Toward Improved Fidelity of Thermal Explosion Simulations

NASA Astrophysics Data System (ADS)

Nichols, A. L.; Becker, R.; Howard, W. M.; Wemhoff, A.

2009-12-01

We will present results of an effort to improve the thermal/chemical/mechanical modeling of HMX based explosives like LX04 and LX10 for thermal cook-off The original HMX model and analysis scheme were developed by Yoh et al. for use in the ALE3D modeling framework. The current results were built to remedy the deficiencies of that original model. We concentrated our efforts in four areas. The first area was addition of porosity to the chemical material model framework in ALE3D that is used to model the HMX explosive formulation. This is needed to handle the roughly 2% porosity in solid explosives. The second area was the improvement of the HMX reaction network, which included a reactive phase change model base on work by Henson et al. The third area required adding early decomposition gas species to the CHEETAH material database to develop more accurate equations of state for gaseous intermediates and products. Finally, it was necessary to improve the implicit mechanics module in ALE3D to more naturally handle the long time scales associated with thermal cook-off The application of the resulting framework to the analysis of the Scaled Thermal Explosion (STEX) experiments will be discussed.

Critical Robotic Lunar Missions

NASA Astrophysics Data System (ADS)

Plescia, J. B.

2018-04-01

Perhaps the most critical missions to understanding lunar history are in situ dating and network missions. These would constrain the volcanic and thermal history and interior structure. These data would better constrain lunar evolution models.

Distributed Energy Resources Customer Adoption Model Plus (DER-CAM+), Version 1.0.0

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

Stadler, Michael; Cardorso, Goncalo; Mashayekh, Salman

DER-CAM+ v1.0.0 is internally referred to as DER-CAM v5.0.0. Due to fundamental changes from previous versions, a new name (DER-CAM+) will be used for DER-CAM version 5.0.0 and above. DER-CAM+ is a Decision Support Tool for Decentralized Energy Systems that has been tailored for microgrid applications, and now explicitly considers electrical and thermal networks within a microgrid, ancillary services, and operating reserve. DER-CAM was initially created as an exclusively economic energy model, able to find the cost minimizing combination and operation profile of a set of DER technologies that meet energy loads of a building or microgrid for a typicalmore » test year. The previous versions of DER-CAM were formulated without modeling the electrical/thermal networks within the microgrid, and hence, used aggregate single-node approaches. Furthermore, they were not able to consider operating reserve constraints, and microgrid revenue streams from participating in ancillary services markets. This new version DER-CAM+ considers these issues by including electrical power flow and thermal flow equations and constraints in the microgrid, revenues from various ancillary services markets, and operating reserve constraints.« less

Multiscale Modeling of UHTC: Thermal Conductivity

NASA Technical Reports Server (NTRS)

Lawson, John W.; Murry, Daw; Squire, Thomas; Bauschlicher, Charles W.

2012-01-01

We are developing a multiscale framework in computational modeling for the ultra high temperature ceramics (UHTC) ZrB2 and HfB2. These materials are characterized by high melting point, good strength, and reasonable oxidation resistance. They are candidate materials for a number of applications in extreme environments including sharp leading edges of hypersonic aircraft. In particular, we used a combination of ab initio methods, atomistic simulations and continuum computations to obtain insights into fundamental properties of these materials. Ab initio methods were used to compute basic structural, mechanical and thermal properties. From these results, a database was constructed to fit a Tersoff style interatomic potential suitable for atomistic simulations. These potentials were used to evaluate the lattice thermal conductivity of single crystals and the thermal resistance of simple grain boundaries. Finite element method (FEM) computations using atomistic results as inputs were performed with meshes constructed on SEM images thereby modeling the realistic microstructure. These continuum computations showed the reduction in thermal conductivity due to the grain boundary network.

Spatial statistical network models for stream and river temperature in New England, USA

EPA Science Inventory

Watershed managers are challenged by the need for predictive temperature models with sufficient accuracy and geographic breadth for practical use. We described thermal regimes of New England rivers and streams based on a reduced set of metrics for the May–September growing ...

The brain as a system of nested but partially overlapping networks. Heuristic relevance of the model for brain physiology and pathology.

PubMed

Agnati, L F; Guidolin, D; Fuxe, K

2007-01-01

A new model of the brain organization is proposed. The model is based on the assumption that a global molecular network enmeshes the entire central nervous system. Thus, brain extra-cellular and intra-cellular molecular networks are proposed to communicate at the level of special plasma membrane regions (e.g., the lipid rafts) where horizontal molecular networks can represent input/output regions allowing the cell to have informational exchanges with the extracellular environment. Furthermore, some "pervasive signals" such as field potentials, pressure waves and thermal gradients that affect large parts of the brain cellular and molecular networks are discussed. Finally, at least two learning paradigms are analyzed taking into account the possible role of Volume Transmission: the so-called model of "temporal difference learning" and the "Turing B-unorganised machine". The relevance of this new view of brain organization for a deeper understanding of some neurophysiological and neuropathological aspects of its function is briefly discussed.

Transverse thermal conductivity of porous materials made from aligned nano- and microcylindrical pores

NASA Astrophysics Data System (ADS)

Prasher, Ravi

2006-09-01

Nanoporous and microporous materials made from aligned cylindrical pores play important roles in present technologies and will play even bigger roles in future technologies. The insight into the phonon thermal conductivity of these materials is important and relevant in many technologies and applications. Since the mean free path of phonons can be comparable to the pore size and interpore distance, diffusion-approximation based effective medium models cannot be used to predict the thermal conductivity of these materials. Strictly speaking, the Boltzmann transport equation (BTE) must be solved to capture the ballistic nature of thermal transport; however, solving BTE in such a complex network of pores is impractical. As an alternative, we propose an approximate ballistic-diffusive microscopic effective medium model for predicting the thermal conductivity of phonons in two-dimensional nanoporous and microporous materials made from aligned cylindrical pores. The model captures the size effects due to the pore diameter and the interpore distance and reduces to diffusion-approximation based models for macroporous materials. The results are in good agreement with experimental data.

Identification Approach to Alleviate Effects of Unmeasured Heat Gains for MIMO Building Thermal Systems

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

Cai, Jie; Kim, Donghun; Braun, James E.

It is important to have practical methods for constructing a good mathematical model for a building's thermal system for energy audits, retrofit analysis and advanced building controls, e.g. model predictive control. Identification approaches based on semi-physical model structures are popular in building science for those purposes. However conventional gray box identification approaches applied to thermal networks would fail when significant unmeasured heat gains present in estimation data. Although this situation is very common and practical, there has been little research to tackle this issue in building science. This paper presents an overall identification approach to alleviate influences of unmeasured disturbances,more » and hence to obtain improved gray-box building models. The approach was applied to an existing open space building and the performance is demonstrated.« less

Effects of Thermal Variability on Broadband Seismometers: Controlled Experiments, Observations, and Implications

NASA Astrophysics Data System (ADS)

Doody, C.; Ringler, A. T.; Anthony, R. E.; Wilson, D.; Holland, A. A.; Hutt, C. R.; Sandoval, L. D.

2017-12-01

Although taking steps to isolate seismic instruments from temperature fluctuations is routine practice within the seismological community, the necessary level of thermal stability required in a broadband installation to avoid generating noise is largely unknown. In order to quantify the temperature sensitivity of seismometers over a broad range of frequencies, we artificially induced local temperature changes on three different models of seismometers to empirically measure the effect of thermal variations on seismometer output. We found that temperature changes above 0.002˚C per day show upwards of 10% change in broadband seismometer amplitude when compared to thermally stable reference measurements. We also find that rises in sensor incoherent self-noise increase with temperature variation; these increases in noise can be modeled as 1/f noise (pink noise). While seismometer output changes that correlate with temperature changes are likely correctable, this increase in 1/f noise is unlikely to be easily corrected for. These experimental results are also compared to data from Global Seismographic Network (GSN)-IRIS/USGS network station TUC (Tucson, Arizona) which is well instrumented with temperature sensors, as well as three different broadband sensors, each of which uses a different method of thermal isolation (i.e. Styrofoam box, 1.2m posthole within the pier, and water bricks). We show that isolating sensors with water bricks, as well as posthole and borehole installations, thermally isolate sensors well enough to remove any thermal variability that would affect their output. We find that better seismometer installations which provide thermal stability below 0.002 ˚C per day could help to improve long-period vertical seismic data across the GSN by decreasing temperature-driven 1/f noise.

Product-sum universality and Rushbrooke inequality in explosive percolation

NASA Astrophysics Data System (ADS)

Sabbir, M. M. H.; Hassan, M. K.

2018-05-01

We study explosive percolation (EP) on an Erdös-Rényi network for product rule (PR) and sum rule (SR). Initially, it was claimed that EP describes discontinuous phase transition; now it is well accepted as a probabilistic model for thermal continuous phase transition (CPT). However, no model for CPT is complete unless we know how to relate its observable quantities with those of thermal CPT. To this end, we define entropy and specific heat, redefine susceptibility, and show that they behave exactly like their thermal counterparts. We obtain the critical exponents ν ,α ,β , and γ numerically and find that both PR and SR belong to the same universality class and obey Rushbrooke inequality.

Object-Oriented Dynamic Bayesian Network-Templates for Modelling Mechatronic Systems

DTIC Science & Technology

2002-05-04

daimlerchrysler.com Abstract are widespread. For modelling mechanical systems The object-oriented paradigma is a new but proven technol- ADAMS [31 or...hardware (sub-)systems. On the Software side thermal flow or hydraulics, see Figure 1. It also contains a the object-oriented paradigma is by now (at

Applications of a New England stream temperature model to ...

EPA Pesticide Factsheets

We have applied a statistical stream network (SSN) model to predict stream thermal metrics (summer monthly medians, growing season maximum magnitude and timing, and daily rates of change) across New England nontidal streams and rivers, excluding northern Maine watersheds that extend into Canada (Detenbeck et al., in review). We excluded stream temperature observations within one kilometer downstream of dams from our model development, so our predictions for those reaches represent potential thermal regimes in the absence of dam effects. We used stream thermal thresholds for mean July temperatures delineating transitions between coldwater, transitional coolwater, and warmwater fish communities derived by Beauchene et al. (2014) to classify expected stream and river thermal regimes across New England. Within the model domain and based on 2006 land-use and air temperatures, the model predicts that 21.8% of stream + river kilometers would support coldwater fish communities (mean July water temperatures 22.3 degrees C mean July temperatures). Application of the model allows us to assess potential condition given full riparian zone restoration as well as potential loss of cold or coolwater habitat given loss of riparian shading. Given restoration of all ripa

Probability of conductive bond formation in a percolating network of nanowires with fusible tips

NASA Astrophysics Data System (ADS)

Rykaczewski, Konrad; Wang, Robert Y.

2018-03-01

Meeting the heat dissipation demands of microelectronic devices requires development of polymeric composites with high thermal conductivity. This property is drastically improved by percolation networks of metallic filler particles that have their particle-to-particle contact resistances reduced through thermal or electromagnetic fusing. However, composites with fused metallic fillers are electrically conductive, which prevents their application within the chip-board and the inter-chip gaps. Here, we propose that electrically insulating composites for these purposes can be achieved by the application of fusible metallic coatings to the tips of nanowires with thermally conductive but electrically insulating cores. We derive analytical models that relate the ratio of the coated and total nanowire lengths to the fraction of fused, and thus conductive, bonds within percolating networks of these structures. We consider two types of materials for these fusible coatings. First, we consider silver-like coatings, which form only conductive bonds when contacting the silver-like coating of another nanowire. Second, we consider liquid metal-like coatings, which form conductive bonds regardless of whether they contact a coated or an uncoated segment of another nanowire. These models were validated using Monte Carlo simulations, which also revealed that electrical short-circuiting is highly unlikely until most of the wire is coated. Furthermore, we demonstrate that switching the tip coating from silver- to liquid metal-like materials can double the fraction of conductive bonds. Consequently, this work provides motivation to develop scalable methods for fabrication of the hybrid liquid-coated nanowires, whose dispersion in a polymer matrix is predicted to yield highly thermally conductive but electrically insulating composites.

Predicted effects of future climate warming on thermal habitat suitability for Lake Sturgeon (Acipenser fulvescens, Rafinesque, 1817) in rivers in Wisconsin, USA

USGS Publications Warehouse

Lyons, John D.; Stewart, Jana S.

2015-01-01

The Lake Sturgeon (Acipenser fulvescens, Rafinesque, 1817) may be threatened by future climate warming. The purpose of this study was to identify river reaches in Wisconsin, USA, where they might be vulnerable to warming water temperatures. In Wisconsin, A. fulvescens is known from 2291 km of large-river habitat that has been fragmented into 48 discrete river-lake networks isolated by impassable dams. Although the exact temperature tolerances are uncertain, water temperatures above 28–30°C are potentially less suitable for this coolwater species. Predictions from 13 downscaled global climate models were input to a lotic water temperature model to estimate amounts of potential thermally less-suitable habitat at present and for 2046–2065. Currently, 341 km (14.9%) of the known habitat are estimated to regularly exceed 28°C for an entire day, but only 6 km (0.3%) to exceed 30°C. In 2046–2065, 685–2164 km (29.9–94.5%) are projected to exceed 28°C and 33–1056 km (1.4–46.1%) to exceed 30°C. Most river-lake networks have cooler segments, large tributaries, or lakes that might provide temporary escape from potentially less suitable temperatures, but 12 short networks in the Lower Fox and Middle Wisconsin rivers totaling 93.6 km are projected to have no potential thermal refugia. One possible adaptation to climate change could be to provide fish passage or translocation so that riverine Lake Sturgeon might have access to more thermally suitable habitats.

Stochastic IMT (Insulator-Metal-Transition) Neurons: An Interplay of Thermal and Threshold Noise at Bifurcation

PubMed Central

Parihar, Abhinav; Jerry, Matthew; Datta, Suman; Raychowdhury, Arijit

2018-01-01

Artificial neural networks can harness stochasticity in multiple ways to enable a vast class of computationally powerful models. Boltzmann machines and other stochastic neural networks have been shown to outperform their deterministic counterparts by allowing dynamical systems to escape local energy minima. Electronic implementation of such stochastic networks is currently limited to addition of algorithmic noise to digital machines which is inherently inefficient; albeit recent efforts to harness physical noise in devices for stochasticity have shown promise. To succeed in fabricating electronic neuromorphic networks we need experimental evidence of devices with measurable and controllable stochasticity which is complemented with the development of reliable statistical models of such observed stochasticity. Current research literature has sparse evidence of the former and a complete lack of the latter. This motivates the current article where we demonstrate a stochastic neuron using an insulator-metal-transition (IMT) device, based on electrically induced phase-transition, in series with a tunable resistance. We show that an IMT neuron has dynamics similar to a piecewise linear FitzHugh-Nagumo (FHN) neuron and incorporates all characteristics of a spiking neuron in the device phenomena. We experimentally demonstrate spontaneous stochastic spiking along with electrically controllable firing probabilities using Vanadium Dioxide (VO2) based IMT neurons which show a sigmoid-like transfer function. The stochastic spiking is explained by two noise sources - thermal noise and threshold fluctuations, which act as precursors of bifurcation. As such, the IMT neuron is modeled as an Ornstein-Uhlenbeck (OU) process with a fluctuating boundary resulting in transfer curves that closely match experiments. The moments of interspike intervals are calculated analytically by extending the first-passage-time (FPT) models for Ornstein-Uhlenbeck (OU) process to include a fluctuating boundary. We find that the coefficient of variation of interspike intervals depend on the relative proportion of thermal and threshold noise, where threshold noise is the dominant source in the current experimental demonstrations. As one of the first comprehensive studies of a stochastic neuron hardware and its statistical properties, this article would enable efficient implementation of a large class of neuro-mimetic networks and algorithms. PMID:29670508

Stochastic IMT (Insulator-Metal-Transition) Neurons: An Interplay of Thermal and Threshold Noise at Bifurcation.

PubMed

Parihar, Abhinav; Jerry, Matthew; Datta, Suman; Raychowdhury, Arijit

2018-01-01

Artificial neural networks can harness stochasticity in multiple ways to enable a vast class of computationally powerful models. Boltzmann machines and other stochastic neural networks have been shown to outperform their deterministic counterparts by allowing dynamical systems to escape local energy minima. Electronic implementation of such stochastic networks is currently limited to addition of algorithmic noise to digital machines which is inherently inefficient; albeit recent efforts to harness physical noise in devices for stochasticity have shown promise. To succeed in fabricating electronic neuromorphic networks we need experimental evidence of devices with measurable and controllable stochasticity which is complemented with the development of reliable statistical models of such observed stochasticity. Current research literature has sparse evidence of the former and a complete lack of the latter. This motivates the current article where we demonstrate a stochastic neuron using an insulator-metal-transition (IMT) device, based on electrically induced phase-transition, in series with a tunable resistance. We show that an IMT neuron has dynamics similar to a piecewise linear FitzHugh-Nagumo (FHN) neuron and incorporates all characteristics of a spiking neuron in the device phenomena. We experimentally demonstrate spontaneous stochastic spiking along with electrically controllable firing probabilities using Vanadium Dioxide (VO 2 ) based IMT neurons which show a sigmoid-like transfer function. The stochastic spiking is explained by two noise sources - thermal noise and threshold fluctuations, which act as precursors of bifurcation. As such, the IMT neuron is modeled as an Ornstein-Uhlenbeck (OU) process with a fluctuating boundary resulting in transfer curves that closely match experiments. The moments of interspike intervals are calculated analytically by extending the first-passage-time (FPT) models for Ornstein-Uhlenbeck (OU) process to include a fluctuating boundary. We find that the coefficient of variation of interspike intervals depend on the relative proportion of thermal and threshold noise, where threshold noise is the dominant source in the current experimental demonstrations. As one of the first comprehensive studies of a stochastic neuron hardware and its statistical properties, this article would enable efficient implementation of a large class of neuro-mimetic networks and algorithms.

Stability Enhancement of Silver Nanowire Networks with Conformal ZnO Coatings Deposited by Atmospheric Pressure Spatial Atomic Layer Deposition.

PubMed

Khan, Afzal; Nguyen, Viet Huong; Muñoz-Rojas, David; Aghazadehchors, Sara; Jiménez, Carmen; Nguyen, Ngoc Duy; Bellet, Daniel

2018-06-06

Silver nanowire (AgNW) networks offer excellent electrical and optical properties and have emerged as one of the most attractive alternatives to transparent conductive oxides to be used in flexible optoelectronic applications. However, AgNW networks still suffer from chemical, thermal, and electrical instabilities, which in some cases can hinder their efficient integration as transparent electrodes in devices such as solar cells, transparent heaters, touch screens, and organic light emitting diodes. We have used atmospheric pressure spatial atomic layer deposition (AP-SALD) to fabricate hybrid transparent electrode materials in which the AgNW network is protected by a conformal thin layer of zinc oxide. The choice of AP-SALD allows us to maintain the low-cost and scalable processing of AgNW-based transparent electrodes. The effects of the ZnO coating thickness on the physical properties of AgNW networks are presented. The composite electrodes show a drastic enhancement of both thermal and electrical stabilities. We found that bare AgNWs were stable only up to 300 °C when subjected to thermal ramps, whereas the ZnO coating improved the stability up to 500 °C. Similarly, ZnO-coated AgNWs exhibited an increase of 100% in electrical stability with respect to bare networks, withstanding up to 18 V. A simple physical model shows that the origin of the stability improvement is the result of hindered silver atomic diffusion thanks to the presence of the thin oxide layer and the quality of the interfaces of hybrid electrodes. The effects of ZnO coating on both the network adhesion and optical transparency are also discussed. Finally, we show that the AP-SALD ZnO-coated AgNW networks can be effectively used as very stable transparent heaters.

Vertically Aligned and Interconnected SiC Nanowire Networks Leading to Significantly Enhanced Thermal Conductivity of Polymer Composites.

PubMed

Yao, Yimin; Zhu, Xiaodong; Zeng, Xiaoliang; Sun, Rong; Xu, Jian-Bin; Wong, Ching-Ping

2018-03-21

Efficient heat removal via thermal management materials has become one of the most critical challenges in the development of modern microelectronic devices. However, previously reported polymer composites exhibit limited enhancement of thermal conductivity, even when highly loaded with thermally conductive fillers, because of the lack of efficient heat transfer pathways. Herein, we report vertically aligned and interconnected SiC nanowire (SiCNW) networks as efficient fillers for polymer composites, achieving significantly enhanced thermal conductivity. The SiCNW networks are produced by freeze-casting nanowire aqueous suspensions followed by thermal sintering to consolidate the nanowire junctions, exhibiting a hierarchical architecture in which honeycomb-like SiCNW layers are aligned. The composite obtained by infiltrating SiCNW networks with epoxy resin, at a relatively low SiCNW loading of 2.17 vol %, represents a high through-plane thermal conductivity (1.67 W m -1 K -1 ) compared to the pure matrix, which is equivalent to a significant enhancement of 406.6% per 1 vol % loading. The orderly SiCNW network which can act as a macroscopic expressway for phonon transport is believed to be the main contributor for the excellent thermal performance. This strategy provides insights for the design of high-performance composites with potential to be used in advanced thermal management materials.

Volume and porosity thermal regulation in lipid mesophases by coupling mobile ligands to soft membranes

NASA Astrophysics Data System (ADS)

Parolini, Lucia; Mognetti, Bortolo M.; Kotar, Jurij; Eiser, Erika; Cicuta, Pietro; di Michele, Lorenzo

2015-01-01

Short DNA linkers are increasingly being exploited for driving-specific self-assembly of Brownian objects. DNA-functionalized colloids can assemble into ordered or amorphous materials with tailored morphology. Recently, the same approach has been applied to compliant units, including emulsion droplets and lipid vesicles. The liquid structure of these substrates introduces new degrees of freedom: the tethers can diffuse and rearrange, radically changing the physics of the interactions. Unlike droplets, vesicles are extremely deformable and DNA-mediated adhesion causes significant shape adjustments. We investigate experimentally the thermal response of pairs and networks of DNA-tethered liposomes and observe two intriguing and possibly useful collective properties: negative thermal expansion and tuneable porosity of the liposome networks. A model providing a thorough understanding of this unexpected phenomenon is developed, explaining the emergent properties out of the interplay between the temperature-dependent deformability of the vesicles and the DNA-mediated adhesive forces.

Volume and porosity thermal regulation in lipid mesophases by coupling mobile ligands to soft membranes

PubMed Central

Parolini, Lucia; Mognetti, Bortolo M.; Kotar, Jurij; Eiser, Erika; Cicuta, Pietro; Di Michele, Lorenzo

2015-01-01

Short DNA linkers are increasingly being exploited for driving-specific self-assembly of Brownian objects. DNA-functionalized colloids can assemble into ordered or amorphous materials with tailored morphology. Recently, the same approach has been applied to compliant units, including emulsion droplets and lipid vesicles. The liquid structure of these substrates introduces new degrees of freedom: the tethers can diffuse and rearrange, radically changing the physics of the interactions. Unlike droplets, vesicles are extremely deformable and DNA-mediated adhesion causes significant shape adjustments. We investigate experimentally the thermal response of pairs and networks of DNA-tethered liposomes and observe two intriguing and possibly useful collective properties: negative thermal expansion and tuneable porosity of the liposome networks. A model providing a thorough understanding of this unexpected phenomenon is developed, explaining the emergent properties out of the interplay between the temperature-dependent deformability of the vesicles and the DNA-mediated adhesive forces. PMID:25565580

Spatial and temporal variability in the effects of wildfire and drought on thermal habitat for a desert trout

USGS Publications Warehouse

Schultz, Luke; Heck, Michael; Hockman-Wert, David; Allai, T; Wengerd, Seth J.; Cook, NA; Dunham, Jason B.

2017-01-01

We studied how drought and an associated stressor, wildfire, influenced stream flow permanence and thermal regimes in a Great Basin stream network. We quantified these responses by collecting information with a spatially extensive network of data loggers. To understand the effects of wildfire specifically, we used data from 4 additional sites that were installed prior to a 2012 fire that burned nearly the entire watershed. Within the sampled network 73 reaches were classified as perennial, yet only 51 contained surface water during logger installation in 2014. Among the sites with pre-fire temperature data, we observed 2–4 °C increases in maximum daily stream temperature relative to an unburned control in the month following the fire; effects (elevated up to 6.6 °C) appeared to persist for at least one year. When observed August mean temperatures in 2015 (the peak of regionally severe drought) were compared to those predicted by a regional stream temperature model, we observed deviations of −2.1°-3.5°. The model under-predicted and over-predicted August mean by > 1 °C in 54% and 10% of sites, respectively, and deviance from predicted was negatively associated with elevation. Combined drought and post-fire conditions appeared to greatly restrict thermally-suitable habitat for Lahontan cutthroat trout (Oncorhynchus clarkii henshawi).

Toward Improved Fidelity of Thermal Explosion Simulations

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

Nichols, A L; Becker, R; Howard, W M

2009-07-17

We will present results of an effort to improve the thermal/chemical/mechanical modeling of HMX based explosive like LX04 and LX10 for thermal cook-off. The original HMX model and analysis scheme were developed by Yoh et.al. for use in the ALE3D modeling framework. The current results were built to remedy the deficiencies of that original model. We concentrated our efforts in four areas. The first area was addition of porosity to the chemical material model framework in ALE3D that is used to model the HMX explosive formulation. This is needed to handle the roughly 2% porosity in solid explosives. The secondmore » area was the improvement of the HMX reaction network, which included the inclusion of a reactive phase change model base on work by Henson et.al. The third area required adding early decomposition gas species to the CHEETAH material database to develop more accurate equations of state for gaseous intermediates and products. Finally, it was necessary to improve the implicit mechanics module in ALE3D to more naturally handle the long time scales associated with thermal cook-off. The application of the resulting framework to the analysis of the Scaled Thermal Explosion (STEX) experiments will be discussed.« less

A thermodynamic analysis of a novel bidirectional district heating and cooling network

DOE PAGES

Zarin Pass, R.; Wetter, M.; Piette, M. A.

2017-11-29

In this study, we evaluate an ambient, bidirectional thermal network, which uses a single circuit for both district heating and cooling. When in net more cooling is needed than heating, the system circulates from a central plant in one direction. When more heating is needed, the system circulates in the opposite direction. A large benefit of this design is that buildings can recover waste heat from each other directly. We analyze the thermodynamic performance of the bidirectional system. Because the bidirectional system represents the state-of-the-art in design for district systems, its peak energy efficiency represents an upper bound on themore » thermal performance of any district heating and cooling system. However, because any network has mechanical and thermal distribution losses, we develop a diversity criterion to understand when the bidirectional system may be a more energy-efficient alternative to modern individual-building systems. We show that a simple model of a low-density, high-distribution loss network is more efficient than aggregated individual buildings if there is at least 1 unit of cooling energy per 5.7 units of simultaneous heating energy (or vice versa). We apply this criterion to reference building profiles in three cities to look for promising clusters.« less

A thermodynamic analysis of a novel bidirectional district heating and cooling network

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

Zarin Pass, R.; Wetter, M.; Piette, M. A.

In this study, we evaluate an ambient, bidirectional thermal network, which uses a single circuit for both district heating and cooling. When in net more cooling is needed than heating, the system circulates from a central plant in one direction. When more heating is needed, the system circulates in the opposite direction. A large benefit of this design is that buildings can recover waste heat from each other directly. We analyze the thermodynamic performance of the bidirectional system. Because the bidirectional system represents the state-of-the-art in design for district systems, its peak energy efficiency represents an upper bound on themore » thermal performance of any district heating and cooling system. However, because any network has mechanical and thermal distribution losses, we develop a diversity criterion to understand when the bidirectional system may be a more energy-efficient alternative to modern individual-building systems. We show that a simple model of a low-density, high-distribution loss network is more efficient than aggregated individual buildings if there is at least 1 unit of cooling energy per 5.7 units of simultaneous heating energy (or vice versa). We apply this criterion to reference building profiles in three cities to look for promising clusters.« less

Envisioning, quantifying, and managing thermal regimes on river networks

Treesearch

E. Ashley Steel; Timothy J. Beechie; Christian E. Torgersen; Aimee H. Fullerton

2017-01-01

Water temperatures fluctuate in time and space, creating diverse thermal regimes on river networks. Temporal variability in these thermal landscapes has important biological and ecological consequences because of nonlinearities in physiological reactions; spatial diversity in thermal landscapes provides aquatic organisms with options to maximize growth and survival....

Electrohydrodynamic fibrillation governed enhanced thermal transport in dielectric colloids under a field stimulus.

PubMed

Dhar, Purbarun; Maganti, Lakshmi Sirisha; Harikrishnan, A R

2018-05-30

Electrorheological (ER) fluids are known to exhibit enhanced viscous effects under an electric field stimulus. The present article reports the hitherto unreported phenomenon of greatly enhanced thermal conductivity in such electro-active colloidal dispersions in the presence of an externally applied electric field. Typical ER fluids are synthesized employing dielectric fluids and nanoparticles and experiments are performed employing an in-house designed setup. Greatly augmented thermal conductivity under a field's influence was observed. Enhanced thermal conduction along the fibril structures under the field effect is theorized as the crux of the mechanism. The formation of fibril structures has also been experimentally verified employing microscopy. Based on classical models for ER fluids, a mathematical formalism has been developed to predict the propensity of chain formation and statistically feasible chain dynamics at given Mason numbers. Further, a thermal resistance network model is employed to computationally predict the enhanced thermal conduction across the fibrillary colloid microstructure. Good agreement between the mathematical model and the experimental observations is achieved. The domineering role of thermal conductivity over relative permittivity has been shown by proposing a modified Hashin-Shtrikman (HS) formalism. The findings have implications towards better physical understanding and design of ER fluids from both 'smart' viscoelastic as well as thermally active materials points of view.

A simplified fracture network model for studying the efficiency of a single well semi open loop heat exchanger in fractured crystalline rock

NASA Astrophysics Data System (ADS)

de La Bernardie, Jérôme; de Dreuzy, Jean-Raynald; Bour, Olivier; Thierion, Charlotte; Ausseur, Jean-Yves; Lesuer, Hervé; Le Borgne, Tanguy

2016-04-01

Geothermal energy is a renewable energy source particularly attractive due to associated low greenhouse gas emission rates. Crystalline rocks are in general considered of poor interest for geothermal applications at shallow depths (< 100m), because of the low permeability of the medium. In some cases, fractures may enhance permeability, but thermal energy storage at these shallow depths is still remaining very challenging because of the complexity of fractured media. The purpose of this study is to test the possibility of efficient thermal energy storage in shallow fractured rocks with a single well semi open loop heat exchanger (standing column well). For doing so, a simplified numerical model of fractured media is considered with few fractures. Here we present the different steps for building the model and for achieving the sensitivity analysis. First, an analytical and dimensional study on the equations has been achieved to highlight the main parameters that control the optimization of the system. In a second step, multiphysics software COMSOL was used to achieve numerical simulations in a very simplified model of fractured media. The objective was to test the efficiency of such a system to store and recover thermal energy depending on i) the few parameters controlling fracture network geometry (size and number of fractures) and ii) the frequency of cycles used to store and recover thermal energy. The results have then been compared to reference shallow geothermal systems already set up for porous media. Through this study, relationships between structure, heat exchanges and storage may be highlighted.

Introducing ab initio based neural networks for transition-rate prediction in kinetic Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Messina, Luca; Castin, Nicolas; Domain, Christophe; Olsson, Pär

2017-02-01

The quality of kinetic Monte Carlo (KMC) simulations of microstructure evolution in alloys relies on the parametrization of point-defect migration rates, which are complex functions of the local chemical composition and can be calculated accurately with ab initio methods. However, constructing reliable models that ensure the best possible transfer of physical information from ab initio to KMC is a challenging task. This work presents an innovative approach, where the transition rates are predicted by artificial neural networks trained on a database of 2000 migration barriers, obtained with density functional theory (DFT) in place of interatomic potentials. The method is tested on copper precipitation in thermally aged iron alloys, by means of a hybrid atomistic-object KMC model. For the object part of the model, the stability and mobility properties of copper-vacancy clusters are analyzed by means of independent atomistic KMC simulations, driven by the same neural networks. The cluster diffusion coefficients and mean free paths are found to increase with size, confirming the dominant role of coarsening of medium- and large-sized clusters in the precipitation kinetics. The evolution under thermal aging is in better agreement with experiments with respect to a previous interatomic-potential model, especially concerning the experiment time scales. However, the model underestimates the solubility of copper in iron due to the excessively high solution energy predicted by the chosen DFT method. Nevertheless, this work proves the capability of neural networks to transfer complex ab initio physical properties to higher-scale models, and facilitates the extension to systems with increasing chemical complexity, setting the ground for reliable microstructure evolution simulations in a wide range of alloys and applications.

Advertising and Irreversible Opinion Spreading in Complex Social Networks

NASA Astrophysics Data System (ADS)

Candia, Julián

Irreversible opinion spreading phenomena are studied on small-world and scale-free networks by means of the magnetic Eden model, a nonequilibrium kinetic model for the growth of binary mixtures in contact with a thermal bath. In this model, the opinion of an individual is affected by those of their acquaintances, but opinion changes (analogous to spin flips in an Ising-like model) are not allowed. We focus on the influence of advertising, which is represented by external magnetic fields. The interplay and competition between temperature and fields lead to order-disorder transitions, which are found to also depend on the link density and the topology of the complex network substrate. The effects of advertising campaigns with variable duration, as well as the best cost-effective strategies to achieve consensus within different scenarios, are also discussed.

Investigation of nanoparticle agglomeration on the effective thermal conductivity of a composite material

NASA Astrophysics Data System (ADS)

Webb, Anthony J.

Phase Change Materials (PCMs), like paraffin wax, can be used for passive thermal management of portable electronics if their overall bulk thermal conductivity is increased through the addition of highly conducting nanoparticles. Finite Element Analysis (FEA) is used to investigate the influence of nanoparticle agglomeration on the overall conductive thermal transport in a nanoenhanced composite by dictating the thermal conductivity of individual elements according to their local inclusion volume fraction and characteristics inside a low conducting PCM matrix. The inclusion density distribution is dictated by an agglomeration factor, and the effective thermal conductivity of each element is calculated from the nanoparticle volume fraction using a method similar to the Representative Volume Element (RVE) methodology. FEA studies are performed for 2-D and 3-D models. In the 2-D model, the grain boundary is fixed at x = 0 for simplicity. For the 3-D model, the grain boundary geometry is randomly varied. A negligible 2-D effect on thermal transport in the 2-D model is seen, so a 1-D thermal resistance network is created for comparison, and the results agree within 4%.The influence of the agglomeration factor and contact Biot number on the overall bulk thermal conductivity is determined by applying Fourier's Law on the entire simulated composite. For the 2-D and 3-D models with a contact Biot number above 1, the overall bulk thermal conductivity decreases prior to the percolation threshold being met and then increases with increasing agglomeration. Finally, a MatlabRTM based image processing tool is created to estimate the agglomeration factor based on an experimental image of a nanoparticle distribution, with a calculated approximate agglomeration value of Beta*L = 5 which results in a bulk thermal conductivity of 0.278 W/(m-K).

Efficient energy transfer in light-harvesting systems: Quantum-classical comparison, flux network, and robustness analysis

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

Wu Jianlan; Department of Chemistry, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, Massachusetts 02139; Liu Fan

2012-11-07

Following the calculation of optimal energy transfer in thermal environment in our first paper [J. L. Wu, F. Liu, Y. Shen, J. S. Cao, and R. J. Silbey, New J. Phys. 12, 105012 (2010)], full quantum dynamics and leading-order 'classical' hopping kinetics are compared in the seven-site Fenna-Matthews-Olson (FMO) protein complex. The difference between these two dynamic descriptions is due to higher-order quantum corrections. Two thermal bath models, classical white noise (the Haken-Strobl-Reineker (HSR) model) and quantum Debye model, are considered. In the seven-site FMO model, we observe that higher-order corrections lead to negligible changes in the trapping time ormore » in energy transfer efficiency around the optimal and physiological conditions (2% in the HSR model and 0.1% in the quantum Debye model for the initial site at BChl 1). However, using the concept of integrated flux, we can identify significant differences in branching probabilities of the energy transfer network between hopping kinetics and quantum dynamics (26% in the HSR model and 32% in the quantum Debye model for the initial site at BChl 1). This observation indicates that the quantum coherence can significantly change the distribution of energy transfer pathways in the flux network with the efficiency nearly the same. The quantum-classical comparison of the average trapping time with the removal of the bottleneck site, BChl 4, demonstrates the robustness of the efficient energy transfer by the mechanism of multi-site quantum coherence. To reconcile with the latest eight-site FMO model which is also investigated in the third paper [J. Moix, J. L. Wu, P. F. Huo, D. F. Coker, and J. S. Cao, J. Phys. Chem. Lett. 2, 3045 (2011)], the quantum-classical comparison with the flux network analysis is summarized in Appendix C. The eight-site FMO model yields similar trapping time and network structure as the seven-site FMO model but leads to a more disperse distribution of energy transfer pathways.« less

Upper Stage Tank Thermodynamic Modeling Using SINDA/FLUINT

NASA Technical Reports Server (NTRS)

Schallhorn, Paul; Campbell, D. Michael; Chase, Sukhdeep; Piquero, Jorge; Fortenberry, Cindy; Li, Xiaoyi; Grob, Lisa

2006-01-01

Modeling to predict the condition of cryogenic propellants in an upper stage of a launch vehicle is necessary for mission planning and successful execution. Traditionally, this effort was performed using custom, in-house proprietary codes, limiting accessibility and application. Phenomena responsible for influencing the thermodynamic state of the propellant have been characterized as distinct events whose sequence defines a mission. These events include thermal stratification, passive thermal control roll (rotation), slosh, and engine firing. This paper demonstrates the use of an off the shelf, commercially available, thermal/fluid-network code to predict the thermodynamic state of propellant during the coast phase between engine firings, i.e. the first three of the above identified events. Results of this effort will also be presented.

Dimension- and shape-dependent thermal transport in nano-patterned thin films investigated by scanning thermal microscopy

NASA Astrophysics Data System (ADS)

Ge, Yunfei; Zhang, Yuan; Weaver, Jonathan M. R.; Dobson, Phillip S.

2017-12-01

Scanning thermal microscopy (SThM) is a technique which is often used for the measurement of the thermal conductivity of materials at the nanometre scale. The impact of nano-scale feature size and shape on apparent thermal conductivity, as measured using SThM, has been investigated. To achieve this, our recently developed topography-free samples with 200 and 400 nm wide gold wires (50 nm thick) of length of 400-2500 nm were fabricated and their thermal resistance measured and analysed. This data was used in the development and validation of a rigorous but simple heat transfer model that describes a nanoscopic contact to an object with finite shape and size. This model, in combination with a recently proposed thermal resistance network, was then used to calculate the SThM probe signal obtained by measuring these features. These calculated values closely matched the experimental results obtained from the topography-free sample. By using the model to analyse the dimensional dependence of thermal resistance, we demonstrate that feature size and shape has a significant impact on measured thermal properties that can result in a misinterpretation of material thermal conductivity. In the case of a gold nanowire embedded within a silicon nitride matrix it is found that the apparent thermal conductivity of the wire appears to be depressed by a factor of twenty from the true value. These results clearly demonstrate the importance of knowing both probe-sample thermal interactions and feature dimensions as well as shape when using SThM to quantify material thermal properties. Finally, the new model is used to identify the heat flux sensitivity, as well as the effective contact size of the conventional SThM system used in this study.

Battery Pack Life Estimation through Cell Degradation Data and Pack Thermal Modeling for BAS+ Li-Ion Batteries. Cooperative Research and Development Final Report, CRADA Number CRD-12-489

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

Smith, Kandler

Battery Life estimation is one of the key inputs required for Hybrid applications for all GM Hybrid/EV/EREV/PHEV programs. For each Hybrid vehicle program, GM has instituted multi-parameter Design of Experiments generating test data at Cell level and also Pack level on a reduced basis. Based on experience, generating test data on a pack level is found to be very expensive, resource intensive and sometimes less reliable. The proposed collaborative project will focus on a methodology to estimate Battery life based on cell degradation data combined with pack thermal modeling. NREL has previously developed cell-level battery aging models and pack-level thermal/electricalmore » network models, though these models are currently not integrated. When coupled together, the models are expected to describe pack-level thermal and aging response of individual cells. GM and NREL will use data collected for GM's Bas+ battery system for evaluation of the proposed methodology and assess to what degree these models can replace pack-level aging experiments in the future.« less

Multiscale Modeling of Ultra High Temperature Ceramics (UHTC) ZrB2 and HfB2: Application to Lattice Thermal Conductivity

NASA Technical Reports Server (NTRS)

Lawson, John W.; Daw, Murray S.; Squire, Thomas H.; Bauschlicher, Charles W.

2012-01-01

We are developing a multiscale framework in computational modeling for the ultra high temperature ceramics (UHTC) ZrB2 and HfB2. These materials are characterized by high melting point, good strength, and reasonable oxidation resistance. They are candidate materials for a number of applications in extreme environments including sharp leading edges of hypersonic aircraft. In particular, we used a combination of ab initio methods, atomistic simulations and continuum computations to obtain insights into fundamental properties of these materials. Ab initio methods were used to compute basic structural, mechanical and thermal properties. From these results, a database was constructed to fit a Tersoff style interatomic potential suitable for atomistic simulations. These potentials were used to evaluate the lattice thermal conductivity of single crystals and the thermal resistance of simple grain boundaries. Finite element method (FEM) computations using atomistic results as inputs were performed with meshes constructed on SEM images thereby modeling the realistic microstructure. These continuum computations showed the reduction in thermal conductivity due to the grain boundary network.

Non-thermal transitions in a model inspired by moral decisions

NASA Astrophysics Data System (ADS)

Alamino, Roberto C.

2016-08-01

This work introduces a model in which agents of a network act upon one another according to three different kinds of moral decisions. These decisions are based on an increasing level of sophistication in the empathy capacity of the agent, a hierarchy which we name Piaget’s ladder. The decision strategy of the agents is non-rational, in the sense they are arbitrarily fixed, and the model presents quenched disorder given by the distribution of its defining parameters. An analytical solution for this model is obtained in the large system limit as well as a leading order correction for finite-size systems which shows that typical realisations of the model develop a phase structure with both continuous and discontinuous non-thermal transitions.

Single well thermal tracer test, a new experimental set up for characterizing thermal transport in fractured media

NASA Astrophysics Data System (ADS)

de La Bernardie, Jérôme; Bour, Olivier; Guihéneuf, Nicolas; Chatton, Eliot; Labasque, Thierry; Longuevergne, Laurent; Le Lay, Hugo; Koch, Floriant; Gerard, Marie-Françoise; Le Borgne, Tanguy

2017-04-01

Thermal transport in fractured media depends on the hydrological properties of fractures and thermal characteristics of rock. Tracer tests using heat as tracer can thus be a good alternative to characterize fractured media for shallow geothermal needs. This study investigates the possibility of implementing a new thermal tracer test set up, the single well thermal tracer test, to characterize hydraulic and thermal transport properties of fractured crystalline rock. The experimental setup is based on injecting hot water in a fracture isolated by a double straddle packer in the borehole while pumping and monitoring the temperature in a fracture crossing the same borehole at greater elevation. One difficulty comes from the fact that injection and withdrawal are achieved in the same borehole involving thermal losses along the injection tube that may disturb the heat recovery signal. To be able to well localize the heat influx, we implemented a Fiber-Optic Distributed Temperature Sensing (FO-DTS) which allows the temperature monitoring with high spatial and temporal resolution (29 centimeters and 30 seconds respectively). Several tests, at different pumping and injection rates, were performed in a crystalline rock aquifer at the experimental site of Ploemeur (H+ observatory network). We show through signal processing how the thermal breakthrough may be extracted thanks to Fiber-Optic distributed temperature measurements. In particular, we demonstrate how detailed distributed temperature measurements were useful to identify different inflows and to estimate how much heat was transported and stored within the fractures network. Thermal breakthrough curves of single well thermal tracer tests were then interpreted with a simple analytical model to characterize hydraulic and thermal characteristics of the fractured media. We finally discuss the advantages of these tests compared to cross-borehole thermal tracer tests.

Imbedded-Fracture Formulation of THMC Processes in Fractured Media

NASA Astrophysics Data System (ADS)

Yeh, G. T.; Tsai, C. H.; Sung, R.

2016-12-01

Fractured media consist of porous materials and fracture networks. There exist four approaches to mathematically formulating THMC (Thermal-Hydrology-Mechanics-Chemistry) processes models in the system: (1) Equivalent Porous Media, (2) Dual Porosity or Dual Continuum, (3) Heterogeneous Media, and (4) Discrete Fracture Network. The first approach cannot explicitly explore the interactions between porous materials and fracture networks. The second approach introduces too many extra parameters (namely, exchange coefficients) between two media. The third approach may make the problems too stiff because the order of material heterogeneity may be too much. The fourth approach ignore the interaction between porous materials and fracture networks. This talk presents an alternative approach in which fracture networks are modeled with a lower dimension than the surrounding porous materials. Theoretical derivation of mathematical formulations will be given. An example will be illustrated to show the feasibility of this approach.

Elasticity in Physically Cross-Linked Amyloid Fibril Networks.

PubMed

Cao, Yiping; Bolisetty, Sreenath; Adamcik, Jozef; Mezzenga, Raffaele

2018-04-13

We provide a constitutive model of semiflexible and rigid amyloid fibril networks by combining the affine thermal model of network elasticity with the Derjaguin-Landau-Vervey-Overbeek (DLVO) theory of electrostatically charged colloids. When compared to rheological experiments on β-lactoglobulin and lysozyme amyloid networks, this approach provides the correct scaling of elasticity versus both concentration (G∼c^{2.2} and G∼c^{2.5} for semiflexible and rigid fibrils, respectively) and ionic strength (G∼I^{4.4} and G∼I^{3.8} for β-lactoglobulin and lysozyme, independent from fibril flexibility). The pivotal role played by the screening salt is to reduce the electrostatic barrier among amyloid fibrils, converting labile physical entanglements into long-lived cross-links. This gives a power-law behavior of G with I having exponents significantly larger than in other semiflexible polymer networks (e.g., actin) and carrying DLVO traits specific to the individual amyloid fibrils.

Elasticity in Physically Cross-Linked Amyloid Fibril Networks

NASA Astrophysics Data System (ADS)

Cao, Yiping; Bolisetty, Sreenath; Adamcik, Jozef; Mezzenga, Raffaele

2018-04-01

We provide a constitutive model of semiflexible and rigid amyloid fibril networks by combining the affine thermal model of network elasticity with the Derjaguin-Landau-Vervey-Overbeek (DLVO) theory of electrostatically charged colloids. When compared to rheological experiments on β -lactoglobulin and lysozyme amyloid networks, this approach provides the correct scaling of elasticity versus both concentration (G ˜c2.2 and G ˜c2.5 for semiflexible and rigid fibrils, respectively) and ionic strength (G ˜I4.4 and G ˜I3.8 for β -lactoglobulin and lysozyme, independent from fibril flexibility). The pivotal role played by the screening salt is to reduce the electrostatic barrier among amyloid fibrils, converting labile physical entanglements into long-lived cross-links. This gives a power-law behavior of G with I having exponents significantly larger than in other semiflexible polymer networks (e.g., actin) and carrying DLVO traits specific to the individual amyloid fibrils.

Irreversible opinion spreading on scale-free networks

NASA Astrophysics Data System (ADS)

Candia, Julián

2007-02-01

We study the dynamical and critical behavior of a model for irreversible opinion spreading on Barabási-Albert (BA) scale-free networks by performing extensive Monte Carlo simulations. The opinion spreading within an inhomogeneous society is investigated by means of the magnetic Eden model, a nonequilibrium kinetic model for the growth of binary mixtures in contact with a thermal bath. The deposition dynamics, which is studied as a function of the degree of the occupied sites, shows evidence for the leading role played by hubs in the growth process. Systems of finite size grow either ordered or disordered, depending on the temperature. By means of standard finite-size scaling procedures, the effective order-disorder phase transitions are found to persist in the thermodynamic limit. This critical behavior, however, is absent in related equilibrium spin systems such as the Ising model on BA scale-free networks, which in the thermodynamic limit only displays a ferromagnetic phase. The dependence of these results on the degree exponent is also discussed for the case of uncorrelated scale-free networks.

Electrical network method for the thermal or structural characterization of a conducting material sample or structure

DOEpatents

Ortiz, Marco G.

1993-01-01

A method for modeling a conducting material sample or structure system, as an electrical network of resistances in which each resistance of the network is representative of a specific physical region of the system. The method encompasses measuring a resistance between two external leads and using this measurement in a series of equations describing the network to solve for the network resistances for a specified region and temperature. A calibration system is then developed using the calculated resistances at specified temperatures. This allows for the translation of the calculated resistances to a region temperature. The method can also be used to detect and quantify structural defects in the system.

Electrical network method for the thermal or structural characterization of a conducting material sample or structure

DOEpatents

Ortiz, M.G.

1993-06-08

A method for modeling a conducting material sample or structure system, as an electrical network of resistances in which each resistance of the network is representative of a specific physical region of the system. The method encompasses measuring a resistance between two external leads and using this measurement in a series of equations describing the network to solve for the network resistances for a specified region and temperature. A calibration system is then developed using the calculated resistances at specified temperatures. This allows for the translation of the calculated resistances to a region temperature. The method can also be used to detect and quantify structural defects in the system.

The analysis of thermal network of district heating system from investor point of view

NASA Astrophysics Data System (ADS)

Takács, Ján; Rácz, Lukáš

2016-06-01

The hydraulics of a thermal network of a district heating system is a very important issue, to which not enough attention is often paid. In this paper the authors want to point out some of the important aspects of the design and operation of thermal networks in district heating systems. The design boundary conditions of a heat distribution network and the requirements on active pressure - circulation pump - influencing the operation costs of the centralized district heating system as a whole, are analyzed in detail. The heat generators and the heat exchange stations are designed according to the design heat loads after thermal insulation, and modern boiler units are installed in the heating plant.

Flow distribution analysis on the cooling tube network of ITER thermal shield

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

Nam, Kwanwoo; Chung, Wooho; Noh, Chang Hyun

2014-01-29

Thermal shield (TS) is to be installed between the vacuum vessel or the cryostat and the magnets in ITER tokamak to reduce the thermal radiation load to the magnets operating at 4.2K. The TS is cooled by pressurized helium gas at the inlet temperature of 80K. The cooling tube is welded on the TS panel surface and the composed flow network of the TS cooling tubes is complex. The flow rate in each panel should be matched to the thermal design value for effective radiation shielding. This paper presents one dimensional analysis on the flow distribution of cooling tube networkmore » for the ITER TS. The hydraulic cooling tube network is modeled by an electrical analogy. Only the cooling tube on the TS surface and its connecting pipe from the manifold are considered in the analysis model. Considering the frictional factor and the local loss in the cooling tube, the hydraulic resistance is expressed as a linear function with respect to mass flow rate. Sub-circuits in the TS are analyzed separately because each circuit is controlled by its own control valve independently. It is found that flow rates in some panels are insufficient compared with the design values. In order to improve the flow distribution, two kinds of design modifications are proposed. The first one is to connect the tubes of the adjacent panels. This will increase the resistance of the tube on the panel where the flow rate is excessive. The other design suggestion is that an orifice is installed at the exit of tube routing where the flow rate is to be reduced. The analysis for the design suggestions shows that the flow mal-distribution is improved significantly.« less

Modeling of macrosegregation caused by volumetric deformation in a coherent mushy zone

NASA Astrophysics Data System (ADS)

Nicolli, Lilia C.; Mo, Asbjørn; M'hamdi, Mohammed

2005-02-01

A two-phase volume-averaged continuum model is presented that quantifies macrosegregation formation during solidification of metallic alloys caused by deformation of the dendritic network and associated melt flow in the coherent part of the mushy zone. Also, the macrosegregation formation associated with the solidification shrinkage (inverse segregation) is taken into account. Based on experimental evidence established elsewhere, volumetric viscoplastic deformation (densification/dilatation) of the coherent dendritic network is included in the model. While the thermomechanical model previously outlined (M. M’Hamdi, A. Mo, and C.L. Martin: Metall. Mater. Trans. A, 2002, vol. 33A, pp. 2081-93) has been used to calculate the temperature and velocity fields associated with the thermally induced deformations and shrinkage driven melt flow, the solute conservation equation including both the liquid and a solid volume-averaged velocity is solved in the present study. In modeling examples, the macrosegregation formation caused by mechanically imposed as well as by thermally induced deformations has been calculated. The modeling results for an Al-4 wt pct Cu alloy indicate that even quite small volumetric strains (≈2 pct), which can be associated with thermally induced deformations, can lead to a macroscopic composition variation in the final casting comparable to that resulting from the solidification shrinkage induced melt flow. These results can be explained by the relatively large volumetric viscoplastic deformation in the coherent mush resulting from the applied constitutive model, as well as the relatively large difference in composition for the studied Al-Cu alloy in the solid and liquid phases at high solid fractions at which the deformation takes place.

Prediction of global solar irradiance based on time series analysis: Application to solar thermal power plants energy production planning

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

Martin, Luis; Marchante, Ruth; Cony, Marco

2010-10-15

Due to strong increase of solar power generation, the predictions of incoming solar energy are acquiring more importance. Photovoltaic and solar thermal are the main sources of electricity generation from solar energy. In the case of solar thermal energy plants with storage energy system, its management and operation need reliable predictions of solar irradiance with the same temporal resolution as the temporal capacity of the back-up system. These plants can work like a conventional power plant and compete in the energy stock market avoiding intermittence in electricity production. This work presents a comparisons of statistical models based on time seriesmore » applied to predict half daily values of global solar irradiance with a temporal horizon of 3 days. Half daily values consist of accumulated hourly global solar irradiance from solar raise to solar noon and from noon until dawn for each day. The dataset of ground solar radiation used belongs to stations of Spanish National Weather Service (AEMet). The models tested are autoregressive, neural networks and fuzzy logic models. Due to the fact that half daily solar irradiance time series is non-stationary, it has been necessary to transform it to two new stationary variables (clearness index and lost component) which are used as input of the predictive models. Improvement in terms of RMSD of the models essayed is compared against the model based on persistence. The validation process shows that all models essayed improve persistence. The best approach to forecast half daily values of solar irradiance is neural network models with lost component as input, except Lerida station where models based on clearness index have less uncertainty because this magnitude has a linear behaviour and it is easier to simulate by models. (author)« less

Energetics in a model of prebiotic evolution

NASA Astrophysics Data System (ADS)

Intoy, B. F.; Halley, J. W.

2017-12-01

Previously we reported [A. Wynveen et al., Phys. Rev. E 89, 022725 (2014), 10.1103/PhysRevE.89.022725] that requiring that the systems regarded as lifelike be out of chemical equilibrium in a model of abstracted polymers undergoing ligation and scission first introduced by Kauffman [S. A. Kauffman, The Origins of Order (Oxford University Press, New York, 1993), Chap. 7] implied that lifelike systems were most probable when the reaction network was sparse. The model was entirely statistical and took no account of the bond energies or other energetic constraints. Here we report results of an extension of the model to include effects of a finite bonding energy in the model. We studied two conditions: (1) A food set is continuously replenished and the total polymer population is constrained but the system is otherwise isolated and (2) in addition to the constraints in (1) the system is in contact with a finite-temperature heat bath. In each case, detailed balance in the dynamics is guaranteed during the computations by continuous recomputation of a temperature [in case (1)] and of the chemical potential (in both cases) toward which the system is driven by the dynamics. In the isolated case, the probability of reaching a metastable nonequilibrium state in this model depends significantly on the composition of the food set, and the nonequilibrium states satisfying lifelike condition turn out to be at energies and particle numbers consistent with an equilibrium state at high negative temperature. As a function of the sparseness of the reaction network, the lifelike probability is nonmonotonic, as in our previous model, but the maximum probability occurs when the network is less sparse. In the case of contact with a thermal bath at a positive ambient temperature, we identify two types of metastable nonequilibrium states, termed locally and thermally alive, and locally dead and thermally alive, and evaluate their likelihood of appearance, finding maxima at an optimal temperature and an optimal degree of sparseness in the network. We use a Euclidean metric in the space of polymer populations to distinguish these states from one another and from fully equilibrated states. The metric can be used to characterize the degree and type of chemical equilibrium in observed systems, as we illustrate for the proteome of the ribosome.

A feed-forward neural network for modeling feeding behavior of group-housed grow-finish pigs with respect to thermal conditions

USDA-ARS?s Scientific Manuscript database

Feeding patterns of pigs in the grow-finish phase have been investigated for use in management decisions, identifying sick animals, and determining genetic differences within a herd. Development of models to predict swine feeding behavior has been limited due the large number of potential environmen...

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.

CRYogenic Orbital TEstbed Ground Test Article Thermal Analysis

NASA Technical Reports Server (NTRS)

Piryk, David; Schallhorn, Paul; Walls, Laurie; Stopnitzky, Benny; Rhys, Noah; Wollen, Mark

2012-01-01

The purpose of this study was to anchor thermal and fluid system models to CRYOTE ground test data. The CRYOTE ground test artide was jointly developed by Innovative Engineering Solutions, United Launch Alliance and NASA KSC. The test article was constructed out of a titanium alloy tank, Sapphire 77 composite skin (similar to G10), an external secondary payload adapter ring, thermal vent system, multi layer insulation and various data acquisition instrumentation. In efforts to understand heat loads throughout this system, the GTA (filled with liquid nitrogen for safety purposes) was subjected to a series of tests in a vacuum chamber at Marshall Space Flight Center. By anchoring analytical models against test data, higher fidelity thermal environment predictions can be made for future flight articles which would eventually demonstrate critical cryogenic fluid management technologies such as system chilldown, transfer, pressure control and long term storage. Significant factors that influenced heat loads included radiative environments, multi-layer insulation performance, tank fill levels and pressures and even contact conductance coefficients. This report demonstrates how analytical thermal/fluid networks were established and includes supporting rationale for specific thermal responses.

Modeling thermal stress propagation during hydraulic stimulation of geothermal wells

NASA Astrophysics Data System (ADS)

Jansen, Gunnar; Miller, Stephen A.

2017-04-01

A large fraction of the world's water and energy resources are located in naturally fractured reservoirs within the earth's crust. Depending on the lithology and tectonic history of a formation, fracture networks can range from dense and homogeneous highly fractured networks to single large scale fractures dominating the flow behavior. Understanding the dynamics of such reservoirs in terms of flow and transport is crucial to successful application of engineered geothermal systems (also known as enhanced geothermal systems or EGS) for geothermal energy production in the future. Fractured reservoirs are considered to consist of two distinct separate media, namely the fracture and matrix space respectively. Fractures are generally thin, highly conductive containing only small amounts of fluid, whereas the matrix rock provides high fluid storage but typically has much smaller permeability. Simulation of flow and transport through fractured porous media is challenging due to the high permeability contrast between the fractures and the surrounding rock matrix. However, accurate and efficient simulation of flow through a fracture network is crucial in order to understand, optimize and engineer reservoirs. It has been a research topic for several decades and is still under active research. Accurate fluid flow simulations through field-scale fractured reservoirs are still limited by the power of current computer processing units (CPU). We present an efficient implementation of the embedded discrete fracture model, which is a promising new technique in modeling the behavior of enhanced geothermal systems. An efficient coupling strategy is determined for numerical performance of the model. We provide new insight into the coupled modeling of fluid flow, heat transport of engineered geothermal reservoirs with focus on the thermal stress changes during the stimulation process. We further investigate the interplay of thermal and poro-elastic stress changes in the reservoir. Combined with a analytical formulation for the injection temperatures in the open hole section of a geothermal well, the stress changes induced during the injection period of reservoir development can be studied.

A simple prioritization tool to diagnose impairment of stream temperature for coldwater fishes in the Great Basin

USGS Publications Warehouse

Falke, Jeffrey A.; Dunham, Jason B.; Hockman-Wert, David; Pahl, Randy

2016-01-01

We provide a simple framework for diagnosing the impairment of stream water temperature for coldwater fishes across broad spatial extents based on a weight-of-evidence approach that integrates biological criteria, species distribution models, and geostatistical models of stream temperature. As a test case, we applied our approach to identify stream reaches most likely to be thermally impaired for Lahontan Cutthroat Trout Oncorhynchus clarkii henshawi in the upper Reese River, located in the northern Great Basin, Nevada. We first evaluated the capability of stream thermal regime descriptors to explain variation across 170 sites, and we found that the 7-d moving average of daily maximum stream temperatures (7DADM) provided minimal among-descriptor redundancy and, based on an upper threshold of 20°C, was also a good indicator of acute and chronic thermal stress. Next, we quantified the range of Lahontan Cutthroat Trout within our study area using a geographic distribution model. Finally, we used a geostatistical model to assess spatial variation in 7DADM and predict potential thermal impairment at the stream reach scale. We found that whereas 38% of reaches in our study area exceeded a 7DADM of 20°C and 35% were significantly warmer than predicted, only 17% both exceeded the biological criterion and were significantly warmer than predicted. This filtering allowed us to identify locations where physical and biological impairment were most likely within the network and that would represent the highest management priorities. Although our approach lacks the precision of more comprehensive approaches, it provides a broader context for diagnosing impairment and is a useful means of identifying priorities for more detailed evaluations across broad and heterogeneous stream networks.

Great Thermal Conductivity Enhancement of Silicone Composite with Ultra-Long Copper Nanowires.

PubMed

Zhang, Liye; Yin, Junshan; Yu, Wei; Wang, Mingzhu; Xie, Huaqing

2017-12-01

In this paper, ultra-long copper nanowires (CuNWs) were successfully synthesized at a large scale by hydrothermal reduction of divalent copper ion using oleylamine and oleic acid as dual ligands. The characteristic of CuNWs is hard and linear, which is clearly different from graphene nanoplatelets (GNPs) and multi-wall carbon nanotubes (MWCNTs). The thermal properties and models of silicone composites with three nanomaterials have been mainly researched. The maximum of thermal conductivity enhancement is up to 215% with only 1.0 vol.% CuNW loading, which is much higher than GNPs and MWCNTs. It is due to the ultra-long CuNWs with a length of more than 100 μm, which facilitates the formation of effective thermal-conductive networks, resulting in great enhancement of thermal conductivity.

Great Thermal Conductivity Enhancement of Silicone Composite with Ultra-Long Copper Nanowires

NASA Astrophysics Data System (ADS)

Zhang, Liye; Yin, Junshan; Yu, Wei; Wang, Mingzhu; Xie, Huaqing

2017-07-01

In this paper, ultra-long copper nanowires (CuNWs) were successfully synthesized at a large scale by hydrothermal reduction of divalent copper ion using oleylamine and oleic acid as dual ligands. The characteristic of CuNWs is hard and linear, which is clearly different from graphene nanoplatelets (GNPs) and multi-wall carbon nanotubes (MWCNTs). The thermal properties and models of silicone composites with three nanomaterials have been mainly researched. The maximum of thermal conductivity enhancement is up to 215% with only 1.0 vol.% CuNW loading, which is much higher than GNPs and MWCNTs. It is due to the ultra-long CuNWs with a length of more than 100 μm, which facilitates the formation of effective thermal-conductive networks, resulting in great enhancement of thermal conductivity.

Lumped-Element Dynamic Electro-Thermal model of a superconducting magnet

NASA Astrophysics Data System (ADS)

Ravaioli, E.; Auchmann, B.; Maciejewski, M.; ten Kate, H. H. J.; Verweij, A. P.

2016-12-01

Modeling accurately electro-thermal transients occurring in a superconducting magnet is challenging. The behavior of the magnet is the result of complex phenomena occurring in distinct physical domains (electrical, magnetic and thermal) at very different spatial and time scales. Combined multi-domain effects significantly affect the dynamic behavior of the system and are to be taken into account in a coherent and consistent model. A new methodology for developing a Lumped-Element Dynamic Electro-Thermal (LEDET) model of a superconducting magnet is presented. This model includes non-linear dynamic effects such as the dependence of the magnet's differential self-inductance on the presence of inter-filament and inter-strand coupling currents in the conductor. These effects are usually not taken into account because superconducting magnets are primarily operated in stationary conditions. However, they often have significant impact on magnet performance, particularly when the magnet is subject to high ramp rates. Following the LEDET method, the complex interdependence between the electro-magnetic and thermal domains can be modeled with three sub-networks of lumped-elements, reproducing the electrical transient in the main magnet circuit, the thermal transient in the coil cross-section, and the electro-magnetic transient of the inter-filament and inter-strand coupling currents in the superconductor. The same simulation environment can simultaneously model macroscopic electrical transients and phenomena at the level of superconducting strands. The model developed is a very useful tool for reproducing and predicting the performance of conventional quench protection systems based on energy extraction and quench heaters, and of the innovative CLIQ protection system as well.

Development of Embedded Vascular Networks in FRP for Active/Passive Thermal Management

DTIC Science & Technology

2015-04-01

Passive Thermal Management Katarzyna...To) 30 September 2012 – 31 December 2014 4. TITLE AND SUBTITLE Development of Embedded Vascular Networks in FRP for Active/ Passive Thermal Management   5a...Active/ Passive   Thermal   Management   Reference:       EOARD  grant  (FA8655-­‐12-­‐1-­‐2144)   Investigators:    

Critical behavior and correlations on scale-free small-world networks: Application to network design

NASA Astrophysics Data System (ADS)

Ostilli, M.; Ferreira, A. L.; Mendes, J. F. F.

2011-06-01

We analyze critical phenomena on networks generated as the union of hidden variable models (networks with any desired degree sequence) with arbitrary graphs. The resulting networks are general small worlds similar to those à la Watts and Strogatz, but with a heterogeneous degree distribution. We prove that the critical behavior (thermal or percolative) remains completely unchanged by the presence of finite loops (or finite clustering). Then, we show that, in large but finite networks, correlations of two given spins may be strong, i.e., approximately power-law-like, at any temperature. Quite interestingly, if γ is the exponent for the power-law distribution of the vertex degree, for γ⩽3 and with or without short-range couplings, such strong correlations persist even in the thermodynamic limit, contradicting the common opinion that, in mean-field models, correlations always disappear in this limit. Finally, we provide the optimal choice of rewiring under which percolation phenomena in the rewired network are best performed, a natural criterion to reach best communication features, at least in noncongested regimes.

Aggregation of gluten proteins in model dough after fibre polysaccharide addition.

PubMed

Nawrocka, Agnieszka; Szymańska-Chargot, Monika; Miś, Antoni; Wilczewska, Agnieszka Z; Markiewicz, Karolina H

2017-09-15

FT-Raman spectroscopy, thermogravimetry and differential scanning calorimetry were used to study changes in structure of gluten proteins and their thermal properties influenced by four dietary fibre polysaccharides (microcrystalline cellulose, inulin, apple pectin and citrus pectin) during development of a model dough. The flour reconstituted from wheat starch and wheat gluten was mixed with the polysaccharides in five concentrations: 3%, 6%, 9%, 12% and 18%. The obtained results showed that all polysaccharides induced similar changes in secondary structure of gluten proteins concerning formation of aggregates (1604cm -1 ), H-bonded parallel- and antiparallel-β-sheets (1690cm -1 ) and H-bonded β-turns (1664cm -1 ). These changes concerned mainly glutenins since β-structures are characteristic for them. The observed structural changes confirmed hypothesis about partial dehydration of gluten network after polysaccharides addition. The gluten aggregation and dehydration processes were also reflected in the DSC results, while the TGA ones showed that gluten network remained thermally stable after polysaccharides addition. Copyright © 2017 Elsevier Ltd. All rights reserved.

Non-equilibrium fluctuations of a semi-flexible filament driven by active cross-linkers

NASA Astrophysics Data System (ADS)

Weber, I.; Appert-Rolland, C.; Schehr, G.; Santen, L.

2017-11-01

The cytoskeleton is an inhomogeneous network of semi-flexible filaments, which are involved in a wide variety of active biological processes. Although the cytoskeletal filaments can be very stiff and embedded in a dense and cross-linked network, it has been shown that, in cells, they typically exhibit significant bending on all length scales. In this work we propose a model of a semi-flexible filament deformed by different types of cross-linkers for which one can compute and investigate the bending spectrum. Our model allows to couple the evolution of the deformation of the semi-flexible polymer with the stochastic dynamics of linkers which exert transversal forces onto the filament. We observe a q-2 dependence of the bending spectrum for some biologically relevant parameters and in a certain range of wave numbers q, as observed in some experiments. However, generically, the spatially localized forcing and the non-thermal dynamics both introduce deviations from the thermal-like q-2 spectrum.

A candidate multimodal functional genetic network for thermal adaptation

PubMed Central

Pathak, Rachana; Prajapati, Indira; Bankston, Shannon; Thompson, Aprylle; Usher, Jaytriece; Isokpehi, Raphael D.

2014-01-01

Vertebrate ectotherms such as reptiles provide ideal organisms for the study of adaptation to environmental thermal change. Comparative genomic and exomic studies can recover markers that diverge between warm and cold adapted lineages, but the genes that are functionally related to thermal adaptation may be difficult to identify. We here used a bioinformatics genome-mining approach to predict and identify functions for suitable candidate markers for thermal adaptation in the chicken. We first established a framework of candidate functions for such markers, and then compiled the literature on genes known to adapt to the thermal environment in different lineages of vertebrates. We then identified them in the genomes of human, chicken, and the lizard Anolis carolinensis, and established a functional genetic interaction network in the chicken. Surprisingly, markers initially identified from diverse lineages of vertebrates such as human and fish were all in close functional relationship with each other and more associated than expected by chance. This indicates that the general genetic functional network for thermoregulation and/or thermal adaptation to the environment might be regulated via similar evolutionarily conserved pathways in different vertebrate lineages. We were able to identify seven functions that were statistically overrepresented in this network, corresponding to four of our originally predicted functions plus three unpredicted functions. We describe this network as multimodal: central regulator genes with the function of relaying thermal signal (1), affect genes with different cellular functions, namely (2) lipoprotein metabolism, (3) membrane channels, (4) stress response, (5) response to oxidative stress, (6) muscle contraction and relaxation, and (7) vasodilation, vasoconstriction and regulation of blood pressure. This network constitutes a novel resource for the study of thermal adaptation in the closely related nonavian reptiles and other vertebrate ectotherms. PMID:25289178

Prediction of Austenite Formation Temperatures Using Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Schulze, P.; Schmidl, E.; Grund, T.; Lampke, T.

2016-03-01

For the modeling and design of heat treatments, in consideration of the development/ transformation of the microstructure, different material data depending on the chemical composition, the respective microstructure/phases and the temperature are necessary. Material data are, e.g. the thermal conductivity, heat capacity, thermal expansion and transformation data etc. The quality of thermal simulations strongly depends on the accuracy of the material data. For many materials, the required data - in particular for different microstructures and temperatures - are rare in the literature. In addition, a different chemical composition within the permitted limits of the considered steel alloy cannot be predicted. A solution for this problem is provided by the calculation of material data using Artificial Neural Networks (ANN). In the present study, the start and finish temperatures of the transformation from the bcc lattice to the fcc lattice structure of hypoeutectoid steels are calculated using an Artificial Neural Network. An appropriate database containing different transformation temperatures (austenite formation temperatures) to train the ANN is selected from the literature. In order to find a suitable feedforward network, the network topologies as well as the activation functions of the hidden layers are varied and subsequently evaluated in terms of the prediction accuracy. The transformation temperatures calculated by the ANN exhibit a very good compliance compared to the experimental data. The results show that the prediction performance is even higher compared to classical empirical equations such as Andrews or Brandis. Therefore, it can be assumed that the presented ANN is a convenient tool to distinguish between bcc and fcc phases in hypoeutectoid steels.

ASSESSING THE IMPORTANCE OF THERMAL REFUGE ...

EPA Pesticide Factsheets

Salmon populations require river networks that provide water temperature regimes sufficient to support a diversity of salmonid life histories across space and time. The importance of cold water refuges for migrating adult salmon and steelhead may seem intuitive, and refuges are clearly used by fish during warm water episodes. But quantifying the value of both small and large scale thermal features to salmon populations has been challenging due to the difficulty of mapping thermal regimes at sufficient spatial and temporal resolutions, and integrating thermal regimes into population models. We attempt to address these challenges by using newly-available datasets and modeling approaches to link thermal regimes to salmon populations across scales. We discuss the challenges and opportunities to simulating fish behaviors and linking exposures to migratory and reproductive fitness. In this talk and companion poster, we describe an individual-based modeling approach for assessing sufficiency of thermal refuges for migrating salmon and steelhead in the Columbia River. Many rivers and streams in the Pacific Northwest are currently listed as impaired under the Clean Water Act as a result of high summer water temperatures. Adverse effects of warm waters include impacts to salmon and steelhead populations that may already be stressed by habitat alteration, disease, predation, and fishing pressures. Much effort is being expended to improve conditions for salmon and steelhea

Open quantum generalisation of Hopfield neural networks

NASA Astrophysics Data System (ADS)

Rotondo, P.; Marcuzzi, M.; Garrahan, J. P.; Lesanovsky, I.; Müller, M.

2018-03-01

We propose a new framework to understand how quantum effects may impact on the dynamics of neural networks. We implement the dynamics of neural networks in terms of Markovian open quantum systems, which allows us to treat thermal and quantum coherent effects on the same footing. In particular, we propose an open quantum generalisation of the Hopfield neural network, the simplest toy model of associative memory. We determine its phase diagram and show that quantum fluctuations give rise to a qualitatively new non-equilibrium phase. This novel phase is characterised by limit cycles corresponding to high-dimensional stationary manifolds that may be regarded as a generalisation of storage patterns to the quantum domain.

An Adaptive Network-based Fuzzy Inference System for the detection of thermal and TEC anomalies around the time of the Varzeghan, Iran, (Mw = 6.4) earthquake of 11 August 2012

NASA Astrophysics Data System (ADS)

Akhoondzadeh, M.

2013-09-01

Anomaly detection is extremely important for forecasting the date, location and magnitude of an impending earthquake. In this paper, an Adaptive Network-based Fuzzy Inference System (ANFIS) has been proposed to detect the thermal and Total Electron Content (TEC) anomalies around the time of the Varzeghan, Iran, (Mw = 6.4) earthquake jolted in 11 August 2012 NW Iran. ANFIS is the famous hybrid neuro-fuzzy network for modeling the non-linear complex systems. In this study, also the detected thermal and TEC anomalies using the proposed method are compared to the results dealing with the observed anomalies by applying the classical and intelligent methods including Interquartile, Auto-Regressive Integrated Moving Average (ARIMA), Artificial Neural Network (ANN) and Support Vector Machine (SVM) methods. The duration of the dataset which is comprised from Aqua-MODIS Land Surface Temperature (LST) night-time snapshot images and also Global Ionospheric Maps (GIM), is 62 days. It can be shown that, if the difference between the predicted value using the ANFIS method and the observed value, exceeds the pre-defined threshold value, then the observed precursor value in the absence of non seismic effective parameters could be regarded as precursory anomaly. For two precursors of LST and TEC, the ANFIS method shows very good agreement with the other implemented classical and intelligent methods and this indicates that ANFIS is capable of detecting earthquake anomalies. The applied methods detected anomalous occurrences 1 and 2 days before the earthquake. This paper indicates that the detection of the thermal and TEC anomalies derive their credibility from the overall efficiencies and potentialities of the five integrated methods.

Design and architecture of the Mars relay network planning and analysis framework

NASA Technical Reports Server (NTRS)

Cheung, K. M.; Lee, C. H.

2002-01-01

In this paper we describe the design and architecture of the Mars Network planning and analysis framework that supports generation and validation of efficient planning and scheduling strategy. The goals are to minimize the transmitting time, minimize the delaying time, and/or maximize the network throughputs. The proposed framework would require (1) a client-server architecture to support interactive, batch, WEB, and distributed analysis and planning applications for the relay network analysis scheme, (2) a high-fidelity modeling and simulation environment that expresses link capabilities between spacecraft to spacecraft and spacecraft to Earth stations as time-varying resources, and spacecraft activities, link priority, Solar System dynamic events, the laws of orbital mechanics, and other limiting factors as spacecraft power and thermal constraints, (3) an optimization methodology that casts the resource and constraint models into a standard linear and nonlinear constrained optimization problem that lends itself to commercial off-the-shelf (COTS)planning and scheduling algorithms.

A 1D thermomechanical network transition constitutive model coupled with multiple structural relaxation for shape memory polymers

NASA Astrophysics Data System (ADS)

Zeng, Hao; Xie, Zhimin; Gu, Jianping; Sun, Huiyu

2018-03-01

A new thermomechanical network transition constitutive model is proposed in the study to describe the viscoelastic behavior of shape memory polymers (SMPs). Based on the microstructure of semi-crystalline SMPs, a new simplified transformation equation is proposed to describe the transform of transient networks. And the generalized fractional Maxwell model is introduced in the paper to estimate the temperature-dependent storage modulus. In addition, a neo-KAHR theory with multiple discrete relaxation processes is put forward to study the structural relaxation of the nonlinear thermal strain in cooling/heating processes. The evolution equations of the time- and temperature-dependent stress and strain response are developed. In the model, the thermodynamical and mechanical characteristics of SMPs in the typical thermomechanical cycle are described clearly and the irreversible deformation is studied in detail. Finally, the typical thermomechanical cycles are simulated using the present constitutive model, and the simulation results agree well with the experimental results.

Development and application of artificial neural network models to estimate values of a complex human thermal comfort index associated with urban heat and cool island patterns using air temperature data from a standard meteorological station

NASA Astrophysics Data System (ADS)

Moustris, Konstantinos; Tsiros, Ioannis X.; Tseliou, Areti; Nastos, Panagiotis

2018-04-01

The present study deals with the development and application of artificial neural network models (ANNs) to estimate the values of a complex human thermal comfort-discomfort index associated with urban heat and cool island conditions inside various urban clusters using as only inputs air temperature data from a standard meteorological station. The index used in the study is the Physiologically Equivalent Temperature (PET) index which requires as inputs, among others, air temperature, relative humidity, wind speed, and radiation (short- and long-wave components). For the estimation of PET hourly values, ANN models were developed, appropriately trained, and tested. Model results are compared to values calculated by the PET index based on field monitoring data for various urban clusters (street, square, park, courtyard, and gallery) in the city of Athens (Greece) during an extreme hot weather summer period. For the evaluation of the predictive ability of the developed ANN models, several statistical evaluation indices were applied: the mean bias error, the root mean square error, the index of agreement, the coefficient of determination, the true predictive rate, the false alarm rate, and the Success Index. According to the results, it seems that ANNs present a remarkable ability to estimate hourly PET values within various urban clusters using only hourly values of air temperature. This is very important in cases where the human thermal comfort-discomfort conditions have to be analyzed and the only available parameter is air temperature.

Development and application of artificial neural network models to estimate values of a complex human thermal comfort index associated with urban heat and cool island patterns using air temperature data from a standard meteorological station.

PubMed

Moustris, Konstantinos; Tsiros, Ioannis X; Tseliou, Areti; Nastos, Panagiotis

2018-04-11

The present study deals with the development and application of artificial neural network models (ANNs) to estimate the values of a complex human thermal comfort-discomfort index associated with urban heat and cool island conditions inside various urban clusters using as only inputs air temperature data from a standard meteorological station. The index used in the study is the Physiologically Equivalent Temperature (PET) index which requires as inputs, among others, air temperature, relative humidity, wind speed, and radiation (short- and long-wave components). For the estimation of PET hourly values, ANN models were developed, appropriately trained, and tested. Model results are compared to values calculated by the PET index based on field monitoring data for various urban clusters (street, square, park, courtyard, and gallery) in the city of Athens (Greece) during an extreme hot weather summer period. For the evaluation of the predictive ability of the developed ANN models, several statistical evaluation indices were applied: the mean bias error, the root mean square error, the index of agreement, the coefficient of determination, the true predictive rate, the false alarm rate, and the Success Index. According to the results, it seems that ANNs present a remarkable ability to estimate hourly PET values within various urban clusters using only hourly values of air temperature. This is very important in cases where the human thermal comfort-discomfort conditions have to be analyzed and the only available parameter is air temperature.

Estimation and optimization of thermal performance of evacuated tube solar collector system

NASA Astrophysics Data System (ADS)

Dikmen, Erkan; Ayaz, Mahir; Ezen, H. Hüseyin; Küçüksille, Ecir U.; Şahin, Arzu Şencan

2014-05-01

In this study, artificial neural networks (ANNs) and adaptive neuro-fuzzy (ANFIS) in order to predict the thermal performance of evacuated tube solar collector system have been used. The experimental data for the training and testing of the networks were used. The results of ANN are compared with ANFIS in which the same data sets are used. The R2-value for the thermal performance values of collector is 0.811914 which can be considered as satisfactory. The results obtained when unknown data were presented to the networks are satisfactory and indicate that the proposed method can successfully be used for the prediction of the thermal performance of evacuated tube solar collectors. In addition, new formulations obtained from ANN are presented for the calculation of the thermal performance. The advantages of this approaches compared to the conventional methods are speed, simplicity, and the capacity of the network to learn from examples. In addition, genetic algorithm (GA) was used to maximize the thermal performance of the system. The optimum working conditions of the system were determined by the GA.

Self-diagnostic thermal protection systems for future spacecraft

NASA Astrophysics Data System (ADS)

Hanlon, Alaina B.

The thermal protection system (TPS) represents the greatest risk factor after propulsion for any transatmospheric mission (Dr. Charles Smith, NASA ARC). Any damage to the TPS leaves the space vehicle vulnerable and could result in the loss of human life as happened in the Columbia accident. Aboard the current Space Shuttle Orbiters no system exists to notify the astronauts or ground control if the thermal protection system has been damaged. Through this research, a proof-of-concept monitoring system was developed. The system has two specific applications for thermal protection systems: (1) Improving models used to predict thermal and mechanical response of TPS materials, and (2) Self-diagnosing damage within regions of the TPS and communicating the damage to the appropriate personnel over a potentially unstable network. Mechanical damage is among the most important things to protect the TPS against. Methods to detect the primary types of mechanical damage suffered by thermal protection systems have been developed. Lightweight, low-power sensors were developed to detect any cracks in small regions of a TPS. Implementation of a network of these sensors within 10's to 1000's of regions will eventually provide high spatial resolution of damage detection; allowing for detection of holes in the TPS. Also important in thermal protection material development is to know the ablation rates and time/temperature response of the materials. A new type of sensor has been developed to monitor temperature at different depths within thermal protection materials. The signals being transmitted through the sensors can be multiplexed to allow for mechanical damage and temperature to be monitored using the same sensor.

Optimization of thermal conductivity lightweight brick type AAC (Autoclaved Aerated Concrete) effect of Si & Ca composition by using Artificial Neural Network (ANN)

NASA Astrophysics Data System (ADS)

Zulkifli; Wiryawan, G. P.

2018-03-01

Lightweight brick is the most important component of building construction, therefore it is necessary to have lightweight thermal, mechanical and aqustic thermal properties that meet the standard, in this paper which is discussed is the domain of light brick thermal conductivity properties. The advantage of lightweight brick has a low density (500-650 kg/m3), more economical, can reduce the load 30-40% compared to conventional brick (clay brick). In this research, Artificial Neural Network (ANN) is used to predict the thermal conductivity of lightweight brick type Autoclaved Aerated Concrete (AAC). Based on the training and evaluation that have been done on 10 model of ANN with number of hidden node 1 to 10, obtained that ANN with 3 hidden node have the best performance. It is known from the mean value of MSE (Mean Square Error) validation for three training times of 0.003269. This ANN was further used to predict the thermal conductivity of four light brick samples. The predicted results for each of the AAC1, AAC2, AAC3 and AAC4 light brick samples were 0.243 W/m.K, respectively; 0.29 W/m.K; 0.32 W/m.K; and 0.32 W/m.K. Furthermore, ANN is used to determine the effect of silicon composition (Si), Calcium (Ca), to light brick thermal conductivity. ANN simulation results show that the thermal conductivity increases with increasing Si composition. Si content is allowed maximum of 26.57%, while the Ca content in the range 20.32% - 30.35%.

Complications of stent placement in patients with esophageal cancer: A systematic review and network meta-analysis

PubMed Central

Doosti-Irani, Amin; Mansournia, Mohammad Ali; Rahimi-Foroushani, Abbas; Haddad, Peiman

2017-01-01

Background Palliative treatments and stents are necessary for relieving dysphagia in patients with esophageal cancer. The aim of this study was to simultaneously compare available treatments in terms of complications. Methods Web of Science, Medline, Scopus, Cochrane Library and Embase were searched. Statistical heterogeneity was assessed using the Chi2 test and was quantified by I2. The results of this study were summarized in terms of Risk Ratio (RR). The random effects model was used to report the results. The rank probability for each treatment was calculated using the p-score. Results Out of 17855 references, 24 RCTs reported complications including treatment related death (TRD), bleeding, stent migration, aspiration, severe pain and fistula formation. In the ranking of treatments, thermal ablative therapy (p-score = 0.82), covered Evolution® stent (p-score = 0.70), brachytherapy (p-score = 0.72) and antireflux stent (p-score = 0.74) were better treatments in the network of TRD. Thermal ablative therapy (p-score = 0.86), the conventional stent (p-score = 0.62), covered Evolution® stent (p-score = 0.96) and brachytherapy (p-score = 0.82) were better treatments in the network of bleeding complications. Covered Evolution® (p-score = 0.78), uncovered (p-score = 0.88) and irradiation stents (p-score = 0.65) were better treatments in network of stent migration complications. In the network of severe pain, Conventional self-expandable nitinol alloy covered stent (p-score = 0.73), polyflex (p-score = 0.79), latex prosthesis (p-score = 0.96) and brachytherapy (p-score = 0.65) were better treatments. Conclusion According to our results, thermal ablative therapy, covered Evolution® stents, brachytherapy, and antireflux stents are associated with a lower risk of TRD. Moreover, thermal ablative therapy, conventional, covered Evolution® and brachytherapy had lower risks of bleeding. Overall, fewer complications were associated with covered Evolution® stent and brachytherapy. PMID:28968416

Optimizing Thermal-Elastic Properties of C/C–SiC Composites Using a Hybrid Approach and PSO Algorithm

PubMed Central

Xu, Yingjie; Gao, Tian

2016-01-01

Carbon fiber-reinforced multi-layered pyrocarbon–silicon carbide matrix (C/C–SiC) composites are widely used in aerospace structures. The complicated spatial architecture and material heterogeneity of C/C–SiC composites constitute the challenge for tailoring their properties. Thus, discovering the intrinsic relations between the properties and the microstructures and sequentially optimizing the microstructures to obtain composites with the best performances becomes the key for practical applications. The objective of this work is to optimize the thermal-elastic properties of unidirectional C/C–SiC composites by controlling the multi-layered matrix thicknesses. A hybrid approach based on micromechanical modeling and back propagation (BP) neural network is proposed to predict the thermal-elastic properties of composites. Then, a particle swarm optimization (PSO) algorithm is interfaced with this hybrid model to achieve the optimal design for minimizing the coefficient of thermal expansion (CTE) of composites with the constraint of elastic modulus. Numerical examples demonstrate the effectiveness of the proposed hybrid model and optimization method. PMID:28773343

Quantifying the Influence of Near-Surface Water-Energy Budgets on Soil Thermal Properties Using a Network of Coupled Meteorological and Vadose Zone Instrument Arrays in Indiana, USA

NASA Astrophysics Data System (ADS)

Naylor, S.; Gustin, A. R.; Ellett, K. M.

2012-12-01

Weather stations that collect reliable, sustained meteorological data sets are becoming more widely distributed because of advances in both instrumentation and data server technology. However, sites collecting soil moisture and soil temperature data remain sparse with even fewer locations where complete meteorological data are collected in conjunction with soil data. Thanks to the advent of sensors that collect continuous in-situ thermal properties data for soils, we have gone a step further and incorporated thermal properties measurements as part of hydrologic instrument arrays in central and northern Indiana. The coupled approach provides insights into the variability of soil thermal conductivity and diffusivity attributable to geologic and climatological controls for various hydrogeologic settings. These data are collected to facilitate the optimization of ground-source heat pumps (GSHPs) in the glaciated Midwest by establishing publicly available data that can be used to parameterize system design models. A network of six monitoring sites was developed in Indiana. Sensors that determine thermal conductivity and diffusivity using radial differential temperature measurements around a heating wire were installed at 1.2 meters below ground surface— a typical depth for horizontal GSHP systems. Each site also includes standard meteorological sensors for calculating reference evapotranspiration following the methods by the Food and Agriculture Organization (FAO) of the United Nations. Vadose zone instrumentation includes time domain reflectometry soil-moisture and temperature sensors installed at 0.3-meter depth intervals down to a 1.8-meter depth, in addition to matric potential sensors at 0.15, 0.3, 0.6, and 1.2 meters. Cores collected at 0.3-meter intervals were analyzed in a laboratory for grain size distribution, bulk density, thermal conductivity, and thermal diffusivity. Our work includes developing methods for calibrating thermal properties sensors based on known standards and comparing measurements from transient line heat source devices. Transform equations have been developed to correct in-situ measurements of thermal conductivity and comparing these results with soil moisture data indicates that thermal conductivity can increase by as much as 25 percent during wetting front propagation. Thermal dryout curves have also been modeled based on laboratory conductivity data collected from core samples to verify field measurements, and alternatively, temperature profile data are used to calibrate near-surface temperature gradient models. We compare data collected across various spatial scales to assess the potential for upscaling near-surface thermal regimes based on available soils data. A long-term goal of the monitoring effort is to establish continuous data sets that determine the effect of climate variability on soil thermal properties such that expected ranges in thermal conductivity can be used to determine optimal ground-coupling loop lengths for GSHP systems.

A Steady State and Quasi-Steady Interface Between the Generalized Fluid System Simulation Program and the SINDA/G Thermal Analysis Program

NASA Technical Reports Server (NTRS)

Schallhorn, Paul; Majumdar, Alok; Tiller, Bruce

2001-01-01

A general purpose, one dimensional fluid flow code is currently being interfaced with the thermal analysis program SINDA/G. The flow code, GFSSP, is capable of analyzing steady state and transient flow in a complex network. The flow code is capable of modeling several physical phenomena including compressibility effects, phase changes, body forces (such as gravity and centrifugal) and mixture thermodynamics for multiple species. The addition of GFSSP to SINDA/G provides a significant improvement in convective heat transfer modeling for SINDA/G. The interface development is conducted in multiple phases. This paper describes the first phase of the interface which allows for steady and quasisteady (unsteady solid, steady fluid) conjugate heat transfer modeling.

A simplified, data-constrained approach to estimate the permafrost carbon-climate feedback: The PCN Incubation-Panarctic Thermal (PInc-PanTher) Scaling Approach

NASA Astrophysics Data System (ADS)

Koven, C. D.; Schuur, E.; Schaedel, C.; Bohn, T. J.; Burke, E.; Chen, G.; Chen, X.; Ciais, P.; Grosse, G.; Harden, J. W.; Hayes, D. J.; Hugelius, G.; Jafarov, E. E.; Krinner, G.; Kuhry, P.; Lawrence, D. M.; MacDougall, A.; Marchenko, S. S.; McGuire, A. D.; Natali, S.; Nicolsky, D.; Olefeldt, D.; Peng, S.; Romanovsky, V. E.; Schaefer, K. M.; Strauss, J.; Treat, C. C.; Turetsky, M. R.

2015-12-01

We present an approach to estimate the feedback from large-scale thawing of permafrost soils using a simplified, data-constrained model that combines three elements: soil carbon (C) maps and profiles to identify the distribution and type of C in permafrost soils; incubation experiments to quantify the rates of C lost after thaw; and models of soil thermal dynamics in response to climate warming. We call the approach the Permafrost Carbon Network Incubation-Panarctic Thermal scaling approach (PInc-PanTher). The approach assumes that C stocks do not decompose at all when frozen, but once thawed follow set decomposition trajectories as a function of soil temperature. The trajectories are determined according to a 3-pool decomposition model fitted to incubation data using parameters specific to soil horizon types. We calculate litterfall C inputs required to maintain steady-state C balance for the current climate, and hold those inputs constant. Soil temperatures are taken from the soil thermal modules of ecosystem model simulations forced by a common set of future climate change anomalies under two warming scenarios over the period 2010 to 2100.

Reciprocating air flow for Li-ion battery thermal management to improve temperature uniformity

NASA Astrophysics Data System (ADS)

Mahamud, Rajib; Park, Chanwoo

The thermal management of traction battery systems for electrical-drive vehicles directly affects vehicle dynamic performance, long-term durability and cost of the battery systems. In this paper, a new battery thermal management method using a reciprocating air flow for cylindrical Li-ion (LiMn 2O 4/C) cells was numerically analyzed using (i) a two-dimensional computational fluid dynamics (CFD) model and (ii) a lumped-capacitance thermal model for battery cells and a flow network model. The battery heat generation was approximated by uniform volumetric joule and reversible (entropic) losses. The results of the CFD model were validated with the experimental results of in-line tube-bank systems which approximates the battery cell arrangement considered for this study. The numerical results showed that the reciprocating flow can reduce the cell temperature difference of the battery system by about 4 °C (72% reduction) and the maximum cell temperature by 1.5 °C for a reciprocation period of τ = 120 s as compared with the uni-directional flow case (τ = ∞). Such temperature improvement attributes to the heat redistribution and disturbance of the boundary layers on the formed on the cells due to the periodic flow reversal.

Statistical mechanics of influence maximization with thermal noise

NASA Astrophysics Data System (ADS)

Lynn, Christopher W.; Lee, Daniel D.

2017-03-01

The problem of optimally distributing a budget of influence among individuals in a social network, known as influence maximization, has typically been studied in the context of contagion models and deterministic processes, which fail to capture stochastic interactions inherent in real-world settings. Here, we show that by introducing thermal noise into influence models, the dynamics exactly resemble spins in a heterogeneous Ising system. In this way, influence maximization in the presence of thermal noise has a natural physical interpretation as maximizing the magnetization of an Ising system given a budget of external magnetic field. Using this statistical mechanical formulation, we demonstrate analytically that for small external-field budgets, the optimal influence solutions exhibit a highly non-trivial temperature dependence, focusing on high-degree hub nodes at high temperatures and on easily influenced peripheral nodes at low temperatures. For the general problem, we present a projected gradient ascent algorithm that uses the magnetic susceptibility to calculate locally optimal external-field distributions. We apply our algorithm to synthetic and real-world networks, demonstrating that our analytic results generalize qualitatively. Our work establishes a fruitful connection with statistical mechanics and demonstrates that influence maximization depends crucially on the temperature of the system, a fact that has not been appreciated by existing research.

Simulation of a steady-state integrated human thermal system.

NASA Technical Reports Server (NTRS)

Hsu, F. T.; Fan, L. T.; Hwang, C. L.

1972-01-01

The mathematical model of an integrated human thermal system is formulated. The system consists of an external thermal regulation device on the human body. The purpose of the device (a network of cooling tubes held in contact with the surface of the skin) is to maintain the human body in a state of thermoneutrality. The device is controlled by varying the inlet coolant temperature and coolant mass flow rate. The differential equations of the model are approximated by a set of algebraic equations which result from the application of the explicit forward finite difference method to the differential equations. The integrated human thermal system is simulated for a variety of combinations of the inlet coolant temperature, coolant mass flow rate, and metabolic rates. Two specific cases are considered: (1) the external thermal regulation device is placed only on the head and (2) the devices are placed on the head and the torso. The results of the simulation indicate that when the human body is exposed to hot environment, thermoneutrality can be attained by localized cooling if the operating variables of the external regulation device(s) are properly controlled.

Time-resolved microrheology of actively remodeling actomyosin networks

NASA Astrophysics Data System (ADS)

Silva, Marina Soares e.; Stuhrmann, Björn; Betz, Timo; Koenderink, Gijsje H.

2014-07-01

Living cells constitute an extraordinary state of matter since they are inherently out of thermal equilibrium due to internal metabolic processes. Indeed, measurements of particle motion in the cytoplasm of animal cells have revealed clear signatures of nonthermal fluctuations superposed on passive thermal motion. However, it has been difficult to pinpoint the exact molecular origin of this activity. Here, we employ time-resolved microrheology based on particle tracking to measure nonequilibrium fluctuations produced by myosin motor proteins in a minimal model system composed of purified actin filaments and myosin motors. We show that the motors generate spatially heterogeneous contractile fluctuations, which become less frequent with time as a consequence of motor-driven network remodeling. We analyze the particle tracking data on different length scales, combining particle image velocimetry, an ensemble analysis of the particle trajectories, and finally a kymograph analysis of individual particle trajectories to quantify the length and time scales associated with active particle displacements. All analyses show clear signatures of nonequilibrium activity: the particles exhibit random motion with an enhanced amplitude compared to passive samples, and they exhibit sporadic contractile fluctuations with ballistic motion over large (up to 30 μm) distances. This nonequilibrium activity diminishes with sample age, even though the adenosine triphosphate level is held constant. We propose that network coarsening concentrates motors in large clusters and depletes them from the network, thus reducing the occurrence of contractile fluctuations. Our data provide valuable insight into the physical processes underlying stress generation within motor-driven actin networks and the analysis framework may prove useful for future microrheology studies in cells and model organisms.

Modeling Behavioral Experiment Interaction and Environmental Stimuli for a Synthetic C. elegans.

PubMed

Mujika, Andoni; Leškovský, Peter; Álvarez, Roberto; Otaduy, Miguel A; Epelde, Gorka

2017-01-01

This paper focusses on the simulation of the neural network of the Caenorhabditis elegans living organism, and more specifically in the modeling of the stimuli applied within behavioral experiments and the stimuli that is generated in the interaction of the C. elegans with the environment. To the best of our knowledge, all efforts regarding stimuli modeling for the C. elegans are focused on a single type of stimulus, which is usually tested with a limited subnetwork of the C. elegans neural system. In this paper, we follow a different approach where we model a wide-range of different stimuli, with more flexible neural network configurations and simulations in mind. Moreover, we focus on the stimuli sensation by different types of sensory organs or various sensory principles of the neurons. As part of this work, most common stimuli involved in behavioral assays have been modeled. It includes models for mechanical, thermal, chemical, electrical and light stimuli, and for proprioception-related self-sensed information exchange with the neural network. The developed models have been implemented and tested with the hardware-based Si elegans simulation platform.

Modeling Behavioral Experiment Interaction and Environmental Stimuli for a Synthetic C. elegans

PubMed Central

Mujika, Andoni; Leškovský, Peter; Álvarez, Roberto; Otaduy, Miguel A.; Epelde, Gorka

2017-01-01

This paper focusses on the simulation of the neural network of the Caenorhabditis elegans living organism, and more specifically in the modeling of the stimuli applied within behavioral experiments and the stimuli that is generated in the interaction of the C. elegans with the environment. To the best of our knowledge, all efforts regarding stimuli modeling for the C. elegansare focused on a single type of stimulus, which is usually tested with a limited subnetwork of the C. elegansneural system. In this paper, we follow a different approach where we model a wide-range of different stimuli, with more flexible neural network configurations and simulations in mind. Moreover, we focus on the stimuli sensation by different types of sensory organs or various sensory principles of the neurons. As part of this work, most common stimuli involved in behavioral assays have been modeled. It includes models for mechanical, thermal, chemical, electrical and light stimuli, and for proprioception-related self-sensed information exchange with the neural network. The developed models have been implemented and tested with the hardware-based Si elegans simulation platform. PMID:29276485

Short-term bulk energy storage system scheduling for load leveling in unit commitment: modeling, optimization, and sensitivity analysis

PubMed Central

Hemmati, Reza; Saboori, Hedayat

2016-01-01

Energy storage systems (ESSs) have experienced a very rapid growth in recent years and are expected to be a promising tool in order to improving power system reliability and being economically efficient. The ESSs possess many potential benefits in various areas in the electric power systems. One of the main benefits of an ESS, especially a bulk unit, relies on smoothing the load pattern by decreasing on-peak and increasing off-peak loads, known as load leveling. These devices require new methods and tools in order to model and optimize their effects in the power system studies. In this respect, this paper will model bulk ESSs based on the several technical characteristics, introduce the proposed model in the thermal unit commitment (UC) problem, and analyze it with respect to the various sensitive parameters. The technical limitations of the thermal units and transmission network constraints are also considered in the model. The proposed model is a Mixed Integer Linear Programming (MILP) which can be easily solved by strong commercial solvers (for instance CPLEX) and it is appropriate to be used in the practical large scale networks. The results of implementing the proposed model on a test system reveal that proper load leveling through optimum storage scheduling leads to considerable operation cost reduction with respect to the storage system characteristics. PMID:27222741

Short-term bulk energy storage system scheduling for load leveling in unit commitment: modeling, optimization, and sensitivity analysis.

PubMed

Hemmati, Reza; Saboori, Hedayat

2016-05-01

Energy storage systems (ESSs) have experienced a very rapid growth in recent years and are expected to be a promising tool in order to improving power system reliability and being economically efficient. The ESSs possess many potential benefits in various areas in the electric power systems. One of the main benefits of an ESS, especially a bulk unit, relies on smoothing the load pattern by decreasing on-peak and increasing off-peak loads, known as load leveling. These devices require new methods and tools in order to model and optimize their effects in the power system studies. In this respect, this paper will model bulk ESSs based on the several technical characteristics, introduce the proposed model in the thermal unit commitment (UC) problem, and analyze it with respect to the various sensitive parameters. The technical limitations of the thermal units and transmission network constraints are also considered in the model. The proposed model is a Mixed Integer Linear Programming (MILP) which can be easily solved by strong commercial solvers (for instance CPLEX) and it is appropriate to be used in the practical large scale networks. The results of implementing the proposed model on a test system reveal that proper load leveling through optimum storage scheduling leads to considerable operation cost reduction with respect to the storage system characteristics.

Inverse problem and variation method to optimize cascade heat exchange network in central heating system

NASA Astrophysics Data System (ADS)

Zhang, Yin; Wei, Zhiyuan; Zhang, Yinping; Wang, Xin

2017-12-01

Urban heating in northern China accounts for 40% of total building energy usage. In central heating systems, heat is often transferred from heat source to users by the heat network where several heat exchangers are installed at heat source, substations and terminals respectively. For given overall heating capacity and heat source temperature, increasing the terminal fluid temperature is an effective way to improve the thermal performance of such cascade heat exchange network for energy saving. In this paper, the mathematical optimization model of the cascade heat exchange network with three-stage heat exchangers in series is established. Aim at maximizing the cold fluid temperature for given hot fluid temperature and overall heating capacity, the optimal heat exchange area distribution and the medium fluids' flow rates are determined through inverse problem and variation method. The preliminary results show that the heat exchange areas should be distributed equally for each heat exchanger. It also indicates that in order to improve the thermal performance of the whole system, more heat exchange areas should be allocated to the heat exchanger where flow rate difference between two fluids is relatively small. This work is important for guiding the optimization design of practical cascade heating systems.

Network Capacity Assessment of CHP-based Distributed Generation on Urban Energy Distribution Networks

NASA Astrophysics Data System (ADS)

Zhang, Xianjun

The combined heat and power (CHP)-based distributed generation (DG) or dis-tributed energy resources (DERs) are mature options available in the present energy market, considered to be an effective solution to promote energy efficiency. In the urban environment, the electricity, water and natural gas distribution networks are becoming increasingly interconnected with the growing penetration of the CHP-based DG. Subsequently, this emerging interdependence leads to new topics meriting serious consideration: how much of the CHP-based DG can be accommodated and where to locate these DERs, and given preexisting constraints, how to quantify the mutual impacts on operation performances between these urban energy distribution networks and the CHP-based DG. The early research work was conducted to investigate the feasibility and design methods for one residential microgrid system based on existing electricity, water and gas infrastructures of a residential community, mainly focusing on the economic planning. However, this proposed design method cannot determine the optimal DG sizing and siting for a larger test bed with the given information of energy infrastructures. In this context, a more systematic as well as generalized approach should be developed to solve these problems. In the later study, the model architecture that integrates urban electricity, water and gas distribution networks, and the CHP-based DG system was developed. The proposed approach addressed the challenge of identifying the optimal sizing and siting of the CHP-based DG on these urban energy networks and the mutual impacts on operation performances were also quantified. For this study, the overall objective is to maximize the electrical output and recovered thermal output of the CHP-based DG units. The electricity, gas, and water system models were developed individually and coupled by the developed CHP-based DG system model. The resultant integrated system model is used to constrain the DG's electrical output and recovered thermal output, which are affected by multiple factors and thus analyzed in different case studies. The results indicate that the designed typical gas system is capable of supplying sufficient natural gas for the DG normal operation, while the present water system cannot support the complete recovery of the exhaust heat from the DG units.

Study on Improving Partial Load by Connecting Geo-thermal Heat Pump System to Fuel Cell Network

NASA Astrophysics Data System (ADS)

Obara, Shinya; Kudo, Kazuhiko

Hydrogen piping, the electric power line, and exhaust heat recovery piping of the distributed fuel cells are connected with network, and operational planning is carried out. Reduction of the efficiency in partial load is improved by operation of the geo-thermal heat pump linked to the fuel cell network. The energy demand pattern of the individual houses in Sapporo was introduced. And the analysis method aiming at minimization of the fuel rate by the genetic algorithm was described. The fuel cell network system of an analysis example assumed connecting the fuel cell co-generation of five houses. When geo-thermal heat pump was introduced into fuel cell network system stated in this paper, fuel consumption was reduced 6% rather than the conventional method

Smart thermal networks for smart cities - Introduction of concepts and measures

NASA Astrophysics Data System (ADS)

Schmidt, R. R.; Pol, O.; Basciotti, D.; Page, J.

2012-10-01

In order to contribute to high living standards, climate mitigation and energy supply security, future urban energy systems require a holistic approach. In particular an intelligent integration of thermal networks is necessary. This paper will briefly present the "smart city" concept and introduce an associated definition for smart thermal networks defined on three levels: 1. the interaction with urban planning processes and the interface to the overall urban energy system, 2. the adaptation of the temperature level and 3. supply and demand-side management strategies.

A minimal titration model of the mammalian dynamical heat shock response

NASA Astrophysics Data System (ADS)

Sivéry, Aude; Courtade, Emmanuel; Thommen, Quentin

2016-12-01

Environmental stress, such as oxidative or heat stress, induces the activation of the heat shock response (HSR) and leads to an increase in the heat shock proteins (HSPs) level. These HSPs act as molecular chaperones to maintain cellular proteostasis. Controlled by highly intricate regulatory mechanisms, having stress-induced activation and feedback regulations with multiple partners, the HSR is still incompletely understood. In this context, we propose a minimal molecular model for the gene regulatory network of the HSR that reproduces quantitatively different heat shock experiments both on heat shock factor 1 (HSF1) and HSPs activities. This model, which is based on chemical kinetics laws, is kept with a low dimensionality without altering the biological interpretation of the model dynamics. This simplistic model highlights the titration of HSF1 by chaperones as the guiding line of the network. Moreover, by a steady states analysis of the network, three different temperature stress regimes appear: normal, acute, and chronic, where normal stress corresponds to pseudo thermal adaption. The protein triage that governs the fate of damaged proteins or the different stress regimes are consequences of the titration mechanism. The simplicity of the present model is of interest in order to study detailed modelling of cross regulation between the HSR and other major genetic networks like the cell cycle or the circadian clock.

Big biology meets microclimatology: defining thermal niches of ectotherms at landscape scales for conservation planning.

PubMed

Isaak, Daniel J; Wenger, Seth J; Young, Michael K

2017-04-01

Temperature profoundly affects ecology, a fact ever more evident as the ability to measure thermal environments increases and global changes alter these environments. The spatial structure of thermalscapes is especially relevant to the distribution and abundance of ectothermic organisms, but the ability to describe biothermal relationships at extents and grains relevant to conservation planning has been limited by small or sparse data sets. Here, we combine a large occurrence database of >23 000 aquatic species surveys with stream microclimate scenarios supported by an equally large temperature database for a 149 000-km mountain stream network to describe thermal relationships for 14 fish and amphibian species. Species occurrence probabilities peaked across a wide range of temperatures (7.0-18.8°C) but distinct warm- or cold-edge distribution boundaries were apparent for all species and represented environments where populations may be most sensitive to thermal changes. Warm-edge boundary temperatures for a native species of conservation concern were used with geospatial data sets and a habitat occupancy model to highlight subsets of the network where conservation measures could benefit local populations by maintaining cool temperatures. Linking that strategic approach to local estimates of habitat impairment remains a key challenge but is also an opportunity to build relationships and develop synergies between the research, management, and regulatory communities. As with any data mining or species distribution modeling exercise, care is required in analysis and interpretation of results, but the use of large biological data sets with accurate microclimate scenarios can provide valuable information about the thermal ecology of many ectotherms and a spatially explicit way of guiding conservation investments. © 2017 by the Ecological Society of America.

Impact of fire disturbance on soil thermal and carbon dynamics in Alaskan Tundra and Boreal forest ecosystems

NASA Astrophysics Data System (ADS)

Jiang, Y.; Rastetter, E.; Shaver, G. R.; Rocha, A. V.

2012-12-01

In Alaska, fire disturbance is a major component influencing the soil water and energy balance in both tundra and boreal forest ecosystems. Fire-caused changes in soil environment further affect both above- and below-ground carbon cycles depending on different fire severities. Understanding the effects of fire disturbance on soil thermal change requires implicit modeling work on the post-fire soil thawing and freezing processes. In this study, we model the soil temperature profiles in multiple burned and non-burned sites using a well-developed soil thermal model which fully couples soil water and heat transport. The subsequent change in carbon dynamics is analyzed based on site level observations and simulations from the Multiple Element Limitation (MEL) model. With comparison between burned and non-burned sites, we compare and contrast fire effects on soil thermal and carbon dynamics in continuous permafrost (Anaktuvik fire in north slope), discontinuous permafrost (Erickson Creek fire at Hess Creek) and non-permafrost zone (Delta Junction fire in interior Alaska). Then we check the post-fire recovery of soil temperature profiles at sites with different fire severities in both tundra and boreal forest fire areas. We further project the future changes in soil thermal and carbon dynamics using projected climate data from Scenarios Network for Alaska & Arctic Planning (SNAP). This study provides information to improve the understanding of fire disturbance on soil thermal and carbon dynamics and the consequent response under a warming climate.

A simple node and conductor data generator for SINDA

NASA Technical Reports Server (NTRS)

Gottula, Ronald R.

1992-01-01

This paper presents a simple, automated method to generate NODE and CONDUCTOR DATA for thermal match modes. The method uses personal computer spreadsheets to create SINDA inputs. It was developed in order to make SINDA modeling less time consuming and serves as an alternative to graphical methods. Anyone having some experience using a personal computer can easily implement this process. The user develops spreadsheets to automatically calculate capacitances and conductances based on material properties and dimensional data. The necessary node and conductor information is then taken from the spreadsheets and automatically arranged into the proper format, ready for insertion directly into the SINDA model. This technique provides a number of benefits to the SINDA user such as a reduction in the number of hand calculations, and an ability to very quickly generate a parametric set of NODE and CONDUCTOR DATA blocks. It also provides advantages over graphical thermal modeling systems by retaining the analyst's complete visibility into the thermal network, and by permitting user comments anywhere within the DATA blocks.

Production of Engineered Fabrics Using Artificial Neural Network-Genetic Algorithm Hybrid Model

NASA Astrophysics Data System (ADS)

Mitra, Ashis; Majumdar, Prabal Kumar; Banerjee, Debamalya

2015-10-01

The process of fabric engineering which is generally practised in most of the textile mills is very complicated, repetitive, tedious and time consuming. To eliminate this trial and error approach, a new approach of fabric engineering has been attempted in this work. Data sets of construction parameters [comprising of ends per inch, picks per inch, warp count and weft count] and three fabric properties (namely drape coefficient, air permeability and thermal resistance) of 25 handloom cotton fabrics have been used. The weights and biases of three artificial neural network (ANN) models developed for the prediction of drape coefficient, air permeability and thermal resistance were used to formulate the fitness or objective function and constraints of the optimization problem. The optimization problem was solved using genetic algorithm (GA). In both the fabrics which were attempted for engineering, the target and simulated fabric properties were very close. The GA was able to search the optimum set of fabric construction parameters with reasonably good accuracy except in case of EPI. However, the overall result is encouraging and can be improved further by using larger data sets of handloom fabrics by hybrid ANN-GA model.

The Use of Neural Networks in Identifying Error Sources in Satellite-Derived Tropical SST Estimates

PubMed Central

Lee, Yung-Hsiang; Ho, Chung-Ru; Su, Feng-Chun; Kuo, Nan-Jung; Cheng, Yu-Hsin

2011-01-01

An neural network model of data mining is used to identify error sources in satellite-derived tropical sea surface temperature (SST) estimates from thermal infrared sensors onboard the Geostationary Operational Environmental Satellite (GOES). By using the Back Propagation Network (BPN) algorithm, it is found that air temperature, relative humidity, and wind speed variation are the major factors causing the errors of GOES SST products in the tropical Pacific. The accuracy of SST estimates is also improved by the model. The root mean square error (RMSE) for the daily SST estimate is reduced from 0.58 K to 0.38 K and mean absolute percentage error (MAPE) is 1.03%. For the hourly mean SST estimate, its RMSE is also reduced from 0.66 K to 0.44 K and the MAPE is 1.3%. PMID:22164030

Effect of Liquid-Crystalline Epoxy Backbone Structure on Thermal Conductivity of Epoxy-Alumina Composites

NASA Astrophysics Data System (ADS)

Giang, Thanhkieu; Kim, Jinhwan

2017-01-01

In a series of papers published recently, we clearly demonstrated that the most important factor governing the thermal conductivity of epoxy-Al2O3 composites is the backbone structure of the epoxy. In this study, three more epoxies based on diglycidyl ester-terminated liquid-crystalline epoxy (LCE) have been synthesized to draw conclusions regarding the effect of the epoxy backbone structure on the thermal conductivity of epoxy-alumina composites. The synthesized structures were characterized by proton nuclear magnetic resonance (1H-NMR) and Fourier-transform infrared (FT-IR) spectroscopy. Differential scanning calorimetry, thermogravimetric analysis, and optical microscopy were also employed to examine the thermal and optical properties of the synthesized LCEs and the cured composites. All three LCE resins exhibited typical liquid-crystalline behaviors: clear solid crystalline state below the melting temperature ( T m), sharp crystalline melting at T m, and transition to nematic phase above T m with consequent isotropic phase above the isotropic temperature ( T i). The LCE resins displayed distinct nematic liquid-crystalline phase over a wide temperature range and retained liquid-crystalline phase after curing, with high thermal conductivity of the resulting composite. The thermal conductivity values ranged from 3.09 W/m-K to 3.89 W/m-K for LCE-Al2O3 composites with 50 vol.% filler loading. The steric effect played a governing role in the difference. The neat epoxy resin thermal conductivity was obtained as 0.35 W/m-K to 0.49 W/m-K based on analysis using the Agari-Uno model. The results clearly support the objective of this study in that the thermal conductivity of the LCE-containing networks strongly depended on the epoxy backbone structure and the degree of ordering in the cured network.

Nonlinear force propagation, anisotropic stiffening and non-affine relaxation in a model cytoskeleton

NASA Astrophysics Data System (ADS)

Mizuno, Daisuke; Head, David; Ikebe, Emi; Nakamasu, Akiko; Kinoshita, Suguru; Peijuan, Zhang; Ando, Shoji

2013-03-01

Forces are generated heterogeneously in living cells and transmitted through cytoskeletal networks that respond highly non-linearly. Here, we carry out high-bandwidth passive microrheology on vimentin networks reconstituted in vitro, and observe the nonlinear mechanical response due to forces propagating from a local source applied by an optical tweezer. Since the applied force is constant, the gel becomes equilibrated and the fluctuation-dissipation theorem can be employed to deduce the viscoelasticity of the local environment from the thermal fluctuations of colloidal probes. Our experiments unequivocally demonstrate the anisotropic stiffening of the cytoskeletal network behind the applied force, with greater stiffening in the parallel direction. Quantitative agreement with an affine continuum model is obtained, but only for the response at certain frequency ~ 10-1000 Hz which separates the high-frequency power law and low-frequency elastic behavior of the network. We argue that the failure of the model at lower frequencies is due to the presence of non-affinity, and observe that zero-frequency changes in particle separation can be fitted when an independently-measured, empirical nonaffinity factor is applied.

THMC Modeling of EGS Reservoirs -- Continuum through Discontinuum Representations. Capturing Reservoir Stimulation, Evolution and Induced Seismicity

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

Elsworth, Derek; Izadi, Ghazal; Gan, Quan

This work has investigated the roles of effective stress induced by changes in fluid pressure, temperature and chemistry in contributing to the evolution of permeability and induced seismicity in geothermal reservoirs. This work has developed continuum models [1] to represent the progress or seismicity during both stimulation [2] and production [3]. These methods have been used to resolve anomalous observations of induced seismicity at the Newberry Volcano demonstration project [4] through the application of modeling and experimentation. Later work then focuses on the occurrence of late stage seismicity induced by thermal stresses [5] including the codifying of the timing andmore » severity of such responses [6]. Furthermore, mechanistic linkages between observed seismicity and the evolution of permeability have been developed using data from the Newberry project [7] and benchmarked against field injection experiments. Finally, discontinuum models [8] incorporating the roles of discrete fracture networks have been applied to represent stimulation and then thermal recovery for new arrangements of geothermal wells incorporating the development of flow manifolds [9] in order to increase thermal output and longevity in EGS systems.« less

Thermal mapping as a valuable tool for road weather forecast and winter road maintenance: an example from the Italian Alps

NASA Astrophysics Data System (ADS)

Todeschini, Ilaria; Di Napoli, Claudia; Pretto, Ilaria; Merler, Giacomo; Cavaliere, Roberto; Apolloni, Roberto; Antonacci, Gianluca; Piazza, Andrea; Benedetti, Guido

2016-08-01

During the winter period ice is likely to form on roads, making pavement surfaces slippery and increasing accident risk. Road surface temperature (RST) is one of the most important parameters in ice formation. The LIFE+ "CLEANROADS" project aims to forecast RSTs in advance in order to support road maintenance services in the timely and effective preparation of preventive anti-icing measures. This support is provided through a novel MDSS (Maintenance Decision Support System). The final goal of the project is to quantitatively demonstrate that the implemented MDSS is capable to minimize the consumption of chemical anti-icing reagents (e.g. sodium chloride) and the associated environmental (water and air) impact while maintaining the current high levels of road safety. In the CLEAN-ROADS system RSTs have been forecast by applying the numerical model METRo (Model of the Environment and Temperature of Roads) to a network of RWIS (Road Weather Information System) stations installed on a test route in the Adige Valley (Italy). This forecast is however local and does not take into account typical peculiarities along road network, such as the presence of road sections that are particularly prone to ice formation. Thermal mapping, i.e. the acquisition of mobile RST measurements through infrared thermometry, permits to (i) identify and map those sections, and (ii) extend the forecast from a RWIS station to adjacent areas. The processing of thermal mapping signals is however challenging because of random variations in the road surface emissivity. To overcome this we have acquired several thermal mapping traces along the test route during winter seasons 2014-2015 and 2015-2016. We have then defined a "characteristic" thermal fingerprint as a function of all its historical thermal mapping signals, and used it to spatialize local METRo forecasts. Preliminary results suggest the high potential of such a technique for winter road applications.

Envisioning, quantifying, and managing thermal regimes on river networks

USGS Publications Warehouse

Steel, E. Ashley; Beechie, Timothy J.; Torgersen, Christian E.; Fullerton, Aimee H.

2017-01-01

Water temperatures fluctuate in time and space, creating diverse thermal regimes on river networks. Temporal variability in these thermal landscapes has important biological and ecological consequences because of nonlinearities in physiological reactions; spatial diversity in thermal landscapes provides aquatic organisms with options to maximize growth and survival. However, human activities and climate change threaten to alter the dynamics of riverine thermal regimes. New data and tools can identify particular facets of the thermal landscape that describe ecological and management concerns and that are linked to human actions. The emerging complexity of thermal landscapes demands innovations in communication, opens the door to exciting research opportunities on the human impacts to and biological consequences of thermal variability, suggests improvements in monitoring programs to better capture empirical patterns, provides a framework for suites of actions to restore and protect the natural processes that drive thermal complexity, and indicates opportunities for better managing thermal landscapes.

A new approach for categorizing pig lying behaviour based on a Delaunay triangulation method.

PubMed

Nasirahmadi, A; Hensel, O; Edwards, S A; Sturm, B

2017-01-01

Machine vision-based monitoring of pig lying behaviour is a fast and non-intrusive approach that could be used to improve animal health and welfare. Four pens with 22 pigs in each were selected at a commercial pig farm and monitored for 15 days using top view cameras. Three thermal categories were selected relative to room setpoint temperature. An image processing technique based on Delaunay triangulation (DT) was utilized. Different lying patterns (close, normal and far) were defined regarding the perimeter of each DT triangle and the percentages of each lying pattern were obtained in each thermal category. A method using a multilayer perceptron (MLP) neural network, to automatically classify group lying behaviour of pigs into three thermal categories, was developed and tested for its feasibility. The DT features (mean value of perimeters, maximum and minimum length of sides of triangles) were calculated as inputs for the MLP classifier. The network was trained, validated and tested and the results revealed that MLP could classify lying features into the three thermal categories with high overall accuracy (95.6%). The technique indicates that a combination of image processing, MLP classification and mathematical modelling can be used as a precise method for quantifying pig lying behaviour in welfare investigations.

Estimating Top-of-Atmosphere Thermal Infrared Radiance Using MERRA-2 Atmospheric Data

NASA Astrophysics Data System (ADS)

Kleynhans, Tania

Space borne thermal infrared sensors have been extensively used for environmental research as well as cross-calibration of other thermal sensing systems. Thermal infrared data from satellites such as Landsat and Terra/MODIS have limited temporal resolution (with a repeat cycle of 1 to 2 days for Terra/MODIS, and 16 days for Landsat). Thermal instruments with finer temporal resolution on geostationary satellites have limited utility for cross-calibration due to their large view angles. Reanalysis atmospheric data is available on a global spatial grid at three hour intervals making it a potential alternative to existing satellite image data. This research explores using the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis data product to predict top-of-atmosphere (TOA) thermal infrared radiance globally at time scales finer than available satellite data. The MERRA-2 data product provides global atmospheric data every three hours from 1980 to the present. Due to the high temporal resolution of the MERRA-2 data product, opportunities for novel research and applications are presented. While MERRA-2 has been used in renewable energy and hydrological studies, this work seeks to leverage the model to predict TOA thermal radiance. Two approaches have been followed, namely physics-based approach and a supervised learning approach, using Terra/MODIS band 31 thermal infrared data as reference. The first physics-based model uses forward modeling to predict TOA thermal radiance. The second model infers the presence of clouds from the MERRA-2 atmospheric data, before applying an atmospheric radiative transfer model. The last physics-based model parameterized the previous model to minimize computation time. The second approach applied four different supervised learning algorithms to the atmospheric data. The algorithms included a linear least squares regression model, a non-linear support vector regression (SVR) model, a multi-layer perceptron (MLP), and a convolutional neural network (CNN). This research found that the multi-layer perceptron model produced the lowest error rates overall, with an RMSE of 1.22W / m2 sr mum when compared to actual Terra/MODIS band 31 image data. This research further aimed to characterize the errors associated with each method so that any potential user will have the best information available should they wish to apply these methods towards their own application.

Neural Network Model for Thermal Inactivation of Salmonella Typhimurium to Elimination in Ground Chicken: Acquisition of Data by Whole Sample Enrichment, Miniature Most-Probable-Number Method.

PubMed

Oscar, T P

2017-01-01

Predictive models are valuable tools for assessing food safety. Existing thermal inactivation models for Salmonella and ground chicken do not provide predictions above 71°C, which is below the recommended final cooked temperature of 73.9°C for chicken. They also do not predict when all Salmonella are eliminated without extrapolating beyond the data used to develop them. Thus, a study was undertaken to develop a model for thermal inactivation of Salmonella to elimination in ground chicken at temperatures above those of existing models. Ground chicken thigh portions (0.76 cm 3 ) in microcentrifuge tubes were inoculated with 4.45 ± 0.25 log most probable number (MPN) of a single strain of Salmonella Typhimurium (chicken isolate). They were cooked at 50 to 100°C in 2 or 2.5°C increments in a heating block that simulated two-sided pan frying. A whole sample enrichment, miniature MPN (WSE-mMPN) method was used for enumeration. The lower limit of detection was one Salmonella cell per portion. MPN data were used to develop a multiple-layer feedforward neural network model. Model performance was evaluated using the acceptable prediction zone (APZ) method. The proportion of residuals in an APZ (pAPZ) from -1 log (fail-safe) to 0.5 log (fail-dangerous) was 0.911 (379 of 416) for dependent data and 0.910 (162 of 178) for independent data for interpolation. A pAPZ ≥0.7 indicated that model predictions had acceptable bias and accuracy. There were no local prediction problems because pAPZ for individual thermal inactivation curves ranged from 0.813 to 1.000. Independent data for interpolation satisfied the test data criteria of the APZ method. Thus, the model was successfully validated. Predicted times for a 1-log reduction ranged from 9.6 min at 56°C to 0.71 min at 100°C. Predicted times for elimination ranged from 8.6 min at 60°C to 1.4 min at 100°C. The model will be a valuable new tool for predicting and managing this important risk to public health.

Self-constructed tree-shape high thermal conductivity nanosilver networks in epoxy.

PubMed

Pashayi, Kamyar; Fard, Hafez Raeisi; Lai, Fengyuan; Iruvanti, Sushumna; Plawsky, Joel; Borca-Tasciuc, Theodorian

2014-04-21

We report the formation of high aspect ratio nanoscale tree-shape silver networks in epoxy, at low temperatures (<150 °C) and atmospheric pressures, that are correlated to a ∼200 fold enhancement of thermal conductivity (κ) of the nanocomposite compared to the polymer matrix. The networks form through a three-step process comprising of self-assembly by diffusion limited aggregation of polyvinylpyrrolidone (PVP) coated nanoparticles, removal of PVP coating from the surface, and sintering of silver nanoparticles in high aspect ratio networked structures. Controlling self-assembly and sintering by carefully designed multistep temperature and time processing leads to κ of our silver nanocomposites that are up to 300% of the present state of the art polymer nanocomposites at similar volume fractions. Our investigation of the κ enhancements enabled by tree-shaped network nanocomposites provides a basis for the development of new polymer nanocomposites for thermal transport and storage applications.

Development of concepts for the management of thermal resources in urban areas - Assessment of transferability from the Basel (Switzerland) and Zaragoza (Spain) case studies

NASA Astrophysics Data System (ADS)

Epting, Jannis; García-Gil, Alejandro; Huggenberger, Peter; Vázquez-Suñe, Enric; Mueller, Matthias H.

2017-05-01

The shallow subsurface in urban areas is increasingly used by shallow geothermal energy systems as a renewable energy resource and as a cheap cooling medium, e.g. for building air conditioning. In combination with further anthropogenic activities, this results in altered thermal regimes in the subsurface and the so-called subsurface urban heat island effect. Successful thermal management of urban groundwater resources requires understanding the relative contributions of the different thermal parameters and boundary conditions that result in the "present thermal state" of individual urban groundwater bodies. To evaluate the "present thermal state" of urban groundwater bodies, good quality data are required to characterize the hydraulic and thermal aquifer parameters. This process also involved adequate monitoring systems which provide consistent subsurface temperature measurements and are the basis for parameterizing numerical heat-transport models. This study is based on previous work already published for two urban groundwater bodies in Basel (CH) and Zaragoza (ES), where comprehensive monitoring networks (hydraulics and temperature) as well as calibrated high-resolution numerical flow- and heat-transport models have been analyzed. The "present thermal state" and how it developed according to the different hydraulic and thermal boundary conditions is compared to a "potential natural state" in order to assess the anthropogenic thermal changes that have already occurred in the urban groundwater bodies we investigated. This comparison allows us to describe the various processes concerning groundwater flow and thermal regimes for the different urban settings. Furthermore, the results facilitate defining goals for specific aquifer regions, including future aquifer use and urbanization, as well as evaluating the thermal use potential for these regions. As one example for a more sustainable thermal use of subsurface water resources, we introduce the thermal management concept of the "relaxation factor", which is a first approach to overcome the present policy of "first come, first served". Remediation measures to regenerate overheated urban aquifers are also introduced. The transferability of the applied methods to other urban areas is discussed. It is shown that an appropriate selection of locations for monitoring hydraulic and thermal boundary conditions make it possible to implement representative interpretations of groundwater flow and thermal regimes as well as to set up high-resolution numerical flow- and heat-transport models. Those models are the basis for the sustainable management of thermal resources.

Indomethacin uptake into poly(2-hydroxyethyl methacrylate-co-3,9-divinyl-2,4,8,10-tetraoxaspiro [5.5]-undecane) network: In vitro and in vivo controlled release study.

PubMed

Nita, Loredana E; Chiriac, Aurica P; Nistor, Manuela T; Tartau, Liliana

2012-04-15

Networks based on poly(2-hydroxyethyl methacrylate-co-3,9-divinyl-2,4,8,10-tetraoxaspiro [5.5]-undecane), synthesized through radical dispersion polymerization, were used as template for indomethacin (INN) as model drug. The copolymers were characterized by swelling studies at three pH values (2.4, 5.5 and 7.4) and two temperatures (room temperature 24 °C and physiological temperature 37 °C). Fourier transform infrared (FTIR) spectroscopic analysis was used to sustain the copolymer structures. Scanning electron microscopy (SEM) and thermogravimetric (TG) investigations were used to examine microstructure and appreciate the thermal stability of the polymer samples. The studies of the INN drug release from the copolymer networks were in vitro performed. The in vivo study results (biocompatibility tests, somatic nociceptive experimental model (tail flick test) and visceral nociceptive experimental model (writhing test)) are also reported in this paper. Copyright © 2012 Elsevier B.V. All rights reserved.

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

Optical and mechanical behaviors of glassy silicone networks derived from linear siloxane precursors

NASA Astrophysics Data System (ADS)

Jang, Heejun; Seo, Wooram; Kim, Hyungsun; Lee, Yoonjoo; Kim, Younghee

2016-01-01

Silicon-based inorganic polymers are promising materials as matrix materials for glass fiber composites because of their good process ability, transparency, and thermal property. In this study, for utilization as a matrix precursor for a glass-fiber-reinforced composite, glassy silicone networks were prepared via hydrosilylation of linear/pendant Si-H polysiloxanes and the C=C bonds of viny-lterminated linear/cyclic polysiloxanes. 13C nuclear magnetic resonance spectroscopy was used to determine the structure of the cross-linked states, and a thermal analysis was performed. To assess the mechanical properties of the glassy silicone networks, we performed nanoindentation and 4-point bending tests. Cross-linked networks derived from siloxane polymers are thermally and optically more stable at high temperatures. Different cross-linking agents led to final networks with different properties due to differences in the molecular weights and structures. After stepped postcuring, the Young's modulus and the hardness of the glassy silicone networks increased; however, the brittleness also increased. The characteristics of the cross-linking agent played an important role in the functional glassy silicone networks.

Comprehensive 3D-elastohydrodynamic simulation of hermetic compressor crank drive

NASA Astrophysics Data System (ADS)

Posch, S.; Hopfgartner, J.; Berger, E.; Zuber, B.; Almbauer, R.; Schöllauf, P.

2017-08-01

Mechanical, electrical and thermodynamic losses form the major loss mechanisms of hermetic compressors for refrigeration application. The present work deals with the investigation of the mechanical losses of a hermetic compressor crank drive. Focus is on 3d-elastohydrodynamic (EHD) modelling of the journal bearings, piston-liner contact and piston secondary motion in combination with multi-body and structural dynamics of the crank drive elements. A detailed description of the model development within the commercial software AVL EXCITE Power Unit is given in the work. The model is used to create a comprehensive analysis of the mechanical losses of a hermetic compressor. Further on, a parametric study concerning oil viscosity and compressor speed is carried out which shows the possibilities of the usage of the model in the development process of hermetic compressors for refrigeration application. Additionally, the usage of the results in an overall thermal network for the determination of the thermal compressor behaviour is discussed.

Simulating the effect of climate change on stream temperature in the Trout Lake Watershed, Wisconsin

USGS Publications Warehouse

Selbig, William R.

2015-01-01

The potential for increases in stream temperature across many spatial and temporal scales as a result of climate change can pose a difficult challenge for environmental managers, especially when addressing thermal requirements for sensitive aquatic species. This study evaluates simulated changes to the thermal regime of three northern Wisconsin streams in response to a projected changing climate using a modeling framework and considers implications of thermal stresses to the fish community. The Stream Network Temperature Model (SNTEMP) was used in combination with a coupled groundwater and surface water flow model to assess forecasts in climate from six global circulation models and three emission scenarios. Model results suggest that annual average stream temperature will steadily increase approximately 1.1 to 3.2 °C (varying by stream) by the year 2100 with differences in magnitude between emission scenarios. Daily mean stream temperature during the months of July and August, a period when cold-water fish communities are most sensitive, showed excursions from optimal temperatures with increased frequency compared to current conditions. Projections of daily mean stream temperature, in some cases, were no longer in the range necessary to sustain a cold water fishery.

A novel multiphysic model for simulation of swelling equilibrium of ionized thermal-stimulus responsive hydrogels

NASA Astrophysics Data System (ADS)

Li, Hua; Wang, Xiaogui; Yan, Guoping; Lam, K. Y.; Cheng, Sixue; Zou, Tao; Zhuo, Renxi

2005-03-01

In this paper, a novel multiphysic mathematical model is developed for simulation of swelling equilibrium of ionized temperature sensitive hydrogels with the volume phase transition, and it is termed the multi-effect-coupling thermal-stimulus (MECtherm) model. This model consists of the steady-state Nernst-Planck equation, Poisson equation and swelling equilibrium governing equation based on the Flory's mean field theory, in which two types of polymer-solvent interaction parameters, as the functions of temperature and polymer-network volume fraction, are specified with or without consideration of the hydrogen bond interaction. In order to examine the MECtherm model consisting of nonlinear partial differential equations, a meshless Hermite-Cloud method is used for numerical solution of one-dimensional swelling equilibrium of thermal-stimulus responsive hydrogels immersed in a bathing solution. The computed results are in very good agreements with experimental data for the variation of volume swelling ratio with temperature. The influences of the salt concentration and initial fixed-charge density are discussed in detail on the variations of volume swelling ratio of hydrogels, mobile ion concentrations and electric potential of both interior hydrogels and exterior bathing solution.

Simulating the effect of climate change on stream temperature in the Trout Lake Watershed, Wisconsin.

PubMed

Selbig, William R

2015-07-15

The potential for increases in stream temperature across many spatial and temporal scales as a result of climate change can pose a difficult challenge for environmental managers, especially when addressing thermal requirements for sensitive aquatic species. This study evaluates simulated changes to the thermal regime of three northern Wisconsin streams in response to a projected changing climate using a modeling framework and considers implications of thermal stresses to the fish community. The Stream Network Temperature Model (SNTEMP) was used in combination with a coupled groundwater and surface water flow model to assess forecasts in climate from six global circulation models and three emission scenarios. Model results suggest that annual average stream temperature will steadily increase approximately 1.1 to 3.2°C (varying by stream) by the year 2100 with differences in magnitude between emission scenarios. Daily mean stream temperature during the months of July and August, a period when cold-water fish communities are most sensitive, showed excursions from optimal temperatures with increased frequency compared to current conditions. Projections of daily mean stream temperature, in some cases, were no longer in the range necessary to sustain a cold water fishery. Published by Elsevier B.V.

Application of artificial neural networks to thermal detection of disbonds

NASA Technical Reports Server (NTRS)

Prabhu, D. R.; Howell, P. A.; Syed, H. I.; Winfree, W. P.

1992-01-01

A novel technique for processing thermal data is presented and applied to simulation as well as experimental data. Using a neural network of thermal data classification, good classification accuracies are obtained, and the resulting images exhibit very good contrast between bonded and disbonded locations. In order to minimize the preprocessing required before using the network of classification, the temperature values were directly employed to train a network using data from an on-site testing run of a commercial aircraft. Training was extremely fast, and the resulting classification also agreed reasonably well with an ultrasonic characterization of the panel. The results obtained using one sample show the partially disbonded vertical doubler. The vertical lines along the doubler correspond to the original extent of the doubler obtained using blueprints of the aircraft.

Development of multilayer perceptron networks for isothermal time temperature transformation prediction of U-Mo-X alloys

NASA Astrophysics Data System (ADS)

Johns, Jesse M.; Burkes, Douglas

2017-07-01

In this work, a multilayered perceptron (MLP) network is used to develop predictive isothermal time-temperature-transformation (TTT) models covering a range of U-Mo binary and ternary alloys. The selected ternary alloys for model development are U-Mo-Ru, U-Mo-Nb, U-Mo-Zr, U-Mo-Cr, and U-Mo-Re. These model's ability to predict 'novel' U-Mo alloys is shown quite well despite the discrepancies between literature sources for similar alloys which likely arise from different thermal-mechanical processing conditions. These models are developed with the primary purpose of informing experimental decisions. Additional experimental insight is necessary in order to reduce the number of experiments required to isolate ideal alloys. These models allow test planners to evaluate areas of experimental interest; once initial tests are conducted, the model can be updated and further improve follow-on testing decisions. The model also improves analysis capabilities by reducing the number of data points necessary from any particular test. For example, if one or two isotherms are measured during a test, the model can construct the rest of the TTT curve over a wide range of temperature and time. This modeling capability reduces the cost of experiments while also improving the value of the results from the tests. The reduced costs could result in improved material characterization and therefore improved fundamental understanding of TTT dynamics. As additional understanding of phenomena driving TTTs is acquired, this type of MLP model can be used to populate unknowns (such as material impurity and other thermal mechanical properties) from past literature sources.

Correlation Function Approach for Estimating Thermal Conductivity in Highly Porous Fibrous Materials

NASA Technical Reports Server (NTRS)

Martinez-Garcia, Jorge; Braginsky, Leonid; Shklover, Valery; Lawson, John W.

2011-01-01

Heat transport in highly porous fiber networks is analyzed via two-point correlation functions. Fibers are assumed to be long and thin to allow a large number of crossing points per fiber. The network is characterized by three parameters: the fiber aspect ratio, the porosity and the anisotropy of the structure. We show that the effective thermal conductivity of the system can be estimated from knowledge of the porosity and the correlation lengths of the correlation functions obtained from a fiber structure image. As an application, the effects of the fiber aspect ratio and the network anisotropy on the thermal conductivity is studied.

Simulated juvenile salmon growth and phenology respond to altered thermal regimes and stream network shape

EPA Science Inventory

Context. Thermally diverse habitats may afford fish protection from climate change by providing opportunities to behaviorally optimize growing conditions. However, it is unclear what role the spatial properties of river networks will play in determining risk. Objectives. We hypot...

Charge transport in nanoscale "all-inorganic" networks of semiconductor nanorods linked by metal domains.

PubMed

Lavieville, Romain; Zhang, Yang; Casu, Alberto; Genovese, Alessandro; Manna, Liberato; Di Fabrizio, Enzo; Krahne, Roman

2012-04-24

Charge transport across metal-semiconductor interfaces at the nanoscale is a crucial issue in nanoelectronics. Chains of semiconductor nanorods linked by Au particles represent an ideal model system in this respect, because the metal-semiconductor interface is an intrinsic feature of the nanosystem and does not manifest solely as the contact to the macroscopic external electrodes. Here we investigate charge transport mechanisms in all-inorganic hybrid metal-semiconductor networks fabricated via self-assembly in solution, in which CdSe nanorods were linked to each other by Au nanoparticles. Thermal annealing of our devices changed the morphology of the networks and resulted in the removal of small Au domains that were present on the lateral nanorod facets, and in ripening of the Au nanoparticles in the nanorod junctions with more homogeneous metal-semiconductor interfaces. In such thermally annealed devices the voltage dependence of the current at room temperature can be well described by a Schottky barrier lowering at a metal semiconductor contact under reverse bias, if the spherical shape of the gold nanoparticles is considered. In this case the natural logarithm of the current does not follow the square-root dependence of the voltage as in the bulk, but that of V(2/3). From our fitting with this model we extract the effective permittivity that agrees well with theoretical predictions for the permittivity near the surface of CdSe nanorods. Furthermore, the annealing improved the network conductance at cryogenic temperatures, which could be related to the reduction of the number of trap states.

The contribution of geology and groundwater studies to city-scale ground heat network strategies: A case study from Cardiff, UK

NASA Astrophysics Data System (ADS)

Boon, David; Farr, Gareth; Patton, Ashley; Kendall, Rhian; James, Laura; Abesser, Corinna; Busby, Jonathan; Schofield, David; White, Debbie; Gooddy, Daren; James, David; Williams, Bernie; Tucker, David; Knowles, Steve; Harcombe, Gareth

2016-04-01

The development of integrated heat network strategies involving exploitation of the shallow subsurface requires knowledge of ground conditions at the feasibility stage, and throughout the life of the system. We describe an approach to the assessment of ground constraints and energy opportunities in data-rich urban areas. Geological and hydrogeological investigations have formed a core component of the strategy development for sustainable thermal use of the subsurface in Cardiff, UK. We present findings from a 12 month project titled 'Ground Heat Network at a City Scale', which was co-funded by NERC/BGS and the UK Government through the InnovateUK Energy Catalyst grant in 2015-16. The project examined the technical feasibility of extracting low grade waste heat from a shallow gravel aquifer using a cluster of open loop ground source heat pumps. Heat demand mapping was carried out separately. The ground condition assessment approach involved the following steps: (1) city-wide baseline groundwater temperature mapping in 2014 with seasonal monitoring for at least 12 months prior to heat pump installation (Patton et al 2015); (2) desk top and field-based investigation of the aquifer system to determine groundwater levels, likely flow directions, sustainable pumping yields, water chemistry, and boundary conditions; (3) creation of a 3D geological framework model with physical property testing and model attribution; (4) use steps 1-3 to develop conceptual ground models and production of maps and GIS data layers to support scenario planning, and initial heat network concept designs; (5) heat flow modelling in FEFLOW software to analyse sustainability and predict potential thermal breakthrough in higher risk areas; (6) installation of a shallow open loop GSHP research observatory with real-time monitoring of groundwater bodies to provide data for heat flow model validation and feedback for system control. In conclusion, early ground condition modelling and subsurface monitoring have provided an initial indication of ground constraints and opportunities supporting development of aquifer thermal energy systems in Cardiff. Ground models should consider the past and future anthropogenic processes that influence and modify the condition of the ground. These include heat losses from buildings, modification of the groundwater regime by artificial pumping, sewers, and other GSH schemes, and construction hazards such as buried infrastructure, old foundations, land contamination and un-exploded ordnance. This knowledge base forms the foundation for a 'whole life' approach for sustainable thermal use of the subsurface. Benefits of the approach include; timely and easy to understand information for land use and financial resource planning, reduced financial risk for developers and investors, clear evidence to help improve public perception of GSHP technology, and provision of independent environmental data to satisfy the needs of the regulator. References: Patton, A.M., Farr, G.J., Boon, D.P., James, D.R., Williams, B., Newell, A.J. 2015. Shallow Groundwater Temperatures and the Urban Heat Island Effect: the First U.K City-wide Geothermal Map to Support Development of Ground Source Heating Systems Strategy. Geophysical Research Abstracts. EGU 2015 Vienna, Austria. (Poster)

Catchment controls on water temperature and the development of simple metrics to inform riparian zone management

NASA Astrophysics Data System (ADS)

Johnson, Matthew; Wilby, Robert

2015-04-01

Water temperature is a key water quality parameter and is critical to aquatic life Therefore, rising temperatures due to climate and environmental change will have major consequences for river biota. As such, it is important to understand the environmental controls of the thermal regime of rivers. The Loughborough University TEmperature Network (LUTEN) consists of a distributed network of 25 sites along 40 km of two rivers in the English Peak District, from their source to confluence. As a result, the network covers a range of hydrological, sedimentary, geomorphic and land-use conditions. At each site, air and water temperature have been recorded at a 15-minute resolution for over 4 years. Water temperature is spatially patchy and temporally variable in the monitored rivers. For example, the annual temperature range at Beresford Dale is over 18° C, whereas 8 km downstream it is less than 8° C. This heterogeneity leads to some sites being more vulnerable to future warming than others. The sensitivity of sites to climate was quantified by comparing the parameters of logistic regression models, constructed at each site, that relate water temperature to air temperature. These analyses, coupled with catchment modelling suggest that reaches that are surface-water dominated with minimal shade and relatively low water volumes are most susceptible to warming. Such reaches tended to occur at intermediate distances from rivers source in the monitored catchments. Reaches that were groundwater dominated had relatively stable thermal regimes, which were relatively unaffected by inter-annual changes in climatic conditions. Such areas could provide important thermal refuge to many organisms, which is supported by monitoring of the invertebrate community in the catchment. The phenology (i.e. timing of life events) of some species remained consistent between years in a river reach with a stable thermal regime, but changed markedly in other areas of the river. Consequently, areas of thermal refuge could be important in the context of future climate change, potentially maintaining populations of animals excluded from other parts of the river during hot summer months. International management strategies to mitigate rising temperatures tend to focus on the protection, enhancement or creation of riparian shade. Simple metrics derived from catchment landscape models, the heat capacity of water, and modelled solar radiation receipt, suggest that approximately 1 km of deep riparian shading is necessary to offset a 1° C rise in temperature in the monitored catchments. A similar value is likely to be obtained for similar sized rivers at similar latitudes. Trees would take 20 years to attain sufficient height to shade the necessary solar angles. However, 1 km of deep riparian shade will have substantial impacts on the hydrological and geomorphological functioning of the river, beyond simply altering the thermal regime. Consequently, successful management of rising water temperature in rivers will require catchment scale consideration, as part of an integrated management plan.

Adaptiveness in monotone pseudo-Boolean optimization and stochastic neural computation.

PubMed

Grossi, Giuliano

2009-08-01

Hopfield neural network (HNN) is a nonlinear computational model successfully applied in finding near-optimal solutions of several difficult combinatorial problems. In many cases, the network energy function is obtained through a learning procedure so that its minima are states falling into a proper subspace (feasible region) of the search space. However, because of the network nonlinearity, a number of undesirable local energy minima emerge from the learning procedure, significantly effecting the network performance. In the neural model analyzed here, we combine both a penalty and a stochastic process in order to enhance the performance of a binary HNN. The penalty strategy allows us to gradually lead the search towards states representing feasible solutions, so avoiding oscillatory behaviors or asymptotically instable convergence. Presence of stochastic dynamics potentially prevents the network to fall into shallow local minima of the energy function, i.e., quite far from global optimum. Hence, for a given fixed network topology, the desired final distribution on the states can be reached by carefully modulating such process. The model uses pseudo-Boolean functions both to express problem constraints and cost function; a combination of these two functions is then interpreted as energy of the neural network. A wide variety of NP-hard problems fall in the class of problems that can be solved by the model at hand, particularly those having a monotonic quadratic pseudo-Boolean function as constraint function. That is, functions easily derived by closed algebraic expressions representing the constraint structure and easy (polynomial time) to maximize. We show the asymptotic convergence properties of this model characterizing its state space distribution at thermal equilibrium in terms of Markov chain and give evidence of its ability to find high quality solutions on benchmarks and randomly generated instances of two specific problems taken from the computational graph theory.

Improved detection of highly energetic materials traces on surfaces by standoff laser-induced thermal emission incorporating neural networks

NASA Astrophysics Data System (ADS)

Figueroa-Navedo, Amanda; Galán-Freyle, Nataly Y.; Pacheco-Londoño, Leonardo C.; Hernández-Rivera, Samuel P.

2013-05-01

Terrorists conceal highly energetic materials (HEM) as Improvised Explosive Devices (IED) in various types of materials such as PVC, wood, Teflon, aluminum, acrylic, carton and rubber to disguise them from detection equipment used by military and security agency personnel. Infrared emissions (IREs) of substrates, with and without HEM, were measured to generate models for detection and discrimination. Multivariable analysis techniques such as principal component analysis (PCA), soft independent modeling by class analogy (SIMCA), partial least squares-discriminant analysis (PLS-DA), support vector machine (SVM) and neural networks (NN) were employed to generate models, in which the emission of IR light from heated samples was stimulated using a CO2 laser giving rise to laser induced thermal emission (LITE) of HEMs. Traces of a specific target threat chemical explosive: PETN in surface concentrations of 10 to 300 ug/cm2 were studied on the surfaces mentioned. Custom built experimental setup used a CO2 laser as a heating source positioned with a telescope, where a minimal loss in reflective optics was reported, for the Mid-IR at a distance of 4 m and 32 scans at 10 s. SVM-DA resulted in the best statistical technique for a discrimination performance of 97%. PLS-DA accurately predicted over 94% and NN 88%.

Preparation and application of silver nanopaste as thermal interface materials

NASA Astrophysics Data System (ADS)

Zou, Lianfeng

The power densities in electronic devices have increased dramatically; heat dissipation has become a major challenge in high performance electronics applications. We have investigated a new type of resin-free hybrid silver nanopastes, which contain silver micro-flakes with particle sizes of 1 - 10 um and silver nanoparticles with diameters of 3 - 8 nm. The assemble temperature can be as low as 150oC due to the low sintering temperature of silver nanoparticles. The fused silver micro-and nanoparticles in TIM form continuous metallic networks, resulting in good thermal, electrical and mechanical bonding. The steady-state thermal gradient measurement show the bulk thermal conductivity between 20W/ (m*K) and 100 W/ (m*K), which is higher than commercial product in the market. The application specific performance of the nanopaste has been using LED lamp on heat sinks as model test vehicle.

Thermal modelling of cooling tool cutting when milling by electrical analogy

NASA Astrophysics Data System (ADS)

Benabid, F.; Arrouf, M.; Assas, M.; Benmoussa, H.

2010-06-01

Measurement temperatures by (some devises) are applied immediately after shut-down and may be corrected for the temperature drop that occurs in the interval between shut-down and measurement. This paper presents a new procedure for thermal modelling of the tool cutting used just after machining; when the tool is out off the chip in order to extrapolate the cutting temperature from the temperature measured when the tool is at stand still. A fin approximation is made in enhancing heat loss (by conduction and convection) to air stream is used. In the modelling we introduce an equivalent thermal network to estimate the cutting temperature as a function of specific energy. In another hand, a local modified element lumped conduction equation is used to predict the temperature gradient with time when the tool is being cooled, with initial and boundary conditions. These predictions provide a detailed view of the global heat transfer coefficient as a function of cutting speed because the heat loss for the tool in air stream is an order of magnitude larger than in normal environment. Finally we deduct the cutting temperature by inverse method.

Integration of Decentralized Thermal Storages Within District Heating (DH) Networks

NASA Astrophysics Data System (ADS)

Schuchardt, Georg K.

2016-12-01

Thermal Storages and Thermal Accumulators are an important component within District Heating (DH) systems, adding flexibility and offering additional business opportunities for these systems. Furthermore, these components have a major impact on the energy and exergy efficiency as well as the heat losses of the heat distribution system. Especially the integration of Thermal Storages within ill-conditioned parts of the overall DH system enhances the efficiency of the heat distribution. Regarding an illustrative and simplified example for a DH system, the interactions of different heat storage concepts (centralized and decentralized) and the heat losses, energy and exergy efficiencies will be examined by considering the thermal state of the heat distribution network.

Experiment and Artificial Neural Network Prediction of Thermal Conductivity and Viscosity for Alumina-Water Nanofluids

PubMed Central

Zhao, Ningbo; Li, Zhiming

2017-01-01

To effectively predict the thermal conductivity and viscosity of alumina (Al2O3)-water nanofluids, an artificial neural network (ANN) approach was investigated in the present study. Firstly, using a two-step method, four Al2O3-water nanofluids were prepared respectively by dispersing different volume fractions (1.31%, 2.72%, 4.25%, and 5.92%) of nanoparticles with the average diameter of 30 nm. On this basis, the thermal conductivity and viscosity of the above nanofluids were analyzed experimentally under various temperatures ranging from 296 to 313 K. Then a radial basis function (RBF) neural network was constructed to predict the thermal conductivity and viscosity of Al2O3-water nanofluids as a function of nanoparticle volume fraction and temperature. The experimental results showed that both nanoparticle volume fraction and temperature could enhance the thermal conductivity of Al2O3-water nanofluids. However, the viscosity only depended strongly on Al2O3 nanoparticle volume fraction and was increased slightly by changing temperature. In addition, the comparative analysis revealed that the RBF neural network had an excellent ability to predict the thermal conductivity and viscosity of Al2O3-water nanofluids with the mean absolute percent errors of 0.5177% and 0.5618%, respectively. This demonstrated that the ANN provided an effective way to predict the thermophysical properties of nanofluids with limited experimental data. PMID:28772913

Experiment and Artificial Neural Network Prediction of Thermal Conductivity and Viscosity for Alumina-Water Nanofluids.

PubMed

Zhao, Ningbo; Li, Zhiming

2017-05-19

To effectively predict the thermal conductivity and viscosity of alumina (Al₂O₃)-water nanofluids, an artificial neural network (ANN) approach was investigated in the present study. Firstly, using a two-step method, four Al₂O₃-water nanofluids were prepared respectively by dispersing different volume fractions (1.31%, 2.72%, 4.25%, and 5.92%) of nanoparticles with the average diameter of 30 nm. On this basis, the thermal conductivity and viscosity of the above nanofluids were analyzed experimentally under various temperatures ranging from 296 to 313 K. Then a radial basis function (RBF) neural network was constructed to predict the thermal conductivity and viscosity of Al₂O₃-water nanofluids as a function of nanoparticle volume fraction and temperature. The experimental results showed that both nanoparticle volume fraction and temperature could enhance the thermal conductivity of Al₂O₃-water nanofluids. However, the viscosity only depended strongly on Al₂O₃ nanoparticle volume fraction and was increased slightly by changing temperature. In addition, the comparative analysis revealed that the RBF neural network had an excellent ability to predict the thermal conductivity and viscosity of Al₂O₃-water nanofluids with the mean absolute percent errors of 0.5177% and 0.5618%, respectively. This demonstrated that the ANN provided an effective way to predict the thermophysical properties of nanofluids with limited experimental data.

Used Fuel Disposal in Crystalline Rocks. FY15 Progress Report

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

Wang, Yifeng

2015-08-20

The objective of the Crystalline Disposal R&D Work Package is to advance our understanding of long-term disposal of used fuel in crystalline rocks and to develop necessary experimental and computational capabilities to evaluate various disposal concepts in such media. Chapter headings are as follows: Fuel matrix degradation model and its integration with performance assessments, Investigation of thermal effects on the chemical behavior of clays, Investigation of uranium diffusion and retardation in bentonite, Long-term diffusion of U(VI) in bentonite: dependence on density, Sorption and desorption of plutonium by bentonite, Dissolution of plutonium intrinsic colloids in the presence of clay and asmore » a function of temperature, Laboratory investigation of colloid-facilitated transport of cesium by bentonite colloids in a crystalline rock system, Development and demonstration of discrete fracture network model, Fracture continuum model and its comparison with discrete fracture network model.« less

Gray-Box Approach for Thermal Modelling of Buildings for Applications in District Heating and Cooling Networks

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

Saurav, Kumar; Chandan, Vikas

District-heating-and-cooling (DHC) systems are a proven energy solution that has been deployed for many years in a growing number of urban areas worldwide. They comprise a variety of technologies that seek to develop synergies between the production and supply of heat, cooling, domestic hot water and electricity. Although the benefits of DHC systems are significant and have been widely acclaimed, yet the full potential of modern DHC systems remains largely untapped. There are several opportunities for development of energy efficient DHC systems, which will enable the effective exploitation of alternative renewable resources, waste heat recovery, etc., in order to increasemore » the overall efficiency and facilitate the transition towards the next generation of DHC systems. This motivated the need for modelling these complex systems. Large-scale modelling of DHC-networks is challenging, as it has several components such as buildings, pipes, valves, heating source, etc., interacting with each other. In this paper, we focus on building modelling. In particular, we present a gray-box methodology for thermal modelling of buildings. Gray-box modelling is a hybrid of data driven and physics based models where, coefficients of the equations from physics based models are learned using data. This approach allows us to capture the dynamics of the buildings more effectively as compared to pure data driven approach. Additionally, this approach results in a simpler models as compared to pure physics based models. We first develop the individual components of the building such as temperature evolution, flow controller, etc. These individual models are then integrated in to the complete gray-box model for the building. The model is validated using data collected from one of the buildings at Lule{\\aa}, a city on the coast of northern Sweden.« less

Photon Statistics of Propagating Thermal Microwaves

NASA Astrophysics Data System (ADS)

Deppe, F.; Goetz, J.; Eder, P.; Fischer, M.; Pogorzalek, S.; Xie, E.; Fedorov, K. G.; Marx, A.; Gross, R.

In experiments with superconducting quantum circuits, characterizing the photon statistics of propagating microwave fields is a fundamental task. This task is in particular relevant for thermal fields, which are omnipresent noise sources in superconducting quantum circuits covering all relevant frequency regimes. We quantify the n2 + n photon number variance of thermal microwave photons emitted from a black-body radiator for mean photon numbers 0 . 05 <= n <= 1 . 5. In addition, we also use the fields as a sensitive probe for second-order decoherence effects of the qubit. Specifically, we investigate the influence of thermal fields on the low-frequency spectrum of the qubit parameter fluctuations. We find an enhacement of the white noise contribution of the noise power spectral density. Our data confirms a model of thermally activated two-level states interacting with the qubit. Supported by the German Research Foundation through FE 1564/1-1, the doctorate programs ExQM of the Elite Network of Bavaria, and the IMPRS Quantum Science and Technology.

Investigation of the role of thermal boundary layer processes in initiating convection under the NASA SPACE Field Program

NASA Technical Reports Server (NTRS)

Mcnider, Richard T.; Song, Aaron; Casey, Dan; Crosson, William; Wetzel, Peter

1993-01-01

The current NWS ground based network is not sufficient to capture the dynamic or thermodynamic structure leading to the initiation and organization of air mass moist convective events. Under this investigation we intend to use boundary layer mesoscale models (McNider and Pielke, 1981) to examine the dynamic triggering of convection due to topography and surface thermal contrasts. VAS and MAN's estimates of moisture will be coupled with the dynamic solution to provide an estimate of the total convective potential. Visible GOES images will be used to specify incoming insolation which may lead to surface thermal contrasts and JR skin temperatures will be used to estimate surface moisture (via the surface thermal inertia) (Weizel and Chang, 1988) which can also induce surface thermal contrasts. We will use the SPACE-COHMEX data base to evaluate the ability of the joint mesoscale model satellite products to show skill in predicting the development of air mass convection. We will develop images of model vertical velocity and satellite thermodynamic measures to derive images of predicted convective potential. We will then after suitable geographic registration carry out a pixel by pixel correlation between the model/satellite convective potential and the 'truth' which are the visible images. During the first half of the first year of this investigation we have concentrated on two aspects of the project. The first has been in generating vertical velocity fields from the model for COHMEX case days. We have taken June 19 as the first case and have run the mesoscale model at several different grid resolutions. We are currently developing the composite model/satellite convective image. The second aspect has been the attempted calibration of the surface energy budget to provide the proper horizontal thermal contrasts for convective initiation. We have made extensive progress on this aspect using the FIFE data as a test data set. The calibration technique looks very promising.

Dependence of physical and mechanical properties on polymer architecture for model polymer networks

NASA Astrophysics Data System (ADS)

Guo, Ruilan

Effect of architecture at nanoscale on the macroscopic properties of polymer materials has long been a field of major interest, as evidenced by inhomogeneities in networks, multimodal network topologies, etc. The primary purpose of this research is to establish the architecture-property relationship of polymer networks by studying the physical and mechanical responses of a series of topologically different PTHF networks. Monodispersed allyl-tenninated PTHF precursors were synthesized through "living" cationic polymerization and functional end-capping. Model networks of various crosslink densities and inhomogeneities levels (unimodal, bimodal and clustered) were prepared by endlinking precursors via thiol-ene reaction. Thermal characteristics, i.e., glass transition, melting point, and heat of fusion, of model PTHF networks were investigated as functions of crosslink density and inhomogeneities, which showed different dependence on these two architectural parameters. Study of freezing point depression (FPD) of solvent confined in swollen networks indicated that the size of solvent microcrystals is comparable to the mesh size formed by intercrosslink chains depending on crosslink density and inhomogeneities. Relationship between crystal size and FPD provided a good reflection of the existing architecture facts in the networks. Mechanical responses of elastic chains to uniaxial strains were studied through SANS. Spatial inhomogeneities in bimodal and clustered networks gave rise to "abnormal butterfly patterns", which became more pronounced as elongation ratio increases. Radii of gyration of chains were analyzed at directions parallel and perpendicular to stretching axis. Dependence of Rg on lambda was compared to three rubber elasticity models and the molecular deformation mechanisms for unimodal, bimodal and clustered networks were explored. The thesis focused its last part on the investigation of evolution of free volume distribution of linear polymer (PE) subjected to uniaxial strain at various temperatures using a combination of MD, hard sphere probe method and Voronoi tessellation. Combined effects of temperature and strain on free volume were studied and mechanism of formation of large and ellipsoidal free volume voids was explored.

Network analysis of oyster transcriptome revealed a cascade of cellular responses during recovery after heat shock.

PubMed

Zhang, Lingling; Hou, Rui; Su, Hailin; Hu, Xiaoli; Wang, Shi; Bao, Zhenmin

2012-01-01

Oysters, as a major group of marine bivalves, can tolerate a wide range of natural and anthropogenic stressors including heat stress. Recent studies have shown that oysters pretreated with heat shock can result in induced heat tolerance. A systematic study of cellular recovery from heat shock may provide insights into the mechanism of acquired thermal tolerance. In this study, we performed the first network analysis of oyster transcriptome by reanalyzing microarray data from a previous study. Network analysis revealed a cascade of cellular responses during oyster recovery after heat shock and identified responsive gene modules and key genes. Our study demonstrates the power of network analysis in a non-model organism with poor gene annotations, which can lead to new discoveries that go beyond the focus on individual genes.

Equilibrium & Nonequilibrium Fluctuation Effects in Biopolymer Networks

NASA Astrophysics Data System (ADS)

Kachan, Devin Michael

Fluctuation-induced interactions are an important organizing principle in a variety of soft matter systems. In this dissertation, I explore the role of both thermal and active fluctuations within cross-linked polymer networks. The systems I study are in large part inspired by the amazing physics found within the cytoskeleton of eukaryotic cells. I first predict and verify the existence of a thermal Casimir force between cross-linkers bound to a semi-flexible polymer. The calculation is complicated by the appearance of second order derivatives in the bending Hamiltonian for such polymers, which requires a careful evaluation of the the path integral formulation of the partition function in order to arrive at the physically correct continuum limit and properly address ultraviolet divergences. I find that cross linkers interact along a filament with an attractive logarithmic potential proportional to thermal energy. The proportionality constant depends on whether and how the cross linkers constrain the relative angle between the two filaments to which they are bound. The interaction has important implications for the synthesis of biopolymer bundles within cells. I model the cross-linkers as existing in two phases: bound to the bundle and free in solution. When the cross-linkers are bound, they behave as a one-dimensional gas of particles interacting with the Casimir force, while the free phase is a simple ideal gas. Demanding equilibrium between the two phases, I find a discontinuous transition between a sparsely and a densely bound bundle. This discontinuous condensation transition induced by the long-ranged nature of the Casimir interaction allows for a similarly abrupt structural transition in semiflexible filament networks between a low cross linker density isotropic phase and a higher cross link density bundle network. This work is supported by the results of finite element Brownian dynamics simulations of semiflexible filaments and transient cross-linkers. I speculate that cells take advantage of this equilibrium effect by tuning near the transition point, where small changes in free cross-linker density will affect large structural rearrangements between free filament networks and networks of bundles. Cells are naturally found far from equilibrium, where the active influx of energy from ATP consumption controls the dynamics. Motor proteins actively generate forces within biopolymer networks, and one may ask how these differ from the random stresses characteristic of equilibrium fluctuations. Besides the trivial observation that the magnitude is independent of temperature, I find that the processive nature of the motors creates a temporally correlated, or colored, noise spectrum. I model the network with a nonlinear scalar elastic theory in the presence of active driving, and study the long distance and large scale properties of the system with renormalization group techniques. I find that there is a new critical point associated with diverging correlation time, and that the colored noise produces novel frequency dependence in the renormalized transport coefficients. Finally, I study marginally elastic solids which have vanishing shear modulus due to the presence of soft modes, modes with zero deformation cost. Although network coordination is a useful metric for determining the mechanical response of random spring networks in mechanical equilibrium, it is insufficient for describing networks under external stress. In particular, under-constrained networks which are fluid-like at zero load will dynamically stiffen at a critical strain, as observed in numerical simulations and experimentally in many biopolymer networks. Drawing upon analogies to the stress induced unjamming of emulsions, I develop a kinetic theory to explain the rigidity transition in spring and filament networks. Describing the dynamic evolution of non-affine deformation via a simple mechanistic picture, I recover the emergent nonlinear strain-stiffening behavior and compare this behavior to the yield stress flow seen in soft glassy fluids. I extend this theory to account for coordination number inhomogeneities and predict a breakdown of universal scaling near the critical point at sufficiently high disorder, and discuss the utility for this type of model in describing biopolymer networks.

Neural network-based preprocessing to estimate the parameters of the X-ray emission of a single-temperature thermal plasma

NASA Astrophysics Data System (ADS)

Ichinohe, Y.; Yamada, S.; Miyazaki, N.; Saito, S.

2018-04-01

We present data preprocessing based on an artificial neural network to estimate the parameters of the X-ray emission spectra of a single-temperature thermal plasma. The method finds appropriate parameters close to the global optimum. The neural network is designed to learn the parameters of the thermal plasma (temperature, abundance, normalization and redshift) of the input spectra. After training using 9000 simulated X-ray spectra, the network has grown to predict all the unknown parameters with uncertainties of about a few per cent. The performance dependence on the network structure has been studied. We applied the neural network to an actual high-resolution spectrum obtained with Hitomi. The predicted plasma parameters agree with the known best-fitting parameters of the Perseus cluster within uncertainties of ≲10 per cent. The result shows that neural networks trained by simulated data might possibly be used to extract a feature built in the data. This would reduce human-intensive preprocessing costs before detailed spectral analysis, and would help us make the best use of the large quantities of spectral data that will be available in the coming decades.

A modeling assessment of the thermal regime for an urban sport fishery

USGS Publications Warehouse

Bartholow, John M.

1991-01-01

Water temperature is almost certainly a limiting factor in the maintenance of a self-sustaining rainbow trout (Oncorhynchus mykiss, formerly Salmo gairdneri) and brown trout (Salmo trutta) fishery in the lower reaches of the Cache la Poudre River near Fort Collins, Colorado, USA. Irrigation diversions dewater portions of the river, but cold reservoir releases moderate water temperatures during some periods. The US Fish and Wildlife Service’s Stream Network Temperature Model (SNTEMP) was applied to a 31-km segment of the river using readily available stream geometry and hydrological and meteorological data. The calibrated model produced satisfactory water temperature predictions (R2=0.88,P3/sec would be needed to maintain suitable summer temperatures throughout most of the study area. Such flows would be especially beneficial during weekends when current irrigation patterns reduce flows. The model indicated that increasing the riparian shade would result in little improvement in water temperatures but that decreasing the stream width would result in significant temperature reductions. Introduction of a more thermally tolerant redband trout (Oncorhynchus sp.), or smallmouth bass (Micropterus dolomieui) might prove beneficial to the fishery. Construction of deep pools for thermal refugia might also be helpful.

Nanoscale current spreading analysis in solution-processed graphene oxide/silver nanowire transparent electrodes via conductive atomic force microscopy

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

Shaw, Joseph E.; Perumal, Ajay; Bradley, Donal D. C.

2016-05-21

We use conductive atomic force microscopy (CAFM) to study the origin of long-range conductivity in model transparent conductive electrodes composed of networks of reduced graphene oxide (rGO{sub X}) and silver nanowires (AgNWs), with nanoscale spatial resolution. Pristine networks of rGO{sub X} (1–3 monolayers-thick) and AgNWs exhibit sheet resistances of ∼100–1000 kΩ/□ and 100–900 Ω/□, respectively. When the materials are deposited sequentially to form bilayer rGO{sub X}/AgNW electrodes and thermally annealed at 200 °C, the sheet resistance reduces by up to 36% as compared to pristine AgNW networks. CAFM was used to analyze the current spreading in both systems in order to identify themore » nanoscale phenomena responsible for this effect. For rGO{sub X} networks, the low intra-flake conductivity and the inter-flake contact resistance is found to dominate the macroscopic sheet resistance, while for AgNW networks the latter is determined by the density of the inter-AgNW junctions and their associated resistance. In the case of the bilayer rGO{sub X}/AgNWs' networks, rGO{sub X} flakes are found to form conductive “bridges” between AgNWs. We show that these additional nanoscopic electrical connections are responsible for the enhanced macroscopic conductivity of the bilayer rGO{sub X}/AgNW electrodes. Finally, the critical role of thermal annealing on the formation of these nanoscopic connections is discussed.« less

Sensitivity of Inverse Estimation of 2004 Elemental Carbon Emissions Inventory in the United States to the Choice of Observational Networks

EPA Science Inventory

Choice of observational networks used for inverse re-estimation of elemental (or black) carbon (EC) emissions in the United States impacts results. We convert the Thermal Optical Transmittance (TOT) EC measurements to the Thermal Optical Reflectance (TOR) equivalent to make full...

Modeling of Propagation of Interacting Cracks Under Hydraulic Pressure Gradient

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

Huang, Hai; Mattson, Earl Douglas; Podgorney, Robert Karl

A robust and reliable numerical model for fracture initiation and propagation, which includes the interactions among propagating fractures and the coupling between deformation, fracturing and fluid flow in fracture apertures and in the permeable rock matrix, would be an important tool for developing a better understanding of fracturing behaviors of crystalline brittle rocks driven by thermal and (or) hydraulic pressure gradients. In this paper, we present a physics-based hydraulic fracturing simulator based on coupling a quasi-static discrete element model (DEM) for deformation and fracturing with conjugate lattice network flow model for fluid flow in both fractures and porous matrix. Fracturingmore » is represented explicitly by removing broken bonds from the network to represent microcracks. Initiation of new microfractures and growth and coalescence of the microcracks leads to the formation of macroscopic fractures when external and/or internal loads are applied. The coupled DEM-network flow model reproduces realistic growth pattern of hydraulic fractures. In particular, simulation results of perforated horizontal wellbore clearly demonstrate that elastic interactions among multiple propagating fractures, fluid viscosity, strong coupling between fluid pressure fluctuations within fractures and fracturing, and lower length scale heterogeneities, collectively lead to complicated fracturing patterns.« less

Analysis of high vacuum systems using SINDA'85

NASA Technical Reports Server (NTRS)

Spivey, R. A.; Clanton, S. E.; Moore, J. D.

1993-01-01

The theory, algorithms, and test data correlation analysis of a math model developed to predict performance of the Space Station Freedom Vacuum Exhaust System are presented. The theory used to predict the flow characteristics of viscous, transition, and molecular flow is presented in detail. Development of user subroutines which predict the flow characteristics in conjunction with the SINDA'85/FLUINT analysis software are discussed. The resistance-capacitance network approach with application to vacuum system analysis is demonstrated and results from the model are correlated with test data. The model was developed to predict the performance of the Space Station Freedom Vacuum Exhaust System. However, the unique use of the user subroutines developed in this model and written into the SINDA'85/FLUINT thermal analysis model provides a powerful tool that can be used to predict the transient performance of vacuum systems and gas flow in tubes of virtually any geometry. This can be accomplished using a resistance-capacitance (R-C) method very similar to the methods used to perform thermal analyses.

High-resolution Mapping of Permafrost and Soil Freeze/thaw Dynamics in the Tibetan Plateau Based on Multi-sensor Satellite Observations

NASA Astrophysics Data System (ADS)

Zhang, W.; Yi, Y.; Yang, K.; Kimball, J. S.

2016-12-01

The Tibetan Plateau (TP) is underlain by the world's largest extent of alpine permafrost ( 2.5×106 km2), dominated by sporadic and discontinuous permafrost with strong sensitivity to climate warming. Detailed permafrost distributions and patterns in most of the TP region are still unknown due to extremely sparse in-situ observations in this region characterized by heterogeneous land cover and large temporal dynamics in surface soil moisture conditions. Therefore, satellite-based temperature and moisture observations are essential for high-resolution mapping of permafrost distribution and soil active layer changes in the TP region. In this study, we quantify the TP regional permafrost distribution at 1-km resolution using a detailed satellite data-driven soil thermal process model (GIPL2). The soil thermal model is calibrated and validated using in-situ soil temperature/moisture observations from the CAMP/Tibet field campaign (9 sites: 0-300 cm soil depth sampling from 1997-2007), a multi-scale soil moisture and temperature monitoring network in the central TP (CTP-SMTMN, 57 sites: 5-40 cm, 2010-2014) and across the whole plateau (China Meteorology Administration, 98 sites: 0-320 cm, 2000-2015). Our preliminary results using the CAMP/Tibet and CTP-SMTMN network observations indicate strong controls of surface thermal and soil moisture conditions on soil freeze/thaw dynamics, which vary greatly with underlying topography, soil texture and vegetation cover. For regional mapping of soil freeze/thaw and permafrost dynamics, we use the most recent soil moisture retrievals from the NASA SMAP (Soil Moisture Active Passive) sensor to account for the effects of temporal soil moisture dynamics on soil thermal heat transfer, with surface thermal conditions defined by MODIS (Moderate Resolution Imaging Spectroradiometer) land surface temperature records. Our study provides the first 1-km map of spatial patterns and recent changes of permafrost conditions in the TP.

Managing fish habitat for flow and temperature extremes ...

EPA Pesticide Factsheets

Summer low flows and stream temperature maxima are key drivers affecting the sustainability of fish populations. Thus, it is critical to understand both the natural templates of spatiotemporal variability, how these are shifting due to anthropogenic influences of development and climate change, and how these impacts can be moderated by natural and constructed green infrastructure. Low flow statistics of New England streams have been characterized using a combination of regression equations to describe long-term averages as a function of indicators of hydrologic regime (rain- versus snow-dominated), precipitation, evapotranspiration or temperature, surface water storage, baseflow recession rates, and impervious cover. Difference equations have been constructed to describe interannual variation in low flow as a function of changing air temperature, precipitation, and ocean-atmospheric teleconnection indices. Spatial statistical network models have been applied to explore fine-scale variability of thermal regimes along stream networks in New England as a function of variables describing natural and altered energy inputs, groundwater contributions, and retention time. Low flows exacerbate temperature impacts by reducing thermal inertia of streams to energy inputs. Based on these models, we can construct scenarios of fish habitat suitability using current and projected future climate and the potential for preservation and restoration of historic habitat regimes th

In vivo dynamical behavior of yeast chromatin modeled as an entangled polymer network with constraint release

NASA Astrophysics Data System (ADS)

Wang, Chenxi; Kilfoil, Maria L.

2013-03-01

The high fidelity segregation of chromatin is the central problem in cell mitosis. The role of mechanics underlying this, however, is undetermined. Work in this area has largely focused on cytoskeletal elements of the process. Preliminary work in our lab suggests the mechanical properties of chromatin are fundamental in this process. Nevertheless, the mechanical properties of chromatin in the cellular context are not well-characterized. For better understanding of the role of mechanics in this cellular process, and of the chromatin mechanics in vivo generally, a systematic dynamical description of chromatin in vivo is required. Accordingly, we label specific sites on chromatin with fluorescent proteins of different wave lengths, enabling us to detect multiple spots separately in 3D and track their displacements in time inside living yeast cells. We analyze the pairwise cross-correlated motion between spots as a function of relative distance along the DNA contour. Comparison between the reptation model and our data serves to test our conjecture that chromatin in the cell is basically an entangled polymer network under constraints to thermal motion, and removal of constraints by non-thermal cellular processes is expected to affect its dynamic behavior.

Heat transfer analysis of skin during thermal therapy using thermal wave equation.

PubMed

Kashcooli, Meisam; Salimpour, Mohammad Reza; Shirani, Ebrahim

2017-02-01

Specifying exact geometry of vessel network and its effect on temperature distribution in living tissues is one of the most complicated problems of the bioheat field. In this paper, the effects of blood vessels on temperature distribution in a skin tissue subjected to various thermal therapy conditions are investigated. Present model consists of counter-current multilevel vessel network embedded in a three-dimensional triple-layered skin structure. Branching angles of vessels are calculated using the physiological principle of minimum work. Length and diameter ratios are specified using length doubling rule and Cube law, respectively. By solving continuity, momentum and energy equations for blood flow and Pennes and modified Pennes bioheat equations for the tissue, temperature distributions in the tissue are measured. Effects of considering modified Pennes bioheat equation are investigated, comprehensively. It is also observed that blood has an impressive role in temperature distribution of the tissue, especially at high temperatures. The effects of different parameters such as boundary conditions, relaxation time, thermal properties of skin, metabolism and pulse heat flux on temperature distribution are investigated. Tremendous effect of boundary condition type at the lower boundary is noted. It seems that neither insulation nor constant temperature at this boundary can completely describe the real physical phenomena. It is expected that real temperature at the lower levels is somewhat between two predicted values. The effect of temperature on the thermal properties of skin tissue is considered. It is shown that considering temperature dependent values for thermal conductivity is important in the temperature distribution estimation of skin tissue; however, the effect of temperature dependent values for specific heat capacity is negligible. It is seen that considering modified Pennes equation in processes with high heat flux during low times is significant. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

Thermal decomposition of cyanate ester resins

DOT National Transportation Integrated Search

2001-09-01

Polycyanurate networks were prepared by thermal polymerization of cyanate ester monomers containing two or more cyanate ester : (O-CN) functional groups. The thermal decomposition chemistry of nine different polycyanurates was studied by : ther...

Transient thermal analysis of fluid systems

NASA Technical Reports Server (NTRS)

Chandler, G. D.; Trust, R. D.

1977-01-01

Computer program performs transient thermal analysis of any 2-node to 200-node-thermal network, which transports heat by fluid flow convection. Program can be modified to add conduction along tubes and radiation.

Facile synthesis of a mesoporous Co3O4 network for Li-storage via thermal decomposition of an amorphous metal complex.

PubMed

Wen, Wei; Wu, Jin-Ming; Cao, Min-Hua

2014-11-07

A facile strategy is developed for mass fabrication of porous Co3O4 networks via the thermal decomposition of an amorphous cobalt-based complex. At a low mass loading, the achieved porous Co3O4 network exhibits excellent performance for lithium storage, which has a high capacity of 587 mA h g(-1) after 500 cycles at a current density of 1000 mA g(-1).

Thermal impulse response and the temperature preference of Escherichia coli

NASA Astrophysics Data System (ADS)

Ryu, William

2010-03-01

From a broad perspective, exposure to environmental temperature changes is a universal condition of living organisms. Escherichia coli is a powerful model system to study how a biochemical network measures and processes thermal information to produce adaptive changes in behavior. E. coli performs thermotaxis, directing its movements to a preferred temperature in spatial thermal gradients. How does the system perform thermotaxis? Where biologically is this analog value of thermal preference stored? Previous studies using populations of cells have shown that E.coli accumulate in spatial thermal gradients, but these experiments did not cleanly separate thermal responses from chemotactic responses. Here we have isolated the thermal behavior by studying the thermal impulse response of single, tethered cells. The motor output of cells was measured in response to small, impulsive increases in temperature, delivered by an infrared laser, over a range of ambient temperature (23 to 43 degrees C). The thermal impulse response at temperatures < 31 degrees C is similar to the chemotactic impulse response: both follow a similar time course, share the same directionality, and show biphasic characteristics. At temperatures > 31 degrees C, some cells show an inverted response, switching from warm- to cold-seeking behavior. The fraction of inverted responses increases nonlinearly with temperature, switching steeply at the preferred temperature of 37 degrees C.

Thermal luminescence spectroscopy chemical imaging sensor.

PubMed

Carrieri, Arthur H; Buican, Tudor N; Roese, Erik S; Sutter, James; Samuels, Alan C

2012-10-01

The authors present a pseudo-active chemical imaging sensor model embodying irradiative transient heating, temperature nonequilibrium thermal luminescence spectroscopy, differential hyperspectral imaging, and artificial neural network technologies integrated together. We elaborate on various optimizations, simulations, and animations of the integrated sensor design and apply it to the terrestrial chemical contamination problem, where the interstitial contaminant compounds of detection interest (analytes) comprise liquid chemical warfare agents, their various derivative condensed phase compounds, and other material of a life-threatening nature. The sensor must measure and process a dynamic pattern of absorptive-emissive middle infrared molecular signature spectra of subject analytes to perform its chemical imaging and standoff detection functions successfully.

Thermal stability of electron-irradiated poly(tetrafluoroethylene) - X-ray photoelectron and mass spectroscopic study

NASA Technical Reports Server (NTRS)

Wheeler, Donald R.; Pepper, Stephen V.

1990-01-01

Polytetrafluoroethylene (PTFE) was subjected to 3 keV electron bombardment and then heated in vacuum to 300 C. The behavior of the material as a function of radiation dose and temperature was studied by X-ray photoelectron spectroscopy (XPS) of the surface and mass spectroscopy of the species evolved. Lightly damaged material heated to 300 C evolved saturated fluorocarbon species, whereas unsaturated fluorocarbon species were evolved from heavily damaged material. After heating the heavily damaged material, those features in the XPS spectrum that were associated with damage diminished, giving the appearance that the radiation damage had annealed. The observations were interpreted by incorporating mass transport of severed chain fragments and thermal decomposition of severely damaged material into the branched and cross-linked network model of irradiated PTFE. The apparent annealing of the radiation damage was due to covering of the network by saturated fragments that easily diffused through the decomposed material to the surface region upon heating.

Low-molecular-weight gelators: elucidating the principles of gelation based on gelator solubility and a cooperative self-assembly model.

PubMed

Hirst, Andrew R; Coates, Ian A; Boucheteau, Thomas R; Miravet, Juan F; Escuder, Beatriu; Castelletto, Valeria; Hamley, Ian W; Smith, David K

2008-07-16

This paper highlights the key role played by solubility in influencing gelation and demonstrates that many facets of the gelation process depend on this vital parameter. In particular, we relate thermal stability ( T gel) and minimum gelation concentration (MGC) values of small-molecule gelation in terms of the solubility and cooperative self-assembly of gelator building blocks. By employing a van't Hoff analysis of solubility data, determined from simple NMR measurements, we are able to generate T calc values that reflect the calculated temperature for complete solubilization of the networked gelator. The concentration dependence of T calc allows the previously difficult to rationalize "plateau-region" thermal stability values to be elucidated in terms of gelator molecular design. This is demonstrated for a family of four gelators with lysine units attached to each end of an aliphatic diamine, with different peripheral groups (Z or Boc) in different locations on the periphery of the molecule. By tuning the peripheral protecting groups of the gelators, the solubility of the system is modified, which in turn controls the saturation point of the system and hence controls the concentration at which network formation takes place. We report that the critical concentration ( C crit) of gelator incorporated into the solid-phase sample-spanning network within the gel is invariant of gelator structural design. However, because some systems have higher solubilities, they are less effective gelators and require the application of higher total concentrations to achieve gelation, hence shedding light on the role of the MGC parameter in gelation. Furthermore, gelator structural design also modulates the level of cooperative self-assembly through solubility effects, as determined by applying a cooperative binding model to NMR data. Finally, the effect of gelator chemical design on the spatial organization of the networked gelator was probed by small-angle neutron and X-ray scattering (SANS/SAXS) on the native gel, and a tentative self-assembly model was proposed.

Effects of thermal variability on broadband seismometers: Controlled experiments, observations, and implications

USGS Publications Warehouse

Doody, Claire; Ringler, Adam; Anthony, Robert E.; Wilson, David; Holland, Austin; Hutt, Charles R.; Sandoval, Leo

2017-01-01

Isolating seismic instruments from temperature fluctuations is routine practice within the seismological community. However, the necessary degree of thermal stability required in broadband installations to avoid generating noise or compromising the fidelity in the seismic records is largely unknown and likely application dependent. To quantify the temperature sensitivity of seismometers over a broad range of frequencies, we artificially induced local temperature changes on three different models of seismometers to measure the effect of thermal variations on seismometer output. We found that diurnal temperature changes above 0.002°C root mean square (rms) showed significant changes in velocity and acceleration output in comparison to thermally stable reference measurements. We also found that sensor incoherent self‐noise increased with temperature variation; these increases in noise can be modeled as 1/f">1/f noise (pink noise), and are unlikely to be easily corrected for. These experimental results are compared with the data from Incorporated Research Institutions for Seismology (IRIS) U.S. Geological Survey (USGS) Global Seismographic Network (GSN) station TUC (Tucson, Arizona). This station is well instrumented with temperature sensors and has three different broadband seismometers, each of which uses a different method of thermal isolation. We show that the water bricks and borehole installations give ample temperature attenuation to thermally isolate seismometers from diurnal thermal variability that would compromise seismic data. We find that seismometer installations that provide thermal stability below 0.002°C rms could help to improve long‐period vertical seismic data across the GSN by decreasing temperature‐driven 1/f">1/f noise.

The Reverse Thermal Effect in Epoxy Resins and Moisture Absorption in Semi-Interpenetrating Polymer Networks.

NASA Astrophysics Data System (ADS)

El-Sa'Ad, Leila

1989-12-01

Available from UMI in association with The British Library. Requires signed TDF. Epoxy resins exhibit many desirable properties which make them ideal subjects for use as matrices of composite materials in many commercial, military and space applications. However, due to their high cross-link density they are often brittle. Epoxy resin networks have been modified by incorporating tough, ductile thermoplastics. Such systems are referred to as Semi-Interpenetrating Polymer Networks (Semi-IPN). Systematic modification to the thermoplastics backbone allowed the morphology of the blend to be controlled from a homogeneous one-phase structure to fully separated structures. The moisture absorption by composites in humid environments has been found to lead to a deterioration in the physical and mechanical properties of the matrix. Therefore, in order to utilize composites to their full potential, their response to hot/wet environments must be known. The aims of this investigation were two-fold. Firstly, to study the effect of varying the temperature of exposure at different stages in the absorption process on the water absorption behaviour of a TGDDM/DDS epoxy resin system. Secondly, to study water absorption characteristics, under isothermal conditions, of Semi-Interpenetrating Polymer Networks possessing different morphologies, and develop a theoretical model to evaluate the diffusion coefficients of the two-phase structures. The mathematical treatment used in this analysis was based on Fick's second law of diffusion. Tests were performed on specimens immersed in water at 10 ^circ, 40^circ and 70^circC, their absorption behaviour and swelling behaviour, as a consequence of water absorption, were investigated. The absorption results of the variable temperature absorption tests indicated a saturation dependence on the absorption behaviour. Specimens saturated at a high temperature will undergo further absorption when transferred to a lower temperature. This behaviour was termed the "reverse thermal effect". The swelling results suggested that it is more tightly bound water in the polymer which takes part in the reverse thermal effect. The absorption results for the Semi-Interpenetrating Polymer Networks suggested that the two key parameters which affected the moisture uptake were the morphology of the network and the percentage of epoxy resin in the system.

Development of multilayer perceptron networks for isothermal time temperature transformation prediction of U-Mo-X alloys

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

Johns, Jesse M.; Burkes, Douglas

In this work, a multilayered perceptron (MLP) network is used to develop predictive isothermal time-temperature-transformation (TTT) models covering a range of U-Mo binary and ternary alloys. The selected ternary alloys for model development are U-Mo-Ru, U-Mo-Nb, U-Mo-Zr, U-Mo-Cr, and U-Mo-Re. These model’s ability to predict 'novel' U-Mo alloys is shown quite well despite the discrepancies between literature sources for similar alloys which likely arise from different thermal-mechanical processing conditions. These models are developed with the primary purpose of informing experimental decisions. Additional experimental insight is necessary in order to reduce the number of experiments required to isolate ideal alloys. Thesemore » models allow test planners to evaluate areas of experimental interest; once initial tests are conducted, the model can be updated and further improve follow-on testing decisions. The model also improves analysis capabilities by reducing the number of data points necessary from any particular test. For example, if one or two isotherms are measured during a test, the model can construct the rest of the TTT curve over a wide range of temperature and time. This modeling capability reduces the cost of experiments while also improving the value of the results from the tests. The reduced costs could result in improved material characterization and therefore improved fundamental understanding of TTT dynamics. As additional understanding of phenomena driving TTTs is acquired, this type of MLP model can be used to populate unknowns (such as material impurity and other thermal mechanical properties) from past literature sources.« less

Initial inclusion of thermodynamic considerations in Kayenta.

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

Brannon, Rebecca Moss; Bishop, Joseph E.; Fuller, Timothy J.

A persistent challenge in simulating damage of natural geological materials, as well as rock-like engineered materials, is the development of efficient and accurate constitutive models. The common feature for these brittle and quasi-brittle materials are the presence of flaws such as porosity and network of microcracks. The desired models need to be able to predict the material responses over a wide range of porosities and strain rate. Kayenta (formerly called the Sandia GeoModel) is a unified general-purpose constitutive model that strikes a balance between first-principles micromechanics and phenomenological or semi-empirical modeling strategies. However, despite its sophistication and ability to reducemore » to several classical plasticity theories, Kayenta is incapable of modeling deformation of ductile materials in which deformation is dominated by dislocation generation and movement which can lead to significant heating. This stems from Kayenta's roots as a geological model, where heating due to inelastic deformation is often neglected or presumed to be incorporated implicitly through the elastic moduli. The sophistication of Kayenta and its large set of extensive features, however, make Kayenta an attractive candidate model to which thermal effects can be added. This report outlines the initial work in doing just that, extending the capabilities of Kayenta to include deformation of ductile materials, for which thermal effects cannot be neglected. Thermal effects are included based on an assumption of adiabatic loading by computing the bulk and thermal responses of the material with the Kerley Mie-Grueneisen equation of state and adjusting the yield surface according to the updated thermal state. This new version of Kayenta, referred to as Thermo-Kayenta throughout this report, is capable of reducing to classical Johnson-Cook plasticity in special case single element simulations and has been used to obtain reasonable results in more complicated Taylor impact simulations in LS-Dyna. Despite these successes, however, Thermo-Kayenta requires additional refinement for it to be consistent in the thermodynamic sense and for it to be considered superior to other, more mature thermoplastic models. The initial thermal development, results, and required refinements are all detailed in the following report.« less

A Hybrid Demand Response Simulator Version 1.0

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

2012-05-02

A hybrid demand response simulator is developed to test different control algorithms for centralized and distributed demand response (DR) programs in a small distribution power grid. The HDRS is designed to model a wide variety of DR services such as peak having, load shifting, arbitrage, spinning reserves, load following, regulation, emergency load shedding, etc. The HDRS does not model the dynamic behaviors of the loads, rather, it simulates the load scheduling and dispatch process. The load models include TCAs (water heaters, air conditioners, refrigerators, freezers, etc) and non-TCAs (lighting, washer, dishwasher, etc.) The ambient temperature changes, thermal resistance, capacitance, andmore » the unit control logics can be modeled for TCA loads. The use patterns of the non-TCA can be modeled by probability of use and probabilistic durations. Some of the communication network characteristics, such as delays and errors, can also be modeled. Most importantly, because the simulator is modular and greatly simplified the thermal models for TCA loads, it is very easy and fast to be used to test and validate different control algorithms in a simulated environment.« less

Electrical conductivity modeling and experimental study of densely packed SWCNT networks.

PubMed

Jack, D A; Yeh, C-S; Liang, Z; Li, S; Park, J G; Fielding, J C

2010-05-14

Single-walled carbon nanotube (SWCNT) networks have become a subject of interest due to their ability to support structural, thermal and electrical loadings, but to date their application has been hindered due, in large part, to the inability to model macroscopic responses in an industrial product with any reasonable confidence. This paper seeks to address the relationship between macroscale electrical conductivity and the nanostructure of a dense network composed of SWCNTs and presents a uniquely formulated physics-based computational model for electrical conductivity predictions. The proposed model incorporates physics-based stochastic parameters for the individual nanotubes to construct the nanostructure such as: an experimentally obtained orientation distribution function, experimentally derived length and diameter distributions, and assumed distributions of chirality and registry of individual CNTs. Case studies are presented to investigate the relationship between macroscale conductivity and nanostructured variations in the bulk stochastic length, diameter and orientation distributions. Simulation results correspond nicely with those available in the literature for case studies of conductivity versus length and conductivity versus diameter. In addition, predictions for the increasing anisotropy of the bulk conductivity as a function of the tube orientation distribution are in reasonable agreement with our experimental results. Examples are presented to demonstrate the importance of incorporating various stochastic characteristics in bulk conductivity predictions. Finally, a design consideration for industrial applications is discussed based on localized network power emission considerations and may lend insight to the design engineer to better predict network failure under high current loading applications.

Modification of a neuronal network direction using stepwise photo-thermal etching of an agarose architecture.

PubMed

Suzuki, Ikurou; Sugio, Yoshihiro; Moriguchi, Hiroyuki; Jimbo, Yasuhiko; Yasuda, Kenji

2004-07-01

Control over spatial distribution of individual neurons and the pattern of neural network provides an important tool for studying information processing pathways during neural network formation. Moreover, the knowledge of the direction of synaptic connections between cells in each neural network can provide detailed information on the relationship between the forward and feedback signaling. We have developed a method for topographical control of the direction of synaptic connections within a living neuronal network using a new type of individual-cell-based on-chip cell-cultivation system with an agarose microchamber array (AMCA). The advantages of this system include the possibility to control positions and number of cultured cells as well as flexible control of the direction of elongation of axons through stepwise melting of narrow grooves. Such micrometer-order microchannels are obtained by photo-thermal etching of agarose where a portion of the gel is melted with a 1064-nm infrared laser beam. Using this system, we created neural network from individual Rat hippocampal cells. We were able to control elongation of individual axons during cultivation (from cells contained within the AMCA) by non-destructive stepwise photo-thermal etching. We have demonstrated the potential of our on-chip AMCA cell cultivation system for the controlled development of individual cell-based neural networks.

Parallel and orthogonal stimulus in ultradiluted neural networks

NASA Astrophysics Data System (ADS)

Sobral, G. A., Jr.; Vieira, V. M.; Lyra, M. L.; da Silva, C. R.

2006-10-01

Extending a model due to Derrida, Gardner, and Zippelius, we have studied the recognition ability of an extreme and asymmetrically diluted version of the Hopfield model for associative memory by including the effect of a stimulus in the dynamics of the system. We obtain exact results for the dynamic evolution of the average network superposition. The stimulus field was considered as proportional to the overlapping of the state of the system with a particular stimulated pattern. Two situations were analyzed, namely, the external stimulus acting on the initialization pattern (parallel stimulus) and the external stimulus acting on a pattern orthogonal to the initialization one (orthogonal stimulus). In both cases, we obtained the complete phase diagram in the parameter space composed of the stimulus field, thermal noise, and network capacity. Our results show that the system improves its recognition ability for parallel stimulus. For orthogonal stimulus two recognition phases emerge with the system locking at the initialization or stimulated pattern. We confront our analytical results with numerical simulations for the noiseless case T=0 .

Towards overcoming the Monte Carlo sign problem with tensor networks

NASA Astrophysics Data System (ADS)

Bañuls, Mari Carmen; Cichy, Krzysztof; Ignacio Cirac, J.; Jansen, Karl; Kühn, Stefan; Saito, Hana

2017-03-01

The study of lattice gauge theories with Monte Carlo simulations is hindered by the infamous sign problem that appears under certain circumstances, in particular at non-zero chemical potential. So far, there is no universal method to overcome this problem. However, recent years brought a new class of non-perturbative Hamiltonian techniques named tensor networks, where the sign problem is absent. In previous work, we have demonstrated that this approach, in particular matrix product states in 1+1 dimensions, can be used to perform precise calculations in a lattice gauge theory, the massless and massive Schwinger model. We have computed the mass spectrum of this theory, its thermal properties and real-time dynamics. In this work, we review these results and we extend our calculations to the case of two flavours and non-zero chemical potential. We are able to reliably reproduce known analytical results for this model, thus demonstrating that tensor networks can tackle the sign problem of a lattice gauge theory at finite density.

Modeling water partition in composite gels of BSA with gelatin following high pressure treatment.

PubMed

Semasaka, Carine; Mhaske, Pranita; Buckow, Roman; Kasapis, Stefan

2018-11-01

Changes in the structural properties of hydrogels made with gelatin and bovine serum albumin mixtures were recorded following exposure to high pressure at 300 MPa for 15 min at 10 and 80 °C. Dynamic oscillation, SEM, FTIR and blending law modelling were utilised to rationalise results. Pressurization at the low temperature end yielded continuous gelatin networks supporting discontinuous BSA inclusions, whereas an inverted dispersion was formed at the high temperature end with the continuous BSA network suspending the discontinuous gelatin inclusions. Lewis and Nielsen equations followed the mechanical properties of the composites thus arguing that solvent partition between the two phases was always in favour of the polymer forming the continuous network. As far as we are aware, this is the first attempt to elucidate the solvent partition in pressurised hydrogel composites using blending law theory. Outcomes were contrasted with earlier work where binary mixtures were subjected only to thermal treatment. Copyright © 2018. Published by Elsevier Ltd.

Spatial and temporal variation of water temperature regimes on the Snoqualmie River network

Treesearch

Ashley E. Steel; Colin Sowder; Erin E. Peterson

2016-01-01

Although mean temperatures change annually and are highly correlated with elevation, the entire thermal regime on the Snoqualmie River, Washington, USA does not simply shift with elevation or season. Particular facets of the thermal regime have unique spatial patterns on the river network and at particular times of the year. We used a spatially and temporally dense...

Thermal non-equilibrium in porous medium adjacent to vertical plate: ANN approach

NASA Astrophysics Data System (ADS)

Ahmed, N. J. Salman; Ahamed, K. S. Nazim; Al-Rashed, Abdullah A. A. A.; Kamangar, Sarfaraz; Athani, Abdulgaphur

2018-05-01

Thermal non-equilibrium in porous medium is a condition that refers to temperature discrepancy in solid matrix and fluid of porous medium. This type of flow is complex flow requiring complex set of partial differential equations that govern the flow behavior. The current work is undertaken to predict the thermal non-equilibrium behavior of porous medium adjacent to vertical plate using artificial neural network. A set of neurons in 3 layers are trained to predict the heat transfer characteristics. It is found that the thermal non-equilibrium heat transfer behavior in terms of Nusselt number of fluid as well as solid phase can be predicted accurately by using well-trained neural network.

Calculating electronic tunnel currents in networks of disordered irregularly shaped nanoparticles by mapping networks to arrays of parallel nonlinear resistors

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

Aghili Yajadda, Mir Massoud

2014-10-21

We have shown both theoretically and experimentally that tunnel currents in networks of disordered irregularly shaped nanoparticles (NPs) can be calculated by considering the networks as arrays of parallel nonlinear resistors. Each resistor is described by a one-dimensional or a two-dimensional array of equal size nanoparticles that the tunnel junction gaps between nanoparticles in each resistor is assumed to be equal. The number of tunnel junctions between two contact electrodes and the tunnel junction gaps between nanoparticles are found to be functions of Coulomb blockade energies. In addition, the tunnel barriers between nanoparticles were considered to be tilted at highmore » voltages. Furthermore, the role of thermal expansion coefficient of the tunnel junction gaps on the tunnel current is taken into account. The model calculations fit very well to the experimental data of a network of disordered gold nanoparticles, a forest of multi-wall carbon nanotubes, and a network of few-layer graphene nanoplates over a wide temperature range (5-300 K) at low and high DC bias voltages (0.001 mV–50 V). Our investigations indicate, although electron cotunneling in networks of disordered irregularly shaped NPs may occur, non-Arrhenius behavior at low temperatures cannot be described by the cotunneling model due to size distribution in the networks and irregular shape of nanoparticles. Non-Arrhenius behavior of the samples at zero bias voltage limit was attributed to the disorder in the samples. Unlike the electron cotunneling model, we found that the crossover from Arrhenius to non-Arrhenius behavior occurs at two temperatures, one at a high temperature and the other at a low temperature.« less

Enhanced dewaterability of sludge during anaerobic digestion with thermal hydrolysis pretreatment: New insights through structure evolution.

PubMed

Zhang, Jingsi; Li, Ning; Dai, Xiaohu; Tao, Wenquan; Jenkinson, Ian R; Li, Zhuo

2017-12-19

Comprehensive insights into the sludge digestate dewaterability were gained through porous network structure of sludge. We measured the evolution of digestate dewaterability, represented by the solid content of centrifugally dewatered cake, in high-solids sequencing batch digesters with and without thermal hydrolysis pretreatment (THP). The results show that the dewaterability of the sludge after digestion was improved by 3.5% (±0.5%) for unpretreated sludge and 5.1% (±0.4%) for thermally hydrolyzed sludge. Compared to the unpretreated sludge digestate, thermal hydrolysis pretreatment eventually resulted in an improvement of dewaterability by 4.6% (±0.5%). Smaller particle size and larger surface area of sludge were induced by thermal hydrolysis and anaerobic digestion treatments. The structure strength and compactness of sludge, represented by elastic modulus and fractal dimension respectively, decreased with increase of digestion time. The porous network structure was broken up by thermal hydrolysis pretreatment and was further weakened during anaerobic digestion, which correspondingly improved the dewaterability of digestates. The logarithm of elastic modulus increased linearly with fractal dimension regardless of the pretreatment. Both fractal dimension and elastic modulus showed linear relationship with dewaterability. The rheological characterization combined with the analysis of fractal dimension of sewage sludge porous network structure was found applicable in quantitative evaluation of sludge dewaterability, which depended positively on both thermal hydrolysis and anaerobic digestion. Copyright © 2017 Elsevier Ltd. All rights reserved.

Computation of the effective mechanical response of biological networks accounting for large configuration changes.

PubMed

El Nady, K; Ganghoffer, J F

2016-05-01

The asymptotic homogenization technique is involved to derive the effective elastic response of biological membranes viewed as repetitive beam networks. Thereby, a systematic methodology is established, allowing the prediction of the overall mechanical properties of biological membranes in the nonlinear regime, reflecting the influence of the geometrical and mechanical micro-parameters of the network structure on the overall response of the equivalent continuum. Biomembranes networks are classified based on nodal connectivity, so that we analyze in this work 3, 4 and 6-connectivity networks, which are representative of most biological networks. The individual filaments of the network are described as undulated beams prone to entropic elasticity, with tensile moduli determined from their persistence length. The effective micropolar continuum evaluated as a continuum substitute of the biological network has a kinematics reflecting the discrete network deformation modes, involving a nodal displacement and a microrotation. The statics involves the classical Cauchy stress and internal moments encapsulated into couple stresses, which develop internal work in duality to microcurvatures reflecting local network undulations. The relative ratio of the characteristic bending length of the effective micropolar continuum to the unit cell size determines the relevant choice of the equivalent medium. In most cases, the Cauchy continuum is sufficient to model biomembranes. The peptidoglycan network may exhibit a re-entrant hexagonal configuration due to thermal or pressure fluctuations, for which micropolar effects become important. The homogenized responses are in good agreement with FE simulations performed over the whole network. The predictive nature of the employed homogenization technique allows the identification of a strain energy density of a hyperelastic model, for the purpose of performing structural calculations of the shape evolutions of biomembranes. Copyright © 2015 Elsevier Ltd. All rights reserved.

User's Manual: Thermal Radiation Analysis System TRASYS 2

NASA Technical Reports Server (NTRS)

Jensen, C. L.

1981-01-01

A digital computer software system with generalized capability to solve the radiation related aspects of thermal analysis problems is presented. When used in conjunction with a generalized thermal analysis program such as the systems improved numerical differencing analyzer program, any thermal problem that can be expressed in terms of a lumped parameter R-C thermal network can be solved. The function of TRASYS is twofold. It provides: (a) Internode radiation interchange data; and (b) Incident and absorbed heat rate data from environmental radiant heat sources. Data of both types is provided in a format directly usable by the thermal analyzer programs. The system allows the user to write his own executive or driver program which organizes and directs the program library routines toward solution of each specific problem in the most expeditious manner. The user also may write his own output routines, thus the system data output can directly interface with any thermal analyzer using the R-C network concept.

Thermal property tuning in aligned carbon nanotube films and random entangled carbon nanotube films by ion irradiation

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

Wang, Jing; Chen, Di; Wang, Xuemei

2015-10-12

Ion irradiation effects on thermal property changes are compared between aligned carbon nanotube (A-CNT) films and randomly entangled carbon nanotube (R-CNT) films. After H, C, and Fe ion irradiation, a focusing ion beam with sub-mm diameter is used as a heating source, and an infrared signal is recorded to extract thermal conductivity. Ion irradiation decreases thermal conductivity of A-CNT films, but increases that of R-CNT films. We explain the opposite trends by the fact that neighboring CNT bundles are loosely bonded in A-CNT films, which makes it difficult to create inter-tube linkage/bonding upon ion irradiation. In a comparison, in R-CNTmore » films, which have dense tube networking, carbon displacements are easily trapped between touching tubes and act as inter-tube linkage to promote off-axial phonon transport. The enhancement overcomes the phonon transport loss due to phonon-defect scattering along the axial direction. A model is established to explain the dependence of thermal conductivity changes on ion irradiation parameters including ion species, energies, and current.« less

System Error Compensation Methodology Based on a Neural Network for a Micromachined Inertial Measurement Unit

PubMed Central

Liu, Shi Qiang; Zhu, Rong

2016-01-01

Errors compensation of micromachined-inertial-measurement-units (MIMU) is essential in practical applications. This paper presents a new compensation method using a neural-network-based identification for MIMU, which capably solves the universal problems of cross-coupling, misalignment, eccentricity, and other deterministic errors existing in a three-dimensional integrated system. Using a neural network to model a complex multivariate and nonlinear coupling system, the errors could be readily compensated through a comprehensive calibration. In this paper, we also present a thermal-gas MIMU based on thermal expansion, which measures three-axis angular rates and three-axis accelerations using only three thermal-gas inertial sensors, each of which capably measures one-axis angular rate and one-axis acceleration simultaneously in one chip. The developed MIMU (100 × 100 × 100 mm3) possesses the advantages of simple structure, high shock resistance, and large measuring ranges (three-axes angular rates of ±4000°/s and three-axes accelerations of ±10 g) compared with conventional MIMU, due to using gas medium instead of mechanical proof mass as the key moving and sensing elements. However, the gas MIMU suffers from cross-coupling effects, which corrupt the system accuracy. The proposed compensation method is, therefore, applied to compensate the system errors of the MIMU. Experiments validate the effectiveness of the compensation, and the measurement errors of three-axis angular rates and three-axis accelerations are reduced to less than 1% and 3% of uncompensated errors in the rotation range of ±600°/s and the acceleration range of ±1 g, respectively. PMID:26840314

Experimental Investigation of Mechanical and Thermal Properties of Silica Nanoparticle-Reinforced Poly(acrylamide) Nanocomposite Hydrogels

PubMed Central

O’Brien, Victor; Chang, Andrew; Blanco, Matthew; Zabalegui, Aitor; Lee, Hohyun; Asuri, Prashanth

2015-01-01

Current studies investigating properties of nanoparticle-reinforced polymers have shown that nanocomposites often exhibit improved properties compared to neat polymers. However, over two decades of research, using both experimental studies and modeling analyses, has not fully elucidated the mechanistic underpinnings behind these enhancements. Moreover, few studies have focused on developing an understanding among two or more polymer properties affected by incorporation of nanomaterials. In our study, we investigated the elastic and thermal properties of poly(acrylamide) hydrogels containing silica nanoparticles. Both nanoparticle concentration and size affected hydrogel properties, with similar trends in enhancements observed for elastic modulus and thermal diffusivity. We also observed significantly lower swellability for hydrogel nanocomposites relative to neat hydrogels, consistent with previous work suggesting that nanoparticles can mediate pseudo crosslinking within polymer networks. Collectively, these results indicate the ability to develop next-generation composite materials with enhanced mechanical and thermal properties by increasing the average crosslinking density using nanoparticles. PMID:26301505

Magnetic cooling for microkelvin nanoelectronics on a cryofree platform.

PubMed

Palma, M; Maradan, D; Casparis, L; Liu, T-M; Froning, F N M; Zumbühl, D M

2017-04-01

We present a parallel network of 16 demagnetization refrigerators mounted on a cryofree dilution refrigerator aimed to cool nanoelectronic devices to sub-millikelvin temperatures. To measure the refrigerator temperature, the thermal motion of electrons in a Ag wire-thermalized by a spot-weld to one of the Cu nuclear refrigerators-is inductively picked-up by a superconducting gradiometer and amplified by a SQUID mounted at 4 K. The noise thermometer as well as other thermometers are used to characterize the performance of the system, finding magnetic field independent heat-leaks of a few nW/mol, cold times of several days below 1 mK, and a lowest temperature of 150 μK of one of the nuclear stages in a final field of 80 mT, close to the intrinsic SQUID noise of about 100 μK. A simple thermal model of the system capturing the nuclear refrigerator, heat leaks, and thermal and Korringa links describes the main features very well, including rather high refrigerator efficiencies typically above 80%.

Computational Modeling and Real-Time Control of Patient-Specific Laser Treatment of Cancer

PubMed Central

Fuentes, D.; Oden, J. T.; Diller, K. R.; Hazle, J. D.; Elliott, A.; Shetty, A.; Stafford, R. J.

2014-01-01

An adaptive feedback control system is presented which employs a computational model of bioheat transfer in living tissue to guide, in real-time, laser treatments of prostate cancer monitored by magnetic resonance thermal imaging (MRTI). The system is built on what can be referred to as cyberinfrastructure - a complex structure of high-speed network, large-scale parallel computing devices, laser optics, imaging, visualizations, inverse-analysis algorithms, mesh generation, and control systems that guide laser therapy to optimally control the ablation of cancerous tissue. The computational system has been successfully tested on in-vivo, canine prostate. Over the course of an 18 minute laser induced thermal therapy (LITT) performed at M.D. Anderson Cancer Center (MDACC) in Houston, Texas, the computational models were calibrated to intra-operative real time thermal imaging treatment data and the calibrated models controlled the bioheat transfer to within 5°C of the predetermined treatment plan. The computational arena is in Austin, Texas and managed at the Institute for Computational Engineering and Sciences (ICES). The system is designed to control the bioheat transfer remotely while simultaneously providing real-time remote visualization of the on-going treatment. Post operative histology of the canine prostate reveal that the damage region was within the targeted 1.2cm diameter treatment objective. PMID:19148754

Computational modeling and real-time control of patient-specific laser treatment of cancer.

PubMed

Fuentes, D; Oden, J T; Diller, K R; Hazle, J D; Elliott, A; Shetty, A; Stafford, R J

2009-04-01

An adaptive feedback control system is presented which employs a computational model of bioheat transfer in living tissue to guide, in real-time, laser treatments of prostate cancer monitored by magnetic resonance thermal imaging. The system is built on what can be referred to as cyberinfrastructure-a complex structure of high-speed network, large-scale parallel computing devices, laser optics, imaging, visualizations, inverse-analysis algorithms, mesh generation, and control systems that guide laser therapy to optimally control the ablation of cancerous tissue. The computational system has been successfully tested on in vivo, canine prostate. Over the course of an 18 min laser-induced thermal therapy performed at M.D. Anderson Cancer Center (MDACC) in Houston, Texas, the computational models were calibrated to intra-operative real-time thermal imaging treatment data and the calibrated models controlled the bioheat transfer to within 5 degrees C of the predetermined treatment plan. The computational arena is in Austin, Texas and managed at the Institute for Computational Engineering and Sciences (ICES). The system is designed to control the bioheat transfer remotely while simultaneously providing real-time remote visualization of the on-going treatment. Post-operative histology of the canine prostate reveal that the damage region was within the targeted 1.2 cm diameter treatment objective.

Modeling Mass and Thermal Transport in Thin Porous Media of PEM Fuel Cells

NASA Astrophysics Data System (ADS)

Konduru, Vinaykumar

Water transport in the Porous Transport Layer (PTL) plays an important role in the efficient operation of polymer electrolyte membrane fuel cells (PEMFC). Excessive water content as well as dry operating conditions are unfavorable for efficient and reliable operation of the fuel cell. The effect of thermal conductivity and porosity on water management are investigated by simulating two-phase flow in the PTL of the fuel cell using a network model. In the model, the PTL consists of a pore-phase and a solid-phase. Different models of the PTLs are generated using independent Weibull distributions for the pore-phase and the solid-phase. The specific arrangement of the pores and solid elements is varied to obtain different PTL realizations for the same Weibull parameters. The properties of PTL are varied by changing the porosity and thermal conductivity. The parameters affecting operating conditions include the temperature, relative humidity in the flow channel and voltage and current density. In addition, a novel high-speed capable Surface Plasmon Resonance (SPR) microscope was built based on Kretschmann's configuration utilizing a collimated Kohler illumination. The SPR allows thin film characterization in a thickness of approximately 0-200nm by measuring the changes in the refractive index. Various independent experiments were run to measure film thickness during droplet coalescence during condensation.

A Novel Optical Model for Remote Sensing of Near-Surface Soil Moisture

NASA Astrophysics Data System (ADS)

Babaeian, E.; Sadeghi, M.; Jones, S. B.; Tuller, M.

2016-12-01

Common triangle and trapezoid methods that are based on both optical and thermal remote sensing (RS) information have been widely applied in the past to estimate near-surface soil moisture from the soil temperature - vegetation index space (e.g., LST-NDVI). For most cases, this approach assumes a linear relationship between soil moisture and temperature. Though this linearity assumption yields reasonable moisture estimates, it is not always justified as evidenced by laboratory and field measurements. Furthermore, this approach requires optical as well as thermal RS data for definition of the land surface temperature (LST) - vegetation index space, therefore, it is not applicable to satellites that do not provide thermal output such as the ESA Sentinel-2. To overcome these limitations, we propose a novel trapezoid model that only relies on optical NIR and SWIR data. The new model was validated using Sentinel-2 and Landsat-8 data for the semiarid Walnut Gulch (AZ) and sub humid Little Washita (OK) watersheds that vastly differ in land use and surface cover and provide excellent ground-truth moisture information from extensive sensor networks. Preliminary results for 2015-2016 indicate significant potential of the new model with a RMSE smaller than 4% volumetric near-surface moisture content and also confirm the enhanced utility of the high spatially and temporally resolved Sentinel-2 data.

Initial study of thermal energy storage in unconfined aquifers. [UCATES

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

Haitjema, H.M.; Strack, O.D.L.

1986-04-01

Convective heat transport in unconfined aquifers is modeled in a semi-analytic way. The transient groundwater flow is modeled by superposition of analytic functions, whereby changes in the aquifer storage are represented by a network of triangles, each with a linearly varying sink distribution. This analytic formulation incorporates the nonlinearity of the differential equation for unconfined flow and eliminates numerical dispersion in modeling heat convection. The thermal losses through the aquifer base and vadose zone are modeled rather crudely. Only vertical heat conduction is considered in these boundaries, whereby a linearly varying temperature is assumed at all times. The latter assumptionmore » appears reasonable for thin aquifer boundaries. However, assuming such thin aquifer boundaries may lead to an overestimation of the thermal losses when the aquifer base is regarded as infinitely thick in reality. The approach is implemented in the computer program UCATES, which serves as a first step toward the development of a comprehensive screening tool for ATES systems in unconfined aquifers. In its present form, the program is capable of predicting the relative effects of regional flow on the efficiency of ATES systems. However, only after a more realistic heatloss mechanism is incorporated in UCATES will reliable predictions of absolute ATES efficiencies be possible.« less

Theoretical Modeling and Computer Simulations for the Origins and Evolution of Reproducing Molecular Systems and Complex Systems with Many Interactive Parts

NASA Technical Reports Server (NTRS)

Liang, Shoudan

2000-01-01

Our research effort has produced nine publications in peer-reviewed journals listed at the end of this report. The work reported here are in the following areas: (1) genetic network modeling; (2) autocatalytic model of pre-biotic evolution; (3) theoretical and computational studies of strongly correlated electron systems; (4) reducing thermal oscillations in atomic force microscope; (5) transcription termination mechanism in prokaryotic cells; and (6) the low glutamine usage in thennophiles obtained by studying completely sequenced genomes. We discuss the main accomplishments of these publications.

Thermal Conductivity Prediction of Soil in Complex Plant Soil System using Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Wardani, A. K.; Purqon, A.

2016-08-01

Thermal conductivity is one of thermal properties of soil in seed germination and plants growth. Different soil types have different thermal conductivity. One of soft-computing promising method to predict thermal conductivity of soil types is Artificial Neural Network (ANN). In this study, we estimate the thermal conductivity of soil prediction in a soil-plant complex systems using ANN. With a feed-forward multilayer trained with back-propagation with 4, 10 and 1 on the input, hidden and output layers respectively. Our input are heating time, temperature and thermal resistance with thermal conductivity of soil as a target. ANN prediction demonstrates a good agreement with Mean Squared Error-testing (MSEte) of 9.56 x 10-7 for soils with green beans and those of bare soils is 7.00 × 10-7 respectively Green beans grow only on black-clay soil with a thermal conductivity of 0.7 W/m K with a sufficient water content. Our results demonstrate that temperature, moisture content, colour, texture and structure of soil are greatly affect to the thermal conductivity of soil in seed germination and plant growth. In future, it is potentially applied to estimate more complex compositions of plant-soil systems.

Development & experimental validation of a SINDA/FLUINT thermal/fluid/electrical model of a multi-tube AMTEC cell

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

Hendricks, T.J.; Borkowski, C.A.; Huang, C.

1998-01-01

AMTEC (Alkali Metal Thermal-to-Electric Conversion) cell development has received increased attention and funding in the space power community because of several desirable performance characteristics compared to current radioisotope thermoelectric generation and solar photovoltaic (PV) power generation. AMTEC cell development is critically dependent upon the ability to predict thermal, fluid dynamic and electrical performance of an AMTEC cell which has many complex thermal, fluid dynamic and electrical processes and interactions occurring simultaneously. Development of predictive capability is critical to understanding the complex processes and interactions within the AMTEC cell, and thereby creating the ability to design high-performance, cost-effective AMTEC cells. Amore » flexible, sophisticated thermal/fluid/electrical model of an operating AMTEC cell has been developed using the SINDA/FLUINT analysis software. This model can accurately simulate AMTEC cell performance at any hot side and cold side temperature combination desired, for any voltage and current conditions, and for a broad range of cell design parameters involving the cell dimensions, current collector and electrode design, electrode performance parameters, and cell wall and thermal shield emissivity. The model simulates the thermal radiation network within the AMTEC cell using RadCAD thermal radiation analysis; hot side, cold side and cell wall conductive and radiative coupling; BASE (Beta Alumina Solid Electrode) tube electrochemistry, including electrode over-potentials; the fluid dynamics of the low-pressure sodium vapor flow to the condenser and liquid sodium flow in the wick; sodium condensation at the condenser; and high-temperature sodium evaporation in the wick. The model predicts the temperature profiles within the AMTEC cell walls, the BASE tube temperature profiles, the sodium temperature profile in the artery return, temperature profiles in the evaporator, thermal energy flows throughout the AMTEC cell, all sodium pressure drops from hot BASE tubes to the condenser, the current, voltage, and power output from the cell, and the cell efficiency. This AMTEC cell model is so powerful and flexible that it is used in radioisotope AMTEC power system design, solar AMTEC power system design, and combustion-driven power system design on several projects at Advanced Modular Power Systems, Inc. (AMPS). The model has been successfully validated against actual cell experimental data and its performance predictions agree very well with experimental data on PX-5B cells and other test cells at AMPS. {copyright} {ital 1998 American Institute of Physics.}« less

Construction of 3D Skeleton for Polymer Composites Achieving a High Thermal Conductivity.

PubMed

Yao, Yimin; Sun, Jiajia; Zeng, Xiaoliang; Sun, Rong; Xu, Jian-Bin; Wong, Ching-Ping

2018-03-01

Owing to the growing heat removal issue in modern electronic devices, electrically insulating polymer composites with high thermal conductivity have drawn much attention during the past decade. However, the conventional method to improve through-plane thermal conductivity of these polymer composites usually yields an undesired value (below 3.0 Wm -1 K -1 ). Here, construction of a 3D phonon skeleton is reported composed of stacked boron nitride (BN) platelets reinforced with reduced graphene oxide (rGO) for epoxy composites by the combination of ice-templated and infiltrating methods. At a low filler loading of 13.16 vol%, the resulting 3D BN-rGO/epoxy composites exhibit an ultrahigh through-plane thermal conductivity of 5.05 Wm -1 K -1 as the best thermal-conduction performance reported so far for BN sheet-based composites. Theoretical models qualitatively demonstrate that this enhancement results from the formation of phonon-matching 3D BN-rGO networks, leading to high rates of phonon transport. The strong potential application for thermal management has been demonstrated by the surface temperature variations of the composites with time during heating and cooling. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A nonaffine network model for elastomers undergoing finite deformations

NASA Astrophysics Data System (ADS)

Davidson, Jacob D.; Goulbourne, N. C.

2013-08-01

In this work, we construct a new physics-based model of rubber elasticity to capture the strain softening, strain hardening, and deformation-state dependent response of rubber materials undergoing finite deformations. This model is unique in its ability to capture large-stretch mechanical behavior with parameters that are connected to the polymer chemistry and can also be easily identified with the important characteristics of the macroscopic stress-stretch response. The microscopic picture consists of two components: a crosslinked network of Langevin chains and an entangled network with chains confined to a nonaffine tube. These represent, respectively, changes in entropy due to thermally averaged chain conformations and changes in entropy due to the magnitude of these conformational fluctuations. A simple analytical form for the strain energy density is obtained using Rubinstein and Panyukov's single-chain description of network behavior. The model only depends on three parameters that together define the initial modulus, extent of strain softening, and the onset of strain hardening. Fits to large stretch data for natural rubber, silicone rubber, VHB 4905 (polyacrylate rubber), and b186 rubber (a carbon black-filled rubber) are presented, and a comparison is made with other similar constitutive models of large-stretch rubber elasticity. We demonstrate that the proposed model provides a complete description of elastomers undergoing large deformations for different applied loading configurations. Moreover, since the strain energy is obtained using a clear set of physical assumptions, this model may be tested and used to interpret the results of computer simulation and experiments on polymers of known microscopic structure.

Seismic and thermal structure of the crust and uppermost mantle beneath Antarctica from inversion of multiple seismic datasets

NASA Astrophysics Data System (ADS)

Wiens, D.; Shen, W.; Anandakrishnan, S.; Aster, R. C.; Gerstoft, P.; Bromirski, P. D.; Dalziel, I.; Hansen, S. E.; Heeszel, D.; Huerta, A. D.; Nyblade, A.; Stephen, R. A.; Wilson, T. J.; Winberry, J. P.; Stern, T. A.

2017-12-01

Since the last decade of the 20th century, over 200 broadband seismic stations have been deployed across Antarctica (e.g., temporary networks such as TAMSEIS, AGAP/GAMSEIS, POLENET/ANET, TAMNNET and RIS/DRIS by U.S. geoscientists as well as stations deployed by Japan, Britain, China, Norway, and other countries). In this presentation, we discuss our recent efforts to build reference crustal and uppermost mantle shear velocity (Vs) and thermal models for continental Antarctica based on those seismic arrays. By combing the high resolution Rayleigh wave dispersion maps derived from both ambient noise and teleseismic earthquakes, together with P receiver function waveforms, we develop a 3-D Vs model for the crust and uppermost mantle beneath Central and West Antarctica to a depth of 200 km. Additionally, using this 3-D seismic model to constrain the crustal structure, we re-invert for the upper mantle thermal structure using the surface wave data within a thermodynamic framework and construct a 3-D thermal model for the Antarctic lithosphere. The final product, a high resolution thermal model together with associated uncertainty estimates from the Monte Carlo inversion, allows us to derive lithospheric thickness and surface heat flux maps for much of the continent. West Antarctica shows a much thinner lithosphere ( 50-90 km) than East Antarctica ( 130-230 km), with a sharp transition along the Transantarctic Mountains (TAM). A variety of geological features, including a slower/hotter but highly heterogeneous West Antarctica and a much faster/colder East Antarctic craton, are present in the 3-D seismic/thermal models. Notably, slow seismic velocities observed in the uppermost mantle beneath the southern TAM are interpreted as a signature of lithospheric foundering and replacement with hot asthenosphere. The high resolution image of these features from the 3-D models helps further investigation of the dynamic state of Antarctica's lithosphere and underlying asthenosphere and provides key constraints on the interaction between the solid Earth and the West Antarctic Ice Sheet.

Machine learning with neural networks - a case study of estimating thermal conductivity with ancient well-log data

NASA Astrophysics Data System (ADS)

Harrison, Benjamin; Sandiford, Mike; McLaren, Sandra

2016-04-01

Supervised machine learning algorithms attempt to build a predictive model using empirical data. Their aim is to take a known set of input data along with known responses to the data, and adaptively train a model to generate predictions for new data inputs. A key attraction to their use is the ability to perform as function approximators where the definition of an explicit relationship between variables is infeasible. We present a novel means of estimating thermal conductivity using a supervised self-organising map algorithm, trained on about 150 thermal conductivity measurements, and using a suite of five electric logs common to 14 boreholes. A key motivation of the study was to supplement the small number of direct measurements of thermal conductivity with the decades of borehole data acquired in the Gippsland Basin to produce more confident calculations of surface heat flow. A previous attempt to generate estimates from well-log data in the Gippsland Basin using classic petrophysical log interpretation methods was able to produce reasonable synthetic thermal conductivity logs for only four boreholes. The current study has extended this to a further ten boreholes. Interesting outcomes from the study are: the method appears stable at very low sample sizes (< ~100); the SOM permits quantitative analysis of essentially qualitative uncalibrated well-log data; and the method's moderate success at prediction with minimal effort tuning the algorithm's parameters.

Modeling of heat flow and effective thermal conductivity of fractured media: Analytical and numerical methods

NASA Astrophysics Data System (ADS)

Nguyen, S. T.; Vu, M.-H.; Vu, M. N.; Tang, A. M.

2017-05-01

The present work aims to modeling the thermal conductivity of fractured materials using homogenization-based analytical and pattern-based numerical methods. These materials are considered as a network of cracks distributed inside a solid matrix. Heat flow through such media is perturbed by the crack system. The problem of heat flow across a single crack is firstly investigated. The classical Eshelby's solution, extended to the thermal conduction problem of an ellipsoidal inclusion embedding in an infinite homogeneous matrix, gives an analytical solution of temperature discontinuity across a non-conducting penny-shaped crack. This solution is then validated by the numerical simulation based on the finite elements method. The numerical simulation allows analyzing the effect of crack conductivity. The problem of a single crack is then extended to a medium containing multiple cracks. Analytical estimations for effective thermal conductivity, that take into account the interaction between cracks and their spatial distribution, are developed for the case of non-conducting cracks. Pattern-based numerical method is then employed for both cases non-conducting and conducting cracks. In the case of non-conducting cracks, numerical and analytical methods, both account for the spatial distribution of the cracks, fit perfectly. In the case of conducting cracks, the numerical analyzing of crack conductivity effect shows that highly conducting cracks weakly affect heat flow and the effective thermal conductivity of fractured media.

Thermal Modeling of Permafrost Melt by Overlying Lava Flows with Applications to Flow-associated Outflow Channel Volumes in the Cerberus Plains, Mars

NASA Technical Reports Server (NTRS)

Chase, Z. A. J.; Sakimoto, S. E. H.

2003-01-01

The Cerberus region of Mars has numerous geologically recent fluvial and volcanic features superimposed spatially, with some of them using the same flow channels and apparent vent structures. Lava-water interaction landforms such as psuedocraters suggest some interaction of emplacing lava flows with underlying ground ice or water. This study investigates a related interaction type a region where the emplaced lava might have melted underlying ice in the regolith, as there are small outflow channel networks emerging from the flank flows of a lava shield over a portion of the Eastern Cerberus Rupes. Specifically, we use high-resolution Mars Orbiter Laser Altimeter (MOLA) topography to constrain channel and flow dimensions, and thus estimate the thermal pulse from the emplaced lava into the substrate and the resulting melting durations and refreezing intervals. These preliminary thermal models indicate that the observed flows could easily create thermal pulse(s) sufficient to melt enough ground ice to fill the observed fluvial small outflow channels. Depending on flow eruption timing and hydraulic recharge times, this system could easily have produced multiple thermal pulses and fluvial releases. This specific case suggests that regional small water releases from similar cases may be more common than suspected, and that there is a possibility for future fluvial releases if ground ices are currently present and future volcanic eruptions in this young region are possible.

Effect of a non-thermal, atmospheric-pressure, plasma brush on conversion of model self-etch adhesive formulations compared to conventional photo-polymerization

PubMed Central

Chen, Mingsheng; Zhang, Ying; Yao, Xiaomei; Li, Hao; Yu, Qingsong; Wang, Yong

2012-01-01

Objective To determine the effectiveness and efficiency of non-thermal, atmospheric plasmas for inducing polymerization of model dental self-etch adhesives. Methods The monomer mixtures used were bis-[2-(methacryloyloxy)ethyl] phosphate (2MP) and 2-hydroxyethyl methacrylate (HEMA), with mass ratios of 70/30, 50/50 and 30/70. Water was added to the above formulations: 10–30 wt%. These monomer/water mixtures were treated steadily for 40 s under a non-thermal atmospheric plasma brush working at temperatures from 32° to 35°C. For comparison, photo-initiators were added to the above formulations for photo-polymerization studies, which were light-cured for 40 s. The degree of conversion (DC) of both the plasma- and light-cured samples was measured using FTIR spectroscopy with an attenuated total reflectance attachment. Results The non-thermal plasma brush was effective in inducing polymerization of the model self-etch adhesives. The presence of water did not negatively affect the DC of plasma-cured samples. Indeed, DC values slightly increased, with increasing water content in adhesives: from 58.3% to 68.7% when the water content increased from 10% to 30% in the adhesives with a 50/50 (2MP/HEMA) mass ratio. Conversion values of the plasma-cured groups were higher than those of light-cured samples with the same mass ratio and water content. Spectral differences between the plasma- and light-cured groups indicate subtle structural distinctions in the resultant polymer networks. Significance This research if the first to demonstrate that the non-thermal plasma brush induces polymerization of model adhesives under clinical settings by direct/indirect energy transfer. This device shows promise for polymerization of dental composite restorations having enhanced properties and performance. PMID:23018084

A model for the hydrologic and climatic behavior of water on Mars

NASA Technical Reports Server (NTRS)

Clifford, Stephen M.

1993-01-01

An analysis is carried out of the hydrologic response of a water-rich Mars to climate change and to the physical and thermal evolution of its crust, with particular attention given to the potential role of the subsurface transport, assuming that the current models of insolation-driven change describe reasonably the atmospheric leg of the planet's long-term hydrologic cycle. Among the items considered are the thermal and hydrologic properties of the crust, the potential distribution of ground ice and ground water, the stability and replenishment of equatorial ground ice, basal melting and the polar mass balance, the thermal evolution of the early cryosphere, the recharge of the valley networks and outflow, and several processes that are likely to drive the large-scale vertical and horizontal transport of H2O within the crust. The results lead to the conclusion that subsurface transport has likely played an important role in the geomorphic evolution of the Martian surface and the long-term cycling of H2O between the atmosphere, polar caps, and near-surface crust.

Millimeter and X-Ray Emission from the 5 July 2012 Solar Flare

NASA Astrophysics Data System (ADS)

Tsap, Y. T.; Smirnova, V. V.; Motorina, G. G.; Morgachev, A. S.; Kuznetsov, S. A.; Nagnibeda, V. G.; Ryzhov, V. S.

2018-03-01

The 5 July 2012 solar flare SOL2012-07-05T11:44 (11:39 - 11:49 UT) with an increasing millimeter spectrum between 93 and 140 GHz is considered. We use space and ground-based observations in X-ray, extreme ultraviolet, microwave, and millimeter wave ranges obtained with the Reuven Ramaty High-Energy Solar Spectroscopic Imager, Solar Dynamics Observatory (SDO), Geostationary Operational Environmental Satellite, Radio Solar Telescope Network, and Bauman Moscow State Technical University millimeter radio telescope RT-7.5. The main parameters of thermal and accelerated electrons were determined through X-ray spectral fitting assuming the homogeneous thermal source and thick-target model. From the data of the Atmospheric Imaging Assembly/SDO and differential-emission-measure calculations it is shown that the thermal coronal plasma gives a negligible contribution to the millimeter flare emission. Model calculations suggest that the observed increase of millimeter spectral flux with frequency is determined by gyrosynchrotron emission of high-energy (≳ 300 keV) electrons in the chromosphere. The consequences of the results are discussed in the light of the flare-energy-release mechanisms.

Atomistic Modeling of Thermal Conductivity of Epoxy Nanotube Composites

NASA Astrophysics Data System (ADS)

Fasanella, Nicholas A.; Sundararaghavan, Veera

2016-05-01

The Green-Kubo method was used to investigate the thermal conductivity as a function of temperature for epoxy/single wall carbon nanotube (SWNT) nanocomposites. An epoxy network of DGEBA-DDS was built using the `dendrimer' growth approach, and conductivity was computed by taking into account long-range Coulombic forces via a k-space approach. Thermal conductivity was calculated in the direction perpendicular to, and along the SWNT axis for functionalized and pristine SWNT/epoxy nanocomposites. Inefficient phonon transport at the ends of nanotubes is an important factor in the thermal conductivity of the nanocomposites, and for this reason discontinuous nanotubes were modeled in addition to long nanotubes. The thermal conductivity of the long, pristine SWNT/epoxy system is equivalent to that of an isolated SWNT along its axis, but there was a 27% reduction perpendicular to the nanotube axis. The functionalized, long SWNT/epoxy system had a very large increase in thermal conductivity along the nanotube axis (~700%), as well as the directions perpendicular to the nanotube (64%). The discontinuous nanotubes displayed an increased thermal conductivity along the SWNT axis compared to neat epoxy (103-115% for the pristine SWNT/epoxy, and 91-103% for functionalized SWNT/epoxy system). The functionalized system also showed a 42% improvement perpendicular to the nanotube, while the pristine SWNT/epoxy system had no improvement over epoxy. The thermal conductivity tensor is averaged over all possible orientations to see the effects of randomly orientated nanotubes, and allow for experimental comparison. Excellent agreement is seen for the discontinuous, pristine SWNT/epoxy nanocomposite. These simulations demonstrate there exists a threshold of the SWNT length where the best improvement for a composite system with randomly oriented nanotubes would transition from pristine SWNTs to functionalized SWNTs.

Determination of the Thermal Properties of Sands as Affected by Water Content, Drainage/Wetting, and Porosity Conditions for Sands With Different Grain Sizes

NASA Astrophysics Data System (ADS)

Smits, K. M.; Sakaki, T.; Limsuwat, A.; Illangasekare, T. H.

2009-05-01

It is widely recognized that liquid water, water vapor and temperature movement in the subsurface near the land/atmosphere interface are strongly coupled, influencing many agricultural, biological and engineering applications such as irrigation practices, the assessment of contaminant transport and the detection of buried landmines. In these systems, a clear understanding of how variations in water content, soil drainage/wetting history, porosity conditions and grain size affect the soil's thermal behavior is needed, however, the consideration of all factors is rare as very few experimental data showing the effects of these variations are available. In this study, the effect of soil moisture, drainage/wetting history, and porosity on the thermal conductivity of sandy soils with different grain sizes was investigated. For this experimental investigation, several recent sensor based technologies were compiled into a Tempe cell modified to have a network of sampling ports, continuously monitoring water saturation, capillary pressure, temperature, and soil thermal properties. The water table was established at mid elevation of the cell and then lowered slowly. The initially saturated soil sample was subjected to slow drainage, wetting, and secondary drainage cycles. After liquid water drainage ceased, evaporation was induced at the surface to remove soil moisture from the sample to obtain thermal conductivity data below the residual saturation. For the test soils studied, thermal conductivity increased with increasing moisture content, soil density and grain size while thermal conductivity values were similar for soil drying/wetting behavior. Thermal properties measured in this study were then compared with independent estimates made using empirical models from literature. These soils will be used in a proposed set of experiments in intermediate scale test tanks to obtain data to validate methods and modeling tools used for landmine detection.

Remarks on the chemical Fokker-Planck and Langevin equations: Nonphysical currents at equilibrium.

PubMed

Ceccato, Alessandro; Frezzato, Diego

2018-02-14

The chemical Langevin equation and the associated chemical Fokker-Planck equation are well-known continuous approximations of the discrete stochastic evolution of reaction networks. In this work, we show that these approximations suffer from a physical inconsistency, namely, the presence of nonphysical probability currents at the thermal equilibrium even for closed and fully detailed-balanced kinetic schemes. An illustration is given for a model case.

System-level Analysis of Chilled Water Systems Aboard Naval Ships

DTIC Science & Technology

2015-06-24

developed one-dimensional partial differen- tial equation models that simulate time-dependent hy- drodynamics and heat transport in a piping network...Thermal zone extents. 2) Piping path and diameter. 3) Specifications and locations of chillers, heat ex- changers, pumps and valves. The framework of the... pipes and provides boundary conditions for the end of the connecting pipes . Pumps, valves, bends and heat exchangers are such components. These

Teasing apart the effects of natural and constructed green ...

EPA Pesticide Factsheets

Summer low flows and stream temperature maxima are key drivers affecting the sustainability of fish populations. Thus, it is critical to understand both the natural templates of spatiotemporal variability, how these are shifting due to anthropogenic influences of development and climate change, and how these impacts can be moderated by natural and constructed green infrastructure. Low flow statistics of New England streams have been characterized using a combination of regression equations to describe long-term averages as a function of indicators of hydrologic regime (rain- versus snow-dominated), precipitation, evapotranspiration or temperature, surface water storage, baseflow recession rates, and impervious cover. Difference equations have been constructed to describe interannual variation in low flow as a function of changing air temperature, precipitation, and ocean-atmospheric teleconnection indices. Spatial statistical network models have been applied to explore fine-scale variability of thermal regimes along stream networks in New England as a function of variables describing natural and altered energy inputs, groundwater contributions, and retention time. Low flows exacerbate temperature impacts by reducing thermal inertia of streams to energy inputs. Based on these models, we can construct scenarios of fish habitat suitability using current and projected future climate and the potential for preservation and restoration of historic habitat regimes th

Laser surface fusion of plasma sprayed ceramic turbine seals

NASA Technical Reports Server (NTRS)

Wisander, D. W.; Bill, R. C. (Inventor)

1981-01-01

The thermal shock resistance of a ceramic layer is improved. An improved abradable lining that is deposited on a shroud forming a gas path seal in turbomachinery is emphasized. Improved thermal shock resistance of a shroud is effective through the deliberate introduction of 'benign' cracks. These are microcracks which will not propagate appreciably upon exposure to the thermal shock environment in which a turbine seal must function. Laser surface fusion treatment is used to introduce these microcracks. The ceramic surface is laser scanned to form a continuous dense layer. As this cools and solidifies, shrinkage results in the formation of a very fine crack network. The presence of this deliberately introduced fine crack network precludes the formation of a catastrophic crack during thermal shock exposure.

Influence of the Atmospheric Model on Hanle Diagnostics

NASA Astrophysics Data System (ADS)

Ishikawa, Ryohko; Uitenbroek, Han; Goto, Motoshi; Iida, Yusuke; Tsuneta, Saku

2018-05-01

We clarify the uncertainty in the inferred magnetic field vector via the Hanle diagnostics of the hydrogen Lyman-α line when the stratification of the underlying atmosphere is unknown. We calculate the anisotropy of the radiation field with plane-parallel semi-empirical models under the nonlocal thermal equilibrium condition and derive linear polarization signals for all possible parameters of magnetic field vectors based on an analytical solution of the atomic polarization and Hanle effect. We find that the semi-empirical models of the inter-network region (FAL-A) and network region (FAL-F) show similar degrees of anisotropy in the radiation field, and this similarity results in an acceptable inversion error ( e.g., {˜} 40 G instead of 50 G in field strength and {˜} 100° instead of 90° in inclination) when FAL-A and FAL-F are swapped. However, the semi-empirical models of FAL-C (averaged quiet-Sun model including both inter-network and network regions) and FAL-P (plage regions) yield an atomic polarization that deviates from all other models, which makes it difficult to precisely determine the magnetic field vector if the correct atmospheric model is not known ( e.g., the inversion error is much larger than 40% of the field strength; {>} 70 G instead of 50 G). These results clearly demonstrate that the choice of model atmosphere is important for Hanle diagnostics. As is well known, one way to constrain the average atmospheric stratification is to measure the center-to-limb variation of the linear polarization signals. The dependence of the center-to-limb variations on the atmospheric model is also presented in this paper.

An electrical model of vapor-anode, multitube AMTEC cells[Alkali Metal Thermal to Electric Conversion

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

Tournier, J.M.; El-Genk, M.S.

1998-07-01

A two-dimensional electrical model of vapor-anode, multi-tube AMTEC cells was developed, which included four options of current collector configurations. Simulation results of several cells tested at AFRL showed that electrical losses in the current collector networks and the connecting leads were negligible. The polarization/concentration losses in the TiN electrodes were significant, amounting to 25%--50% of the cell theoretical power, while the contact and BASE ionic losses amounted to less than 16% of the cell theoretical power.

Motion control in free-standing shape-memory actuators

NASA Astrophysics Data System (ADS)

Belmonte, Alberto; Lama, Giuseppe C.; Cerruti, Pierfrancesco; Ambrogi, Veronica; Fernández-Francos, Xavier; De la Flor, Silvia

2018-07-01

In this work, free-standing shape-memory thermally triggered actuators are developed by laminating ‘thiol-epoxy’-based glassy thermoset (GT) and stretched liquid-crystalline network (LCN) films. A sequential curing process was used to obtain GTs with tailored thermomechanical properties and network relaxation dynamics, and also to assemble the final actuator. The actuation extent, rate and time were studied by varying the GT and the heating rate in thermo-actuation with an experimental approach. The results demonstrate that it is possible to tailor the actuation rate and time by designing GT materials with a glass transition temperature close to that of the liquid-crystalline-to-isotropic phase transition of the LCN, thus making it possible to couple the two processes. Such coupling is also possible in rapid heating processes even when the glass transition temperature of the GT is clearly lower than the isotropization temperature of the LCN, depending on the network relaxation dynamics of the GT and the presence of thermal gradients within the actuators. Interestingly, varying the GT network relaxation dynamics does not affect the actuation extent. As predicted by the analytical model developed in our previous work, the modulus of the GT layer is mainly responsible for the actuation extent. Finally, to demonstrate the enhanced control of the actuation, specifically designed actuators were assembled in a three-dimensional actuating device able to make complex motions (including ‘S-type’ bending). This approach makes it possible to engineer advanced functional materials for application in self-adaptable structures and soft robotics.

Adaptive Neuro-Fuzzy Inference System (ANFIS)-Based Models for Predicting the Weld Bead Width and Depth of Penetration from the Infrared Thermal Image of the Weld Pool

NASA Astrophysics Data System (ADS)

Subashini, L.; Vasudevan, M.

2012-02-01

Type 316 LN stainless steel is the major structural material used in the construction of nuclear reactors. Activated flux tungsten inert gas (A-TIG) welding has been developed to increase the depth of penetration because the depth of penetration achievable in single-pass TIG welding is limited. Real-time monitoring and control of weld processes is gaining importance because of the requirement of remoter welding process technologies. Hence, it is essential to develop computational methodologies based on an adaptive neuro fuzzy inference system (ANFIS) or artificial neural network (ANN) for predicting and controlling the depth of penetration and weld bead width during A-TIG welding of type 316 LN stainless steel. In the current work, A-TIG welding experiments have been carried out on 6-mm-thick plates of 316 LN stainless steel by varying the welding current. During welding, infrared (IR) thermal images of the weld pool have been acquired in real time, and the features have been extracted from the IR thermal images of the weld pool. The welding current values, along with the extracted features such as length, width of the hot spot, thermal area determined from the Gaussian fit, and thermal bead width computed from the first derivative curve were used as inputs, whereas the measured depth of penetration and weld bead width were used as output of the respective models. Accurate ANFIS models have been developed for predicting the depth of penetration and the weld bead width during TIG welding of 6-mm-thick 316 LN stainless steel plates. A good correlation between the measured and predicted values of weld bead width and depth of penetration were observed in the developed models. The performance of the ANFIS models are compared with that of the ANN models.

Active transport on disordered microtubule networks: the generalized random velocity model.

PubMed

Kahana, Aviv; Kenan, Gilad; Feingold, Mario; Elbaum, Michael; Granek, Rony

2008-11-01

The motion of small cargo particles on microtubules by means of motor proteins in disordered microtubule networks is investigated theoretically using both analytical tools and computer simulations. Different network topologies in two and three dimensions are considered, one of which has been recently studied experimentally by Salman [Biophys. J. 89, 2134 (2005)]. A generalization of the random velocity model is used to derive the mean-square displacement of the cargo particle. We find that all cases belong to the class of anomalous superdiffusion, which is sensitive mainly to the dimensionality of the network and only marginally to its topology. Yet in three dimensions the motion is very close to simple diffusion, with sublogarithmic corrections that depend on the network topology. When details of the thermal diffusion in the bulk solution are included, no significant change to the asymptotic time behavior is found. However, a small asymmetry in the mean microtubule polarity affects the corresponding long-time behavior. We also study a three-dimensional model of the microtubule network in living animal cells. Three first-passage-time problems of intracellular transport are simulated and analyzed for different motor processivities: (i) cargo that originates near the nucleus and has to reach the membrane, (ii) cargo that originates from the membrane and has to reach the nucleus, and (iii) cargo that leaves the nucleus and has to reach a specific target in the cytoplasm. We conclude that while a higher motor processivity increases the transport efficiency in cases (i) and (ii), in case (iii) it has the opposite effect. We conjecture that the balance between the different network tasks, as manifested in cases (i) and (ii) versus case (iii), may be the reason for the evolutionary choice of a finite motor processivity.

Active transport on disordered microtubule networks: The generalized random velocity model

NASA Astrophysics Data System (ADS)

Kahana, Aviv; Kenan, Gilad; Feingold, Mario; Elbaum, Michael; Granek, Rony

2008-11-01

The motion of small cargo particles on microtubules by means of motor proteins in disordered microtubule networks is investigated theoretically using both analytical tools and computer simulations. Different network topologies in two and three dimensions are considered, one of which has been recently studied experimentally by Salman [Biophys. J. 89, 2134 (2005)]. A generalization of the random velocity model is used to derive the mean-square displacement of the cargo particle. We find that all cases belong to the class of anomalous superdiffusion, which is sensitive mainly to the dimensionality of the network and only marginally to its topology. Yet in three dimensions the motion is very close to simple diffusion, with sublogarithmic corrections that depend on the network topology. When details of the thermal diffusion in the bulk solution are included, no significant change to the asymptotic time behavior is found. However, a small asymmetry in the mean microtubule polarity affects the corresponding long-time behavior. We also study a three-dimensional model of the microtubule network in living animal cells. Three first-passage-time problems of intracellular transport are simulated and analyzed for different motor processivities: (i) cargo that originates near the nucleus and has to reach the membrane, (ii) cargo that originates from the membrane and has to reach the nucleus, and (iii) cargo that leaves the nucleus and has to reach a specific target in the cytoplasm. We conclude that while a higher motor processivity increases the transport efficiency in cases (i) and (ii), in case (iii) it has the opposite effect. We conjecture that the balance between the different network tasks, as manifested in cases (i) and (ii) versus case (iii), may be the reason for the evolutionary choice of a finite motor processivity.

Thermal conductivity in Bi0.5Sb1.5Te3+x and the role of dense dislocation arrays at grain boundaries.

PubMed

Deng, Rigui; Su, Xianli; Zheng, Zheng; Liu, Wei; Yan, Yonggao; Zhang, Qingjie; Dravid, Vinayak P; Uher, Ctirad; Kanatzidis, Mercouri G; Tang, Xinfeng

2018-06-01

Several prominent mechanisms for reduction in thermal conductivity have been shown in recent years to improve the figure of merit for thermoelectric materials. Such a mechanism is a hierarchical all-length-scale architecturing that recognizes the role of all microstructure elements, from atomic to nano to microscales, in reducing (lattice) thermal conductivity. In this context, there have been recent claims of remarkably low (lattice) thermal conductivity in Bi 0.5 Sb 1.5 Te 3 that are attributed to seemingly ordinary grain boundary dislocation networks. These high densities of dislocation networks in Bi 0.5 Sb 1.5 Te 3 were generated via unconventional materials processing with excess Te (which formed liquid phase, thereby facilitating sintering), followed by spark plasma sintering under pressure to squeeze out the liquid. We reproduced a practically identical microstructure, following practically identical processing strategies, but with noticeably different (higher) thermal conductivity than that claimed before. We show that the resultant microstructure is anisotropic, with notable difference of thermal and charge transport properties across and along two orthonormal directions, analogous to anisotropic crystals. Thus, we believe that grain boundary dislocation networks are not the primary cause of enhanced ZT through reduction in thermal conductivity. Instead, we can reproduce the purported high ZT through a favorable but impractical and incorrect combination of thermal conductivity measured along the pressing direction of anisotropy while charge transport measured in the direction perpendicular to the anisotropic direction. We believe that our work underscores the need for consistency in charge and thermal transport measurements for unified and verifiable measurements of thermoelectric (and related) properties and phenomena.

Object localization in handheld thermal images for fireground understanding

NASA Astrophysics Data System (ADS)

Vandecasteele, Florian; Merci, Bart; Jalalvand, Azarakhsh; Verstockt, Steven

2017-05-01

Despite the broad application of the handheld thermal imaging cameras in firefighting, its usage is mostly limited to subjective interpretation by the person carrying the device. As remedies to overcome this limitation, object localization and classification mechanisms could assist the fireground understanding and help with the automated localization, characterization and spatio-temporal (spreading) analysis of the fire. An automated understanding of thermal images can enrich the conventional knowledge-based firefighting techniques by providing the information from the data and sensing-driven approaches. In this work, transfer learning is applied on multi-labeling convolutional neural network architectures for object localization and recognition in monocular visual, infrared and multispectral dynamic images. Furthermore, the possibility of analyzing fire scene images is studied and their current limitations are discussed. Finally, the understanding of the room configuration (i.e., objects location) for indoor localization in reduced visibility environments and the linking with Building Information Models (BIM) are investigated.

Power flow analysis and optimal locations of resistive type superconducting fault current limiters.

PubMed

Zhang, Xiuchang; Ruiz, Harold S; Geng, Jianzhao; Shen, Boyang; Fu, Lin; Zhang, Heng; Coombs, Tim A

2016-01-01

Based on conventional approaches for the integration of resistive-type superconducting fault current limiters (SFCLs) on electric distribution networks, SFCL models largely rely on the insertion of a step or exponential resistance that is determined by a predefined quenching time. In this paper, we expand the scope of the aforementioned models by considering the actual behaviour of an SFCL in terms of the temperature dynamic power-law dependence between the electrical field and the current density, characteristic of high temperature superconductors. Our results are compared to the step-resistance models for the sake of discussion and clarity of the conclusions. Both SFCL models were integrated into a power system model built based on the UK power standard, to study the impact of these protection strategies on the performance of the overall electricity network. As a representative renewable energy source, a 90 MVA wind farm was considered for the simulations. Three fault conditions were simulated, and the figures for the fault current reduction predicted by both fault current limiting models have been compared in terms of multiple current measuring points and allocation strategies. Consequently, we have shown that the incorporation of the E - J characteristics and thermal properties of the superconductor at the simulation level of electric power systems, is crucial for estimations of reliability and determining the optimal locations of resistive type SFCLs in distributed power networks. Our results may help decision making by distribution network operators regarding investment and promotion of SFCL technologies, as it is possible to determine the maximum number of SFCLs necessary to protect against different fault conditions at multiple locations.

Thermalnet: a Deep Convolutional Network for Synthetic Thermal Image Generation

NASA Astrophysics Data System (ADS)

Kniaz, V. V.; Gorbatsevich, V. S.; Mizginov, V. A.

2017-05-01

Deep convolutional neural networks have dramatically changed the landscape of the modern computer vision. Nowadays methods based on deep neural networks show the best performance among image recognition and object detection algorithms. While polishing of network architectures received a lot of scholar attention, from the practical point of view the preparation of a large image dataset for a successful training of a neural network became one of major challenges. This challenge is particularly profound for image recognition in wavelengths lying outside the visible spectrum. For example no infrared or radar image datasets large enough for successful training of a deep neural network are available to date in public domain. Recent advances of deep neural networks prove that they are also capable to do arbitrary image transformations such as super-resolution image generation, grayscale image colorisation and imitation of style of a given artist. Thus a natural question arise: how could be deep neural networks used for augmentation of existing large image datasets? This paper is focused on the development of the Thermalnet deep convolutional neural network for augmentation of existing large visible image datasets with synthetic thermal images. The Thermalnet network architecture is inspired by colorisation deep neural networks.

Dendrimersomes Exhibit Lamellar-to-Sponge Phase Transitions.

PubMed

Wilner, Samantha E; Xiao, Qi; Graber, Zachary T; Sherman, Samuel E; Percec, Virgil; Baumgart, Tobias

2018-05-15

Lamellar to nonlamellar membrane shape transitions play essential roles in key cellular processes, such as membrane fusion and fission, and occur in response to external stimuli, including drug treatment and heat. A subset of these transitions can be modeled by means of thermally inducible amphiphile assemblies. We previously reported on mixtures of hydrogenated, fluorinated, and hybrid Janus dendrimers (JDs) that self-assemble into complex dendrimersomes (DMSs), including dumbbells, and serve as promising models for understanding the complexity of biological membranes. Here we show, by means of a variety of complementary techniques, that DMSs formed by single JDs or by mixtures of JDs undergo a thermally induced lamellar-to-sponge transition. Consistent with the formation of a three-dimensional bilayer network, we show that DMSs become more permeable to water-soluble fluorophores after transitioning to the sponge phase. These DMSs may be useful not only in modeling isotropic membrane rearrangements of biological systems but also in drug delivery since nonlamellar delivery vehicles can promote endosomal disruption and cargo release.

Pyroelectric Energy Scavenging Techniques for Self-Powered Nuclear Reactor Wireless Sensor Networks

DOE PAGES

Hunter, Scott Robert; Lavrik, Nickolay V; Datskos, Panos G; ...

2014-11-01

Recent advances in technologies for harvesting waste thermal energy from ambient environments present an opportunity to implement truly wireless sensor nodes in nuclear power plants. These sensors could continue to operate during extended station blackouts and during periods when operation of the plant s internal power distribution system has been disrupted. The energy required to power the wireless sensors must be generated using energy harvesting techniques from locally available energy sources, and the energy consumption within the sensor circuitry must therefore be low to minimize power and hence the size requirements of the energy harvester. Harvesting electrical energy from thermalmore » energy sources can be achieved using pyroelectric or thermoelectric conversion techniques. Recent modeling and experimental studies have shown that pyroelectric techniques can be cost competitive with thermoelectrics in self powered wireless sensor applications and, using new temperature cycling techniques, has the potential to be several times as efficient as thermoelectrics under comparable operating conditions. The development of a new thermal energy harvester concept, based on temperature cycled pyroelectric thermal-to-electrical energy conversion, is outlined. This paper outlines the modeling of cantilever and pyroelectric structures and single element devices that demonstrate the potential of this technology for the development of high efficiency thermal-to-electrical energy conversion devices.« less

Pyroelectric Energy Scavenging Techniques for Self-Powered Nuclear Reactor Wireless Sensor Networks

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

Hunter, Scott Robert; Lavrik, Nickolay V; Datskos, Panos G

Recent advances in technologies for harvesting waste thermal energy from ambient environments present an opportunity to implement truly wireless sensor nodes in nuclear power plants. These sensors could continue to operate during extended station blackouts and during periods when operation of the plant s internal power distribution system has been disrupted. The energy required to power the wireless sensors must be generated using energy harvesting techniques from locally available energy sources, and the energy consumption within the sensor circuitry must therefore be low to minimize power and hence the size requirements of the energy harvester. Harvesting electrical energy from thermalmore » energy sources can be achieved using pyroelectric or thermoelectric conversion techniques. Recent modeling and experimental studies have shown that pyroelectric techniques can be cost competitive with thermoelectrics in self powered wireless sensor applications and, using new temperature cycling techniques, has the potential to be several times as efficient as thermoelectrics under comparable operating conditions. The development of a new thermal energy harvester concept, based on temperature cycled pyroelectric thermal-to-electrical energy conversion, is outlined. This paper outlines the modeling of cantilever and pyroelectric structures and single element devices that demonstrate the potential of this technology for the development of high efficiency thermal-to-electrical energy conversion devices.« less

Modeling thermal inkjet and cell printing process using modified pseudopotential and thermal lattice Boltzmann methods.

PubMed

Sohrabi, Salman; Liu, Yaling

2018-03-01

Pseudopotential lattice Boltzmann methods (LBMs) can simulate a phase transition in high-density ratio multiphase flow systems. If coupled with thermal LBMs through equation of state, they can be used to study instantaneous phase transition phenomena with a high-temperature gradient where only one set of formulations in an LBM system can handle liquid, vapor, phase transition, and heat transport. However, at lower temperatures an unrealistic spurious current at the interface introduces instability and limits its application in real flow system. In this study, we proposed new modifications to the LBM system to minimize a spurious current which enables us to study nucleation dynamic at room temperature. To demonstrate the capabilities of this approach, the thermal ejection process is modeled as one example of a complex flow system. In an inkjet printer, a thermal pulse instantly heats up the liquid in a microfluidic chamber and nucleates bubble vapor providing the pressure pulse necessary to eject droplets at high speed. Our modified method can present a more realistic model of the explosive vaporization process since it can also capture a high-temperature/density gradient at nucleation region. Thermal inkjet technology has been successfully applied for printing cells, but cells are susceptible to mechanical damage or death as they squeeze out of the nozzle head. To study cell deformation, a spring network model, representing cells, is connected to the LBM through the immersed boundary method. Looking into strain and stress distribution of a cell membrane at its most deformed state, it is found that a high stretching rate effectively increases the rupture tension. In other words, membrane deformation energy is released through creation of multiple smaller nanopores rather than big pores. Overall, concurrently simulating multiphase flow, phase transition, heat transfer, and cell deformation in one unified LB platform, we are able to provide a better insight into the bubble dynamic and cell mechanical damage during the printing process.

Modeling thermal inkjet and cell printing process using modified pseudopotential and thermal lattice Boltzmann methods

NASA Astrophysics Data System (ADS)

Sohrabi, Salman; Liu, Yaling

2018-03-01

Pseudopotential lattice Boltzmann methods (LBMs) can simulate a phase transition in high-density ratio multiphase flow systems. If coupled with thermal LBMs through equation of state, they can be used to study instantaneous phase transition phenomena with a high-temperature gradient where only one set of formulations in an LBM system can handle liquid, vapor, phase transition, and heat transport. However, at lower temperatures an unrealistic spurious current at the interface introduces instability and limits its application in real flow system. In this study, we proposed new modifications to the LBM system to minimize a spurious current which enables us to study nucleation dynamic at room temperature. To demonstrate the capabilities of this approach, the thermal ejection process is modeled as one example of a complex flow system. In an inkjet printer, a thermal pulse instantly heats up the liquid in a microfluidic chamber and nucleates bubble vapor providing the pressure pulse necessary to eject droplets at high speed. Our modified method can present a more realistic model of the explosive vaporization process since it can also capture a high-temperature/density gradient at nucleation region. Thermal inkjet technology has been successfully applied for printing cells, but cells are susceptible to mechanical damage or death as they squeeze out of the nozzle head. To study cell deformation, a spring network model, representing cells, is connected to the LBM through the immersed boundary method. Looking into strain and stress distribution of a cell membrane at its most deformed state, it is found that a high stretching rate effectively increases the rupture tension. In other words, membrane deformation energy is released through creation of multiple smaller nanopores rather than big pores. Overall, concurrently simulating multiphase flow, phase transition, heat transfer, and cell deformation in one unified LB platform, we are able to provide a better insight into the bubble dynamic and cell mechanical damage during the printing process.

Using complex networks towards information retrieval and diagnostics in multidimensional imaging

NASA Astrophysics Data System (ADS)

Banerjee, Soumya Jyoti; Azharuddin, Mohammad; Sen, Debanjan; Savale, Smruti; Datta, Himadri; Dasgupta, Anjan Kr; Roy, Soumen

2015-12-01

We present a fresh and broad yet simple approach towards information retrieval in general and diagnostics in particular by applying the theory of complex networks on multidimensional, dynamic images. We demonstrate a successful use of our method with the time series generated from high content thermal imaging videos of patients suffering from the aqueous deficient dry eye (ADDE) disease. Remarkably, network analyses of thermal imaging time series of contact lens users and patients upon whom Laser-Assisted in situ Keratomileusis (Lasik) surgery has been conducted, exhibit pronounced similarity with results obtained from ADDE patients. We also propose a general framework for the transformation of multidimensional images to networks for futuristic biometry. Our approach is general and scalable to other fluctuation-based devices where network parameters derived from fluctuations, act as effective discriminators and diagnostic markers.

Using complex networks towards information retrieval and diagnostics in multidimensional imaging.

PubMed

Banerjee, Soumya Jyoti; Azharuddin, Mohammad; Sen, Debanjan; Savale, Smruti; Datta, Himadri; Dasgupta, Anjan Kr; Roy, Soumen

2015-12-02

We present a fresh and broad yet simple approach towards information retrieval in general and diagnostics in particular by applying the theory of complex networks on multidimensional, dynamic images. We demonstrate a successful use of our method with the time series generated from high content thermal imaging videos of patients suffering from the aqueous deficient dry eye (ADDE) disease. Remarkably, network analyses of thermal imaging time series of contact lens users and patients upon whom Laser-Assisted in situ Keratomileusis (Lasik) surgery has been conducted, exhibit pronounced similarity with results obtained from ADDE patients. We also propose a general framework for the transformation of multidimensional images to networks for futuristic biometry. Our approach is general and scalable to other fluctuation-based devices where network parameters derived from fluctuations, act as effective discriminators and diagnostic markers.

Using complex networks towards information retrieval and diagnostics in multidimensional imaging

PubMed Central

Banerjee, Soumya Jyoti; Azharuddin, Mohammad; Sen, Debanjan; Savale, Smruti; Datta, Himadri; Dasgupta, Anjan Kr; Roy, Soumen

2015-01-01

We present a fresh and broad yet simple approach towards information retrieval in general and diagnostics in particular by applying the theory of complex networks on multidimensional, dynamic images. We demonstrate a successful use of our method with the time series generated from high content thermal imaging videos of patients suffering from the aqueous deficient dry eye (ADDE) disease. Remarkably, network analyses of thermal imaging time series of contact lens users and patients upon whom Laser-Assisted in situ Keratomileusis (Lasik) surgery has been conducted, exhibit pronounced similarity with results obtained from ADDE patients. We also propose a general framework for the transformation of multidimensional images to networks for futuristic biometry. Our approach is general and scalable to other fluctuation-based devices where network parameters derived from fluctuations, act as effective discriminators and diagnostic markers. PMID:26626047

A stream temperature model for the Peace-Athabasca River basin

NASA Astrophysics Data System (ADS)

Morales-Marin, L. A.; Rokaya, P.; Wheater, H. S.; Lindenschmidt, K. E.

2017-12-01

Water temperature plays a fundamental role in water ecosystem functioning. Because it regulates flow energy and metabolic rates in organism productivity over a broad spectrum of space and time scales, water temperature constitutes an important indicator of aquatic ecosystems health. In cold region basins, stream water temperature modelling is also fundamental to predict ice freeze-up and break-up events in order to improve flood management. Multiple model approaches such as linear and multivariable regression methods, neural network and thermal energy budged models have been developed and implemented to simulate stream water temperature. Most of these models have been applied to specific stream reaches and trained using observed data, but very little has been done to simulate water temperature in large catchment river networks. We present the coupling of RBM model, a semi-Lagrangian water temperature model for advection-dominated river system, and MESH, a semi-distributed hydrological model, to simulate stream water temperature in river catchments. The coupled models are implemented in the Peace-Athabasca River basin in order to analyze the variation in stream temperature regimes under changing hydrological and meteorological conditions. Uncertainty of stream temperature simulations is also assessed in order to determine the degree of reliability of the estimates.

Winter risk estimations through infrared cameras an principal component analysis

NASA Astrophysics Data System (ADS)

Marchetti, M.; Dumoulin, J.; Ibos, L.

2012-04-01

Thermal mapping has been implemented since the late eighties to measure road pavement temperature along with some other atmospheric parameters to establish a winter risk describing the susceptibility of road network to ice occurrence. Measurements are done using a vehicle circulating on the road network in various road weather conditions. When the dew point temperature drops below road surface temperature a risk of ice occurs and therefore a loss of grip risk for circulating vehicles. To avoid too much influence of the sun, and to see the thermal behavior of the pavement enhanced, thermal mapping is usually done before dawn during winter time. That is when the energy accumulated by the road during daytime is mainly dissipated (by radiation, by conduction and by convection) and before the road structure starts a new cycle. This analysis is mainly done when a new road network is built, or when some major pavement changes are made, or when modifications in the road surroundings took place that might affect the thermal heat balance. This helps road managers to install sensors to monitor road status on specific locations identified as dangerous, or simply to install specific road signs. Measurements are anyhow time-consuming. Indeed, a whole road network can hardly be analysed at once, and has to be partitioned in stretches that could be done in the open time window to avoid temperature artefacts due to a rising sun. The LRPC Nancy has been using a thermal mapping vehicle with now two infrared cameras. Road events were collected by the operator to help the analysis of the network thermal response. A conventional radiometer with appropriate performances was used as a reference. The objective of the work was to compare results from the radiometer and the cameras. All the atmospheric parameters measured by the different sensors such as air temperature and relative humidity were used as input parameters for the infrared camera when recording thermal images. Road thermal heterogeneities were clearly identified, while usually missed by a conventional radiometer. In the case presented here, the two lanes of the road could be properly observed. Promising perspectives appeared to increase the measurement rate. Furthermore, to cope with the climatic constraints of the winter measurements as to build a dynamic winter risk, a multivariate data analysis approach was implemented. Principal component analysis was performed and enabled to set up of dynamic thermal signature with a great agreement between statistical results and field measurements.

UTCI—Why another thermal index?

NASA Astrophysics Data System (ADS)

Jendritzky, Gerd; de Dear, Richard; Havenith, George

2012-05-01

Existing procedures for the assessment of the thermal environment in the fields of public weather services, public health systems, precautionary planning, urban design, tourism and recreation and climate impact research exhibit significant shortcomings. This is most evident for simple (mostly two-parameter) indices, when comparing them to complete heat budget models developed since the 1960s. ISB Commission 6 took up the idea of developing a Universal Thermal Climate Index (UTCI) based on the most advanced multi-node model of thermoregulation representing progress in science within the last three to four decades, both in thermo-physiological and heat exchange theory. Creating the essential research synergies for the development of UTCI required pooling the resources of multidisciplinary experts in the fields of thermal physiology, mathematical modelling, occupational medicine, meteorological data handling (in particular radiation modelling) and application development in a network. It was possible to extend the expertise of ISB Commission 6 substantially by COST (a European programme promoting Cooperation in Science and Technology) Action 730 so that finally over 45 scientists from 23 countries (Australia, Canada, Israel, several Europe countries, New Zealand, and the United States) worked together. The work was performed under the umbrella of the WMO Commission on Climatology (CCl). After extensive evaluations, Fiala's multi-node human physiology and thermal comfort model (FPC) was adopted for this study. The model was validated extensively, applying as yet unused data from other research groups, and extended for the purposes of the project. This model was coupled with a state-of-the-art clothing model taking into consideration behavioural adaptation of clothing insulation by the general urban population in response to actual environmental temperature. UTCI was then derived conceptually as an equivalent temperature (ET). Thus, for any combination of air temperature, wind, radiation, and humidity (stress), UTCI is defined as the isothermal air temperature of the reference condition that would elicit the same dynamic response (strain) of the physiological model. As UTCI is based on contemporary science its use will standardise applications in the major fields of human biometeorology, thus making research results comparable and physiologically relevant.

Improving Shade Modelling in a Regional River Temperature Model Using Fine-Scale LIDAR Data

NASA Astrophysics Data System (ADS)

Hannah, D. M.; Loicq, P.; Moatar, F.; Beaufort, A.; Melin, E.; Jullian, Y.

2015-12-01

Air temperature is often considered as a proxy of the stream temperature to model the distribution areas of aquatic species water temperature is not available at a regional scale. To simulate the water temperature at a regional scale (105 km²), a physically-based model using the equilibrium temperature concept and including upstream-downstream propagation of the thermal signal was developed and applied to the entire Loire basin (Beaufort et al., submitted). This model, called T-NET (Temperature-NETwork) is based on a hydrographical network topology. Computations are made hourly on 52,000 reaches which average 1.7 km long in the Loire drainage basin. The model gives a median Root Mean Square Error of 1.8°C at hourly time step on the basis of 128 water temperature stations (2008-2012). In that version of the model, tree shadings is modelled by a constant factor proportional to the vegetation cover on 10 meters sides the river reaches. According to sensitivity analysis, improving the shade representation would enhance T-NET accuracy, especially for the maximum daily temperatures, which are currently not very well modelized. This study evaluates the most efficient way (accuracy/computing time) to improve the shade model thanks to 1-m resolution LIDAR data available on tributary of the LoireRiver (317 km long and an area of 8280 km²). Two methods are tested and compared: the first one is a spatially explicit computation of the cast shadow for every LIDAR pixel. The second is based on averaged vegetation cover characteristics of buffers and reaches of variable size. Validation of the water temperature model is made against 4 temperature sensors well spread along the stream, as well as two airborne thermal infrared imageries acquired in summer 2014 and winter 2015 over a 80 km reach. The poster will present the optimal length- and crosswise scale to characterize the vegetation from LIDAR data.

Refined Three-Dimensional Modelling of Thermally-Driven Flow in the Bormio System (Central Italian Alps)

NASA Astrophysics Data System (ADS)

Volpi, Giorgio; Riva, Federico; Frattini, Paolo; Battista Crosta, Giovanni; Magri, Fabien

2016-04-01

Thermal springs are widespread in the European Alps, where more than 80 geothermal sites are known and exploited. The quantitative assessment of those thermal flow systems is a challenging issue and requires accurate conceptual model and a thorough understanding of thermo-hydraulic properties of the aquifers. Accordingly in the last years, several qualitative studies were carried out to understand the heat and fluid transport processes driving deep fluids from the reservoir to the springs. Our work focused on thermal circulation and fluid outflows of the area around Bormio (Central Italian Alps), where nine geothermal springs discharge from dolomite bodies located close to a regional alpine thrust, called the Zebrù Line. At this site, water is heated in deep circulation systems and vigorously upwells at temperature of about 40°C. The aim of this paper is to explore the mechanisms of heat and fluid transport in the Bormio area by carrying out refined steady and transient three-dimensional finite element simulations of thermally-driven flow and to quantitatively assess the source area of the thermal waters. The full regional model (ca. 700 km2) is discretized with a highly refined triangular finite element planar grid obtained with Midas GTS NX software. The structural 3D features of the regional Zebrù thrust are built by interpolating series of geological cross sections using Fracman. A script was developed to convert and implement the thrust grid into FEFLOW mesh that comprises ca. 4 million elements. The numerical results support the observed discharge rates and temperature field within the simulated domain. Flow and temperature patterns suggest that thermal groundwater flows through a deep system crossing both sedimentary and metamorphic lithotypes, and a fracture network associated to the thrust system. Besides providing a numerical framework to simulate complex fractured systems, this example gives insights into the influence of deep alpine structures on groundwater circulation that underlies the development of many hydrothermal systems.

Method of fabricating an abradable gas path seal

NASA Technical Reports Server (NTRS)

Bill, R. C.; Wisander, D. W. (Inventor)

1984-01-01

The thermal shock resistance of a ceramic layer is improved. The invention is particularly directed to an improved abradable lining that is deposited on shroud forming a gas path in turbomachinery. Improved thermal shock resistance of a shroud is effected through the deliberate introduction of benign cracks. These are microcracks which will not propagate appreciably upon exposure to the thermal shock environment in which a turbine seal must function. Laser surface fusion treatment is used to introduce these microcracks. The ceramic surface is laser scanned to form a continuous dense layer. As this layer cools and solidifies, shrinkage results in the formation of a very fine crack network. The presence of this deliberately introduced fine crack network precludes the formation of a catastrophic crack during thermal shock exposure.

USA National Phenology Network's volunteer-contributed observations yield predictive models of phenological transitions.

PubMed

Crimmins, Theresa M; Crimmins, Michael A; Gerst, Katharine L; Rosemartin, Alyssa H; Weltzin, Jake F

2017-01-01

In support of science and society, the USA National Phenology Network (USA-NPN) maintains a rapidly growing, continental-scale, species-rich dataset of plant and animal phenology observations that with over 10 million records is the largest such database in the United States. The aim of this study was to explore the potential that exists in the broad and rich volunteer-collected dataset maintained by the USA-NPN for constructing models predicting the timing of phenological transition across species' ranges within the continental United States. Contributed voluntarily by professional and citizen scientists, these opportunistically collected observations are characterized by spatial clustering, inconsistent spatial and temporal sampling, and short temporal depth (2009-present). Whether data exhibiting such limitations can be used to develop predictive models appropriate for use across large geographic regions has not yet been explored. We constructed predictive models for phenophases that are the most abundant in the database and also relevant to management applications for all species with available data, regardless of plant growth habit, location, geographic extent, or temporal depth of the observations. We implemented a very basic model formulation-thermal time models with a fixed start date. Sufficient data were available to construct 107 individual species × phenophase models. Remarkably, given the limited temporal depth of this dataset and the simple modeling approach used, fifteen of these models (14%) met our criteria for model fit and error. The majority of these models represented the "breaking leaf buds" and "leaves" phenophases and represented shrub or tree growth forms. Accumulated growing degree day (GDD) thresholds that emerged ranged from 454 GDDs (Amelanchier canadensis-breaking leaf buds) to 1,300 GDDs (Prunus serotina-open flowers). Such candidate thermal time thresholds can be used to produce real-time and short-term forecast maps of the timing of these phenophase transition. In addition, many of the candidate models that emerged were suitable for use across the majority of the species' geographic ranges. Real-time and forecast maps of phenophase transitions could support a wide range of natural resource management applications, including invasive plant management, issuing asthma and allergy alerts, and anticipating frost damage for crops in vulnerable states. Our finding that several viable thermal time threshold models that work across the majority of the species ranges could be constructed from the USA-NPN database provides clear evidence that great potential exists this dataset to develop more enhanced predictive models for additional species and phenophases. Further, the candidate models that emerged have immediate utility for supporting a wide range of management applications.

Neuro-Fuzzy Computational Technique to Control Load Frequency in Hydro-Thermal Interconnected Power System

NASA Astrophysics Data System (ADS)

Prakash, S.; Sinha, S. K.

2015-09-01

In this research work, two areas hydro-thermal power system connected through tie-lines is considered. The perturbation of frequencies at the areas and resulting tie line power flows arise due to unpredictable load variations that cause mismatch between the generated and demanded powers. Due to rising and falling power demand, the real and reactive power balance is harmed; hence frequency and voltage get deviated from nominal value. This necessitates designing of an accurate and fast controller to maintain the system parameters at nominal value. The main purpose of system generation control is to balance the system generation against the load and losses so that the desired frequency and power interchange between neighboring systems are maintained. The intelligent controllers like fuzzy logic, artificial neural network (ANN) and hybrid fuzzy neural network approaches are used for automatic generation control for the two area interconnected power systems. Area 1 consists of thermal reheat power plant whereas area 2 consists of hydro power plant with electric governor. Performance evaluation is carried out by using intelligent (ANFIS, ANN and fuzzy) control and conventional PI and PID control approaches. To enhance the performance of controller sliding surface i.e. variable structure control is included. The model of interconnected power system has been developed with all five types of said controllers and simulated using MATLAB/SIMULINK package. The performance of the intelligent controllers has been compared with the conventional PI and PID controllers for the interconnected power system. A comparison of ANFIS, ANN, Fuzzy and PI, PID based approaches shows the superiority of proposed ANFIS over ANN, fuzzy and PI, PID. Thus the hybrid fuzzy neural network controller has better dynamic response i.e., quick in operation, reduced error magnitude and minimized frequency transients.

Interfacing the Generalized Fluid System Simulation Program with the SINDA/G Thermal Program

NASA Technical Reports Server (NTRS)

Schallhorn, Paul; Palmiter, Christopher; Farmer, Jeffery; Lycans, Randall; Tiller, Bruce

2000-01-01

A general purpose, one dimensional fluid flow code has been interfaced with the thermal analysis program SINDA/G. The flow code, GFSSP, is capable of analyzing steady state and transient flow in a complex network. The flow code is capable of modeling several physical phenomena including compressibility effects, phase changes, body forces (such as gravity and centrifugal) and mixture thermodynamics for multiple species. The addition of GFSSP to SINDA/G provides a significant improvement in convective heat transfer modeling for SINDA/G. The interface development was conducted in two phases. This paper describes the first (which allows for steady and quasi-steady - unsteady solid, steady fluid - conjugate heat transfer modeling). The second (full transient conjugate heat transfer modeling) phase of the interface development will be addressed in a later paper. Phase 1 development has been benchmarked to an analytical solution with excellent agreement. Additional test cases for each development phase demonstrate desired features of the interface. The results of the benchmark case, three additional test cases and a practical application are presented herein.

A method of optimized neural network by L-M algorithm to transformer winding hot spot temperature forecasting

NASA Astrophysics Data System (ADS)

Wei, B. G.; Wu, X. Y.; Yao, Z. F.; Huang, H.

2017-11-01

Transformers are essential devices of the power system. The accurate computation of the highest temperature (HST) of a transformer’s windings is very significant, as for the HST is a fundamental parameter in controlling the load operation mode and influencing the life time of the insulation. Based on the analysis of the heat transfer processes and the thermal characteristics inside transformers, there is taken into consideration the influence of factors like the sunshine, external wind speed etc. on the oil-immersed transformers. Experimental data and the neural network are used for modeling and protesting of the HST, and furthermore, investigations are conducted on the optimization of the structure and algorithms of neutral network are conducted. Comparison is made between the measured values and calculated values by using the recommended algorithm of IEC60076 and by using the neural network algorithm proposed by the authors; comparison that shows that the value computed with the neural network algorithm approximates better the measured value than the value computed with the algorithm proposed by IEC60076.

Piezocomposite Actuator Arrays for Correcting and Controlling Wavefront Error in Reflectors

NASA Technical Reports Server (NTRS)

Bradford, Samuel Case; Peterson, Lee D.; Ohara, Catherine M.; Shi, Fang; Agnes, Greg S.; Hoffman, Samuel M.; Wilkie, William Keats

2012-01-01

Three reflectors have been developed and tested to assess the performance of a distributed network of piezocomposite actuators for correcting thermal deformations and total wave-front error. The primary testbed article is an active composite reflector, composed of a spherically curved panel with a graphite face sheet and aluminum honeycomb core composite, and then augmented with a network of 90 distributed piezoelectric composite actuators. The piezoelectric actuator system may be used for correcting as-built residual shape errors, and for controlling low-order, thermally-induced quasi-static distortions of the panel. In this study, thermally-induced surface deformations of 1 to 5 microns were deliberately introduced onto the reflector, then measured using a speckle holography interferometer system. The reflector surface figure was subsequently corrected to a tolerance of 50 nm using the actuators embedded in the reflector's back face sheet. Two additional test articles were constructed: a borosilicate at window at 150 mm diameter with 18 actuators bonded to the back surface; and a direct metal laser sintered reflector with spherical curvature, 230 mm diameter, and 12 actuators bonded to the back surface. In the case of the glass reflector, absolute measurements were performed with an interferometer and the absolute surface was corrected. These test articles were evaluated to determine their absolute surface control capabilities, as well as to assess a multiphysics modeling effort developed under this program for the prediction of active reflector response. This paper will describe the design, construction, and testing of active reflector systems under thermal loads, and subsequent correction of surface shape via distributed peizeoelctric actuation.

Spatial Estimation of Soil Moisture Using Synthetic Aperture Radar in Alaska

NASA Astrophysics Data System (ADS)

Meade, N. G.; Hinzman, L. D.; Kane, D. L.

1999-01-01

A spatially distributed Model of Arctic Thermal and Hydrologic processes (MATH) has been developed. One of the attributes of this model is the spatial and temporal prediction of soil moisture in the active layer. The spatially distributed output from this model required verification data obtained through remote sensing to assess performance at the watershed scale independently. Therefore, a neural network was trained to predict soil moisture contents near the ground surface. The input to train the neural network is synthetic aperture radar (SAR) pixel value, and field measurements of soil moisture, and vegetation, which were used as a surrogate for surface roughness. Once the network was trained, soil moisture predictions were made based on SAR pixel value and vegetation. These results were then used for comparison with results from the hydrologic model. The quality of neural network input was less than anticipated. Our digital elevation model (DEM) was not of high enough resolution to allow exact co-registration with soil moisture measurements; therefore, the statistical correlations were not as good as hoped. However, the spatial pattern of the SAR derived soil moisture contents compares favorably with the hydrologic MATH model results. Primary surface parameters that effect SAR include topography, surface roughness, vegetation cover and soil texture. Single parameters that are considered to influence SAR include incident angle of the radar, polarization of the radiation, signal strength and returning signal integration, to name a few. These factors influence the reflectance, but if one adequately quantifies the influences of terrain and roughness, it is considered possible to extract information on soil moisture from SAR imagery analysis and in turn use SAR imagery to validate hydrologic models

Protein thermal denaturation is modulated by central residues in the protein structure network.

PubMed

Souza, Valquiria P; Ikegami, Cecília M; Arantes, Guilherme M; Marana, Sandro R

2016-03-01

Network structural analysis, known as residue interaction networks or graphs (RIN or RIG, respectively) or protein structural networks or graphs (PSN or PSG, respectively), comprises a useful tool for detecting important residues for protein function, stability, folding and allostery. In RIN, the tertiary structure is represented by a network in which residues (nodes) are connected by interactions (edges). Such structural networks have consistently presented a few central residues that are important for shortening the pathways linking any two residues in a protein structure. To experimentally demonstrate that central residues effectively participate in protein properties, mutations were directed to seven central residues of the β-glucosidase Sfβgly (β-D-glucoside glucohydrolase; EC 3.2.1.21). These mutations reduced the thermal stability of the enzyme, as evaluated by changes in transition temperature (Tm ) and the denaturation rate at 45 °C. Moreover, mutations directed to the vicinity of a central residue also caused significant decreases in the Tm of Sfβgly and clearly increased the unfolding rate constant at 45 °C. However, mutations at noncentral residues or at surrounding residues did not affect the thermal stability of Sfβgly. Therefore, the data reported in the present study suggest that the perturbation of the central residues reduced the stability of the native structure of Sfβgly. These results are in agreement with previous findings showing that networks are robust, whereas attacks on central nodes cause network failure. Finally, the present study demonstrates that central residues underlie the functional properties of proteins. © 2016 Federation of European Biochemical Societies.

Assessing high shares of renewable energies in district heating systems - a case study for the city of Herten

NASA Astrophysics Data System (ADS)

Aydemir, Ali; Popovski, Eftim; Bellstädt, Daniel; Fleiter, Tobias; Büchele, Richard

2017-11-01

Many earlier studies have assessed the DH generation mix without taking explicitly into account future changes in the building stock and heat demand. The approach of this study consists of three steps that combine stock modeling, energy demand forecasting, and simulation of different energy technologies. First, a detailed residential building stock model for Herten is constructed by using remote sensing together with a typology for the German building stock. Second, a bottom-up simulation model is used which calculates the thermal energy demand based on energy-related investments in buildings in order to forecast the thermal demand up to 2050. Third, solar thermal fields in combination with large-scale heat pumps are sized as an alternative to the current coal-fired CHPs. We finally assess cost of heat and CO2 reduction for these units for two scenarios which differ with regard to the DH expansion. It can be concluded that up to 2030 and 2050 a substantial reduction in buildings heat demand due to the improved building insulation is expected. The falling heat demand in the DH substantially reduces the economic feasibility of new RES generation capacity. This reduction might be compensated by continuously connecting apartment buildings to the DH network until 2050.

Comparison of Analytical and Numerical Performance Predictions for an International Space Station Node 3 Internal Active Thermal Control System Regenerative Heat Exchanger

NASA Technical Reports Server (NTRS)

Wise, Stephen A.; Holt, James M.

2002-01-01

The complexity of International Space Station (ISS) systems modeling often necessitates the concurrence of various dissimilar, parallel analysis techniques to validate modeling. This was the case with a feasibility and performance study of the ISS Node 3 Regenerative Heat Exchanger (RHX). A thermo-hydraulic network model was created and analyzed in SINDA/FLUINT. A less complex, closed form solution of the systems dynamics was created using an Excel Spreadsheet. The purpose of this paper is to provide a brief description of the modeling processes utilized, the results and benefits of each to the ISS Node 3 RHX study.

Comparison of Analytical and Numerical Performance Predictions for a Regenerative Heat Exchanger in the International Space Station Node 3 Internal Active Thermal Control System

NASA Technical Reports Server (NTRS)

Wise, Stephen A.; Holt, James M.; Turner, Larry D. (Technical Monitor)

2001-01-01

The complexity of International Space Station (ISS) systems modeling often necessitates the concurrence of various dissimilar, parallel analysis techniques to validate modeling. This was the case with a feasibility and performance study of the ISS Node 3 Regenerative Heat Exchanger (RHX). A thermo-hydraulic network model was created and analyzed in SINDA/FLUINT. A less complex, closed form solution of the system dynamics was created using Excel. The purpose of this paper is to provide a brief description of the modeling processes utilized, the results and benefits of each to the ISS Node 3 RHX study.

Mechano-genetic DNA hydrogels as a simple, reconstituted model to probe the effect of active fluctuations on gene transcription

NASA Astrophysics Data System (ADS)

Nguyen, Dan; Saleh, Omar

Active fluctuations - non-directed fluctuations attributable, not to thermal energy, but to non-equilibrium processes - are thought to influence biology by increasing the diffusive motion of biomolecules. Dense DNA regions within cells (i.e. chromatin) are expected to exhibit such phenomena, as they are cross-linked networks that continually experience propagating forces arising from dynamic cellular activity. Additional agitation within these gene-encoding DNA networks could have potential genetic consequences. By changing the local mobility of transcriptional machinery and regulatory proteins towards/from their binding sites, and thereby influencing transcription rates, active fluctuations could prove to be a physical means of modulating gene expression. To begin probing this effect, we construct genetic DNA hydrogels, as a simple, reconstituted model of chromatin, and quantify transcriptional output from these hydrogels in the presence/absence of active fluctuations.

A Case Study of Wind-PV-Thermal-Bundled AC/DC Power Transmission from a Weak AC Network

NASA Astrophysics Data System (ADS)

Xiao, H. W.; Du, W. J.; Wang, H. F.; Song, Y. T.; Wang, Q.; Ding, J.; Chen, D. Z.; Wei, W.

2017-05-01

Wind power generation and photovoltaic (PV) power generation bundled with the support by conventional thermal generation enables the generation controllable and more suitable for being sent over to remote load centre which are beneficial for the stability of weak sending end systems. Meanwhile, HVDC for long-distance power transmission is of many significant technique advantages. Hence the effects of wind-PV-thermal-bundled power transmission by AC/DC on power system have become an actively pursued research subject recently. Firstly, this paper introduces the technical merits and difficulties of wind-photovoltaic-thermal bundled power transmission by AC/DC systems in terms of meeting the requirement of large-scale renewable power transmission. Secondly, a system model which contains a weak wind-PV-thermal-bundled sending end system and a receiving end system in together with a parallel AC/DC interconnection transmission system is established. Finally, the significant impacts of several factors which includes the power transmission ratio between the DC and AC line, the distance between the sending end system and receiving end system, the penetration rate of wind power and the sending end system structure on system stability are studied.

[Design of an microwave applicator using for tumor in superficial layer].

PubMed

Sun, Bing; Lu, Xiaofeng; Cao, Yi

2010-05-01

A 2.45 GHz microstrip applicator using single rectangle sheet structure is presented. Based on the radiant principle of microstrip antenna, the applicator's parameter is designed and the simulating model is set and optimized in HFSS. Measured by network analyzer, the technical target of this applicator is complied with design demand. During irradiation experiment, based on 30 W power, 30 mm radiation distance and 15 min duration experiment condition, the thermal field distribution map of phantom is obtained from the far-infrared image instrument. The 3D map shows that the region of thermal field centre has small radius and deep heat penetration. The microwave energy from this applicator can reach the tumor in superficial layer without heat injuring normal tissue around it.

Synthesis of carbon nanotube (CNT)-entangled CuO nanotube networks via CNT-catalytic growth and in situ thermal oxidation as additive-free anodes for lithium ion batteries

NASA Astrophysics Data System (ADS)

Cui, Xia; Song, Bo; Cheng, Shisu; Xie, Yun; Shao, Yijiang; Sun, Yueming

2018-01-01

We demonstrated the utility of carbon nanotubes (CNTs) as a catalyst and conductive agent to synthesize CNT-entangled copper nanowire (CuNW-CNT) networks within a melted mixture of hexadecylamine and cetyltrimethy ammounium bromide. The CuNW-CNT networks were further in situ thermally oxidized into CuO nanotube-CNT (CuONT-CNT) with the high retention of network structure. The binder- and conducting-additive-free anodes constructed using the CuONT-CNT networks exhibited high performance, such as high capability (557.7 mAh g-1 at 0.2 °C after 200 cycles), high Coulombic efficiency (near 100%), good rate performance (385.5 mAh g-1 at 5 °C and 310.3 mAh g-1 at 10 °C), and long cycling life.

Linking plate reconstructions with deforming lithosphere to geodynamic models

NASA Astrophysics Data System (ADS)

Müller, R. D.; Gurnis, M.; Flament, N.; Seton, M.; Spasojevic, S.; Williams, S.; Zahirovic, S.

2011-12-01

While global computational models are rapidly advancing in terms of their capabilities, there is an increasing need for assimilating observations into these models and/or ground-truthing model outputs. The open-source and platform independent GPlates software fills this gap. It was originally conceived as a tool to interactively visualize and manipulate classical rigid plate reconstructions and represent them as time-dependent topological networks of editable plate boundaries. The user can export time-dependent plate velocity meshes that can be used either to define initial surface boundary conditions for geodynamic models or alternatively impose plate motions throughout a geodynamic model run. However, tectonic plates are not rigid, and neglecting plate deformation, especially that of the edges of overriding plates, can result in significant misplacing of plate boundaries through time. A new, substantially re-engineered version of GPlates is now being developed that allows an embedding of deforming plates into topological plate boundary networks. We use geophysical and geological data to define the limit between rigid and deforming areas, and the deformation history of non-rigid blocks. The velocity field predicted by these reconstructions can then be used as a time-dependent surface boundary condition in regional or global 3-D geodynamic models, or alternatively as an initial boundary condition for a particular plate configuration at a given time. For time-dependent models with imposed plate motions (e.g. using CitcomS) we incorporate the continental lithosphere by embedding compositionally distinct crust and continental lithosphere within the thermal lithosphere. We define three isostatic columns of different thickness and buoyancy based on the tectonothermal age of the continents: Archean, Proterozoic and Phanerozoic. In the fourth isostatic column, the oceans, the thickness of the thermal lithosphere is assimilated using a half-space cooling model. We also define the thickness of the thermal lithosphere for different continental types, with the exception of the deforming areas that are fully dynamic. Finally, we introduce a "slab assimilation" method in which the thermal structure of the slab, derived analytically, is progressively assimilated into the upper mantle through time. This method not only improves the continuity of slabs in forward models with imposed plate motions, but it also allows us to model flat slab segments that are particularly relevant for understanding dynamic surface topography. When it comes to post-processing and visualisation, GPlates allows the user to import time-dependent model output image stacks to visualise mantle properties (e.g. temperature) at a given depth through time, with plate boundaries and other data attached to plates overlain. This approach provides an avenue to simultaneously investigate the contributions of lithospheric deformation and mantle flow to surface topography. Currently GPlates is being used in conjunction with the codes CitcomS, Terra, BEMEarth and the adaptive mesh refinement code Rhea. A GPlates python plugin infrastructure makes it easy to extend interoperability with other geodynamic modelling codes.

Thermal Degradation Studies of Polyurethane/POSS Nanohybrid Elastomers

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

Lewicki, J P; Pielichowski, K; TremblotDeLaCroix, P

2010-03-05

Reported here is the synthesis of a series of Polyurethane/POSS nanohybrid elastomers, the characterization of their thermal stability and degradation behavior at elevated temperatures using a combination of Thermal Gravimetric Analysis (TGA) and Thermal Volatilization Analysis (TVA). A series of PU elastomers systems have been formulated incorporating varying levels of 1,2-propanediol-heptaisobutyl-POSS (PHIPOSS) as a chain extender unit, replacing butane diol. The bulk thermal stability of the nanohybrid systems has been characterized using TGA. Results indicate that covalent incorporation of POSS into the PU elastomer network increase the non-oxidative thermal stability of the systems. TVA analysis of the thermal degradation ofmore » the POSS/PU hybrid elastomers have demonstrated that the hybrid systems are indeed more thermally stable when compared to the unmodified PU matrix; evolving significantly reduced levels of volatile degradation products and exhibiting a {approx}30 C increase in onset degradation temperature. Furthermore, characterization of the distribution of degradation products from both unmodified and hybrid systems indicate that the inclusion of POSS in the PU network is directly influencing the degradation pathways of both the soft and hard block components of the elastomers: The POSS/PU hybrid systems show reduced levels of CO, CO2, water and increased levels of THF as products of thermal degradation.« less

Modeling of steam distillation mechanism during steam injection process using artificial intelligence.

PubMed

Daryasafar, Amin; Ahadi, Arash; Kharrat, Riyaz

2014-01-01

Steam distillation as one of the important mechanisms has a great role in oil recovery in thermal methods and so it is important to simulate this process experimentally and theoretically. In this work, the simulation of steam distillation is performed on sixteen sets of crude oil data found in the literature. Artificial intelligence (AI) tools such as artificial neural network (ANN) and also adaptive neurofuzzy interference system (ANFIS) are used in this study as effective methods to simulate the distillate recoveries of these sets of data. Thirteen sets of data were used to train the models and three sets were used to test the models. The developed models are highly compatible with respect to input oil properties and can predict the distillate yield with minimum entry. For showing the performance of the proposed models, simulation of steam distillation is also done using modified Peng-Robinson equation of state. Comparison between the calculated distillates by ANFIS and neural network models and also equation of state-based method indicates that the errors of the ANFIS model for training data and test data sets are lower than those of other methods.

Modeling of Steam Distillation Mechanism during Steam Injection Process Using Artificial Intelligence

PubMed Central

Ahadi, Arash; Kharrat, Riyaz

2014-01-01

Steam distillation as one of the important mechanisms has a great role in oil recovery in thermal methods and so it is important to simulate this process experimentally and theoretically. In this work, the simulation of steam distillation is performed on sixteen sets of crude oil data found in the literature. Artificial intelligence (AI) tools such as artificial neural network (ANN) and also adaptive neurofuzzy interference system (ANFIS) are used in this study as effective methods to simulate the distillate recoveries of these sets of data. Thirteen sets of data were used to train the models and three sets were used to test the models. The developed models are highly compatible with respect to input oil properties and can predict the distillate yield with minimum entry. For showing the performance of the proposed models, simulation of steam distillation is also done using modified Peng-Robinson equation of state. Comparison between the calculated distillates by ANFIS and neural network models and also equation of state-based method indicates that the errors of the ANFIS model for training data and test data sets are lower than those of other methods. PMID:24883365

Energy challenges in optical access and aggregation networks.

PubMed

Kilper, Daniel C; Rastegarfar, Houman

2016-03-06

Scalability is a critical issue for access and aggregation networks as they must support the growth in both the size of data capacity demands and the multiplicity of access points. The number of connected devices, the Internet of Things, is growing to the tens of billions. Prevailing communication paradigms are reaching physical limitations that make continued growth problematic. Challenges are emerging in electronic and optical systems and energy increasingly plays a central role. With the spectral efficiency of optical systems approaching the Shannon limit, increasing parallelism is required to support higher capacities. For electronic systems, as the density and speed increases, the total system energy, thermal density and energy per bit are moving into regimes that become impractical to support-for example requiring single-chip processor powers above the 100 W limit common today. We examine communication network scaling and energy use from the Internet core down to the computer processor core and consider implications for optical networks. Optical switching in data centres is identified as a potential model from which scalable access and aggregation networks for the future Internet, with the application of integrated photonic devices and intelligent hybrid networking, will emerge. © 2016 The Author(s).

Six-port optical switch for cluster-mesh photonic network-on-chip

NASA Astrophysics Data System (ADS)

Jia, Hao; Zhou, Ting; Zhao, Yunchou; Xia, Yuhao; Dai, Jincheng; Zhang, Lei; Ding, Jianfeng; Fu, Xin; Yang, Lin

2018-05-01

Photonic network-on-chip for high-performance multi-core processors has attracted substantial interest in recent years as it offers a systematic method to meet the demand of large bandwidth, low latency and low power dissipation. In this paper we demonstrate a non-blocking six-port optical switch for cluster-mesh photonic network-on-chip. The architecture is constructed by substituting three optical switching units of typical Spanke-Benes network to optical waveguide crossings. Compared with Spanke-Benes network, the number of optical switching units is reduced by 20%, while the connectivity of routing path is maintained. By this way the footprint and power consumption can be reduced at the expense of sacrificing the network latency performance in some cases. The device is realized by 12 thermally tuned silicon Mach-Zehnder optical switching units. Its theoretical spectral responses are evaluated by establishing a numerical model. The experimental spectral responses are also characterized, which indicates that the optical signal-to-noise ratios of the optical switch are larger than 13.5 dB in the wavelength range from 1525 nm to 1565 nm. Data transmission experiment with the data rate of 32 Gbps is implemented for each optical link.

A comparison of classical and intelligent methods to detect potential thermal anomalies before the 11 August 2012 Varzeghan, Iran, earthquake (Mw = 6.4)

NASA Astrophysics Data System (ADS)

Akhoondzadeh, M.

2013-04-01

In this paper, a number of classical and intelligent methods, including interquartile, autoregressive integrated moving average (ARIMA), artificial neural network (ANN) and support vector machine (SVM), have been proposed to quantify potential thermal anomalies around the time of the 11 August 2012 Varzeghan, Iran, earthquake (Mw = 6.4). The duration of the data set, which is comprised of Aqua-MODIS land surface temperature (LST) night-time snapshot images, is 62 days. In order to quantify variations of LST data obtained from satellite images, the air temperature (AT) data derived from the meteorological station close to the earthquake epicenter has been taken into account. For the models examined here, results indicate the following: (i) ARIMA models, which are the most widely used in the time series community for short-term forecasting, are quickly and easily implemented, and can efficiently act through linear solutions. (ii) A multilayer perceptron (MLP) feed-forward neural network can be a suitable non-parametric method to detect the anomalous changes of a non-linear time series such as variations of LST. (iii) Since SVMs are often used due to their many advantages for classification and regression tasks, it can be shown that, if the difference between the predicted value using the SVM method and the observed value exceeds the pre-defined threshold value, then the observed value could be regarded as an anomaly. (iv) ANN and SVM methods could be powerful tools in modeling complex phenomena such as earthquake precursor time series where we may not know what the underlying data generating process is. There is good agreement in the results obtained from the different methods for quantifying potential anomalies in a given LST time series. This paper indicates that the detection of the potential thermal anomalies derive credibility from the overall efficiencies and potentialities of the four integrated methods.

Continuous monitoring of Hawaiian volcanoes with thermal cameras

USGS Publications Warehouse

Patrick, Matthew R.; Orr, Tim R.; Antolik, Loren; Lee, Robert Lopaka; Kamibayashi, Kevan P.

2014-01-01

Continuously operating thermal cameras are becoming more common around the world for volcano monitoring, and offer distinct advantages over conventional visual webcams for observing volcanic activity. Thermal cameras can sometimes “see” through volcanic fume that obscures views to visual webcams and the naked eye, and often provide a much clearer view of the extent of high temperature areas and activity levels. We describe a thermal camera network recently installed by the Hawaiian Volcano Observatory to monitor Kīlauea’s summit and east rift zone eruptions (at Halema‘uma‘u and Pu‘u ‘Ō‘ō craters, respectively) and to keep watch on Mauna Loa’s summit caldera. The cameras are long-wave, temperature-calibrated models protected in custom enclosures, and often positioned on crater rims close to active vents. Images are transmitted back to the observatory in real-time, and numerous Matlab scripts manage the data and provide automated analyses and alarms. The cameras have greatly improved HVO’s observations of surface eruptive activity, which includes highly dynamic lava lake activity at Halema‘uma‘u, major disruptions to Pu‘u ‘Ō‘ō crater and several fissure eruptions.

CDOT thermal mapping report.

DOT National Transportation Integrated Search

2014-06-01

Thermal Mapping surveys were carried out on approximately 1000 miles of the Colorado Department : of Transportations (CDOTs) roads. The purpose of these surveys was to identify road surface : variations across the network to determine whether f...

Interplay between structure and transport properties of molten salt mixtures of ZnCl2-NaCl-KCl: A molecular dynamics study.

PubMed

Manga, Venkateswara Rao; Swinteck, Nichlas; Bringuier, Stefan; Lucas, Pierre; Deymier, Pierre; Muralidharan, Krishna

2016-03-07

Molten mixtures of network-forming covalently bonded ZnCl2 and network-modifying ionically bonded NaCl and KCl salts are investigated as high-temperature heat transfer fluids for concentrating solar power plants. Specifically, using molecular dynamics simulations, the interplay between the extent of the network structure, composition, and the transport properties (viscosity, thermal conductivity, and diffusion) of ZnCl2-NaCl-KCl molten salts is characterized. The Stokes-Einstein/Eyring relationship is found to break down in these network-forming liquids at high concentrations of ZnCl2 (>63 mol. %), while the Eyring relationship is seen with increasing KCl concentration. Further, the network modification due to the addition of K ions leads to formation of non-bridging terminal Cl ions, which in turn lead to a positive temperature dependence of thermal conductivity in these melts. This new understanding of transport in these ternary liquids enables the identification of appropriate concentrations of the network formers and network modifiers to design heat transfer fluids with desired transport properties for concentrating solar power plants.

Predicting heat stress index in Sasso hens using automatic linear modeling and artificial neural network

NASA Astrophysics Data System (ADS)

Yakubu, A.; Oluremi, O. I. A.; Ekpo, E. I.

2018-03-01

There is an increasing use of robust analytical algorithms in the prediction of heat stress. The present investigation therefore, was carried out to forecast heat stress index (HSI) in Sasso laying hens. One hundred and sixty seven records on the thermo-physiological parameters of the birds were utilized. They were reared on deep litter and battery cage systems. Data were collected when the birds were 42- and 52-week of age. The independent variables fitted were housing system, age of birds, rectal temperature (RT), pulse rate (PR), and respiratory rate (RR). The response variable was HSI. Data were analyzed using automatic linear modeling (ALM) and artificial neural network (ANN) procedures. The ALM model building method involved Forward Stepwise using the F Statistic criterion. As regards ANN, multilayer perceptron (MLP) with back-propagation network was used. The ANN network was trained with 90% of the data set while 10% were dedicated to testing for model validation. RR and PR were the two parameters of utmost importance in the prediction of HSI. However, the fractional importance of RR was higher than that of PR in both ALM (0.947 versus 0.053) and ANN (0.677 versus 0.274) models. The two models also predicted HSI effectively with high degree of accuracy [r = 0.980, R 2 = 0.961, adjusted R 2 = 0.961, and RMSE = 0.05168 (ALM); r = 0.983, R 2 = 0.966; adjusted R 2 = 0.966, and RMSE = 0.04806 (ANN)]. The present information may be exploited in the development of a heat stress chart based largely on RR. This may aid detection of thermal discomfort in a poultry house under tropical and subtropical conditions.

Predicting heat stress index in Sasso hens using automatic linear modeling and artificial neural network.

PubMed

Yakubu, A; Oluremi, O I A; Ekpo, E I

2018-03-17

There is an increasing use of robust analytical algorithms in the prediction of heat stress. The present investigation therefore, was carried out to forecast heat stress index (HSI) in Sasso laying hens. One hundred and sixty seven records on the thermo-physiological parameters of the birds were utilized. They were reared on deep litter and battery cage systems. Data were collected when the birds were 42- and 52-week of age. The independent variables fitted were housing system, age of birds, rectal temperature (RT), pulse rate (PR), and respiratory rate (RR). The response variable was HSI. Data were analyzed using automatic linear modeling (ALM) and artificial neural network (ANN) procedures. The ALM model building method involved Forward Stepwise using the F Statistic criterion. As regards ANN, multilayer perceptron (MLP) with back-propagation network was used. The ANN network was trained with 90% of the data set while 10% were dedicated to testing for model validation. RR and PR were the two parameters of utmost importance in the prediction of HSI. However, the fractional importance of RR was higher than that of PR in both ALM (0.947 versus 0.053) and ANN (0.677 versus 0.274) models. The two models also predicted HSI effectively with high degree of accuracy [r = 0.980, R 2  = 0.961, adjusted R 2  = 0.961, and RMSE = 0.05168 (ALM); r = 0.983, R 2  = 0.966; adjusted R 2  = 0.966, and RMSE = 0.04806 (ANN)]. The present information may be exploited in the development of a heat stress chart based largely on RR. This may aid detection of thermal discomfort in a poultry house under tropical and subtropical conditions.

Significance of Thermal Fluvial Incision and Bedrock Transfer due to Ice Advection on Greenland Ice Sheet Topography

NASA Astrophysics Data System (ADS)

Crozier, J. A.; Karlstrom, L.; Yang, K.

2017-12-01

Ice sheet surface topography reflects a complicated combination of processes that act directly upon the surface and that are products of ice advection. Using recently-available high resolution ice velocity, imagery, ice surface elevation, and bedrock elevation data sets, we seek to determine the domain of significance of two important processes - thermal fluvial incision and transfer of bedrock topography through the ice sheet - on controlling surface topography in the ablation zone. Evaluating such controls is important for understanding how melting of the GIS surface during the melt season may be directly imprinted in topography through supraglacial drainage networks, and indirectly imprinted through its contribution to basal sliding that affects bedrock transfer. We use methods developed by (Karlstrom and Yang, 2016) to identify supraglacial stream networks on the GIS, and use high resolution surface digital elevation models as well as gridded ice velocity and melt rate models to quantify surface processes. We implement a numerically efficient Fourier domain bedrock transfer function (Gudmundsson, 2003) to predict surface topography due to ice advection over bedrock topography obtained from radar. Despite a number of simplifying assumptions, the bedrock transfer function predicts the observed ice sheet surface in most regions of the GIS with ˜90% accuracy, regardless of the presence or absence of supraglacial drainage networks. This supports the hypothesis that bedrock is the most significant driver of ice surface topography on wavelengths similar to ice thickness. Ice surface topographic asymmetry on the GIS is common, with slopes in the direction of ice flow steeper than those faced opposite to ice flow, consistent with bedrock transfer theory. At smaller wavelengths, topography consistent with fluvial erosion by surface hydrologic features is evident. We quantify the effect of ice advection versus fluvial thermal erosion on supraglacial longitudinal stream profiles, as a function of location on the GIS (hence ice thickness and background melt rate) using spectral techniques to quantify longitudinal stream profiles. This work should provide a predictive guide for which processes are responsible for ice sheet topography scales from several m (DEM resolution) up to several ice thicknesses.

Using Sentinel-1 and Landsat 8 satellite images to estimate surface soil moisture content.

NASA Astrophysics Data System (ADS)

Mexis, Philippos-Dimitrios; Alexakis, Dimitrios D.; Daliakopoulos, Ioannis N.; Tsanis, Ioannis K.

2016-04-01

Nowadays, the potential for more accurate assessment of Soil Moisture (SM) content exploiting Earth Observation (EO) technology, by exploring the use of synergistic approaches among a variety of EO instruments has emerged. This study is the first to investigate the potential of Synthetic Aperture Radar (SAR) (Sentinel-1) and optical (Landsat 8) images in combination with ground measurements to estimate volumetric SM content in support of water management and agricultural practices. SAR and optical data are downloaded and corrected in terms of atmospheric, geometric and radiometric corrections. SAR images are also corrected in terms of roughness and vegetation with the synergistic use of Oh and Topp models using a dataset consisting of backscattering coefficients and corresponding direct measurements of ground parameters (moisture, roughness). Following, various vegetation indices (NDVI, SAVI, MSAVI, EVI, etc.) are estimated to record diachronically the vegetation regime within the study area and as auxiliary data in the final modeling. Furthermore, thermal images from optical data are corrected and incorporated to the overall approach. The basic principle of Thermal InfraRed (TIR) method is that Land Surface Temperature (LST) is sensitive to surface SM content due to its impact on surface heating process (heat capacity and thermal conductivity) under bare soil or sparse vegetation cover conditions. Ground truth data are collected from a Time-domain reflectometer (TRD) gauge network established in western Crete, Greece, during 2015. Sophisticated algorithms based on Artificial Neural Networks (ANNs) and Multiple Linear Regression (MLR) approaches are used to explore the statistical relationship between backscattering measurements and SM content. Results highlight the potential of SAR and optical satellite images to contribute to effective SM content detection in support of water resources management and precision agriculture. Keywords: Sentinel-1, Landsat 8, Soil moisture content, Artificial Neural Network, Multiple Linear Regression The study was fully supported by the CASCADE project. The CASCADE Project is financed by the European Commission FP7 program, ENV.2011.2.1.4-2 - 'Behaviour of ecosystems, thresholds and tipping points', EU Grant agreement: 283068.

Thermal Interface Comparisons Under Flight Like Conditions

NASA Technical Reports Server (NTRS)

Rodriquez-Ruiz, Juan

2008-01-01

Thermal interface materials are used in bolted interfaces to promote good thermal conduction between the two. The mounting surface can include panels, heat pipes, electronics boxes, etc.. . On Lunar Reconnaissance Orbiter (LRO) project the results are directly applicable: a) Several high power avionics boxes b) Several interfaces from RWA to radiator through heat pipe network

Elastic properties and short-range structural order in mixed network former glasses.

PubMed

Wang, Weimin; Christensen, Randilynn; Curtis, Brittany; Hynek, David; Keizer, Sydney; Wang, James; Feller, Steve; Martin, Steve W; Kieffer, John

2017-06-21

Elastic properties of alkali containing glasses are of great interest not only because they provide information about overall structural integrity but also they are related to other properties such as thermal conductivity and ion mobility. In this study, we investigate two mixed-network former glass systems, sodium borosilicate 0.2Na 2 O + 0.8[xBO 1.5 + (1 - x)SiO 2 ] and sodium borogermanate 0.2Na 2 O + 0.8[xBO 1.5 + (1 - x)GeO 2 ] glasses. By mixing network formers, the network topology can be changed while keeping the network modifier concentration constant, which allows for the effect of network structure on elastic properties to be analyzed over a wide parametric range. In addition to non-linear, non-additive mixed-glass former effects, maxima are observed in longitudinal, shear and Young's moduli with increasing atomic number density. By combining results from NMR spectroscopy and Brillouin light scattering with a newly developed statistical thermodynamic reaction equilibrium model, it is possible to determine the relative proportions of all network structural units. This new analysis reveals that the structural characteristic predominantly responsible for effective mechanical load transmission in these glasses is a high density of network cations coordinated by four or more bridging oxygens, as it provides for establishing a network of covalent bonds among these cations with connectivity in three dimensions.

Modeling of thermal coupling in VO2-based oscillatory neural networks

NASA Astrophysics Data System (ADS)

Velichko, Andrey; Belyaev, Maksim; Putrolaynen, Vadim; Perminov, Valentin; Pergament, Alexander

2018-01-01

In this study, we have demonstrated the possibility of using the thermal coupling to control the dynamics of operation of coupled VO2 oscillators. Based on the example of a 'switch-microheater' pair, we have explored the synchronization and dissynchronization modes of a single oscillator with respect to an external harmonic heat impact. The features of changes in the spectra are shown, in particular, the effect of the natural frequency attraction to the affecting signal frequency and the self-oscillation noise reduction effects at synchronization. The time constant of the temperature effect for the considered system configuration is in the range 7-140 μs, which allows operation in the oscillation frequency range of up to ∼70 kHz. A model estimate of the minimum temperature sensitivity of the switch is δTswitch ∼ 0.2 K, and the effective action radius RTC of the switch-to-switch thermal coupling is not less than 25 μm. Nevertheless, as the simulation shows, the frequency range can be significantly extended up to the values of 1-30 GHz if using nanometer-scale switches (heaters).

Thermally Stimulated Currents in Nanocrystalline Titania

PubMed Central

Bruzzi, Mara; Mori, Riccardo; Baldi, Andrea; Cavallaro, Alessandro; Scaringella, Monica

2018-01-01

A thorough study on the distribution of defect-related active energy levels has been performed on nanocrystalline TiO2. Films have been deposited on thick-alumina printed circuit boards equipped with electrical contacts, heater and temperature sensors, to carry out a detailed thermally stimulated currents analysis on a wide temperature range (5–630 K), in view to evidence contributions from shallow to deep energy levels within the gap. Data have been processed by numerically modelling electrical transport. The model considers both free and hopping contribution to conduction, a density of states characterized by an exponential tail of localized states below the conduction band and the convolution of standard Thermally Stimulated Currents (TSC) emissions with gaussian distributions to take into account the variability in energy due to local perturbations in the highly disordered network. Results show that in the low temperature range, up to 200 K, hopping within the exponential band tail represents the main contribution to electrical conduction. Above room temperature, electrical conduction is dominated by free carriers contribution and by emissions from deep energy levels, with a defect density ranging within 1014–1018 cm−3, associated with physio- and chemi-sorbed water vapour, OH groups and to oxygen vacancies. PMID:29303976

Thermally Stimulated Currents in Nanocrystalline Titania.

PubMed

Bruzzi, Mara; Mori, Riccardo; Baldi, Andrea; Carnevale, Ennio Antonio; Cavallaro, Alessandro; Scaringella, Monica

2018-01-05

A thorough study on the distribution of defect-related active energy levels has been performed on nanocrystalline TiO₂. Films have been deposited on thick-alumina printed circuit boards equipped with electrical contacts, heater and temperature sensors, to carry out a detailed thermally stimulated currents analysis on a wide temperature range (5-630 K), in view to evidence contributions from shallow to deep energy levels within the gap. Data have been processed by numerically modelling electrical transport. The model considers both free and hopping contribution to conduction, a density of states characterized by an exponential tail of localized states below the conduction band and the convolution of standard Thermally Stimulated Currents (TSC) emissions with gaussian distributions to take into account the variability in energy due to local perturbations in the highly disordered network. Results show that in the low temperature range, up to 200 K, hopping within the exponential band tail represents the main contribution to electrical conduction. Above room temperature, electrical conduction is dominated by free carriers contribution and by emissions from deep energy levels, with a defect density ranging within 10 14 -10 18 cm -3 , associated with physio- and chemi-sorbed water vapour, OH groups and to oxygen vacancies.

Using Laser Scanners to Augment the Systematic Error Pointing Model

NASA Astrophysics Data System (ADS)

Wernicke, D. R.

2016-08-01

The antennas of the Deep Space Network (DSN) rely on precise pointing algorithms to communicate with spacecraft that are billions of miles away. Although the existing systematic error pointing model is effective at reducing blind pointing errors due to static misalignments, several of its terms have a strong dependence on seasonal and even daily thermal variation and are thus not easily modeled. Changes in the thermal state of the structure create a separation from the model and introduce a varying pointing offset. Compensating for this varying offset is possible by augmenting the pointing model with laser scanners. In this approach, laser scanners mounted to the alidade measure structural displacements while a series of transformations generate correction angles. Two sets of experiments were conducted in August 2015 using commercially available laser scanners. When compared with historical monopulse corrections under similar conditions, the computed corrections are within 3 mdeg of the mean. However, although the results show promise, several key challenges relating to the sensitivity of the optical equipment to sunlight render an implementation of this approach impractical. Other measurement devices such as inclinometers may be implementable at a significantly lower cost.

Electrical circuit modeling and analysis of microwave acoustic interaction with biological tissues.

PubMed

Gao, Fei; Zheng, Qian; Zheng, Yuanjin

2014-05-01

Numerical study of microwave imaging and microwave-induced thermoacoustic imaging utilizes finite difference time domain (FDTD) analysis for simulation of microwave and acoustic interaction with biological tissues, which is time consuming due to complex grid-segmentation and numerous calculations, not straightforward due to no analytical solution and physical explanation, and incompatible with hardware development requiring circuit simulator such as SPICE. In this paper, instead of conventional FDTD numerical simulation, an equivalent electrical circuit model is proposed to model the microwave acoustic interaction with biological tissues for fast simulation and quantitative analysis in both one and two dimensions (2D). The equivalent circuit of ideal point-like tissue for microwave-acoustic interaction is proposed including transmission line, voltage-controlled current source, envelop detector, and resistor-inductor-capacitor (RLC) network, to model the microwave scattering, thermal expansion, and acoustic generation. Based on which, two-port network of the point-like tissue is built and characterized using pseudo S-parameters and transducer gain. Two dimensional circuit network including acoustic scatterer and acoustic channel is also constructed to model the 2D spatial information and acoustic scattering effect in heterogeneous medium. Both FDTD simulation, circuit simulation, and experimental measurement are performed to compare the results in terms of time domain, frequency domain, and pseudo S-parameters characterization. 2D circuit network simulation is also performed under different scenarios including different sizes of tumors and the effect of acoustic scatterer. The proposed circuit model of microwave acoustic interaction with biological tissue could give good agreement with FDTD simulated and experimental measured results. The pseudo S-parameters and characteristic gain could globally evaluate the performance of tumor detection. The 2D circuit network enables the potential to combine the quasi-numerical simulation and circuit simulation in a uniform simulator for codesign and simulation of a microwave acoustic imaging system, bridging bioeffect study and hardware development seamlessly.

Signal processing and neural network toolbox and its application to failure diagnosis and prognosis

NASA Astrophysics Data System (ADS)

Tu, Fang; Wen, Fang; Willett, Peter K.; Pattipati, Krishna R.; Jordan, Eric H.

2001-07-01

Many systems are comprised of components equipped with self-testing capability; however, if the system is complex involving feedback and the self-testing itself may occasionally be faulty, tracing faults to a single or multiple causes is difficult. Moreover, many sensors are incapable of reliable decision-making on their own. In such cases, a signal processing front-end that can match inference needs will be very helpful. The work is concerned with providing an object-oriented simulation environment for signal processing and neural network-based fault diagnosis and prognosis. In the toolbox, we implemented a wide range of spectral and statistical manipulation methods such as filters, harmonic analyzers, transient detectors, and multi-resolution decomposition to extract features for failure events from data collected by data sensors. Then we evaluated multiple learning paradigms for general classification, diagnosis and prognosis. The network models evaluated include Restricted Coulomb Energy (RCE) Neural Network, Learning Vector Quantization (LVQ), Decision Trees (C4.5), Fuzzy Adaptive Resonance Theory (FuzzyArtmap), Linear Discriminant Rule (LDR), Quadratic Discriminant Rule (QDR), Radial Basis Functions (RBF), Multiple Layer Perceptrons (MLP) and Single Layer Perceptrons (SLP). Validation techniques, such as N-fold cross-validation and bootstrap techniques, are employed for evaluating the robustness of network models. The trained networks are evaluated for their performance using test data on the basis of percent error rates obtained via cross-validation, time efficiency, generalization ability to unseen faults. Finally, the usage of neural networks for the prediction of residual life of turbine blades with thermal barrier coatings is described and the results are shown. The neural network toolbox has also been applied to fault diagnosis in mixed-signal circuits.

Two-Phase Thermal Switching System for a Small, Extended Duration Lunar Science Platform

NASA Technical Reports Server (NTRS)

Bugby, D.; Farmer, J.; OConnor, B.; Wirzburger, M.; Abel, E.; Stouffer, C.

2010-01-01

Issue: extended duration lunar science platforms, using solar/battery or radioisotope power, require thermal switching systems that: a) Provide efficient cooling during the 15-earth-day 390 K lunar day; b) Consume minimal power during the 15-earth-day 100 K lunar night. Objective: carry out an analytical study of thermal switching systems that can meet the thermal requirements of: a) International Lunar Network (ILN) anchor node mission - primary focus; b) Other missions such as polar crater landers. ILN Anchor Nodes: network of geophysical science platforms to better understand the interior structure/composition of the moon: a) Rationale: no data since Apollo seismic stations ceased operation in 1977; b) Anchor Nodes: small, low-power, long-life (6-yr) landers with seismographic and a few other science instruments (see next chart); c) WEB: warm electronics box houses ILN anchor node electronics/batteries. Technology Need: thermal switching system that will keep the WEB cool during the lunar day and warm during the lunar night.

Spatial layout optimization design of multi-type LEDs lighting source based on photoelectrothermal coupling theory

NASA Astrophysics Data System (ADS)

Xue, Lingyun; Li, Guang; Chen, Qingguang; Rao, Huanle; Xu, Ping

2018-03-01

Multiple LED-based spectral synthesis technology has been widely used in the fields of solar simulator, color mixing, and artificial lighting of plant factory and so on. Generally, amounts of LEDs are spatially arranged with compact layout to obtain the high power density output. Mutual thermal spreading among LEDs will produce the coupled thermal effect which will additionally increase the junction temperature of LED. Affected by the Photoelectric thermal coupling effect of LED, the spectrum of LED will shift and luminous efficiency will decrease. Correspondingly, the spectral synthesis result will mismatch. Therefore, thermal management of LED spatial layout plays an important role for multi-LEDs light source system. In the paper, the thermal dissipation network topology model considering the mutual thermal spreading effect among the LEDs is proposed for multi-LEDs system with various types of power. The junction temperature increment cased by the thermal coupling has the great relation with the spatial arrangement. To minimize the thermal coupling effect, an optimized method of LED spatial layout for the specific light source structure is presented and analyzed. The results showed that layout of LED with high-power are arranged in the corner and low-power in the center. Finally, according to this method, it is convenient to determine the spatial layout of LEDs in a system having any kind of light source structure, and has the advantages of being universally applicable to facilitate adjustment.

Assessment of human thermal comfort and mitigation measures in different urban climatotopes

NASA Astrophysics Data System (ADS)

Müller, N.; Kuttler, W.

2012-04-01

This study analyses thermal comfort in the model city of Oberhausen as an example for the densely populated metropolitan region Ruhr, Germany. As thermal loads increase due to climate change negative impacts especially for city dwellers will arise. Therefore mitigation strategies should be developed and considered in urban planning today to prevent future thermal stress. The method consists of the combination of in-situ measurements and numerical model simulations. So in a first step the actual thermal situation is determined and then possible mitigation strategies are derived. A measuring network was installed in eight climatotopes for a one year period recording air temperature, relative humidity, wind speed and wind direction. Based on these parameters the human thermal comfort in terms of physiological equivalent temperature (PET) was calculated by RayMan Pro software. Thus the human comfort of different climatotopes was determined. Heat stress in different land uses varies, so excess thermal loads in urban areas could be detected. Based on the measuring results mitigation strategies were developed, such as increasing areas with high evaporation capacity (green areas and water bodies). These strategies were implemented as different plan scenarios in the microscale urban climate model ENVI-met. The best measure should be identified by comparing the range and effect of these scenarios. Simulations were run in three of the eight climatotopes (city center, suburban and open land site) to analyse the effectiveness of the mitigation strategies in several land use structures. These cover the range of values of all eight climatotopes and therefore provide representative results. In the model area of 21 ha total, the modified section in the different plan scenarios was 1 ha. Thus the effect of small-scale changes could be analysed. Such areas can arise due to population decline and structural changes and hold conversion potential. Emphasis was also laid on analysing the effectiveness of water bodies, which need further research in contrast to well analysed vegetation areas. Results show different thermal loads in the miscellaneous climatotopes due to land use structures. Both measurements and model simulations demonstrate the positive effect on thermal comfort due to augmentation of areas with high evaporation capacity. These effects can be especially well detected in summer, when heat stress is most pronounced. The measurement based PET calculations show a maximum difference of 4 K PET between inner city and open land site in summer nights. Simulation results overall present a PET reduction of 1-3 K. The average PET reduction in the city center site is about 2 K, while the maximum reduction in the suburban site can exceed 5 K. In urban areas parks are particularly advisable as mitigation measure, because they reduce thermal stress both by tree shading and evapotranspiration.

Evolving ecological networks and the emergence of biodiversity patterns across temperature gradients.

PubMed

Stegen, James C; Ferriere, Regis; Enquist, Brian J

2012-03-22

In ectothermic organisms, it is hypothesized that metabolic rates mediate influences of temperature on the ecological and evolutionary processes governing biodiversity. However, it is unclear how and to what extent the influence of temperature on metabolism scales up to shape large-scale diversity patterns. In order to clarify the roles of temperature and metabolism, new theory is needed. Here, we establish such theory and model eco-evolutionary dynamics of trophic networks along a broad temperature gradient. In the model temperature can influence, via metabolism, resource supply, consumers' vital rates and mutation rate. Mutation causes heritable variation in consumer body size, which diversifies and governs consumer function in the ecological network. The model predicts diversity to increase with temperature if resource supply is temperature-dependent, whereas temperature-dependent consumer vital rates cause diversity to decrease with increasing temperature. When combining both thermal dependencies, a unimodal temperature-diversity pattern evolves, which is reinforced by temperature-dependent mutation rate. Studying coexistence criteria for two consumers showed that these outcomes are owing to temperature effects on mutual invasibility and facilitation. Our theory shows how and why metabolism can influence diversity, generates predictions useful for understanding biodiversity gradients and represents an extendable framework that could include factors such as colonization history and niche conservatism.

Prediction of temperature and HAZ in thermal-based processes with Gaussian heat source by a hybrid GA-ANN model

NASA Astrophysics Data System (ADS)

Fazli Shahri, Hamid Reza; Mahdavinejad, Ramezanali

2018-02-01

Thermal-based processes with Gaussian heat source often produce excessive temperature which can impose thermally-affected layers in specimens. Therefore, the temperature distribution and Heat Affected Zone (HAZ) of materials are two critical factors which are influenced by different process parameters. Measurement of the HAZ thickness and temperature distribution within the processes are not only difficult but also expensive. This research aims at finding a valuable knowledge on these factors by prediction of the process through a novel combinatory model. In this study, an integrated Artificial Neural Network (ANN) and genetic algorithm (GA) was used to predict the HAZ and temperature distribution of the specimens. To end this, a series of full factorial design of experiments were conducted by applying a Gaussian heat flux on Ti-6Al-4 V at first, then the temperature of the specimen was measured by Infrared thermography. The HAZ width of each sample was investigated through measuring the microhardness. Secondly, the experimental data was used to create a GA-ANN model. The efficiency of GA in design and optimization of the architecture of ANN was investigated. The GA was used to determine the optimal number of neurons in hidden layer, learning rate and momentum coefficient of both output and hidden layers of ANN. Finally, the reliability of models was assessed according to the experimental results and statistical indicators. The results demonstrated that the combinatory model predicted the HAZ and temperature more effective than a trial-and-error ANN model.

Thermal fluctuations and elastic relaxation in the compressed exponential dynamics of colloidal gels

NASA Astrophysics Data System (ADS)

Bouzid, Mehdi; Colombo, Jader; Del Gado, Emanuela

Colloidal gels belong to the class of amorphous systems, they are disordered elastic solids that can form at very low volume fraction, via aggregation into a rich variety of networks. They exhibit a slow relaxation process in the aging regime similar to the glassy dynamics. A wide range of experiments on colloidal gels show unusual compressed exponential of the relaxation dynamical properties. We use molecular dynamics simulation to investigate how the dynamic change with the age of the system. Upon breaking and reorganization of the network structure, the system may display stretched or compressed exponential relaxation. We show that the transition between these two regimes is associated to the interplay between thermally activated rearrangements and the elastic relaxation of internal stresses. In particular, ballistic-like displacements emerge from the non local relaxation of internal stresses mediated by a series of ''micro-collapses''. When thermal fluctuations dominate, the gel restructuring involves instead more homogeneous displacements across the heterogeneous gel network, leading to a stretched exponential type of relaxation.

Monitoring of Thermal Protection Systems Using Robust Self-Organizing Optical Fiber Sensing Networks

NASA Technical Reports Server (NTRS)

Richards, Lance

2013-01-01

The general aim of this work is to develop and demonstrate a prototype structural health monitoring system for thermal protection systems that incorporates piezoelectric acoustic emission (AE) sensors to detect the occurrence and location of damaging impacts, and an optical fiber Bragg grating (FBG) sensor network to evaluate the effect of detected damage on the thermal conductivity of the TPS material. Following detection of an impact, the TPS would be exposed to a heat source, possibly the sun, and the temperature distribution on the inner surface in the vicinity of the impact measured by the FBG network. A similar procedure could also be carried out as a screening test immediately prior to re-entry. The implications of any detected anomalies in the measured temperature distribution will be evaluated for their significance in relation to the performance of the TPS during re-entry. Such a robust TPS health monitoring system would ensure overall crew safety throughout the mission, especially during reentry

A gigantically increased ratio of electrical to thermal conductivity and synergistically enhanced thermoelectric properties in interface-controlled TiO2-RGO nanocomposites.

PubMed

Nam, Woo Hyun; Lim, Young Soo; Kim, Woochul; Seo, Hyeon Kook; Dae, Kyun Seong; Lee, Soonil; Seo, Won-Seon; Lee, Jeong Yong

2017-06-14

We report synergistically enhanced thermoelectric properties through the independently controlled charge and thermal transport properties in a TiO 2 -reduced graphene oxide (RGO) nanocomposite. By the consolidation of TiO 2 -RGO hybrid powder using spark plasma sintering, we prepared an interface-controlled TiO 2 -RGO nanocomposite where its grain boundaries are covered with the RGO network. Both the enhancement in electrical conductivity and the reduction in thermal conductivity were simultaneously achieved thanks to the beneficial effects of the RGO network, and detailed mechanisms are discussed. This led to the gigantic increase in the ratio of electrical to thermal conductivity by six orders of magnitude and also the synergistic enhancement in the thermoelectric figure of merit by two orders. Our results present a strategy for the realization of 'phonon-glass electron-crystals' through interface control using graphene in graphene hybrid thermoelectric materials.

Experimental and artificial neural network based prediction of performance and emission characteristics of DI diesel engine using Calophyllum inophyllum methyl ester at different nozzle opening pressure

NASA Astrophysics Data System (ADS)

Vairamuthu, G.; Thangagiri, B.; Sundarapandian, S.

2018-01-01

The present work investigates the effect of varying Nozzle Opening Pressures (NOP) from 220 bar to 250 bar on performance, emissions and combustion characteristics of Calophyllum inophyllum Methyl Ester (CIME) in a constant speed, Direct Injection (DI) diesel engine using Artificial Neural Network (ANN) approach. An ANN model has been developed to predict a correlation between specific fuel consumption (SFC), brake thermal efficiency (BTE), exhaust gas temperature (EGT), Unburnt hydrocarbon (UBHC), CO, CO2, NOx and smoke density using load, blend (B0 and B100) and NOP as input data. A standard Back-Propagation Algorithm (BPA) for the engine is used in this model. A Multi Layer Perceptron network (MLP) is used for nonlinear mapping between the input and the output parameters. An ANN model can predict the performance of diesel engine and the exhaust emissions with correlation coefficient (R2) in the range of 0.98-1. Mean Relative Errors (MRE) values are in the range of 0.46-5.8%, while the Mean Square Errors (MSE) are found to be very low. It is evident that the ANN models are reliable tools for the prediction of DI diesel engine performance and emissions. The test results show that the optimum NOP is 250 bar with B100.

New insights in dehydration stress behavior of two maize hybrids using advanced distributed reactivity model (DRM). Responses to the impact of 24-epibrassinolide

PubMed Central

Janković, Bojan; Janković, Marija; Nikolić, Bogdan; Dimkić, Ivica; Lalević, Blažo; Raičević, Vera

2017-01-01

Proposed distributed reactivity model of dehydration for seedling parts of two various maize hybrids (ZP434, ZP704) was established. Dehydration stresses were induced thermally, which is also accompanied by response of hybrids to heat stress. It was found that an increased value of activation energy counterparts within radicle dehydration of ZP434, with a high concentration of 24-epibrassinolide (24-EBL) at elevated operating temperatures, probably causes activation of diffusion mechanisms in cutin network and may increases likelihood of formation of free volumes, large enough to accommodate diffusing molecule. Many small random effects were detected and can be correlated with micro-disturbing in a space filled with water caused by thermal gradients, increasing capillary phenomena, and which can induce thermo-capillary migration. The influence of seedling content of various sugars and minerals on dehydration was also examined. Estimated distributed reactivity models indicate a dependence of reactivity on structural arrangements, due to present interactions between water molecules and chemical species within the plant. PMID:28644899

New insights in dehydration stress behavior of two maize hybrids using advanced distributed reactivity model (DRM). Responses to the impact of 24-epibrassinolide.

PubMed

Waisi, Hadi; Janković, Bojan; Janković, Marija; Nikolić, Bogdan; Dimkić, Ivica; Lalević, Blažo; Raičević, Vera

2017-01-01

Proposed distributed reactivity model of dehydration for seedling parts of two various maize hybrids (ZP434, ZP704) was established. Dehydration stresses were induced thermally, which is also accompanied by response of hybrids to heat stress. It was found that an increased value of activation energy counterparts within radicle dehydration of ZP434, with a high concentration of 24-epibrassinolide (24-EBL) at elevated operating temperatures, probably causes activation of diffusion mechanisms in cutin network and may increases likelihood of formation of free volumes, large enough to accommodate diffusing molecule. Many small random effects were detected and can be correlated with micro-disturbing in a space filled with water caused by thermal gradients, increasing capillary phenomena, and which can induce thermo-capillary migration. The influence of seedling content of various sugars and minerals on dehydration was also examined. Estimated distributed reactivity models indicate a dependence of reactivity on structural arrangements, due to present interactions between water molecules and chemical species within the plant.

Thermochemistry and vertical mixing in the tropospheres of Uranus and Neptune: How convection inhibition can affect the derivation of deep oxygen abundances

NASA Astrophysics Data System (ADS)

Cavalié, T.; Venot, O.; Selsis, F.; Hersant, F.; Hartogh, P.; Leconte, J.

2017-07-01

Thermochemical models have been used in the past to constrain the deep oxygen abundance in the gas and ice giant planets from tropospheric CO spectroscopic measurements. Knowing the oxygen abundance of these planets is a key to better understand their formation. These models have widely used dry and/or moist adiabats to extrapolate temperatures from the measured values in the upper troposphere down to the level where the thermochemical equilibrium between H2O and CO is established. The mean molecular mass gradient produced by the condensation of H2O stabilizes the atmosphere against convection and results in a vertical thermal profile and H2O distribution that departs significantly from previous estimates. We revisit O/H estimates using an atmospheric structure that accounts for the inhibition of the convection by condensation. We use a thermochemical network and the latest observations of CO in Uranus and Neptune to calculate the internal oxygen enrichment required to satisfy both these new estimates of the thermal profile and the observations. We also present the current limitations of such modeling.

MATLAB/Simulink Framework for Modeling Complex Coolant Flow Configurations of Advanced Automotive Thermal Management Systems: Preprint

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

Titov, Eugene; Lustbader, Jason; Leighton, Daniel

The National Renewable Energy Laboratory's (NREL's) CoolSim MATLAB/Simulink modeling framework was extended by including a newly developed coolant loop solution method aimed at reducing the simulation effort for arbitrarily complex thermal management systems. The new approach does not require the user to identify specific coolant loops and their flow. The user only needs to connect the fluid network elements in a manner consistent with the desired schematic. Using the new solution method, a model of NREL's advanced combined coolant loop system for electric vehicles was created that reflected the test system architecture. This system was built using components provided bymore » the MAHLE Group and included both air conditioning and heat pump modes. Validation with test bench data and verification with the previous solution method were performed for 10 operating points spanning a range of ambient temperatures between -2 degrees C and 43 degrees C. The largest root mean square difference between pressure, temperature, energy and mass flow rate data and simulation results was less than 7%.« less

MATLAB/Simulink Framework for Modeling Complex Coolant Flow Configurations of Advanced Automotive Thermal Management Systems

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

Titov, Gene; Lustbader, Jason; Leighton, Daniel

The National Renewable Energy Laboratory's (NREL's) CoolSim MATLAB/Simulink modeling framework was extended by including a newly developed coolant loop solution method aimed at reducing the simulation effort for arbitrarily complex thermal management systems. The new approach does not require the user to identify specific coolant loops and their flow. The user only needs to connect the fluid network elements in a manner consistent with the desired schematic. Using the new solution method, a model of NREL's advanced combined coolant loop system for electric vehicles was created that reflected the test system architecture. This system was built using components provided bymore » the MAHLE Group and included both air conditioning and heat pump modes. Validation with test bench data and verification with the previous solution method were performed for 10 operating points spanning a range of ambient temperatures between -2 degrees C and 43 degrees C. The largest root mean square difference between pressure, temperature, energy and mass flow rate data and simulation results was less than 7%.« less

Optimal and Adaptive Control of Flow in a Thermal Convection Loop

NASA Astrophysics Data System (ADS)

Yuen, Po Ki; Bau, Haim

1998-11-01

In theory and experiment, we use nonlinear and linear optimal and adaptive controllers to suppress the naturally occurring chaotic convection in a thermal convection loop. The thermal convection loop is a simple experimental analog of the Lorenz equations, and it provides a convenient platform for testing and comparing the performance of various control strategies in a fluid mechanical setting. The performance of the optimal and adaptive controllers is compared with that of a previously developed simple feedback controller (Singer, J., Wang, Y., & Bau, H., H., 1991, Physical Review Letters, 66,123-1125.)(Wang, Y., Singer, J., & Bau, H., H., 1992, J. Fluid Mechanics, 237, 479-498.), a nonlinear controller with a cubic nonlinearity(Yuen, P., & Bau, H., H., 1996, J. Fluid Mechanics, 317, 91-109.), and a neural net controller(Yuen, P., & Bau, H., H., 1998, Neural Networks, 11, 557 - 569, 1998.). It is demonstrated that an adaptive controller can perform successfully even when the system's model is not known.

Health Monitoring of Thermal Barrier Coatings by Mid-Infrared Reflectance

NASA Technical Reports Server (NTRS)

Eldridge, J. I.; Spuckler, C. M.; Nesbitt, J. A.; Street, K. W.

2002-01-01

Mid-infrared (MIR) reflectance is shown to be a powerful tool for monitoring the integrity of 8wt% yttria-stabilized zirconia (8YSZ) thermal barrier coatings (TBCs). Because of the translucent nature of plasma-sprayed 8YSZ TBCs, particularly at MIR wavelengths (3 to 5 microns), measured reflectance does not only originate from the TBC surface, but contains strong contributions from internal scattering within the coating as well as reflectance from the underlying TBC/substrate interface. Therefore, changes in MIR reflectance measurements can be used to monitor the progression of TBC delamination. In particular, MIR reflectance is shown to reproducibly track the progression of TBC delamination produced by repeated thermal cycling (to 1163 C) of plasma-sprayed 8YSZ TBCs on Rene N5 superalloy substrates. To understand the changes in MIR reflectance with the progression of a delamination crack network, a four-flux scattering model is used to predict the increase in MIR reflectance produced by the introduction of these cracks.

Sensitivity of New England Stream Temperatures to Air Temperature and Precipitation Under Projected Climate

NASA Astrophysics Data System (ADS)

Huang, T.; Samal, N. R.; Wollheim, W. M.; Stewart, R. J.; Zuidema, S.; Prousevitch, A.; Glidden, S.

2015-12-01

The thermal response of streams and rivers to changing climate will influence aquatic habitat. This study examines the impact that changing climate has on stream temperatures in the Merrimack River, NH/MA USA using the Framework for Aquatic Modeling in the Earth System (FrAMES), a spatially distributed river network model driven by air temperature, air humidity, wind speed, precipitation, and solar radiation. Streamflow and water temperatures are simulated at a 45-second (latitude x longitude) river grid resolution for 135 years under historical and projected climate variability. Contemporary streamflow (Nash-Sutcliffe Coefficient = 0.77) and river temperatures (Nash-Sutcliffe Coefficient = 0.89) matched at downstream USGS gauge data well. A suite of model runs were made in combination with uniformly increased daily summer air temperatures by 2oC, 4 oC and 6 oC as well as adjusted precipitation by -40%, -30%, -20%, -10% and +10% as a sensitivity analysis to explore a broad range of potential future climates. We analyzed the summer stream temperatures and the percent of river length unsuitable for cold to warm water fish habitats. Impacts are greatest in large rivers due to the accumulation of river temperature warming throughout the entire river network. Cold water fish (i.e. brook trout) are most strongly affected while, warm water fish (i.e. largemouth bass) aren't expected to be impacted. The changes in stream temperatures under various potential climate scenarios will provide a better understanding of the specific impact that air temperature and precipitation have on aquatic thermal regimes and habitat.

Engineering molecular machines

NASA Astrophysics Data System (ADS)

Erman, Burak

2016-04-01

Biological molecular motors use chemical energy, mostly in the form of ATP hydrolysis, and convert it to mechanical energy. Correlated thermal fluctuations are essential for the function of a molecular machine and it is the hydrolysis of ATP that modifies the correlated fluctuations of the system. Correlations are consequences of the molecular architecture of the protein. The idea that synthetic molecular machines may be constructed by designing the proper molecular architecture is challenging. In their paper, Sarkar et al (2016 New J. Phys. 18 043006) propose a synthetic molecular motor based on the coarse grained elastic network model of proteins and show by numerical simulations that motor function is realized, ranging from deterministic to thermal, depending on temperature. This work opens up a new range of possibilities of molecular architecture based engine design.

Multi-stage rescheduling of generation, load shedding and short-term transmission capacity for emergency state control

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

Krogh, B.; Chow, J.H.; Javid, H.S.

1983-05-01

A multi-stage formulation of the problem of scheduling generation, load shedding and short term transmission capacity for the alleviation of a viability emergency is presented. The formulation includes generation rate of change constraints, a linear network solution, and a model of the short term thermal overload capacity of transmission lines. The concept of rotating transmission line overloads for emergency state control is developed. The ideas are illustrated by a numerical example.

IR sensors and imagers in networked operations

NASA Astrophysics Data System (ADS)

Breiter, Rainer; Cabanski, Wolfgang

2005-05-01

"Network-centric Warfare" is a common slogan describing an overall concept of networked operation of sensors, information and weapons to gain command and control superiority. Referring to IR sensors, integration and fusion of different channels like day/night or SAR images or the ability to spread image data among various users are typical requirements. Looking for concrete implementations the German Army future infantryman IdZ is an example where a group of ten soldiers build a unit with every soldier equipped with a personal digital assistant (PDA) for information display, day photo camera and a high performance thermal imager for every unit. The challenge to allow networked operation among such a unit is bringing information together and distribution over a capable network. So also AIM's thermal reconnaissance and targeting sight HuntIR which was selected for the IdZ program provides this capabilities by an optional wireless interface. Besides the global approach of Network-centric Warfare network technology can also be an interesting solution for digital image data distribution and signal processing behind the FPA replacing analog video networks or specific point to point interfaces. The resulting architecture can provide capabilities of data fusion from e.g. IR dual-band or IR multicolor sensors. AIM has participated in a German/UK collaboration program to produce a demonstrator for day/IR video distribution via Gigabit Ethernet for vehicle applications. In this study Ethernet technology was chosen for network implementation and a set of electronics was developed for capturing video data of IR and day imagers and Gigabit Ethernet video distribution. The demonstrator setup follows the requirements of current and future vehicles having a set of day and night imager cameras and a crew station with several members. Replacing the analog video path by a digital video network also makes it easy to implement embedded training by simply feeding the network with simulation data. The paper addresses the special capabilities, requirements and design considerations of IR sensors and imagers in applications like thermal weapon sights and UAVs for networked operating infantry forces.

Neural computing thermal comfort index PMV for the indoor environment intelligent control system

NASA Astrophysics Data System (ADS)

Liu, Chang; Chen, Yifei

2013-03-01

Providing indoor thermal comfort and saving energy are two main goals of indoor environmental control system. An intelligent comfort control system by combining the intelligent control and minimum power control strategies for the indoor environment is presented in this paper. In the system, for realizing the comfort control, the predicted mean vote (PMV) is designed as the control goal, and with chastening formulas of PMV, it is controlled to optimize for improving indoor comfort lever by considering six comfort related variables. On the other hand, a RBF neural network based on genetic algorithm is designed to calculate PMV for better performance and overcoming the nonlinear feature of the PMV calculation better. The formulas given in the paper are presented for calculating the expected output values basing on the input samples, and the RBF network model is trained depending on input samples and the expected output values. The simulation result is proved that the design of the intelligent calculation method is valid. Moreover, this method has a lot of advancements such as high precision, fast dynamic response and good system performance are reached, it can be used in practice with requested calculating error.

Disentangling neighbors and extended range density oscillations in monatomic amorphous semiconductors.

PubMed

Roorda, S; Martin, C; Droui, M; Chicoine, M; Kazimirov, A; Kycia, S

2012-06-22

High energy x-ray diffraction measurements of pure amorphous Ge were made and its radial distribution function (RDF) was determined at high resolution, revealing new information on the atomic structure of amorphous semiconductors. Fine structure in the second peak in the RDF provides evidence that a fraction of third neighbors are closer than some second neighbors; taking this into account leads to a narrow distribution of tetrahedral bond angles, (8.5 ± 0.1)°. A small peak which appears near 5 Å upon thermal annealing shows that some ordering in the dihedral bond-angle distribution takes place during structural relaxation. Extended range order is detected (in both a-Ge and a-Si) which persists to beyond 20 Å, and both the periodicity and its decay length increase upon thermal annealing. Previously, the effect of structural relaxation was only detected at intermediate range, involving reduced tetrahedral bond-angle distortions. These results enhance our understanding of the atomic order in continuous random networks and place significantly more stringent requirements on computer models intending to describe these networks, or their alternatives which attempt to describe the structure in terms of an arrangement of paracrystals.

Watching ultrafast responses of structure and magnetism in condensed matter with momentum-resolved probes

PubMed Central

Johnson, S. L.; Savoini, M.; Beaud, P.; Ingold, G.; Staub, U.; Carbone, F.; Castiglioni, L.; Hengsberger, M.; Osterwalder, J.

2017-01-01

We present a non-comprehensive review of some representative experimental studies in crystalline condensed matter systems where the effects of intense ultrashort light pulses are probed using x-ray diffraction and photoelectron spectroscopy. On an ultrafast (sub-picosecond) time scale, conventional concepts derived from the assumption of thermodynamic equilibrium must often be modified in order to adequately describe the time-dependent changes in material properties. There are several commonly adopted approaches to this modification, appropriate in different experimental circumstances. One approach is to treat the material as a collection of quasi-thermal subsystems in thermal contact with each other in the so-called “N-temperature” models. On the other extreme, one can also treat the time-dependent changes as fully coherent dynamics of a sometimes complex network of excitations. Here, we present examples of experiments that fall into each of these categories, as well as experiments that partake of both models. We conclude with a discussion of the limitations and future potential of these concepts. PMID:29308418

Noninvasive glucose monitoring by optical reflective and thermal emission spectroscopic measurements

NASA Astrophysics Data System (ADS)

Saetchnikov, V. A.; Tcherniavskaia, E. A.; Schiffner, G.

2005-08-01

Noninvasive method for blood glucose monitoring in cutaneous tissue based on reflective spectrometry combined with a thermal emission spectroscopy has been developed. Regression analysis, neural network algorithms and cluster analysis are used for data processing.

A modeling assessment of the thermal regime for an urban sport fishery

NASA Astrophysics Data System (ADS)

Bartholow, John M.

1991-11-01

Water temperature is almost certainly a limiting factor in the maintenance of a self-sustaining rainbow trout ( Oncorhynchus mykiss, formerly Salmo gairdneri) and brown trout ( Salmo trutta) fishery in the lower reaches of the Cache la Poudre River near Fort Collins, Colorado, USA. Irrigation diversions dewater portions of the river, but cold reservoir releases moderate water temperatures during some periods. The US Fish and Wildlife Service’s Stream Network Temperature Model (SNTEMP) was applied to a 31-km segment of the river using readily available stream geometry and hydrological and meteorological data. The calibrated model produced satisfactory water temperature predictions ( R 2=0.88, P<0.001, N=49) for a 62-day summer period. It was used to evaluate a variety of flow and nonflow alternatives to keep water temperatures below 23.3°C for the trout. Supplemental flows or reduced diversions of 3 m3/sec would be needed to maintain suitable summer temperatures throughout most of the study area. Such flows would be especially beneficial during weekends when current irrigation patterns reduce flows. The model indicated that increasing the riparian shade would result in little improvement in water temperatures but that decreasing the stream width would result in significant temperature reductions. Introduction of a more thermally tolerant redband trout ( Oncorhynchus sp.), or smallmouth bass ( Micropterus dolomieui) might prove beneficial to the fishery. Construction of deep pools for thermal refugia might also be helpful.

Dimensionless Numbers For Morphological, Thermal And Biogeochemical Controls Of Hyporheic Processes

NASA Astrophysics Data System (ADS)

Bellin, Alberto; Marzadri, Alessandra; Tonina, Daniele

2013-04-01

Transport of solutes and heat within the hyporheic zone are interface processes that gained growing attention in the last decade, when several modelling strategies have been proposed, mainly at the local or reach scale. We propose to upscale local hyporheic biogeochemical processes to reach and network scales by means of a Lagrangian modelling framework, which allows to consider the impact of the flow structure on the processes modelled. This analysis shows that geochemical processes can be parametrized through two new Damköhler numbers, DaO, and DaT. DaO = ?up,50-?lim is defined as the ratio between the median hyporheic residence time, ?up,50 and the time of consuming dissolved oxygen to a prescribed threshold concentration, ?lim, below which reductive reactions are activated. It quantifies the biogeochemical status of the hyporheic zone and could be a metric for upscaling local hyporheic biogeochemical processes to reach and river-network scale processes. In addition, ?up,50 is the time scale of hyporheic advection; while ?lim is the representative time scale of biogeochemical reactions and indicates the distance along the streamline, measured as the time needed to travel that distance, that a particle of water travels before the dissolved oxygen concentration declines to [DO]lim, the value at which denitrification is activated. We show that DaO is representative of the redox status and indicates whether the hyporheic zone is a source or a sink of nitrate. Values of DaO larger than 1 indicate prevailing anaerobic conditions, whereas values smaller than 1 prevailing aerobic conditions. Similarly, DaT quantifies the importance of the temperature daily oscillations of the stream water on the hyporheic environment. It is defined as the ratio between ?up,50, and the time limit at which the ratio between the amplitude of the temperature oscillation within the hyporheic zone (evaluated along the streamline) and in the stream water is smaller than e-1. We show that values of DaT > 1 indicate a thermally stable hyporheic zone, where organism metabolism is not influenced by surface water thermal oscillations and biogeochemical reaction rates depend on the mean daily stream water temperature. Values smaller than 1 suggest that organisms need to adapt to the daily thermal variations and biogeochemical reaction rates will depend on the daily fluctuations induced by stream water.

Nonlinear dynamics of ice-wedge networks and resulting sensitivity to severe cooling events.

PubMed

Plug, L J; Werner, B T

2002-06-27

Patterns of subsurface wedges of ice that form along cooling-induced tension fractures, expressed at the ground surface by ridges or troughs spaced 10 30 m apart, are ubiquitous in polar lowlands. Fossilized ice wedges, which are widespread at lower latitudes, have been used to infer the duration and mean temperature of cold periods within Proterozoic and Quaternary climates, and recent climate trends have been inferred from fracture frequency in active ice wedges. Here we present simulations from a numerical model for the evolution of ice-wedge networks over a range of climate scenarios, based on the interactions between thermal tensile stress, fracture and ice wedges. We find that short-lived periods of severe cooling permanently alter the spacing between ice wedges as well as their fracture frequency. This affects the rate at which the widths of ice wedges increase as well as the network's response to subsequent climate change. We conclude that wedge spacing and width in ice-wedge networks mainly reflect infrequent episodes of rapidly falling ground temperatures rather than mean conditions.

Thermotaxis is a Robust Mechanism for Thermoregulation in C. elegans Nematodes

PubMed Central

Ramot, Daniel; MacInnis, Bronwyn L.; Lee, Hau-Chen; Goodman, Miriam B.

2013-01-01

Many biochemical networks are robust to variations in network or stimulus parameters. Although robustness is considered an important design principle of such networks, it is not known whether this principle also applies to higher-level biological processes such as animal behavior. In thermal gradients, C. elegans uses thermotaxis to bias its movement along the direction of the gradient. Here we develop a detailed, quantitative map of C. elegans thermotaxis and use these data to derive a computational model of thermotaxis in the soil, a natural environment of C. elegans. This computational analysis indicates that thermotaxis enables animals to avoid temperatures at which they cannot reproduce, to limit excursions from their adapted temperature, and to remain relatively close to the surface of the soil, where oxygen is abundant. Furthermore, our analysis reveals that this mechanism is robust to large variations in the parameters governing both worm locomotion and temperature fluctuations in the soil. We suggest that, similar to biochemical networks, animals evolve behavioral strategies that are robust, rather than strategies that rely on fine-tuning of specific behavioral parameters. PMID:19020047

Modeling and analysis of chill and fill processes for the cryogenic storage and transfer engineering development unit tank

NASA Astrophysics Data System (ADS)

Hedayat, A.; Cartagena, W.; Majumdar, A. K.; LeClair, A. C.

2016-03-01

NASA's future missions may require long-term storage and transfer of cryogenic propellants. The Engineering Development Unit (EDU), a NASA in-house effort supported by both Marshall Space Flight Center (MSFC) and Glenn Research Center, is a cryogenic fluid management (CFM) test article that primarily serves as a manufacturing pathfinder and a risk reduction task for a future CFM payload. The EDU test article comprises a flight-like tank, internal components, insulation, and attachment struts. The EDU is designed to perform integrated passive thermal control performance testing with liquid hydrogen (LH2) in a test-like vacuum environment. A series of tests, with LH2 as a testing fluid, was conducted at Test Stand 300 at MSFC during the summer of 2014. The objective of this effort was to develop a thermal/fluid model for evaluating the thermodynamic behavior of the EDU tank during the chill and fill processes. The Generalized Fluid System Simulation Program, an MSFC in-house general-purpose computer program for flow network analysis, was utilized to model and simulate the chill and fill portion of the testing. The model contained the LH2 supply source, feed system, EDU tank, and vent system. The test setup, modeling description, and comparison of model predictions with the test data are presented.

Thermal model development and validation for rapid filling of high pressure hydrogen tanks

DOE PAGES

Johnson, Terry A.; Bozinoski, Radoslav; Ye, Jianjun; ...

2015-06-30

This paper describes the development of thermal models for the filling of high pressure hydrogen tanks with experimental validation. Two models are presented; the first uses a one-dimensional, transient, network flow analysis code developed at Sandia National Labs, and the second uses the commercially available CFD analysis tool Fluent. These models were developed to help assess the safety of Type IV high pressure hydrogen tanks during the filling process. The primary concern for these tanks is due to the increased susceptibility to fatigue failure of the liner caused by the fill process. Thus, a thorough understanding of temperature changes ofmore » the hydrogen gas and the heat transfer to the tank walls is essential. The effects of initial pressure, filling time, and fill procedure were investigated to quantify the temperature change and verify the accuracy of the models. In this paper we show that the predictions of mass averaged gas temperature for the one and three-dimensional models compare well with the experiment and both can be used to make predictions for final mass delivery. Furthermore, due to buoyancy and other three-dimensional effects, however, the maximum wall temperature cannot be predicted using one-dimensional tools alone which means that a three-dimensional analysis is required for a safety assessment of the system.« less

Modeling and Analysis of Chill and Fill Processes for the EDU Tank

NASA Technical Reports Server (NTRS)

Hedayat, A.; Cartagena, W.; Majumdar, A. K.; Leclair, A. C.

2015-01-01

NASA's future missions may require long-term storage and transfer of cryogenic propellants. The Engineering Development Unit (EDU), a NASA in-house effort supported by both Marshall Space Flight Center (MSFC) and Glenn Research Center (GRC), is a Cryogenic Fluid Management (CFM) test article that primarily serves as a manufacturing pathfinder and a risk reduction task for a future CFM payload. The EDU test article, comprises a flight like tank, internal components, insulation, and attachment struts. The EDU is designed to perform integrated passive thermal control performance testing with liquid hydrogen in a space-like vacuum environment. A series of tests, with liquid hydrogen as a testing fluid, was conducted at Test Stand 300 at MSFC during summer of 2014. The objective of this effort was to develop a thermal/fluid model for evaluating the thermodynamic behavior of the EDU tank during the chill and fill processes. Generalized Fluid System Simulation Program (GFSSP), an MSFC in-house general-purpose computer program for flow network analysis, was utilized to model and simulate the chill and fill portion of the testing. The model contained the liquid hydrogen supply source, feed system, EDU tank, and vent system. The modeling description and comparison of model predictions with the test data will be presented in the final paper.

Modeling of ultrashort pulsed laser irradiation in the cornea based on parabolic and hyperbolic heat equations using electrical analogy

NASA Astrophysics Data System (ADS)

Gheitaghy, A. M.; Takabi, B.; Alizadeh, M.

2014-03-01

Hyperbolic and parabolic heat equations are formulated to study a nonperfused homogeneous transparent cornea irradiated by high power and ultrashort pulsed laser in the Laser Thermo Keratoplasty (LTK) surgery. Energy absorption inside the cornea is modeled using the Beer-Lambert law that is incorporated as an exponentially decaying heat source. The hyperbolic and parabolic bioheat models of the tissue were solved by exploiting the mathematical analogy between thermal and electrical systems, by using robust circuit simulation program called Hspice to get the solutions of simultaneous RLC and RC transmission line networks. This method can be used to rapidly calculate the temperature in laser-irradiated tissue at time and space domain. It is found that internal energy gained from the irradiated field results in a rapid rise of temperature in the cornea surface during the early heating period, while the hyperbolic wave model predicts a higher temperature rise than the classical heat diffusion model. In addition, this paper investigates and examines the effect of some critical parameters such as relaxation time, convection coefficient, radiation, tear evaporation and variable thermal conductivity of cornea. Accordingly, it is found that a better accordance between hyperbolic and parabolic models will be achieved by time.

Thermal Properties of Consolidated Granular Salt as a Backfill Material

NASA Astrophysics Data System (ADS)

Paneru, Laxmi P.; Bauer, Stephen J.; Stormont, John C.

2018-03-01

Granular salt has been proposed as backfill material in drifts and shafts of a nuclear waste disposal facility where it will serve to conduct heat away from the waste to the host rock. Creep closure of excavations in rock salt will consolidate (reduce the porosity of) the granular salt. This study involved measuring the thermal conductivity and specific heat of granular salt as a function of porosity and temperature to aid in understanding how thermal properties will change during granular salt consolidation accomplished at pressures and temperatures consistent with a nuclear waste disposal facility. Thermal properties of samples from laboratory-consolidated granular salt and in situ consolidated granular salt were measured using a transient plane source method at temperatures ranging from 50 to 250 °C. Additional measurements were taken on a single crystal of halite and dilated polycrystalline rock salt. Thermal conductivity of granular salt decreased with increases in temperature and porosity. Specific heat of granular salt at lower temperatures decreased with increasing porosity. At higher temperatures, porosity dependence was not apparent. The thermal conductivity and specific heat data were fit to empirical models and compared with results presented in the literature. At comparable densities, the thermal conductivities of granular salt samples consolidated hydrostatically in this study were greater than those measured previously on samples formed by quasi-static pressing. Petrographic studies of the consolidated salt indicate that the consolidation method influenced the nature of the porosity; these observations are used to explain the variation of measured thermal conductivities between the two consolidation methods. Thermal conductivity of dilated polycrystalline salt was lower than consolidated salt at comparable porosities. The pervasive crack network along grain boundaries in dilated salt impedes heat flow and results in a lower thermal conductivity compared to hydrostatically consolidated salt.

Projected climate-induced habitat loss for salmonids in the John Day River network, Oregon, U.S.A.

USGS Publications Warehouse

Ruesch, Aaron S.; Torgersen, Christian E.; Lawler, Joshua J.; Olden, Julian D.; Peterson, Erin E.; Volk, Carol J.; Lawrence, David J.

2012-01-01

Climate change will likely have profound effects on cold-water species of freshwater fishes. As temperatures rise, cold-water fish distributions may shift and contract in response. Predicting the effects of projected stream warming in stream networks is complicated by the generally poor correlation between water temperature and air temperature. Spatial dependencies in stream networks are complex because the geography of stream processes is governed by dimensions of flow direction and network structure. Therefore, forecasting climate-driven range shifts of stream biota has lagged behind similar terrestrial modeling efforts. We predicted climate-induced changes in summer thermal habitat for 3 cold-water fish species—juvenile Chinook salmon, rainbow trout, and bull trout (Oncorhynchus tshawytscha, O. mykiss, and Salvelinus confluentus, respectively)—in the John Day River basin, northwestern United States. We used a spatially explicit statistical model designed to predict water temperature in stream networks on the basis of flow and spatial connectivity. The spatial distribution of stream temperature extremes during summers from 1993 through 2009 was largely governed by solar radiation and interannual extremes of air temperature. For a moderate climate change scenario, estimated declines by 2100 in the volume of habitat for Chinook salmon, rainbow trout, and bull trout were 69–95%, 51–87%, and 86–100%, respectively. Although some restoration strategies may be able to offset these projected effects, such forecasts point to how and where restoration and management efforts might focus.

Thermal Regulation of Heat Transfer Processes

DTIC Science & Technology

2014-10-02

determine the contrasts of thermophysical properties of composites and thin films , and various approaches to regulate heat transport processes. In the...nanofluids, 2) thermal regulation of optical properties in thin film , and 3) thermal regulation of phase transition for efficient steam generation...stress generated during the crystals growth forces CNTs to contact with each other and form a conductive percolation network. Hence the composite

Suppression of anomalous synchronization and nonstationary behavior of neural network under small-world topology

NASA Astrophysics Data System (ADS)

Boaretto, B. R. R.; Budzinski, R. C.; Prado, T. L.; Kurths, J.; Lopes, S. R.

2018-05-01

It is known that neural networks under small-world topology can present anomalous synchronization and nonstationary behavior for weak coupling regimes. Here, we propose methods to suppress the anomalous synchronization and also to diminish the nonstationary behavior occurring in weakly coupled neural network under small-world topology. We consider a network of 2000 thermally sensitive identical neurons, based on the model of Hodgkin-Huxley in a small-world topology, with the probability of adding non local connection equal to p = 0 . 001. Based on experimental protocols to suppress anomalous synchronization, as well as nonstationary behavior of the neural network dynamics, we make use of (i) external stimulus (pulsed current); (ii) biologic parameters changing (neuron membrane conductance changes); and (iii) body temperature changes. Quantification analysis to evaluate phase synchronization makes use of the Kuramoto's order parameter, while recurrence quantification analysis, particularly the determinism, computed over the easily accessible mean field of network, the local field potential (LFP), is used to evaluate nonstationary states. We show that the methods proposed can control the anomalous synchronization and nonstationarity occurring for weak coupling parameter without any effect on the individual neuron dynamics, neither in the expected asymptotic synchronized states occurring for large values of the coupling parameter.

Prediction of the thermal imaging minimum resolvable (circle) temperature difference with neural network application.

PubMed

Fang, Yi-Chin; Wu, Bo-Wen

2008-12-01

Thermal imaging is an important technology in both national defense and the private sector. An advantage of thermal imaging is its ability to be deployed while fully engaged in duties, not limited by weather or the brightness of indoor or outdoor conditions. However, in an outdoor environment, many factors, including atmospheric decay, target shape, great distance, fog, temperature out of range and diffraction limits can lead to bad image formation, which directly affects the accuracy of object recognition. The visual characteristics of the human eye mean that it has a much better capacity for picture recognition under normal conditions than artificial intelligence does. However, conditions of interference significantly reduce this capacity for picture recognition for instance, fatigue impairs human eyesight. Hence, psychological and physiological factors can affect the result when the human eye is adopted to measure MRTD (minimum resolvable temperature difference) and MRCTD (minimum resolvable circle temperature difference). This study explores thermal imaging recognition, and presents a method for effectively choosing the characteristic values and processing the images fully. Neural network technology is successfully applied to recognize thermal imaging and predict MRTD and MRCTD (Appendix A), exceeding thermal imaging recognition under fatigue and the limits of the human eye.

Applications of a thermal-based two-source energy balance model using Priestley-Taylor approach for surface temperature partitioning under advective conditions

NASA Astrophysics Data System (ADS)

Song, Lisheng; Kustas, William P.; Liu, Shaomin; Colaizzi, Paul D.; Nieto, Hector; Xu, Ziwei; Ma, Yanfei; Li, Mingsong; Xu, Tongren; Agam, Nurit; Tolk, Judy A.; Evett, Steven R.

2016-09-01

In this study ground measured soil and vegetation component temperatures and composite temperature from a high spatial resolution thermal camera and a network of thermal-IR sensors collected in an irrigated maize field and in an irrigated cotton field are used to assess and refine the component temperature partitioning approach in the Two-Source Energy Balance (TSEB) model. A refinement to TSEB using a non-iterative approach based on the application of the Priestley-Taylor formulation for surface temperature partitioning and estimating soil evaporation from soil moisture observations under advective conditions (TSEB-A) was developed. This modified TSEB formulation improved the agreement between observed and modeled soil and vegetation temperatures. In addition, the TSEB-A model output of evapotranspiration (ET) and the components evaporation (E), transpiration (T) when compared to ground observations using the stable isotopic method and eddy covariance (EC) technique from the HiWATER experiment and with microlysimeters and a large monolithic weighing lysimeter from the BEAREX08 experiment showed good agreement. Difference between the modeled and measured ET measurements were less than 10% and 20% on a daytime basis for HiWATER and BEAREX08 data sets, respectively. The TSEB-A model was found to accurately reproduce the temporal dynamics of E, T and ET over a full growing season under the advective conditions existing for these irrigated crops located in arid/semi-arid climates. With satellite data this TSEB-A modeling framework could potentially be used as a tool for improving water use efficiency and conservation practices in water limited regions. However, TSEB-A requires soil moisture information which is not currently available routinely from satellite at the field scale.

Assessment of the MHD capability in the ATHENA code using data from the ALEX facility

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

Roth, P.A.

1989-03-01

The ATHENA (Advanced Thermal Hydraulic Energy Network Analyzer) code is a system transient analysis code with multi-loop, multi-fluid capabilities, which is available to the fusion community at the National Magnetic Fusion Energy Computing Center (NMFECC). The work reported here assesses the ATHENA magnetohydrodynamic (MHD) pressure drop model for liquid metals flowing through a strong magnetic field. An ATHENA model was developed for two simple geometry, adiabatic test sections used in the Argonne Liquid Metal Experiment (ALEX) at Argonne National Laboratory (ANL). The pressure drops calculated by ATHENA agreed well with the experimental results from the ALEX facility.

Quantum Assisted Learning for Registration of MODIS Images

NASA Astrophysics Data System (ADS)

Pelissier, C.; Le Moigne, J.; Fekete, G.; Halem, M.

2017-12-01

The advent of the first large scale quantum annealer by D-Wave has led to an increased interest in quantum computing. However, the quantum annealing computer of the D-Wave is limited to either solving Quadratic Unconstrained Binary Optimization problems (QUBOs) or using the ground state sampling of an Ising system that can be produced by the D-Wave. These restrictions make it challenging to find algorithms to accelerate the computation of typical Earth Science applications. A major difficulty is that most applications have continuous real-valued parameters rather than binary. Here we present an exploratory study using the ground state sampling to train artificial neural networks (ANNs) to carry out image registration of MODIS images. The key idea to using the D-Wave to train networks is that the quantum chip behaves thermally like Boltzmann machines (BMs), and BMs are known to be successful at recognizing patterns in images. The ground state sampling of the D-Wave also depends on the dynamics of the adiabatic evolution and is subject to other non-thermal fluctuations, but the statistics are thought to be similar and ANNs tend to be robust under fluctuations. In light of this, the D-Wave ground state sampling is used to define a Boltzmann like generative model and is investigated to register MODIS images. Image intensities of MODIS images are transformed using a Discrete Cosine Transform and used to train a several layers network to learn how to align images to a reference image. The network layers consist of an initial sigmoid layer acting as a binary filter of the input followed by a strict binarization using Bernoulli sampling, and then fed into a Boltzmann machine. The output is then classified using a soft-max layer. Results are presented and discussed.

Application of a neural network for reflectance spectrum classification

NASA Astrophysics Data System (ADS)

Yang, Gefei; Gartley, Michael

2017-05-01

Traditional reflectance spectrum classification algorithms are based on comparing spectrum across the electromagnetic spectrum anywhere from the ultra-violet to the thermal infrared regions. These methods analyze reflectance on a pixel by pixel basis. Inspired by high performance that Convolution Neural Networks (CNN) have demonstrated in image classification, we applied a neural network to analyze directional reflectance pattern images. By using the bidirectional reflectance distribution function (BRDF) data, we can reformulate the 4-dimensional into 2 dimensions, namely incident direction × reflected direction × channels. Meanwhile, RIT's micro-DIRSIG model is utilized to simulate additional training samples for improving the robustness of the neural networks training. Unlike traditional classification by using hand-designed feature extraction with a trainable classifier, neural networks create several layers to learn a feature hierarchy from pixels to classifier and all layers are trained jointly. Hence, the our approach of utilizing the angular features are different to traditional methods utilizing spatial features. Although training processing typically has a large computational cost, simple classifiers work well when subsequently using neural network generated features. Currently, most popular neural networks such as VGG, GoogLeNet and AlexNet are trained based on RGB spatial image data. Our approach aims to build a directional reflectance spectrum based neural network to help us to understand from another perspective. At the end of this paper, we compare the difference among several classifiers and analyze the trade-off among neural networks parameters.

Formation of Valley Networks in a Cold and Icy Early Mars Climate: Predictions for Erosion Rates and Channel Morphology

NASA Astrophysics Data System (ADS)

Cassanelli, J.

2017-12-01

Mars is host to a diverse array of valley networks, systems of linear-to-sinuous depressions which are widely distributed across the surface and which exhibit branching patterns similar to the dendritic drainage patterns of terrestrial fluvial systems. Characteristics of the valley networks are indicative of an origin by fluvial activity, providing among the most compelling evidence for the past presence of flowing liquid water on the surface of Mars. Stratigraphic and crater age dating techniques suggest that the formation of the valley networks occurred predominantly during the early geologic history of Mars ( 3.7 Ga). However, whether the valley networks formed predominantly by rainfall in a relatively warm and wet early Mars climate, or by snowmelt and episodic rainfall in an ambient cold and icy climate, remains disputed. Understanding the formative environment of the valley networks will help distinguish between these warm and cold end-member early Mars climate models. Here we test a conceptual model for channel incision and evolution under cold and icy conditions with a substrate characterized by the presence of an ice-free dry active layer and subjacent ice-cemented regolith, similar to that found in the Antarctic McMurdo Dry Valleys. We implement numerical thermal models, quantitative erosion and transport estimates, and morphometric analyses in order to outline predictions for (1) the precise nature and structure of the substrate, (2) fluvial erosion/incision rates, and (3) channel morphology. Model predictions are compared against morphologic and morphometric observational data to evaluate consistency with the assumed cold climate scenario. In the cold climate scenario, the substrate is predicted to be characterized by a kilometers-thick globally-continuous cryosphere below a 50-100 meter thick desiccated ice-free zone. Initial results suggest that, with the predicted substrate structure, fluvial channel erosion and morphology in a cold early Mars climate exposed to episodic high temperatures will not differ significantly from that in a warm climate. The fundamentally different hydrologic conditions are likely to influence other aspects of valley network morphology and morphometry including: drainage density, drainage pattern, and stream orders.

A new methodology for determination of macroscopic transport parameters in drying porous media

NASA Astrophysics Data System (ADS)

Attari Moghaddam, A.; Kharaghani, A.; Tsotsas, E.; Prat, M.

2015-12-01

Two main approaches have been used to model the drying process: The first approach considers the partially saturated porous medium as a continuum and partial differential equations are used to describe the mass, momentum and energy balances of the fluid phases. The continuum-scale models (CM) obtained by this approach involve constitutive laws which require effective material properties, such as the diffusivity, permeability, and thermal conductivity which are often determined by experiments. The second approach considers the material at the pore scale, where the void space is represented by a network of pores (PN). Micro- or nanofluidics models used in each pore give rise to a large system of ordinary differential equations with degrees of freedom at each node of the pore network. In this work, the moisture transport coefficient (D), the pseudo desorption isotherm inside the network and at the evaporative surface are estimated from the post-processing of the three-dimensional pore network drying simulations for fifteen realizations of the pore space geometry from a given probability distribution. A slice sampling method is used in order to extract these parameters from PN simulations. The moisture transport coefficient obtained in this way is shown in Fig. 1a. The minimum of average D values demonstrates the transition between liquid dominated moisture transport region and vapor dominated moisture transport region; a similar behavior has been observed in previous experimental findings. A function is fitted to the average D values and then is fed into the non-linear moisture diffusion equation. The saturation profiles obtained from PN and CM simulations are shown in Fig. 1b. Figure 1: (a) extracted moisture transport coefficient during drying for fifteen realizations of the pore network, (b) average moisture profiles during drying obtained from PN and CM simulations.

Molecular Modeling of Aerospace Polymer Matrices Including Carbon Nanotube-Enhanced Epoxy

NASA Astrophysics Data System (ADS)

Radue, Matthew S.

Carbon fiber (CF) composites are increasingly replacing metals used in major structural parts of aircraft, spacecraft, and automobiles. The current limitations of carbon fiber composites are addressed through computational material design by modeling the salient aerospace matrix materials. Molecular Dynamics (MD) models of epoxies with and without carbon nanotube (CNT) reinforcement and models of pure bismaleimides (BMIs) were developed to elucidate structure-property relationships for improved selection and tailoring of matrices. The influence of monomer functionality on the mechanical properties of epoxies is studied using the Reax Force Field (ReaxFF). From deformation simulations, the Young's modulus, yield point, and Poisson's ratio are calculated and analyzed. The results demonstrate an increase in stiffness and yield strength with increasing resin functionality. Comparison between the network structures of distinct epoxies is further advanced by the Monomeric Degree Index (MDI). Experimental validation demonstrates the MD results correctly predict the relationship in Young's moduli for all epoxies modeled. Therefore, the ReaxFF is confirmed to be a useful tool for studying the mechanical behavior of epoxies. While epoxies have been well-studied using MD, there has been no concerted effort to model cured BMI polymers due to the complexity of the network-forming reactions. A novel, adaptable crosslinking framework is developed for implementing 5 distinct cure reactions of Matrimid-5292 (a BMI resin) and investigating the network structure using MD simulations. The influence of different cure reactions and extent of curing are analyzed on the several thermo-mechanical properties such as mass density, glass transition temperature, coefficient of thermal expansion, elastic moduli, and thermal conductivity. The developed crosslinked models correctly predict experimentally observed trends for various properties. Finally, the epoxies modeled (di-, tri-, and tetra-functionalresins) are simulated with embedded CNT to understand how the affinity to nanoparticles affects the mechanical response. Multiscale modeling techniques are then employed to translate the molecular phenomena observed to predict the behavior of realistic composites. The effective stiffness of hybrid composites are predicted for CNT/epoxy composites with randomly oriented CNTs, for CF/CNT/epoxy systems with aligned CFs and randomly oriented CNTs, and for woven CF/CNT/epoxy fabric with randomly oriented CNTs. The results indicate that in the CNT/epoxy systems the epoxy type has a significant influence on the elastic properties. For the CF/CNT/epoxy hybrid composites, the axial modulus is highly influenced by CF concentration, while the transverse modulus is primarily affected by the CNT weight fraction.

Investigation of thermal transport in polymer composites with percolating networks of silver thin films by the flash diffusivity method

NASA Astrophysics Data System (ADS)

Pettersen, Sigurd R.; Nagao, Shijo; Kristiansen, Helge; Helland, Susanne; Njagi, John; Suganuma, Katsuaki; Zhang, Zhiliang; He, Jianying

2017-01-01

The flash diffusivity method, also known as laser flash analysis (LFA), is commonly used to obtain the thermal diffusivity (α) and thermal conductivity (κ) of materials, due to its relative simplicity, rapid measurements, small sample size requirement, and standardized commercially available instruments. In this work, an epoxy adhesive was filled with a large fraction of homogeneous micron-sized polymethylmethacrylate spheres coated with thin silver films, such that a percolating metallic network that dominated the electric and thermal transport formed through the polymer at <3 vol. % silver. Specific heat capacity (Cp) was measured from the LFA measurements by a comparative method and from the total and reversible heat flow signals of modulated differential scanning calorimetry (MDSC). κ was estimated as the product of α, Cp, and density (ρ) and was found to vary significantly with the method to find Cp. The electron contribution was found from the electrical conductivity by the Wiedemann-Franz law and was used to elucidate the thermal transport mechanisms in the composite. A theoretical background for the various methods is included.

Cooling rates for glass containing lunar compositions

NASA Technical Reports Server (NTRS)

Fang, C. Y.; Yinnon, H.; Uhlmann, D. R.

1983-01-01

Cooling rates required to form glassy or partly-crystalline bodies of 14 lunar compositions have been estimated using a previously introduced, simplified model. The calculated cooling rates are found to be in good agreement with cooling rates measured for the same compositions. Measurements are also reported of the liquidus temperature and glass transition temperature for each composition. Inferred cooling rates are combined with heat flow analyses to obtain insight into the thermal histories of samples 15422, 14162, 15025, 74220, 74241, 10084, 15425, and 15427. The critical cooling rates required to form glasses of 24 lunar compositions, including the 14 compositions of the present study, are suggested to increase systematically with increasing ratio of total network modifiers/total network formers in the compositions. This reflects the importance of melt viscosity in affecting glass formation.

Method of Calculating the Correction Factors for Cable Dimensioning in Smart Grids

NASA Astrophysics Data System (ADS)

Simutkin, M.; Tuzikova, V.; Tlusty, J.; Tulsky, V.; Muller, Z.

2017-04-01

One of the main causes of overloading electrical equipment by currents of higher harmonics is the great increasing of a number of non-linear electricity power consumers. Non-sinusoidal voltages and currents affect the operation of electrical equipment, reducing its lifetime, increases the voltage and power losses in the network, reducing its capacity. There are standards that respects emissions amount of higher harmonics current that cannot provide interference limit for a safe level in power grid. The article presents a method for determining a correction factor to the long-term allowable current of the cable, which allows for this influence. Using mathematical models in the software Elcut, it was described thermal processes in the cable in case the flow of non-sinusoidal current. Developed in the article theoretical principles, methods, mathematical models allow us to calculate the correction factor to account for the effect of higher harmonics in the current spectrum for network equipment in any type of non-linear load.

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

Sobral, G. A. Jr.; Vieira, V. M.; Lyra, M. L.

Extending a model due to Derrida, Gardner, and Zippelius, we have studied the recognition ability of an extreme and asymmetrically diluted version of the Hopfield model for associative memory by including the effect of a stimulus in the dynamics of the system. We obtain exact results for the dynamic evolution of the average network superposition. The stimulus field was considered as proportional to the overlapping of the state of the system with a particular stimulated pattern. Two situations were analyzed, namely, the external stimulus acting on the initialization pattern (parallel stimulus) and the external stimulus acting on a pattern orthogonalmore » to the initialization one (orthogonal stimulus). In both cases, we obtained the complete phase diagram in the parameter space composed of the stimulus field, thermal noise, and network capacity. Our results show that the system improves its recognition ability for parallel stimulus. For orthogonal stimulus two recognition phases emerge with the system locking at the initialization or stimulated pattern. We confront our analytical results with numerical simulations for the noiseless case T=0.« less

An adjoint-based sensitivity analysis of thermoacoustic network models

NASA Astrophysics Data System (ADS)

Sogaro, Francesca; Morgans, Aimee; Schmid, Peter

2017-11-01

Thermoacoustic instability is a phenomenon that occurs in numerous combustion systems, from rockets to land-based gas turbines. The acoustic oscillations of these systems are of significant importance as they can result in severe vibrations, thrust oscillations, thermal stresses and mechanical loads that lead to fatigue or even failure. In this work we use a low-order network model representation of a combustor system where linear acoustics are solved together with the appropriate boundary conditions, area change jump conditions, acoustic dampers and an appropriate flame transfer function. Special emphasis is directed towards the interaction between acoustically driven instabilities and flame-intrinsic modes. Adjoint methods are used to perform a sensitivity analysis of the spectral properties of the system to changes in the parameters involved. An exchange of modal identity between acoustic and intrinsic modes will be demonstrated and analyzed. The results provide insight into the interplay between various mode types and build a quantitative foundation for the design of combustors.

Thermoelectric Generators for Automotive Waste Heat Recovery Systems Part I: Numerical Modeling and Baseline Model Analysis

NASA Astrophysics Data System (ADS)

Kumar, Sumeet; Heister, Stephen D.; Xu, Xianfan; Salvador, James R.; Meisner, Gregory P.

2013-04-01

A numerical model has been developed to simulate coupled thermal and electrical energy transfer processes in a thermoelectric generator (TEG) designed for automotive waste heat recovery systems. This model is capable of computing the overall heat transferred, the electrical power output, and the associated pressure drop for given inlet conditions of the exhaust gas and the available TEG volume. Multiple-filled skutterudites and conventional bismuth telluride are considered for thermoelectric modules (TEMs) for conversion of waste heat from exhaust into usable electrical power. Heat transfer between the hot exhaust gas and the hot side of the TEMs is enhanced with the use of a plate-fin heat exchanger integrated within the TEG and using liquid coolant on the cold side. The TEG is discretized along the exhaust flow direction using a finite-volume method. Each control volume is modeled as a thermal resistance network which consists of integrated submodels including a heat exchanger and a thermoelectric device. The pressure drop along the TEG is calculated using standard pressure loss correlations and viscous drag models. The model is validated to preserve global energy balances and is applied to analyze a prototype TEG with data provided by General Motors. Detailed results are provided for local and global heat transfer and electric power generation. In the companion paper, the model is then applied to consider various TEG topologies using skutterudite and bismuth telluride TEMs.

Assessing sufficiency of thermal riverscapes for resilient salmon and steelhead populations

EPA Science Inventory

Resilient salmon populations require river networks that provide water temperature regimes sufficient to support a diversity of salmonid life histories across space and time. Efforts to protect, enhance and restore watershed thermal regimes for salmon may target specific location...

Spatial statistical network models for stream and river temperature in New England, USA

NASA Astrophysics Data System (ADS)

Detenbeck, Naomi E.; Morrison, Alisa C.; Abele, Ralph W.; Kopp, Darin A.

2016-08-01

Watershed managers are challenged by the need for predictive temperature models with sufficient accuracy and geographic breadth for practical use. We described thermal regimes of New England rivers and streams based on a reduced set of metrics for the May-September growing season (July or August median temperature, diurnal rate of change, and magnitude and timing of growing season maximum) chosen through principal component analysis of 78 candidate metrics. We then developed and assessed spatial statistical models for each of these metrics, incorporating spatial autocorrelation based on both distance along the flow network and Euclidean distance between points. Calculation of spatial autocorrelation based on travel or retention time in place of network distance yielded tighter-fitting Torgegrams with less scatter but did not improve overall model prediction accuracy. We predicted monthly median July or August stream temperatures as a function of median air temperature, estimated urban heat island effect, shaded solar radiation, main channel slope, watershed storage (percent lake and wetland area), percent coarse-grained surficial deposits, and presence or maximum depth of a lake immediately upstream, with an overall root-mean-square prediction error of 1.4 and 1.5°C, respectively. Growing season maximum water temperature varied as a function of air temperature, local channel slope, shaded August solar radiation, imperviousness, and watershed storage. Predictive models for July or August daily range, maximum daily rate of change, and timing of growing season maximum were statistically significant but explained a much lower proportion of variance than the above models (5-14% of total).

Thermal and dynamic range characterization of a photonics-based RF amplifier

NASA Astrophysics Data System (ADS)

Noque, D. F.; Borges, R. M.; Muniz, A. L. M.; Bogoni, A.; Cerqueira S., Arismar, Jr.

2018-05-01

This work reports a thermal and dynamic range characterization of an ultra-wideband photonics-based RF amplifier for microwave and mm-waves future 5G optical-wireless networks. The proposed technology applies the four-wave mixing nonlinear effect to provide RF amplification in analog and digital radio-over-fiber systems. The experimental analysis from 300 kHz to 50 GHz takes into account different figures of merit, such as RF gain, spurious-free dynamic range and RF output power stability as a function of temperature. The thermal characterization from -10 to +70 °C demonstrates a 27 dB flat photonics-assisted RF gain over the entire frequency range under real operational conditions of a base station for illustrating the feasibility of the photonics-assisted RF amplifier for 5G networks.

Using barometric time series of the IMS infrasound network for a global analysis of thermally induced atmospheric tides

NASA Astrophysics Data System (ADS)

Hupe, Patrick; Ceranna, Lars; Pilger, Christoph

2018-04-01

The International Monitoring System (IMS) has been established to monitor compliance with the Comprehensive Nuclear-Test-Ban Treaty and comprises four technologies, one of which is infrasound. When fully established, the IMS infrasound network consists of 60 sites uniformly distributed around the globe. Besides its primary purpose of determining explosions in the atmosphere, the recorded data reveal information on other anthropogenic and natural infrasound sources. Furthermore, the almost continuous multi-year recordings of differential and absolute air pressure allow for analysing the atmospheric conditions. In this paper, spectral analysis tools are applied to derive atmospheric dynamics from barometric time series. Based on the solar atmospheric tides, a methodology for performing geographic and temporal variability analyses is presented, which is supposed to serve for upcoming studies related to atmospheric dynamics. The surplus value of using the IMS infrasound network data for such purposes is demonstrated by comparing the findings on the thermal tides with previous studies and the Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2), which represents the solar tides well in its surface pressure fields. Absolute air pressure recordings reveal geographical characteristics of atmospheric tides related to the solar day and even to the lunar day. We therefore claim the chosen methodology of using the IMS infrasound network to be applicable for global and temporal studies on specific atmospheric dynamics. Given the accuracy and high temporal resolution of the barometric data from the IMS infrasound network, interactions with gravity waves and planetary waves can be examined in future for refining the knowledge of atmospheric dynamics, e.g. the origin of tidal harmonics up to 9 cycles per day as found in the barometric data sets. Data assimilation in empirical models of solar tides would be a valuable application of the IMS infrasound data.

Mechanism study of biopolymer hair as a coupled thermo-water responsive smart material

NASA Astrophysics Data System (ADS)

Xiao, Xueliang; Zhou, Hongtao; Qian, Kun

2017-03-01

Animal hairs existing broadly in nature are found to be effectively responsive to stimuli of heat and water in sequence for shape deformation and recovery, namely, coupled shape memory function (CSMF). In the paper, the ability of thermo-water sensitive CSMF was first time investigated for animal hairs, the structural and molecular networks for net-points and switches were therefrom identified. Experimentally, animal hair manifested a high ability of shape fixation in thermal processing and good shape recovery by water stimulus. Characterizations of two stimuli (heating and hydration) were performed systematically on hair’s deformation, recovery, viscoelasticity and chemical components (crystalline phase, key bonds inamorphous area). The variations of related chemical components in molecular networks were also explored. A hybrid structural network model was thereafter proposed to interpret the thermo-water sensitive CSMF of hair. This study of two-sequential-stimuli CSMF is original and inspired to explore more complex functions of other smart natural materials and expected to make much smarter synthetic polymers.

Spectra of Adjacency Matrices in Networks of Extreme Introverts and Extroverts

NASA Astrophysics Data System (ADS)

Bassler, Kevin E.; Ezzatabadipour, Mohammadmehdi; Zia, R. K. P.

Many interesting properties were discovered in recent studies of preferred degree networks, suitable for describing social behavior of individuals who tend to prefer a certain number of contacts. In an extreme version (coined the XIE model), introverts always cut links while extroverts always add them. While the intra-group links are static, the cross-links are dynamic and lead to an ensemble of bipartite graphs, with extraordinary correlations between elements of the incidence matrix: nij In the steady state, this system can be regarded as one in thermal equilibrium with long-ranged interactions between the nij's, and displays an extreme Thouless effect. Here, we report simulation studies of a different perspective of networks, namely, the spectra associated with this ensemble of adjacency matrices {aij } . As a baseline, we first consider the spectra associated with a simple random (Erdős-Rényi) ensemble of bipartite graphs, where simulation results can be understood analytically. Work supported by the NSF through Grant DMR-1507371.

Honeycomb structural composite polymer network of gelatin and functional cellulose ester for controlled release of omeprazole.

PubMed

Zhuang, Chen; Shi, Chengmei; Tao, Furong; Cui, Yuezhi

2017-12-01

The functionalized cellulose ester MCN was firstly synthesized and used to cross-link gelatin by amidation between -NH 2 in gelatin and active ester groups in MCN to form a composite polymer network Gel-MCN, which was confirmed by Van Slyke method, FTIR, XRD and TGA-DTG spectra. The model drug omeprazole was loaded in Gel-MCN composites mainly by electrostatic interaction and hydrogen bonds, which were certified by FTIR, XRD and TGA-DSC. Thermal stability, anti-biodegradability, mechanical property and surface hydrophobicity of the composites with different cross-linking extents and drug loading were systematically investigated. SEM images demonstrated the honeycomb structural cells of cross-linked gelatin networks and this ensured drug entrapment. The drug release mechanism was dominated by a combined effect of diffusion and degradation, and the release rate decreased with cross-linking degree increased. The developed drug delivery system had profound significance in improving pesticide effect and bioavailability of drugs. Copyright © 2017. Published by Elsevier B.V.

Dreaming of Atmospheres

NASA Astrophysics Data System (ADS)

Waldmann, I. P.

2016-04-01

Here, we introduce the RobERt (Robotic Exoplanet Recognition) algorithm for the classification of exoplanetary emission spectra. Spectral retrieval of exoplanetary atmospheres frequently requires the preselection of molecular/atomic opacities to be defined by the user. In the era of open-source, automated, and self-sufficient retrieval algorithms, manual input should be avoided. User dependent input could, in worst-case scenarios, lead to incomplete models and biases in the retrieval. The RobERt algorithm is based on deep-belief neural (DBN) networks trained to accurately recognize molecular signatures for a wide range of planets, atmospheric thermal profiles, and compositions. Reconstructions of the learned features, also referred to as the “dreams” of the network, indicate good convergence and an accurate representation of molecular features in the DBN. Using these deep neural networks, we work toward retrieval algorithms that themselves understand the nature of the observed spectra, are able to learn from current and past data, and make sensible qualitative preselections of atmospheric opacities to be used for the quantitative stage of the retrieval process.

Wet deposition monitoring and modelling in New Brunswick — An area dominated by wet deposition due to long-range transport

NASA Astrophysics Data System (ADS)

Davis, Claude S.

Two wet deposition monitoring networks, the Coleson Cove Precipitation Monitoring Network (CCPMN) (12 stations) located in the Coleson Cove-Saint John area of south New Brunswick, and the Expanded New Brunswick Precipitation Monitoring Network (ENBPMN) (6 stations) covering the remainder of the province, were established in May 1988. The monitoring networks and a complementary modelling study were implemented to assess the relative contributions of local and distant sources to wet deposition in New Brunswick. Quality assurance/quality control activities for the networks included independent external audits, collocated samplers at one site and comparisons of weekly measurements at the ENBPMN sampler and the Canadian Air and Precipitation Monitoring Network (CAPMoN) sampler which makes daily measurements. The intercomparisons provided reassurance that the networks provided high quality data. Analysis of 2 years (June 1988-May 1990) data from the networks included routine statistical analyses for acid rain chemistry as well as analysis of 1 year of daily back trajectory data from Harcourt, New Brunswick. Three-day back trajectories determined at 12-h intervals from Harcourt on days with precipitatio showed that air masses originate mainly from regions in Quebec, Ontario and northeast U.S.A. which are known to have high sulphur oxide emissions. Some 18 trajectories were associated with 50% of the wet sulphate deposition and over 200 trajectories with 75% of the deposition in the 1-year period ending 31 May 1989. The MESOPUFF model, applied to an 800 km by 800 km domain that included the entire province of New Brunswick, was used to make predictions of wet sulphate and nitrate deposition at each of the wet deposition monitoring stations for a 2-year period, 1 June 1988-31 May 1990. Model predictions averaged over all receptors due to all sources in the model domain accounted for 7-25% of the measured seasonal average wet sulphate deposition and less than 3% of the measured wet nitrate deposition at all monitoring stations. Wet deposition in New Brunswick is thus dominated by distant sources through long-range transport. The model estimated that the oil-fired Coleson Cove thermal generating station contributed between 7% and 16% to the seasonal wet sulphur deposition and less than 3% of the seasonal wet nitrogen deposition at monitoring stations in the Coleson Cove-Saint John area. The estimates for wet nitrogen deposition are limited by the NO χ emissions information which is considered less reliable than SO 2 emissions information.

Thermal decay of rhodopsin: role of hydrogen bonds in thermal isomerization of 11-cis retinal in the binding site and hydrolysis of protonated Schiff base.

PubMed

Liu, Jian; Liu, Monica Yun; Nguyen, Jennifer B; Bhagat, Aditi; Mooney, Victoria; Yan, Elsa C Y

2009-07-01

Although thermal stability of the G protein-coupled receptor rhodopsin is directly related to its extremely low dark noise level and has recently generated considerable interest, the chemistry behind the thermal decay process of rhodopsin has remained unclear. Using UV-vis spectroscopy and HPLC analysis, we have demonstrated that the thermal decay of rhodopsin involves both hydrolysis of the protonated Schiff base and thermal isomerization of 11-cis to all-trans retinal. Examining the unfolding of rhodopsin by circular dichroism spectroscopy and measuring the rate of thermal isomerization of 11-cis retinal in solution, we conclude that the observed thermal isomerization of 11-cis to all-trans retinal happens when 11-cis retinal is in the binding pocket of rhodopsin. Furthermore, we demonstrate that solvent deuterium isotope effects are involved in the thermal decay process by decreasing the rates of thermal isomerization and hydrolysis, suggesting that the rate-determining step of these processes involves breaking hydrogen bonds. These results provide insight into understanding the critical role of an extensive hydrogen-bonding network on stabilizing the inactive state of rhodopsin and contribute to our current understanding of the low dark noise level of rhodopsin, which enables this specialized protein to function as an extremely sensitive biological light detector. Because similar hydrogen-bonding networks have also been suggested by structural analysis of two other GPCRs, beta1 and beta2 adrenergic receptors, our results could reveal a general role of hydrogen bonds in facilitating GPCR function.

Energy efficiency in waste-to-energy and its relevance with regard to climate control.

PubMed

Ragossnig, Arne M; Wartha, Christian; Kirchner, Andreas

2008-02-01

This article focuses on systematically highlighting the ways to optimize waste-to-energy plants in terms of their energy efficiency as an indicator of the positive effect with regard to climate control. Potentials for increasing energy efficiency are identified and grouped into categories. The measures mentioned are illustrated by real-world examples. As an example, district cooling as a means for increasing energy efficiency in the district heating network of Vienna is described. Furthermore a scenario analysis shows the relevance of energy efficiency in waste management scenarios based on thermal treatment of waste with regard to climate control. The description is based on a model that comprises all relevant processes from the collection and transportation up to the thermal treatment of waste. The model has been applied for household-like commercial waste. The alternatives compared are a combined heat and power incinerator, which is being introduced in many places as an industrial utility boiler or in metropolitan areas where there is a demand for district heating and a classical municipal solid waste incinerator producing solely electrical power. For comparative purposes a direct landfilling scenario has been included in the scenario analysis. It is shown that the energy efficiency of thermal treatment facilities is crucial to the quantity of greenhouse gases emitted.

A Neural Network Based Intelligent Predictive Sensor for Cloudiness, Solar Radiation and Air Temperature

PubMed Central

Ferreira, Pedro M.; Gomes, João M.; Martins, Igor A. C.; Ruano, António E.

2012-01-01

Accurate measurements of global solar radiation and atmospheric temperature, as well as the availability of the predictions of their evolution over time, are important for different areas of applications, such as agriculture, renewable energy and energy management, or thermal comfort in buildings. For this reason, an intelligent, light-weight and portable sensor was developed, using artificial neural network models as the time-series predictor mechanisms. These have been identified with the aid of a procedure based on the multi-objective genetic algorithm. As cloudiness is the most significant factor affecting the solar radiation reaching a particular location on the Earth surface, it has great impact on the performance of predictive solar radiation models for that location. This work also represents one step towards the improvement of such models by using ground-to-sky hemispherical colour digital images as a means to estimate cloudiness by the fraction of visible sky corresponding to clouds and to clear sky. The implementation of predictive models in the prototype has been validated and the system is able to function reliably, providing measurements and four-hour forecasts of cloudiness, solar radiation and air temperature. PMID:23202230

Atomistic modeling of thermomechanical properties of SWNT/Epoxy nanocomposites

NASA Astrophysics Data System (ADS)

Fasanella, Nicholas; Sundararaghavan, Veera

2015-09-01

Molecular dynamics simulations are performed to compute thermomechanical properties of cured epoxy resins reinforced with pristine and covalently functionalized carbon nanotubes. A DGEBA-DDS epoxy network was built using the ‘dendrimer’ growth approach where 75% of available epoxy sites were cross-linked. The epoxy model is verified through comparisons to experiments, and simulations are performed on nanotube reinforced cross-linked epoxy matrix using the CVFF force field in LAMMPS. Full stiffness matrices and linear coefficient of thermal expansion vectors are obtained for the nanocomposite. Large increases in stiffness and large decreases in thermal expansion were seen along the direction of the nanotube for both nanocomposite systems when compared to neat epoxy. The direction transverse to nanotube saw a 40% increase in stiffness due to covalent functionalization over neat epoxy at 1 K whereas the pristine nanotube system only saw a 7% increase due to van der Waals effects. The functionalized SWNT/epoxy nanocomposite showed an additional 42% decrease in thermal expansion along the nanotube direction when compared to the pristine SWNT/epoxy nanocomposite. The stiffness matrices are rotated over every possible orientation to simulate the effects of an isotropic system of randomly oriented nanotubes in the epoxy. The randomly oriented covalently functionalized SWNT/Epoxy nanocomposites showed substantial improvements over the plain epoxy in terms of higher stiffness (200% increase) and lower thermal expansion (32% reduction). Through MD simulations, we develop means to build simulation cells, perform annealing to reach correct densities, compute thermomechanical properties and compare with experiments.

PREDICTIVE MODELING OF ACOUSTIC SIGNALS FROM THERMOACOUSTIC POWER SENSORS (TAPS)

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

Dumm, Christopher M.; Vipperman, Jeffrey S.

2016-06-30

Thermoacoustic Power Sensor (TAPS) technology offers the potential for self-powered, wireless measurement of nuclear reactor core operating conditions. TAPS are based on thermoacoustic engines, which harness thermal energy from fission reactions to generate acoustic waves by virtue of gas motion through a porous stack of thermally nonconductive material. TAPS can be placed in the core, where they generate acoustic waves whose frequency and amplitude are proportional to the local temperature and radiation flux, respectively. TAPS acoustic signals are not measured directly at the TAPS; rather, they propagate wirelessly from an individual TAPS through the reactor, and ultimately to a low-powermore » receiver network on the vessel’s exterior. In order to rely on TAPS as primary instrumentation, reactor-specific models which account for geometric/acoustic complexities in the signal propagation environment must be used to predict the amplitude and frequency of TAPS signals at receiver locations. The reactor state may then be derived by comparing receiver signals to the reference levels established by predictive modeling. In this paper, we develop and experimentally benchmark a methodology for predictive modeling of the signals generated by a TAPS system, with the intent of subsequently extending these efforts to modeling of TAPS in a liquid sodium environmen« less

Static Chemistry in Disks or Clouds

NASA Astrophysics Data System (ADS)

Semenov, D.; Wiebe, D.

2006-11-01

This FORTRAN77 code can be used to model static, time-dependent chemistry in ISM and circumstellar disks. Current version is based on the OSU'06 gas-grain astrochemical network with all updates to the reaction rates, and includes surface chemistry from Hasegawa & Herbst (1993) and Hasegawa, Herbst, and Leung (1992). Surface chemistry can be modeled either with the standard rate equation approach or modified rate equation approach (useful in disks). Gas-grain interactions include sticking of neutral molecules to grains, dissociative recombination of ions on grains as well as thermal, UV, X-ray, and CRP-induced desorption of frozen species. An advanced X-ray chemistry and 3 grain sizes with power-law size distribution are also included. An deuterium extension to this chemical model is available.

Multiscale Modeling of Carbon Nanotube-Epoxy Nanocomposites

NASA Astrophysics Data System (ADS)

Fasanella, Nicholas A.

Epoxy-composites are widely used in the aerospace industry. In order to improve upon stiffness and thermal conductivity; carbon nanotube additives to epoxies are being explored. This dissertation presents multiscale modeling techniques to study the engineering properties of single walled carbon nanotube (SWNT)-epoxy nanocomposites, consisting of pristine and covalently functionalized systems. Using Molecular Dynamics (MD), thermomechanical properties were calculated for a representative polymer unit cell. Finite Element (FE) and orientation distribution function (ODF) based methods were used in a multiscale framework to obtain macroscale properties. An epoxy network was built using the dendrimer growth approach. The epoxy model was verified by matching the experimental glass transition temperature, density, and dilatation. MD, via the constant valence force field (CVFF), was used to explore the mechanical and dilatometric effects of adding pristine and functionalized SWNTs to epoxy. Full stiffness matrices and linear coefficient of thermal expansion vectors were obtained. The Green-Kubo method was used to investigate the thermal conductivity as a function of temperature for the various nanocomposites. Inefficient phonon transport at the ends of nanotubes is an important factor in the thermal conductivity of the nanocomposites, and for this reason discontinuous nanotubes were modeled in addition to long nanotubes. To obtain continuum-scale elastic properties from the MD data, multiscale modeling was considered to give better control over the volume fraction of nanotubes, and investigate the effects of nanotube alignment. Two methods were considered; an FE based method, and an ODF based method. The FE method probabilistically assigned elastic properties of elements from the MD lattice results based on the desired volume fraction and alignment of the nanotubes. For the ODF method, a distribution function was generated based on the desired amount of nanotube alignment; and the stiffness matrix was calculated. A rule of mixture approach was implemented in the ODF model to vary the SWNT volume fraction. Both the ODF and FE models are compared and contrasted. ODF analysis is significantly faster for nanocomposites and is a novel contribution in this thesis. Multiscale modeling allows for the effects of nanofillers in epoxy systems to be characterized without having to run costly experiments.

Mechanism for Tuning the Hydrophobicity of Microfibrillated Cellulose Films by Controlled Thermal Release of Encapsulated Wax

PubMed Central

Rastogi, Vibhore Kumar; Stanssens, Dirk; Samyn, Pieter

2014-01-01

Although films of microfibrillated cellulose (MFC) have good oxygen barrier properties due to its fine network structure, properties strongly deteriorate after absorption of water. In this work, a new approach has been followed for actively tuning the water resistance of a MFC fiber network by the inclusion of dispersed organic nanoparticles with encapsulated plant wax. The modified pulp suspensions have been casted into films and were subsequently cured at 40 to 220 °C. As such, static water contact angles can be specifically tuned from 120 to 150° by selection of the curing temperature in relation with the intrinsic transition temperatures of the modified pulp, as determined by thermal analysis. The appearance of encapsulated wax after curing was followed by a combination of morphological analysis, infrared spectroscopy and Raman mapping, showing balanced mechanisms of progressive release and migration of wax into the fiber network controlling the surface properties and water contact angles. Finally, the appearance of nanoparticles covered with a thin wax layer after complete thermal release provides highest hydrophobicity. PMID:28788241

Monitoring of Thermal Protection Systems and MMOD using Robust Self-Organizing Optical Fiber Sensing Networks

NASA Technical Reports Server (NTRS)

Richards, Lance

2014-01-01

The general aim of this work is to develop and demonstrate a prototype structural health monitoring system for thermal protection systems that incorporates piezoelectric acoustic emission (AE) sensors to detect the occurrence and location of damaging impacts, such as those from Micrometeoroid Orbital Debris (MMOD). The approach uses an optical fiber Bragg grating (FBG) sensor network to evaluate the effect of detected damage on the thermal conductivity of the TPS material. Following detection of an impact, the TPS would be exposed to a heat source, possibly the sun, and the temperature distribution on the inner surface in the vicinity of the impact measured by the FBG network. A similar procedure could also be carried out as a screening test immediately prior to re-entry. The implications of any detected anomalies in the measured temperature distribution will be evaluated for their significance in relation to the performance of the TPS during reentry. Such a robust TPS health monitoring system would ensure overall crew safety throughout the mission, especially during reentry.

Quantum State Transfer via Noisy Photonic and Phononic Waveguides

NASA Astrophysics Data System (ADS)

Vermersch, B.; Guimond, P.-O.; Pichler, H.; Zoller, P.

2017-03-01

We describe a quantum state transfer protocol, where a quantum state of photons stored in a first cavity can be faithfully transferred to a second distant cavity via an infinite 1D waveguide, while being immune to arbitrary noise (e.g., thermal noise) injected into the waveguide. We extend the model and protocol to a cavity QED setup, where atomic ensembles, or single atoms representing quantum memory, are coupled to a cavity mode. We present a detailed study of sensitivity to imperfections, and apply a quantum error correction protocol to account for random losses (or additions) of photons in the waveguide. Our numerical analysis is enabled by matrix product state techniques to simulate the complete quantum circuit, which we generalize to include thermal input fields. Our discussion applies both to photonic and phononic quantum networks.

A comparative study on improved Arrhenius-type and artificial neural network models to predict high-temperature flow behaviors in 20MnNiMo alloy.

PubMed

Quan, Guo-zheng; Yu, Chun-tang; Liu, Ying-ying; Xia, Yu-feng

2014-01-01

The stress-strain data of 20MnNiMo alloy were collected from a series of hot compressions on Gleeble-1500 thermal-mechanical simulator in the temperature range of 1173 ∼ 1473 K and strain rate range of 0.01 ∼ 10 s(-1). Based on the experimental data, the improved Arrhenius-type constitutive model and the artificial neural network (ANN) model were established to predict the high temperature flow stress of as-cast 20MnNiMo alloy. The accuracy and reliability of the improved Arrhenius-type model and the trained ANN model were further evaluated in terms of the correlation coefficient (R), the average absolute relative error (AARE), and the relative error (η). For the former, R and AARE were found to be 0.9954 and 5.26%, respectively, while, for the latter, 0.9997 and 1.02%, respectively. The relative errors (η) of the improved Arrhenius-type model and the ANN model were, respectively, in the range of -39.99% ∼ 35.05% and -3.77% ∼ 16.74%. As for the former, only 16.3% of the test data set possesses η-values within ± 1%, while, as for the latter, more than 79% possesses. The results indicate that the ANN model presents a higher predictable ability than the improved Arrhenius-type constitutive model.

Irrigation system management assisted by thermal imagery and spatial statistics

USDA-ARS?s Scientific Manuscript database

Thermal imaging has the potential to assist with many aspects of irrigation management including scheduling water application, detecting leaky irrigation canals, and gauging the overall effectiveness of water distribution networks used in furrow irrigation. Many challenges exist for the use of therm...

Conditional repair by locally switching the thermal healing capability of dynamic covalent polymers with light

PubMed Central

Fuhrmann, Anne; Göstl, Robert; Wendt, Robert; Kötteritzsch, Julia; Hager, Martin D.; Schubert, Ulrich S.; Brademann-Jock, Kerstin; Thünemann, Andreas F.; Nöchel, Ulrich; Behl, Marc; Hecht, Stefan

2016-01-01

Healable materials could play an important role in reducing the environmental footprint of our modern technological society through extending the life cycles of consumer products and constructions. However, as most healing processes are carried out by heat alone, the ability to heal damage generally kills the parent material's thermal and mechanical properties. Here we present a dynamic covalent polymer network whose thermal healing ability can be switched ‘on' and ‘off' on demand by light, thereby providing local control over repair while retaining the advantageous macroscopic properties of static polymer networks. We employ a photoswitchable furan-based crosslinker, which reacts with short and mobile maleimide-substituted poly(lauryl methacrylate) chains forming strong covalent bonds while simultaneously allowing the reversible, spatiotemporally resolved control over thermally induced de- and re-crosslinking. We reason that our system can be adapted to more complex materials and has the potential to impact applications in responsive coatings, photolithography and microfabrication. PMID:27941924

Dual path mechanism in the thermal reduction of graphene oxide.

PubMed

Larciprete, Rosanna; Fabris, Stefano; Sun, Tao; Lacovig, Paolo; Baraldi, Alessandro; Lizzit, Silvano

2011-11-02

Graphene is easily produced by thermally reducing graphene oxide. However, defect formation in the C network during deoxygenation compromises the charge carrier mobility in the reduced material. Understanding the mechanisms of the thermal reactions is essential for defining alternative routes able to limit the density of defects generated by carbon evolution. Here, we identify a dual path mechanism in the thermal reduction of graphene oxide driven by the oxygen coverage: at low surface density, the O atoms adsorbed as epoxy groups evolve as O(2) leaving the C network unmodified. At higher coverage, the formation of other O-containing species opens competing reaction channels, which consume the C backbone. We combined spectroscopic tools and ab initio calculations to probe the species residing on the surface and those released in the gas phase during heating and to identify reaction pathways and rate-limiting steps. Our results illuminate the current puzzling scenario of the low temperature gasification of graphene oxide.

Conditional repair by locally switching the thermal healing capability of dynamic covalent polymers with light

NASA Astrophysics Data System (ADS)

Fuhrmann, Anne; Göstl, Robert; Wendt, Robert; Kötteritzsch, Julia; Hager, Martin D.; Schubert, Ulrich S.; Brademann-Jock, Kerstin; Thünemann, Andreas F.; Nöchel, Ulrich; Behl, Marc; Hecht, Stefan

2016-12-01

Healable materials could play an important role in reducing the environmental footprint of our modern technological society through extending the life cycles of consumer products and constructions. However, as most healing processes are carried out by heat alone, the ability to heal damage generally kills the parent material's thermal and mechanical properties. Here we present a dynamic covalent polymer network whose thermal healing ability can be switched `on' and `off' on demand by light, thereby providing local control over repair while retaining the advantageous macroscopic properties of static polymer networks. We employ a photoswitchable furan-based crosslinker, which reacts with short and mobile maleimide-substituted poly(lauryl methacrylate) chains forming strong covalent bonds while simultaneously allowing the reversible, spatiotemporally resolved control over thermally induced de- and re-crosslinking. We reason that our system can be adapted to more complex materials and has the potential to impact applications in responsive coatings, photolithography and microfabrication.

Development of concepts for the management of shallow geothermal resources in urban areas - Experience gained from the Basel and Zaragoza case studies

NASA Astrophysics Data System (ADS)

García-Gil, Alejandro; Epting, Jannis; Mueller, Matthias H.; Huggenberger, Peter; Vázquez-Suñé, Enric

2015-04-01

In urban areas the shallow subsurface often is used as a heat resource (shallow geothermal energy), i.e. for the installation and operation of a broad variety of geothermal systems. Increasingly, groundwater is used as a low-cost heat sink, e.g. for building acclimatization. Together with other shallow geothermal exploitation systems significantly increased groundwater temperatures have been observed in many urban areas (urban heat island effect). The experience obtained from two selected case study cities in Basel (CH) and Zaragoza (ES) has allowed developing concepts and methods for the management of thermal resources in urban areas. Both case study cities already have a comprehensive monitoring network operating (hydraulics and temperature) as well as calibrated high-resolution numerical groundwater flow and heat-transport models. The existing datasets and models have allowed to compile and compare the different hydraulic and thermal boundary conditions for both groundwater bodies, including: (1) River boundaries (River Rhine and Ebro), (2) Regional hydraulic and thermal settings, (3) Interaction with the atmosphere under consideration of urbanization and (4) Anthropogenic quantitative and thermal groundwater use. The potential natural states of the considered groundwater bodies also have been investigated for different urban settings and varying processes concerning groundwater flow and thermal regimes. Moreover, concepts for the management of thermal resources in urban areas and the transferability of the applied methods to other urban areas are discussed. The methods used provide an appropriate selection of parameters (spatiotemporal resolution) that have to be measured for representative interpretations of groundwater flow and thermal regimes of specific groundwater bodies. From the experience acquired from the case studies it is shown that understanding the variable influences of the specific geological and hydrogeological as well as hydraulic and thermal boundary conditions in urban settings is crucial. It also could be shown that good quality data are necessary to appropriately define and investigate thermal boundary conditions and the temperature development in urban systems. Groundwater temperatures in both investigated groundwater bodies are already over-heated and essentially impede further thermal groundwater use for cooling purposes. Current legislation approaches are not suitable to evaluate new concessions for thermal exploitation. Therefore, novel approaches for the assessment of new concessions which take into account the complex interaction of natural boundaries as well as existing shallow geothermal systems have to be developed.

Modeling of coupled heat transfer and reactive transport processesin porous media: Application to seepage studies at Yucca Mountain, Nevada

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

Mukhopadhyay, Sumit; Sonnenthal, Eric L.; Spycher, Nicolas

When hot radioactive waste is placed in subsurface tunnels, a series of complex changes occurs in the surrounding medium. The water in the pore space of the medium undergoes vaporization and boiling. Subsequently, vapor migrates out of the matrix pore space, moving away from the tunnel through the permeable fracture network. This migration is propelled by buoyancy, by the increased vapor pressure caused by heating and boiling, and through local convection. In cooler regions, the vapor condenses on fracture walls, where it drains through the fracture network. Slow imbibition of water thereafter leads to gradual rewetting of the rock matrix.more » These thermal and hydrological processes also bring about chemical changes in the medium. Amorphous silica precipitates from boiling and evaporation, and calcite from heating and CO2 volatilization. The precipitation of amorphous silica, and to a much lesser extent calcite, results in long-term permeability reduction. Evaporative concentration also results in the precipitation of gypsum (or anhydrite), halite, fluorite and other salts. These evaporative minerals eventually redissolve after the boiling period is over, however, their precipitation results in a significant temporary decrease in permeability. Reduction of permeability is also associated with changes in fracture capillary characteristics. In short, the coupled thermal-hydrological-chemical (THC) processes dynamically alter the hydrological properties of the rock. A model based on the TOUGHREACT reactive transport software is presented here to investigate the impact of THC processes on flow near an emplacement tunnel at Yucca Mountain, Nevada. We show how transient changes in hydrological properties caused by THC processes often lead to local flow channeling and saturation increases above the tunnel. For models that include only permeability changes to fractures, such local flow channeling may lead to seepage relative to models where THC effects are ignored. However, coupled THC seepage models that include both permeability and capillary changes to fractures may not show this additional seepage.« less

Modeling of coupled heat transfer and reactive transport processesin porous media: Application to seepage studies at Yucca Mountain, Nevada

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

Mukhopadhyay, S.; Sonnenthal, E.L.; Spycher, N.

When hot radioactive waste is placed in subsurface tunnels, a series of complex changes occurs in the surrounding medium. The water in the pore space of the medium undergoes vaporization and boiling. Subsequently, vapor migrates out of the matrix pore space, moving away from the tunnel through the permeable fracture network. This migration is propelled by buoyancy, by the increased vapor pressure caused by heating and boiling, and through local convection. In cooler regions, the vapor condenses on fracture walls, where it drains through the fracture network. Slow imbibition of water thereafter leads to gradual rewetting of the rock matrix.more » These thermal and hydrological processes also bring about chemical changes in the medium. Amorphous silica precipitates from boiling and evaporation, and calcite from heating and CO{sub 2} volatilization. The precipitation of amorphous silica, and to a much lesser extent calcite, results in long-term permeability reduction. Evaporative concentration also results in the precipitation of gypsum (or anhydrite), halite, fluorite and other salts. These evaporative minerals eventually redissolve after the boiling period is over, however, their precipitation results in a significant temporary decrease in permeability. Reduction of permeability is also associated with changes in fracture capillary characteristics. In short, the coupled thermal-hydrological-chemical (THC) processes dynamically alter the hydrological properties of the rock. A model based on the TOUGHREACT reactive transport software is presented here to investigate the impact of THC processes on flow near an emplacement tunnel at Yucca Mountain, Nevada. We show how transient changes in hydrological properties caused by THC processes often lead to local flow channeling and saturation increases above the tunnel. For models that include only permeability changes to fractures, such local flow channeling may lead to seepage relative to models where THC effects are ignored. However, coupled THC seepage models that include both permeability and capillary changes to fractures may not show this additional seepage.« less

Experimental study on occupant's thermal responses under the non-uniform conditions in vehicle cabin during the heating period

NASA Astrophysics Data System (ADS)

Zhang, Wencan; Chen, Jiqing; Lan, Fengchong

2014-03-01

The existing investigations on thermal comfort mostly focus on the thermal environment conditions, especially of the air-flow field and the temperature distributions in vehicle cabin. Less attention appears to direct to the thermal comfort or thermal sensation of occupants, even to the relationship between thermal conditions and thermal sensation. In this paper, a series of experiments were designed and conducted for understanding the non-uniform conditions and the occupant's thermal responses in vehicle cabin during the heating period. To accurately assess the transient temperature distribution in cabin in common daily condition, the air temperature at a number of positions is measured in a full size vehicle cabin under natural winter environment in South China by using a discrete thermocouples network. The occupant body is divided into nine segments, the skin temperature at each segment and the occupant's local thermal sensation at the head, body, upper limb and lower limb are monitored continuously. The skin temperature is observed by using a discrete thermocouples network, and the local thermal sensation is evaluated by using a seven-point thermal comfort survey questionnaire proposed by American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc(ASHRAE) Standard. The relationship between the skin temperature and the thermal sensation is discussed and regressed by statistics method. The results show that the interior air temperature is highly non-uniform over the vehicle cabin. The locations where the occupants sit have a significant effect on the occupant's thermal responses, including the skin temperature and the thermal sensation. The skin temperature and thermal sensation are quite different between body segments due to the effect of non-uniform conditions, clothing resistance, and the human thermal regulating system. A quantitative relationship between the thermal sensation and the skin temperature at each body segment of occupant in real life traffic is presented. The investigation result indicates that the skin temperature is a robust index to evaluate the thermal sensation. Applying the skin temperature to designing and controlling parameters of the heating, ventilation and air conditioning(HVAC) system may benefit the thermal comfort and reducing energy consumption.

Modeling and observational occurrences of near-surface drainage in Utopia Planitia, Mars

NASA Astrophysics Data System (ADS)

Costard, F.; Sejourne, A.; Kargel, J.; Godin, E.

2016-12-01

During the past 15 years, evidence for an ice-rich planet Mars has rapidly mounted, become increasingly varied in terms of types of deposits and types of observational data, and has become more widespread across the surface. The mid-latitudes of Mars, especially Utopia Planitia, show many types of interesting landforms similar to those in periglacial landscapes on Earth that suggest the presence of ice-rich permafrost. These include thermal contraction polygonal networks, scalloped terrains similar to thermokarst pits, debris flows, small mounds like pingos and rock glaciers. Here, we address questions concerning the influence of meltwater in the Utopia Planitia (UP) landscape using analogs of near-surface melting and drainage along ice-wedge troughs on Bylot Island, northern Canada. In Utopia Planitia, based on the identification of sinuous channel-like pits within polygonal networks, we suggest that episodic underground melting was possible under severe periglacial climate conditions. In UP, the collapse pattern and morphology of unconnected sinuous elongated pits that follow the polygon crack are similar to underground melting in Bylot Island (Nunavut, Canada). Based on this terrestrial analogue, we develop a thermal model that consists of a thick insulating dusty layer over ice-saturated dust during a period of slight climatic warming relative to today's climate. In the model, the melting point is reached at depths down to 150 m. We suggest that small-scale melting could have occurred below ground within ground-ice polygonal fractures and pooled in underground cavities. Then the water may have been released episodically causing mechanical erosion as well as undermining and collapse. After melting, the dry surface dusty layer might have been blown away, thus exposing the degraded terrain of the substrate layer.

Prediction of the mass gain during high temperature oxidation of aluminized nanostructured nickel using adaptive neuro-fuzzy inference system

NASA Astrophysics Data System (ADS)

Hayati, M.; Rashidi, A. M.; Rezaei, A.

2012-10-01

In this paper, the applicability of ANFIS as an accurate model for the prediction of the mass gain during high temperature oxidation using experimental data obtained for aluminized nanostructured (NS) nickel is presented. For developing the model, exposure time and temperature are taken as input and the mass gain as output. A hybrid learning algorithm consists of back-propagation and least-squares estimation is used for training the network. We have compared the proposed ANFIS model with experimental data. The predicted data are found to be in good agreement with the experimental data with mean relative error less than 1.1%. Therefore, we can use ANFIS model to predict the performances of thermal systems in engineering applications, such as modeling the mass gain for NS materials.

Thermal Diffusion Fractionation of Cr and V Isotope in Silicate Melt

NASA Astrophysics Data System (ADS)

Lin, X.; Lundstrom, C.

2017-12-01

Earth's mantle is isotopically heavy relative to chondrites for V, Cr and some other siderophile elements. A possible solution is that isotopic fractionation by thermal diffusion occurs in a thermal boundary layer between solid mantle and an underlying basal magma ocean (BMO:Labrosse et al.,2007). If so, isotopically light composition might partition into the core, resulting in a complimentary isotopically heavy solid mantle. To verify how much fractionation could happen in this process, piston cylinder experiment were conducted to investigate the fractionation of Cr and V isotope ratios in partially molten silicate under an imposed temperature gradient from 1650 °C to 1350 °C at 1 GPa for 10 to 50 hours to reach a steady state isotopic profile. The temperature profile for experiments was determined by the spinel-growth method at the same pressure and temperature. Experimental runs result in 100% glass at the hot end progressing to nearly 100 % olivine at the cold end. Major and minor element concentrations of run products show systematic changes with temperature. Glass MgO contents increase and Al2O3 and CaO contents decrease by several weight percent as temperature increases across the charge. These are well modeled using IRIDIUM (Boudreau 2003) to simulate the experiments. Isotopic composition measurements of Cr and V at different temperatures are in progress, providing the first determinations of thermal diffusion isotopic sensitivity, Ω (permil isotopic fractionation per temperature offset per mass unit) for these elements. These results will be compared with previously determined Ω for network formers and modifiers and used in a BMO-based thermal diffusion model for formation of Earth's isotopically heavy mantle.

Methanol ice co-desorption as a mechanism to explain cold methanol in the gas-phase

NASA Astrophysics Data System (ADS)

Ligterink, N. F. W.; Walsh, C.; Bhuin, R. G.; Vissapragada, S.; van Scheltinga, J. Terwisscha; Linnartz, H.

2018-05-01

Context. Methanol is formed via surface reactions on icy dust grains. Methanol is also detected in the gas-phase at temperatures below its thermal desorption temperature and at levels higher than can be explained by pure gas-phase chemistry. The process that controls the transition from solid state to gas-phase methanol in cold environments is not understood. Aims: The goal of this work is to investigate whether thermal CO desorption provides an indirect pathway for methanol to co-desorb at low temperatures. Methods: Mixed CH3OH:CO/CH4 ices were heated under ultra-high vacuum conditions and ice contents are traced using RAIRS (reflection absorption IR spectroscopy), while desorbing species were detected mass spectrometrically. An updated gas-grain chemical network was used to test the impact of the results of these experiments. The physical model used is applicable for TW Hya, a protoplanetary disk in which cold gas-phase methanol has recently been detected. Results: Methanol release together with thermal CO desorption is found to be an ineffective process in the experiments, resulting in an upper limit of ≤ 7.3 × 10-7 CH3OH molecules per CO molecule over all ice mixtures considered. Chemical modelling based on the upper limits shows that co-desorption rates as low as 10-6 CH3OH molecules per CO molecule are high enough to release substantial amounts of methanol to the gas-phase at and around the location of the CO thermal desorption front in a protoplanetary disk. The impact of thermal co-desorption of CH3OH with CO as a grain-gas bridge mechanism is compared with that of UV induced photodesorption and chemisorption.

Method for the thermal characterization, visualization, and integrity evaluation of conducting material samples or complex structures

DOEpatents

Ortiz, Marcos G.

1992-01-01

A method for modeling a conducting material sample or structure (herein called a system) as at least two regions which comprise an electrical network of resistances, for measuring electric resistance between at least two selected pairs of external leads attached to the surface of the system, wherein at least one external lead is attached to the surface of each of the regions, and, using basic circuit theory, for translating measured resistances into temperatures or thermophysical properties in corresponding regions of the system.

Method for the thermal characterization, visualization, and integrity evaluation of conducting material samples or complex structures

DOEpatents

Ortiz, M.G.

1992-11-24

Disclosed is a method for modeling a conducting material sample or structure (herein called a system) as at least two regions which comprise an electrical network of resistances, for measuring electric resistance between at least two selected pairs of external leads attached to the surface of the system, wherein at least one external lead is attached to the surface of each of the regions, and, using basic circuit theory, for translating measured resistances into temperatures or thermophysical properties in corresponding regions of the system. 16 figs.

Coupling Field Theory with Mesoscopic Dynamical Simulations of Multicomponent Lipid Bilayers

PubMed Central

McWhirter, J. Liam; Ayton, Gary; Voth, Gregory A.

2004-01-01

A method for simulating a two-component lipid bilayer membrane in the mesoscopic regime is presented. The membrane is modeled as an elastic network of bonded points; the spring constants of these bonds are parameterized by the microscopic bulk modulus estimated from earlier atomistic nonequilibrium molecular dynamics simulations for several bilayer mixtures of DMPC and cholesterol. The modulus depends on the composition of a point in the elastic membrane model. The dynamics of the composition field is governed by the Cahn-Hilliard equation where a free energy functional models the coupling between the composition and curvature fields. The strength of the bonds in the elastic network are then modulated noting local changes in the composition and using a fit to the nonequilibrium molecular dynamics simulation data. Estimates for the magnitude and sign of the coupling parameter in the free energy model are made treating the bending modulus as a function of composition. A procedure for assigning the remaining parameters in the free energy model is also outlined. It is found that the square of the mean curvature averaged over the entire simulation box is enhanced if the strength of the bonds in the elastic network are modulated in response to local changes in the composition field. We suggest that this simulation method could also be used to determine if phase coexistence affects the stress response of the membrane to uniform dilations in area. This response, measured in the mesoscopic regime, is already known to be conditioned or renormalized by thermal undulations. PMID:15347594

Lower-mantle plume beneath the Yellowstone hotspot revealed by core waves

NASA Astrophysics Data System (ADS)

Nelson, Peter L.; Grand, Stephen P.

2018-04-01

The Yellowstone hotspot, located in North America, is an intraplate source of magmatism the cause of which is hotly debated. Some argue that a deep mantle plume sourced at the base of the mantle supplies the heat beneath Yellowstone, whereas others claim shallower subduction or lithospheric-related processes can explain the anomalous magmatism. Here we present a shear wave tomography model for the deep mantle beneath the western United States that was made using the travel times of core waves recorded by the dense USArray seismic network. The model reveals a single narrow, cylindrically shaped slow anomaly, approximately 350 km in diameter that we interpret as a whole-mantle plume. The anomaly is tilted to the northeast and extends from the core-mantle boundary to the surficial position of the Yellowstone hotspot. The structure gradually decreases in strength from the deepest mantle towards the surface and if it is purely a thermal anomaly this implies an initial excess temperature of 650 to 850 °C. Our results strongly support a deep origin for the Yellowstone hotspot, and also provide evidence for the existence of thin thermal mantle plumes that are currently beyond the resolution of global tomography models.

Full-scale simulation and reduced-order modeling of a thermoacoustic engine

NASA Astrophysics Data System (ADS)

Scalo, Carlo; Lin, Jeff; Lele, Sanjiva; Hesselink, Lambertus

2013-11-01

We have carried out the first three-dimensional numerical simulation of a thermoacoustic Stirling heat-engine. The goal is to lay the groundwork for full-scale Navier-Stokes simulations to advance the state-of-the-art low-order modeling and design of such devices. The model adopted is a long resonator with a heat-exchanger/regenerator (HX/REG) unit on one end - the only component not directly resolved. A temperature difference across the HX/REG unit of 200 K is sufficient to initiate the thermoacoustic instability. The latter is a Lagrangian process that only intensifies acoustic waves traveling in the direction of the imposed temperature gradient. An acoustic network of traveling waves is thus obtained and compared against low-order prediction tools such as DeltaEC. Non-linear effects such as system-wide streaming flow patterns are rapidly established. These are responsible for the mean advection of hot fluid away from the HX/REG (i.e. thermal leakage). This unwanted effect is contained by the introduction of a second ambient heat-exchanger allowing for the establishment of a dynamical thermal equilibrium in the system. A limit cycle is obtained at +178 dB.

Regional Monitoring Networks (RMN) to Detect Changing Baselines in Freshwater Wadeable Streams (Final Report)

EPA Science Inventory

The United States Environmental Protection Agency (U.S. EPA) is working with its regional offices, states, tribes, and other entities to establish Regional Monitoring Networks (RMNs) at which biological, thermal, and hydrologic data are collected from freshwater wadeable streams ...

Nickel ferrite aerogels with monodisperse nanoscale building blocks--the importance of processing temperature and atmosphere.

PubMed

Pettigrew, Katherine A; Long, Jeffrey W; Carpenter, Everett E; Baker, Colin C; Lytle, Justin C; Chervin, Christopher N; Logan, Michael S; Stroud, Rhonda M; Rolison, Debra R

2008-04-01

Using two-step (air/argon) thermal processing, sol-gel-derived nickel-iron oxide aerogels are transformed into monodisperse, networked nanocrystalline magnetic oxides of NiFe(2)O(4) with particle diameters that can be ripened with increasing temperature under argon to 4.6, 6.4, and 8.8 nm. Processing in air alone yields poorly crystalline materials; heating in argon alone leads to single phase, but diversiform, polydisperse NiFe(2)O(4), which hampers interpretation of the magnetic properties of the nanoarchitectures. The two-step method yields an improved model system to study magnetic effects as a function of size on the nanoscale while maintaining the particles within the size regime of single domain magnets, as networked building blocks, not agglomerates, and without stabilizing ligands capping the surface.

Thermal pollution impacts on rivers and power supply in the Mississippi River watershed

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

Miara, Ariel; Vorosmarty, Charles J.; Macknick, Jordan E.

Thermal pollution from power plants degrades riverine ecosystems with ramifications beyond the natural environment as it affects power supply. The transport of thermal effluents along river reaches may lead to plant-to-plant interferences by elevating condenser inlet temperatures at downstream locations, which lower thermal efficiencies and trigger regulatory-forced power curtailments. We evaluate thermal pollution impacts on rivers and power supply across 128 plants with once-through cooling technologies in the Mississippi River watershed. By leveraging river network topologies with higher resolutions (0.05 degrees) than previous studies, we reveal the need to address the issue in a more spatially resolved manner, capable ofmore » uncovering diverse impacts across individual plants, river reaches and sub-basins. Results show that the use of coarse river network resolutions may lead to substantial overestimations in magnitude and length of impaired river reaches. Overall, there is a modest limitation on power production due to thermal pollution, given existing infrastructure, regulatory and climate conditions. However, tradeoffs between thermal pollution and electricity generation show important implications for the role of alternative cooling technologies and environmental regulation under current and future climates. Recirculating cooling technologies may nearly eliminate thermal pollution and improve power system reliability under stressed climate-water conditions. Regulatory limits also reduce thermal pollution, but at the expense of significant reductions in electricity generation capacity. However, results show several instances when power production capacity rises at individual plants when regulatory limits reduce upstream thermal pollution. Furthermore, these dynamics across energy-water systems highlight the need for high-resolution simulations and the value of coherent planning and optimization across infrastructure with mutual dependencies on natural resources to overcome climate-water constraints on productivity and bring to fruition energy and environmental win-win opportunities.« less

Thermal pollution impacts on rivers and power supply in the Mississippi River watershed

DOE PAGES

Miara, Ariel; Vorosmarty, Charles J.; Macknick, Jordan E.; ...

2018-03-08

Thermal pollution from power plants degrades riverine ecosystems with ramifications beyond the natural environment as it affects power supply. The transport of thermal effluents along river reaches may lead to plant-to-plant interferences by elevating condenser inlet temperatures at downstream locations, which lower thermal efficiencies and trigger regulatory-forced power curtailments. We evaluate thermal pollution impacts on rivers and power supply across 128 plants with once-through cooling technologies in the Mississippi River watershed. By leveraging river network topologies with higher resolutions (0.05 degrees) than previous studies, we reveal the need to address the issue in a more spatially resolved manner, capable ofmore » uncovering diverse impacts across individual plants, river reaches and sub-basins. Results show that the use of coarse river network resolutions may lead to substantial overestimations in magnitude and length of impaired river reaches. Overall, there is a modest limitation on power production due to thermal pollution, given existing infrastructure, regulatory and climate conditions. However, tradeoffs between thermal pollution and electricity generation show important implications for the role of alternative cooling technologies and environmental regulation under current and future climates. Recirculating cooling technologies may nearly eliminate thermal pollution and improve power system reliability under stressed climate-water conditions. Regulatory limits also reduce thermal pollution, but at the expense of significant reductions in electricity generation capacity. However, results show several instances when power production capacity rises at individual plants when regulatory limits reduce upstream thermal pollution. Furthermore, these dynamics across energy-water systems highlight the need for high-resolution simulations and the value of coherent planning and optimization across infrastructure with mutual dependencies on natural resources to overcome climate-water constraints on productivity and bring to fruition energy and environmental win-win opportunities.« less

Thermal pollution impacts on rivers and power supply in the Mississippi River watershed

NASA Astrophysics Data System (ADS)

Miara, Ariel; Vörösmarty, Charles J.; Macknick, Jordan E.; Tidwell, Vincent C.; Fekete, Balazs; Corsi, Fabio; Newmark, Robin

2018-03-01

Thermal pollution from power plants degrades riverine ecosystems with ramifications beyond the natural environment as it affects power supply. The transport of thermal effluents along river reaches may lead to plant-to-plant interferences by elevating condenser inlet temperatures at downstream locations, which lower thermal efficiencies and trigger regulatory-forced power curtailments. We evaluate thermal pollution impacts on rivers and power supply across 128 plants with once-through cooling technologies in the Mississippi River watershed. By leveraging river network topologies with higher resolutions (0.05°) than previous studies, we reveal the need to address the issue in a more spatially resolved manner, capable of uncovering diverse impacts across individual plants, river reaches and sub-basins. Results show that the use of coarse river network resolutions may lead to substantial overestimations in magnitude and length of impaired river reaches. Overall, there is a modest limitation on power production due to thermal pollution, given existing infrastructure, regulatory and climate conditions. However, tradeoffs between thermal pollution and electricity generation show important implications for the role of alternative cooling technologies and environmental regulation under current and future climates. Recirculating cooling technologies may nearly eliminate thermal pollution and improve power system reliability under stressed climate-water conditions. Regulatory limits also reduce thermal pollution, but at the expense of significant reductions in electricity generation capacity. However, results show several instances when power production capacity rises at individual plants when regulatory limits reduce upstream thermal pollution. These dynamics across energy-water systems highlight the need for high-resolution simulations and the value of coherent planning and optimization across infrastructure with mutual dependencies on natural resources to overcome climate-water constraints on productivity and bring to fruition energy and environmental win-win opportunities.

High-Thermal-Conductivity Fabrics

NASA Technical Reports Server (NTRS)

Chibante, L. P. Felipe

2012-01-01

Heat management with common textiles such as nylon and spandex is hindered by the poor thermal conductivity from the skin surface to cooling surfaces. This innovation showed marked improvement in thermal conductivity of the individual fibers and tubing, as well as components assembled from them. The problem is centered on improving the heat removal of the liquid-cooled ventilation garments (LCVGs) used by astronauts. The current design uses an extensive network of water-cooling tubes that introduces bulkiness and discomfort, and increases fatigue. Range of motion and ease of movement are affected as well. The current technology is the same as developed during the Apollo program of the 1960s. Tubing material is hand-threaded through a spandex/nylon mesh layer, in a series of loops throughout the torso and limbs such that there is close, form-fitting contact with the user. Usually, there is a nylon liner layer to improve comfort. Circulating water is chilled by an external heat exchanger (sublimator). The purpose of this innovation is to produce new LCVG components with improved thermal conductivity. This was addressed using nanocomposite engineering incorporating high-thermalconductivity nanoscale fillers in the fabric and tubing components. Specifically, carbon nanotubes were added using normal processing methods such as thermoplastic melt mixing (compounding twin screw extruder) and downstream processing (fiber spinning, tubing extrusion). Fibers were produced as yarns and woven into fabric cloths. The application of isotropic nanofillers can be modeled using a modified Nielsen Model for conductive fillers in a matrix based on Einstein s viscosity model. This is a drop-in technology with no additional equipment needed. The loading is limited by the ability to maintain adequate dispersion. Undispersed materials will plug filtering screens in processing equipment. Generally, the viscosity increases were acceptable, and allowed the filled polymers to still be processed.The novel feature is that fabrics do not inherently possess good thermal conductivity. In fact, fabrics are used for thermal insulation, not heat removal. The technology represents the first material that is a wearable fabric, based on company textiles and materials that will significantly conduct heat.

Lattice topology dictates photon statistics.

PubMed

Kondakci, H Esat; Abouraddy, Ayman F; Saleh, Bahaa E A

2017-08-21

Propagation of coherent light through a disordered network is accompanied by randomization and possible conversion into thermal light. Here, we show that network topology plays a decisive role in determining the statistics of the emerging field if the underlying lattice is endowed with chiral symmetry. In such lattices, eigenmode pairs come in skew-symmetric pairs with oppositely signed eigenvalues. By examining one-dimensional arrays of randomly coupled waveguides arranged on linear and ring topologies, we are led to a remarkable prediction: the field circularity and the photon statistics in ring lattices are dictated by its parity while the same quantities are insensitive to the parity of a linear lattice. For a ring lattice, adding or subtracting a single lattice site can switch the photon statistics from super-thermal to sub-thermal, or vice versa. This behavior is understood by examining the real and imaginary fields on a lattice exhibiting chiral symmetry, which form two strands that interleave along the lattice sites. These strands can be fully braided around an even-sited ring lattice thereby producing super-thermal photon statistics, while an odd-sited lattice is incommensurate with such an arrangement and the statistics become sub-thermal.

The NASA Fireball Network All-Sky Cameras

NASA Technical Reports Server (NTRS)

Suggs, Rob M.

2011-01-01

The construction of small, inexpensive all-sky cameras designed specifically for the NASA Fireball Network is described. The use of off-the-shelf electronics, optics, and plumbing materials results in a robust and easy to duplicate design. Engineering challenges such as weather-proofing and thermal control and their mitigation are described. Field-of-view and gain adjustments to assure uniformity across the network will also be detailed.

Potential and challenges in use of thermal imaging for humid region irrigation system management

USDA-ARS?s Scientific Manuscript database

Thermal imaging has shown potential to assist with many aspects of irrigation management including scheduling water application, detecting leaky irrigation canals, and gauging the overall effectiveness of water distribution networks used in furrow irrigation. Many challenges exist for the use of the...

Development of the FHR advanced natural circulation analysis code and application to FHR safety analysis

DOE PAGES

Guo, Z.; Zweibaum, N.; Shao, M.; ...

2016-04-19

The University of California, Berkeley (UCB) is performing thermal hydraulics safety analysis to develop the technical basis for design and licensing of fluoride-salt-cooled, high-temperature reactors (FHRs). FHR designs investigated by UCB use natural circulation for emergency, passive decay heat removal when normal decay heat removal systems fail. The FHR advanced natural circulation analysis (FANCY) code has been developed for assessment of passive decay heat removal capability and safety analysis of these innovative system designs. The FANCY code uses a one-dimensional, semi-implicit scheme to solve for pressure-linked mass, momentum and energy conservation equations. Graph theory is used to automatically generate amore » staggered mesh for complicated pipe network systems. Heat structure models have been implemented for three types of boundary conditions (Dirichlet, Neumann and Robin boundary conditions). Heat structures can be composed of several layers of different materials, and are used for simulation of heat structure temperature distribution and heat transfer rate. Control models are used to simulate sequences of events or trips of safety systems. A proportional-integral controller is also used to automatically make thermal hydraulic systems reach desired steady state conditions. A point kinetics model is used to model reactor kinetics behavior with temperature reactivity feedback. The underlying large sparse linear systems in these models are efficiently solved by using direct and iterative solvers provided by the SuperLU code on high performance machines. Input interfaces are designed to increase the flexibility of simulation for complicated thermal hydraulic systems. In conclusion, this paper mainly focuses on the methodology used to develop the FANCY code, and safety analysis of the Mark 1 pebble-bed FHR under development at UCB is performed.« less

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

Guo, Z.; Zweibaum, N.; Shao, M.

The University of California, Berkeley (UCB) is performing thermal hydraulics safety analysis to develop the technical basis for design and licensing of fluoride-salt-cooled, high-temperature reactors (FHRs). FHR designs investigated by UCB use natural circulation for emergency, passive decay heat removal when normal decay heat removal systems fail. The FHR advanced natural circulation analysis (FANCY) code has been developed for assessment of passive decay heat removal capability and safety analysis of these innovative system designs. The FANCY code uses a one-dimensional, semi-implicit scheme to solve for pressure-linked mass, momentum and energy conservation equations. Graph theory is used to automatically generate amore » staggered mesh for complicated pipe network systems. Heat structure models have been implemented for three types of boundary conditions (Dirichlet, Neumann and Robin boundary conditions). Heat structures can be composed of several layers of different materials, and are used for simulation of heat structure temperature distribution and heat transfer rate. Control models are used to simulate sequences of events or trips of safety systems. A proportional-integral controller is also used to automatically make thermal hydraulic systems reach desired steady state conditions. A point kinetics model is used to model reactor kinetics behavior with temperature reactivity feedback. The underlying large sparse linear systems in these models are efficiently solved by using direct and iterative solvers provided by the SuperLU code on high performance machines. Input interfaces are designed to increase the flexibility of simulation for complicated thermal hydraulic systems. In conclusion, this paper mainly focuses on the methodology used to develop the FANCY code, and safety analysis of the Mark 1 pebble-bed FHR under development at UCB is performed.« less

Multi-Scale Thermal Heat Tracer Tests for Characterizing Transport Processes and Flow Channelling in Fractured Media: Theory and Field Experiments

NASA Astrophysics Data System (ADS)

de La Bernardie, J.; Klepikova, M.; Bour, O.; Le Borgne, T.; Dentz, M.; Guihéneuf, N.; Gerard, M. F.; Lavenant, N.

2017-12-01

The characterization of flow and transport in fractured media is particularly challenging because hydraulic conductivity and transport properties are often strongly dependent on the geometric structure of the fracture surfaces. Here we show how thermal tracer tests may be an excellent complement to conservative solute tracer tests to infer fracture geometry and flow channeling. We performed a series of thermal tracer tests at different scales in a crystalline rock aquifer at the experimental site of Ploemeur (H+ observatory network). The first type of thermal tracer tests are push-pull tracer tests at different scales. The temporal and spatial scaling of heat recovery, measured from thermal breakthrough curves, shows a clear signature of flow channeling. In particular, the late time tailing of heat recovery under channeled flow is shown to diverge from the T(t) α t-1,5 behavior expected for the classical parallel plate model and follow the scaling T(t) α 1/t(logt)2 for a simple channel modeled as a tube. Flow channeling is also manifested on the spatial scaling of heat recovery as flow channeling affects the decay of the thermal breakthrough peak amplitude and the increase of the peak time with scale. The second type of thermal tracer tests are flow-through tracer tests where a pulse of hot water was injected in a fracture isolated by a double straddle packer while pumping at the same flow rate in another fracture at a distance of about 10 meters to create a dipole flow field. Comparison with a solute tracer test performed under the same conditions also present a clear signature of flow channeling. We derive analytical expressions for the retardation and decay of the thermal breakthrough peak amplitude for different fracture geometries and show that the observed differences between thermal and solute breakthrough can be explained only by channelized flow. These results suggest that heat transport is much more sensitive to fracture heterogeneity and flow channeling than conservative solute transport. These findings, which bring new insights on the effect of flow channeling on heat transfer in fractured rocks, show how heat recovery in geothermal systems may be controlled by fracture geometry. This highlights the interest of thermal tracer tests as a complement to solute tracers tests to infer fracture aperture and geometry.

Analytical thermal resistance model for high power double-clad fiber on rectangular plate with convective cooling at upper and lower surfaces

NASA Astrophysics Data System (ADS)

Lv, Yi; Zheng, Huai; Liu, Sheng

2018-07-01

Whether convective heat transfer on the upper surface of the substrate is used or not, the thermal resistance network models of optical fiber embedded in the substrate are established in this research. These models are applied to calculate the heat dissipation in a high power ytterbium doped double-clad fiber (YDCF) power amplifier. Firstly, the temperature values of two points on the fiber are tested when there is no convective heat transfer on the upper surface. Then, the numerical simulation is used to verify the temperature change of the fiber with the effective convective heat transfer coefficient of the lower surface heff increasing when the upper surface is subjected to three loading conditions with hu as 1, 5 and 15 W/(m2 K), respectively. The axial temperature distribution of the optical fiber is also presented at four different values for hu when heff is 30 W/(m2 K). Absolute values of the relative errors are less than 7.08%. The results show that the analytical models can accurately calculate the temperature distribution of the optical fiber when the fiber is encapsulated into the substrate. The corresponding relationship is helpful to further optimize packaging design of the fiber cooling system.

Switching "on" and "off" the adhesion in stimuli-responsive elastomers.

PubMed

Kaiser, S; Radl, S V; Manhart, J; Ayalur-Karunakaran, S; Griesser, T; Moser, A; Ganser, C; Teichert, C; Kern, W; Schlögl, S

2018-03-28

The present work aims at the preparation of dry adhesives with switchable bonding properties by using the reversible nature of the [4πs+4πs] cycloaddition of anthracenes. Photo-responsive hydrogenated carboxylated nitrile butadiene rubber with photo-responsive pendant anthracene groups is prepared by one-pot synthesis. The formation of 3D networks relies on the photodimerization of the anthracene moieties upon UV exposure (λ > 300 nm). Controlled cleavage of the crosslink sites is achieved by either deep UV exposure (λ = 254 nm) or thermal dissociation at 70 °C. The kinetics of the optical and thermal cleavage routes are compared in thin films using UV-vis spectroscopy and their influence on the reversibility of the network is detailed. Going from thin films to free standing samples the modulation of the network structure and thermo-mechanical properties over repeated crosslinking and cleavage cycles are characterized by low-field NMR spectroscopy and dynamic mechanical analysis. The applicability of the stimuli-responsive networks as adhesives with reversible bonding properties is demonstrated. The results evidence that the reversibility of the crosslinking reaction enables a controlled switching "on" and "off" of adhesion properties. The recovery of the adhesion force amounts to 75 and 80% for photo- and thermal dissociation, respectively. Spatial control of adhesion properties is evidenced by adhesion force mapping experiments of photo-patterned films.

On the formation of well-aligned ZnO nanowall networks by catalyst-free thermal evaporation method

NASA Astrophysics Data System (ADS)

Yin, Zhigang; Chen, Nuofu; Dai, Ruixuan; Liu, Lei; Zhang, Xingwang; Wang, Xiaohui; Wu, Jinliang; Chai, Chunlin

2007-07-01

Two-dimensional ZnO nanowall networks were grown on ZnO-coated silicon by thermal evaporation at low temperature without catalysts or additives. All of the results from scanning electronic spectroscope, X-ray diffraction and Raman scattering confirmed that the ZnO nanowalls were vertically aligned and c-axis oriented. The room-temperature photoluminescence spectra showed a dominated UV peak at 378 nm, and a much suppressed orange emission centered at ˜590 nm. This demonstrates fairly good crystal quality and optical properties of the product. A possible three-step, zinc vapor-controlled process was proposed to explain the growth of well-aligned ZnO nanowall networks. The pre-coated ZnO template layer plays a key role during the synthesis process, which guides the growth direction of the synthesized products.

Fast Rotational Diffusion of Water Molecules in a 2D Hydrogen Bond Network at Cryogenic Temperatures

NASA Astrophysics Data System (ADS)

Prisk, T. R.; Hoffmann, C.; Kolesnikov, A. I.; Mamontov, E.; Podlesnyak, A. A.; Wang, X.; Kent, P. R. C.; Anovitz, L. M.

2018-05-01

Individual water molecules or small clusters of water molecules contained within microporous minerals present an extreme case of confinement where the local structure of hydrogen bond networks are dramatically altered from bulk water. In the zinc silicate hemimorphite, the water molecules form a two-dimensional hydrogen bond network with hydroxyl groups in the crystal framework. Here, we present a combined experimental and theoretical study of the structure and dynamics of water molecules within this network. The water molecules undergo a continuous phase transition in their orientational configuration analogous to a two-dimensional Ising model. The incoherent dynamic structure factor reveals two thermally activated relaxation processes, one on a subpicosecond timescale and another on a 10-100 ps timescale, between 70 and 130 K. The slow process is an in-plane reorientation of the water molecule involving the breaking of hydrogen bonds with a framework that, despite the low temperatures involved, is analogous to rotational diffusion of water molecules in the bulk liquid. The fast process is a localized motion of the water molecule with no apparent analogs among known bulk or confined phases of water.

Fast Rotational Diffusion of Water Molecules in a 2D Hydrogen Bond Network at Cryogenic Temperatures

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

Prisk, Timothy; Hoffmann, Christina; Kolesnikov, Alexander I.

Individual water molecules or small clusters of water molecules contained within microporous minerals present an extreme case of confinement where the local structure of hydrogen bond networks are dramatically altered from bulk water. In the zinc silicate hemimorphite, the water molecules form a two-dimensional hydrogen bond network with hydroxyl groups in the crystal framework. Here in this paper, we present a combined experimental and theoretical study of the structure and dynamics of water molecules within this network. The water molecules undergo a continuous phase transition in their orientational configuration analogous to a two-dimensional Ising model. The incoherent dynamic structure factormore » reveals two thermally activated relaxation processes, one on a subpicosecond timescale and another on a 10–100 ps timescale, between 70 and 130 K. The slow process is an in-plane reorientation of the water molecule involving the breaking of hydrogen bonds with a framework that, despite the low temperatures involved, is analogous to rotational diffusion of water molecules in the bulk liquid. The fast process is a localized motion of the water molecule with no apparent analogs among known bulk or confined phases of water.« less

Fast Rotational Diffusion of Water Molecules in a 2D Hydrogen Bond Network at Cryogenic Temperatures

DOE PAGES

Prisk, Timothy; Hoffmann, Christina; Kolesnikov, Alexander I.; ...

2018-05-09

Individual water molecules or small clusters of water molecules contained within microporous minerals present an extreme case of confinement where the local structure of hydrogen bond networks are dramatically altered from bulk water. In the zinc silicate hemimorphite, the water molecules form a two-dimensional hydrogen bond network with hydroxyl groups in the crystal framework. Here in this paper, we present a combined experimental and theoretical study of the structure and dynamics of water molecules within this network. The water molecules undergo a continuous phase transition in their orientational configuration analogous to a two-dimensional Ising model. The incoherent dynamic structure factormore » reveals two thermally activated relaxation processes, one on a subpicosecond timescale and another on a 10–100 ps timescale, between 70 and 130 K. The slow process is an in-plane reorientation of the water molecule involving the breaking of hydrogen bonds with a framework that, despite the low temperatures involved, is analogous to rotational diffusion of water molecules in the bulk liquid. The fast process is a localized motion of the water molecule with no apparent analogs among known bulk or confined phases of water.« less

An adaptive random search for short term generation scheduling with network constraints.

PubMed

Marmolejo, J A; Velasco, Jonás; Selley, Héctor J

2017-01-01

This paper presents an adaptive random search approach to address a short term generation scheduling with network constraints, which determines the startup and shutdown schedules of thermal units over a given planning horizon. In this model, we consider the transmission network through capacity limits and line losses. The mathematical model is stated in the form of a Mixed Integer Non Linear Problem with binary variables. The proposed heuristic is a population-based method that generates a set of new potential solutions via a random search strategy. The random search is based on the Markov Chain Monte Carlo method. The main key of the proposed method is that the noise level of the random search is adaptively controlled in order to exploring and exploiting the entire search space. In order to improve the solutions, we consider coupling a local search into random search process. Several test systems are presented to evaluate the performance of the proposed heuristic. We use a commercial optimizer to compare the quality of the solutions provided by the proposed method. The solution of the proposed algorithm showed a significant reduction in computational effort with respect to the full-scale outer approximation commercial solver. Numerical results show the potential and robustness of our approach.

Stabilization of burn conditions in a thermonuclear reactor using artificial neural networks

NASA Astrophysics Data System (ADS)

Vitela, Javier E.; Martinell, Julio J.

1998-02-01

In this work we develop an artificial neural network (ANN) for the feedback stabilization of a thermonuclear reactor at nearly ignited burn conditions. A volume-averaged zero-dimensional nonlinear model is used to represent the time evolution of the electron density, the relative density of alpha particles and the temperature of the plasma, where a particular scaling law for the energy confinement time previously used by other authors, was adopted. The control actions include the concurrent modulation of the D-T refuelling rate, the injection of a neutral He-4 beam and an auxiliary heating power modulation, which are constrained to take values within a maximum and minimum levels. For this purpose a feedforward multilayer artificial neural network with sigmoidal activation function is trained using a back-propagation through-time technique. Numerical examples are used to illustrate the behaviour of the resulting ANN-dynamical system configuration. It is concluded that the resulting ANN can successfully stabilize the nonlinear model of the thermonuclear reactor at nearly ignited conditions for temperature and density departures significantly far from their nominal operating values. The NN-dynamical system configuration is shown to be robust with respect to the thermalization time of the alpha particles for perturbations within the region used to train the NN.

Regional Monitoring Networks to Detect Climate Change Effects in Stream Ecosystems (External Review Draft)

EPA Science Inventory

The United States Environmental Protection Agency (U.S. EPA) is working with its regional offices, states, tribes, and other entities to establish Regional Monitoring Networks (RMNs) at which biological, thermal, and hydrologic data will be collected from freshwater wadeable stre...

Accurate atomistic potentials and training sets for boron-nitride nanostructures

NASA Astrophysics Data System (ADS)

Tamblyn, Isaac

Boron nitride nanotubes exhibit exceptional structural, mechanical, and thermal properties. They are optically transparent and have high thermal stability, suggesting a wide range of opportunities for structural reinforcement of materials. Modeling can play an important role in determining the optimal approach to integrating nanotubes into a supporting matrix. Developing accurate, atomistic scale models of such nanoscale interfaces embedded within composites is challenging, however, due to the mismatch of length scales involved. Typical nanotube diameters range from 5-50 nm, with a length as large as a micron (i.e. a relevant length-scale for structural reinforcement). Unlike their carbon-based counterparts, well tested and transferable interatomic force fields are not common for BNNT. In light of this, we have developed an extensive training database of BN rich materials, under conditions relevant for BNNT synthesis and composites based on extensive first principles molecular dynamics simulations. Using this data, we have produced an artificial neural network potential capable of reproducing the accuracy of first principles data at significantly reduced computational cost, allowing for accurate simulation at the much larger length scales needed for composite design.

Crack networks in damaged glass

NASA Astrophysics Data System (ADS)

Mallet, Celine; Fortin, Jerome; Gueguen, Yves

2013-04-01

We investigate how cracks develop and propagate in synthetic glass samples. Cracks are introduced in glass by a thermal shock of 300oC. Crack network is documented from optical and electronic microscopy on these samples that have been submitted to a thermal shock only. Samples are cylinder of 80 mm length and 40 mm diameter. Sections were cut along the cylinder axis and perpendicular to it. Using SEM, crack lengths and apertures can be measured. Optical microscopy allows to get the crack distribution over the entire sample. The sample average crack length is 3 mm. The average aperture is 6 ± 3μm. There is however a clear difference between the sample core, where the crack network has approximatively a transverse isotrope symmetry and the outer ring, where cracks are smaller and more numerous. By measuring before and after the thermal treatment the radial P and S wave velocities in room conditions, we can determine the total crack density which is 0.24. Thermally cracked samples, as described above, were submitted to creep tests. Constant axial stress and lateral stress were applied. Several experiments were performed at different stress values. Samples are saturated for 48 hours (to get an homogeneous pore fluid distribution), the axial stress is increased up to 80% of the sample strength. Stress step tests were performed in order to get creep data. The evolution of strain (axial and radial strain) is measured using strain gages, gap sensors (for the global axial strain) and pore volume change (for the volumetric strain). Creep data are interpreted as evidence of sub-critical crack growth in the cracked glass samples. The above microstructural observations are used, together with a crack propagation model, to account for the creep behavior. Assuming that (i) the observed volumetric strain rate is due to crack propagation and (ii) crack aspect ratio is constant we calculate the creep rate. We obtain some value on the crack propagation during a 24 hours of constant stress test. At each of these test, crack propagate of 0.3 to 0.4 mm. From the initial average crack length of 3 mm, the crack reach the size of 5.8 mm at the end of a complete creep test (with 8 constant stress step of 24 hours).

21SSD: a new public 21-cm EoR database

NASA Astrophysics Data System (ADS)

Eames, Evan; Semelin, Benoît

2018-05-01

With current efforts inching closer to detecting the 21-cm signal from the Epoch of Reionization (EoR), proper preparation will require publicly available simulated models of the various forms the signal could take. In this work we present a database of such models, available at 21ssd.obspm.fr. The models are created with a fully-coupled radiative hydrodynamic simulation (LICORICE), and are created at high resolution (10243). We also begin to analyse and explore the possible 21-cm EoR signals (with Power Spectra and Pixel Distribution Functions), and study the effects of thermal noise on our ability to recover the signal out to high redshifts. Finally, we begin to explore the concepts of `distance' between different models, which represents a crucial step towards optimising parameter space sampling, training neural networks, and finally extracting parameter values from observations.

Sensing the heat stress by Mammalian cells.

PubMed

Cates, Jordan; Graham, Garrett C; Omattage, Natalie; Pavesich, Elizabeth; Setliff, Ian; Shaw, Jack; Smith, Caitlin Lee; Lipan, Ovidiu

2011-08-11

The heat-shock response network controls the adaptation and survival of the cell against environmental stress. This network is highly conserved and is connected with many other signaling pathways. A key element of the heat-shock network is the heat-shock transcription factor-1 (HSF), which is transiently activated by elevated temperatures. HSF translocates to the nucleus upon elevated temperatures, forming homotrimeric complexes. The HSF homotrimers bind to the heat shock element on the DNA and control the expression of the hsp70 gene. The Hsp70 proteins protect cells from thermal stress. Thermal stress causes the unfolding of proteins, perturbing thus the pathways under their control. By binding to these proteins, Hsp70 allows them to refold and prevents their aggregation. The modulation of the activity of the hsp70-promoter by the intensity of the input stress is thus critical for cell's survival. The promoter activity starts from a basal level and rapidly increases once the stress is applied, reaches a maximum level and attenuates slowely back to the basal level. This phenomenon is the hallmark of many experimental studies and of all computational network analysis. The molecular construct used as a measure of the response to thermal stress is a Hsp70-GFP fusion gene transfected in Chinese hamster ovary (CHO) cells. The time profile of the GFP protein depends on the transient activity, Transient(t), of the heat shock system. The function Transient(t) depends on hsp70 promoter activity, transcriptional regulation and the translation initiation effects elicited by the heat stress. The GFP time profile is recorded using flow cytometry measurements, a technique that allows a quantitative measurement of the fluorescence of a large number of cells (104). The GFP responses to one and two heat shocks were measured for 261 conditions of different temperatures and durations. We found that: (i) the response of the cell to two consecutive shocks (i.e., no recovery time in between shocks) depends on the order of the input shocks, that is the shocks do not commute; (ii) the responses may be classified as mild or severe, depending on the temperature level and the duration of the heat shock and (iii) the response is highly sensitive to small variations in temperature. We propose a mathematical model that maps temperature into the transient activity using experimental data that describes the time course of the response to input thermal stress. The model is built on thermotolerance without recovery time, sharp sensitivity to small variations in temperature and the existence of mild and severe classes of stress responses. The theoretical predictions are tested against experimental data using a series of double-shock inputs. The theoretical structure is represented by a sequence of three cascade processes that transform the input stress into the transient activity. The structure of the cascade is nonlinear-linear-nonlinear (NLN). The first nonlinear system (N) from the NLN structure represents the amplification of small changes in the environmental temperature; the linear system (L) represents the thermotolerance without recovery time, whereas the last system (N) represents the transition of the cell's response from a mild to a severe shock.

Transient and asymptotic behavior in a regular network model for the ice-albedo feedback under thermal forcing

NASA Astrophysics Data System (ADS)

Mueller-Stoffels, M.; Wackerbauer, R.

2010-12-01

The Arctic ocean and sea ice form a feedback system which plays an important role in the global climate. Variations of the global ice and snow distribution have a significant effect on the planetary albedo which governs the absorption of shortwave radiation. The complexity of highly parametrized GCMs makes it very difficult to assess single feedback processes in the climate system without the concurrent use of simple models where the physics are understood [1][2][3]. We introduce a complex systems model to investigate thermodynamic feedback processes in an Arctic ice-ocean layer. The ice-ocean layer is represented as a regular network of coupled cells. The state of each cell is determined by its energy content, which also defines the phase of the cell. The energy transport between cells is described with nonlinear and heterogeneous diffusion constants. And the time-evolution of the ice-ocean is driven by shortwave, longwave and lateral oceanic and atmospheric thermal forcing. This model is designed to study the stability of an ice cover under various heat intake scenarios. The network structure of the model allows to easily introduce albedo heterogeneities due to aging ice, wind blown snow cover, and ice movement to explore the time-evolution and pattern formation (melt ponds) processes in the Arctic sea ice. The solely thermodynamic model exhibits two stable states; one in the perennially ice covered domain and one in the perennially open water domain. Their existence is due to the temperature dependence of the longwave radiative budget. Transition between these states can be forced via lateral heat fluxes. During the transition from the ice covered to the open water stable state the ice albedo feedback effects are manifested as an increased warming rate of the ice cover together with enhanced seasonal energy oscillations. In the current model realization seasonal ice cover is present as a transient state only. Furthermore, the model exhibits hysteresis between the ice covered and the open water state when varying the lateral atmospheric (or oceanic) heat intake. Once the ice-ocean layer has transitioned from the ice covered to the open water stable state significant cooling (reduction of lateral fluxes) is necessary to return to the ice covered stable state. We also find that ocean heat fluxes are more efficient than atmospheric heat fluxes to melt Arctic sea ice; only small portions of heat entering from the bottom of the ice-ocean layer induce already a transition to the stable asymptotic state with perennial open water. This indicates that ocean currents, understood as heat conveyors, can play a significant role in melting continuous ice covers. This is consistent with the findings of Shimada et al. for the Canada basin [4]. References: [1] S. Bony et al., How well do we understand and evaluate climate change feedback processes?, J of Climate 19, 3445 (2006). [2]I. Eisenman and J.S. Wettlaufer, Nonlinear threshold behavior during the loss of Arctic sea ice, PNAS 106, 28 (2009). [3]A.S. Thorndike, A Toy Model Linking Atmospheric and Thermal Radiation and Sea Ice Growth, JGR 97, 9401 (1992). [4] K. Shimada et al., Paci[|#12#|]c Ocean inflow: Influence on catastrophic reduction of sea ice cover in the Arctic Ocean, GRL 33, L08605 (2006).

Synergistic effect of selectively distributed AlN/MWCNT hybrid fillers on the morphological, mechanical and thermal properties of polycarbonate/maleated poly[styrene-b-(ethylene-co-butylene)- b-styrene] triblock copolymer (SEBS-g-MA) composites

NASA Astrophysics Data System (ADS)

Xiao, Chao; Leng, Xinyu; Wang, Hui; Su, Zheng; Zhang, Xian; Chen, Lin; Zheng, Kang; Tian, Xingyou

2017-02-01

A quaternary nanocomposite polycarbonate (PC)- multi-walled carbon nanotubes (MWCNT)/SEBS-g-MA (SM)-AlN is prepared by controlling the selective distribution of nano-fillers via melt-blending. Through a two-step mixing method, surface modified AlN is selectively dispersed in the island-like SM phase; meanwhile, MWCNT acting as bridges are mainly located in the continuous phase of PC. This ‘island-bridge’ morphology is confirmed by scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The selective localization results agree well with the theoretical predictions. Dynamic mechanical analysis (DMA) indicates that the addition of hybrid fillers improved the storage modulus selectively. Thermogravimetric analysis (TGA) shows that the thermal stability of the PC/SM blends increased significantly; the degradation kinetic has also been changed due to the synergistic effects of the fillers. This novel ‘island-bridge’ network contributes a higher thermal conductivity at low filler content as the effective thermal conductivity reached 0.72 W m-1 K-1, which is three times higher than that of 70PC/30SM. The experimental observations coincide well with the optimizing model results.

Dreaming of Atmospheres

NASA Astrophysics Data System (ADS)

Waldmann, Ingo

2016-10-01

Radiative transfer retrievals have become the standard in modelling of exoplanetary transmission and emission spectra. Analysing currently available observations of exoplanetary atmospheres often invoke large and correlated parameter spaces that can be difficult to map or constrain.To address these issues, we have developed the Tau-REx (tau-retrieval of exoplanets) retrieval and the RobERt spectral recognition algorithms. Tau-REx is a bayesian atmospheric retrieval framework using Nested Sampling and cluster computing to fully map these large correlated parameter spaces. Nonetheless, data volumes can become prohibitively large and we must often select a subset of potential molecular/atomic absorbers in an atmosphere.In the era of open-source, automated and self-sufficient retrieval algorithms, such manual input should be avoided. User dependent input could, in worst case scenarios, lead to incomplete models and biases in the retrieval. The RobERt algorithm is build to address these issues. RobERt is a deep belief neural (DBN) networks trained to accurately recognise molecular signatures for a wide range of planets, atmospheric thermal profiles and compositions. Using these deep neural networks, we work towards retrieval algorithms that themselves understand the nature of the observed spectra, are able to learn from current and past data and make sensible qualitative preselections of atmospheric opacities to be used for the quantitative stage of the retrieval process.In this talk I will discuss how neural networks and Bayesian Nested Sampling can be used to solve highly degenerate spectral retrieval problems and what 'dreaming' neural networks can tell us about atmospheric characteristics.

Autonomous Sensorweb Operations for Integrated Space, In-Situ Monitoring of Volcanic Activity

NASA Technical Reports Server (NTRS)

Chien, Steve A.; Doubleday, Joshua; Kedar, Sharon; Davies, Ashley G.; Lahusen, Richard; Song, Wenzhan; Shirazi, Behrooz; Mandl, Daniel; Frye, Stuart

2010-01-01

We have deployed and demonstrated operations of an integrated space in-situ sensorweb for monitoring volcanic activity. This sensorweb includes a network of ground sensors deployed to the Mount Saint Helens volcano as well as the Earth Observing One spacecraft. The ground operations and space operations are interlinked in that ground-based intelligent event detections can cause the space segment to acquire additional data via observation requests and space-based data acquisitions (thermal imagery) can trigger reconfigurations of the ground network to allocate increased bandwidth to areas of the network best situated to observe the activity. The space-based operations are enabled by an automated mission planning and tasking capability which utilizes several Opengeospatial Consortium (OGC) Sensorweb Enablement (SWE) standards which enable acquiring data, alerts, and tasking using web services. The ground-based segment also supports similar protocols to enable seamless tasking and data delivery. The space-based segment also supports onboard development of data products (thermal summary images indicating areas of activity, quicklook context images, and thermal activity alerts). These onboard developed products have reduced data volume (compared to the complete images) which enables them to be transmitted to the ground more rapidly in engineering channels.

On Designing Thermal-Aware Localized QoS Routing Protocol for in-vivo Sensor Nodes in Wireless Body Area Networks.

PubMed

Monowar, Muhammad Mostafa; Bajaber, Fuad

2015-06-15

In this paper, we address the thermal rise and Quality-of-Service (QoS) provisioning issue for an intra-body Wireless Body Area Network (WBAN) having in-vivo sensor nodes. We propose a thermal-aware QoS routing protocol, called TLQoS, that facilitates the system in achieving desired QoS in terms of delay and reliability for diverse traffic types, as well as avoids the formation of highly heated nodes known as hotspot(s), and keeps the temperature rise along the network to an acceptable level. TLQoS exploits modular architecture wherein different modules perform integrated operations in providing multiple QoS service with lower temperature rise. To address the challenges of highly dynamic wireless environment inside the human body. TLQoS implements potential-based localized routing that requires only local neighborhood information. TLQoS avoids routing loop formation as well as reduces the number of hop traversal exploiting hybrid potential, and tuning a configurable parameter. We perform extensive simulations of TLQoS, and the results show that TLQoS has significant performance improvements over state-of-the-art approaches.

On Designing Thermal-Aware Localized QoS Routing Protocol for in-vivo Sensor Nodes in Wireless Body Area Networks

PubMed Central

Monowar, Muhammad Mostafa; Bajaber, Fuad

2015-01-01

In this paper, we address the thermal rise and Quality-of-Service (QoS) provisioning issue for an intra-body Wireless Body Area Network (WBAN) having in-vivo sensor nodes. We propose a thermal-aware QoS routing protocol, called TLQoS, that facilitates the system in achieving desired QoS in terms of delay and reliability for diverse traffic types, as well as avoids the formation of highly heated nodes known as hotspot(s), and keeps the temperature rise along the network to an acceptable level. TLQoS exploits modular architecture wherein different modules perform integrated operations in providing multiple QoS service with lower temperature rise. To address the challenges of highly dynamic wireless environment inside the human body. TLQoS implements potential-based localized routing that requires only local neighborhood information. TLQoS avoids routing loop formation as well as reduces the number of hop traversal exploiting hybrid potential, and tuning a configurable parameter. We perform extensive simulations of TLQoS, and the results show that TLQoS has significant performance improvements over state-of-the-art approaches. PMID:26083228

The Multi-Spectral Solar Telescope Array (MSSTA)

NASA Technical Reports Server (NTRS)

Walker, A. B. C., Jr.; Barbee, Troy W., Jr.; Hoover, Richard B.

1997-01-01

In 1987, our consortium pioneered the application of normal incidence multilayer X-ray optics to solar physics by obtaining the first high resolution narrow band, "thermally differentiated" images of the corona', using the emissions of the Fe IX/Fe X complex at ((lambda)lambda) approx. 171 A to 175 A, and He II Lyman (beta) at 256 A. Subsequently, we developed a rocket borne solar observatory, the Multi Spectral Solar Telescope Array (MSSTA) that pioneered multi-thermal imaging of the solar atmosphere, using high resolution narrow band X-ray, EUV and FUV optical systems. Analysis of MSSTA observations has resulted in four significant insights into the structure of the solar atmosphere: (1) the diameter of coronal loops is essentially constant along their length; (2) models of the thermal and density structure of polar plumes based on MSSTA observations have been shown to be consistent with the thesis that they are the source of high speed solar wind streams; (3) the magnetic structure of the footpoints of polar plumes is monopolar, and their thermal structure is consistent with the thesis that the chromosphere at their footpoints is heated by conduction from above; (4) coronal bright points are small loops, typically 3,500 - 20,000 km long (5 sec - 30 sec); their footpoints are located at the poles of bipolar magnetic structures that are are distinguished from other network elements by having a brighter Lyman a signature. Loop models derived for 26 bright points are consistent with the thesis that the chromosphere at their footpoints is heated by conduction from the corona.

Probing many-body localization with neural networks

NASA Astrophysics Data System (ADS)

Schindler, Frank; Regnault, Nicolas; Neupert, Titus

2017-06-01

We show that a simple artificial neural network trained on entanglement spectra of individual states of a many-body quantum system can be used to determine the transition between a many-body localized and a thermalizing regime. Specifically, we study the Heisenberg spin-1/2 chain in a random external field. We employ a multilayer perceptron with a single hidden layer, which is trained on labeled entanglement spectra pertaining to the fully localized and fully thermal regimes. We then apply this network to classify spectra belonging to states in the transition region. For training, we use a cost function that contains, in addition to the usual error and regularization parts, a term that favors a confident classification of the transition region states. The resulting phase diagram is in good agreement with the one obtained by more conventional methods and can be computed for small systems. In particular, the neural network outperforms conventional methods in classifying individual eigenstates pertaining to a single disorder realization. It allows us to map out the structure of these eigenstates across the transition with spatial resolution. Furthermore, we analyze the network operation using the dreaming technique to show that the neural network correctly learns by itself the power-law structure of the entanglement spectra in the many-body localized regime.

Design of coherent receiver optical front end for unamplified applications.

PubMed

Zhang, Bo; Malouin, Christian; Schmidt, Theodore J

2012-01-30

Advanced modulation schemes together with coherent detection and digital signal processing has enabled the next generation high-bandwidth optical communication systems. One of the key advantages of coherent detection is its superior receiver sensitivity compared to direct detection receivers due to the gain provided by the local oscillator (LO). In unamplified applications, such as metro and edge networks, the ultimate receiver sensitivity is dictated by the amount of shot noise, thermal noise, and the residual beating of the local oscillator with relative intensity noise (LO-RIN). We show that the best sensitivity is achieved when the thermal noise is balanced with the residual LO-RIN beat noise, which results in an optimum LO power. The impact of thermal noise from the transimpedance amplifier (TIA), the RIN from the LO, and the common mode rejection ratio (CMRR) from a balanced photodiode are individually analyzed via analytical models and compared to numerical simulations. The analytical model results match well with those of the numerical simulations, providing a simplified method to quantify the impact of receiver design tradeoffs. For a practical 100 Gb/s integrated coherent receiver with 7% FEC overhead, we show that an optimum receiver sensitivity of -33 dBm can be achieved at GFEC cliff of 8.55E-5 if the LO power is optimized at 11 dBm. We also discuss a potential method to monitor the imperfections of a balanced and integrated coherent receiver.

Analysis of hybrid electric/thermofluidic inputs for wet shape memory alloy actuators

NASA Astrophysics Data System (ADS)

Flemming, Leslie; Mascaro, Stephen

2013-01-01

A wet shape memory alloy (SMA) actuator is characterized by an SMA wire embedded within a compliant fluid-filled tube. Heating and cooling of the SMA wire produces a linear contraction and extension of the wire. Thermal energy can be transferred to and from the wire using combinations of resistive heating and free/forced convection. This paper analyzes the speed and efficiency of a simulated wet SMA actuator using a variety of control strategies involving different combinations of electrical and thermofluidic inputs. A computational fluid dynamics (CFD) model is used in conjunction with a temperature-strain model of the SMA wire to simulate the thermal response of the wire and compute strains, contraction/extension times and efficiency. The simulations produce cycle rates of up to 5 Hz for electrical heating and fluidic cooling, and up to 2 Hz for fluidic heating and cooling. The simulated results demonstrate efficiencies up to 0.5% for electric heating and up to 0.2% for fluidic heating. Using both electric and fluidic inputs concurrently improves the speed and efficiency of the actuator and allows for the actuator to remain contracted without continually delivering energy to the actuator, because of the thermal capacitance of the hot fluid. The characterized speeds and efficiencies are key requirements for implementing broader research efforts involving the intelligent control of electric and thermofluidic networks to optimize the speed and efficiency of wet actuator arrays.

Variations on a theme - the evolution of hydrocarbon solids. I. Compositional and spectral modelling - the eRCN and DG models

NASA Astrophysics Data System (ADS)

Jones, A. P.

2012-04-01

Context. The compositional properties of hydrogenated amorphous carbons are known to evolve in response to the local conditions. Aims: We present a model for low-temperature, amorphous hydrocarbon solids, based on the microphysical properties of random and defected networks of carbon and hydrogen atoms, that can be used to study and predict the evolution of their properties in the interstellar medium. Methods: We adopt an adaptable and prescriptive approach to model these materials, which is based on a random covalent network (RCN) model, extended here to a full compositional derivation (the eRCN model), and a defective graphite (DG) model for the hydrogen poorer materials where the eRCN model is no longer valid. Results: We provide simple expressions that enable the determination of the structural, infrared and spectral properties of amorphous hydrocarbon grains as a function of the hydrogen atomic fraction, XH. Structural annealing, resulting from hydrogen atom loss, results in a transition from H-rich, aliphatic-rich to H-poor, aromatic-rich materials. Conclusions: The model predicts changes in the optical properties of hydrogenated amorphous carbon dust in response to the likely UV photon-driven and/or thermal annealing processes resulting, principally, from the radiation field in the environment. We show how this dust component will evolve, compositionally and structurally in the interstellar medium in response to the local conditions. Appendices A and B are available in electronic form at http://www.aanda.org

A Comparative Study on Improved Arrhenius-Type and Artificial Neural Network Models to Predict High-Temperature Flow Behaviors in 20MnNiMo Alloy

PubMed Central

Yu, Chun-tang; Liu, Ying-ying; Xia, Yu-feng

2014-01-01

The stress-strain data of 20MnNiMo alloy were collected from a series of hot compressions on Gleeble-1500 thermal-mechanical simulator in the temperature range of 1173∼1473 K and strain rate range of 0.01∼10 s−1. Based on the experimental data, the improved Arrhenius-type constitutive model and the artificial neural network (ANN) model were established to predict the high temperature flow stress of as-cast 20MnNiMo alloy. The accuracy and reliability of the improved Arrhenius-type model and the trained ANN model were further evaluated in terms of the correlation coefficient (R), the average absolute relative error (AARE), and the relative error (η). For the former, R and AARE were found to be 0.9954 and 5.26%, respectively, while, for the latter, 0.9997 and 1.02%, respectively. The relative errors (η) of the improved Arrhenius-type model and the ANN model were, respectively, in the range of −39.99%∼35.05% and −3.77%∼16.74%. As for the former, only 16.3% of the test data set possesses η-values within ±1%, while, as for the latter, more than 79% possesses. The results indicate that the ANN model presents a higher predictable ability than the improved Arrhenius-type constitutive model. PMID:24688358

Dual percolation behaviors of electrical and thermal conductivity in metal-ceramic composites

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

Sun, K.; Zhang, Z. D.; Qian, L.

2016-02-08

The thermal and electrical properties including the permittivity spectra in radio frequency region were investigated for copper/yttrium iron garnet (Cu/YIG) composites. Interestingly, the percolation behaviors in electrical and thermal conductivity were obtained due to the formation of copper particles' networks. Beyond the electrical percolation threshold, negative permittivity was observed and plasmon frequency was reduced by several orders of magnitude. With the increase in copper content, the thermal conductivity was gradually increased; meanwhile, the phonon scattering effect and thermal resistance get enhanced, so the rate of increase in thermal conductivity gradually slows down. Hopefully, Cu/YIG composites with tunable electrical and thermalmore » properties have great potentials for electromagnetic interference shielding and electromagnetic wave attenuation.« less

Pyrolysis reaction networks for lignin model compounds: unraveling thermal deconstruction of β-O-4 and α-O-4 compounds

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

Choi, Yong S.; Singh, Rahul; Zhang, Jing

2016-01-01

Although lignin is one of the main components of biomass, its pyrolysis chemistry is not well understood due to complex heterogeneity. To gain insights into this chemistry, the pyrolysis of seven lignin model compounds (five ..beta..-O-4 and two ..alpha..-O-4 linked molecules) was investigated in a micropyrolyzer connected to GC-MS/FID. According to quantitative product mole balance for the reaction networks, concerted retro-ene fragmentation and homolytic dissociation were strongly suggested as the initial reaction step for ..beta..-O-4 compounds and ..alpha..-O-4 compounds, respectively. The difference in reaction pathway between compounds with different linkages was believed to result from thermodynamics of the radical initiation.more » The rate constants for the different reaction pathways were predicted from ab initio density functional theory calculations and pre-exponential literature values. The computational findings were consistent with the experiment results, further supporting the different pyrolysis mechanisms for the ..beta..-ether linked and ..alpha..-ether linked compounds. A combination of the two pathways from the dimeric model compounds was able to describe qualitatively the pyrolysis of a trimeric lignin model compound containing both ..beta..-O-4 and ..alpha..-O-4 linkages.« less

Correlating Free-Volume Hole Distribution to the Glass Transition Temperature of Epoxy Polymers.

PubMed

Aramoon, Amin; Breitzman, Timothy D; Woodward, Christopher; El-Awady, Jaafar A

2017-09-07

A new algorithm is developed to quantify the free-volume hole distribution and its evolution in coarse-grained molecular dynamics simulations of polymeric networks. This is achieved by analyzing the geometry of the network rather than a voxelized image of the structure to accurately and efficiently find and quantify free-volume hole distributions within large scale simulations of polymer networks. The free-volume holes are quantified by fitting the largest ellipsoids and spheres in the free-volumes between polymer chains. The free-volume hole distributions calculated from this algorithm are shown to be in excellent agreement with those measured from positron annihilation lifetime spectroscopy (PALS) experiments at different temperature and pressures. Based on the results predicted using this algorithm, an evolution model is proposed for the thermal behavior of an individual free-volume hole. This model is calibrated such that the average radius of free-volumes holes mimics the one predicted from the simulations. The model is then employed to predict the glass-transition temperature of epoxy polymers with different degrees of cross-linking and lengths of prepolymers. Comparison between the predicted glass-transition temperatures and those measured from simulations or experiments implies that this model is capable of successfully predicting the glass-transition temperature of the material using only a PDF of the initial free-volume holes radii of each microstructure. This provides an effective approach for the optimized design of polymeric systems on the basis of the glass-transition temperature, degree of cross-linking, and average length of prepolymers.

Feasibility of conducting wetfall chemistry investigations around the Bowen Power Plant

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

Chen, N.C.J.; Patrinos, A.A.N.

1979-10-01

The feasibility of expanding the Meteorological Effects of Thermal Energy Releases - Oak Ridge National Laboratory (METER-ORNL) research at Bower Power Plant, a coal-fired power plant in northwest Georgia, to include wetfall chemistry is evaluated using results of similar studies around other power plants, several atmospheric washout models, analysis of spatial variability in precipitation, and field logistical considerations. An optimal wetfall chemistry network design is proposed, incorporating the inner portion of the existing rain-gauge network and augmented by additional sites to ensure adequate coverage of probable target areas. The predicted sulfate production rate differs by about four orders of magnitudemore » among the models reviewed with a pH of 3. No model can claim superiority over any other model without substantive data verification. The spatial uniformity in rain amount is evaluated using four storms that occurred at the METER-ORNL network. Values of spatial variability ranged from 8 to 31% and decreased as the mean rainfall increased. The field study of wetfall chemistry will require a minimum of 5 persons to operate the approximately 50 collectors covering an area of 740 km/sup 2/. Preliminary wetfall-only samples collected on an event basis showed lower pH and higher electrical conductivity of precipitation collected about 5 km downwind of the power plant relative to samples collected upwind. Wetfall samples collected on a weekly basis using automatic samplers, however, showed variable results, with no consistent pattern. This suggests the need for event sampling to minimize variable rain volume and multiple-source effects often associated with weekly samples.« less

Integrating EarthScope Data to Constrain the Long-Term Effects of Tectonism on Continental Lithosphere

NASA Astrophysics Data System (ADS)

Porter, R. C.; van der Lee, S.

2017-12-01

One of the most significant products of the EarthScope experiment has been the development of new seismic tomography models that take advantage of the consistent station design, regular 70-km station spacing, and wide aperture of the EarthScope Transportable Array (TA) network. These models have led to the discovery and interpretation of additional compositional, thermal, and density anomalies throughout the continental US, especially within tectonically stable regions. The goal of this work is use data from the EarthScope experiment to better elucidate the temporal relationship between tectonic activity and seismic velocities. To accomplish this, we compile several upper-mantle seismic velocity models from the Incorporated Research Institute for Seismology (IRIS) Earth Model Collaboration (EMC) and compare these to a tectonic age model we compiled using geochemical ages from the Interdisciplinary Earth Data Alliance: EarthChem Database. Results from this work confirms quantitatively that the time elapsed since the most recent tectonic event is a dominant influence on seismic velocities within the upper mantle across North America. To further understand this relationship, we apply mineral-physics models for peridotite to estimate upper-mantle temperatures for the continental US from tomographically imaged shear velocities. This work shows that the relationship between the estimated temperatures and the time elapsed since the most recent tectonic event is broadly consistent with plate cooling models, yet shows intriguing scatter. Ultimately, this work constrains the long-term thermal evolution of continental mantle lithosphere.

Tailored semiconducting carbon nanotube networks with enhanced thermoelectric properties

DOE PAGES

Avery, Azure D.; Zhou, Ben H.; Lee, Jounghee; ...

2016-04-04

Thermoelectric power generation, allowing recovery of part of the energy wasted as heat, is emerging as an important component of renewable energy and energy efficiency portfolios. Although inorganic semiconductors have traditionally been employed in thermoelectric applications, organic semiconductors garner increasing attention as versatile thermoelectric materials. Here we present a combined theoretical and experimental study suggesting that semiconducting single-walled carbon nanotubes with carefully controlled chirality distribution and carrier density are capable of large thermoelectric power factors, higher than 340 μW m -1 K -2, comparable to the best-performing conducting polymers and larger than previously observed for carbon nanotube films. Furthermore, wemore » demonstrate that phonons are the dominant source of thermal conductivity in the networks, and that our carrier doping process significantly reduces the thermal conductivity relative to undoped networks. As a result, these findings provide the scientific underpinning for improved functional organic thermoelectric composites with carbon nanotube inclusions.« less

Tailored semiconducting carbon nanotube networks with enhanced thermoelectric properties

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

Avery, Azure D.; Zhou, Ben H.; Lee, Jounghee

Thermoelectric power generation, allowing recovery of part of the energy wasted as heat, is emerging as an important component of renewable energy and energy efficiency portfolios. Although inorganic semiconductors have traditionally been employed in thermoelectric applications, organic semiconductors garner increasing attention as versatile thermoelectric materials. Here we present a combined theoretical and experimental study suggesting that semiconducting single-walled carbon nanotubes with carefully controlled chirality distribution and carrier density are capable of large thermoelectric power factors, higher than 340 μW m -1 K -2, comparable to the best-performing conducting polymers and larger than previously observed for carbon nanotube films. Furthermore, wemore » demonstrate that phonons are the dominant source of thermal conductivity in the networks, and that our carrier doping process significantly reduces the thermal conductivity relative to undoped networks. As a result, these findings provide the scientific underpinning for improved functional organic thermoelectric composites with carbon nanotube inclusions.« less

Reducing the pollution risk of pesticide using nano networks induced by irradiation and hydrothermal treatment.

PubMed

Sun, Xiao; Liu, Zuojun; Zhang, Guilong; Qiu, Guannan; Zhong, Naiqin; Wu, Lifang; Cai, Dongqing; Wu, Zhengyan

2015-01-01

Traditional pesticides (TP) often do not adhere tightly to crop foliage. They can easily enter the surrounding environment through precipitation and volatilization. This can result in the pollution of the surrounding soil, water, and air. To reduce pesticide pollution, we developed a loss-control pesticide (LCP) by adding attapulgite with a nano networks structure fabricated using high energy electron beam (HEEB) irradiation and hydrothermal treatment to TP. HEEB irradiation effectively dispersed originally aggregated attapulgite through modified thermal, charge, and physical effects. Hydrothermal treatment further enhanced the dispersion of attapulgite to form nano porous networks via thermal and wet expansion effects, which are beneficial for pesticide binding. An LCP has improved retention on crop leaf surfaces. It has a higher adhesion capacity, reduced leaching and volatilization, and extended residual activity compared with the TP formulation. The treatment increases the residual activity of pesticides on crop foliage and decreases environmental pollution.

Investigation of co-combustion characteristics of sewage sludge and coffee grounds mixtures using thermogravimetric analysis coupled to artificial neural networks modeling.

PubMed

Chen, Jiacong; Liu, Jingyong; He, Yao; Huang, Limao; Sun, Shuiyu; Sun, Jian; Chang, KenLin; Kuo, Jiahong; Huang, Shaosong; Ning, Xunan

2017-02-01

Artificial neural network (ANN) modeling was applied to thermal data obtained by non-isothermal thermogravimetric analysis (TGA) from room temperature to 1000°C at three different heating rates in air to predict the TG curves of sewage sludge (SS) and coffee grounds (CG) mixtures. A good agreement between experimental and predicted data verified the accuracy of the ANN approach. The results of co-combustion showed that there were interactions between SS and CG, and the impacts were mostly positive. With the addition of CG, the mass loss rate and the reactivity of SS were increased while charring was reduced. Measured activation energies (E a ) determined by the Kissinger-Akahira-Sunose (KAS) and Ozawa-Flynn-Wall (OFW) methods deviated by <5%. The average value of E a (166.8kJ/mol by KAS and 168.8kJ/mol by OFW, respectively) was the lowest when the fraction of CG in the mixture was 40%. Copyright © 2016 Elsevier Ltd. All rights reserved.

Soil Moisture Content Estimation Based on Sentinel-1 and Auxiliary Earth Observation Products. A Hydrological Approach

PubMed Central

Alexakis, Dimitrios D.; Mexis, Filippos-Dimitrios K.; Vozinaki, Anthi-Eirini K.; Daliakopoulos, Ioannis N.; Tsanis, Ioannis K.

2017-01-01

A methodology for elaborating multi-temporal Sentinel-1 and Landsat 8 satellite images for estimating topsoil Soil Moisture Content (SMC) to support hydrological simulation studies is proposed. After pre-processing the remote sensing data, backscattering coefficient, Normalized Difference Vegetation Index (NDVI), thermal infrared temperature and incidence angle parameters are assessed for their potential to infer ground measurements of SMC, collected at the top 5 cm. A non-linear approach using Artificial Neural Networks (ANNs) is tested. The methodology is applied in Western Crete, Greece, where a SMC gauge network was deployed during 2015. The performance of the proposed algorithm is evaluated using leave-one-out cross validation and sensitivity analysis. ANNs prove to be the most efficient in SMC estimation yielding R2 values between 0.7 and 0.9. The proposed methodology is used to support a hydrological simulation with the HEC-HMS model, applied at the Keramianos basin which is ungauged for SMC. Results and model sensitivity highlight the contribution of combining Sentinel-1 SAR and Landsat 8 images for improving SMC estimates and supporting hydrological studies. PMID:28635625

Soil Moisture Content Estimation Based on Sentinel-1 and Auxiliary Earth Observation Products. A Hydrological Approach.

PubMed

Alexakis, Dimitrios D; Mexis, Filippos-Dimitrios K; Vozinaki, Anthi-Eirini K; Daliakopoulos, Ioannis N; Tsanis, Ioannis K

2017-06-21

A methodology for elaborating multi-temporal Sentinel-1 and Landsat 8 satellite images for estimating topsoil Soil Moisture Content (SMC) to support hydrological simulation studies is proposed. After pre-processing the remote sensing data, backscattering coefficient, Normalized Difference Vegetation Index (NDVI), thermal infrared temperature and incidence angle parameters are assessed for their potential to infer ground measurements of SMC, collected at the top 5 cm. A non-linear approach using Artificial Neural Networks (ANNs) is tested. The methodology is applied in Western Crete, Greece, where a SMC gauge network was deployed during 2015. The performance of the proposed algorithm is evaluated using leave-one-out cross validation and sensitivity analysis. ANNs prove to be the most efficient in SMC estimation yielding R² values between 0.7 and 0.9. The proposed methodology is used to support a hydrological simulation with the HEC-HMS model, applied at the Keramianos basin which is ungauged for SMC. Results and model sensitivity highlight the contribution of combining Sentinel-1 SAR and Landsat 8 images for improving SMC estimates and supporting hydrological studies.

Controlled manipulation of elastomers with radiation: Insights from multiquantum nuclear-magnetic-resonance data and mechanical measurements

NASA Astrophysics Data System (ADS)

Maiti, A.; Weisgraber, T.; Dinh, L. N.; Gee, R. H.; Wilson, T.; Chinn, S.; Maxwell, R. S.

2011-03-01

Filled and cross-linked elastomeric rubbers are versatile network materials with a multitude of applications ranging from artificial organs and biomedical devices to cushions, coatings, adhesives, interconnects, and seismic-isolation, thermal, and electrical barriers. External factors such as mechanical stress, temperature fluctuations, or radiation are known to create chemical changes in such materials that can directly affect the molecular weight distribution (MWD) of the polymer between cross-links and alter the structural and mechanical properties. From a materials science point of view it is highly desirable to understand, affect, and manipulate such property changes in a controlled manner. Unfortunately, that has not yet been possible due to the lack of experimental characterization of such networks under controlled environments. In this work we expose a known rubber material to controlled dosages of γ radiation and utilize a newly developed multiquantum nuclear-magnetic-resonance technique to characterize the MWD as a function of radiation. We show that such data along with mechanical stress-strain measurements are amenable to accurate analysis by simple network models and yield important insights into radiation-induced molecular-level processes.

Neural-Network Approach to Hyperspectral Data Analysis for Volcanic Ash Clouds Monitoring

NASA Astrophysics Data System (ADS)

Piscini, Alessandro; Ventress, Lucy; Carboni, Elisa; Grainger, Roy Gordon; Del Frate, Fabio

2015-11-01

In this study three artificial neural networks (ANN) were implemented in order to emulate a retrieval model and to estimate the ash Aerosol optical Depth (AOD), particle effective radius (reff) and cloud height from volcanic eruption using hyperspectral remotely sensed data. ANNs were trained using a selection of Infrared Atmospheric Sounding Interferometer (IASI) channels in Thermal Infrared (TIR) as inputs, and the corresponding ash parameters retrieved obtained using the Oxford retrievals as target outputs. The retrieval is demonstrated for the eruption of the Eyjafjallajo ̈kull volcano (Iceland) occurred in 2010. The results of validation provided root mean square error (RMSE) values between neural network outputs and targets lower than standard deviation (STD) of corresponding target outputs, therefore demonstrating the feasibility to estimate volcanic ash parameters using an ANN approach, and its importance in near real time monitoring activities, owing to its fast application. A high accuracy has been achieved for reff and cloud height estimation, while a decreasing in accuracy was obtained when applying the NN approach for AOD estimation, in particular for those values not well characterized during NN training phase.

Deep greedy learning under thermal variability in full diurnal cycles

NASA Astrophysics Data System (ADS)

Rauss, Patrick; Rosario, Dalton

2017-08-01

We study the generalization and scalability behavior of a deep belief network (DBN) applied to a challenging long-wave infrared hyperspectral dataset, consisting of radiance from several manmade and natural materials within a fixed site located 500 m from an observation tower. The collections cover multiple full diurnal cycles and include different atmospheric conditions. Using complementary priors, a DBN uses a greedy algorithm that can learn deep, directed belief networks one layer at a time and has two layers form to provide undirected associative memory. The greedy algorithm initializes a slower learning procedure, which fine-tunes the weights, using a contrastive version of the wake-sleep algorithm. After fine-tuning, a network with three hidden layers forms a very good generative model of the joint distribution of spectral data and their labels, despite significant data variability between and within classes due to environmental and temperature variation occurring within and between full diurnal cycles. We argue, however, that more questions than answers are raised regarding the generalization capacity of these deep nets through experiments aimed at investigating their training and augmented learning behavior.

DREAMING OF ATMOSPHERES

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

Waldmann, I. P., E-mail: ingo@star.ucl.ac.uk

Here, we introduce the RobERt (Robotic Exoplanet Recognition) algorithm for the classification of exoplanetary emission spectra. Spectral retrieval of exoplanetary atmospheres frequently requires the preselection of molecular/atomic opacities to be defined by the user. In the era of open-source, automated, and self-sufficient retrieval algorithms, manual input should be avoided. User dependent input could, in worst-case scenarios, lead to incomplete models and biases in the retrieval. The RobERt algorithm is based on deep-belief neural (DBN) networks trained to accurately recognize molecular signatures for a wide range of planets, atmospheric thermal profiles, and compositions. Reconstructions of the learned features, also referred to as themore » “dreams” of the network, indicate good convergence and an accurate representation of molecular features in the DBN. Using these deep neural networks, we work toward retrieval algorithms that themselves understand the nature of the observed spectra, are able to learn from current and past data, and make sensible qualitative preselections of atmospheric opacities to be used for the quantitative stage of the retrieval process.« less

Thermodynamics and mechanics of photochemcially reacting polymers

NASA Astrophysics Data System (ADS)

Long, Rong; Qi, H. Jerry; Dunn, Martin L.

2013-11-01

We develop a thermodynamics and mechanics theory for polymers that when irradiated with light, undergo photochemical reactions that alter their macromolecular structure, e.g., by bond breaking and/or reformation, and in turn affect their mechanical and physical behavior. This emerging class of highly-engineered active materials shows great promise for myriad applications and is a subset of a broader class of polymers with covalent bonds that can be dynamically tuned with various environmental stimuli. We formulate a general thermodynamic and kinetic framework to model the complex photochemical-thermal-mechanical coupling in these materials. Our theory considers the behavior of a polymer that is subjected to the combination of mechanical and thermal loading while simultaneously irradiated by light with multiple frequency components and directions. We introduce an approach to model the photochemical reactions that can change the network topology, resulting chemical species transport, heat conduction and finite deformation. We describe the interaction of the material with light via a radiometric description and show how it can be linked to a full electromagnetic treatment when appropriate and if desired. Our approach is sufficiently general to permit the modeling of various materials that operate via different photochemical reaction mechanisms. After formulating the general theory, we specialize it to a polymer that when irradiated with light undergoes a series of photochemical reactions that cause chain scission and reformation which continuously rearrange the polymer network into a stress-free configuration. Based on the operant physical mechanisms we develop a constitutive model using a polymer chain decomposition and evolution approach to track the molecular structure changes during simultaneous irradiation and mechanical loading. In the special case of isothermal conditions with monochromatic and unidirectional irradiation, we recover a previous model based on intuitive ad-hoc assumptions and thus put it on strong thermodynamic footing. Finally we use our model to simulate the behavior of a polymer that is biaxially stretched and then irradiated with light from one side. We simulate the process and emphasize the spontaneous bending that occurs due to inhomogeneous photoinduced stress relaxation. From our theory, we obtain an analytical expression of a characteristic time for photo-induced stress relaxation in terms of the dominating system parameters.

Learning phase transitions by confusion

NASA Astrophysics Data System (ADS)

van Nieuwenburg, Evert P. L.; Liu, Ye-Hua; Huber, Sebastian D.

2017-02-01

Classifying phases of matter is key to our understanding of many problems in physics. For quantum-mechanical systems in particular, the task can be daunting due to the exponentially large Hilbert space. With modern computing power and access to ever-larger data sets, classification problems are now routinely solved using machine-learning techniques. Here, we propose a neural-network approach to finding phase transitions, based on the performance of a neural network after it is trained with data that are deliberately labelled incorrectly. We demonstrate the success of this method on the topological phase transition in the Kitaev chain, the thermal phase transition in the classical Ising model, and the many-body-localization transition in a disordered quantum spin chain. Our method does not depend on order parameters, knowledge of the topological content of the phases, or any other specifics of the transition at hand. It therefore paves the way to the development of a generic tool for identifying unexplored phase transitions.

Learning phase transitions by confusion

NASA Astrophysics Data System (ADS)

van Nieuwenburg, Evert; Liu, Ye-Hua; Huber, Sebastian

Classifying phases of matter is a central problem in physics. For quantum mechanical systems, this task can be daunting owing to the exponentially large Hilbert space. Thanks to the available computing power and access to ever larger data sets, classification problems are now routinely solved using machine learning techniques. Here, we propose to use a neural network based approach to find transitions depending on the performance of the neural network after training it with deliberately incorrectly labelled data. We demonstrate the success of this method on the topological phase transition in the Kitaev chain, the thermal phase transition in the classical Ising model, and the many-body-localization transition in a disordered quantum spin chain. Our method does not depend on order parameters, knowledge of the topological content of the phases, or any other specifics of the transition at hand. It therefore paves the way to a generic tool to identify unexplored transitions.

A tensor network approach to many-body localization

NASA Astrophysics Data System (ADS)

Yu, Xiongjie; Pekker, David; Clark, Bryan

Understanding the many-body localized phase requires access to eigenstates in the middle of the many-body spectrum. While exact-diagonalization is able to access these eigenstates, it is restricted to systems sizes of about 22 spins. To overcome this limitation, we develop tensor network algorithms which increase the accessible system size by an order of magnitude. We describe both our new algorithms as well as the additional physics about MBL we can extract from them. For example, we demonstrate the power of these methods by verifying the breakdown of the Eigenstate Thermalization Hypothesis (ETH) in the many-body localized phase of the random field Heisenberg model, and show the saturation of entanglement in the MBL phase and generate eigenstates that differ by local excitations. Work was supported by AFOSR FA9550-10-1-0524 and FA9550-12-1-0057, the Kaufmann foundation, and SciDAC FG02-12ER46875.

A neural network controller for hydronic heating systems of solar buildings.

PubMed

Argiriou, Athanassios A; Bellas-Velidis, Ioannis; Kummert, Michaël; André, Philippe

2004-04-01

An artificial neural network (ANN)-based controller for hydronic heating plants of buildings is presented. The controller has forecasting capabilities: it includes a meteorological module, forecasting the ambient temperature and solar irradiance, an indoor temperature predictor module, a supply temperature predictor module and an optimizing module for the water supply temperature. All ANN modules are based on the Feed Forward Back Propagation (FFBP) model. The operation of the controller has been tested experimentally, on a real-scale office building during real operating conditions. The operation results were compared to those of a conventional controller. The performance was also assessed via numerical simulation. The detailed thermal simulation tool for solar systems and buildings TRNSYS was used. Both experimental and numerical results showed that the expected percentage of energy savings with respect to a conventional controller is of about 15% under North European weather conditions.

Combined TGA-MS kinetic analysis of multistep processes. Thermal decomposition and ceramification of polysilazane and polysiloxane preceramic polymers.

PubMed

García-Garrido, C; Sánchez-Jiménez, P E; Pérez-Maqueda, L A; Perejón, A; Criado, José M

2016-10-26

The polymer-to-ceramic transformation kinetics of two widely employed ceramic precursors, 1,3,5,7-tetramethyl-1,3,5,7-tetravinylcyclotetrasiloxane (TTCS) and polyureamethylvinylsilazane (CERASET), have been investigated using coupled thermogravimetry and mass spectrometry (TG-MS), Raman, XRD and FTIR. The thermally induced decomposition of the pre-ceramic polymer is the critical step in the synthesis of polymer derived ceramics (PDCs) and accurate kinetic modeling is key to attaining a complete understanding of the underlying process and to attempt any behavior predictions. However, obtaining a precise kinetic description of processes of such complexity, consisting of several largely overlapping physico-chemical processes comprising the cleavage of the starting polymeric network and the release of organic moieties, is extremely difficult. Here, by using the evolved gases detected by MS as a guide it has been possible to determine the number of steps that compose the overall process, which was subsequently resolved using a semiempirical deconvolution method based on the Frasier-Suzuki function. Such a function is more appropriate that the more usual Gaussian or Lorentzian functions since it takes into account the intrinsic asymmetry of kinetic curves. Then, the kinetic parameters of each constituent step were independently determined using both model-free and model-fitting procedures, and it was found that the processes obey mostly diffusion models which can be attributed to the diffusion of the released gases through the solid matrix. The validity of the obtained kinetic parameters was tested not only by the successful reconstruction of the original experimental curves, but also by predicting the kinetic curves of the overall processes yielded by different thermal schedules and by a mixed TTCS-CERASET precursor.

Physical modeling and characterization of thermo-acoustic loudspeakers made of silver nano-wire films

NASA Astrophysics Data System (ADS)

La Torraca, P.; Larcher, L.; Bobinger, M.; Pavan, P.; Seeber, B.; Lugli, P.

2017-06-01

Recent developments of ultra-low heat capacity nanostructured materials revived the interest in the thermo-acoustic (TA) loudspeaker technology, which shows important advantages compared to the classical dynamic loudspeakers as they feature a lower cost and weight, flexibility, conformability to the surface of various shapes, and transparency. The development of the TA loudspeaker technology requires accurate physical models connecting the material properties to the thermal and acoustic speaker's performance. We present here a combined theoretical and experimental analysis of TA loudspeakers, where the electro-thermal and the thermo-acoustic transductions are handled separately, thus allowing an in-depth description of both the pressure and temperature dynamics. The electro-thermal transduction is analyzed by accounting for all the heat flow processes taking place between the TA loudspeaker and the surrounding environment, with focus on their frequency dependence. The thermo-acoustic conversion is studied by solving the coupled thermo-acoustic equations, derived from the Navier-Stokes equations, and by exploiting the Huygens-Fresnel principle to decompose the TA loudspeaker surface into a dense set of TA point sources. A general formulation of the 3D pressure field is derived summing up the TA point source contributions via a Rayleigh integral. The model is validated against temperature and sound pressure level measured on the TA loudspeaker sample made of a Silver Nanowire random network deposited on a polyimide substrate. A good agreement is found between measurements and simulations, demonstrating that the model is capable of connecting material properties to the thermo-acoustic performance of the device, thus providing a valuable tool for the design and optimization of TA loudspeakers.

Experimental Investigation of A Heat Pipe-Assisted Latent Heat Thermal Energy Storage System

NASA Astrophysics Data System (ADS)

Tiari, Saeed; Mahdavi, Mahboobe; Qiu, Songgang

2016-11-01

In the present work, different operation modes of a latent heat thermal energy storage system assisted by a heat pipe network were studied experimentally. Rubitherm RT55 enclosed by a vertical cylindrical container was used as the Phase Change Material (PCM). The embedded heat pipe network consisting of a primary heat pipe and an array of four secondary heat pipes were employed to transfer heat to the PCM. The primary heat pipe transports heat from the heat source to the heat sink. The secondary heat pipes transfer the extra heat from the heat source to PCM during charging process or retrieve thermal energy from PCM during discharging process. The effects of heat transfer fluid (HTF) flow rate and temperature on the thermal performance of the system were investigated for both charging and discharging processes. It was found that the HTF flow rate has a significant effect on the total charging time of the system. Increasing the HTF flow rate results in a remarkable increase in the system input thermal power. The results also showed that the discharging process is hardly affected by the HTF flow rate but HTF temperature plays an important role in both charging and discharging processes. The authors would like to acknowledge the financial supports by Temple University for the project.

Global and Local Gravity Field Models of the Moon Using GRAIL Primary and Extended Mission Data

NASA Technical Reports Server (NTRS)

Goossens, Sander; Lemoine, Frank G.; Sabaka, Terence J.; Nicholas, Joseph B.; Mazarico, Erwan; Rowlands, David D.; Loomis, Bryant D.; Chinn, Douglas S.; Neumann, Gregory A.; Smith, David E.;

Performance of a Protected Wireless Sensor Network in a Fire. Analysis of Fire Spread and Data Transmission

PubMed Central

Antoine-Santoni, Thierry; Santucci, Jean-François; de Gentili, Emmanuelle; Silvani, Xavier; Morandini, Frederic

2009-01-01

The paper deals with a Wireless Sensor Network (WSN) as a reliable solution for capturing the kinematics of a fire front spreading over a fuel bed. To provide reliable information in fire studies and support fire fighting strategies, a Wireless Sensor Network must be able to perform three sequential actions: 1) sensing thermal data in the open as the gas temperature; 2) detecting a fire i.e., the spatial position of a flame; 3) tracking the fire spread during its spatial and temporal evolution. One of the great challenges in performing fire front tracking with a WSN is to avoid the destruction of motes by the fire. This paper therefore shows the performance of Wireless Sensor Network when the motes are protected with a thermal insulation dedicated to track a fire spreading across vegetative fuels on a field scale. The resulting experimental WSN is then used in series of wildfire experiments performed in the open in vegetation areas ranging in size from 50 to 1,000 m2. PMID:22454563

Performance of a protected wireless sensor network in a fire. Analysis of fire spread and data transmission.

PubMed

Antoine-Santoni, Thierry; Santucci, Jean-François; de Gentili, Emmanuelle; Silvani, Xavier; Morandini, Frederic

2009-01-01

The paper deals with a Wireless Sensor Network (WSN) as a reliable solution for capturing the kinematics of a fire front spreading over a fuel bed. To provide reliable information in fire studies and support fire fighting strategies, a Wireless Sensor Network must be able to perform three sequential actions: 1) sensing thermal data in the open as the gas temperature; 2) detecting a fire i.e., the spatial position of a flame; 3) tracking the fire spread during its spatial and temporal evolution. One of the great challenges in performing fire front tracking with a WSN is to avoid the destruction of motes by the fire. This paper therefore shows the performance of Wireless Sensor Network when the motes are protected with a thermal insulation dedicated to track a fire spreading across vegetative fuels on a field scale. The resulting experimental WSN is then used in series of wildfire experiments performed in the open in vegetation areas ranging in size from 50 to 1,000 m(2).

PCB-level Electro thermal Coupling Simulation Analysis

NASA Astrophysics Data System (ADS)

Zhou, Runjing; Shao, Xuchen

2017-10-01

Power transmission network needs to transmit more current with the increase of the power density. The problem of temperature rise and the reliability is becoming more and more serious. In order to accurately design the power supply system, we must consider the influence of the power supply system including Joule heat, air convection and other factors. Therefore, this paper analyzes the relationship between the electric circuit and the thermal circuit on the basis of the theory of electric circuit and thermal circuit.

Improvement of calculation method for electrical parameters of short network of ore-thermal furnaces

NASA Astrophysics Data System (ADS)

Aliferov, A. I.; Bikeev, R. A.; Goreva, L. P.

2017-10-01

The paper describes a new calculation method for active and inductive resistance of split interleaved current leads packages in ore-thermal electric furnaces. The method is developed on basis of regression analysis of dependencies of active and inductive resistances of the packages on their geometrical parameters, mutual disposition and interleaving pattern. These multi-parametric calculations have been performed with ANSYS software. The proposed method allows solving split current lead electrical parameters minimization and balancing problems for ore-thermal furnaces.

Mirrored continuum and molecular scale simulations of the ignition of gamma phase RDX

NASA Astrophysics Data System (ADS)

Stewart, D. Scott; Chaudhuri, Santanu; Joshi, Kaushik; Lee, Kibaek

2017-01-01

We describe the ignition of an explosive crystal of gamma-phase RDX due to a thermal hot spot with reactive molecular dynamics (RMD), with first-principles trained, reactive force field based molecular potentials that represents an extremely complex reaction network. The RMD simulation is analyzed by sorting molecular product fragments into high and low molecular weight groups, to represent identifiable components that can be interpreted by a continuum model. A continuum model based on a Gibbs formulation has a single temperature and stress state for the mixture. The continuum simulation that mirrors the atomistic simulation allows us to study the atomistic simulation in the familiar physical chemistry framework and provides an essential, continuum/atomistic link.

Assessment of the MHD capability in the ATHENA code using data from the ALEX (Argonne Liquid Metal Experiment) facility

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

Roth, P.A.

1988-10-28

The ATHENA (Advanced Thermal Hydraulic Energy Network Analyzer) code is a system transient analysis code with multi-loop, multi-fluid capabilities, which is available to the fusion community at the National Magnetic Fusion Energy Computing Center (NMFECC). The work reported here assesses the ATHENA magnetohydrodynamic (MHD) pressure drop model for liquid metals flowing through a strong magnetic field. An ATHENA model was developed for two simple geometry, adiabatic test sections used in the Argonne Liquid Metal Experiment (ALEX) at Argonne National Laboratory (ANL). The pressure drops calculated by ATHENA agreed well with the experimental results from the ALEX facility. 13 refs., 4more » figs., 2 tabs.« less

Remote Thermal Analysis Through the Internet

NASA Astrophysics Data System (ADS)

Malroy, Eric T.

2002-07-01

The Heater of the Hypersonic Tunnel Facility (HTF) was modeled using SINDA/FLUINT thermal software. A description of the model is given. The project presented the opportunity of interfacing the thermal model with the Internet and was a demonstration that complex analysis is possible through the Internet. Some of the issues that need to be addressed related to interfacing software with the Internet are the following: justification for using the Internet, selection of the web server, choice of the CGI language, security of the system, communication among the parties, maintenance of state between web pages, and simultaneous users on the Internet system. The opportunities available for using the Internet for analysis are many and can present a significant jump in technology. This paper presents a vision how interfacing with the Internet could develop in the future. Using a separate Optical Internet (OI) for analysis, coupled with virtual reality analysis rooms (VRAR), could provide a synergistic environment to couple together engineering analysis within industry, academia, and government. The process of analysis could be broken down into sub-components so that specialization could occur resulting in superior quality, minimized cost and reduced time for engineering analysis and manufacturing. Some possible subcomponents of the system are solver routines, databases, Graphical User Interfaces, engineering design software, VRARs, computer processing, CAD systems, manufacturing, and a plethora of other options only limited by ones imagination. On a larger scope, the specialization of companies on the optical network would allow companies to rapidly construct and reconstruct their infrastructure based on changing economic conditions. This could transform business.