The contribution of NOAA/CMDL ground-based measurements to understanding long-term stratospheric changes

NASA Astrophysics Data System (ADS)

Montzka, S. A.; Butler, J. H.; Dutton, G.; Thompson, T. M.; Hall, B.; Mondeel, D. J.; Elkins, J. W.

2005-05-01

The El-Nino/Southern-Oscillation (ENSO) dominates interannual climate variability and plays, therefore, a key role in seasonal-to-interannual prediction. Much is known by now about the main physical mechanisms that give rise to and modulate ENSO, but the values of several parameters that enter these mechanisms are an important unknown. We apply Extended Kalman Filtering (EKF) for both model state and parameter estimation in an intermediate, nonlinear, coupled ocean--atmosphere model of ENSO. The coupled model consists of an upper-ocean, reduced-gravity model of the Tropical Pacific and a steady-state atmospheric response to the sea surface temperature (SST). The model errors are assumed to be mainly in the atmospheric wind stress, and assimilated data are equatorial Pacific SSTs. Model behavior is very sensitive to two key parameters: (i) μ, the ocean-atmosphere coupling coefficient between SST and wind stress anomalies; and (ii) δs, the surface-layer coefficient. Previous work has shown that δs determines the period of the model's self-sustained oscillation, while μ measures the degree of nonlinearity. Depending on the values of these parameters, the spatio-temporal pattern of model solutions is either that of a delayed oscillator or of a westward propagating mode. Estimation of these parameters is tested first on synthetic data and allows us to recover the delayed-oscillator mode starting from model parameter values that correspond to the westward-propagating case. Assimilation of SST data from the NCEP-NCAR Reanalysis-2 shows that the parameters can vary on fairly short time scales and switch between values that approximate the two distinct modes of ENSO behavior. Rapid adjustments of these parameters occur, in particular, during strong ENSO events. Ways to apply EKF parameter estimation efficiently to state-of-the-art coupled ocean--atmosphere GCMs will be discussed.

Parameter estimation in a human operator describing function model for a two-dimensional tracking task

NASA Technical Reports Server (NTRS)

Vanlunteren, A.

1977-01-01

A previously described parameter estimation program was applied to a number of control tasks, each involving a human operator model consisting of more than one describing function. One of these experiments is treated in more detail. It consisted of a two dimensional tracking task with identical controlled elements. The tracking errors were presented on one display as two vertically moving horizontal lines. Each loop had its own manipulator. The two forcing functions were mutually independent and consisted each of 9 sine waves. A human operator model was chosen consisting of 4 describing functions, thus taking into account possible linear cross couplings. From the Fourier coefficients of the relevant signals the model parameters were estimated after alignment, averaging over a number of runs and decoupling. The results show that for the elements in the main loops the crossover model applies. A weak linear cross coupling existed with the same dynamics as the elements in the main loops but with a negative sign.

An estimation of the main wetting branch of the soil water retention curve based on its main drying branch using the machine learning method

NASA Astrophysics Data System (ADS)

Lamorski, Krzysztof; Šimūnek, Jiří; Sławiński, Cezary; Lamorska, Joanna

2017-02-01

In this paper, we estimated using the machine learning methodology the main wetting branch of the soil water retention curve based on the knowledge of the main drying branch and other, optional, basic soil characteristics (particle size distribution, bulk density, organic matter content, or soil specific surface). The support vector machine algorithm was used for the models' development. The data needed by this algorithm for model training and validation consisted of 104 different undisturbed soil core samples collected from the topsoil layer (A horizon) of different soil profiles in Poland. The main wetting and drying branches of SWRC, as well as other basic soil physical characteristics, were determined for all soil samples. Models relying on different sets of input parameters were developed and validated. The analysis showed that taking into account other input parameters (i.e., particle size distribution, bulk density, organic matter content, or soil specific surface) than information about the drying branch of the SWRC has essentially no impact on the models' estimations. Developed models are validated and compared with well-known models that can be used for the same purpose, such as the Mualem (1977) (M77) and Kool and Parker (1987) (KP87) models. The developed models estimate the main wetting SWRC branch with estimation errors (RMSE = 0.018 m3/m3) that are significantly lower than those for the M77 (RMSE = 0.025 m3/m3) or KP87 (RMSE = 0. 047 m3/m3) models.

Global optimization framework for solar building design

NASA Astrophysics Data System (ADS)

Silva, N.; Alves, N.; Pascoal-Faria, P.

2017-07-01

The generative modeling paradigm is a shift from static models to flexible models. It describes a modeling process using functions, methods and operators. The result is an algorithmic description of the construction process. Each evaluation of such an algorithm creates a model instance, which depends on its input parameters (width, height, volume, roof angle, orientation, location). These values are normally chosen according to aesthetic aspects and style. In this study, the model's parameters are automatically generated according to an objective function. A generative model can be optimized according to its parameters, in this way, the best solution for a constrained problem is determined. Besides the establishment of an overall framework design, this work consists on the identification of different building shapes and their main parameters, the creation of an algorithmic description for these main shapes and the formulation of the objective function, respecting a building's energy consumption (solar energy, heating and insulation). Additionally, the conception of an optimization pipeline, combining an energy calculation tool with a geometric scripting engine is presented. The methods developed leads to an automated and optimized 3D shape generation for the projected building (based on the desired conditions and according to specific constrains). The approach proposed will help in the construction of real buildings that account for less energy consumption and for a more sustainable world.

Thermal oil recovery method using self-contained windelectric sets

NASA Astrophysics Data System (ADS)

Belsky, A. A.; Korolyov, I. A.

2018-05-01

The paper reviews challenges associated with questions of efficiency of thermal methods of impact on productive oil strata. The concept of using electrothermal complexes with WEG power supply for the indicated purposes was proposed and justified, their operating principles, main advantages and disadvantages, as well as a schematechnical solution for the implementation of the intensification of oil extraction, were considered. A mathematical model for finding the operating characteristics of WEG is presented and its main energy parameters are determined. The adequacy of the mathematical model is confirmed by laboratory simulation stand tests with nominal parameters.

[Collaborative application of BEPS at different time steps.

PubMed

Lu, Wei; Fan, Wen Yi; Tian, Tian

2016-09-01

BEPSHourly is committed to simulate the ecological and physiological process of vegetation at hourly time steps, and is often applied to analyze the diurnal change of gross primary productivity (GPP), net primary productivity (NPP) at site scale because of its more complex model structure and time-consuming solving process. However, daily photosynthetic rate calculation in BEPSDaily model is simpler and less time-consuming, not involving many iterative processes. It is suitable for simulating the regional primary productivity and analyzing the spatial distribution of regional carbon sources and sinks. According to the characteristics and applicability of BEPSDaily and BEPSHourly models, this paper proposed a method of collaborative application of BEPS at daily and hourly time steps. Firstly, BEPSHourly was used to optimize the main photosynthetic parameters: the maximum rate of carboxylation (V c max ) and the maximum rate of photosynthetic electron transport (J max ) at site scale, and then the two optimized parameters were introduced into BEPSDaily model to estimate regional NPP at regional scale. The results showed that optimization of the main photosynthesis parameters based on the flux data could improve the simulate ability of the model. The primary productivity of different forest types in descending order was deciduous broad-leaved forest, mixed forest, coniferous forest in 2011. The collaborative application of carbon cycle models at different steps proposed in this study could effectively optimize the main photosynthesis parameters V c max and J max , simulate the monthly averaged diurnal GPP, NPP, calculate the regional NPP, and analyze the spatial distribution of regional carbon sources and sinks.

Assessing statistical differences between parameters estimates in Partial Least Squares path modeling.

PubMed

Rodríguez-Entrena, Macario; Schuberth, Florian; Gelhard, Carsten

2018-01-01

Structural equation modeling using partial least squares (PLS-SEM) has become a main-stream modeling approach in various disciplines. Nevertheless, prior literature still lacks a practical guidance on how to properly test for differences between parameter estimates. Whereas existing techniques such as parametric and non-parametric approaches in PLS multi-group analysis solely allow to assess differences between parameters that are estimated for different subpopulations, the study at hand introduces a technique that allows to also assess whether two parameter estimates that are derived from the same sample are statistically different. To illustrate this advancement to PLS-SEM, we particularly refer to a reduced version of the well-established technology acceptance model.

Stochastic mechanical model of vocal folds for producing jitter and for identifying pathologies through real voices.

PubMed

Cataldo, E; Soize, C

2018-06-06

Jitter, in voice production applications, is a random phenomenon characterized by the deviation of the glottal cycle length with respect to a mean value. Its study can help in identifying pathologies related to the vocal folds according to the values obtained through the different ways to measure it. This paper aims to propose a stochastic model, considering three control parameters, to generate jitter based on a deterministic one-mass model for the dynamics of the vocal folds and to identify parameters from the stochastic model taking into account real voice signals experimentally obtained. To solve the corresponding stochastic inverse problem, the cost function used is based on the distance between probability density functions of the random variables associated with the fundamental frequencies obtained by the experimental voices and the simulated ones, and also on the distance between features extracted from the voice signals, simulated and experimental, to calculate jitter. The results obtained show that the model proposed is valid and some samples of voices are synthesized considering the identified parameters for normal and pathological cases. The strategy adopted is also a novelty and mainly because a solution was obtained. In addition to the use of three parameters to construct the model of jitter, it is the discussion of a parameter related to the bandwidth of the power spectral density function of the stochastic process to measure the quality of the signal generated. A study about the influence of all the main parameters is also performed. The identification of the parameters of the model considering pathological cases is maybe of all novelties introduced by the paper the most interesting. Copyright © 2018 Elsevier Ltd. All rights reserved.

Regression analysis and transfer function in estimating the parameters of central pulse waves from brachial pulse wave.

PubMed

Chai Rui; Li Si-Man; Xu Li-Sheng; Yao Yang; Hao Li-Ling

2017-07-01

This study mainly analyzed the parameters such as ascending branch slope (A_slope), dicrotic notch height (Hn), diastolic area (Ad) and systolic area (As) diastolic blood pressure (DBP), systolic blood pressure (SBP), pulse pressure (PP), subendocardial viability ratio (SEVR), waveform parameter (k), stroke volume (SV), cardiac output (CO) and peripheral resistance (RS) of central pulse wave invasively and non-invasively measured. These parameters extracted from the central pulse wave invasively measured were compared with the parameters measured from the brachial pulse waves by a regression model and a transfer function model. The accuracy of the parameters which were estimated by the regression model and the transfer function model was compared too. Our findings showed that in addition to the k value, the above parameters of the central pulse wave and the brachial pulse wave invasively measured had positive correlation. Both the regression model parameters including A_slope, DBP, SEVR and the transfer function model parameters had good consistency with the parameters invasively measured, and they had the same effect of consistency. The regression equations of the three parameters were expressed by Y'=a+bx. The SBP, PP, SV, CO of central pulse wave could be calculated through the regression model, but their accuracies were worse than that of transfer function model.

Interpersonal distance modeling during fighting activities.

PubMed

Dietrich, Gilles; Bredin, Jonathan; Kerlirzin, Yves

2010-10-01

The aim of this article is to elaborate a general framework for modeling dual opposition activities, or more generally, dual interaction. The main hypothesis is that opposition behavior can be measured directly from a global variable and that the relative distance between the two subjects can be this parameter. Moreover, this parameter should be considered as multidimensional parameter depending not only on the dynamics of the subjects but also on the "internal" parameters of the subjects, such as sociological and/or emotional states. Standard and simple mechanical formalization will be used to model this multifactorial distance. To illustrate such a general modeling methodology, this model was compared with actual data from an opposition activity like Japanese fencing (kendo). This model captures not only coupled coordination, but more generally interaction in two-subject activities.

Development of wavelet-ANN models to predict water quality parameters in Hilo Bay, Pacific Ocean.

PubMed

Alizadeh, Mohamad Javad; Kavianpour, Mohamad Reza

2015-09-15

The main objective of this study is to apply artificial neural network (ANN) and wavelet-neural network (WNN) models for predicting a variety of ocean water quality parameters. In this regard, several water quality parameters in Hilo Bay, Pacific Ocean, are taken under consideration. Different combinations of water quality parameters are applied as input variables to predict daily values of salinity, temperature and DO as well as hourly values of DO. The results demonstrate that the WNN models are superior to the ANN models. Also, the hourly models developed for DO prediction outperform the daily models of DO. For the daily models, the most accurate model has R equal to 0.96, while for the hourly model it reaches up to 0.98. Overall, the results show the ability of the model to monitor the ocean parameters, in condition with missing data, or when regular measurement and monitoring are impossible. Copyright © 2015 Elsevier Ltd. All rights reserved.

Environmental Factors' Consideration at Industrial Transportation Organization in the «Seaport - Dry port» System

NASA Astrophysics Data System (ADS)

Muravev, Dmitri; Rakhmangulov, Aleksandr

2016-11-01

Currently, container shipping development is directly associated with an increase of warehouse areas for containers' storage. One of the most successful types of container terminal is an intermodal terminal called a dry port. Main pollution sources during the organization of intermodal transport are considered. A system of dry port parameters, which are recommended for the evaluation of different scenarios for a seaport infrastructure development at the stage of its strategic planning, is proposed in this paper. The authors have developed a method for determining the optimal values of the main dry port parameters by simulation modeling in the programming software Any- Logic. Dependencies thatwere obtained as a result of modeling experiments prove the adequacy of main selected dry port parameters for the effective scenarios' evaluation of throughput and handling capacity at existing seaports at the stage of strategic planning and a rational dry port location, allowed ensuring the improvement of the ecological situation in a port city.

Equivalent source modeling of the core magnetic field using magsat data

NASA Technical Reports Server (NTRS)

Mayhew, M. A.; Estes, R. H.

1983-01-01

Experiments are carried out on fitting the main field using different numbers of equivalent sources arranged in equal area at fixed radii at and inside the core-mantle boundary. In fixing the radius for a given series of runs, the convergence problems that result from the extreme nonlinearity of the problem when dipole positions are allowed to vary are avoided. Results are presented from a comparison between this approach and the standard spherical harmonic approach for modeling the main field in terms of accuracy and computational efficiency. The modeling of the main field with an equivalent dipole representation is found to be comparable to the standard spherical harmonic approach in accuracy. The 32 deg dipole density (42 dipoles) corresponds approximately to an eleventh degree/order spherical harmonic expansion (143 parameters), whereas the 21 dipole density (92 dipoles) corresponds to approximately a seventeenth degree and order expansion (323 parameters). It is pointed out that fixing the dipole positions results in rapid convergence of the dipole solutions for single-epoch models.

Effects of climate change on evapotranspiration over the Okavango Delta water resources

NASA Astrophysics Data System (ADS)

Moses, Oliver; Hambira, Wame L.

2018-06-01

In semi-arid developing countries, most poor people depend on contaminated surface or groundwater resources since they do not have access to safe and centrally supplied water. These water resources are threatened by several factors that include high evapotranspiration rates. In the Okavango Delta region in the north-western Botswana, communities facing insufficient centrally supplied water rely mainly on the surface water resources of the Delta. The Delta loses about 98% of its water through evapotranspiration. However, the 2% remaining water rescues the communities facing insufficient water from the main stream water supply. To understand the effects of climate change on evapotranspiration over the Okavango Delta water resources, this study analysed trends in the main climatic parameters needed as input variables in evapotranspiration models. The Mann Kendall test was used in the analysis. Trend analysis is crucial since it reveals the direction of trends in the climatic parameters, which is helpful in determining the effects of climate change on evapotranspiration. The main climatic parameters required as input variables in evapotranspiration models that were of interest in this study were wind speeds, solar radiation and relative humidity. Very little research has been conducted on these climatic parameters in the Okavango Delta region. The conducted trend analysis was more on wind speeds, which had relatively longer data records than the other two climatic parameters of interest. Generally, statistically significant increasing trends have been found, which suggests that climate change is likely to further increase evapotranspiration over the Okavango Delta water resources.

Attitude error response of structures to actuator/sensor noise

NASA Technical Reports Server (NTRS)

Balakrishnan, A. V.

1991-01-01

Explicit closed-form formulas are presented for the RMS attitude-error response to sensor and actuator noise for co-located actuators/sensors as a function of both control-gain parameters and structure parameters. The main point of departure is the use of continuum models. In particular the anisotropic Timoshenko model is used for lattice trusses typified by the NASA EPS Structure Model and the Evolutionary Model. One conclusion is that the maximum attainable improvement in the attitude error varying either structure parameters or control gains is 3 dB for the axial and torsion modes, the bending being essentially insensitive. The results are similar whether the Bernoulli model or the anisotropic Timoshenko model is used.

A Method for Modeling the Intrinsic Dynamics of Intraindividual Variability: Recovering the Parameters of Simulated Oscillators in Multi-Wave Panel Data.

ERIC Educational Resources Information Center

Boker, Steven M.; Nesselroade, John R.

2002-01-01

Examined two methods for fitting models of intrinsic dynamics to intraindividual variability data by testing these techniques' behavior in equations through simulation studies. Among the main results is the demonstration that a local linear approximation of derivatives can accurately recover the parameters of a simulated linear oscillator, with…

Lumped-parameters equivalent circuit for condenser microphones modeling.

PubMed

Esteves, Josué; Rufer, Libor; Ekeom, Didace; Basrour, Skandar

2017-10-01

This work presents a lumped parameters equivalent model of condenser microphone based on analogies between acoustic, mechanical, fluidic, and electrical domains. Parameters of the model were determined mainly through analytical relations and/or finite element method (FEM) simulations. Special attention was paid to the air gap modeling and to the use of proper boundary condition. Corresponding lumped-parameters were obtained as results of FEM simulations. Because of its simplicity, the model allows a fast simulation and is readily usable for microphone design. This work shows the validation of the equivalent circuit on three real cases of capacitive microphones, including both traditional and Micro-Electro-Mechanical Systems structures. In all cases, it has been demonstrated that the sensitivity and other related data obtained from the equivalent circuit are in very good agreement with available measurement data.

Probabilistic calibration of the distributed hydrological model RIBS applied to real-time flood forecasting: the Harod river basin case study (Israel)

NASA Astrophysics Data System (ADS)

Nesti, Alice; Mediero, Luis; Garrote, Luis; Caporali, Enrica

2010-05-01

An automatic probabilistic calibration method for distributed rainfall-runoff models is presented. The high number of parameters in hydrologic distributed models makes special demands on the optimization procedure to estimate model parameters. With the proposed technique it is possible to reduce the complexity of calibration while maintaining adequate model predictions. The first step of the calibration procedure of the main model parameters is done manually with the aim to identify their variation range. Afterwards a Monte-Carlo technique is applied, which consists on repetitive model simulations with randomly generated parameters. The Monte Carlo Analysis Toolbox (MCAT) includes a number of analysis methods to evaluate the results of these Monte Carlo parameter sampling experiments. The study investigates the use of a global sensitivity analysis as a screening tool to reduce the parametric dimensionality of multi-objective hydrological model calibration problems, while maximizing the information extracted from hydrological response data. The method is applied to the calibration of the RIBS flood forecasting model in the Harod river basin, placed on Israel. The Harod basin has an extension of 180 km2. The catchment has a Mediterranean climate and it is mainly characterized by a desert landscape, with a soil that is able to absorb large quantities of rainfall and at the same time is capable to generate high peaks of discharge. Radar rainfall data with 6 minute temporal resolution are available as input to the model. The aim of the study is the validation of the model for real-time flood forecasting, in order to evaluate the benefits of improved precipitation forecasting within the FLASH European project.

Uncertainty quantification of voice signal production mechanical model and experimental updating

NASA Astrophysics Data System (ADS)

Cataldo, E.; Soize, C.; Sampaio, R.

2013-11-01

The aim of this paper is to analyze the uncertainty quantification in a voice production mechanical model and update the probability density function corresponding to the tension parameter using the Bayes method and experimental data. Three parameters are considered uncertain in the voice production mechanical model used: the tension parameter, the neutral glottal area and the subglottal pressure. The tension parameter of the vocal folds is mainly responsible for the changing of the fundamental frequency of a voice signal, generated by a mechanical/mathematical model for producing voiced sounds. The three uncertain parameters are modeled by random variables. The probability density function related to the tension parameter is considered uniform and the probability density functions related to the neutral glottal area and the subglottal pressure are constructed using the Maximum Entropy Principle. The output of the stochastic computational model is the random voice signal and the Monte Carlo method is used to solve the stochastic equations allowing realizations of the random voice signals to be generated. For each realization of the random voice signal, the corresponding realization of the random fundamental frequency is calculated and the prior pdf of this random fundamental frequency is then estimated. Experimental data are available for the fundamental frequency and the posterior probability density function of the random tension parameter is then estimated using the Bayes method. In addition, an application is performed considering a case with a pathology in the vocal folds. The strategy developed here is important mainly due to two things. The first one is related to the possibility of updating the probability density function of a parameter, the tension parameter of the vocal folds, which cannot be measured direct and the second one is related to the construction of the likelihood function. In general, it is predefined using the known pdf. Here, it is constructed in a new and different manner, using the own system considered.

Discovery and characterization of 3000+ main-sequence binaries from APOGEE spectra

NASA Astrophysics Data System (ADS)

El-Badry, Kareem; Ting, Yuan-Sen; Rix, Hans-Walter; Quataert, Eliot; Weisz, Daniel R.; Cargile, Phillip; Conroy, Charlie; Hogg, David W.; Bergemann, Maria; Liu, Chao

2018-05-01

We develop a data-driven spectral model for identifying and characterizing spatially unresolved multiple-star systems and apply it to APOGEE DR13 spectra of main-sequence stars. Binaries and triples are identified as targets whose spectra can be significantly better fit by a superposition of two or three model spectra, drawn from the same isochrone, than any single-star model. From an initial sample of ˜20 000 main-sequence targets, we identify ˜2500 binaries in which both the primary and secondary stars contribute detectably to the spectrum, simultaneously fitting for the velocities and stellar parameters of both components. We additionally identify and fit ˜200 triple systems, as well as ˜700 velocity-variable systems in which the secondary does not contribute detectably to the spectrum. Our model simplifies the process of simultaneously fitting single- or multi-epoch spectra with composite models and does not depend on a velocity offset between the two components of a binary, making it sensitive to traditionally undetectable systems with periods of hundreds or thousands of years. In agreement with conventional expectations, almost all the spectrally identified binaries with measured parallaxes fall above the main sequence in the colour-magnitude diagram. We find excellent agreement between spectrally and dynamically inferred mass ratios for the ˜600 binaries in which a dynamical mass ratio can be measured from multi-epoch radial velocities. We obtain full orbital solutions for 64 systems, including 14 close binaries within hierarchical triples. We make available catalogues of stellar parameters, abundances, mass ratios, and orbital parameters.

Modeling seasonal variability of carbonate system parameters at the sediment -water interface in the Baltic Sea (Gdansk Deep)

NASA Astrophysics Data System (ADS)

Protsenko, Elizaveta; Yakubov, Shamil; Lessin, Gennady; Yakushev, Evgeniy; Sokołowski, Adam

2017-04-01

A one-dimensional fully-coupled benthic pelagic biogeochemical model BROM (Bottom RedOx Model) was used for simulations of seasonal variability of biogeochemical parameters in the upper sediment, Bottom Boundary Layer and the water column in the Gdansk Deep of the Baltic Sea. This model represents key biogeochemical processes of transformation of C, N, P, Si, O, S, Mn, Fe and the processes of vertical transport in the water column and the sediments. The hydrophysical block of BROM was forced by the output calculated with model GETM (General Estuarine Transport Model). In this study we focused on parameters of carbonate system at Baltic Sea, and mainly on their distributions near the sea-water interface. For validating of BROM we used field data (concentrations of main nutrients at water column and porewater of upper sediment) from the Gulf of Gdansk. The model allowed us to simulate the baseline ranges of seasonal variability of pH, Alkalinity, TIC and calcite/aragonite saturation as well as vertical fluxes of carbon in a region potentially selected for the CCS storage. This work was supported by project EEA CO2MARINE and STEMM-CCS.

Parameterization of the InVEST Crop Pollination Model to spatially predict abundance of wild blueberry (Vaccinium angustifolium Aiton) native bee pollinators in Maine, USA

USGS Publications Warehouse

Groff, Shannon C.; Loftin, Cynthia S.; Drummond, Frank; Bushmann, Sara; McGill, Brian J.

2016-01-01

Non-native honeybees historically have been managed for crop pollination, however, recent population declines draw attention to pollination services provided by native bees. We applied the InVEST Crop Pollination model, developed to predict native bee abundance from habitat resources, in Maine's wild blueberry crop landscape. We evaluated model performance with parameters informed by four approaches: 1) expert opinion; 2) sensitivity analysis; 3) sensitivity analysis informed model optimization; and, 4) simulated annealing (uninformed) model optimization. Uninformed optimization improved model performance by 29% compared to expert opinion-informed model, while sensitivity-analysis informed optimization improved model performance by 54%. This suggests that expert opinion may not result in the best parameter values for the InVEST model. The proportion of deciduous/mixed forest within 2000 m of a blueberry field also reliably predicted native bee abundance in blueberry fields, however, the InVEST model provides an efficient tool to estimate bee abundance beyond the field perimeter.

On justification of efficient Energy-Force parameters of Hydraulic-excavator main mechanisms

NASA Astrophysics Data System (ADS)

Komissarov, Anatoliy; Lagunova, Yuliya; Shestakov, Viktor; Lukashuk, Olga

2018-03-01

The article formulates requirements for energy-efficient designs of the operational equipment of a hydraulic excavator (its boom, stick and bucket) and defines, for a mechanism of that equipment, a new term “performance characteristic”. The drives of main rotation mechanisms of the equipment are realized by hydraulic actuators (hydraulic cylinders) and transmission (leverage) mechanisms, with the actuators (the cylinders themselves, their pistons and piston rods) also acting as links of the leverage. Those drives are characterized by the complexity of translating mechanical-energy parameters of the actuators into energy parameters of the driven links (a boom, a stick and a bucket). Relations between those parameters depend as much on the types of mechanical characteristics of the hydraulic actuators as on the types of structural schematics of the transmission mechanisms. To assess how energy-force parameters of the driven links change when a typical operation is performed, it was proposed to calculate performance characteristics of the main mechanisms as represented by a set of values of transfer functions, i.e. by functional dependences between driven links and driving links (actuators). Another term “ideal performance characteristic” of a mechanism was introduced. Based on operation-emulating models for the main mechanisms of hydraulic excavators, analytical expressions were derived to calculate kinematic and force transfer functions of the main mechanisms.

Models of Pilot Behavior and Their Use to Evaluate the State of Pilot Training

NASA Astrophysics Data System (ADS)

Jirgl, Miroslav; Jalovecky, Rudolf; Bradac, Zdenek

2016-07-01

This article discusses the possibilities of obtaining new information related to human behavior, namely the changes or progressive development of pilots' abilities during training. The main assumption is that a pilot's ability can be evaluated based on a corresponding behavioral model whose parameters are estimated using mathematical identification procedures. The mean values of the identified parameters are obtained via statistical methods. These parameters are then monitored and their changes evaluated. In this context, the paper introduces and examines relevant mathematical models of human (pilot) behavior, the pilot-aircraft interaction, and an example of the mathematical analysis.

Reduced-order modelling of parameter-dependent, linear and nonlinear dynamic partial differential equation models.

PubMed

Shah, A A; Xing, W W; Triantafyllidis, V

2017-04-01

In this paper, we develop reduced-order models for dynamic, parameter-dependent, linear and nonlinear partial differential equations using proper orthogonal decomposition (POD). The main challenges are to accurately and efficiently approximate the POD bases for new parameter values and, in the case of nonlinear problems, to efficiently handle the nonlinear terms. We use a Bayesian nonlinear regression approach to learn the snapshots of the solutions and the nonlinearities for new parameter values. Computational efficiency is ensured by using manifold learning to perform the emulation in a low-dimensional space. The accuracy of the method is demonstrated on a linear and a nonlinear example, with comparisons with a global basis approach.

Reduced-order modelling of parameter-dependent, linear and nonlinear dynamic partial differential equation models

PubMed Central

Xing, W. W.; Triantafyllidis, V.

2017-01-01

In this paper, we develop reduced-order models for dynamic, parameter-dependent, linear and nonlinear partial differential equations using proper orthogonal decomposition (POD). The main challenges are to accurately and efficiently approximate the POD bases for new parameter values and, in the case of nonlinear problems, to efficiently handle the nonlinear terms. We use a Bayesian nonlinear regression approach to learn the snapshots of the solutions and the nonlinearities for new parameter values. Computational efficiency is ensured by using manifold learning to perform the emulation in a low-dimensional space. The accuracy of the method is demonstrated on a linear and a nonlinear example, with comparisons with a global basis approach. PMID:28484327

Numerical modeling techniques for flood analysis

NASA Astrophysics Data System (ADS)

Anees, Mohd Talha; Abdullah, K.; Nawawi, M. N. M.; Ab Rahman, Nik Norulaini Nik; Piah, Abd. Rahni Mt.; Zakaria, Nor Azazi; Syakir, M. I.; Mohd. Omar, A. K.

2016-12-01

Topographic and climatic changes are the main causes of abrupt flooding in tropical areas. It is the need to find out exact causes and effects of these changes. Numerical modeling techniques plays a vital role for such studies due to their use of hydrological parameters which are strongly linked with topographic changes. In this review, some of the widely used models utilizing hydrological and river modeling parameters and their estimation in data sparse region are discussed. Shortcomings of 1D and 2D numerical models and the possible improvements over these models through 3D modeling are also discussed. It is found that the HEC-RAS and FLO 2D model are best in terms of economical and accurate flood analysis for river and floodplain modeling respectively. Limitations of FLO 2D in floodplain modeling mainly such as floodplain elevation differences and its vertical roughness in grids were found which can be improve through 3D model. Therefore, 3D model was found to be more suitable than 1D and 2D models in terms of vertical accuracy in grid cells. It was also found that 3D models for open channel flows already developed recently but not for floodplain. Hence, it was suggested that a 3D model for floodplain should be developed by considering all hydrological and high resolution topographic parameter's models, discussed in this review, to enhance the findings of causes and effects of flooding.

Optimizing pulsed Nd:YAG laser beam welding process parameters to attain maximum ultimate tensile strength for thin AISI316L sheet using response surface methodology and simulated annealing algorithm

NASA Astrophysics Data System (ADS)

Torabi, Amir; Kolahan, Farhad

2018-07-01

Pulsed laser welding is a powerful technique especially suitable for joining thin sheet metals. In this study, based on experimental data, pulsed laser welding of thin AISI316L austenitic stainless steel sheet has been modeled and optimized. The experimental data required for modeling are gathered as per Central Composite Design matrix in Response Surface Methodology (RSM) with full replication of 31 runs. Ultimate Tensile Strength (UTS) is considered as the main quality measure in laser welding. Furthermore, the important process parameters including peak power, pulse duration, pulse frequency and welding speed are selected as input process parameters. The relation between input parameters and the output response is established via full quadratic response surface regression with confidence level of 95%. The adequacy of the regression model was verified using Analysis of Variance technique results. The main effects of each factor and the interactions effects with other factors were analyzed graphically in contour and surface plot. Next, to maximum joint UTS, the best combinations of parameters levels were specified using RSM. Moreover, the mathematical model is implanted into a Simulated Annealing (SA) optimization algorithm to determine the optimal values of process parameters. The results obtained by both SA and RSM optimization techniques are in good agreement. The optimal parameters settings for peak power of 1800 W, pulse duration of 4.5 ms, frequency of 4.2 Hz and welding speed of 0.5 mm/s would result in a welded joint with 96% of the base metal UTS. Computational results clearly demonstrate that the proposed modeling and optimization procedures perform quite well for pulsed laser welding process.

Evaluating performances of simplified physically based landslide susceptibility models.

NASA Astrophysics Data System (ADS)

Capparelli, Giovanna; Formetta, Giuseppe; Versace, Pasquale

2015-04-01

Rainfall induced shallow landslides cause significant damages involving loss of life and properties. Prediction of shallow landslides susceptible locations is a complex task that involves many disciplines: hydrology, geotechnical science, geomorphology, and statistics. Usually to accomplish this task two main approaches are used: statistical or physically based model. This paper presents a package of GIS based models for landslide susceptibility analysis. It was integrated in the NewAge-JGrass hydrological model using the Object Modeling System (OMS) modeling framework. The package includes three simplified physically based models for landslides susceptibility analysis (M1, M2, and M3) and a component for models verifications. It computes eight goodness of fit indices (GOF) by comparing pixel-by-pixel model results and measurements data. Moreover, the package integration in NewAge-JGrass allows the use of other components such as geographic information system tools to manage inputs-output processes, and automatic calibration algorithms to estimate model parameters. The system offers the possibility to investigate and fairly compare the quality and the robustness of models and models parameters, according a procedure that includes: i) model parameters estimation by optimizing each of the GOF index separately, ii) models evaluation in the ROC plane by using each of the optimal parameter set, and iii) GOF robustness evaluation by assessing their sensitivity to the input parameter variation. This procedure was repeated for all three models. The system was applied for a case study in Calabria (Italy) along the Salerno-Reggio Calabria highway, between Cosenza and Altilia municipality. The analysis provided that among all the optimized indices and all the three models, Average Index (AI) optimization coupled with model M3 is the best modeling solution for our test case. This research was funded by PON Project No. 01_01503 "Integrated Systems for Hydrogeological Risk Monitoring, Early Warning and Mitigation Along the Main Lifelines", CUP B31H11000370005, in the framework of the National Operational Program for "Research and Competitiveness" 2007-2013.

Modeling and characteristic of the SMT Board Plug connector in high speed optical communication system

NASA Astrophysics Data System (ADS)

Wu, Haoran; Dong, Zhenzhen; Wang, Tanglin; Zhao, Heng; Feng, Junbo; Cui, Naidi; Teng, Jie; Guo, Jin

2015-04-01

Modeling and characteristic of the SMT Board Plug connector, which is used to connect micro optical transceiver to the main board, are proposed and analyzed in this paper. When the high speed signal transfers from the PCB of transceiver to main board through SMT Board Plug connector, the structure and material discontinuity of the connector causes insertion losses and impedance mismatches. This makes the performance of high speed digital system exacerbated. So it is essential to analyze the signal transfer characteristics of the connector and find out what factors affected the signal quality at the design stage of the digital system. To solve this problem, Ansoft's High Frequency Structure Simulator (HFSS), based on the finite element method, was employed to build accurate 3D models, analyze the effects of various structure parameters, and obtain the full-wave characteristics of the SMT Board Plug connectors in this paper. Then an equivalent circuit model was developed. The circuit parameters were extracted precisely in the frequency range of interests by using the curve fitting method in ADS software, and the result was in good agreement with HFSS simulations up to 8GHz with different structure parameters. At last, the measurement results of S-parameter and eye diagram were given and the S-parameters showed good coincidence between the measurement and HFSS simulation up to 4GHz.

Displacement-based back-analysis of the model parameters of the Nuozhadu high earth-rockfill dam.

PubMed

Wu, Yongkang; Yuan, Huina; Zhang, Bingyin; Zhang, Zongliang; Yu, Yuzhen

2014-01-01

The parameters of the constitutive model, the creep model, and the wetting model of materials of the Nuozhadu high earth-rockfill dam were back-analyzed together based on field monitoring displacement data by employing an intelligent back-analysis method. In this method, an artificial neural network is used as a substitute for time-consuming finite element analysis, and an evolutionary algorithm is applied for both network training and parameter optimization. To avoid simultaneous back-analysis of many parameters, the model parameters of the three main dam materials are decoupled and back-analyzed separately in a particular order. Displacement back-analyses were performed at different stages of the construction period, with and without considering the creep and wetting deformations. Good agreement between the numerical results and the monitoring data was obtained for most observation points, which implies that the back-analysis method and decoupling method are effective for solving complex problems with multiple models and parameters. The comparison of calculation results based on different sets of back-analyzed model parameters indicates the necessity of taking the effects of creep and wetting into consideration in the numerical analyses of high earth-rockfill dams. With the resulting model parameters, the stress and deformation distributions at completion are predicted and analyzed.

A robust observer based on H∞ filtering with parameter uncertainties combined with Neural Networks for estimation of vehicle roll angle

NASA Astrophysics Data System (ADS)

Boada, Beatriz L.; Boada, Maria Jesus L.; Vargas-Melendez, Leandro; Diaz, Vicente

2018-01-01

Nowadays, one of the main objectives in road transport is to decrease the number of accident victims. Rollover accidents caused nearly 33% of all deaths from passenger vehicle crashes. Roll Stability Control (RSC) systems prevent vehicles from untripped rollover accidents. The lateral load transfer is the main parameter which is taken into account in the RSC systems. This parameter is related to the roll angle, which can be directly measured from a dual-antenna GPS. Nevertheless, this is a costly technique. For this reason, roll angle has to be estimated. In this paper, a novel observer based on H∞ filtering in combination with a neural network (NN) for the vehicle roll angle estimation is proposed. The design of this observer is based on four main criteria: to use a simplified vehicle model, to use signals of sensors which are installed onboard in current vehicles, to consider the inaccuracy in the system model and to attenuate the effect of the external disturbances. Experimental results show the effectiveness of the proposed observer.

Main steam line break accident simulation of APR1400 using the model of ATLAS facility

NASA Astrophysics Data System (ADS)

Ekariansyah, A. S.; Deswandri; Sunaryo, Geni R.

2018-02-01

A main steam line break simulation for APR1400 as an advanced design of PWR has been performed using the RELAP5 code. The simulation was conducted in a model of thermal-hydraulic test facility called as ATLAS, which represents a scaled down facility of the APR1400 design. The main steam line break event is described in a open-access safety report document, in which initial conditions and assumptionsfor the analysis were utilized in performing the simulation and analysis of the selected parameter. The objective of this work was to conduct a benchmark activities by comparing the simulation results of the CESEC-III code as a conservative approach code with the results of RELAP5 as a best-estimate code. Based on the simulation results, a general similarity in the behavior of selected parameters was observed between the two codes. However the degree of accuracy still needs further research an analysis by comparing with the other best-estimate code. Uncertainties arising from the ATLAS model should be minimized by taking into account much more specific data in developing the APR1400 model.

Transitions induced by speed in self-propelled particles system with attractive interactions

NASA Astrophysics Data System (ADS)

Cambui, Dorilson. S.; Rosas, Alexandre

2018-05-01

In this work, we consider a system of self-propelled particles with attractive interactions in two dimensions. The model presents an order-disorder transition with the speed playing the role of the control parameter. In order to characterize the transition, we investigate the behavior of the order parameter and the Binder cumulant as a function of the speed. Our main finding is that the transition can be either continuous or discontinuous depending on two parameter of the model: the strength of the noise and the radius of attraction.

Combined Parameter and State Estimation Problem in a Complex Domain: RF Hyperthermia Treatment Using Nanoparticles

NASA Astrophysics Data System (ADS)

Bermeo Varon, L. A.; Orlande, H. R. B.; Eliçabe, G. E.

2016-09-01

The particle filter methods have been widely used to solve inverse problems with sequential Bayesian inference in dynamic models, simultaneously estimating sequential state variables and fixed model parameters. This methods are an approximation of sequences of probability distributions of interest, that using a large set of random samples, with presence uncertainties in the model, measurements and parameters. In this paper the main focus is the solution combined parameters and state estimation in the radiofrequency hyperthermia with nanoparticles in a complex domain. This domain contains different tissues like muscle, pancreas, lungs, small intestine and a tumor which is loaded iron oxide nanoparticles. The results indicated that excellent agreements between estimated and exact value are obtained.

Modeling the human body/seat system in a vibration environment.

PubMed

Rosen, Jacob; Arcan, Mircea

2003-04-01

The vibration environment is a common man-made artificial surrounding with which humans have a limited tolerance to cope due to their body dynamics. This research studied the dynamic characteristics of a seated human body/seat system in a vibration environment. The main result is a multi degrees of freedom lumped parameter model that synthesizes two basic dynamics: (i) global human dynamics, the apparent mass phenomenon, including a systematic set of the model parameters for simulating various conditions like body posture, backrest, footrest, muscle tension, and vibration directions, and (ii) the local human dynamics, represented by the human pelvis/vibrating seat contact, using a cushioning interface. The model and its selected parameters successfully described the main effects of the apparent mass phenomenon compared to experimental data documented in the literature. The model provided an analytical tool for human body dynamics research. It also enabled a primary tool for seat and cushioning design. The model was further used to develop design guidelines for a composite cushion using the principle of quasi-uniform body/seat contact force distribution. In terms of evenly distributing the contact forces, the best result for the different materials and cushion geometries simulated in the current study was achieved using a two layer shaped geometry cushion built from three materials. Combining the geometry and the mechanical characteristics of a structure under large deformation into a lumped parameter model enables successful analysis of the human/seat interface system and provides practical results for body protection in dynamic environment.

Identification of quasi-steady compressor characteristics from transient data

NASA Technical Reports Server (NTRS)

Nunes, K. B.; Rock, S. M.

1984-01-01

The principal goal was to demonstrate that nonlinear compressor map parameters, which govern an in-stall response, can be identified from test data using parameter identification techniques. The tasks included developing and then applying an identification procedure to data generated by NASA LeRC on a hybrid computer. Two levels of model detail were employed. First was a lumped compressor rig model; second was a simplified turbofan model. The main outputs are the tools and procedures generated to accomplish the identification.

Simulation of the Quantity, Variability, and Timing of Streamflow in the Dennys River Basin, Maine, by Use of a Precipitation-Runoff Watershed Model

USGS Publications Warehouse

Dudley, Robert W.

2008-01-01

The U.S. Geological Survey (USGS), in cooperation with the Maine Department of Marine Resources Bureau of Sea Run Fisheries and Habitat, began a study in 2004 to characterize the quantity, variability, and timing of streamflow in the Dennys River. The study included a synoptic summary of historical streamflow data at a long-term streamflow gage, collecting data from an additional four short-term streamflow gages, and the development and evaluation of a distributed-parameter watershed model for the Dennys River Basin. The watershed model used in this investigation was the USGS Precipitation-Runoff Modeling System (PRMS). The Geographic Information System (GIS) Weasel was used to delineate the Dennys River Basin and subbasins and derive parameters for their physical geographic features. Calibration of the models used in this investigation involved a four-step procedure in which model output was evaluated against four calibration data sets using computed objective functions for solar radiation, potential evapotranspiration, annual and seasonal water budgets, and daily streamflows. The calibration procedure involved thousands of model runs and was carried out using the USGS software application Luca (Let us calibrate). Luca uses the Shuffled Complex Evolution (SCE) global search algorithm to calibrate the model parameters. The SCE method reliably produces satisfactory solutions for large, complex optimization problems. The primary calibration effort went into the Dennys main stem watershed model. Calibrated parameter values obtained for the Dennys main stem model were transferred to the Cathance Stream model, and a similar four-step SCE calibration procedure was performed; this effort was undertaken to determine the potential to transfer modeling information to a nearby basin in the same region. The calibrated Dennys main stem watershed model performed with Nash-Sutcliffe efficiency (NSE) statistic values for the calibration period and evaluation period of 0.79 and 0.76, respectively. The Cathance Stream model had an NSE value of 0.68. The Dennys River Basin models make use of limited streamflow-gaging station data and provide information to characterize subbasin hydrology. The calibrated PRMS watershed models of the Dennys River Basin provide simulated daily streamflow time series from October 1, 1985, through September 30, 2006, for nearly any location within the basin. These models enable natural-resources managers to characterize the timing and quantity of water moving through the basin to support many endeavors including geochemical calculations, water-use assessment, Atlantic salmon population dynamics and migration modeling, habitat modeling and assessment, and other resource-management scenario evaluations. Characterizing streamflow contributions from subbasins in the basin and the relative amounts of surface- and ground-water contributions to streamflow throughout the basin will lead to a better understanding of water quantity and quality in the basin. Improved water-resources information will support Atlantic salmon protection efforts.

Simple Electrolyzer Model Development for High-Temperature Electrolysis System Analysis Using Solid Oxide Electrolysis Cell

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

JaeHwa Koh; DuckJoo Yoon; Chang H. Oh

2010-07-01

An electrolyzer model for the analysis of a hydrogen-production system using a solid oxide electrolysis cell (SOEC) has been developed, and the effects for principal parameters have been estimated by sensitivity studies based on the developed model. The main parameters considered are current density, area specific resistance, temperature, pressure, and molar fraction and flow rates in the inlet and outlet. Finally, a simple model for a high-temperature hydrogen-production system using the solid oxide electrolysis cell integrated with very high temperature reactors is estimated.

Predictive modeling of transient storage and nutrient uptake: Implications for stream restoration

USGS Publications Warehouse

O'Connor, Ben L.; Hondzo, Miki; Harvey, Judson W.

2010-01-01

This study examined two key aspects of reactive transport modeling for stream restoration purposes: the accuracy of the nutrient spiraling and transient storage models for quantifying reach-scale nutrient uptake, and the ability to quantify transport parameters using measurements and scaling techniques in order to improve upon traditional conservative tracer fitting methods. Nitrate (NO3–) uptake rates inferred using the nutrient spiraling model underestimated the total NO3– mass loss by 82%, which was attributed to the exclusion of dispersion and transient storage. The transient storage model was more accurate with respect to the NO3– mass loss (±20%) and also demonstrated that uptake in the main channel was more significant than in storage zones. Conservative tracer fitting was unable to produce transport parameter estimates for a riffle-pool transition of the study reach, while forward modeling of solute transport using measured/scaled transport parameters matched conservative tracer breakthrough curves for all reaches. Additionally, solute exchange between the main channel and embayment surface storage zones was quantified using first-order theory. These results demonstrate that it is vital to account for transient storage in quantifying nutrient uptake, and the continued development of measurement/scaling techniques is needed for reactive transport modeling of streams with complex hydraulic and geomorphic conditions.

Validation of DYSTOOL for unsteady aerodynamic modeling of 2D airfoils

NASA Astrophysics Data System (ADS)

González, A.; Gomez-Iradi, S.; Munduate, X.

2014-06-01

From the point of view of wind turbine modeling, an important group of tools is based on blade element momentum (BEM) theory using 2D aerodynamic calculations on the blade elements. Due to the importance of this sectional computation of the blades, the National Renewable Wind Energy Center of Spain (CENER) developed DYSTOOL, an aerodynamic code for 2D airfoil modeling based on the Beddoes-Leishman model. The main focus here is related to the model parameters, whose values depend on the airfoil or the operating conditions. In this work, the values of the parameters are adjusted using available experimental or CFD data. The present document is mainly related to the validation of the results of DYSTOOL for 2D airfoils. The results of the computations have been compared with unsteady experimental data of the S809 and NACA0015 profiles. Some of the cases have also been modeled using the CFD code WMB (Wind Multi Block), within the framework of a collaboration with ACCIONA Windpower. The validation has been performed using pitch oscillations with different reduced frequencies, Reynolds numbers, amplitudes and mean angles of attack. The results have shown a good agreement using the methodology of adjustment for the value of the parameters. DYSTOOL have demonstrated to be a promising tool for 2D airfoil unsteady aerodynamic modeling.

Iron and manganese removal: Recent advances in modelling treatment efficiency by rapid sand filtration.

PubMed

Vries, D; Bertelkamp, C; Schoonenberg Kegel, F; Hofs, B; Dusseldorp, J; Bruins, J H; de Vet, W; van den Akker, B

2017-02-01

A model has been developed that takes into account the main characteristics of (submerged) rapid filtration: the water quality parameters of the influent water, notably pH, iron(II) and manganese(II) concentrations, homogeneous oxidation in the supernatant layer, surface sorption and heterogeneous oxidation kinetics in the filter, and filter media adsorption characteristics. Simplifying assumptions are made to enable validation in practice, while maintaining the main mechanisms involved in iron(II) and manganese(II) removal. Adsorption isotherm data collected from different Dutch treatment sites show that Fe(II)/Mn(II) adsorption may vary substantially between them, but generally increases with higher pH. The model is sensitive to (experimentally) determined adsorption parameters and the heterogeneous oxidation rate. Model results coincide with experimental values when the heterogeneous rate constants are calibrated. Copyright © 2016 Elsevier Ltd. All rights reserved.

Model verification of mixed dynamic systems. [POGO problem in liquid propellant rockets

NASA Technical Reports Server (NTRS)

Chrostowski, J. D.; Evensen, D. A.; Hasselman, T. K.

1978-01-01

A parameter-estimation method is described for verifying the mathematical model of mixed (combined interactive components from various engineering fields) dynamic systems against pertinent experimental data. The model verification problem is divided into two separate parts: defining a proper model and evaluating the parameters of that model. The main idea is to use differences between measured and predicted behavior (response) to adjust automatically the key parameters of a model so as to minimize response differences. To achieve the goal of modeling flexibility, the method combines the convenience of automated matrix generation with the generality of direct matrix input. The equations of motion are treated in first-order form, allowing for nonsymmetric matrices, modeling of general networks, and complex-mode analysis. The effectiveness of the method is demonstrated for an example problem involving a complex hydraulic-mechanical system.

MAIN software for density averaging, model building, structure refinement and validation

PubMed Central

Turk, Dušan

2013-01-01

MAIN is software that has been designed to interactively perform the complex tasks of macromolecular crystal structure determination and validation. Using MAIN, it is possible to perform density modification, manual and semi-automated or automated model building and rebuilding, real- and reciprocal-space structure optimization and refinement, map calculations and various types of molecular structure validation. The prompt availability of various analytical tools and the immediate visualization of molecular and map objects allow a user to efficiently progress towards the completed refined structure. The extraordinary depth perception of molecular objects in three dimensions that is provided by MAIN is achieved by the clarity and contrast of colours and the smooth rotation of the displayed objects. MAIN allows simultaneous work on several molecular models and various crystal forms. The strength of MAIN lies in its manipulation of averaged density maps and molecular models when noncrystallographic symmetry (NCS) is present. Using MAIN, it is possible to optimize NCS parameters and envelopes and to refine the structure in single or multiple crystal forms. PMID:23897458

Retrospective forecast of ETAS model with daily parameters estimate

NASA Astrophysics Data System (ADS)

Falcone, Giuseppe; Murru, Maura; Console, Rodolfo; Marzocchi, Warner; Zhuang, Jiancang

2016-04-01

We present a retrospective ETAS (Epidemic Type of Aftershock Sequence) model based on the daily updating of free parameters during the background, the learning and the test phase of a seismic sequence. The idea was born after the 2011 Tohoku-Oki earthquake. The CSEP (Collaboratory for the Study of Earthquake Predictability) Center in Japan provided an appropriate testing benchmark for the five 1-day submitted models. Of all the models, only one was able to successfully predict the number of events that really happened. This result was verified using both the real time and the revised catalogs. The main cause of the failure was in the underestimation of the forecasted events, due to model parameters maintained fixed during the test. Moreover, the absence in the learning catalog of an event similar to the magnitude of the mainshock (M9.0), which drastically changed the seismicity in the area, made the learning parameters not suitable to describe the real seismicity. As an example of this methodological development we show the evolution of the model parameters during the last two strong seismic sequences in Italy: the 2009 L'Aquila and the 2012 Reggio Emilia episodes. The achievement of the model with daily updated parameters is compared with that of same model where the parameters remain fixed during the test time.

Calibration of a biome-biogeochemical cycles model for modeling the net primary production of teak forests through inverse modeling of remotely sensed data

NASA Astrophysics Data System (ADS)

Imvitthaya, Chomchid; Honda, Kiyoshi; Lertlum, Surat; Tangtham, Nipon

2011-01-01

In this paper, we present the results of a net primary production (NPP) modeling of teak (Tectona grandis Lin F.), an important species in tropical deciduous forests. The biome-biogeochemical cycles or Biome-BGC model was calibrated to estimate net NPP through the inverse modeling approach. A genetic algorithm (GA) was linked with Biome-BGC to determine the optimal ecophysiological model parameters. The Biome-BGC was calibrated by adjusting the ecophysiological model parameters to fit the simulated LAI to the satellite LAI (SPOT-Vegetation), and the best fitness confirmed the high accuracy of generated ecophysioligical parameter from GA. The modeled NPP, using optimized parameters from GA as input data, was evaluated using daily NPP derived by the MODIS satellite and the annual field data in northern Thailand. The results showed that NPP obtained using the optimized ecophysiological parameters were more accurate than those obtained using default literature parameterization. This improvement occurred mainly because the model's optimized parameters reduced the bias by reducing systematic underestimation in the model. These Biome-BGC results can be effectively applied in teak forests in tropical areas. The study proposes a more effective method of using GA to determine ecophysiological parameters at the site level and represents a first step toward the analysis of the carbon budget of teak plantations at the regional scale.

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

Duane, Greg; Tsonis, Anastasios; Kocarev, Ljupco

This collaborative reserach has several components but the main idea is that when imperfect copies of a given nonlinear dynamical system are coupled, they may synchronize for some set of coupling parameters. This idea is to be tested for several IPCC-like models each one with its own formulation and representing an “imperfect” copy of the true climate system. By computing the coupling parameters, which will lead the models to a synchronized state, a consensus on climate change simulations may be achieved.

Flight test planning and parameter extraction for rotorcraft system identification

NASA Technical Reports Server (NTRS)

Wang, J. C.; Demiroz, M. Y.; Talbot, P. D.

1986-01-01

The present study is concerned with the mathematical modelling of aircraft dynamics on the basis of an investigation conducted with the aid of the Rotor System Research Aircraft (RSRA). The particular characteristics of RSRA make it possible to investigate aircraft properties which cannot be readily studied elsewhere, for example in the wind tunnel. The considered experiment had mainly the objective to develop an improved understanding of the physics of rotor flapping dynamics and rotor loads in maneuvers. The employed approach is based on a utilization of parameter identification methodology (PID) with application to helicopters. A better understanding of the contribution of the main rotor to the overall aircraft forces and moments is also to be obtained. Attention is given to the mathematical model of a rotorcraft system, an integrated identification method, flight data processing, and the identification of RSRA mathematical models.

A methodology for global-sensitivity analysis of time-dependent outputs in systems biology modelling.

PubMed

Sumner, T; Shephard, E; Bogle, I D L

2012-09-07

One of the main challenges in the development of mathematical and computational models of biological systems is the precise estimation of parameter values. Understanding the effects of uncertainties in parameter values on model behaviour is crucial to the successful use of these models. Global sensitivity analysis (SA) can be used to quantify the variability in model predictions resulting from the uncertainty in multiple parameters and to shed light on the biological mechanisms driving system behaviour. We present a new methodology for global SA in systems biology which is computationally efficient and can be used to identify the key parameters and their interactions which drive the dynamic behaviour of a complex biological model. The approach combines functional principal component analysis with established global SA techniques. The methodology is applied to a model of the insulin signalling pathway, defects of which are a major cause of type 2 diabetes and a number of key features of the system are identified.

Study on residual stresses in ultrasonic torsional vibration assisted micro-milling

NASA Astrophysics Data System (ADS)

Lu, Zesheng; Hu, Haijun; Sun, Yazhou; Sun, Qing

2010-10-01

It is well known that machining induced residual stresses can seriously affect the dimensional accuracy, corrosion and wear resistance, etc., and further influence the longevity and reliability of Micro-Optical Components (MOC). In Ultrasonic Torsional Vibration Assisted Micro-milling (UTVAM), cutting parameters, vibration parameters, mill cutter parameters, the status of wear length of tool flank are the main factors which affect residual stresses. A 2D model of UTVAM was established with FE analysis software ABAQUS. Johnson-Cook's flow stress model and shear failure principle are used as the workpiece material model and failure principle, while friction between tool and workpiece uses modified Coulomb's law whose sliding friction area is combined with sticking friction. By means of FEA, the influence rules of cutting parameters, vibration parameters, mill cutter parameters, the status of wear length of tool flank on residual stresses are obtained, which provides a basis for choosing optimal process parameters and improving the longevity and reliability of MOC.

Optimal control problems of epidemic systems with parameter uncertainties: application to a malaria two-age-classes transmission model with asymptomatic carriers.

PubMed

Mwanga, Gasper G; Haario, Heikki; Capasso, Vicenzo

2015-03-01

The main scope of this paper is to study the optimal control practices of malaria, by discussing the implementation of a catalog of optimal control strategies in presence of parameter uncertainties, which is typical of infectious diseases data. In this study we focus on a deterministic mathematical model for the transmission of malaria, including in particular asymptomatic carriers and two age classes in the human population. A partial qualitative analysis of the relevant ODE system has been carried out, leading to a realistic threshold parameter. For the deterministic model under consideration, four possible control strategies have been analyzed: the use of Long-lasting treated mosquito nets, indoor residual spraying, screening and treatment of symptomatic and asymptomatic individuals. The numerical results show that using optimal control the disease can be brought to a stable disease free equilibrium when all four controls are used. The Incremental Cost-Effectiveness Ratio (ICER) for all possible combinations of the disease-control measures is determined. The numerical simulations of the optimal control in the presence of parameter uncertainty demonstrate the robustness of the optimal control: the main conclusions of the optimal control remain unchanged, even if inevitable variability remains in the control profiles. The results provide a promising framework for the designing of cost-effective strategies for disease controls with multiple interventions, even under considerable uncertainty of model parameters. Copyright © 2014 Elsevier Inc. All rights reserved.

Structural dynamic analysis of the Space Shuttle Main Engine

NASA Technical Reports Server (NTRS)

Scott, L. P.; Jamison, G. T.; Mccutcheon, W. A.; Price, J. M.

1981-01-01

This structural dynamic analysis supports development of the SSME by evaluating components subjected to critical dynamic loads, identifying significant parameters, and evaluating solution methods. Engine operating parameters at both rated and full power levels are considered. Detailed structural dynamic analyses of operationally critical and life limited components support the assessment of engine design modifications and environmental changes. Engine system test results are utilized to verify analytic model simulations. The SSME main chamber injector assembly is an assembly of 600 injector elements which are called LOX posts. The overall LOX post analysis procedure is shown.

Understanding Coupling of Global and Diffuse Solar Radiation with Climatic Variability

NASA Astrophysics Data System (ADS)

Hamdan, Lubna

Global solar radiation data is very important for wide variety of applications and scientific studies. However, this data is not readily available because of the cost of measuring equipment and the tedious maintenance and calibration requirements. Wide variety of models have been introduced by researchers to estimate and/or predict the global solar radiations and its components (direct and diffuse radiation) using other readily obtainable atmospheric parameters. The goal of this research is to understand the coupling of global and diffuse solar radiation with climatic variability, by investigating the relationships between these radiations and atmospheric parameters. For this purpose, we applied multilinear regression analysis on the data of National Solar Radiation Database 1991--2010 Update. The analysis showed that the main atmospheric parameters that affect the amount of global radiation received on earth's surface are cloud cover and relative humidity. Global radiation correlates negatively with both variables. Linear models are excellent approximations for the relationship between atmospheric parameters and global radiation. A linear model with the predictors total cloud cover, relative humidity, and extraterrestrial radiation is able to explain around 98% of the variability in global radiation. For diffuse radiation, the analysis showed that the main atmospheric parameters that affect the amount received on earth's surface are cloud cover and aerosol optical depth. Diffuse radiation correlates positively with both variables. Linear models are very good approximations for the relationship between atmospheric parameters and diffuse radiation. A linear model with the predictors total cloud cover, aerosol optical depth, and extraterrestrial radiation is able to explain around 91% of the variability in diffuse radiation. Prediction analysis showed that the linear models we fitted were able to predict diffuse radiation with efficiency of test adjusted R2 values equal to 0.93, using the data of total cloud cover, aerosol optical depth, relative humidity and extraterrestrial radiation. However, for prediction purposes, using nonlinear terms or nonlinear models might enhance the prediction of diffuse radiation.

A strong correlation between induced peak dynamic Coulomb stress change from the 1992 M7.3 Landers, California, earthquake and the hypocenter of the 1999 M7.1 Hector Mine, California, earthquake

NASA Astrophysics Data System (ADS)

Kilb, Debi

2003-01-01

The 1992 M7.3 Landers earthquake may have played a role in triggering the 1999 M7.1 Hector Mine earthquake as suggested by their close spatial (˜20 km) proximity. Current investigations of triggering by static stress changes produce differing conclusions when small variations in parameter values are employed. Here I test the hypothesis that large-amplitude dynamic stress changes, induced by the Landers rupture, acted to promote the Hector Mine earthquake. I use a flat layer reflectivity method to model the Landers earthquake displacement seismograms. By requiring agreement between the model seismograms and data, I can constrain the Landers main shock parameters and velocity model. A similar reflectivity method is used to compute the evolution of stress changes. I find a strong positive correlation between the Hector Mine hypocenter and regions of large (>4 MPa) dynamic Coulomb stress changes (peak Δσf(t)) induced by the Landers main shock. A positive correlation is also found with large dynamic normal and shear stress changes. Uncertainties in peak Δσf(t) (1.3 MPa) are only 28% of the median value (4.6 MPa) determined from an extensive set (160) of model parameters. Therefore the correlation with dynamic stresses is robust to a range of Hector Mine main shock parameters, as well as to variations in the friction and Skempton's coefficients used in the calculations. These results imply dynamic stress changes may be an important part of earthquake trigging, such that large-amplitude stress changes alter the properties of an existing fault in a way that promotes fault failure.

A new model for in situ nitrogen incorporation into 4H-SiC during epitaxy

PubMed Central

Ferro, Gabriel; Chaussende, Didier

2017-01-01

Nitrogen doping of 4H-SiC during vapor phase epitaxy is still lacking of a general model explaining the apparently contradictory trends obtained by different teams. In this paper, the evolutions of nitrogen incorporation (on both polar Si and C faces) as a function of the main growth parameters (C/Si ratio, temperature, pressure and growth rate) are reviewed and explained using a model based on surface exchanges between the gas phase and the uppermost 4H-SiC atomic layers. In this model, N incorporation is driven mainly by the transient formation of C vacancies, due to H2 etching, at the surface or near the surface. It is shown that all the growth parameters are influencing the probability of C vacancies formation in a similar manner as they do for N incorporation. The surface exchange model proposes a new framework for explaining the experimental results even beyond the commonly accepted reactor type dependency. PMID:28211528

Modeling of Waves Propagating in Water with a Crushed Ice Layer on the Free Surface

NASA Astrophysics Data System (ADS)

Szmidt, Kazimierz

2017-12-01

A transformation of gravitational waves in fluid of constant depth with a crushed ice layer floating on the free fluid surface is considered. The propagating waves undergo a slight damping along their path of propagation. The main goal of the study is to construct an approximate descriptive model of this phenomenon.With regard to small displacements of the free surface, a viscous type model of damping is considered, which corresponds to a continuous distribution of dash-pots at the free surface of the fluid. A constant parameter of the dampers is assumed in advance as known parameter of damping. This parameter may be obtained by means of experiments in a laboratory flume.

Parameters estimation using the first passage times method in a jump-diffusion model

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

Khaldi, K., E-mail: kkhaldi@umbb.dz; LIMOSE Laboratory, Boumerdes University, 35000; Meddahi, S., E-mail: samia.meddahi@gmail.com

2016-06-02

The main purposes of this paper are two contributions: (1) it presents a new method, which is the first passage time (FPT method) generalized for all passage times (GPT method), in order to estimate the parameters of stochastic Jump-Diffusion process. (2) it compares in a time series model, share price of gold, the empirical results of the estimation and forecasts obtained with the GPT method and those obtained by the moments method and the FPT method applied to the Merton Jump-Diffusion (MJD) model.

The Influence of Atmosphere Parameters on the Signal for Remote Sensing Polarimetric Electro-Optical Systems

NASA Astrophysics Data System (ADS)

Budak, Vladimir P.; Korkin, Sergey V.

2009-03-01

The singularity subtraction on the vectorial modification of spherical harmonics method (VMSH) of the solution of the vectorial radiative transfer equation boundary problem is applied to the problem of influence of atmosphere parameters on the polarimetric system signal. We assume in this model different phase matrices (Mie, Rayleigh, and Henyey-Greenstein), reflecting bottom and particle size distribution. The authors describe the main features of the model and some results of its implementation.

Mechanical performance and parameter sensitivity analysis of 3D braided composites joints.

PubMed

Wu, Yue; Nan, Bo; Chen, Liang

2014-01-01

3D braided composite joints are the important components in CFRP truss, which have significant influence on the reliability and lightweight of structures. To investigate the mechanical performance of 3D braided composite joints, a numerical method based on the microscopic mechanics is put forward, the modeling technologies, including the material constants selection, element type, grid size, and the boundary conditions, are discussed in detail. Secondly, a method for determination of ultimate bearing capacity is established, which can consider the strength failure. Finally, the effect of load parameters, geometric parameters, and process parameters on the ultimate bearing capacity of joints is analyzed by the global sensitivity analysis method. The results show that the main pipe diameter thickness ratio γ, the main pipe diameter D, and the braided angle α are sensitive to the ultimate bearing capacity N.

Laser welding of polymers: phenomenological model for a quick and reliable process quality estimation considering beam shape influences

NASA Astrophysics Data System (ADS)

Timpe, Nathalie F.; Stuch, Julia; Scholl, Marcus; Russek, Ulrich A.

2016-03-01

This contribution presents a phenomenological, analytical model for laser welding of polymers which is suited for a quick process quality estimation for the practitioner. Besides material properties of the polymer and processing parameters like welding pressure, feed rate and laser power the model is based on a simple few parameter description of the size and shape of the laser power density distribution (PDD) in the processing zone. The model allows an estimation of the weld seam tensile strength. It is based on energy balance considerations within a thin sheet with the thickness of the optical penetration depth on the surface of the absorbing welding partner. The joining process itself is modelled by a phenomenological approach. The model reproduces the experimentally known process windows for the main process parameters correctly. Using the parameters describing the shape of the laser PDD the critical dependence of the process windows on the PDD shape will be predicted and compared with experiments. The adaption of the model to other laser manufacturing processes where the PDD influence can be modelled comparably will be discussed.

Comparison of Two Global Sensitivity Analysis Methods for Hydrologic Modeling over the Columbia River Basin

NASA Astrophysics Data System (ADS)

Hameed, M.; Demirel, M. C.; Moradkhani, H.

2015-12-01

Global Sensitivity Analysis (GSA) approach helps identify the effectiveness of model parameters or inputs and thus provides essential information about the model performance. In this study, the effects of the Sacramento Soil Moisture Accounting (SAC-SMA) model parameters, forcing data, and initial conditions are analysed by using two GSA methods: Sobol' and Fourier Amplitude Sensitivity Test (FAST). The simulations are carried out over five sub-basins within the Columbia River Basin (CRB) for three different periods: one-year, four-year, and seven-year. Four factors are considered and evaluated by using the two sensitivity analysis methods: the simulation length, parameter range, model initial conditions, and the reliability of the global sensitivity analysis methods. The reliability of the sensitivity analysis results is compared based on 1) the agreement between the two sensitivity analysis methods (Sobol' and FAST) in terms of highlighting the same parameters or input as the most influential parameters or input and 2) how the methods are cohered in ranking these sensitive parameters under the same conditions (sub-basins and simulation length). The results show the coherence between the Sobol' and FAST sensitivity analysis methods. Additionally, it is found that FAST method is sufficient to evaluate the main effects of the model parameters and inputs. Another conclusion of this study is that the smaller parameter or initial condition ranges, the more consistency and coherence between the sensitivity analysis methods results.

A 3D Visualization and Analysis Model of the Earth Orbit, Milankovitch Cycles and Insolation.

NASA Astrophysics Data System (ADS)

Kostadinov, Tihomir; Gilb, Roy

2013-04-01

Milankovitch theory postulates that periodic variability of Earth's orbital elements is a major climate forcing mechanism. Although controversies remain, ample geologic evidence supports the major role of the Milankovitch cycles in climate, e.g. glacial-interglacial cycles. There are three Milankovitch orbital parameters: orbital eccentricity (main periodicities of ~100,000 and ~400,000 years), precession (quantified as the longitude of perihelion, main periodicities 19,000-24,000 years) and obliquity of the ecliptic (Earth's axial tilt, main periodicity 41,000 years). The combination of these parameters controls the spatio-temporal patterns of incoming solar radiation (insolation) and the timing of the seasons with respect to perihelion, as well as season duration. The complex interplay of the Milankovitch orbital parameters on various time scales makes assessment and visualization of Earth's orbit and insolation variability challenging. It is difficult to appreciate the pivotal importance of Kepler's laws of planetary motion in controlling the effects of Milankovitch cycles on insolation patterns. These factors also make Earth-Sun geometry and Milankovitch theory difficult to teach effectively. Here, an astronomically precise and accurate Earth orbit visualization model is presented. The model offers 3D visualizations of Earth's orbital geometry, Milankovitch parameters and the ensuing insolation forcings. Both research and educational uses are envisioned for the model, which is developed in Matlab® as a user-friendly graphical user interface (GUI). We present the user with a choice between the Berger et al. (1978) and Laskar et al. (2004) astronomical solutions for eccentricity, obliquity and precession. A "demo" mode is also available, which allows the three Milankovitch parameters to be varied independently of each other (and over much larger ranges than the naturally occurring ones), so the user can isolate the effects of each parameter on orbital geometry, the seasons, and insolation. Users select a calendar date and the Earth is placed in its orbit using Kepler's laws; the calendar can be started on either vernal equinox (March 20) or perihelion (Jan. 3). Global insolation is computed as a function of latitude and day of year, using the chosen Milankovitch parameters. 3D surface plots of insolation and insolation anomalies (with respect to J2000) are then produced. Insolation computations use the model's own orbital geometry with no additional a-priori input other than the Milankovitch parameter solutions. Insolation computations are successfully validated against Laskar et al. (2004) values. The model outputs other relevant parameters as well, e.g. Earth's radius-vector length, solar declination and day length for the chosen date and latitude. Time-series plots of the Milankovitch parameters and EPICA ice core CO2 and temperature data can be produced. Envisioned future developments include computational efficiency improvements, more options for insolation plots on user-chosen spatio-temporal scales, and overlaying additional paleoclimatological proxy data.

A BAYESIAN METHOD OF ESTIMATING KINETIC PARAMETERS FOR THE INACTIVATION OF CRYPTOSPORIDIUM PARVUM OOCYSTS WITH CHLORINE DIOXIDE AND OZONE

EPA Science Inventory

The main objective of this paper is to use Bayesian methods to estimate the kinetic parameters for the inactivation kinetics of Cryptosporidium parvum oocysts with chlorine dioxide or ozone which are characterized by the delayed Chick-Watson model, i.e., a lag phase or shoulder f...

Sensitivity analysis of a model of CO2 exchange in tundra ecosystems by the adjoint method

NASA Technical Reports Server (NTRS)

Waelbroek, C.; Louis, J.-F.

1995-01-01

A model of net primary production (NPP), decomposition, and nitrogen cycling in tundra ecosystems has been developed. The adjoint technique is used to study the sensitivity of the computed annual net CO2 flux to perturbation in initial conditions, climatic inputs, and model's main parameters describing current seasonal CO2 exchange in wet sedge tundra at Barrow, Alaska. The results show that net CO2 flux is most sensitive to parameters characterizing litter chemical composition and more sensitive to decomposition parameters than to NPP parameters. This underlines the fact that in nutrient-limited ecosystems, decomposition drives net CO2 exchange by controlling mineralization of main nutrients. The results also indicate that the short-term (1 year) response of wet sedge tundra to CO2-induced warming is a significant increase in CO2 emission, creating a positive feedback to atmosphreic CO2 accumulation. However, a cloudiness increase during the same year can severely alter this response and lead to either a slight decrease or a strong increase in emitted CO2, depending on its exact timing. These results demonstrate that the adjoint method is well suited to study systems encountering regime changes, as a single run of the adjoint model provides sensitivities of the net CO2 flux to perturbations in all parameters and variables at any time of the year. Moreover, it is shown that large errors due to the presence of thresholds can be avoided by first delimiting the range of applicability of the adjoint results.

Study of Parameters And Methods of LL-Ⅳ Distributed Hydrological Model in DMIP2

NASA Astrophysics Data System (ADS)

Li, L.; Wu, J.; Wang, X.; Yang, C.; Zhao, Y.; Zhou, H.

2008-05-01

: The Physics-based distributed hydrological model is considered as an important developing period from the traditional experience-hydrology to the physical hydrology. The Hydrology Laboratory of the NOAA National Weather Service proposes the first and second phase of the Distributed Model Intercomparison Project (DMIP)，that it is a great epoch-making work. LL distributed hydrological model has been developed to the fourth generation since it was established in 1997 on the Fengman-I district reservoir area (11000 km2).The LL-I distributed hydrological model was born with the applications of flood control system in the Fengman-I in China. LL-II was developed under the DMIP-I support, it is combined with GIS, RS, GPS, radar rainfall measurement.LL-III was established along with Applications of LL Distributed Model on Water Resources which was supported by the 973-projects of The Ministry of Science and Technology of the People's Republic of China. LL-Ⅳ was developed to face China's water problem. Combined with Blue River and the Baron Fork River basin of DMIP-II, the convection-diffusion equation of non-saturated and saturated seepage was derived from the soil water dynamics and continuous equation. In view of the technical characteristics of the model, the advantage of using convection-diffusion equation to compute confluence overall is longer period of predictable, saving memory space, fast budgeting, clear physical concepts, etc. The determination of parameters of hydrological model is the key, including experience coefficients and parameters of physical parameters. There are methods of experience, inversion, and the optimization to determine the model parameters, and each has advantages and disadvantages. This paper briefly introduces the LL-Ⅳ distribution hydrological model equations, and particularly introduces methods of parameters determination and simulation results on Blue River and Baron Fork River basin for DMIP-II. The soil moisture diffusion coefficient and coefficient of hydraulic conductivity are involved all through the LL-Ⅳ distribution of runoff and slope convergence model, used mainly empirical formula to determine. It's used optimization methods to calculate the two parameters of evaporation capacity (coefficient of bare land and vegetation land), two parameters of interception and wave velocity of Overland Flow, interflow and groundwater. The approach of determining wave velocity of River Network confluence and diffusion coefficient is: 1. Estimate roughness based mainly on digital information such as land use, soil texture, etc. 2.Establish the empirical formula. Another method is called convection-diffusion numerical inversion.

Watershed scale response to climate change--Cathance Stream Basin, Maine

USGS Publications Warehouse

Dudley, Robert W.; Hay, Lauren E.; Markstrom, Steven L.; Hodgkins, Glenn A.

2012-01-01

Fourteen basins for which the Precipitation Runoff Modeling System has been calibrated and evaluated were selected as study sites. Precipitation Runoff Modeling System is a deterministic, distributed parameter watershed model developed to evaluate the effects of various combinations of precipitation, temperature, and land use on streamflow and general basin hydrology. Output from five General Circulation Model simulations and four emission scenarios were used to develop an ensemble of climate-change scenarios for each basin. These ensembles were simulated with the corresponding Precipitation Runoff Modeling System model. This fact sheet summarizes the hydrologic effect and sensitivity of the Precipitation Runoff Modeling System simulations to climate change for the Cathance Stream Basin, Maine.

Calibration of material models for estimating impact of construction quality on life cycle performance of pavements.

DOT National Transportation Integrated Search

2006-02-01

Constructing a pavement that will perform well throughout its expected design life is the main goal of any highway agency. The relationship between construction parameters and pavement life, defined by structural models, can be described using materi...

To center or not to center? Investigating inertia with a multilevel autoregressive model.

PubMed

Hamaker, Ellen L; Grasman, Raoul P P P

2014-01-01

Whether level 1 predictors should be centered per cluster has received considerable attention in the multilevel literature. While most agree that there is no one preferred approach, it has also been argued that cluster mean centering is desirable when the within-cluster slope and the between-cluster slope are expected to deviate, and the main interest is in the within-cluster slope. However, we show in a series of simulations that if one has a multilevel autoregressive model in which the level 1 predictor is the lagged outcome variable (i.e., the outcome variable at the previous occasion), cluster mean centering will in general lead to a downward bias in the parameter estimate of the within-cluster slope (i.e., the autoregressive relationship). This is particularly relevant if the main question is whether there is on average an autoregressive effect. Nonetheless, we show that if the main interest is in estimating the effect of a level 2 predictor on the autoregressive parameter (i.e., a cross-level interaction), cluster mean centering should be preferred over other forms of centering. Hence, researchers should be clear on what is considered the main goal of their study, and base their choice of centering method on this when using a multilevel autoregressive model.

To center or not to center? Investigating inertia with a multilevel autoregressive model

PubMed Central

Hamaker, Ellen L.; Grasman, Raoul P. P. P.

2015-01-01

Whether level 1 predictors should be centered per cluster has received considerable attention in the multilevel literature. While most agree that there is no one preferred approach, it has also been argued that cluster mean centering is desirable when the within-cluster slope and the between-cluster slope are expected to deviate, and the main interest is in the within-cluster slope. However, we show in a series of simulations that if one has a multilevel autoregressive model in which the level 1 predictor is the lagged outcome variable (i.e., the outcome variable at the previous occasion), cluster mean centering will in general lead to a downward bias in the parameter estimate of the within-cluster slope (i.e., the autoregressive relationship). This is particularly relevant if the main question is whether there is on average an autoregressive effect. Nonetheless, we show that if the main interest is in estimating the effect of a level 2 predictor on the autoregressive parameter (i.e., a cross-level interaction), cluster mean centering should be preferred over other forms of centering. Hence, researchers should be clear on what is considered the main goal of their study, and base their choice of centering method on this when using a multilevel autoregressive model. PMID:25688215

Comparison of techniques for approximating ocean bottom topography in a wave-refraction computer model

NASA Technical Reports Server (NTRS)

Poole, L. R.

1975-01-01

A study of the effects of using different methods for approximating bottom topography in a wave-refraction computer model was conducted. Approximation techniques involving quadratic least squares, cubic least squares, and constrained bicubic polynomial interpolation were compared for computed wave patterns and parameters in the region of Saco Bay, Maine. Although substantial local differences can be attributed to use of the different approximation techniques, results indicated that overall computed wave patterns and parameter distributions were quite similar.

Atherosclerotic plaque delamination: Experiments and 2D finite element model to simulate plaque peeling in two strains of transgenic mice.

PubMed

Merei, Bilal; Badel, Pierre; Davis, Lindsey; Sutton, Michael A; Avril, Stéphane; Lessner, Susan M

2017-03-01

Finite element analyses using cohesive zone models (CZM) can be used to predict the fracture of atherosclerotic plaques but this requires setting appropriate values of the model parameters. In this study, material parameters of a CZM were identified for the first time on two groups of mice (ApoE -/- and ApoE -/- Col8 -/- ) using the measured force-displacement curves acquired during delamination tests. To this end, a 2D finite-element model of each plaque was solved using an explicit integration scheme. Each constituent of the plaque was modeled with a neo-Hookean strain energy density function and a CZM was used for the interface. The model parameters were calibrated by minimizing the quadratic deviation between the experimental force displacement curves and the model predictions. The elastic parameter of the plaque and the CZM interfacial parameter were successfully identified for a cohort of 11 mice. The results revealed that only the elastic parameter was significantly different between the two groups, ApoE -/- Col8 -/- plaques being less stiff than ApoE -/- plaques. Finally, this study demonstrated that a simple 2D finite element model with cohesive elements can reproduce fairly well the plaque peeling global response. Future work will focus on understanding the main biological determinants of regional and inter-individual variations of the material parameters used in the model. Copyright © 2016 Elsevier Ltd. All rights reserved.

Evaluation of the low-level laser therapy application parameters for skin burn treatment in experimental model: a systematic review.

PubMed

Brassolatti, Patricia; de Andrade, Ana Laura Martins; Bossini, Paulo Sérgio; Otterço, Albaiza Nicoletti; Parizotto, Nivaldo Antônio

2018-05-05

Burn is defined as a traumatic injury of thermal origin, which affects the organic tissue. Low-level laser therapy (LLLT) has gained great prominence as a treatment in this type of injury; however, the application parameters are still controversial in the literature. The aims of this study were to review the literature studies that use LLLT as a treatment in burns conducted in an experimental model, discuss the main parameters used, and highlight the benefits found in order to choose an appropriate therapeutic window to be applied in this type of injury. The selection of the studies related to the theme was carried out in the main databases (PubMed, Cochrane Library, LILACS, Web of Science, and Scopus in the period from 2001 to 2017). Subsequently, the articles were then chosen that fell within the inclusion criteria previously established. In the end, 22 were evaluated, and the main parameters were presented. The analyzed studies presented both LLLT use in continuous and pulsed mode. Differences between the parameters used (power, fluence, and total energy) were observed. In addition, the protocols are distinct as to the type of injury and the number of treatment sessions. Among the results obtained by the authors are the improvements in the local microcirculation and cellular proliferation; however, a study reported no effects with LLLT as a treatment. LLLT is effective in accelerating the healing process. However, there is immense difficulty in establishing the most adequate protocol, due to the great discrepancy found in the applied dosimetry values.

Estimation of parameters in rational reaction rates of molecular biological systems via weighted least squares

NASA Astrophysics Data System (ADS)

Wu, Fang-Xiang; Mu, Lei; Shi, Zhong-Ke

2010-01-01

The models of gene regulatory networks are often derived from statistical thermodynamics principle or Michaelis-Menten kinetics equation. As a result, the models contain rational reaction rates which are nonlinear in both parameters and states. It is challenging to estimate parameters nonlinear in a model although there have been many traditional nonlinear parameter estimation methods such as Gauss-Newton iteration method and its variants. In this article, we develop a two-step method to estimate the parameters in rational reaction rates of gene regulatory networks via weighted linear least squares. This method takes the special structure of rational reaction rates into consideration. That is, in the rational reaction rates, the numerator and the denominator are linear in parameters. By designing a special weight matrix for the linear least squares, parameters in the numerator and the denominator can be estimated by solving two linear least squares problems. The main advantage of the developed method is that it can produce the analytical solutions to the estimation of parameters in rational reaction rates which originally is nonlinear parameter estimation problem. The developed method is applied to a couple of gene regulatory networks. The simulation results show the superior performance over Gauss-Newton method.

Application of the migration models implemented in the decision system MOIRA-PLUS to assess the long term behaviour of (137)Cs in water and fish of the Baltic Sea.

PubMed

Monte, Luigi

2014-08-01

This work presents and discusses the results of an application of the contaminant migration models implemented in the decision support system MOIRA-PLUS to simulate the time behaviour of the concentrations of (137)Cs of Chernobyl origin in water and fish of the Baltic Sea. The results of the models were compared with the extensive sets of highly reliable empirical data of radionuclide contamination available from international databases and covering a period of, approximately, twenty years. The model application involved three main phases: a) the customisation performed by using hydrological, morphometric and water circulation data obtained from the literature; b) a blind test of the model results, in the sense that the models made use of default values of the migration parameters to predict the dynamics of the contaminant in the environmental components; and c) the adjustment of the model parameter values to improve the agreement of the predictions with the empirical data. The results of the blind test showed that the models successfully predicted the empirical contamination values within the expected range of uncertainty of the predictions (confidence level at 68% of approximately a factor 2). The parameter adjustment can be helpful for the assessment of the fluxes of water circulating among the main sub-basins of the Baltic Sea, substantiating the usefulness of radionuclides to trace the movement of masses of water in seas. Copyright © 2014 Elsevier Ltd. All rights reserved.

The theory and method of variable frequency directional seismic wave under the complex geologic conditions

NASA Astrophysics Data System (ADS)

Jiang, T.; Yue, Y.

2017-12-01

It is well known that the mono-frequency directional seismic wave technology can concentrate seismic waves into a beam. However, little work on the method and effect of variable frequency directional seismic wave under complex geological conditions have been done .We studied the variable frequency directional wave theory in several aspects. Firstly, we studied the relation between directional parameters and the direction of the main beam. Secondly, we analyzed the parameters that affect the beam width of main beam significantly, such as spacing of vibrator, wavelet dominant frequency, and number of vibrator. In addition, we will study different characteristics of variable frequency directional seismic wave in typical velocity models. In order to examine the propagation characteristics of directional seismic wave, we designed appropriate parameters according to the character of direction parameters, which is capable to enhance the energy of the main beam direction. Further study on directional seismic wave was discussed in the viewpoint of power spectral. The results indicate that the energy intensity of main beam direction increased 2 to 6 times for a multi-ore body velocity model. It showed us that the variable frequency directional seismic technology provided an effective way to strengthen the target signals under complex geological conditions. For concave interface model, we introduced complicated directional seismic technology which supports multiple main beams to obtain high quality data. Finally, we applied the 9-element variable frequency directional seismic wave technology to process the raw data acquired in a oil-shale exploration area. The results show that the depth of exploration increased 4 times with directional seismic wave method. Based on the above analysis, we draw the conclusion that the variable frequency directional seismic wave technology can improve the target signals of different geologic conditions and increase exploration depth with little cost. Due to inconvenience of hydraulic vibrators in complicated surface area, we suggest that the combination of high frequency portable vibrator and variable frequency directional seismic wave method is an alternative technology to increase depth of exploration or prospecting.

One-dimensional velocity model of the Middle Kura Depresion from local earthquakes data of Azerbaijan

NASA Astrophysics Data System (ADS)

Yetirmishli, G. C.; Kazimova, S. E.; Kazimov, I. E.

2011-09-01

We present the method for determining the velocity model of the Earth's crust and the parameters of earthquakes in the Middle Kura Depression from the data of network telemetry in Azerbaijan. Application of this method allowed us to recalculate the main parameters of the hypocenters of the earthquake, to compute the corrections to the arrival times of P and S waves at the observation station, and to significantly improve the accuracy in determining the coordinates of the earthquakes. The model was constructed using the VELEST program, which calculates one-dimensional minimal velocity models from the travel times of seismic waves.

Defining a procedure for predicting the duration of the approximately isothermal segments within the proposed drying regime as a function of the drying air parameters

NASA Astrophysics Data System (ADS)

Vasić, M.; Radojević, Z.

2017-08-01

One of the main disadvantages of the recently reported method, for setting up the drying regime based on the theory of moisture migration during drying, lies in a fact that it is based on a large number of isothermal experiments. In addition each isothermal experiment requires the use of different drying air parameters. The main goal of this paper was to find a way how to reduce the number of isothermal experiments without affecting the quality of the previously proposed calculation method. The first task was to define the lower and upper inputs as well as the output of the “black box” which will be used in the Box-Wilkinson’s orthogonal multi-factorial experimental design. Three inputs (drying air temperature, humidity and velocity) were used within the experimental design. The output parameter of the model represents the time interval between any two chosen characteristic points presented on the Deff - t. The second task was to calculate the output parameter for each planed experiments. The final output of the model is the equation which can predict the time interval between any two chosen characteristic points as a function of the drying air parameters. This equation is valid for any value of the drying air parameters which are within the defined area designated with lower and upper limiting values.

Understanding and Mitigating Vortex-Dominated, Tip-Leakage and End-Wall Losses in a Transonic Splittered Rotor Stage

DTIC Science & Technology

2015-04-23

blade geometry parameters the TPL design 9   tool was initiated by running the MATLAB script (*.m) Main_SpeedLine_Auto. Main_SpeedLine_Auto...SolidWorks for solid model generation of the blade shapes. Computational Analysis With solid models generated of the gas -path air wedge, automated...287 mm (11.3 in) Constrained by existing TCR geometry Number of Passages 12 None A blade tip-down design approach was used. The outputs of the

Macroscopic singlet oxygen model incorporating photobleaching as an input parameter

NASA Astrophysics Data System (ADS)

Kim, Michele M.; Finlay, Jarod C.; Zhu, Timothy C.

2015-03-01

A macroscopic singlet oxygen model for photodynamic therapy (PDT) has been used extensively to calculate the reacted singlet oxygen concentration for various photosensitizers. The four photophysical parameters (ξ, σ, β, δ) and threshold singlet oxygen dose ([1O2]r,sh) can be found for various drugs and drug-light intervals using a fitting algorithm. The input parameters for this model include the fluence, photosensitizer concentration, optical properties, and necrosis radius. An additional input variable of photobleaching was implemented in this study to optimize the results. Photobleaching was measured by using the pre-PDT and post-PDT sensitizer concentrations. Using the RIF model of murine fibrosarcoma, mice were treated with a linear source with fluence rates from 12 - 150 mW/cm and total fluences from 24 - 135 J/cm. The two main drugs investigated were benzoporphyrin derivative monoacid ring A (BPD) and 2-[1-hexyloxyethyl]-2-devinyl pyropheophorbide-a (HPPH). Previously published photophysical parameters were fine-tuned and verified using photobleaching as the additional fitting parameter. Furthermore, photobleaching can be used as an indicator of the robustness of the model for the particular mouse experiment by comparing the experimental and model-calculated photobleaching ratio.

Slow-Slip Phenomena Represented by the One-Dimensional Burridge-Knopoff Model of Earthquakes

NASA Astrophysics Data System (ADS)

Kawamura, Hikaru; Yamamoto, Maho; Ueda, Yushi

2018-05-01

Slow-slip phenomena, including afterslips and silent earthquakes, are studied using a one-dimensional Burridge-Knopoff model that obeys the rate-and-state dependent friction law. By varying only a few model parameters, this simple model allows reproducing a variety of seismic slips within a single framework, including main shocks, precursory nucleation processes, afterslips, and silent earthquakes.

Validation of a mathematical model of the bovine estrous cycle for cows with different estrous cycle characteristics.

PubMed

Boer, H M T; Butler, S T; Stötzel, C; Te Pas, M F W; Veerkamp, R F; Woelders, H

2017-11-01

A recently developed mechanistic mathematical model of the bovine estrous cycle was parameterized to fit empirical data sets collected during one estrous cycle of 31 individual cows, with the main objective to further validate the model. The a priori criteria for validation were (1) the resulting model can simulate the measured data correctly (i.e. goodness of fit), and (2) this is achieved without needing extreme, probably non-physiological parameter values. We used a least squares optimization procedure to identify parameter configurations for the mathematical model to fit the empirical in vivo measurements of follicle and corpus luteum sizes, and the plasma concentrations of progesterone, estradiol, FSH and LH for each cow. The model was capable of accommodating normal variation in estrous cycle characteristics of individual cows. With the parameter sets estimated for the individual cows, the model behavior changed for 21 cows, with improved fit of the simulated output curves for 18 of these 21 cows. Moreover, the number of follicular waves was predicted correctly for 18 of the 25 two-wave and three-wave cows, without extreme parameter value changes. Estimation of specific parameters confirmed results of previous model simulations indicating that parameters involved in luteolytic signaling are very important for regulation of general estrous cycle characteristics, and are likely responsible for differences in estrous cycle characteristics between cows.

Simulation of spatial and temporal properties of aftershocks by means of the fiber bundle model

NASA Astrophysics Data System (ADS)

Monterrubio-Velasco, Marisol; Zúñiga, F. R.; Márquez-Ramírez, Victor Hugo; Figueroa-Soto, Angel

2017-11-01

The rupture processes of any heterogeneous material constitute a complex physical problem. Earthquake aftershocks show temporal and spatial behaviors which are consequence of the heterogeneous stress distribution and multiple rupturing following the main shock. This process is difficult to model deterministically due to the number of parameters and physical conditions, which are largely unknown. In order to shed light on the minimum requirements for the generation of aftershock clusters, in this study, we perform a simulation of the main features of such a complex process by means of a fiber bundle (FB) type model. The FB model has been widely used to analyze the fracture process in heterogeneous materials. It is a simple but powerful tool that allows modeling the main characteristics of a medium such as the brittle shallow crust of the earth. In this work, we incorporate spatial properties, such as the Coulomb stress change pattern, which help simulate observed characteristics of aftershock sequences. In particular, we introduce a parameter ( P) that controls the probability of spatial distribution of initial loads. Also, we use a "conservation" parameter ( π), which accounts for the load dissipation of the system, and demonstrate its influence on the simulated spatio-temporal patterns. Based on numerical results, we find that P has to be in the range 0.06 < P < 0.30, whilst π needs to be limited by a very narrow range ( 0.60 < π < 0.66) in order to reproduce aftershocks pattern characteristics which resemble those of observed sequences. This means that the system requires a small difference in the spatial distribution of initial stress, and a very particular fraction of load transfer in order to generate realistic aftershocks.

ERM model analysis for adaptation to hydrological model errors

NASA Astrophysics Data System (ADS)

Baymani-Nezhad, M.; Han, D.

2018-05-01

Hydrological conditions are changed continuously and these phenomenons generate errors on flood forecasting models and will lead to get unrealistic results. Therefore, to overcome these difficulties, a concept called model updating is proposed in hydrological studies. Real-time model updating is one of the challenging processes in hydrological sciences and has not been entirely solved due to lack of knowledge about the future state of the catchment under study. Basically, in terms of flood forecasting process, errors propagated from the rainfall-runoff model are enumerated as the main source of uncertainty in the forecasting model. Hence, to dominate the exciting errors, several methods have been proposed by researchers to update the rainfall-runoff models such as parameter updating, model state updating, and correction on input data. The current study focuses on investigations about the ability of rainfall-runoff model parameters to cope with three types of existing errors, timing, shape and volume as the common errors in hydrological modelling. The new lumped model, the ERM model, has been selected for this study to evaluate its parameters for its use in model updating to cope with the stated errors. Investigation about ten events proves that the ERM model parameters can be updated to cope with the errors without the need to recalibrate the model.

Parameter estimation using meta-heuristics in systems biology: a comprehensive review.

PubMed

Sun, Jianyong; Garibaldi, Jonathan M; Hodgman, Charlie

2012-01-01

This paper gives a comprehensive review of the application of meta-heuristics to optimization problems in systems biology, mainly focussing on the parameter estimation problem (also called the inverse problem or model calibration). It is intended for either the system biologist who wishes to learn more about the various optimization techniques available and/or the meta-heuristic optimizer who is interested in applying such techniques to problems in systems biology. First, the parameter estimation problems emerging from different areas of systems biology are described from the point of view of machine learning. Brief descriptions of various meta-heuristics developed for these problems follow, along with outlines of their advantages and disadvantages. Several important issues in applying meta-heuristics to the systems biology modelling problem are addressed, including the reliability and identifiability of model parameters, optimal design of experiments, and so on. Finally, we highlight some possible future research directions in this field.

A Note on the Specification of Error Structures in Latent Interaction Models

ERIC Educational Resources Information Center

Mao, Xiulin; Harring, Jeffrey R.; Hancock, Gregory R.

2015-01-01

Latent interaction models have motivated a great deal of methodological research, mainly in the area of estimating such models. Product-indicator methods have been shown to be competitive with other methods of estimation in terms of parameter bias and standard error accuracy, and their continued popularity in empirical studies is due, in part, to…

Computational control of flexible aerospace systems

NASA Technical Reports Server (NTRS)

Sharpe, Lonnie, Jr.; Shen, Ji Yao

1994-01-01

The main objective of this project is to establish a distributed parameter modeling technique for structural analysis, parameter estimation, vibration suppression and control synthesis of large flexible aerospace structures. This report concentrates on the research outputs produced in the last two years. The main accomplishments can be summarized as follows. A new version of the PDEMOD Code had been completed based on several incomplete versions. The verification of the code had been conducted by comparing the results with those examples for which the exact theoretical solutions can be obtained. The theoretical background of the package and the verification examples has been reported in a technical paper submitted to the Joint Applied Mechanics & Material Conference, ASME. A brief USER'S MANUAL had been compiled, which includes three parts: (1) Input data preparation; (2) Explanation of the Subroutines; and (3) Specification of control variables. Meanwhile, a theoretical investigation of the NASA MSFC two-dimensional ground-based manipulator facility by using distributed parameter modeling technique has been conducted. A new mathematical treatment for dynamic analysis and control of large flexible manipulator systems has been conceived, which may provide an embryonic form of a more sophisticated mathematical model for future modified versions of the PDEMOD Codes.

The design of the Langmuir probe onboard a seismo-electromagnetic satellite

NASA Astrophysics Data System (ADS)

Guan, Yi-bing; Wang, Sh-ijin; Liu, Chao; Feng, Yu-bo

2011-08-01

The double Langmuir probe, as a payload of a seism-electromagnetic satellite, has been designed for in situ measurements of the parameters of the ionosphere plasma on the 500km altitude orbit to research the electromagnetic coupling between the solid-earth activities and the ionosphere disturbances. The Langmuir probe is comprised of two spherical sensors: the diameter of the smaller one is 1cm and the other one is 5cm. The two sensors are mounted on two parallel booms on the satellite, which are half meter far from each other. The two main ionosphere parameters measured by the Langmuir probe are electron density and electron temperature, which are computed from the I-V curves. The I-V curve is given by a current flow through a sensor in case of a sweep voltage is applied to the sensor. There are three main work models for the Langmuir probe: the normal model, the burst model and the decontamination model. The normal model is for the general measurement of the ionosphere parameters around the globe with 1s time resolution, while the burst model is to measure the ionosphere over the interested areas, like the areas with more earthquake activities, with 0.5s time resolution. The decontamination model would work if the I-V curves shown hysteresis phenomenon, which indicated that the sensors may be contaminated by the outgassing of the satellite. The description of the Langmuir probe instrument and its capabilities is provided.

On the effect of model parameters on forecast objects

NASA Astrophysics Data System (ADS)

Marzban, Caren; Jones, Corinne; Li, Ning; Sandgathe, Scott

2018-04-01

Many physics-based numerical models produce a gridded, spatial field of forecasts, e.g., a temperature map. The field for some quantities generally consists of spatially coherent and disconnected objects. Such objects arise in many problems, including precipitation forecasts in atmospheric models, eddy currents in ocean models, and models of forest fires. Certain features of these objects (e.g., location, size, intensity, and shape) are generally of interest. Here, a methodology is developed for assessing the impact of model parameters on the features of forecast objects. The main ingredients of the methodology include the use of (1) Latin hypercube sampling for varying the values of the model parameters, (2) statistical clustering algorithms for identifying objects, (3) multivariate multiple regression for assessing the impact of multiple model parameters on the distribution (across the forecast domain) of object features, and (4) methods for reducing the number of hypothesis tests and controlling the resulting errors. The final output of the methodology is a series of box plots and confidence intervals that visually display the sensitivities. The methodology is demonstrated on precipitation forecasts from a mesoscale numerical weather prediction model.

Stochastic Modeling and Analysis of Multiple Nonlinear Accelerated Degradation Processes through Information Fusion

PubMed Central

Sun, Fuqiang; Liu, Le; Li, Xiaoyang; Liao, Haitao

2016-01-01

Accelerated degradation testing (ADT) is an efficient technique for evaluating the lifetime of a highly reliable product whose underlying failure process may be traced by the degradation of the product’s performance parameters with time. However, most research on ADT mainly focuses on a single performance parameter. In reality, the performance of a modern product is usually characterized by multiple parameters, and the degradation paths are usually nonlinear. To address such problems, this paper develops a new s-dependent nonlinear ADT model for products with multiple performance parameters using a general Wiener process and copulas. The general Wiener process models the nonlinear ADT data, and the dependency among different degradation measures is analyzed using the copula method. An engineering case study on a tuner’s ADT data is conducted to demonstrate the effectiveness of the proposed method. The results illustrate that the proposed method is quite effective in estimating the lifetime of a product with s-dependent performance parameters. PMID:27509499

Stochastic Modeling and Analysis of Multiple Nonlinear Accelerated Degradation Processes through Information Fusion.

PubMed

Sun, Fuqiang; Liu, Le; Li, Xiaoyang; Liao, Haitao

2016-08-06

Accelerated degradation testing (ADT) is an efficient technique for evaluating the lifetime of a highly reliable product whose underlying failure process may be traced by the degradation of the product's performance parameters with time. However, most research on ADT mainly focuses on a single performance parameter. In reality, the performance of a modern product is usually characterized by multiple parameters, and the degradation paths are usually nonlinear. To address such problems, this paper develops a new s-dependent nonlinear ADT model for products with multiple performance parameters using a general Wiener process and copulas. The general Wiener process models the nonlinear ADT data, and the dependency among different degradation measures is analyzed using the copula method. An engineering case study on a tuner's ADT data is conducted to demonstrate the effectiveness of the proposed method. The results illustrate that the proposed method is quite effective in estimating the lifetime of a product with s-dependent performance parameters.

Is there a `universal' dynamic zero-parameter hydrological model? Evaluation of a dynamic Budyko model in US and India

NASA Astrophysics Data System (ADS)

Patnaik, S.; Biswal, B.; Sharma, V. C.

2017-12-01

River flow varies greatly in space and time, and the single biggest challenge for hydrologists and ecologists around the world is the fact that most rivers are either ungauged or poorly gauged. Although it is relatively easier to predict long-term average flow of a river using the `universal' zero-parameter Budyko model, lack of data hinders short-term flow prediction at ungauged locations using traditional hydrological models as they require observed flow data for model calibration. Flow prediction in ungauged basins thus requires a dynamic 'zero-parameter' hydrological model. One way to achieve this is to regionalize a dynamic hydrological model's parameters. However, a regionalization method based zero-parameter dynamic hydrological model is not `universal'. An alternative attempt was made recently to develop a zero-parameter dynamic model by defining an instantaneous dryness index as a function of antecedent rainfall and solar energy inputs with the help of a decay function and using the original Budyko function. The model was tested first in 63 US catchments and later in 50 Indian catchments. The median Nash-Sutcliffe efficiency (NSE) was found to be close to 0.4 in both the cases. Although improvements need to be incorporated in order to use the model for reliable prediction, the main aim of this study was to rather understand hydrological processes. The overall results here seem to suggest that the dynamic zero-parameter Budyko model is `universal.' In other words natural catchments around the world are strikingly similar to each other in the way they respond to hydrologic inputs; we thus need to focus more on utilizing catchment similarities in hydrological modelling instead of over parameterizing our models.

Improving flood forecasting capability of physically based distributed hydrological model by parameter optimization

NASA Astrophysics Data System (ADS)

Chen, Y.; Li, J.; Xu, H.

2015-10-01

Physically based distributed hydrological models discrete the terrain of the whole catchment into a number of grid cells at fine resolution, and assimilate different terrain data and precipitation to different cells, and are regarded to have the potential to improve the catchment hydrological processes simulation and prediction capability. In the early stage, physically based distributed hydrological models are assumed to derive model parameters from the terrain properties directly, so there is no need to calibrate model parameters, but unfortunately, the uncertanties associated with this model parameter deriving is very high, which impacted their application in flood forecasting, so parameter optimization may also be necessary. There are two main purposes for this study, the first is to propose a parameter optimization method for physically based distributed hydrological models in catchment flood forecasting by using PSO algorithm and to test its competence and to improve its performances, the second is to explore the possibility of improving physically based distributed hydrological models capability in cathcment flood forecasting by parameter optimization. In this paper, based on the scalar concept, a general framework for parameter optimization of the PBDHMs for catchment flood forecasting is first proposed that could be used for all PBDHMs. Then, with Liuxihe model as the study model, which is a physically based distributed hydrological model proposed for catchment flood forecasting, the improverd Particle Swarm Optimization (PSO) algorithm is developed for the parameter optimization of Liuxihe model in catchment flood forecasting, the improvements include to adopt the linear decreasing inertia weight strategy to change the inertia weight, and the arccosine function strategy to adjust the acceleration coefficients. This method has been tested in two catchments in southern China with different sizes, and the results show that the improved PSO algorithm could be used for Liuxihe model parameter optimization effectively, and could improve the model capability largely in catchment flood forecasting, thus proven that parameter optimization is necessary to improve the flood forecasting capability of physically based distributed hydrological model. It also has been found that the appropriate particle number and the maximum evolution number of PSO algorithm used for Liuxihe model catchment flood forcasting is 20 and 30, respectively.

Parameter sensitivity analysis of a 1-D cold region lake model for land-surface schemes

NASA Astrophysics Data System (ADS)

Guerrero, José-Luis; Pernica, Patricia; Wheater, Howard; Mackay, Murray; Spence, Chris

2017-12-01

Lakes might be sentinels of climate change, but the uncertainty in their main feedback to the atmosphere - heat-exchange fluxes - is often not considered within climate models. Additionally, these fluxes are seldom measured, hindering critical evaluation of model output. Analysis of the Canadian Small Lake Model (CSLM), a one-dimensional integral lake model, was performed to assess its ability to reproduce diurnal and seasonal variations in heat fluxes and the sensitivity of simulated fluxes to changes in model parameters, i.e., turbulent transport parameters and the light extinction coefficient (Kd). A C++ open-source software package, Problem Solving environment for Uncertainty Analysis and Design Exploration (PSUADE), was used to perform sensitivity analysis (SA) and identify the parameters that dominate model behavior. The generalized likelihood uncertainty estimation (GLUE) was applied to quantify the fluxes' uncertainty, comparing daily-averaged eddy-covariance observations to the output of CSLM. Seven qualitative and two quantitative SA methods were tested, and the posterior likelihoods of the modeled parameters, obtained from the GLUE analysis, were used to determine the dominant parameters and the uncertainty in the modeled fluxes. Despite the ubiquity of the equifinality issue - different parameter-value combinations yielding equivalent results - the answer to the question was unequivocal: Kd, a measure of how much light penetrates the lake, dominates sensible and latent heat fluxes, and the uncertainty in their estimates is strongly related to the accuracy with which Kd is determined. This is important since accurate and continuous measurements of Kd could reduce modeling uncertainty.

Uncertainty quantification and global sensitivity analysis of the Los Alamos sea ice model

NASA Astrophysics Data System (ADS)

Urrego-Blanco, Jorge R.; Urban, Nathan M.; Hunke, Elizabeth C.; Turner, Adrian K.; Jeffery, Nicole

2016-04-01

Changes in the high-latitude climate system have the potential to affect global climate through feedbacks with the atmosphere and connections with midlatitudes. Sea ice and climate models used to understand these changes have uncertainties that need to be characterized and quantified. We present a quantitative way to assess uncertainty in complex computer models, which is a new approach in the analysis of sea ice models. We characterize parametric uncertainty in the Los Alamos sea ice model (CICE) in a standalone configuration and quantify the sensitivity of sea ice area, extent, and volume with respect to uncertainty in 39 individual model parameters. Unlike common sensitivity analyses conducted in previous studies where parameters are varied one at a time, this study uses a global variance-based approach in which Sobol' sequences are used to efficiently sample the full 39-dimensional parameter space. We implement a fast emulator of the sea ice model whose predictions of sea ice extent, area, and volume are used to compute the Sobol' sensitivity indices of the 39 parameters. Main effects and interactions among the most influential parameters are also estimated by a nonparametric regression technique based on generalized additive models. A ranking based on the sensitivity indices indicates that model predictions are most sensitive to snow parameters such as snow conductivity and grain size, and the drainage of melt ponds. It is recommended that research be prioritized toward more accurately determining these most influential parameter values by observational studies or by improving parameterizations in the sea ice model.

Development of a 5 MW reference gearbox for offshore wind turbines: 5 MW reference gearbox

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

Nejad, Amir Rasekhi; Guo, Yi; Gao, Zhen

2015-07-27

This paper presents detailed descriptions, modeling parameters and technical data of a 5MW high-speed gearbox developed for the National Renewable Energy Laboratory offshore 5MW baseline wind turbine. The main aim of this paper is to support the concept studies and research for large offshore wind turbines by providing a baseline gearbox model with detailed modeling parameters. This baseline gearbox follows the most conventional design types of those used in wind turbines. It is based on the four-point supports: two main bearings and two torque arms. The gearbox consists of three stages: two planetary and one parallel stage gears. The gearmore » ratios among the stages are calculated in a way to obtain the minimum gearbox weight. The gearbox components are designed and selected based on the offshore wind turbine design codes and validated by comparison to the data available from large offshore wind turbine prototypes. All parameters required to establish the dynamic model of the gearbox are then provided. Moreover, a maintenance map indicating components with high to low probability of failure is shown. The 5 MW reference gearbox can be used as a baseline for research on wind turbine gearboxes and comparison studies. It can also be employed in global analysis tools to represent a more realistic model of a gearbox in a coupled analysis.« less

Extension of D-H parameter method to hybrid manipulators used in robot-assisted surgery.

PubMed

Singh, Amanpreet; Singla, Ashish; Soni, Sanjeev

2015-10-01

The main focus of this work is to extend the applicability of D-H parameter method to develop a kinematic model of a hybrid manipulator. A hybrid manipulator is a combination of open- and closed-loop chains and contains planar and spatial links. It has been found in the literature that D-H parameter method leads to ambiguities, when dealing with closed-loop chains. In this work, it has been observed that the D-H parameter method, when applied to a hybrid manipulator, results in an orientational inconsistency, because of which the method cannot be used to develop the kinematic model. In this article, the concept of dummy frames is proposed to resolve the orientational inconsistency and to develop the kinematic model of a hybrid manipulator. Moreover, the prototype of 7-degree-of-freedom hybrid manipulator, known as a surgeon-side manipulator to assist the surgeon during a medical surgery, is also developed to validate the kinematic model derived in this work. © IMechE 2015.

The necessity of HVAC system for the registered architectural cultural heritage building

NASA Astrophysics Data System (ADS)

Popovici, Cătălin George; Hudişteanu, Sebastian Valeriu; Cherecheş, Nelu-Cristian

2018-02-01

This study is intended to highlight the role of the ventilation and air conditioning system for a theatre. It was chosen as a case study the "Vasile Alecsandri" National Theatre of Jassy. The paper also sought to make a comparison in three distinct scenarios for HVAC Main Hall system - ventilation and air conditioning system of the Main Hall doesn't work; only the ventilation system of the Main Hall works and ventilation and air conditioning system of the Main Hall works. For analysing the comfort parameters, the ANSYS-Fluent software was used to build a 2D model of the building and simulation of HVAC system functionality during winter season, in all three scenarios. For the studied scenarios, the external conditions of Jassy and the indoor conditions of the theatre, when the entire spectacle hall is occupied were considered. The main aspects evaluated for each case were the air temperature, air velocity and relative humidity. The results are presented comparatively as plots and spectra of the interest parameters.

Measurement of Hydrologic Streamflow Metrics and Estimation of Streamflow with Lumped Parameter Models in a Managed Lake System, Sebago Lake, Maine

NASA Astrophysics Data System (ADS)

Reeve, A. S.; Martin, D.; Smith, S. M.

2013-12-01

Surface waters within the Sebago Lake watershed (southern Maine, USA) provide a variety of economically and intrinsically valuable recreational, commercial and environmental services. Different stakeholder groups for the 118 km2 Sebago Lake and surrounding watershed advocate for different lake and watershed management strategies, focusing on the operation of a dam at the outflow from Sebago Lake. While lake level in Sebago Lake has been monitored for over a century, limited data is available on the hydrologic processes that drive lake level and therefore impact how dam operation (and other changes to the region) will influence the hydroperiod of the lake. To fill this information gap several tasks were undertaken including: 1) deploying data logging pressure transducers to continuously monitor stream stage in nine tributaries, 2) measuring stream discharge at these sites to create rating curves for the nine tributaries, and using the resulting continuous discharge records to 3) calibrate lumped parameter computer models based on the GR4J model, modified to include a degree-day snowmelt routine. These lumped parameter models have been integrated with a simple lake water-balance model to estimate lake level and its response to different scenarios including dam management strategies. To date, about three years of stream stage data have been used to estimate stream discharge in all monitored tributaries (data collection is ongoing). Baseflow separation indices (BFI) for 2010 and 2011 using the USGS software PART and the Eckhart digital filter in WHAT range from 0.80-0.86 in the Crooked River and Richmill Outlet,followed by Northwest (0.75) and Muddy (0.53-0.56) Rivers, with the lowest BFI measured in Sticky River (0.41-0.56). The BFI values indicate most streams have significant groundwater (or other storage) inputs. The lumped parameter watershed model has been calibrated for four streams (Nash-Sutcliffe = 0.4 to 0.9), with the other major tributaries containing hydraulic structures that are not included in the lumped parameter model. Calibrated watershed models tend to substantially underestimate the highest streamflows while overestimating low flows. An early June 2012 event caused extremely high flows with discharge in the Crooked River (the most significant tributary) peaking at about 85 m3/day. The lumped parameter model dramatically underestimated this important and anomalous event, but provided a reasonable prediction of flows throughout the rest of 2012. Ongoing work includes incorporating hydraulic structures in the lumped parameter model and using the available data to drive the lake water-balance model that has been prepared.

Nonlinear-regression groundwater flow modeling of a deep regional aquifer system

USGS Publications Warehouse

Cooley, Richard L.; Konikow, Leonard F.; Naff, Richard L.

1986-01-01

A nonlinear regression groundwater flow model, based on a Galerkin finite-element discretization, was used to analyze steady state two-dimensional groundwater flow in the areally extensive Madison aquifer in a 75,000 mi2 area of the Northern Great Plains. Regression parameters estimated include intrinsic permeabilities of the main aquifer and separate lineament zones, discharges from eight major springs surrounding the Black Hills, and specified heads on the model boundaries. Aquifer thickness and temperature variations were included as specified functions. The regression model was applied using sequential F testing so that the fewest number and simplest zonation of intrinsic permeabilities, combined with the simplest overall model, were evaluated initially; additional complexities (such as subdivisions of zones and variations in temperature and thickness) were added in stages to evaluate the subsequent degree of improvement in the model results. It was found that only the eight major springs, a single main aquifer intrinsic permeability, two separate lineament intrinsic permeabilities of much smaller values, and temperature variations are warranted by the observed data (hydraulic heads and prior information on some parameters) for inclusion in a model that attempts to explain significant controls on groundwater flow. Addition of thickness variations did not significantly improve model results; however, thickness variations were included in the final model because they are fairly well defined. Effects on the observed head distribution from other features, such as vertical leakage and regional variations in intrinsic permeability, apparently were overshadowed by measurement errors in the observed heads. Estimates of the parameters correspond well to estimates obtained from other independent sources.

Nonlinear-Regression Groundwater Flow Modeling of a Deep Regional Aquifer System

NASA Astrophysics Data System (ADS)

Cooley, Richard L.; Konikow, Leonard F.; Naff, Richard L.

1986-12-01

A nonlinear regression groundwater flow model, based on a Galerkin finite-element discretization, was used to analyze steady state two-dimensional groundwater flow in the areally extensive Madison aquifer in a 75,000 mi2 area of the Northern Great Plains. Regression parameters estimated include intrinsic permeabilities of the main aquifer and separate lineament zones, discharges from eight major springs surrounding the Black Hills, and specified heads on the model boundaries. Aquifer thickness and temperature variations were included as specified functions. The regression model was applied using sequential F testing so that the fewest number and simplest zonation of intrinsic permeabilities, combined with the simplest overall model, were evaluated initially; additional complexities (such as subdivisions of zones and variations in temperature and thickness) were added in stages to evaluate the subsequent degree of improvement in the model results. It was found that only the eight major springs, a single main aquifer intrinsic permeability, two separate lineament intrinsic permeabilities of much smaller values, and temperature variations are warranted by the observed data (hydraulic heads and prior information on some parameters) for inclusion in a model that attempts to explain significant controls on groundwater flow. Addition of thickness variations did not significantly improve model results; however, thickness variations were included in the final model because they are fairly well defined. Effects on the observed head distribution from other features, such as vertical leakage and regional variations in intrinsic permeability, apparently were overshadowed by measurement errors in the observed heads. Estimates of the parameters correspond well to estimates obtained from other independent sources.

Uncertainty analysis in geospatial merit matrix–based hydropower resource assessment

DOE PAGES

Pasha, M. Fayzul K.; Yeasmin, Dilruba; Saetern, Sen; ...

2016-03-30

Hydraulic head and mean annual streamflow, two main input parameters in hydropower resource assessment, are not measured at every point along the stream. Translation and interpolation are used to derive these parameters, resulting in uncertainties. This study estimates the uncertainties and their effects on model output parameters: the total potential power and the number of potential locations (stream-reach). These parameters are quantified through Monte Carlo Simulation (MCS) linking with a geospatial merit matrix based hydropower resource assessment (GMM-HRA) Model. The methodology is applied to flat, mild, and steep terrains. Results show that the uncertainty associated with the hydraulic head ismore » within 20% for mild and steep terrains, and the uncertainty associated with streamflow is around 16% for all three terrains. Output uncertainty increases as input uncertainty increases. However, output uncertainty is around 10% to 20% of the input uncertainty, demonstrating the robustness of the GMM-HRA model. Hydraulic head is more sensitive to output parameters in steep terrain than in flat and mild terrains. Furthermore, mean annual streamflow is more sensitive to output parameters in flat terrain.« less

Comparison of existing models to simulate anaerobic digestion of lipid-rich waste.

PubMed

Béline, F; Rodriguez-Mendez, R; Girault, R; Bihan, Y Le; Lessard, P

2017-02-01

Models for anaerobic digestion of lipid-rich waste taking inhibition into account were reviewed and, if necessary, adjusted to the ADM1 model framework in order to compare them. Experimental data from anaerobic digestion of slaughterhouse waste at an organic loading rate (OLR) ranging from 0.3 to 1.9kgVSm -3 d -1 were used to compare and evaluate models. Experimental data obtained at low OLRs were accurately modeled whatever the model thereby validating the stoichiometric parameters used and influent fractionation. However, at higher OLRs, although inhibition parameters were optimized to reduce differences between experimental and simulated data, no model was able to accurately simulate accumulation of substrates and intermediates, mainly due to the wrong simulation of pH. A simulation using pH based on experimental data showed that acetogenesis and methanogenesis were the most sensitive steps to LCFA inhibition and enabled identification of the inhibition parameters of both steps. Copyright © 2016 Elsevier Ltd. All rights reserved.

Progressive Learning of Topic Modeling Parameters: A Visual Analytics Framework.

PubMed

El-Assady, Mennatallah; Sevastjanova, Rita; Sperrle, Fabian; Keim, Daniel; Collins, Christopher

2018-01-01

Topic modeling algorithms are widely used to analyze the thematic composition of text corpora but remain difficult to interpret and adjust. Addressing these limitations, we present a modular visual analytics framework, tackling the understandability and adaptability of topic models through a user-driven reinforcement learning process which does not require a deep understanding of the underlying topic modeling algorithms. Given a document corpus, our approach initializes two algorithm configurations based on a parameter space analysis that enhances document separability. We abstract the model complexity in an interactive visual workspace for exploring the automatic matching results of two models, investigating topic summaries, analyzing parameter distributions, and reviewing documents. The main contribution of our work is an iterative decision-making technique in which users provide a document-based relevance feedback that allows the framework to converge to a user-endorsed topic distribution. We also report feedback from a two-stage study which shows that our technique results in topic model quality improvements on two independent measures.

Uncertainty quantification and global sensitivity analysis of the Los Alamos sea ice model

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

Urrego-Blanco, Jorge Rolando; Urban, Nathan Mark; Hunke, Elizabeth Clare

Changes in the high-latitude climate system have the potential to affect global climate through feedbacks with the atmosphere and connections with midlatitudes. Sea ice and climate models used to understand these changes have uncertainties that need to be characterized and quantified. We present a quantitative way to assess uncertainty in complex computer models, which is a new approach in the analysis of sea ice models. We characterize parametric uncertainty in the Los Alamos sea ice model (CICE) in a standalone configuration and quantify the sensitivity of sea ice area, extent, and volume with respect to uncertainty in 39 individual modelmore » parameters. Unlike common sensitivity analyses conducted in previous studies where parameters are varied one at a time, this study uses a global variance-based approach in which Sobol' sequences are used to efficiently sample the full 39-dimensional parameter space. We implement a fast emulator of the sea ice model whose predictions of sea ice extent, area, and volume are used to compute the Sobol' sensitivity indices of the 39 parameters. Main effects and interactions among the most influential parameters are also estimated by a nonparametric regression technique based on generalized additive models. A ranking based on the sensitivity indices indicates that model predictions are most sensitive to snow parameters such as snow conductivity and grain size, and the drainage of melt ponds. Lastly, it is recommended that research be prioritized toward more accurately determining these most influential parameter values by observational studies or by improving parameterizations in the sea ice model.« less

Uncertainty quantification and global sensitivity analysis of the Los Alamos sea ice model

DOE PAGES

Urrego-Blanco, Jorge Rolando; Urban, Nathan Mark; Hunke, Elizabeth Clare; ...

2016-04-01

Changes in the high-latitude climate system have the potential to affect global climate through feedbacks with the atmosphere and connections with midlatitudes. Sea ice and climate models used to understand these changes have uncertainties that need to be characterized and quantified. We present a quantitative way to assess uncertainty in complex computer models, which is a new approach in the analysis of sea ice models. We characterize parametric uncertainty in the Los Alamos sea ice model (CICE) in a standalone configuration and quantify the sensitivity of sea ice area, extent, and volume with respect to uncertainty in 39 individual modelmore » parameters. Unlike common sensitivity analyses conducted in previous studies where parameters are varied one at a time, this study uses a global variance-based approach in which Sobol' sequences are used to efficiently sample the full 39-dimensional parameter space. We implement a fast emulator of the sea ice model whose predictions of sea ice extent, area, and volume are used to compute the Sobol' sensitivity indices of the 39 parameters. Main effects and interactions among the most influential parameters are also estimated by a nonparametric regression technique based on generalized additive models. A ranking based on the sensitivity indices indicates that model predictions are most sensitive to snow parameters such as snow conductivity and grain size, and the drainage of melt ponds. Lastly, it is recommended that research be prioritized toward more accurately determining these most influential parameter values by observational studies or by improving parameterizations in the sea ice model.« less

Uncertainty based modeling of rainfall-runoff: Combined differential evolution adaptive Metropolis (DREAM) and K-means clustering

NASA Astrophysics Data System (ADS)

Zahmatkesh, Zahra; Karamouz, Mohammad; Nazif, Sara

2015-09-01

Simulation of rainfall-runoff process in urban areas is of great importance considering the consequences and damages of extreme runoff events and floods. The first issue in flood hazard analysis is rainfall simulation. Large scale climate signals have been proved to be effective in rainfall simulation and prediction. In this study, an integrated scheme is developed for rainfall-runoff modeling considering different sources of uncertainty. This scheme includes three main steps of rainfall forecasting, rainfall-runoff simulation and future runoff prediction. In the first step, data driven models are developed and used to forecast rainfall using large scale climate signals as rainfall predictors. Due to high effect of different sources of uncertainty on the output of hydrologic models, in the second step uncertainty associated with input data, model parameters and model structure is incorporated in rainfall-runoff modeling and simulation. Three rainfall-runoff simulation models are developed for consideration of model conceptual (structural) uncertainty in real time runoff forecasting. To analyze the uncertainty of the model structure, streamflows generated by alternative rainfall-runoff models are combined, through developing a weighting method based on K-means clustering. Model parameters and input uncertainty are investigated using an adaptive Markov Chain Monte Carlo method. Finally, calibrated rainfall-runoff models are driven using the forecasted rainfall to predict future runoff for the watershed. The proposed scheme is employed in the case study of the Bronx River watershed, New York City. Results of uncertainty analysis of rainfall-runoff modeling reveal that simultaneous estimation of model parameters and input uncertainty significantly changes the probability distribution of the model parameters. It is also observed that by combining the outputs of the hydrological models using the proposed clustering scheme, the accuracy of runoff simulation in the watershed is remarkably improved up to 50% in comparison to the simulations by the individual models. Results indicate that the developed methodology not only provides reliable tools for rainfall and runoff modeling, but also adequate time for incorporating required mitigation measures in dealing with potentially extreme runoff events and flood hazard. Results of this study can be used in identification of the main factors affecting flood hazard analysis.

Automated system for generation of soil moisture products for agricultural drought assessment

NASA Astrophysics Data System (ADS)

Raja Shekhar, S. S.; Chandrasekar, K.; Sesha Sai, M. V. R.; Diwakar, P. G.; Dadhwal, V. K.

2014-11-01

Drought is a frequently occurring disaster affecting lives of millions of people across the world every year. Several parameters, indices and models are being used globally to forecast / early warning of drought and monitoring drought for its prevalence, persistence and severity. Since drought is a complex phenomenon, large number of parameter/index need to be evaluated to sufficiently address the problem. It is a challenge to generate input parameters from different sources like space based data, ground data and collateral data in short intervals of time, where there may be limitation in terms of processing power, availability of domain expertise, specialized models & tools. In this study, effort has been made to automate the derivation of one of the important parameter in the drought studies viz Soil Moisture. Soil water balance bucket model is in vogue to arrive at soil moisture products, which is widely popular for its sensitivity to soil conditions and rainfall parameters. This model has been encoded into "Fish-Bone" architecture using COM technologies and Open Source libraries for best possible automation to fulfill the needs for a standard procedure of preparing input parameters and processing routines. The main aim of the system is to provide operational environment for generation of soil moisture products by facilitating users to concentrate on further enhancements and implementation of these parameters in related areas of research, without re-discovering the established models. Emphasis of the architecture is mainly based on available open source libraries for GIS and Raster IO operations for different file formats to ensure that the products can be widely distributed without the burden of any commercial dependencies. Further the system is automated to the extent of user free operations if required with inbuilt chain processing for every day generation of products at specified intervals. Operational software has inbuilt capabilities to automatically download requisite input parameters like rainfall, Potential Evapotranspiration (PET) from respective servers. It can import file formats like .grd, .hdf, .img, generic binary etc, perform geometric correction and re-project the files to native projection system. The software takes into account the weather, crop and soil parameters to run the designed soil water balance model. The software also has additional features like time compositing of outputs to generate weekly, fortnightly profiles for further analysis. Other tools to generate "Area Favorable for Crop Sowing" using the daily soil moisture with highly customizable parameters interface has been provided. A whole India analysis would now take a mere 20 seconds for generation of soil moisture products which would normally take one hour per day using commercial software.

Models for patients' recruitment in clinical trials and sensitivity analysis.

PubMed

Mijoule, Guillaume; Savy, Stéphanie; Savy, Nicolas

2012-07-20

Taking a decision on the feasibility and estimating the duration of patients' recruitment in a clinical trial are very important but very hard questions to answer, mainly because of the huge variability of the system. The more elaborated works on this topic are those of Anisimov and co-authors, where they investigate modelling of the enrolment period by using Gamma-Poisson processes, which allows to develop statistical tools that can help the manager of the clinical trial to answer these questions and thus help him to plan the trial. The main idea is to consider an ongoing study at an intermediate time, denoted t(1). Data collected on [0,t(1)] allow to calibrate the parameters of the model, which are then used to make predictions on what will happen after t(1). This method allows us to estimate the probability of ending the trial on time and give possible corrective actions to the trial manager especially regarding how many centres have to be open to finish on time. In this paper, we investigate a Pareto-Poisson model, which we compare with the Gamma-Poisson one. We will discuss the accuracy of the estimation of the parameters and compare the models on a set of real case data. We make the comparison on various criteria : the expected recruitment duration, the quality of fitting to the data and its sensitivity to parameter errors. We discuss the influence of the centres opening dates on the estimation of the duration. This is a very important question to deal with in the setting of our data set. In fact, these dates are not known. For this discussion, we consider a uniformly distributed approach. Finally, we study the sensitivity of the expected duration of the trial with respect to the parameters of the model : we calculate to what extent an error on the estimation of the parameters generates an error in the prediction of the duration.

Uncertainty Quantification and Sensitivity Analysis in the CICE v5.1 Sea Ice Model

NASA Astrophysics Data System (ADS)

Urrego-Blanco, J. R.; Urban, N. M.

2015-12-01

Changes in the high latitude climate system have the potential to affect global climate through feedbacks with the atmosphere and connections with mid latitudes. Sea ice and climate models used to understand these changes have uncertainties that need to be characterized and quantified. In this work we characterize parametric uncertainty in Los Alamos Sea Ice model (CICE) and quantify the sensitivity of sea ice area, extent and volume with respect to uncertainty in about 40 individual model parameters. Unlike common sensitivity analyses conducted in previous studies where parameters are varied one-at-a-time, this study uses a global variance-based approach in which Sobol sequences are used to efficiently sample the full 40-dimensional parameter space. This approach requires a very large number of model evaluations, which are expensive to run. A more computationally efficient approach is implemented by training and cross-validating a surrogate (emulator) of the sea ice model with model output from 400 model runs. The emulator is used to make predictions of sea ice extent, area, and volume at several model configurations, which are then used to compute the Sobol sensitivity indices of the 40 parameters. A ranking based on the sensitivity indices indicates that model output is most sensitive to snow parameters such as conductivity and grain size, and the drainage of melt ponds. The main effects and interactions among the most influential parameters are also estimated by a non-parametric regression technique based on generalized additive models. It is recommended research to be prioritized towards more accurately determining these most influential parameters values by observational studies or by improving existing parameterizations in the sea ice model.

Integrating satellite actual evapotranspiration patterns into distributed model parametrization and evaluation for a mesoscale catchment

NASA Astrophysics Data System (ADS)

Demirel, M. C.; Mai, J.; Stisen, S.; Mendiguren González, G.; Koch, J.; Samaniego, L. E.

2016-12-01

Distributed hydrologic models are traditionally calibrated and evaluated against observations of streamflow. Spatially distributed remote sensing observations offer a great opportunity to enhance spatial model calibration schemes. For that it is important to identify the model parameters that can change spatial patterns before the satellite based hydrologic model calibration. Our study is based on two main pillars: first we use spatial sensitivity analysis to identify the key parameters controlling the spatial distribution of actual evapotranspiration (AET). Second, we investigate the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mesoscale Hydrologic Model (mHM). This distributed model is selected as it allows for a change in the spatial distribution of key soil parameters through the calibration of pedo-transfer function parameters and includes options for using fully distributed daily Leaf Area Index (LAI) directly as input. In addition the simulated AET can be estimated at the spatial resolution suitable for comparison to the spatial patterns observed using MODIS data. We introduce a new dynamic scaling function employing remotely sensed vegetation to downscale coarse reference evapotranspiration. In total, 17 parameters of 47 mHM parameters are identified using both sequential screening and Latin hypercube one-at-a-time sampling methods. The spatial patterns are found to be sensitive to the vegetation parameters whereas streamflow dynamics are sensitive to the PTF parameters. The results of multi-objective model calibration show that calibration of mHM against observed streamflow does not reduce the spatial errors in AET while they improve only the streamflow simulations. We will further examine the results of model calibration using only multi spatial objective functions measuring the association between observed AET and simulated AET maps and another case including spatial and streamflow metrics together.

Effects of temporal and spatial resolution of calibration data on integrated hydrologic water quality model identification

NASA Astrophysics Data System (ADS)

Jiang, Sanyuan; Jomaa, Seifeddine; Büttner, Olaf; Rode, Michael

2014-05-01

Hydrological water quality modeling is increasingly used for investigating runoff and nutrient transport processes as well as watershed management but it is mostly unclear how data availablity determins model identification. In this study, the HYPE (HYdrological Predictions for the Environment) model, which is a process-based, semi-distributed hydrological water quality model, was applied in two different mesoscale catchments (Selke (463 km2) and Weida (99 km2)) located in central Germany to simulate discharge and inorganic nitrogen (IN) transport. PEST and DREAM(ZS) were combined with the HYPE model to conduct parameter calibration and uncertainty analysis. Split-sample test was used for model calibration (1994-1999) and validation (1999-2004). IN concentration and daily IN load were found to be highly correlated with discharge, indicating that IN leaching is mainly controlled by runoff. Both dynamics and balances of water and IN load were well captured with NSE greater than 0.83 during validation period. Multi-objective calibration (calibrating hydrological and water quality parameters simultaneously) was found to outperform step-wise calibration in terms of model robustness. Multi-site calibration was able to improve model performance at internal sites, decrease parameter posterior uncertainty and prediction uncertainty. Nitrogen-process parameters calibrated using continuous daily averages of nitrate-N concentration observations produced better and more robust simulations of IN concentration and load, lower posterior parameter uncertainty and IN concentration prediction uncertainty compared to the calibration against uncontinuous biweekly nitrate-N concentration measurements. Both PEST and DREAM(ZS) are efficient in parameter calibration. However, DREAM(ZS) is more sound in terms of parameter identification and uncertainty analysis than PEST because of its capability to evolve parameter posterior distributions and estimate prediction uncertainty based on global search and Bayesian inference schemes.

Refined Dummy Atom Model of Mg(2+) by Simple Parameter Screening Strategy with Revised Experimental Solvation Free Energy.

PubMed

Jiang, Yang; Zhang, Haiyang; Feng, Wei; Tan, Tianwei

2015-12-28

Metal ions play an important role in the catalysis of metalloenzymes. To investigate metalloenzymes via molecular modeling, a set of accurate force field parameters for metal ions is highly imperative. To extend its application range and improve the performance, the dummy atom model of metal ions was refined through a simple parameter screening strategy using the Mg(2+) ion as an example. Using the AMBER ff03 force field with the TIP3P model, the refined model accurately reproduced the experimental geometric and thermodynamic properties of Mg(2+). Compared with point charge models and previous dummy atom models, the refined dummy atom model yields an enhanced performance for producing reliable ATP/GTP-Mg(2+)-protein conformations in three metalloenzyme systems with single or double metal centers. Similar to other unbounded models, the refined model failed to reproduce the Mg-Mg distance and favored a monodentate binding of carboxylate groups, and these drawbacks needed to be considered with care. The outperformance of the refined model is mainly attributed to the use of a revised (more accurate) experimental solvation free energy and a suitable free energy correction protocol. This work provides a parameter screening strategy that can be readily applied to refine the dummy atom models for metal ions.

Innovation Analysis Approach to Design Parameters of High Speed Train Carriage and Their Intrinsic Complexity Relationships

NASA Astrophysics Data System (ADS)

Xiao, Shou-Ne; Wang, Ming-Meng; Hu, Guang-Zhong; Yang, Guang-Wu

2017-09-01

In view of the problem that it's difficult to accurately grasp the influence range and transmission path of the vehicle top design requirements on the underlying design parameters. Applying directed-weighted complex network to product parameter model is an important method that can clarify the relationships between product parameters and establish the top-down design of a product. The relationships of the product parameters of each node are calculated via a simple path searching algorithm, and the main design parameters are extracted by analysis and comparison. A uniform definition of the index formula for out-in degree can be provided based on the analysis of out-in-degree width and depth and control strength of train carriage body parameters. Vehicle gauge, axle load, crosswind and other parameters with higher values of the out-degree index are the most important boundary conditions; the most considerable performance indices are the parameters that have higher values of the out-in-degree index including torsional stiffness, maximum testing speed, service life of the vehicle, and so on; the main design parameters contain train carriage body weight, train weight per extended metre, train height and other parameters with higher values of the in-degree index. The network not only provides theoretical guidance for exploring the relationship of design parameters, but also further enriches the application of forward design method to high-speed trains.

Oceanic influence on seasonal malaria outbreaks over Senegal and Sahel. Predictability using S4CAST model

NASA Astrophysics Data System (ADS)

Diouf, Ibrahima; Deme, Abdoulaye; Rodriguez-Fonseca, Belen; Suárez-Moreno, Roberto; Cisse, Moustapha; Ndione, Jacques-André; Thierno Gaye, Amadou

2014-05-01

Senegal and, in general, West African regions are affected by important outbreaks of diseases with destructive consequences for human population, livestock and country's economy. The vector-borne diseases such as mainly malaria, Rift Valley Fever and dengue are affected by the interanual to decadal variability of climate. Analysis of the spatial and temporal variability of climate parameters and associated oceanic patterns is important in order to assess the climate impact on malaria transmission. In this study, the approach developed to study the malaria-climate link is predefined by the QWeCI project (Quantifying Weather and Climate Impacts on Health in Developing Countries). Preliminary observations and simulations results over Senegal Ferlo region, confirm that the risk of malaria transmission is mainly linked to climate parameters such as rainfall, temperature and relative humidity; and a lag of one to two months between the maximum of malaria and the maximum of climate parameters as rainfall is observed. As climate variables are able to be predicted from oceanic SST variability in remote regions, this study explores seasonal predictability of malaria incidence outbreaks from previous sea surface temperatures conditions in different ocean basins. We have found causal or coincident relationship between El Niño and malaria parameters by coupling LMM UNILIV malaria model and S4CAST statistiscal model with the aim of predicting the malaria parameters with more than 6 months in advance. In particular, El Niño is linked to an important decrease of the number of mosquitoes and the malaria incidence. Results from this research, after assessing the seasonal malaria parameters, are expected to be useful for decision makers to better access to climate forecasts and application on health in the framework of rolling back malaria transmission.

Dynamics of a delayed intraguild predation model with harvesting

NASA Astrophysics Data System (ADS)

Collera, Juancho A.; Balilo, Aldrin T.

2018-03-01

In [1], a delayed three-species intraguild predation (IGP) model was considered. This particular tri-trophic community module includes a predator and its prey which share a common basal resource for their sustenance [3]. Here, it is assumed that in the absence of predation, the growth of the basal resource follows the delayed logistic equation. Without delay time, the IGP model in [1] reduces to the system considered in [7] where it was shown that IGP may induce chaos even if the functional responses are linear. Meanwhile, in [2] the delayed IGP model in [1] was generalized to include harvesting. Under the assumption that the basal resource has some economic value, a constant harvesting term on the basal resource was incorporated. However, both models in [1] and [2] use the delay time as the main parameter. In this research, we studied the delayed IGP model in [1] with the addition of linear harvesting term on each of the three species. The dynamical behavior of this system is examined using the harvesting rates as main parameter. In particular, we give conditions on the existence, stability, and bifurcations of equilibrium solutions of this system. This allows us to better understand the effects of harvesting in terms of the survival or extinction of one or more species in our system. Numerical simulations are carried out to illustrate our results. In fact, we show that the chaotic behavior in [7] unfolds when the harvesting rate parameter is varied.

Temporal modelling and forecasting of the airborne pollen of Cupressaceae on the southwestern Iberian Peninsula.

PubMed

Silva-Palacios, Inmaculada; Fernández-Rodríguez, Santiago; Durán-Barroso, Pablo; Tormo-Molina, Rafael; Maya-Manzano, José María; Gonzalo-Garijo, Ángela

2016-02-01

Cupressaceae includes species cultivated as ornamentals in the urban environment. This study aims to investigate airborne pollen data for Cupressaceae on the southwestern Iberian Peninsula over a 21-year period and to analyse the trends in these data and their relationship with meteorological parameters using time series analysis. Aerobiological sampling was conducted from 1993 to 2013 in Badajoz (SW Spain). The main pollen season for Cupressaceae lasted, on average, 58 days, ranging from 55 to 112 days, from 24 January to 22 March. Furthermore, a short-term forecasting model has been developed for daily pollen concentrations. The model proposed to forecast the airborne pollen concentration is described by one equation. This expression is composed of two terms: the first term represents the pollen concentration trend in the air according to the average concentration of the previous 10 days; the second term is obtained from considering the actual pollen concentration value, which is calculated based on the most representative meteorological parameters multiplied by a fitting coefficient. Temperature was the main meteorological factor by its influence over daily pollen forecast, being the rain the second most important factor. This model represents a good approach to a continuous balance model of Cupressaceae pollen concentration and is supported by a close agreement between the observed and predicted mean concentrations. The novelty of the proposed model is the analysis of meteorological parameters that are not frequently used in Aerobiology.

Parameter identification of process simulation models as a means for knowledge acquisition and technology transfer

NASA Astrophysics Data System (ADS)

Batzias, Dimitris F.; Ifanti, Konstantina

2012-12-01

Process simulation models are usually empirical, therefore there is an inherent difficulty in serving as carriers for knowledge acquisition and technology transfer, since their parameters have no physical meaning to facilitate verification of the dependence on the production conditions; in such a case, a 'black box' regression model or a neural network might be used to simply connect input-output characteristics. In several cases, scientific/mechanismic models may be proved valid, in which case parameter identification is required to find out the independent/explanatory variables and parameters, which each parameter depends on. This is a difficult task, since the phenomenological level at which each parameter is defined is different. In this paper, we have developed a methodological framework under the form of an algorithmic procedure to solve this problem. The main parts of this procedure are: (i) stratification of relevant knowledge in discrete layers immediately adjacent to the layer that the initial model under investigation belongs to, (ii) design of the ontology corresponding to these layers, (iii) elimination of the less relevant parts of the ontology by thinning, (iv) retrieval of the stronger interrelations between the remaining nodes within the revised ontological network, and (v) parameter identification taking into account the most influential interrelations revealed in (iv). The functionality of this methodology is demonstrated by quoting two representative case examples on wastewater treatment.

Voice Quality Modelling for Expressive Speech Synthesis

PubMed Central

Socoró, Joan Claudi

2014-01-01

This paper presents the perceptual experiments that were carried out in order to validate the methodology of transforming expressive speech styles using voice quality (VoQ) parameters modelling, along with the well-known prosody (F 0, duration, and energy), from a neutral style into a number of expressive ones. The main goal was to validate the usefulness of VoQ in the enhancement of expressive synthetic speech in terms of speech quality and style identification. A harmonic plus noise model (HNM) was used to modify VoQ and prosodic parameters that were extracted from an expressive speech corpus. Perception test results indicated the improvement of obtained expressive speech styles using VoQ modelling along with prosodic characteristics. PMID:24587738

Linear and nonlinear equivalent circuit modeling of CMUTs.

PubMed

Lohfink, Annette; Eccardt, Peter-Christian

2005-12-01

Using piston radiator and plate capacitance theory capacitive micromachined ultrasound transducers (CMUT) membrane cells can be described by one-dimensional (1-D) model parameters. This paper describes in detail a new method, which derives a 1-D model for CMUT arrays from finite-element methods (FEM) simulations. A few static and harmonic FEM analyses of a single CMUT membrane cell are sufficient to derive the mechanical and electrical parameters of an equivalent piston as the moving part of the cell area. For an array of parallel-driven cells, the acoustic parameters are derived as a complex mechanical fluid impedance, depending on the membrane shape form. As a main advantage, the nonlinear behavior of the CMUT can be investigated much easier and faster compared to FEM simulations, e.g., for a design of the maximum applicable voltage depending on the input signal. The 1-D parameter model allows an easy description of the CMUT behavior in air and fluids and simplifies the investigation of wave propagation within the connecting fluid represented by FEM or transmission line matrix (TLM) models.

Stepwise sensitivity analysis from qualitative to quantitative: Application to the terrestrial hydrological modeling of a Conjunctive Surface-Subsurface Process (CSSP) land surface model

NASA Astrophysics Data System (ADS)

Gan, Yanjun; Liang, Xin-Zhong; Duan, Qingyun; Choi, Hyun Il; Dai, Yongjiu; Wu, Huan

2015-06-01

An uncertainty quantification framework was employed to examine the sensitivities of 24 model parameters from a newly developed Conjunctive Surface-Subsurface Process (CSSP) land surface model (LSM). The sensitivity analysis (SA) was performed over 18 representative watersheds in the contiguous United States to examine the influence of model parameters in the simulation of terrestrial hydrological processes. Two normalized metrics, relative bias (RB) and Nash-Sutcliffe efficiency (NSE), were adopted to assess the fit between simulated and observed streamflow discharge (SD) and evapotranspiration (ET) for a 14 year period. SA was conducted using a multiobjective two-stage approach, in which the first stage was a qualitative SA using the Latin Hypercube-based One-At-a-Time (LH-OAT) screening, and the second stage was a quantitative SA using the Multivariate Adaptive Regression Splines (MARS)-based Sobol' sensitivity indices. This approach combines the merits of qualitative and quantitative global SA methods, and is effective and efficient for understanding and simplifying large, complex system models. Ten of the 24 parameters were identified as important across different watersheds. The contribution of each parameter to the total response variance was then quantified by Sobol' sensitivity indices. Generally, parameter interactions contribute the most to the response variance of the CSSP, and only 5 out of 24 parameters dominate model behavior. Four photosynthetic and respiratory parameters are shown to be influential to ET, whereas reference depth for saturated hydraulic conductivity is the most influential parameter for SD in most watersheds. Parameter sensitivity patterns mainly depend on hydroclimatic regime, as well as vegetation type and soil texture. This article was corrected on 26 JUN 2015. See the end of the full text for details.

The validation of a generalized Hooke's law for coronary arteries.

PubMed

Wang, Chong; Zhang, Wei; Kassab, Ghassan S

2008-01-01

The exponential form of constitutive model is widely used in biomechanical studies of blood vessels. There are two main issues, however, with this model: 1) the curve fits of experimental data are not always satisfactory, and 2) the material parameters may be oversensitive. A new type of strain measure in a generalized Hooke's law for blood vessels was recently proposed by our group to address these issues. The new model has one nonlinear parameter and six linear parameters. In this study, the stress-strain equation is validated by fitting the model to experimental data of porcine coronary arteries. Material constants of left anterior descending artery and right coronary artery for the Hooke's law were computed with a separable nonlinear least-squares method with an excellent goodness of fit. A parameter sensitivity analysis shows that the stability of material constants is improved compared with the exponential model and a biphasic model. A boundary value problem was solved to demonstrate that the model prediction can match the measured arterial deformation under experimental loading conditions. The validated constitutive relation will serve as a basis for the solution of various boundary value problems of cardiovascular biomechanics.

On the influence of tyre and structural properties on the stability of bicycles

NASA Astrophysics Data System (ADS)

Doria, Alberto; Roa Melo, Sergio Daniel

2018-06-01

In recent years the Whipple Carvallo Bicycle Model has been extended to analyse high speed stability of bicycles. Various researchers have developed models taking into account the effects of front frame compliance and tyre properties, nonetheless, a systematic analysis has not been yet carried out. This paper aims at analysing parametrically the influence of front frame compliance and tyre properties on the open loop stability of bicycles. Some indexes based on the eigenvalues of the dynamic system are defined to evaluate quantitatively bicycle stability. The parametric analysis is carried out with a factorial design approach to determine the most influential parameters. A commuting and a racing bicycle are considered and numerical results show different effects of the various parameters on each bicycle. In the commuting bicycle, the tyre properties have greater influence than front frame compliance, and the weave mode has the main effect on stability. Conversely, in the racing bicycle, the front frame compliance parameters have greater influence than tyre properties, and the wobble mode has the main effect on stability.

Folding and stability of helical bundle proteins from coarse-grained models.

PubMed

Kapoor, Abhijeet; Travesset, Alex

2013-07-01

We develop a coarse-grained model where solvent is considered implicitly, electrostatics are included as short-range interactions, and side-chains are coarse-grained to a single bead. The model depends on three main parameters: hydrophobic, electrostatic, and side-chain hydrogen bond strength. The parameters are determined by considering three level of approximations and characterizing the folding for three selected proteins (training set). Nine additional proteins (containing up to 126 residues) as well as mutated versions (test set) are folded with the given parameters. In all folding simulations, the initial state is a random coil configuration. Besides the native state, some proteins fold into an additional state differing in the topology (structure of the helical bundle). We discuss the stability of the native states, and compare the dynamics of our model to all atom molecular dynamics simulations as well as some general properties on the interactions governing folding dynamics. Copyright © 2013 Wiley Periodicals, Inc.

A note on `a replenishment policy for items with price-dependent demand, time-proportional deterioration and no shortages'

NASA Astrophysics Data System (ADS)

Shah, Nita H.; Soni, Hardik N.; Gupta, Jyoti

2014-08-01

In a recent paper, Begum et al. (2012, International Journal of Systems Science, 43, 903-910) established pricing and replenishment policy for an inventory system with price-sensitive demand rate, time-proportional deterioration rate which follows three parameters, Weibull distribution and no shortages. In their model formulation, it is observed that the retailer's stock level reaches zero before the deterioration occurs. Consequently, the model resulted in traditional inventory model with price sensitive demand rate and no shortages. Hence, the main purpose of this note is to modify and present complete model formulation for Begum et al. (2012). The proposed model is validated by a numerical example and the sensitivity analysis of parameters is carried out.

A multipurpose model of Hermes-Columbus docking mechanism

NASA Technical Reports Server (NTRS)

Gonzalez-Vallejo, J. J.; Fehse, W.; Tobias, A.

1992-01-01

One of the foreseen missions of the HERMES spacevehicle is the servicing to the Columbus Free Flying Laboratory (MTFF). Docking between the two spacecraft is a critical operation in which the Docking Mechanism (DM) has a major role. In order to analyze and assess robustness of initially selected concepts and to identify suitable implementation solutions, through the investigation of main parameters involved in the docking functions, a multipurpose model of DM was developed and tested. This paper describes the main design features as well as the process of calibrating and testing.

Application of Time-series Model to Predict Groundwater Quality Parameters for Agriculture: (Plain Mehran Case Study)

NASA Astrophysics Data System (ADS)

Mehrdad Mirsanjari, Mir; Mohammadyari, Fatemeh

2018-03-01

Underground water is regarded as considerable water source which is mainly available in arid and semi arid with deficient surface water source. Forecasting of hydrological variables are suitable tools in water resources management. On the other hand, time series concepts is considered efficient means in forecasting process of water management. In this study the data including qualitative parameters (electrical conductivity and sodium adsorption ratio) of 17 underground water wells in Mehran Plain has been used to model the trend of parameters change over time. Using determined model, the qualitative parameters of groundwater is predicted for the next seven years. Data from 2003 to 2016 has been collected and were fitted by AR, MA, ARMA, ARIMA and SARIMA models. Afterward, the best model is determined using information criterion or Akaike (AIC) and correlation coefficient. After modeling parameters, the map of agricultural land use in 2016 and 2023 were generated and the changes between these years were studied. Based on the results, the average of predicted SAR (Sodium Adsorption Rate) in all wells in the year 2023 will increase compared to 2016. EC (Electrical Conductivity) average in the ninth and fifteenth holes and decreases in other wells will be increased. The results indicate that the quality of groundwater for Agriculture Plain Mehran will decline in seven years.

Coupled electromechanical model of the heart: Parallel finite element formulation.

PubMed

Lafortune, Pierre; Arís, Ruth; Vázquez, Mariano; Houzeaux, Guillaume

2012-01-01

In this paper, a highly parallel coupled electromechanical model of the heart is presented and assessed. The parallel-coupled model is thoroughly discussed, with scalability proven up to hundreds of cores. This work focuses on the mechanical part, including the constitutive model (proposing some modifications to pre-existent models), the numerical scheme and the coupling strategy. The model is next assessed through two examples. First, the simulation of a small piece of cardiac tissue is used to introduce the main features of the coupled model and calibrate its parameters against experimental evidence. Then, a more realistic problem is solved using those parameters, with a mesh of the Oxford ventricular rabbit model. The results of both examples demonstrate the capability of the model to run efficiently in hundreds of processors and to reproduce some basic characteristic of cardiac deformation.

Alpha-canonical form representation of the open loop dynamics of the Space Shuttle main engine

NASA Technical Reports Server (NTRS)

Duyar, Almet; Eldem, Vasfi; Merrill, Walter C.; Guo, Ten-Huei

1991-01-01

A parameter and structure estimation technique for multivariable systems is used to obtain a state space representation of open loop dynamics of the space shuttle main engine in alpha-canonical form. The parameterization being used is both minimal and unique. The simplified linear model may be used for fault detection studies and control system design and development.

Using global sensitivity analysis of demographic models for ecological impact assessment.

PubMed

Aiello-Lammens, Matthew E; Akçakaya, H Resit

2017-02-01

Population viability analysis (PVA) is widely used to assess population-level impacts of environmental changes on species. When combined with sensitivity analysis, PVA yields insights into the effects of parameter and model structure uncertainty. This helps researchers prioritize efforts for further data collection so that model improvements are efficient and helps managers prioritize conservation and management actions. Usually, sensitivity is analyzed by varying one input parameter at a time and observing the influence that variation has over model outcomes. This approach does not account for interactions among parameters. Global sensitivity analysis (GSA) overcomes this limitation by varying several model inputs simultaneously. Then, regression techniques allow measuring the importance of input-parameter uncertainties. In many conservation applications, the goal of demographic modeling is to assess how different scenarios of impact or management cause changes in a population. This is challenging because the uncertainty of input-parameter values can be confounded with the effect of impacts and management actions. We developed a GSA method that separates model outcome uncertainty resulting from parameter uncertainty from that resulting from projected ecological impacts or simulated management actions, effectively separating the 2 main questions that sensitivity analysis asks. We applied this method to assess the effects of predicted sea-level rise on Snowy Plover (Charadrius nivosus). A relatively small number of replicate models (approximately 100) resulted in consistent measures of variable importance when not trying to separate the effects of ecological impacts from parameter uncertainty. However, many more replicate models (approximately 500) were required to separate these effects. These differences are important to consider when using demographic models to estimate ecological impacts of management actions. © 2016 Society for Conservation Biology.

Estimation of Ecosystem Parameters of the Community Land Model with DREAM: Evaluation of the Potential for Upscaling Net Ecosystem Exchange

NASA Astrophysics Data System (ADS)

Hendricks Franssen, H. J.; Post, H.; Vrugt, J. A.; Fox, A. M.; Baatz, R.; Kumbhar, P.; Vereecken, H.

2015-12-01

Estimation of net ecosystem exchange (NEE) by land surface models is strongly affected by uncertain ecosystem parameters and initial conditions. A possible approach is the estimation of plant functional type (PFT) specific parameters for sites with measurement data like NEE and application of the parameters at other sites with the same PFT and no measurements. This upscaling strategy was evaluated in this work for sites in Germany and France. Ecosystem parameters and initial conditions were estimated with NEE-time series of one year length, or a time series of only one season. The DREAM(zs) algorithm was used for the estimation of parameters and initial conditions. DREAM(zs) is not limited to Gaussian distributions and can condition to large time series of measurement data simultaneously. DREAM(zs) was used in combination with the Community Land Model (CLM) v4.5. Parameter estimates were evaluated by model predictions at the same site for an independent verification period. In addition, the parameter estimates were evaluated at other, independent sites situated >500km away with the same PFT. The main conclusions are: i) simulations with estimated parameters reproduced better the NEE measurement data in the verification periods, including the annual NEE-sum (23% improvement), annual NEE-cycle and average diurnal NEE course (error reduction by factor 1,6); ii) estimated parameters based on seasonal NEE-data outperformed estimated parameters based on yearly data; iii) in addition, those seasonal parameters were often also significantly different from their yearly equivalents; iv) estimated parameters were significantly different if initial conditions were estimated together with the parameters. We conclude that estimated PFT-specific parameters improve land surface model predictions significantly at independent verification sites and for independent verification periods so that their potential for upscaling is demonstrated. However, simulation results also indicate that possibly the estimated parameters mask other model errors. This would imply that their application at climatic time scales would not improve model predictions. A central question is whether the integration of many different data streams (e.g., biomass, remotely sensed LAI) could solve the problems indicated here.

Influences of brain tissue poroelastic constants on intracranial pressure (ICP) during constant-rate infusion.

PubMed

Li, Xiaogai; von Holst, Hans; Kleiven, Svein

2013-01-01

A 3D finite element (FE) model has been developed to study the mean intracranial pressure (ICP) response during constant-rate infusion using linear poroelasticity. Due to the uncertainties in the poroelastic constants for brain tissue, the influence of each of the main parameters on the transient ICP infusion curve was studied. As a prerequisite for transient analysis, steady-state simulations were performed first. The simulated steady-state pressure distribution in the brain tissue for a normal cerebrospinal fluid (CSF) circulation system showed good correlation with experiments from the literature. Furthermore, steady-state ICP closely followed the infusion experiments at different infusion rates. The verified steady-state models then served as a baseline for the subsequent transient models. For transient analysis, the simulated ICP shows a similar tendency to that found in the experiments, however, different values of the poroelastic constants have a significant effect on the infusion curve. The influence of the main poroelastic parameters including the Biot coefficient α, Skempton coefficient B, drained Young's modulus E, Poisson's ratio ν, permeability κ, CSF absorption conductance C(b) and external venous pressure p(b) was studied to investigate the influence on the pressure response. It was found that the value of the specific storage term S(ε) is the dominant factor that influences the infusion curve, and the drained Young's modulus E was identified as the dominant parameter second to S(ε). Based on the simulated infusion curves from the FE model, artificial neural network (ANN) was used to find an optimised parameter set that best fit the experimental curve. The infusion curves from both the FE simulation and using ANN confirmed the limitation of linear poroelasticity in modelling the transient constant-rate infusion.

Teleseismic Body Wave Analysis for the 27 September 2003 Altai, Earthquake (Mw7.4) and Large Aftershocks

NASA Astrophysics Data System (ADS)

Gomez-Gonzalez, J. M.; Mellors, R.

2007-05-01

We investigate the kinematics of the rupture process for the September 27, 2003, Mw7.3, Altai earthquake and its associated large aftershocks. This is the largest earthquake striking the Altai mountains within the last 50 years, which provides important constraints on the ongoing tectonics. The fault plane solution obtained by teleseismic body waveform modeling indicated a predominantly strike-slip event (strike=130, dip=75, rake 170), Scalar moment for the main shock ranges from 0.688 to 1.196E+20 N m, a source duration of about 20 to 42 s, and an average centroid depth of 10 km. Source duration would indicate a fault length of about 130 - 270 km. The main shock was followed closely by two aftershocks (Mw5.7, Mw6.4) occurred the same day, another aftershock (Mw6.7) occurred on 1 October , 2003. We also modeled the second aftershock (Mw6.4) to asses geometric similarities during their respective rupture process. This aftershock occurred spatially very close to the mainshock and possesses a similar fault plane solution (strike=128, dip=71, rake=154), and centroid depth (13 km). Several local conditions, such as the crustal model and fault geometry, affect the correct estimation of some source parameters. We perfume a sensitivity evaluation of several parameters, including centroid depth, scalar moment and source duration, based on a point and finite source modeling. The point source approximation results are the departure parameters for the finite source exploration. We evaluate the different reported parameters to discard poor constrained models. In addition, deformation data acquired by InSAR are also included in the analysis.

Towards a new parameterization of ice particles growth

NASA Astrophysics Data System (ADS)

Krakovska, Svitlana; Khotyayintsev, Volodymyr; Bardakov, Roman; Shpyg, Vitaliy

2017-04-01

Ice particles are the main component of polar clouds, unlike in warmer regions. That is why correct representation of ice particle formation and growth in NWP and other numerical atmospheric models is crucial for understanding of the whole chain of water transformation, including precipitation formation and its further deposition as snow in polar glaciers. Currently, parameterization of ice in atmospheric models is among the most difficult challenges. In the presented research, we present a renewed theoretical analysis of the evolution of mixed cloud or cold fog from the moment of ice nuclei activation until complete crystallization. The simplified model is proposed that includes both supercooled cloud droplets and initially uniform particles of ice, as well as water vapor. We obtain independent dimensionless input parameters of a cloud, and find main scenarios and stages of evolution of the microphysical state of the cloud. The characteristic times and particle sizes have been found, as well as the peculiarities of microphysical processes at each stage of evolution. In the future, the proposed original and physically grounded approximations may serve as a basis for a new scientifically substantiated and numerically efficient parameterizations of microphysical processes in mixed clouds for modern atmospheric models. The relevance of theoretical analysis is confirmed by numerical modeling for a wide range of combinations of possible conditions in the atmosphere, including cold polar regions. The main conclusion of the research is that until complete disappearance of cloud droplets, the growth of ice particles occurs at a practically constant humidity corresponding to the saturated humidity over water, regardless to all other parameters of a cloud. This process can be described by the one differential equation of the first order. Moreover, a dimensionless parameter has been proposed as a quantitative criterion of a transition from dominant depositional to intense collectional growth of ice particles; it could be used in models with bulk parameterization of cloud and precipitation formation processes.

Launch Vehicle Propulsion Parameter Design Multiple Selection Criteria

NASA Technical Reports Server (NTRS)

Shelton, Joey Dewayne

2004-01-01

The optimization tool described herein addresses and emphasizes the use of computer tools to model a system and focuses on a concept development approach for a liquid hydrogen/liquid oxygen single-stage-to-orbit system, but more particularly the development of the optimized system using new techniques. This methodology uses new and innovative tools to run Monte Carlo simulations, genetic algorithm solvers, and statistical models in order to optimize a design concept. The concept launch vehicle and propulsion system were modeled and optimized to determine the best design for weight and cost by varying design and technology parameters. Uncertainty levels were applied using Monte Carlo Simulations and the model output was compared to the National Aeronautics and Space Administration Space Shuttle Main Engine. Several key conclusions are summarized here for the model results. First, the Gross Liftoff Weight and Dry Weight were 67% higher for the design case for minimization of Design, Development, Test and Evaluation cost when compared to the weights determined by the minimization of Gross Liftoff Weight case. In turn, the Design, Development, Test and Evaluation cost was 53% higher for optimized Gross Liftoff Weight case when compared to the cost determined by case for minimization of Design, Development, Test and Evaluation cost. Therefore, a 53% increase in Design, Development, Test and Evaluation cost results in a 67% reduction in Gross Liftoff Weight. Secondly, the tool outputs define the sensitivity of propulsion parameters, technology and cost factors and how these parameters differ when cost and weight are optimized separately. A key finding was that for a Space Shuttle Main Engine thrust level the oxidizer/fuel ratio of 6.6 resulted in the lowest Gross Liftoff Weight rather than at 5.2 for the maximum specific impulse, demonstrating the relationships between specific impulse, engine weight, tank volume and tank weight. Lastly, the optimum chamber pressure for Gross Liftoff Weight minimization was 2713 pounds per square inch as compared to 3162 for the Design, Development, Test and Evaluation cost optimization case. This chamber pressure range is close to 3000 pounds per square inch for the Space Shuttle Main Engine.

Solar System Test of Gravitational Theories

NASA Technical Reports Server (NTRS)

Shapiro, Irwin I.

2003-01-01

We are engaged in testing gravitational theory, mainly using observations of objects in the solar system and mainly on the interplanetary scale. Our goal is either to detect departures from the standard model (general relativity) - if any exist within the level of sensitivity of our data - or to place tighter bounds on such departures. For this project, we have analyzed a combination of observational data with our model of the solar system, including primarily planetary radar ranging, lunar laser ranging, and spacecraft tracking, but also including both pulsar timing and pulsar VLBI measurements. In the past year, we have included new data in the analysis, primarily tracking data from the Mars Pathfinder mission. Although these data are relatively few in number, they extend the time span of high-precision tracking on the surface of Mars from six years to over 20. As a result, the statistical standard deviation of our estimate of Mars precession rate has nearly halved, and the rest of the parameters in our solar-system model have experienced a corresponding, albeit smaller, improvement (about 20% for t,he relevant asteroid masses, 10% for the semimajor axis of Mars orbit, and smaller amounts for most other parameters). In the coming year, we plan to continue adding data to our set, as available. Ne 2 expect to use these data and improved models to obtain estimates of the gravitational- theory parameters and to publish these results.

Dependence of intramyocardial pressure and coronary flow on ventricular loading and contractility: a model study.

PubMed

Bovendeerd, Peter H M; Borsje, Petra; Arts, Theo; van De Vosse, Frans N

2006-12-01

The phasic coronary arterial inflow during the normal cardiac cycle has been explained with simple (waterfall, intramyocardial pump) models, emphasizing the role of ventricular pressure. To explain changes in isovolumic and low afterload beats, these models were extended with the effect of three-dimensional wall stress, nonlinear characteristics of the coronary bed, and extravascular fluid exchange. With the associated increase in the number of model parameters, a detailed parameter sensitivity analysis has become difficult. Therefore we investigated the primary relations between ventricular pressure and volume, wall stress, intramyocardial pressure and coronary blood flow, with a mathematical model with a limited number of parameters. The model replicates several experimental observations: the phasic character of coronary inflow is virtually independent of maximum ventricular pressure, the amplitude of the coronary flow signal varies about proportionally with cardiac contractility, and intramyocardial pressure in the ventricular wall may exceed ventricular pressure. A parameter sensitivity analysis shows that the normalized amplitude of coronary inflow is mainly determined by contractility, reflected in ventricular pressure and, at low ventricular volumes, radial wall stress. Normalized flow amplitude is less sensitive to myocardial coronary compliance and resistance, and to the relation between active fiber stress, time, and sarcomere shortening velocity.

A multidisciplinary methodological approach for slope stability assessment of an area prone to shallow landslides

NASA Astrophysics Data System (ADS)

Bordoni, Massimiliano; Meisina, Claudia; Valentino, Roberto; Bittelli, Marco; Battista Bischetti, Gian; Vercesi, Alberto; Chersich, Silvia; Giuseppina Persichillo, Maria

2016-04-01

Rainfall-induced shallow landslides are widespread slope instabilities phenomena in several hilly and mountainous contexts all over the world. Due to their high density of diffusion also in small areas, they can provoke important damages to terrains, infrastructures, buildings, and, sometimes, loss of human lives. Shallow landslides affect superficial soils of limited thickness (generally lower than 2 m), located above weathered or not bedrock levels. Their triggering mechanism is strictly linked to the hydrological response of the soils to rainfall events. Thus, it becomes fundamental a comprehensive analysis of the soil properties which can influence the susceptibility of a slope to shallow landslides. In this study, a multidisciplinary approach was followed for the characterization of the soils and the individuation of the triggering conditions in an area particularly prone to shallow failures, for slope stability assessment. This area corresponded to the hilly sector of North-Eastern Oltrepò Pavese (Lombardy Region, Northern Italy), where the density of shallow landslides is really high, reaching more than 36 landslides per km2. The soils of the study area were analyzed through a multidisciplinary characterization, which took into account for the main geotechnical, mechanical and mineralogical parameters and also for the main pedological features of the materials. This approach allowed for identifying the main features and the horizons which could influence the soil behavior in relation to the conditions that are preparatory to shallow landslides development. In a test-site slope, representative of the main geomorphological, geological and landslides distribution characteristics typical of the study area, a continuous in time monitoring of meteorological (rainfall amount, air temperature, air humidity, atmospheric pressure, net solar radiation, wind speed and direction) and hydrological (soil water content, pore water pressure) parameters was implemented. In this way, the triggering mechanism of shallow failures in the study area was identified and the effects of the different hydrological parameters on slope stability assessment through a simplified physically-based model (Lu and Godt's model) was quantified. In several slopes, representative of the main land uses (cultivated vineyards, abandoned vineyards, shrub lands, woodlands) of the study area, soil root reinforcement of the vegetation of the slopes was measured since root density and root tensile strength. This parameter was, then, integrated in the same simplified physically-based model (Lu and Godt's model), in order to improve the assessment of slope instabilities. Moreover, this analysis allowed for a better identification of the land use classes more susceptible to shallow landslides, furnishing an important tool for land planning.

Scaling relations for a needle-like electron beam plasma from the self-similar behavior in beam propagation

NASA Astrophysics Data System (ADS)

Bai, Xiaoyan; Chen, Chen; Li, Hong; Liu, Wandong; Chen, Wei

2017-10-01

Scaling relations of the main parameters of a needle-like electron beam plasma (EBP) to the initial beam energy, beam current, and discharge pressures are presented. The relations characterize the main features of the plasma in three parameter space and can provide great convenience in plasma design with electron beams. First, starting from the self-similar behavior of electron beam propagation, energy and charge depositions in beam propagation were expressed analytically as functions of the three parameters. Second, according to the complete coupled theoretical model of an EBP and appropriate assumptions, independent equations controlling the density and space charges were derived. Analytical expressions for the density and charges versus functions of energy and charge depositions were obtained. Finally, with the combination of the expressions derived in the above two steps, scaling relations of the density and potential to the three parameters were constructed. Meanwhile, numerical simulations were used to test part of the scaling relations.

Water quality modeling in the dead end sections of drinking water (Supplement)

EPA Pesticide Factsheets

Dead-end sections of drinking water distribution networks are known to be problematic zones in terms of water quality degradation. Extended residence time due to water stagnation leads to rapid reduction of disinfectant residuals allowing the regrowth of microbial pathogens. Water quality models developed so far apply spatial aggregation and temporal averaging techniques for hydraulic parameters by assigning hourly averaged water demands to the main nodes of the network. Although this practice has generally resulted in minimal loss of accuracy for the predicted disinfectant concentrations in main water transmission lines, this is not the case for the peripheries of the distribution network. This study proposes a new approach for simulating disinfectant residuals in dead end pipes while accounting for both spatial and temporal variability in hydraulic and transport parameters. A stochastic demand generator was developed to represent residential water pulses based on a non-homogenous Poisson process. Dispersive solute transport was considered using highly dynamic dispersion rates. A genetic algorithm was used tocalibrate the axial hydraulic profile of the dead-end pipe based on the different demand shares of the withdrawal nodes. A parametric sensitivity analysis was done to assess the model performance under variation of different simulation parameters. A group of Monte-Carlo ensembles was carried out to investigate the influence of spatial and temporal variation

Water Quality Modeling in the Dead End Sections of Drinking ...

EPA Pesticide Factsheets

Dead-end sections of drinking water distribution networks are known to be problematic zones in terms of water quality degradation. Extended residence time due to water stagnation leads to rapid reduction of disinfectant residuals allowing the regrowth of microbial pathogens. Water quality models developed so far apply spatial aggregation and temporal averaging techniques for hydraulic parameters by assigning hourly averaged water demands to the main nodes of the network. Although this practice has generally resulted in minimal loss of accuracy for the predicted disinfectant concentrations in main water transmission lines, this is not the case for the peripheries of a distribution network. This study proposes a new approach for simulating disinfectant residuals in dead end pipes while accounting for both spatial and temporal variability in hydraulic and transport parameters. A stochastic demand generator was developed to represent residential water pulses based on a non-homogenous Poisson process. Dispersive solute transport was considered using highly dynamic dispersion rates. A genetic algorithm was used to calibrate the axial hydraulic profile of the dead-end pipe based on the different demand shares of the withdrawal nodes. A parametric sensitivity analysis was done to assess the model performance under variation of different simulation parameters. A group of Monte-Carlo ensembles was carried out to investigate the influence of spatial and temporal variations

Combining the ‘bottom up’ and ‘top down’ approaches in pharmacokinetic modelling: fitting PBPK models to observed clinical data

PubMed Central

Tsamandouras, Nikolaos; Rostami-Hodjegan, Amin; Aarons, Leon

2015-01-01

Pharmacokinetic models range from being entirely exploratory and empirical, to semi-mechanistic and ultimately complex physiologically based pharmacokinetic (PBPK) models. This choice is conditional on the modelling purpose as well as the amount and quality of the available data. The main advantage of PBPK models is that they can be used to extrapolate outside the studied population and experimental conditions. The trade-off for this advantage is a complex system of differential equations with a considerable number of model parameters. When these parameters cannot be informed from in vitro or in silico experiments they are usually optimized with respect to observed clinical data. Parameter estimation in complex models is a challenging task associated with many methodological issues which are discussed here with specific recommendations. Concepts such as structural and practical identifiability are described with regards to PBPK modelling and the value of experimental design and sensitivity analyses is sketched out. Parameter estimation approaches are discussed, while we also highlight the importance of not neglecting the covariance structure between model parameters and the uncertainty and population variability that is associated with them. Finally the possibility of using model order reduction techniques and minimal semi-mechanistic models that retain the physiological-mechanistic nature only in the parts of the model which are relevant to the desired modelling purpose is emphasized. Careful attention to all the above issues allows us to integrate successfully information from in vitro or in silico experiments together with information deriving from observed clinical data and develop mechanistically sound models with clinical relevance. PMID:24033787

Optimization-Based Inverse Identification of the Parameters of a Concrete Cap Material Model

NASA Astrophysics Data System (ADS)

Král, Petr; Hokeš, Filip; Hušek, Martin; Kala, Jiří; Hradil, Petr

2017-10-01

Issues concerning the advanced numerical analysis of concrete building structures in sophisticated computing systems currently require the involvement of nonlinear mechanics tools. The efforts to design safer, more durable and mainly more economically efficient concrete structures are supported via the use of advanced nonlinear concrete material models and the geometrically nonlinear approach. The application of nonlinear mechanics tools undoubtedly presents another step towards the approximation of the real behaviour of concrete building structures within the framework of computer numerical simulations. However, the success rate of this application depends on having a perfect understanding of the behaviour of the concrete material models used and having a perfect understanding of the used material model parameters meaning. The effective application of nonlinear concrete material models within computer simulations often becomes very problematic because these material models very often contain parameters (material constants) whose values are difficult to obtain. However, getting of the correct values of material parameters is very important to ensure proper function of a concrete material model used. Today, one possibility, which permits successful solution of the mentioned problem, is the use of optimization algorithms for the purpose of the optimization-based inverse material parameter identification. Parameter identification goes hand in hand with experimental investigation while it trying to find parameter values of the used material model so that the resulting data obtained from the computer simulation will best approximate the experimental data. This paper is focused on the optimization-based inverse identification of the parameters of a concrete cap material model which is known under the name the Continuous Surface Cap Model. Within this paper, material parameters of the model are identified on the basis of interaction between nonlinear computer simulations, gradient based and nature inspired optimization algorithms and experimental data, the latter of which take the form of a load-extension curve obtained from the evaluation of uniaxial tensile test results. The aim of this research was to obtain material model parameters corresponding to the quasi-static tensile loading which may be further used for the research involving dynamic and high-speed tensile loading. Based on the obtained results it can be concluded that the set goal has been reached.

Reconstruction of Twist Torque in Main Parachute Risers

NASA Technical Reports Server (NTRS)

Day, Joshua D.

2015-01-01

The reconstruction of twist torque in the Main Parachute Risers of the Capsule Parachute Assembly System (CPAS) has been successfully used to validate CPAS Model Memo conservative twist torque equations. Reconstruction of basic, one degree of freedom drop tests was used to create a functional process for the evaluation of more complex, rigid body simulation. The roll, pitch, and yaw of the body, the fly-out angles of the parachutes, and the relative location of the parachutes to the body are inputs to the torque simulation. The data collected by the Inertial Measurement Unit (IMU) was used to calculate the true torque. The simulation then used photogrammetric and IMU data as inputs into the Model Memo equations. The results were then compared to the true torque results to validate the Model Memo equations. The Model Memo parameters were based off of steel risers and the parameters will need to be re-evaluated for different materials. Photogrammetric data was found to be more accurate than the inertial data in accounting for the relative rotation between payload and cluster. The Model Memo equations were generally a good match and when not matching were generally conservative.

Ice phase in altocumulus clouds over Leipzig: remote sensing observations and detailed modeling

NASA Astrophysics Data System (ADS)

Simmel, M.; Bühl, J.; Ansmann, A.; Tegen, I.

2015-09-01

The present work combines remote sensing observations and detailed cloud modeling to investigate two altocumulus cloud cases observed over Leipzig, Germany. A suite of remote sensing instruments was able to detect primary ice at rather high temperatures of -6 °C. For comparison, a second mixed phase case at about -25 °C is introduced. To further look into the details of cloud microphysical processes, a simple dynamics model of the Asai-Kasahara (AK) type is combined with detailed spectral microphysics (SPECS) forming the model system AK-SPECS. Vertical velocities are prescribed to force the dynamics, as well as main cloud features, to be close to the observations. Subsequently, sensitivity studies with respect to ice microphysical parameters are carried out with the aim to quantify the most important sensitivities for the cases investigated. For the cases selected, the liquid phase is mainly determined by the model dynamics (location and strength of vertical velocity), whereas the ice phase is much more sensitive to the microphysical parameters (ice nucleating particle (INP) number, ice particle shape). The choice of ice particle shape may induce large uncertainties that are on the same order as those for the temperature-dependent INP number distribution.

Ice phase in altocumulus clouds over Leipzig: remote sensing observations and detailed modelling

NASA Astrophysics Data System (ADS)

Simmel, M.; Bühl, J.; Ansmann, A.; Tegen, I.

2015-01-01

The present work combines remote sensing observations and detailed cloud modeling to investigate two altocumulus cloud cases observed over Leipzig, Germany. A suite of remote sensing instruments was able to detect primary ice at rather warm temperatures of -6 °C. For comparison, a second mixed phase case at about -25 °C is introduced. To further look into the details of cloud microphysical processes a simple dynamics model of the Asai-Kasahara type is combined with detailed spectral microphysics forming the model system AK-SPECS. Vertical velocities are prescribed to force the dynamics as well as main cloud features to be close to the observations. Subsequently, sensitivity studies with respect to ice microphysical parameters are carried out with the aim to quantify the most important sensitivities for the cases investigated. For the cases selected, the liquid phase is mainly determined by the model dynamics (location and strength of vertical velocity) whereas the ice phase is much more sensitive to the microphysical parameters (ice nuclei (IN) number, ice particle shape). The choice of ice particle shape may induce large uncertainties which are in the same order as those for the temperature-dependent IN number distribution.

Modeling and Prediction of Krueger Device Noise

NASA Technical Reports Server (NTRS)

Guo, Yueping; Burley, Casey L.; Thomas, Russell H.

2016-01-01

This paper presents the development of a noise prediction model for aircraft Krueger flap devices that are considered as alternatives to leading edge slotted slats. The prediction model decomposes the total Krueger noise into four components, generated by the unsteady flows, respectively, in the cove under the pressure side surface of the Krueger, in the gap between the Krueger trailing edge and the main wing, around the brackets supporting the Krueger device, and around the cavity on the lower side of the main wing. For each noise component, the modeling follows a physics-based approach that aims at capturing the dominant noise-generating features in the flow and developing correlations between the noise and the flow parameters that control the noise generation processes. The far field noise is modeled using each of the four noise component's respective spectral functions, far field directivities, Mach number dependencies, component amplitudes, and other parametric trends. Preliminary validations are carried out by using small scale experimental data, and two applications are discussed; one for conventional aircraft and the other for advanced configurations. The former focuses on the parametric trends of Krueger noise on design parameters, while the latter reveals its importance in relation to other airframe noise components.

The timbre model

NASA Astrophysics Data System (ADS)

Jensen, Kristoffer

2002-11-01

A timbre model is proposed for use in multiple applications. This model, which encompasses all voiced isolated musical instruments, has an intuitive parameter set, fixed size, and separates the sounds in dimensions akin to the timbre dimensions as proposed in timbre research. The analysis of the model parameters is fully documented, and it proposes, in particular, a method for the estimation of the difficult decay/release split-point. The main parameters of the model are the spectral envelope, the attack/release durations and relative amplitudes, and the inharmonicity and the shimmer and jitter (which provide both for the slow random variations of the frequencies and amplitudes, and also for additive noises). Some of the applications include synthesis, where a real-time application is being developed with an intuitive gui, classification, and search of sounds based on the content of the sounds, and a further understanding of acoustic musical instrument behavior. In order to present the background of the model, this presentation will start with sinusoidal A/S, some timbre perception research, then present the timbre model, show the validity for individual music instrument sounds, and finally introduce some expression additions to the model.

Simulation of Runoff and Reservoir Inflow for Use in a Flood-Analysis Model for the Delaware River, Pennsylvania, New Jersey, and New York, 2004-2006

USGS Publications Warehouse

Goode, Daniel J.; Koerkle, Edward H.; Hoffman, Scott A.; Regan, R. Steve; Hay, Lauren E.; Markstrom, Steven L.

2010-01-01

A model was developed to simulate inflow to reservoirs and watershed runoff to streams during three high-flow events between September 2004 and June 2006 for the main-stem subbasin of the Delaware River draining to Trenton, N.J. The model software is a modified version of the U.S. Geological Survey (USGS) Precipitation-Runoff Modeling System (PRMS), a modular, physically based, distributed-parameter modeling system developed to evaluate the impacts of various combinations of precipitation, climate, and land use on surface-water runoff and general basin hydrology. The PRMS model simulates time periods associated with main-stem flooding that occurred in September 2004, April 2005, and June 2006 and uses both daily and hourly time steps. Output from the PRMS model was formatted for use as inflows to a separately documented reservoir and riverrouting model, the HEC-ResSim model, developed by the U.S. Army Corps of Engineers Hydrologic Engineering Center to evaluate flooding. The models were integrated through a graphical user interface. The study area is the 6,780 square-mile watershed of the Delaware River in the states of Pennsylvania, New Jersey, and New York that drains to Trenton, N.J. A geospatial database was created for use with a geographic information system to assist model discretization, determine land-surface characterization, and estimate model parameters. The USGS National Elevation Dataset at 100-meter resolution, a Digital Elevation Model (DEM), was used for model discretization into streams and hydrologic response units. In addition, geospatial processing was used to estimate initial model parameters from the DEM and other data layers, including land use. The model discretization represents the study area using 869 hydrologic response units and 452 stream segments. The model climate data for point stations were obtained from multiple sources. These sources included daily data for 22 National Weather Service (NWS) Cooperative Climate Station network stations, hourly data for 15 stations from the National Climatic Data Center, hourly data for 1 station from the NWS Middle Atlantic River Forecast Center records, and daily and hourly data for 7 stations operated by the New York City Department of Environmental Protection. The NWS Multisensor Precipitation Estimate data set for 2001-2007 was used for computing daily precipitation for the model and for computing hourly precipitation for storm simulation periods. Calibration of the PRMS model included regression and optimization algorithms, as well as manual adjustments of model parameters. The general goal of the calibration procedure was to minimize the difference between discharge measured at USGS streamgages and the corresponding discharge simulated by the model. Daily streamflow data from 35 USGS streamgages were used in model calibration. The streamflow data represent areas draining from 20.2 to 6,780 square miles. The PRMS model simulates reservoir inflow and watershed runoff for use as input into HECResSim for the purpose of evaluating and comparing the effects of different watershed conditions on main-stem flooding in the Delaware River watershed draining to Trenton, N.J. The PRMS model is useful as a planning tool to simulate the effects of land-use changes and different antecedent conditions on local runoff and reservoir inflow and, as input to the HEC-ResSim model, on flood flows in the main stem of the Delaware River.

A fuzzy rumor spreading model based on transmission capacity

NASA Astrophysics Data System (ADS)

Zhang, Yi; Xu, Jiuping; Wu, Yue

This paper proposes a rumor spreading model that considers three main factors: the event importance, event ambiguity, and the publics critical sense, each of which are defined by decision makers using linguistic descriptions and then transformed into triangular fuzzy numbers. To calculate the resultant force of these three factors, the transmission capacity and a new parameter category with fuzzy variables are determined. A rumor spreading model is then proposed which has fuzzy parameters rather than the fixed parameters in traditional models. As the proposed model considers the comprehensive factors affecting rumors from three aspects rather than examining special factors from a particular aspect. The proposed rumor spreading model is tested using different parameters for several different conditions on BA networks and three special cases are simulated. The simulation results for all three cases suggested that events of low importance, those that are only clarifying facts, and those that are strongly critical do not result in rumors. Therefore, the model assessment results were proven to be in agreement with reality. Parameters for the model were then determined and applied to an analysis of the 7.23 Yong-Wen line major transportation accident (YWMTA). When the simulated data were compared with the real data from this accident, the results demonstrated that the interval for the rumor spreading key point in the model was accurate, and that the key point for the YWMTA rumor spread fell into the range estimated by the model.

GEODYN programmers guide, volume 2, part 1

NASA Technical Reports Server (NTRS)

Mullins, N. E.; Goad, C. C.; Dao, N. C.; Martin, T. V.; Boulware, N. L.; Chin, M. M.

1972-01-01

A guide to the GEODYN Program is presented. The program estimates orbit and geodetic parameters. It possesses the capability to estimate that set of orbital elements, station positions, measurement biases, and a set of force model parameters such that the orbital tracking data from multiple arcs of multiple satellites best fit the entire set of estimated parameters. GEODYN consists of 113 different program segments, including the main program, subroutines, functions, and block data routines. All are in G or H level FORTRAN and are currently operational on GSFC's IBM 360/95 and IBM 360/91.

Determination of Kinetic Parameters for the Thermal Decomposition of Parthenium hysterophorus

NASA Astrophysics Data System (ADS)

Dhaundiyal, Alok; Singh, Suraj B.; Hanon, Muammel M.; Rawat, Rekha

2018-02-01

A kinetic study of pyrolysis process of Parthenium hysterophorous is carried out by using thermogravimetric analysis (TGA) equipment. The present study investigates the thermal degradation and determination of the kinetic parameters such as activation E and the frequency factor A using model-free methods given by Flynn Wall and Ozawa (FWO), Kissinger-Akahira-Sonuse (KAS) and Kissinger, and model-fitting (Coats Redfern). The results derived from thermal decomposition process demarcate decomposition of Parthenium hysterophorous among the three main stages, such as dehydration, active and passive pyrolysis. It is shown through DTG thermograms that the increase in the heating rate caused temperature peaks at maximum weight loss rate to shift towards higher temperature regime. The results are compared with Coats Redfern (Integral method) and experimental results have shown that values of kinetic parameters obtained from model-free methods are in good agreement. Whereas the results obtained through Coats Redfern model at different heating rates are not promising, however, the diffusion models provided the good fitting with the experimental data.

Generating Models of Infinite-State Communication Protocols Using Regular Inference with Abstraction

NASA Astrophysics Data System (ADS)

Aarts, Fides; Jonsson, Bengt; Uijen, Johan

In order to facilitate model-based verification and validation, effort is underway to develop techniques for generating models of communication system components from observations of their external behavior. Most previous such work has employed regular inference techniques which generate modest-size finite-state models. They typically suppress parameters of messages, although these have a significant impact on control flow in many communication protocols. We present a framework, which adapts regular inference to include data parameters in messages and states for generating components with large or infinite message alphabets. A main idea is to adapt the framework of predicate abstraction, successfully used in formal verification. Since we are in a black-box setting, the abstraction must be supplied externally, using information about how the component manages data parameters. We have implemented our techniques by connecting the LearnLib tool for regular inference with the protocol simulator ns-2, and generated a model of the SIP component as implemented in ns-2.

Application of 3-Dimensional Printing Technology to Construct an Eye Model for Fundus Viewing Study

PubMed Central

Li, Xinhua; Gao, Zhishan; Yuan, Dongqing; Liu, Qinghuai

2014-01-01

Objective To construct a life-sized eye model using the three-dimensional (3D) printing technology for fundus viewing study of the viewing system. Methods We devised our schematic model eye based on Navarro's eye and redesigned some parameters because of the change of the corneal material and the implantation of intraocular lenses (IOLs). Optical performance of our schematic model eye was compared with Navarro's schematic eye and other two reported physical model eyes using the ZEMAX optical design software. With computer aided design (CAD) software, we designed the 3D digital model of the main structure of the physical model eye, which was used for three-dimensional (3D) printing. Together with the main printed structure, polymethyl methacrylate(PMMA) aspherical cornea, variable iris, and IOLs were assembled to a physical eye model. Angle scale bars were glued from posterior to periphery of the retina. Then we fabricated other three physical models with different states of ammetropia. Optical parameters of these physical eye models were measured to verify the 3D printing accuracy. Results In on-axis calculations, our schematic model eye possessed similar size of spot diagram compared with Navarro's and Bakaraju's model eye, much smaller than Arianpour's model eye. Moreover, the spherical aberration of our schematic eye was much less than other three model eyes. While in off- axis simulation, it possessed a bit higher coma and similar astigmatism, field curvature and distortion. The MTF curves showed that all the model eyes diminished in resolution with increasing field of view, and the diminished tendency of resolution of our physical eye model was similar to the Navarro's eye. The measured parameters of our eye models with different status of ametropia were in line with the theoretical value. Conclusions The schematic eye model we designed can well simulate the optical performance of the human eye, and the fabricated physical one can be used as a tool in fundus range viewing research. PMID:25393277

Application of 3-dimensional printing technology to construct an eye model for fundus viewing study.

PubMed

Xie, Ping; Hu, Zizhong; Zhang, Xiaojun; Li, Xinhua; Gao, Zhishan; Yuan, Dongqing; Liu, Qinghuai

2014-01-01

To construct a life-sized eye model using the three-dimensional (3D) printing technology for fundus viewing study of the viewing system. We devised our schematic model eye based on Navarro's eye and redesigned some parameters because of the change of the corneal material and the implantation of intraocular lenses (IOLs). Optical performance of our schematic model eye was compared with Navarro's schematic eye and other two reported physical model eyes using the ZEMAX optical design software. With computer aided design (CAD) software, we designed the 3D digital model of the main structure of the physical model eye, which was used for three-dimensional (3D) printing. Together with the main printed structure, polymethyl methacrylate(PMMA) aspherical cornea, variable iris, and IOLs were assembled to a physical eye model. Angle scale bars were glued from posterior to periphery of the retina. Then we fabricated other three physical models with different states of ammetropia. Optical parameters of these physical eye models were measured to verify the 3D printing accuracy. In on-axis calculations, our schematic model eye possessed similar size of spot diagram compared with Navarro's and Bakaraju's model eye, much smaller than Arianpour's model eye. Moreover, the spherical aberration of our schematic eye was much less than other three model eyes. While in off- axis simulation, it possessed a bit higher coma and similar astigmatism, field curvature and distortion. The MTF curves showed that all the model eyes diminished in resolution with increasing field of view, and the diminished tendency of resolution of our physical eye model was similar to the Navarro's eye. The measured parameters of our eye models with different status of ametropia were in line with the theoretical value. The schematic eye model we designed can well simulate the optical performance of the human eye, and the fabricated physical one can be used as a tool in fundus range viewing research.

Gender recognition from vocal source

NASA Astrophysics Data System (ADS)

Sorokin, V. N.; Makarov, I. S.

2008-07-01

Efficiency of automatic recognition of male and female voices based on solving the inverse problem for glottis area dynamics and for waveform of the glottal airflow volume velocity pulse is studied. The inverse problem is regularized through the use of analytical models of the voice excitation pulse and of the dynamics of the glottis area, as well as the model of one-dimensional glottal airflow. Parameters of these models and spectral parameters of the volume velocity pulse are considered. The following parameters are found to be most promising: the instant of maximum glottis area, the maximum derivative of the area, the slope of the spectrum of the glottal airflow volume velocity pulse, the amplitude ratios of harmonics of this spectrum, and the pitch. On the plane of the first two main components in the space of these parameters, an almost twofold decrease in the classification error relative to that for the pitch alone is attained. The male voice recognition probability is found to be 94.7%, and the female voice recognition probability is 95.9%.

Photovoltaic Grid-Connected Modeling and Characterization Based on Experimental Results.

PubMed

Humada, Ali M; Hojabri, Mojgan; Sulaiman, Mohd Herwan Bin; Hamada, Hussein M; Ahmed, Mushtaq N

2016-01-01

A grid-connected photovoltaic (PV) system operates under fluctuated weather condition has been modeled and characterized based on specific test bed. A mathematical model of a small-scale PV system has been developed mainly for residential usage, and the potential results have been simulated. The proposed PV model based on three PV parameters, which are the photocurrent, IL, the reverse diode saturation current, Io, the ideality factor of diode, n. Accuracy of the proposed model and its parameters evaluated based on different benchmarks. The results showed that the proposed model fitting the experimental results with high accuracy compare to the other models, as well as the I-V characteristic curve. The results of this study can be considered valuable in terms of the installation of a grid-connected PV system in fluctuated climatic conditions.

Photovoltaic Grid-Connected Modeling and Characterization Based on Experimental Results

PubMed Central

Humada, Ali M.; Hojabri, Mojgan; Sulaiman, Mohd Herwan Bin; Hamada, Hussein M.; Ahmed, Mushtaq N.

2016-01-01

A grid-connected photovoltaic (PV) system operates under fluctuated weather condition has been modeled and characterized based on specific test bed. A mathematical model of a small-scale PV system has been developed mainly for residential usage, and the potential results have been simulated. The proposed PV model based on three PV parameters, which are the photocurrent, IL, the reverse diode saturation current, Io, the ideality factor of diode, n. Accuracy of the proposed model and its parameters evaluated based on different benchmarks. The results showed that the proposed model fitting the experimental results with high accuracy compare to the other models, as well as the I-V characteristic curve. The results of this study can be considered valuable in terms of the installation of a grid-connected PV system in fluctuated climatic conditions. PMID:27035575

Real-Time Classification of Exercise Exertion Levels Using Discriminant Analysis of HRV Data.

PubMed

Jeong, In Cheol; Finkelstein, Joseph

2015-01-01

Heart rate variability (HRV) was shown to reflect activation of sympathetic nervous system however it is not clear which set of HRV parameters is optimal for real-time classification of exercise exertion levels. There is no studies that compared potential of two types of HRV parameters (time-domain and frequency-domain) in predicting exercise exertion level using discriminant analysis. The main goal of this study was to compare potential of HRV time-domain parameters versus HRV frequency-domain parameters in classifying exercise exertion level. Rest, exercise, and recovery categories were used in classification models. Overall 79.5% classification agreement by the time-domain parameters as compared to overall 52.8% classification agreement by frequency-domain parameters demonstrated that the time-domain parameters had higher potential in classifying exercise exertion levels.

Real-Time Monitoring and Prediction of the Pilot Vehicle System (PVS) Closed-Loop Stability

NASA Astrophysics Data System (ADS)

Mandal, Tanmay Kumar

Understanding human control behavior is an important step for improving the safety of future aircraft. Considerable resources are invested during the design phase of an aircraft to ensure that the aircraft has desirable handling qualities. However, human pilots exhibit a wide range of control behaviors that are a function of external stimulus, aircraft dynamics, and human psychological properties (such as workload, stress factor, confidence, and sense of urgency factor). This variability is difficult to address comprehensively during the design phase and may lead to undesirable pilot-aircraft interaction, such as pilot-induced oscillations (PIO). This creates the need to keep track of human pilot performance in real-time to monitor the pilot vehicle system (PVS) stability. This work focused on studying human pilot behavior for the longitudinal axis of a remotely controlled research aircraft and using human-in-the-loop (HuIL) simulations to obtain information about the human controlled system (HCS) stability. The work in this dissertation is divided into two main parts: PIO analysis and human control model parameters estimation. To replicate different flight conditions, this study included time delay and elevator rate limiting phenomena, typical of actuator dynamics during the experiments. To study human control behavior, this study employed the McRuer model for single-input single-output manual compensatory tasks. McRuer model is a lead-lag controller with time delay which has been shown to adequately model manual compensatory tasks. This dissertation presents a novel technique to estimate McRuer model parameters in real-time and associated validation using HuIL simulations to correctly predict HCS stability. The McRuer model parameters were estimated in real-time using a Kalman filter approach. The estimated parameters were then used to analyze the stability of the closed-loop HCS and verify them against the experimental data. Therefore, the main contribution of this dissertation is the design of an unscented Kalman filter-based algorithm to estimate McRuer model parameters in real time, and a framework to validate this algorithm for single-input single-output manual compensatory tasks to predict instabilities.

Sensitivity analysis with the regional climate model COSMO-CLM over the CORDEX-MENA domain

NASA Astrophysics Data System (ADS)

Bucchignani, E.; Cattaneo, L.; Panitz, H.-J.; Mercogliano, P.

2016-02-01

The results of a sensitivity work based on ERA-Interim driven COSMO-CLM simulations over the Middle East-North Africa (CORDEX-MENA) domain are presented. All simulations were performed at 0.44° spatial resolution. The purpose of this study was to ascertain model performances with respect to changes in physical and tuning parameters which are mainly related to surface, convection, radiation and cloud parameterizations. Evaluation was performed for the whole CORDEX-MENA region and six sub-regions, comparing a set of 26 COSMO-CLM runs against a combination of available ground observations, satellite products and reanalysis data to assess temperature, precipitation, cloud cover and mean sea level pressure. The model proved to be very sensitive to changes in physical parameters. The optimized configuration allows COSMO-CLM to improve the simulated main climate features of this area. Its main characteristics consist in the new parameterization of albedo, based on Moderate Resolution Imaging Spectroradiometer data, and the new parameterization of aerosol, based on NASA-GISS AOD distributions. When applying this configuration, Mean Absolute Error values for the considered variables are as follows: about 1.2 °C for temperature, about 15 mm/month for precipitation, about 9 % for total cloud cover, and about 0.6 hPa for mean sea level pressure.

A review of the solar array manufacturing industry costing standards

NASA Technical Reports Server (NTRS)

1977-01-01

The solar array manufacturing industry costing standards model is designed to compare the cost of producing solar arrays using alternative manufacturing processes. Constructive criticism of the methodology used is intended to enhance its implementation as a practical design tool. Three main elements of the procedure include workbook format and presentation, theoretical model validity and standard financial parameters.

Argo Development Program.

DTIC Science & Technology

1986-06-01

nonlinear form and account for uncertainties in model parameters, structural simplifications of the model, and disturbances. This technique summarizes...SHARPS system. *The take into account the coupling between axes two curves are nearly identical, except that the without becoming unwieldy. The low...are mainly caused by errors and control errors and accounts for the bandwidth limitations and the simulated current. observed offsets. The overshoot

Problems of low-parameter equations of state

NASA Astrophysics Data System (ADS)

Petrik, G. G.

2017-11-01

The paper focuses on the system approach to problems of low-parametric equations of state (EOS). It is a continuation of the investigations in the field of substantiated prognosis of properties on two levels, molecular and thermodynamic. Two sets of low-parameter EOS have been considered based on two very simple molecular-level models. The first one consists of EOS of van der Waals type (a modification of van der Waals EOS proposed for spheres). The main problem of these EOS is a weak connection with the micro-level, which raise many uncertainties. The second group of EOS has been derived by the author independently of the ideas of van der Waals based on the model of interacting point centers (IPC). All the parameters of the EOS have a meaning and are associated with the manifestation of attractive and repulsive forces. The relationship between them is found to be the control parameter of the thermodynamic level. In this case, EOS IPC passes into a one-parameter family. It is shown that many EOS of vdW-type can be included in the framework of the PC model. Simultaneously, all their parameters acquire a physical meaning.

Extreme Learning Machine and Particle Swarm Optimization in optimizing CNC turning operation

NASA Astrophysics Data System (ADS)

Janahiraman, Tiagrajah V.; Ahmad, Nooraziah; Hani Nordin, Farah

2018-04-01

The CNC machine is controlled by manipulating cutting parameters that could directly influence the process performance. Many optimization methods has been applied to obtain the optimal cutting parameters for the desired performance function. Nonetheless, the industry still uses the traditional technique to obtain those values. Lack of knowledge on optimization techniques is the main reason for this issue to be prolonged. Therefore, the simple yet easy to implement, Optimal Cutting Parameters Selection System is introduced to help the manufacturer to easily understand and determine the best optimal parameters for their turning operation. This new system consists of two stages which are modelling and optimization. In modelling of input-output and in-process parameters, the hybrid of Extreme Learning Machine and Particle Swarm Optimization is applied. This modelling technique tend to converge faster than other artificial intelligent technique and give accurate result. For the optimization stage, again the Particle Swarm Optimization is used to get the optimal cutting parameters based on the performance function preferred by the manufacturer. Overall, the system can reduce the gap between academic world and the industry by introducing a simple yet easy to implement optimization technique. This novel optimization technique can give accurate result besides being the fastest technique.

A simplified model of precipitation enhancement over a heterogeneous surface

NASA Astrophysics Data System (ADS)

Cioni, Guido; Hohenegger, Cathy

2018-06-01

Soil moisture heterogeneities influence the onset of convection and subsequent evolution of precipitating systems through the triggering of mesoscale circulations. However, local evaporation also plays a role in determining precipitation amounts. Here we aim at disentangling the effect of advection and evaporation on precipitation over the course of a diurnal cycle by formulating a simple conceptual model. The derivation of the model is inspired by the results of simulations performed with a high-resolution (250 m) large eddy simulation model over a surface with varying degrees of heterogeneity. A key element of the conceptual model is the representation of precipitation as a weighted sum of advection and evaporation, each weighed by its own efficiency. The model is then used to isolate the main parameters that control precipitation variations over a spatially drier patch. It is found that these changes surprisingly do not depend on soil moisture itself but instead purely on parameters that describe the atmospheric initial state. The likelihood for enhanced precipitation over drier soils is discussed based on these parameters. Additional experiments are used to test the validity of the model.

Critical patch-size for two-sex populations.

PubMed

Andreguetto Maciel, Gabriel; Mendes Coutinho, Renato; André Kraenkel, Roberto

2018-06-01

As environments become increasingly degraded, mainly due to human activities, species are often subject to isolated habitats surrounded by unfavorable regions. Since the pioneering work by Skellam [25] mathematical models have provided useful insights into the population persistence in such cases. Most of these models, however, neglect the sex structure of populations and the differences between males and females. In this work we investigate, through a reaction-diffusion system, the dynamics of a sex-structured population in a single semipermeable patch. The critical patch size for persistence is determined from implicit relationships between model parameters. The effects of the various growth and movement parameters are also investigated. Copyright © 2018 Elsevier Inc. All rights reserved.

Improving flood forecasting capability of physically based distributed hydrological models by parameter optimization

NASA Astrophysics Data System (ADS)

Chen, Y.; Li, J.; Xu, H.

2016-01-01

Physically based distributed hydrological models (hereafter referred to as PBDHMs) divide the terrain of the whole catchment into a number of grid cells at fine resolution and assimilate different terrain data and precipitation to different cells. They are regarded to have the potential to improve the catchment hydrological process simulation and prediction capability. In the early stage, physically based distributed hydrological models are assumed to derive model parameters from the terrain properties directly, so there is no need to calibrate model parameters. However, unfortunately the uncertainties associated with this model derivation are very high, which impacted their application in flood forecasting, so parameter optimization may also be necessary. There are two main purposes for this study: the first is to propose a parameter optimization method for physically based distributed hydrological models in catchment flood forecasting by using particle swarm optimization (PSO) algorithm and to test its competence and to improve its performances; the second is to explore the possibility of improving physically based distributed hydrological model capability in catchment flood forecasting by parameter optimization. In this paper, based on the scalar concept, a general framework for parameter optimization of the PBDHMs for catchment flood forecasting is first proposed that could be used for all PBDHMs. Then, with the Liuxihe model as the study model, which is a physically based distributed hydrological model proposed for catchment flood forecasting, the improved PSO algorithm is developed for the parameter optimization of the Liuxihe model in catchment flood forecasting. The improvements include adoption of the linearly decreasing inertia weight strategy to change the inertia weight and the arccosine function strategy to adjust the acceleration coefficients. This method has been tested in two catchments in southern China with different sizes, and the results show that the improved PSO algorithm could be used for the Liuxihe model parameter optimization effectively and could improve the model capability largely in catchment flood forecasting, thus proving that parameter optimization is necessary to improve the flood forecasting capability of physically based distributed hydrological models. It also has been found that the appropriate particle number and the maximum evolution number of PSO algorithm used for the Liuxihe model catchment flood forecasting are 20 and 30 respectively.

A coupled two-dimensional main chain torsional potential for protein dynamics: generation and implementation.

PubMed

Li, Yongxiu; Gao, Ya; Zhang, Xuqiang; Wang, Xingyu; Mou, Lirong; Duan, Lili; He, Xiao; Mei, Ye; Zhang, John Z H

2013-09-01

Main chain torsions of alanine dipeptide are parameterized into coupled 2-dimensional Fourier expansions based on quantum mechanical (QM) calculations at M06 2X/aug-cc-pvtz//HF/6-31G** level. Solvation effect is considered by employing polarizable continuum model. Utilization of the M06 2X functional leads to precise potential energy surface that is comparable to or even better than MP2 level, but with much less computational demand. Parameterization of the 2D expansions is against the full main chain torsion space instead of just a few low energy conformations. This procedure is similar to that for the development of AMBER03 force field, except unique weighting factor was assigned to all the grid points. To avoid inconsistency between quantum mechanical calculations and molecular modeling, the model peptide is further optimized at molecular mechanics level with main chain dihedral angles fixed before the calculation of the conformational energy on molecular mechanical level at each grid point, during which generalized Born model is employed. Difference in solvation models at quantum mechanics and molecular mechanics levels makes this parameterization procedure less straightforward. All force field parameters other than main chain torsions are taken from existing AMBER force field. With this new main chain torsion terms, we have studied the main chain dihedral distributions of ALA dipeptide and pentapeptide in aqueous solution. The results demonstrate that 2D main chain torsion is effective in delineating the energy variation associated with rotations along main chain dihedrals. This work is an implication for the necessity of more accurate description of main chain torsions in the future development of ab initio force field and it also raises a challenge to the development of quantum mechanical methods, especially the quantum mechanical solvation models.

Interpretation of environmental tracers in groundwater systems with stagnant water zones.

PubMed

Maloszewski, Piotr; Stichler, Willibald; Zuber, Andrzej

2004-03-01

Lumped-parameter models are commonly applied for determining the age of water from time records of transient environmental tracers. The simplest models (e.g. piston flow or exponential) are also applicable for dating based on the decay or accumulation of tracers in groundwater systems. The models are based on the assumption that the transit time distribution function (exit age distribution function) of the tracer particles in the investigated system adequately represents the distribution of flow lines and is described by a simple function. A chosen or fitted function (called the response function) describes the transit time distribution of a tracer which would be observed at the output (discharge area, spring, stream, or pumping wells) in the case of an instantaneous injection at the entrance (recharge area). Due to large space and time scales, response functions are not measurable in groundwater systems, therefore, functions known from other fields of science, mainly from chemical engineering, are usually used. The type of response function and the values of its parameters define the lumped-parameter model of a system. The main parameter is the mean transit time of tracer through the system, which under favourable conditions may represent the mean age of mobile water. The parameters of the model are found by fitting calculated concentrations to the experimental records of concentrations measured at the outlet. The mean transit time of tracer (often called the tracer age), whether equal to the mean age of water or not, serves in adequate combinations with other data for determining other useful parameters, e.g. the recharge rate or the content of water in the system. The transit time distribution and its mean value serve for confirmation or determination of the conceptual model of the system and/or estimation of its potential vulnerability to anthropogenic pollution. In the interpretation of environmental tracer data with the aid of the lumped-parameter models, the influence of diffusion exchange between mobile water and stagnant or quasi-stagnant water is seldom considered, though it leads to large differences between tracer and water ages. Therefore, the article is focused on the transit time distribution functions of the most common lumped-parameter models, particularly those applicable for the interpretation of environmental tracer data in double-porosity aquifers, or aquifers in which aquitard diffusion may play an important role. A case study is recalled for a confined aquifer in which the diffusion exchange with aquitard most probably strongly influenced the transport of environmental tracers. Another case study presented is related to the interpretation of environmental tracer data obtained from lysimeters installed in the unsaturated zone with a fraction of stagnant water.

Model Parameter Estimation Experiment (MOPEX): An overview of science strategy and major results from the second and third workshops

USGS Publications Warehouse

Duan, Q.; Schaake, J.; Andreassian, V.; Franks, S.; Goteti, G.; Gupta, H.V.; Gusev, Y.M.; Habets, F.; Hall, A.; Hay, L.; Hogue, T.; Huang, M.; Leavesley, G.; Liang, X.; Nasonova, O.N.; Noilhan, J.; Oudin, L.; Sorooshian, S.; Wagener, T.; Wood, E.F.

2006-01-01

The Model Parameter Estimation Experiment (MOPEX) is an international project aimed at developing enhanced techniques for the a priori estimation of parameters in hydrologic models and in land surface parameterization schemes of atmospheric models. The MOPEX science strategy involves three major steps: data preparation, a priori parameter estimation methodology development, and demonstration of parameter transferability. A comprehensive MOPEX database has been developed that contains historical hydrometeorological data and land surface characteristics data for many hydrologic basins in the United States (US) and in other countries. This database is being continuously expanded to include more basins in all parts of the world. A number of international MOPEX workshops have been convened to bring together interested hydrologists and land surface modelers from all over world to exchange knowledge and experience in developing a priori parameter estimation techniques. This paper describes the results from the second and third MOPEX workshops. The specific objective of these workshops is to examine the state of a priori parameter estimation techniques and how they can be potentially improved with observations from well-monitored hydrologic basins. Participants of the second and third MOPEX workshops were provided with data from 12 basins in the southeastern US and were asked to carry out a series of numerical experiments using a priori parameters as well as calibrated parameters developed for their respective hydrologic models. Different modeling groups carried out all the required experiments independently using eight different models, and the results from these models have been assembled for analysis in this paper. This paper presents an overview of the MOPEX experiment and its design. The main experimental results are analyzed. A key finding is that existing a priori parameter estimation procedures are problematic and need improvement. Significant improvement of these procedures may be achieved through model calibration of well-monitored hydrologic basins. This paper concludes with a discussion of the lessons learned, and points out further work and future strategy. ?? 2005 Elsevier Ltd. All rights reserved.

On the choice of the functional form of the aftershocks decay equation

NASA Astrophysics Data System (ADS)

Gasperini, P.; Lolli, B.

2003-04-01

To infer the optimal form of the rate equation describing the decay of aftershock sequences, we analyzed the correlation among parameter estimates made for New Zealand (Eberhard-Phillips, 1998) and Italy (Lolli and Gasperini, 2003), for the simple model proposed by Reasenberg and Jones (1989) λ(t)=10a+b(Mm-Mmin)over(t+c)^p} We found significant correlations between the sequence productivity parameter a and all other ones (p, c and b) and between p and c. At odd with previous findings (Guo and Ogata, 1995; 1997) we did not find instead correlation between b and p. We verified that the explicit inclusion in the formula of the time decay normalization integral removes the correlation of a with both parameters p and c. We also found, separately for both regions, that assuming the linear coefficient of main shock magnitude M_m about 2/3b makes parameter a also independent of b. The a parameter of the resulting rate equation λ(t)= 10a+2/3bMm-bMmin/ (t+c)^pint_ST(t+c)-pdt being almost independent of the other ones, can be reliably considered the expressions of a peculiar property of the seismogenic process. Thus we can infer that the new equation could be more appropriate than the previous one to predict sequence behavior in different areas. This formulation has also been applied to more sophisticated models of the epidemic type (ETAS), letting the coefficient of the main shock magnitude to vary freely. Some preliminary experiments give estimates close to 1/2b for this parameter.

Image informative maps for component-wise estimating parameters of signal-dependent noise

NASA Astrophysics Data System (ADS)

Uss, Mykhail L.; Vozel, Benoit; Lukin, Vladimir V.; Chehdi, Kacem

2013-01-01

We deal with the problem of blind parameter estimation of signal-dependent noise from mono-component image data. Multispectral or color images can be processed in a component-wise manner. The main results obtained rest on the assumption that the image texture and noise parameters estimation problems are interdependent. A two-dimensional fractal Brownian motion (fBm) model is used for locally describing image texture. A polynomial model is assumed for the purpose of describing the signal-dependent noise variance dependence on image intensity. Using the maximum likelihood approach, estimates of both fBm-model and noise parameters are obtained. It is demonstrated that Fisher information (FI) on noise parameters contained in an image is distributed nonuniformly over intensity coordinates (an image intensity range). It is also shown how to find the most informative intensities and the corresponding image areas for a given noisy image. The proposed estimator benefits from these detected areas to improve the estimation accuracy of signal-dependent noise parameters. Finally, the potential estimation accuracy (Cramér-Rao Lower Bound, or CRLB) of noise parameters is derived, providing confidence intervals of these estimates for a given image. In the experiment, the proposed and existing state-of-the-art noise variance estimators are compared for a large image database using CRLB-based statistical efficiency criteria.

Stochastic or statistic? Comparing flow duration curve models in ungauged basins and changing climates

NASA Astrophysics Data System (ADS)

Müller, M. F.; Thompson, S. E.

2015-09-01

The prediction of flow duration curves (FDCs) in ungauged basins remains an important task for hydrologists given the practical relevance of FDCs for water management and infrastructure design. Predicting FDCs in ungauged basins typically requires spatial interpolation of statistical or model parameters. This task is complicated if climate becomes non-stationary, as the prediction challenge now also requires extrapolation through time. In this context, process-based models for FDCs that mechanistically link the streamflow distribution to climate and landscape factors may have an advantage over purely statistical methods to predict FDCs. This study compares a stochastic (process-based) and statistical method for FDC prediction in both stationary and non-stationary contexts, using Nepal as a case study. Under contemporary conditions, both models perform well in predicting FDCs, with Nash-Sutcliffe coefficients above 0.80 in 75 % of the tested catchments. The main drives of uncertainty differ between the models: parameter interpolation was the main source of error for the statistical model, while violations of the assumptions of the process-based model represented the main source of its error. The process-based approach performed better than the statistical approach in numerical simulations with non-stationary climate drivers. The predictions of the statistical method under non-stationary rainfall conditions were poor if (i) local runoff coefficients were not accurately determined from the gauge network, or (ii) streamflow variability was strongly affected by changes in rainfall. A Monte Carlo analysis shows that the streamflow regimes in catchments characterized by a strong wet-season runoff and a rapid, strongly non-linear hydrologic response are particularly sensitive to changes in rainfall statistics. In these cases, process-based prediction approaches are strongly favored over statistical models.

Comparing statistical and process-based flow duration curve models in ungauged basins and changing rain regimes

NASA Astrophysics Data System (ADS)

Müller, M. F.; Thompson, S. E.

2016-02-01

The prediction of flow duration curves (FDCs) in ungauged basins remains an important task for hydrologists given the practical relevance of FDCs for water management and infrastructure design. Predicting FDCs in ungauged basins typically requires spatial interpolation of statistical or model parameters. This task is complicated if climate becomes non-stationary, as the prediction challenge now also requires extrapolation through time. In this context, process-based models for FDCs that mechanistically link the streamflow distribution to climate and landscape factors may have an advantage over purely statistical methods to predict FDCs. This study compares a stochastic (process-based) and statistical method for FDC prediction in both stationary and non-stationary contexts, using Nepal as a case study. Under contemporary conditions, both models perform well in predicting FDCs, with Nash-Sutcliffe coefficients above 0.80 in 75 % of the tested catchments. The main drivers of uncertainty differ between the models: parameter interpolation was the main source of error for the statistical model, while violations of the assumptions of the process-based model represented the main source of its error. The process-based approach performed better than the statistical approach in numerical simulations with non-stationary climate drivers. The predictions of the statistical method under non-stationary rainfall conditions were poor if (i) local runoff coefficients were not accurately determined from the gauge network, or (ii) streamflow variability was strongly affected by changes in rainfall. A Monte Carlo analysis shows that the streamflow regimes in catchments characterized by frequent wet-season runoff and a rapid, strongly non-linear hydrologic response are particularly sensitive to changes in rainfall statistics. In these cases, process-based prediction approaches are favored over statistical models.

Mathematical 3D modelling and sensitivity analysis of multipolar radiofrequency ablation in the spine.

PubMed

Matschek, Janine; Bullinger, Eric; von Haeseler, Friedrich; Skalej, Martin; Findeisen, Rolf

2017-02-01

Radiofrequency ablation is a valuable tool in the treatment of many diseases, especially cancer. However, controlled heating up to apoptosis of the desired target tissue in complex situations, e.g. in the spine, is challenging and requires experienced interventionalists. For such challenging situations a mathematical model of radiofrequency ablation allows to understand, improve and optimise the outcome of the medical therapy. The main contribution of this work is the derivation of a tailored, yet expandable mathematical model, for the simulation, analysis, planning and control of radiofrequency ablation in complex situations. The dynamic model consists of partial differential equations that describe the potential and temperature distribution during intervention. To account for multipolar operation, time-dependent boundary conditions are introduced. Spatially distributed parameters, like tissue conductivity and blood perfusion, allow to describe the complex 3D environment representing diverse involved tissue types in the spine. To identify the key parameters affecting the prediction quality of the model, the influence of the parameters on the temperature distribution is investigated via a sensitivity analysis. Simulations underpin the quality of the derived model and the analysis approach. The proposed modelling and analysis schemes set the basis for intervention planning, state- and parameter estimation, and control. Copyright © 2016. Published by Elsevier Inc.

Modelling and analysis of creep deformation and fracture in a 1 Cr 1/2 Mo ferritic steel

NASA Astrophysics Data System (ADS)

Dyson, B. F.; Osgerby, D.

A quantitative model, based upon a proposed new mechanism of creep deformation in particle-hardened alloys, has been validated by analysis of creep data from a 13CrMo 4 4 (1Cr 1/2 Mo) material tested under a range of stresses and temperatures. The methodology that has been used to extract the model parameters quantifies, as a first approximation, only the main degradation (damage) processes - in the case of the 1CR 1/2 Mo steel, these are considered to be the parallel operation of particle-coarsening and a progressively increasing stress due to a constant-load boundary condition. These 'global' model parameters can then be modified (only slightly) as required to obtain a detailed description and 'fit' to the rupture lifetime and strain/time trajectory of any individual test. The global model parameter approach may be thought of as predicting average behavior and the detailed fits as taking account of uncertainties (scatter) due to variability in the material. Using the global parameter dataset, predictions have also been made of behavior under biaxial stressing; constant straining rate; constant total strain (stress relaxation) and the likely success or otherwise of metallographic and mechanical remanent lifetime procedures.

A size-structured model of bacterial growth and reproduction.

PubMed

Ellermeyer, S F; Pilyugin, S S

2012-01-01

We consider a size-structured bacterial population model in which the rate of cell growth is both size- and time-dependent and the average per capita reproduction rate is specified as a model parameter. It is shown that the model admits classical solutions. The population-level and distribution-level behaviours of these solutions are then determined in terms of the model parameters. The distribution-level behaviour is found to be different from that found in similar models of bacterial population dynamics. Rather than convergence to a stable size distribution, we find that size distributions repeat in cycles. This phenomenon is observed in similar models only under special assumptions on the functional form of the size-dependent growth rate factor. Our main results are illustrated with examples, and we also provide an introductory study of the bacterial growth in a chemostat within the framework of our model.

Stress-based animal models of depression: Do we actually know what we are doing?

PubMed

Yin, Xin; Guven, Nuri; Dietis, Nikolas

2016-12-01

Depression is one of the leading causes of disability and a significant health-concern worldwide. Much of our current understanding on the pathogenesis of depression and the pharmacology of antidepressant drugs is based on pre-clinical models. Three of the most popular stress-based rodent models are the forced swimming test, the chronic mild stress paradigm and the learned helplessness model. Despite their recognizable advantages and limitations, they are associated with an immense variability due to the high number of design parameters that define them. Only few studies have reported how minor modifications of these parameters affect the model phenotype. Thus, the existing variability in how these models are used has been a strong barrier for drug development as well as benchmark and evaluation of these pre-clinical models of depression. It also has been the source of confusing variability in the experimental outcomes between research groups using the same models. In this review, we summarize the known variability in the experimental protocols, identify the main and relevant parameters for each model and describe the variable values using characteristic examples. Our view of depression and our efforts to discover novel and effective antidepressants is largely based on our detailed knowledge of these testing paradigms, and requires a sound understanding around the importance of individual parameters to optimize and improve these pre-clinical models. Copyright © 2016 Elsevier B.V. All rights reserved.

Determination of adsorption parameters in numerical simulation for polymer flooding

NASA Astrophysics Data System (ADS)

Bao, Pengyu; Li, Aifen; Luo, Shuai; Dang, Xu

2018-02-01

A study on the determination of adsorption parameters for polymer flooding simulation was carried out. The study mainly includes polymer static adsorption and dynamic adsorption. The law of adsorption amount changing with polymer concentration and core permeability was presented, and the one-dimensional numerical model of CMG was established under the support of a large number of experimental data. The adsorption laws of adsorption experiments were applied to the one-dimensional numerical model to compare the influence of two adsorption laws on the historical matching results. The results show that the static adsorption and dynamic adsorption abide by different rules, and differ greatly in adsorption. If the static adsorption results were directly applied to the numerical model, the difficulty of the historical matching will increase. Therefore, dynamic adsorption tests in the porous medium are necessary before the process of parameter adjustment in order to achieve the ideal history matching result.

Identification of material parameters for plasticity models: A comparative study on the finite element model updating and the virtual fields method

NASA Astrophysics Data System (ADS)

Martins, J. M. P.; Thuillier, S.; Andrade-Campos, A.

2018-05-01

The identification of material parameters, for a given constitutive model, can be seen as the first step before any practical application. In the last years, the field of material parameters identification received an important boost with the development of full-field measurement techniques, such as Digital Image Correlation. These techniques enable the use of heterogeneous displacement/strain fields, which contain more information than the classical homogeneous tests. Consequently, different techniques have been developed to extract material parameters from full-field measurements. In this study, two of these techniques are addressed, the Finite Element Model Updating (FEMU) and the Virtual Fields Method (VFM). The main idea behind FEMU is to update the parameters of a constitutive model implemented in a finite element model until both numerical and experimental results match, whereas VFM makes use of the Principle of Virtual Work and does not require any finite element simulation. Though both techniques proved their feasibility in linear and non-linear constitutive models, it is rather difficult to rank their robustness in plasticity. The purpose of this work is to perform a comparative study in the case of elasto-plastic models. Details concerning the implementation of each strategy are presented. Moreover, a dedicated code for VFM within a large strain framework is developed. The reconstruction of the stress field is performed through a user subroutine. A heterogeneous tensile test is considered to compare FEMU and VFM strategies.

Photospheres of hot stars. IV - Spectral type O4

NASA Technical Reports Server (NTRS)

Bohannan, Bruce; Abbott, David C.; Voels, Stephen A.; Hummer, David G.

1990-01-01

The basic stellar parameters of a supergiant (Zeta Pup) and two main-sequence stars, 9 Sgr and HD 46223, at spectral class O4 are determined using line profile analysis. The stellar parameters are determined by comparing high signal-to-noise hydrogen and helium line profiles with those from stellar atmosphere models which include the effect of radiation scattered back onto the photosphere from an overlying stellar wind, an effect referred to as wind blanketing. At spectral class O4, the inclusion of wind-blanketing in the model atmosphere reduces the effective temperature by an average of 10 percent. This shift in effective temperature is also reflected by shifts in several other stellar parameters relative to previous O4 spectral-type calibrations. It is also shown through the analysis of the two O4 V stars that scatter in spectral type calibrations is introduced by assuming that the observed line profile reflects the photospheric stellar parameters.

Comparison of Atmospheric Parameters Derived from In-Situ and Hyper-/Multispectral Remote Sensing Data of Beautiful Bavarian Lakes

NASA Astrophysics Data System (ADS)

Riedel, S.; Gege, P.; Schneider, M.; Pfug, B.; Oppelt, N.

2016-08-01

Atmospheric correction is a critical step and can be a limiting factor in the extraction of aquatic ecosystem parameters from remote sensing data of coastal and lake waters. Atmospheric correction models commonly in use for open ocean water and land surfaces can lead to large errors when applied to hyperspectral images taken from satellite or aircraft. The main problems arise from uncertainties in aerosol parameters and neglecting the adjacency effect, which originates from multiple scattering of upwelling radiance from the surrounding land. To better understand the challenges for developing an atmospheric correction model suitable for lakes, we compare atmospheric parameters derived from Sentinel- 2A and airborne hyperspectral data (HySpex) of two Bavarian lakes (Klostersee, Lake Starnberg) with in-situ measurements performed with RAMSES and Ibsen spectrometer systems and a Microtops sun photometer.

Soil Erosion as a stochastic process

NASA Astrophysics Data System (ADS)

Casper, Markus C.

2015-04-01

The main tools to provide estimations concerning risk and amount of erosion are different types of soil erosion models: on the one hand, there are empirically based model concepts on the other hand there are more physically based or process based models. However, both types of models have substantial weak points. All empirical model concepts are only capable of providing rough estimates over larger temporal and spatial scales, they do not account for many driving factors that are in the scope of scenario related analysis. In addition, the physically based models contain important empirical parts and hence, the demand for universality and transferability is not given. As a common feature, we find, that all models rely on parameters and input variables, which are to certain, extend spatially and temporally averaged. A central question is whether the apparent heterogeneity of soil properties or the random nature of driving forces needs to be better considered in our modelling concepts. Traditionally, researchers have attempted to remove spatial and temporal variability through homogenization. However, homogenization has been achieved through physical manipulation of the system, or by statistical averaging procedures. The price for obtaining this homogenized (average) model concepts of soils and soil related processes has often been a failure to recognize the profound importance of heterogeneity in many of the properties and processes that we study. Especially soil infiltrability and the resistance (also called "critical shear stress" or "critical stream power") are the most important empirical factors of physically based erosion models. The erosion resistance is theoretically a substrate specific parameter, but in reality, the threshold where soil erosion begins is determined experimentally. The soil infiltrability is often calculated with empirical relationships (e.g. based on grain size distribution). Consequently, to better fit reality, this value needs to be corrected experimentally. To overcome this disadvantage of our actual models, soil erosion models are needed that are able to use stochastic directly variables and parameter distributions. There are only some minor approaches in this direction. The most advanced is the model "STOSEM" proposed by Sidorchuk in 2005. In this model, only a small part of the soil erosion processes is described, the aggregate detachment and the aggregate transport by flowing water. The concept is highly simplified, for example, many parameters are temporally invariant. Nevertheless, the main problem is that our existing measurements and experiments are not geared to provide stochastic parameters (e.g. as probability density functions); in the best case they deliver a statistical validation of the mean values. Again, we get effective parameters, spatially and temporally averaged. There is an urgent need for laboratory and field experiments on overland flow structure, raindrop effects and erosion rate, which deliver information on spatial and temporal structure of soil and surface properties and processes.

Transient states of air parameters after a stoppage and re-start of the main fan / Stany przejściowe parametrów powietrza po postoju i załączeniu wentylatora głównego

NASA Astrophysics Data System (ADS)

Wasilewski, Stanisław

2012-12-01

A stoppage of the main ventilation fan constitutes a disturbance of ventilation conditions of a deepmine and its effects can cause serious hazards by generating transient states of air and gas flow. Main ventilation fans are the basic deep-mine facilities; therefore, under mining regulations it is only allowed to stop them with the consent and under the conditions specified by the mine maintenance manager. The stoppage of the main ventilation fan may be accompanied by transient air parameters, including the air pressure and flow patterns. There is even the likelihood of reversing the direction of air flow, which, in case of methane mines, can pose a major hazard, particularly in sections of the mine with fire fields or large goaf areas. At the same time, stoppages of deep-mine main ventilation fans create interesting research conditions, which if conducted under the supervision of the monitoring systems, can provide much information about the transient processes of pressure, air and gas flow in underground workings. This article is a discussion of air parameter observations in mine workings made as part of such experiments. It also presents the procedure of the experiments, conducted in three mines. They involved the observation of transient processes of mine air parameters, and most interestingly, the recording of pressure and air and gas flow in the workings of the mine ventilation networks by mine monitoring systems and using specialist recording instruments. In mining practice, both in Poland and elsewhere, software tools and computer modelling methods are used to try and reproduce the conditions prior to and during disasters based on the existing network model and monitoring system data. The use of these tools to simulate the alternatives of combating and liquidation of the gas-fire hazard after its occurrence is an important issue. Measurement data collected during the experiments provides interesting research material for the verification and validation of the software tools used for the simulation of processes occurring in deep-mine ventilation systems.

The alfa and beta of tumours: a review of parameters of the linear-quadratic model, derived from clinical radiotherapy studies.

PubMed

van Leeuwen, C M; Oei, A L; Crezee, J; Bel, A; Franken, N A P; Stalpers, L J A; Kok, H P

2018-05-16

Prediction of radiobiological response is a major challenge in radiotherapy. Of several radiobiological models, the linear-quadratic (LQ) model has been best validated by experimental and clinical data. Clinically, the LQ model is mainly used to estimate equivalent radiotherapy schedules (e.g. calculate the equivalent dose in 2 Gy fractions, EQD 2 ), but increasingly also to predict tumour control probability (TCP) and normal tissue complication probability (NTCP) using logistic models. The selection of accurate LQ parameters α, β and α/β is pivotal for a reliable estimate of radiation response. The aim of this review is to provide an overview of published values for the LQ parameters of human tumours as a guideline for radiation oncologists and radiation researchers to select appropriate radiobiological parameter values for LQ modelling in clinical radiotherapy. We performed a systematic literature search and found sixty-four clinical studies reporting α, β and α/β for tumours. Tumour site, histology, stage, number of patients, type of LQ model, radiation type, TCP model, clinical endpoint and radiobiological parameter estimates were extracted. Next, we stratified by tumour site and by tumour histology. Study heterogeneity was expressed by the I 2 statistic, i.e. the percentage of variance in reported values not explained by chance. A large heterogeneity in LQ parameters was found within and between studies (I 2  > 75%). For the same tumour site, differences in histology partially explain differences in the LQ parameters: epithelial tumours have higher α/β values than adenocarcinomas. For tumour sites with different histologies, such as in oesophageal cancer, the α/β estimates correlate well with histology. However, many other factors contribute to the study heterogeneity of LQ parameters, e.g. tumour stage, type of LQ model, TCP model and clinical endpoint (i.e. survival, tumour control and biochemical control). The value of LQ parameters for tumours as published in clinical radiotherapy studies depends on many clinical and methodological factors. Therefore, for clinical use of the LQ model, LQ parameters for tumour should be selected carefully, based on tumour site, histology and the applied LQ model. To account for uncertainties in LQ parameter estimates, exploring a range of values is recommended.

Impact of the calibration period on the conceptual rainfall-runoff model parameter estimates

NASA Astrophysics Data System (ADS)

Todorovic, Andrijana; Plavsic, Jasna

2015-04-01

A conceptual rainfall-runoff model is defined by its structure and parameters, which are commonly inferred through model calibration. Parameter estimates depend on objective function(s), optimisation method, and calibration period. Model calibration over different periods may result in dissimilar parameter estimates, while model efficiency decreases outside calibration period. Problem of model (parameter) transferability, which conditions reliability of hydrologic simulations, has been investigated for decades. In this paper, dependence of the parameter estimates and model performance on calibration period is analysed. The main question that is addressed is: are there any changes in optimised parameters and model efficiency that can be linked to the changes in hydrologic or meteorological variables (flow, precipitation and temperature)? Conceptual, semi-distributed HBV-light model is calibrated over five-year periods shifted by a year (sliding time windows). Length of the calibration periods is selected to enable identification of all parameters. One water year of model warm-up precedes every simulation, which starts with the beginning of a water year. The model is calibrated using the built-in GAP optimisation algorithm. The objective function used for calibration is composed of Nash-Sutcliffe coefficient for flows and logarithms of flows, and volumetric error, all of which participate in the composite objective function with approximately equal weights. Same prior parameter ranges are used in all simulations. The model is calibrated against flows observed at the Slovac stream gauge on the Kolubara River in Serbia (records from 1954 to 2013). There are no trends in precipitation nor in flows, however, there is a statistically significant increasing trend in temperatures at this catchment. Parameter variability across the calibration periods is quantified in terms of standard deviations of normalised parameters, enabling detection of the most variable parameters. Correlation coefficients among optimised model parameters and total precipitation P, mean temperature T and mean flow Q are calculated to give an insight into parameter dependence on the hydrometeorological drivers. The results reveal high sensitivity of almost all model parameters towards calibration period. The highest variability is displayed by the refreezing coefficient, water holding capacity, and temperature gradient. The only statistically significant (decreasing) trend is detected in the evapotranspiration reduction threshold. Statistically significant correlation is detected between the precipitation gradient and precipitation depth, and between the time-area histogram base and flows. All other correlations are not statistically significant, implying that changes in optimised parameters cannot generally be linked to the changes in P, T or Q. As for the model performance, the model reproduces the observed runoff satisfactorily, though the runoff is slightly overestimated in wet periods. The Nash-Sutcliffe efficiency coefficient (NSE) ranges from 0.44 to 0.79. Higher NSE values are obtained over wetter periods, what is supported by statistically significant correlation between NSE and flows. Overall, no systematic variations in parameters or in model performance are detected. Parameter variability may therefore rather be attributed to errors in data or inadequacies in the model structure. Further research is required to examine the impact of the calibration strategy or model structure on the variability in optimised parameters in time.

Kinetics modelling of color deterioration during thermal processing of tomato paste with the use of response surface methodology

NASA Astrophysics Data System (ADS)

Ganje, Mohammad; Jafari, Seid Mahdi; Farzaneh, Vahid; Malekjani, Narges

2018-06-01

To study the kinetics of color degradation, the tomato paste was designed to be processed at three different temperatures including 60, 70 and 80 °C for 25, 50, 75 and 100 min. a/b ratio, total color difference, saturation index and hue angle were calculated with the use of three main color parameters including L (lightness), a (redness-greenness) and b (yellowness-blueness) values. Kinetics of color degradation was developed by Arrhenius equation and the alterations were modelled with the use of response surface methodology (RSM). It was detected that all of the studied responses followed a first order reaction kinetics with an exception in TCD parameter (zeroth order). TCD and a/b respectively with the highest and lowest activation energy presented the highest sensitivity to the temperature alterations. The maximum and minimum rates of alterations were observed by TCD and b parameters, respectively. It was obviously determined that all of the studied parameters (responses) were affected by the selected independent parameters.

Oceanic influence on seasonal malaria outbreaks over Senegal and Sahel

NASA Astrophysics Data System (ADS)

Diouf, Ibrahima; Rodríguez de Fonseca, Belen; Deme, Abdoulaye; Cisse Cisse, Moustapha; Ndione Ndione, Jaques-Andre; Gaye, Amadou T.; Suarez, Roberto

2015-04-01

Beyond assessment and analysis of observed and simulated malaria parameters, this study is furthermore undertaken in the framework of predictability of malaria outbreaks in Senegal and remote regions in Sahel, which are found to take place two months after the rainy season. The predictors are the sea surface temperature anomalous patterns at different ocean basins mainly over the Pacific and Atlantic as they are related to changes in air temperature, humidity, rainfall and wind. A relationship between El Niño and anomalous malaria parameters is found. The malaria parameters are calculated with the Liverpool Malaria Model (LMM) using meteorological datasets from different reanalysis products. A hindcast of these parameters is performed using the Sea Surface temperature based Statistical Seasonal ForeCAST (S4CAST) model developed at UCM in order to predict malaria parameters some months in advance. The results of this work will be useful for decision makers to better access to climate forecasts and application on malaria transmission risk.

Physical and geometrical parameters of VCBS XIII: HIP 105947

NASA Astrophysics Data System (ADS)

Gumaan Masda, Suhail; Al-Wardat, Mashhoor Ahmed; Pathan, Jiyaulla Khan Moula Khan

2018-06-01

The best physical and geometrical parameters of the main sequence close visual binary system (CVBS), HIP 105947, are presented. These parameters have been constructed conclusively using Al-Wardat’s complex method for analyzing CVBSs, which is a method for constructing a synthetic spectral energy distribution (SED) for the entire binary system using individual SEDs for each component star. The model atmospheres are in its turn built using the Kurucz (ATLAS9) line-blanketed plane-parallel models. At the same time, the orbital parameters for the system are calculated using Tokovinin’s dynamical method for constructing the best orbits of an interferometric binary system. Moreover, the mass-sum of the components, as well as the Δθ and Δρ residuals for the system, is introduced. The combination of Al-Wardat’s and Tokovinin’s methods yields the best estimations of the physical and geometrical parameters. The positions of the components in the system on the evolutionary tracks and isochrones are plotted and the formation and evolution of the system are discussed.

VizieR Online Data Catalog: Be star rotational velocities distribution (Zorec+, 2016)

NASA Astrophysics Data System (ADS)

Zorec, J.; Fremat, Y.; Domiciano de Souza, A.; Royer, F.; Cidale, L.; Hubert, A.-M.; Semaan, T.; Martayan, C.; Cochetti, Y. R.; Arias, M. L.; Aidelman, Y.; Stee, P.

2016-06-01

Table 1 contains apparent fundamental parameters of the 233 Galactic Be stars. For each Be star is given the HD number, the effective temperature, effective surface gravity and bolometric luminosity. They correspond to the parameters of a plan parallel model of stellar atmosphere that fits the energy distribution of the stellar apparent hemisphere rotationally deformed. In Table 1 are also given the color excess E(B-V) and the vsini rotation parameter determined with model atmospheres of rigidly rotating stars. For each parameter is given the 1sigma uncertainty. In the notes are given the authors that produced some reported the data or the methods used to obtain the data. Table 4 contains parent-non-rotating-counterpart fundamental parameters of 233 Be stars: effective temperature, effective surface gravity, bolometric luminosity in solar units, stellar mass in solar units, fractional main-sequence stellar age, pnrc-apparent rotational velocity, critical velocity, ratio of centrifugal-force to gravity in the equator, inclination angle of the rotational axis. (2 data files).

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

Liese, Eric; Zitney, Stephen E.

A multi-stage centrifugal compressor model is presented with emphasis on analyzing use of an exit flow coefficient vs. an inlet flow coefficient performance parameter to predict off-design conditions in the critical region of a supercritical carbon dioxide (CO 2) power cycle. A description of the performance parameters is given along with their implementation in a design model (number of stages, basic sizing, etc.) and a dynamic model (for use in transient studies). A design case is shown for two compressors, a bypass compressor and a main compressor, as defined in a process simulation of a 10 megawatt (MW) supercritical COmore » 2 recompression Brayton cycle. Simulation results are presented for a simple open cycle and closed cycle process with changes to the inlet temperature of the main compressor which operates near the CO 2 critical point. Results showed some difference in results using the exit vs. inlet flow coefficient correction, however, it was not significant for the range of conditions examined. Here, this paper also serves as a reference for future works, including a full process simulation of the 10 MW recompression Brayton cycle.« less

Comparison of main-shock and aftershock fragility curves developed for New Zealand and US buildings

USGS Publications Warehouse

Uma, S.R.; Ryu, H.; Luco, N.; Liel, A.B.; Raghunandan, M.

2011-01-01

Seismic risk assessment involves the development of fragility functions to express the relationship between ground motion intensity and damage potential. In evaluating the risk associated with the building inventory in a region, it is essential to capture 'actual' characteristics of the buildings and group them so that 'generic building types' can be generated for further analysis of their damage potential. Variations in building characteristics across regions/countries largely influence the resulting fragility functions, such that building models are unsuitable to be adopted for risk assessment in any other region where a different set of building is present. In this paper, for a given building type (represented in terms of height and structural system), typical New Zealand and US building models are considered to illustrate the differences in structural model parameters and their effects on resulting fragility functions for a set of main-shocks and aftershocks. From this study, the general conclusion is that the methodology and assumptions used to derive basic capacity curve parameters have a considerable influence on fragility curves.

Improved object optimal synthetic description, modeling, learning, and discrimination by GEOGINE computational kernel

NASA Astrophysics Data System (ADS)

Fiorini, Rodolfo A.; Dacquino, Gianfranco

2005-03-01

GEOGINE (GEOmetrical enGINE), a state-of-the-art OMG (Ontological Model Generator) based on n-D Tensor Invariants for n-Dimensional shape/texture optimal synthetic representation, description and learning, was presented in previous conferences elsewhere recently. Improved computational algorithms based on the computational invariant theory of finite groups in Euclidean space and a demo application is presented. Progressive model automatic generation is discussed. GEOGINE can be used as an efficient computational kernel for fast reliable application development and delivery in advanced biomedical engineering, biometric, intelligent computing, target recognition, content image retrieval, data mining technological areas mainly. Ontology can be regarded as a logical theory accounting for the intended meaning of a formal dictionary, i.e., its ontological commitment to a particular conceptualization of the world object. According to this approach, "n-D Tensor Calculus" can be considered a "Formal Language" to reliably compute optimized "n-Dimensional Tensor Invariants" as specific object "invariant parameter and attribute words" for automated n-Dimensional shape/texture optimal synthetic object description by incremental model generation. The class of those "invariant parameter and attribute words" can be thought as a specific "Formal Vocabulary" learned from a "Generalized Formal Dictionary" of the "Computational Tensor Invariants" language. Even object chromatic attributes can be effectively and reliably computed from object geometric parameters into robust colour shape invariant characteristics. As a matter of fact, any highly sophisticated application needing effective, robust object geometric/colour invariant attribute capture and parameterization features, for reliable automated object learning and discrimination can deeply benefit from GEOGINE progressive automated model generation computational kernel performance. Main operational advantages over previous, similar approaches are: 1) Progressive Automated Invariant Model Generation, 2) Invariant Minimal Complete Description Set for computational efficiency, 3) Arbitrary Model Precision for robust object description and identification.

Performance of two predictive uncertainty estimation approaches for conceptual Rainfall-Runoff Model: Bayesian Joint Inference and Hydrologic Uncertainty Post-processing

NASA Astrophysics Data System (ADS)

Hernández-López, Mario R.; Romero-Cuéllar, Jonathan; Camilo Múnera-Estrada, Juan; Coccia, Gabriele; Francés, Félix

2017-04-01

It is noticeably important to emphasize the role of uncertainty particularly when the model forecasts are used to support decision-making and water management. This research compares two approaches for the evaluation of the predictive uncertainty in hydrological modeling. First approach is the Bayesian Joint Inference of hydrological and error models. Second approach is carried out through the Model Conditional Processor using the Truncated Normal Distribution in the transformed space. This comparison is focused on the predictive distribution reliability. The case study is applied to two basins included in the Model Parameter Estimation Experiment (MOPEX). These two basins, which have different hydrological complexity, are the French Broad River (North Carolina) and the Guadalupe River (Texas). The results indicate that generally, both approaches are able to provide similar predictive performances. However, the differences between them can arise in basins with complex hydrology (e.g. ephemeral basins). This is because obtained results with Bayesian Joint Inference are strongly dependent on the suitability of the hypothesized error model. Similarly, the results in the case of the Model Conditional Processor are mainly influenced by the selected model of tails or even by the selected full probability distribution model of the data in the real space, and by the definition of the Truncated Normal Distribution in the transformed space. In summary, the different hypotheses that the modeler choose on each of the two approaches are the main cause of the different results. This research also explores a proper combination of both methodologies which could be useful to achieve less biased hydrological parameter estimation. For this approach, firstly the predictive distribution is obtained through the Model Conditional Processor. Secondly, this predictive distribution is used to derive the corresponding additive error model which is employed for the hydrological parameter estimation with the Bayesian Joint Inference methodology.

Parameter dependences of the separatrix density in nitrogen seeded ASDEX Upgrade H-mode discharges

NASA Astrophysics Data System (ADS)

Kallenbach, A.; Sun, H. J.; Eich, T.; Carralero, D.; Hobirk, J.; Scarabosio, A.; Siccinio, M.; ASDEX Upgrade Team; EUROfusion MST1 Team

2018-04-01

The upstream separatrix electron density is an important interface parameter for core performance and divertor power exhaust. It has been measured in ASDEX Upgrade H-mode discharges by means of Thomson scattering using a self-consistent estimate of the upstream electron temperature under the assumption of Spitzer-Härm electron conduction. Its dependence on various plasma parameters has been tested for different plasma conditions in H-mode. The leading parameter determining n e,sep was found to be the neutral divertor pressure, which can be considered as an engineering parameter since it is determined mainly by the gas puff rate and the pumping speed. The experimentally found parameter dependence of n e,sep, which is dominated by the divertor neutral pressure, could be approximately reconciled by 2-point modelling.

A New Strategy in Observer Modeling for Greenhouse Cucumber Seedling Growth

PubMed Central

Qiu, Quan; Zheng, Chenfei; Wang, Wenping; Qiao, Xiaojun; Bai, He; Yu, Jingquan; Shi, Kai

2017-01-01

State observer is an essential component in computerized control loops for greenhouse-crop systems. However, the current accomplishments of observer modeling for greenhouse-crop systems mainly focus on mass/energy balance, ignoring physiological responses of crops. As a result, state observers for crop physiological responses are rarely developed, and control operations are typically made based on experience rather than actual crop requirements. In addition, existing observer models require a large number of parameters, leading to heavy computational load and poor application feasibility. To address these problems, we present a new state observer modeling strategy that takes both environmental information and crop physiological responses into consideration during the observer modeling process. Using greenhouse cucumber seedlings as an instance, we sample 10 physiological parameters of cucumber seedlings at different time point during the exponential growth stage, and employ them to build growth state observers together with 8 environmental parameters. Support vector machine (SVM) acts as the mathematical tool for observer modeling. Canonical correlation analysis (CCA) is used to select the dominant environmental and physiological parameters in the modeling process. With the dominant parameters, simplified observer models are built and tested. We conduct contrast experiments with different input parameter combinations on simplified and un-simplified observers. Experimental results indicate that physiological information can improve the prediction accuracies of the growth state observers. Furthermore, the simplified observer models can give equivalent or even better performance than the un-simplified ones, which verifies the feasibility of CCA. The current study can enable state observers to reflect crop requirements and make them feasible for applications with simplified shapes, which is significant for developing intelligent greenhouse control systems for modern greenhouse production. PMID:28848565

A New Strategy in Observer Modeling for Greenhouse Cucumber Seedling Growth.

PubMed

Qiu, Quan; Zheng, Chenfei; Wang, Wenping; Qiao, Xiaojun; Bai, He; Yu, Jingquan; Shi, Kai

2017-01-01

State observer is an essential component in computerized control loops for greenhouse-crop systems. However, the current accomplishments of observer modeling for greenhouse-crop systems mainly focus on mass/energy balance, ignoring physiological responses of crops. As a result, state observers for crop physiological responses are rarely developed, and control operations are typically made based on experience rather than actual crop requirements. In addition, existing observer models require a large number of parameters, leading to heavy computational load and poor application feasibility. To address these problems, we present a new state observer modeling strategy that takes both environmental information and crop physiological responses into consideration during the observer modeling process. Using greenhouse cucumber seedlings as an instance, we sample 10 physiological parameters of cucumber seedlings at different time point during the exponential growth stage, and employ them to build growth state observers together with 8 environmental parameters. Support vector machine (SVM) acts as the mathematical tool for observer modeling. Canonical correlation analysis (CCA) is used to select the dominant environmental and physiological parameters in the modeling process. With the dominant parameters, simplified observer models are built and tested. We conduct contrast experiments with different input parameter combinations on simplified and un-simplified observers. Experimental results indicate that physiological information can improve the prediction accuracies of the growth state observers. Furthermore, the simplified observer models can give equivalent or even better performance than the un-simplified ones, which verifies the feasibility of CCA. The current study can enable state observers to reflect crop requirements and make them feasible for applications with simplified shapes, which is significant for developing intelligent greenhouse control systems for modern greenhouse production.

Modelling an induced thermal plume with data from electrical resistivity tomography and distributed temperature sensing: a case study in northeast Italy

NASA Astrophysics Data System (ADS)

Cultrera, Matteo; Boaga, Jacopo; Di Sipio, Eloisa; Dalla Santa, Giorgia; De Seta, Massimiliano; Galgaro, Antonio

2018-05-01

Groundwater tracer tests are often used to improve aquifer characterization, but they present several disadvantages, such as the need to pour solutions or dyes into the aquifer system and alteration of the water's chemical properties. Thus, tracers can affect the groundwater flow mechanics and data interpretation becomes more complex, hindering effective study of ground heat pumps for low enthalpy geothermal systems. This paper presents a preliminary methodology based on a multidisciplinary application of heat as a tracer for defining the main parameters of shallow aquifers. The field monitoring techniques electrical resistivity tomography (ERT) and distributed temperature sensing (DTS) are noninvasive and were applied to a shallow-aquifer test site in northeast Italy. The combination of these measurement techniques supports the definition of the main aquifer parameters and therefore the construction of a reliable conceptual model, which is then described through the numerical code FEFLOW. This model is calibrated with DTS and validated by ERT outcomes. The reliability of the numerical model in terms of fate and transport is thereby enhanced, leading to the potential for better environmental management and protection of groundwater resources through more cost-effective solutions.

Chimera patterns in two-dimensional networks of coupled neurons.

PubMed

Schmidt, Alexander; Kasimatis, Theodoros; Hizanidis, Johanne; Provata, Astero; Hövel, Philipp

2017-03-01

We discuss synchronization patterns in networks of FitzHugh-Nagumo and leaky integrate-and-fire oscillators coupled in a two-dimensional toroidal geometry. A common feature between the two models is the presence of fast and slow dynamics, a typical characteristic of neurons. Earlier studies have demonstrated that both models when coupled nonlocally in one-dimensional ring networks produce chimera states for a large range of parameter values. In this study, we give evidence of a plethora of two-dimensional chimera patterns of various shapes, including spots, rings, stripes, and grids, observed in both models, as well as additional patterns found mainly in the FitzHugh-Nagumo system. Both systems exhibit multistability: For the same parameter values, different initial conditions give rise to different dynamical states. Transitions occur between various patterns when the parameters (coupling range, coupling strength, refractory period, and coupling phase) are varied. Many patterns observed in the two models follow similar rules. For example, the diameter of the rings grows linearly with the coupling radius.

Is our medical school socially accountable? The case of Faculty of Medicine, Suez Canal University.

PubMed

Hosny, Somaya; Ghaly, Mona; Boelen, Charles

2015-04-01

Faculty of Medicine, Suez Canal University (FOM/SCU) was established as community oriented school with innovative educational strategies. Social accountability represents the commitment of the medical school towards the community it serves. To assess FOM/SCU compliance to social accountability using the "Conceptualization, Production, Usability" (CPU) model. FOM/SCU's practice was reviewed against CPU model parameters. CPU consists of three domains, 11 sections and 31 parameters. Data were collected through unstructured interviews with the main stakeholders and documents review since 2005 to 2013. FOM/SCU shows general compliance to the three domains of the CPU. Very good compliance was shown to the "P" domain of the model through FOM/SCU's innovative educational system, students and faculty members. More work is needed on the "C" and "U" domains. FOM/SCU complies with many parameters of the CPU model; however, more work should be accomplished to comply with some items in the C and U domains so that FOM/SCU can be recognized as a proactive socially accountable school.

Chimera patterns in two-dimensional networks of coupled neurons

NASA Astrophysics Data System (ADS)

Schmidt, Alexander; Kasimatis, Theodoros; Hizanidis, Johanne; Provata, Astero; Hövel, Philipp

2017-03-01

We discuss synchronization patterns in networks of FitzHugh-Nagumo and leaky integrate-and-fire oscillators coupled in a two-dimensional toroidal geometry. A common feature between the two models is the presence of fast and slow dynamics, a typical characteristic of neurons. Earlier studies have demonstrated that both models when coupled nonlocally in one-dimensional ring networks produce chimera states for a large range of parameter values. In this study, we give evidence of a plethora of two-dimensional chimera patterns of various shapes, including spots, rings, stripes, and grids, observed in both models, as well as additional patterns found mainly in the FitzHugh-Nagumo system. Both systems exhibit multistability: For the same parameter values, different initial conditions give rise to different dynamical states. Transitions occur between various patterns when the parameters (coupling range, coupling strength, refractory period, and coupling phase) are varied. Many patterns observed in the two models follow similar rules. For example, the diameter of the rings grows linearly with the coupling radius.

Sensitivity analysis of discharge patterns of subthalamic nucleus in the model of basal ganglia in Parkinson disease.

PubMed

Singh, Jyotsna; Singh, Phool; Malik, Vikas

2017-01-01

Parkinson disease alters the information patterns in movement related pathways in brain. Experimental results performed on rats show that the activity patterns changes from single spike activity to mixed burst mode in Parkinson disease. However the cause of this change in activity pattern is not yet completely understood. Subthalamic nucleus is one of the main nuclei involved in the origin of motor dysfunction in Parkinson disease. In this paper, a single compartment conductance based model is considered which focuses on subthalamic nucleus and synaptic input from globus pallidus (external). This model shows highly nonlinear behavior with respect to various intrinsic parameters. Behavior of model has been presented with the help of activity patterns generated in healthy and Parkinson condition. These patterns have been compared by calculating their correlation coefficient for different values of intrinsic parameters. Results display that the activity patterns are very sensitive to various intrinsic parameters and calcium shows some promising results which provide insights into the motor dysfunction.

THE NuSTAR X-RAY SPECTRUM OF HERCULES X-1: A RADIATION-DOMINATED RADIATIVE SHOCK

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

Wolff, Michael T.; Wood, Kent S.; Becker, Peter A.

2016-11-10

We report on new spectral modeling of the accreting X-ray pulsar Hercules X-1. Our radiation-dominated radiative shock model is an implementation of the analytic work of Becker and Wolff on Comptonized accretion flows onto magnetic neutron stars. We obtain a good fit to the spin-phase-averaged 4–78 keV X-ray spectrum observed by the Nuclear Spectroscopic Telescope Array during a main-on phase of the Her X-1 35 day accretion disk precession period. This model allows us to estimate the accretion rate, the Comptonizing temperature of the radiating plasma, the radius of the magnetic polar cap, and the average scattering opacity parameters inmore » the accretion column. This is in contrast to previous phenomenological models that characterized the shape of the X-ray spectrum, but could not determine the physical parameters of the accretion flow. We describe the spectral fitting details and discuss the interpretation of the accretion flow physical parameters.« less

A physiology-based model describing heterogeneity in glucose metabolism: the core of the Eindhoven Diabetes Education Simulator (E-DES).

PubMed

Maas, Anne H; Rozendaal, Yvonne J W; van Pul, Carola; Hilbers, Peter A J; Cottaar, Ward J; Haak, Harm R; van Riel, Natal A W

2015-03-01

Current diabetes education methods are costly, time-consuming, and do not actively engage the patient. Here, we describe the development and verification of the physiological model for healthy subjects that forms the basis of the Eindhoven Diabetes Education Simulator (E-DES). E-DES shall provide diabetes patients with an individualized virtual practice environment incorporating the main factors that influence glycemic control: food, exercise, and medication. The physiological model consists of 4 compartments for which the inflow and outflow of glucose and insulin are calculated using 6 nonlinear coupled differential equations and 14 parameters. These parameters are estimated on 12 sets of oral glucose tolerance test (OGTT) data (226 healthy subjects) obtained from literature. The resulting parameter set is verified on 8 separate literature OGTT data sets (229 subjects). The model is considered verified if 95% of the glucose data points lie within an acceptance range of ±20% of the corresponding model value. All glucose data points of the verification data sets lie within the predefined acceptance range. Physiological processes represented in the model include insulin resistance and β-cell function. Adjusting the corresponding parameters allows to describe heterogeneity in the data and shows the capabilities of this model for individualization. We have verified the physiological model of the E-DES for healthy subjects. Heterogeneity of the data has successfully been modeled by adjusting the 4 parameters describing insulin resistance and β-cell function. Our model will form the basis of a simulator providing individualized education on glucose control. © 2014 Diabetes Technology Society.

A Main Sequence For Quasars

NASA Astrophysics Data System (ADS)

Marziani, Paola; Sulentic, J. W.; Dultzin, D.; Negrete, A.; del Olmo, A.; Martínez-Carballo, M. A.; Stirpe, G. M.; D'Onofrio, M.; Perea, J.

2016-10-01

The 4D eigenvector 1 parameter space defined by Sulentic et al. may be seen as a surrogate H-R diagram for quasars. As in the stellar H-R diagram, a source sequence can be easily identified. In the case of quasars, the main sequence appears to be mainly driven by Eddington ratio. A transition Eddington ratio may in part explain the striking observational differences between quasars at opposite ends of the main sequence. The eigenvector-1 approach opens the door towards properly contextualized models of quasar physics, geometry and kinematics. We review some of the progress that has been made over the past 15 years, and point out still unsolved issues.

Joint parameter and state estimation algorithms for real-time traffic monitoring.

DOT National Transportation Integrated Search

2013-12-01

A common approach to traffic monitoring is to combine a macroscopic traffic flow model with traffic sensor data in a process called state estimation, data fusion, or data assimilation. The main challenge of traffic state estimation is the integration...

Performance Evaluation and Parameter Identification on DROID III

NASA Technical Reports Server (NTRS)

Plumb, Julianna J.

2011-01-01

The DROID III project consisted of two main parts. The former, performance evaluation, focused on the performance characteristics of the aircraft such as lift to drag ratio, thrust required for level flight, and rate of climb. The latter, parameter identification, focused on finding the aerodynamic coefficients for the aircraft using a system that creates a mathematical model to match the flight data of doublet maneuvers and the aircraft s response. Both portions of the project called for flight testing and that data is now available on account of this project. The conclusion of the project is that the performance evaluation data is well-within desired standards but could be improved with a thrust model, and that parameter identification is still in need of more data processing but seems to produce reasonable results thus far.

Dynamic stiffness of chemically and physically ageing rubber vibration isolators in the audible frequency range. Part 1: constitutive equations

NASA Astrophysics Data System (ADS)

Kari, Leif

2017-09-01

The constitutive equations of chemically and physically ageing rubber in the audible frequency range are modelled as a function of ageing temperature, ageing time, actual temperature, time and frequency. The constitutive equations are derived by assuming nearly incompressible material with elastic spherical response and viscoelastic deviatoric response, using Mittag-Leffler relaxation function of fractional derivative type, the main advantage being the minimum material parameters needed to successfully fit experimental data over a broad frequency range. The material is furthermore assumed essentially entropic and thermo-mechanically simple while using a modified William-Landel-Ferry shift function to take into account temperature dependence and physical ageing, with fractional free volume evolution modelled by a nonlinear, fractional differential equation with relaxation time identical to that of the stress response and related to the fractional free volume by Doolittle equation. Physical ageing is a reversible ageing process, including trapping and freeing of polymer chain ends, polymer chain reorganizations and free volume changes. In contrast, chemical ageing is an irreversible process, mainly attributed to oxygen reaction with polymer network either damaging the network by scission or reformation of new polymer links. The chemical ageing is modelled by inner variables that are determined by inner fractional evolution equations. Finally, the model parameters are fitted to measurements results of natural rubber over a broad audible frequency range, and various parameter studies are performed including comparison with results obtained by ordinary, non-fractional ageing evolution differential equations.

Simulation of streamflow in the Pleasant, Narraguagus, Sheepscot, and Royal Rivers, Maine, using watershed models

USGS Publications Warehouse

Dudley, Robert W.; Nielsen, Martha G.

2011-01-01

The U.S. Geological Survey (USGS) began a study in 2008 to investigate anticipated changes in summer streamflows and stream temperatures in four coastal Maine river basins and the potential effects of those changes on populations of endangered Atlantic salmon. To achieve this purpose, it was necessary to characterize the quantity and timing of streamflow in these rivers by developing and evaluating a distributed-parameter watershed model for a part of each river basin by using the USGS Precipitation-Runoff Modeling System (PRMS). The GIS (geographic information system) Weasel, a USGS software application, was used to delineate the four study basins and their many subbasins, and to derive parameters for their geographic features. The models were calibrated using a four-step optimization procedure in which model output was evaluated against four datasets for calibrating solar radiation, potential evapotranspiration, annual and seasonal water balances, and daily streamflows. The calibration procedure involved thousands of model runs that used the USGS software application Luca (Let us calibrate). Luca uses the Shuffled Complex Evolution (SCE) global search algorithm to calibrate the model parameters. The calibrated watershed models performed satisfactorily, in that Nash-Sutcliffe efficiency (NSE) statistic values for the calibration periods ranged from 0.59 to 0.75 (on a scale of negative infinity to 1) and NSE statistic values for the evaluation periods ranged from 0.55 to 0.73. The calibrated watershed models simulate daily streamflow at many locations in each study basin. These models enable natural resources managers to characterize the timing and amount of streamflow in order to support a variety of water-resources efforts including water-quality calculations, assessments of water use, modeling of population dynamics and migration of Atlantic salmon, modeling and assessment of habitat, and simulation of anticipated changes to streamflow and water temperature resulting from changes forecast for air temperature and precipitation.

Nanoseismicity and picoseismicity rate changes from static stress triggering caused by a Mw 2.2 earthquake in Mponeng gold mine, South Africa

NASA Astrophysics Data System (ADS)

Kozłowska, Maria; Orlecka-Sikora, Beata; Kwiatek, Grzegorz; Boettcher, Margaret S.; Dresen, Georg

2015-01-01

Static stress changes following large earthquakes are known to affect the rate and distribution of aftershocks, yet this process has not been thoroughly investigated for nanoseismicity and picoseismicity at centimeter length scales. Here we utilize a unique data set of M ≥ -3.4 earthquakes following a Mw 2.2 earthquake in Mponeng gold mine, South Africa, that was recorded during a quiet interval in the mine to investigate if rate- and state-based modeling is valid for shallow, mining-induced seismicity. We use Dieterich's (1994) rate- and state-dependent formulation for earthquake productivity, which requires estimation of four parameters: (1) Coulomb stress changes due to the main shock, (2) the reference seismicity rate, (3) frictional resistance parameter, and (4) the duration of aftershock relaxation time. Comparisons of the modeled spatiotemporal patterns of seismicity based on two different source models with the observed distribution show that while the spatial patterns match well, the rate of modeled aftershocks is lower than the observed rate. To test our model, we used three metrics of the goodness-of-fit evaluation. The null hypothesis, of no significant difference between modeled and observed seismicity rates, was only rejected in the depth interval containing the main shock. Results show that mining-induced earthquakes may be followed by a stress relaxation expressed through aftershocks located on the rupture plane and in regions of positive Coulomb stress change. Furthermore, we demonstrate that the main features of the temporal and spatial distributions of very small, mining-induced earthquakes can be successfully determined using rate- and state-based stress modeling.

Comparing Families of Dynamic Causal Models

PubMed Central

Penny, Will D.; Stephan, Klaas E.; Daunizeau, Jean; Rosa, Maria J.; Friston, Karl J.; Schofield, Thomas M.; Leff, Alex P.

2010-01-01

Mathematical models of scientific data can be formally compared using Bayesian model evidence. Previous applications in the biological sciences have mainly focussed on model selection in which one first selects the model with the highest evidence and then makes inferences based on the parameters of that model. This “best model” approach is very useful but can become brittle if there are a large number of models to compare, and if different subjects use different models. To overcome this shortcoming we propose the combination of two further approaches: (i) family level inference and (ii) Bayesian model averaging within families. Family level inference removes uncertainty about aspects of model structure other than the characteristic of interest. For example: What are the inputs to the system? Is processing serial or parallel? Is it linear or nonlinear? Is it mediated by a single, crucial connection? We apply Bayesian model averaging within families to provide inferences about parameters that are independent of further assumptions about model structure. We illustrate the methods using Dynamic Causal Models of brain imaging data. PMID:20300649

Dependence of Intramyocardial Pressure and Coronary Flow on Ventricular Loading and Contractility: A Model Study

PubMed Central

Borsje, Petra; Arts, Theo; van De Vosse, Frans N.

2006-01-01

The phasic coronary arterial inflow during the normal cardiac cycle has been explained with simple (waterfall, intramyocardial pump) models, emphasizing the role of ventricular pressure. To explain changes in isovolumic and low afterload beats, these models were extended with the effect of three-dimensional wall stress, nonlinear characteristics of the coronary bed, and extravascular fluid exchange. With the associated increase in the number of model parameters, a detailed parameter sensitivity analysis has become difficult. Therefore we investigated the primary relations between ventricular pressure and volume, wall stress, intramyocardial pressure and coronary blood flow, with a mathematical model with a limited number of parameters. The model replicates several experimental observations: the phasic character of coronary inflow is virtually independent of maximum ventricular pressure, the amplitude of the coronary flow signal varies about proportionally with cardiac contractility, and intramyocardial pressure in the ventricular wall may exceed ventricular pressure. A parameter sensitivity analysis shows that the normalized amplitude of coronary inflow is mainly determined by contractility, reflected in ventricular pressure and, at low ventricular volumes, radial wall stress. Normalized flow amplitude is less sensitive to myocardial coronary compliance and resistance, and to the relation between active fiber stress, time, and sarcomere shortening velocity. PMID:17048105

Nested Sampling for Bayesian Model Comparison in the Context of Salmonella Disease Dynamics

PubMed Central

Dybowski, Richard; McKinley, Trevelyan J.; Mastroeni, Pietro; Restif, Olivier

2013-01-01

Understanding the mechanisms underlying the observed dynamics of complex biological systems requires the statistical assessment and comparison of multiple alternative models. Although this has traditionally been done using maximum likelihood-based methods such as Akaike's Information Criterion (AIC), Bayesian methods have gained in popularity because they provide more informative output in the form of posterior probability distributions. However, comparison between multiple models in a Bayesian framework is made difficult by the computational cost of numerical integration over large parameter spaces. A new, efficient method for the computation of posterior probabilities has recently been proposed and applied to complex problems from the physical sciences. Here we demonstrate how nested sampling can be used for inference and model comparison in biological sciences. We present a reanalysis of data from experimental infection of mice with Salmonella enterica showing the distribution of bacteria in liver cells. In addition to confirming the main finding of the original analysis, which relied on AIC, our approach provides: (a) integration across the parameter space, (b) estimation of the posterior parameter distributions (with visualisations of parameter correlations), and (c) estimation of the posterior predictive distributions for goodness-of-fit assessments of the models. The goodness-of-fit results suggest that alternative mechanistic models and a relaxation of the quasi-stationary assumption should be considered. PMID:24376528

Energy- and wave-based beam-tracing prediction of room-acoustical parameters using different boundary conditions.

PubMed

Yousefzadeh, Behrooz; Hodgson, Murray

2012-09-01

A beam-tracing model was used to study the acoustical responses of three empty, rectangular rooms with different boundary conditions. The model is wave-based (accounting for sound phase) and can be applied to rooms with extended-reaction surfaces that are made of multiple layers of solid, fluid, or poroelastic materials-the acoustical properties of these surfaces are calculated using Biot theory. Three room-acoustical parameters were studied in various room configurations: sound strength, reverberation time, and RApid Speech Transmission Index. The main objective was to investigate the effects of modeling surfaces as either local or extended reaction on predicted values of these three parameters. Moreover, the significance of modeling interference effects was investigated, including the study of sound phase-change on surface reflection. Modeling surfaces as of local or extended reaction was found to be significant for surfaces consisting of multiple layers, specifically when one of the layers is air. For multilayers of solid materials with an air-cavity, this was most significant around their mass-air-mass resonance frequencies. Accounting for interference effects made significant changes in the predicted values of all parameters. Modeling phase change on reflection, on the other hand, was found to be relatively much less significant.

An evaluation of the predictive capabilities of CTRW and MRMT

NASA Astrophysics Data System (ADS)

Fiori, Aldo; Zarlenga, Antonio; Gotovac, Hrvoje; Jankovic, Igor; Cvetkovic, Vladimir; Dagan, Gedeon

2016-04-01

The prediction capability of two approximate models of non-Fickian transport in highly heterogeneous aquifers is checked by comparison with accurate numerical simulations, for mean uniform flow of velocity U. The two models considered are the MRMT (Multi Rate Mass Transfer) and CTRW (Continuous Time Random Walk) models. Both circumvent the need to solve the flow and transport equations by using proxy models, which provide the BTC μ(x,t) depending on a vector a of unknown 5 parameters. Although underlain by different conceptualisations, the two models have a similar mathematical structure. The proponents of the models suggest using field transport experiments at a small scale to calibrate a, toward predicting transport at larger scale. The strategy was tested with the aid of accurate numerical simulations in two and three dimensions from the literature. First, the 5 parameter values were calibrated by using the simulated μ at a control plane close to the injection one and subsequently using these same parameters for predicting μ at further 10 control planes. It is found that the two methods perform equally well, though the parameters identification is nonunique, with a large set of parameters providing similar fitting. Also, errors in the determination of the mean eulerian velocity may lead to significant shifts of the predicted BTC. It is found that the simulated BTCs satisfy Markovianity: they can be found as n-fold convolutions of a "kernel", in line with the models' main assumption.

Joint state and parameter estimation of the hemodynamic model by particle smoother expectation maximization method

NASA Astrophysics Data System (ADS)

Aslan, Serdar; Taylan Cemgil, Ali; Akın, Ata

2016-08-01

Objective. In this paper, we aimed for the robust estimation of the parameters and states of the hemodynamic model by using blood oxygen level dependent signal. Approach. In the fMRI literature, there are only a few successful methods that are able to make a joint estimation of the states and parameters of the hemodynamic model. In this paper, we implemented a maximum likelihood based method called the particle smoother expectation maximization (PSEM) algorithm for the joint state and parameter estimation. Main results. Former sequential Monte Carlo methods were only reliable in the hemodynamic state estimates. They were claimed to outperform the local linearization (LL) filter and the extended Kalman filter (EKF). The PSEM algorithm is compared with the most successful method called square-root cubature Kalman smoother (SCKS) for both state and parameter estimation. SCKS was found to be better than the dynamic expectation maximization (DEM) algorithm, which was shown to be a better estimator than EKF, LL and particle filters. Significance. PSEM was more accurate than SCKS for both the state and the parameter estimation. Hence, PSEM seems to be the most accurate method for the system identification and state estimation for the hemodynamic model inversion literature. This paper do not compare its results with Tikhonov-regularized Newton—CKF (TNF-CKF), a recent robust method which works in filtering sense.

[The validation of the parameters for a basic model of a power supply layout for general x-ray diagnostic apparatus].

PubMed

Blinov, N N

2000-01-01

Specifications for the main element of a modern X-ray diagnostic device an X-ray feeder are formulated. There is evidence for choosing its parameters. The new rational routine of X-ray study and the layout of a X-ray room are proposed. Information on the up-to-date commercially manufactured basic medium-frequency general-purpose X-ray feeder "URP-30 SCh Amico" is given.

Optimization of parameters affecting signal intensity in an LTQ-orbitrap in negative ion mode: A design of experiments approach.

PubMed

Lemonakis, Nikolaos; Skaltsounis, Alexios-Leandros; Tsarbopoulos, Anthony; Gikas, Evagelos

2016-01-15

A multistage optimization of all the parameters affecting detection/response in an LTQ-orbitrap analyzer was performed, using a design of experiments methodology. The signal intensity, a critical issue for mass analysis, was investigated and the optimization process was completed in three successive steps, taking into account the three main regions of an orbitrap, the ion generation, the ion transmission and the ion detection regions. Oleuropein and hydroxytyrosol were selected as the model compounds. Overall, applying this methodology the sensitivity was increased more than 24%, the resolution more than 6.5%, whereas the elapsed scan time was reduced nearly to its half. A high-resolution LTQ Orbitrap Discovery mass spectrometer was used for the determination of the analytes of interest. Thus, oleuropein and hydroxytyrosol were infused via the instruments syringe pump and they were analyzed employing electrospray ionization (ESI) in the negative high-resolution full-scan ion mode. The parameters of the three main regions of the LTQ-orbitrap were independently optimized in terms of maximum sensitivity. In this context, factorial design, response surface model and Plackett-Burman experiments were performed and analysis of variance was carried out to evaluate the validity of the statistical model and to determine the most significant parameters for signal intensity. The optimum MS conditions for each analyte were summarized and the method optimum condition was achieved by maximizing the desirability function. Our observation showed good agreement between the predicted optimum response and the responses collected at the predicted optimum conditions. Copyright © 2015 Elsevier B.V. All rights reserved.

An improved numerical model suggests potential differences of wind-blown sand between on Earth and Mars

NASA Astrophysics Data System (ADS)

Bo, T. L.; Fu, L. T.; Liu, L.; Zheng, X. J.

2017-06-01

The studies on wind-blown sand are crucial for understanding the change of climate and landscape on Mars. However, the disadvantages of the saltation models may result in unreliable predictions. In this paper, the saltation model has been improved from two main aspects, the aerodynamic surface roughness and the lift-off parameters. The aerodynamic surface roughness is expressed as function of particle size, wind strength, air density, and air dynamic viscosity. The lift-off parameters are improved through including the dependence of restitution coefficient on incident parameters and the correlation between saltating speed and angle. The improved model proved to be capable of reproducing the observed data well in both stable stage and evolution process. The modeling of wind-blown sand is promoted by all improved aspects, and the dependence of restitution coefficient on incident parameters could not be ignored. The constant restitution coefficient and uncorrelated lift-off parameter distributions would lead to both the overestimation of the sand transport rate and apparent surface roughness and the delay of evolution process. The distribution of lift-off speed and the evolution of lift-off parameters on Mars are found to be different from those on Earth. This may thus suggest that it is inappropriate to predict the evolution of wind-blown sand by using the lift-off velocity obtained in steady state saltation. And it also may be problematic to predict the wind-blown sand on Mars through applying the lift-off velocity obtained upon terrestrial conditions directly.

Detection of the toughest: Pedestrian injury risk as a smooth function of age.

PubMed

Niebuhr, Tobias; Junge, Mirko

2017-07-04

Though it is common to refer to age-specific groups (e.g., children, adults, elderly), smooth trends conditional on age are mainly ignored in the literature. The present study examines the pedestrian injury risk in full-frontal pedestrian-to-passenger car accidents and incorporates age-in addition to collision speed and injury severity-as a plug-in parameter. Recent work introduced a model for pedestrian injury risk functions using explicit formulae with easily interpretable model parameters. This model is expanded by pedestrian age as another model parameter. Using the German In-Depth Accident Study (GIDAS) to obtain age-specific risk proportions, the model parameters are fitted to the raw data and then smoothed by broken-line regression. The approach supplies explicit probabilities for pedestrian injury risk conditional on pedestrian age, collision speed, and injury severity under investigation. All results yield consistency to each other in the sense that risks for more severe injuries are less probable than those for less severe injuries. As a side product, the approach indicates specific ages at which the risk behavior fundamentally changes. These threshold values can be interpreted as the most robust ages for pedestrians. The obtained age-wise risk functions can be aggregated and adapted to any population. The presented approach is formulated in such general terms that in can be directly used for other data sets or additional parameters; for example, the pedestrian's sex. Thus far, no other study using age as a plug-in parameter can be found.

A general Bayesian framework for calibrating and evaluating stochastic models of annual multi-site hydrological data

NASA Astrophysics Data System (ADS)

Frost, Andrew J.; Thyer, Mark A.; Srikanthan, R.; Kuczera, George

2007-07-01

SummaryMulti-site simulation of hydrological data are required for drought risk assessment of large multi-reservoir water supply systems. In this paper, a general Bayesian framework is presented for the calibration and evaluation of multi-site hydrological data at annual timescales. Models included within this framework are the hidden Markov model (HMM) and the widely used lag-1 autoregressive (AR(1)) model. These models are extended by the inclusion of a Box-Cox transformation and a spatial correlation function in a multi-site setting. Parameter uncertainty is evaluated using Markov chain Monte Carlo techniques. Models are evaluated by their ability to reproduce a range of important extreme statistics and compared using Bayesian model selection techniques which evaluate model probabilities. The case study, using multi-site annual rainfall data situated within catchments which contribute to Sydney's main water supply, provided the following results: Firstly, in terms of model probabilities and diagnostics, the inclusion of the Box-Cox transformation was preferred. Secondly the AR(1) and HMM performed similarly, while some other proposed AR(1)/HMM models with regionally pooled parameters had greater posterior probability than these two models. The practical significance of parameter and model uncertainty was illustrated using a case study involving drought security analysis for urban water supply. It was shown that ignoring parameter uncertainty resulted in a significant overestimate of reservoir yield and an underestimation of system vulnerability to severe drought.

Individual differences in emotion processing: how similar are diffusion model parameters across tasks?

PubMed

Mueller, Christina J; White, Corey N; Kuchinke, Lars

2017-11-27

The goal of this study was to replicate findings of diffusion model parameters capturing emotion effects in a lexical decision task and investigating whether these findings extend to other tasks of implicit emotion processing. Additionally, we were interested in the stability of diffusion model parameters across emotional stimuli and tasks for individual subjects. Responses to words in a lexical decision task were compared with responses to faces in a gender categorization task for stimuli of the emotion categories: happy, neutral and fear. Main effects of emotion as well as stability of emerging response style patterns as evident in diffusion model parameters across these tasks were analyzed. Based on earlier findings, drift rates were assumed to be more similar in response to stimuli of the same emotion category compared to stimuli of a different emotion category. Results showed that emotion effects of the tasks differed with a processing advantage for happy followed by neutral and fear-related words in the lexical decision task and a processing advantage for neutral followed by happy and fearful faces in the gender categorization task. Both emotion effects were captured in estimated drift rate parameters-and in case of the lexical decision task also in the non-decision time parameters. A principal component analysis showed that contrary to our hypothesis drift rates were more similar within a specific task context than within a specific emotion category. Individual response patterns of subjects across tasks were evident in significant correlations regarding diffusion model parameters including response styles, non-decision times and information accumulation.

A mathematical model for the Andean Tiwanaku civilization collapse: climate variations.

PubMed

Flores, J C; Bologna, Mauro; Urzagasti, Deterlino

2011-12-21

We propose a mathematical nonlinear model for the Tiwanaku civilization collapse based on the assumption, supported by archeological data, that a drought caused a lack of the main resource, water. We evaluate the parameter of our model using archaeological data. According to our numerical simulation the population core should have decreased from 45,000 to 2000 inhabitants due to lake surface contraction. Copyright © 2011 Elsevier Ltd. All rights reserved.

Modeling of a ring rosen-type piezoelectric transformer by Hamilton's principle.

PubMed

Nadal, Clément; Pigache, Francois; Erhart, Jiří

2015-04-01

This paper deals with the analytical modeling of a ring Rosen-type piezoelectric transformer. The developed model is based on a Hamiltonian approach, enabling to obtain main parameters and performance evaluation for the first radial vibratory modes. Methodology is detailed, and final results, both the input admittance and the electric potential distribution on the surface of the secondary part, are compared with numerical and experimental ones for discussion and validation.

Multifactorial modelling of high-temperature treatment of timber in the saturated water steam medium

NASA Astrophysics Data System (ADS)

Prosvirnikov, D. B.; Safin, R. G.; Ziatdinova, D. F.; Timerbaev, N. F.; Lashkov, V. A.

2016-04-01

The paper analyses experimental data obtained in studies of high-temperature treatment of softwood and hardwood in an environment of saturated water steam. Data were processed in the Curve Expert software for the purpose of statistical modelling of processes and phenomena occurring during this process. The multifactorial modelling resulted in the empirical dependences, allowing determining the main parameters of this type of hydrothermal treatment with high accuracy.

Microphysically derived expressions for rate-and-state friction and fault stability parameters

NASA Astrophysics Data System (ADS)

Chen, Jianye; Niemeijer, Andre; Spiers, Christopher

2017-04-01

Rate-and-state friction (RSF) laws and associated parameters are extensively applied to fault mechanics, mainly on an empirical basis with a limited understanding of the underlying physical mechanisms. We recently established a general microphysical model [Chen and Spiers, 2016], for describing both steady-state and transient frictional behavior of any granular fault gouge material undergoing deformation by granular flow plus an arbitrary creep mechanism at grain contacts, such as pressure solution. We further showed that the model is able to reproduce typical experimental frictional results, namely "velocity stepping" and "slide-hold-slide" sequences, in satisfactory agreement with the main features and trends observed. Here, we extend our model, which we explored only numerically thus far, to obtain analytical solutions for the classical rate and state friction parameters from a purely microphysical modelling basis. By analytically solving the constitutive equations of the model under various boundary conditions, physically meaningful, theoretical expressions for the RSF parameters, i.e. a, b and Dc, are obtained. We also apply linear stability analysis to a spring-slider system, describing interface friction using our model, to yield analytical expressions of the critical stiffness (Kc) and critical recurrence wavelength (Wc) of the system. The values of a , b and Dc, as well as Kc and Wc, predicted by these expressions agree well with the numerical modeling results and acceptably with values obtained from experiments, on calcite for instance. Inserting the parameters obtained into classical RSF laws (slowness and slip laws) and conducting forward modelling gives simulated friction behavior that is fully consistent with the direct predictions of our numerically implemented model. Numerical tests with friction obeying our model show that the slip stability of fault motion exhibits a transition from stable sliding, via self-sustained oscillations, to stick slips with decreasing elastic stiffness, decreasing loading rate, and increasing normal stress, which is fully consistent with our linear stability analysis and also with previous RSF models that employed constant values of the RSF parameters. Importantly, our analytical expressions for. a, b, Dc, Kc and Wc, are functions of the internal microstructure of the fault (porosity, grain size and shear zone thickness), the material properties of the fault gouge (e.g. creep law parameters like activation energy, stress sensitivity, grain size sensitivity), and the ambient conditions the fault is subjected to (temperature and normal stress). The expressions obtained thus have clear physical meaning allowing a more meaningful extrapolation to natural conditions. On the basis of these physics-based expressions, seismological implications for slip on natural faults (e.g. subduction zone interfaces, faults in carbonate terrains) are discussed. Reference Chen, J., and C. J. Spiers (2016), Rate and state frictional and healing behavior of carbonate fault gouge explained using microphysical model, J. Geophys. Res., 121, doi:10.1002/2016JB013470.

Mathematical Model of Ammonia Handling in the Rat Renal Medulla

PubMed Central

Noiret, Lorette; Baigent, Stephen; Jalan, Rajiv; Thomas, S. Randall

2015-01-01

The kidney is one of the main organs that produces ammonia and release it into the circulation. Under normal conditions, between 30 and 50% of the ammonia produced in the kidney is excreted in the urine, the rest being absorbed into the systemic circulation via the renal vein. In acidosis and in some pathological conditions, the proportion of urinary excretion can increase to 70% of the ammonia produced in the kidney. Mechanisms regulating the balance between urinary excretion and renal vein release are not fully understood. We developed a mathematical model that reflects current thinking about renal ammonia handling in order to investigate the role of each tubular segment and identify some of the components which might control this balance. The model treats the movements of water, sodium chloride, urea, NH3 and NH4+, and non-reabsorbable solute in an idealized renal medulla of the rat at steady state. A parameter study was performed to identify the transport parameters and microenvironmental conditions that most affect the rate of urinary ammonia excretion. Our results suggest that urinary ammonia excretion is mainly determined by those parameters that affect ammonia recycling in the loops of Henle. In particular, our results suggest a critical role for interstitial pH in the outer medulla and for luminal pH along the inner medullary collecting ducts. PMID:26280830

flexsurv: A Platform for Parametric Survival Modeling in R

PubMed Central

Jackson, Christopher H.

2018-01-01

flexsurv is an R package for fully-parametric modeling of survival data. Any parametric time-to-event distribution may be fitted if the user supplies a probability density or hazard function, and ideally also their cumulative versions. Standard survival distributions are built in, including the three and four-parameter generalized gamma and F distributions. Any parameter of any distribution can be modeled as a linear or log-linear function of covariates. The package also includes the spline model of Royston and Parmar (2002), in which both baseline survival and covariate effects can be arbitrarily flexible parametric functions of time. The main model-fitting function, flexsurvreg, uses the familiar syntax of survreg from the standard survival package (Therneau 2016). Censoring or left-truncation are specified in ‘Surv’ objects. The models are fitted by maximizing the full log-likelihood, and estimates and confidence intervals for any function of the model parameters can be printed or plotted. flexsurv also provides functions for fitting and predicting from fully-parametric multi-state models, and connects with the mstate package (de Wreede, Fiocco, and Putter 2011). This article explains the methods and design principles of the package, giving several worked examples of its use. PMID:29593450

Musings on cosmological relaxation and the hierarchy problem

NASA Astrophysics Data System (ADS)

Jaeckel, Joerg; Mehta, Viraf M.; Witkowski, Lukas T.

2016-03-01

Recently Graham, Kaplan and Rajendran proposed cosmological relaxation as a mechanism for generating a hierarchically small Higgs vacuum expectation value. Inspired by this we collect some thoughts on steps towards a solution to the electroweak hierarchy problem and apply them to the original model of cosmological relaxation [Phys. Rev. Lett. 115, 221801 (2015)]. To do so, we study the dynamics of the model and determine the relation between the fundamental input parameters and the electroweak vacuum expectation value. Depending on the input parameters the model exhibits three qualitatively different regimes, two of which allow for hierarchically small Higgs vacuum expectation values. One leads to standard electroweak symmetry breaking whereas in the other regime electroweak symmetry is mainly broken by a Higgs source term. While the latter is not acceptable in a model based on the QCD axion, in non-QCD models this may lead to new and interesting signatures in Higgs observables. Overall, we confirm that cosmological relaxation can successfully give rise to a hierarchically small Higgs vacuum expectation value if (at least) one model parameter is chosen sufficiently small. However, we find that the required level of tuning for achieving this hierarchy in relaxation models can be much more severe than in the Standard Model.

Comparison of three nondestructive and contactless techniques for investigations of recombination parameters on an example of silicon samples

NASA Astrophysics Data System (ADS)

Chrobak, Ł.; Maliński, M.

2018-06-01

This paper presents a comparison of three nondestructive and contactless techniques used for determination of recombination parameters of silicon samples. They are: photoacoustic method, modulated free carriers absorption method and the photothermal radiometry method. In the paper the experimental set-ups used for measurements of the recombination parameters in these methods as also theoretical models used for interpretation of obtained experimental data have been presented and described. The experimental results and their respective fits obtained with these nondestructive techniques are shown and discussed. The values of the recombination parameters obtained with these methods are also presented and compared. Main advantages and disadvantages of presented methods have been discussed.

Integrative neural networks model for prediction of sediment rating curve parameters for ungauged basins

NASA Astrophysics Data System (ADS)

Atieh, M.; Mehltretter, S. L.; Gharabaghi, B.; Rudra, R.

2015-12-01

One of the most uncertain modeling tasks in hydrology is the prediction of ungauged stream sediment load and concentration statistics. This study presents integrated artificial neural networks (ANN) models for prediction of sediment rating curve parameters (rating curve coefficient α and rating curve exponent β) for ungauged basins. The ANN models integrate a comprehensive list of input parameters to improve the accuracy achieved; the input parameters used include: soil, land use, topographic, climatic, and hydrometric data sets. The ANN models were trained on the randomly selected 2/3 of the dataset of 94 gauged streams in Ontario, Canada and validated on the remaining 1/3. The developed models have high correlation coefficients of 0.92 and 0.86 for α and β, respectively. The ANN model for the rating coefficient α is directly proportional to rainfall erosivity factor, soil erodibility factor, and apportionment entropy disorder index, whereas it is inversely proportional to vegetation cover and mean annual snowfall. The ANN model for the rating exponent β is directly proportional to mean annual precipitation, the apportionment entropy disorder index, main channel slope, standard deviation of daily discharge, and inversely proportional to the fraction of basin area covered by wetlands and swamps. Sediment rating curves are essential tools for the calculation of sediment load, concentration-duration curve (CDC), and concentration-duration-frequency (CDF) analysis for more accurate assessment of water quality for ungauged basins.

Towards Characterization, Modeling, and Uncertainty Quantification in Multi-scale Mechanics of Oragnic-rich Shales

NASA Astrophysics Data System (ADS)

Abedi, S.; Mashhadian, M.; Noshadravan, A.

2015-12-01

Increasing the efficiency and sustainability in operation of hydrocarbon recovery from organic-rich shales requires a fundamental understanding of chemomechanical properties of organic-rich shales. This understanding is manifested in form of physics-bases predictive models capable of capturing highly heterogeneous and multi-scale structure of organic-rich shale materials. In this work we present a framework of experimental characterization, micromechanical modeling, and uncertainty quantification that spans from nanoscale to macroscale. Application of experiments such as coupled grid nano-indentation and energy dispersive x-ray spectroscopy and micromechanical modeling attributing the role of organic maturity to the texture of the material, allow us to identify unique clay mechanical properties among different samples that are independent of maturity of shale formations and total organic content. The results can then be used to inform the physically-based multiscale model for organic rich shales consisting of three levels that spans from the scale of elementary building blocks (e.g. clay minerals in clay-dominated formations) of organic rich shales to the scale of the macroscopic inorganic/organic hard/soft inclusion composite. Although this approach is powerful in capturing the effective properties of organic-rich shale in an average sense, it does not account for the uncertainty in compositional and mechanical model parameters. Thus, we take this model one step forward by systematically incorporating the main sources of uncertainty in modeling multiscale behavior of organic-rich shales. In particular we account for the uncertainty in main model parameters at different scales such as porosity, elastic properties and mineralogy mass percent. To that end, we use Maximum Entropy Principle and random matrix theory to construct probabilistic descriptions of model inputs based on available information. The Monte Carlo simulation is then carried out to propagate the uncertainty and consequently construct probabilistic descriptions of properties at multiple length-scales. The combination of experimental characterization and stochastic multi-scale modeling presented in this work improves the robustness in the prediction of essential subsurface parameters in engineering scale.

Analogue modelling of inclined, brittle-ductile transpression: Testing analytical models through natural shear zones (external Betics)

NASA Astrophysics Data System (ADS)

Barcos, L.; Díaz-Azpiroz, M.; Balanyá, J. C.; Expósito, I.; Jiménez-Bonilla, A.; Faccenna, C.

2016-07-01

The combination of analytical and analogue models gives new opportunities to better understand the kinematic parameters controlling the evolution of transpression zones. In this work, we carried out a set of analogue models using the kinematic parameters of transpressional deformation obtained by applying a general triclinic transpression analytical model to a tabular-shaped shear zone in the external Betic Chain (Torcal de Antequera massif). According to the results of the analytical model, we used two oblique convergence angles to reproduce the main structural and kinematic features of structural domains observed within the Torcal de Antequera massif (α = 15° for the outer domains and α = 30° for the inner domain). Two parallel inclined backstops (one fixed and the other mobile) reproduce the geometry of the shear zone walls of the natural case. Additionally, we applied digital particle image velocimetry (PIV) method to calculate the velocity field of the incremental deformation. Our results suggest that the spatial distribution of the main structures observed in the Torcal de Antequera massif reflects different modes of strain partitioning and strain localization between two domain types, which are related to the variation in the oblique convergence angle and the presence of steep planar velocity - and rheological - discontinuities (the shear zone walls in the natural case). In the 15° model, strain partitioning is simple and strain localization is high: a single narrow shear zone is developed close and parallel to the fixed backstop, bounded by strike-slip faults and internally deformed by R and P shears. In the 30° model, strain partitioning is strong, generating regularly spaced oblique-to-the backstops thrusts and strike-slip faults. At final stages of the 30° experiment, deformation affects the entire model box. Our results show that the application of analytical modelling to natural transpressive zones related to upper crustal deformation facilitates to constrain the geometrical parameters of analogue models.

Dynamic energy budget as a basis to model population-level effects of zinc-spiked sediments in the gastropod Valvata piscinalis.

PubMed

Ducrot, Virginie; Péry, Alexandre R R; Mons, Raphaël; Quéau, Hervé; Charles, Sandrine; Garric, Jeanne

2007-08-01

This paper presents original toxicity test designs and mathematical models that may be used to assess the deleterious effects of toxicants on Valvata piscinalis (Mollusca, Gastropoda). Results obtained for zinc, used as a reference toxicant, are presented. The feeding behavior, juvenile survival, growth, age at puberty, onset of reproduction, number of breedings during the life cycle, and fecundity were significantly altered when the snails were exposed to zinc-spiked sediments. Dynamic energy budget models (DEBtox) adequately predicted the effects of zinc on the V. piscinalis life cycle. They also provided estimates for lifecycle parameters that were used to parameterize a demographic model, based on a Z-transformed life-cycle graph. The effect threshold for the population growth rate (lambda) was estimated at 259 mg/kg dry sediment of zinc, showing that significant changes in abundance may occur at environmental concentrations. Significant effects occurring just above this threshold value were mainly caused by the severe impairment of reproductive endpoints. Sensitivity analysis showed that the value of lambda depended mainly on the juvenile survival rate. The impairment of this latter parameter may result in extinction of V. piscinalis. Finally, the present study highlights advantages of the proposed modeling approach in V. piscinalis and possible transfer to other test species and contaminants.

Three-dimensional effects for radio frequency antenna modeling

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

Carter, M.D.; Batchelor, D.B.; Stallings, D.C.

1994-10-15

Electromagnetic field calculations for radio frequency (rf) antennas in two dimensions (2-D) neglect finite antenna length effects as well as the feeders leading to the main current strap. The 2-D calculations predict that the return currents in the sidewalls of the antenna structure depend strongly on the plasma parameters, but this prediction is suspect because of experimental evidence. To study the validity of the 2-D approximation, the Multiple Antenna Implementation System (MAntIS) has been used to perform three-dimensional (3-D) modeling of the power spectrum, plasma loading, and inductance for a relevant loop antenna design. Effects on antenna performance caused bymore » feeders to the main current strap and conducting sidewalls are considered. The modeling shows that the feeders affect the launched power spectrum in an indirect way by forcing the driven rf current to return in the antenna structure rather than the plasma, as in the 2-D model. It has also been found that poloidal dependencies in the plasma impedance matrix can reduce the loading predicted from that predicted in the 2-D model. For some plasma parameters, the combined 3-D effects can lead to a reduction in the predicted loading by as much as a factor of 2 from that given by the 2-D model, even with end-effect corrections for the 2-D model.« less

Three-dimensional effects for radio frequency antenna modeling

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

Carter, M.D.; Batchelor, D.B.; Stallings, D.C.

1993-12-31

Electromagnetic field calculations for radio frequency (rf) antennas in two dimensions (2-D) neglect finite antenna length effects as well as the feeders leading to the main current strap. The 2-D calculations predict that the return currents in the sidewalls of the antenna structure depend strongly on the plasma parameters, but this prediction is suspect because of experimental evidence. To study the validity of the 2-D approximation, the Multiple Antenna Implementation System (MAntIS) has been used to perform three-dimensional (3-D) modeling of the power spectrum, plasma loading, and inductance for a relevant loop antenna design. Effects on antenna performance caused bymore » feeders to the main current strap and conducting sidewalls are considered. The modeling shows that the feeders affect the launched power spectrum in an indirect way by forcing the driven rf current to return in the antenna structure rather than the plasma, as in the 2-D model. It has also been found that poloidal dependencies in the plasma impedance matrix can reduce the loading predicted from that predicted in the 2-D model. For some plasma parameters, the combined 3-D effects can lead to a reduction in the predicted loading by as much as a factor of 2 from that given by the 2-D model, even with end-effect corrections for the 2-D model.« less

Comparison of mathematical models of fibrosis. Comment on "Towards a unified approach in the modeling of fibrosis: A review with research perspectives" by M. Ben Amar and C. Bianca

NASA Astrophysics Data System (ADS)

Kachapova, Farida

2016-07-01

Mathematical and computational models in biology and medicine help to improve diagnostics and medical treatments. Modeling of pathological fibrosis is reviewed by M. Ben Amar and C. Bianca in [4]. Pathological fibrosis is the process when excessive fibrous tissue is deposited on an organ or tissue during a wound healing and can obliterate their normal function. In [4] the phenomena of fibrosis are briefly explained including the causes, mechanism and management; research models of pathological fibrosis are described, compared and critically analyzed. Different models are suitable at different levels: molecular, cellular and tissue. The main goal of mathematical modeling of fibrosis is to predict long term behavior of the system depending on bifurcation parameters; there are two main trends: inhibition of fibrosis due to an active immune system and swelling of fibrosis because of a weak immune system.

On how to avoid input and structural uncertainties corrupt the inference of hydrological parameters using a Bayesian framework

NASA Astrophysics Data System (ADS)

Hernández, Mario R.; Francés, Félix

2015-04-01

One phase of the hydrological models implementation process, significantly contributing to the hydrological predictions uncertainty, is the calibration phase in which values of the unknown model parameters are tuned by optimizing an objective function. An unsuitable error model (e.g. Standard Least Squares or SLS) introduces noise into the estimation of the parameters. The main sources of this noise are the input errors and the hydrological model structural deficiencies. Thus, the biased calibrated parameters cause the divergence model phenomenon, where the errors variance of the (spatially and temporally) forecasted flows far exceeds the errors variance in the fitting period, and provoke the loss of part or all of the physical meaning of the modeled processes. In other words, yielding a calibrated hydrological model which works well, but not for the right reasons. Besides, an unsuitable error model yields a non-reliable predictive uncertainty assessment. Hence, with the aim of prevent all these undesirable effects, this research focuses on the Bayesian joint inference (BJI) of both the hydrological and error model parameters, considering a general additive (GA) error model that allows for correlation, non-stationarity (in variance and bias) and non-normality of model residuals. As hydrological model, it has been used a conceptual distributed model called TETIS, with a particular split structure of the effective model parameters. Bayesian inference has been performed with the aid of a Markov Chain Monte Carlo (MCMC) algorithm called Dream-ZS. MCMC algorithm quantifies the uncertainty of the hydrological and error model parameters by getting the joint posterior probability distribution, conditioned on the observed flows. The BJI methodology is a very powerful and reliable tool, but it must be used correctly this is, if non-stationarity in errors variance and bias is modeled, the Total Laws must be taken into account. The results of this research show that the application of BJI with a GA error model outperforms the hydrological parameters robustness (diminishing the divergence model phenomenon) and improves the reliability of the streamflow predictive distribution, in respect of the results of a bad error model as SLS. Finally, the most likely prediction in a validation period, for both BJI+GA and SLS error models shows a similar performance.

Estimating Phenomenological Parameters in Multi-Assets Markets

NASA Astrophysics Data System (ADS)

Raffaelli, Giacomo; Marsili, Matteo

Financial correlations exhibit a non-trivial dynamic behavior. This is reproduced by a simple phenomenological model of a multi-asset financial market, which takes into account the impact of portfolio investment on price dynamics. This captures the fact that correlations determine the optimal portfolio but are affected by investment based on it. Such a feedback on correlations gives rise to an instability when the volume of investment exceeds a critical value. Close to the critical point the model exhibits dynamical correlations very similar to those observed in real markets. We discuss how the model's parameter can be estimated in real market data with a maximum likelihood principle. This confirms the main conclusion that real markets operate close to a dynamically unstable point.

Numerical algorithms based on Galerkin methods for the modeling of reactive interfaces in photoelectrochemical (PEC) solar cells

NASA Astrophysics Data System (ADS)

Harmon, Michael; Gamba, Irene M.; Ren, Kui

2016-12-01

This work concerns the numerical solution of a coupled system of self-consistent reaction-drift-diffusion-Poisson equations that describes the macroscopic dynamics of charge transport in photoelectrochemical (PEC) solar cells with reactive semiconductor and electrolyte interfaces. We present three numerical algorithms, mainly based on a mixed finite element and a local discontinuous Galerkin method for spatial discretization, with carefully chosen numerical fluxes, and implicit-explicit time stepping techniques, for solving the time-dependent nonlinear systems of partial differential equations. We perform computational simulations under various model parameters to demonstrate the performance of the proposed numerical algorithms as well as the impact of these parameters on the solution to the model.

Parameter variation effects on temperature elevation in a steady-state, one-dimensional thermal model for millimeter wave exposure of one- and three-layer human tissue.

PubMed

Kanezaki, Akio; Hirata, Akimasa; Watanabe, Soichi; Shirai, Hiroshi

2010-08-21

The present study describes theoretical parametric analysis of the steady-state temperature elevation in one-dimensional three-layer (skin, fat and muscle) and one-layer (skin only) models due to millimeter-wave exposure. The motivation of this fundamental investigation is that some variability of warmth sensation in the human skin has been reported. An analytical solution for a bioheat equation was derived by using the Laplace transform for the one-dimensional human models. Approximate expressions were obtained to investigate the dependence of temperature elevation on different thermal and tissue thickness parameters. It was shown that the temperature elevation on the body surface decreases monotonically with the blood perfusion rate, heat conductivity and heat transfer from the body to air. Also revealed were the conditions where maximum and minimum surface temperature elevations were observed for different thermal and tissue thickness parameters. The surface temperature elevation in the three-layer model is 1.3-2.8 times greater than that in the one-layer model. The main reason for this difference is attributed to the adiabatic nature of the fat layer. By considering the variation range of thermal and tissue thickness parameters which causes the maximum and minimum temperature elevations, the dominant parameter influencing the surface temperature elevation was found to be the heat transfer coefficient between the body surface and air.

On the possible correlation between the Gutenberg-Richter parameters of the frequency-magnitude relationship

NASA Astrophysics Data System (ADS)

Perez-Oregon, J.; Muñoz-Diosdado, A.; Rudolf-Navarro, A. H.; Guzmán-Sáenz, A.; Angulo-Brown, F.

2018-05-01

The study of the Gutenberg-Richter (GR) parameters a and b has been very important to describe and characterize the seismicity over the different seismic provinces around the world. As far as we know, the possible correlation between the GR parameters a and b has not received enough attention. Bayrak et al. reported the a and b values for 27 active seismic regions around the boundaries of the main tectonic plates of the world. From these data, we found that there exists a positive correlation between the a and b parameters (R = 0.85, R 2 = 0.72). On the other hand, we made around 150 computer runs of a spring-block model proposed by Olami et al. (Phys Rev Lett 68(8):1244-1247, 1992). This model roughly emulates the interaction between two fault planes and it reaches a self-organized critical state. With these simulations, we also found that the a and b parameters are positively correlated. Motivated by these results, we propose an analytical demonstration that indeed a and b are positively correlated. In addition, we discuss on other possible applications of the spring-block model to actual seismicity and to frictional experiments made with sandpapers.

Imitative modeling automatic system Control of steam pressure in the main steam collector with the influence on the main Servomotor steam turbine

NASA Astrophysics Data System (ADS)

Andriushin, A. V.; Zverkov, V. P.; Kuzishchin, V. F.; Ryzhkov, O. S.; Sabanin, V. R.

2017-11-01

The research and setting results of steam pressure in the main steam collector “Do itself” automatic control system (ACS) with high-speed feedback on steam pressure in the turbine regulating stage are presented. The ACS setup is performed on the simulation model of the controlled object developed for this purpose with load-dependent static and dynamic characteristics and a non-linear control algorithm with pulse control of the turbine main servomotor. A method for tuning nonlinear ACS with a numerical algorithm for multiparametric optimization and a procedure for separate dynamic adjustment of control devices in a two-loop ACS are proposed and implemented. It is shown that the nonlinear ACS adjusted with the proposed method with the regulators constant parameters ensures reliable and high-quality operation without the occurrence of oscillations in the transient processes the operating range of the turbine loads.

Temporal gravity field modeling based on least square collocation with short-arc approach

NASA Astrophysics Data System (ADS)

ran, jiangjun; Zhong, Min; Xu, Houze; Liu, Chengshu; Tangdamrongsub, Natthachet

2014-05-01

After the launch of the Gravity Recovery And Climate Experiment (GRACE) in 2002, several research centers have attempted to produce the finest gravity model based on different approaches. In this study, we present an alternative approach to derive the Earth's gravity field, and two main objectives are discussed. Firstly, we seek the optimal method to estimate the accelerometer parameters, and secondly, we intend to recover the monthly gravity model based on least square collocation method. The method has been paid less attention compared to the least square adjustment method because of the massive computational resource's requirement. The positions of twin satellites are treated as pseudo-observations and unknown parameters at the same time. The variance covariance matrices of the pseudo-observations and the unknown parameters are valuable information to improve the accuracy of the estimated gravity solutions. Our analyses showed that introducing a drift parameter as an additional accelerometer parameter, compared to using only a bias parameter, leads to a significant improvement of our estimated monthly gravity field. The gravity errors outside the continents are significantly reduced based on the selected set of the accelerometer parameters. We introduced the improved gravity model namely the second version of Institute of Geodesy and Geophysics, Chinese Academy of Sciences (IGG-CAS 02). The accuracy of IGG-CAS 02 model is comparable to the gravity solutions computed from the Geoforschungszentrum (GFZ), the Center for Space Research (CSR) and the NASA Jet Propulsion Laboratory (JPL). In term of the equivalent water height, the correlation coefficients over the study regions (the Yangtze River valley, the Sahara desert, and the Amazon) among four gravity models are greater than 0.80.

A Semiautomatic Pipeline for Be Star Light Curves

NASA Astrophysics Data System (ADS)

Rímulo, L. R.; Carciofi, A. C.; Rivinius, T.; Okazaki, A.

2016-11-01

Observational and theoretical studies from the last decade have shown that the Viscous Decretion Disk (VDD) scenario, in which turbulent viscosity is the physical mechanism responsible for the transport of material and angular momentum ejected from the star to the outer regions of the disk, is the only viable model for explaining the circumstellar disks of Be stars. In the α-disk approach applied to the VDD, the dimensionless parameter α is a measure of the turbulent viscosity. Recently, combining the time-dependent evolution of a VDD α-disk with non-LTE radiative transfer calculations, the first measurement of the α parameter was made, for the disk dissipation of the Be star ω CMa. It was found that α≍ 1 for that Be disk. The main motivation of this present work is the statistical determination of the α parameter. For this purpose, we present a pipeline that will allow the semiautomatic determination of the α parameter of several dozens of light curves of Be stars available from photometric surveys, In this contribution, we describe the pipeline, outlining the main staps required for the semiautomatic analysis of light curves

Modelling biological invasions: species traits, species interactions, and habitat heterogeneity.

PubMed

Cannas, Sergio A; Marco, Diana E; Páez, Sergio A

2003-05-01

In this paper we explore the integration of different factors to understand, predict and control ecological invasions, through a general cellular automaton model especially developed. The model includes life history traits of several species in a modular structure interacting multiple cellular automata. We performed simulations using field values corresponding to the exotic Gleditsia triacanthos and native co-dominant trees in a montane area. Presence of G. triacanthos juvenile bank was a determinant condition for invasion success. Main parameters influencing invasion velocity were mean seed dispersal distance and minimum reproductive age. Seed production had a small influence on the invasion velocity. Velocities predicted by the model agreed well with estimations from field data. Values of population density predicted matched field values closely. The modular structure of the model, the explicit interaction between the invader and the native species, and the simplicity of parameters and transition rules are novel features of the model.

The Effect of Improved Sub-Daily Earth Rotation Models on Global GPS Data Processing

NASA Astrophysics Data System (ADS)

Yoon, S.; Choi, K. K.

2017-12-01

Throughout the various International GNSS Service (IGS) products, strong periodic signals have been observed around the 14 day period. This signal is clearly visible in all IGS time-series such as those related to orbit ephemerides, Earth rotation parameters (ERP) and ground station coordinates. Recent studies show that errors in the sub-daily Earth rotation models are the main factors that induce such noise. Current IGS orbit processing standards adopted the IERS 2010 convention and its sub-daily Earth rotation model. Since the IERS convention had published, recent advances in the VLBI analysis have made contributions to update the sub-daily Earth rotation models. We have compared several proposed sub-daily Earth rotation models and show the effect of using those models on orbit ephemeris, Earth rotation parameters and ground station coordinates generated by the NGS global GPS data processing strategy.

The log-periodic-AR(1)-GARCH(1,1) model for financial crashes

NASA Astrophysics Data System (ADS)

Gazola, L.; Fernandes, C.; Pizzinga, A.; Riera, R.

2008-02-01

This paper intends to meet recent claims for the attainment of more rigorous statistical methodology within the econophysics literature. To this end, we consider an econometric approach to investigate the outcomes of the log-periodic model of price movements, which has been largely used to forecast financial crashes. In order to accomplish reliable statistical inference for unknown parameters, we incorporate an autoregressive dynamic and a conditional heteroskedasticity structure in the error term of the original model, yielding the log-periodic-AR(1)-GARCH(1,1) model. Both the original and the extended models are fitted to financial indices of U. S. market, namely S&P500 and NASDAQ. Our analysis reveal two main points: (i) the log-periodic-AR(1)-GARCH(1,1) model has residuals with better statistical properties and (ii) the estimation of the parameter concerning the time of the financial crash has been improved.

Nonisothermal Carbothermal Reduction Kinetics of Titanium-Bearing Blast Furnace Slag

NASA Astrophysics Data System (ADS)

Hu, Mengjun; Wei, Ruirui; Hu, Meilong; Wen, Liangying; Ying, Fangqing

2018-05-01

The kinetics of carbothermal reduction of titanium-bearing blast furnace (BF) slag has been studied by thermogravimetric analysis and quadrupole mass spectrometry. The kinetic parameters (activation energy, preexponential factor, and reaction model function) were determined using the Flynn-Wall-Ozawa and Šatava-Šesták methods. The results indicated that reduction of titanium-bearing BF slag can be divided into two stages, namely reduction of phases containing iron and gasification of carbon (< 1095°C), followed by reduction of phases containing titanium (> 1095°C). CO2 was the main off-gas in the temperature range of 530-700°C, whereas CO became the main off-gas when the temperature was greater than 900°C. The activation energy calculated using the Flynn-Wall-Ozawa method was 221.2 kJ/mol. D4 is the mechanism function for carbothermal reduction of titanium-bearing BF slag. Meanwhile, a nonisothermal reduction model is proposed based on the obtained kinetic parameters.

Analysis of Artificial Neural Network in Erosion Modeling: A Case Study of Serang Watershed

NASA Astrophysics Data System (ADS)

Arif, N.; Danoedoro, P.; Hartono

2017-12-01

Erosion modeling is an important measuring tool for both land users and decision makers to evaluate land cultivation and thus it is necessary to have a model to represent the actual reality. Erosion models are a complex model because of uncertainty data with different sources and processing procedures. Artificial neural networks can be relied on for complex and non-linear data processing such as erosion data. The main difficulty in artificial neural network training is the determination of the value of each network input parameters, i.e. hidden layer, momentum, learning rate, momentum, and RMS. This study tested the capability of artificial neural network application in the prediction of erosion risk with some input parameters through multiple simulations to get good classification results. The model was implemented in Serang Watershed, Kulonprogo, Yogyakarta which is one of the critical potential watersheds in Indonesia. The simulation results showed the number of iterations that gave a significant effect on the accuracy compared to other parameters. A small number of iterations can produce good accuracy if the combination of other parameters was right. In this case, one hidden layer was sufficient to produce good accuracy. The highest training accuracy achieved in this study was 99.32%, occurred in ANN 14 simulation with combination of network input parameters of 1 HL; LR 0.01; M 0.5; RMS 0.0001, and the number of iterations of 15000. The ANN training accuracy was not influenced by the number of channels, namely input dataset (erosion factors) as well as data dimensions, rather it was determined by changes in network parameters.

Development of Standard Fuel Models in Boreal Forests of Northeast China through Calibration and Validation

PubMed Central

Cai, Longyan; He, Hong S.; Wu, Zhiwei; Lewis, Benard L.; Liang, Yu

2014-01-01

Understanding the fire prediction capabilities of fuel models is vital to forest fire management. Various fuel models have been developed in the Great Xing'an Mountains in Northeast China. However, the performances of these fuel models have not been tested for historical occurrences of wildfires. Consequently, the applicability of these models requires further investigation. Thus, this paper aims to develop standard fuel models. Seven vegetation types were combined into three fuel models according to potential fire behaviors which were clustered using Euclidean distance algorithms. Fuel model parameter sensitivity was analyzed by the Morris screening method. Results showed that the fuel model parameters 1-hour time-lag loading, dead heat content, live heat content, 1-hour time-lag SAV(Surface Area-to-Volume), live shrub SAV, and fuel bed depth have high sensitivity. Two main sensitive fuel parameters: 1-hour time-lag loading and fuel bed depth, were determined as adjustment parameters because of their high spatio-temporal variability. The FARSITE model was then used to test the fire prediction capabilities of the combined fuel models (uncalibrated fuel models). FARSITE was shown to yield an unrealistic prediction of the historical fire. However, the calibrated fuel models significantly improved the capabilities of the fuel models to predict the actual fire with an accuracy of 89%. Validation results also showed that the model can estimate the actual fires with an accuracy exceeding 56% by using the calibrated fuel models. Therefore, these fuel models can be efficiently used to calculate fire behaviors, which can be helpful in forest fire management. PMID:24714164

Skipped Stage Modeling and Testing of the CPAS Main Parachutes

NASA Technical Reports Server (NTRS)

Varela, Jose G.; Ray, Eric S.

2013-01-01

The Capsule Parachute Assembly System (CPAS) has undergone the transition from modeling a skipped stage event using a simulation that treats a cluster of parachutes as a single composite canopy to the capability of simulating each parachute individually. This capability along with data obtained from skipped stage flight tests has been crucial in modeling the behavior of a skipping canopy as well as the crowding effect on non-skipping ("lagging") neighbors. For the finite mass inflation of CPAS Main parachutes, the cluster is assumed to inflate nominally through the nominal fill time, at which point the skipping parachute continues inflating. This sub-phase modeling method was used to reconstruct three flight tests involving skipped stages. Best fit inflation parameters were determined for both the skipping and lagging canopies.

Thermal cut-off response modelling of universal motors

NASA Astrophysics Data System (ADS)

Thangaveloo, Kashveen; Chin, Yung Shin

2017-04-01

This paper presents a model to predict the thermal cut-off (TCO) response behaviour in universal motors. The mathematical model includes the calculations of heat loss in the universal motor and the flow characteristics around the TCO component which together are the main parameters for TCO response prediction. In order to accurately predict the TCO component temperature, factors like the TCO component resistance, the effect of ambient, and the flow conditions through the motor are taken into account to improve the prediction accuracy of the model.

Modelling of volatility in monetary transmission mechanism

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

Dobešová, Anna; Klepáč, Václav; Kolman, Pavel

2015-03-10

The aim of this paper is to compare different approaches to modeling of volatility in monetary transmission mechanism. For this purpose we built time-varying parameter VAR (TVP-VAR) model with stochastic volatility and VAR-DCC-GARCH model with conditional variance. The data from three European countries are included in the analysis: the Czech Republic, Germany and Slovakia. Results show that VAR-DCC-GARCH system captures higher volatility of observed variables but main trends and detected breaks are generally identical in both approaches.

Validation of the alternating conditional estimation algorithm for estimation of flexible extensions of Cox's proportional hazards model with nonlinear constraints on the parameters.

PubMed

Wynant, Willy; Abrahamowicz, Michal

2016-11-01

Standard optimization algorithms for maximizing likelihood may not be applicable to the estimation of those flexible multivariable models that are nonlinear in their parameters. For applications where the model's structure permits separating estimation of mutually exclusive subsets of parameters into distinct steps, we propose the alternating conditional estimation (ACE) algorithm. We validate the algorithm, in simulations, for estimation of two flexible extensions of Cox's proportional hazards model where the standard maximum partial likelihood estimation does not apply, with simultaneous modeling of (1) nonlinear and time-dependent effects of continuous covariates on the hazard, and (2) nonlinear interaction and main effects of the same variable. We also apply the algorithm in real-life analyses to estimate nonlinear and time-dependent effects of prognostic factors for mortality in colon cancer. Analyses of both simulated and real-life data illustrate good statistical properties of the ACE algorithm and its ability to yield new potentially useful insights about the data structure. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Mathematical Modeling of Dual Layer Shell Type Recuperation System for Biogas Dehumidification

NASA Astrophysics Data System (ADS)

Gendelis, S.; Timuhins, A.; Laizans, A.; Bandeniece, L.

2015-12-01

The main aim of the current paper is to create a mathematical model for dual layer shell type recuperation system, which allows reducing the heat losses from the biomass digester and water amount in the biogas without any additional mechanical or chemical components. The idea of this system is to reduce the temperature of the outflowing gas by creating two-layered counter-flow heat exchanger around the walls of biogas digester, thus increasing a thermal resistance and the gas temperature, resulting in a condensation on a colder surface. Complex mathematical model, including surface condensation, is developed for this type of biogas dehumidifier and the parameter study is carried out for a wide range of parameters. The model is reduced to 1D case to make numerical calculations faster. It is shown that latent heat of condensation is very important for the total heat balance and the condensation rate is highly dependent on insulation between layers and outside temperature. Modelling results allow finding optimal geometrical parameters for the known gas flow and predicting the condensation rate for different system setups and seasons.

Signal Processing in Periodically Forced Gradient Frequency Neural Networks

PubMed Central

Kim, Ji Chul; Large, Edward W.

2015-01-01

Oscillatory instability at the Hopf bifurcation is a dynamical phenomenon that has been suggested to characterize active non-linear processes observed in the auditory system. Networks of oscillators poised near Hopf bifurcation points and tuned to tonotopically distributed frequencies have been used as models of auditory processing at various levels, but systematic investigation of the dynamical properties of such oscillatory networks is still lacking. Here we provide a dynamical systems analysis of a canonical model for gradient frequency neural networks driven by a periodic signal. We use linear stability analysis to identify various driven behaviors of canonical oscillators for all possible ranges of model and forcing parameters. The analysis shows that canonical oscillators exhibit qualitatively different sets of driven states and transitions for different regimes of model parameters. We classify the parameter regimes into four main categories based on their distinct signal processing capabilities. This analysis will lead to deeper understanding of the diverse behaviors of neural systems under periodic forcing and can inform the design of oscillatory network models of auditory signal processing. PMID:26733858

Combined Yamamoto approach for simultaneous estimation of adsorption isotherm and kinetic parameters in ion-exchange chromatography.

PubMed

Rüdt, Matthias; Gillet, Florian; Heege, Stefanie; Hitzler, Julian; Kalbfuss, Bernd; Guélat, Bertrand

2015-09-25

Application of model-based design is appealing to support the development of protein chromatography in the biopharmaceutical industry. However, the required efforts for parameter estimation are frequently perceived as time-consuming and expensive. In order to speed-up this work, a new parameter estimation approach for modelling ion-exchange chromatography in linear conditions was developed. It aims at reducing the time and protein demand for the model calibration. The method combines the estimation of kinetic and thermodynamic parameters based on the simultaneous variation of the gradient slope and the residence time in a set of five linear gradient elutions. The parameters are estimated from a Yamamoto plot and a gradient-adjusted Van Deemter plot. The combined approach increases the information extracted per experiment compared to the individual methods. As a proof of concept, the combined approach was successfully applied for a monoclonal antibody on a cation-exchanger and for a Fc-fusion protein on an anion-exchange resin. The individual parameter estimations for the mAb confirmed that the new approach maintained the accuracy of the usual Yamamoto and Van Deemter plots. In the second case, offline size-exclusion chromatography was performed in order to estimate the thermodynamic parameters of an impurity (high molecular weight species) simultaneously with the main product. Finally, the parameters obtained from the combined approach were used in a lumped kinetic model to simulate the chromatography runs. The simulated chromatograms obtained for a wide range of gradient lengths and residence times showed only small deviations compared to the experimental data. Copyright © 2015 Elsevier B.V. All rights reserved.

[Parameter optimization of BEPS model based on the flux data of the temperate deciduous broad-leaved forest in Northeast China.

PubMed

Lu, Wei; Fan, Wen Yi; Tian, Tian

2016-05-01

Keeping other parameters as empirical constants, different numerical combinations of the main photosynthetic parameters V c max and J max were conducted to estimate daily GPP by using the iteration method in this paper. To optimize V c max and J max in BEPSHourly model at hourly time steps, simulated daily GPP using different numerical combinations of the parameters were compared with the flux tower data obtained from the temperate deciduous broad-leaved forest of the Maoershan Forest Farm in Northeast China. Comparing the simulated daily GPP with the observed flux data in 2011, the results showed that optimal V c max and J max for the deciduous broad-leaved forest in Northeast China were 41.1 μmol·m -2 ·s -1 and 82.8 μmol·m -2 ·s -1 respectively with the minimal RMSE and the maximum R 2 of 1.10 g C·m -2 ·d -1 and 0.95. After V c max and J max optimization, BEPSHourly model simulated the seasonal variation of GPP better.

Competitions hatch butterfly attractors in foreign exchange markets

NASA Astrophysics Data System (ADS)

Jin, Yu Ying

2005-03-01

Chaos in foreign exchange markets is a common issue of concern in the study of economic dynamics. In this work, we mainly investigate the competition effect on chaos in foreign exchange markets. As one of the main economic structures in the globalization process, competition between two target exchange rates with the same base currency forms a simple competitive exchange rate relation, where each exchange rate follows the chaotic model of De Grauwe (Exchange Rate Theory-Chaotic Models of Foreign Exchange Markets, Blackwell, Oxford, Cambridge, MA, 1993). The main discovery is, while each exchange rate is in its non-chaotic parameter regions, the effect of competition will “hatch” butterfly-like chaotic attractors in the competitive market. The positive Lyapunov exponent in the market explains the reason why chaos occurs.

Linking aquifer spatial properties and non-Fickian transport in mobile-immobile like alluvial settings

USGS Publications Warehouse

Zhang, Yong; Green, Christopher T.; Baeumer, Boris

2014-01-01

Time-nonlocal transport models can describe non-Fickian diffusion observed in geological media, but the physical meaning of parameters can be ambiguous, and most applications are limited to curve-fitting. This study explores methods for predicting the parameters of a temporally tempered Lévy motion (TTLM) model for transient sub-diffusion in mobile–immobile like alluvial settings represented by high-resolution hydrofacies models. The TTLM model is a concise multi-rate mass transfer (MRMT) model that describes a linear mass transfer process where the transfer kinetics and late-time transport behavior are controlled by properties of the host medium, especially the immobile domain. The intrinsic connection between the MRMT and TTLM models helps to estimate the main time-nonlocal parameters in the TTLM model (which are the time scale index, the capacity coefficient, and the truncation parameter) either semi-analytically or empirically from the measurable aquifer properties. Further applications show that the TTLM model captures the observed solute snapshots, the breakthrough curves, and the spatial moments of plumes up to the fourth order. Most importantly, the a priori estimation of the time-nonlocal parameters outside of any breakthrough fitting procedure provides a reliable “blind” prediction of the late-time dynamics of subdiffusion observed in a spectrum of alluvial settings. Predictability of the time-nonlocal parameters may be due to the fact that the late-time subdiffusion is not affected by the exact location of each immobile zone, but rather is controlled by the time spent in immobile blocks surrounding the pathway of solute particles. Results also show that the effective dispersion coefficient has to be fitted due to the scale effect of transport, and the mean velocity can differ from local measurements or volume averages. The link between medium heterogeneity and time-nonlocal parameters will help to improve model predictability for non-Fickian transport in alluvial settings.

Streamflow hindcasting in European river basins via multi-parametric ensemble of the mesoscale hydrologic model (mHM)

NASA Astrophysics Data System (ADS)

Noh, Seong Jin; Rakovec, Oldrich; Kumar, Rohini; Samaniego, Luis

2016-04-01

There have been tremendous improvements in distributed hydrologic modeling (DHM) which made a process-based simulation with a high spatiotemporal resolution applicable on a large spatial scale. Despite of increasing information on heterogeneous property of a catchment, DHM is still subject to uncertainties inherently coming from model structure, parameters and input forcing. Sequential data assimilation (DA) may facilitate improved streamflow prediction via DHM using real-time observations to correct internal model states. In conventional DA methods such as state updating, parametric uncertainty is, however, often ignored mainly due to practical limitations of methodology to specify modeling uncertainty with limited ensemble members. If parametric uncertainty related with routing and runoff components is not incorporated properly, predictive uncertainty by DHM may be insufficient to capture dynamics of observations, which may deteriorate predictability. Recently, a multi-scale parameter regionalization (MPR) method was proposed to make hydrologic predictions at different scales using a same set of model parameters without losing much of the model performance. The MPR method incorporated within the mesoscale hydrologic model (mHM, http://www.ufz.de/mhm) could effectively represent and control uncertainty of high-dimensional parameters in a distributed model using global parameters. In this study, we present a global multi-parametric ensemble approach to incorporate parametric uncertainty of DHM in DA to improve streamflow predictions. To effectively represent and control uncertainty of high-dimensional parameters with limited number of ensemble, MPR method is incorporated with DA. Lagged particle filtering is utilized to consider the response times and non-Gaussian characteristics of internal hydrologic processes. The hindcasting experiments are implemented to evaluate impacts of the proposed DA method on streamflow predictions in multiple European river basins having different climate and catchment characteristics. Because augmentation of parameters is not required within an assimilation window, the approach could be stable with limited ensemble members and viable for practical uses.

Spectroscopic and physical parameters of Galactic O-type stars. III. Mass discrepancy and rotational mixing

NASA Astrophysics Data System (ADS)

Markova, N.; Puls, J.; Langer, N.

2018-05-01

Context. Massive stars play a key role in the evolution of galaxies and our Universe. Aims: Our goal is to compare observed and predicted properties of single Galactic O stars to identify and constrain uncertain physical parameters and processes in stellar evolution and atmosphere models. Methods: We used a sample of 53 objects of all luminosity classes and with spectral types from O3 to O9.7. For 30 of these, we determined the main photospheric and wind parameters, including projected rotational rates accounting for macroturbulence, and He and N surface abundances, using optical spectroscopy and applying the model atmosphere code FASTWIND. For the remaining objects, similar data from the literature, based on analyses by means of the CMFGEN code, were used instead. The properties of our sample were then compared to published predictions based on two grids of single massive star evolution models that include rotationally induced mixing. Results: Any of the considered model grids face problem in simultaneously reproducing the stellar masses, equatorial gravities, surface abundances, and rotation rates of our sample stars. The spectroscopic masses derived for objects below 30 M⊙ tend to be smaller than the evolutionary ones, no matter which of the two grids have been used as a reference. While this result may indicate the need to improve the model atmosphere calculations (e.g. regarding the treatment of turbulent pressure), our analysis shows that the established mass problem cannot be fully explained in terms of inaccurate parameters obtained by quantitative spectroscopy or inadequate model values of Vrot on the zero age main sequence. Within each luminosity class, we find a close correlation of N surface abundance and luminosity, and a stronger N enrichment in more massive and evolved O stars. Additionally, we also find a correlation of the surface nitrogen and helium abundances. The large number of nitrogen-enriched stars above 30 M⊙ argues for rotationally induced mixing as the most likely explanation. However, none of the considered models can match the observed trends correctly, especially in the high mass regime. Conclusions: We confirm mass discrepancy for objects in the low mass O-star regime. We conclude that the rotationally induced mixing of helium to the stellar surface is too strong in some of the models. We also suggest that present inadequacies of the models to represent the N enrichment in more massive stars with relatively slow rotation might be related (among other issues) to problematic efficiencies of rotational mixing. We are left with a picture in which invoking binarity and magnetic fields is required to achieve a more complete agreement of the observed surface properties of a population of massive main-sequence stars with corresponding evolutionary models.

Control Parameters Optimization Based on Co-Simulation of a Mechatronic System for an UA-Based Two-Axis Inertially Stabilized Platform.

PubMed

Zhou, Xiangyang; Zhao, Beilei; Gong, Guohao

2015-08-14

This paper presents a method based on co-simulation of a mechatronic system to optimize the control parameters of a two-axis inertially stabilized platform system (ISP) applied in an unmanned airship (UA), by which high control performance and reliability of the ISP system are achieved. First, a three-dimensional structural model of the ISP is built by using the three-dimensional parametric CAD software SOLIDWORKS(®); then, to analyze the system's kinematic and dynamic characteristics under operating conditions, dynamics modeling is conducted by using the multi-body dynamics software ADAMS™, thus the main dynamic parameters such as displacement, velocity, acceleration and reaction curve are obtained, respectively, through simulation analysis. Then, those dynamic parameters were input into the established MATLAB(®) SIMULINK(®) controller to simulate and test the performance of the control system. By these means, the ISP control parameters are optimized. To verify the methods, experiments were carried out by applying the optimized parameters to the control system of a two-axis ISP. The results show that the co-simulation by using virtual prototyping (VP) is effective to obtain optimized ISP control parameters, eventually leading to high ISP control performance.

Control Parameters Optimization Based on Co-Simulation of a Mechatronic System for an UA-Based Two-Axis Inertially Stabilized Platform

PubMed Central

Zhou, Xiangyang; Zhao, Beilei; Gong, Guohao

2015-01-01

This paper presents a method based on co-simulation of a mechatronic system to optimize the control parameters of a two-axis inertially stabilized platform system (ISP) applied in an unmanned airship (UA), by which high control performance and reliability of the ISP system are achieved. First, a three-dimensional structural model of the ISP is built by using the three-dimensional parametric CAD software SOLIDWORKS®; then, to analyze the system’s kinematic and dynamic characteristics under operating conditions, dynamics modeling is conducted by using the multi-body dynamics software ADAMS™, thus the main dynamic parameters such as displacement, velocity, acceleration and reaction curve are obtained, respectively, through simulation analysis. Then, those dynamic parameters were input into the established MATLAB® SIMULINK® controller to simulate and test the performance of the control system. By these means, the ISP control parameters are optimized. To verify the methods, experiments were carried out by applying the optimized parameters to the control system of a two-axis ISP. The results show that the co-simulation by using virtual prototyping (VP) is effective to obtain optimized ISP control parameters, eventually leading to high ISP control performance. PMID:26287210

Model parameter-related optimal perturbations and their contributions to El Niño prediction errors

NASA Astrophysics Data System (ADS)

Tao, Ling-Jiang; Gao, Chuan; Zhang, Rong-Hua

2018-04-01

Errors in initial conditions and model parameters (MPs) are the main sources that limit the accuracy of ENSO predictions. In addition to exploring the initial error-induced prediction errors, model errors are equally important in determining prediction performance. In this paper, the MP-related optimal errors that can cause prominent error growth in ENSO predictions are investigated using an intermediate coupled model (ICM) and a conditional nonlinear optimal perturbation (CNOP) approach. Two MPs related to the Bjerknes feedback are considered in the CNOP analysis: one involves the SST-surface wind coupling ({α _τ } ), and the other involves the thermocline effect on the SST ({α _{Te}} ). The MP-related optimal perturbations (denoted as CNOP-P) are found uniformly positive and restrained in a small region: the {α _τ } component is mainly concentrated in the central equatorial Pacific, and the {α _{Te}} component is mainly located in the eastern cold tongue region. This kind of CNOP-P enhances the strength of the Bjerknes feedback and induces an El Niño- or La Niña-like error evolution, resulting in an El Niño-like systematic bias in this model. The CNOP-P is also found to play a role in the spring predictability barrier (SPB) for ENSO predictions. Evidently, such error growth is primarily attributed to MP errors in small areas based on the localized distribution of CNOP-P. Further sensitivity experiments firmly indicate that ENSO simulations are sensitive to the representation of SST-surface wind coupling in the central Pacific and to the thermocline effect in the eastern Pacific in the ICM. These results provide guidance and theoretical support for the future improvement in numerical models to reduce the systematic bias and SPB phenomenon in ENSO predictions.

Modeling and FE Simulation of Quenchable High Strength Steels Sheet Metal Hot Forming Process

NASA Astrophysics Data System (ADS)

Liu, Hongsheng; Bao, Jun; Xing, Zhongwen; Zhang, Dejin; Song, Baoyu; Lei, Chengxi

2011-08-01

High strength steel (HSS) sheet metal hot forming process is investigated by means of numerical simulations. With regard to a reliable numerical process design, the knowledge of the thermal and thermo-mechanical properties is essential. In this article, tensile tests are performed to examine the flow stress of the material HSS 22MnB5 at different strains, strain rates, and temperatures. Constitutive model based on phenomenological approach is developed to describe the thermo-mechanical properties of the material 22MnB5 by fitting the experimental data. A 2D coupled thermo-mechanical finite element (FE) model is developed to simulate the HSS sheet metal hot forming process for U-channel part. The ABAQUS/explicit model is used conduct the hot forming stage simulations, and ABAQUS/implicit model is used for accurately predicting the springback which happens at the end of hot forming stage. Material modeling and FE numerical simulations are carried out to investigate the effect of the processing parameters on the hot forming process. The processing parameters have significant influence on the microstructure of U-channel part. The springback after hot forming stage is the main factor impairing the shape precision of hot-formed part. The mechanism of springback is advanced and verified through numerical simulations and tensile loading-unloading tests. Creep strain is found in the tensile loading-unloading test under isothermal condition and has a distinct effect on springback. According to the numerical and experimental results, it can be concluded that springback is mainly caused by different cooling rats and the nonhomogengeous shrink of material during hot forming process, the creep strain is the main factor influencing the amount of the springback.

Evaluation of trade influence on economic growth rate by computational intelligence approach

NASA Astrophysics Data System (ADS)

Sokolov-Mladenović, Svetlana; Milovančević, Milos; Mladenović, Igor

2017-01-01

In this study was analyzed the influence of trade parameters on the economic growth forecasting accuracy. Computational intelligence method was used for the analyzing since the method can handle highly nonlinear data. It is known that the economic growth could be modeled based on the different trade parameters. In this study five input parameters were considered. These input parameters were: trade in services, exports of goods and services, imports of goods and services, trade and merchandise trade. All these parameters were calculated as added percentages in gross domestic product (GDP). The main goal was to select which parameters are the most impactful on the economic growth percentage. GDP was used as economic growth indicator. Results show that the imports of goods and services has the highest influence on the economic growth forecasting accuracy.

A hybrid learning method for constructing compact rule-based fuzzy models.

PubMed

Zhao, Wanqing; Niu, Qun; Li, Kang; Irwin, George W

2013-12-01

The Takagi–Sugeno–Kang-type rule-based fuzzy model has found many applications in different fields; a major challenge is, however, to build a compact model with optimized model parameters which leads to satisfactory model performance. To produce a compact model, most existing approaches mainly focus on selecting an appropriate number of fuzzy rules. In contrast, this paper considers not only the selection of fuzzy rules but also the structure of each rule premise and consequent, leading to the development of a novel compact rule-based fuzzy model. Here, each fuzzy rule is associated with two sets of input attributes, in which the first is used for constructing the rule premise and the other is employed in the rule consequent. A new hybrid learning method combining the modified harmony search method with a fast recursive algorithm is hereby proposed to determine the structure and the parameters for the rule premises and consequents. This is a hard mixed-integer nonlinear optimization problem, and the proposed hybrid method solves the problem by employing an embedded framework, leading to a significantly reduced number of model parameters and a small number of fuzzy rules with each being as simple as possible. Results from three examples are presented to demonstrate the compactness (in terms of the number of model parameters and the number of rules) and the performance of the fuzzy models obtained by the proposed hybrid learning method, in comparison with other techniques from the literature.

Impact of the irregular microgeometry of polyurethane foam on the macroscopic acoustic behavior predicted by a unit-cell model.

PubMed

Doutres, O; Ouisse, M; Atalla, N; Ichchou, M

2014-10-01

This paper deals with the prediction of the macroscopic sound absorption behavior of highly porous polyurethane foams using two unit-cell microstructure-based models recently developed by Doutres, Atalla, and Dong [J. Appl. Phys. 110, 064901 (2011); J. Appl. Phys. 113, 054901 (2013)]. In these models, the porous material is idealized as a packing of a tetrakaidecahedra unit-cell representative of the disordered network that constitutes the porous frame. The non-acoustic parameters involved in the classical Johnson-Champoux-Allard model (i.e., porosity, airflow resistivity, tortuosity, etc.) are derived from characteristic properties of the unit-cell and semi-empirical relationships. A global sensitivity analysis is performed on these two models in order to investigate how the variability associated with the measured unit-cell characteristics affects the models outputs. This allows identification of the possible limitations of a unit-cell micro-macro approach due to microstructure irregularity. The sensitivity analysis mainly shows that for moderately and highly reticulated polyurethane foams, the strut length parameter is the key parameter since it greatly impacts three important non-acoustic parameters and causes large uncertainty on the sound absorption coefficient even if its measurement variability is moderate. For foams with a slight inhomogeneity and anisotropy, a micro-macro model associated to cell size measurements should be preferred.

Kinetic modeling of the photocatalytic degradation of clofibric acid in a slurry reactor.

PubMed

Manassero, Agustina; Satuf, María Lucila; Alfano, Orlando Mario

2015-01-01

A kinetic study of the photocatalytic degradation of the pharmaceutical clofibric acid is presented. Experiments were carried out under UV radiation employing titanium dioxide in water suspension. The main reaction intermediates were identified and quantified. Intrinsic expressions to represent the kinetics of clofibric acid and the main intermediates were derived. The modeling of the radiation field in the reactor was carried out by Monte Carlo simulation. Experimental runs were performed by varying the catalyst concentration and the incident radiation. Kinetic parameters were estimated from the experiments by applying a non-linear regression procedure. Good agreement was obtained between model predictions and experimental data, with an error of 5.9 % in the estimations of the primary pollutant concentration.

ConvAn: a convergence analyzing tool for optimization of biochemical networks.

PubMed

Kostromins, Andrejs; Mozga, Ivars; Stalidzans, Egils

2012-01-01

Dynamic models of biochemical networks usually are described as a system of nonlinear differential equations. In case of optimization of models for purpose of parameter estimation or design of new properties mainly numerical methods are used. That causes problems of optimization predictability as most of numerical optimization methods have stochastic properties and the convergence of the objective function to the global optimum is hardly predictable. Determination of suitable optimization method and necessary duration of optimization becomes critical in case of evaluation of high number of combinations of adjustable parameters or in case of large dynamic models. This task is complex due to variety of optimization methods, software tools and nonlinearity features of models in different parameter spaces. A software tool ConvAn is developed to analyze statistical properties of convergence dynamics for optimization runs with particular optimization method, model, software tool, set of optimization method parameters and number of adjustable parameters of the model. The convergence curves can be normalized automatically to enable comparison of different methods and models in the same scale. By the help of the biochemistry adapted graphical user interface of ConvAn it is possible to compare different optimization methods in terms of ability to find the global optima or values close to that as well as the necessary computational time to reach them. It is possible to estimate the optimization performance for different number of adjustable parameters. The functionality of ConvAn enables statistical assessment of necessary optimization time depending on the necessary optimization accuracy. Optimization methods, which are not suitable for a particular optimization task, can be rejected if they have poor repeatability or convergence properties. The software ConvAn is freely available on www.biosystems.lv/convan. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Experimental study of main rotor/tail rotor/airframe interactions in hover. Volume 1: Text and figures

NASA Technical Reports Server (NTRS)

Balch, D. T.; Saccullo, A.; Sheehy, T. W.

1983-01-01

To assist in identifying and quantifying the relevant parameters associated with the complex topic of main rotor/fuselage/tail rotor interference, a model scale hover test was conducted in the Model Rotor Hover Facility. The test was conducted using the basic model test rig, fuselage skins to represent a UH-60A BLACK HAWK helicopter, 4 sets of rotor blades of varying geometry (i.e., twist, airfoils and solidity) and a model tail rotor that could be relocated to give changes in rotor clearance (axially, laterally, and vertically), can't angle and operating model (pusher or tractor). The description of the models and the tests, data analysis and summary (including plots) are included. The customary system of units gas used for principal measurements and calculations. Expressions in both SI units and customary units are used with the SI units stated first and the customary units afterwords, in parenthesis.

Reconstruction of refocusing and all-in-focus images based on forward simulation model of plenoptic camera

NASA Astrophysics Data System (ADS)

Zhang, Rumin; Liu, Peng; Liu, Dijun; Su, Guobin

2015-12-01

In this paper, we establish a forward simulation model of plenoptic camera which is implemented by inserting a micro-lens array in a conventional camera. The simulation model is used to emulate how the space objects at different depths are imaged by the main lens then remapped by the micro-lens and finally captured on the 2D sensor. We can easily modify the parameters of the simulation model such as the focal lengths and diameters of the main lens and micro-lens and the number of micro-lens. Employing the spatial integration, the refocused images and all-in-focus images are rendered based on the plenoptic images produced by the model. The forward simulation model can be used to determine the trade-offs between different configurations and to test any new researches related to plenoptic camera without the need of prototype.

Mechanical relaxation in a Zr-based bulk metallic glass: Analysis based on physical models

NASA Astrophysics Data System (ADS)

Qiao, J. C.; Pelletier, J. M.

2012-08-01

The mechanical relaxation behavior in a Zr55Cu30Ni5Al10 bulk metallic glass is investigated by dynamic mechanical analysis in both temperature and frequency domains. Master curves can be obtained for the storage modulus G' and for the loss modulus G'', confirming the validity of the time-temperature superposition principle. Different models are discussed to describe the main (α) relaxation, e.g., Debye model, Havriliak-Negami (HN) model, Kohlrausch-Williams-Watt (KWW) model, and quasi-point defects (QPDs) model. The main relaxation in bulk metallic glass cannot be described using a single relaxation time. The HN model, the KWW model, and the QPD theory can be used to fit the data of mechanical spectroscopy experiments. However, unlike the HN model and the KWW model, some physical parameters are introduced in QPD model, i.e., atomic mobility and correlation factor, giving, therefore, a new physical approach to understand the mechanical relaxation in bulk metallic glasses.

Seismic Parameters of Mining-Induced Aftershock Sequences for Re-entry Protocol Development

NASA Astrophysics Data System (ADS)

Vallejos, Javier A.; Estay, Rodrigo A.

2018-03-01

A common characteristic of deep mines in hard rock is induced seismicity. This results from stress changes and rock failure around mining excavations. Following large seismic events, there is an increase in the levels of seismicity, which gradually decay with time. Restricting access to areas of a mine for enough time to allow this decay of seismic events is the main approach in re-entry strategies. The statistical properties of aftershock sequences can be studied with three scaling relations: (1) Gutenberg-Richter frequency magnitude, (2) the modified Omori's law (MOL) for the temporal decay, and (3) Båth's law for the magnitude of the largest aftershock. In this paper, these three scaling relations, in addition to the stochastic Reasenberg-Jones model are applied to study the characteristic parameters of 11 large magnitude mining-induced aftershock sequences in four mines in Ontario, Canada. To provide guidelines for re-entry protocol development, the dependence of the scaling relation parameters on the magnitude of the main event are studied. Some relations between the parameters and the magnitude of the main event are found. Using these relationships and the scaling relations, a space-time-magnitude re-entry protocol is developed. These findings provide a first approximation to concise and well-justified guidelines for re-entry protocol development applicable to the range of mining conditions found in Ontario, Canada.

Measurement of myocardial blood flow by cardiovascular magnetic resonance perfusion: comparison of distributed parameter and Fermi models with single and dual bolus.

PubMed

Papanastasiou, Giorgos; Williams, Michelle C; Kershaw, Lucy E; Dweck, Marc R; Alam, Shirjel; Mirsadraee, Saeed; Connell, Martin; Gray, Calum; MacGillivray, Tom; Newby, David E; Semple, Scott Ik

2015-02-17

Mathematical modeling of cardiovascular magnetic resonance perfusion data allows absolute quantification of myocardial blood flow. Saturation of left ventricle signal during standard contrast administration can compromise the input function used when applying these models. This saturation effect is evident during application of standard Fermi models in single bolus perfusion data. Dual bolus injection protocols have been suggested to eliminate saturation but are much less practical in the clinical setting. The distributed parameter model can also be used for absolute quantification but has not been applied in patients with coronary artery disease. We assessed whether distributed parameter modeling might be less dependent on arterial input function saturation than Fermi modeling in healthy volunteers. We validated the accuracy of each model in detecting reduced myocardial blood flow in stenotic vessels versus gold-standard invasive methods. Eight healthy subjects were scanned using a dual bolus cardiac perfusion protocol at 3T. We performed both single and dual bolus analysis of these data using the distributed parameter and Fermi models. For the dual bolus analysis, a scaled pre-bolus arterial input function was used. In single bolus analysis, the arterial input function was extracted from the main bolus. We also performed analysis using both models of single bolus data obtained from five patients with coronary artery disease and findings were compared against independent invasive coronary angiography and fractional flow reserve. Statistical significance was defined as two-sided P value < 0.05. Fermi models overestimated myocardial blood flow in healthy volunteers due to arterial input function saturation in single bolus analysis compared to dual bolus analysis (P < 0.05). No difference was observed in these volunteers when applying distributed parameter-myocardial blood flow between single and dual bolus analysis. In patients, distributed parameter modeling was able to detect reduced myocardial blood flow at stress (<2.5 mL/min/mL of tissue) in all 12 stenotic vessels compared to only 9 for Fermi modeling. Comparison of single bolus versus dual bolus values suggests that distributed parameter modeling is less dependent on arterial input function saturation than Fermi modeling. Distributed parameter modeling showed excellent accuracy in detecting reduced myocardial blood flow in all stenotic vessels.

Uncertainty Quantification and Global Sensitivity Analysis of Subsurface Flow Parameters to Gravimetric Variations During Pumping Tests in Unconfined Aquifers

NASA Astrophysics Data System (ADS)

Maina, Fadji Zaouna; Guadagnini, Alberto

2018-01-01

We study the contribution of typically uncertain subsurface flow parameters to gravity changes that can be recorded during pumping tests in unconfined aquifers. We do so in the framework of a Global Sensitivity Analysis and quantify the effects of uncertainty of such parameters on the first four statistical moments of the probability distribution of gravimetric variations induced by the operation of the well. System parameters are grouped into two main categories, respectively, governing groundwater flow in the unsaturated and saturated portions of the domain. We ground our work on the three-dimensional analytical model proposed by Mishra and Neuman (2011), which fully takes into account the richness of the physical process taking place across the unsaturated and saturated zones and storage effects in a finite radius pumping well. The relative influence of model parameter uncertainties on drawdown, moisture content, and gravity changes are quantified through (a) the Sobol' indices, derived from a classical decomposition of variance and (b) recently developed indices quantifying the relative contribution of each uncertain model parameter to the (ensemble) mean, skewness, and kurtosis of the model output. Our results document (i) the importance of the effects of the parameters governing the unsaturated flow dynamics on the mean and variance of local drawdown and gravity changes; (ii) the marked sensitivity (as expressed in terms of the statistical moments analyzed) of gravity changes to the employed water retention curve model parameter, specific yield, and storage, and (iii) the influential role of hydraulic conductivity of the unsaturated and saturated zones to the skewness and kurtosis of gravimetric variation distributions. The observed temporal dynamics of the strength of the relative contribution of system parameters to gravimetric variations suggest that gravity data have a clear potential to provide useful information for estimating the key hydraulic parameters of the system.

Encapsulation of brewing yeast in alginate/chitosan matrix: lab-scale optimization of lager beer fermentation.

PubMed

Naydenova, Vessela; Badova, Mariyana; Vassilev, Stoyan; Iliev, Vasil; Kaneva, Maria; Kostov, Georgi

2014-03-04

Two mathematical models were developed for studying the effect of main fermentation temperature ( T MF ), immobilized cell mass ( M IC ) and original wort extract (OE) on beer fermentation with alginate-chitosan microcapsules with a liquid core. During the experiments, the investigated parameters were varied in order to find the optimal conditions for beer fermentation with immobilized cells. The basic beer characteristics, i.e. extract, ethanol, biomass concentration, pH and colour, as well as the concentration of aldehydes and vicinal diketones, were measured. The results suggested that the process parameters represented a powerful tool in controlling the fermentation time. Subsequently, the optimized process parameters were used to produce beer in laboratory batch fermentation. The system productivity was also investigated and the data were used for the development of another mathematical model.

Encapsulation of brewing yeast in alginate/chitosan matrix: lab-scale optimization of lager beer fermentation

PubMed Central

Naydenova, Vessela; Badova, Mariyana; Vassilev, Stoyan; Iliev, Vasil; Kaneva, Maria; Kostov, Georgi

2014-01-01

Two mathematical models were developed for studying the effect of main fermentation temperature (T MF), immobilized cell mass (M IC) and original wort extract (OE) on beer fermentation with alginate-chitosan microcapsules with a liquid core. During the experiments, the investigated parameters were varied in order to find the optimal conditions for beer fermentation with immobilized cells. The basic beer characteristics, i.e. extract, ethanol, biomass concentration, pH and colour, as well as the concentration of aldehydes and vicinal diketones, were measured. The results suggested that the process parameters represented a powerful tool in controlling the fermentation time. Subsequently, the optimized process parameters were used to produce beer in laboratory batch fermentation. The system productivity was also investigated and the data were used for the development of another mathematical model. PMID:26019512

A Comprehensive Model of the Near-Earth Magnetic Field. Phase 3

NASA Technical Reports Server (NTRS)

Sabaka, Terence J.; Olsen, Nils; Langel, Robert A.

2000-01-01

The near-Earth magnetic field is due to sources in Earth's core, ionosphere, magnetosphere, lithosphere, and from coupling currents between ionosphere and magnetosphere and between hemispheres. Traditionally, the main field (low degree internal field) and magnetospheric field have been modeled simultaneously, and fields from other sources modeled separately. Such a scheme, however, can introduce spurious features. A new model, designated CMP3 (Comprehensive Model: Phase 3), has been derived from quiet-time Magsat and POGO satellite measurements and observatory hourly and annual means measurements as part of an effort to coestimate fields from all of these sources. This model represents a significant advancement in the treatment of the aforementioned field sources over previous attempts, and includes an accounting for main field influences on the magnetosphere, main field and solar activity influences on the ionosphere, seasonal influences on the coupling currents, a priori characterization of ionospheric and magnetospheric influence on Earth-induced fields, and an explicit parameterization and estimation of the lithospheric field. The result of this effort is a model whose fits to the data are generally superior to previous models and whose parameter states for the various constituent sources are very reasonable.

Modeling phytoplankton community in reservoirs. A comparison between taxonomic and functional groups-based models.

PubMed

Di Maggio, Jimena; Fernández, Carolina; Parodi, Elisa R; Diaz, M Soledad; Estrada, Vanina

2016-01-01

In this paper we address the formulation of two mechanistic water quality models that differ in the way the phytoplankton community is described. We carry out parameter estimation subject to differential-algebraic constraints and validation for each model and comparison between models performance. The first approach aggregates phytoplankton species based on their phylogenetic characteristics (Taxonomic group model) and the second one, on their morpho-functional properties following Reynolds' classification (Functional group model). The latter approach takes into account tolerance and sensitivity to environmental conditions. The constrained parameter estimation problems are formulated within an equation oriented framework, with a maximum likelihood objective function. The study site is Paso de las Piedras Reservoir (Argentina), which supplies water for consumption for 450,000 population. Numerical results show that phytoplankton morpho-functional groups more closely represent each species growth requirements within the group. Each model performance is quantitatively assessed by three diagnostic measures. Parameter estimation results for seasonal dynamics of the phytoplankton community and main biogeochemical variables for a one-year time horizon are presented and compared for both models, showing the functional group model enhanced performance. Finally, we explore increasing nutrient loading scenarios and predict their effect on phytoplankton dynamics throughout a one-year time horizon. Copyright © 2015 Elsevier Ltd. All rights reserved.

Equifinality and process-based modelling

NASA Astrophysics Data System (ADS)

Khatami, S.; Peel, M. C.; Peterson, T. J.; Western, A. W.

2017-12-01

Equifinality is understood as one of the fundamental difficulties in the study of open complex systems, including catchment hydrology. A review of the hydrologic literature reveals that the term equifinality has been widely used, but in many cases inconsistently and without coherent recognition of the various facets of equifinality, which can lead to ambiguity but also methodological fallacies. Therefore, in this study we first characterise the term equifinality within the context of hydrological modelling by reviewing the genesis of the concept of equifinality and then presenting a theoretical framework. During past decades, equifinality has mainly been studied as a subset of aleatory (arising due to randomness) uncertainty and for the assessment of model parameter uncertainty. Although the connection between parameter uncertainty and equifinality is undeniable, we argue there is more to equifinality than just aleatory parameter uncertainty. That is, the importance of equifinality and epistemic uncertainty (arising due to lack of knowledge) and their implications is overlooked in our current practice of model evaluation. Equifinality and epistemic uncertainty in studying, modelling, and evaluating hydrologic processes are treated as if they can be simply discussed in (or often reduced to) probabilistic terms (as for aleatory uncertainty). The deficiencies of this approach to conceptual rainfall-runoff modelling are demonstrated for selected Australian catchments by examination of parameter and internal flux distributions and interactions within SIMHYD. On this basis, we present a new approach that expands equifinality concept beyond model parameters to inform epistemic uncertainty. The new approach potentially facilitates the identification and development of more physically plausible models and model evaluation schemes particularly within the multiple working hypotheses framework, and is generalisable to other fields of environmental modelling as well.

Ultimate dynamics of the Kirschner-Panetta model: Tumor eradication and related problems

NASA Astrophysics Data System (ADS)

Starkov, Konstantin E.; Krishchenko, Alexander P.

2017-10-01

In this paper we consider the ultimate dynamics of the Kirschner-Panetta model which was created for studying the immune response to tumors under special types of immunotherapy. New ultimate upper bounds for compact invariant sets of this model are given, as well as sufficient conditions for the existence of a positively invariant polytope. We establish three types of conditions for the nonexistence of compact invariant sets in the domain of the tumor-cell population. Our main results are two types of conditions for global tumor elimination depending on the ratio between the proliferation rate of the immune cells and their mortality rate. These conditions are described in terms of simple algebraic inequalities imposed on model parameters and treatment parameters. Our theoretical studies of ultimate dynamics are complemented by numerical simulation results.

Modelling of electron beam induced nanowire attraction

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

Bitzer, Lucas A.; Benson, Niels, E-mail: niels.benson@uni-due.de; Schmechel, Roland

2016-04-14

Scanning electron microscope (SEM) induced nanowire (NW) attraction or bundling is a well known effect, which is mainly ascribed to structural or material dependent properties. However, there have also been recent reports of electron beam induced nanowire bending by SEM imaging, which is not fully explained by the current models, especially when considering the electro-dynamic interaction between NWs. In this article, we contribute to the understanding of this phenomenon, by introducing an electro-dynamic model based on capacitor and Lorentz force interaction, where the active NW bending is stimulated by an electromagnetic force between individual wires. The model includes geometrical, electrical,more » and mechanical NW parameters, as well as the influence of the electron beam source parameters and is validated using in-situ observations of electron beam induced GaAs nanowire (NW) bending by SEM imaging.« less

Modeling biosorption of Cr(VI) onto Ulva compressa L. from aqueous solutions.

PubMed

Aid, Asma; Amokrane, Samira; Nibou, Djamel; Mekatel, Elhadj; Trari, Mohamed; Hulea, Vasile

2018-01-01

The marine biomass Ulva compressa L. (ECL) was used as a low-cost biosorbent for the removal of Cr(VI) from contaminated aqueous solutions. The operating variables were optimized: pH ∼ 2, initial concentration of 25 mg/L, solid/liquid ratio of 6 g/L and a temperature of 50 °C, leading to an uptake elimination of 96%. A full factorial experimental design technique enabled us to obtain a mathematical model describing the Cr(VI) biosorption and to study the main effects and interactions among operational parameters. The equilibrium isotherm was analyzed by the Langmuir, Freundlich and Dubinin-Radushkevich (D-R) models; it has been found that the adsorption process follows well the Langmuir model. Kinetic studies showed that the pseudo-second order model describes suitably the experimental data. The thermodynamic parameters indicated an endothermic heat and a spontaneity of the Cr(VI) biosorption onto ECL.

Spatiotemporal and random parameter panel data models of traffic crash fatalities in Vietnam.

PubMed

Truong, Long T; Kieu, Le-Minh; Vu, Tuan A

2016-09-01

This paper investigates factors associated with traffic crash fatalities in 63 provinces of Vietnam during the period from 2012 to 2014. Random effect negative binomial (RENB) and random parameter negative binomial (RPNB) panel data models are adopted to consider spatial heterogeneity across provinces. In addition, a spatiotemporal model with conditional autoregressive priors (ST-CAR) is utilised to account for spatiotemporal autocorrelation in the data. The statistical comparison indicates the ST-CAR model outperforms the RENB and RPNB models. Estimation results provide several significant findings. For example, traffic crash fatalities tend to be higher in provinces with greater numbers of level crossings. Passenger distance travelled and road lengths are also positively associated with fatalities. However, hospital densities are negatively associated with fatalities. The safety impact of the national highway 1A, the main transport corridor of the country, is also highlighted. Copyright © 2016 Elsevier Ltd. All rights reserved.

CATS - A process-based model for turbulent turbidite systems at the reservoir scale

NASA Astrophysics Data System (ADS)

Teles, Vanessa; Chauveau, Benoît; Joseph, Philippe; Weill, Pierre; Maktouf, Fakher

2016-09-01

The Cellular Automata for Turbidite systems (CATS) model is intended to simulate the fine architecture and facies distribution of turbidite reservoirs with a multi-event and process-based approach. The main processes of low-density turbulent turbidity flow are modeled: downslope sediment-laden flow, entrainment of ambient water, erosion and deposition of several distinct lithologies. This numerical model, derived from (Salles, 2006; Salles et al., 2007), proposes a new approach based on the Rouse concentration profile to consider the flow capacity to carry the sediment load in suspension. In CATS, the flow distribution on a given topography is modeled with local rules between neighboring cells (cellular automata) based on potential and kinetic energy balance and diffusion concepts. Input parameters are the initial flow parameters and a 3D topography at depositional time. An overview of CATS capabilities in different contexts is presented and discussed.

Correlation and evaluation of inplane stability characteristics for an advanced bearingless main rotor

NASA Technical Reports Server (NTRS)

Weller, W. H.

1983-01-01

A program of experimental and analytical research was performed to demonstrate the degree of correlation achieved between measured and computed rotor inplane stability characteristics. The experimental data were obtained from hover and wind tunnel tests of a scaled bearingless main rotor model. Both isolated rotor and free-hub conditions were tested. Test parameters included blade built-in cone and sweep angles; rotor inplane structural stiffness and damping; pitch link stiffness and location; and fuselage damping, inertia, and natural frequency. Analytical results for many test conditions were obtained. In addition, the analytical and experimental results were examined to ascertain the effects of the test parameters on rotor ground and air resonance stability. The results from this program are presented herein in tabular and graphical form.

Uncertainty analysis in 3D global models: Aerosol representation in MOZART-4

NASA Astrophysics Data System (ADS)

Gasore, J.; Prinn, R. G.

2012-12-01

The Probabilistic Collocation Method (PCM) has been proven to be an efficient general method of uncertainty analysis in atmospheric models (Tatang et al 1997, Cohen&Prinn 2011). However, its application has been mainly limited to urban- and regional-scale models and chemical source-sink models, because of the drastic increase in computational cost when the dimension of uncertain parameters increases. Moreover, the high-dimensional output of global models has to be reduced to allow a computationally reasonable number of polynomials to be generated. This dimensional reduction has been mainly achieved by grouping the model grids into a few regions based on prior knowledge and expectations; urban versus rural for instance. As the model output is used to estimate the coefficients of the polynomial chaos expansion (PCE), the arbitrariness in the regional aggregation can generate problems in estimating uncertainties. To address these issues in a complex model, we apply the probabilistic collocation method of uncertainty analysis to the aerosol representation in MOZART-4, which is a 3D global chemical transport model (Emmons et al., 2010). Thereafter, we deterministically delineate the model output surface into regions of homogeneous response using the method of Principal Component Analysis. This allows the quantification of the uncertainty associated with the dimensional reduction. Because only a bulk mass is calculated online in Mozart-4, a lognormal number distribution is assumed with a priori fixed scale and location parameters, to calculate the surface area for heterogeneous reactions involving tropospheric oxidants. We have applied the PCM to the six parameters of the lognormal number distributions of Black Carbon, Organic Carbon and Sulfate. We have carried out a Monte-Carlo sampling from the probability density functions of the six uncertain parameters, using the reduced PCE model. The global mean concentration of major tropospheric oxidants did not show a significant variation in response to the variation in input parameters. However, a substantial variation at regional and temporal scale has been found. Tatang M. A., Pan W., Prinn R G., McRae G. J., An efficient method for parametric uncertainty analysis of numerical geophysical models, J. Gephys. Res., 102, 21925-21932, 1997. Cohen, J.B., and R.G. Prinn, Development of a fast, urban chemistry metamodel for inclusion in global models,Atmos. Chem. Phys., 11, 7629-7656, doi:10.5194/acp-11-7629-2011, 2011. Emmons L. K., Walters S., Hess P. G., Lamarque J. -F., P_ster G. G., Fillmore D., Granier C., Guenther A., Kinnison D., Laepple T., Orlando J., Tie X., Tyndall G., Wiedinmyer C., Baughcum S. L., Kloster J. S., Description and evaluation of the Model for Ozone and Related chemical Tracers, version 4 (MOZART-4). Geosci. Model Dev., 3, 4367, 2010.

Modeling Business Processes of the Social Insurance Fund in Information System Runa WFE

NASA Astrophysics Data System (ADS)

Kataev, M. Yu; Bulysheva, L. A.; Xu, Li D.; Loseva, N. V.

2016-08-01

Introduction - Business processes are gradually becoming a tool that allows you at a new level to put employees or to make more efficient document management system. In these directions the main work, and presents the largest possible number of publications. However, business processes are still poorly implemented in public institutions, where it is very difficult to formalize the main existing processes. Us attempts to build a system of business processes for such state agencies as the Russian social insurance Fund (SIF), where virtually all of the processes, when different inputs have the same output: public service. The parameters of the state services (as a rule, time limits) are set by state laws and regulations. The article provides a brief overview of the FSS, the formulation of requirements to business processes, the justification of the choice of software for modeling business processes and create models of work in the system Runa WFE and optimization models one of the main business processes of the FSS. The result of the work of Runa WFE is an optimized model of the business process of FSS.

Impact of state updating and multi-parametric ensemble for streamflow hindcasting in European river basins

NASA Astrophysics Data System (ADS)

Noh, S. J.; Rakovec, O.; Kumar, R.; Samaniego, L. E.

2015-12-01

Accurate and reliable streamflow prediction is essential to mitigate social and economic damage coming from water-related disasters such as flood and drought. Sequential data assimilation (DA) may facilitate improved streamflow prediction using real-time observations to correct internal model states. In conventional DA methods such as state updating, parametric uncertainty is often ignored mainly due to practical limitations of methodology to specify modeling uncertainty with limited ensemble members. However, if parametric uncertainty related with routing and runoff components is not incorporated properly, predictive uncertainty by model ensemble may be insufficient to capture dynamics of observations, which may deteriorate predictability. Recently, a multi-scale parameter regionalization (MPR) method was proposed to make hydrologic predictions at different scales using a same set of model parameters without losing much of the model performance. The MPR method incorporated within the mesoscale hydrologic model (mHM, http://www.ufz.de/mhm) could effectively represent and control uncertainty of high-dimensional parameters in a distributed model using global parameters. In this study, we evaluate impacts of streamflow data assimilation over European river basins. Especially, a multi-parametric ensemble approach is tested to consider the effects of parametric uncertainty in DA. Because augmentation of parameters is not required within an assimilation window, the approach could be more stable with limited ensemble members and have potential for operational uses. To consider the response times and non-Gaussian characteristics of internal hydrologic processes, lagged particle filtering is utilized. The presentation will be focused on gains and limitations of streamflow data assimilation and multi-parametric ensemble method over large-scale basins.

Modeling and parameters identification of 2-keto-L-gulonic acid fed-batch fermentation.

PubMed

Wang, Tao; Sun, Jibin; Yuan, Jingqi

2015-04-01

This article presents a modeling approach for industrial 2-keto-L-gulonic acid (2-KGA) fed-batch fermentation by the mixed culture of Ketogulonicigenium vulgare (K. vulgare) and Bacillus megaterium (B. megaterium). A macrokinetic model of K. vulgare is constructed based on the simplified metabolic pathways. The reaction rates obtained from the macrokinetic model are then coupled into a bioreactor model such that the relationship between substrate feeding rates and the main state variables, e.g., the concentrations of the biomass, substrate and product, is constructed. A differential evolution algorithm using the Lozi map as the random number generator is utilized to perform the model parameters identification, with the industrial data of 2-KGA fed-batch fermentation. Validation results demonstrate that the model simulations of substrate and product concentrations are well in coincidence with the measurements. Furthermore, the model simulations of biomass concentrations reflect principally the growth kinetics of the two microbes in the mixed culture.

Control and performance of the AGS and AGS Booster Main Magnet Power Supplies

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

Reece, R.K.; Casella, R.; Culwick, B.

1993-06-01

Techniques for precision control of the main magnet power supplies for the AGS and AGS Booster synchrotron will be discussed. Both synchrotrons are designed to operate in a Pulse-to-Pulse Modulation (PPM) environment with a Supercycle Generator defining and distributing global timing events for the AGS Facility. Details of modelling, real-time feedback and feedforward systems, generation and distribution of real time field data, operational parameters and an overview of performance for both machines are included.

Control and performance of the AGS and AGS Booster Main Magnet Power Supplies

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

Reece, R.K.; Casella, R.; Culwick, B.

1993-01-01

Techniques for precision control of the main magnet power supplies for the AGS and AGS Booster synchrotron will be discussed. Both synchrotrons are designed to operate in a Pulse-to-Pulse Modulation (PPM) environment with a Supercycle Generator defining and distributing global timing events for the AGS Facility. Details of modelling, real-time feedback and feedforward systems, generation and distribution of real time field data, operational parameters and an overview of performance for both machines are included.

Bayes factors and multimodel inference

USGS Publications Warehouse

Link, W.A.; Barker, R.J.; Thomson, David L.; Cooch, Evan G.; Conroy, Michael J.

2009-01-01

Multimodel inference has two main themes: model selection, and model averaging. Model averaging is a means of making inference conditional on a model set, rather than on a selected model, allowing formal recognition of the uncertainty associated with model choice. The Bayesian paradigm provides a natural framework for model averaging, and provides a context for evaluation of the commonly used AIC weights. We review Bayesian multimodel inference, noting the importance of Bayes factors. Noting the sensitivity of Bayes factors to the choice of priors on parameters, we define and propose nonpreferential priors as offering a reasonable standard for objective multimodel inference.

Variance-based Sensitivity Analysis of Large-scale Hydrological Model to Prepare an Ensemble-based SWOT-like Data Assimilation Experiments

NASA Astrophysics Data System (ADS)

Emery, C. M.; Biancamaria, S.; Boone, A. A.; Ricci, S. M.; Garambois, P. A.; Decharme, B.; Rochoux, M. C.

2015-12-01

Land Surface Models (LSM) coupled with River Routing schemes (RRM), are used in Global Climate Models (GCM) to simulate the continental part of the water cycle. They are key component of GCM as they provide boundary conditions to atmospheric and oceanic models. However, at global scale, errors arise mainly from simplified physics, atmospheric forcing, and input parameters. More particularly, those used in RRM, such as river width, depth and friction coefficients, are difficult to calibrate and are mostly derived from geomorphologic relationships, which may not always be realistic. In situ measurements are then used to calibrate these relationships and validate the model, but global in situ data are very sparse. Additionally, due to the lack of existing global river geomorphology database and accurate forcing, models are run at coarse resolution. This is typically the case of the ISBA-TRIP model used in this study.A complementary alternative to in-situ data are satellite observations. In this regard, the Surface Water and Ocean Topography (SWOT) satellite mission, jointly developed by NASA/CNES/CSA/UKSA and scheduled for launch around 2020, should be very valuable to calibrate RRM parameters. It will provide maps of water surface elevation for rivers wider than 100 meters over continental surfaces in between 78°S and 78°N and also direct observation of river geomorphological parameters such as width ans slope.Yet, before assimilating such kind of data, it is needed to analyze RRM temporal sensitivity to time-constant parameters. This study presents such analysis over large river basins for the TRIP RRM. Model output uncertainty, represented by unconditional variance, is decomposed into ordered contribution from each parameter. Doing a time-dependent analysis allows then to identify to which parameters modeled water level and discharge are the most sensitive along a hydrological year. The results show that local parameters directly impact water levels, while discharge is more affected by parameters from the whole upstream drainage area. Understanding model output variance behavior will have a direct impact on the design and performance of the ensemble-based data assimilation platform, for which uncertainties are also modeled by variances. It will help to select more objectively RRM parameters to correct.

Modelling of Cosmic Molecular Masers: Introduction to a Computation Cookbook

NASA Astrophysics Data System (ADS)

Sobolev, Andrej M.; Gray, Malcolm D.

2012-07-01

Numerical modeling of molecular masers is necessary in order to understand their nature and diagnostic capabilities. Model construction requires elaboration of a basic description which allows computation, that is a definition of the parameter space and basic physical relations. Usually, this requires additional thorough studies that can consist of the following stages/parts: relevant molecular spectroscopy and collisional rate coefficients; conditions in and around the masing region (that part of space where population inversion is realized); geometry and size of the masing region (including the question of whether maser spots are discrete clumps or line-of-sight correlations in a much bigger region) and propagation of maser radiation. Output of the maser computer modeling can have the following forms: exploration of parameter space (where do inversions appear in particular maser transitions and their combinations, which parameter values describe a `typical' source, and so on); modeling of individual sources (line flux ratios, spectra, images and their variability); analysis of the pumping mechanism; predictions (new maser transitions, correlations in variability of different maser transitions, and the like). Described schemes (constituents and hierarchy) of the model input and output are based mainly on the experience of the authors and make no claim to be dogmatic.

Validation of Storm Water Management Model Storm Control Measures Modules

NASA Astrophysics Data System (ADS)

Simon, M. A.; Platz, M. C.

2017-12-01

EPA's Storm Water Management Model (SWMM) is a computational code heavily relied upon by industry for the simulation of wastewater and stormwater infrastructure performance. Many municipalities are relying on SWMM results to design multi-billion-dollar, multi-decade infrastructure upgrades. Since the 1970's, EPA and others have developed five major releases, the most recent ones containing storm control measures modules for green infrastructure. The main objective of this study was to quantify the accuracy with which SWMM v5.1.10 simulates the hydrologic activity of previously monitored low impact developments. Model performance was evaluated with a mathematical comparison of outflow hydrographs and total outflow volumes, using empirical data and a multi-event, multi-objective calibration method. The calibration methodology utilized PEST++ Version 3, a parameter estimation tool, which aided in the selection of unmeasured hydrologic parameters. From the validation study and sensitivity analysis, several model improvements were identified to advance SWMM LID Module performance for permeable pavements, infiltration units and green roofs, and these were performed and reported herein. Overall, it was determined that SWMM can successfully simulate low impact development controls given accurate model confirmation, parameter measurement, and model calibration.

Optimization of process parameters in CNC turning of aluminium alloy using hybrid RSM cum TLBO approach

NASA Astrophysics Data System (ADS)

Rudrapati, R.; Sahoo, P.; Bandyopadhyay, A.

2016-09-01

The main aim of the present work is to analyse the significance of turning parameters on surface roughness in computer numerically controlled (CNC) turning operation while machining of aluminium alloy material. Spindle speed, feed rate and depth of cut have been considered as machining parameters. Experimental runs have been conducted as per Box-Behnken design method. After experimentation, surface roughness is measured by using stylus profile meter. Factor effects have been studied through analysis of variance. Mathematical modelling has been done by response surface methodology, to made relationships between the input parameters and output response. Finally, process optimization has been made by teaching learning based optimization (TLBO) algorithm. Predicted turning condition has been validated through confirmatory experiment.

Objective calibration of numerical weather prediction models

NASA Astrophysics Data System (ADS)

Voudouri, A.; Khain, P.; Carmona, I.; Bellprat, O.; Grazzini, F.; Avgoustoglou, E.; Bettems, J. M.; Kaufmann, P.

2017-07-01

Numerical weather prediction (NWP) and climate models use parameterization schemes for physical processes, which often include free or poorly confined parameters. Model developers normally calibrate the values of these parameters subjectively to improve the agreement of forecasts with available observations, a procedure referred as expert tuning. A practicable objective multi-variate calibration method build on a quadratic meta-model (MM), that has been applied for a regional climate model (RCM) has shown to be at least as good as expert tuning. Based on these results, an approach to implement the methodology to an NWP model is presented in this study. Challenges in transferring the methodology from RCM to NWP are not only restricted to the use of higher resolution and different time scales. The sensitivity of the NWP model quality with respect to the model parameter space has to be clarified, as well as optimize the overall procedure, in terms of required amount of computing resources for the calibration of an NWP model. Three free model parameters affecting mainly turbulence parameterization schemes were originally selected with respect to their influence on the variables associated to daily forecasts such as daily minimum and maximum 2 m temperature as well as 24 h accumulated precipitation. Preliminary results indicate that it is both affordable in terms of computer resources and meaningful in terms of improved forecast quality. In addition, the proposed methodology has the advantage of being a replicable procedure that can be applied when an updated model version is launched and/or customize the same model implementation over different climatological areas.

Multi-objective calibration and uncertainty analysis of hydrologic models; A comparative study between formal and informal methods

NASA Astrophysics Data System (ADS)

Shafii, M.; Tolson, B.; Matott, L. S.

2012-04-01

Hydrologic modeling has benefited from significant developments over the past two decades. This has resulted in building of higher levels of complexity into hydrologic models, which eventually makes the model evaluation process (parameter estimation via calibration and uncertainty analysis) more challenging. In order to avoid unreasonable parameter estimates, many researchers have suggested implementation of multi-criteria calibration schemes. Furthermore, for predictive hydrologic models to be useful, proper consideration of uncertainty is essential. Consequently, recent research has emphasized comprehensive model assessment procedures in which multi-criteria parameter estimation is combined with statistically-based uncertainty analysis routines such as Bayesian inference using Markov Chain Monte Carlo (MCMC) sampling. Such a procedure relies on the use of formal likelihood functions based on statistical assumptions, and moreover, the Bayesian inference structured on MCMC samplers requires a considerably large number of simulations. Due to these issues, especially in complex non-linear hydrological models, a variety of alternative informal approaches have been proposed for uncertainty analysis in the multi-criteria context. This study aims at exploring a number of such informal uncertainty analysis techniques in multi-criteria calibration of hydrological models. The informal methods addressed in this study are (i) Pareto optimality which quantifies the parameter uncertainty using the Pareto solutions, (ii) DDS-AU which uses the weighted sum of objective functions to derive the prediction limits, and (iii) GLUE which describes the total uncertainty through identification of behavioral solutions. The main objective is to compare such methods with MCMC-based Bayesian inference with respect to factors such as computational burden, and predictive capacity, which are evaluated based on multiple comparative measures. The measures for comparison are calculated both for calibration and evaluation periods. The uncertainty analysis methodologies are applied to a simple 5-parameter rainfall-runoff model, called HYMOD.

An improved method for nonlinear parameter estimation: a case study of the Rössler model

NASA Astrophysics Data System (ADS)

He, Wen-Ping; Wang, Liu; Jiang, Yun-Di; Wan, Shi-Quan

2016-08-01

Parameter estimation is an important research topic in nonlinear dynamics. Based on the evolutionary algorithm (EA), Wang et al. (2014) present a new scheme for nonlinear parameter estimation and numerical tests indicate that the estimation precision is satisfactory. However, the convergence rate of the EA is relatively slow when multiple unknown parameters in a multidimensional dynamical system are estimated simultaneously. To solve this problem, an improved method for parameter estimation of nonlinear dynamical equations is provided in the present paper. The main idea of the improved scheme is to use all of the known time series for all of the components in some dynamical equations to estimate the parameters in single component one by one, instead of estimating all of the parameters in all of the components simultaneously. Thus, we can estimate all of the parameters stage by stage. The performance of the improved method was tested using a classic chaotic system—Rössler model. The numerical tests show that the amended parameter estimation scheme can greatly improve the searching efficiency and that there is a significant increase in the convergence rate of the EA, particularly for multiparameter estimation in multidimensional dynamical equations. Moreover, the results indicate that the accuracy of parameter estimation and the CPU time consumed by the presented method have no obvious dependence on the sample size.

Combined effect of external damper and cross-tie on the modal response of hybrid two-cable networks

NASA Astrophysics Data System (ADS)

Ahmad, Javaid; Cheng, Shaohong; Ghrib, Faouzi

2018-03-01

Combining external dampers and cross-ties into a hybrid system to control bridge stay cable vibrations can address deficiencies associated with these two commonly used vibration control solutions while retaining their respective merits. Despite successful implementation of this strategy on a few cable-stayed bridges, behavior of such a structural system is still not fully understood. In the current study, an analytical model of a hybrid system consisting of two parallel taut cables interconnected by a transverse linear flexible cross-tie, with one cable also equipped with a transverse linear viscous damper close to one end support, is developed. The proposed model is validated by an experimental work in the literature and an independent numerical simulation. A parametric study is conducted to comprehend the impact of main design parameters on the performance of a hybrid system in terms of the in-plane frequency, the damping and the degree of mode localization of the system's fundamental mode. In addition, the concept of isoquant curve is applied not only to appreciate the effect of simultaneous variation in main design parameters on the modal behavior of a hybrid system, but also to identify the optimal ranges of these parameters to achieve the required cable vibration control effect.

Rhelogical constraints on ridge formation on Icy Satellites

NASA Astrophysics Data System (ADS)

Rudolph, M. L.; Manga, M.

2010-12-01

The processes responsible for forming ridges on Europa remain poorly understood. We use a continuum damage mechanics approach to model ridge formation. The main objectives of this contribution are to constrain (1) choice of rheological parameters and (2) maximum ridge size and rate of formation. The key rheological parameters to constrain appear in the evolution equation for a damage variable (D): ˙ {D} = B <<σ >>r}(1-D){-k-α D (p)/(μ ) and in the equation relating damage accumulation to volumetric changes, Jρ 0 = δ (1-D). Similar damage evolution laws have been applied to terrestrial glaciers and to the analysis of rock mechanics experiments. However, it is reasonable to expect that, like viscosity, the rheological constants B, α , and δ depend strongly on temperature, composition, and ice grain size. In order to determine whether the damage model is appropriate for Europa’s ridges, we must find values of the unknown damage parameters that reproduce ridge topography. We perform a suite of numerical experiments to identify the region of parameter space conducive to ridge production and show the sensitivity to changes in each unknown parameter.

Aircraft dual-shaft jet engine with indirect action fuel flow controller

NASA Astrophysics Data System (ADS)

Tudosie, Alexandru-Nicolae

2017-06-01

The paper deals with an aircraft single-jet engine's control system, based on a fuel flow controller. Considering the engine as controlled object and its thrust the most important operation effect, from the multitude of engine's parameters only its rotational speed n is measurable and proportional to its thrust, so engine's speed has become the most important controlled parameter. Engine's control system is based on fuel injection Qi dosage, while the output is engine's speed n. Based on embedded system's main parts' mathematical models, the author has described the system by its block diagram with transfer functions; furthermore, some Simulink-Matlab simulations are performed, concerning embedded system quality (its output parameters time behavior) and, meanwhile, some conclusions concerning engine's parameters mutual influences are revealed. Quantitative determinations are based on author's previous research results and contributions, as well as on existing models (taken from technical literature). The method can be extended for any multi-spool engine, single- or twin-jet.

On the theory of multi-pulse vibro-impact mechanisms

NASA Astrophysics Data System (ADS)

Igumnov, L. A.; Metrikin, V. S.; Nikiforova, I. V.; Ipatov, A. A.

2017-11-01

This paper presents a mathematical model of a new multi-striker eccentric shock-vibration mechanism with a crank-sliding bar vibration exciter and an arbitrary number of pistons. Analytical solutions for the parameters of the model are obtained to determine the regions of existence of stable periodic motions. Under the assumption of an absolutely inelastic collision of the piston, we derive equations that single out a bifurcational unattainable boundary in the parameter space, which has a countable number of arbitrarily complex stable periodic motions in its neighbourhood. We present results of numerical simulations, which illustrate the existence of periodic and stochastic motions. The methods proposed in this paper for investigating the dynamical characteristics of the new crank-type conrod mechanisms allow practitioners to indicate regions in the parameter space, which allow tuning these mechanisms into the most efficient periodic mode of operation, and to effectively analyze the main changes in their operational regimes when the system parameters are changed.

Estimation of improved resolution soil moisture in vegetated areas using passive AMSR-E data

NASA Astrophysics Data System (ADS)

Moradizadeh, Mina; Saradjian, Mohammad R.

2018-03-01

Microwave remote sensing provides a unique capability for soil parameter retrievals. Therefore, various soil parameters estimation models have been developed using brightness temperature (BT) measured by passive microwave sensors. Due to the low resolution of satellite microwave radiometer data, the main goal of this study is to develop a downscaling approach to improve the spatial resolution of soil moisture estimates with the use of higher resolution visible/infrared sensor data. Accordingly, after the soil parameters have been obtained using Simultaneous Land Parameters Retrieval Model algorithm, the downscaling method has been applied to the soil moisture estimations that have been validated against in situ soil moisture data. Advance Microwave Scanning Radiometer-EOS BT data in Soil Moisture Experiment 2003 region in the south and north of Oklahoma have been used to this end. Results illustrated that the soil moisture variability is effectively captured at 5 km spatial scales without a significant degradation of the accuracy.

Can arsenic occurrence rate in bedrock aquifers be predicted?

USGS Publications Warehouse

Yang, Qiang; Jung, Hun Bok; Marvinney, Robert G.; Culbertson, Charles W.; Zheng, Yan

2012-01-01

A high percentage (31%) of groundwater samples from bedrock aquifers in the greater Augusta area, Maine was found to contain greater than 10 μg L–1 of arsenic. Elevated arsenic concentrations are associated with bedrock geology, and more frequently observed in samples with high pH, low dissolved oxygen, and low nitrate. These associations were quantitatively compared by statistical analysis. Stepwise logistic regression models using bedrock geology and/or water chemistry parameters are developed and tested with external data sets to explore the feasibility of predicting groundwater arsenic occurrence rates (the percentages of arsenic concentrations higher than 10 μg L–1) in bedrock aquifers. Despite the under-prediction of high arsenic occurrence rates, models including groundwater geochemistry parameters predict arsenic occurrence rates better than those with bedrock geology only. Such simple models with very few parameters can be applied to obtain a preliminary arsenic risk assessment in bedrock aquifers at local to intermediate scales at other localities with similar geology.

Model development for naphthenic acids ozonation process.

PubMed

Al Jibouri, Ali Kamel H; Wu, Jiangning

2015-02-01

Naphthenic acids (NAs) are toxic constituents of oil sands process-affected water (OSPW) which is generated during the extraction of bitumen from oil sands. NAs consist mainly of carboxylic acids which are generally biorefractory. For the treatment of OSPW, ozonation is a very beneficial method. It can significantly reduce the concentration of NAs and it can also convert NAs from biorefractory to biodegradable. In this study, a factorial design (2(4)) was used for the ozonation of OSPW to study the influences of the operating parameters (ozone concentration, oxygen/ozone flow rate, pH, and mixing) on the removal of a model NAs in a semi-batch reactor. It was found that ozone concentration had the most significant effect on the NAs concentration compared to other parameters. An empirical model was developed to correlate the concentration of NAs with ozone concentration, oxygen/ozone flow rate, and pH. In addition, a theoretical analysis was conducted to gain the insight into the relationship between the removal of NAs and the operating parameters.

Can arsenic occurrence rates in bedrock aquifers be predicted?

PubMed Central

Yang, Qiang; Jung, Hun Bok; Marvinney, Robert G.; Culbertson, Charles W.; Zheng, Yan

2012-01-01

A high percentage (31%) of groundwater samples from bedrock aquifers in the greater Augusta area, Maine was found to contain greater than 10 µg L−1 of arsenic. Elevated arsenic concentrations are associated with bedrock geology, and more frequently observed in samples with high pH, low dissolved oxygen, and low nitrate. These associations were quantitatively compared by statistical analysis. Stepwise logistic regression models using bedrock geology and/or water chemistry parameters are developed and tested with external data sets to explore the feasibility of predicting groundwater arsenic occurrence rates (the percentages of arsenic concentrations higher than 10 µg L−1) in bedrock aquifers. Despite the under-prediction of high arsenic occurrence rates, models including groundwater geochemistry parameters predict arsenic occurrence rates better than those with bedrock geology only. Such simple models with very few parameters can be applied to obtain a preliminary arsenic risk assessment in bedrock aquifers at local to intermediate scales at other localities with similar geology. PMID:22260208

Half-blind remote sensing image restoration with partly unknown degradation

NASA Astrophysics Data System (ADS)

Xie, Meihua; Yan, Fengxia

2017-01-01

The problem of image restoration has been extensively studied for its practical importance and theoretical interest. This paper mainly discusses the problem of image restoration with partly unknown kernel. In this model, the degraded kernel function is known but its parameters are unknown. With this model, we should estimate the parameters in Gaussian kernel and the real image simultaneity. For this new problem, a total variation restoration model is put out and an intersect direction iteration algorithm is designed. Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index Measurement (SSIM) are used to measure the performance of the method. Numerical results show that we can estimate the parameters in kernel accurately, and the new method has both much higher PSNR and much higher SSIM than the expectation maximization (EM) method in many cases. In addition, the accuracy of estimation is not sensitive to noise. Furthermore, even though the support of the kernel is unknown, we can also use this method to get accurate estimation.

DIRECT N-BODY MODELING OF THE OLD OPEN CLUSTER NGC 188: A DETAILED COMPARISON OF THEORETICAL AND OBSERVED BINARY STAR AND BLUE STRAGGLER POPULATIONS

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

Geller, Aaron M.; Hurley, Jarrod R.; Mathieu, Robert D., E-mail: a-geller@northwestern.edu, E-mail: mathieu@astro.wisc.edu, E-mail: jhurley@astro.swin.edu.au

2013-01-01

Following on from a recently completed radial-velocity survey of the old (7 Gyr) open cluster NGC 188 in which we studied in detail the solar-type hard binaries and blue stragglers of the cluster, here we investigate the dynamical evolution of NGC 188 through a sophisticated N-body model. Importantly, we employ the observed binary properties of the young (180 Myr) open cluster M35, where possible, to guide our choices for parameters of the initial binary population. We apply pre-main-sequence tidal circularization and a substantial increase to the main-sequence tidal circularization rate, both of which are necessary to match the observed tidalmore » circularization periods in the literature, including that of NGC 188. At 7 Gyr the main-sequence solar-type hard-binary population in the model matches that of NGC 188 in both binary frequency and distributions of orbital parameters. This agreement between the model and observations is in a large part due to the similarities between the NGC 188 and M35 solar-type binaries. Indeed, among the 7 Gyr main-sequence binaries in the model, only those with P {approx}> 1000 days begin to show potentially observable evidence for modifications by dynamical encounters, even after 7 Gyr of evolution within the star cluster. This emphasizes the importance of defining accurate initial conditions for star cluster models, which we propose is best accomplished through comparisons with observations of young open clusters like M35. Furthermore, this finding suggests that observations of the present-day binaries in even old open clusters can provide valuable information on their primordial binary populations. However, despite the model's success at matching the observed solar-type main-sequence population, the model underproduces blue stragglers and produces an overabundance of long-period circular main-sequence-white-dwarf binaries as compared with the true cluster. We explore several potential solutions to the paucity of blue stragglers and conclude that the model dramatically underproduces blue stragglers through mass-transfer processes. We suggest that common-envelope evolution may have been incorrectly imposed on the progenitors of the spurious long-period circular main-sequence-white-dwarf binaries, which perhaps instead should have gone through stable mass transfer to create blue stragglers, thereby bringing both the number and binary frequency of the blue straggler population in the model into agreement with the true blue stragglers in NGC 188. Thus, improvements in the physics of mass transfer and common-envelope evolution employed in the model may in fact solve both discrepancies with the observations. This project highlights the unique accessibility of open clusters to both comprehensive observational surveys and full-scale N-body simulations, both of which have only recently matured sufficiently to enable such a project, and underscores the importance of open clusters to the study of star cluster dynamics.« less

Predictive modeling of slope deposits and comparisons of two small areas in Northern Germany

NASA Astrophysics Data System (ADS)

Shary, Peter A.; Sharaya, Larisa S.; Mitusov, Andrew V.

2017-08-01

Methods for correct quantitative comparison of several terrains are important in the development and use of quantitative landscape evolution models, and they need to introduce specific modeling parameters. We introduce such parameters and compare two small terrains with respect to the link slope-valley for the description of slope deposits (colluvium) in them. We show that colluvium accumulation in small areas cannot be described by linear models and thus introduce non-linear models. Two small areas, Perdoel (0.29 ha) and Bornhöved (3.2 ha), are studied. Slope deposits in the both are mainly in dry valleys, with a total thickness Mtotal up to 2.0 m in Perdoel and up to 1.2 m in Bornhöved. Parent materials are mainly Pleistocene sands aged 30 kyr BP. Exponential models of multiple regression that use a 1-m LiDAR DEM (digital elevation model) explained 70-93% of spatial variability in Mtotal. Parameters DH12 and DV12 of horizontal and vertical distances are introduced that permit to characterize and compare conditions of colluvium formation for various terrains. The study areas differ 3.7 times by the parameter DH12 that describes a horizontal distance from thalwegs at which Mtotal diminishes 2.72 times. DH12 is greater in Bornhöved (29.7 m) than in Perdoel (8.12 m). We relate this difference in DH12 to the distinction between types of the link slope-valley: a regional type if catchment area of a region outside a given small area plays an important role, and a local type when accumulation of colluvium from valley banks within a small area is of more importance. We argue that the link slope-valley is regional in Perdoel and local in Bornhöved. Peaks of colluvium thickness were found on thalwegs of three studied valleys by both direct measurements in a trench, and model surfaces of Mtotal. A hypothesis on the formation mechanism of such peaks is discussed. The parameter DV12 describes a vertical distance from a peak of colluvium thickness along valley bottom at which Mtotal diminishes 2.72 times; values of this parameter differ 1.4 times for the study areas. DV12 is greater in Perdoel (3.0 m) than in Bornhöved (2.1 m) thus indicating more sharp peaks of Mtotal in Bornhöved. Exponential models allow construction of predictive maps of buried Pleistocene surfaces for both the terrains and calculate colluvium volumes with an error 4.2% for Perdoel and 7.1% for Bornhöved. Comparisons of buried and present surfaces showed that the latter are more smoothed, more strongly in valleys where flow branching is increased.

Global sensitivity analysis of the BSM2 dynamic influent disturbance scenario generator.

PubMed

Flores-Alsina, Xavier; Gernaey, Krist V; Jeppsson, Ulf

2012-01-01

This paper presents the results of a global sensitivity analysis (GSA) of a phenomenological model that generates dynamic wastewater treatment plant (WWTP) influent disturbance scenarios. This influent model is part of the Benchmark Simulation Model (BSM) family and creates realistic dry/wet weather files describing diurnal, weekend and seasonal variations through the combination of different generic model blocks, i.e. households, industry, rainfall and infiltration. The GSA is carried out by combining Monte Carlo simulations and standardized regression coefficients (SRC). Cluster analysis is then applied, classifying the influence of the model parameters into strong, medium and weak. The results show that the method is able to decompose the variance of the model predictions (R(2)> 0.9) satisfactorily, thus identifying the model parameters with strongest impact on several flow rate descriptors calculated at different time resolutions. Catchment size (PE) and the production of wastewater per person equivalent (QperPE) are two parameters that strongly influence the yearly average dry weather flow rate and its variability. Wet weather conditions are mainly affected by three parameters: (1) the probability of occurrence of a rain event (Llrain); (2) the catchment size, incorporated in the model as a parameter representing the conversion from mm rain · day(-1) to m(3) · day(-1) (Qpermm); and, (3) the quantity of rain falling on permeable areas (aH). The case study also shows that in both dry and wet weather conditions the SRC ranking changes when the time scale of the analysis is modified, thus demonstrating the potential to identify the effect of the model parameters on the fast/medium/slow dynamics of the flow rate. The paper ends with a discussion on the interpretation of GSA results and of the advantages of using synthetic dynamic flow rate data for WWTP influent scenario generation. This section also includes general suggestions on how to use the proposed methodology to any influent generator to adapt the created time series to a modeller's demands.

Modeling Stone Columns.

PubMed

Castro, Jorge

2017-07-11

This paper reviews the main modeling techniques for stone columns, both ordinary stone columns and geosynthetic-encased stone columns. The paper tries to encompass the more recent advances and recommendations in the topic. Regarding the geometrical model, the main options are the "unit cell", longitudinal gravel trenches in plane strain conditions, cylindrical rings of gravel in axial symmetry conditions, equivalent homogeneous soil with improved properties and three-dimensional models, either a full three-dimensional model or just a three-dimensional row or slice of columns. Some guidelines for obtaining these simplified geometrical models are provided and the particular case of groups of columns under footings is also analyzed. For the latter case, there is a column critical length that is around twice the footing width for non-encased columns in a homogeneous soft soil. In the literature, the column critical length is sometimes given as a function of the column length, which leads to some disparities in its value. Here it is shown that the column critical length mainly depends on the footing dimensions. Some other features related with column modeling are also briefly presented, such as the influence of column installation. Finally, some guidance and recommendations are provided on parameter selection for the study of stone columns.

Modeling Stone Columns

PubMed Central

2017-01-01

This paper reviews the main modeling techniques for stone columns, both ordinary stone columns and geosynthetic-encased stone columns. The paper tries to encompass the more recent advances and recommendations in the topic. Regarding the geometrical model, the main options are the “unit cell”, longitudinal gravel trenches in plane strain conditions, cylindrical rings of gravel in axial symmetry conditions, equivalent homogeneous soil with improved properties and three-dimensional models, either a full three-dimensional model or just a three-dimensional row or slice of columns. Some guidelines for obtaining these simplified geometrical models are provided and the particular case of groups of columns under footings is also analyzed. For the latter case, there is a column critical length that is around twice the footing width for non-encased columns in a homogeneous soft soil. In the literature, the column critical length is sometimes given as a function of the column length, which leads to some disparities in its value. Here it is shown that the column critical length mainly depends on the footing dimensions. Some other features related with column modeling are also briefly presented, such as the influence of column installation. Finally, some guidance and recommendations are provided on parameter selection for the study of stone columns. PMID:28773146

Cheetah: Starspot modeling code

NASA Astrophysics Data System (ADS)

Walkowicz, Lucianne; Thomas, Michael; Finkestein, Adam

2014-12-01

Cheetah models starspots in photometric data (lightcurves) by calculating the modulation of a light curve due to starspots. The main parameters of the program are the linear and quadratic limb darkening coefficients, stellar inclination, spot locations and sizes, and the intensity ratio of the spots to the stellar photosphere. Cheetah uses uniform spot contrast and the minimum number of spots needed to produce a good fit and ignores bright regions for the sake of simplicity.

Mixed-phase altocumulus clouds over Leipzig: Remote sensing measurements and spectral cloud microphysics simulations

NASA Astrophysics Data System (ADS)

Simmel, Martin; Bühl, Johannes; Ansmann, Albert; Tegen, Ina

2015-04-01

The present work combines remote sensing observations and detailed microphysics cloud modeling to investigate two altocumulus cloud cases observed over Leipzig, Germany. A suite of remote sensing instruments was able to detect primary ice at rather warm temperatures of -6°C. For comparison, a second mixed phase case at about -25°C is introduced. To further look into the details of cloud microphysical processes a simple dynamics model of the Asai-Kasahara type is combined with detailed spectral microphysics forming the model system AK-SPECS. Temperature and humidity profiles are taken either from observation (radiosonde) or GDAS reanalysis. Vertical velocities are prescribed to force the dynamics as well as main cloud features to be close to the observations. Subsequently, sensitivity studies with respect to dynamical as well as ice microphysical parameters are carried out with the aim to quantify the most important sensitivities for the cases investigated. For the cases selected, the liquid phase is mainly determined by the model dynamics (location and strength of vertical velocity) whereas the ice phase is much more sensitive to the microphysical parameters (ice nuclei (IN) number, ice particle shape). The choice of ice particle shape may induce large uncertainties which are in the same order as those for the temperature-dependent IN number distribution.

Pest control through viral disease: mathematical modeling and analysis.

PubMed

Bhattacharyya, S; Bhattacharya, D K

2006-01-07

This paper deals with the mathematical modeling of pest management under viral infection (i.e. using viral pesticide) and analysis of its essential mathematical features. As the viral infection induces host lysis which releases more virus into the environment, on the average 'kappa' viruses per host, kappain(1,infinity), the 'virus replication parameter' is chosen as the main parameter on which the dynamics of the infection depends. We prove that there exists a threshold value kappa(0) beyond which the endemic equilibrium bifurcates from the free disease one. Still for increasing kappa values, the endemic equilibrium bifurcates towards a periodic solution. We further analyse the orbital stability of the periodic orbits arising from bifurcation by applying Poor's condition. A concluding discussion with numerical simulation of the model is then presented.

Subionospheric VLF Propagation Modelling During a solar flares

NASA Astrophysics Data System (ADS)

Akel, A. F.

2013-05-01

This work aims to present a preliminary study of the behavior of the lower ionosphere under transient regimes of ionization through the technique of wave propagation of VLF (Very Low Frequency). For this, we characterized the lower ionosphere by two traditional (wait) parameters H' and β which are found by VLF radio modelling using the computational code of subionospheric radio propagation LWPC(Long Wave Propagation Capability). The main effects and behaviors investigated in this study was due to a solar flare 2M class near solar minimum at 03/25/2008. We changed Solar zenith angle dependence of the ionospheric parameters H' and β for diurnal time by a polynomial equation. For this study we used the available data the South America VLF Network (SAVNET) and show the results between modeling and data

THE MAYAK WORKER DOSIMETRY SYSTEM (MWDS-2013) FOR INTERNALLY DEPOSITED PLUTONIUM: AN OVERVIEW

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

Birchall, A.; Vostrotin, V.; Puncher, M.

The Mayak Worker Dosimetry System (MWDS-2013) is a system for interpreting measurement data from Mayak workers from both internal and external sources. This paper is concerned with the calculation of annual organ doses for Mayak workers exposed to plutonium aerosols, where the measurement data consists mainly of activity of plutonium in urine samples. The system utilises the latest biokinetic and dosimetric models, and unlike its predecessors, takes explicit account of uncertainties in both the measurement data and model parameters. The aim of this paper is to describe the complete MWDS-2013 system (including model parameter values and their uncertainties) and themore » methodology used (including all the relevant equations) and the assumptions made. Where necessary, supplementary papers which justify specific assumptions are cited.« less

Adsorptive removal of pharmaceuticals from water by commercial and waste-based carbons.

PubMed

Calisto, Vânia; Ferreira, Catarina I A; Oliveira, João A B P; Otero, Marta; Esteves, Valdemar I

2015-04-01

This work describes the single adsorption of seven pharmaceuticals (carbamazepine, oxazepam, sulfamethoxazole, piroxicam, cetirizine, venlafaxine and paroxetine) from water onto a commercially available activated carbon and a non-activated carbon produced by pyrolysis of primary paper mill sludge. Kinetics and equilibrium adsorption studies were performed using a batch experimental approach. For all pharmaceuticals, both carbons presented fast kinetics (equilibrium times varying from less than 5 min to 120 min), mainly described by a pseudo-second order model. Equilibrium data were appropriately described by the Langmuir and Freundlich isotherm models, the last one giving slightly higher correlation coefficients. The fitted parameters obtained for both models were quite different for the seven pharmaceuticals under study. In order to evaluate the influence of water solubility, log Kow, pKa, polar surface area and number of hydrogen bond acceptors of pharmaceuticals on the adsorption parameters, multiple linear regression analysis was performed. The variability is mainly due to log Kow followed by water solubility, in the case of the waste-based carbon, and due to water solubility in the case of the commercial activated carbon. Copyright © 2015 Elsevier Ltd. All rights reserved.

The Impeller Exit Flow Coefficient As a Performance Map Variable for Predicting Centrifugal Compressor Off-Design Operation Applied to a Supercritical CO 2 Working Fluid

DOE PAGES

Liese, Eric; Zitney, Stephen E.

2017-06-26

A multi-stage centrifugal compressor model is presented with emphasis on analyzing use of an exit flow coefficient vs. an inlet flow coefficient performance parameter to predict off-design conditions in the critical region of a supercritical carbon dioxide (CO 2) power cycle. A description of the performance parameters is given along with their implementation in a design model (number of stages, basic sizing, etc.) and a dynamic model (for use in transient studies). A design case is shown for two compressors, a bypass compressor and a main compressor, as defined in a process simulation of a 10 megawatt (MW) supercritical COmore » 2 recompression Brayton cycle. Simulation results are presented for a simple open cycle and closed cycle process with changes to the inlet temperature of the main compressor which operates near the CO 2 critical point. Results showed some difference in results using the exit vs. inlet flow coefficient correction, however, it was not significant for the range of conditions examined. Here, this paper also serves as a reference for future works, including a full process simulation of the 10 MW recompression Brayton cycle.« less

The Impeller Exit Flow Coefficient As a Performance Map Variable for Predicting Centrifugal Compressor Off-Design Operation Applied to a Supercritical CO 2 Working Fluid

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

Liese, Eric; Zitney, Stephen E.

A multi-stage centrifugal compressor model is presented with emphasis on analyzing use of an exit flow coefficient vs. an inlet flow coefficient performance parameter to predict off-design conditions in the critical region of a supercritical carbon dioxide (CO 2) power cycle. A description of the performance parameters is given along with their implementation in a design model (number of stages, basic sizing, etc.) and a dynamic model (for use in transient studies). A design case is shown for two compressors, a bypass compressor and a main compressor, as defined in a process simulation of a 10 megawatt (MW) supercritical COmore » 2 recompression Brayton cycle. Simulation results are presented for a simple open cycle and closed cycle process with changes to the inlet temperature of the main compressor which operates near the CO 2 critical point. Results showed some difference in results using the exit vs. inlet flow coefficient correction, however, it was not significant for the range of conditions examined. Here, this paper also serves as a reference for future works, including a full process simulation of the 10 MW recompression Brayton cycle.« less

INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Solvable Catalyzed Birth-Death-Exchange Competition Model of Three Species

NASA Astrophysics Data System (ADS)

Wang, Hai-Feng; Lin, Zhen-Quan; Gao, Yan; Zhang, Heng

2009-10-01

A competition model of three species in exchange-driven aggregation growth is proposed. In the model, three distinct aggregates grow by exchange of monomers and in parallel, birth of species A is catalyzed by species B and death of species A is catalyzed by species C. The rates for both catalysis processes are proportional to kjν and kjω respectively, where ν(Ω) is a parameter reflecting the dependence of the catalysis reaction rate of birth (death) on the catalyst aggregate's size. The kinetic evolution behaviors of the three species are investigated by the rate equation approach based on the mean-field theory. The form of the aggregate size distribution of A-species ak(t) is found to be dependent crucially on the two catalysis rate kernel parameters. The results show that (i) in case of μ <= 0, the form of ak(t) mainly depends on the competition between self-exchange of species A and species-C-catalyzed death of species A; (ii) in case of ν > 0, the form of ak(t) mainly depends on the competition between species-B-catalyzed birth of species A and species-C-catalyzed death of species A.

Statistical thermodynamics of long straight rigid rods on triangular lattices: nematic order and adsorption thermodynamic functions.

PubMed

Matoz-Fernandez, D A; Linares, D H; Ramirez-Pastor, A J

2012-09-04

The statistical thermodynamics of straight rigid rods of length k on triangular lattices was developed on a generalization in the spirit of the lattice-gas model and the classical Guggenheim-DiMarzio approximation. In this scheme, the Helmholtz free energy and its derivatives were written in terms of the order parameter, δ, which characterizes the nematic phase occurring in the system at intermediate densities. Then, using the principle of minimum free energy with δ as a parameter, the main adsorption properties were calculated. Comparisons with Monte Carlo simulations and experimental data were performed in order to evaluate the outcome and limitations of the theoretical model.

An imprecise probability approach for squeal instability analysis based on evidence theory

NASA Astrophysics Data System (ADS)

Lü, Hui; Shangguan, Wen-Bin; Yu, Dejie

2017-01-01

An imprecise probability approach based on evidence theory is proposed for squeal instability analysis of uncertain disc brakes in this paper. First, the squeal instability of the finite element (FE) model of a disc brake is investigated and its dominant unstable eigenvalue is detected by running two typical numerical simulations, i.e., complex eigenvalue analysis (CEA) and transient dynamical analysis. Next, the uncertainty mainly caused by contact and friction is taken into account and some key parameters of the brake are described as uncertain parameters. All these uncertain parameters are usually involved with imprecise data such as incomplete information and conflict information. Finally, a squeal instability analysis model considering imprecise uncertainty is established by integrating evidence theory, Taylor expansion, subinterval analysis and surrogate model. In the proposed analysis model, the uncertain parameters with imprecise data are treated as evidence variables, and the belief measure and plausibility measure are employed to evaluate system squeal instability. The effectiveness of the proposed approach is demonstrated by numerical examples and some interesting observations and conclusions are summarized from the analyses and discussions. The proposed approach is generally limited to the squeal problems without too many investigated parameters. It can be considered as a potential method for squeal instability analysis, which will act as the first step to reduce squeal noise of uncertain brakes with imprecise information.

Approximate Bayesian Computation in the estimation of the parameters of the Forbush decrease model

NASA Astrophysics Data System (ADS)

Wawrzynczak, A.; Kopka, P.

2017-12-01

Realistic modeling of the complicated phenomena as Forbush decrease of the galactic cosmic ray intensity is a quite challenging task. One aspect is a numerical solution of the Fokker-Planck equation in five-dimensional space (three spatial variables, the time and particles energy). The second difficulty arises from a lack of detailed knowledge about the spatial and time profiles of the parameters responsible for the creation of the Forbush decrease. Among these parameters, the central role plays a diffusion coefficient. Assessment of the correctness of the proposed model can be done only by comparison of the model output with the experimental observations of the galactic cosmic ray intensity. We apply the Approximate Bayesian Computation (ABC) methodology to match the Forbush decrease model to experimental data. The ABC method is becoming increasing exploited for dynamic complex problems in which the likelihood function is costly to compute. The main idea of all ABC methods is to accept samples as an approximate posterior draw if its associated modeled data are close enough to the observed one. In this paper, we present application of the Sequential Monte Carlo Approximate Bayesian Computation algorithm scanning the space of the diffusion coefficient parameters. The proposed algorithm is adopted to create the model of the Forbush decrease observed by the neutron monitors at the Earth in March 2002. The model of the Forbush decrease is based on the stochastic approach to the solution of the Fokker-Planck equation.

Cost effectiveness of pediatric pneumococcal conjugate vaccines: a comparative assessment of decision-making tools.

PubMed

Chaiyakunapruk, Nathorn; Somkrua, Ratchadaporn; Hutubessy, Raymond; Henao, Ana Maria; Hombach, Joachim; Melegaro, Alessia; Edmunds, John W; Beutels, Philippe

2011-05-12

Several decision support tools have been developed to aid policymaking regarding the adoption of pneumococcal conjugate vaccine (PCV) into national pediatric immunization programs. The lack of critical appraisal of these tools makes it difficult for decision makers to understand and choose between them. With the aim to guide policymakers on their optimal use, we compared publicly available decision-making tools in relation to their methods, influential parameters and results. The World Health Organization (WHO) requested access to several publicly available cost-effectiveness (CE) tools for PCV from both public and private provenance. All tools were critically assessed according to the WHO's guide for economic evaluations of immunization programs. Key attributes and characteristics were compared and a series of sensitivity analyses was performed to determine the main drivers of the results. The results were compared based on a standardized set of input parameters and assumptions. Three cost-effectiveness modeling tools were provided, including two cohort-based (Pan-American Health Organization (PAHO) ProVac Initiative TriVac, and PneumoADIP) and one population-based model (GlaxoSmithKline's SUPREMES). They all compared the introduction of PCV into national pediatric immunization program with no PCV use. The models were different in terms of model attributes, structure, and data requirement, but captured a similar range of diseases. Herd effects were estimated using different approaches in each model. The main driving parameters were vaccine efficacy against pneumococcal pneumonia, vaccine price, vaccine coverage, serotype coverage and disease burden. With a standardized set of input parameters developed for cohort modeling, TriVac and PneumoADIP produced similar incremental costs and health outcomes, and incremental cost-effectiveness ratios. Vaccine cost (dose price and number of doses), vaccine efficacy and epidemiology of critical endpoint (for example, incidence of pneumonia, distribution of serotypes causing pneumonia) were influential parameters in the models we compared. Understanding the differences and similarities of such CE tools through regular comparisons could render decision-making processes in different countries more efficient, as well as providing guiding information for further clinical and epidemiological research. A tool comparison exercise using standardized data sets can help model developers to be more transparent about their model structure and assumptions and provide analysts and decision makers with a more in-depth view behind the disease dynamics. Adherence to the WHO guide of economic evaluations of immunization programs may also facilitate this process. Please see related article: http://www.biomedcentral.com/1741-7007/9/55.

Mechanical modeling and characterization of meniscus tissue using flat punch indentation and inverse finite element method.

PubMed

Seyfi, Behzad; Fatouraee, Nasser; Imeni, Milad

2018-01-01

In this paper, to characterize the mechanical properties of meniscus by considering its local microstructure, a novel nonlinear poroviscoelastic Finite Element (FE) model has been developed. To obtain the mechanical response of meniscus, indentation experiments were performed on bovine meniscus samples. The ramp-relaxation test scenario with different depths and preloads was designed to capture the mechanical characteristics of the tissue in different regions of the medial and lateral menisci. Thereafter, a FE simulation was performed considering experimental conditions. Constitutive parameters were optimized by solving a FE-based inverse problem using the heuristic Simulated Annealing (SA) optimization algorithm. These parameters were ranged according to previously reported data to improve the optimization procedure. Based on the results, the mechanical properties of meniscus were highly influenced by both superficial and main layers. At low indentation depths, a high percentage relaxation (p < 0.01) with a high relaxation rate (p < 0.05) was obtained, due to the poroelastic and viscoelastic nature of the superficial layer. Increasing both penetration depth and preload level involved the main layer response and caused alterations in hyperelastic and viscoelastic parameters of the tissue, such that for both layers, the shear modulus was increased (p < 0.01) while the rate and percentage of relaxation were decreased (p < 0.01). Results reflect that, shear modulus of the main layer in anterior region is higher than central and posterior sites in medial meniscus. In contrast, in lateral meniscus, posterior side is stiffer than central and anterior sides. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Bi-Directional Prediction of Carbon Fiber Production Using a Combination of Improved Particle Swarm Optimization and Support Vector Machine.

PubMed

Xiao, Chuncai; Hao, Kuangrong; Ding, Yongsheng

2014-12-30

This paper creates a bi-directional prediction model to predict the performance of carbon fiber and the productive parameters based on a support vector machine (SVM) and improved particle swarm optimization (IPSO) algorithm (SVM-IPSO). In the SVM, it is crucial to select the parameters that have an important impact on the performance of prediction. The IPSO is proposed to optimize them, and then the SVM-IPSO model is applied to the bi-directional prediction of carbon fiber production. The predictive accuracy of SVM is mainly dependent on its parameters, and IPSO is thus exploited to seek the optimal parameters for SVM in order to improve its prediction capability. Inspired by a cell communication mechanism, we propose IPSO by incorporating information of the global best solution into the search strategy to improve exploitation, and we employ IPSO to establish the bi-directional prediction model: in the direction of the forward prediction, we consider productive parameters as input and property indexes as output; in the direction of the backward prediction, we consider property indexes as input and productive parameters as output, and in this case, the model becomes a scheme design for novel style carbon fibers. The results from a set of the experimental data show that the proposed model can outperform the radial basis function neural network (RNN), the basic particle swarm optimization (PSO) method and the hybrid approach of genetic algorithm and improved particle swarm optimization (GA-IPSO) method in most of the experiments. In other words, simulation results demonstrate the effectiveness and advantages of the SVM-IPSO model in dealing with the problem of forecasting.

Thrombus segmentation by texture dynamics from microscopic image sequences

NASA Astrophysics Data System (ADS)

Brieu, Nicolas; Serbanovic-Canic, Jovana; Cvejic, Ana; Stemple, Derek; Ouwehand, Willem; Navab, Nassir; Groher, Martin

2010-03-01

The genetic factors of thrombosis are commonly explored by microscopically imaging the coagulation of blood cells induced by injuring a vessel of mice or of zebrafish mutants. The latter species is particularly interesting since skin transparency permits to non-invasively acquire microscopic images of the scene with a CCD camera and to estimate the parameters characterizing the thrombus development. These parameters are currently determined by manual outlining, which is both error prone and extremely time consuming. Even though a technique for automatic thrombus extraction would be highly valuable for gene analysts, little work can be found, which is mainly due to very low image contrast and spurious structures. In this work, we propose to semi-automatically segment the thrombus over time from microscopic image sequences of wild-type zebrafish larvae. To compensate the lack of valuable spatial information, our main idea consists of exploiting the temporal information by modeling the variations of the pixel intensities over successive temporal windows with a linear Markov-based dynamic texture formalization. We then derive an image from the estimated model parameters, which represents the probability of a pixel to belong to the thrombus. We employ this probability image to accurately estimate the thrombus position via an active contour segmentation incorporating also prior and spatial information of the underlying intensity images. The performance of our approach is tested on three microscopic image sequences. We show that the thrombus is accurately tracked over time in each sequence if the respective parameters controlling prior influence and contour stiffness are correctly chosen.

Testing Models of Stellar Structure and Evolution I. Comparison with Detached Eclipsing Binaries

NASA Astrophysics Data System (ADS)

del Burgo, C.; Allende Prieto, C.

2018-05-01

We present the results of an analysis aimed at testing the accuracy and precision of the PARSEC v1.2S library of stellar evolution models, combined with a Bayesian approach, to infer stellar parameters. We mainly employ the online DEBCat catalogue by Southworth, a compilation of detached eclipsing binary systems with published measurements of masses and radii to ˜ 2 per cent precision. We select a sample of 318 binary components, with masses between 0.10 and 14.5 solar units, and distances between 1.3 pc and ˜ 8 kpc for Galactic objects and ˜ 44-68 kpc for the extragalactic ones. The Bayesian analysis applied takes on input effective temperature, radius, and [Fe/H], and their uncertainties, returning theoretical predictions for other stellar parameters. From the comparison with dynamical masses, we conclude inferred masses are precisely derived for stars on the main-sequence and in the core-helium-burning phase, with respective uncertainties of 4 per cent and 7 per cent, on average. Subgiants and red giants masses are predicted within 14 per cent, and early asymptotic giant branch stars within 24 per cent. These results are helpful to further improve the models, in particular for advanced evolutionary stages for which our understanding is limited. We obtain distances and ages for the binary systems and compare them, whenever possible, with precise literature estimates, finding excellent agreement. We discuss evolutionary effects and the challenges associated with the inference of stellar ages from evolutionary models. We also provide useful polynomial fittings to theoretical zero-age main-sequence relations.

Application of interleaving models for the description of intrusive layering at the fronts of deep polar water in the Eurasian Basin (Arctic)

NASA Astrophysics Data System (ADS)

Kuzmina, N. P.; Zhurbas, N. V.; Emelianov, M. V.; Pyzhevich, M. L.

2014-09-01

Interleaving models of pure thermohaline and baroclinic frontal zones are applied to describe intrusions at the fronts found in the upper part of the Deep Polar Water (DPW) when the stratification was absolutely stable. It is assumed that differential mixing is the main mechanism of the intrusion formation. Important parameters of the interleaving such as the growth rate, vertical scale, and slope of the most unstable modes relative to the horizontal plane are calculated. It was found that the interleaving model for a pure thermohaline front satisfactory describes the important intrusion parameters observed at the frontal zone. In the case of a baroclinic front, satisfactory agreement over all the interleaving parameters is observed between the model calculations and observations provided that the vertical momentum diffusivity significantly exceeds the corresponding coefficient of mass diffusivity. Under specific (reasonable) constraints of the vertical momentum diffusivity, the most unstable mode has a vertical scale approximately two-three times smaller than the vertical scale of the observed intrusions. A thorough discussion of the results is presented.

Safe uses of Hill's model: an exact comparison with the Adair-Klotz model

PubMed Central

2011-01-01

Background The Hill function and the related Hill model are used frequently to study processes in the living cell. There are very few studies investigating the situations in which the model can be safely used. For example, it has been shown, at the mean field level, that the dose response curve obtained from a Hill model agrees well with the dose response curves obtained from a more complicated Adair-Klotz model, provided that the parameters of the Adair-Klotz model describe strongly cooperative binding. However, it has not been established whether such findings can be extended to other properties and non-mean field (stochastic) versions of the same, or other, models. Results In this work a rather generic quantitative framework for approaching such a problem is suggested. The main idea is to focus on comparing the particle number distribution functions for Hill's and Adair-Klotz's models instead of investigating a particular property (e.g. the dose response curve). The approach is valid for any model that can be mathematically related to the Hill model. The Adair-Klotz model is used to illustrate the technique. One main and two auxiliary similarity measures were introduced to compare the distributions in a quantitative way. Both time dependent and the equilibrium properties of the similarity measures were studied. Conclusions A strongly cooperative Adair-Klotz model can be replaced by a suitable Hill model in such a way that any property computed from the two models, even the one describing stochastic features, is approximately the same. The quantitative analysis showed that boundaries of the regions in the parameter space where the models behave in the same way exhibit a rather rich structure. PMID:21521501

Particle filter based hybrid prognostics for health monitoring of uncertain systems in bond graph framework

NASA Astrophysics Data System (ADS)

Jha, Mayank Shekhar; Dauphin-Tanguy, G.; Ould-Bouamama, B.

2016-06-01

The paper's main objective is to address the problem of health monitoring of system parameters in Bond Graph (BG) modeling framework, by exploiting its structural and causal properties. The system in feedback control loop is considered uncertain globally. Parametric uncertainty is modeled in interval form. The system parameter is undergoing degradation (prognostic candidate) and its degradation model is assumed to be known a priori. The detection of degradation commencement is done in a passive manner which involves interval valued robust adaptive thresholds over the nominal part of the uncertain BG-derived interval valued analytical redundancy relations (I-ARRs). The latter forms an efficient diagnostic module. The prognostics problem is cast as joint state-parameter estimation problem, a hybrid prognostic approach, wherein the fault model is constructed by considering the statistical degradation model of the system parameter (prognostic candidate). The observation equation is constructed from nominal part of the I-ARR. Using particle filter (PF) algorithms; the estimation of state of health (state of prognostic candidate) and associated hidden time-varying degradation progression parameters is achieved in probabilistic terms. A simplified variance adaptation scheme is proposed. Associated uncertainties which arise out of noisy measurements, parametric degradation process, environmental conditions etc. are effectively managed by PF. This allows the production of effective predictions of the remaining useful life of the prognostic candidate with suitable confidence bounds. The effectiveness of the novel methodology is demonstrated through simulations and experiments on a mechatronic system.

The soil water characteristic as new class of closed-form parametric expressions for the flow duration curve

NASA Astrophysics Data System (ADS)

Sadegh, M.; Vrugt, J. A.; Gupta, H. V.; Xu, C.

2016-04-01

The flow duration curve is a signature catchment characteristic that depicts graphically the relationship between the exceedance probability of streamflow and its magnitude. This curve is relatively easy to create and interpret, and is used widely for hydrologic analysis, water quality management, and the design of hydroelectric power plants (among others). Several mathematical expressions have been proposed to mimic the FDC. Yet, these efforts have not been particularly successful, in large part because available functions are not flexible enough to portray accurately the functional shape of the FDC for a large range of catchments and contrasting hydrologic behaviors. Here, we extend the work of Vrugt and Sadegh (2013) and introduce several commonly used models of the soil water characteristic as new class of closed-form parametric expressions for the flow duration curve. These soil water retention functions are relatively simple to use, contain between two to three parameters, and mimic closely the empirical FDCs of 430 catchments of the MOPEX data set. We then relate the calibrated parameter values of these models to physical and climatological characteristics of the watershed using multivariate linear regression analysis, and evaluate the regionalization potential of our proposed models against those of the literature. If quality of fit is of main importance then the 3-parameter van Genuchten model is preferred, whereas the 2-parameter lognormal, 3-parameter GEV and generalized Pareto models show greater promise for regionalization.

Kinematics of Stars from the TGAS (Gaia DR1) Catalogue

NASA Astrophysics Data System (ADS)

Vityazev, V. V.; Popov, A. V.; Tsvetkov, A. S.; Petrov, S. D.; Trofimov, D. A.; Kiyaev, V. I.

2018-04-01

Based on the stellar proper motions of the TGAS (Gaia DR1) catalogue, we have analyzed the velocity field of main-sequence stars and red giants from the TGAS catalogue with heliocentric distances up to 1.5 kpc. We have obtained four variants of kinematic parameters corresponding to different methods of calculating the distances from the parallaxes of stars measured with large relative errors. We have established that within the Ogorodnikov-Milne model changing the variant of distances affects significantly only the solar velocity components relative to the chosen centroid of stars, provided that the solution is obtained in narrow ranges of distances (0.1 kpc). The estimates of all the remaining kinematic parameters change little. This allows the Oort coefficients and related Galactic rotation parameters as well as all the remaining Ogorodnikov-Milne model parameters (except for the solar terms) to be reliably estimated irrespective of the parallax measurement accuracy. The main results obtained from main-sequence stars in the range of distances from 0.1 to 1.5 kpc are: A = 16.29 ± 0.06 km s-1 kpc-1, B = -11.90 ± 0.05 km s-1 kpc-1, C = -2.99 ± 0.06 km s-1 kpc-1, K = -4.04 ± 0.16 km s-1 kpc-1, and the Galactic rotation period P = 217.41 ± 0.60 Myr. The analogous results obtained from red giants in the range from 0.2 to 1.6 kpc are: the Oort constants A = 13.32 ± 0.09 km s-1 kpc-1, B = -12.71 ± 0.06 km s-1 kpc-1, C = -2.04 ± 0.08 km s-1 kpc-1, K = -2.72 ± 0.19 km s-1 kpc-1, and the Galactic rotation period P = 236.03 ± 0.98 Myr. The Galactic rotation velocity gradient along the radius vector (the slope of the Galactic rotation curve) is -4.32 ± 0.08 km s-1 kpc-1 for main-sequence stars and -0.61 ± 0.11 km s-1 kpc-1 for red giants. This suggests that the Galactic rotation velocity determined from main-sequence stars decreases with increasing distance from the Galactic center faster than it does for red giants.

Characterization of the High-Albedo NEA 3691 Bede

NASA Technical Reports Server (NTRS)

Wooden, Diane H.; Lederer, Susan M.; Jehin, Emmanuel; Rozitis, Benjamin; Jefferson, Jeffrey D.; Nelson, Tyler W.; Dotson, Jessie L.; Ryan, Erin L.; Howell, Ellen S.; Fernandez, Yanga R.;

Characterization of the high-albedo NEA 3691 Bede

NASA Astrophysics Data System (ADS)

Wooden, Diane H.; Lederer, Susan M.; Jehin, Emmanuel; Rozitis, Benjamin; Jefferson, Jeffrey D.; Nelson, Tyler W.; Dotson, Jessie L.; Ryan, Erin L.; Howell, Ellen S.; Fernandez, Yanga R.; Lovell, Amy J.; Woodward, Charles E.; Harker, David Emerson

2016-10-01

Characterization of NEAs provides important inputs to models for atmospheric entry, risk assessment and mitigation. Diameter is a key parameter because diameter translates to kinetic energy in atmospheric entry. Diameters can be derived from the absolute magnitude, H(PA=0deg), and from thermal modeling of observed IR fluxes. For both methods, the albedo (pv) is important - high pv surfaces have cooler temperatures, larger diameters for a given Hmag, and shallower phase curves (larger slope parameter G). Thermal model parameters are coupled, however, so that a higher thermal inertia also results in a cooler surface temperature. Multiple parameters contribute to constraining the diameter.Observations made at multiple observing geometries can contribute to understanding the relationships between and potentially breaking some of the degeneracies between parameters. We present data and analyses on NEA 3691 Bede with the aim of best constraining the diameter and pv from a combination of thermal modeling and light curve analyses. We employ our UKIRT+Michelle mid-IR photometric observations of 3691 Bede's thermal emission at 2 phase angles (27&43 deg 2015-03-19 & 04-13), in addition to WISE data (33deg 2010-05-27, Mainzer+2011).Observing geometries differ by solar phase angles and by moderate changes in heliocentric distance (e.g., further distances produce somewhat cooler surface temperatures). With the NEATM model and for a constant IR beaming parameter (eta=constant), there is a family of solutions for (diameter, pv, G, eta) where G is the slope parameter from the H-G Relation. NEATM models employing Pravec+2012's choice of G=0.43, produce D=1.8 km and pv≈0.4, given that G=0.43 is assumed from studies of main belt asteroids (Warner+2009). We present an analysis of the light curve of 3691 Bede to constrain G from observations. We also investigate fitting thermophysical models (TPM, Rozitis+11) to constrain the coupled parameters of thermal inertia (Gamma) and surface roughness, which in turn affect diameter and pv. Surface composition can be related to pv. This study focuses on understanding and characterizing the dependency of parameters with the aim of constraining diameter, pv and thermal inertia for 3691 Bede.

Neutrino oscillations and Non-Standard Interactions

NASA Astrophysics Data System (ADS)

Farzan, Yasaman; Tórtola, Mariam

2018-02-01

Current neutrino experiments are measuring the neutrino mixing parameters with an unprecedented accuracy. The upcoming generation of neutrino experiments will be sensitive to subdominant oscillation effects that can give information on the yet-unknown neutrino parameters: the Dirac CP-violating phase, the mass ordering and the octant of θ_{23}. Determining the exact values of neutrino mass and mixing parameters is crucial to test neutrino models and flavor symmetries designed to predict these neutrino parameters. In the first part of this review, we summarize the current status of the neutrino oscillation parameter determination. We consider the most recent data from all solar experiments and the atmospheric data from Super-Kamiokande, IceCube and ANTARES. We also implement the data from the reactor neutrino experiments KamLAND, Daya Bay, RENO and Double Chooz as well as the long baseline neutrino data from MINOS, T2K and NOvA. If in addition to the standard interactions, neutrinos have subdominant yet-unknown Non-Standard Interactions (NSI) with matter fields, extracting the values of these parameters will suffer from new degeneracies and ambiguities. We review such effects and formulate the conditions on the NSI parameters under which the precision measurement of neutrino oscillation parameters can be distorted. Like standard weak interactions, the non-standard interaction can be categorized into two groups: Charged Current (CC) NSI and Neutral Current (NC) NSI. Our focus will be mainly on neutral current NSI because it is possible to build a class of models that give rise to sizeable NC NSI with discernible effects on neutrino oscillation. These models are based on new U(1) gauge symmetry with a gauge boson of mass ≲ 10 MeV. The UV complete model should be of course electroweak invariant which in general implies that along with neutrinos, charged fermions also acquire new interactions on which there are strong bounds. We enumerate the bounds that already exist on the electroweak symmetric models and demonstrate that it is possible to build viable models avoiding all these bounds. In the end, we review methods to test these models and suggest approaches to break the degeneracies in deriving neutrino mass parameters caused by NSI.

Integrable Time-Dependent Quantum Hamiltonians

NASA Astrophysics Data System (ADS)

Sinitsyn, Nikolai A.; Yuzbashyan, Emil A.; Chernyak, Vladimir Y.; Patra, Aniket; Sun, Chen

2018-05-01

We formulate a set of conditions under which the nonstationary Schrödinger equation with a time-dependent Hamiltonian is exactly solvable analytically. The main requirement is the existence of a non-Abelian gauge field with zero curvature in the space of system parameters. Known solvable multistate Landau-Zener models satisfy these conditions. Our method provides a strategy to incorporate time dependence into various quantum integrable models while maintaining their integrability. We also validate some prior conjectures, including the solution of the driven generalized Tavis-Cummings model.

The influence of ligament modelling strategies on the predictive capability of finite element models of the human knee joint.

PubMed

Naghibi Beidokhti, Hamid; Janssen, Dennis; van de Groes, Sebastiaan; Hazrati, Javad; Van den Boogaard, Ton; Verdonschot, Nico

2017-12-08

In finite element (FE) models knee ligaments can represented either by a group of one-dimensional springs, or by three-dimensional continuum elements based on segmentations. Continuum models closer approximate the anatomy, and facilitate ligament wrapping, while spring models are computationally less expensive. The mechanical properties of ligaments can be based on literature, or adjusted specifically for the subject. In the current study we investigated the effect of ligament modelling strategy on the predictive capability of FE models of the human knee joint. The effect of literature-based versus specimen-specific optimized material parameters was evaluated. Experiments were performed on three human cadaver knees, which were modelled in FE models with ligaments represented either using springs, or using continuum representations. In spring representation collateral ligaments were each modelled with three and cruciate ligaments with two single-element bundles. Stiffness parameters and pre-strains were optimized based on laxity tests for both approaches. Validation experiments were conducted to evaluate the outcomes of the FE models. Models (both spring and continuum) with subject-specific properties improved the predicted kinematics and contact outcome parameters. Models incorporating literature-based parameters, and particularly the spring models (with the representations implemented in this study), led to relatively high errors in kinematics and contact pressures. Using a continuum modelling approach resulted in more accurate contact outcome variables than the spring representation with two (cruciate ligaments) and three (collateral ligaments) single-element-bundle representations. However, when the prediction of joint kinematics is of main interest, spring ligament models provide a faster option with acceptable outcome. Copyright © 2017 Elsevier Ltd. All rights reserved.

A waste characterisation procedure for ADM1 implementation based on degradation kinetics.

PubMed

Girault, R; Bridoux, G; Nauleau, F; Poullain, C; Buffet, J; Steyer, J-P; Sadowski, A G; Béline, F

2012-09-01

In this study, a procedure accounting for degradation kinetics was developed to split the total COD of a substrate into each input state variable required for Anaerobic Digestion Model n°1. The procedure is based on the combination of batch experimental degradation tests ("anaerobic respirometry") and numerical interpretation of the results obtained (optimisation of the ADM1 input state variable set). The effects of the main operating parameters, such as the substrate to inoculum ratio in batch experiments and the origin of the inoculum, were investigated. Combined with biochemical fractionation of the total COD of substrates, this method enabled determination of an ADM1-consistent input state variable set for each substrate with affordable identifiability. The substrate to inoculum ratio in the batch experiments and the origin of the inoculum influenced input state variables. However, based on results modelled for a CSTR fed with the substrate concerned, these effects were not significant. Indeed, if the optimal ranges of these operational parameters are respected, uncertainty in COD fractionation is mainly limited to temporal variability of the properties of the substrates. As the method is based on kinetics and is easy to implement for a wide range of substrates, it is a very promising way to numerically predict the effect of design parameters on the efficiency of an anaerobic CSTR. This method thus promotes the use of modelling for the design and optimisation of anaerobic processes. Copyright © 2012 Elsevier Ltd. All rights reserved.

Experimental analysis of chaotic neural network models for combinatorial optimization under a unifying framework.

PubMed

Kwok, T; Smith, K A

2000-09-01

The aim of this paper is to study both the theoretical and experimental properties of chaotic neural network (CNN) models for solving combinatorial optimization problems. Previously we have proposed a unifying framework which encompasses the three main model types, namely, Chen and Aihara's chaotic simulated annealing (CSA) with decaying self-coupling, Wang and Smith's CSA with decaying timestep, and the Hopfield network with chaotic noise. Each of these models can be represented as a special case under the framework for certain conditions. This paper combines the framework with experimental results to provide new insights into the effect of the chaotic neurodynamics of each model. By solving the N-queen problem of various sizes with computer simulations, the CNN models are compared in different parameter spaces, with optimization performance measured in terms of feasibility, efficiency, robustness and scalability. Furthermore, characteristic chaotic neurodynamics crucial to effective optimization are identified, together with a guide to choosing the corresponding model parameters.

Reducing the Anaerobic Digestion Model No. 1 for its application to an industrial wastewater treatment plant treating winery effluent wastewater.

PubMed

García-Diéguez, Carlos; Bernard, Olivier; Roca, Enrique

2013-03-01

The Anaerobic Digestion Model No. 1 (ADM1) is a complex model which is widely accepted as a common platform for anaerobic process modeling and simulation. However, it has a large number of parameters and states that hinder its calibration and use in control applications. A principal component analysis (PCA) technique was extended and applied to simplify the ADM1 using data of an industrial wastewater treatment plant processing winery effluent. The method shows that the main model features could be obtained with a minimum of two reactions. A reduced stoichiometric matrix was identified and the kinetic parameters were estimated on the basis of representative known biochemical kinetics (Monod and Haldane). The obtained reduced model takes into account the measured states in the anaerobic wastewater treatment (AWT) plant and reproduces the dynamics of the process fairly accurately. The reduced model can support on-line control, optimization and supervision strategies for AWT plants. Copyright © 2013 Elsevier Ltd. All rights reserved.

Age and gender specific biokinetic model for strontium in humans

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

Shagina, N. B.; Tolstykh, E. I.; Degteva, M. O.

A biokinetic model for strontium in humans is necessary for quantification of internal doses due to strontium radioisotopes. The ICRP-recommended biokinetic model for strontium has limitation for use in a population study, because it is not gender specific and does not cover all age ranges. The extensive Techa River data set on 90Sr in humans (tens of thousands of measurements) is a unique source of data on long-term strontium retention for men and women of all ages at intake. These, as well as published data, were used for evaluation of age- and gender-specific parameters for a new compartment biokinetic modelmore » for strontium (Sr-AGe model). The Sr-AGe model has similar structure as the ICRP model for the alkaline earth elements. The following parameters were mainly reevaluated: gastro-intestinal absorption and parameters related to the processes of bone formation and resorption defining calcium and strontium transfers in skeletal compartments. The Sr-AGe model satisfactorily describes available data sets on strontium retention for different kinds of intake (dietary and intravenous) at different ages (0–80 years old) and demonstrates good agreement with data sets for different ethnic groups. The Sr-AGe model can be used for dose assessment in epidemiological studies of general population exposed to ingested strontium radioisotopes.« less

Computer vision-based method for classification of wheat grains using artificial neural network.

PubMed

Sabanci, Kadir; Kayabasi, Ahmet; Toktas, Abdurrahim

2017-06-01

A simplified computer vision-based application using artificial neural network (ANN) depending on multilayer perceptron (MLP) for accurately classifying wheat grains into bread or durum is presented. The images of 100 bread and 100 durum wheat grains are taken via a high-resolution camera and subjected to pre-processing. The main visual features of four dimensions, three colors and five textures are acquired using image-processing techniques (IPTs). A total of 21 visual features are reproduced from the 12 main features to diversify the input population for training and testing the ANN model. The data sets of visual features are considered as input parameters of the ANN model. The ANN with four different input data subsets is modelled to classify the wheat grains into bread or durum. The ANN model is trained with 180 grains and its accuracy tested with 20 grains from a total of 200 wheat grains. Seven input parameters that are most effective on the classifying results are determined using the correlation-based CfsSubsetEval algorithm to simplify the ANN model. The results of the ANN model are compared in terms of accuracy rate. The best result is achieved with a mean absolute error (MAE) of 9.8 × 10 -6 by the simplified ANN model. This shows that the proposed classifier based on computer vision can be successfully exploited to automatically classify a variety of grains. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Asteroseismology of hybrid δ Scuti-γ Doradus pulsating stars

NASA Astrophysics Data System (ADS)

Sánchez Arias, J. P.; Córsico, A. H.; Althaus, L. G.

2017-01-01

Context. Hybrid δ Scuti-γ Doradus pulsating stars show acoustic (p) oscillation modes typical of δ Scuti variable stars, and gravity (g) pulsation modes characteristic of γ Doradus variable stars simultaneously excited. Observations from space missions such as MOST, CoRoT, and Kepler have revealed a large number of hybrid δ Scuti-γ Doradus pulsators, thus paving the way for an exciting new channel of asteroseismic studies. Aims: We perform detailed asteroseismological modelling of five hybrid δ Scuti-γ Doradus stars. Methods: A grid-based modeling approach was employed to sound the internal structure of the target stars using stellar models ranging from the zero-age main sequence to the terminal-age main sequence, varying parameters such as stellar mass, effective temperature, metallicity and core overshooting. Their adiabatic radial (ℓ = 0) and non-radial (ℓ = 1,2,3) p and g mode periods were computed. Two model-fitting procedures were used to search for asteroseismological models that best reproduce the observed pulsation spectra of each target star. Results: We derive the fundamental parameters and the evolutionary status of five hybrid δ Scuti-γ Doradus variable stars recently observed by the CoRoT and Kepler space missions: CoRoT 105733033, CoRoT 100866999, KIC 11145123, KIC 9244992, and HD 49434. The asteroseismological model for each star results from different criteria of model selection, in which we take full advantage of the richness of periods that characterises the pulsation spectra for this kind of star.

Phenomenological model of visual acuity

NASA Astrophysics Data System (ADS)

Gómez-Pedrero, José A.; Alonso, José

2016-12-01

We propose in this work a model for describing visual acuity (V) as a function of defocus and pupil diameter. Although the model is mainly based on geometrical optics, it also incorporates nongeometrical effects phenomenologically. Compared to similar visual acuity models, the proposed one considers the effect of astigmatism and the variability of best corrected V among individuals; it also takes into account the accommodation and the "tolerance to defocus," the latter through a phenomenological parameter. We have fitted the model to the V data provided in the works of Holladay et al. and Peters, showing the ability of this model to accurately describe the variation of V against blur and pupil diameter. We have also performed a comparison between the proposed model and others previously published in the literature. The model is mainly intended for use in the design of ophthalmic compensations, but it can also be useful in other fields such as visual ergonomics, design of visual tests, and optical instrumentation.

Modeling birds on wires.

PubMed

Aydoğdu, A; Frasca, P; D'Apice, C; Manzo, R; Thornton, J M; Gachomo, B; Wilson, T; Cheung, B; Tariq, U; Saidel, W; Piccoli, B

2017-02-21

In this paper we introduce a mathematical model to study the group dynamics of birds resting on wires. The model is agent-based and postulates attraction-repulsion forces between the interacting birds: the interactions are "topological", in the sense that they involve a given number of neighbors irrespective of their distance. The model is first mathematically analyzed and then simulated to study its main properties: we observe that the model predicts birds to be more widely spaced near the borders of each group. We compare the results from the model with experimental data, derived from the analysis of pictures of pigeons and starlings taken in New Jersey: two different image elaboration protocols allow us to establish a good agreement with the model and to quantify its main parameters. We also discuss the potential handedness of the birds, by analyzing the group organization features and the group dynamics at the arrival of new birds. Finally, we propose a more refined mathematical model that describes landing and departing birds by suitable stochastic processes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Extending amulti-scale parameter regionalization (MPR) method by introducing parameter constrained optimization and flexible transfer functions

NASA Astrophysics Data System (ADS)

Klotz, Daniel; Herrnegger, Mathew; Schulz, Karsten

2015-04-01

A multi-scale parameter-estimation method, as presented by Samaniego et al. (2010), is implemented and extended for the conceptual hydrological model COSERO. COSERO is a HBV-type model that is specialized for alpine-environments, but has been applied over a wide range of basins all over the world (see: Kling et al., 2014 for an overview). Within the methodology available small-scale information (DEM, soil texture, land cover, etc.) is used to estimate the coarse-scale model parameters by applying a set of transfer-functions (TFs) and subsequent averaging methods, whereby only TF hyper-parameters are optimized against available observations (e.g. runoff data). The parameter regionalisation approach was extended in order to allow for a more meta-heuristical handling of the transfer-functions. The two main novelties are: 1. An explicit introduction of constrains into parameter estimation scheme: The constraint scheme replaces invalid parts of the transfer-function-solution space with valid solutions. It is inspired by applications in evolutionary algorithms and related to the combination of learning and evolution. This allows the consideration of physical and numerical constraints as well as the incorporation of a priori modeller-experience into the parameter estimation. 2. Spline-based transfer-functions: Spline-based functions enable arbitrary forms of transfer-functions: This is of importance since in many cases the general relationship between sub-grid information and parameters are known, but not the form of the transfer-function itself. The contribution presents the results and experiences with the adopted method and the introduced extensions. Simulation are performed for the pre-alpine/alpine Traisen catchment in Lower Austria. References: Samaniego, L., Kumar, R., Attinger, S. (2010): Multiscale parameter regionalization of a grid-based hydrologic model at the mesoscale, Water Resour. Res., doi: 10.1029/2008WR007327 Kling, H., Stanzel, P., Fuchs, M., and Nachtnebel, H. P. (2014): Performance of the COSERO precipitation-runoff model under non-stationary conditions in basins with different climates, Hydrolog. Sci. J., doi: 10.1080/02626667.2014.959956.

Modelling of the physico-chemical behaviour of clay minerals with a thermo-kinetic model taking into account particles morphology in compacted material.

NASA Astrophysics Data System (ADS)

Sali, D.; Fritz, B.; Clément, C.; Michau, N.

2003-04-01

Modelling of fluid-mineral interactions is largely used in Earth Sciences studies to better understand the involved physicochemical processes and their long-term effect on the materials behaviour. Numerical models simplify the processes but try to preserve their main characteristics. Therefore the modelling results strongly depend on the data quality describing initial physicochemical conditions for rock materials, fluids and gases, and on the realistic way of processes representations. The current geo-chemical models do not well take into account rock porosity and permeability and the particle morphology of clay minerals. In compacted materials like those considered as barriers in waste repositories, low permeability rocks like mudstones or compacted powders will be used : they contain mainly fine particles and the geochemical models used for predicting their interactions with fluids tend to misjudge their surface areas, which are fundamental parameters in kinetic modelling. The purpose of this study was to improve how to take into account the particles morphology in the thermo-kinetic code KINDIS and the reactive transport code KIRMAT. A new function was integrated in these codes, considering the reaction surface area as a volume depending parameter and the calculated evolution of the mass balance in the system was coupled with the evolution of reactive surface areas. We made application exercises for numerical validation of these new versions of the codes and the results were compared with those of the pre-existing thermo-kinetic code KINDIS. Several points are highlighted. Taking into account reactive surface area evolution during simulation modifies the predicted mass transfers related to fluid-minerals interactions. Different secondary mineral phases are also observed during modelling. The evolution of the reactive surface parameter helps to solve the competition effects between different phases present in the system which are all able to fix the chemical elements mobilised by the water-minerals interaction processes. To validate our model we simulated the compacted bentonite (MX80) studied for engineered barriers for radioactive waste confinement and mainly composed of Na-Ca-montmorillonite. The study of particles morphology and reactive surfaces evolutions reveals that aqueous ions have a complex behaviour, especially when competitions between various mineral phases occur. In that case, our model predicts a preferential precipitation of finest particles, favouring smectites instead of zeolites. This work is a part of a PhD Thesis supported by Andra, the French Radioactive Waste Management Agency.

A comprehensive evaluation of various sensitivity analysis methods: A case study with a hydrological model

DOE PAGES

Gan, Yanjun; Duan, Qingyun; Gong, Wei; ...

2014-01-01

Sensitivity analysis (SA) is a commonly used approach for identifying important parameters that dominate model behaviors. We use a newly developed software package, a Problem Solving environment for Uncertainty Analysis and Design Exploration (PSUADE), to evaluate the effectiveness and efficiency of ten widely used SA methods, including seven qualitative and three quantitative ones. All SA methods are tested using a variety of sampling techniques to screen out the most sensitive (i.e., important) parameters from the insensitive ones. The Sacramento Soil Moisture Accounting (SAC-SMA) model, which has thirteen tunable parameters, is used for illustration. The South Branch Potomac River basin nearmore » Springfield, West Virginia in the U.S. is chosen as the study area. The key findings from this study are: (1) For qualitative SA methods, Correlation Analysis (CA), Regression Analysis (RA), and Gaussian Process (GP) screening methods are shown to be not effective in this example. Morris One-At-a-Time (MOAT) screening is the most efficient, needing only 280 samples to identify the most important parameters, but it is the least robust method. Multivariate Adaptive Regression Splines (MARS), Delta Test (DT) and Sum-Of-Trees (SOT) screening methods need about 400–600 samples for the same purpose. Monte Carlo (MC), Orthogonal Array (OA) and Orthogonal Array based Latin Hypercube (OALH) are appropriate sampling techniques for them; (2) For quantitative SA methods, at least 2777 samples are needed for Fourier Amplitude Sensitivity Test (FAST) to identity parameter main effect. McKay method needs about 360 samples to evaluate the main effect, more than 1000 samples to assess the two-way interaction effect. OALH and LPτ (LPTAU) sampling techniques are more appropriate for McKay method. For the Sobol' method, the minimum samples needed are 1050 to compute the first-order and total sensitivity indices correctly. These comparisons show that qualitative SA methods are more efficient but less accurate and robust than quantitative ones.« less

SARTools: A DESeq2- and EdgeR-Based R Pipeline for Comprehensive Differential Analysis of RNA-Seq Data.

PubMed

Varet, Hugo; Brillet-Guéguen, Loraine; Coppée, Jean-Yves; Dillies, Marie-Agnès

2016-01-01

Several R packages exist for the detection of differentially expressed genes from RNA-Seq data. The analysis process includes three main steps, namely normalization, dispersion estimation and test for differential expression. Quality control steps along this process are recommended but not mandatory, and failing to check the characteristics of the dataset may lead to spurious results. In addition, normalization methods and statistical models are not exchangeable across the packages without adequate transformations the users are often not aware of. Thus, dedicated analysis pipelines are needed to include systematic quality control steps and prevent errors from misusing the proposed methods. SARTools is an R pipeline for differential analysis of RNA-Seq count data. It can handle designs involving two or more conditions of a single biological factor with or without a blocking factor (such as a batch effect or a sample pairing). It is based on DESeq2 and edgeR and is composed of an R package and two R script templates (for DESeq2 and edgeR respectively). Tuning a small number of parameters and executing one of the R scripts, users have access to the full results of the analysis, including lists of differentially expressed genes and a HTML report that (i) displays diagnostic plots for quality control and model hypotheses checking and (ii) keeps track of the whole analysis process, parameter values and versions of the R packages used. SARTools provides systematic quality controls of the dataset as well as diagnostic plots that help to tune the model parameters. It gives access to the main parameters of DESeq2 and edgeR and prevents untrained users from misusing some functionalities of both packages. By keeping track of all the parameters of the analysis process it fits the requirements of reproducible research.

Understanding mechanisms that control fish spawning and larval recruitment: Parameter optimization of an Eulerian model (SEAPODYM-SP) with Peruvian anchovy and sardine eggs and larvae data

NASA Astrophysics Data System (ADS)

Hernandez, Olga; Lehodey, Patrick; Senina, Inna; Echevin, Vincent; Ayón, Patricia; Bertrand, Arnaud; Gaspar, Philippe

2014-04-01

The Spatial Ecosystem And Populations Dynamics Model "SEAPODYM", based on a system of Eulerian equations and initially developed for large pelagic fish (e.g., tuna), was modified to describe spawning habitat and eggs and larvae dynamics of small pelagic fish. The spawning habitat is critical since it controls the initial recruitment of larvae and the subsequent spatio-temporal variability of natural mortality during their drift with currents. A robust statistical approach based on Maximum Likelihood Estimation is presented to optimize the model parameters defining the spawning habitat and the eggs and larvae dynamics. To improve parameterization, eggs and larvae density observations are assimilated in the model. The model and its associated optimization approach allow investigating the significance of the mechanisms proposed to control fish spawning habitat and larval recruitment: temperature, prey abundance, trade-off between prey and predators, and retention and dispersion processes. An application to the Peruvian anchovy (Engraulis ringens) and sardine (Sardinops sagax) illustrates the ability of the model to simulate the main features of spatial dynamics of these two species in the Humboldt Current System. For both species, in climatological conditions, the main observed spatial patterns are well reproduced and are explained by the impact of prey and predator abundance and by physical retention with currents, while temperature has a lower impact. In agreement with observations, sardine larvae are mainly predicted in the northern part of the Peruvian shelf (5-10°S), while anchovy larvae extend further south. Deoxygenation, which can potentially limit the accessibility of adult fish to spawning areas, does not appear to have an impact in our model setting. Conversely, the observed seasonality in spawning activity, especially the spawning rest period in austral autumn, is not well simulated. It is proposed that this seasonal cycle is more likely driven by the spatio-temporal dynamics of adult fish constituting the spawning biomass and not yet included in the model.

Using aerial images for establishing a workflow for the quantification of water management measures

NASA Astrophysics Data System (ADS)

Leuschner, Annette; Merz, Christoph; van Gasselt, Stephan; Steidl, Jörg

2017-04-01

Quantified landscape characteristics, such as morphology, land use or hydrological conditions, play an important role for hydrological investigations as landscape parameters directly control the overall water balance. A powerful assimilation and geospatial analysis of remote sensing datasets in combination with hydrological modeling allows to quantify landscape parameters and water balances efficiently. This study focuses on the development of a workflow to extract hydrologically relevant data from aerial image datasets and derived products in order to allow an effective parametrization of a hydrological model. Consistent and self-contained data source are indispensable for achieving reasonable modeling results. In order to minimize uncertainties and inconsistencies, input parameters for modeling should be extracted from one remote-sensing dataset mainly if possbile. Here, aerial images have been chosen because of their high spatial and spectral resolution that permits the extraction of various model relevant parameters, like morphology, land-use or artificial drainage-systems. The methodological repertoire to extract environmental parameters range from analyses of digital terrain models, multispectral classification and segmentation of land use distribution maps and mapping of artificial drainage-systems based on spectral and visual inspection. The workflow has been tested for a mesoscale catchment area which forms a characteristic hydrological system of a young moraine landscape located in the state of Brandenburg, Germany. These dataset were used as input-dataset for multi-temporal hydrological modelling of water balances to detect and quantify anthropogenic and meteorological impacts. ArcSWAT, as a GIS-implemented extension and graphical user input interface for the Soil Water Assessment Tool (SWAT) was chosen. The results of this modeling approach provide the basis for anticipating future development of the hydrological system, and regarding system changes for the adaption of water resource management decisions.

A sensitivity analysis method for the body segment inertial parameters based on ground reaction and joint moment regressor matrices.

PubMed

Futamure, Sumire; Bonnet, Vincent; Dumas, Raphael; Venture, Gentiane

2017-11-07

This paper presents a method allowing a simple and efficient sensitivity analysis of dynamics parameters of complex whole-body human model. The proposed method is based on the ground reaction and joint moment regressor matrices, developed initially in robotics system identification theory, and involved in the equations of motion of the human body. The regressor matrices are linear relatively to the segment inertial parameters allowing us to use simple sensitivity analysis methods. The sensitivity analysis method was applied over gait dynamics and kinematics data of nine subjects and with a 15 segments 3D model of the locomotor apparatus. According to the proposed sensitivity indices, 76 segments inertial parameters out the 150 of the mechanical model were considered as not influent for gait. The main findings were that the segment masses were influent and that, at the exception of the trunk, moment of inertia were not influent for the computation of the ground reaction forces and moments and the joint moments. The same method also shows numerically that at least 90% of the lower-limb joint moments during the stance phase can be estimated only from a force-plate and kinematics data without knowing any of the segment inertial parameters. Copyright © 2017 Elsevier Ltd. All rights reserved.

Sobol's sensitivity analysis for a fuel cell stack assembly model with the aid of structure-selection techniques

NASA Astrophysics Data System (ADS)

Zhang, Wei; Cho, Chongdu; Piao, Changhao; Choi, Hojoon

2016-01-01

This paper presents a novel method for identifying the main parameters affecting the stress distribution of the components used in assembly modeling of proton exchange membrane fuel cell (PEMFC) stack. This method is a combination of an approximation model and Sobol's method, which allows a fast global sensitivity analysis for a set of uncertain parameters using only a limited number of calculations. Seven major parameters, i.e., Young's modulus of the end plate and the membrane electrode assembly (MEA), the contact stiffness between the MEA and bipolar plate (BPP), the X and Y positions of the bolts, the pressure of each bolt, and the thickness of the end plate, are investigated regarding their effect on four metrics, i.e., the maximum stresses of the MEA, BPP, and end plate, and the stress distribution percentage of the MEA. The analysis reveals the individual effects of each parameter and its interactions with the other parameters. The results show that the X position of a bolt has a major influence on the maximum stresses of the BPP and end plate, whereas the thickness of the end plate has the strongest effect on both the maximum stress and the stress distribution percentage of the MEA.

Genetic algorithm based input selection for a neural network function approximator with applications to SSME health monitoring

NASA Technical Reports Server (NTRS)

Peck, Charles C.; Dhawan, Atam P.; Meyer, Claudia M.

1991-01-01

A genetic algorithm is used to select the inputs to a neural network function approximator. In the application considered, modeling critical parameters of the space shuttle main engine (SSME), the functional relationship between measured parameters is unknown and complex. Furthermore, the number of possible input parameters is quite large. Many approaches have been used for input selection, but they are either subjective or do not consider the complex multivariate relationships between parameters. Due to the optimization and space searching capabilities of genetic algorithms they were employed to systematize the input selection process. The results suggest that the genetic algorithm can generate parameter lists of high quality without the explicit use of problem domain knowledge. Suggestions for improving the performance of the input selection process are also provided.

Development of a SMA-Based, Slat-Gap Filler for Airframe Noise Reduction

NASA Technical Reports Server (NTRS)

Turner, Travis L.; Long, David L.

2015-01-01

Noise produced by unsteady flow around aircraft structures, termed airframe noise, is an important source of aircraft noise during the approach and landing phases of flight. Conventional leading-edge-slat devices for high lift on typical transport aircraft are a prominent source of airframe noise. Many concepts for slat noise reduction have been investigated. Slat-cove fillers have emerged as an attractive solution, but they maintain the gap flow, leaving some noise production mechanisms unabated, and thus represent a nonoptimal solution. Drooped-leading-edge (DLE) concepts have been proposed as "optimal" because the gap flow is eliminated. The deployed leading edge device is not distinct and separate from the main wing in DLE concepts and the high-lift performance suffers at high angles of attack (alpha) as a consequence. Elusive high-alpha performance and excessive weight penalty have stymied DLE development. The fact that high-lift performance of DLE systems is only affected at high alpha suggests another concept that simultaneously achieves the high-lift of the baseline airfoil and the noise reduction of DLE concepts. The concept involves utilizing a conventional leading-edge slat device and a deformable structure that is deployed from the leading edge of the main wing and closes the gap between the slat and main wing, termed a slat-gap filler (SGF). The deployable structure consists of a portion of the skin of the main wing and it is driven in conjunction with the slat during deployment and retraction. Benchtop models have been developed to assess the feasibility and to study important parameters. Computational models have assisted in the bench-top model design and provided valuable insight in the parameter space as well as the feasibility.

No Evidence for Extensions to the Standard Cosmological Model.

PubMed

Heavens, Alan; Fantaye, Yabebal; Sellentin, Elena; Eggers, Hans; Hosenie, Zafiirah; Kroon, Steve; Mootoovaloo, Arrykrishna

2017-09-08

We compute the Bayesian evidence for models considered in the main analysis of Planck cosmic microwave background data. By utilizing carefully defined nearest-neighbor distances in parameter space, we reuse the Monte Carlo Markov chains already produced for parameter inference to compute Bayes factors B for many different model-data set combinations. The standard 6-parameter flat cold dark matter model with a cosmological constant (ΛCDM) is favored over all other models considered, with curvature being mildly favored only when cosmic microwave background lensing is not included. Many alternative models are strongly disfavored by the data, including primordial correlated isocurvature models (lnB=-7.8), nonzero scalar-to-tensor ratio (lnB=-4.3), running of the spectral index (lnB=-4.7), curvature (lnB=-3.6), nonstandard numbers of neutrinos (lnB=-3.1), nonstandard neutrino masses (lnB=-3.2), nonstandard lensing potential (lnB=-4.6), evolving dark energy (lnB=-3.2), sterile neutrinos (lnB=-6.9), and extra sterile neutrinos with a nonzero scalar-to-tensor ratio (lnB=-10.8). Other models are less strongly disfavored with respect to flat ΛCDM. As with all analyses based on Bayesian evidence, the final numbers depend on the widths of the parameter priors. We adopt the priors used in the Planck analysis, while performing a prior sensitivity analysis. Our quantitative conclusion is that extensions beyond the standard cosmological model are disfavored by Planck data. Only when newer Hubble constant measurements are included does ΛCDM become disfavored, and only mildly, compared with a dynamical dark energy model (lnB∼+2).

No Evidence for Extensions to the Standard Cosmological Model

NASA Astrophysics Data System (ADS)

Heavens, Alan; Fantaye, Yabebal; Sellentin, Elena; Eggers, Hans; Hosenie, Zafiirah; Kroon, Steve; Mootoovaloo, Arrykrishna

2017-09-01

We compute the Bayesian evidence for models considered in the main analysis of Planck cosmic microwave background data. By utilizing carefully defined nearest-neighbor distances in parameter space, we reuse the Monte Carlo Markov chains already produced for parameter inference to compute Bayes factors B for many different model-data set combinations. The standard 6-parameter flat cold dark matter model with a cosmological constant (Λ CDM ) is favored over all other models considered, with curvature being mildly favored only when cosmic microwave background lensing is not included. Many alternative models are strongly disfavored by the data, including primordial correlated isocurvature models (ln B =-7.8 ), nonzero scalar-to-tensor ratio (ln B =-4.3 ), running of the spectral index (ln B =-4.7 ), curvature (ln B =-3.6 ), nonstandard numbers of neutrinos (ln B =-3.1 ), nonstandard neutrino masses (ln B =-3.2 ), nonstandard lensing potential (ln B =-4.6 ), evolving dark energy (ln B =-3.2 ), sterile neutrinos (ln B =-6.9 ), and extra sterile neutrinos with a nonzero scalar-to-tensor ratio (ln B =-10.8 ). Other models are less strongly disfavored with respect to flat Λ CDM . As with all analyses based on Bayesian evidence, the final numbers depend on the widths of the parameter priors. We adopt the priors used in the Planck analysis, while performing a prior sensitivity analysis. Our quantitative conclusion is that extensions beyond the standard cosmological model are disfavored by Planck data. Only when newer Hubble constant measurements are included does Λ CDM become disfavored, and only mildly, compared with a dynamical dark energy model (ln B ˜+2 ).

Modulation instability in high power laser amplifiers.

PubMed

Rubenchik, Alexander M; Turitsyn, Sergey K; Fedoruk, Michail P

2010-01-18

The modulation instability (MI) is one of the main factors responsible for the degradation of beam quality in high-power laser systems. The so-called B-integral restriction is commonly used as the criteria for MI control in passive optics devices. For amplifiers the adiabatic model, assuming locally the Bespalov-Talanov expression for MI growth, is commonly used to estimate the destructive impact of the instability. We present here the exact solution of MI development in amplifiers. We determine the parameters which control the effect of MI in amplifiers and calculate the MI growth rate as a function of those parameters. The safety range of operational parameters is presented. The results of the exact calculations are compared with the adiabatic model, and the range of validity of the latest is determined. We demonstrate that for practical situations the adiabatic approximation noticeably overestimates MI. The additional margin of laser system design is quantified.

Competing phases, phase separation, and coexistence in the extended one-dimensional bosonic Hubbard model

DOE PAGES

Batrouni, G. G.; Rousseau, V. G.; Scalettar, R. T.; ...

2014-11-17

Here, we study the phase diagram of the one-dimensional bosonic Hubbard model with contact (U) and near neighbor (V ) interactions focusing on the gapped Haldane insulating (HI) phase which is characterized by an exotic nonlocal order parameter. The parameter regime (U, V and μ) where this phase exists and how it competes with other phases such as the supersolid (SS) phase, is incompletely understood. We use the Stochastic Green Function quantum Monte Carlo algorithm as well as the density matrix renormalization group to map out the phase diagram. The HI exists only at = 1, the SS phase existsmore » for a very wide range of parameters (including commensurate fillings) and displays power law decay in the one body Green function were our main conclusions. Additionally, we show that at fixed integer density, the system exhibits phase separation in the (U, V ) plane.« less

Fault detection in heavy duty wheels by advanced vibration processing techniques and lumped parameter modeling

NASA Astrophysics Data System (ADS)

Malago`, M.; Mucchi, E.; Dalpiaz, G.

2016-03-01

Heavy duty wheels are used in applications such as automatic vehicles and are mainly composed of a polyurethane tread glued to a cast iron hub. In the manufacturing process, the adhesive application between tread and hub is a critical assembly phase, since it is completely made by an operator and a contamination of the bond area may happen. Furthermore, the presence of rust on the hub surface can contribute to worsen the adherence interface, reducing the operating life. In this scenario, a quality control procedure for fault detection to be used at the end of the manufacturing process has been developed. This procedure is based on vibration processing techniques and takes advantages of the results of a lumped parameter model. Indicators based on cyclostationarity can be considered as key parameters to be adopted in a monitoring test station at the end of the production line due to their not deterministic characteristics.

Numerical investigation of pulmonary drug delivery under mechanical ventilation conditions

NASA Astrophysics Data System (ADS)

Banerjee, Arindam; van Rhein, Timothy

2012-11-01

The effects of mechanical ventilation waveform on fluid flow and particle deposition were studied in a computer model of the human airways. The frequency with which aerosolized drugs are delivered to mechanically ventilated patients demonstrates the importance of understanding the effects of ventilation parameters. This study focuses specifically on the effects of mechanical ventilation waveforms using a computer model of the airways of patient undergoing mechanical ventilation treatment from the endotracheal tube to generation G7. Waveforms were modeled as those commonly used by commercial mechanical ventilators. Turbulence was modeled with LES. User defined particle force models were used to model the drag force with the Cunningham correction factor, the Saffman lift force, and Brownian motion force. The endotracheal tube (ETT) was found to be an important geometric feature, causing a fluid jet towards the right main bronchus, increased turbulence, and a recirculation zone in the right main bronchus. In addition to the enhanced deposition seen at the carinas of the airway bifurcations, enhanced deposition was also seen in the right main bronchus due to impaction and turbulent dispersion resulting from the fluid structures created by the ETT. Authors acknowledge financial support through University of Missouri Research Board Award.

The review of dynamic monitoring technology for crop growth

NASA Astrophysics Data System (ADS)

Zhang, Hong-wei; Chen, Huai-liang; Zou, Chun-hui; Yu, Wei-dong

2010-10-01

In this paper, crop growth monitoring methods are described elaborately. The crop growth models, Netherlands-Wageningen model system, the United States-GOSSYM model and CERES models, Australia APSIM model and CCSODS model system in China, are introduced here more focus on the theories of mechanism, applications, etc. The methods and application of remote sensing monitoring methods, which based on leaf area index (LAI) and biomass were proposed by different scholars at home and abroad, are highly stressed in the paper. The monitoring methods of remote sensing coupling with crop growth models are talked out at large, including the method of "forced law" which using remote sensing retrieval state parameters as the crop growth model parameters input, and then to enhance the dynamic simulation accuracy of crop growth model and the method of "assimilation of Law" which by reducing the gap difference between the value of remote sensing retrieval and the simulated values of crop growth model and thus to estimate the initial value or parameter values to increasing the simulation accuracy. At last, the developing trend of monitoring methods are proposed based on the advantages and shortcomings in previous studies, it is assured that the combination of remote sensing with moderate resolution data of FY-3A, MODIS, etc., crop growth model, "3S" system and observation in situ are the main methods in refinement of dynamic monitoring and quantitative assessment techniques for crop growth in future.

Warpage analysis in injection moulding process

NASA Astrophysics Data System (ADS)

Hidayah, M. H. N.; Shayfull, Z.; Nasir, S. M.; Fathullah, M.; Hazwan, M. H. M.

2017-09-01

This study was concentrated on the effects of process parameters in plastic injection moulding process towards warpage problem by using Autodesk Moldflow Insight (AMI) software for the simulation. In this study, plastic dispenser of dental floss has been analysed with thermoplastic material of Polypropylene (PP) used as the moulded material and details properties of 80 Tonne Nessei NEX 1000 injection moulding machine also has been used in this study. The variable parameters of the process are packing pressure, packing time, melt temperature and cooling time. Minimization of warpage obtained from the optimization and analysis data from the Design Expert software. Integration of Response Surface Methodology (RSM), Center Composite Design (CCD) with polynomial models that has been obtained from Design of Experiment (DOE) is the method used in this study. The results show that packing pressure is the main factor that will contribute to the formation of warpage in x-axis and y-axis. While in z-axis, the main factor is melt temperature and packing time is the less significant among the four parameters in x, y and z-axes. From optimal processing parameter, the value of warpage in x, y and z-axis have been optimised by 21.60%, 26.45% and 24.53%, respectively.

Stellar Parameters in an Instant with Machine Learning. Application to Kepler LEGACY Targets

NASA Astrophysics Data System (ADS)

Bellinger, Earl P.; Angelou, George C.; Hekker, Saskia; Basu, Sarbani; Ball, Warrick H.; Guggenberger, Elisabet

2017-10-01

With the advent of dedicated photometric space missions, the ability to rapidly process huge catalogues of stars has become paramount. Bellinger and Angelou et al. [1] recently introduced a new method based on machine learning for inferring the stellar parameters of main-sequence stars exhibiting solar-like oscillations. The method makes precise predictions that are consistent with other methods, but with the advantages of being able to explore many more parameters while costing practically no time. Here we apply the method to 52 so-called "LEGACY" main-sequence stars observed by the Kepler space mission. For each star, we present estimates and uncertainties of mass, age, radius, luminosity, core hydrogen abundance, surface helium abundance, surface gravity, initial helium abundance, and initial metallicity as well as estimates of their evolutionary model parameters of mixing length, overshooting coeffcient, and diffusion multiplication factor. We obtain median uncertainties in stellar age, mass, and radius of 14.8%, 3.6%, and 1.7%, respectively. The source code for all analyses and for all figures appearing in this manuscript can be found electronically at https://github.com/earlbellinger/asteroseismology

The cultural implications of growth: Modeling nonlinear interaction of trait selection and population dynamics

NASA Astrophysics Data System (ADS)

Antoci, Angelo; Galeotti, Marcello; Russu, Paolo; Luigi Sacco, Pier

2018-05-01

In this paper, we study a nonlinear model of the interaction between trait selection and population dynamics, building on previous work of Ghirlanda et al. [Theor. Popul. Biol. 77, 181-188 (2010)] and Antoci et al. [Commun. Nonlinear Sci. Numer. Simul. 58, 92-106 (2018)]. We establish some basic properties of the model dynamics and present some simulations of the fine-grained structure of alternative dynamic regimes for chosen combinations of parameters. The role of the parameters that govern the reinforcement/corruption of maladaptive vs. adaptive traits is of special importance in determining the model's dynamic evolution. The main implication of this result is the need to pay special attention to the structural forces that may favor the emergence and consolidation of maladaptive traits in contemporary socio-economies, as it is the case, for example, for the stimulation of dysfunctional consumption habits and lifestyles in the pursuit of short-term profits.

Polarization properties and microfacet-based modelling of white, grey and coloured matte diffuse reflection standards

NASA Astrophysics Data System (ADS)

Quast, T.; Schirmacher, A.; Hauer, K.-O.; Koo, A.

2018-02-01

To elucidate the influence of polarization in diffuse reflectometry, we performed a series of measurements in several bidirectional geometries and determined the Stokes parameters of the diffusely reflected radiation. Different types of matte reflection standards were used, including several common white standards and ceramic colour standards. The dependence of the polarization on the sample type, wavelength and geometry have been studied systematically, the main influence factors have been identified: The effect is largest at large angles of incidence or detection and at wavelengths where the magnitude of the reflectance is small. The results for the colour standards have been modelled using a microfacet-based reflection theory which is derived from the well-known model of Torrance and Sparrow. Although the theory is very simple and only has three free parameters, the agreement with the measured data is very good, all essential features of the data can be reproduced by the model.

Numerical modeling and preliminary validation of drag-based vertical axis wind turbine

NASA Astrophysics Data System (ADS)

Krysiński, Tomasz; Buliński, Zbigniew; Nowak, Andrzej J.

2015-03-01

The main purpose of this article is to verify and validate the mathematical description of the airflow around a wind turbine with vertical axis of rotation, which could be considered as representative for this type of devices. Mathematical modeling of the airflow around wind turbines in particular those with the vertical axis is a problematic matter due to the complex nature of this highly swirled flow. Moreover, it is turbulent flow accompanied by a rotation of the rotor and the dynamic boundary layer separation. In such conditions, the key aspects of the mathematical model are accurate turbulence description, definition of circular motion as well as accompanying effects like centrifugal force or the Coriolis force and parameters of spatial and temporal discretization. The paper presents the impact of the different simulation parameters on the obtained results of the wind turbine simulation. Analysed models have been validated against experimental data published in the literature.

Fundamental Rotorcraft Acoustic Modeling From Experiments (FRAME)

NASA Technical Reports Server (NTRS)

Greenwood, Eric

2011-01-01

A new methodology is developed for the construction of helicopter source noise models for use in mission planning tools from experimental measurements of helicopter external noise radiation. The models are constructed by employing a parameter identification method to an assumed analytical model of the rotor harmonic noise sources. This new method allows for the identification of individual rotor harmonic noise sources and allows them to be characterized in terms of their individual non-dimensional governing parameters. The method is applied to both wind tunnel measurements and ground noise measurements of two-bladed rotors. The method is shown to match the parametric trends of main rotor harmonic noise, allowing accurate estimates of the dominant rotorcraft noise sources to be made for operating conditions based on a small number of measurements taken at different operating conditions. The ability of this method to estimate changes in noise radiation due to changes in ambient conditions is also demonstrated.

Use of Artificial Neural Networks to Examine Parameters Affecting the Immobilization of Streptokinase in Chitosan

PubMed Central

Modaresi, Seyed Mohamad Sadegh; Faramarzi, Mohammad Ali; Soltani, Arash; Baharifar, Hadi; Amani, Amir

2014-01-01

Streptokinase is a potent fibrinolytic agent which is widely used in treatment of deep vein thrombosis (DVT), pulmonary embolism (PE) and acute myocardial infarction (MI). Major limitation of this enzyme is its short biological half-life in the blood stream. Our previous report showed that complexing streptokinase with chitosan could be a solution to overcome this limitation. The aim of this research was to establish an artificial neural networks (ANNs) model for identifying main factors influencing the loading efficiency of streptokinase, as an essential parameter determining efficacy of the enzyme. Three variables, namely, chitosan concentration, buffer pH and enzyme concentration were considered as input values and the loading efficiency was used as output. Subsequently, the experimental data were modeled and the model was validated against a set of unseen data. The developed model indicated chitosan concentration as probably the most important factor, having reverse effect on the loading efficiency. PMID:25587327

The cultural implications of growth: Modeling nonlinear interaction of trait selection and population dynamics.

PubMed

Antoci, Angelo; Galeotti, Marcello; Russu, Paolo; Luigi Sacco, Pier

2018-05-01

In this paper, we study a nonlinear model of the interaction between trait selection and population dynamics, building on previous work of Ghirlanda et al. [Theor. Popul. Biol. 77, 181-188 (2010)] and Antoci et al. [Commun. Nonlinear Sci. Numer. Simul. 58, 92-106 (2018)]. We establish some basic properties of the model dynamics and present some simulations of the fine-grained structure of alternative dynamic regimes for chosen combinations of parameters. The role of the parameters that govern the reinforcement/corruption of maladaptive vs. adaptive traits is of special importance in determining the model's dynamic evolution. The main implication of this result is the need to pay special attention to the structural forces that may favor the emergence and consolidation of maladaptive traits in contemporary socio-economies, as it is the case, for example, for the stimulation of dysfunctional consumption habits and lifestyles in the pursuit of short-term profits.

Study of the influence of selected anisotropic parameter in the Barlat's model on the drawpiece shape

NASA Astrophysics Data System (ADS)

Kaldunski, Pawel; Kukielka, Leon; Patyk, Radoslaw; Kulakowska, Agnieszka; Bohdal, Lukasz; Chodor, Jaroslaw; Kukielka, Krzysztof

2018-05-01

In this paper, the numerical analysis and computer simulation of deep drawing process has been presented. The incremental model of the process in updated Lagrangian formulation with the regard of the geometrical and physical nonlinearity has been evaluated by variational and the finite element methods. The Frederic Barlat's model taking into consideration the anisotropy of materials in three main and six tangents directions has been used. The work out application in Ansys/Ls-Dyna program allows complex step by step analysis and prognoses: the shape, dimensions and state stress and strains of drawpiece. The paper presents the influence of selected anisotropic parameter in the Barlat's model on the drawpiece shape, which includes: height, sheet thickness and maximum drawing force. The important factors determining the proper formation of drawpiece and the ways of their determination have been described.

On storm movement and its applications

NASA Astrophysics Data System (ADS)

Niemczynowicz, Janusz

Rainfall-runoff models applicable for design and analysis of sewage systems in urban areas are further developed in order to represent better different physical processes going on on an urban catchment. However, one important part of the modelling procedure, the generation of the rainfall input is still a weak point. The main problem is lack of adequate rainfall data which represent temporal and spatial variations of the natural rainfall process. Storm movement is a natural phenomenon which influences urban runoff. However, the rainfall movement and its influence on runoff generation process is not represented in presently available urban runoff simulation models. Physical description of the rainfall movement and its parameters is given based on detailed measurements performed on twelve gauges in Lund, Sweden. The paper discusses the significance of the rainfall movement on the runoff generation process and gives suggestions how the rainfall movement parameters may be used in runoff modelling.

X(1835), X(2120), and X(2370) in flux tube models

NASA Astrophysics Data System (ADS)

Deng, Chengrong; Ping, Jialun; Yang, Youchang; Wang, Fan

2012-07-01

Nonstrange hexaquark state q3q¯3 spectrum is systematically studied by using the Gaussian expansion method in flux tube models with a six-body confinement potential. All the model parameters are fixed by baryon properties, so the calculation of hexaquark state q3q¯3 is parameter-free. It is found that some ground states of q3q¯3 are stable against disintegrating into a baryon and an anti-baryon. The main components of X(1835) and X(2370), which are observed in the radiative decay of J/ψ by BES collaboration, can be described as compact hexaquark states N8N¯8 and Δ8Δ¯8 with quantum numbers IGJPC=0+0-+, respectively. These bound states should be color confinement resonances with three-dimensional configurations similar to a rugby ball, however, X(2120) can not be accommodated in this model approach.

PROGEN: An automated modelling algorithm for the generation of complete protein structures from the α-carbon atomic coordinates

NASA Astrophysics Data System (ADS)

Mandal, Chhabinath; Linthicum, D. Scott

1993-04-01

A modelling algorithm (PROGEN) for the generation of complete protein atomic coordinates from only the α-carbon coordinates is described. PROGEN utilizes an optimal geometry parameter (OGP) database for the positioning of atoms for each amino acid of the polypeptide model. The OGP database was established by examining the statistical correlations between 23 different intra-peptide and inter-peptide geometric parameters relative to the α-carbon distances for each amino acid in a library of 19 known proteins from the Brookhaven Protein Database (BPDB). The OGP files for specific amino acids and peptides were used to generate the atomic positions, with respect to α-carbons, for main-chain and side-chain atoms in the modelled structure. Refinement of the initial model was accomplished using energy minimization (EM) and molecular dynamics techniques. PROGEN was tested using 60 known proteins in the BPDB, representing a wide spectrum of primary and secondary structures. Comparison between PROGEN models and BPDB crystal reference structures gave r.m.s.d. values for peptide main-chain atoms between 0.29 and 0.76 Å, with a grand average of 0.53 Å for all 60 models. The r.m.s.d. for all non-hydrogen atoms ranged between 1.44 and 1.93 Å for the 60 polypeptide models. PROGEN was also able to make the correct assignment of cis- or trans-proline configurations in the protein structures examined. PROGEN offers a fully automatic building and refinement procedure and requires no special or specific structural considerations for the protein to be modelled.

Numerical analysis of the diffusive mass transport in brain tissues with applications to optical sensors

NASA Astrophysics Data System (ADS)

Neculae, Adrian P.; Otte, Andreas; Curticapean, Dan

2013-03-01

In the brain-cell microenvironment, diffusion plays an important role: apart from delivering glucose and oxygen from the vascular system to brain cells, it also moves informational substances between cells. The brain is an extremely complex structure of interwoven, intercommunicating cells, but recent theoretical and experimental works showed that the classical laws of diffusion, cast in the framework of porous media theory, can deliver an accurate quantitative description of the way molecules are transported through this tissue. The mathematical modeling and the numerical simulations are successfully applied in the investigation of diffusion processes in tissues, replacing the costly laboratory investigations. Nevertheless, modeling must rely on highly accurate information regarding the main parameters (tortuosity, volume fraction) which characterize the tissue, obtained by structural and functional imaging. The usual techniques to measure the diffusion mechanism in brain tissue are the radiotracer method, the real time iontophoretic method and integrative optical imaging using fluorescence microscopy. A promising technique for obtaining the values for characteristic parameters of the transport equation is the direct optical investigation using optical fibers. The analysis of these parameters also reveals how the local geometry of the brain changes with time or under pathological conditions. This paper presents a set of computations concerning the mass transport inside the brain tissue, for different types of cells. By measuring the time evolution of the concentration profile of an injected substance and using suitable fitting procedures, the main parameters characterizing the tissue can be determined. This type of analysis could be an important tool in understanding the functional mechanisms of effective drug delivery in complex structures such as the brain tissue. It also offers possibilities to realize optical imaging methods for in vitro and in vivo measurements using optical fibers. The model also may help in radiotracer biomarker models for the understanding of the mechanism of action of new chemical entities.

Phytoplankton competition and coexistence: Intrinsic ecosystem dynamics and impact of vertical mixing

NASA Astrophysics Data System (ADS)

Perruche, Coralie; Rivière, Pascal; Pondaven, Philippe; Carton, Xavier

2010-04-01

This paper aims at studying analytically the functioning of a very simple ecosystem model with two phytoplankton species. First, using the dynamical system theory, we determine its nonlinear equilibria, their stability and characteristic timescales with a focus on phytoplankton competition. Particular attention is paid to the model sensitivity to parameter change. Then, the influence of vertical mixing and sinking of detritus on the vertically-distributed ecosystem model is investigated. The analytical results reveal a high diversity of ecosystem structures with fixed points and limit cycles that are mainly sensitive to variations of light intensity and total amount of nitrogen matter. The sensitivity to other parameters such as re-mineralisation, growth and grazing rates is also specified. Besides, the equilibrium analysis shows a complete segregation of the two phytoplankton species in the whole parameter space. The embedding of our ecosystem model into a one-dimensional numerical model with diffusion turns out to allow coexistence between phytoplankton species, providing a possible solution to the 'paradox of plankton' in the sense that it prevents the competitive exclusion of one phytoplankton species. These results improve our knowledge of the factors that control the structure and functioning of plankton communities.

Bias correction in the realized stochastic volatility model for daily volatility on the Tokyo Stock Exchange

NASA Astrophysics Data System (ADS)

Takaishi, Tetsuya

2018-06-01

The realized stochastic volatility model has been introduced to estimate more accurate volatility by using both daily returns and realized volatility. The main advantage of the model is that no special bias-correction factor for the realized volatility is required a priori. Instead, the model introduces a bias-correction parameter responsible for the bias hidden in realized volatility. We empirically investigate the bias-correction parameter for realized volatilities calculated at various sampling frequencies for six stocks on the Tokyo Stock Exchange, and then show that the dynamic behavior of the bias-correction parameter as a function of sampling frequency is qualitatively similar to that of the Hansen-Lunde bias-correction factor although their values are substantially different. Under the stochastic diffusion assumption of the return dynamics, we investigate the accuracy of estimated volatilities by examining the standardized returns. We find that while the moments of the standardized returns from low-frequency realized volatilities are consistent with the expectation from the Gaussian variables, the deviation from the expectation becomes considerably large at high frequencies. This indicates that the realized stochastic volatility model itself cannot completely remove bias at high frequencies.

A Computational Model of the Fetal Circulation to Quantify Blood Redistribution in Intrauterine Growth Restriction

PubMed Central

Garcia-Canadilla, Patricia; Rudenick, Paula A.; Crispi, Fatima; Cruz-Lemini, Monica; Palau, Georgina; Camara, Oscar; Gratacos, Eduard; Bijens, Bart H.

2014-01-01

Intrauterine growth restriction (IUGR) due to placental insufficiency is associated with blood flow redistribution in order to maintain delivery of oxygenated blood to the brain. Given that, in the fetus the aortic isthmus (AoI) is a key arterial connection between the cerebral and placental circulations, quantifying AoI blood flow has been proposed to assess this brain sparing effect in clinical practice. While numerous clinical studies have studied this parameter, fundamental understanding of its determinant factors and its quantitative relation with other aspects of haemodynamic remodeling has been limited. Computational models of the cardiovascular circulation have been proposed for exactly this purpose since they allow both for studying the contributions from isolated parameters as well as estimating properties that cannot be directly assessed from clinical measurements. Therefore, a computational model of the fetal circulation was developed, including the key elements related to fetal blood redistribution and using measured cardiac outflow profiles to allow personalization. The model was first calibrated using patient-specific Doppler data from a healthy fetus. Next, in order to understand the contributions of the main parameters determining blood redistribution, AoI and middle cerebral artery (MCA) flow changes were studied by variation of cerebral and peripheral-placental resistances. Finally, to study how this affects an individual fetus, the model was fitted to three IUGR cases with different degrees of severity. In conclusion, the proposed computational model provides a good approximation to assess blood flow changes in the fetal circulation. The results support that while MCA flow is mainly determined by a fall in brain resistance, the AoI is influenced by a balance between increased peripheral-placental and decreased cerebral resistances. Personalizing the model allows for quantifying the balance between cerebral and peripheral-placental remodeling, thus providing potentially novel information to aid clinical follow up. PMID:24921933

Adaptation of an urban land surface model to a tropical suburban area: Offline evaluation, sensitivity analysis, and optimization of TEB/ISBA (SURFEX)

NASA Astrophysics Data System (ADS)

Harshan, Suraj

The main objective of the present thesis is the improvement of the TEB/ISBA (SURFEX) urban land surface model (ULSM) through comprehensive evaluation, sensitivity analysis, and optimization experiments using energy balance and radiative and air temperature data observed during 11 months at a tropical sub-urban site in Singapore. Overall the performance of the model is satisfactory, with a small underestimation of net radiation and an overestimation of sensible heat flux. Weaknesses in predicting the latent heat flux are apparent with smaller model values during daytime and the model also significantly underpredicts both the daytime peak and nighttime storage heat. Surface temperatures of all facets are generally overpredicted. Significant variation exists in the model behaviour between dry and wet seasons. The vegetation parametrization used in the model is inadequate to represent the moisture dynamics, producing unrealistically low latent heat fluxes during a particularly dry period. The comprehensive evaluation of the USLM shows the need for accurate estimation of input parameter values for present site. Since obtaining many of these parameters through empirical methods is not feasible, the present study employed a two step approach aimed at providing information about the most sensitive parameters and an optimized parameter set from model calibration. Two well established sensitivity analysis methods (global: Sobol and local: Morris) and a state-of-the-art multiobjective evolutionary algorithm (Borg) were employed for sensitivity analysis and parameter estimation. Experiments were carried out for three different weather periods. The analysis indicates that roof related parameters are the most important ones in controlling the behaviour of the sensible heat flux and net radiation flux, with roof and road albedo as the most influential parameters. Soil moisture initialization parameters are important in controlling the latent heat flux. The built (town) fraction has a significant influence on all fluxes considered. Comparison between the Sobol and Morris methods shows similar sensitivities, indicating the robustness of the present analysis and that the Morris method can be employed as a computationally cheaper alternative of Sobol's method. Optimization as well as the sensitivity experiments for the three periods (dry, wet and mixed), show a noticeable difference in parameter sensitivity and parameter convergence, indicating inadequacies in model formulation. Existence of a significant proportion of less sensitive parameters might be indicating an over-parametrized model. Borg MOEA showed great promise in optimizing the input parameters set. The optimized model modified using the site specific values for thermal roughness length parametrization shows an improvement in the performances of outgoing longwave radiation flux, overall surface temperature, heat storage flux and sensible heat flux.

Exploring the site-selective binding of jatrorrhizine to human serum albumin: spectroscopic and molecular modeling approaches.

PubMed

Mi, Ran; Hu, Yan-Jun; Fan, Xiao-Yang; Ouyang, Yu; Bai, Ai-Min

2014-01-03

This paper exploring the site-selective binding of jatrorrhizine to human serum albumin (HSA) under physiological conditions (pH=7.4). The investigation was carried out using fluorescence spectroscopy, UV-vis spectroscopy, and molecular modeling. The results of fluorescence quenching and UV-vis absorption spectra experiments indicated the formation of the complex of HSA-jatrorrhizine. Binding parameters calculating from Stern-Volmer method and Scatchard method were calculated at 298, 304 and 310 K, with the corresponding thermodynamic parameters ΔG, ΔH and ΔS as well. Binding parameters calculating from Stern-Volmer method and Scatchard method showed that jatrorrhizine bind to HSA with the binding affinities of the order 10(4) L mol(-1). The thermodynamic parameters studies revealed that the binding was characterized by negative enthalpy and positive entropy changes and the electrostatic interactions play a major role for jatrorrhizine-HSA association. Site marker competitive displacement experiments and molecular modeling calculation demonstrating that jatrorrhizine is mainly located within the hydrophobic pocket of the subdomain IIIA of HSA. Furthermore, the synchronous fluorescence spectra suggested that the association between jatrorrhizine and HSA changed molecular conformation of HSA. Copyright © 2013. Published by Elsevier B.V.

Dynamics of large-scale brain activity in normal arousal states and epileptic seizures

NASA Astrophysics Data System (ADS)

Robinson, P. A.; Rennie, C. J.; Rowe, D. L.

2002-04-01

Links between electroencephalograms (EEGs) and underlying aspects of neurophysiology and anatomy are poorly understood. Here a nonlinear continuum model of large-scale brain electrical activity is used to analyze arousal states and their stability and nonlinear dynamics for physiologically realistic parameters. A simple ordered arousal sequence in a reduced parameter space is inferred and found to be consistent with experimentally determined parameters of waking states. Instabilities arise at spectral peaks of the major clinically observed EEG rhythms-mainly slow wave, delta, theta, alpha, and sleep spindle-with each instability zone lying near its most common experimental precursor arousal states in the reduced space. Theta, alpha, and spindle instabilities evolve toward low-dimensional nonlinear limit cycles that correspond closely to EEGs of petit mal seizures for theta instability, and grand mal seizures for the other types. Nonlinear stimulus-induced entrainment and seizures are also seen, EEG spectra and potentials evoked by stimuli are reproduced, and numerous other points of experimental agreement are found. Inverse modeling enables physiological parameters underlying observed EEGs to be determined by a new, noninvasive route. This model thus provides a single, powerful framework for quantitative understanding of a wide variety of brain phenomena.

Inverse modeling of geochemical and mechanical compaction in sedimentary basins

NASA Astrophysics Data System (ADS)

Colombo, Ivo; Porta, Giovanni Michele; Guadagnini, Alberto

2015-04-01

We study key phenomena driving the feedback between sediment compaction processes and fluid flow in stratified sedimentary basins formed through lithification of sand and clay sediments after deposition. Processes we consider are mechanic compaction of the host rock and the geochemical compaction due to quartz cementation in sandstones. Key objectives of our study include (i) the quantification of the influence of the uncertainty of the model input parameters on the model output and (ii) the application of an inverse modeling technique to field scale data. Proper accounting of the feedback between sediment compaction processes and fluid flow in the subsurface is key to quantify a wide set of environmentally and industrially relevant phenomena. These include, e.g., compaction-driven brine and/or saltwater flow at deep locations and its influence on (a) tracer concentrations observed in shallow sediments, (b) build up of fluid overpressure, (c) hydrocarbon generation and migration, (d) subsidence due to groundwater and/or hydrocarbons withdrawal, and (e) formation of ore deposits. Main processes driving the diagenesis of sediments after deposition are mechanical compaction due to overburden and precipitation/dissolution associated with reactive transport. The natural evolution of sedimentary basins is characterized by geological time scales, thus preventing direct and exhaustive measurement of the system dynamical changes. The outputs of compaction models are plagued by uncertainty because of the incomplete knowledge of the models and parameters governing diagenesis. Development of robust methodologies for inverse modeling and parameter estimation under uncertainty is therefore crucial to the quantification of natural compaction phenomena. We employ a numerical methodology based on three building blocks: (i) space-time discretization of the compaction process; (ii) representation of target output variables through a Polynomial Chaos Expansion (PCE); and (iii) model inversion (parameter estimation) within a maximum likelihood framework. In this context, the PCE-based surrogate model enables one to (i) minimize the computational cost associated with the (forward and inverse) modeling procedures leading to uncertainty quantification and parameter estimation, and (ii) compute the full set of Sobol indices quantifying the contribution of each uncertain parameter to the variability of target state variables. Results are illustrated through the simulation of one-dimensional test cases. The analyses focuses on the calibration of model parameters through literature field cases. The quality of parameter estimates is then analyzed as a function of number, type and location of data.

Modeling of Transionospheric Radio Propagation

DTIC Science & Technology

1975-08-01

entitled RFMOD, contains the main elements of the scattering theory, the morphological model for ionospheric irregularity strength and other...phasor lies within an elemental area on the complex plain. To begin, we write E as the resultant of its long-term mean (E) and a zero-mean, randomly...totally defined by either of these sets of three parameters (i.e., the three real variances or the real R and the real and imaginary parts of B ). Most

Flow adjustment inside homogeneous canopies after a leading edge – An analytical approach backed by LES

DOE PAGES

Kroniger, Konstantin; Banerjee, Tirtha; De Roo, Frederik; ...

2017-10-06

A two-dimensional analytical model for describing the mean flow behavior inside a vegetation canopy after a leading edge in neutral conditions was developed and tested by means of large eddy simulations (LES) employing the LES code PALM. The analytical model is developed for the region directly after the canopy edge, the adjustment region, where one-dimensional canopy models fail due to the sharp change in roughness. The derivation of this adjustment region model is based on an analytic solution of the two-dimensional Reynolds averaged Navier–Stokes equation in neutral conditions for a canopy with constant plant area density (PAD). The main assumptionsmore » for solving the governing equations are separability of the velocity components concerning the spatial variables and the neglection of the Reynolds stress gradients. These two assumptions are verified by means of LES. To determine the emerging model parameters, a simultaneous fitting scheme was applied to the velocity and pressure data of a reference LES simulation. Furthermore a sensitivity analysis of the adjustment region model, equipped with the previously calculated parameters, was performed varying the three relevant length, the canopy height ( h), the canopy length and the adjustment length ( Lc), in additional LES. Even if the model parameters are, in general, functions of h/ Lc, it was found out that the model is capable of predicting the flow quantities in various cases, when using constant parameters. Subsequently the adjustment region model is combined with the one-dimensional model of Massman, which is applicable for the interior of the canopy, to attain an analytical model capable of describing the mean flow for the full canopy domain. As a result, the model is tested against an analytical model based on a linearization approach.« less

Flow adjustment inside homogeneous canopies after a leading edge – An analytical approach backed by LES

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

Kroniger, Konstantin; Banerjee, Tirtha; De Roo, Frederik

A two-dimensional analytical model for describing the mean flow behavior inside a vegetation canopy after a leading edge in neutral conditions was developed and tested by means of large eddy simulations (LES) employing the LES code PALM. The analytical model is developed for the region directly after the canopy edge, the adjustment region, where one-dimensional canopy models fail due to the sharp change in roughness. The derivation of this adjustment region model is based on an analytic solution of the two-dimensional Reynolds averaged Navier–Stokes equation in neutral conditions for a canopy with constant plant area density (PAD). The main assumptionsmore » for solving the governing equations are separability of the velocity components concerning the spatial variables and the neglection of the Reynolds stress gradients. These two assumptions are verified by means of LES. To determine the emerging model parameters, a simultaneous fitting scheme was applied to the velocity and pressure data of a reference LES simulation. Furthermore a sensitivity analysis of the adjustment region model, equipped with the previously calculated parameters, was performed varying the three relevant length, the canopy height ( h), the canopy length and the adjustment length ( Lc), in additional LES. Even if the model parameters are, in general, functions of h/ Lc, it was found out that the model is capable of predicting the flow quantities in various cases, when using constant parameters. Subsequently the adjustment region model is combined with the one-dimensional model of Massman, which is applicable for the interior of the canopy, to attain an analytical model capable of describing the mean flow for the full canopy domain. As a result, the model is tested against an analytical model based on a linearization approach.« less

Simulation of ethane steam cracking with severity evaluation

NASA Astrophysics Data System (ADS)

Rosli, M. N.; Aziz, N.

2016-11-01

Understanding the influence of operating parameters towards cracking severity is paramount in ensuring optimum operation of an ethylene plant. However, changing the parameters in an actual plant for data collection can be dangerous. Thus, a simulation model for ethane steam cracking furnace is developed using ASPEN Plus for the assessment. The process performance is evaluated with cracking severity factors and main product yields. Three severity factors are used for evaluation due to their ease of measurement, which are methane yield (Ymet), Ethylene-Ethane Ratio (EER) and Propylene-Ethylene Ratio (PER). The result shows that cracking severity is primarily influenced by reactor temperature. Operating the furnace with coil outlet temperature ranging between 850°C to 950°C and steam-to-hydrocarbon ratio of 0.3 to 0.5 has led to optimum main product yield.

Mathematical Model and Calibration Procedure of a PSD Sensor Used in Local Positioning Systems.

PubMed

Rodríguez-Navarro, David; Lázaro-Galilea, José Luis; Bravo-Muñoz, Ignacio; Gardel-Vicente, Alfredo; Domingo-Perez, Francisco; Tsirigotis, Georgios

2016-09-15

Here, we propose a mathematical model and a calibration procedure for a PSD (position sensitive device) sensor equipped with an optical system, to enable accurate measurement of the angle of arrival of one or more beams of light emitted by infrared (IR) transmitters located at distances of between 4 and 6 m. To achieve this objective, it was necessary to characterize the intrinsic parameters that model the system and obtain their values. This first approach was based on a pin-hole model, to which system nonlinearities were added, and this was used to model the points obtained with the nA currents provided by the PSD. In addition, we analyzed the main sources of error, including PSD sensor signal noise, gain factor imbalances and PSD sensor distortion. The results indicated that the proposed model and method provided satisfactory calibration and yielded precise parameter values, enabling accurate measurement of the angle of arrival with a low degree of error, as evidenced by the experimental results.

About the Modeling of Radio Source Time Series as Linear Splines

NASA Astrophysics Data System (ADS)

Karbon, Maria; Heinkelmann, Robert; Mora-Diaz, Julian; Xu, Minghui; Nilsson, Tobias; Schuh, Harald

2016-12-01

Many of the time series of radio sources observed in geodetic VLBI show variations, caused mainly by changes in source structure. However, until now it has been common practice to consider source positions as invariant, or to exclude known misbehaving sources from the datum conditions. This may lead to a degradation of the estimated parameters, as unmodeled apparent source position variations can propagate to the other parameters through the least squares adjustment. In this paper we will introduce an automated algorithm capable of parameterizing the radio source coordinates as linear splines.

Electrospinning of Polyaniline/Poly(Lactic Acid) Ultrathin Fibers: Process and Statistical Modeling using a Non-Gaussian Approach

USDA-ARS?s Scientific Manuscript database

Fibers of poly(lactic acid) (PLA) blended with p-toluenesulfonic acid-doped polyaniline, PAni.TSA, were obtained by lectrospinning, following a factorial design which was used mainly to study the effect of four process parameters (PLA solution concentration, PAni solution concentration, applied volt...

Helicopter main-rotor speed effects on far-field acoustic levels

NASA Technical Reports Server (NTRS)

Mueller, Arnold W.; Childress, Otis S.; Hardesty, Mark

1987-01-01

The design of a helicopter is based on an understanding of many parameters and their interactions. For example, in the design stage of a helicopter, the weight, engine, and rotor speed must be considered along with the rotor geometry when considering helicopter operations. However, the relationship between the noise radiated from the helicopter and these parameters is not well understood, with only limited model and full-scale test data to study. In general, these data have shown that reduced rotor speeds result in reduced far-field noise levels. This paper reviews the status of a recent helicopter noise research project designed to provide experimental flight data to be used to better understand helicopter rotor-speed effects on far-field acoustic levels. Preliminary results are presented relative to tests conducted with a McDonnell Douglas model 500E helicopter operating with the rotor speed as the control variable over the range of 103% of the main-rotor speed (NR) to 75% NR, and with the forward speed maintained at a constant value of 80 knots.

Investigation on the effect of geometrical and geotechnical parameters on elongated offshore piles using fuzzy inference systems

NASA Astrophysics Data System (ADS)

Aminfar, Ali; Mojtahedi, Alireza; Ahmadi, Hamid; Aminfar, Mohammad Hossain

2017-06-01

Among numerous offshore structures used in oil extraction, jacket platforms are still the most favorable ones in shallow waters. In such structures, log piles are used to pin the substructure of the platform to the seabed. The pile's geometrical and geotechnical properties are considered as the main parameters in designing these structures. In this study, ANSYS was used as the FE modeling software to study the geometrical and geotechnical properties of the offshore piles and their effects on supporting jacket platforms. For this purpose, the FE analysis has been done to provide the preliminary data for the fuzzy-logic post-process. The resulting data were implemented to create Fuzzy Inference System (FIS) classifications. The resultant data of the sensitivity analysis suggested that the orientation degree is the main factor in the pile's geometrical behavior because piles which had the optimal operational degree of about 5° are more sustained. Finally, the results showed that the related fuzzified data supported the FE model and provided an insight for extended offshore pile designs.

Sensitivity analysis and uncertainty estimation in ash concentration simulations and tephra deposit daily forecasted at Mt. Etna, in Italy

NASA Astrophysics Data System (ADS)

Prestifilippo, Michele; Scollo, Simona; Tarantola, Stefano

2015-04-01

The uncertainty in volcanic ash forecasts may depend on our knowledge of the model input parameters and our capability to represent the dynamic of an incoming eruption. Forecasts help governments to reduce risks associated with volcanic eruptions and for this reason different kinds of analysis that help to understand the effect that each input parameter has on model outputs are necessary. We present an iterative approach based on the sequential combination of sensitivity analysis, parameter estimation procedure and Monte Carlo-based uncertainty analysis, applied to the lagrangian volcanic ash dispersal model PUFF. We modify the main input parameters as the total mass, the total grain-size distribution, the plume thickness, the shape of the eruption column, the sedimentation models and the diffusion coefficient, perform thousands of simulations and analyze the results. The study is carried out on two different Etna scenarios: the sub-plinian eruption of 22 July 1998 that formed an eruption column rising 12 km above sea level and lasted some minutes and the lava fountain eruption having features similar to the 2011-2013 events that produced eruption column high up to several kilometers above sea level and lasted some hours. Sensitivity analyses and uncertainty estimation results help us to address the measurements that volcanologists should perform during volcanic crisis to reduce the model uncertainty.

Determining Experimental Parameters for Thermal-Mechanical Forming Simulation considering Martensite Formation in Austenitic Stainless Steel

NASA Astrophysics Data System (ADS)

Schmid, Philipp; Liewald, Mathias

2011-08-01

The forming behavior of metastable austenitic stainless steel is mainly dominated by the temperature-dependent TRIP effect (transformation induced plasticity). Of course, the high dependency of material properties on the temperature level during forming means the temperature must be considered during the FE analysis. The strain-induced formation of α'-martensite from austenite can be represented by using finite element programs utilizing suitable models such as the Haensel-model. This paper discusses the determination of parameters for a completely thermal-mechanical forming simulation in LS-DYNA based on the material model of Haensel. The measurement of the martensite evolution in non-isothermal tensile tests was performed with metastable austenitic stainless steel EN 1.4301 at different rolling directions between 0° and 90 °. This allows an estimation of the influence of the rolling direction to the martensite formation. Of specific importance is the accuracy of the martensite content measured by magnetic induction methods (Feritscope). The observation of different factors, such as stress dependence of the magnetisation, blank thickness and numerous calibration curves discloses a substantial important influence on the parameter determination for the material models. The parameters obtained for use of Haensel model and temperature-dependent friction coefficients are used to simulate forming process of a real component and to validate its implementation in the commercial code LS-DYNA.

On the Use of the Beta Distribution in Probabilistic Resource Assessments

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

Olea, Ricardo A., E-mail: olea@usgs.gov

2011-12-15

The triangular distribution is a popular choice when it comes to modeling bounded continuous random variables. Its wide acceptance derives mostly from its simple analytic properties and the ease with which modelers can specify its three parameters through the extremes and the mode. On the negative side, hardly any real process follows a triangular distribution, which from the outset puts at a disadvantage any model employing triangular distributions. At a time when numerical techniques such as the Monte Carlo method are displacing analytic approaches in stochastic resource assessments, easy specification remains the most attractive characteristic of the triangular distribution. Themore » beta distribution is another continuous distribution defined within a finite interval offering wider flexibility in style of variation, thus allowing consideration of models in which the random variables closely follow the observed or expected styles of variation. Despite its more complex definition, generation of values following a beta distribution is as straightforward as generating values following a triangular distribution, leaving the selection of parameters as the main impediment to practically considering beta distributions. This contribution intends to promote the acceptance of the beta distribution by explaining its properties and offering several suggestions to facilitate the specification of its two shape parameters. In general, given the same distributional parameters, use of the beta distributions in stochastic modeling may yield significantly different results, yet better estimates, than the triangular distribution.« less

Asymptotic limits of some models for sound propagation in porous media and the assignment of the pore characteristic lengths.

PubMed

Horoshenkov, Kirill V; Groby, Jean-Philippe; Dazel, Olivier

2016-05-01

Modeling of sound propagation in porous media requires the knowledge of several intrinsic material parameters, some of which are difficult or impossible to measure directly, particularly in the case of a porous medium which is composed of pores with a wide range of scales and random interconnections. Four particular parameters which are rarely measured non-acoustically, but used extensively in a number of acoustical models, are the viscous and thermal characteristic lengths, thermal permeability, and Pride parameter. The main purpose of this work is to show how these parameters relate to the pore size distribution which is a routine characteristic measured non-acoustically. This is achieved through the analysis of the asymptotic behavior of four analytical models which have been developed previously to predict the dynamic density and/or compressibility of the equivalent fluid in a porous medium. In this work the models proposed by Johnson, Koplik, and Dashn [J. Fluid Mech. 176, 379-402 (1987)], Champoux and Allard [J. Appl. Phys. 70(4), 1975-1979 (1991)], Pride, Morgan, and Gangi [Phys. Rev. B 47, 4964-4978 (1993)], and Horoshenkov, Attenborough, and Chandler-Wilde [J. Acoust. Soc. Am. 104, 1198-1209 (1998)] are compared. The findings are then used to compare the behavior of the complex dynamic density and compressibility of the fluid in a material pore with uniform and variable cross-sections.

Subordinated continuous-time AR processes and their application to modeling behavior of mechanical system

NASA Astrophysics Data System (ADS)

Gajda, Janusz; Wyłomańska, Agnieszka; Zimroz, Radosław

2016-12-01

Many real data exhibit behavior adequate to subdiffusion processes. Very often it is manifested by so-called ;trapping events;. The visible evidence of subdiffusion we observe not only in financial time series but also in technical data. In this paper we propose a model which can be used for description of such kind of data. The model is based on the continuous time autoregressive time series with stable noise delayed by the infinitely divisible inverse subordinator. The proposed system can be applied to real datasets with short-time dependence, visible jumps and mentioned periods of stagnation. In this paper we extend the theoretical considerations in analysis of subordinated processes and propose a new model that exhibits mentioned properties. We concentrate on the main characteristics of the examined subordinated process expressed mainly in the language of the measures of dependence which are main tools used in statistical investigation of real data. We present also the simulation procedure of the considered system and indicate how to estimate its parameters. The theoretical results we illustrate by the analysis of real technical data.

Fermentation of Saccharomyces cerevisiae - Combining kinetic modeling and optimization techniques points out avenues to effective process design.

PubMed

Scheiblauer, Johannes; Scheiner, Stefan; Joksch, Martin; Kavsek, Barbara

2018-09-14

A combined experimental/theoretical approach is presented, for improving the predictability of Saccharomyces cerevisiae fermentations. In particular, a mathematical model was developed explicitly taking into account the main mechanisms of the fermentation process, allowing for continuous computation of key process variables, including the biomass concentration and the respiratory quotient (RQ). For model calibration and experimental validation, batch and fed-batch fermentations were carried out. Comparison of the model-predicted biomass concentrations and RQ developments with the corresponding experimentally recorded values shows a remarkably good agreement for both batch and fed-batch processes, confirming the adequacy of the model. Furthermore, sensitivity studies were performed, in order to identify model parameters whose variations have significant effects on the model predictions: our model responds with significant sensitivity to the variations of only six parameters. These studies provide a valuable basis for model reduction, as also demonstrated in this paper. Finally, optimization-based parametric studies demonstrate how our model can be utilized for improving the efficiency of Saccharomyces cerevisiae fermentations. Copyright © 2018 Elsevier Ltd. All rights reserved.

An action potential-driven model of soleus muscle activation dynamics for locomotor-like movements

NASA Astrophysics Data System (ADS)

Kim, Hojeong; Sandercock, Thomas G.; Heckman, C. J.

2015-08-01

Objective. The goal of this study was to develop a physiologically plausible, computationally robust model for muscle activation dynamics (A(t)) under physiologically relevant excitation and movement. Approach. The interaction of excitation and movement on A(t) was investigated comparing the force production between a cat soleus muscle and its Hill-type model. For capturing A(t) under excitation and movement variation, a modular modeling framework was proposed comprising of three compartments: (1) spikes-to-[Ca2+]; (2) [Ca2+]-to-A; and (3) A-to-force transformation. The individual signal transformations were modeled based on physiological factors so that the parameter values could be separately determined for individual modules directly based on experimental data. Main results. The strong dependency of A(t) on excitation frequency and muscle length was found during both isometric and dynamically-moving contractions. The identified dependencies of A(t) under the static and dynamic conditions could be incorporated in the modular modeling framework by modulating the model parameters as a function of movement input. The new modeling approach was also applicable to cat soleus muscles producing waveforms independent of those used to set the model parameters. Significance. This study provides a modeling framework for spike-driven muscle responses during movement, that is suitable not only for insights into molecular mechanisms underlying muscle behaviors but also for large scale simulations.

A computational framework for testing arrhythmia marker sensitivities to model parameters in functionally calibrated populations of atrial cells

NASA Astrophysics Data System (ADS)

Vagos, Márcia R.; Arevalo, Hermenegild; de Oliveira, Bernardo Lino; Sundnes, Joakim; Maleckar, Mary M.

2017-09-01

Models of cardiac cell electrophysiology are complex non-linear systems which can be used to gain insight into mechanisms of cardiac dynamics in both healthy and pathological conditions. However, the complexity of cardiac models can make mechanistic insight difficult. Moreover, these are typically fitted to averaged experimental data which do not incorporate the variability in observations. Recently, building populations of models to incorporate inter- and intra-subject variability in simulations has been combined with sensitivity analysis (SA) to uncover novel ionic mechanisms and potentially clarify arrhythmogenic behaviors. We used the Koivumäki human atrial cell model to create two populations, representing normal Sinus Rhythm (nSR) and chronic Atrial Fibrillation (cAF), by varying 22 key model parameters. In each population, 14 biomarkers related to the action potential and dynamic restitution were extracted. Populations were calibrated based on distributions of biomarkers to obtain reasonable physiological behavior, and subjected to SA to quantify correlations between model parameters and pro-arrhythmia markers. The two populations showed distinct behaviors under steady state and dynamic pacing. The nSR population revealed greater variability, and more unstable dynamic restitution, as compared to the cAF population, suggesting that simulated cAF remodeling rendered cells more stable to parameter variation and rate adaptation. SA revealed that the biomarkers depended mainly on five ionic currents, with noted differences in sensitivities to these between nSR and cAF. Also, parameters could be selected to produce a model variant with no alternans and unaltered action potential morphology, highlighting that unstable dynamical behavior may be driven by specific cell parameter settings. These results ultimately suggest that arrhythmia maintenance in cAF may not be due to instability in cell membrane excitability, but rather due to tissue-level effects which promote initiation and maintenance of reentrant arrhythmia.

Evaluation of deep moonquake source parameters: Implication for fault characteristics and thermal state

NASA Astrophysics Data System (ADS)

Kawamura, Taichi; Lognonné, Philippe; Nishikawa, Yasuhiro; Tanaka, Satoshi

2017-07-01

While deep moonquakes are seismic events commonly observed on the Moon, their source mechanism is still unexplained. The two main issues are poorly constrained source parameters and incompatibilities between the thermal profiles suggested by many studies and the apparent need for brittle properties at these depths. In this study, we reinvestigated the deep moonquake data to reestimate its source parameters and uncover the characteristics of deep moonquake faults that differ from those on Earth. We first improve the estimation of source parameters through spectral analysis using "new" broadband seismic records made by combining those of the Apollo long- and short-period seismometers. We use the broader frequency band of the combined spectra to estimate corner frequencies and DC values of spectra, which are important parameters to constrain the source parameters. We further use the spectral features to estimate seismic moments and stress drops for more than 100 deep moonquake events from three different source regions. This study revealed that deep moonquake faults are extremely smooth compared to terrestrial faults. Second, we reevaluate the brittle-ductile transition temperature that is consistent with the obtained source parameters. We show that the source parameters imply that the tidal stress is the main source of the stress glut causing deep moonquakes and the large strain rate from tides makes the brittle-ductile transition temperature higher. Higher transition temperatures open a new possibility to construct a thermal model that is consistent with deep moonquake occurrence and pressure condition and thereby improve our understandings of the deep moonquake source mechanism.

Shock Layer Radiation Modeling and Uncertainty for Mars Entry

NASA Technical Reports Server (NTRS)

Johnston, Christopher O.; Brandis, Aaron M.; Sutton, Kenneth

2012-01-01

A model for simulating nonequilibrium radiation from Mars entry shock layers is presented. A new chemical kinetic rate model is developed that provides good agreement with recent EAST and X2 shock tube radiation measurements. This model includes a CO dissociation rate that is a factor of 13 larger than the rate used widely in previous models. Uncertainties in the proposed rates are assessed along with uncertainties in translational-vibrational relaxation modeling parameters. The stagnation point radiative flux uncertainty due to these flowfield modeling parameter uncertainties is computed to vary from 50 to 200% for a range of free-stream conditions, with densities ranging from 5e-5 to 5e-4 kg/m3 and velocities ranging from of 6.3 to 7.7 km/s. These conditions cover the range of anticipated peak radiative heating conditions for proposed hypersonic inflatable aerodynamic decelerators (HIADs). Modeling parameters for the radiative spectrum are compiled along with a non-Boltzmann rate model for the dominant radiating molecules, CO, CN, and C2. A method for treating non-local absorption in the non-Boltzmann model is developed, which is shown to result in up to a 50% increase in the radiative flux through absorption by the CO 4th Positive band. The sensitivity of the radiative flux to the radiation modeling parameters is presented and the uncertainty for each parameter is assessed. The stagnation point radiative flux uncertainty due to these radiation modeling parameter uncertainties is computed to vary from 18 to 167% for the considered range of free-stream conditions. The total radiative flux uncertainty is computed as the root sum square of the flowfield and radiation parametric uncertainties, which results in total uncertainties ranging from 50 to 260%. The main contributors to these significant uncertainties are the CO dissociation rate and the CO heavy-particle excitation rates. Applying the baseline flowfield and radiation models developed in this work, the radiative heating for the Mars Pathfinder probe is predicted to be nearly 20 W/cm2. In contrast to previous studies, this value is shown to be significant relative to the convective heating.

Study of Falling Roof Vibrations in a Production Face at Roof Support Resistance in the Form of Concentrated Force

NASA Astrophysics Data System (ADS)

Buyalich, G. D.; Buyalich, K. G.; Umrikhina, V. Yu

2016-08-01

One of the main reasons of roof support failures in production faces is mismatch of their parameters and parameters of dynamic impact on the metal structure from the falling roof during its secondary convergences. To assess the parameters of vibrational interaction of roof support with the roof, it was suggested to use computational models of forces application and a partial differential equation of fourth order describing this process, its numerical solution allowed to assess frequency, amplitude and speed of roof strata movement depending on physical and mechanical properties of the roof strata as well as on load bearing and geometry parameters of the roof support. To simplify solving of the differential equation, roof support response was taken as the concentrated force.

Implementation of the Global Parameters Determination in Gaia's Astrometric Solution (AGIS)

NASA Astrophysics Data System (ADS)

Raison, F.; Olias, A.; Hobbs, D.; Lindegren, L.

2010-12-01

Gaia is ESA’s space astrometry mission with a foreseen launch date in early 2012. Its main objective is to perform a stellar census of the 1000 Million brightest objects in our galaxy (completeness to V=20 mag) from which an astrometric catalog of micro-arcsec level accuracy will be constructed. A key element in this endeavor is the Astrometric Global Iterative Solution (AGIS). A core part of AGIS is to determine the accurate spacecraft attitude, geometric instrument calibration and astrometric model parameters for a well-behaved subset of all the objects (the ‘primary stars’). In addition, a small number of global parameters will be estimated, one of these being PPN γ. We present here the implementation of the algorithms dedicated to the determination of the global parameters.

Laboratory investigation and simulation of breakthrough curves in karst conduits with pools

NASA Astrophysics Data System (ADS)

Zhao, Xiaoer; Chang, Yong; Wu, Jichun; Peng, Fu

2017-12-01

A series of laboratory experiments are performed under various hydrological conditions to analyze the effect of pools in pipes on breakthrough curves (BTCs). The BTCs are generated after instantaneous injections of NaCl tracer solution. In order to test the feasibility of reproducing the BTCs and obtain transport parameters, three modeling approaches have been applied: the equilibrium model, the linear graphical method and the two-region nonequilibrium model. The investigation results show that pools induce tailing of the BTCs, and the shapes of BTCs depend on pool geometries and hydrological conditions. The simulations reveal that the two-region nonequilibrium model yields the best fits to experimental BTCs because the model can describe the transient storage in pools by the partition coefficient and the mass transfer coefficient. The model parameters indicate that pools produce high dispersion. The increased tailing occurs mainly because the partition coefficient decreases, as the number of pools increases. When comparing the tracer BTCs obtained using the two types of pools with the same size, the more appreciable BTC tails that occur for symmetrical pools likely result mainly from the less intense exchange between the water in the pools and the water in the pipe, because the partition coefficients for the two types of pools are virtually identical. Dispersivity values decrease as flow rates increase; however, the trend in dispersion is not clear. The reduced tailing is attributed to a decrease in immobile water with increasing flow rate. It provides evidence for hydrodynamically controlled tailing effects.

Modelling highly variable environmental factors to assess potential microbial respiration in complex floodplain landscapes

PubMed Central

Tritthart, Michael; Welti, Nina; Bondar-Kunze, Elisabeth; Pinay, Gilles; Hein, Thomas; Habersack, Helmut

2011-01-01

The hydrological exchange conditions strongly determine the biogeochemical dynamics in river systems. More specifically, the connectivity of surface waters between main channels and floodplains is directly controlling the delivery of organic matter and nutrients into the floodplains, where biogeochemical processes recycle them with high rates of activity. Hence, an in-depth understanding of the connectivity patterns between main channel and floodplains is important for the modelling of potential gas emissions in floodplain landscapes. A modelling framework that combines steady-state hydrodynamic simulations with long-term discharge hydrographs was developed to calculate water depths as well as statistical probabilities and event durations for every node of a computation mesh being connected to the main river. The modelling framework was applied to two study sites in the floodplains of the Austrian Danube River, East of Vienna. Validation of modelled flood events showed good agreement with gauge readings. Together with measured sediment properties, results of the validated connectivity model were used as basis for a predictive model yielding patterns of potential microbial respiration based on the best fit between characteristics of a number of sampling sites and the corresponding modelled parameters. Hot spots of potential microbial respiration were found in areas of lower connectivity if connected during higher discharges and areas of high water depths. PMID:27667961

Sensitivity of geological, geochemical and hydrologic parameters in complex reactive transport systems for in-situ uranium bioremediation

NASA Astrophysics Data System (ADS)

Yang, G.; Maher, K.; Caers, J.

2015-12-01

Groundwater contamination associated with remediated uranium mill tailings is a challenging environmental problem, particularly within the Colorado River Basin. To examine the effectiveness of in-situ bioremediation of U(VI), acetate injection has been proposed and tested at the Rifle pilot site. There have been several geologic modeling and simulated contaminant transport investigations, to evaluate the potential outcomes of the process and identify crucial factors for successful uranium reduction. Ultimately, findings from these studies would contribute to accurate predictions of the efficacy of uranium reduction. However, all these previous studies have considered limited model complexities, either because of the concern that data is too sparse to resolve such complex systems or because some parameters are assumed to be less important. Such simplified initial modeling, however, limits the predictive power of the model. Moreover, previous studies have not yet focused on spatial heterogeneity of various modeling components and its impact on the spatial distribution of the immobilized uranium (U(IV)). In this study, we study the impact of uncertainty on 21 parameters on model responses by means of recently developed distance-based global sensitivity analysis (DGSA), to study the main effects and interactions of parameters of various types. The 21 parameters include, for example, spatial variability of initial uranium concentration, mean hydraulic conductivity, and variogram structures of hydraulic conductivity. DGSA allows for studying multi-variate model responses based on spatial and non-spatial model parameters. When calculating the distances between model responses, in addition to the overall uranium reduction efficacy, we also considered the spatial profiles of the immobilized uranium concentration as target response. Results show that the mean hydraulic conductivity and the mineral reaction rate are the two most sensitive parameters with regard to the overall uranium reduction. But in terms of spatial distribution of immobilized uranium, initial conditions of uranium concentration and spatial uncertainty in hydraulic conductivity also become important. These analyses serve as the first step of further prediction practices of the complex uranium transport and reaction systems.

A Bayesian inverse modeling approach to estimate soil hydraulic properties of a toposequence in southeastern Amazonia.

NASA Astrophysics Data System (ADS)

Stucchi Boschi, Raquel; Qin, Mingming; Gimenez, Daniel; Cooper, Miguel

2016-04-01

Modeling is an important tool for better understanding and assessing land use impacts on landscape processes. A key point for environmental modeling is the knowledge of soil hydraulic properties. However, direct determination of soil hydraulic properties is difficult and costly, particularly in vast and remote regions such as one constituting the Amazon Biome. One way to overcome this problem is to extrapolate accurately estimated data to pedologically similar sites. The van Genuchten (VG) parametric equation is the most commonly used for modeling SWRC. The use of a Bayesian approach in combination with the Markov chain Monte Carlo to estimate the VG parameters has several advantages compared to the widely used global optimization techniques. The Bayesian approach provides posterior distributions of parameters that are independent from the initial values and allow for uncertainty analyses. The main objectives of this study were: i) to estimate hydraulic parameters from data of pasture and forest sites by the Bayesian inverse modeling approach; and ii) to investigate the extrapolation of the estimated VG parameters to a nearby toposequence with pedologically similar soils to those used for its estimate. The parameters were estimated from volumetric water content and tension observations obtained after rainfall events during a 207-day period from pasture and forest sites located in the southeastern Amazon region. These data were used to run HYDRUS-1D under a Differential Evolution Adaptive Metropolis (DREAM) scheme 10,000 times, and only the last 2,500 times were used to calculate the posterior distributions of each hydraulic parameter along with 95% confidence intervals (CI) of volumetric water content and tension time series. Then, the posterior distributions were used to generate hydraulic parameters for two nearby toposequences composed by six soil profiles, three are under forest and three are under pasture. The parameters of the nearby site were accepted when the predicted tension time series were within the 95% CI which is derived from the calibration site using DREAM scheme.

MEGNO-analysis of the orbital evolution of GEO objects. (Russian Title: MEGNO-анализ орбитальной эволюции объектов зоны ГЕО )

NASA Astrophysics Data System (ADS)

Aleksandrova, A. G.; Chuvashov, I. N.; Bordovitsyna, T. V.

2011-07-01

The results of investigations of the instability of orbits in the GEO are presentеd. Average parameter MEGNO as main indicator of chaotic state has been used. The parameter is computed by combined numerical integration of equations of the motion, equations in variation and equations of MEGNO parameters. The results have been obtained using software package "Numerical model of the systems artificial satellite motion", implemented on the cluster "Skiff Cyberia".

A Parameter Identification Method for Helicopter Noise Source Identification and Physics-Based Semi-Empirical Modeling

NASA Technical Reports Server (NTRS)

Greenwood, Eric, II; Schmitz, Fredric H.

2010-01-01

A new physics-based parameter identification method for rotor harmonic noise sources is developed using an acoustic inverse simulation technique. This new method allows for the identification of individual rotor harmonic noise sources and allows them to be characterized in terms of their individual non-dimensional governing parameters. This new method is applied to both wind tunnel measurements and ground noise measurements of two-bladed rotors. The method is shown to match the parametric trends of main rotor Blade-Vortex Interaction (BVI) noise, allowing accurate estimates of BVI noise to be made for operating conditions based on a small number of measurements taken at different operating conditions.

Application of tire dynamics to aircraft landing gear design analysis

NASA Technical Reports Server (NTRS)

Black, R. J.

1983-01-01

The tire plays a key part in many analyses used for design of aircraft landing gear. Examples include structural design of wheels, landing gear shimmy, brake whirl, chatter and squeal, complex combination of chatter and shimmy on main landing gear (MLG) systems, anti-skid performance, gear walk, and rough terrain loads and performance. Tire parameters needed in the various analyses are discussed. Two tire models are discussed for shimmy analysis, the modified Moreland approach and the von Schlippe-Dietrich approach. It is shown that the Moreland model can be derived from the Von Schlippe-Dietrich model by certain approximations. The remaining analysis areas are discussed in general terms and the tire parameters needed for each are identified. Accurate tire data allows more accurate design analysis and the correct prediction of dynamic performance of aircraft landing gear.

Studies of a general flat space/boson star transition model in a box through a language similar to holographic superconductors

NASA Astrophysics Data System (ADS)

Peng, Yan

2017-07-01

We study a general flat space/boson star transition model in quasi-local ensemble through approaches familiar from holographic superconductor theories. We manage to find a parameter ψ 2, which is proved to be useful in disclosing properties of phase transitions. In this work, we explore effects of the scalar mass, scalar charge and Stückelberg mechanism on the critical phase transition points and the order of transitions mainly from behaviors of the parameter ψ 2. We mention that properties of transitions in quasi-local gravity are strikingly similar to those in holographic superconductor models. We also obtain an analytical relation ψ 2 ∝ ( μ - μ c )1/2, which also holds for the condensed scalar operator in the holographic insulator/superconductor system in accordance with mean field theories.

Probabilistic failure assessment with application to solid rocket motors

NASA Technical Reports Server (NTRS)

Jan, Darrell L.; Davidson, Barry D.; Moore, Nicholas R.

1990-01-01

A quantitative methodology is being developed for assessment of risk of failure of solid rocket motors. This probabilistic methodology employs best available engineering models and available information in a stochastic framework. The framework accounts for incomplete knowledge of governing parameters, intrinsic variability, and failure model specification error. Earlier case studies have been conducted on several failure modes of the Space Shuttle Main Engine. Work in progress on application of this probabilistic approach to large solid rocket boosters such as the Advanced Solid Rocket Motor for the Space Shuttle is described. Failure due to debonding has been selected as the first case study for large solid rocket motors (SRMs) since it accounts for a significant number of historical SRM failures. Impact of incomplete knowledge of governing parameters and failure model specification errors is expected to be important.

Hydrogeophysics and remote sensing for the design of hydrogeological conceptual models in hard rocks - Sardón catchment (Spain)

NASA Astrophysics Data System (ADS)

Francés, Alain P.; Lubczynski, Maciek W.; Roy, Jean; Santos, Fernando A. M.; Mahmoudzadeh Ardekani, Mohammad R.

2014-11-01

Hard rock aquifers are highly heterogeneous and hydrogeologically complex. To contribute to the design of hydrogeological conceptual models of hard rock aquifers, we propose a multi-techniques methodology based on a downward approach that combines remote sensing (RS), non-invasive hydrogeophysics and hydrogeological field data acquisition. The proposed methodology is particularly suitable for data scarce areas. It was applied in the pilot research area of Sardón catchment (80 km2) located west of Salamanca (Spain). The area was selected because of hard-rock hydrogeology, semi-arid climate and scarcity of groundwater resources. The proposed methodology consisted of three main steps. First, we detected the main hydrogeological features at the catchment scale by processing: (i) a high resolution digital terrain model to map lineaments and to outline fault zones; and (ii) high-resolution, multispectral satellite QuickBird and WorldView-2 images to map the outcropping granite. Second, we characterized at the local scale the hydrogeological features identified at step one with: i) ground penetrating radar (GPR) to assess groundwater table depth complementing the available monitoring network data; ii) 2D electric resistivity tomography (ERT) and frequency domain electromagnetic (FDEM) to retrieve the hydrostratigraphy along selected survey transects; iii) magnetic resonance soundings (MRS) to retrieve the hydrostratigraphy and aquifer parameters at the selected survey sites. In the third step, we drilled 5 boreholes (25 to 48 m deep) and performed slug tests to verify the hydrogeophysical interpretation and to calibrate the MRS parameters. Finally, we compiled and integrated all acquired data to define the geometry and parameters of the Sardón aquifer at the catchment scale. In line with a general conceptual model of hard rock aquifers, we identified two main hydrostratigraphic layers: a saprolite layer and a fissured layer. Both layers were intersected and drained by fault zones that control the hydrogeology of the catchment. The spatial discontinuities of the saprolite layer were well defined by RS techniques while subsurface geometry and aquifer parameters by hydrogeophysics. The GPR method was able to detect shallow water table at depth between 1 and 3 m b.g.s. The hydrostratigraphy and parameterization of the fissured layer remained uncertain because ERT and FDEM geophysical methods were quantitatively not conclusive while MRS detectability was restricted by low volumetric water content. The proposed multi-technique methodology integrating cost efficient RS, hydrogeophysics and hydrogeological field investigations allowed us to characterize geometrically and parametrically the Sardón hard rock aquifer system, facilitating the design of hydrogeological conceptual model of the area.

Comprehensive cosmographic analysis by Markov chain method

NASA Astrophysics Data System (ADS)

Capozziello, S.; Lazkoz, R.; Salzano, V.

2011-12-01

We study the possibility of extracting model independent information about the dynamics of the Universe by using cosmography. We intend to explore it systematically, to learn about its limitations and its real possibilities. Here we are sticking to the series expansion approach on which cosmography is based. We apply it to different data sets: Supernovae type Ia (SNeIa), Hubble parameter extracted from differential galaxy ages, gamma ray bursts, and the baryon acoustic oscillations data. We go beyond past results in the literature extending the series expansion up to the fourth order in the scale factor, which implies the analysis of the deceleration q0, the jerk j0, and the snap s0. We use the Markov chain Monte Carlo method (MCMC) to analyze the data statistically. We also try to relate direct results from cosmography to dark energy (DE) dynamical models parametrized by the Chevallier-Polarski-Linder model, extracting clues about the matter content and the dark energy parameters. The main results are: (a) even if relying on a mathematical approximate assumption such as the scale factor series expansion in terms of time, cosmography can be extremely useful in assessing dynamical properties of the Universe; (b) the deceleration parameter clearly confirms the present acceleration phase; (c) the MCMC method can help giving narrower constraints in parameter estimation, in particular for higher order cosmographic parameters (the jerk and the snap), with respect to the literature; and (d) both the estimation of the jerk and the DE parameters reflect the possibility of a deviation from the ΛCDM cosmological model.

A users manual for the method of moments Aircraft Modeling Code (AMC), version 2

NASA Technical Reports Server (NTRS)

Peters, M. E.; Newman, E. H.

1994-01-01

This report serves as a user's manual for Version 2 of the 'Aircraft Modeling Code' or AMC. AMC is a user-oriented computer code, based on the method of moments (MM), for the analysis of the radiation and/or scattering from geometries consisting of a main body or fuselage shape with attached wings and fins. The shape of the main body is described by defining its cross section at several stations along its length. Wings, fins, rotor blades, and radiating monopoles can then be attached to the main body. Although AMC was specifically designed for aircraft or helicopter shapes, it can also be applied to missiles, ships, submarines, jet inlets, automobiles, spacecraft, etc. The problem geometry and run control parameters are specified via a two character command language input format. This report describes the input command language and also includes several examples which illustrate typical code inputs and outputs.

A user's manual for the method of moments Aircraft Modeling Code (AMC)

NASA Technical Reports Server (NTRS)

Peters, M. E.; Newman, E. H.

1989-01-01

This report serves as a user's manual for the Aircraft Modeling Code or AMC. AMC is a user-oriented computer code, based on the method of moments (MM), for the analysis of the radiation and/or scattering from geometries consisting of a main body or fuselage shape with attached wings and fins. The shape of the main body is described by defining its cross section at several stations along its length. Wings, fins, rotor blades, and radiating monopoles can then be attached to the main body. Although AMC was specifically designed for aircraft or helicopter shapes, it can also be applied to missiles, ships, submarines, jet inlets, automobiles, spacecraft, etc. The problem geometry and run control parameters are specified via a two character command language input format. The input command language is described and several examples which illustrate typical code inputs and outputs are also included.

On the distributions of annual and seasonal daily rainfall extremes in central Arizona and their spatial variability

NASA Astrophysics Data System (ADS)

Mascaro, Giuseppe

2018-04-01

This study uses daily rainfall records of a dense network of 240 gauges in central Arizona to gain insights on (i) the variability of the seasonal distributions of rainfall extremes; (ii) how the seasonal distributions affect the shape of the annual distribution; and (iii) the presence of spatial patterns and orographic control for these distributions. For this aim, recent methodological advancements in peak-over-threshold analysis and application of the Generalized Pareto Distribution (GPD) were used to assess the suitability of the GPD hypothesis and improve the estimation of its parameters, while limiting the effect of short sample sizes. The distribution of daily rainfall extremes was found to be heavy-tailed (i.e., GPD shape parameter ξ > 0) during the summer season, dominated by convective monsoonal thunderstorms. The exponential distribution (a special case of GPD with ξ = 0) was instead showed to be appropriate for modeling wintertime daily rainfall extremes, mainly caused by cold fronts transported by westerly flow. The annual distribution exhibited a mixed behavior, with lighter upper tails than those found in summer. A hybrid model mixing the two seasonal distributions was demonstrated capable of reproducing the annual distribution. Organized spatial patterns, mainly controlled by elevation, were observed for the GPD scale parameter, while ξ did not show any clear control of location or orography. The quantiles returned by the GPD were found to be very similar to those provided by the National Oceanic and Atmospheric Administration (NOAA) Atlas 14, which used the Generalized Extreme Value (GEV) distribution. Results of this work are useful to improve statistical modeling of daily rainfall extremes at high spatial resolution and provide diagnostic tools for assessing the ability of climate models to simulate extreme events.

Contact Versus Non-Contact Measurement of a Helicopter Main Rotor Composite Blade

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

Luczak, Marcin; Dziedziech, Kajetan; Peeters, Bart

2010-05-28

The dynamic characterization of lightweight structures is particularly complex as the impact of the weight of sensors and instrumentation (cables, mounting of exciters...) can distort the results. Varying mass loading or constraint effects between partial measurements may determine several errors on the final conclusions. Frequency shifts can lead to erroneous interpretations of the dynamics parameters. Typically these errors remain limited to a few percent. Inconsistent data sets however can result in major processing errors, with all related consequences towards applications based on the consistency assumption, such as global modal parameter identification, model-based damage detection and FRF-based matrix inversion in substructuring,more » load identification and transfer path analysis [1]. This paper addresses the subject of accuracy in the context of the measurement of the dynamic properties of a particular lightweight structure. It presents a comprehensive comparative study between the use of accelerometer, laser vibrometer (scanning LDV) and PU-probe (acoustic particle velocity and pressure) measurements to measure the structural responses, with as final aim the comparison of modal model quality assessment. The object of the investigation is a composite material blade from the main rotor of a helicopter. The presented results are part of an extensive test campaign performed with application of SIMO, MIMO, random and harmonic excitation, and the use of the mentioned contact and non-contact measurement techniques. The advantages and disadvantages of the applied instrumentation are discussed. Presented are real-life measurement problems related to the different set up conditions. Finally an analysis of estimated models is made in view of assessing the applicability of the various measurement approaches for successful fault detection based on modal parameters observation as well as in uncertain non-deterministic numerical model updating.« less

Contact Versus Non-Contact Measurement of a Helicopter Main Rotor Composite Blade

NASA Astrophysics Data System (ADS)

Luczak, Marcin; Dziedziech, Kajetan; Vivolo, Marianna; Desmet, Wim; Peeters, Bart; Van der Auweraer, Herman

2010-05-01

The dynamic characterization of lightweight structures is particularly complex as the impact of the weight of sensors and instrumentation (cables, mounting of exciters…) can distort the results. Varying mass loading or constraint effects between partial measurements may determine several errors on the final conclusions. Frequency shifts can lead to erroneous interpretations of the dynamics parameters. Typically these errors remain limited to a few percent. Inconsistent data sets however can result in major processing errors, with all related consequences towards applications based on the consistency assumption, such as global modal parameter identification, model-based damage detection and FRF-based matrix inversion in substructuring, load identification and transfer path analysis [1]. This paper addresses the subject of accuracy in the context of the measurement of the dynamic properties of a particular lightweight structure. It presents a comprehensive comparative study between the use of accelerometer, laser vibrometer (scanning LDV) and PU-probe (acoustic particle velocity and pressure) measurements to measure the structural responses, with as final aim the comparison of modal model quality assessment. The object of the investigation is a composite material blade from the main rotor of a helicopter. The presented results are part of an extensive test campaign performed with application of SIMO, MIMO, random and harmonic excitation, and the use of the mentioned contact and non-contact measurement techniques. The advantages and disadvantages of the applied instrumentation are discussed. Presented are real-life measurement problems related to the different set up conditions. Finally an analysis of estimated models is made in view of assessing the applicability of the various measurement approaches for successful fault detection based on modal parameters observation as well as in uncertain non-deterministic numerical model updating.

Forecasting the mortality rates using Lee-Carter model and Heligman-Pollard model

NASA Astrophysics Data System (ADS)

Ibrahim, R. I.; Ngataman, N.; Abrisam, W. N. A. Wan Mohd

2017-09-01

Improvement in life expectancies has driven further declines in mortality. The sustained reduction in mortality rates and its systematic underestimation has been attracting the significant interest of researchers in recent years because of its potential impact on population size and structure, social security systems, and (from an actuarial perspective) the life insurance and pensions industry worldwide. Among all forecasting methods, the Lee-Carter model has been widely accepted by the actuarial community and Heligman-Pollard model has been widely used by researchers in modelling and forecasting future mortality. Therefore, this paper only focuses on Lee-Carter model and Heligman-Pollard model. The main objective of this paper is to investigate how accurately these two models will perform using Malaysian data. Since these models involves nonlinear equations that are explicitly difficult to solve, the Matrix Laboratory Version 8.0 (MATLAB 8.0) software will be used to estimate the parameters of the models. Autoregressive Integrated Moving Average (ARIMA) procedure is applied to acquire the forecasted parameters for both models as the forecasted mortality rates are obtained by using all the values of forecasted parameters. To investigate the accuracy of the estimation, the forecasted results will be compared against actual data of mortality rates. The results indicate that both models provide better results for male population. However, for the elderly female population, Heligman-Pollard model seems to underestimate to the mortality rates while Lee-Carter model seems to overestimate to the mortality rates.

Studies of HZE particle interactions and transport for space radiation protection purposes

NASA Technical Reports Server (NTRS)

Townsend, Lawrence W.; Wilson, John W.; Schimmerling, Walter; Wong, Mervyn

1987-01-01

The main emphasis is on developing general methods for accurately predicting high-energy heavy ion (HZE) particle interactions and transport for use by researchers in mission planning studies, in evaluating astronaut self-shielding factors, and in spacecraft shield design and optimization studies. The two research tasks are: (1) to develop computationally fast and accurate solutions to the Boltzmann (transport) equation; and (2) to develop accurate HZE interaction models, from fundamental physical considerations, for use as inputs into these transport codes. Accurate solutions to the HZE transport problem have been formulated through a combination of analytical and numerical techniques. In addition, theoretical models for the input interaction parameters are under development: stopping powers, nuclear absorption cross sections, and fragmentation parameters.

Design of Magnetic Charged Particle Lens Using Analytical Potential Formula

NASA Astrophysics Data System (ADS)

Al-Batat, A. H.; Yaseen, M. J.; Abbas, S. R.; Al-Amshani, M. S.; Hasan, H. S.

2018-05-01

In the current research was to benefit from the potential of the two cylindrical electric lenses to be used in the product a mathematical model from which, one can determine the magnetic field distribution of the charged particle objective lens. With aid of simulink in matlab environment, some simulink models have been building to determine the distribution of the target function and their related axial functions along the optical axis of the charged particle lens. The present study showed that the physical parameters (i.e., the maximum value, Bmax, and the half width W of the field distribution) and the objective properties of the charged particle lens have been affected by varying the main geometrical parameter of the lens named the bore radius R.

Uncertainty quantification and propagation in nuclear density functional theory

DOE PAGES

Schunck, N.; McDonnell, J. D.; Higdon, D.; ...

2015-12-23

Nuclear density functional theory (DFT) is one of the main theoretical tools used to study the properties of heavy and superheavy elements, or to describe the structure of nuclei far from stability. While on-going eff orts seek to better root nuclear DFT in the theory of nuclear forces, energy functionals remain semi-phenomenological constructions that depend on a set of parameters adjusted to experimental data in fi nite nuclei. In this study, we review recent eff orts to quantify the related uncertainties, and propagate them to model predictions. In particular, we cover the topics of parameter estimation for inverse problems, statisticalmore » analysis of model uncertainties and Bayesian inference methods. Illustrative examples are taken from the literature.« less

Is organic matter alone sufficient to predict isoproturon sorption in calcareous soils?

PubMed

El Arfaoui, Achouak; Sayen, Stéphanie; Paris, Michaël; Keziou, Amor; Couderchet, Michel; Guillon, Emmanuel

2012-08-15

Eleven soils collected from Champagne-Ardenne area (France) were used to investigate isoproturon sorption in laboratory conditions. Our results identified the organic matter (OM) and the ratio of calcite content to OM content (Rt) as the main two parameters governing isoproturon retention in soils. While organic matter favored pesticide sorption, calcite had an antagonistic effect since it limited isoproturon retention. The Rt ratio of calcite content to organic matter content in soils appeared to be a parameter that should be considered in predictive models in addition to OM in regions presenting calcareous soils. Adsorption of isoproturon as a function of Rt and OM was successfully described through a simple empirical model. Copyright © 2012 Elsevier B.V. All rights reserved.

A Model-Based Probabilistic Inversion Framework for Wire Fault Detection Using TDR

NASA Technical Reports Server (NTRS)

Schuet, Stefan R.; Timucin, Dogan A.; Wheeler, Kevin R.

2010-01-01

Time-domain reflectometry (TDR) is one of the standard methods for diagnosing faults in electrical wiring and interconnect systems, with a long-standing history focused mainly on hardware development of both high-fidelity systems for laboratory use and portable hand-held devices for field deployment. While these devices can easily assess distance to hard faults such as sustained opens or shorts, their ability to assess subtle but important degradation such as chafing remains an open question. This paper presents a unified framework for TDR-based chafing fault detection in lossy coaxial cables by combining an S-parameter based forward modeling approach with a probabilistic (Bayesian) inference algorithm. Results are presented for the estimation of nominal and faulty cable parameters from laboratory data.

Kinetic Modeling of Sunflower Grain Filling and Fatty Acid Biosynthesis

PubMed Central

Durruty, Ignacio; Aguirrezábal, Luis A. N.; Echarte, María M.

2016-01-01

Grain growth and oil biosynthesis are complex processes that involve various enzymes placed in different sub-cellular compartments of the grain. In order to understand the mechanisms controlling grain weight and composition, we need mathematical models capable of simulating the dynamic behavior of the main components of the grain during the grain filling stage. In this paper, we present a non-structured mechanistic kinetic model developed for sunflower grains. The model was first calibrated for sunflower hybrid ACA855. The calibrated model was able to predict the theoretical amount of carbohydrate equivalents allocated to the grain, grain growth and the dynamics of the oil and non-oil fraction, while considering maintenance requirements and leaf senescence. Incorporating into the model the serial-parallel nature of fatty acid biosynthesis permitted a good representation of the kinetics of palmitic, stearic, oleic, and linoleic acids production. A sensitivity analysis showed that the relative influence of input parameters changed along grain development. Grain growth was mostly affected by the specific growth parameter (μ′) while fatty acid composition strongly depended on their own maximum specific rate parameters. The model was successfully applied to two additional hybrids (MG2 and DK3820). The proposed model can be the first building block toward the development of a more sophisticated model, capable of predicting the effects of environmental conditions on grain weight and composition, in a comprehensive and quantitative way. PMID:27242809

Kinetic modeling of light limitation and sulfur deprivation effects in the induction of hydrogen production with Chlamydomonas reinhardtii: Part I. Model development and parameter identification.

PubMed

Fouchard, Swanny; Pruvost, Jérémy; Degrenne, Benoit; Titica, Mariana; Legrand, Jack

2009-01-01

Chlamydomonas reinhardtii is a green microalga capable of turning its metabolism towards H2 production under specific conditions. However this H2 production, narrowly linked to the photosynthetic process, results from complex metabolic reactions highly dependent on the environmental conditions of the cells. A kinetic model has been developed to relate culture evolution from standard photosynthetic growth to H2 producing cells. It represents transition in sulfur-deprived conditions, known to lead to H2 production in Chlamydomonas reinhardtii, and the two main processes then induced which are an over-accumulation of intracellular starch and a progressive reduction of PSII activity for anoxia achievement. Because these phenomena are directly linked to the photosynthetic growth, two kinetic models were associated, the first (one) introducing light dependency (Haldane type model associated to a radiative light transfer model), the second (one) making growth a function of available sulfur amount under extracellular and intracellular forms (Droop formulation). The model parameters identification was realized from experimental data obtained with especially designed experiments and a sensitivity analysis of the model to its parameters was also conducted. Model behavior was finally studied showing interdependency between light transfer conditions, photosynthetic growth, sulfate uptake, photosynthetic activity and O2 release, during transition from oxygenic growth to anoxic H2 production conditions.

CAA modeling of helicopter main rotor in hover

NASA Astrophysics Data System (ADS)

Kusyumov, Alexander N.; Mikhailov, Sergey A.; Batrakov, Andrey S.; Kusyumov, Sergey A.; Barakos, George

In this work rotor aeroacoustics in hover is considered. Farfield observers are used and the nearfield flow parameters are obtained using the in house HMB and commercial Fluent CFD codes (identical hexa-grids are used for both solvers). Farfield noise at a remote observer position is calculated at post processing stage using FW-H solver implemented in Fluent and HMB. The main rotor of the UH-1H helicopter is considered as a test case for comparison to experimental data. The sound pressure level is estimated for different rotor blade collectives and observation angles.

Mathematical model of the methane replacement by carbon dioxide in the gas hydrate reservoir taking into account the diffusion kinetics

NASA Astrophysics Data System (ADS)

Musakaev, N. G.; Khasanov, M. K.; Rafikova, G. R.

2018-03-01

The problem of the replacement of methane in its hydrate by carbon dioxide in a porous medium is considered. The gas-exchange kinetics scheme is proposed in which the intensity of the process is limited by the diffusion of CO2 through the hydrate layer formed between the gas mixture flow and the CH4 hydrate. Dynamics of the main parameters of the process is numerically investigated. The main characteristic stages of the process are determined.

Elaboration of the α-model derived from the BCS theory of superconductivity

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

Johnston, David C.

2013-10-14

The single-band α-model of superconductivity (Padamsee et al 1973 J. Low Temp. Phys. 12 387) is a popular model that was adapted from the single-band Bardeen–Cooper–Schrieffer (BCS) theory of superconductivity mainly to allow fits to electronic heat capacity versus temperature T data that deviate from the BCS prediction. The model assumes that the normalized superconducting order parameter Δ(T)/Δ(0) and therefore the normalized London penetration depth λL(T)/λL(0) are the same as in BCS theory, calculated using the BCS value αBCS ≈ 1.764 of α ≡ Δ(0)/kBTc, where kB is The single-band α-model of superconductivity (Padamsee et al 1973 J. Low Temp.more » Phys. 12 387) is a popular model that was adapted from the single-band Bardeen–Cooper–Schrieffer (BCS) theory of superconductivity mainly to allow fits to electronic heat capacity versus temperature T data that deviate from the BCS prediction. The model assumes that the normalized superconducting order parameter Δ(T)/Δ(0) and therefore the normalized London penetration depth λL(T)/λL(0) are the same as in BCS theory, calculated using the BCS value αBCS ≈ 1.764 of α ≡ Δ(0)/kBTc, where kB is Boltzmann's constant and Tc is the superconducting transition temperature. On the other hand, to calculate the electronic free energy, entropy, heat capacity and thermodynamic critical field versus T, the α-model takes α to be an adjustable parameter. Here we write the BCS equations and limiting behaviors for the superconducting state thermodynamic properties explicitly in terms of α, as needed for calculations within the α-model, and present plots of the results versus T and α that are compared with the respective BCS predictions. Mechanisms such as gap anisotropy and strong coupling that can cause deviations of the thermodynamics from the BCS predictions, especially the heat capacity jump at Tc, are considered. Extensions of the α-model that have appeared in the literature, such as the two-band model, are also discussed. Tables of values of Δ(T)/Δ(0), the normalized London parameter Λ(T)/Λ(0) and λL(T)/λL(0) calculated from the BCS theory using α = αBCS are provided, which are the same in the α-model by assumption. Tables of values of the entropy, heat capacity and thermodynamic critical field versus T for seven values of α, including αBCS, are also presented.« less

A structural model of the VEGF signalling pathway: emergence of robustness and redundancy properties.

PubMed

Lignet, Floriane; Calvez, Vincent; Grenier, Emmanuel; Ribba, Benjamin

2013-02-01

The vascular endothelial growth factor (VEGF) is known as one of the main promoter of angiogenesis - the process of blood vessel formation. Angiogenesis has been recognized as a key stage for cancer development and metastasis. In this paper, we propose a structural model of the main molecular pathways involved in the endothelial cells response to VEGF stimuli. The model, built on qualitative information from knowledge databases, is composed of 38 ordinary differential equations with 78 parameters and focuses on the signalling driving endothelial cell proliferation, migration and resistance to apoptosis. Following a VEGF stimulus, the model predicts an increase of proliferation and migration capability, and a decrease in the apoptosis activity. Model simulations and sensitivity analysis highlight the emergence of robustness and redundancy properties of the pathway. If further calibrated and validated, this model could serve as tool to analyse and formulate new hypothesis on th e VEGF signalling cascade and its role in cancer development and treatment.

The impact of sea surface currents in wave power potential modeling

NASA Astrophysics Data System (ADS)

Zodiatis, George; Galanis, George; Kallos, George; Nikolaidis, Andreas; Kalogeri, Christina; Liakatas, Aristotelis; Stylianou, Stavros

2015-11-01

The impact of sea surface currents to the estimation and modeling of wave energy potential over an area of increased economic interest, the Eastern Mediterranean Sea, is investigated in this work. High-resolution atmospheric, wave, and circulation models, the latter downscaled from the regional Mediterranean Forecasting System (MFS) of the Copernicus marine service (former MyOcean regional MFS system), are utilized towards this goal. The modeled data are analyzed by means of a variety of statistical tools measuring the potential changes not only in the main wave characteristics, but also in the general distribution of the wave energy and the wave parameters that mainly affect it, when using sea surface currents as a forcing to the wave models. The obtained results prove that the impact of the sea surface currents is quite significant in wave energy-related modeling, as well as temporally and spatially dependent. These facts are revealing the necessity of the utilization of the sea surface currents characteristics in renewable energy studies in conjunction with their meteo-ocean forecasting counterparts.

Predicting the scanning branches of hysteretic soil water-retention capacity with use of the method of mathematical modeling

NASA Astrophysics Data System (ADS)

Terleev, V.; Ginevsky, R.; Lazarev, V.; Nikonorov, A.; Togo, I.; Topaj, A.; Moiseev, K.; Abakumov, E.; Melnichuk, A.; Dunaieva, I.

2017-10-01

A mathematical model of the hysteresis of the water-retention capacity of the soil is proposed. The parameters of the model are interpreted within the framework of physical concepts of the structure and capillary properties of soil pores. On the basis of the model, a computer program with an interface that allows for dialogue with the user is developed. The program has some of options: visualization of experimental data; identification of the model parameters with use of measured data by means of an optimizing algorithm; graphical presentation of the hysteresis loop with application of the assigned parameters. Using the program, computational experiments were carried out, which consisted in verifying the identifiability of the model parameters from data on the main branches, and also in testing the ability to predict the scanning branches of the hysteresis loop. For the experiments, literature data on two sandy soils were used. The absence of an “artificial pump effect” is proved. A sufficiently high accuracy of the prediction of the scanning branches of the hysteresis loop has been achieved in comparison with the three models of the precursors. The practical importance of the proposed model and computer program, which is developed on its basis, is to ensure the calculation of precision irrigation rates. The application of such rates in irrigation farming will help to prevent excess moisture from flowing beyond the root layer of the soil and, thus, minimize the unproductive loss of irrigation water and agrochemicals, as well as reduce the risk of groundwater contamination and natural water eutrophication.

Immersion freezing by natural dust based on a soccer ball model with the Community Atmospheric Model version 5: climate effects

NASA Astrophysics Data System (ADS)

Wang, Yong; Liu, Xiaohong

2014-12-01

We introduce a simplified version of the soccer ball model (SBM) developed by Niedermeier et al (2014 Geophys. Res. Lett. 41 736-741) into the Community Atmospheric Model version 5 (CAM5). It is the first time that SBM is used in an atmospheric model to parameterize the heterogeneous ice nucleation. The SBM, which was simplified for its suitable application in atmospheric models, uses the classical nucleation theory to describe the immersion/condensation freezing by dust in the mixed-phase cloud regime. Uncertain parameters (mean contact angle, standard deviation of contact angle probability distribution, and number of surface sites) in the SBM are constrained by fitting them to recent natural dust (Saharan dust) datasets. With the SBM in CAM5, we investigate the sensitivity of modeled cloud properties to the SBM parameters, and find significant seasonal and regional differences in the sensitivity among the three SBM parameters. Changes of mean contact angle and the number of surface sites lead to changes of cloud properties in Arctic in spring, which could be attributed to the transport of dust ice nuclei to this region. In winter, significant changes of cloud properties induced by these two parameters mainly occur in northern hemispheric mid-latitudes (e.g., East Asia). In comparison, no obvious changes of cloud properties caused by changes of standard deviation can be found in all the seasons. These results are valuable for understanding the heterogeneous ice nucleation behavior, and useful for guiding the future model developments.

Informational Entropy and Bridge Scour Estimation under Complex Hydraulic Scenarios

NASA Astrophysics Data System (ADS)

Pizarro, Alonso; Link, Oscar; Fiorentino, Mauro; Samela, Caterina; Manfreda, Salvatore

2017-04-01

Bridges are important for society because they allow social, cultural and economic connectivity. Flood events can compromise the safety of bridge piers up to the complete collapse. The Bridge Scour phenomena has been described by empirical formulae deduced from hydraulic laboratory experiments. The range of applicability of such models is restricted by the specific hydraulic conditions or flume geometry used for their derivation (e.g., water depth, mean flow velocity, pier diameter and sediment properties). We seek to identify a general formulation able to capture the main dynamic of the process in order to cover a wide range of hydraulic and geometric configuration, allowing to extend our analysis in different contexts. Therefore, exploiting the Principle of Maximum Entropy (POME) and applying it on the recently proposed dimensionless Effective flow work, W*, we derived a simple model characterized by only one parameter. The proposed Bridge Scour Entropic (BRISENT) model shows good performances under complex hydraulic conditions as well as under steady-state flow. Moreover, the model was able to capture the evolution of scour in several hydraulic configurations even if the model contains only one parameter. Furthermore, results show that the model parameter is controlled by the geometric configurations of the experiment. This offers a possible strategy to obtain a priori model parameter calibration. The BRISENT model represents a good candidate for estimating the time-dependent scour depth under complex hydraulic scenarios. The authors are keen to apply this idea for describing the scour behavior during a real flood event. Keywords: Informational entropy, Sediment transport, Bridge pier scour, Effective flow work.

Eye and Head Movement Characteristics in Free Visual Search of Flight-Simulator Imagery

DTIC Science & Technology

2010-03-01

conspicuity. However, only gaze amplitude varied significantly with IFOV. A two- parameter (scale and exponent) power function was fitted to the...main-sequence amplitude-duration data. Both parameters varied significantly with target conspicuity, but in opposite directions. Neither parameter ...IFOV. A two- parameter (scale and exponent) power function was fitted to the main-sequence amplitude-duration data. Both parameters varied

A method for landing gear modeling and simulation with experimental validation

NASA Technical Reports Server (NTRS)

Daniels, James N.

1996-01-01

This document presents an approach for modeling and simulating landing gear systems. Specifically, a nonlinear model of an A-6 Intruder Main Gear is developed, simulated, and validated against static and dynamic test data. This model includes nonlinear effects such as a polytropic gas model, velocity squared damping, a geometry governed model for the discharge coefficients, stick-slip friction effects and a nonlinear tire spring and damping model. An Adams-Moulton predictor corrector was used to integrate the equations of motion until a discontinuity caused by a stick-slip friction model was reached, at which point, a Runga-Kutta routine integrated past the discontinuity and returned the problem solution back to the predictor corrector. Run times of this software are around 2 mins. per 1 sec. of simulation under dynamic circumstances. To validate the model, engineers at the Aircraft Landing Dynamics facilities at NASA Langley Research Center installed one A-6 main gear on a drop carriage and used a hydraulic shaker table to provide simulated runway inputs to the gear. Model parameters were tuned to produce excellent agreement for many cases.

A multiphysics 3D model of tissue growth under interstitial perfusion in a tissue-engineering bioreactor.

PubMed

Nava, Michele M; Raimondi, Manuela T; Pietrabissa, Riccardo

2013-11-01

The main challenge in engineered cartilage consists in understanding and controlling the growth process towards a functional tissue. Mathematical and computational modelling can help in the optimal design of the bioreactor configuration and in a quantitative understanding of important culture parameters. In this work, we present a multiphysics computational model for the prediction of cartilage tissue growth in an interstitial perfusion bioreactor. The model consists of two separate sub-models, one two-dimensional (2D) sub-model and one three-dimensional (3D) sub-model, which are coupled between each other. These sub-models account both for the hydrodynamic microenvironment imposed by the bioreactor, using a model based on the Navier-Stokes equation, the mass transport equation and the biomass growth. The biomass, assumed as a phase comprising cells and the synthesised extracellular matrix, has been modelled by using a moving boundary approach. In particular, the boundary at the fluid-biomass interface is moving with a velocity depending from the local oxygen concentration and viscous stress. In this work, we show that all parameters predicted, such as oxygen concentration and wall shear stress, by the 2D sub-model with respect to the ones predicted by the 3D sub-model are systematically overestimated and thus the tissue growth, which directly depends on these parameters. This implies that further predictive models for tissue growth should take into account of the three dimensionality of the problem for any scaffold microarchitecture.

Getting a feel for parameters: using interactive parallel plots as a tool for parameter identification in the new rainfall-runoff model WALRUS

NASA Astrophysics Data System (ADS)

Brauer, Claudia; Torfs, Paul; Teuling, Ryan; Uijlenhoet, Remko

2015-04-01

Recently, we developed the Wageningen Lowland Runoff Simulator (WALRUS) to fill the gap between complex, spatially distributed models often used in lowland catchments and simple, parametric models which have mostly been developed for mountainous catchments (Brauer et al., 2014ab). This parametric rainfall-runoff model can be used all over the world in both freely draining lowland catchments and polders with controlled water levels. The open source model code is implemented in R and can be downloaded from www.github.com/ClaudiaBrauer/WALRUS. The structure and code of WALRUS are simple, which facilitates detailed investigation of the effect of parameters on all model variables. WALRUS contains only four parameters requiring calibration; they are intended to have a strong, qualitative relation with catchment characteristics. Parameter estimation remains a challenge, however. The model structure contains three main feedbacks: (1) between groundwater and surface water; (2) between saturated and unsaturated zone; (3) between catchment wetness and (quick/slow) flowroute division. These feedbacks represent essential rainfall-runoff processes in lowland catchments, but increase the risk of parameter dependence and equifinality. Therefore, model performance should not only be judged based on a comparison between modelled and observed discharges, but also based on the plausibility of the internal modelled variables. Here, we present a method to analyse the effect of parameter values on internal model states and fluxes in a qualitative and intuitive way using interactive parallel plotting. We applied WALRUS to ten Dutch catchments with different sizes, slopes and soil types and both freely draining and polder areas. The model was run with a large number of parameter sets, which were created using Latin Hypercube Sampling. The model output was characterised in terms of several signatures, both measures of goodness of fit and statistics of internal model variables (such as the percentage of rain water travelling through the quickflow reservoir). End users can then eliminate parameter combinations with unrealistic outcomes based on expert knowledge using interactive parallel plots. In these plots, for instance, ranges can be selected for each signature and only model runs which yield signature values in these ranges are highlighted. The resulting selection of realistic parameter sets can be used for ensemble simulations. C.C. Brauer, A.J. Teuling, P.J.J.F. Torfs, R. Uijlenhoet (2014a): The Wageningen Lowland Runoff Simulator (WALRUS): a lumped rainfall-runoff model for catchments with shallow groundwater, Geoscientific Model Development, 7, 2313-2332, www.geosci-model-dev.net/7/2313/2014/gmd-7-2313-2014.pdf C.C. Brauer, P.J.J.F. Torfs, A.J. Teuling, R. Uijlenhoet (2014b): The Wageningen Lowland Runoff Simulator (WALRUS): application to the Hupsel Brook catchment and Cabauw polder, Hydrology and Earth System Sciences, 18, 4007-4028, www.hydrol-earth-syst-sci.net/18/4007/2014/hess-18-4007-2014.pdf

Comparison of Malaria Simulations Driven by Meteorological Observations and Reanalysis Products in Senegal.

PubMed

Diouf, Ibrahima; Rodriguez-Fonseca, Belen; Deme, Abdoulaye; Caminade, Cyril; Morse, Andrew P; Cisse, Moustapha; Sy, Ibrahima; Dia, Ibrahima; Ermert, Volker; Ndione, Jacques-André; Gaye, Amadou Thierno

2017-09-25

The analysis of the spatial and temporal variability of climate parameters is crucial to study the impact of climate-sensitive vector-borne diseases such as malaria. The use of malaria models is an alternative way of producing potential malaria historical data for Senegal due to the lack of reliable observations for malaria outbreaks over a long time period. Consequently, here we use the Liverpool Malaria Model (LMM), driven by different climatic datasets, in order to study and validate simulated malaria parameters over Senegal. The findings confirm that the risk of malaria transmission is mainly linked to climate variables such as rainfall and temperature as well as specific landscape characteristics. For the whole of Senegal, a lag of two months is generally observed between the peak of rainfall in August and the maximum number of reported malaria cases in October. The malaria transmission season usually takes place from September to November, corresponding to the second peak of temperature occurring in October. Observed malaria data from the Programme National de Lutte contre le Paludisme (PNLP, National Malaria control Programme in Senegal) and outputs from the meteorological data used in this study were compared. The malaria model outputs present some consistencies with observed malaria dynamics over Senegal, and further allow the exploration of simulations performed with reanalysis data sets over a longer time period. The simulated malaria risk significantly decreased during the 1970s and 1980s over Senegal. This result is consistent with the observed decrease of malaria vectors and malaria cases reported by field entomologists and clinicians in the literature. The main differences between model outputs and observations regard amplitude, but can be related not only to reanalysis deficiencies but also to other environmental and socio-economic factors that are not included in this mechanistic malaria model framework. The present study can be considered as a validation of the reliability of reanalysis to be used as inputs for the calculation of malaria parameters in the Sahel using dynamical malaria models.

Parameter variation of the one-diode model of a-Si and a- Si/μc-Si solar cells for modeling light-induced degradation

NASA Astrophysics Data System (ADS)

Weicht, J. A.; Hamelmann, F. U.; Behrens, G.

2014-11-01

For analyzing the long-term behavior of thin film a-Si/μc-Si photovoltaic modules, it is important to observe the light-induced degradation (LID) in dependence of the temperature for the parameters of the one-diode model for solar cells. According to the IEC 61646 standard, the impact of LID on module parameters of these thin film cells is determined at a constant temperature of 50°C with an irradiation of 1000 W/m2 at open circuit conditions. Previous papers examined the LID of thin film a-Si cells with different temperatures and some others are about a-Si/μc-Si. In these previous papers not all parameters of the one-diode model are examined. We observed the serial resistance (Rs), parallel resistance (Rp), short circuit current (Isc), open circuit voltage (Uoc), the maximum power point (MPP: Umpp, Impp and Pmpp) and the diode factor (n). Since the main reason for the LID of silicon-based thin films is the Staebler Wronski effect in the a-Si part of the cell, the temperature dependence of the healing of defects for all parameters of the one-diode model is also taken into account. We are also measuring modules with different kind of transparent conductive oxides: In a-Si thin film solar cells fluorine-doped tin oxide (FTO) is used and for thin film solar cells of a-Si/μc-Si boron- doped zinc oxide is used. In our work we describe an approach for transferring the parameters of a one-diode model for tandem thin film solar cells into the one-diode model for each part of the solar cell. The measurement of degradation and regeneration at higher temperatures is the necessary base for optimization of the different silicon-based thin films in warm hot climate.

Asteroseismology from multi-month Kepler photometry: the evolved Sun-like stars KIC 10273246 and KIC 10920273

NASA Astrophysics Data System (ADS)

Campante, T. L.; Handberg, R.; Mathur, S.; Appourchaux, T.; Bedding, T. R.; Chaplin, W. J.; García, R. A.; Mosser, B.; Benomar, O.; Bonanno, A.; Corsaro, E.; Fletcher, S. T.; Gaulme, P.; Hekker, S.; Karoff, C.; Régulo, C.; Salabert, D.; Verner, G. A.; White, T. R.; Houdek, G.; Brandão, I. M.; Creevey, O. L.; Doǧan, G.; Bazot, M.; Christensen-Dalsgaard, J.; Cunha, M. S.; Elsworth, Y.; Huber, D.; Kjeldsen, H.; Lundkvist, M.; Molenda-Żakowicz, J.; Monteiro, M. J. P. F. G.; Stello, D.; Clarke, B. D.; Girouard, F. R.; Hall, J. R.

2011-10-01

Context. The evolved main-sequence Sun-like stars KIC 10273246 (F-type) and KIC 10920273 (G-type) were observed with the NASA Kepler satellite for approximately ten months with a duty cycle in excess of 90%. Such continuous and long observations are unprecedented for solar-type stars other than the Sun. Aims: We aimed mainly at extracting estimates of p-mode frequencies - as well as of other individual mode parameters - from the power spectra of the light curves of both stars, thus providing scope for a full seismic characterization. Methods: The light curves were corrected for instrumental effects in a manner independent of the Kepler science pipeline. Estimation of individual mode parameters was based both on the maximization of the likelihood of a model describing the power spectrum and on a classic prewhitening method. Finally, we employed a procedure for selecting frequency lists to be used in stellar modeling. Results: A total of 30 and 21 modes of degree l = 0,1,2 - spanning at least eight radial orders - have been identified for KIC 10273246 and KIC 10920273, respectively. Two avoided crossings (l = 1 ridge) have been identified for KIC 10273246, whereas one avoided crossing plus another likely one have been identified for KIC 10920273. Good agreement is found between observed and predicted mode amplitudes for the F-type star KIC 10273246, based on a revised scaling relation. Estimates are given of the rotational periods, the parameters describing stellar granulation and the global asteroseismic parameters Δν and νmax.

Research on Bell-Shaped Vibratory Angular Rate Gyro's Character of Resonator

PubMed Central

Su, Zhong; Fu, Mengyin; Li, Qing; Liu, Ning; Liu, Hong

2013-01-01

Bell-shaped vibratory angular rate gyro (abbreviated as BVG) is a new type Coriolis vibratory gyro that was inspired by Chinese traditional clocks. The resonator fuses based on a variable thickness axisymmetric multicurved surface shell. Its characteristics can directly influence the performance of BVG. The BVG structure not only has capabilities of bearing high overload, high impact and, compared with the tuning fork, vibrating beam, shell and a comb structure, but also a higher frequency to overcome the influence of the disturbance of the exterior environment than the same sized hemispherical resonator gyroscope (HRG) and the traditional cylinder vibratory gyroscope. It can be widely applied in high dynamic low precision angular rate measurement occasions. The main work is as follows: the issue mainly analyzes the structure and basic principle, and investigates the bell-shaped resonator's mathematical model. The reasonable structural parameters are obtained from finite element analysis and an intelligent platform. Using the current solid vibration gyro theory analyzes the structural characteristics and principles of BVG. The bell-shaped resonator is simplified as a paraboloid of the revolution mechanical model, which has a fixed closed end and a free opened end. It obtains the natural frequency and vibration modes based on the theory of elasticity. The structural parameters are obtained from the orthogonal method by the research on the structural parameters of the resonator analysis. It obtains the modal analysis, stress analysis and impact analysis with the chosen parameters. Finally, using the turntable experiment verifies the gyro effect of the BVG. PMID:23575033

A physically based catchment partitioning method for hydrological analysis

NASA Astrophysics Data System (ADS)

Menduni, Giovanni; Riboni, Vittoria

2000-07-01

We propose a partitioning method for the topographic surface, which is particularly suitable for hydrological distributed modelling and shallow-landslide distributed modelling. The model provides variable mesh size and appears to be a natural evolution of contour-based digital terrain models. The proposed method allows the drainage network to be derived from the contour lines. The single channels are calculated via a search for the steepest downslope lines. Then, for each network node, the contributing area is determined by means of a search for both steepest upslope and downslope lines. This leads to the basin being partitioned into physically based finite elements delimited by irregular polygons. In particular, the distributed computation of local geomorphological parameters (i.e. aspect, average slope and elevation, main stream length, concentration time, etc.) can be performed easily for each single element. The contributing area system, together with the information on the distribution of geomorphological parameters provide a useful tool for distributed hydrological modelling and simulation of environmental processes such as erosion, sediment transport and shallow landslides.

The effect of friction in the hold down post spherical bearings on hold down post loads

NASA Technical Reports Server (NTRS)

Richardson, James A.

1990-01-01

The effect of friction at the connection of the Solid Rocket Booster (SRB) aft skirt and the mobile launch platform (MLP) hold down posts was analyzed. A simplified model of the shuttle response during the Space Shuttle Main Engine (SSME) buildup was constructed. The model included the effect of stick-slip friction for the rotation of the skirt about the spherical bearing. Current finite element models assume the joint is completely frictionless in rotation and therefore no moment is transferred between the skirt and the hold down posts. The model was partially verified against test data and preliminary parameter studies were performed. The parameter studies indicated that the coefficient of friction strongly influenced the moment on the hold down posts. The coefficient of friction had little effect on hold down post vertical loads, however. Further calibration of the model is necessary before the effect of friction on the hold down post horizontal loads can be analyzed.

DEM modeling of flexible structures against granular material avalanches

NASA Astrophysics Data System (ADS)

Lambert, Stéphane; Albaba, Adel; Nicot, François; Chareyre, Bruno

2016-04-01

This article presents the numerical modeling of flexible structures intended to contain avalanches of granular and coarse material (e.g. rock slide, a debris slide). The numerical model is based on a discrete element method (YADE-Dem). The DEM modeling of both the flowing granular material and the flexible structure are detailed before presenting some results. The flowing material consists of a dry polydisperse granular material accounting for the non-sphericity of real materials. The flexible structure consists in a metallic net hanged on main cables, connected to the ground via anchors, on both sides of the channel, including dissipators. All these components were modeled as flexible beams or wires, with mechanical parameters defined from literature data. The simulation results are presented with the aim of investigating the variability of the structure response depending on different parameters related to the structure (inclination of the fence, with/without brakes, mesh size opening), but also to the channel (inclination). Results are then compared with existing recommendations in similar fields.

Evaluation of modeled bacteria loads along an impaired stream reach receiving discharge from a municipal separate storm sewer system in Independence, Mo.

USGS Publications Warehouse

Flickinger, Allison; Christensen, Eric D.

2017-01-01

The Little Blue River in Jackson County, Missouri, was listed as impaired in 2012 due to Escherichia coli (E. coli) from urban runoff and storm sewers. A study was initiated to characterize E. coli concentrations and loads to aid in the development of a total maximum daily load implementation plan. Longitudinal sampling along the stream revealed spatial and temporal variability in E. coli loads. Regression models were developed to better represent E. coli variability in the impaired reach using continuous hydrologic and water-quality parameters as predictive parameters. Daily loads calculated from main-stem samples were significantly higher downstream compared to upstream even though there was no significant difference between the upstream and downstream measured concentrations and no significant conclusions could be drawn from model-estimated loads due to model-associated uncertainty. Increasing sample frequency could decrease the bias and increase the accuracy of the modeled results.

Cost and performance model for redox flow batteries

NASA Astrophysics Data System (ADS)

Viswanathan, Vilayanur; Crawford, Alasdair; Stephenson, David; Kim, Soowhan; Wang, Wei; Li, Bin; Coffey, Greg; Thomsen, Ed; Graff, Gordon; Balducci, Patrick; Kintner-Meyer, Michael; Sprenkle, Vincent

2014-02-01

A cost model is developed for all vanadium and iron-vanadium redox flow batteries. Electrochemical performance modeling is done to estimate stack performance at various power densities as a function of state of charge and operating conditions. This is supplemented with a shunt current model and a pumping loss model to estimate actual system efficiency. The operating parameters such as power density, flow rates and design parameters such as electrode aspect ratio and flow frame channel dimensions are adjusted to maximize efficiency and minimize capital costs. Detailed cost estimates are obtained from various vendors to calculate cost estimates for present, near-term and optimistic scenarios. The most cost-effective chemistries with optimum operating conditions for power or energy intensive applications are determined, providing a roadmap for battery management systems development for redox flow batteries. The main drivers for cost reduction for various chemistries are identified as a function of the energy to power ratio of the storage system. Levelized cost analysis further guide suitability of various chemistries for different applications.

Analysis of habitat characteristics of small pelagic fish based on generalized additive models in Kepulauan Seribu Waters

NASA Astrophysics Data System (ADS)

Rivai, A. A.; Siregar, V. P.; Agus, S. B.; Yasuma, H.

2018-03-01

One of the required information for sustainable fisheries management is about the habitat characteristics of a fish species. This information can be used to map the distribution of fish and map the potential fishing ground. This study aimed to analyze the habitat characteristics of small pelagic fishes (anchovy, squid, sardine and scads) which were mainly caught by lift net in Kepulauan Seribu waters. Research on habitat characteristics had been widely done, but the use of total suspended solid (TSS) parameters in this analysis is still lacking. TSS parameter which was extracted from Landsat 8 along with five other oceanographic parameters, CPUE data and location of fishing ground data from lift net fisheries in Kepulauan Seribu were included in this analysis. This analysis used Generalized Additive Models (GAMs) to evaluate the relationship between CPUE and oceanographic parameters. The results of the analysis showed that each fish species had different habitat characteristics. TSS and sea surface height had a great influence on the value of CPUE from each species. All the oceanographic parameters affected the CPUE of each species. This study demonstrated the effective use of GAMs to identify the essential habitat of a fish species.

Aerodynamic parameters of High-Angle-of attack Research Vehicle (HARV) estimated from flight data

NASA Technical Reports Server (NTRS)

Klein, Vladislav; Ratvasky, Thomas R.; Cobleigh, Brent R.

1990-01-01

Aerodynamic parameters of the High-Angle-of-Attack Research Aircraft (HARV) were estimated from flight data at different values of the angle of attack between 10 degrees and 50 degrees. The main part of the data was obtained from small amplitude longitudinal and lateral maneuvers. A small number of large amplitude maneuvers was also used in the estimation. The measured data were first checked for their compatibility. It was found that the accuracy of air data was degraded by unexplained bias errors. Then, the data were analyzed by a stepwise regression method for obtaining a structure of aerodynamic model equations and least squares parameter estimates. Because of high data collinearity in several maneuvers, some of the longitudinal and all lateral maneuvers were reanalyzed by using two biased estimation techniques, the principal components regression and mixed estimation. The estimated parameters in the form of stability and control derivatives, and aerodynamic coefficients were plotted against the angle of attack and compared with the wind tunnel measurements. The influential parameters are, in general, estimated with acceptable accuracy and most of them are in agreement with wind tunnel results. The simulated responses of the aircraft showed good prediction capabilities of the resulting model.

Application of all relevant feature selection for failure analysis of parameter-induced simulation crashes in climate models

NASA Astrophysics Data System (ADS)

Paja, W.; Wrzesień, M.; Niemiec, R.; Rudnicki, W. R.

2015-07-01

The climate models are extremely complex pieces of software. They reflect best knowledge on physical components of the climate, nevertheless, they contain several parameters, which are too weakly constrained by observations, and can potentially lead to a crash of simulation. Recently a study by Lucas et al. (2013) has shown that machine learning methods can be used for predicting which combinations of parameters can lead to crash of simulation, and hence which processes described by these parameters need refined analyses. In the current study we reanalyse the dataset used in this research using different methodology. We confirm the main conclusion of the original study concerning suitability of machine learning for prediction of crashes. We show, that only three of the eight parameters indicated in the original study as relevant for prediction of the crash are indeed strongly relevant, three other are relevant but redundant, and two are not relevant at all. We also show that the variance due to split of data between training and validation sets has large influence both on accuracy of predictions and relative importance of variables, hence only cross-validated approach can deliver robust prediction of performance and relevance of variables.

Ergodicity-breaking bifurcations and tunneling in hyperbolic transport models

NASA Astrophysics Data System (ADS)

Giona, M.; Brasiello, A.; Crescitelli, S.

2015-11-01

One of the main differences between parabolic transport, associated with Langevin equations driven by Wiener processes, and hyperbolic models related to generalized Kac equations driven by Poisson processes, is the occurrence in the latter of multiple stable invariant densities (Frobenius multiplicity) in certain regions of the parameter space. This phenomenon is associated with the occurrence in linear hyperbolic balance equations of a typical bifurcation, referred to as the ergodicity-breaking bifurcation, the properties of which are thoroughly analyzed.

Tachyon logamediate inflation on the brane

NASA Astrophysics Data System (ADS)

Kamali, Vahid; Nik, Elahe Navaee

2017-07-01

According to a Barrow solution for the scale factor of the universe, the main properties of the tachyon inflation model in the framework of the RSII braneworld are studied. Within this framework the basic slow-roll parameters are calculated analytically. We compare this inflationary scenario to the latest observational data. The predicted spectral index and the tensor-to-scalar fluctuation ratio are in excellent agreement with those of Planck 2015. The current predictions are consistent with those of viable inflationary models.

Updated T2K measurements of muon neutrino and antineutrino disappearance using 1.5 ×1 021 protons on target

NASA Astrophysics Data System (ADS)

Abe, K.; Amey, J.; Andreopoulos, C.; Antonova, M.; Aoki, S.; Ariga, A.; Ashida, Y.; Autiero, D.; Ban, S.; Barbi, M.; Barker, G. J.; Barr, G.; Barry, C.; Bartet-Friburg, P.; Batkiewicz, M.; Berardi, V.; Berkman, S.; Bhadra, S.; Bienstock, S.; Blondel, A.; Bolognesi, S.; Bordoni, S.; Boyd, S. B.; Brailsford, D.; Bravar, A.; Bronner, C.; Buizza Avanzini, M.; Calland, R. G.; Campbell, T.; Cao, S.; Cartwright, S. L.; Catanesi, M. G.; Cervera, A.; Chappell, A.; Checchia, C.; Cherdack, D.; Chikuma, N.; Christodoulou, G.; Clifton, A.; Coleman, J.; Collazuol, G.; Coplowe, D.; Cudd, A.; Dabrowska, A.; De Rosa, G.; Dealtry, T.; Denner, P. F.; Dennis, S. R.; Densham, C.; Dewhurst, D.; Di Lodovico, F.; Dolan, S.; Drapier, O.; Duffy, K. E.; Dumarchez, J.; Dunne, P.; Dziewiecki, M.; Emery-Schrenk, S.; Ereditato, A.; Feusels, T.; Finch, A. J.; Fiorentini, G. A.; Friend, M.; Fujii, Y.; Fukuda, D.; Fukuda, Y.; Galymov, V.; Garcia, A.; Giganti, C.; Gizzarelli, F.; Golan, T.; Gonin, M.; Hadley, D. R.; Haegel, L.; Haigh, J. T.; Hansen, D.; Harada, J.; Hartz, M.; Hasegawa, T.; Hastings, N. C.; Hayashino, T.; Hayato, Y.; Helmer, R. L.; Hillairet, A.; Hiraki, T.; Hiramoto, A.; Hirota, S.; Hogan, M.; Holeczek, J.; Hosomi, F.; Huang, K.; Ichikawa, A. K.; Ikeda, M.; Imber, J.; Insler, J.; Intonti, R. A.; Ishida, T.; Ishii, T.; Iwai, E.; Iwamoto, K.; Izmaylov, A.; Jamieson, B.; Jiang, M.; Johnson, S.; Jonsson, P.; Jung, C. K.; Kabirnezhad, M.; Kaboth, A. C.; Kajita, T.; Kakuno, H.; Kameda, J.; Karlen, D.; Katori, T.; Kearns, E.; Khabibullin, M.; Khotjantsev, A.; Kim, H.; Kim, J.; King, S.; Kisiel, J.; Knight, A.; Knox, A.; Kobayashi, T.; Koch, L.; Koga, T.; Koller, P. P.; Konaka, A.; Kormos, L. L.; Korzenev, A.; Koshio, Y.; Kowalik, K.; Kropp, W.; Kudenko, Y.; Kurjata, R.; Kutter, T.; Lagoda, J.; Lamont, I.; Lamoureux, M.; Larkin, E.; Lasorak, P.; Laveder, M.; Lawe, M.; Licciardi, M.; Lindner, T.; Liptak, Z. J.; Litchfield, R. P.; Li, X.; Longhin, A.; Lopez, J. P.; Lou, T.; Ludovici, L.; Lu, X.; Magaletti, L.; Mahn, K.; Malek, M.; Manly, S.; Maret, L.; Marino, A. D.; Martin, J. F.; Martins, P.; Martynenko, S.; Maruyama, T.; Matveev, V.; Mavrokoridis, K.; Ma, W. Y.; Mazzucato, E.; McCarthy, M.; McCauley, N.; McFarland, K. S.; McGrew, C.; Mefodiev, A.; Metelko, C.; Mezzetto, M.; Mijakowski, P.; Minamino, A.; Mineev, O.; Mine, S.; Missert, A.; Miura, M.; Moriyama, S.; Morrison, J.; Mueller, Th. A.; Myslik, J.; Nakadaira, T.; Nakahata, M.; Nakamura, K. G.; Nakamura, K.; Nakamura, K. D.; Nakanishi, Y.; Nakayama, S.; Nakaya, T.; Nakayoshi, K.; Nantais, C.; Nielsen, C.; Nirkko, M.; Nishikawa, K.; Nishimura, Y.; Novella, P.; Nowak, J.; O'Keeffe, H. M.; Okumura, K.; Okusawa, T.; Oryszczak, W.; Oser, S. M.; Ovsyannikova, T.; Owen, R. A.; Oyama, Y.; Palladino, V.; Palomino, J. L.; Paolone, V.; Patel, N. D.; Paudyal, P.; Pavin, M.; Payne, D.; Perkin, J. D.; Petrov, Y.; Pickard, L.; Pickering, L.; Pinzon Guerra, E. S.; Pistillo, C.; Popov, B.; Posiadala-Zezula, M.; Poutissou, J.-M.; Poutissou, R.; Pritchard, A.; Przewlocki, P.; Quilain, B.; Radermacher, T.; Radicioni, E.; Ratoff, P. N.; Ravonel, M.; Rayner, M. A.; Redij, A.; Reinherz-Aronis, E.; Riccio, C.; Rondio, E.; Rossi, B.; Roth, S.; Rubbia, A.; Ruggeri, A. C.; Rychter, A.; Sakashita, K.; Sánchez, F.; Scantamburlo, E.; Scholberg, K.; Schwehr, J.; Scott, M.; Seiya, Y.; Sekiguchi, T.; Sekiya, H.; Sgalaberna, D.; Shah, R.; Shaikhiev, A.; Shaker, F.; Shaw, D.; Shiozawa, M.; Shirahige, T.; Short, S.; Smy, M.; Sobczyk, J. T.; Sobel, H.; Sorel, M.; Southwell, L.; Steinmann, J.; Stewart, T.; Stowell, P.; Suda, Y.; Suvorov, S.; Suzuki, A.; Suzuki, S. Y.; Suzuki, Y.; Tacik, R.; Tada, M.; Takeda, A.; Takeuchi, Y.; Tamura, R.; Tanaka, H. K.; Tanaka, H. A.; Terhorst, D.; Terri, R.; Thakore, T.; Thompson, L. F.; Tobayama, S.; Toki, W.; Tomura, T.; Touramanis, C.; Tsukamoto, T.; Tzanov, M.; Uchida, Y.; Vagins, M.; Vallari, Z.; Vasseur, G.; Vilela, C.; Vladisavljevic, T.; Wachala, T.; Walter, C. W.; Wark, D.; Wascko, M. O.; Weber, A.; Wendell, R.; Wilkes, R. J.; Wilking, M. J.; Wilkinson, C.; Wilson, J. R.; Wilson, R. J.; Wret, C.; Yamada, Y.; Yamamoto, K.; Yamamoto, M.; Yanagisawa, C.; Yano, T.; Yen, S.; Yershov, N.; Yokoyama, M.; Yoshida, K.; Yuan, T.; Yu, M.; Zalewska, A.; Zalipska, J.; Zambelli, L.; Zaremba, K.; Ziembicki, M.; Zimmerman, E. D.; Zito, M.; Żmuda, J.; T2K Collaboration

2017-07-01

We report measurements by the T2K experiment of the parameters θ23 and Δ m322 governing the disappearance of muon neutrinos and antineutrinos in the three-flavor neutrino oscillation model. Utilizing the ability of the experiment to run with either a mainly neutrino or a mainly antineutrino beam, the parameters are measured separately for neutrinos and antineutrinos. Using 7.482 ×1 020 POT in neutrino running mode and 7.471 ×1 020 POT in antineutrino mode, T2K obtained sin2(θ23)=0.5 1-0.07+0.08 and Δ m322=2.5 3-0.13+0.15×10-3 eV2/c4 for neutrinos, and sin2(θ¯23)=0.4 2-0.07+0.25 and Δm¯ 2 32=2.5 5-0.27+0.33×10-3 eV2/c4 for antineutrinos (assuming normal mass ordering). No significant differences between the values of the parameters describing the disappearance of muon neutrinos and antineutrinos were observed.

Main controlling factors and forecasting models of lead accumulation in earthworms based on low-level lead-contaminated soils.

PubMed

Tang, Ronggui; Ding, Changfeng; Ma, Yibing; Wan, Mengxue; Zhang, Taolin; Wang, Xingxiang

2018-06-02

To explore the main controlling factors in soil and build a predictive model between the lead concentrations in earthworms (Pb earthworm ) and the soil physicochemical parameters, 13 soils with low level of lead contamination were used to conduct toxicity experiments using earthworms. The results indicated that a relatively high bioaccumulation factor appeared in the soils with low pH values. The lead concentrations between earthworms and soils after log transformation had a significantly positive correlation (R 2  = 0.46, P < 0.0001, n = 39). Stepwise multiple linear regression analysis derived a fitting empirical model between Pb earthworm and the soil physicochemical properties: log(Pb earthworm ) = 0.96log(Pb soil ) - 0.74log(OC) - 0.22pH + 0.95, (R 2  = 0.66, n = 39). Furthermore, path analysis confirmed that the Pb concentrations in the soil (Pb soil ), soil pH, and soil organic carbon (OC) were the primary controlling factors of Pb earthworm with high pathway parameters (0.71, - 0.51, and - 0.49, respectively). The predictive model based on Pb earthworm in a nationwide range of soils with low-level lead contamination could provide a reference for the establishment of safety thresholds in Pb-contaminated soils from the perspective of soil-animal systems.

Crack propagation modelling for high strength steel welded structural details

NASA Astrophysics Data System (ADS)

Mecséri, B. J.; Kövesdi, B.

2017-05-01

Nowadays the barrier of applying HSS (High Strength Steel) material in bridge structures is their low fatigue strength related to yield strength. This paper focuses on the fatigue behaviour of a structural details (a gusset plate connection) made from NSS and HSS material, which is frequently used in bridges in Hungary. An experimental research program is carried out at the Budapest University of Technology and Economics to investigate the fatigue lifetime of this structural detail type through the same test specimens made from S235 and S420 steel grades. The main aim of the experimental research program is to study the differences in the crack propagation and the fatigue lifetime between normal and high strength steel structures. Based on the observed fatigue crack pattern the main direction and velocity of the crack propagation is determined. In parallel to the tests finite element model (FEM) are also developed, which model can handle the crack propagation. Using the measured strain data in the tests and the calculated values from the FE model, the approximation of the material parameters of the Paris law are calculated step-by-step, and their calculated values are evaluated. The same material properties are determined for NSS and also for HSS specimens as well, and the differences are discussed. In the current paper, the results of the experiments, the calculation method of the material parameters and the calculated values are introduced.

Global sensitivity analysis of a local water balance model predicting evaporation, water yield and drought

NASA Astrophysics Data System (ADS)

Speich, Matthias; Zappa, Massimiliano; Lischke, Heike

2017-04-01

Evaporation and transpiration affect both catchment water yield and the growing conditions for vegetation. They are driven by climate, but also depend on vegetation, soil and land surface properties. In hydrological and land surface models, these properties may be included as constant parameters, or as state variables. Often, little is known about the effect of these variables on model outputs. In the present study, the effect of surface properties on evaporation was assessed in a global sensitivity analysis. To this effect, we developed a simple local water balance model combining state-of-the-art process formulations for evaporation, transpiration and soil water balance. The model is vertically one-dimensional, and the relative simplicity of its process formulations makes it suitable for integration in a spatially distributed model at regional scale. The main model outputs are annual total evaporation (TE, i.e. the sum of transpiration, soil evaporation and interception), and a drought index (DI), which is based on the ratio of actual and potential transpiration. This index represents the growing conditions for forest trees. The sensitivity analysis was conducted in two steps. First, a screening analysis was applied to identify unimportant parameters out of an initial set of 19 parameters. In a second step, a statistical meta-model was applied to a sample of 800 model runs, in which the values of the important parameters were varied. Parameter effect and interactions were analyzed with effects plots. The model was driven with forcing data from ten meteorological stations in Switzerland, representing a wide range of precipitation regimes across a strong temperature gradient. Of the 19 original parameters, eight were identified as important in the screening analysis. Both steps highlighted the importance of Plant Available Water Capacity (AWC) and Leaf Area Index (LAI). However, their effect varies greatly across stations. For example, while a transition from a sparse to a closed forest canopy has almost no effect on annual TE at warm and dry sites, it increases TE by up to 100 mm/year at cold-humid and warm-humid sites. Further parameters of importance describe infiltration, as well as canopy resistance and its response to environmental variables. This study offers insights for future development of hydrological and ecohydrological models. First, it shows that although local water balance is primarily controlled by climate, the vegetation and soil parameters may have a large impact on the outputs. Second, it indicates that modeling studies should prioritize a realistic parameterization of LAI and AWC, while other parameters may be set to fixed values. Third, it illustrates to which extent parameter effect and interactions depend on local climate.

Retrieval of pine forest biomass using JPL AIRSAR data

NASA Technical Reports Server (NTRS)

Beaudoin, A.; Letoan, T.; Zagolski, F.; Hsu, C. C.; Han, H. C.; Kong, J. A.

1992-01-01

The analysis of Jet Propulsion Laboratory (JPL) Airborne Synthetic Aperture Radar (AIRSAR) data over the Landes forest in South-West France revealed strong correlation between L- and especially P-band sigma degrees and the pine forest biomass. To explain the physical link of radar backscatter to biomass, a polarimetric backscattering model was developed and validated. Then the model was used in a simulation study to predict sigma degree sensitivity to undesired canopy and environmental parameters. Main results concerning the data analysis, modeling, and simulation at P-band are reported.

Short cell-penetrating peptides: a model of interactions with gene promoter sites.

PubMed

Khavinson, V Kh; Tarnovskaya, S I; Linkova, N S; Pronyaeva, V E; Shataeva, L K; Yakutseni, P P

2013-01-01

Analysis of the main parameters of molecular mechanics (number of hydrogen bonds, hydrophobic and electrostatic interactions, DNA-peptide complex minimization energy) provided the data to validate the previously proposed qualitative models of peptide-DNA interactions and to evaluate their quantitative characteristics. Based on these estimations, a three-dimensional model of Lys-Glu and Ala-Glu-Asp-Gly peptide interactions with DNA sites (GCAG and ATTTC) located in the promoter zones of genes encoding CD5, IL-2, MMP2, and Tram1 signal molecules.

Basic research for the geodynamics program

NASA Technical Reports Server (NTRS)

1986-01-01

Further development of utility program software for analyzing final results of Earth rotation parameter determination from different space geodetic systems was completed. Main simulation experiments were performed. Results and conclusions were compiled. The utilization of range-difference observations in geodynamics is also examined. A method based on the Bayesian philosophy and entropy measure of information is given for the elucidation of time-dependent models of crustal motions as part of a proposed algorithm. The strategy of model discrimination and design of measurements is illustrated in an example for the case of crustal deformation models.

Intermediate-term forecasting of aftershocks from an early aftershock sequence: Bayesian and ensemble forecasting approaches

NASA Astrophysics Data System (ADS)

Omi, Takahiro; Ogata, Yosihiko; Hirata, Yoshito; Aihara, Kazuyuki

2015-04-01

Because aftershock occurrences can cause significant seismic risks for a considerable time after the main shock, prospective forecasting of the intermediate-term aftershock activity as soon as possible is important. The epidemic-type aftershock sequence (ETAS) model with the maximum likelihood estimate effectively reproduces general aftershock activity including secondary or higher-order aftershocks and can be employed for the forecasting. However, because we cannot always expect the accurate parameter estimation from incomplete early aftershock data where many events are missing, such forecasting using only a single estimated parameter set (plug-in forecasting) can frequently perform poorly. Therefore, we here propose Bayesian forecasting that combines the forecasts by the ETAS model with various probable parameter sets given the data. By conducting forecasting tests of 1 month period aftershocks based on the first 1 day data after the main shock as an example of the early intermediate-term forecasting, we show that the Bayesian forecasting performs better than the plug-in forecasting on average in terms of the log-likelihood score. Furthermore, to improve forecasting of large aftershocks, we apply a nonparametric (NP) model using magnitude data during the learning period and compare its forecasting performance with that of the Gutenberg-Richter (G-R) formula. We show that the NP forecast performs better than the G-R formula in some cases but worse in other cases. Therefore, robust forecasting can be obtained by employing an ensemble forecast that combines the two complementary forecasts. Our proposed method is useful for a stable unbiased intermediate-term assessment of aftershock probabilities.

A review of ADM1 extensions, applications, and analysis: 2002-2005.

PubMed

Batstone, D J; Keller, J; Steyer, J P

2006-01-01

Since publication of the Scientific and Technical Report (STR) describing the ADM1, the model has been extensively used, and analysed in both academic and practical applications. Adoption of the ADM1 in popular systems analysis tools such as the new wastewater benchmark (BSM2), and its use as a virtual industrial system can stimulate modelling of anaerobic processes by researchers and practitioners outside the core expertise of anaerobic processes. It has been used as a default structural element that allows researchers to concentrate on new extensions such as sulfate reduction, and new applications such as distributed parameter modelling of biofilms. The key limitations for anaerobic modelling originally identified in the STR were: (i) regulation of products from glucose fermentation, (ii) parameter values, and variability, and (iii) specific extensions. Parameter analysis has been widespread, and some detailed extensions have been developed (e.g., sulfate reduction). A verified extension that describes regulation of products from glucose fermentation is still limited, though there are promising fundamental approaches. This is a critical issue, given the current interest in renewable hydrogen production from carbohydrate-type waste. Critical analysis of the model has mainly focused on model structure reduction, hydrogen inhibition functions, and the default parameter set recommended in the STR. This default parameter set has largely been verified as a reasonable compromise, especially for wastewater sludge digestion. One criticism of note is that the ADM1 stoichiometry focuses on catabolism rather than anabolism. This means that inorganic carbon can be used unrealistically as a carbon source during some anabolic reactions. Advances and novel applications have also been made in the present issue, which focuses on the ADM1. These papers also explore a number of novel areas not originally envisaged in this review.

Continuous Dissolved Oxygen Measurements and Modelling Metabolism in Peatland Streams

PubMed Central

Dick, Jonathan J.; Soulsby, Chris; Birkel, Christian; Malcolm, Iain; Tetzlaff, Doerthe

2016-01-01

Stream water dissolved oxygen was monitored in a 3.2km2 moorland headwater catchment in the Scottish Highlands. The stream consists of three 1st order headwaters and a 2nd order main stem. The stream network is fringed by peat soils with no riparian trees, though dwarf shrubs provide shading in the lower catchment. Dissolved oxygen (DO) is regulated by the balance between atmospheric re-aeration and the metabolic processes of photosynthesis and respiration. DO was continuously measured for >1 year and the data used to calibrate a mass balance model, to estimate primary production, respiration and re-aeration for a 1st order site and in the 2nd order main stem. Results showed that the stream was always heterotrophic at both sites. Sites were most heterotrophic in the summer reflecting higher levels of stream metabolism. The 1st order stream appeared more heterotrophic which was consistent with the evident greater biomass of macrophytes in the 2nd order stream, with resulting higher primary productivity. Comparison between respiration, primary production, re-aeration and potential physical controls revealed only weak relationships. However, the most basic model parameters (e.g. the parameter linking light and photosynthesis) controlling ecosystem processes resulted in significant differences between the sites which seem related to the stream channel geometry. PMID:27556278

Precise side-chain conformation analysis of L-phenylalanine in α-helical polypeptide by quantum-chemical calculation and 13C CP-MAS NMR measurement

NASA Astrophysics Data System (ADS)

Niimura, Subaru; Suzuki, Junya; Kurosu, Hiromichi; Yamanobe, Takeshi; Shoji, Akira

2010-04-01

To clarify the positive role of side-chain conformation in the stability of protein secondary structure (main-chain conformation), we successfully calculated the optimization structure of a well-defined α-helical octadecapeptide composed of L-alanine (Ala) and L-phenylalanine (Phe) residues, H-(Ala) 8-Phe-(Ala) 9-OH, based on the molecular orbital calculation with density functional theory (DFT/B3LYP/6-31G(d)). From the total energy and the precise secondary structural parameters such as main-chain dihedral angles and hydrogen-bond parameters of the optimized structure, we confirmed that the conformational stability of an α-helix is affected dominantly by the side-chain conformation ( χ1) of the Phe residue in this system: model A ( T form: around 180° of χ1) is most stable in α-helix and model B ( G + form: around -60° of χ1) is next stable, but model C ( G - form: around 60° of χ1) is less stable. In addition, we demonstrate that the stable conformation of poly( L-phenylalanine) is an α-helix with the side-chain T form, by comparison of the carbonyl 13C chemical shift measured by 13C CP-MAS NMR and the calculated one.

Influence of Averaging Preprocessing on Image Analysis with a Markov Random Field Model

NASA Astrophysics Data System (ADS)

Sakamoto, Hirotaka; Nakanishi-Ohno, Yoshinori; Okada, Masato

2018-02-01

This paper describes our investigations into the influence of averaging preprocessing on the performance of image analysis. Averaging preprocessing involves a trade-off: image averaging is often undertaken to reduce noise while the number of image data available for image analysis is decreased. We formulated a process of generating image data by using a Markov random field (MRF) model to achieve image analysis tasks such as image restoration and hyper-parameter estimation by a Bayesian approach. According to the notions of Bayesian inference, posterior distributions were analyzed to evaluate the influence of averaging. There are three main results. First, we found that the performance of image restoration with a predetermined value for hyper-parameters is invariant regardless of whether averaging is conducted. We then found that the performance of hyper-parameter estimation deteriorates due to averaging. Our analysis of the negative logarithm of the posterior probability, which is called the free energy based on an analogy with statistical mechanics, indicated that the confidence of hyper-parameter estimation remains higher without averaging. Finally, we found that when the hyper-parameters are estimated from the data, the performance of image restoration worsens as averaging is undertaken. We conclude that averaging adversely influences the performance of image analysis through hyper-parameter estimation.

Genetic algorithm parameters tuning for resource-constrained project scheduling problem

NASA Astrophysics Data System (ADS)

Tian, Xingke; Yuan, Shengrui

2018-04-01

Project Scheduling Problem (RCPSP) is a kind of important scheduling problem. To achieve a certain optimal goal such as the shortest duration, the smallest cost, the resource balance and so on, it is required to arrange the start and finish of all tasks under the condition of satisfying project timing constraints and resource constraints. In theory, the problem belongs to the NP-hard problem, and the model is abundant. Many combinatorial optimization problems are special cases of RCPSP, such as job shop scheduling, flow shop scheduling and so on. At present, the genetic algorithm (GA) has been used to deal with the classical RCPSP problem and achieved remarkable results. Vast scholars have also studied the improved genetic algorithm for the RCPSP problem, which makes it to solve the RCPSP problem more efficiently and accurately. However, for the selection of the main parameters of the genetic algorithm, there is no parameter optimization in these studies. Generally, we used the empirical method, but it cannot ensure to meet the optimal parameters. In this paper, the problem was carried out, which is the blind selection of parameters in the process of solving the RCPSP problem. We made sampling analysis, the establishment of proxy model and ultimately solved the optimal parameters.

Leader-follower formation control of underactuated surface vehicles based on sliding mode control and parameter estimation.

PubMed

Sun, Zhijian; Zhang, Guoqing; Lu, Yu; Zhang, Weidong

2018-01-01

This paper studies the leader-follower formation control of underactuated surface vehicles with model uncertainties and environmental disturbances. A parameter estimation and upper bound estimation based sliding mode control scheme is proposed to solve the problem of the unknown plant parameters and environmental disturbances. For each of these leader-follower formation systems, the dynamic equations of position and attitude are analyzed using coordinate transformation with the aid of the backstepping technique. All the variables are guaranteed to be uniformly ultimately bounded stable in the closed-loop system, which is proven by the distribution design Lyapunov function synthesis. The main advantages of this approach are that: first, parameter estimation based sliding mode control can enhance the robustness of the closed-loop system in presence of model uncertainties and environmental disturbances; second, a continuous function is developed to replace the signum function in the design of sliding mode scheme, which devotes to reduce the chattering of the control system. Finally, numerical simulations are given to demonstrate the effectiveness of the proposed method. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Application of Quality by Design to the characterization of the cell culture process of an Fc-Fusion protein.

PubMed

Rouiller, Yolande; Solacroup, Thomas; Deparis, Véronique; Barbafieri, Marco; Gleixner, Ralf; Broly, Hervé; Eon-Duval, Alex

2012-06-01

The production bioreactor step of an Fc-Fusion protein manufacturing cell culture process was characterized following Quality by Design principles. Using scientific knowledge derived from the literature and process knowledge gathered during development studies and manufacturing to support clinical trials, potential critical and key process parameters with a possible impact on product quality and process performance, respectively, were determined during a risk assessment exercise. The identified process parameters were evaluated using a design of experiment approach. The regression models generated from the data allowed characterizing the impact of the identified process parameters on quality attributes. The main parameters having an impact on product titer were pH and dissolved oxygen, while those having the highest impact on process- and product-related impurities and variants were pH and culture duration. The models derived from characterization studies were used to define the cell culture process design space. The design space limits were set in such a way as to ensure that the drug substance material would consistently have the desired quality. Copyright © 2012 Elsevier B.V. All rights reserved.

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

DOE PAGES

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

2015-10-30

An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

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

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less

Aerobic stabilization of biological sludge characterized by an extremely low decay rate: modeling, identifiability analysis and parameter estimation.

PubMed

Martínez-García, C G; Olguín, M T; Fall, C

2014-08-01

Aerobic digestion batch tests were run on a sludge model that contained only two fractions, the heterotrophic biomass (XH) and its endogenous residue (XP). The objective was to describe the stabilization of the sludge and estimate the endogenous decay parameters. Modeling was performed with Aquasim, based on long-term data of volatile suspended solids and chemical oxygen demand (VSS, COD). Sensitivity analyses were carried out to determine the conditions for unique identifiability of the parameters. Importantly, it was found that the COD/VSS ratio of the endogenous residues (1.06) was significantly lower than for the active biomass fraction (1.48). The decay rate constant of the studied sludge (low bH, 0.025 d(-1)) was one-tenth that usually observed (0.2d(-1)), which has two main practical significances. Digestion time required is much more long; also the oxygen uptake rate might be <1.5 mg O₂/gTSSh (biosolids standards), without there being significant decline in the biomass. Copyright © 2014 Elsevier Ltd. All rights reserved.

Serial robot for the trajectory optimization and error compensation of TMT mask exchange system

NASA Astrophysics Data System (ADS)

Wang, Jianping; Zhang, Feifan; Zhou, Zengxiang; Zhai, Chao

2015-10-01

Mask exchange system is the main part of Multi-Object Broadband Imaging Echellette (MOBIE) on the Thirty Meter Telescope (TMT). According to the conception of the TMT mask exchange system, the pre-design was introduced in the paper which was based on IRB 140 robot. The stiffness model of IRB 140 in SolidWorks was analyzed under different gravity vectors for further error compensation. In order to find the right location and path planning, the robot and the mask cassette model was imported into MOBIE model to perform different schemes simulation. And obtained the initial installation position and routing. Based on these initial parameters, IRB 140 robot was operated to simulate the path and estimate the mask exchange time. Meanwhile, MATLAB and ADAMS software were used to perform simulation analysis and optimize the route to acquire the kinematics parameters and compare with the experiment results. After simulation and experimental research mentioned in the paper, the theoretical reference was acquired which could high efficient improve the structure of the mask exchange system parameters optimization of the path and precision of the robot position.

Numerical Study of Suspension Plasma Spraying

NASA Astrophysics Data System (ADS)

Farrokhpanah, Amirsaman; Coyle, Thomas W.; Mostaghimi, Javad

2017-01-01

A numerical study of suspension plasma spraying is presented in the current work. The liquid suspension jet is replaced with a train of droplets containing the suspension particles injected into the plasma flow. Atomization, evaporation, and melting of different components are considered for droplets and particles as they travel toward the substrate. Effect of different parameters on particle conditions during flight and upon impact on the substrate is investigated. Initially, influence of the torch operating conditions such as inlet flow rate and power is studied. Additionally, effect of injector parameters like injection location, flow rate, and angle is examined. The model used in the current study takes high-temperature gradients and non-continuum effects into account. Moreover, the important effect of change in physical properties of suspension droplets as a result of evaporation is included in the model. These mainly include variations in heat transfer properties and viscosity. Utilizing this improved model, several test cases have been considered to better evaluate the effect of different parameters on the quality of particles during flight and upon impact on the substrate.