Modelling of Water Turbidity Parameters in a Water Treatment Plant
Directory of Open Access Journals (Sweden)
A. S. KOVO
2005-01-01
Full Text Available The high cost of chemical analysis of water has necessitated various researches into finding alternative method of determining portable water quality. This paper is aimed at modelling the turbidity value as a water quality parameter. Mathematical models for turbidity removal were developed based on the relationships between water turbidity and other water criteria. Results showed that the turbidity of water is the cumulative effect of the individual parameters/factors affecting the system. A model equation for the evaluation and prediction of a clarifier’s performance was developed:Model: T = T0(-1.36729 + 0.037101∙10λpH + 0.048928t + 0.00741387∙alkThe developed model will aid the predictive assessment of water treatment plant performance. The limitations of the models are as a result of insufficient variable considered during the conceptualization.
Determining extreme parameter correlation in ground water models
DEFF Research Database (Denmark)
Hill, Mary Cole; Østerby, Ole
2003-01-01
In ground water flow system models with hydraulic-head observations but without significant imposed or observed flows, extreme parameter correlation generally exists. As a result, hydraulic conductivity and recharge parameters cannot be uniquely estimated. In complicated problems, such correlation...... correlation coefficients, but it required sensitivities that were one to two significant digits less accurate than those that required using parameter correlation coefficients; and (3) both the SVD and parameter correlation coefficients identified extremely correlated parameters better when the parameters...
Sensitivity of a Shallow-Water Model to Parameters
Kazantsev, Eugene
2011-01-01
An adjoint based technique is applied to a shallow water model in order to estimate the influence of the model's parameters on the solution. Among parameters the bottom topography, initial conditions, boundary conditions on rigid boundaries, viscosity coefficients Coriolis parameter and the amplitude of the wind stress tension are considered. Their influence is analyzed from three points of view: 1. flexibility of the model with respect to a parameter that is related to the lowest value of the cost function that can be obtained in the data assimilation experiment that controls this parameter; 2. possibility to improve the model by the parameter's control, i.e. whether the solution with the optimal parameter remains close to observations after the end of control; 3. sensitivity of the model solution to the parameter in a classical sense. That implies the analysis of the sensitivity estimates and their comparison with each other and with the local Lyapunov exponents that characterize the sensitivity of the mode...
A simulation of water pollution model parameter estimation
Kibler, J. F.
1976-01-01
A parameter estimation procedure for a water pollution transport model is elaborated. A two-dimensional instantaneous-release shear-diffusion model serves as representative of a simple transport process. Pollution concentration levels are arrived at via modeling of a remote-sensing system. The remote-sensed data are simulated by adding Gaussian noise to the concentration level values generated via the transport model. Model parameters are estimated from the simulated data using a least-squares batch processor. Resolution, sensor array size, and number and location of sensor readings can be found from the accuracies of the parameter estimates.
Revised Parameters for the AMOEBA Polarizable Atomic Multipole Water Model.
Laury, Marie L; Wang, Lee-Ping; Pande, Vijay S; Head-Gordon, Teresa; Ponder, Jay W
2015-07-23
A set of improved parameters for the AMOEBA polarizable atomic multipole water model is developed. An automated procedure, ForceBalance, is used to adjust model parameters to enforce agreement with ab initio-derived results for water clusters and experimental data for a variety of liquid phase properties across a broad temperature range. The values reported here for the new AMOEBA14 water model represent a substantial improvement over the previous AMOEBA03 model. The AMOEBA14 model accurately predicts the temperature of maximum density and qualitatively matches the experimental density curve across temperatures from 249 to 373 K. Excellent agreement is observed for the AMOEBA14 model in comparison to experimental properties as a function of temperature, including the second virial coefficient, enthalpy of vaporization, isothermal compressibility, thermal expansion coefficient, and dielectric constant. The viscosity, self-diffusion constant, and surface tension are also well reproduced. In comparison to high-level ab initio results for clusters of 2-20 water molecules, the AMOEBA14 model yields results similar to AMOEBA03 and the direct polarization iAMOEBA models. With advances in computing power, calibration data, and optimization techniques, we recommend the use of the AMOEBA14 water model for future studies employing a polarizable water model.
Multiscale Parameter Regionalization for consistent global water resources modelling
Wanders, Niko; Wood, Eric; Pan, Ming; Samaniego, Luis; Thober, Stephan; Kumar, Rohini; Sutanudjaja, Edwin; van Beek, Rens; Bierkens, Marc F. P.
2017-04-01
Due to an increasing demand for high- and hyper-resolution water resources information, it has become increasingly important to ensure consistency in model simulations across scales. This consistency can be ensured by scale independent parameterization of the land surface processes, even after calibration of the water resource model. Here, we use the Multiscale Parameter Regionalization technique (MPR, Samaniego et al. 2010, WRR) to allow for a novel, spatially consistent, scale independent parameterization of the global water resource model PCR-GLOBWB. The implementation of MPR in PCR-GLOBWB allows for calibration at coarse resolutions and subsequent parameter transfer to the hyper-resolution. In this study, the model was calibrated at 50 km resolution over Europe and validation carried out at resolutions of 50 km, 10 km and 1 km. MPR allows for a direct transfer of the calibrated transfer function parameters across scales and we find that we can maintain consistent land-atmosphere fluxes across scales. Here we focus on the 2003 European drought and show that the new parameterization allows for high-resolution calibrated simulations of water resources during the drought. For example, we find a reduction from 29% to 9.4% in the percentile difference in the annual evaporative flux across scales when compared against default simulations. Soil moisture errors are reduced from 25% to 6.9%, clearly indicating the benefits of the MPR implementation. This new parameterization allows us to show more spatial detail in water resources simulations that are consistent across scales and also allow validation of discharge for smaller catchments, even with calibrations at a coarse 50 km resolution. The implementation of MPR allows for novel high-resolution calibrated simulations of a global water resources model, providing calibrated high-resolution model simulations with transferred parameter sets from coarse resolutions. The applied methodology can be transferred to other
Modelling of bio-optical parameters of open ocean waters
Directory of Open Access Journals (Sweden)
Vadim N. Pelevin
2001-12-01
Full Text Available An original method for estimating the concentration of chlorophyll pigments, absorption of yellow substance and absorption of suspended matter without pigments and yellow substance in detritus using spectral diffuse attenuation coefficient for downwelling irradiance and irradiance reflectance data has been applied to sea waters of different types in the open ocean (case 1. Using the effective numerical single parameter classification with the water type optical index m as a parameter over the whole range of the open ocean waters, the calculations have been carried out and the light absorption spectra of sea waters tabulated. These spectra are used to optimize the absorption models and thus to estimate the concentrations of the main admixtures in sea water. The value of m can be determined from direct measurements of the downward irradiance attenuation coefficient at 500 nm or calculated from remote sensing data using the regressions given in the article. The sea water composition can then be readily estimated from the tables given for any open ocean area if that one parameter m characterizing the basin is known.
Parameter selection and model research on remote sensing evaluation for nearshore water quality
Institute of Scientific and Technical Information of China (English)
LEI Guibin; ZHANG Ying; PAN Delu; WANG Difeng; FU Dongyang
2016-01-01
Using remote sensing technology for water quality evaluation is an inevitable trend in marine environmental monitoring. However, fewer categories of water quality parameters can be monitored by remote sensing technology than the 35 specified in GB3097-1997 Marine Water Quality Standard. Therefore, we considered which parameters must be selected by remote sensing and how to model for water quality evaluation using the finite parameters. In this paper, focused on Leizhou Peninsula nearshore waters, we found N, P, COD, PH and DO to be the dominant parameters of water quality by analyzing measured data. Then, mathematical statistics was used to determine that the relationship among the five parameters was COD>DO>P>N>pH. Finally, five-parameter, four-parameter and three-parameter water quality evaluation models were established and compared. The results showed that COD, DO, P and N were the necessary parameters for remote sensing evaluation of the Leizhou Peninsula nearshore water quality, and the optimal comprehensive water quality evaluation model was the four-parameter model. This work may serve as a reference for monitoring the quality of other marine waters by remote sensing.
Water quality modelling for ephemeral rivers: Model development and parameter assessment
Mannina, Giorgio; Viviani, Gaspare
2010-11-01
SummaryRiver water quality models can be valuable tools for the assessment and management of receiving water body quality. However, such water quality models require accurate model calibration in order to specify model parameters. Reliable model calibration requires an extensive array of water quality data that are generally rare and resource-intensive, both economically and in terms of human resources, to collect. In the case of small rivers, such data are scarce due to the fact that these rivers are generally considered too insignificant, from a practical and economic viewpoint, to justify the investment of such considerable time and resources. As a consequence, the literature contains very few studies on the water quality modelling for small rivers, and such studies as have been published are fairly limited in scope. In this paper, a simplified river water quality model is presented. The model is an extension of the Streeter-Phelps model and takes into account the physico-chemical and biological processes most relevant to modelling the quality of receiving water bodies (i.e., degradation of dissolved carbonaceous substances, ammonium oxidation, algal uptake and denitrification, dissolved oxygen balance, including depletion by degradation processes and supply by physical reaeration and photosynthetic production). The model has been applied to an Italian case study, the Oreto river (IT), which has been the object of an Italian research project aimed at assessing the river's water quality. For this reason, several monitoring campaigns have been previously carried out in order to collect water quantity and quality data on this river system. In particular, twelve river cross sections were monitored, and both flow and water quality data were collected for each cross section. The results of the calibrated model show satisfactory agreement with the measured data and results reveal important differences between the parameters used to model small rivers as compared to
Analysis of transients in advanced heavy water reactor using lumped parameter models
Energy Technology Data Exchange (ETDEWEB)
Manmohan Pandey; Venkata Ramana Eaga; Sankar Sastry, P. [Department of Mechanical Engineering, Indian Institute of Technology Guwahati, Guwahati (India); Gupta, S.K.; Lele, H.G.; Chatterjee, B. [Reactor Safety Division, Bhabha Atomic Research Centre, Mumbai (India)
2005-07-01
Full text of publication follows: Analysis of transients occurring in nuclear power plants, arising from the complex interplay between core neutronics and thermal-hydraulics, is important for their operation and safety. Numerical simulations of such transients can be carried out extensively at very low computational cost by using lumped parameter mathematical models. The Advanced Heavy Water Reactor (AHWR), being developed in India, is a vertical pressure tube type reactor cooled by boiling light water under natural circulation, using thorium as fuel and heavy water as moderator. In the present work, nonlinear and linear lumped parameter dynamic models for AHWR have been developed and validated with a distributed parameter model. The nonlinear lumped model is based on point reactor kinetics equations and one-dimensional homogeneous equilibrium model of two-phase flow. The distributed model is built with RELAP5/MOD3.2 code. Various types of transients have been simulated numerically, using the lumped model as well as RELAP5. The results have been compared and parameters tuned to make the lumped model match the distributed model (RELAP5) in terms of steady state as well as dynamic behaviour. The linear model has been derived by linearizing the nonlinear model for small perturbations about the steady state. Numerical simulations of transients using the linear model have been compared with results obtained from the nonlinear model. Thus, the range of validity of the linear model has been determined. Stability characteristics of AHWR have been investigated using the lumped parameter models. (authors)
COMPUTER MODELING OF SELECTED WATER QUALITY PARAMETERS IN WATER DISTRIBUTION SYSTEMS
Directory of Open Access Journals (Sweden)
Wojciech Kruszyński
2016-06-01
Full Text Available The paper presents the results of computer modeling of flowsand the age of the water in two rural communi-ties province Podlasie - Rutka and Jeleniewo. The model is made using Epanet. In the study, a series of variants of models simulating the behavior of existing distribution systems and water analyzes were performed century. Analysis of the age of the water in water works modeled showed areas where standing water is aging, not having the estuary and not giving way to fresh. Age of water in the pipes is an important indicator of its quality and shelf life. The longer standing water in the aqueduct, the more likely that it will develop dangerous bacteria and produce deposits which remain on the walls of the ducts.
Estimation of Water Quality Parameters Using the Regression Model with Fuzzy K-Means Clustering
Directory of Open Access Journals (Sweden)
Muntadher A. SHAREEF
2014-07-01
Full Text Available the traditional methods in remote sensing used for monitoring and estimating pollutants are generally relied on the spectral response or scattering reflected from water. In this work, a new method has been proposed to find contaminants and determine the Water Quality Parameters (WQPs based on theories of the texture analysis. Empirical statistical models have been developed to estimate and classify contaminants in the water. Gray Level Co-occurrence Matrix (GLCM is used to estimate six texture parameters: contrast, correlation, energy, homogeneity, entropy and variance. These parameters are used to estimate the regression model with three WQPs. Finally, the fuzzy K-means clustering was used to generalize the water quality estimation on all segmented image. Using the in situ measurements and IKONOS data, the obtained results show that texture parameters and high resolution remote sensing able to monitor and predicate the distribution of WQPs in large rivers.
The identifiability of parameters in a water quality model of the Biebrza River, Poland
Perk, van der M.; Bierkens, M.F.P.
1997-01-01
The identifiability of model parameters of a steady state water quality model of the Biebrza River and the resulting variation in model results was examined by applying the Monte Carlo method which combines calibration, identifiability analysis, uncertainty analysis, and sensitivity analysis. The wa
Jhorar, R.K.
2002-01-01
Key words: evapotranspiration, effective soil hydraulic parameters, remote sensing, regional water management, groundwater use, Bhakra Irrigation System, India.The meaningful application of water management simulation models at regional scale for the analysis of alternate water manage
Michalik, Thomas; Multsch, Sebastian; Frede, Hans-Georg; Breuer, Lutz
2016-04-01
Water for agriculture is strongly limited in arid and semi-arid regions and often of low quality in terms of salinity. The application of saline waters for irrigation increases the salt load in the rooting zone and has to be managed by leaching to maintain a healthy soil, i.e. to wash out salts by additional irrigation. Dynamic simulation models are helpful tools to calculate the root zone water fluxes and soil salinity content in order to investigate best management practices. However, there is little information on structural and parameter uncertainty for simulations regarding the water and salt balance of saline irrigation. Hence, we established a multi-model system with four different models (AquaCrop, RZWQM, SWAP, Hydrus1D/UNSATCHEM) to analyze the structural and parameter uncertainty by using the Global Likelihood and Uncertainty Estimation (GLUE) method. Hydrus1D/UNSATCHEM and SWAP were set up with multiple sets of different implemented functions (e.g. matric and osmotic stress for root water uptake) which results in a broad range of different model structures. The simulations were evaluated against soil water and salinity content observations. The posterior distribution of the GLUE analysis gives behavioral parameters sets and reveals uncertainty intervals for parameter uncertainty. Throughout all of the model sets, most parameters accounting for the soil water balance show a low uncertainty, only one or two out of five to six parameters in each model set displays a high uncertainty (e.g. pore-size distribution index in SWAP and Hydrus1D/UNSATCHEM). The differences between the models and model setups reveal the structural uncertainty. The highest structural uncertainty is observed for deep percolation fluxes between the model sets of Hydrus1D/UNSATCHEM (~200 mm) and RZWQM (~500 mm) that are more than twice as high for the latter. The model sets show a high variation in uncertainty intervals for deep percolation as well, with an interquartile range (IQR) of
INFLUENCE OF TECHNOLOGICAL PARAMETERS ON AGROTEXTILES WATER ABSORBENCY USING ANOVA MODEL
Directory of Open Access Journals (Sweden)
LUPU Iuliana G.
2016-05-01
Full Text Available Agrotextiles are now days extensively being used in horticulture, farming and other agricultural activities. Agriculture and textiles are the largest industries in the world providing basic needs such as food and clothing. Agrotextiles plays a significant role to help control environment for crop protection, eliminate variations in climate, weather change and generate optimum condition for plant growth. Water absorptive capacity is a very important property of needle-punched nonwovens used as irrigation substrate in horticulture. Nonwovens used as watering substrate distribute water uniformly and act as slight water buffer owing to the absorbent capacity. The paper analyzes the influence of needling process parameters on water absorptive capacity of needle-punched nonwovens by using ANOVA model. The model allows the identification of optimal action parameters in a shorter time and with less material expenses than by experimental research. The frequency of needle board and needle depth penetration has been used as independent variables while the water absorptive capacity as dependent variable for ANOVA regression model. Based on employed ANOVA model we have established that there is a significant influence of needling parameters on water absorbent capacity. The higher of depth needle penetration and needle board frequency, the higher is the compactness of fabric. A less porous structure has a lower water absorptive capacity.
Distributed parameter modeling and thermal analysis of a spiral water wall in a supercritical boiler
Directory of Open Access Journals (Sweden)
Zheng Shu
2013-01-01
Full Text Available In this paper, a distributed parameter model for the evaporation system of a supercritical spiral water wall boiler is developed based on a 3-D temperature field. The mathematical method is formulated for predicting the heat flux and the metal-surface temperature. The results show that the influence of the heat flux distribution is more obvious than that of the heat transfer coefficient distribution in the spiral water wall tube, and the peak of the heat transfer coefficient decreases with an increment of supercritical pressure. This distributed parameter model can be used for a 600 MW supercritical-pressure power plant.
Shareef, Muntadher A.; Toumi, Abdelmalek; Khenchaf, Ali
2014-10-01
Remote sensing is one of the most important tools for monitoring and assisting to estimate and predict Water Quality parameters (WQPs). The traditional methods used for monitoring pollutants are generally relied on optical images. In this paper, we present a new approach based on the Synthetic Aperture Radar (SAR) images which we used to map the region of interest and to estimate the WQPs. To achieve this estimation quality, the texture analysis is exploited to improve the regression models. These models are established and developed to estimate six common concerned water quality parameters from texture parameters extracted from Terra SAR-X data. In this purpose, the Gray Level Cooccurrence Matrix (GLCM) is used to estimate several regression models using six texture parameters such as contrast, correlation, energy, homogeneity, entropy and variance. For each predicted model, an accuracy value is computed from the probability value given by the regression analysis model of each parameter. In order to validate our approach, we have used tow dataset of water region for training and test process. To evaluate and validate the proposed model, we applied it on the training set. In the last stage, we used the fuzzy K-means clustering to generalize the water quality estimation on the whole of water region extracted from segmented Terra SAR-X image. Also, the obtained results showed that there are a good statistical correlation between the in situ water quality and Terra SAR-X data, and also demonstrated that the characteristics obtained by texture analysis are able to monitor and predicate the distribution of WQPs in large rivers with high accuracy.
Model calibration and parameter estimation for environmental and water resource systems
Sun, Ne-Zheng
2015-01-01
This three-part book provides a comprehensive and systematic introduction to the development of useful models for complex systems. Part 1 covers the classical inverse problem for parameter estimation in both deterministic and statistical frameworks, Part 2 is dedicated to system identification, hyperparameter estimation, and model dimension reduction, and Part 3 considers how to collect data and construct reliable models for prediction and decision-making. For the first time, topics such as multiscale inversion, stochastic field parameterization, level set method, machine learning, global sensitivity analysis, data assimilation, model uncertainty quantification, robust design, and goal-oriented modeling, are systematically described and summarized in a single book from the perspective of model inversion, and elucidated with numerical examples from environmental and water resources modeling. Readers of this book will not only learn basic concepts and methods for simple parameter estimation, but also get famili...
Directory of Open Access Journals (Sweden)
E. Mikhailov
2013-01-01
Full Text Available In this study we derive and apply a mass-based hygroscopicity parameter interaction model for efficient description of concentration-dependent water uptake by atmospheric aerosol particles with complex chemical composition. The model approach builds on the single hygroscopicity parameter model of Petters and Kreidenweis (2007. We introduce an observable mass-based hygroscopicity parameter κ_{m} which can be deconvoluted into a dilute hygroscopicity parameter (κ_{m}^{0} and additional self- and cross-interaction parameters describing non-ideal solution behavior and concentration dependencies of single- and multi-component systems.
For reference aerosol samples of sodium chloride and ammonium sulfate, the κ_{m}-interaction model (KIM captures the experimentally observed concentration and humidity dependence of the hygroscopicity parameter and is in good agreement with an accurate reference model based on the Pitzer ion-interaction approach (Aerosol Inorganic Model, AIM. Experimental results for pure organic particles (malonic acid, levoglucosan and for mixed organic-inorganic particles (malonic acid – ammonium sulfate are also well reproduced by KIM, taking into account apparent or equilibrium solubilities for stepwise or gradual deliquescence and efflorescence transitions.
The mixed organic-inorganic particles as well as atmospheric aerosol samples exhibit three distinctly different regimes of hygroscopicity: (I a quasi-eutonic deliquescence & efflorescence regime at low-humidity where substances are just partly dissolved and exist also in a non-dissolved phase, (II a gradual deliquescence & efflorescence regime at intermediate humidity where different solutes undergo gradual dissolution or solidification in the aqueous phase; and (III a dilute regime at high humidity where the solutes are fully dissolved approaching their dilute hygroscopicity.
For atmospheric aerosol samples
Forecasting Models for Some Water Quality Parameters of Shatt Al-Hilla River, Iraq
Directory of Open Access Journals (Sweden)
Rafa H. Al-Suhili
2017-07-01
Full Text Available This paper provides Artificial Neural Networks model versions for forecasting the monthly averages of some chemical water quality parameters of Shatt Al-Hilla River, which is located at Hilla City, south of Iraq. The water quality parameters investigated were Sulphate, Magnesium, Calcium, Alkalinity, and Total Hardness. Results indicate that for Sulphate and Calcium high correlation coefficients models were observed to be (0.9 and 0.88, while for Magnesium, Alkalinity and Hardness low correlation coefficients model were observed to be (0.48,0.58, and 0.51 respectively. Serial correlation behavior of these variables indicate at that high lag time correlations sequences are observed for the first two variables and low ones for the last three water quality parameters. A serial correlation coefficient analysis was done and indicates that as the variable exhibited weak lag correlation structure, then a successful ANN forecasting model could not be obtained even if many trials were done to enhance it's performance, such as increasing the number of nodes, the lagged input variables, and/or changing the learning rate and the momentum term values, or the use of different types of activation functions. On the other hand, those variables that have a strong lag correlation structure can easily fit successful ANN forecasting models
Directory of Open Access Journals (Sweden)
Z. Katambara
2014-01-01
Full Text Available Producing more rice while using less water is among the calls in water scarce regions so as to feed the growing population and cope with the changing climate. Among the suitable techniques towards this achievement is the use of system of rice intensification (SRI, which has been reported as an approach that uses less water and has high water productivity and water use efficiency. Despite its promising results, the use of SRI practice in Tanzania is limited due to less knowledge with regard to the transplanting age, plant spacing, and minimum soil moisture to be allowed for irrigation, and alternate wetting and drying interval for various geographical locations. The AquaCrop crop water productivity model, which is capable of simulating crop water requirements and yield for a given parameter set, was used to identify suitable SRI parameters for Mkindo area in Morogoro region, Tanzania. Using no stress in soil fertility, plant spacings ranging from 5 cm to 50 cm were evaluated. Results suggest that the yield and biomass produced per ha increase with decreasing spacing from 50 cm to 20 cm. Preliminary field results suggest that the optimum spacing is round 25 cm. However, the model structure does not take into consideration number of tillers produced. As such, the study calls for incorporation of the tillering processes into AquaCrop model.
Directory of Open Access Journals (Sweden)
Boronina Lyudmila Vladimirovna
2012-12-01
Full Text Available Improvement of water intake technologies are of great importance. These technologies are required to provide high quality water intake and treatment; they must be sufficiently simple and reliable, and they must be easily adjustable to particular local conditions. A mathematical model of a water supply area near the filtering water intake is proposed. On its basis, a software package designated for the calculation of parameters of the supply area along with its graphical representation is developed. To improve the efficiency of water treatment plants, the authors propose a new method of their integration into the landscape by taking account of velocity distributions in the water supply area within the water reservoir where the plant installation is planned. In the proposed relationship, the filtration rate and the scattering rate at the outlet of the supply area are taken into account, and they assure more precise projections of the inlet velocity. In the present study, assessment of accuracy of the mathematical model involving the scattering of a turbulent flow has been done. The assessment procedure is based on verification of the mean values equality hypothesis and on comparison with the experimental data. The results and conclusions obtained by means of the method developed by the authors have been verified through comparison of deviations of specific values calculated through the employment of similar algorithms in MathCAD, Maple and PLUMBING. The method of the water supply area analysis, with the turbulent scattering area having been taken into account, and the software package enable to numerically estimate the efficiency of the pre-purification process by tailoring a number of parameters of the filtering component of the water intake to the river hydrodynamic properties. Therefore, the method and the software package provide a new tool for better design, installation and operation of water treatment plants with respect to filtration and
Parameter Identification for a New Circuit Model Aimed to Predict Body Water Volume
Directory of Open Access Journals (Sweden)
GHEORGHE, A.-G.
2012-11-01
Full Text Available Intracellular and extracellular water volumes in the human body have been computed using a sequence of models starting with a linear first order RC circuit (Cole model and finishing with the De Lorenzo model. This last model employs a fractional order impedance whose parameters are identified using the frequency characteristics of the impedance module and phase, the latter being not unique. While the Cole model has a two octaves frequency validity range, the De Lorenzo model can be used for three decades. A new linear RC model, valid for a three decades frequency range, is proposed. This circuit can be viewed as an extension of the Cole model for a larger frequency interval, unlike similar models proposed by the same authors.
Recommended Parameter Values for GENII Modeling of Radionuclides in Routine Air and Water Releases
Energy Technology Data Exchange (ETDEWEB)
Snyder, Sandra F.; Arimescu, Carmen; Napier, Bruce A.; Hay, Tristan R.
2012-11-01
The GENII v2 code is used to estimate dose to individuals or populations from the release of radioactive materials into air or water. Numerous parameter values are required for input into this code. User-defined parameters cover the spectrum from chemical data, meteorological data, agricultural data, and behavioral data. This document is a summary of parameter values that reflect conditions in the United States. Reasonable regional and age-dependent data is summarized. Data availability and quality varies. The set of parameters described address scenarios for chronic air emissions or chronic releases to public waterways. Considerations for the special tritium and carbon-14 models are briefly addressed. GENIIv2.10.0 is the current software version that this document supports.
Parameter regionalization of a monthly water balance model for the conterminous United States
Bock, Andrew R.; Hay, Lauren E.; McCabe, Gregory J.; Markstrom, Steven L.; Atkinson, R. Dwight
2016-07-01
A parameter regionalization scheme to transfer parameter values from gaged to ungaged areas for a monthly water balance model (MWBM) was developed and tested for the conterminous United States (CONUS). The Fourier Amplitude Sensitivity Test, a global-sensitivity algorithm, was implemented on a MWBM to generate parameter sensitivities on a set of 109 951 hydrologic response units (HRUs) across the CONUS. The HRUs were grouped into 110 calibration regions based on similar parameter sensitivities. Subsequently, measured runoff from 1575 streamgages within the calibration regions were used to calibrate the MWBM parameters to produce parameter sets for each calibration region. Measured and simulated runoff at the 1575 streamgages showed good correspondence for the majority of the CONUS, with a median computed Nash-Sutcliffe efficiency coefficient of 0.76 over all streamgages. These methods maximize the use of available runoff information, resulting in a calibrated CONUS-wide application of the MWBM suitable for providing estimates of water availability at the HRU resolution for both gaged and ungaged areas of the CONUS.
Khadam, Ibrahim M.; Kaluarachchi, Jagath J.
2006-10-01
SummaryWater quality modeling is important to assess the health of a watershed and to make necessary management decisions to control existing and future pollution of receiving water bodies. The existing export coefficient approach is attractive due to minimum data requirements; however, this method does not account for hydrologic variability. In this paper, an erosion-scaled export coefficient approach is proposed that can model and explain the hydrologic variability in predicting the annual phosphorus (P) loading to the receiving stream. Here sediment discharge was introduced into the export coefficient model as a surrogate for hydrologic variability. Application of this approach to model P in the Fishtrap Creek of Washington State showed the superiority of this approach compared to the traditional export coefficient approach, while maintaining its simplicity and low data requirement characteristics. In addition, a Bayesian framework is proposed to assess the parameter uncertainty of the export coefficient method instead of subjective assignment of uncertainty. This work also showed through a joint variability-uncertainty analysis the importance of separate consideration of hydrologic variability and parameter uncertainty, as these represent two independent and important characteristics of the overall model uncertainty. The paper also recommends the use of a longitudinal data collection scheme to reduce the uncertainty in export coefficients.
Measurement and mathematical modelling of nutrient level and water quality parameters.
Alasl, M Kashefi; Khosravi, M; Hosseini, M; Pazuki, G R; Nezakati Esmail Zadeh, R
2012-01-01
Physico-chemical water quality parameters and nutrient levels such as water temperature, turbidity, saturated oxygen, dissolved oxygen, pH, chlorophyll-a, salinity, conductivity, total nitrogen and total phosphorus, were measured from April to September 2011 in the Karaj dam area, Iran. Total nitrogen in water was modelled using an artificial neural network system. In the proposed system, water temperature, depth, saturated oxygen, dissolved oxygen, pH, chlorophyll-a, salinity, turbidity and conductivity were considered as input data, and the total nitrogen in water was considered as output. The weights and biases for various systems were obtained by the quick propagation, batch back propagation, incremental back propagation, genetic and Levenberg-Marquardt algorithms. The proposed system uses 144 experimental data points; 70% of the experimental data are randomly selected for training the network and 30% of the data are used for testing. The best network topology was obtained as (9-5-1) using the quick propagation method with tangent transform function. The average absolute deviation percentages (AAD%) are 2.329 and 2.301 for training and testing processes, respectively. It is emphasized that the results of the artificial neural network (ANN) model are compatible with the experimental data.
Dam, van J.C.
2000-01-01
Water flow and solute transport in top soils are important elements in many environmental studies. The agro- and ecohydrological model SWAP (Soil-Water-Plant-Atmosphere) has been developed to simulate simultaneously water flow, solute transport, heat flow and crop growth at field scale level. The ma
Gayler, Sebastian; Salima-Sultana, Daisy; Selle, Benny; Ingwersen, Joachim; Wizemann, Hans-Dieter; Högy, Petra; Streck, Thilo
2016-04-01
Soil water extraction by roots affects the dynamics and distribution of soil moisture and controls transpiration, which influences soil-vegetation-atmosphere feedback processes. Consequently, root water uptake requires close attention when predicting water fluxes across the land surface, e.g., in agricultural crop models or in land surface schemes of weather and climate models. The key parameters for a successful simultaneous simulation of soil moisture dynamics and evapotranspiration in Richards equation-based models are the soil hydraulic parameters, which describe the shapes of the soil water retention curve and the soil hydraulic conductivity curve. As measurements of these parameters are expensive and their estimation from basic soil data via pedotransfer functions is rather inaccurate, the values of the soil hydraulic parameters are frequently inversely estimated by fitting the model to measured time series of soil water content and evapotranspiration. It is common to simulate root water uptake and transpiration by simple stress functions, which describe from which soil layer water is absorbed by roots and predict when total crop transpiration is decreased in case of soil water limitations. As for most of the biogeophysical processes simulated in crop and land surface models, there exist several alternative functional relationships for simulating root water uptake and there is no clear reason for preferring one process representation over another. The error associated with alternative representations of root water uptake, however, contributes to structural model uncertainty and the choice of the root water uptake model may have a significant impact on the values of the soil hydraulic parameters estimated inversely. In this study, we use the agroecosystem model system Expert-N to simulate soil moisture dynamics and evapotranspiration at three agricultural field sites located in two contrasting regions in Southwest Germany (Kraichgau, Swabian Alb). The Richards
Riml, J.; Wörman, A.
2009-12-01
Knowledge about both hydrochemical processes and watershed characteristics are key factors when trying to model transportation and retention of nutrients in a river system. The proposed parameterization method opens for the possibility to introduce independently measured parameters in lumped (compartmental) models. The analysis provides a better understanding of the model structure and aids in the calculation of optimal parameter values. The investigation uses a 1D distributed network model and parameterizes the result in a form appropriate for a compartmental model structure that has been developed for Swedish conditions during decades. The main tool for the analysis is the comparison of temporal moments between the two model structures. The parameterization gives information about the importance of river hydraulics but also about the effect of geomorphological processes such as the river network structure and parameter variability within the watershed. The methodology does also reveal information about predominating processes during distinctive hydrological conditions.
Local order parameters for use in driving homogeneous ice nucleation with all-atom models of water.
Reinhardt, Aleks; Doye, Jonathan P K; Noya, Eva G; Vega, Carlos
2012-11-21
We present a local order parameter based on the standard Steinhardt-Ten Wolde approach that is capable both of tracking and of driving homogeneous ice nucleation in simulations of all-atom models of water. We demonstrate that it is capable of forcing the growth of ice nuclei in supercooled liquid water simulated using the TIP4P/2005 model using over-biassed umbrella sampling Monte Carlo simulations. However, even with such an order parameter, the dynamics of ice growth in deeply supercooled liquid water in all-atom models of water are shown to be very slow, and so the computation of free energy landscapes and nucleation rates remains extremely challenging.
Directory of Open Access Journals (Sweden)
Yan Han
2013-01-01
Full Text Available An interval-parameter fuzzy linear programming with stochastic vertices (IFLPSV method is developed for water resources management under uncertainty by coupling interval-parameter fuzzy linear programming (IFLP with stochastic programming (SP. As an extension of existing interval parameter fuzzy linear programming, the developed IFLPSV approach has advantages in dealing with dual uncertainty optimization problems, which uncertainty presents as interval parameter with stochastic vertices in both of the objective functions and constraints. The developed IFLPSV method improves upon the IFLP method by allowing dual uncertainty parameters to be incorporated into the optimization processes. A hybrid intelligent algorithm based on genetic algorithm and artificial neural network is used to solve the developed model. The developed method is then applied to water resources allocation in Beijing city of China in 2020, where water resources shortage is a challenging issue. The results indicate that reasonable solutions have been obtained, which are helpful and useful for decision makers. Although the amount of water supply from Guanting and Miyun reservoirs is declining with rainfall reduction, water supply from the South-to-North Water Transfer project will have important impact on water supply structure of Beijing city, particularly in dry year and extraordinary dry year.
Energy Technology Data Exchange (ETDEWEB)
Ibsen, Lars Bo; Liingaard, M.
2006-12-15
A lumped-parameter model represents the frequency dependent soil-structure interaction of a massless foundation placed on or embedded into an unbounded soil domain. In this technical report the steps of establishing a lumped-parameter model are presented. Following sections are included in this report: Static and dynamic formulation, Simple lumped-parameter models and Advanced lumped-parameter models. (au)
A Statistical Model for Estimation of Ichthyofauna Quality Based on Water Parameters in Oituz Bazin
Directory of Open Access Journals (Sweden)
Popescu Carmen
2015-06-01
Full Text Available Fish represents an important food source for people worldwide. Moreover, although considered a very old occupation, fishing continues to provide jobs, especially for the people living in the coastal countries. The quality of surface waters affects the quality of fish as a food source. For this reason, the present study aims to assess the quality of the ichthyofauna in the Oituz River and some of its tributaries using several parameters that have been computed based on the biometric data of the biological material gathered during 2004-2008, in correlation with the water pH and water temperature. The present paper also highlights some observations regarding the changes of the analyzed ecosystems, as well as some recommendations regarding the fish consumption in the studied basin, considered as a food source for humans.
Energy Technology Data Exchange (ETDEWEB)
Schneider, S.; Jacques, D.; Mallants, D.
2010-02-15
For modelling complex hydrological problems, realistic models and accurate hydraulic properties are needed. A mechanistic model (HYDRUS-1D) and a compartment model are evaluated for simulating the water balance in a soil-vegetation-atmosphere system using time series of measured water content at several depths in two lysimeters in a podzol soil with Scots Pine vegetation. 10 calibration scenarios are used to investigate the impact of the model type and the number of horizons in the profile on the calibration accuracy. Main results are: (i) with a large number of soil layers, both models describe accurately the water contents at all depths, (II) the number of soil layers is the major factor that controls the quality of the calibration. The compartment model is as an abstracted model and the mechanistic model is our reference model. Drainage values are the considered output. Drainage values simulated by the abstracted model were close to those of the reference model when averaged over a sufficiently long period (about 9 months). This result suggests that drainage values obtained with an abstracted model are reliably when averaged over sufficiently long periods; the abstracted model needs less computational time without an important loss of accuracy.
Xi, Qing; Li, Zhao-Fu; Luo, Chuan
2014-05-01
Sensitivity analysis of hydrology and water quality parameters has a great significance for integrated model's construction and application. Based on AnnAGNPS model's mechanism, terrain, hydrology and meteorology, field management, soil and other four major categories of 31 parameters were selected for the sensitivity analysis in Zhongtian river watershed which is a typical small watershed of hilly region in the Taihu Lake, and then used the perturbation method to evaluate the sensitivity of the parameters to the model's simulation results. The results showed that: in the 11 terrain parameters, LS was sensitive to all the model results, RMN, RS and RVC were generally sensitive and less sensitive to the output of sediment but insensitive to the remaining results. For hydrometeorological parameters, CN was more sensitive to runoff and sediment and relatively sensitive for the rest results. In field management, fertilizer and vegetation parameters, CCC, CRM and RR were less sensitive to sediment and particulate pollutants, the six fertilizer parameters (FR, FD, FID, FOD, FIP, FOP) were particularly sensitive for nitrogen and phosphorus nutrients. For soil parameters, K is quite sensitive to all the results except the runoff, the four parameters of the soil's nitrogen and phosphorus ratio (SONR, SINR, SOPR, SIPR) were less sensitive to the corresponding results. The simulation and verification results of runoff in Zhongtian watershed show a good accuracy with the deviation less than 10% during 2005- 2010. Research results have a direct reference value on AnnAGNPS model's parameter selection and calibration adjustment. The runoff simulation results of the study area also proved that the sensitivity analysis was practicable to the parameter's adjustment and showed the adaptability to the hydrology simulation in the Taihu Lake basin's hilly region and provide reference for the model's promotion in China.
Zhang, Y. Y.; Shao, Q. X.; Ye, A. Z.; Xing, H. T.; Xia, J.
2016-02-01
Integrated water system modeling is a feasible approach to understanding severe water crises in the world and promoting the implementation of integrated river basin management. In this study, a classic hydrological model (the time variant gain model: TVGM) was extended to an integrated water system model by coupling multiple water-related processes in hydrology, biogeochemistry, water quality, and ecology, and considering the interference of human activities. A parameter analysis tool, which included sensitivity analysis, autocalibration and model performance evaluation, was developed to improve modeling efficiency. To demonstrate the model performances, the Shaying River catchment, which is the largest highly regulated and heavily polluted tributary of the Huai River basin in China, was selected as the case study area. The model performances were evaluated on the key water-related components including runoff, water quality, diffuse pollution load (or nonpoint sources) and crop yield. Results showed that our proposed model simulated most components reasonably well. The simulated daily runoff at most regulated and less-regulated stations matched well with the observations. The average correlation coefficient and Nash-Sutcliffe efficiency were 0.85 and 0.70, respectively. Both the simulated low and high flows at most stations were improved when the dam regulation was considered. The daily ammonium-nitrogen (NH4-N) concentration was also well captured with the average correlation coefficient of 0.67. Furthermore, the diffuse source load of NH4-N and the corn yield were reasonably simulated at the administrative region scale. This integrated water system model is expected to improve the simulation performances with extension to more model functionalities, and to provide a scientific basis for the implementation in integrated river basin managements.
Directory of Open Access Journals (Sweden)
B. Scharnagl
2011-10-01
Full Text Available In situ observations of soil water state variables under natural boundary conditions are often used to estimate the soil hydraulic properties. However, many contributions to the soil hydrological literature have demonstrated that the information content of such data is insufficient to accurately and precisely estimate all the soil hydraulic parameters. In this case study, we explored to which degree prior information about the soil hydraulic parameters can help improve parameter identifiability in inverse modelling of in situ soil water dynamics under natural boundary conditions. We used percentages of sand, silt, and clay as input variables to the ROSETTA pedotransfer function that predicts the parameters in the van Genuchten-Mualem (VGM model of the soil hydraulic functions. To derive additional information about the correlation structure of the predicted parameters, which is not readily provided by ROSETTA, we employed a Monte Carlo approach. We formulated three prior distributions that incorporate to different extents the prior information about the VGM parameters derived with ROSETTA. The inverse problem was posed in a formal Bayesian framework and solved using Markov chain Monte Carlo (MCMC simulation with the DiffeRential Evolution Adaptive Metropolis (DREAM algorithm. Synthetic and real-world soil water content data were used to illustrate the approach. The results of this study demonstrated that prior information about the soil hydraulic parameters significantly improved parameter identifiability and that this approach was effective and robust, even in case of biased prior information. To be effective and robust, however, it was essential to use a prior distribution that incorporates information about parameter correlation.
Directory of Open Access Journals (Sweden)
Dariusz Zdebik
2015-01-01
Full Text Available This paper presents a method for calibration of activated sludge model with the use of computer program BioWin. Computer scheme has been developed on the basis of waste water treatment plant operating in the sequential – flow technology. For calibration of the activated sludge model data of influent and treated effluent from the existing object were used. As a result of conducted analysis was a change in biokinetic model and kinetic parameters parameters of wastewater treatment facilities. The presented method of study of the selected parameters impact on the activated sludge biokinetic model (including autotrophs maximum growth rate, the share of organic slurry in suspension general operational, efficiency secondary settling tanks can be used for conducting simulation studies of other treatment plants.
Shao, Dongguo; Yang, Haidong; Xiao, Yi; Liu, Biyu
2014-01-01
A new method is proposed based on the finite difference method (FDM), differential evolution algorithm and Markov Chain Monte Carlo (MCMC) simulation to identify water quality model parameters of an open channel in a long distance water transfer project. Firstly, this parameter identification problem is considered as a Bayesian estimation problem and the forward numerical model is solved by FDM, and the posterior probability density function of the parameters is deduced. Then these parameters are estimated using a sampling method with differential evolution algorithm and MCMC simulation. Finally this proposed method is compared with FDM-MCMC by a twin experiment. The results show that the proposed method can be used to identify water quality model parameters of an open channel in a long distance water transfer project under different scenarios better with fewer iterations, higher reliability and anti-noise capability compared with FDM-MCMC. Therefore, it provides a new idea and method to solve the traceability problem in sudden water pollution accidents.
Peterson, Eric W.; Wicks, Carol M.
2006-09-01
SummaryQuestions about the importance of conduit geometry and about the values of hydraulic parameters in controlling ground-water flow and solute transport through karstic aquifers have remained largely speculative. One goal of this project was to assess the role that the conduit geometry and the hydraulic parameters have on controlling transport dynamics within karstic aquifers. The storm water management model (SWMM) was applied to the Devil's Icebox-Connor's Cave System in central Missouri, USA. Simulations with incremental changes to conduit geometry or hydraulic parameters were performed with the output compared to a calibrated baseline model. Ten percent changes in the length or width of a conduit produced statistically significant different fluid flow responses. The model exhibited minimal sensitivity to slope and infiltration rates; however, slight changes in Manning's roughness coefficient can highly alter the simulated output. Traditionally, the difference in flow dynamics between karstified aquifers and porous media aquifers has led to the idea that modeling of karst aquifers is more difficult and less precise than modeling of porous media aquifers. When evaluated against models for porous media aquifers, SWMM produced results that were as accurate (10% error compared to basecase). In addition, SWMM has the advantage of providing data about local flow. While SWMM may be an appropriate modeling technique for some karstic aquifers, SWMM should not be viewed as a universal solution to modeling karst systems.
Directory of Open Access Journals (Sweden)
Amit K. Sharma
2011-02-01
Full Text Available The design of photoreactor and its modeling parameters for removal of environmental pollutants in water are described. The work will provide the instructions to design of photoreactor with modeling parameters, and to allow these parameters to communicate degradation efficiency of the analyte in water samples. The modeling parameters are outlined by which the photoreactor can use UV source to degrade the composition of pollutant. The operation of degradation through photoreactor is applied to the study of degradation rate of pollutant i.e. malathion and the produced informative data at various time intervals also correlated with UV-vis spectrophotometry for the validation of results. The purpose of designed photoreactor is to know the best percentage degradability of pollutants at micro to nano gram levels using nanosemiconductor sensitizer like TiO2. Such designs promises the high impact at very low levels, less time consuming process, low consumable solvents and suit for field application purposes which focuses the merits of the designed photoreactor.
Metzger, Christine; Nilsson, Mats B.; Peichl, Matthias; Jansson, Per-Erik
2016-12-01
In contrast to previous peatland carbon dioxide (CO2) model sensitivity analyses, which usually focussed on only one or a few processes, this study investigates interactions between various biotic and abiotic processes and their parameters by comparing CoupModel v5 results with multiple observation variables. Many interactions were found not only within but also between various process categories simulating plant growth, decomposition, radiation interception, soil temperature, aerodynamic resistance, transpiration, soil hydrology and snow. Each measurement variable was sensitive to up to 10 (out of 54) parameters, from up to 7 different process categories. The constrained parameter ranges varied, depending on the variable and performance index chosen as criteria, and on other calibrated parameters (equifinalities). Therefore, transferring parameter ranges between models needs to be done with caution, especially if such ranges were achieved by only considering a few processes. The identified interactions and constrained parameters will be of great interest to use for comparisons with model results and data from similar ecosystems. All of the available measurement variables (net ecosystem exchange, leaf area index, sensible and latent heat fluxes, net radiation, soil temperatures, water table depth and snow depth) improved the model constraint. If hydraulic properties or water content were measured, further parameters could be constrained, resolving several equifinalities and reducing model uncertainty. The presented results highlight the importance of considering biotic and abiotic processes together and can help modellers and experimentalists to design and calibrate models as well as to direct experimental set-ups in peatland ecosystems towards modelling needs.
DEFF Research Database (Denmark)
Ibsen, Lars Bo; Liingaard, Morten
A lumped-parameter model represents the frequency dependent soil-structure interaction of a massless foundation placed on or embedded into an unbounded soil domain. The lumped-parameter model development have been reported by (Wolf 1991b; Wolf 1991a; Wolf and Paronesso 1991; Wolf and Paronesso 19...
Energy Technology Data Exchange (ETDEWEB)
Champion, C. [Universite Paul Verlaine-Metz, Laboratoire de Physique Moleculaire et des Collisions, 1 Boulevard Arago, Technopole 2000, 57078 Metz (France)], E-mail: champion@univ-metz.fr; Incerti, S. [CNRS/IN2P3, Centre d' Etudes Nucleaires de Bordeaux-Gradignan, UMR 5797, Gradignan F-33175 (France); Universite de Bordeaux, Centre d' Etudes Nucleaires de Bordeaux-Gradignan, UMR 5797, Gradignan F-33175 (France); Aouchiche, H.; Oubaziz, D. [Universite M. Mammeri, Laboratoire de Mecanique, Structure et Energetique, BP 17, Tizi-Ouzou 15000 (Algeria)
2009-09-15
The present work provides an accurate description of the elastic scattering process for low-energy electrons (10 eV-10 keV) in liquid water by means of a free-parameter quantum-mechanical treatment. The calculations are performed in the partial-wave formalism by means of a total interaction potential taking into account a static contribution as well as fine effects like exchange and polarization contributions. The obtained results in terms of singly differential and total cross sections exhibit relatively good agreement with available experimental data (in gaseous water). They have been incorporated into the Geant4 toolkit, which has been recently extended with physics processes for microdosimetry applications in liquid water down to the electronvolt scale. They offer an improved alternative to the semi-empirical and to the screened Rutherford models already available in this very low-energy extension.
A survey of catfish pond water chemistry parameters for copper toxicity modelling
Water samples were collected from 20 catfish ponds in 2015 to obtain data useful in predicting copper toxicity and chemical behavior. Ponds were located in major catfish producing areas of west Alabama, east Arkansas, and Mississippi. Pond types included traditional levee ponds, split-ponds, water...
Rodrigo-Ilarri, Javier; Segura-Sobrino, Francisco; Rodrigo-Clavero, Maria-Elena
2014-05-01
Landfills are commonly used as the final deposit of urban solid waste. Despite the waste is previously processed on a treatment plant, the final amount of organic matter which reaches the landfill is large however. The biodegradation of this organic matter forms a mixture of greenhouse gases (essentially Methane and Carbon-Dioxide as well as Ammonia and Hydrogen Sulfide). From the environmental point of view, solid waste landfills are therefore considered to be one of the main greenhouse gas sources. Different mathematical models are usually applied to predict the amount of biogas produced on real landfills. The waste chemical composition and the availability of water in the solid waste appear to be the main parameters of these models. Results obtained when performing a sensitivity analysis over the biogas production model parameters under real conditions are shown. The importance of a proper characterizacion of the waste as well as the necessity of improving the understanding of the behaviour and development of the water on the unsaturated mass of waste are emphasized.
Kramers, G.; Dam, van J.C.; Ritsema, C.J.; Stagnitti, F.; Oostindie, K.; Dekker, L.W.
2005-01-01
A modified version of the popular agrohydrological model SWAP has been used to evaluate modelling of soil water flow and crop growth at field situations in which water repellency causes preferential flow. The parameter sensitivity in such situations has been studied. Three options to model soil
Regionalisation of parameters of a large-scale water quality model in Lithuania using PAIC-SWAT
Zarrineh, Nina; van Griensven, Ann; Sennikovs, Juris; Bekere, Liga; Plunge, Svajunas
2015-04-01
To comply with the EU Water Framework Directive, all water bodies need to achieve good ecological status. To reach these goals, the Environmental Protection Agency (AAA) has to elaborate river basin districts management plans and programmes of measures for all catchments in Lithuania. For this purpose, a Soil and Water Assessment Tool (SWAT) model was set up for all Lithuanian catchments using the most recent version of SWAT2012 rev627 implemented and imbedded in a Python workflow by the Center of Processes Analysis and Research (PAIC). The model was calibrated and evaluated using all monitoring data of river discharge, nitrogen and phosphorous concentrations and load. A regionalisation strategy has been set up by identifying 13 hydrological regions according to the runoff formation and hydrological conditions. In each region, a representative catchment was selected and calibrated using a combination of manual and automated calibration techniques. After final parameterization and fulfilling of calibrating and validating evaluation criteria, the same parameters sets have been extrapolated to other catchments within the same hydrological region. Multi variable cal/val strategy was implemented for the following variables: river flow and in-stream NO3, Total Nitrogen, PO4 and Total Phosphorous concentrations. The criteria used for calibration, validation and extrapolation are: Nash-Sutcliffe Efficiency (NSE) for flow and R-squared for water quality variables and PBIAS (percentage bias) for all variables. For the hydrological calibration, NSE values greater than 0.5 should be achieved, while for validation and extrapolation the threshold is respectively 0.4 and 0.3. PBIAS errors have to be less than 20% for calibration and for validation and extrapolation less than 25% and 30%, respectively. In water quality calibration, R-squared should be achieved to 0.5 for calibration and for validation and extrapolation to 0.4 and 0.3 respectively for nitrogen variables. Besides
Directory of Open Access Journals (Sweden)
Dario Constantinescu
2016-12-01
Full Text Available Drought stress is a major abiotic stres threatening plant and crop productivity. In case of fleshy fruits, understanding Drought stress is a major abiotic stress threatening plant and crop productivity. In case of fleshy fruits, understanding mechanisms governing water and carbon accumulations and identifying genes, QTLs and phenotypes, that will enable trade-offs between fruit growth and quality under Water Deficit (WD condition is a crucial challenge for breeders and growers. In the present work, 117 recombinant inbred lines of a population of Solanum lycopersicum were phenotyped under control and WD conditions. Plant water status, fruit growth and composition were measured and data were used to calibrate a process-based model describing water and carbon fluxes in a growing fruit as a function of plant and environment. Eight genotype-dependent model parameters were estimated using a multiobjective evolutionary algorithm in order to minimize the prediction errors of fruit dry and fresh mass throughout fruit development. WD increased the fruit dry matter content (up to 85 % and decreased its fresh weight (up to 60 %, big fruit size genotypes being the most sensitive. The mean normalized root mean squared errors of the predictions ranged between 16-18 % in the population. Variability in model genotypic parameters allowed us to explore diverse genetic strategies in response to WD. An interesting group of genotypes could be discriminated in which i the low loss of fresh mass under WD was associated with high active uptake of sugars and low value of the maximum cell wall extensibility, and ii the high dry matter content in control treatment (C was associated with a slow decrease of mass flow. Using 501 SNP markers genotyped across the genome, a QTL analysis of model parameters allowed to detect three main QTLs related to xylem and phloem conductivities, on chromosomes 2, 4 and 8. The model was then applied to design ideotypes with high dry matter
Energy Technology Data Exchange (ETDEWEB)
Xu, S.; Peddle, D.R.; Coburn, C.A.; Kienzle, S. [Univ. of Lethbridge, Dept. of Geography, Lethbridge, Alberta (Canada)
2008-06-15
Net primary productivity (NPP) is a key component of the terrestrial carbon cycle and is important in ecological, watershed, and forest management studies, and more broadly in global climate change research. Determining the relative importance and magnitude of uncertainty of NPP model inputs is important for proper carbon reporting over larger areas and time periods. This paper presents a systematic evaluation of the boreal ecosystem productivity simulator (BEPS) model in mountainous terrain using an established montane forest test site in Kananaskis, Alberta, in the Canadian Rocky Mountains. Model runs were based on forest (land cover, leaf area index (LAI), biomass) and climate-water inputs (solar radiation, temperature, precipitation, humidity, soil water holding capacity) derived from digital elevation model (DEM) derivatives, climate data, geographical information system (GIS) functions, and topographically corrected satellite imagery. Four sensitivity analyses were conducted as a controlled series of experiments involving (i) NPP individual parameter sensitivity for a full growing season, (ii) NPP independent variation tests (parameter {mu} {+-} 1{sigma}), (iii) factorial analyses to assess more complex multiple-factor interactions, and (iv) topographic correction. The results, validated against field measurements, showed that modeled NPP was sensitive to most inputs measured in the study area, with LAI and forest type the most important forest input, and solar radiation the most important climate input. Soil available water holding capacity expressed as a function of wetness index was only significant in conjunction with precipitation when both parameters represented a moisture-deficit situation. NPP uncertainty resulting from topographic influence was equivalent to 140 kg C ha{sup -1}{center_dot}year{sup -1}. This suggested that topographic correction of model inputs is important for accurate NPP estimation. The BEPS model, designed originally for flat
Response model parameter linking
Barrett, Michelle Derbenwick
2015-01-01
With a few exceptions, the problem of linking item response model parameters from different item calibrations has been conceptualized as an instance of the problem of equating observed scores on different test forms. This thesis argues, however, that the use of item response models does not require
2008-12-01
opposite to the fluoride leaving group through an SN2 -type reaction . Competition exists between a breaking of the P-S bond and a breaking of the P- OEt...model (PCM) in Gaussian03 to predict reaction rates of hydrolysis. 1. INTRODUCTION In previous research, empirical methods showed that uptake of... reaction . Verification that a transi- tion state was obtained in the degradation pathway was ob- tained by carefully tracing the reaction path in both direc
2004-03-01
Experimental study of the hydrothermal formation of kaolinite. Chem. Geol. 156, 171-190. Hull A. B. and Hull J. R. (1987) Geometric modeling of...A. and Barnes H. L. (1991a) Mechanisms of pyrite and marcasite formation from solution: III. Hydrothermal processes. Geochim. Cosmochim. Acta 55...12 3.1.1.2 Amorphous SiO2, Cristobalite , and SiO2 Polymorph Precipitation...................... 14 3.1.2 Feldspars
Directory of Open Access Journals (Sweden)
Sylvain Ferrant
2016-02-01
Full Text Available Sentinel-2 (S2 earth observation satellite mission, launched in 2015, is foreseen to promote within-field decisions in Precision Agriculture (PA for both: (1 optimizing crop production; and (2 regulating environmental impacts. In this second scope, a set of Leaf Area Index (LAI derived from S2 type time-series (2006–2010, using Formosat-2 satellite is used to spatially constrain the within-field crop growth and the related nitrogen contamination of surface water simulated at a small experimental catchment scale with the distributed agro-hydrological model Topography Nitrogen Transfer and Transformation (TNT2. The Soil Water Holding Capacity (SWHC, represented by two parameters, soil depth and retention porosity, is used to fit the yearly maximum of LAI (LAX at each pixel of the satellite image. Possible combinations of soil parameters, defining 154 realistic SWHC found on the study site are used to force spatially homogeneous SWHC. LAX simulated at the pixel level for the 154 SWHC, for each of the five years of the study period, are recorded and hereafter referred to as synthetic LAX. Optimal SWHCyear_I,pixel_j, corresponding to minimal difference between observed and synthetic LAXyear_I,pixel_j, is selected for each pixel, independent of the value at neighboring pixels. Each re-estimated soil maps are used to re-simulate LAXyear_I. Results show that simulated and synthetic LAXyear_I,allpixels obtained from SWHCyear_I,allpixels are close and accurately fit the observed LAXyear_I,allpixels (RMSE = 0.05 m2/m2 to 0.2 and R2 = 0.99 to 0.94, except for the year 2008 (RMSE = 0.8 m2/m2 and R2 = 0.8. These results show that optimal SWHC can be derived from remote sensing series for one year. Unique SWHC solutions for each pixel that limit the LAX error for the five years to less than 0.2 m2/m2 are found for only 10% of the pixels. Selection of unique soil parameters using multi-year LAX and neighborhood solution is expected to deliver more robust soil
Distributed Parameter Modelling Applications
DEFF Research Database (Denmark)
2011-01-01
Here the issue of distributed parameter models is addressed. Spatial variations as well as time are considered important. Several applications for both steady state and dynamic applications are given. These relate to the processing of oil shale, the granulation of industrial fertilizers and the d......Here the issue of distributed parameter models is addressed. Spatial variations as well as time are considered important. Several applications for both steady state and dynamic applications are given. These relate to the processing of oil shale, the granulation of industrial fertilizers...... sands processing. The fertilizer granulation model considers the dynamics of MAP-DAP (mono and diammonium phosphates) production within an industrial granulator, that involves complex crystallisation, chemical reaction and particle growth, captured through population balances. A final example considers...
Directory of Open Access Journals (Sweden)
Li Wang
2017-02-01
Full Text Available The ability to obtain appropriate parameters for an advanced pressurized water reactor (PWR unit model is of great significance for power system analysis. The attributes of that ability include the following: nonlinear relationships, long transition time, intercoupled parameters and difficult obtainment from practical test, posed complexity and difficult parameter identification. In this paper, a model and a parameter identification method for the PWR primary loop system were investigated. A parameter identification process was proposed, using a particle swarm optimization (PSO algorithm that is based on random perturbation (RP-PSO. The identification process included model variable initialization based on the differential equations of each sub-module and program setting method, parameter obtainment through sub-module identification in the Matlab/Simulink Software (Math Works Inc., Natick, MA, USA as well as adaptation analysis for an integrated model. A lot of parameter identification work was carried out, the results of which verified the effectiveness of the method. It was found that the change of some parameters, like the fuel temperature and coolant temperature feedback coefficients, changed the model gain, of which the trajectory sensitivities were not zero. Thus, obtaining their appropriate values had significant effects on the simulation results. The trajectory sensitivities of some parameters in the core neutron dynamic module were interrelated, causing the parameters to be difficult to identify. The model parameter sensitivity could be different, which would be influenced by the model input conditions, reflecting the parameter identifiability difficulty degree for various input conditions.
Liang, Shidong; Jia, Haifeng; Xu, Changqing; Xu, Te; Melching, Charles
2016-08-01
Facing increasingly serious water pollution, the Chinese government is changing the environmental management strategy from solely pollutant concentration control to a Total Maximum Daily Load (TMDL) program, and water quality models are increasingly being applied to determine the allowable pollutant load in the TMDL. Despite the frequent use of models, few studies have focused on how parameter uncertainty in water quality models affect the allowable pollutant loads in the TMDL program, particularly for complicated and high-dimension water quality models. Uncertainty analysis for such models is limited by time-consuming simulation and high-dimensionality and nonlinearity in parameter spaces. In this study, an allowable pollutant load calculation platform was established using the Environmental Fluid Dynamics Code (EFDC), which is a widely applied hydrodynamic-water quality model. A Bayesian approach, i.e. the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm, which is a high-efficiency, multi-chain Markov Chain Monte Carlo (MCMC) method, was applied to assess the effects of parameter uncertainty on the water quality model simulations and its influence on the allowable pollutant load calculation in the TMDL program. Miyun Reservoir, which is the most important surface drinking water source for Beijing, suffers from eutrophication and was selected as a case study. The relations between pollutant loads and water quality indicators are obtained through a graphical method in the simulation platform. Ranges of allowable pollutant loads were obtained according to the results of parameter uncertainty analysis, i.e. Total Organic Carbon (TOC): 581.5-1030.6t·yr(-1); Total Phosphorus (TP): 23.3-31.0t·yr(-1); and Total Nitrogen (TN): 480-1918.0t·yr(-1). The wide ranges of allowable pollutant loads reveal the importance of parameter uncertainty analysis in a TMDL program for allowable pollutant load calculation and margin of safety (MOS) determination. The sources
Energy Technology Data Exchange (ETDEWEB)
Liang, Shidong, E-mail: emblembl@sina.com [School of Environment, Tsinghua University, 1 Qinghuayuan, Haidian District, Beijing 100084 (China); Jia, Haifeng, E-mail: jhf@tsinghua.edu.cn [School of Environment, Tsinghua University, 1 Qinghuayuan, Haidian District, Beijing 100084 (China); Xu, Changqing, E-mail: 2008changqing@163.com [School of Environment, Tsinghua University, 1 Qinghuayuan, Haidian District, Beijing 100084 (China); Xu, Te, E-mail: xt_lichking@qq.com [School of Environment, Tsinghua University, 1 Qinghuayuan, Haidian District, Beijing 100084 (China); Melching, Charles, E-mail: steve.melching17@gmail.com [Melching Water Solutions, 4030 W. Edgerton Avenue, Greenfield, WI 53221 (United States)
2016-08-01
Facing increasingly serious water pollution, the Chinese government is changing the environmental management strategy from solely pollutant concentration control to a Total Maximum Daily Load (TMDL) program, and water quality models are increasingly being applied to determine the allowable pollutant load in the TMDL. Despite the frequent use of models, few studies have focused on how parameter uncertainty in water quality models affect the allowable pollutant loads in the TMDL program, particularly for complicated and high-dimension water quality models. Uncertainty analysis for such models is limited by time-consuming simulation and high-dimensionality and nonlinearity in parameter spaces. In this study, an allowable pollutant load calculation platform was established using the Environmental Fluid Dynamics Code (EFDC), which is a widely applied hydrodynamic-water quality model. A Bayesian approach, i.e. the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm, which is a high-efficiency, multi-chain Markov Chain Monte Carlo (MCMC) method, was applied to assess the effects of parameter uncertainty on the water quality model simulations and its influence on the allowable pollutant load calculation in the TMDL program. Miyun Reservoir, which is the most important surface drinking water source for Beijing, suffers from eutrophication and was selected as a case study. The relations between pollutant loads and water quality indicators are obtained through a graphical method in the simulation platform. Ranges of allowable pollutant loads were obtained according to the results of parameter uncertainty analysis, i.e. Total Organic Carbon (TOC): 581.5–1030.6 t·yr{sup −1}; Total Phosphorus (TP): 23.3–31.0 t·yr{sup −1}; and Total Nitrogen (TN): 480–1918.0 t·yr{sup −1}. The wide ranges of allowable pollutant loads reveal the importance of parameter uncertainty analysis in a TMDL program for allowable pollutant load calculation and margin of safety (MOS
Joung, In Suk; Cheatham, Thomas E
2009-10-01
The dynamic and energetic properties of the alkali and halide ions were calculated using molecular dynamics (MD) and free energy simulations with various different water and ion force fields including our recently developed water-model-specific ion parameters. The properties calculated were activity coefficients, diffusion coefficients, residence times of atomic pairs, association constants, and solubility. Through calculation of these properties, we can assess the validity and range of applicability of the simple pair potential models and better understand their limitations. Due to extreme computational demands, the activity coefficients were only calculated for a subset of the models. The results qualitatively agree with experiment. Calculated diffusion coefficients and residence times between cation-anion, water-cation, and water-anion showed differences depending on the choice of water and ion force field used. The calculated solubilities of the alkali-halide salts were generally lower than the true solubility of the salts. However, for both the TIP4P(EW) and SPC/E water-model-specific ion parameters, solubility was reasonably well-reproduced. Finally, the correlations among the various properties led to the following conclusions: (1) The reliability of the ion force fields is significantly affected by the specific choice of water model. (2) Ion-ion interactions are very important to accurately simulate the properties, especially solubility. (3) The SPC/E and TIP4P(EW) water-model-specific ion force fields are preferred for simulation in high salt environments compared to the other ion force fields.
Zhang, Ningyi; Li, Gang; Yu, Shanxiang; An, Dongsheng; Sun, Qian; Luo, Weihong; Yin, Xinyou
2017-01-01
Accurately predicting photosynthesis in response to water and nitrogen stress is the first step toward predicting crop growth, yield and many quality traits under fluctuating environmental conditions. While mechanistic models are capable of predicting photosynthesis under fluctuating environmental conditions, simplifying the parameterization procedure is important toward a wide range of model applications. In this study, the biochemical photosynthesis model of Farquhar, von Caemmerer and Berry (the FvCB model) and the stomatal conductance model of Ball, Woodrow and Berry which was revised by Leuning and Yin (the BWB-Leuning-Yin model) were parameterized for Lilium (L. auratum × speciosum “Sorbonne”) grown under different water and nitrogen conditions. Linear relationships were found between biochemical parameters of the FvCB model and leaf nitrogen content per unit leaf area (Na), and between mesophyll conductance and Na under different water and nitrogen conditions. By incorporating these Na-dependent linear relationships, the FvCB model was able to predict the net photosynthetic rate (An) in response to all water and nitrogen conditions. In contrast, stomatal conductance (gs) can be accurately predicted if parameters in the BWB-Leuning-Yin model were adjusted specifically to water conditions; otherwise gs was underestimated by 9% under well-watered conditions and was overestimated by 13% under water-deficit conditions. However, the 13% overestimation of gs under water-deficit conditions led to only 9% overestimation of An by the coupled FvCB and BWB-Leuning-Yin model whereas the 9% underestimation of gs under well-watered conditions affected little the prediction of An. Our results indicate that to accurately predict An and gs under different water and nitrogen conditions, only a few parameters in the BWB-Leuning-Yin model need to be adjusted according to water conditions whereas all other parameters are either conservative or can be adjusted according to
Timbe, E.; Windhorst, D.; Crespo, P.; Frede, H.-G.; Feyen, J.; Breuer, L.
2014-04-01
Weekly samples from surface waters, springs, soil water and rainfall were collected in a 76.9 km2 mountain rain forest catchment and its tributaries in southern Ecuador. Time series of the stable water isotopes δ18O and δ2H were used to calculate mean transit times (MTTs) and the transit time distribution functions (TTDs) solving the convolution method for seven lumped-parameter models. For each model setup, the generalized likelihood uncertainty estimation (GLUE) methodology was applied to find the best predictions, behavioral solutions and parameter identifiability. For the study basin, TTDs based on model types such as the linear-piston flow for soil waters and the exponential-piston flow for surface waters and springs performed better than more versatile equations such as the gamma and the two parallel linear reservoirs. Notwithstanding both approaches yielded a better goodness of fit for most sites, but with considerable larger uncertainty shown by GLUE. Among the tested models, corresponding results were obtained for soil waters with short MTTs (ranging from 2 to 9 weeks). For waters with longer MTTs differences were found, suggesting that for those cases the MTT should be based at least on an intercomparison of several models. Under dominant baseflow conditions long MTTs for stream water ≥ 2 yr were detected, a phenomenon also observed for shallow springs. Short MTTs for water in the top soil layer indicate a rapid exchange of surface waters with deeper soil horizons. Differences in travel times between soils suggest that there is evidence of a land use effect on flow generation.
Directory of Open Access Journals (Sweden)
Ranran Li
2015-09-01
Full Text Available An integrated approach using the inverse method and Bayesian approach, combined with a lake eutrophication water quality model, was developed for parameter estimation and water environmental capacity (WEC analysis. The model was used to support load reduction and effective water quality management in the Taihu Lake system in eastern China. Water quality was surveyed yearly from 1987 to 2010. Total nitrogen (TN and total phosphorus (TP were selected as water quality model variables. Decay rates of TN and TP were estimated using the proposed approach. WECs of TN and TP in 2011 were determined based on the estimated decay rates. Results showed that the historical loading was beyond the WEC, thus, reduction of nitrogen and phosphorus input is necessary to meet water quality goals. Then WEC and allowable discharge capacity (ADC in 2015 and 2020 were predicted. The reduction ratios of ADC during these years were also provided. All of these enable decision makers to assess the influence of each loading and visualize potential load reductions under different water quality goals, and then to formulate a reasonable water quality management strategy.
Energy Technology Data Exchange (ETDEWEB)
Shatat, M.I.M.; Mahkamov, K. [School of Engineering, Durham University, South Road, Durham, DH1 3LE (United Kingdom)
2010-01-15
The paper describes the experimental investigations of the performance of a multi-stage water desalination still connected to a heat pipe evacuated tube solar collector with aperture area of 1.7 m{sup 2}. The multi-stage solar still water desalination system was designed to recover latent heat from evaporation and condensation processes in four stages. The variation in the solar radiation during a typical mid-summer day in the Middle East region was simulated on the test rig using an array of 110 halogen floodlights covering the area of the collector. The results of tests demonstrate that the system produces about 9 kg of fresh water per day and has a solar collector efficiency of about 68%. However, the overall efficiency of the laboratory test rig at this stage of the investigations was found to be at the level of 33% due to excessive heat losses in the system. The analysis of the distilled water showed that its quality was within the World Health Organization guidelines. The still's operation was numerically simulated by employing a mathematical model based on a system of ordinary energy and mass conservation differential equations written for each stage of the still. A computer program was developed for transient simulations of the evaporation and condensation processes inside the multi-stage still. Experimental results obtained and theoretical predictions were found to be in good agreement. The results on the determination of rational design dimensions and number of stages of the still for a given aperture of the solar collector are also presented in this work. (author)
Bertoldi, Giacomo; Cordano, Emanuele; Brenner, Johannes; Senoner, Samuel; Della Chiesa, Stefano; Niedrist, Georg
2017-04-01
In mountain regions, the plot- and catchment-scale water and energy budgets are controlled by a complex interplay of different abiotic (i.e. topography, geology, climate) and biotic (i.e. vegetation, land management) controlling factors. When integrated, physically-based eco-hydrological models are used in mountain areas, there are a large number of parameters, topographic and boundary conditions that need to be chosen. However, data on soil and land-cover properties are relatively scarce and do not reflect the strong variability at the local scale. For this reason, tools for uncertainty quantification and optimal parameters identification are essential not only to improve model performances, but also to identify most relevant parameters to be measured in the field and to evaluate the impact of different assumptions for topographic and boundary conditions (surface, lateral and subsurface water and energy fluxes), which are usually unknown. In this contribution, we present the results of a sensitivity analysis exercise for a set of 20 experimental stations located in the Italian Alps, representative of different conditions in terms of topography (elevation, slope, aspect), land use (pastures, meadows, and apple orchards), soil type and groundwater influence. Besides micrometeorological parameters, each station provides soil water content at different depths, and in three stations (one for each land cover) eddy covariance fluxes. The aims of this work are: (I) To present an approach for improving calibration of plot-scale soil moisture and evapotranspiration (ET). (II) To identify the most sensitive parameters and relevant factors controlling temporal and spatial differences among sites. (III) Identify possible model structural deficiencies or uncertainties in boundary conditions. Simulations have been performed with the GEOtop 2.0 model, which is a physically-based, fully distributed integrated eco-hydrological model that has been specifically designed for mountain
Cooper, H. J.; Crosson, W. L.; Smith, E. A.
1992-01-01
The measured atmospheric parameters and the fluxes of latent and sensible heat across the biosphere-atmosphere interface collected during the water-stressed period of the First ISLSCP Field Experiment (FIFE) were compared with those calculated by an experimental version of the Biosphere-Atmosphere Transfer Scheme (Ex-BATS). It is shown that the brightness temperature (T(B)) values observed near the surface during FIFE 1987 are closely correlated to in-canopy temperatures calculated by Ex-BATS. The 1987 near-surface observations of T(B) are also well correlated to AVHHR channels 4 and 5 measurements. An inverted form of Ex-BATS was applied to determine the associated required in-canopy temperatures, T(icr), and regressions between T(icr) and T(B) found from the 1987 data were applied to the 1989 observed T(B) at a different site. The T(icr) so estimated showed excellent correlation to the 1989 model calculated T(icr).
The ability to predict water quality in lakes is important since lakes are sources of water for agriculture, drinking, and recreational uses. Lakes are also home to a dynamic ecosystem of lacustrine wetlands and deep waters. They are sensitive to pH changes and are dependent on d...
Photovoltaic module parameters acquisition model
Cibira, Gabriel; Koščová, Marcela
2014-09-01
This paper presents basic procedures for photovoltaic (PV) module parameters acquisition using MATLAB and Simulink modelling. In first step, MATLAB and Simulink theoretical model are set to calculate I-V and P-V characteristics for PV module based on equivalent electrical circuit. Then, limited I-V data string is obtained from examined PV module using standard measurement equipment at standard irradiation and temperature conditions and stated into MATLAB data matrix as a reference model. Next, the theoretical model is optimized to keep-up with the reference model and to learn its basic parameters relations, over sparse data matrix. Finally, PV module parameters are deliverable for acquisition at different realistic irradiation, temperature conditions as well as series resistance. Besides of output power characteristics and efficiency calculation for PV module or system, proposed model validates computing statistical deviation compared to reference model.
Mode choice model parameters estimation
Strnad, Irena
2010-01-01
The present work focuses on parameter estimation of two mode choice models: multinomial logit and EVA 2 model, where four different modes and five different trip purposes are taken into account. Mode choice model discusses the behavioral aspect of mode choice making and enables its application to a traffic model. Mode choice model includes mode choice affecting trip factors by using each mode and their relative importance to choice made. When trip factor values are known, it...
Tao, Yang; Li, Yong; Zhou, Ruiyun; Chu, Dinh-Toi; Su, Lijuan; Han, Yongbin; Zhou, Jianzhong
2016-10-01
In the study, osmotically dehydrated cherry tomatoes were partially dried to water activity between 0.746 and 0.868, vacuum-packed and stored at 4-30 °C for 60 days. Adaptive neuro-fuzzy inference system (ANFIS) was utilized to predict the physicochemical and microbiological parameters of these partially dried cherry tomatoes during storage. Satisfactory accuracies were obtained when ANFIS was used to predict the lycopene and total phenolic contents, color and microbial contamination. The coefficients of determination for all the ANFIS models were higher than 0.86 and showed better performance for prediction compared with models developed by response surface methodology. Through ANFIS modeling, the effects of storage conditions on the properties of partially dried cherry tomatoes were visualized. Generally, contents of lycopene and total phenolics decreased with the increase in water activity, temperature and storage time, while aerobic plate count and number of yeasts and molds increased at high water activities and temperatures. Overall, ANFIS approach can be used as an effective tool to study the quality decrease and microbial pollution of partially dried cherry tomatoes during storage, as well as identify the suitable preservation conditions.
B. Scharnagl; J.A. Vrugt; H. Vereecken; M. Herbst
2011-01-01
In situ observations of soil water state variables under natural boundary conditions are often used to estimate the soil hydraulic properties. However, many contributions to the soil hydrological literature have demonstrated that the information content of such data is insufficient to accurately and
Padró, Juan M; Ponzinibbio, Agustín; Mesa, Leidy B Agudelo; Reta, Mario
2011-03-01
The partition coefficients, P(IL/w), for different probe molecules as well as for compounds of biological interest between the room-temperature ionic liquids (RTILs) 1-butyl-3-methylimidazolium hexafluorophosphate, [BMIM][PF(6)], 1-hexyl-3-methylimidazolium hexafluorophosphate, [HMIM][PF(6)], 1-octyl-3-methylimidazolium tetrafluoroborate, [OMIM][BF(4)] and water were accurately measured. [BMIM][PF(6)] and [OMIM][BF(4)] were synthesized by adapting a procedure from the literature to a simpler, single-vessel and faster methodology, with a much lesser consumption of organic solvent. We employed the solvation-parameter model to elucidate the general chemical interactions involved in RTIL/water partitioning. With this purpose, we have selected different solute descriptor parameters that measure polarity, polarizability, hydrogen-bond-donor and hydrogen-bond-acceptor interactions, and cavity formation for a set of specifically selected probe molecules (the training set). The obtained multiparametric equations were used to predict the partition coefficients for compounds not present in the training set (the test set), most being of biological interest. Partial solubility of the ionic liquid in water (and water into the ionic liquid) was taken into account to explain the obtained results. This fact has not been deeply considered up to date. Solute descriptors were obtained from the literature, when available, or else calculated through commercial software. An excellent agreement between calculated and experimental log P(IL/w) values was obtained, which demonstrated that the resulting multiparametric equations are robust and allow predicting partitioning for any organic molecule in the biphasic systems studied.
Estimation of ground water hydraulic parameters
Energy Technology Data Exchange (ETDEWEB)
Hvilshoej, Soeren
1998-11-01
The main objective was to assess field methods to determine ground water hydraulic parameters and to develop and apply new analysis methods to selected field techniques. A field site in Vejen, Denmark, which previously has been intensively investigated on the basis of a large amount of mini slug tests and tracer tests, was chosen for experimental application and evaluation. Particular interest was in analysing partially penetrating pumping tests and a recently proposed single-well dipole test. Three wells were constructed in which partially penetrating pumping tests and multi-level single-well dipole tests were performed. In addition, multi-level slug tests, flow meter tests, gamma-logs, and geologic characterisation of soil samples were carried out. In addition to the three Vejen analyses, data from previously published partially penetrating pumping tests were analysed assuming homogeneous anisotropic aquifer conditions. In the present study methods were developed to analyse partially penetrating pumping tests and multi-level single-well dipole tests based on an inverse numerical model. The obtained horizontal hydraulic conductivities from the partially penetrating pumping tests were in accordance with measurements obtained from multi-level slug tests and mini slug tests. Accordance was also achieved between the anisotropy ratios determined from partially penetrating pumping tests and multi-level single-well dipole tests. It was demonstrated that the partially penetrating pumping test analysed by and inverse numerical model is a very valuable technique that may provide hydraulic information on the storage terms and the vertical distribution of the horizontal and vertical hydraulic conductivity under both confined and unconfined aquifer conditions. (EG) 138 refs.
Hallbauer-Zadorozhnaya, Valeriya; Santarato, Giovanni; Abu Zeid, Nasser
2015-08-01
In this paper, two separate but related goals are tackled. The first one is to demonstrate that in some saturated rock textures the non-linear behaviour of induced polarization (IP) and the violation of Ohm's law not only are real phenomena, but they can also be satisfactorily predicted by a suitable physical-mathematical model, which is our second goal. This model is based on Fick's second law. As the model links the specific dependence of resistivity and chargeability of a laboratory sample to the injected current and this in turn to its pore size distribution, it is able to predict pore size distribution from laboratory measurements, in good agreement with mercury injection capillary pressure test results. This fact opens up the possibility for hydrogeophysical applications on a macro scale. Mathematical modelling shows that the chargeability acquired in the field under normal conditions, that is at low current, will always be very small and approximately proportional to the applied current. A suitable field test site for demonstrating the possible reliance of both resistivity and chargeability on current was selected and a specific measuring strategy was established. Two data sets were acquired using different injected current strengths, while keeping the charging time constant. Observed variations of resistivity and chargeability are in agreement with those predicted by the mathematical model. These field test data should however be considered preliminary. If confirmed by further evidence, these facts may lead to changing the procedure of acquiring field measurements in future, and perhaps may encourage the design and building of a new specific geo-resistivity meter. This paper also shows that the well-known Marshall and Madden's equations based on Fick's law cannot be solved without specific boundary conditions.
HSPF 模型水文水质参数敏感性分析%Sensitivity Analysis of Hydrological and Water Quality Parameters of HSPF Model
Institute of Scientific and Technical Information of China (English)
罗川; 李兆富; 席庆; 潘剑君
2014-01-01
参数敏感性分析是模型不确定性量化的重要环节，有助于对关键参数的识别，减少参数的不确定性影响，进而提高参数优化效率。以太湖地区典型小流域为研究区，采用扰动分析法对 HSPF 模型水文模块、泥沙模块以及氮磷输移等水文、水质模拟过程的参数进行了敏感性分析。研究结果显示：水文模块选取的17个参数中有7个敏感：UZSN、INFILT、AGWRC 对径流的敏感级别为芋类，LZSN、DEEPFR、INTFW、IRC 敏感级别为域类。泥沙透水地面模块选取的9个参数中，KSER、KGER、JGER 为芋类敏感参数， JSER 为郁类敏感参数；不透水地面模块选取的4个参数中，KEIM、JEIM、ACCSDP 对泥沙产量的敏感级别为芋类；河道模块选取的5个参数中，KSAND、EXPSND 为芋类敏感参数，TAUCS、TAUCD 为域类敏感参数。总氮模拟选取了23个参数分析敏感性，其中WSQOP、SQOLIM、MON-GRND-CONC 为郁类敏感参数，KATM20、MON-IFLW-CONC 为芋类敏感参数，TCNIT、PHYSET、MALGR敏感级别为域类。磷素输移模拟选取了12个参数，MON-GRND-CONC 敏感级别为芋类，MON-POTFW、MON-IFLW-CONC、MALGR、PHYSET 敏感级别为域类。研究结果对于开展基于 HSPF 模型的流域水文水质研究工作参数的选取具有一定的参考价值，尤其对于太湖周边地区众多低山丘陵小流域进行 HSPF 模型水文水质模拟时敏感性参数的选取具有借鉴意义。%Model sensitivity analysis measures the variability of output variables caused by perturbations in parameter values and input data. It is important for parameter selection, model calibration, and model improvement. As one of the integrated watershed model, HSPF(Hydro-logical Simulation Program-Fortran)model has a lot of parameters related to the physical characteristics of local watershed. In order to as-certain the sensitive parameters for hydrology and water quality simulation of HSPF model
Roe, Byron
2013-01-01
The effect of correlations between model parameters and nuisance parameters is discussed, in the context of fitting model parameters to data. Modifications to the usual $\\chi^2$ method are required. Fake data studies, as used at present, will not be optimum. Problems will occur for applications of the Maltoni-Schwetz \\cite{ms} theorem. Neutrino oscillations are used as examples, but the problems discussed here are general ones, which are often not addressed.
Energy Technology Data Exchange (ETDEWEB)
Luo, Xiangyu; Li, Hongyi; Leung, Lai-Yung; Tesfa, Teklu K.; Getirana, Augusto; Papa, Fabrice; Hess, Laura L.
2017-03-23
Surface water dynamics play an important role in water, energy and carbon cycles of the Amazon Basin. A macro-scale inundation scheme was integrated with a surface-water transport model and the extended model was applied in this vast basin. We addressed the challenges of improving basin-wide geomorphological parameters and river flow representation for large-scale applications. Vegetation-caused biases embedded in the HydroSHEDS DEM data were alleviated by using a vegetation height map of about 1-km resolution and a land cover dataset of about 90-m resolution. The average elevation deduction from the DEM correction was about 13.2 m for the entire basin. Basin-wide empirical formulae for channel cross-sectional geometry were adjusted based on local information for the major portion of the basin, which could significantly reduce the cross-sectional area for the channels of some subregions. The Manning roughness coefficient of the channel varied with the channel depth to reflect the general rule that the relative importance of riverbed resistance in river flow declined with the increase of river size. The entire basin was discretized into 5395 subbasins (with an average area of 1091.7 km2), which were used as computation units. The model was driven by runoff estimates of 14 years (1994 – 2007) generated by the ISBA land surface model. The simulated results were evaluated against in situ streamflow records, and remotely sensed Envisat altimetry data and GIEMS inundation data. The hydrographs were reproduced fairly well for the majority of 13 major stream gauges. For the 11 subbasins containing or close to 11 of the 13 gauges, the timing of river stage fluctuations was captured; for most of the 11 subbasins, the magnitude of river stage fluctuations was represented well. The inundation estimates were comparable to the GIEMS observations. Sensitivity analyses demonstrated that refining floodplain topography, channel morphology and Manning roughness coefficients, as
Consistent Stochastic Modelling of Meteocean Design Parameters
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard; Sterndorff, M. J.
2000-01-01
Consistent stochastic models of metocean design parameters and their directional dependencies are essential for reliability assessment of offshore structures. In this paper a stochastic model for the annual maximum values of the significant wave height, and the associated wind velocity, current...... velocity, and water level is presented. The stochastic model includes statistical uncertainty and dependency between the four stochastic variables. Further, a new stochastic model for annual maximum directional significant wave heights is presented. The model includes dependency between the maximum wave...... height from neighboring directional sectors. Numerical examples are presented where the models are calibrated using the Maximum Likelihood method to data from the central part of the North Sea. The calibration of the directional distributions is made such that the stochastic model for the omnidirectional...
Aerosol water parameterization: a single parameter framework
Metzger, S.; Steil, B.; Abdelkader, M.; Klingmüller, K.; Xu, L.; Penner, J. E.; Fountoukis, C.; Nenes, A.; Lelieveld, J.
2015-11-01
We introduce a framework to efficiently parameterize the aerosol water uptake for mixtures of semi-volatile and non-volatile compounds, based on the coefficient, νi. This solute specific coefficient was introduced in Metzger et al. (2012) to accurately parameterize the single solution hygroscopic growth, considering the Kelvin effect - accounting for the water uptake of concentrated nanometer sized particles up to dilute solutions, i.e., from the compounds relative humidity of deliquescence (RHD) up to supersaturation (Köhler-theory). Here we extend the νi-parameterization from single to mixed solutions. We evaluate our framework at various levels of complexity, by considering the full gas-liquid-solid partitioning for a comprehensive comparison with reference calculations using the E-AIM, EQUISOLV II, ISORROPIA II models as well as textbook examples. We apply our parameterization in EQSAM4clim, the EQuilibrium Simplified Aerosol Model V4 for climate simulations, implemented in a box model and in the global chemistry-climate model EMAC. Our results show: (i) that the νi-approach enables to analytically solve the entire gas-liquid-solid partitioning and the mixed solution water uptake with sufficient accuracy, (ii) that, e.g., pure ammonium nitrate and mixed ammonium nitrate - ammonium sulfate mixtures can be solved with a simple method, and (iii) that the aerosol optical depth (AOD) simulations are in close agreement with remote sensing observations for the year 2005. Long-term evaluation of the EMAC results based on EQSAM4clim and ISORROPIA II will be presented separately.
Aerosol water parameterisation: a single parameter framework
Metzger, Swen; Steil, Benedikt; Abdelkader, Mohamed; Klingmüller, Klaus; Xu, Li; Penner, Joyce E.; Fountoukis, Christos; Nenes, Athanasios; Lelieveld, Jos
2016-06-01
We introduce a framework to efficiently parameterise the aerosol water uptake for mixtures of semi-volatile and non-volatile compounds, based on the coefficient, νi. This solute-specific coefficient was introduced in Metzger et al. (2012) to accurately parameterise the single solution hygroscopic growth, considering the Kelvin effect - accounting for the water uptake of concentrated nanometer-sized particles up to dilute solutions, i.e. from the compounds relative humidity of deliquescence (RHD) up to supersaturation (Köhler theory). Here we extend the νi parameterisation from single to mixed solutions. We evaluate our framework at various levels of complexity, by considering the full gas-liquid-solid partitioning for a comprehensive comparison with reference calculations using the E-AIM, EQUISOLV II and ISORROPIA II models as well as textbook examples. We apply our parameterisation in the EQuilibrium Simplified Aerosol Model V4 (EQSAM4clim) for climate simulations, implemented in a box model and in the global chemistry-climate model EMAC. Our results show (i) that the νi approach enables one to analytically solve the entire gas-liquid-solid partitioning and the mixed solution water uptake with sufficient accuracy, (ii) that ammonium sulfate mixtures can be solved with a simple method, e.g. pure ammonium nitrate and mixed ammonium nitrate and (iii) that the aerosol optical depth (AOD) simulations are in close agreement with remote sensing observations for the year 2005. Long-term evaluation of the EMAC results based on EQSAM4clim and ISORROPIA II will be presented separately.
assessment of water quality parameters of kpeshi lagoon of ghana
African Journals Online (AJOL)
User
ASSESSMENT OF WATER QUALITY PARAMETERS OF. KPESHI LAGOON OF GHANA ... Lagoons are shallow coastal bodies of water separated from the ocean by ... physico-chemical parameters. The main aim is .... factor in eutrophication.
PARAMETER ESTIMATION OF ENGINEERING TURBULENCE MODEL
Institute of Scientific and Technical Information of China (English)
钱炜祺; 蔡金狮
2001-01-01
A parameter estimation algorithm is introduced and used to determine the parameters in the standard k-ε two equation turbulence model (SKE). It can be found from the estimation results that although the parameter estimation method is an effective method to determine model parameters, it is difficult to obtain a set of parameters for SKE to suit all kinds of separated flow and a modification of the turbulence model structure should be considered. So, a new nonlinear k-ε two-equation model (NNKE) is put forward in this paper and the corresponding parameter estimation technique is applied to determine the model parameters. By implementing the NNKE to solve some engineering turbulent flows, it is shown that NNKE is more accurate and versatile than SKE. Thus, the success of NNKE implies that the parameter estimation technique may have a bright prospect in engineering turbulence model research.
Institute of Scientific and Technical Information of China (English)
Juan WU; Jian ZHANG; Wenlin JIA; Huijun XIE; Bo ZHANG
2009-01-01
The effects of chemical oxygen demand (COD) concentration in the influent on nitrous oxide (N2O) emissions, together with the relationships between N2O and water quality parameters in free water surface constructed wetlands, were investigated with laboratoryscale systems. N20 emission and purification performance of wastewater were very strongly dependent on COD concentration in the influent, and the total N2O emission in the system with middle COD influent concentration was the least. The relationships between N2O and the chemical and physical water quality variables were studied by using principal component scores in multiple linear regression analysis to predict N2O flux. The multiple linear regression model against principal components indicated that different water parameters affected N2O flux with different COD concentrations in the influent, but nitrate nitrogen affected N2O flux in all systems.
Identification of hydrological model parameter variation using ensemble Kalman filter
Deng, Chao; Liu, Pan; Guo, Shenglian; Li, Zejun; Wang, Dingbao
2016-12-01
Hydrological model parameters play an important role in the ability of model prediction. In a stationary context, parameters of hydrological models are treated as constants; however, model parameters may vary with time under climate change and anthropogenic activities. The technique of ensemble Kalman filter (EnKF) is proposed to identify the temporal variation of parameters for a two-parameter monthly water balance model (TWBM) by assimilating the runoff observations. Through a synthetic experiment, the proposed method is evaluated with time-invariant (i.e., constant) parameters and different types of parameter variations, including trend, abrupt change and periodicity. Various levels of observation uncertainty are designed to examine the performance of the EnKF. The results show that the EnKF can successfully capture the temporal variations of the model parameters. The application to the Wudinghe basin shows that the water storage capacity (SC) of the TWBM model has an apparent increasing trend during the period from 1958 to 2000. The identified temporal variation of SC is explained by land use and land cover changes due to soil and water conservation measures. In contrast, the application to the Tongtianhe basin shows that the estimated SC has no significant variation during the simulation period of 1982-2013, corresponding to the relatively stationary catchment properties. The evapotranspiration parameter (C) has temporal variations while no obvious change patterns exist. The proposed method provides an effective tool for quantifying the temporal variations of the model parameters, thereby improving the accuracy and reliability of model simulations and forecasts.
Robust estimation of hydrological model parameters
Directory of Open Access Journals (Sweden)
A. Bárdossy
2008-11-01
Full Text Available The estimation of hydrological model parameters is a challenging task. With increasing capacity of computational power several complex optimization algorithms have emerged, but none of the algorithms gives a unique and very best parameter vector. The parameters of fitted hydrological models depend upon the input data. The quality of input data cannot be assured as there may be measurement errors for both input and state variables. In this study a methodology has been developed to find a set of robust parameter vectors for a hydrological model. To see the effect of observational error on parameters, stochastically generated synthetic measurement errors were applied to observed discharge and temperature data. With this modified data, the model was calibrated and the effect of measurement errors on parameters was analysed. It was found that the measurement errors have a significant effect on the best performing parameter vector. The erroneous data led to very different optimal parameter vectors. To overcome this problem and to find a set of robust parameter vectors, a geometrical approach based on Tukey's half space depth was used. The depth of the set of N randomly generated parameters was calculated with respect to the set with the best model performance (Nash-Sutclife efficiency was used for this study for each parameter vector. Based on the depth of parameter vectors, one can find a set of robust parameter vectors. The results show that the parameters chosen according to the above criteria have low sensitivity and perform well when transfered to a different time period. The method is demonstrated on the upper Neckar catchment in Germany. The conceptual HBV model was used for this study.
PARAMETER ESTIMATION IN BREAD BAKING MODEL
Hadiyanto Hadiyanto; AJB van Boxtel
2012-01-01
Bread product quality is highly dependent to the baking process. A model for the development of product quality, which was obtained by using quantitative and qualitative relationships, was calibrated by experiments at a fixed baking temperature of 200°C alone and in combination with 100 W microwave powers. The model parameters were estimated in a stepwise procedure i.e. first, heat and mass transfer related parameters, then the parameters related to product transformations and finally pro...
Parameter counting in models with global symmetries
Energy Technology Data Exchange (ETDEWEB)
Berger, Joshua [Institute for High Energy Phenomenology, Newman Laboratory of Elementary Particle Physics, Cornell University, Ithaca, NY 14853 (United States)], E-mail: jb454@cornell.edu; Grossman, Yuval [Institute for High Energy Phenomenology, Newman Laboratory of Elementary Particle Physics, Cornell University, Ithaca, NY 14853 (United States)], E-mail: yuvalg@lepp.cornell.edu
2009-05-18
We present rules for determining the number of physical parameters in models with exact flavor symmetries. In such models the total number of parameters (physical and unphysical) needed to described a matrix is less than in a model without the symmetries. Several toy examples are studied in order to demonstrate the rules. The use of global symmetries in studying the minimally supersymmetric standard model (MSSM) is examined.
On parameter estimation in deformable models
DEFF Research Database (Denmark)
Fisker, Rune; Carstensen, Jens Michael
1998-01-01
Deformable templates have been intensively studied in image analysis through the last decade, but despite its significance the estimation of model parameters has received little attention. We present a method for supervised and unsupervised model parameter estimation using a general Bayesian...... method is based on a modified version of the EM algorithm. Experimental results for a deformable template used for textile inspection are presented...
Cosmological models with constant deceleration parameter
Energy Technology Data Exchange (ETDEWEB)
Berman, M.S.; de Mello Gomide, F.
1988-02-01
Berman presented elsewhere a law of variation for Hubble's parameter that yields constant deceleration parameter models of the universe. By analyzing Einstein, Pryce-Hoyle and Brans-Dicke cosmologies, we derive here the necessary relations in each model, considering a perfect fluid.
Directory of Open Access Journals (Sweden)
F Farias
2016-09-01
Full Text Available In the oil exploitation, produced fluids are composed of oil, gas, water and sand (depending on the reservoir location. The presence of sand in flow oil leads to several industrial problems for example: erosion and accumulation in valves and pipeline. Thus, it is necessary to stop production for manual cleaning of equipments and pipes. These facts have attracted attention of academic and industrial areas, enabling the appearing of new technologies or improvement of the water/oil/sand separation process. One equipment that has been used to promote phase separation is the hydrocyclone due to high performance of separation and required low cost to installation and maintenance. In this sense, the purpose of this work is to study numerically the effect of geometric parameters (vortex finder diameter of the hydrocyclone and sand concentration on the inlet fluid separation process. A numerical solution of the governing equations was obtained by the ANSYS CFX-11 commercial code. Results of the streamlines, pressure drop and separation efficiency on the hydrocyclone are presented and analyzed. It was observed that the particles concentration and geometry affect the separation efficiency of the hydrocyclone.
Fuzzy Logic Water Quality Index and Importance of Water Quality Parameters
Directory of Open Access Journals (Sweden)
Raman Bai. V
2009-01-01
Full Text Available Determination of status of water quality of a river or any other water sources is highly indeterminate. It is necessary to have a competent model to predict the status of water quality and to advice for type of water treatment for meeting different demands. One such model (UNIQ2007 is developed as an application software in water quality engineering. The unit operates in a fuzzy logic mode including a fuzzification engine receiving a plurality of input variables on its input and being adapted to compute membership function parameters. A processor engine connected downstream of the fuzzification unit will produce fuzzy set, based on fuzzy variable viz. DO, BOD, COD, AN, SS and pH. It has a defuzzification unit operative to translate the inference results into a discrete crisp value of WQI. The UNIQ2007 contains a first memory device connected to the fuzzification unit and containing the set of membership functions, a secondary memory device connected to the defuzzification unit and containing the set of crisp value which appear in the THEN part of the fuzzy rules and an additional memory device connected to the defuzzification unit. More advantageously, UINQ2007 is constructed with control elements having dynamic fuzzy logic properties wherein target non-linearity can be input to result in a perfect evaluation of water quality. The development of the fuzzy model with one river system is explained in this paper. Further the model has been evaluated with the data from few rivers in Malaysia, India and Thailand. This water quality assessor probe can provide better quality index or identify the status of river with 90% perfection. Presently, WQI in most of the countries is referring to physic-chemical parameters only due to great efforts needed to quantify the biological parameters. This study ensures a better method to include pathogens into WQI due to superior capabilities of fuzzy logic in dealing with non-linear, complex and uncertain systems.
[Calculation of parameters in forest evapotranspiration model].
Wang, Anzhi; Pei, Tiefan
2003-12-01
Forest evapotranspiration is an important component not only in water balance, but also in energy balance. It is a great demand for the development of forest hydrology and forest meteorology to simulate the forest evapotranspiration accurately, which is also a theoretical basis for the management and utilization of water resources and forest ecosystem. Taking the broadleaved Korean pine forest on Changbai Mountain as an example, this paper constructed a mechanism model for estimating forest evapotranspiration, based on the aerodynamic principle and energy balance equation. Using the data measured by the Routine Meteorological Measurement System and Open-Path Eddy Covariance Measurement System mounted on the tower in the broadleaved Korean pine forest, the parameters displacement height d, stability functions for momentum phi m, and stability functions for heat phi h were ascertained. The displacement height of the study site was equal to 17.8 m, near to the mean canopy height, and the functions of phi m and phi h changing with gradient Richarson number R i were constructed.
Energy Technology Data Exchange (ETDEWEB)
J.B. Case
1999-12-21
The distribution of seepage in the proposed repository will be highly variable due in part to variations in the spatial distribution of percolations. The performance of the drip shield and the backfill system may divert the water flux around the waste packages to the invert. Diversion will occur along the drift surface, within the backfill, at the drip shield, and at the Waste Package (WP) surface, even after the drip shield and WP have been breached by corrosion. The purpose and objective of this Analysis and Modeling Report (AMR) are to develop a conceptual model and constitutive properties for bounding the volume and rate of seepage water that flows around the drip shield (CRWMS M&O 1999c). This analysis model is to be compatible with the selected repository conceptual design (Wilkins and Heath, 1999) and will be used to evaluate the performance of the Engineered Barrier System (EBS), and to provide input to the EBS Water Distribution and Removal Model. This model supports the Engineered Barrier System (EBS) postclosure performance assessment for the Site Recommendation (SR). This document characterizes the hydrological constitutive properties of the backfill and invert materials (Section 6.2) and a third material that represents a mixture of the two. These include the Overton Sand which is selected as a backfill (Section 5.2), crushed tuff which is selected as the invert (Section 5.1), and a combined material (Sections 5.9 and 5.10) which has retention and hydraulic conductivity properties intermediate to the selected materials for the backfill and the invert. The properties include the grain size distribution, the dry bulk density and porosity, the moisture retention, the intrinsic permeability, the relative permeability, and the material thermal properties. The van Genuchten relationships with curve fit parameters are used to define the basic retention relationship of moisture potential to volumetric moisture content, and the basic relationship of unsaturated
Trait Characteristics of Diffusion Model Parameters
Directory of Open Access Journals (Sweden)
Anna-Lena Schubert
2016-07-01
Full Text Available Cognitive modeling of response time distributions has seen a huge rise in popularity in individual differences research. In particular, several studies have shown that individual differences in the drift rate parameter of the diffusion model, which reflects the speed of information uptake, are substantially related to individual differences in intelligence. However, if diffusion model parameters are to reflect trait-like properties of cognitive processes, they have to qualify as trait-like variables themselves, i.e., they have to be stable across time and consistent over different situations. To assess their trait characteristics, we conducted a latent state-trait analysis of diffusion model parameters estimated from three response time tasks that 114 participants completed at two laboratory sessions eight months apart. Drift rate, boundary separation, and non-decision time parameters showed a great temporal stability over a period of eight months. However, the coefficients of consistency and reliability were only low to moderate and highest for drift rate parameters. These results show that the consistent variance of diffusion model parameters across tasks can be regarded as temporally stable ability parameters. Moreover, they illustrate the need for using broader batteries of response time tasks in future studies on the relationship between diffusion model parameters and intelligence.
Parameter identification in the logistic STAR model
DEFF Research Database (Denmark)
Ekner, Line Elvstrøm; Nejstgaard, Emil
We propose a new and simple parametrization of the so-called speed of transition parameter of the logistic smooth transition autoregressive (LSTAR) model. The new parametrization highlights that a consequence of the well-known identification problem of the speed of transition parameter is that th......We propose a new and simple parametrization of the so-called speed of transition parameter of the logistic smooth transition autoregressive (LSTAR) model. The new parametrization highlights that a consequence of the well-known identification problem of the speed of transition parameter...
WATER QUALITY MODELING OF SUZHOU CREEK
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
Water-quality models are important tools for improving river environment. In this paper, the project "Water Quality Modeling of the Suzhou Creek" was briefly described, including the choice and the principle of the model, the model study and methods, the calibration and verification of the stream model. A set of parameters about water environmental characteristic of the Suzhou Creek were put forward in the period of the third water dispatch experiment in 1999. It is necessary to point out that these parameters will change with the rehabilitation and construction of the Suzhou Creek.
Parameter Estimation of Partial Differential Equation Models
Xun, Xiaolei
2013-09-01
Partial differential equation (PDE) models are commonly used to model complex dynamic systems in applied sciences such as biology and finance. The forms of these PDE models are usually proposed by experts based on their prior knowledge and understanding of the dynamic system. Parameters in PDE models often have interesting scientific interpretations, but their values are often unknown and need to be estimated from the measurements of the dynamic system in the presence of measurement errors. Most PDEs used in practice have no analytic solutions, and can only be solved with numerical methods. Currently, methods for estimating PDE parameters require repeatedly solving PDEs numerically under thousands of candidate parameter values, and thus the computational load is high. In this article, we propose two methods to estimate parameters in PDE models: a parameter cascading method and a Bayesian approach. In both methods, the underlying dynamic process modeled with the PDE model is represented via basis function expansion. For the parameter cascading method, we develop two nested levels of optimization to estimate the PDE parameters. For the Bayesian method, we develop a joint model for data and the PDE and develop a novel hierarchical model allowing us to employ Markov chain Monte Carlo (MCMC) techniques to make posterior inference. Simulation studies show that the Bayesian method and parameter cascading method are comparable, and both outperform other available methods in terms of estimation accuracy. The two methods are demonstrated by estimating parameters in a PDE model from long-range infrared light detection and ranging data. Supplementary materials for this article are available online. © 2013 American Statistical Association.
Application of lumped-parameter models
Energy Technology Data Exchange (ETDEWEB)
Ibsen, Lars Bo; Liingaard, M.
2006-12-15
This technical report concerns the lumped-parameter models for a suction caisson with a ratio between skirt length and foundation diameter equal to 1/2, embedded into an viscoelastic soil. The models are presented for three different values of the shear modulus of the subsoil. Subsequently, the assembly of the dynamic stiffness matrix for the foundation is considered, and the solution for obtaining the steady state response, when using lumped-parameter models is given. (au)
Modeling water waves beyond perturbations
Clamond, Didier
2015-01-01
In this chapter, we illustrate the advantage of variational principles for modeling water waves from an elementary practical viewpoint. The method is based on a `relaxed' variational principle, i.e., on a Lagrangian involving as many variables as possible, and imposing some suitable subordinate constraints. This approach allows the construction of approximations without necessarily relying on a small parameter. This is illustrated via simple examples, namely the Serre equations in shallow water, a generalization of the Klein-Gordon equation in deep water and how to unify these equations in arbitrary depth. The chapter ends with a discussion and caution on how this approach should be used in practice.
PARAMETER ESTIMATION IN BREAD BAKING MODEL
Directory of Open Access Journals (Sweden)
Hadiyanto Hadiyanto
2012-05-01
Full Text Available Bread product quality is highly dependent to the baking process. A model for the development of product quality, which was obtained by using quantitative and qualitative relationships, was calibrated by experiments at a fixed baking temperature of 200°C alone and in combination with 100 W microwave powers. The model parameters were estimated in a stepwise procedure i.e. first, heat and mass transfer related parameters, then the parameters related to product transformations and finally product quality parameters. There was a fair agreement between the calibrated model results and the experimental data. The results showed that the applied simple qualitative relationships for quality performed above expectation. Furthermore, it was confirmed that the microwave input is most meaningful for the internal product properties and not for the surface properties as crispness and color. The model with adjusted parameters was applied in a quality driven food process design procedure to derive a dynamic operation pattern, which was subsequently tested experimentally to calibrate the model. Despite the limited calibration with fixed operation settings, the model predicted well on the behavior under dynamic convective operation and on combined convective and microwave operation. It was expected that the suitability between model and baking system could be improved further by performing calibration experiments at higher temperature and various microwave power levels. Abstrak PERKIRAAN PARAMETER DALAM MODEL UNTUK PROSES BAKING ROTI. Kualitas produk roti sangat tergantung pada proses baking yang digunakan. Suatu model yang telah dikembangkan dengan metode kualitatif dan kuantitaif telah dikalibrasi dengan percobaan pada temperatur 200oC dan dengan kombinasi dengan mikrowave pada 100 Watt. Parameter-parameter model diestimasi dengan prosedur bertahap yaitu pertama, parameter pada model perpindahan masa dan panas, parameter pada model transformasi, dan
Directional spread parameter at intermediate water depth
Digital Repository Service at National Institute of Oceanography (India)
SanilKumar, V.; Deo, M.C.; Anand, N.M.; AshokKumar, K.
formulations (Niedzwecki and Whatley, 1991). The cosine power ‘2s’ model, originally proposed by Longuet-Higgins et al. (1963), is very popular due to its proven generality. 1.1. The cosine power ‘2s’ model The cosine power ‘2s’ model is as follows; D(f,u) 5 G...(s)cos 2s [(u2u m )/2] (1) where G(s) 5 2 2s 2p G 2 (s 1 1) G(2s 1 1) 5 1 2 p G(s 1 1) G(s 1 0.5) (2) and D(f,u) is directional spreading function, f is wave frequency, u is wave direction, u m is mean wave direction, G is gamma function and s is spreading...
Statefinder parameters in two dark energy models
Panotopoulos, Grigoris
2007-01-01
The statefinder parameters ($r,s$) in two dark energy models are studied. In the first, we discuss in four-dimensional General Relativity a two fluid model, in which dark energy and dark matter are allowed to interact with each other. In the second model, we consider the DGP brane model generalized by taking a possible energy exchange between the brane and the bulk into account. We determine the values of the statefinder parameters that correspond to the unique attractor of the system at hand. Furthermore, we produce plots in which we show $s,r$ as functions of red-shift, and the ($s-r$) plane for each model.
Parameter Symmetry of the Interacting Boson Model
Shirokov, A M; Smirnov, Yu F; Shirokov, Andrey M.; Smirnov, Yu. F.
1998-01-01
We discuss the symmetry of the parameter space of the interacting boson model (IBM). It is shown that for any set of the IBM Hamiltonian parameters (with the only exception of the U(5) dynamical symmetry limit) one can always find another set that generates the equivalent spectrum. We discuss the origin of the symmetry and its relevance for physical applications.
Wind Farm Decentralized Dynamic Modeling With Parameters
DEFF Research Database (Denmark)
Soltani, Mohsen; Shakeri, Sayyed Mojtaba; Grunnet, Jacob Deleuran;
2010-01-01
Development of dynamic wind flow models for wind farms is part of the research in European research FP7 project AEOLUS. The objective of this report is to provide decentralized dynamic wind flow models with parameters. The report presents a structure for decentralized flow models with inputs from...
Setting Parameters for Biological Models With ANIMO
Schivo, Stefano; Scholma, Jetse; Karperien, Hermanus Bernardus Johannes; Post, Janine Nicole; van de Pol, Jan Cornelis; Langerak, Romanus; André, Étienne; Frehse, Goran
2014-01-01
ANIMO (Analysis of Networks with Interactive MOdeling) is a software for modeling biological networks, such as e.g. signaling, metabolic or gene networks. An ANIMO model is essentially the sum of a network topology and a number of interaction parameters. The topology describes the interactions
Delineating Parameter Unidentifiabilities in Complex Models
Raman, Dhruva V; Papachristodoulou, Antonis
2016-01-01
Scientists use mathematical modelling to understand and predict the properties of complex physical systems. In highly parameterised models there often exist relationships between parameters over which model predictions are identical, or nearly so. These are known as structural or practical unidentifiabilities, respectively. They are hard to diagnose and make reliable parameter estimation from data impossible. They furthermore imply the existence of an underlying model simplification. We describe a scalable method for detecting unidentifiabilities, and the functional relations defining them, for generic models. This allows for model simplification, and appreciation of which parameters (or functions thereof) cannot be estimated from data. Our algorithm can identify features such as redundant mechanisms and fast timescale subsystems, as well as the regimes in which such approximations are valid. We base our algorithm on a novel quantification of regional parametric sensitivity: multiscale sloppiness. Traditional...
Improvement on Mixograph test through water addition and parameter conversions
Institute of Scientific and Technical Information of China (English)
SUN Jia-zhu[1; YANG Wen-long[1; LIU Dong-cheng[1; ZHAO Jun-tao[2; LUO Guang-bin[1; LI Xin[1; LIU Yan-jun[3; GUO Jin-kao[3; ZHANG Ai-min[1
2015-01-01
To improve Mixograph testing effect, Farinograph measurements were adopted as a quality standard and changes in water absorption and parameter conversion in Mixograph test were explored. Comparative study showed that increasing water absorption to about 73% and converting original parameters to compound parameters in Mixograph tests significantly increased their predictive power for flour quality. These efforts also enabled the adoption of fixed water addition level in Mixograph test and simplified the test procedure significantly. With the success in parameter conversions, Mixograph test results were successfully described by Farinograph parameters, which allow breeders to compare and exchange test results easily. All these changes optimized the official method of Mixograph test with simplified procedure and enhanced reliability and made the Mixograph being the superior tool for quality assessment in wheat-breeding programs.
Improvement on Mixograph test through water addition and parameter conversions
Institute of Scientific and Technical Information of China (English)
SUN Jia-zhu; YANG Wen-long; LIU Dong-cheng; ZHAO Jun-tao; LUO Guang-bin; LI Xin; LIU Yan-jun; GUO Jin-kao; ZHANG Ai-min
2015-01-01
To improve Mixograph testing effect, Farinograph measurements were adopted as a quality standard and changes in water absorption and parameter conversion in Mixograph test were explored. Comparative study showed that increasing water absorption to about 73% and converting original parameters to compound parameters in Mixograph tests signiifcantly increased their predictive power for lfour quality. These efforts also enabled the adoption of ifxed water addition level in Mixograph test and simpliifed the test procedure signiifcantly. With the success in parameter conversions, Mixograph test results were successful y described by Farinograph parameters, which al ow breeders to compare and exchange test results easily. Al these changes optimized the ofifcial method of Mixograph test with simpliifed procedure and enhanced reliability and made the Mixograph being the superior tool for quality assessment in wheat-breeding programs.
Parameter Estimation, Model Reduction and Quantum Filtering
Chase, Bradley A
2009-01-01
This dissertation explores the topics of parameter estimation and model reduction in the context of quantum filtering. Chapters 2 and 3 provide a review of classical and quantum probability theory, stochastic calculus and filtering. Chapter 4 studies the problem of quantum parameter estimation and introduces the quantum particle filter as a practical computational method for parameter estimation via continuous measurement. Chapter 5 applies these techniques in magnetometry and studies the estimator's uncertainty scalings in a double-pass atomic magnetometer. Chapter 6 presents an efficient feedback controller for continuous-time quantum error correction. Chapter 7 presents an exact model of symmetric processes of collective qubit systems.
Hysteresis and uncertainty in soil water-retention curve parameters
Likos, William J.; Lu, Ning; Godt, Jonathan W.
2014-01-01
Accurate estimates of soil hydraulic parameters representing wetting and drying paths are required for predicting hydraulic and mechanical responses in a large number of applications. A comprehensive suite of laboratory experiments was conducted to measure hysteretic soil-water characteristic curves (SWCCs) representing a wide range of soil types. Results were used to quantitatively assess differences and uncertainty in three simplifications frequently adopted to estimate wetting-path SWCC parameters from more easily measured drying curves. They are the following: (1) αw=2αd, (2) nw=nd, and (3) θws=θds, where α, n, and θs are fitting parameters entering van Genuchten’s commonly adopted SWCC model, and the superscripts w and d indicate wetting and drying paths, respectively. The average ratio αw/αd for the data set was 2.24±1.25. Nominally cohesive soils had a lower αw/αd ratio (1.73±0.94) than nominally cohesionless soils (3.14±1.27). The average nw/nd ratio was 1.01±0.11 with no significant dependency on soil type, thus confirming the nw=nd simplification for a wider range of soil types than previously available. Water content at zero suction during wetting (θws) was consistently less than during drying (θds) owing to air entrapment. The θws/θds ratio averaged 0.85±0.10 and was comparable for nominally cohesive (0.87±0.11) and cohesionless (0.81±0.08) soils. Regression statistics are provided to quantitatively account for uncertainty in estimating hysteretic retention curves. Practical consequences are demonstrated for two case studies.
Broadband matched-field inversion for shallow water environment parameters
Institute of Scientific and Technical Information of China (English)
YANG Kunde; MA Yuanliang
2003-01-01
In this paper, broadband multi-frequencies matched-field inversion method is used to determine the environmental parameters in shallow water. According to different conditions, several broadband objective functions are presented. Using ASIAEX2001 experiment data and genetic algorithms, environmental parameters are obtained, especially in sediment.
Parameter Estimation for Thurstone Choice Models
Energy Technology Data Exchange (ETDEWEB)
Vojnovic, Milan [London School of Economics (United Kingdom); Yun, Seyoung [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-04-24
We consider the estimation accuracy of individual strength parameters of a Thurstone choice model when each input observation consists of a choice of one item from a set of two or more items (so called top-1 lists). This model accommodates the well-known choice models such as the Luce choice model for comparison sets of two or more items and the Bradley-Terry model for pair comparisons. We provide a tight characterization of the mean squared error of the maximum likelihood parameter estimator. We also provide similar characterizations for parameter estimators defined by a rank-breaking method, which amounts to deducing one or more pair comparisons from a comparison of two or more items, assuming independence of these pair comparisons, and maximizing a likelihood function derived under these assumptions. We also consider a related binary classification problem where each individual parameter takes value from a set of two possible values and the goal is to correctly classify all items within a prescribed classification error. The results of this paper shed light on how the parameter estimation accuracy depends on given Thurstone choice model and the structure of comparison sets. In particular, we found that for unbiased input comparison sets of a given cardinality, when in expectation each comparison set of given cardinality occurs the same number of times, for a broad class of Thurstone choice models, the mean squared error decreases with the cardinality of comparison sets, but only marginally according to a diminishing returns relation. On the other hand, we found that there exist Thurstone choice models for which the mean squared error of the maximum likelihood parameter estimator can decrease much faster with the cardinality of comparison sets. We report empirical evaluation of some claims and key parameters revealed by theory using both synthetic and real-world input data from some popular sport competitions and online labor platforms.
GIS-Based Hydrogeological-Parameter Modeling
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
A regression model is proposed to relate the variation of water well depth with topographic properties (area and slope), the variation of hydraulic conductivity and vertical decay factor. The implementation of this model in GIS environment (ARC/TNFO) based on known water data and DEM is used to estimate the variation of hydraulic conductivity and decay factor of different lithoiogy units in watershed context.
Delineating parameter unidentifiabilities in complex models
Raman, Dhruva V.; Anderson, James; Papachristodoulou, Antonis
2017-03-01
Scientists use mathematical modeling as a tool for understanding and predicting the properties of complex physical systems. In highly parametrized models there often exist relationships between parameters over which model predictions are identical, or nearly identical. These are known as structural or practical unidentifiabilities, respectively. They are hard to diagnose and make reliable parameter estimation from data impossible. They furthermore imply the existence of an underlying model simplification. We describe a scalable method for detecting unidentifiabilities, as well as the functional relations defining them, for generic models. This allows for model simplification, and appreciation of which parameters (or functions thereof) cannot be estimated from data. Our algorithm can identify features such as redundant mechanisms and fast time-scale subsystems, as well as the regimes in parameter space over which such approximations are valid. We base our algorithm on a quantification of regional parametric sensitivity that we call `multiscale sloppiness'. Traditionally, the link between parametric sensitivity and the conditioning of the parameter estimation problem is made locally, through the Fisher information matrix. This is valid in the regime of infinitesimal measurement uncertainty. We demonstrate the duality between multiscale sloppiness and the geometry of confidence regions surrounding parameter estimates made where measurement uncertainty is non-negligible. Further theoretical relationships are provided linking multiscale sloppiness to the likelihood-ratio test. From this, we show that a local sensitivity analysis (as typically done) is insufficient for determining the reliability of parameter estimation, even with simple (non)linear systems. Our algorithm can provide a tractable alternative. We finally apply our methods to a large-scale, benchmark systems biology model of necrosis factor (NF)-κ B , uncovering unidentifiabilities.
Systematic parameter inference in stochastic mesoscopic modeling
Lei, Huan; Yang, Xiu; Li, Zhen; Karniadakis, George Em
2017-02-01
We propose a method to efficiently determine the optimal coarse-grained force field in mesoscopic stochastic simulations of Newtonian fluid and polymer melt systems modeled by dissipative particle dynamics (DPD) and energy conserving dissipative particle dynamics (eDPD). The response surfaces of various target properties (viscosity, diffusivity, pressure, etc.) with respect to model parameters are constructed based on the generalized polynomial chaos (gPC) expansion using simulation results on sampling points (e.g., individual parameter sets). To alleviate the computational cost to evaluate the target properties, we employ the compressive sensing method to compute the coefficients of the dominant gPC terms given the prior knowledge that the coefficients are "sparse". The proposed method shows comparable accuracy with the standard probabilistic collocation method (PCM) while it imposes a much weaker restriction on the number of the simulation samples especially for systems with high dimensional parametric space. Fully access to the response surfaces within the confidence range enables us to infer the optimal force parameters given the desirable values of target properties at the macroscopic scale. Moreover, it enables us to investigate the intrinsic relationship between the model parameters, identify possible degeneracies in the parameter space, and optimize the model by eliminating model redundancies. The proposed method provides an efficient alternative approach for constructing mesoscopic models by inferring model parameters to recover target properties of the physics systems (e.g., from experimental measurements), where those force field parameters and formulation cannot be derived from the microscopic level in a straight forward way.
Application of lumped-parameter models
DEFF Research Database (Denmark)
Ibsen, Lars Bo; Liingaard, Morten
This technical report concerns the lumped-parameter models for a suction caisson with a ratio between skirt length and foundation diameter equal to 1/2, embedded into an viscoelastic soil. The models are presented for three different values of the shear modulus of the subsoil (section 1.1). Subse...
Models and parameters for environmental radiological assessments
Energy Technology Data Exchange (ETDEWEB)
Miller, C W [ed.
1984-01-01
This book presents a unified compilation of models and parameters appropriate for assessing the impact of radioactive discharges to the environment. Models examined include those developed for the prediction of atmospheric and hydrologic transport and deposition, for terrestrial and aquatic food-chain bioaccumulation, and for internal and external dosimetry. Chapters have been entered separately into the data base. (ACR)
Shaharudin Nuraida; Suradi Nurfarhana; Mohd Kamil Nor Amani Filzah
2017-01-01
An adequate supply of safe drinking water is one of major ways to obtain healthy life. Water filter system is one way to improve the water quality. However, to maintain the performance of the system, it need to undergo the maintenance service. This study evaluate the requirement of maintenance service in water filter system. Water quality was measured before and after maintenance service. Parameters measured were pH, turbidity, residual chlorine, nitrate and heavy metals and these parameters ...
Lumped-parameter Model of a Bucket Foundation
DEFF Research Database (Denmark)
Andersen, Lars; Ibsen, Lars Bo; Liingaard, Morten
2009-01-01
As an alternative to gravity footings or pile foundations, offshore wind turbines at shallow water can be placed on a bucket foundation. The present analysis concerns the development of consistent lumped-parameter models for this type of foundation. The aim is to formulate a computationally effic...
Modelling of intermittent microwave convective drying: parameter sensitivity
Directory of Open Access Journals (Sweden)
Zhang Zhijun
2017-06-01
Full Text Available The reliability of the predictions of a mathematical model is a prerequisite to its utilization. A multiphase porous media model of intermittent microwave convective drying is developed based on the literature. The model considers the liquid water, gas and solid matrix inside of food. The model is simulated by COMSOL software. Its sensitivity parameter is analysed by changing the parameter values by ±20%, with the exception of several parameters. The sensitivity analysis of the process of the microwave power level shows that each parameter: ambient temperature, effective gas diffusivity, and evaporation rate constant, has significant effects on the process. However, the surface mass, heat transfer coefficient, relative and intrinsic permeability of the gas, and capillary diffusivity of water do not have a considerable effect. The evaporation rate constant has minimal parameter sensitivity with a ±20% value change, until it is changed 10-fold. In all results, the temperature and vapour pressure curves show the same trends as the moisture content curve. However, the water saturation at the medium surface and in the centre show different results. Vapour transfer is the major mass transfer phenomenon that affects the drying process.
Modelling of intermittent microwave convective drying: parameter sensitivity
Zhang, Zhijun; Qin, Wenchao; Shi, Bin; Gao, Jingxin; Zhang, Shiwei
2017-06-01
The reliability of the predictions of a mathematical model is a prerequisite to its utilization. A multiphase porous media model of intermittent microwave convective drying is developed based on the literature. The model considers the liquid water, gas and solid matrix inside of food. The model is simulated by COMSOL software. Its sensitivity parameter is analysed by changing the parameter values by ±20%, with the exception of several parameters. The sensitivity analysis of the process of the microwave power level shows that each parameter: ambient temperature, effective gas diffusivity, and evaporation rate constant, has significant effects on the process. However, the surface mass, heat transfer coefficient, relative and intrinsic permeability of the gas, and capillary diffusivity of water do not have a considerable effect. The evaporation rate constant has minimal parameter sensitivity with a ±20% value change, until it is changed 10-fold. In all results, the temperature and vapour pressure curves show the same trends as the moisture content curve. However, the water saturation at the medium surface and in the centre show different results. Vapour transfer is the major mass transfer phenomenon that affects the drying process.
A New Approach for Parameter Optimization in Land Surface Model
Institute of Scientific and Technical Information of China (English)
LI Hongqi; GUO Weidong; SUN Guodong; ZHANG Yaocun; FU Congbin
2011-01-01
In this study,a new parameter optimization method was used to investigate the expansion of conditional nonlinear optimal perturbation (CNOP) in a land surface model (LSM) using long-term enhanced field observations at Tongyn station in Jilin Province,China,combined with a sophisticated LSM (common land model,CoLM).Tongyu station is a reference site of the international Coordinated Energy and Water Cycle Observations Project (CEOP) that has studied semiarid regions that have undergone desertification,salination,and degradation since late 1960s.In this study,three key land-surface parameters,namely,soil color,proportion of sand or clay in soil,and leaf-area index were chosen as parameters to be optimized.Our study comprised three experiments:First,a single-parameter optimization was performed,while the second and third experiments performed triple- and six-parameter optinizations,respectively.Notable improvements in simulating sensible heat flux (SH),latent heat flux (LH),soil temperature (TS),and moisture (MS) at shallow layers were achieved using the optimized parameters.The multiple-parameter optimization experiments performed better than the single-parameter experminent.All results demonstrate that the CNOP method can be used to optimize expanded parameters in an LSM.Moreover,clear mathematical meaning,simple design structure,and rapid computability give this method great potential for further application to parameter optimization in LSMs.
Estimation of Model Parameters for Steerable Needles
Park, Wooram; Reed, Kyle B.; Okamura, Allison M.; Chirikjian, Gregory S.
2010-01-01
Flexible needles with bevel tips are being developed as useful tools for minimally invasive surgery and percutaneous therapy. When such a needle is inserted into soft tissue, it bends due to the asymmetric geometry of the bevel tip. This insertion with bending is not completely repeatable. We characterize the deviations in needle tip pose (position and orientation) by performing repeated needle insertions into artificial tissue. The base of the needle is pushed at a constant speed without rotating, and the covariance of the distribution of the needle tip pose is computed from experimental data. We develop the closed-form equations to describe how the covariance varies with different model parameters. We estimate the model parameters by matching the closed-form covariance and the experimentally obtained covariance. In this work, we use a needle model modified from a previously developed model with two noise parameters. The modified needle model uses three noise parameters to better capture the stochastic behavior of the needle insertion. The modified needle model provides an improvement of the covariance error from 26.1% to 6.55%. PMID:21643451
Estimation of Model Parameters for Steerable Needles.
Park, Wooram; Reed, Kyle B; Okamura, Allison M; Chirikjian, Gregory S
2010-01-01
Flexible needles with bevel tips are being developed as useful tools for minimally invasive surgery and percutaneous therapy. When such a needle is inserted into soft tissue, it bends due to the asymmetric geometry of the bevel tip. This insertion with bending is not completely repeatable. We characterize the deviations in needle tip pose (position and orientation) by performing repeated needle insertions into artificial tissue. The base of the needle is pushed at a constant speed without rotating, and the covariance of the distribution of the needle tip pose is computed from experimental data. We develop the closed-form equations to describe how the covariance varies with different model parameters. We estimate the model parameters by matching the closed-form covariance and the experimentally obtained covariance. In this work, we use a needle model modified from a previously developed model with two noise parameters. The modified needle model uses three noise parameters to better capture the stochastic behavior of the needle insertion. The modified needle model provides an improvement of the covariance error from 26.1% to 6.55%.
An Optimization Model of Tunnel Support Parameters
Directory of Open Access Journals (Sweden)
Su Lijuan
2015-05-01
Full Text Available An optimization model was developed to obtain the ideal values of the primary support parameters of tunnels, which are wide-ranging in high-speed railway design codes when the surrounding rocks are at the III, IV, and V levels. First, several sets of experiments were designed and simulated using the FLAC3D software under an orthogonal experimental design. Six factors, namely, level of surrounding rock, buried depth of tunnel, lateral pressure coefficient, anchor spacing, anchor length, and shotcrete thickness, were considered. Second, a regression equation was generated by conducting a multiple linear regression analysis following the analysis of the simulation results. Finally, the optimization model of support parameters was obtained by solving the regression equation using the least squares method. In practical projects, the optimized values of support parameters could be obtained by integrating known parameters into the proposed model. In this work, the proposed model was verified on the basis of the Liuyang River Tunnel Project. Results show that the optimization model significantly reduces related costs. The proposed model can also be used as a reliable reference for other high-speed railway tunnels.
Energy Technology Data Exchange (ETDEWEB)
Rossman, L.A.
1993-01-01
EPANET represents a third generation of water quality modeling software developed by the U.S. EPA's Drinking Water Research Division, offering significant advances in the state of the art for network water quality analysis. EPANET performs extended period simulation of hydraulic and water quality behavior within water distribution systems. In addition to substance concentration, water age and source tracing can also be simulated. EPANET includes a full featured hydraulic simulation model that can handle various types of pumps, valves, and their control rules. The water quality module is equipped to handle constituent reactions within the bulk pipe flow and at the pipe wall. It also features an efficient computational scheme that automatically determines optimal time steps and pipe segmentation for accurate tracking of material transport over time. EPANET is currently being used in the US to study such issues as loss of chlorine residual, source blending and trihalomethane (THM) formation, how altered tank operation affects water age, and total dissolved solids (TDS) control for an irrigation network.
Arihood, Leslie D.
2009-01-01
In 2005, the U.S. Geological Survey began a pilot study for the National Assessment of Water Availability and Use Program to assess the availability of water and water use in the Great Lakes Basin. Part of the study involves constructing a ground-water flow model for the Lake Michigan part of the Basin. Most ground-water flow occurs in the glacial sediments above the bedrock formations; therefore, adequate representation by the model of the horizontal and vertical hydraulic conductivity of the glacial sediments is important to the accuracy of model simulations. This work processed and analyzed well records to provide the hydrogeologic parameters of horizontal and vertical hydraulic conductivity and ground-water levels for the model layers used to simulated ground-water flow in the glacial sediments. The methods used to convert (1) lithology descriptions into assumed values of horizontal and vertical hydraulic conductivity for entire model layers, (2) aquifer-test data into point values of horizontal hydraulic conductivity, and (3) static water levels into water-level calibration data are presented. A large data set of about 458,000 well driller well logs for monitoring, observation, and water wells was available from three statewide electronic data bases to characterize hydrogeologic parameters. More than 1.8 million records of lithology from the well logs were used to create a lithologic-based representation of horizontal and vertical hydraulic conductivity of the glacial sediments. Specific-capacity data from about 292,000 well logs were converted into horizontal hydraulic conductivity values to determine specific values of horizontal hydraulic conductivity and its aerial variation. About 396,000 well logs contained data on ground-water levels that were assembled into a water-level calibration data set. A lithology-based distribution of hydraulic conductivity was created by use of a computer program to convert well-log lithology descriptions into aquifer or
U.S. Environmental Protection Agency — QUAL2K (or Q2K) is a river and stream water quality model that is intended to represent a modernized version of the QUAL2E (or Q2E) model (Brown and Barnwell 1987).
Analysis of Modeling Parameters on Threaded Screws.
Energy Technology Data Exchange (ETDEWEB)
Vigil, Miquela S. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Brake, Matthew Robert [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Vangoethem, Douglas [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2015-06-01
Assembled mechanical systems often contain a large number of bolted connections. These bolted connections (joints) are integral aspects of the load path for structural dynamics, and, consequently, are paramount for calculating a structure's stiffness and energy dissipation prop- erties. However, analysts have not found the optimal method to model appropriately these bolted joints. The complexity of the screw geometry cause issues when generating a mesh of the model. This paper will explore different approaches to model a screw-substrate connec- tion. Model parameters such as mesh continuity, node alignment, wedge angles, and thread to body element size ratios are examined. The results of this study will give analysts a better understanding of the influences of these parameters and will aide in finding the optimal method to model bolted connections.
Estimating flow and transport parameters in the unsaturated zone with pore water stable isotopes
Directory of Open Access Journals (Sweden)
M. Sprenger
2014-10-01
Full Text Available Determining the soil hydraulic properties is a prerequisite to physically model transient water flow and solute transport in the vadose zone. Estimating these properties by inverse modelling techniques has become more common within the last two decades. While these inverse approaches usually fit simulations to hydrometric data, we expanded the methodology by using independent information about the stable isotope composition of the soil pore water depth profile as a single or additional optimization target. To demonstrate the potential and limits of this approach, we compared the results of three inverse modelling strategies where the fitting targets were (a pore water isotope concentrations, (b a combination of pore water isotope concentrations and soil moisture time series, and (c a two-step approach using first soil moisture data to determine water flow parameters and then the pore water stable isotope concentrations to estimate the solute transport parameters. The analyses were conducted at three study sites with different soil properties and vegetation. The transient unsaturated water flow was simulated by numerically solving the Richards equation with the finite-element code of Hydrus-1D. The transport of deuterium was simulated with the advection-dispersion equation, and the Hydrus code was modified to allow for deuterium loss during evaporation. The Mualem–van Genuchten and the longitudinal dispersivity parameters were determined for two major soil horizons at each site. The results show that approach (a using only the pore water isotope content cannot substitute hydrometric information to derive parameter sets that reflect the observed soil moisture dynamics, but gives comparable results when the parameter space is constrained by pedotransfer functions. Approaches (b and (c using both, the isotope profiles and the soil moisture time series resulted in satisfying model performances and good parameter identifiability. However, approach
Correlation study among water quality parameters an approach to water quality management.
Sinha, D K; Rastogi, G K; Kumar, R; Kumar, N
2009-04-01
To find out an approach to water quality management through correlation studies between various water quality parameters, the statistical regression analysis for six data points of underground drinking water of different hand pumps at J. P. Nagar was carried out. The comparison of estimated values with W.H.O drinking water standards revealed that water of the study area is polluted with reference to a number of physico-chemical parameters studied. Regression analysis suggests that conductivity of underground water is found to be significantly correlated with eight out of twelve water quality parameters studied. It may be suggested that the underground drinking water quality at J. P. Nagar can be checked very effectively by controlling the conductivity of water. The present study may be treated one step forward towards the water quality management.
The Lund Model at Nonzero Impact Parameter
Janik, R A; Janik, Romuald A.; Peschanski, Robi
2003-01-01
We extend the formulation of the longitudinal 1+1 dimensional Lund model to nonzero impact parameter using the minimal area assumption. Complete formulae for the string breaking probability and the momenta of the produced mesons are derived using the string worldsheet Minkowskian helicoid geometry. For strings stretched into the transverse dimension, we find probability distribution with slope linear in m_T similar to the statistical models but without any thermalization assumptions.
IMPROVEMENT OF FLUID PIPE LUMPED PARAMETER MODEL
Institute of Scientific and Technical Information of China (English)
Kong Xiaowu; Wei Jianhua; Qiu Minxiu; Wu Genmao
2004-01-01
The traditional lumped parameter model of fluid pipe is introduced and its drawbacks are pointed out.Furthermore, two suggestions are put forward to remove these drawbacks.Firstly, the structure of equivalent circuit is modified, and then the evaluation of equivalent fluid resistance is change to take the frequency-dependent friction into account.Both simulation and experiment prove that this model is precise to characterize the dynamic behaviors of fluid in pipe.
Estimation of octanol/water partition coefficients using LSER parameters
Luehrs, Dean C.; Hickey, James P.; Godbole, Kalpana A.; Rogers, Tony N.
1998-01-01
The logarithms of octanol/water partition coefficients, logKow, were regressed against the linear solvation energy relationship (LSER) parameters for a training set of 981 diverse organic chemicals. The standard deviation for logKow was 0.49. The regression equation was then used to estimate logKow for a test of 146 chemicals which included pesticides and other diverse polyfunctional compounds. Thus the octanol/water partition coefficient may be estimated by LSER parameters without elaborate software but only moderate accuracy should be expected.
WATER HARDNESS AS AN IMPORTANT PARAMETER OF PH
Directory of Open Access Journals (Sweden)
Žigmund Tóth
2013-02-01
Full Text Available Quality of final product is to great extent influenced by intermediate products that are formed during beer production. In addition quality of pH is one of the most important properties that forms suitable medium for activity of enzymes complexes that have crucial influence on character of produced wort. Moreover enzymes influence the yield of production process and quality of final product as well. Quality of boiling water and especially its hardness have crucial task in terms of keeping optimal qualitative parameters. Water hardness is given by amount of salts, mainly calcium and magnesium salts. It is expressed as absolute hardness which is given by sum of temporary (carbonate and permanent (noncarbonate hardness. In our work we solved the effect of total water hardness on final pH of various intermediate products. We used different water samples and we prepared variants of total hardness by stirring of unpurified water with distilled water thus we achieved various values of hardness. For comparison we prepared several brews with regard to combinations of unpurified water and distilled water. Higher pH of boiling water was caused due to higher water alkalinity that negatively affected enzyme complex present in used malt. Presence of hydrogenphosphates in used malt had high buffering ability and pH lowering ability. Such unfavorable result could be adjust by use of various additions of acidulates that would have in great extent influence on beer final price therefore boiling water adjustment seems to be the most acceptable approach.
Order Parameters of the Dilute A Models
Warnaar, S O; Seaton, K A; Nienhuis, B
1993-01-01
The free energy and local height probabilities of the dilute A models with broken $\\Integer_2$ symmetry are calculated analytically using inversion and corner transfer matrix methods. These models possess four critical branches. The first two branches provide new realisations of the unitary minimal series and the other two branches give a direct product of this series with an Ising model. We identify the integrable perturbations which move the dilute A models away from the critical limit. Generalised order parameters are defined and their critical exponents extracted. The associated conformal weights are found to occur on the diagonal of the relevant Kac table. In an appropriate regime the dilute A$_3$ model lies in the universality class of the Ising model in a magnetic field. In this case we obtain the magnetic exponent $\\delta=15$ directly, without the use of scaling relations.
Testing Linear Models for Ability Parameters in Item Response Models
Glas, Cees A.W.; Hendrawan, Irene
2005-01-01
Methods for testing hypotheses concerning the regression parameters in linear models for the latent person parameters in item response models are presented. Three tests are outlined: A likelihood ratio test, a Lagrange multiplier test and a Wald test. The tests are derived in a marginal maximum like
An Effective Parameter Screening Strategy for High Dimensional Watershed Models
Khare, Y. P.; Martinez, C. J.; Munoz-Carpena, R.
2014-12-01
Watershed simulation models can assess the impacts of natural and anthropogenic disturbances on natural systems. These models have become important tools for tackling a range of water resources problems through their implementation in the formulation and evaluation of Best Management Practices, Total Maximum Daily Loads, and Basin Management Action Plans. For accurate applications of watershed models they need to be thoroughly evaluated through global uncertainty and sensitivity analyses (UA/SA). However, due to the high dimensionality of these models such evaluation becomes extremely time- and resource-consuming. Parameter screening, the qualitative separation of important parameters, has been suggested as an essential step before applying rigorous evaluation techniques such as the Sobol' and Fourier Amplitude Sensitivity Test (FAST) methods in the UA/SA framework. The method of elementary effects (EE) (Morris, 1991) is one of the most widely used screening methodologies. Some of the common parameter sampling strategies for EE, e.g. Optimized Trajectories [OT] (Campolongo et al., 2007) and Modified Optimized Trajectories [MOT] (Ruano et al., 2012), suffer from inconsistencies in the generated parameter distributions, infeasible sample generation time, etc. In this work, we have formulated a new parameter sampling strategy - Sampling for Uniformity (SU) - for parameter screening which is based on the principles of the uniformity of the generated parameter distributions and the spread of the parameter sample. A rigorous multi-criteria evaluation (time, distribution, spread and screening efficiency) of OT, MOT, and SU indicated that SU is superior to other sampling strategies. Comparison of the EE-based parameter importance rankings with those of Sobol' helped to quantify the qualitativeness of the EE parameter screening approach, reinforcing the fact that one should use EE only to reduce the resource burden required by FAST/Sobol' analyses but not to replace it.
Modelling spin Hamiltonian parameters of molecular nanomagnets.
Gupta, Tulika; Rajaraman, Gopalan
2016-07-12
Molecular nanomagnets encompass a wide range of coordination complexes possessing several potential applications. A formidable challenge in realizing these potential applications lies in controlling the magnetic properties of these clusters. Microscopic spin Hamiltonian (SH) parameters describe the magnetic properties of these clusters, and viable ways to control these SH parameters are highly desirable. Computational tools play a proactive role in this area, where SH parameters such as isotropic exchange interaction (J), anisotropic exchange interaction (Jx, Jy, Jz), double exchange interaction (B), zero-field splitting parameters (D, E) and g-tensors can be computed reliably using X-ray structures. In this feature article, we have attempted to provide a holistic view of the modelling of these SH parameters of molecular magnets. The determination of J includes various class of molecules, from di- and polynuclear Mn complexes to the {3d-Gd}, {Gd-Gd} and {Gd-2p} class of complexes. The estimation of anisotropic exchange coupling includes the exchange between an isotropic metal ion and an orbitally degenerate 3d/4d/5d metal ion. The double-exchange section contains some illustrative examples of mixed valance systems, and the section on the estimation of zfs parameters covers some mononuclear transition metal complexes possessing very large axial zfs parameters. The section on the computation of g-anisotropy exclusively covers studies on mononuclear Dy(III) and Er(III) single-ion magnets. The examples depicted in this article clearly illustrate that computational tools not only aid in interpreting and rationalizing the observed magnetic properties but possess the potential to predict new generation MNMs.
Energy Technology Data Exchange (ETDEWEB)
Ducoste, J.; Brauer, R.
1999-07-01
Analysis of a computational fluid dynamics (CFD) model for a water treatment plant clearwell was done. Model parameters were analyzed to determine their influence on the effluent-residence time distribution (RTD) function. The study revealed that several model parameters could have significant impact on the shape of the RTD function and consequently raise the level of uncertainty on accurate predictions of clearwell hydraulics. The study also revealed that although the modeler could select a distribution of values for some of the model parameters, most of these values can be ruled out by requiring the difference between the calculated and theoretical hydraulic retention time to within 5% of the theoretical value.
Systematic parameter inference in stochastic mesoscopic modeling
Lei, Huan; Li, Zhen; Karniadakis, George
2016-01-01
We propose a method to efficiently determine the optimal coarse-grained force field in mesoscopic stochastic simulations of Newtonian fluid and polymer melt systems modeled by dissipative particle dynamics (DPD) and energy conserving dissipative particle dynamics (eDPD). The response surfaces of various target properties (viscosity, diffusivity, pressure, etc.) with respect to model parameters are constructed based on the generalized polynomial chaos (gPC) expansion using simulation results on sampling points (e.g., individual parameter sets). To alleviate the computational cost to evaluate the target properties, we employ the compressive sensing method to compute the coefficients of the dominant gPC terms given the prior knowledge that the coefficients are sparse. The proposed method shows comparable accuracy with the standard probabilistic collocation method (PCM) while it imposes a much weaker restriction on the number of the simulation samples especially for systems with high dimensional parametric space....
10-Day survival of Hyalella azteca as a function of water quality parameters.
Javidmehr, Alireza; Kass, Philip H; Deanovic, Linda A; Connon, Richard E; Werner, Inge
2015-05-01
Estuarine systems are among the most impacted ecosystems due to anthropogenic contaminants; however, they present unique challenges to toxicity testing with regard to varying water quality parameters. The euryhaline amphipod species, Hyalella azteca, is widely used in toxicity testing and well suited for testing estuarine water samples. Nevertheless, the influence of relevant water quality parameters on test endpoints must be quantified in order to efficiently use this species for routine monitoring. Here, we studied the influence of five water quality parameters: electrical conductivity, pH, un-ionized ammonia, dissolved oxygen and temperature, on H. azteca survival in a water column toxicity test. A model was developed to quantify and predict the independent and interacting effects of water quality variables on 10-day survival. The model allows simultaneous assessment of multiple potential predictors recorded during the tests. Data used for modeling came from 1089 tests performed on ambient water samples over a period of three years (2006-2008). The final model reflects significant effects of predictors and their two-way interactions. The effect of each level of all predictors on survival probability of H. azteca was examined by comparing levels of each predictor at a time, while holding all others at their lowest (reference) level. This study showed that predictors of survival in water column tests should not be evaluated in isolation in the interpretation of H. azteca water column tests. Our model provides a useful tool to predict expected control survival based on relevant water quality parameters, and thus enables the use of H. azteca tests for toxicity monitoring in estuaries with a wide range of water quality conditions.
Directory of Open Access Journals (Sweden)
Lezhnin Sergey
2017-01-01
Full Text Available The two-temperature model of the outflow from a vessel with initial supercritical parameters of medium has been realized. The model uses thermodynamic non-equilibrium relaxation approach to describe phase transitions. Based on a new asymptotic model for computing the relaxation time, the outflow of water with supercritical initial pressure and super- and subcritical temperatures has been calculated.
Modelling tourists arrival using time varying parameter
Suciptawati, P.; Sukarsa, K. G.; Kencana, Eka N.
2017-06-01
The importance of tourism and its related sectors to support economic development and poverty reduction in many countries increase researchers’ attentions to study and model tourists’ arrival. This work is aimed to demonstrate time varying parameter (TVP) technique to model the arrival of Korean’s tourists to Bali. The number of Korean tourists whom visiting Bali for period January 2010 to December 2015 were used to model the number of Korean’s tourists to Bali (KOR) as dependent variable. The predictors are the exchange rate of Won to IDR (WON), the inflation rate in Korea (INFKR), and the inflation rate in Indonesia (INFID). Observing tourists visit to Bali tend to fluctuate by their nationality, then the model was built by applying TVP and its parameters were approximated using Kalman Filter algorithm. The results showed all of predictor variables (WON, INFKR, INFID) significantly affect KOR. For in-sample and out-of-sample forecast with ARIMA’s forecasted values for the predictors, TVP model gave mean absolute percentage error (MAPE) as much as 11.24 percent and 12.86 percent, respectively.
Water Relation Parameters of Embryogenic Cultures and Seedlings of Larch
Livingston, Nigel J.; von Aderkas, Patrick; Fuchs, Edgar E.; Reaney, Martin J. T.
1992-01-01
Changes in the water relations parameters of developing somatic embryogenic and xygotic European larch (Larix decidua) were studied. Water release curves were generated by suspending tissue samples over unsaturated NaCl solutions until they reached vapor equilibration with the surrounding air. Twenty solutions were used whose water potentials ranged from −0.05 to −10 MPa. Water release curves were obtained by plotting paired values of tissue relative water content (RWC) and solution potential. Curves were derived for embryonic larch at various stages of development and for hypocotyls and roots from germinated zygotic and somatic embryos. The ability to resist dehydration increased markedly with development. Stage 1 tissue, which consisted of clusters of loosely associated nonchlorophyllous cells, had extremely low bulk elastic modulus (ε) (1.91 MPa) and apoplastic water content (A) (0.023), relatively high osmotic potential (Ψπ) (−0.53 MPa), and lost turgor at 0.56 RWC. In contrast, mature embryoids with primary roots, hypocotyl, and cotyledons (stage 3) had an almost 4-fold increase in A (0.089), significantly higher ε (3.49 MPa), and lower Ψπ (−0.88 MPa) and lost turgor at 0.66 RWC. Hypocotyl tissue from germinated somatic embryos lost turgor at 0.74 RWC and had higher ε, A, and solute accumulation than pregerminated tissue. Hypocotyl tissue resisted dehydration more strongly than root tissue, and differences between root and hypocotyl water relation parameters were more pronounced in xygotic than in somatic seedlings. Highest dehydration resistance was in zygotic hypocotyls. The characterization of the water relations of tissue cultures should allow the development of more consistent and reliable desiccation protocols to induce maturation of embryos and produce synchronously germinating seed. PMID:16653121
Parameter estimation, model reduction and quantum filtering
Chase, Bradley A.
This thesis explores the topics of parameter estimation and model reduction in the context of quantum filtering. The last is a mathematically rigorous formulation of continuous quantum measurement, in which a stream of auxiliary quantum systems is used to infer the state of a target quantum system. Fundamental quantum uncertainties appear as noise which corrupts the probe observations and therefore must be filtered in order to extract information about the target system. This is analogous to the classical filtering problem in which techniques of inference are used to process noisy observations of a system in order to estimate its state. Given the clear similarities between the two filtering problems, I devote the beginning of this thesis to a review of classical and quantum probability theory, stochastic calculus and filtering. This allows for a mathematically rigorous and technically adroit presentation of the quantum filtering problem and solution. Given this foundation, I next consider the related problem of quantum parameter estimation, in which one seeks to infer the strength of a parameter that drives the evolution of a probe quantum system. By embedding this problem in the state estimation problem solved by the quantum filter, I present the optimal Bayesian estimator for a parameter when given continuous measurements of the probe system to which it couples. For cases when the probe takes on a finite number of values, I review a set of sufficient conditions for asymptotic convergence of the estimator. For a continuous-valued parameter, I present a computational method called quantum particle filtering for practical estimation of the parameter. Using these methods, I then study the particular problem of atomic magnetometry and review an experimental method for potentially reducing the uncertainty in the estimate of the magnetic field beyond the standard quantum limit. The technique involves double-passing a probe laser field through the atomic system, giving
Laboratory investigations into some parameters of water-ash mixtures
Energy Technology Data Exchange (ETDEWEB)
Postawa, J.; Stryczek, F.; Kraj, L. (Akademia Gorniczo-Hutnicza, Cracow (Poland). Instytut Gornictwa Podziemnego i Bezpieczenstwa Pracy)
1990-06-01
Presents results of laboratory investigations of certain parameters that are of essential importance in the utilization of water-ash mixtures in underground mining. Mixtures of fly ash and water were examined at 293 K. The following properties of the mixture were investigated: density, fluidity, relative viscosity, structural strength, water separation after 1, 2, 4 and 24 hours, rheological properties and plastic viscosity. The properties were measured by the AzNII cone, Ford cup, shear tester and Fonn viscosimeter. Results are presented for water to ash proportion: 1.5, 2.0, 2.5 and 3.0. The conclusions are reached that water ash mixtures belong to the Bingham (rheostable) fluids, can be transported by gravitational methods and can fill cavities between lumps of caving rubble. Their ability to bind and harden creates a wide application range in mining (sealing caving rubble and fissured zones and execution of packing stoppings). The parameters found can be used in planning and designing stowing operations. 9 refs.
Analysis of physical and chemical parameters of bottled drinking water.
Mahajan, Rakesh Kumar; Walia, T P S; Lark, B S; Sumanjit
2006-04-01
Seventeen different brands of bottled drinking water, collected from different retail shops in Amritsar, were analyzed for different physical and chemical parameters to ascertain their compliability with the prescribed/recommended limits of the World Heath Organization (WHO) and the United States Environmental Protection Agency (USEPA). It was found that the majority of the brands tested were over-treated. Lower values of hardness, total dissolved solids (TDS) and conductance than the prescribed limits of WHO showed that water was deficient in essential minerals. Minerals like magnesium, potassium, calcium and fluoride were present in some cases in such a low concentration that water seemed to be as good as distilled water. Samples showing fluoride lesser than 0.5 mg/l warranted additional sources of fluoride for the people consuming only bottled water for drinking purposes. Zero values for chlorine demand as shown by all the bottled water samples showed that water samples were safe from micro-organisms. In case of heavy metals, only lead had been found to be greater than the limit of 0.015 mg/l as prescribed by WHO and USEPA, in seven out of 17 samples. Lead even at such a low concentration can pose a great health hazard.
Regan, R. Steve; LaFontaine, Jacob H.
2017-10-05
This report documents seven enhancements to the U.S. Geological Survey (USGS) Precipitation-Runoff Modeling System (PRMS) hydrologic simulation code: two time-series input options, two new output options, and three updates of existing capabilities. The enhancements are (1) new dynamic parameter module, (2) new water-use module, (3) new Hydrologic Response Unit (HRU) summary output module, (4) new basin variables summary output module, (5) new stream and lake flow routing module, (6) update to surface-depression storage and flow simulation, and (7) update to the initial-conditions specification. This report relies heavily upon U.S. Geological Survey Techniques and Methods, book 6, chapter B7, which documents PRMS version 4 (PRMS-IV). A brief description of PRMS is included in this report.
Adem Ali, K.; Ortiz, J. D.
2012-12-01
Lake Erie is biological the most active among the Great Lakes and experiences frequent large scale algal bloom during the summer period. Harmful algal blooms (HABs) such as Microcystis aeruginosa have been documented and these are of great concern for human health and are detrimental to the lake's biodiversity. Therefore, efficient lake monitoring tools are required for early detection and forecasting purposes. Satellite remote sensing is an efficient tool with high spatial and temporal coverage that can allow accurate and timely detection of HABs. However, in optically complex aquatic environments such as the Western Basin of Lake Erie (WBLE) where multiple color producing agents (CPAs) including phytoplankton, suspended sediment, and dissolved organic carbon are present the recorded spectra represent a convolution of the spectral responses from multiple constituents and the discrimination between the various constituents requires separation of the mostly overlapping scattering and absorption properties. This presents a challenge to the application of remote sensing data for determining a single in-water constituent. To assess the controls on the optical properties in the lake, we conducted weekly research cruises, collecting samples and conducting in-situ spectroscopy from a total of 90 stations that encompass many of the environments in Lake Erie ranging from deeper waters, shallower bay waters and riverine discharges. First-derivative of the hyperspectral data clearly revealed known spectral features of phytoplankton, a primary constituent in the WBLE, which include absorption minima near 560 and 700 nm attributed to the minimum absorption capacity and fluorescence effects, respectively. The signal also extracted the red absorption peak due to chlorophyll a (a proxy used for phytoplankton density) near 675 nm. Attenuation effects due to dissolved organic matter, detritus and suspended inorganic matters are also evident in the spectral signatures. This study
Parameter optimization in S-system models
Directory of Open Access Journals (Sweden)
Vasconcelos Ana
2008-04-01
Full Text Available Abstract Background The inverse problem of identifying the topology of biological networks from their time series responses is a cornerstone challenge in systems biology. We tackle this challenge here through the parameterization of S-system models. It was previously shown that parameter identification can be performed as an optimization based on the decoupling of the differential S-system equations, which results in a set of algebraic equations. Results A novel parameterization solution is proposed for the identification of S-system models from time series when no information about the network topology is known. The method is based on eigenvector optimization of a matrix formed from multiple regression equations of the linearized decoupled S-system. Furthermore, the algorithm is extended to the optimization of network topologies with constraints on metabolites and fluxes. These constraints rejoin the system in cases where it had been fragmented by decoupling. We demonstrate with synthetic time series why the algorithm can be expected to converge in most cases. Conclusion A procedure was developed that facilitates automated reverse engineering tasks for biological networks using S-systems. The proposed method of eigenvector optimization constitutes an advancement over S-system parameter identification from time series using a recent method called Alternating Regression. The proposed method overcomes convergence issues encountered in alternate regression by identifying nonlinear constraints that restrict the search space to computationally feasible solutions. Because the parameter identification is still performed for each metabolite separately, the modularity and linear time characteristics of the alternating regression method are preserved. Simulation studies illustrate how the proposed algorithm identifies the correct network topology out of a collection of models which all fit the dynamical time series essentially equally well.
Modeling of Parameters of Subcritical Assembly SAD
Petrochenkov, S; Puzynin, I
2005-01-01
The accepted conceptual design of the experimental Subcritical Assembly in Dubna (SAD) is based on the MOX core with a nominal unit capacity of 25 kW (thermal). This corresponds to the multiplication coefficient $k_{\\rm eff} =0.95$ and accelerator beam power 1 kW. A subcritical assembly driven with the existing 660 MeV proton accelerator at the Joint Institute for Nuclear Research has been modelled in order to make choice of the optimal parameters for the future experiments. The Monte Carlo method was used to simulate neutron spectra, energy deposition and doses calculations. Some of the calculation results are presented in the paper.
Baker Syed; Poskar C; Junker Björn
2011-01-01
Abstract In systems biology, experimentally measured parameters are not always available, necessitating the use of computationally based parameter estimation. In order to rely on estimated parameters, it is critical to first determine which parameters can be estimated for a given model and measurement set. This is done with parameter identifiability analysis. A kinetic model of the sucrose accumulation in the sugar cane culm tissue developed by Rohwer et al. was taken as a test case model. Wh...
Moose models with vanishing $S$ parameter
Casalbuoni, R; Dominici, Daniele
2004-01-01
In the linear moose framework, which naturally emerges in deconstruction models, we show that there is a unique solution for the vanishing of the $S$ parameter at the lowest order in the weak interactions. We consider an effective gauge theory based on $K$ SU(2) gauge groups, $K+1$ chiral fields and electroweak groups $SU(2)_L$ and $U(1)_Y$ at the ends of the chain of the moose. $S$ vanishes when a link in the moose chain is cut. As a consequence one has to introduce a dynamical non local field connecting the two ends of the moose. Then the model acquires an additional custodial symmetry which protects this result. We examine also the possibility of a strong suppression of $S$ through an exponential behavior of the link couplings as suggested by Randall Sundrum metric.
Model parameters for simulation of physiological lipids
McGlinchey, Nicholas
2016-01-01
Coarse grain simulation of proteins in their physiological membrane environment can offer insight across timescales, but requires a comprehensive force field. Parameters are explored for multicomponent bilayers composed of unsaturated lipids DOPC and DOPE, mixed‐chain saturation POPC and POPE, and anionic lipids found in bacteria: POPG and cardiolipin. A nonbond representation obtained from multiscale force matching is adapted for these lipids and combined with an improved bonding description of cholesterol. Equilibrating the area per lipid yields robust bilayer simulations and properties for common lipid mixtures with the exception of pure DOPE, which has a known tendency to form nonlamellar phase. The models maintain consistency with an existing lipid–protein interaction model, making the force field of general utility for studying membrane proteins in physiologically representative bilayers. © 2016 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc. PMID:26864972
Considerations for parameter optimization and sensitivity in climate models.
Neelin, J David; Bracco, Annalisa; Luo, Hao; McWilliams, James C; Meyerson, Joyce E
2010-12-14
Climate models exhibit high sensitivity in some respects, such as for differences in predicted precipitation changes under global warming. Despite successful large-scale simulations, regional climatology features prove difficult to constrain toward observations, with challenges including high-dimensionality, computationally expensive simulations, and ambiguity in the choice of objective function. In an atmospheric General Circulation Model forced by observed sea surface temperature or coupled to a mixed-layer ocean, many climatic variables yield rms-error objective functions that vary smoothly through the feasible parameter range. This smoothness occurs despite nonlinearity strong enough to reverse the curvature of the objective function in some parameters, and to imply limitations on multimodel ensemble means as an estimator of global warming precipitation changes. Low-order polynomial fits to the model output spatial fields as a function of parameter (quadratic in model field, fourth-order in objective function) yield surprisingly successful metamodels for many quantities and facilitate a multiobjective optimization approach. Tradeoffs arise as optima for different variables occur at different parameter values, but with agreement in certain directions. Optima often occur at the limit of the feasible parameter range, identifying key parameterization aspects warranting attention--here the interaction of convection with free tropospheric water vapor. Analytic results for spatial fields of leading contributions to the optimization help to visualize tradeoffs at a regional level, e.g., how mismatches between sensitivity and error spatial fields yield regional error under minimization of global objective functions. The approach is sufficiently simple to guide parameter choices and to aid intercomparison of sensitivity properties among climate models.
Building Water Models, A Different Approach
Izadi, Saeed; Onufriev, Alexey V
2014-01-01
Simplified, classical models of water are an integral part of atomistic molecular simulations, especially in biology and chemistry where hydration effects are critical. Yet, despite several decades of effort, these models are still far from perfect. Presented here is an alternative approach to constructing point charge water models - currently, the most commonly used type. In contrast to the conventional approach, we do not impose any geometry constraints on the model other than symmetry. Instead, we optimize the distribution of point charges to best describe the "electrostatics" of the water molecule, which is key to many unusual properties of liquid water. The search for the optimal charge distribution is performed in 2D parameter space of key lowest multipole moments of the model, to find best fit to a small set of bulk water properties at room temperature. A virtually exhaustive search is enabled via analytical equations that relate the charge distribution to the multipole moments. The resulting "optimal"...
Is flow velocity a significant parameter in flood damage modelling?
Directory of Open Access Journals (Sweden)
H. Kreibich
2009-10-01
Full Text Available Flow velocity is generally presumed to influence flood damage. However, this influence is hardly quantified and virtually no damage models take it into account. Therefore, the influences of flow velocity, water depth and combinations of these two impact parameters on various types of flood damage were investigated in five communities affected by the Elbe catchment flood in Germany in 2002. 2-D hydraulic models with high to medium spatial resolutions were used to calculate the impact parameters at the sites in which damage occurred. A significant influence of flow velocity on structural damage, particularly on roads, could be shown in contrast to a minor influence on monetary losses and business interruption. Forecasts of structural damage to road infrastructure should be based on flow velocity alone. The energy head is suggested as a suitable flood impact parameter for reliable forecasting of structural damage to residential buildings above a critical impact level of 2 m of energy head or water depth. However, general consideration of flow velocity in flood damage modelling, particularly for estimating monetary loss, cannot be recommended.
Effect of hyperthermic water bath on parameters of cellular immunity.
Blazícková, S; Rovenský, J; Koska, J; Vigas, M
2000-01-01
Effects of hyperthermic water bath on selected immune parameters (lymphocyte subpopulations, natural killer (NK) cell counts and their activity) were studied in a group of 10 volunteers. Application of hyperthermic water bath (both topical and whole-body) was followed by a significant reduction of relative B lymphocyte counts. Whole-body hyperthermic water bath reduced relative total T lymphocyte counts, increased relative CD8+ T lymphocyte and NK cell counts and increased NK activity. Whole-body hyperthermic bath increased somatotropic hormone (STH) activity in eight out of 10 volunteers; higher relative counts of CD8+ lymphocytes and NK cells were observed compared with the group of volunteers not responding to hyperthermic water bath by STH secretion. In five volunteers STH was released in response to local hyperthermic water bath and the NK activity of lymphocytes also increased but their relative counts did not. The results suggest that these increases in CD8+ lymphocyte and NK cell counts are probably dependent on increased STH production.
Do land parameters matter in large-scale hydrological modelling?
Gudmundsson, Lukas; Seneviratne, Sonia I.
2013-04-01
parameters in ever greater detail. While improved physically-based models are under development, the proposed statistical model can be used to produce full space-time estimates of monthly runoff in Europe, contributing to practical aspects of the discipline including water resources monitoring and seasonal forecasting.
Parameter Estimation of Induction Motors Using Water Cycle Optimization
Directory of Open Access Journals (Sweden)
M. Yazdani-Asrami
2013-12-01
Full Text Available This paper presents the application of recently introduced water cycle algorithm (WCA to optimize the parameters of exact and approximate induction motor from the nameplate data. Considering that induction motors are widely used in industrial applications, these parameters have a significant effect on the accuracy and efficiency of the motors and, ultimately, the overall system performance. Therefore, it is essential to develop algorithms for the parameter estimation of the induction motor. The fundamental concepts and ideas which underlie the proposed method is inspired from nature and based on the observation of water cycle process and how rivers and streams ﬂow to the sea in the real world. The objective function is defined as the minimization of the real values of the relative error between the measured and estimated torques of the machine in different slip points. The proposed WCA approach has been applied on two different sample motors. Results of the proposed method have been compared with other previously applied Meta heuristic methods on the problem, which show the feasibility and the fast convergence of the proposed approach.
Optimized drying parameters of water hyacinths (Eichhornia crassipes. L
Directory of Open Access Journals (Sweden)
Edgardo V. Casas
2012-12-01
Full Text Available The study investigated the optimum drying conditions of water hyacinth to contribute in the improvement of present drying processes. The effects of independent parameters (drying temperature, airflow rate, and number of passes on the responses were determined using the Response Surface Methodology. The response parameters were composed of (1 final moisture content, (2 moisture ratio, (3 drying rate,(4 tensile strength, and (5 browning index. Box and Behnken experimental design represented the design of experiments that resulted in 15 drying runs. Statistical analysis evaluated the treatment effects. Drying temperature significantly affected the drying rate, moisture ratio, and browning index. Airflow rate had a significant effect only on the drying rate, while the number of passes significantly affected both the drying rate and browning index. The optimized conditions for drying the water hyacinth were at drying temperature of 90C, airflow rate of 0.044m3/s, and number of passes equivalent to five. The best modelthat characterizes the drying of water hyacinth is a rational function expressed as:
Accelerated shallow water modeling
Gandham, Rajesh; Medina, David; Warburton, Timothy
2015-04-01
ln this talk we will describe our ongoing developments in accelerated numerical methods for modeling tsunamis, and oceanic fluid flows using two dimensional shallow water model and/or three dimensional incompressible Navier Stokes model discretized with high order discontinuous Galerkin methods. High order discontinuous Galerkin methods can be computationally demanding, requiring extensive computational time to simulate real time events on traditional CPU architectures. However, recent advances in computing architectures and hardware aware algorithms make it possible to reduce simulation time and provide accurate predictions in a timely manner. Hence we tailor these algorithms to take advantage of single instruction multiple data (SIMD) architecture that is seen in modern many core compute devices such as GPUs. We will discuss our unified and extensive many-core programming library OCCA that alleviates the need to completely re-design the solvers to keep up with constantly evolving parallel programming models and hardware architectures. We will present performance results for the flow simulations demonstrating performance leveraging multiple different multi-threading APIs on GPU and CPU targets.
Uncertainty Quantification for Optical Model Parameters
Lovell, A E; Sarich, J; Wild, S M
2016-01-01
Although uncertainty quantification has been making its way into nuclear theory, these methods have yet to be explored in the context of reaction theory. For example, it is well known that different parameterizations of the optical potential can result in different cross sections, but these differences have not been systematically studied and quantified. The purpose of this work is to investigate the uncertainties in nuclear reactions that result from fitting a given model to elastic-scattering data, as well as to study how these uncertainties propagate to the inelastic and transfer channels. We use statistical methods to determine a best fit and create corresponding 95\\% confidence bands. A simple model of the process is fit to elastic-scattering data and used to predict either inelastic or transfer cross sections. In this initial work, we assume that our model is correct, and the only uncertainties come from the variation of the fit parameters. We study a number of reactions involving neutron and deuteron p...
Numerical modeling of partial discharges parameters
Directory of Open Access Journals (Sweden)
Kartalović Nenad M.
2016-01-01
Full Text Available In recent testing of the partial discharges or the use for the diagnosis of insulation condition of high voltage generators, transformers, cables and high voltage equipment develops rapidly. It is a result of the development of electronics, as well as, the development of knowledge about the processes of partial discharges. The aim of this paper is to contribute the better understanding of this phenomenon of partial discharges by consideration of the relevant physical processes in isolation materials and isolation systems. Prebreakdown considers specific processes, and development processes at the local level and their impact on specific isolation material. This approach to the phenomenon of partial discharges needed to allow better take into account relevant discharge parameters as well as better numerical model of partial discharges.
Mathematical Modeling for the Clarifier Units and Turbidity Parameters in AL-KARAMA Treatment Plant
Directory of Open Access Journals (Sweden)
Hayder Mohammed Abdul-Hameed
2005-01-01
Full Text Available The high cost of chemical analysis of water has necessitated various researches into finding alternative method of determining portable water quality. This paper is aimed at modelling the turbidity value as a water quality parameter. Mathematical models for turbidity removal were developed based on the relationships between water turbidity and other water criteria. Results showed that the turbidity of water is the cumulative effect of the individual parameters/factors affecting the system. A model equation for the evaluation and prediction of a clarifiers performance was developed:Model: T = T0(-1.36729 + 0.037101∙10λpH + 0.048928t + 0.00741387∙alkThe developed model will aid the predictive assessment of water treatment plant performance. The limitations of the models are as a result of insufficient variable considered during the conceptualization.
Gupta, Manika; Garg, Naveen Kumar; Srivastava, Prashant K.
2014-05-01
The sensitivity and uncertainty analysis has been carried out for the scalar parameters (soil hydraulic parameters (SHPs)), which govern the simulation of soil water content in the unsaturated soil zone. The study involves field experiments, which were conducted in real field conditions for wheat crop in Roorkee, India under irrigated conditions. Soil samples were taken for the soil profile of 60 cm depth at an interval of 15 cm in the experimental field to determine soil water retention curves (SWRCs). These experimentally determined SWRCs were used to estimate the SHPs by least square optimization under constrained conditions. Sensitivity of the SHPs estimated by various pedotransfer functions (PTFs), that relate various easily measurable soil properties like soil texture, bulk density and organic carbon content, is compared with lab derived parameters to simulate respective soil water retention curves. Sensitivity analysis was carried out using the monte carlo simulations and the one factor at a time approach. The different sets of SHPs, along with experimentally determined saturated permeability, are then used as input parameters in physically based, root water uptake model to ascertain the uncertainties in simulating soil water content. The generalised likelihood uncertainty estimation procedure (GLUE) was subsequently used to estimate the uncertainty bounds (UB) on the model predictions. It was found that the experimentally obtained SHPs were able to simulate the soil water contents with efficiencies of 70-80% at all the depths for the three irrigation treatments. The SHPs obtained from the PTFs, performed with varying uncertainties in simulating the soil water contents. Keywords: Sensitivity analysis, Uncertainty estimation, Pedotransfer functions, Soil hydraulic parameters, Hydrological modelling
Estimating flow and transport parameters in the unsaturated zone with pore water stable isotopes
Sprenger, M.; Volkmann, T. H. M.; Blume, T.; Weiler, M.
2015-06-01
Determining the soil hydraulic properties is a prerequisite to physically model transient water flow and solute transport in the vadose zone. Estimating these properties by inverse modelling techniques has become more common within the last 2 decades. While these inverse approaches usually fit simulations to hydrometric data, we expanded the methodology by using independent information about the stable isotope composition of the soil pore water depth profile as a single or additional optimization target. To demonstrate the potential and limits of this approach, we compared the results of three inverse modelling strategies where the fitting targets were (a) pore water isotope concentrations, (b) a combination of pore water isotope concentrations and soil moisture time series, and (c) a two-step approach using first soil moisture data to determine water flow parameters and then the pore water stable isotope concentrations to estimate the solute transport parameters. The analyses were conducted at three study sites with different soil properties and vegetation. The transient unsaturated water flow was simulated by solving the Richards equation numerically with the finite-element code of HYDRUS-1D. The transport of deuterium was simulated with the advection-dispersion equation, and a modified version of HYDRUS was used, allowing deuterium loss during evaporation. The Mualem-van Genuchten and the longitudinal dispersivity parameters were determined for two major soil horizons at each site. The results show that approach (a), using only the pore water isotope content, cannot substitute hydrometric information to derive parameter sets that reflect the observed soil moisture dynamics but gives comparable results when the parameter space is constrained by pedotransfer functions. Approaches (b) and (c), using both the isotope profiles and the soil moisture time series, resulted in good simulation results with regard to the Kling-Gupta efficiency and good parameter
Parameters-related uncertainty in modeling sugar cane yield with an agro-Land Surface Model
Valade, A.; Ciais, P.; Vuichard, N.; Viovy, N.; Ruget, F.; Gabrielle, B.
2012-12-01
Agro-Land Surface Models (agro-LSM) have been developed from the coupling of specific crop models and large-scale generic vegetation models. They aim at accounting for the spatial distribution and variability of energy, water and carbon fluxes within soil-vegetation-atmosphere continuum with a particular emphasis on how crop phenology and agricultural management practice influence the turbulent fluxes exchanged with the atmosphere, and the underlying water and carbon pools. A part of the uncertainty in these models is related to the many parameters included in the models' equations. In this study, we quantify the parameter-based uncertainty in the simulation of sugar cane biomass production with the agro-LSM ORCHIDEE-STICS on a multi-regional approach with data from sites in Australia, La Reunion and Brazil. First, the main source of uncertainty for the output variables NPP, GPP, and sensible heat flux (SH) is determined through a screening of the main parameters of the model on a multi-site basis leading to the selection of a subset of most sensitive parameters causing most of the uncertainty. In a second step, a sensitivity analysis is carried out on the parameters selected from the screening analysis at a regional scale. For this, a Monte-Carlo sampling method associated with the calculation of Partial Ranked Correlation Coefficients is used. First, we quantify the sensitivity of the output variables to individual input parameters on a regional scale for two regions of intensive sugar cane cultivation in Australia and Brazil. Then, we quantify the overall uncertainty in the simulation's outputs propagated from the uncertainty in the input parameters. Seven parameters are identified by the screening procedure as driving most of the uncertainty in the agro-LSM ORCHIDEE-STICS model output at all sites. These parameters control photosynthesis (optimal temperature of photosynthesis, optimal carboxylation rate), radiation interception (extinction coefficient), root
Classical interaction model for the water molecule.
Baranyai, András; Bartók, Albert
2007-05-14
The authors propose a new classical model for the water molecule. The geometry of the molecule is built on the rigid TIP5P model and has the experimental gas phase dipole moment of water created by four equal point charges. The model preserves its rigidity but the size of the charges increases or decreases following the electric field created by the rest of the molecules. The polarization is expressed by an electric field dependent nonlinear polarization function. The increasing dipole of the molecule slightly increases the size of the water molecule expressed by the oxygen-centered sigma parameter of the Lennard-Jones interaction. After refining the adjustable parameters, the authors performed Monte Carlo simulations to check the ability of the new model in the ice, liquid, and gas phases. They determined the density and internal energy of several ice polymorphs, liquid water, and gaseous water and calculated the heat capacity, the isothermal compressibility, the isobar heat expansion coefficients, and the dielectric constant of ambient water. They also determined the pair-correlation functions of ambient water and calculated the energy of the water dimer. The accuracy of theirs results was satisfactory.
Parameter Optimisation for the Behaviour of Elastic Models over Time
DEFF Research Database (Denmark)
Mosegaard, Jesper
2004-01-01
Optimisation of parameters for elastic models is essential for comparison or finding equivalent behaviour of elastic models when parameters cannot simply be transferred or converted. This is the case with a large range of commonly used elastic models. In this paper we present a general method...... that will optimise parameters based on the behaviour of the elastic models over time....
Model Identification of Linear Parameter Varying Aircraft Systems
Fujimore, Atsushi; Ljung, Lennart
2007-01-01
This article presents a parameter estimation of continuous-time polytopic models for a linear parameter varying (LPV) system. The prediction error method of linear time invariant (LTI) models is modified for polytopic models. The modified prediction error method is applied to an LPV aircraft system whose varying parameter is the flight velocity and model parameters are the stability and control derivatives (SCDs). In an identification simulation, the polytopic model is more suitable for expre...
Study on Effects of Diesel Engine Cooling System Parameters on Water Temperature
Institute of Scientific and Technical Information of China (English)
骆清国; 冯建涛; 刘国夫; 桂勇
2011-01-01
A simulation model for a certain diesel engine cooling system is set up by using GT-COOL. The backwater tem- perature response in different operating conditions is simulated numerically. The effects of single or multiple system parameters on the water temperature are analyzed. The results show that, changing different single parameters, the time taken for the steady backwater temperature is different, but relatively short; and if multiple parameters are changed, the time will be longer. Referred to the thermal balance test, the simulation results are validated and provide a basis for the intelligent con- trol of the cooling system.
Preliminary ECLSS waste water model
Carter, Donald L.; Holder, Donald W., Jr.; Alexander, Kevin; Shaw, R. G.; Hayase, John K.
1991-01-01
A preliminary waste water model for input to the Space Station Freedom (SSF) Environmental Control and Life Support System (ECLSS) Water Processor (WP) has been generated for design purposes. Data have been compiled from various ECLSS tests and flight sample analyses. A discussion of the characterization of the waste streams comprising the model is presented, along with a discussion of the waste water model and the rationale for the inclusion of contaminants in their respective concentrations. The major objective is to establish a methodology for the development of a waste water model and to present the current state of that model.
Preliminary ECLSS waste water model
Carter, Donald L.; Holder, Donald W., Jr.; Alexander, Kevin; Shaw, R. G.; Hayase, John K.
1991-01-01
A preliminary waste water model for input to the Space Station Freedom (SSF) Environmental Control and Life Support System (ECLSS) Water Processor (WP) has been generated for design purposes. Data have been compiled from various ECLSS tests and flight sample analyses. A discussion of the characterization of the waste streams comprising the model is presented, along with a discussion of the waste water model and the rationale for the inclusion of contaminants in their respective concentrations. The major objective is to establish a methodology for the development of a waste water model and to present the current state of that model.
Zare Abyaneh, Hamid
2014-01-01
This paper examined the efficiency of multivariate linear regression (MLR) and artificial neural network (ANN) models in prediction of two major water quality parameters in a wastewater treatment plant. Biochemical oxygen demand (BOD) and chemical oxygen demand (COD) as well as indirect indicators of organic matters are representative parameters for sewer water quality. Performance of the ANN models was evaluated using coefficient of correlation (r), root mean square error (RMSE) and bias values. The computed values of BOD and COD by model, ANN method and regression analysis were in close agreement with their respective measured values. Results showed that the ANN performance model was better than the MLR model. Comparative indices of the optimized ANN with input values of temperature (T), pH, total suspended solid (TSS) and total suspended (TS) for prediction of BOD was RMSE = 25.1 mg/L, r = 0.83 and for prediction of COD was RMSE = 49.4 mg/L, r = 0.81. It was found that the ANN model could be employed successfully in estimating the BOD and COD in the inlet of wastewater biochemical treatment plants. Moreover, sensitive examination results showed that pH parameter have more effect on BOD and COD predicting to another parameters. Also, both implemented models have predicted BOD better than COD.
Jiang, Xiaoli; Wang, Yinling; Li, Maoguo
2014-01-01
The solvent plays an important role in a given chemical reaction. Since most reaction in nature occur in the mixed-solvent systems, a comprehensive principle for solvent optimization was required. By calculating the Hansen solubility parameters (HSP) distance Ra , we designed a model experiment to explore the influence of mixed solvents on the chemical synthesis. The synthesis of polydopamine (PDA) in the water-alcohol system was chosen as model. As predicted, the well-dispersed PDA spheres w...
Soil-Related Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
A. J. Smith
2004-09-09
was defined as AP-SIII.9Q, ''Scientific Analyses''. This analysis revises the previous version with the same name (BSC 2003 [DIRS 161239]), which was itself a revision of one titled ''Evaluate Soil/Radionuclide Removal by Erosion and Leaching'' (CRWMS M&O 2001 [DIRS 152517]). In Revision 00 of this report, the data generated were fixed values (i.e., taking no account of uncertainty and variability). Revision 01 (BSC 2003 [DIRS 161239]) incorporated uncertainty and variability into the values for the bulk density, elemental partition coefficients, average annual loss of soil from erosion, resuspension enhancement factor, and field capacity water content. The current revision of this document improves the transparency and traceability of the products without changing the details of the analysis. This analysis report supports the treatment of six of the features, events, and processes (FEPs) applicable to the Yucca Mountain reference biosphere (DTN: MO0407SEPFEPLA.000 [DIRS 170760]). The use of the more recent FEP list in DTN: MO0407SEPFEPLA.000 [DIRS 170760] represents a deviation from the detail provided in the TWP (BSC 2004 [DIRS 169573]), which referenced a previous version of the FEP list. The parameters developed in this report support treatment of these six FEPs addressed in the biosphere model that are listed in Table 1-1. Inclusion and treatment of FEPs in the biosphere model is described in the ''Biosphere Model Report'' (BSC 2004 [DIRS 169460], Section 6.2).
Transfer function modeling of damping mechanisms in distributed parameter models
Slater, J. C.; Inman, D. J.
1994-01-01
This work formulates a method for the modeling of material damping characteristics in distributed parameter models which may be easily applied to models such as rod, plate, and beam equations. The general linear boundary value vibration equation is modified to incorporate hysteresis effects represented by complex stiffness using the transfer function approach proposed by Golla and Hughes. The governing characteristic equations are decoupled through separation of variables yielding solutions similar to those of undamped classical theory, allowing solution of the steady state as well as transient response. Example problems and solutions are provided demonstrating the similarity of the solutions to those of the classical theories and transient responses of nonviscous systems.
Directory of Open Access Journals (Sweden)
Shaharudin Nuraida
2017-01-01
Full Text Available An adequate supply of safe drinking water is one of major ways to obtain healthy life. Water filter system is one way to improve the water quality. However, to maintain the performance of the system, it need to undergo the maintenance service. This study evaluate the requirement of maintenance service in water filter system. Water quality was measured before and after maintenance service. Parameters measured were pH, turbidity, residual chlorine, nitrate and heavy metals and these parameters were compared with National Drinking Water Quality Standards. Collection of data were involved three housing areas in Johor. The quality of drinking water from water filter system were analysed using pH meter, turbidity meter, DR6000 and Inductively Coupled Plasma-Mass Spectrometer. pH value was increased from 16.4% for before maintenance services to 30.7% for after maintenance service. Increment of removal percentage for turbidity, residual chlorine and nitrate after maintenance were 21.5, 13.6 and 26.7, respectively. This result shows that maintenance service enhance the performance of the system. However, less significant of maintenance service for enhance the removal of heavy metals which the increment of removal percentage in range 0.3 to 9.8. Only aluminium shows percentage removal for after maintenance with 92.8% lower compared to before maintenance service with 95.5%.
On the modeling of internal parameters in hyperelastic biological materials
Giantesio, Giulia
2016-01-01
This paper concerns the behavior of hyperelastic energies depending on an internal parameter. First, the situation in which the internal parameter is a function of the gradient of the deformation is presented. Second, two models where the parameter describes the activation of skeletal muscle tissue are analyzed. In those models, the activation parameter depends on the strain and it is important to consider the derivative of the parameter with respect to the strain in order to capture the proper behavior of the stress.
Luo, Ning; Illman, Walter A.
2016-09-01
Analyses are presented of long-term hydrographs perturbed by variable pumping/injection events in a confined aquifer at a municipal water-supply well field in the Region of Waterloo, Ontario (Canada). Such records are typically not considered for aquifer test analysis. Here, the water-level variations are fingerprinted to pumping/injection rate changes using the Theis model implemented in the WELLS code coupled with PEST. Analyses of these records yield a set of transmissivity ( T) and storativity ( S) estimates between each monitoring and production borehole. These individual estimates are found to poorly predict water-level variations at nearby monitoring boreholes not used in the calibration effort. On the other hand, the geometric means of the individual T and S estimates are similar to those obtained from previous pumping tests conducted at the same site and adequately predict water-level variations in other boreholes. The analyses reveal that long-term municipal water-level records are amenable to analyses using a simple analytical solution to estimate aquifer parameters. However, uniform parameters estimated with analytical solutions should be considered as first rough estimates. More accurate hydraulic parameters should be obtained by calibrating a three-dimensional numerical model that rigorously captures the complexities of the site with these data.
Coupled 1D-2D hydrodynamic inundation model for sewer overflow: Influence of modeling parameters
Directory of Open Access Journals (Sweden)
Adeniyi Ganiyu Adeogun
2015-10-01
Full Text Available This paper presents outcome of our investigation on the influence of modeling parameters on 1D-2D hydrodynamic inundation model for sewer overflow, developed through coupling of an existing 1D sewer network model (SWMM and 2D inundation model (BREZO. The 1D-2D hydrodynamic model was developed for the purpose of examining flood incidence due to surcharged water on overland surface. The investigation was carried out by performing sensitivity analysis on the developed model. For the sensitivity analysis, modeling parameters, such as mesh resolution Digital Elevation Model (DEM resolution and roughness were considered. The outcome of the study shows the model is sensitive to changes in these parameters. The performance of the model is significantly influenced, by the Manning's friction value, the DEM resolution and the area of the triangular mesh. Also, changes in the aforementioned modeling parameters influence the Flood characteristics, such as the inundation extent, the flow depth and the velocity across the model domain.
Modelling water temperature in TOXSWA
Jacobs, C.M.J.; Deneer, J.W.; Adriaanse, P.I.
2010-01-01
A reasonably accurate estimate of the water temperature is necessary for a good description of the degradation of plant protection products in water which is used in the surface water model TOXSWA. Based on a consideration of basic physical processes that describe the influence of weather on the
Directory of Open Access Journals (Sweden)
Y. Sun
2013-04-01
Full Text Available This study demonstrates the possibility of inverting hydrologic parameters using surface flux and runoff observations in version 4 of the Community Land Model (CLM4. Previous studies showed that surface flux and runoff calculations are sensitive to major hydrologic parameters in CLM4 over different watersheds, and illustrated the necessity and possibility of parameter calibration. Two inversion strategies, the deterministic least-square fitting and stochastic Markov-Chain Monte-Carlo (MCMC Bayesian inversion approaches, are evaluated by applying them to CLM4 at selected sites. The unknowns to be estimated include surface and subsurface runoff generation parameters and vadose zone soil water parameters. We find that using model parameters calibrated by the least-square fitting provides little improvements in the model simulations but the sampling-based stochastic inversion approaches are consistent – as more information comes in, the predictive intervals of the calibrated parameters become narrower and the misfits between the calculated and observed responses decrease. In general, parameters that are identified to be significant through sensitivity analyses and statistical tests are better calibrated than those with weak or nonlinear impacts on flux or runoff observations. Temporal resolution of observations has larger impacts on the results of inverse modeling using heat flux data than runoff data. Soil and vegetation cover have important impacts on parameter sensitivities, leading to different patterns of posterior distributions of parameters at different sites. Overall, the MCMC-Bayesian inversion approach effectively and reliably improves the simulation of CLM under different climates and environmental conditions. Bayesian model averaging of the posterior estimates with different reference acceptance probabilities can smooth the posterior distribution and provide more reliable parameter estimates, but at the expense of wider uncertainty
Model comparisons and genetic and environmental parameter ...
African Journals Online (AJOL)
arc
South African Journal of Animal Science 2005, 35 (1) ... Genetic and environmental parameters were estimated for pre- and post-weaning average daily gain ..... and BWT (and medium maternal genetic correlations) indicates that these traits ...
STUDY OF POND WATER QUALITY BY THE ASSESSMENT OF PHYSICOCHEMICAL PARAMETERS AND WATER QUALITY INDEX
Directory of Open Access Journals (Sweden)
Vinod Jena
2013-02-01
Full Text Available Water quality index (WQI is a dimensionless number that combines multiple water quality factors into a single number by normalizing values to subjective rating curves. Conventionally it has been used for evaluating the quality of water for water resources suchas rivers, streams and lakes, etc. The present work is aimed at assessing the Water Quality Index (W.Q.I ofpond water and the impact of human activities on it. Physicochemical parameters were monitored for the calculation of W.Q.I for the rainy, winter and summer seasons. The parameters namely pH, Total hardness, TDS,Calcium, Chloride, Sulphate, Sodium, Potassium, EC and DO values were within the permissible limits on the other hand total alkalinities and magnesium values were exceeding the permissible limits as prescribed by IndianStandards. However, the W.Q.I values in the present investigation were reported to be 83.43, 76.598 and 91.52 for different season indicating that the pond water quality is very poor and not totally safe for human consumption.
Jiang, Xiaoli; Wang, Yinling; Li, Maoguo
2014-08-01
The solvent plays an important role in a given chemical reaction. Since most reaction in nature occur in the mixed-solvent systems, a comprehensive principle for solvent optimization was required. By calculating the Hansen solubility parameters (HSP) distance Ra, we designed a model experiment to explore the influence of mixed solvents on the chemical synthesis. The synthesis of polydopamine (PDA) in the water-alcohol system was chosen as model. As predicted, the well-dispersed PDA spheres were obtained in selected solvents with smaller Ra values: methanol/water, ethanol/water and 2-propanol/water. In addition, the mixed solvent with smaller Ra values gave a higher conversion of dopamine. The strategy for mixed solvent selection is might be useful to choose optimal reaction media for efficient chemical synthesis.
Jiang, Xiaoli; Wang, Yinling; Li, Maoguo
2014-01-01
The solvent plays an important role in a given chemical reaction. Since most reaction in nature occur in the mixed-solvent systems, a comprehensive principle for solvent optimization was required. By calculating the Hansen solubility parameters (HSP) distance Ra, we designed a model experiment to explore the influence of mixed solvents on the chemical synthesis. The synthesis of polydopamine (PDA) in the water-alcohol system was chosen as model. As predicted, the well-dispersed PDA spheres were obtained in selected solvents with smaller Ra values: methanol/water, ethanol/water and 2-propanol/water. In addition, the mixed solvent with smaller Ravalues gave a higher conversion of dopamine. The strategy for mixed solvent selection is might be useful to choose optimal reaction media for efficient chemical synthesis. PMID:25317902
NEW DOCTORAL DEGREE Parameter estimation problem in the Weibull model
Marković, Darija
2009-01-01
In this dissertation we consider the problem of the existence of best parameters in the Weibull model, one of the most widely used statistical models in reliability theory and life data theory. Particular attention is given to a 3-parameter Weibull model. We have listed some of the many applications of this model. We have described some of the classical methods for estimating parameters of the Weibull model, two graphical methods (Weibull probability plot and hazard plot), and two analyt...
Modelling Soil Water Retention for Weed Seed Germination Sensitivity to Water Potential
Directory of Open Access Journals (Sweden)
W. John Bullied
2012-01-01
Full Text Available Soil water retention is important for the study of water availability to germinating weed seeds. Six soil water retention models (Campbell, Brooks-Corey, four- and five-parameter van Genuchten, Tani, and Russo with residual soil water parameter derivations were evaluated to describe water retention for weed seed germination at minimum threshold soil water potential for three hillslope positions. The Campbell, Brooks-Corey, and four-parameter van Genuchten model with modified or estimated forms of the residual parameter had superior but similar data fit. The Campbell model underestimated water retention at a potential less than −0.5 MPa for the upper hillslope that could result in underestimating seed germination. The Tani and Russo models overestimated water retention at a potential less than −0.1 MPa for all hillslope positions. Model selection and residual parameter specification are important for weed seed germination by representing water retention at the level of minimum threshold water potential for germination. Weed seed germination models driven by the hydrothermal soil environment rely on the best-fitting soil water retention model to produce dynamic predictions of seed germination.
Parameter optimization model in electrical discharge machining process
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
Electrical discharge machining (EDM) process, at present is still an experience process, wherein selected parameters are often far from the optimum, and at the same time selecting optimization parameters is costly and time consuming. In this paper,artificial neural network (ANN) and genetic algorithm (GA) are used together to establish the parameter optimization model. An ANN model which adapts Levenberg-Marquardt algorithm has been set up to represent the relationship between material removal rate (MRR) and input parameters, and GA is used to optimize parameters, so that optimization results are obtained. The model is shown to be effective, and MRR is improved using optimized machining parameters.
Hayek, Mohamed
2016-06-01
A general analytical model for one-dimensional transient vertical infiltration is presented. The model is based on a combination of the Brooks and Corey soil water retention function and a generalized hydraulic conductivity function. This leads to power law diffusivity and convective term for which the exponents are functions of the inverse of the pore size distribution index. Accordingly, the proposed analytical solution covers many existing realistic models in the literature. The general form of the analytical solution is simple and it expresses implicitly the depth as function of water content and time. It can be used to model infiltration through semi-infinite dry soils with prescribed water content or flux boundary conditions. Some mathematical expressions of practical importance are also derived. The general form solution is useful for comparison between models, validation of numerical solutions and for better understanding the effect of some hydraulic parameters. Based on the analytical expression, a complete inverse procedure which allows the estimation of the hydraulic parameters from water content measurements is presented.
Water Stress Projection Modeling
2016-09-01
facility. Stationing analysis done with climate forecasting in mind recognizes an unpredictable future, while striving to best prepare for the...to support additional growth. This attribute places a threshold ca- pacity on water supply and treatment, which may be related to treat- ment plant ...et al. 2013). 3.3 Military impacts reduced water Extreme weather events such as droughts, floods, snow, and ice storms have significant impacts on
Estimation of shape model parameters for 3D surfaces
DEFF Research Database (Denmark)
Erbou, Søren Gylling Hemmingsen; Darkner, Sune; Fripp, Jurgen;
2008-01-01
Statistical shape models are widely used as a compact way of representing shape variation. Fitting a shape model to unseen data enables characterizing the data in terms of the model parameters. In this paper a Gauss-Newton optimization scheme is proposed to estimate shape model parameters of 3D s...
Compositional modelling of distributed-parameter systems
Maschke, Bernhard; Schaft, van der Arjan; Lamnabhi-Lagarrigue, F.; Loría, A.; Panteley, E.
2005-01-01
The Hamiltonian formulation of distributed-parameter systems has been a challenging reserach area for quite some time. (A nice introduction, especially with respect to systems stemming from fluid dynamics, can be found in [26], where also a historical account is provided.) The identification of the
Parameter Estimation and Experimental Design in Groundwater Modeling
Institute of Scientific and Technical Information of China (English)
SUN Ne-zheng
2004-01-01
This paper reviews the latest developments on parameter estimation and experimental design in the field of groundwater modeling. Special considerations are given when the structure of the identified parameter is complex and unknown. A new methodology for constructing useful groundwater models is described, which is based on the quantitative relationships among the complexity of model structure, the identifiability of parameter, the sufficiency of data, and the reliability of model application.
A parameter model for dredge plume sediment source terms
Decrop, Boudewijn; De Mulder, Tom; Toorman, Erik; Sas, Marc
2017-01-01
The presented model allows for fast simulations of the near-field behaviour of overflow dredging plumes. Overflow dredging plumes occur when dredging vessels employ a dropshaft release system to discharge the excess sea water, which is pumped into the trailing suction hopper dredger (TSHD) along with the dredged sediments. The fine sediment fraction in the loaded water-sediment mixture does not fully settle before it reaches the overflow shaft. By consequence, the released water contains a fine sediment fraction of time-varying concentration. The sediment grain size is in the range of clays, silt and fine sand; the sediment concentration varies roughly between 10 and 200 g/l in most cases, peaking at even higher value with short duration. In order to assess the environmental impact of the increased turbidity caused by this release, plume dispersion predictions are often carried out. These predictions are usually executed with a large-scale model covering a complete coastal zone, bay, or estuary. A source term of fine sediments is implemented in the hydrodynamic model to simulate the fine sediment dispersion. The large-scale model mesh resolution and governing equations, however, do not allow to simulate the near-field plume behaviour in the vicinity of the ship hull and propellers. Moreover, in the near-field, these plumes are under influence of buoyancy forces and air bubbles. The initial distribution of sediments is therefore unknown and has to be based on crude assumptions at present. The initial (vertical) distribution of the sediment source is indeed of great influence on the final far-field plume dispersion results. In order to study this near-field behaviour, a highly-detailed computationally fluid dynamics (CFD) model was developed. This model contains a realistic geometry of a dredging vessel, buoyancy effects, air bubbles and propeller action, and was validated earlier by comparing with field measurements. A CFD model requires significant simulation times
Parameter sensitivity in satellite-gravity-constrained geothermal modelling
Pastorutti, Alberto; Braitenberg, Carla
2017-04-01
The use of satellite gravity data in thermal structure estimates require identifying the factors that affect the gravity field and are related to the thermal characteristics of the lithosphere. We propose a set of forward-modelled synthetics, investigating the model response in terms of heat flow, temperature, and gravity effect at satellite altitude. The sensitivity analysis concerns the parameters involved, as heat production, thermal conductivity, density and their temperature dependence. We discuss the effect of the horizontal smoothing due to heat conduction, the superposition of the bulk thermal effect of near-surface processes (e.g. advection in ground-water and permeable faults, paleoclimatic effects, blanketing by sediments), and the out-of equilibrium conditions due to tectonic transients. All of them have the potential to distort the gravity-derived estimates.We find that the temperature-conductivity relationship has a small effect with respect to other parameter uncertainties on the modelled temperature depth variation, surface heat flow, thermal lithosphere thickness. We conclude that the global gravity is useful for geothermal studies.
Bayesian approach to decompression sickness model parameter estimation.
Howle, L E; Weber, P W; Nichols, J M
2017-03-01
We examine both maximum likelihood and Bayesian approaches for estimating probabilistic decompression sickness model parameters. Maximum likelihood estimation treats parameters as fixed values and determines the best estimate through repeated trials, whereas the Bayesian approach treats parameters as random variables and determines the parameter probability distributions. We would ultimately like to know the probability that a parameter lies in a certain range rather than simply make statements about the repeatability of our estimator. Although both represent powerful methods of inference, for models with complex or multi-peaked likelihoods, maximum likelihood parameter estimates can prove more difficult to interpret than the estimates of the parameter distributions provided by the Bayesian approach. For models of decompression sickness, we show that while these two estimation methods are complementary, the credible intervals generated by the Bayesian approach are more naturally suited to quantifying uncertainty in the model parameters.
Experimental critical parameters of plutonium metal cylinders flooded with water
Energy Technology Data Exchange (ETDEWEB)
NONE
1996-07-01
Forty-nine critical configurations are reported for experiments involving arrays of 3 kg plutonium metal cylinders moderated and reflected by water. Thirty-four of these describe systems assembled in the laboratory, while 15 others are derived critical parameters inferred from 46 subcritical cases. The arrays included 2x2xN, N = 2, 3, 4, and 5, in one program and 3x3x3 configurations in a later study. All were three-dimensional, nearly square arrays with equal horizontal lattice spacings but a different vertical lattice spacing. Horizontal spacings ranged from units in contact to 180 mm center-to-center; and vertical spacings ranged from about 80 mm to almost 400 mm center-to-center. Several nearly-equilateral 3x3x3 arrays exhibit an extremely sensitive dependence upon horizontal separation for identical vertical spacings. A line array of unreflected and essentially unmoderated canned plutonium metal units appeared to be well subcritical based on measurements made to assure safety during the manual assembly operations. All experiments were performed at two widely separated times in the mid-1970s and early 1980s under two programs at the Rocky Flats Plant`s Critical Mass Laboratory.
Experimental critical parameters of plutonium metal cylinders flooded with water
Energy Technology Data Exchange (ETDEWEB)
NONE
1996-07-01
Forty-nine critical configurations are reported for experiments involving arrays of 3 kg plutonium metal cylinders moderated and reflected by water. Thirty-four of these describe systems assembled in the laboratory, while 15 others are derived critical parameters inferred from 46 subcritical cases. The arrays included 2x2xN, N = 2, 3, 4, and 5, in one program and 3x3x3 configurations in a later study. All were three-dimensional, nearly square arrays with equal horizontal lattice spacings but a different vertical lattice spacing. Horizontal spacings ranged from units in contact to 180 mm center-to-center; and vertical spacings ranged from about 80 mm to almost 400 mm center-to-center. Several nearly-equilateral 3x3x3 arrays exhibit an extremely sensitive dependence upon horizontal separation for identical vertical spacings. A line array of unreflected and essentially unmoderated canned plutonium metal units appeared to be well subcritical based on measurements made to assure safety during the manual assembly operations. All experiments were performed at two widely separated times in the mid-1970s and early 1980s under two programs at the Rocky Flats Plant`s Critical Mass Laboratory.
Diffusive parameters of tritiated water (HTO) and U in chalk
Energy Technology Data Exchange (ETDEWEB)
Descostes, M.; Gandois, O.; Frasca, B.; Radwan, J.; Juery, A. [CEA Saclay, DEN DANS DPC SECR Lab Radionuclides Migration Measurements and Modeling, 91 - Gif sur Yvette (France); Descostes, M. [Univ Evry, CNRS, UMR CEA 8587, Evry (France); Pili, E. [CEA Bruyeres le Chatel, DIF, 91 (France)
2009-06-15
Complete text of publication follows: The feasibility of aquifer storage and recovery systems (ASR) to counteract short and long term imbalances between freshwater supply and demand is currently investigated for the metropolitan area of Perth, Western Australia. During the planned injection of oxic excess water into a deep anoxic aquifer the water quality evolution will depend on the extent and structure of the physical and geochemical heterogeneity and reactivity of the aquifer. A detailed geochemical characterisation was undertaken to determine amount and type of sedimentary reductants within different lithological facies. The incubation of sediment samples from the target aquifer for {approx} 52 days enabled quantification of their oxygen (O{sub 2}) consumption and CO{sub 2} production [1]. Data analysis, in particular the identification of key redox and acid buffering processes, was under-pinned by hydrogeochemical modelling. Results showed that the average measured reductive capacities (MRC) towards O{sub 2} consumption increased from the sand facies, followed by the siltstone facies, and the mud-stone/shale facies. This approach identified pyrite (20 - 100%), sedimentary organic matter (SOM; 3 - 56%), siderite (3 - 28%) and Fe(II)- aluminosilicates (8 - 55%) as the main O{sub 2} reductants. Minute amounts of carbonate acted as buffering minerals, while a bounding pH of 3 indicated acid buffering by K-feldspar dissolution. The supernatants showed elevated aqueous concentrations of Ni, Cd and Pb to be a potential risk for the quality of the recovered water. [1] Hartog, Griffioen and Van der Weijden (2002) Environmental Science and Technology 36(11), 2338-2344
Parameter and Uncertainty Estimation in Groundwater Modelling
DEFF Research Database (Denmark)
Jensen, Jacob Birk
The data basis on which groundwater models are constructed is in general very incomplete, and this leads to uncertainty in model outcome. Groundwater models form the basis for many, often costly decisions and if these are to be made on solid grounds, the uncertainty attached to model results must...... be quantified. This study was motivated by the need to estimate the uncertainty involved in groundwater models.Chapter 2 presents an integrated surface/subsurface unstructured finite difference model that was developed and applied to a synthetic case study.The following two chapters concern calibration...... and uncertainty estimation. Essential issues relating to calibration are discussed. The classical regression methods are described; however, the main focus is on the Generalized Likelihood Uncertainty Estimation (GLUE) methodology. The next two chapters describe case studies in which the GLUE methodology...
Model parameters for representative wetland plant functional groups
Williams, Amber S.; Kiniry, James R.; Mushet, David M.; Smith, Loren M.; McMurry, Scott T.; Attebury, Kelly; Lang, Megan; McCarty, Gregory W.; Shaffer, Jill A.; Effland, William R.; Johnson, Mari-Vaughn V.
2017-01-01
Wetlands provide a wide variety of ecosystem services including water quality remediation, biodiversity refugia, groundwater recharge, and floodwater storage. Realistic estimation of ecosystem service benefits associated with wetlands requires reasonable simulation of the hydrology of each site and realistic simulation of the upland and wetland plant growth cycles. Objectives of this study were to quantify leaf area index (LAI), light extinction coefficient (k), and plant nitrogen (N), phosphorus (P), and potassium (K) concentrations in natural stands of representative plant species for some major plant functional groups in the United States. Functional groups in this study were based on these parameters and plant growth types to enable process-based modeling. We collected data at four locations representing some of the main wetland regions of the United States. At each site, we collected on-the-ground measurements of fraction of light intercepted, LAI, and dry matter within the 2013–2015 growing seasons. Maximum LAI and k variables showed noticeable variations among sites and years, while overall averages and functional group averages give useful estimates for multisite simulation modeling. Variation within each species gives an indication of what can be expected in such natural ecosystems. For P and K, the concentrations from highest to lowest were spikerush (Eleocharis macrostachya), reed canary grass (Phalaris arundinacea), smartweed (Polygonum spp.), cattail (Typha spp.), and hardstem bulrush (Schoenoplectus acutus). Spikerush had the highest N concentration, followed by smartweed, bulrush, reed canary grass, and then cattail. These parameters will be useful for the actual wetland species measured and for the wetland plant functional groups they represent. These parameters and the associated process-based models offer promise as valuable tools for evaluating environmental benefits of wetlands and for evaluating impacts of various agronomic practices in
Phase Equilibria of Water/CO2 and Water/n-Alkane Mixtures from Polarizable Models.
Jiang, Hao; Economou, Ioannis G; Panagiotopoulos, Athanassios Z
2017-02-16
Phase equilibria of water/CO2 and water/n-alkane mixtures over a range of temperatures and pressures were obtained from Monte Carlo simulations in the Gibbs ensemble. Three sets of Drude-type polarizable models for water, namely the BK3, GCP, and HBP models, were combined with a polarizable Gaussian charge CO2 (PGC) model to represent the water/CO2 mixture. The HBP water model describes hydrogen bonds between water and CO2 explicitly. All models underestimate CO2 solubility in water if standard combining rules are used for the dispersion interactions between water and CO2. With the dispersion parameters optimized to phase compositions, the BK3 and GCP models were able to represent the CO2 solubility in water, however, the water composition in CO2-rich phase is systematically underestimated. Accurate representation of compositions for both water- and CO2-rich phases cannot be achieved even after optimizing the cross interaction parameters. By contrast, accurate compositions for both water- and CO2-rich phases were obtained with hydrogen bonding parameters determined from the second virial coefficient for water/CO2. Phase equilibria of water/n-alkane mixtures were also studied using the HBP water and an exponenial-6 united-atom n-alkanes model. The dispersion interactions between water and n-alkanes were optimized to Henry's constants of methane and ethane in water. The HBP water and united-atom n-alkane models underestimate water content in the n-alkane-rich phase; this underestimation is likely due to the neglect of electrostatic and induction energies in the united-atom model.
Parameter redundancy in discrete state‐space and integrated models
McCrea, Rachel S.
2016-01-01
Discrete state‐space models are used in ecology to describe the dynamics of wild animal populations, with parameters, such as the probability of survival, being of ecological interest. For a particular parametrization of a model it is not always clear which parameters can be estimated. This inability to estimate all parameters is known as parameter redundancy or a model is described as nonidentifiable. In this paper we develop methods that can be used to detect parameter redundancy in discrete state‐space models. An exhaustive summary is a combination of parameters that fully specify a model. To use general methods for detecting parameter redundancy a suitable exhaustive summary is required. This paper proposes two methods for the derivation of an exhaustive summary for discrete state‐space models using discrete analogues of methods for continuous state‐space models. We also demonstrate that combining multiple data sets, through the use of an integrated population model, may result in a model in which all parameters are estimable, even though models fitted to the separate data sets may be parameter redundant. PMID:27362826
Parameter redundancy in discrete state-space and integrated models.
Cole, Diana J; McCrea, Rachel S
2016-09-01
Discrete state-space models are used in ecology to describe the dynamics of wild animal populations, with parameters, such as the probability of survival, being of ecological interest. For a particular parametrization of a model it is not always clear which parameters can be estimated. This inability to estimate all parameters is known as parameter redundancy or a model is described as nonidentifiable. In this paper we develop methods that can be used to detect parameter redundancy in discrete state-space models. An exhaustive summary is a combination of parameters that fully specify a model. To use general methods for detecting parameter redundancy a suitable exhaustive summary is required. This paper proposes two methods for the derivation of an exhaustive summary for discrete state-space models using discrete analogues of methods for continuous state-space models. We also demonstrate that combining multiple data sets, through the use of an integrated population model, may result in a model in which all parameters are estimable, even though models fitted to the separate data sets may be parameter redundant. © 2016 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
An automatic and effective parameter optimization method for model tuning
Directory of Open Access Journals (Sweden)
T. Zhang
2015-11-01
simulation results show that the optimum combination of these parameters determined using this method is able to improve the model's overall performance by 9 %. The proposed methodology and software framework can be easily applied to other GCMs to speed up the model development process, especially regarding unavoidable comprehensive parameter tuning during the model development stage.
Ternary interaction parameters in calphad solution models
Energy Technology Data Exchange (ETDEWEB)
Eleno, Luiz T.F., E-mail: luizeleno@usp.br [Universidade de Sao Paulo (USP), SP (Brazil). Instituto de Fisica; Schön, Claudio G., E-mail: schoen@usp.br [Universidade de Sao Paulo (USP), SP (Brazil). Computational Materials Science Laboratory. Department of Metallurgical and Materials Engineering
2014-07-01
For random, diluted, multicomponent solutions, the excess chemical potentials can be expanded in power series of the composition, with coefficients that are pressure- and temperature-dependent. For a binary system, this approach is equivalent to using polynomial truncated expansions, such as the Redlich-Kister series for describing integral thermodynamic quantities. For ternary systems, an equivalent expansion of the excess chemical potentials clearly justifies the inclusion of ternary interaction parameters, which arise naturally in the form of correction terms in higher-order power expansions. To demonstrate this, we carry out truncated polynomial expansions of the excess chemical potential up to the sixth power of the composition variables. (author)
Parks, Melissa
2014-01-01
Model-eliciting activities (MEAs) are not new to those in engineering or mathematics, but they were new to Melissa Parks. Model-eliciting activities are simulated real-world problems that integrate engineering, mathematical, and scientific thinking as students find solutions for specific scenarios. During this process, students generate solutions…
Parameter estimation and error analysis in environmental modeling and computation
Kalmaz, E. E.
1986-01-01
A method for the estimation of parameters and error analysis in the development of nonlinear modeling for environmental impact assessment studies is presented. The modular computer program can interactively fit different nonlinear models to the same set of data, dynamically changing the error structure associated with observed values. Parameter estimation techniques and sequential estimation algorithms employed in parameter identification and model selection are first discussed. Then, least-square parameter estimation procedures are formulated, utilizing differential or integrated equations, and are used to define a model for association of error with experimentally observed data.
Modeled ground water age distributions
Woolfenden, Linda R.; Ginn, Timothy R.
2009-01-01
The age of ground water in any given sample is a distributed quantity representing distributed provenance (in space and time) of the water. Conventional analysis of tracers such as unstable isotopes or anthropogenic chemical species gives discrete or binary measures of the presence of water of a given age. Modeled ground water age distributions provide a continuous measure of contributions from different recharge sources to aquifers. A numerical solution of the ground water age equation of Ginn (1999) was tested both on a hypothetical simplified one-dimensional flow system and under real world conditions. Results from these simulations yield the first continuous distributions of ground water age using this model. Complete age distributions as a function of one and two space dimensions were obtained from both numerical experiments. Simulations in the test problem produced mean ages that were consistent with the expected value at the end of the model domain for all dispersivity values tested, although the mean ages for the two highest dispersivity values deviated slightly from the expected value. Mean ages in the dispersionless case also were consistent with the expected mean ages throughout the physical model domain. Simulations under real world conditions for three dispersivity values resulted in decreasing mean age with increasing dispersivity. This likely is a consequence of an edge effect. However, simulations for all three dispersivity values tested were mass balanced and stable demonstrating that the solution of the ground water age equation can provide estimates of water mass density distributions over age under real world conditions.
Directory of Open Access Journals (Sweden)
Jonathan R Karr
2015-05-01
Full Text Available Whole-cell models that explicitly represent all cellular components at the molecular level have the potential to predict phenotype from genotype. However, even for simple bacteria, whole-cell models will contain thousands of parameters, many of which are poorly characterized or unknown. New algorithms are needed to estimate these parameters and enable researchers to build increasingly comprehensive models. We organized the Dialogue for Reverse Engineering Assessments and Methods (DREAM 8 Whole-Cell Parameter Estimation Challenge to develop new parameter estimation algorithms for whole-cell models. We asked participants to identify a subset of parameters of a whole-cell model given the model's structure and in silico "experimental" data. Here we describe the challenge, the best performing methods, and new insights into the identifiability of whole-cell models. We also describe several valuable lessons we learned toward improving future challenges. Going forward, we believe that collaborative efforts supported by inexpensive cloud computing have the potential to solve whole-cell model parameter estimation.
Parameter estimation of hydrologic models using data assimilation
Kaheil, Y. H.
2005-12-01
The uncertainties associated with the modeling of hydrologic systems sometimes demand that data should be incorporated in an on-line fashion in order to understand the behavior of the system. This paper represents a Bayesian strategy to estimate parameters for hydrologic models in an iterative mode. The paper presents a modified technique called localized Bayesian recursive estimation (LoBaRE) that efficiently identifies the optimum parameter region, avoiding convergence to a single best parameter set. The LoBaRE methodology is tested for parameter estimation for two different types of models: a support vector machine (SVM) model for predicting soil moisture, and the Sacramento Soil Moisture Accounting (SAC-SMA) model for estimating streamflow. The SAC-SMA model has 13 parameters that must be determined. The SVM model has three parameters. Bayesian inference is used to estimate the best parameter set in an iterative fashion. This is done by narrowing the sampling space by imposing uncertainty bounds on the posterior best parameter set and/or updating the "parent" bounds based on their fitness. The new approach results in fast convergence towards the optimal parameter set using minimum training/calibration data and evaluation of fewer parameter sets. The efficacy of the localized methodology is also compared with the previously used Bayesian recursive estimation (BaRE) algorithm.
Storm Water Management Model (SWMM)
EPA's Storm Water Management Model (SWMM) is used throughout the world for planning, analysis and design related to stormwater runoff, combined and sanitary sewers, and other drainage systems in urban areas.
Modelling Ballast Water Transport
Digital Repository Service at National Institute of Oceanography (India)
Jayakumar, S.; Babu, M.T.; Vethamony, P.
by toolbox, available in MIKE software, by predicting the water elevation using the four major constituents M2, S2, K1 and O1 at the coastal tidal stations Okha and Godia (International Hydrographic Bureau, Spec. Pub, Monaco). Subsequently the tidal...-gulf is the highest compared to that on the northern and southern coasts. References Panvelkar, J.S., Bendre, V.M. and A.S.Barve (1986). ?Software for harmonic and spectral analysis of tidal data?, Proc. 3rd Indian Conference on ocean engineering, IIT Bombay, Dec...
Estimation of Kinetic Parameters in an Automotive SCR Catalyst Model
DEFF Research Database (Denmark)
Åberg, Andreas; Widd, Anders; Abildskov, Jens;
2016-01-01
A challenge during the development of models for simulation of the automotive Selective Catalytic Reduction catalyst is the parameter estimation of the kinetic parameters, which can be time consuming and problematic. The parameter estimation is often carried out on small-scale reactor tests, or p...
Mirror symmetry for two parameter models, 2
Candelas, Philip; Katz, S; Morrison, Douglas Robert Ogston; Philip Candelas; Anamaria Font; Sheldon Katz; David R Morrison
1994-01-01
We describe in detail the space of the two K\\"ahler parameters of the Calabi--Yau manifold \\P_4^{(1,1,1,6,9)}[18] by exploiting mirror symmetry. The large complex structure limit of the mirror, which corresponds to the classical large radius limit, is found by studying the monodromy of the periods about the discriminant locus, the boundary of the moduli space corresponding to singular Calabi--Yau manifolds. A symplectic basis of periods is found and the action of the Sp(6,\\Z) generators of the modular group is determined. From the mirror map we compute the instanton expansion of the Yukawa couplings and the generalized N=2 index, arriving at the numbers of instantons of genus zero and genus one of each degree. We also investigate an SL(2,\\Z) symmetry that acts on a boundary of the moduli space.
Accuracy of Parameter Estimation in Gibbs Sampling under the Two-Parameter Logistic Model.
Kim, Seock-Ho; Cohen, Allan S.
The accuracy of Gibbs sampling, a Markov chain Monte Carlo procedure, was considered for estimation of item and ability parameters under the two-parameter logistic model. Memory test data were analyzed to illustrate the Gibbs sampling procedure. Simulated data sets were analyzed using Gibbs sampling and the marginal Bayesian method. The marginal…
On linear models and parameter identifiability in experimental biological systems.
Lamberton, Timothy O; Condon, Nicholas D; Stow, Jennifer L; Hamilton, Nicholas A
2014-10-07
A key problem in the biological sciences is to be able to reliably estimate model parameters from experimental data. This is the well-known problem of parameter identifiability. Here, methods are developed for biologists and other modelers to design optimal experiments to ensure parameter identifiability at a structural level. The main results of the paper are to provide a general methodology for extracting parameters of linear models from an experimentally measured scalar function - the transfer function - and a framework for the identifiability analysis of complex model structures using linked models. Linked models are composed by letting the output of one model become the input to another model which is then experimentally measured. The linked model framework is shown to be applicable to designing experiments to identify the measured sub-model and recover the input from the unmeasured sub-model, even in cases that the unmeasured sub-model is not identifiable. Applications for a set of common model features are demonstrated, and the results combined in an example application to a real-world experimental system. These applications emphasize the insight into answering "where to measure" and "which experimental scheme" questions provided by both the parameter extraction methodology and the linked model framework. The aim is to demonstrate the tools' usefulness in guiding experimental design to maximize parameter information obtained, based on the model structure.
CHAMP: Changepoint Detection Using Approximate Model Parameters
2014-06-01
positions as a Markov chain in which the transition probabilities are defined by the time since the last changepoint: p(τi+1 = t|τi = s) = g(t− s), (1...experimentally verified using artifi- cially generated data and are compared to those of Fearnhead and Liu [5]. 2 Related work Hidden Markov Models (HMMs) are...length α, and maximum number of particles M . Output: Viterbi path of changepoint times and models // Initialize data structures 1: max path, prev queue
Namysłowska-Wilczyńska, Barbara
2016-04-01
This paper presents selected results of research connected with the development of a (3D) geostatistical hydrogeochemical model of the Klodzko Drainage Basin, dedicated to the spatial and time variation in the selected quality parameters of underground water in the Klodzko water intake area (SW part of Poland). The research covers the period 2011÷2012. Spatial analyses of the variation in various quality parameters, i.e, contents of: ammonium ion [gNH4+/m3], NO3- (nitrate ion) [gNO3/m3], PO4-3 (phosphate ion) [gPO4-3/m3], total organic carbon C (TOC) [gC/m3], pH redox potential and temperature C [degrees], were carried out on the basis of the chemical determinations of the quality parameters of underground water samples taken from the wells in the water intake area. Spatial and time variation in the quality parameters was analyzed on the basis of archival data (period 1977÷1999) for 22 (pump and siphon) wells with a depth ranging from 9.5 to 38.0 m b.g.l., later data obtained (November 2011) from tests of water taken from 14 existing wells. The wells were built in the years 1954÷1998. The water abstraction depth (difference between the terrain elevation and the dynamic water table level) is ranged from 276÷286 m a.s.l., with an average of 282.05 m a.s.l. Dynamic water table level is contained between 6.22 m÷16.44 m b.g.l., with a mean value of 9.64 m b.g.l. The latest data (January 2012) acquired from 3 new piezometers, with a depth of 9÷10m, which were made in other locations in the relevant area. Thematic databases, containing original data on coordinates X, Y (latitude, longitude) and Z (terrain elevation and time - years) and on regionalized variables, i.e. the underground water quality parameters in the Klodzko water intake area determined for different analytical configurations (22 wells, 14 wells, 14 wells + 3 piezometers), were created. Both archival data (acquired in the years 1977÷1999) and the latest data (collected in 2011÷2012) were analyzed
WINKLER'S SINGLE-PARAMETER SUBGRADE MODEL FROM ...
African Journals Online (AJOL)
Preferred Customer
[3, 9]. However, mainly due to the simplicity of Winkler's model in practical applications and .... this case, the coefficient B takes the dimension of a ... In plane-strain problems, the assumption of ... loaded circular region; s is the radial coordinate.
Spatial variability of the parameters of a semi-distributed hydrological model
de Lavenne, Alban; Thirel, Guillaume; Andréassian, Vazken; Perrin, Charles; Ramos, Maria-Helena
2016-05-01
Ideally, semi-distributed hydrologic models should provide better streamflow simulations than lumped models, along with spatially-relevant water resources management solutions. However, the spatial distribution of model parameters raises issues related to the calibration strategy and to the identifiability of the parameters. To analyse these issues, we propose to base the evaluation of a semi-distributed model not only on its performance at streamflow gauging stations, but also on the spatial and temporal pattern of the optimised value of its parameters. We implemented calibration over 21 rolling periods and 64 catchments, and we analysed how well each parameter is identified in time and space. Performance and parameter identifiability are analysed comparatively to the calibration of the lumped version of the same model. We show that the semi-distributed model faces more difficulties to identify stable optimal parameter sets. The main difficulty lies in the identification of the parameters responsible for the closure of the water balance (i.e. for the particular model investigated, the intercatchment groundwater flow parameter).
Improved Methodology for Parameter Inference in Nonlinear, Hydrologic Regression Models
Bates, Bryson C.
1992-01-01
A new method is developed for the construction of reliable marginal confidence intervals and joint confidence regions for the parameters of nonlinear, hydrologic regression models. A parameter power transformation is combined with measures of the asymptotic bias and asymptotic skewness of maximum likelihood estimators to determine the transformation constants which cause the bias or skewness to vanish. These optimized constants are used to construct confidence intervals and regions for the transformed model parameters using linear regression theory. The resulting confidence intervals and regions can be easily mapped into the original parameter space to give close approximations to likelihood method confidence intervals and regions for the model parameters. Unlike many other approaches to parameter transformation, the procedure does not use a grid search to find the optimal transformation constants. An example involving the fitting of the Michaelis-Menten model to velocity-discharge data from an Australian gauging station is used to illustrate the usefulness of the methodology.
Aturan Asosiasi Dengan Standar Storet Pada Model Prediksi Parameter Pendukung Uji Kualitas Air Baku
Directory of Open Access Journals (Sweden)
Diana Purwitasari
2015-04-01
Full Text Available Raw Water (Air Baku laboratory analysis is testing physical, chemical and bacteriological characteristicsof water to ensure that water supply is clean, safe and ready for drinking water quality. Analyzing raw water quality in laboratorium needs more time. The proposed system could shorten the laboratory processing time by analyzing daily water production log. Association ruleinthe proposed system was used to generate relation model of water characteristicsfrom the data log provided by local government owned water utilities (PDAM, Perusahaan Daerah Air Minum. The data was transformed first from numerical data into categorical data using STOrage and RETrieval Data Warehouse (STORETstandard.Generated model needs to be simplified because some prediction rules could have the same interpretation. The generated parameter prediction modelwas sufficient to be used as the supporting data for any local policy made related to water supply and sanitationwithout additional costs from standard lab testing of water quality. Some water quality values of chemical characteristics need lab testing. Given the missing values of several chemical characteristics, the generated parameter prediction model still could give better accuracy of 80%-95%. Since PDAM staffmanually validated the generated model, the experiments used small data set.
On retrial queueing model with fuzzy parameters
Ke, Jau-Chuan; Huang, Hsin-I.; Lin, Chuen-Horng
2007-01-01
This work constructs the membership functions of the system characteristics of a retrial queueing model with fuzzy customer arrival, retrial and service rates. The α-cut approach is used to transform a fuzzy retrial-queue into a family of conventional crisp retrial queues in this context. By means of the membership functions of the system characteristics, a set of parametric non-linear programs is developed to describe the family of crisp retrial queues. A numerical example is solved successfully to illustrate the validity of the proposed approach. Because the system characteristics are expressed and governed by the membership functions, more information is provided for use by management. By extending this model to the fuzzy environment, fuzzy retrial-queue is represented more accurately and analytic results are more useful for system designers and practitioners.
Solar parameters for modeling interplanetary background
Bzowski, M; Tokumaru, M; Fujiki, K; Quemerais, E; Lallement, R; Ferron, S; Bochsler, P; McComas, D J
2011-01-01
The goal of the Fully Online Datacenter of Ultraviolet Emissions (FONDUE) Working Team of the International Space Science Institute in Bern, Switzerland, was to establish a common calibration of various UV and EUV heliospheric observations, both spectroscopic and photometric. Realization of this goal required an up-to-date model of spatial distribution of neutral interstellar hydrogen in the heliosphere, and to that end, a credible model of the radiation pressure and ionization processes was needed. This chapter describes the solar factors shaping the distribution of neutral interstellar H in the heliosphere. Presented are the solar Lyman-alpha flux and the solar Lyman-alpha resonant radiation pressure force acting on neutral H atoms in the heliosphere, solar EUV radiation and the photoionization of heliospheric hydrogen, and their evolution in time and the still hypothetical variation with heliolatitude. Further, solar wind and its evolution with solar activity is presented in the context of the charge excha...
He, Minxue; Hogue, Terri S.; Franz, Kristie J.; Margulis, Steven A.; Vrugt, Jasper A.
2011-07-01
The current study evaluates the impacts of various sources of uncertainty involved in hydrologic modeling on parameter behavior and regionalization utilizing different Bayesian likelihood functions and the Differential Evolution Adaptive Metropolis (DREAM) algorithm. The developed likelihood functions differ in their underlying assumptions and treatment of error sources. We apply the developed method to a snow accumulation and ablation model (National Weather Service SNOW17) and generate parameter ensembles to predict snow water equivalent (SWE). Observational data include precipitation and air temperature forcing along with SWE measurements from 24 sites with diverse hydroclimatic characteristics. A multiple linear regression model is used to construct regionalization relationships between model parameters and site characteristics. Results indicate that model structural uncertainty has the largest influence on SNOW17 parameter behavior. Precipitation uncertainty is the second largest source of uncertainty, showing greater impact at wetter sites. Measurement uncertainty in SWE tends to have little impact on the final model parameters and resulting SWE predictions. Considering all sources of uncertainty, parameters related to air temperature and snowfall fraction exhibit the strongest correlations to site characteristics. Parameters related to the length of the melting period also show high correlation to site characteristics. Finally, model structural uncertainty and precipitation uncertainty dramatically alter parameter regionalization relationships in comparison to cases where only uncertainty in model parameters or output measurements is considered. Our results demonstrate that accurate treatment of forcing, parameter, model structural, and calibration data errors is critical for deriving robust regionalization relationships.
Hestir, E. L.; Greenberg, J. A.; Ustin, S. L.
2007-12-01
The Sacramento-San Joaquin River Delta is a highly turbid inland estuary that drains into the Pacific Ocean via the San Francisco Bay. The Delta has become a major ecological concern over the past decade, and the decline of the endangered fish, Delta smelt, has been attributed in part to decreasing turbidity in the Delta. Measuring and monitoring turbidity and Secchi disk depth are important to ecosystem health management and water quality monitoring of inland case-2 waters. The spectral determination of water quality parameters is dependent on (i) the inherent optical properties of water, such as the load of total suspended solids, suspended sediments, humic acids and dissolved organic matter, and planktonic content and composition, and (ii) the apparent optical properties of water which depend on both the medium and the geometric structure of light (surface reflectance, vertical diffuse attenuation). Water quality parameters such as turbidity and Secchi disk depth can be retrieved from hyperspectral remote sensing imagery, remote sensing data collected with many narrow spectral bands, using semi-empirical methods that require regression analysis, or from radiative transfer calculations that model apparent optical properties. We compared the accuracy of both semi-empirical and radiative transfer methods to retrieve turbidity and Secchi disk depths from airborne hyperspectral remote sensing imagery (the HyMap sensor, 450-2500 nm, 10-15nm bandwidth) of the Delta collected in June 2007. Results were validated using extensive field data collected concurrent with image acquisition. Additionally, we examined the effect of resampling the hyperspectral data to multispectral resolutions more commonly found on spaceborne instruments on the accuracy of water constituent retrieval from inland, case-2 waters.
Linear Sigma Models With Strongly Coupled Phases -- One Parameter Models
Hori, Kentaro
2013-01-01
We systematically construct a class of two-dimensional $(2,2)$ supersymmetric gauged linear sigma models with phases in which a continuous subgroup of the gauge group is totally unbroken. We study some of their properties by employing a recently developed technique. The focus of the present work is on models with one K\\"ahler parameter. The models include those corresponding to Calabi-Yau threefolds, extending three examples found earlier by a few more, as well as Calabi-Yau manifolds of other dimensions and non-Calabi-Yau manifolds. The construction leads to predictions of equivalences of D-brane categories, systematically extending earlier examples. There is another type of surprise. Two distinct superconformal field theories corresponding to Calabi-Yau threefolds with different Hodge numbers, $h^{2,1}=23$ versus $h^{2,1}=59$, have exactly the same quantum K\\"ahler moduli space. The strong-weak duality plays a crucial r\\^ole in confirming this, and also is useful in the actual computation of the metric on t...
Parameter identification in tidal models with uncertain boundaries
Bagchi, Arunabha; ten Brummelhuis, P.G.J.; ten Brummelhuis, Paul
1994-01-01
In this paper we consider a simultaneous state and parameter estimation procedure for tidal models with random inputs, which is formulated as a minimization problem. It is assumed that some model parameters are unknown and that the random noise inputs only act upon the open boundaries. The
Exploring the interdependencies between parameters in a material model.
Energy Technology Data Exchange (ETDEWEB)
Silling, Stewart Andrew; Fermen-Coker, Muge
2014-01-01
A method is investigated to reduce the number of numerical parameters in a material model for a solid. The basis of the method is to detect interdependencies between parameters within a class of materials of interest. The method is demonstrated for a set of material property data for iron and steel using the Johnson-Cook plasticity model.
An Alternative Three-Parameter Logistic Item Response Model.
Pashley, Peter J.
Birnbaum's three-parameter logistic function has become a common basis for item response theory modeling, especially within situations where significant guessing behavior is evident. This model is formed through a linear transformation of the two-parameter logistic function in order to facilitate a lower asymptote. This paper discusses an…
Parameter identification in tidal models with uncertain boundaries
Bagchi, Arunabha; Brummelhuis, ten Paul
1994-01-01
In this paper we consider a simultaneous state and parameter estimation procedure for tidal models with random inputs, which is formulated as a minimization problem. It is assumed that some model parameters are unknown and that the random noise inputs only act upon the open boundaries. The hyperboli
A compact cyclic plasticity model with parameter evolution
DEFF Research Database (Denmark)
Krenk, Steen; Tidemann, L.
2017-01-01
, and it is demonstrated that this simple formulation enables very accurate representation of experimental results. An extension of the theory to account for model parameter evolution effects, e.g. in the form of changing yield level, is included in the form of extended evolution equations for the model parameters...
Regionalization of SWAT Model Parameters for Use in Ungauged Watersheds
Directory of Open Access Journals (Sweden)
Indrajeet Chaubey
2010-11-01
Full Text Available There has been a steady shift towards modeling and model-based approaches as primary methods of assessing watershed response to hydrologic inputs and land management, and of quantifying watershed-wide best management practice (BMP effectiveness. Watershed models often require some degree of calibration and validation to achieve adequate watershed and therefore BMP representation. This is, however, only possible for gauged watersheds. There are many watersheds for which there are very little or no monitoring data available, thus the question as to whether it would be possible to extend and/or generalize model parameters obtained through calibration of gauged watersheds to ungauged watersheds within the same region. This study explored the possibility of developing regionalized model parameter sets for use in ungauged watersheds. The study evaluated two regionalization methods: global averaging, and regression-based parameters, on the SWAT model using data from priority watersheds in Arkansas. Resulting parameters were tested and model performance determined on three gauged watersheds. Nash-Sutcliffe efficiencies (NS for stream flow obtained using regression-based parameters (0.53–0.83 compared well with corresponding values obtained through model calibration (0.45–0.90. Model performance obtained using global averaged parameter values was also generally acceptable (0.4 ≤ NS ≤ 0.75. Results from this study indicate that regionalized parameter sets for the SWAT model can be obtained and used for making satisfactory hydrologic response predictions in ungauged watersheds.
Massanelli, J.; Meadows-McDonnell, M.; Konzelman, C.; Moon, J. B.; Kumar, A.; Thomas, J.; Pereira, A.; Naithani, K. J.
2016-12-01
Meeting agricultural water demands is becoming progressively difficult due to population growth and changes in climate. Breeding stress-resilient crops is a viable solution, as information about genetic variation and their role in stress tolerance is becoming available due to advancement in technology. In this study we screened eight diverse rice genotypes for photosynthetic capacity under greenhouse conditions. These include the Asian rice (Oryza sativa) genotypes, drought sensitive Nipponbare, and a transgenic line overexpressing the HYR gene in Nipponbare; six genotypes (Vandana, Bengal, Nagina-22, Glaberrima, Kaybonnet, Ai Chueh Ta Pai Ku) and an African rice O. glaberrima, all selected for varying levels of drought tolerance. We collected CO2 and light response curve data under well-watered and simulated drought conditions in greenhouse. From these curves we estimated photosynthesis model parameters, such as the maximum carboxylation rate (Vcmax), the maximum electron transport rate (Jmax), the maximum gross photosynthesis rate, daytime respiration (Rd), and quantum yield (f). Our results suggest that O. glaberrima and Nipponbare were the most sensitive to drought because Vcmax and Pgmax declined under drought conditions; other drought tolerant genotypes did not show significant changes in these model parameters. Our integrated approach, combining genetic information and photosynthesis modeling, shows promise to quantify drought response parameters and improve crop yield under drought stress conditions.
Institute of Scientific and Technical Information of China (English)
乐平; 杜志敏; 陈小凡; 朱苏阳; 贾虎
2015-01-01
It is well-known that barriers have a significant impact on the production performance of horizontal wells developed in a bottom water drive reservoir. In most cases, reservoir barriers are semi-permeable. Based on previous research on impermeable reservoir barrier, a mathematical flow model was derived for a horizontal well of a bottom water drive reservoir with a semi-permeable barrier. Besides, analytical equations were also presented to calculate critical parameters, such as production rate, pressure and potential difference. The effects of barrier, well and reservoir parameters on our model results were further investigated. The results show that the larger the barrier size is or the higher the barrier location is, the higher the critical production rate and potential difference of a horizontal well are. When the barrier permeability equals the formation permeability or the barrier width equals zero, the critical production rates converge to the values same to that of the case with no barrier. When the barrier permeability equals zero, the problem is regarded as a case of impermeable barrier. This model can be applied to predicting horizontal wells’ critical production parameters in reservoirs with semi-permeable barriers.
NWP model forecast skill optimization via closure parameter variations
Järvinen, H.; Ollinaho, P.; Laine, M.; Solonen, A.; Haario, H.
2012-04-01
We present results of a novel approach to tune predictive skill of numerical weather prediction (NWP) models. These models contain tunable parameters which appear in parameterizations schemes of sub-grid scale physical processes. The current practice is to specify manually the numerical parameter values, based on expert knowledge. We developed recently a concept and method (QJRMS 2011) for on-line estimation of the NWP model parameters via closure parameter variations. The method called EPPES ("Ensemble prediction and parameter estimation system") utilizes ensemble prediction infra-structure for parameter estimation in a very cost-effective way: practically no new computations are introduced. The approach provides an algorithmic decision making tool for model parameter optimization in operational NWP. In EPPES, statistical inference about the NWP model tunable parameters is made by (i) generating an ensemble of predictions so that each member uses different model parameter values, drawn from a proposal distribution, and (ii) feeding-back the relative merits of the parameter values to the proposal distribution, based on evaluation of a suitable likelihood function against verifying observations. In this presentation, the method is first illustrated in low-order numerical tests using a stochastic version of the Lorenz-95 model which effectively emulates the principal features of ensemble prediction systems. The EPPES method correctly detects the unknown and wrongly specified parameters values, and leads to an improved forecast skill. Second, results with an ensemble prediction system emulator, based on the ECHAM5 atmospheric GCM show that the model tuning capability of EPPES scales up to realistic models and ensemble prediction systems. Finally, preliminary results of EPPES in the context of ECMWF forecasting system are presented.
Bayesian estimation of parameters in a regional hydrological model
Directory of Open Access Journals (Sweden)
K. Engeland
2002-01-01
Full Text Available This study evaluates the applicability of the distributed, process-oriented Ecomag model for prediction of daily streamflow in ungauged basins. The Ecomag model is applied as a regional model to nine catchments in the NOPEX area, using Bayesian statistics to estimate the posterior distribution of the model parameters conditioned on the observed streamflow. The distribution is calculated by Markov Chain Monte Carlo (MCMC analysis. The Bayesian method requires formulation of a likelihood function for the parameters and three alternative formulations are used. The first is a subjectively chosen objective function that describes the goodness of fit between the simulated and observed streamflow, as defined in the GLUE framework. The second and third formulations are more statistically correct likelihood models that describe the simulation errors. The full statistical likelihood model describes the simulation errors as an AR(1 process, whereas the simple model excludes the auto-regressive part. The statistical parameters depend on the catchments and the hydrological processes and the statistical and the hydrological parameters are estimated simultaneously. The results show that the simple likelihood model gives the most robust parameter estimates. The simulation error may be explained to a large extent by the catchment characteristics and climatic conditions, so it is possible to transfer knowledge about them to ungauged catchments. The statistical models for the simulation errors indicate that structural errors in the model are more important than parameter uncertainties. Keywords: regional hydrological model, model uncertainty, Bayesian analysis, Markov Chain Monte Carlo analysis
Critical sustainability parameters in defluoridation of drinking water
DEFF Research Database (Denmark)
Bregnhøj, Henrik
Experiences from household and community defluoridation projects have been collected. They are presented in the form of critical parameters that need to be considered for the success of household defluoridation projects. Parameters are classified in three groups. Motivation of households seems to...
Influence of feed ingredients on water quality parameters in RAS
DEFF Research Database (Denmark)
2011-01-01
Although feed by far is providing the major input to RAS, relatively little is published about the correlation between feed composition and the resulting water quality in such systems. In a set-up with 6 identical RAS, each consisting of a fish tank (0.5 m3), a swirl separator, a submerged...... had impact on water quality in the systems as well as on matter removed by the swirl separators. In the RAS water, phosphorous (Ptot and Pdiss) concentrations were reduced by guar gum. Organic matter content (CODdiss) in the water was also reduced. Corresponding to this, more dry matter, more COD...... to the systems for 49 consecutive days. Each week, 24h-water samples (1 sample/hour) were collected from each system. The sludge collected in the swirl separator that day was also collected. Water and sludge were subsequently analysed for nitrogen, phosphorous and organic matter content. Inclusion of guar gum...
River water quality modelling: II
DEFF Research Database (Denmark)
Shanahan, P.; Henze, Mogens; Koncsos, L.
1998-01-01
The U.S. EPA QUAL2E model is currently the standard for river water quality modelling. While QUAL2E is adequate for the regulatory situation for which it was developed (the U.S. wasteload allocation process), there is a need for a more comprehensive framework for research and teaching. Moreover......, and to achieve robust model calibration. Mass balance problems arise from failure to account for mass in the sediment as well as in the water column and due to the fundamental imprecision of BOD as a state variable. (C) 1998 IAWQ Published by Elsevier Science Ltd. All rights reserved....
Quality assessment of water cycle parameters in REMO by radar-lidar synergy
Directory of Open Access Journals (Sweden)
B. Hennemuth
2008-01-01
Full Text Available A comparison study of water cycle parameters derived from ground-based remote-sensing instruments and from the regional model REMO is presented. Observational data sets were collected during three measuring campaigns in summer/autumn 2003 and 2004 at Richard Aßmann Observatory, Lindenberg, Germany. The remote sensing instruments which were used are differential absorption lidar, Doppler lidar, ceilometer, cloud radar, and micro rain radar for the derivation of humidity profiles, ABL height, water vapour flux profiles, cloud parameters, and rain rate. Additionally, surface latent and sensible heat flux and soil moisture were measured. Error ranges and representativity of the data are discussed. For comparisons the regional model REMO was run for all measuring periods with a horizontal resolution of 18 km and 33 vertical levels. Parameter output was every hour. The measured data were transformed to the vertical model grid and averaged in time in order to better match with gridbox model values. The comparisons show that the atmospheric boundary layer is not adequately simulated, on most days it is too shallow and too moist. This is found to be caused by a wrong partitioning of energy at the surface, particularly a too large latent heat flux. The reason is obviously an overestimation of soil moisture during drying periods by the one-layer scheme in the model. The profiles of water vapour transport within the ABL appear to be realistically simulated. The comparison of cloud cover reveals an underestimation of low-level and mid-level clouds by the model, whereas the comparison of high-level clouds is hampered by the inability of the cloud radar to see cirrus clouds above 10 km. Simulated ABL clouds apparently have a too low cloud base, and the vertical extent is underestimated. The ice water content of clouds agree in model and observation whereas the liquid water content is unsufficiently derived from cloud radar reflectivity in the present study
Quality assessment of water cycle parameters in REMO by Radar-Lidar synergy
Directory of Open Access Journals (Sweden)
B. Hennemuth
2007-06-01
Full Text Available A comparison study of water cycle parameters derived from ground-based remote-sensing instruments and from the regional model REMO is presented. Observational data sets were collected during three measuring campaigns in summer/autumn 2003 and 2004 at Richard Aßmann Observatory, Lindenberg, Germany. The remote sensing instruments which were used are differential absorption lidar, Doppler lidar, ceilometer, cloud radar, and micro rain radar for the derivation of humidity profiles, ABL height, water vapour flux profiles, cloud parameters, and rain rate. Additionally, surface latent and sensible heat flux and soil moisture were measured. Error ranges and representativity of the data are discussed. For comparisons the regional model REMO was run for all measuring periods with a horizontal resolution of 18 km and 33 vertical levels. Parameter output was every hour. The measured data were transformed to the vertical model grid and averaged in time in order to better fit with gridbox model values. The comparisons show that the atmospheric boundary layer is not adequately simulated, on most days it is too shallow and too moist. This is found to be caused by a wrong partitioning of energy at the surface, particularly a too large latent heat flux. The reason is obviously an overestimation of soil moisture during drying periods by the one-layer scheme in the model. The profiles of water vapour transport within the ABL appear to be realistically simulated. The comparison of cloud cover reveals an underestimation of low-level and mid-level clouds by the model, whereas the comparison of high-level clouds is hampered by the inability of the cloud radar to see cirrus clouds above 10 km. Simulated ABL clouds apparently have a too low cloud base, and the vertical extent is underestimated. The ice water content of clouds agree in model and observation whereas the liquid water content is unsufficiently derived from cloud radar reflectivity in the present study
Quality assessment of water cycle parameters in REMO by radar-lidar synergy
Hennemuth, B.; Weiss, A.; Bösenberg, J.; Jacob, D.; Linné, H.; Peters, G.; Pfeifer, S.
2008-01-01
A comparison study of water cycle parameters derived from ground-based remote-sensing instruments and from the regional model REMO is presented. Observational data sets were collected during three measuring campaigns in summer/autumn 2003 and 2004 at Richard Aßmann Observatory, Lindenberg, Germany. The remote sensing instruments which were used are differential absorption lidar, Doppler lidar, ceilometer, cloud radar, and micro rain radar for the derivation of humidity profiles, ABL height, water vapour flux profiles, cloud parameters, and rain rate. Additionally, surface latent and sensible heat flux and soil moisture were measured. Error ranges and representativity of the data are discussed. For comparisons the regional model REMO was run for all measuring periods with a horizontal resolution of 18 km and 33 vertical levels. Parameter output was every hour. The measured data were transformed to the vertical model grid and averaged in time in order to better match with gridbox model values. The comparisons show that the atmospheric boundary layer is not adequately simulated, on most days it is too shallow and too moist. This is found to be caused by a wrong partitioning of energy at the surface, particularly a too large latent heat flux. The reason is obviously an overestimation of soil moisture during drying periods by the one-layer scheme in the model. The profiles of water vapour transport within the ABL appear to be realistically simulated. The comparison of cloud cover reveals an underestimation of low-level and mid-level clouds by the model, whereas the comparison of high-level clouds is hampered by the inability of the cloud radar to see cirrus clouds above 10 km. Simulated ABL clouds apparently have a too low cloud base, and the vertical extent is underestimated. The ice water content of clouds agree in model and observation whereas the liquid water content is unsufficiently derived from cloud radar reflectivity in the present study. Rain rates are
Namysłowska-Wilczyńska, Barbara
2016-09-01
This paper presents selected results of research connected with the development of a (3D) geostatistical hydrogeochemical model of the Kłodzko Drainage Basin, dedicated to the spatial variation in the different quality parameters of underground water in the water intake area (SW part of Poland). The research covers the period 2011-2012. Spatial analyses of the variation in various quality parameters, i.e., contents of: iron, manganese, ammonium ion, nitrate ion, phosphate ion, total organic carbon, pH redox potential and temperature, were carried out on the basis of the chemical determinations of the quality parameters of underground water samples taken from the wells in the water intake area. Spatial variation in the parameters was analyzed on the basis of data obtained (November 2011) from tests of water taken from 14 existing wells with a depth ranging from 9.5 to 38.0 m b.g.l. The latest data (January 2012) were obtained (gained) from 3 new piezometers, made in other locations in the relevant area. A depth of these piezometers amounts to 9-10 m. Data derived from 14 wells (2011) and 14 wells + 3 piezometers (2012) were subjected to spatial analyses using geostatistical methods. The evaluation of basic statistics of the quality parameters, including their histograms of distributions, scatter diagrams and correlation coefficient values r were presented. The directional semivariogram function γ(h) and the ordinary (block) kriging procedure were used to build the 3D geostatistical model. The geostatistical parameters of the theoretical models of directional semivariograms of the water quality parameters under study, calculated along the wells depth (taking into account the terrain elevation), were used in the ordinary (block) kriging estimation. The obtained results of estimation, i.e., block diagrams allowed us to determine the levels of increased values of estimated averages Z* of underground water quality parameters.
Some tests for parameter constancy in cointegrated VAR-models
DEFF Research Database (Denmark)
Hansen, Henrik; Johansen, Søren
1999-01-01
Some methods for the evaluation of parameter constancy in vector autoregressive (VAR) models are discussed. Two different ways of re-estimating the VAR model are proposed; one in which all parameters are estimated recursively based upon the likelihood function for the first observations, and anot...... be applied to test the constancy of the long-run parameters in the cointegrated VAR-model. All results are illustrated using a model for the term structure of interest rates on US Treasury securities. ...
Spatio-temporal modeling of nonlinear distributed parameter systems
Li, Han-Xiong
2011-01-01
The purpose of this volume is to provide a brief review of the previous work on model reduction and identifi cation of distributed parameter systems (DPS), and develop new spatio-temporal models and their relevant identifi cation approaches. In this book, a systematic overview and classifi cation on the modeling of DPS is presented fi rst, which includes model reduction, parameter estimation and system identifi cation. Next, a class of block-oriented nonlinear systems in traditional lumped parameter systems (LPS) is extended to DPS, which results in the spatio-temporal Wiener and Hammerstein s
Directory of Open Access Journals (Sweden)
Baker Syed
2011-01-01
Full Text Available Abstract In systems biology, experimentally measured parameters are not always available, necessitating the use of computationally based parameter estimation. In order to rely on estimated parameters, it is critical to first determine which parameters can be estimated for a given model and measurement set. This is done with parameter identifiability analysis. A kinetic model of the sucrose accumulation in the sugar cane culm tissue developed by Rohwer et al. was taken as a test case model. What differentiates this approach is the integration of an orthogonal-based local identifiability method into the unscented Kalman filter (UKF, rather than using the more common observability-based method which has inherent limitations. It also introduces a variable step size based on the system uncertainty of the UKF during the sensitivity calculation. This method identified 10 out of 12 parameters as identifiable. These ten parameters were estimated using the UKF, which was run 97 times. Throughout the repetitions the UKF proved to be more consistent than the estimation algorithms used for comparison.
Baker, Syed Murtuza; Poskar, C Hart; Junker, Björn H
2011-10-11
In systems biology, experimentally measured parameters are not always available, necessitating the use of computationally based parameter estimation. In order to rely on estimated parameters, it is critical to first determine which parameters can be estimated for a given model and measurement set. This is done with parameter identifiability analysis. A kinetic model of the sucrose accumulation in the sugar cane culm tissue developed by Rohwer et al. was taken as a test case model. What differentiates this approach is the integration of an orthogonal-based local identifiability method into the unscented Kalman filter (UKF), rather than using the more common observability-based method which has inherent limitations. It also introduces a variable step size based on the system uncertainty of the UKF during the sensitivity calculation. This method identified 10 out of 12 parameters as identifiable. These ten parameters were estimated using the UKF, which was run 97 times. Throughout the repetitions the UKF proved to be more consistent than the estimation algorithms used for comparison.
The impact of physico-chemical water quality parameters on ...
African Journals Online (AJOL)
from water samples and PCR amplified using universal bacterial primer pairs. PCR products ... riorated due to constant disposal of industrial and domestic waste into the river. Salinisation .... to 16S rRNA sequences in the National Center of Biotechnology ..... composition in Central European running waters examined by.
Weigand, M.; Kemna, A.
2016-06-01
Spectral induced polarization (SIP) data are commonly analysed using phenomenological models. Among these models the Cole-Cole (CC) model is the most popular choice to describe the strength and frequency dependence of distinct polarization peaks in the data. More flexibility regarding the shape of the spectrum is provided by decomposition schemes. Here the spectral response is decomposed into individual responses of a chosen elementary relaxation model, mathematically acting as kernel in the involved integral, based on a broad range of relaxation times. A frequently used kernel function is the Debye model, but also the CC model with some other a priorly specified frequency dispersion (e.g. Warburg model) has been proposed as kernel in the decomposition. The different decomposition approaches in use, also including conductivity and resistivity formulations, pose the question to which degree the integral spectral parameters typically derived from the obtained relaxation time distribution are biased by the approach itself. Based on synthetic SIP data sampled from an ideal CC response, we here investigate how the two most important integral output parameters deviate from the corresponding CC input parameters. We find that the total chargeability may be underestimated by up to 80 per cent and the mean relaxation time may be off by up to three orders of magnitude relative to the original values, depending on the frequency dispersion of the analysed spectrum and the proximity of its peak to the frequency range limits considered in the decomposition. We conclude that a quantitative comparison of SIP parameters across different studies, or the adoption of parameter relationships from other studies, for example when transferring laboratory results to the field, is only possible on the basis of a consistent spectral analysis procedure. This is particularly important when comparing effective CC parameters with spectral parameters derived from decomposition results.
Parameters Estimation of Geographically Weighted Ordinal Logistic Regression (GWOLR) Model
Zuhdi, Shaifudin; Retno Sari Saputro, Dewi; Widyaningsih, Purnami
2017-06-01
A regression model is the representation of relationship between independent variable and dependent variable. The dependent variable has categories used in the logistic regression model to calculate odds on. The logistic regression model for dependent variable has levels in the logistics regression model is ordinal. GWOLR model is an ordinal logistic regression model influenced the geographical location of the observation site. Parameters estimation in the model needed to determine the value of a population based on sample. The purpose of this research is to parameters estimation of GWOLR model using R software. Parameter estimation uses the data amount of dengue fever patients in Semarang City. Observation units used are 144 villages in Semarang City. The results of research get GWOLR model locally for each village and to know probability of number dengue fever patient categories.
Universally sloppy parameter sensitivities in systems biology models.
Directory of Open Access Journals (Sweden)
Ryan N Gutenkunst
2007-10-01
Full Text Available Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a "sloppy" spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.
Tube-Load Model Parameter Estimation for Monitoring Arterial Hemodynamics
Directory of Open Access Journals (Sweden)
Guanqun eZhang
2011-11-01
Full Text Available A useful model of the arterial system is the uniform, lossless tube with parametric load. This tube-load model is able to account for wave propagation and reflection (unlike lumped-parameter models such as the Windkessel while being defined by only a few parameters (unlike comprehensive distributed-parameter models. As a result, the parameters may be readily estimated by accurate fitting of the model to available arterial pressure and flow waveforms so as to permit improved monitoring of arterial hemodynamics. In this paper, we review tube-load model parameter estimation techniques that have appeared in the literature for monitoring wave reflection, large artery compliance, pulse transit time, and central aortic pressure. We begin by motivating the use of the tube-load model for parameter estimation. We then describe the tube-load model, its assumptions and validity, and approaches for estimating its parameters. We next summarize the various techniques and their experimental results while highlighting their advantages over conventional techniques. We conclude the review by suggesting future research directions and describing potential applications.
Tube-Load Model Parameter Estimation for Monitoring Arterial Hemodynamics
Zhang, Guanqun; Hahn, Jin-Oh; Mukkamala, Ramakrishna
2011-01-01
A useful model of the arterial system is the uniform, lossless tube with parametric load. This tube-load model is able to account for wave propagation and reflection (unlike lumped-parameter models such as the Windkessel) while being defined by only a few parameters (unlike comprehensive distributed-parameter models). As a result, the parameters may be readily estimated by accurate fitting of the model to available arterial pressure and flow waveforms so as to permit improved monitoring of arterial hemodynamics. In this paper, we review tube-load model parameter estimation techniques that have appeared in the literature for monitoring wave reflection, large artery compliance, pulse transit time, and central aortic pressure. We begin by motivating the use of the tube-load model for parameter estimation. We then describe the tube-load model, its assumptions and validity, and approaches for estimating its parameters. We next summarize the various techniques and their experimental results while highlighting their advantages over conventional techniques. We conclude the review by suggesting future research directions and describing potential applications. PMID:22053157
Parameter estimation and investigation of a bolted joint model
Shiryayev, O. V.; Page, S. M.; Pettit, C. L.; Slater, J. C.
2007-11-01
Mechanical joints are a primary source of variability in the dynamics of built-up structures. Physical phenomena in the joint are quite complex and therefore too impractical to model at the micro-scale. This motivates the development of lumped parameter joint models with discrete interfaces so that they can be easily implemented in finite element codes. Among the most important considerations in choosing a model for dynamically excited systems is its ability to model energy dissipation. This translates into the need for accurate and reliable methods to measure model parameters and estimate their inherent variability from experiments. The adjusted Iwan model was identified as a promising candidate for representing joint dynamics. Recent research focused on this model has exclusively employed impulse excitation in conjunction with neural networks to identify the model parameters. This paper presents an investigation of an alternative parameter estimation approach for the adjusted Iwan model, which employs data from oscillatory forcing. This approach is shown to produce parameter estimates with precision similar to the impulse excitation method for a range of model parameters.
Modeling and Parameter Estimation of a Small Wind Generation System
Directory of Open Access Journals (Sweden)
Carlos A. Ramírez Gómez
2013-11-01
Full Text Available The modeling and parameter estimation of a small wind generation system is presented in this paper. The system consists of a wind turbine, a permanent magnet synchronous generator, a three phase rectifier, and a direct current load. In order to estimate the parameters wind speed data are registered in a weather station located in the Fraternidad Campus at ITM. Wind speed data were applied to a reference model programed with PSIM software. From that simulation, variables were registered to estimate the parameters. The wind generation system model together with the estimated parameters is an excellent representation of the detailed model, but the estimated model offers a higher flexibility than the programed model in PSIM software.
Parameter estimation of hidden periodic model in random fields
Institute of Scientific and Technical Information of China (English)
何书元
1999-01-01
Two-dimensional hidden periodic model is an important model in random fields. The model is used in the field of two-dimensional signal processing, prediction and spectral analysis. A method of estimating the parameters for the model is designed. The strong consistency of the estimators is proved.
Identification of parameters of discrete-continuous models
Energy Technology Data Exchange (ETDEWEB)
Cekus, Dawid, E-mail: cekus@imipkm.pcz.pl; Warys, Pawel, E-mail: warys@imipkm.pcz.pl [Institute of Mechanics and Machine Design Foundations, Czestochowa University of Technology, Dabrowskiego 73, 42-201 Czestochowa (Poland)
2015-03-10
In the paper, the parameters of a discrete-continuous model have been identified on the basis of experimental investigations and formulation of optimization problem. The discrete-continuous model represents a cantilever stepped Timoshenko beam. The mathematical model has been formulated and solved according to the Lagrange multiplier formalism. Optimization has been based on the genetic algorithm. The presented proceeding’s stages make the identification of any parameters of discrete-continuous systems possible.
Estimating parameters for generalized mass action models with connectivity information
Directory of Open Access Journals (Sweden)
Voit Eberhard O
2009-05-01
Full Text Available Abstract Background Determining the parameters of a mathematical model from quantitative measurements is the main bottleneck of modelling biological systems. Parameter values can be estimated from steady-state data or from dynamic data. The nature of suitable data for these two types of estimation is rather different. For instance, estimations of parameter values in pathway models, such as kinetic orders, rate constants, flux control coefficients or elasticities, from steady-state data are generally based on experiments that measure how a biochemical system responds to small perturbations around the steady state. In contrast, parameter estimation from dynamic data requires time series measurements for all dependent variables. Almost no literature has so far discussed the combined use of both steady-state and transient data for estimating parameter values of biochemical systems. Results In this study we introduce a constrained optimization method for estimating parameter values of biochemical pathway models using steady-state information and transient measurements. The constraints are derived from the flux connectivity relationships of the system at the steady state. Two case studies demonstrate the estimation results with and without flux connectivity constraints. The unconstrained optimal estimates from dynamic data may fit the experiments well, but they do not necessarily maintain the connectivity relationships. As a consequence, individual fluxes may be misrepresented, which may cause problems in later extrapolations. By contrast, the constrained estimation accounting for flux connectivity information reduces this misrepresentation and thereby yields improved model parameters. Conclusion The method combines transient metabolic profiles and steady-state information and leads to the formulation of an inverse parameter estimation task as a constrained optimization problem. Parameter estimation and model selection are simultaneously carried out
Classical nucleation theory of homogeneous freezing of water: thermodynamic and kinetic parameters.
Ickes, Luisa; Welti, André; Hoose, Corinna; Lohmann, Ulrike
2015-02-28
The probability of homogeneous ice nucleation under a set of ambient conditions can be described by nucleation rates using the theoretical framework of Classical Nucleation Theory (CNT). This framework consists of kinetic and thermodynamic parameters, of which three are not well-defined (namely the interfacial tension between ice and water, the activation energy and the prefactor), so that any CNT-based parameterization of homogeneous ice formation is less well-constrained than desired for modeling applications. Different approaches to estimate the thermodynamic and kinetic parameters of CNT are reviewed in this paper and the sensitivity of the calculated nucleation rate to the choice of parameters is investigated. We show that nucleation rates are very sensitive to this choice. The sensitivity is governed by one parameter - the interfacial tension between ice and water, which determines the energetic barrier of the nucleation process. The calculated nucleation rate can differ by more than 25 orders of magnitude depending on the choice of parameterization for this parameter. The second most important parameter is the activation energy of the nucleation process. It can lead to a variation of 16 orders of magnitude. By estimating the nucleation rate from a collection of droplet freezing experiments from the literature, the dependence of these two parameters on temperature is narrowed down. It can be seen that the temperature behavior of these two parameters assumed in the literature does not match with the predicted nucleation rates from the fit in most cases. Moreover a comparison of all possible combinations of theoretical parameterizations of the dominant two free parameters shows that one combination fits the fitted nucleation rates best, which is a description of the interfacial tension coming from a molecular model [Reinhardt and Doye, J. Chem. Phys., 2013, 139, 096102] in combination with the activation energy derived from self-diffusion measurements [Zobrist
40 CFR 141.87 - Monitoring requirements for water quality parameters.
2010-07-01
... 40 Protection of Environment 22 2010-07-01 2010-07-01 false Monitoring requirements for water... § 141.87 Monitoring requirements for water quality parameters. All large water systems, and all small... representative of water quality and treatment conditions throughout the system. (d) Monitoring after State...
Institute of Scientific and Technical Information of China (English)
WANG; Xin; CHENG; Qikang; GAO; Cai; YANG; Pengfei; HUA; Tse
2005-01-01
Fibroblast is a crucial kind of cell in the construction of the tissue engineered dermal equivalent. In order to optimize the cryopreservation protocols of the tissue- engineered dermis, the characteristics of dermal fibroblast in subzero temperatures are required, which include the water permeability of the cell membrane and the apparent activation energy. Using the differential scanning calorimeter (DSC), the volumetric shrinkage during freezing of human dermal fibroblast suspensions was obtained at the cooling rate of 5℃·min-1 in the presence of extracellular ice. To ensure the presence of extracellular ice, a small quantity of ice nucleation bacteria (INA bacteria), pseudomonas syringae was added in the samples. And based on the Karlsson's model, a nonlinear- least-squares curve fitting technique was implemented to calculate the cryogenic parameters. At the reference temperature TR (= 0℃), the water permeability of membrane Lpg = 0.578μm·min-1·atm-1 and the apparent activation energy ELP = 308.8 kJ·mol-1. These parameters were then used to simulate water transport of fibroblast during constant cooling at rates between 0.01―50℃·min-1. The simulation results were analyzed to predict the amount of water left in the cell after dehydration and the "optimal cooling rate" for fibroblast cryopreservation. For the dermal fibroblast with DMEM solution, a cooling rate of 4.6℃·min-1 was optimal.
de C. Teixeira, Antônio H.; Lopes, Hélio L.; Hernandez, Fernando B. T.; Scherer-Warren, Morris; Andrade, Ricardo G.; Neale, Christopher M. U.
2013-10-01
The Nilo Coelho irrigation scheme, located in the semi-arid region of Brazil, is highlighted as an important agricultural irrigated perimeter. Considering the scenario of this fast land use change, the development and application of suitable tools to quantify the trends of the water productivity parameters on a large scale is important. To analyse the effects of land use change within this perimeter, the large-scale values of biomass production (BIO) and actual evapotranspiration (ET) were quantified from 1992 to 2011, under the naturally driest conditions along the year. Monteith's radiation model was applied for estimating the absorbed photosynthetically active radiation (APAR), while the SAFER (Simple Algorithm For Evapotranspiration Retrieving) algorithm was used to retrieve ET. The highest incremental BIO values happened during the years of 1999 and 2005, as a result of the increased agricultural area under production inside the perimeter, when the average differences between irrigated crops and natural vegetation were more than 70 kg ha-1 d-1. Comparing the average ET rates of 1992 (1.6 mm d-1) with those for 2011 (3.1 mm d-1), it was verified that the extra water consumption doubled because of the increments of irrigated areas along the years. More uniformity along the years on both water productivity parameters occurred for natural vegetation, evidenced by the lower values of standard deviation when comparing to irrigated crops. The heterogeneity of ET values under irrigation conditions are due to the different species, crop stages, cultural and water managements.
Semiempirical model of soil water hysteresis
Nimmo, J.R.
1992-01-01
In order to represent hysteretic soil water retention curves accurately using as few measurements as possible, a new semiempirical model has been developed. It has two postulates related to physical characteristics of the medium, and two parameters, each with a definite physical interpretation, whose values are determined empirically for a given porous medium. Tests of the model show that it provides high-quality optimized fits to measured water content vs. matric pressure wetting curves for a wide variety of media. A practical use of this model is to provide a complete simulated main wetting curve for a medium where only a main drying curve and two points on the wetting curve have been measured. -from Author
Multi-objective global sensitivity analysis of the WRF model parameters
Quan, Jiping; Di, Zhenhua; Duan, Qingyun; Gong, Wei; Wang, Chen
2015-04-01
Tuning model parameters to match model simulations with observations can be an effective way to enhance the performance of numerical weather prediction (NWP) models such as Weather Research and Forecasting (WRF) model. However, this is a very complicated process as a typical NWP model involves many model parameters and many output variables. One must take a multi-objective approach to ensure all of the major simulated model outputs are satisfactory. This talk presents the results of an investigation of multi-objective parameter sensitivity analysis of the WRF model to different model outputs, including conventional surface meteorological variables such as precipitation, surface temperature, humidity and wind speed, as well as atmospheric variables such as total precipitable water, cloud cover, boundary layer height and outgoing long radiation at the top of the atmosphere. The goal of this study is to identify the most important parameters that affect the predictive skill of short-range meteorological forecasts by the WRF model. The study was performed over the Greater Beijing Region of China. A total of 23 adjustable parameters from seven different physical parameterization schemes were considered. Using a multi-objective global sensitivity analysis method, we examined the WRF model parameter sensitivities to the 5-day simulations of the aforementioned model outputs. The results show that parameter sensitivities vary with different model outputs. But three to four of the parameters are shown to be sensitive to all model outputs considered. The sensitivity results from this research can be the basis for future model parameter optimization of the WRF model.
Seasonal variations of water and sediment quality parameters in ...
African Journals Online (AJOL)
2012-10-16
Oct 16, 2012 ... Reed pans, classified as a particular type of pan, are usually defined as pans ..... in these systems (Grundling and Dada, 1999; Richards, 2001;. Grundling et .... and Ecological Water Requirements (Quantity) Workshop Report.
Centrifuge modeling of one-step outflow tests for unsaturated parameter estimations
Directory of Open Access Journals (Sweden)
H. Nakajima
2006-01-01
Full Text Available Centrifuge modeling of one-step outflow tests were carried out using a 2-m radius geotechnical centrifuge, and the cumulative outflow and transient pore water pressure were measured during the tests at multiple gravity levels. Based on the scaling laws of centrifuge modeling, the measurements generally showed reasonable agreement with prototype data calculated from forward simulations with input parameters determined from standard laboratory tests. The parameter optimizations were examined for three different combinations of input data sets using the test measurements. Within the gravity level examined in this study up to 40g, the optimized unsaturated parameters compared well when accurate pore water pressure measurements were included along with cumulative outflow as input data. With its capability to implement variety of instrumentations under well controlled initial and boundary conditions and to shorten testing time, the centrifuge modeling technique is attractive as an alternative experimental method that provides more freedom to set inverse problem conditions for the parameter estimation.
Towards predictive food process models: A protocol for parameter estimation.
Vilas, Carlos; Arias-Méndez, Ana; Garcia, Miriam R; Alonso, Antonio A; Balsa-Canto, E
2016-05-31
Mathematical models, in particular, physics-based models, are essential tools to food product and process design, optimization and control. The success of mathematical models relies on their predictive capabilities. However, describing physical, chemical and biological changes in food processing requires the values of some, typically unknown, parameters. Therefore, parameter estimation from experimental data is critical to achieving desired model predictive properties. This work takes a new look into the parameter estimation (or identification) problem in food process modeling. First, we examine common pitfalls such as lack of identifiability and multimodality. Second, we present the theoretical background of a parameter identification protocol intended to deal with those challenges. And, to finish, we illustrate the performance of the proposed protocol with an example related to the thermal processing of packaged foods.
Estimation of the input parameters in the Feller neuronal model
Ditlevsen, Susanne; Lansky, Petr
2006-06-01
The stochastic Feller neuronal model is studied, and estimators of the model input parameters, depending on the firing regime of the process, are derived. Closed expressions for the first two moments of functionals of the first-passage time (FTP) through a constant boundary in the suprathreshold regime are derived, which are used to calculate moment estimators. In the subthreshold regime, the exponentiality of the FTP is utilized to characterize the input parameters. The methods are illustrated on simulated data. Finally, approximations of the first-passage-time moments are suggested, and biological interpretations and comparisons of the parameters in the Feller and the Ornstein-Uhlenbeck models are discussed.
An automatic and effective parameter optimization method for model tuning
Directory of Open Access Journals (Sweden)
T. Zhang
2015-05-01
Full Text Available Physical parameterizations in General Circulation Models (GCMs, having various uncertain parameters, greatly impact model performance and model climate sensitivity. Traditional manual and empirical tuning of these parameters is time consuming and ineffective. In this study, a "three-step" methodology is proposed to automatically and effectively obtain the optimum combination of some key parameters in cloud and convective parameterizations according to a comprehensive objective evaluation metrics. Different from the traditional optimization methods, two extra steps, one determines parameter sensitivity and the other chooses the optimum initial value of sensitive parameters, are introduced before the downhill simplex method to reduce the computational cost and improve the tuning performance. Atmospheric GCM simulation results show that the optimum combination of these parameters determined using this method is able to improve the model's overall performance by 9%. The proposed methodology and software framework can be easily applied to other GCMs to speed up the model development process, especially regarding unavoidable comprehensive parameters tuning during the model development stage.
Optimal parameters for the FFA-Beddoes dynamic stall model
Energy Technology Data Exchange (ETDEWEB)
Bjoerck, A.; Mert, M. [FFA, The Aeronautical Research Institute of Sweden, Bromma (Sweden); Madsen, H.A. [Risoe National Lab., Roskilde (Denmark)
1999-03-01
Unsteady aerodynamic effects, like dynamic stall, must be considered in calculation of dynamic forces for wind turbines. Models incorporated in aero-elastic programs are of semi-empirical nature. Resulting aerodynamic forces therefore depend on values used for the semi-empiricial parameters. In this paper a study of finding appropriate parameters to use with the Beddoes-Leishman model is discussed. Minimisation of the `tracking error` between results from 2D wind tunnel tests and simulation with the model is used to find optimum values for the parameters. The resulting optimum parameters show a large variation from case to case. Using these different sets of optimum parameters in the calculation of blade vibrations, give rise to quite different predictions of aerodynamic damping which is discussed. (au)
The EPANET water quality model
Energy Technology Data Exchange (ETDEWEB)
Rossman, L.A. [Environmental Protection Agency, Cincinnati, OH (United States)
1995-10-01
EPANET is a software package developed by US EPA`s Drinking Water Research Division for modeling hydraulic and water quality behavior within water distribution systems. Starting with a geometric description of the pipe network, a set of initial conditions, estimates of water usage, and a set of rules for how the system is operated, EPANET predicts all flows, pressures, and water quality levels throughout the network during an extended period of operation. In addition to substance concentration, water age and source tracing can also be simulated. EPANET offers a number of advanced features including: modular, highly portable C language code with no pre-set limits on network size; a simple data input format based on a problem oriented language; a full-featured hydraulic simulator; improved water quality algorithms; analysis of water quality reactions both within the bulk flow and at the pipe wall; an optional graphical user interface running under Microsoft{reg_sign} Windows{trademark}. The Windows user interface allows one to edit EPANET input files, run a simulation, and view the results all within a single program. Simulation output can be visualized through: color-coded maps of the distribution system with full zooming, panning and labeling capabilities and a slider control to move forward or backward through time; spreadsheet-like tables that can be searched for entries meeting a specified criterion; and time series graphs of both predicted and observed values for any variable at any location in the network. EPANET is currently being used to analyze a number of water quality issues in different distribution systems across the country. These include: chlorine decay dynamics, raw water source blending, altered tank operation, and integration with real-time monitoring and control systems.
Water Distribution and Removal Model
Energy Technology Data Exchange (ETDEWEB)
Y. Deng; N. Chipman; E.L. Hardin
2005-08-26
The design of the Yucca Mountain high level radioactive waste repository depends on the performance of the engineered barrier system (EBS). To support the total system performance assessment (TSPA), the Engineered Barrier System Degradation, Flow, and Transport Process Model Report (EBS PMR) is developed to describe the thermal, mechanical, chemical, hydrological, biological, and radionuclide transport processes within the emplacement drifts, which includes the following major analysis/model reports (AMRs): (1) EBS Water Distribution and Removal (WD&R) Model; (2) EBS Physical and Chemical Environment (P&CE) Model; (3) EBS Radionuclide Transport (EBS RNT) Model; and (4) EBS Multiscale Thermohydrologic (TH) Model. Technical information, including data, analyses, models, software, and supporting documents will be provided to defend the applicability of these models for their intended purpose of evaluating the postclosure performance of the Yucca Mountain repository system. The WD&R model ARM is important to the site recommendation. Water distribution and removal represents one component of the overall EBS. Under some conditions, liquid water will seep into emplacement drifts through fractures in the host rock and move generally downward, potentially contacting waste packages. After waste packages are breached by corrosion, some of this seepage water will contact the waste, dissolve or suspend radionuclides, and ultimately carry radionuclides through the EBS to the near-field host rock. Lateral diversion of liquid water within the drift will occur at the inner drift surface, and more significantly from the operation of engineered structures such as drip shields and the outer surface of waste packages. If most of the seepage flux can be diverted laterally and removed from the drifts before contacting the wastes, the release of radionuclides from the EBS can be controlled, resulting in a proportional reduction in dose release at the accessible environment. The purposes
Pedotransfer functions to estimate water retention parameters of soils in northeastern Brazil
Directory of Open Access Journals (Sweden)
Alexandre Hugo Cezar Barros
2013-04-01
Full Text Available Pedotransfer functions (PTF were developed to estimate the parameters (α, n, θr and θs of the van Genuchten model (1980 to describe soil water retention curves. The data came from various sources, mainly from studies conducted by universities in Northeast Brazil, by the Brazilian Agricultural Research Corporation (Embrapa and by a corporation for the development of the São Francisco and Parnaíba river basins (Codevasf, totaling 786 retention curves, which were divided into two data sets: 85 % for the development of PTFs, and 15 % for testing and validation, considered independent data. Aside from the development of general PTFs for all soils together, specific PTFs were developed for the soil classes Ultisols, Oxisols, Entisols, and Alfisols by multiple regression techniques, using a stepwise procedure (forward and backward to select the best predictors. Two types of PTFs were developed: the first included all predictors (soil density, proportions of sand, silt, clay, and organic matter, and the second only the proportions of sand, silt and clay. The evaluation of adequacy of the PTFs was based on the correlation coefficient (R and Willmott index (d. To evaluate the PTF for the moisture content at specific pressure heads, we used the root mean square error (RMSE. The PTF-predicted retention curve is relatively poor, except for the residual water content. The inclusion of organic matter as a PTF predictor improved the prediction of parameter a of van Genuchten. The performance of soil-class-specific PTFs was not better than of the general PTF. Except for the water content of saturated soil estimated by particle size distribution, the tested models for water content prediction at specific pressure heads proved satisfactory. Predictions of water content at pressure heads more negative than -0.6 m, using a PTF considering particle size distribution, are only slightly lower than those obtained by PTFs including bulk density and organic matter
Do Lumped-Parameter Models Provide the Correct Geometrical Damping?
DEFF Research Database (Denmark)
Andersen, Lars
This paper concerns the formulation of lumped-parameter models for rigid footings on homogenous or stratified soil. Such models only contain a few degrees of freedom, which makes them ideal for inclusion in aero-elastic codes for wind turbines and other models applied to fast evaluation of struct......This paper concerns the formulation of lumped-parameter models for rigid footings on homogenous or stratified soil. Such models only contain a few degrees of freedom, which makes them ideal for inclusion in aero-elastic codes for wind turbines and other models applied to fast evaluation...... response during excitation and the geometrical damping related to free vibrations of a hexagonal footing. The optimal order of a lumped-parameter model is determined for each degree of freedom, i.e. horizontal and vertical translation as well as torsion and rocking. In particular, the necessity of coupling...... between horizontal sliding and rocking is discussed....
Parameter Estimation for a Computable General Equilibrium Model
DEFF Research Database (Denmark)
Arndt, Channing; Robinson, Sherman; Tarp, Finn
. Second, it permits incorporation of prior information on parameter values. Third, it can be applied in the absence of copious data. Finally, it supplies measures of the capacity of the model to reproduce the historical record and the statistical significance of parameter estimates. The method is applied...
Estimating winter wheat phenological parameters: Implications for crop modeling
Crop parameters, such as the timing of developmental events, are critical for accurate simulation results in crop simulation models, yet uncertainty often exists in determining the parameters. Factors contributing to the uncertainty include: a) sources of variation within a plant (i.e., within diffe...
Bates, P. D.; Neal, J. C.; Fewtrell, T. J.
2012-12-01
In this we paper we consider two related questions. First, we address the issue of how much physical complexity is necessary in a model in order to simulate floodplain inundation to within validation data error. This is achieved through development of a single code/multiple physics hydraulic model (LISFLOOD-FP) where different degrees of complexity can be switched on or off. Different configurations of this code are applied to four benchmark test cases, and compared to the results of a number of industry standard models. Second we address the issue of how parameter sensitivity and transferability change with increasing complexity using numerical experiments with models of different physical and geometric intricacy. Hydraulic models are a good example system with which to address such generic modelling questions as: (1) they have a strong physical basis; (2) there is only one set of equations to solve; (3) they require only topography and boundary conditions as input data; and (4) they typically require only a single free parameter, namely boundary friction. In terms of complexity required we show that for the problem of sub-critical floodplain inundation a number of codes of different dimensionality and resolution can be found to fit uncertain model validation data equally well, and that in this situation Occam's razor emerges as a useful logic to guide model selection. We find also find that model skill usually improves more rapidly with increases in model spatial resolution than increases in physical complexity, and that standard approaches to testing hydraulic models against laboratory data or analytical solutions may fail to identify this important fact. Lastly, we find that in benchmark testing studies significant differences can exist between codes with identical numerical solution techniques as a result of auxiliary choices regarding the specifics of model implementation that are frequently unreported by code developers. As a consequence, making sound
Retrospective forecast of ETAS model with daily parameters estimate
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.
Parameter Estimates in Differential Equation Models for Population Growth
Winkel, Brian J.
2011-01-01
We estimate the parameters present in several differential equation models of population growth, specifically logistic growth models and two-species competition models. We discuss student-evolved strategies and offer "Mathematica" code for a gradient search approach. We use historical (1930s) data from microbial studies of the Russian biologist,…
Dynamic Modeling and Parameter Identification of Power Systems
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
@@ The generator, the excitation system, the steam turbine and speed governor, and the load are the so called four key models of power systems. Mathematical modeling and parameter identification for the four key models are of great importance as the basis for designing, operating, and analyzing power systems.
Dynamic Load Model using PSO-Based Parameter Estimation
Taoka, Hisao; Matsuki, Junya; Tomoda, Michiya; Hayashi, Yasuhiro; Yamagishi, Yoshio; Kanao, Norikazu
This paper presents a new method for estimating unknown parameters of dynamic load model as a parallel composite of a constant impedance load and an induction motor behind a series constant reactance. An adequate dynamic load model is essential for evaluating power system stability, and this model can represent the behavior of actual load by using appropriate parameters. However, the problem of this model is that a lot of parameters are necessary and it is not easy to estimate a lot of unknown parameters. We propose an estimating method based on Particle Swarm Optimization (PSO) which is a non-linear optimization method by using the data of voltage, active power and reactive power measured at voltage sag.
Parameter Estimation for the Thurstone Case III Model.
Mackay, David B.; Chaiy, Seoil
1982-01-01
The ability of three estimation criteria to recover parameters of the Thurstone Case V and Case III models from comparative judgment data was investigated via Monte Carlo techniques. Significant differences in recovery are shown to exist. (Author/JKS)
Institute of Scientific and Technical Information of China (English)
Youlong XIA; Zong-Liang YANG; Paul L. STOFFA; Mrinal K. SEN
2005-01-01
Most previous land-surface model calibration studies have defined global ranges for their parameters to search for optimal parameter sets. Little work has been conducted to study the impacts of realistic versus global ranges as well as model complexities on the calibration and uncertainty estimates. The primary purpose of this paper is to investigate these impacts by employing Bayesian Stochastic Inversion (BSI)to the Chameleon Surface Model (CHASM). The CHASM was designed to explore the general aspects of land-surface energy balance representation within a common modeling framework that can be run from a simple energy balance formulation to a complex mosaic type structure. The BSI is an uncertainty estimation technique based on Bayes theorem, importance sampling, and very fast simulated annealing.The model forcing data and surface flux data were collected at seven sites representing a wide range of climate and vegetation conditions. For each site, four experiments were performed with simple and complex CHASM formulations as well as realistic and global parameter ranges. Twenty eight experiments were conducted and 50 000 parameter sets were used for each run. The results show that the use of global and realistic ranges gives similar simulations for both modes for most sites, but the global ranges tend to produce some unreasonable optimal parameter values. Comparison of simple and complex modes shows that the simple mode has more parameters with unreasonable optimal values. Use of parameter ranges and model complexities have significant impacts on frequency distribution of parameters, marginal posterior probability density functions, and estimates of uncertainty of simulated sensible and latent heat fluxes.Comparison between model complexity and parameter ranges shows that the former has more significant impacts on parameter and uncertainty estimations.
Enthalpy and entropy interaction parameters of sodium chloride with some monosaccharides in water
Institute of Scientific and Technical Information of China (English)
ZHUO; Kelei; WANG; Jianji; BAI; Guangyue; YAN; Haike; WANG
2004-01-01
Dilution enthalpies of sodium chloride and some monosaccharides (glucose, galactose, xylose, arabinose, and fructose) in water and mixing enthalpies of aqueous sodium chloride and these monosaccharide solutions were measured by using an improved precision semimicro-titration calorimeter. Transfer enthalpies of sodium chloride from water to aqueous saccharide solutions were evaluated as well as enthalpy interaction parameters of sodium chloride with these monosaccharides in water. Combined with Gibbs energy interaction parameters, entropy interaction parameters were also obtained. The results show that interactions of the saccharides with sodium chloride depend on the stereochemistry of saccharide molecules. These interaction parameters can identify stereochemical structure of saccharide molecules.
Evaluation of physico-chemical and microbial parameters on water ...
African Journals Online (AJOL)
Microsoft Windows
production of acid and gas from the fermentation of lactose in any of the tubes is a .... The total dissolved solid (TDS) is the sum of the cations cations and anions .... Abbasi SA (2002). Water quality indices, state of the art report, National.
Changes in water quality parameters due to in-sewer processes.
Boxall, J; Shepherd, W; Guymer, I; Fox, K
2003-01-01
Combined sewer systems contain a large number of organic and inorganic pollutants from both domestic and industrial sources. These pollutants are often retained within the combined sewer system for significant lengths of time before entering sewage treatment works, or being spilt to a watercourse via a combined sewer overflow (CSO) during storm conditions. Currently little knowledge exists concerning the effects of in sewer processes on pollutants. Understanding of in-sewer processes is important for the effective and efficient design of treatment works and CSO chambers and for impact assessments on receiving waters. A series of studies covering storm and dry weather flow conditions were undertaken with the aim of investigating the nature of in-sewer processes. These studies consisted of marking a body of water with a fluorescent tracer. The tracer was then monitored at a series of downstream sites, and discrete samples collected from the body of water as it progressed through the sewer. The samples were analysed for water quality parameters and these results investigated in tandem with the detailed hydraulic information gained through the tracer studies. The results highlight the hydraulic differences between storm and dry weather conditions such as increased travel times and mixing under storm conditions. The Advection Dispersion Equation (ADE) and Aggregated Dead Zone (ADZ) model parameters have been quantified for the tracer data. The ADE mixing coefficient is shown to increase by an order of magnitude for storm conditions. The ADZ dispersive fraction parameter is shown to be approximately constant with flow. Chemical reactions and decay within the sewer system were found to be consistent with oxygen limitation.
Directory of Open Access Journals (Sweden)
Ahmed I. Al-Amoud
2014-06-01
Full Text Available The effects of water temperature and structural parameters of a labyrinth emitter on drip irrigation hydraulic performance were investigated. The inside structural parameters of the trapezoidal labyrinth emitter include path width (W and length (L, trapezoidal unit numbers (N, height (H, and spacing (S. Laboratory experiments were conducted using five different types of labyrinth-channel emitters (three non-pressure compensating and two pressure-compensating emitters commonly used for subsurface drip irrigation systems. The water temperature effect on the hydraulic characteristics at various operating pressures was recorded and a comparison was made to identify the most effective structural parameter on emitter performance. The pressure compensating emitter flow exponent (x average was 0.014, while non-pressure compensating emitter’s values average was 0.456, indicating that the sensitivity of non-pressure compensating emitters to pressure variation is an obvious characteristic (p<0.001 of this type of emitters. The effects of water temperature on emitter flow rate were insignificant (p>0.05 at various operating pressures, where the flow rate index values for emitters were around one. The effects of water temperature on manufacturer’s coefficient of variation (CV values for all emitters were insignificant (p>0.05. The CV values of the non-pressure compensating emitters were lower than those of pressure compensating emitters. This is typical for most compensating models because they are manufactured with more elements than non-compensating emitters are. The results of regression analysis indicate that N and H are the essential factors (p<0.001 to affect the hydraulic performance.
Comparing spatial and temporal transferability of hydrological model parameters
Patil, Sopan D.; Stieglitz, Marc
2015-06-01
Operational use of hydrological models requires the transfer of calibrated parameters either in time (for streamflow forecasting) or space (for prediction at ungauged catchments) or both. Although the effects of spatial and temporal parameter transfer on catchment streamflow predictions have been well studied individually, a direct comparison of these approaches is much less documented. Here, we compare three different schemes of parameter transfer, viz., temporal, spatial, and spatiotemporal, using a spatially lumped hydrological model called EXP-HYDRO at 294 catchments across the continental United States. Results show that the temporal parameter transfer scheme performs best, with lowest decline in prediction performance (median decline of 4.2%) as measured using the Kling-Gupta efficiency metric. More interestingly, negligible difference in prediction performance is observed between the spatial and spatiotemporal parameter transfer schemes (median decline of 12.4% and 13.9% respectively). We further demonstrate that the superiority of temporal parameter transfer scheme is preserved even when: (1) spatial distance between donor and receiver catchments is reduced, or (2) temporal lag between calibration and validation periods is increased. Nonetheless, increase in the temporal lag between calibration and validation periods reduces the overall performance gap between the three parameter transfer schemes. Results suggest that spatiotemporal transfer of hydrological model parameters has the potential to be a viable option for climate change related hydrological studies, as envisioned in the "trading space for time" framework. However, further research is still needed to explore the relationship between spatial and temporal aspects of catchment hydrological variability.
Combined Estimation of Hydrogeologic Conceptual Model and Parameter Uncertainty
Energy Technology Data Exchange (ETDEWEB)
Meyer, Philip D.; Ye, Ming; Neuman, Shlomo P.; Cantrell, Kirk J.
2004-03-01
The objective of the research described in this report is the development and application of a methodology for comprehensively assessing the hydrogeologic uncertainties involved in dose assessment, including uncertainties associated with conceptual models, parameters, and scenarios. This report describes and applies a statistical method to quantitatively estimate the combined uncertainty in model predictions arising from conceptual model and parameter uncertainties. The method relies on model averaging to combine the predictions of a set of alternative models. Implementation is driven by the available data. When there is minimal site-specific data the method can be carried out with prior parameter estimates based on generic data and subjective prior model probabilities. For sites with observations of system behavior (and optionally data characterizing model parameters), the method uses model calibration to update the prior parameter estimates and model probabilities based on the correspondence between model predictions and site observations. The set of model alternatives can contain both simplified and complex models, with the requirement that all models be based on the same set of data. The method was applied to the geostatistical modeling of air permeability at a fractured rock site. Seven alternative variogram models of log air permeability were considered to represent data from single-hole pneumatic injection tests in six boreholes at the site. Unbiased maximum likelihood estimates of variogram and drift parameters were obtained for each model. Standard information criteria provided an ambiguous ranking of the models, which would not justify selecting one of them and discarding all others as is commonly done in practice. Instead, some of the models were eliminated based on their negligibly small updated probabilities and the rest were used to project the measured log permeabilities by kriging onto a rock volume containing the six boreholes. These four
Parameter Estimation for Groundwater Models under Uncertain Irrigation Data.
Demissie, Yonas; Valocchi, Albert; Cai, Ximing; Brozovic, Nicholas; Senay, Gabriel; Gebremichael, Mekonnen
2015-01-01
The success of modeling groundwater is strongly influenced by the accuracy of the model parameters that are used to characterize the subsurface system. However, the presence of uncertainty and possibly bias in groundwater model source/sink terms may lead to biased estimates of model parameters and model predictions when the standard regression-based inverse modeling techniques are used. This study first quantifies the levels of bias in groundwater model parameters and predictions due to the presence of errors in irrigation data. Then, a new inverse modeling technique called input uncertainty weighted least-squares (IUWLS) is presented for unbiased estimation of the parameters when pumping and other source/sink data are uncertain. The approach uses the concept of generalized least-squares method with the weight of the objective function depending on the level of pumping uncertainty and iteratively adjusted during the parameter optimization process. We have conducted both analytical and numerical experiments, using irrigation pumping data from the Republican River Basin in Nebraska, to evaluate the performance of ordinary least-squares (OLS) and IUWLS calibration methods under different levels of uncertainty of irrigation data and calibration conditions. The result from the OLS method shows the presence of statistically significant (p irrigation pumping uncertainties during the calibration procedures, the proposed IUWLS is able to minimize the bias effectively without adding significant computational burden to the calibration processes.
Parameter estimation for groundwater models under uncertain irrigation data
Demissie, Yonas; Valocchi, Albert J.; Cai, Ximing; Brozovic, Nicholas; Senay, Gabriel; Gebremichael, Mekonnen
2015-01-01
The success of modeling groundwater is strongly influenced by the accuracy of the model parameters that are used to characterize the subsurface system. However, the presence of uncertainty and possibly bias in groundwater model source/sink terms may lead to biased estimates of model parameters and model predictions when the standard regression-based inverse modeling techniques are used. This study first quantifies the levels of bias in groundwater model parameters and predictions due to the presence of errors in irrigation data. Then, a new inverse modeling technique called input uncertainty weighted least-squares (IUWLS) is presented for unbiased estimation of the parameters when pumping and other source/sink data are uncertain. The approach uses the concept of generalized least-squares method with the weight of the objective function depending on the level of pumping uncertainty and iteratively adjusted during the parameter optimization process. We have conducted both analytical and numerical experiments, using irrigation pumping data from the Republican River Basin in Nebraska, to evaluate the performance of ordinary least-squares (OLS) and IUWLS calibration methods under different levels of uncertainty of irrigation data and calibration conditions. The result from the OLS method shows the presence of statistically significant (p irrigation pumping uncertainties during the calibration procedures, the proposed IUWLS is able to minimize the bias effectively without adding significant computational burden to the calibration processes.
Parameter estimation in stochastic rainfall-runoff models
DEFF Research Database (Denmark)
Jonsdottir, Harpa; Madsen, Henrik; Palsson, Olafur Petur
2006-01-01
the parameters, including the noise terms. The parameter estimation method is a maximum likelihood method (ML) where the likelihood function is evaluated using a Kalman filter technique. The ML method estimates the parameters in a prediction error settings, i.e. the sum of squared prediction error is minimized....... For a comparison the parameters are also estimated by an output error method, where the sum of squared simulation error is minimized. The former methodology is optimal for short-term prediction whereas the latter is optimal for simulations. Hence, depending on the purpose it is possible to select whether...... the parameter values are optimal for simulation or prediction. The data originates from Iceland and the model is designed for Icelandic conditions, including a snow routine for mountainous areas. The model demands only two input data series, precipitation and temperature and one output data series...
Transformations among CE–CVM model parameters for multicomponent systems
Indian Academy of Sciences (India)
B Nageswara Sarma; Shrikant Lele
2005-06-01
In the development of thermodynamic databases for multicomponent systems using the cluster expansion–cluster variation methods, we need to have a consistent procedure for expressing the model parameters (CECs) of a higher order system in terms of those of the lower order subsystems and to an independent set of parameters which exclusively represent interactions of the higher order systems. Such a procedure is presented in detail in this communication. Furthermore, the details of transformations required to express the model parameters in one basis from those defined in another basis for the same system are also presented.
Validation of a spatial–temporal soil water movement and plant water uptake model
HEPPELL, J.
2014-06-01
© 2014, (publisher). All rights reserved. Management and irrigation of plants increasingly relies on accurate mathematical models for the movement of water within unsaturated soils. Current models often use values for water content and soil parameters that are averaged over the soil profile. However, many applications require models to more accurately represent the soil–plant–atmosphere continuum, in particular, water movement and saturation within specific parts of the soil profile. In this paper a mathematical model for water uptake by a plant root system from unsaturated soil is presented. The model provides an estimate of the water content level within the soil at different depths, and the uptake of water by the root system. The model was validated using field data, which include hourly water content values at five different soil depths under a grass/herb cover over 1 year, to obtain a fully calibrated system for plant water uptake with respect to climate conditions. When compared quantitatively to a simple water balance model, the proposed model achieves a better fit to the experimental data due to its ability to vary water content with depth. To accurately model the water content in the soil profile, the soil water retention curve and saturated hydraulic conductivity needed to vary with depth.
SPOTting Model Parameters Using a Ready-Made Python Package.
Houska, Tobias; Kraft, Philipp; Chamorro-Chavez, Alejandro; Breuer, Lutz
2015-01-01
The choice for specific parameter estimation methods is often more dependent on its availability than its performance. We developed SPOTPY (Statistical Parameter Optimization Tool), an open source python package containing a comprehensive set of methods typically used to calibrate, analyze and optimize parameters for a wide range of ecological models. SPOTPY currently contains eight widely used algorithms, 11 objective functions, and can sample from eight parameter distributions. SPOTPY has a model-independent structure and can be run in parallel from the workstation to large computation clusters using the Message Passing Interface (MPI). We tested SPOTPY in five different case studies to parameterize the Rosenbrock, Griewank and Ackley functions, a one-dimensional physically based soil moisture routine, where we searched for parameters of the van Genuchten-Mualem function and a calibration of a biogeochemistry model with different objective functions. The case studies reveal that the implemented SPOTPY methods can be used for any model with just a minimal amount of code for maximal power of parameter optimization. They further show the benefit of having one package at hand that includes number of well performing parameter search methods, since not every case study can be solved sufficiently with every algorithm or every objective function.
SPOTting Model Parameters Using a Ready-Made Python Package.
Directory of Open Access Journals (Sweden)
Tobias Houska
Full Text Available The choice for specific parameter estimation methods is often more dependent on its availability than its performance. We developed SPOTPY (Statistical Parameter Optimization Tool, an open source python package containing a comprehensive set of methods typically used to calibrate, analyze and optimize parameters for a wide range of ecological models. SPOTPY currently contains eight widely used algorithms, 11 objective functions, and can sample from eight parameter distributions. SPOTPY has a model-independent structure and can be run in parallel from the workstation to large computation clusters using the Message Passing Interface (MPI. We tested SPOTPY in five different case studies to parameterize the Rosenbrock, Griewank and Ackley functions, a one-dimensional physically based soil moisture routine, where we searched for parameters of the van Genuchten-Mualem function and a calibration of a biogeochemistry model with different objective functions. The case studies reveal that the implemented SPOTPY methods can be used for any model with just a minimal amount of code for maximal power of parameter optimization. They further show the benefit of having one package at hand that includes number of well performing parameter search methods, since not every case study can be solved sufficiently with every algorithm or every objective function.
Numerical modeling of piezoelectric transducers using physical parameters.
Cappon, Hans; Keesman, Karel J
2012-05-01
Design of ultrasonic equipment is frequently facilitated with numerical models. These numerical models, however, need a calibration step, because usually not all characteristics of the materials used are known. Characterization of material properties combined with numerical simulations and experimental data can be used to acquire valid estimates of the material parameters. In our design application, a finite element (FE) model of an ultrasonic particle separator, driven by an ultrasonic transducer in thickness mode, is required. A limited set of material parameters for the piezoelectric transducer were obtained from the manufacturer, thus preserving prior physical knowledge to a large extent. The remaining unknown parameters were estimated from impedance analysis with a simple experimental setup combined with a numerical optimization routine using 2-D and 3-D FE models. Thus, a full set of physically interpretable material parameters was obtained for our specific purpose. The approach provides adequate accuracy of the estimates of the material parameters, near 1%. These parameter estimates will subsequently be applied in future design simulations, without the need to go through an entire series of characterization experiments. Finally, a sensitivity study showed that small variations of 1% in the main parameters caused changes near 1% in the eigenfrequency, but changes up to 7% in the admittance peak, thus influencing the efficiency of the system. Temperature will already cause these small variations in response; thus, a frequency control unit is required when actually manufacturing an efficient ultrasonic separation system.
Parameter estimation and model selection in computational biology.
Directory of Open Access Journals (Sweden)
Gabriele Lillacci
2010-03-01
Full Text Available A central challenge in computational modeling of biological systems is the determination of the model parameters. Typically, only a fraction of the parameters (such as kinetic rate constants are experimentally measured, while the rest are often fitted. The fitting process is usually based on experimental time course measurements of observables, which are used to assign parameter values that minimize some measure of the error between these measurements and the corresponding model prediction. The measurements, which can come from immunoblotting assays, fluorescent markers, etc., tend to be very noisy and taken at a limited number of time points. In this work we present a new approach to the problem of parameter selection of biological models. We show how one can use a dynamic recursive estimator, known as extended Kalman filter, to arrive at estimates of the model parameters. The proposed method follows. First, we use a variation of the Kalman filter that is particularly well suited to biological applications to obtain a first guess for the unknown parameters. Secondly, we employ an a posteriori identifiability test to check the reliability of the estimates. Finally, we solve an optimization problem to refine the first guess in case it should not be accurate enough. The final estimates are guaranteed to be statistically consistent with the measurements. Furthermore, we show how the same tools can be used to discriminate among alternate models of the same biological process. We demonstrate these ideas by applying our methods to two examples, namely a model of the heat shock response in E. coli, and a model of a synthetic gene regulation system. The methods presented are quite general and may be applied to a wide class of biological systems where noisy measurements are used for parameter estimation or model selection.
Impact of the calibration period on the conceptual rainfall-runoff model parameter estimates
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
Ward, Adam S.; Kelleher, Christa A.; Mason, Seth J. K.; Wagener, Thorsten; McIntyre, Neil; McGlynn, Brian L.; Runkel, Robert L.; Payn, Robert A.
2017-01-01
Researchers and practitioners alike often need to understand and characterize how water and solutes move through a stream in terms of the relative importance of in-stream and near-stream storage and transport processes. In-channel and subsurface storage processes are highly variable in space and time and difficult to measure. Storage estimates are commonly obtained using transient-storage models (TSMs) of the experimentally obtained solute-tracer test data. The TSM equations represent key transport and storage processes with a suite of numerical parameters. Parameter values are estimated via inverse modeling, in which parameter values are iteratively changed until model simulations closely match observed solute-tracer data. Several investigators have shown that TSM parameter estimates can be highly uncertain. When this is the case, parameter values cannot be used reliably to interpret stream-reach functioning. However, authors of most TSM studies do not evaluate or report parameter certainty. Here, we present a software tool linked to the One-dimensional Transport with Inflow and Storage (OTIS) model that enables researchers to conduct uncertainty analyses via Monte-Carlo parameter sampling and to visualize uncertainty and sensitivity results. We demonstrate application of our tool to 2 case studies and compare our results to output obtained from more traditional implementation of the OTIS model. We conclude by suggesting best practices for transient-storage modeling and recommend that future applications of TSMs include assessments of parameter certainty to support comparisons and more reliable interpretations of transport processes.
Energy Technology Data Exchange (ETDEWEB)
Hamimid, M., E-mail: Hamimid_mourad@hotmail.com [Laboratoire de modelisation des systemes energetiques LMSE, Universite de Biskra, BP 145, 07000 Biskra (Algeria); Mimoune, S.M., E-mail: s.m.mimoune@mselab.org [Laboratoire de modelisation des systemes energetiques LMSE, Universite de Biskra, BP 145, 07000 Biskra (Algeria); Feliachi, M., E-mail: mouloud.feliachi@univ-nantes.fr [IREENA-IUT, CRTT, 37 Boulevard de l' Universite, BP 406, 44602 Saint Nazaire Cedex (France)
2012-07-01
In this present work, the minor hysteresis loops model based on parameters scaling of the modified Jiles-Atherton model is evaluated by using judicious expressions. These expressions give the minor hysteresis loops parameters as a function of the major hysteresis loop ones. They have exponential form and are obtained by parameters identification using the stochastic optimization method 'simulated annealing'. The main parameters influencing the data fitting are three parameters, the pinning parameter k, the mean filed parameter {alpha} and the parameter which characterizes the shape of anhysteretic magnetization curve a. To validate this model, calculated minor hysteresis loops are compared with measured ones and good agreements are obtained.
World water dynamics: global modeling of water resources.
Simonovic, Slobodan P
2002-11-01
The growing scarcity of fresh and clean water is among the most important issues facing civilization in the 21st century. Despite the growing attention to a chronic, pernicious crisis in world's water resources our ability to correctly assess and predict global water availability, use and balance is still quite limited. An attempt is documented here in modeling global world water resources using system dynamics approach. Water resources sector (quantity and quality) is integrated with five sectors that drive industrial growth: population; agriculture; economy; nonrenewable resources; and persistent pollution. WorldWater model is developed on the basis of the last version of World3 model. Simulations of world water dynamics with WorldWater indicate that there is a strong relationship between the world water resources and future industrial growth of the world. It is also shown that the water pollution is the most important future water issue on the global level.
YUSUBOV FAXRADDIN VALI; SHIXALIYEV КARAM SEYFI; ABDULLAYEVA МAYA YADIGAR
2016-01-01
The article describes an identification of optimal parameters for surface water purification from oil and oil products by sorbent based on worn automotive tires. In thus Optimal parameters for water surface purification from oil and oil products by sorbent have been found out on the basis of constructed regression model of the process.
Modelling of the water retention characteristic of deformable soils
Directory of Open Access Journals (Sweden)
Wang Yu
2016-01-01
Full Text Available A recently proposed water retention model has been further developed for the application on unsaturated deformable soils. The physical mechanisms underpinning the water retention characteristic of soils was at first described in terms of traditional theories of capillarity and interfacial physical chemistry at pore level. Then upscaling to macroscopic level of material scale in terms of average volume theorem produces an analytical formula for the water retention characteristic. The methodology produces an explicit form of the water retention curve as a function of three state parameters: the suction, the degree-of-water-saturation and the void-ratio. At last, the model has been tested using experimental measurements.
MODELING OF FUEL SPRAY CHARACTERISTICS AND DIESEL COMBUSTION CHAMBER PARAMETERS
Directory of Open Access Journals (Sweden)
G. M. Kukharonak
2011-01-01
Full Text Available The computer model for coordination of fuel spray characteristics with diesel combustion chamber parameters has been created in the paper. The model allows to observe fuel sprays develоpment in diesel cylinder at any moment of injection, to calculate characteristics of fuel sprays with due account of a shape and dimensions of a combustion chamber, timely to change fuel injection characteristics and supercharging parameters, shape and dimensions of a combustion chamber. Moreover the computer model permits to determine parameters of holes in an injector nozzle that provides the required fuel sprays characteristics at the stage of designing a diesel engine. Combustion chamber parameters for 4ЧН11/12.5 diesel engine have been determined in the paper.
Mathematically Modeling Parameters Influencing Surface Roughness in CNC Milling
Directory of Open Access Journals (Sweden)
Engin Nas
2012-01-01
Full Text Available In this study, steel AISI 1050 is subjected to process of face milling in CNC milling machine and such parameters as cutting speed, feed rate, cutting tip, depth of cut influencing the surface roughness are investigated experimentally. Four different experiments are conducted by creating different combinations for parameters. In conducted experiments, cutting tools, which are coated by PVD method used in forcing steel and spheroidal graphite cast iron are used. Surface roughness values, which are obtained by using specified parameters with cutting tools, are measured and correlation between measured surface roughness values and parameters is modeled mathematically by using curve fitting algorithm. Mathematical models are evaluated according to coefficients of determination (R2 and the most ideal one is suggested for theoretical works. Mathematical models, which are proposed for each experiment, are estipulated.
Regionalization parameters of conceptual rainfall-runoff model
Osuch, M.
2003-04-01
Main goal of this study was to develop techniques for the a priori estimation parameters of hydrological model. Conceptual hydrological model CLIRUN was applied to around 50 catchment in Poland. The size of catchments range from 1 000 to 100 000 km2. The model was calibrated for a number of gauged catchments with different catchment characteristics. The parameters of model were related to different climatic and physical catchment characteristics (topography, land use, vegetation and soil type). The relationships were tested by comparing observed and simulated runoff series from the gauged catchment that were not used in the calibration. The model performance using regional parameters was promising for most of the calibration and validation catchments.
Uncertainty Assessment in Urban Storm Water Drainage Modelling
DEFF Research Database (Denmark)
Thorndahl, Søren
The object of this paper is to make an overall description of the author's PhD study, concerning uncertainties in numerical urban storm water drainage models. Initially an uncertainty localization and assessment of model inputs and parameters as well as uncertainties caused by different model...
Weibull Parameters Estimation Based on Physics of Failure Model
DEFF Research Database (Denmark)
Kostandyan, Erik; Sørensen, John Dalsgaard
2012-01-01
Reliability estimation procedures are discussed for the example of fatigue development in solder joints using a physics of failure model. The accumulated damage is estimated based on a physics of failure model, the Rainflow counting algorithm and the Miner’s rule. A threshold model is used...... distribution. Methods from structural reliability analysis are used to model the uncertainties and to assess the reliability for fatigue failure. Maximum Likelihood and Least Square estimation techniques are used to estimate fatigue life distribution parameters....
Long-term effects of water pH changes on hematological parameters ...
African Journals Online (AJOL)
Yomi
2012-02-14
Feb 14, 2012 ... face between fish and its environment for gas transfer, acid-base ... and low water pH on ion balance and ammonia excretion in freshwater fish ... Water quality parameters of the stored water were measured at the beginning of ...
Performance Prediction of Two-Phase Geothermal Reservoir using Lumped Parameter Model
Nurlaela, F.; Sutopo
2016-09-01
Many studies have been conducted to simulate performance of low-temperature geothermal reservoirs using lumped parameter method. Limited work had been done on applying non-isothermal lumped parameter models to higher temperature geothermal reservoirs. In this study, the lumped parameter method was applied to high-temperature two phase geothermal reservoirs. The model couples both energy and mass balance equations thus can predict temperature, pressure and fluid saturation changes in the reservoir as a result of production, reinjection of water, and/or natural recharge. This method was validated using reservoir simulation results of TOUGH2. As the results, the two phase lumped parameter model simulation without recharge shows good matching, however reservoir model with recharge condition show quite good conformity.
MODELING PARAMETERS OF ARC OF ELECTRIC ARC FURNACE
Directory of Open Access Journals (Sweden)
R.N. Khrestin
2015-08-01
Full Text Available Purpose. The aim is to build a mathematical model of the electric arc of arc furnace (EAF. The model should clearly show the relationship between the main parameters of the arc. These parameters determine the properties of the arc and the possibility of optimization of melting mode. Methodology. We have built a fairly simple model of the arc, which satisfies the above requirements. The model is designed for the analysis of electromagnetic processes arc of varying length. We have compared the results obtained when testing the model with the results obtained on actual furnaces. Results. During melting in real chipboard under the influence of changes in temperature changes its properties arc plasma. The proposed model takes into account these changes. Adjusting the length of the arc is the main way to regulate the mode of smelting chipboard. The arc length is controlled by the movement of the drive electrode. The model reflects the dynamic changes in the parameters of the arc when changing her length. We got the dynamic current-voltage characteristics (CVC of the arc for the different stages of melting. We got the arc voltage waveform and identified criteria by which possible identified stage of smelting. Originality. In contrast to the previously known models, this model clearly shows the relationship between the main parameters of the arc EAF: arc voltage Ud, amperage arc id and length arc d. Comparison of the simulation results and experimental data obtained from real particleboard showed the adequacy of the constructed model. It was found that character of change of magnitude Md, helps determine the stage of melting. Practical value. It turned out that the model can be used to simulate smelting in EAF any capacity. Thus, when designing the system of control mechanism for moving the electrode, the model takes into account changes in the parameters of the arc and it can significantly reduce electrode material consumption and energy consumption
Environmental Transport Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
M. Wasiolek
2004-09-10
This analysis report is one of the technical reports documenting the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the total system performance assessment for the license application (TSPA-LA) for the geologic repository at Yucca Mountain. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows relationships among the reports developed for biosphere modeling and biosphere abstraction products for the TSPA-LA, as identified in the ''Technical Work Plan for Biosphere Modeling and Expert Support'' (BSC 2004 [DIRS 169573]) (TWP). This figure provides an understanding of how this report contributes to biosphere modeling in support of the license application (LA). This report is one of the five reports that develop input parameter values for the biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the conceptual model and the mathematical model. The input parameter reports, shown to the right of the Biosphere Model Report in Figure 1-1, contain detailed description of the model input parameters. The output of this report is used as direct input in the ''Nominal Performance Biosphere Dose Conversion Factor Analysis'' and in the ''Disruptive Event Biosphere Dose Conversion Factor Analysis'' that calculate the values of biosphere dose conversion factors (BDCFs) for the groundwater and volcanic ash exposure scenarios, respectively. The purpose of this analysis was to develop biosphere model parameter values related to radionuclide transport and accumulation in the environment. These parameters support calculations of radionuclide concentrations in the environmental media (e.g., soil, crops, animal products, and air) resulting from a given radionuclide concentration at the source of contamination (i.e., either in groundwater or in volcanic ash). The analysis
Stochastic Still Water Response Model
DEFF Research Database (Denmark)
Friis-Hansen, Peter; Ditlevsen, Ove Dalager
2002-01-01
In this study a stochastic field model for the still water loading is formulated where the statistics (mean value, standard deviation, and correlation) of the sectional forces are obtained by integration of the load field over the relevant part of the ship structure. The objective of the model...... is to establish the stochastic load field conditional on a given draft and trim of the vessel. The model contributes to a realistic modelling of the stochastic load processes to be used in a reliability evaluation of the ship hull. Emphasis is given to container vessels. The formulation of the model for obtaining...... the stochastic cargo container load field is based on a queuing and loading policy that assumes containers are handled by a first-come-first-serve policy. The load field is assumed to be Gaussian. The ballast system is imposed to counteract the angle of heel and to regulate both the draft and the trim caused...
Institute of Scientific and Technical Information of China (English)
王俊良; 李鹏; 高金良; 袁一星; 汤维佳
2011-01-01
The application of GPS survey techniques is to enhance the accuracy and reliability in modeling water distribution network, as well as reducing amount of work during the primary stage. Taking a large city in northeast China for example, combined with the total station instrument under GPS-RTK mode, water source nodes and pressure monitoring points were measured precisely and three-dimensionally. The elevations of valves and pressure gauges in the measurement of pipeline resistance and valve resistance were also acquired. The results are more precise than those measured with traditional estimating methods. Different points in the area can be measured synchronously, which simplifies many procedures during measurement of pipelines and improves the working efficiency. Digital network graphics is more precise, which can prevent human errors and ensure the accuracy of the model. So it is proved to be a new work mode in modeling water distribution network.%为提高给水管网水力模型的精确性和可信度,减少管网建模初期基础资料收集的工作量,在给水管网建模过程中引入GPS实测.以东北某特大城市为例,通过全站仪结合GPS的方法,采用GPS-RTK模式,对水源节点及压力监测点进行高精度的三维测量,并且获取管道阻力和阀门阻力实测中压力表和阀门的标高,其精度远高于传统估算方法的.GPS可做到区域内多点同时同步测量,简化了大范围内管线测量的诸多工作程序,极大地提高了工作效率;同时还提高了数字化管网图形精度,在全微机操作条件下避免了人为误差,确保了模型精度,是管网数字化的一种全新作业方式.
Inhalation Exposure Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
K. Rautenstrauch
2004-09-10
This analysis is one of 10 reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. Inhalation Exposure Input Parameters for the Biosphere Model is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the Technical Work Plan for Biosphere Modeling and Expert Support (BSC 2004 [DIRS 169573]). This analysis report defines and justifies values of mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception.
Environmental Transport Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
M. A. Wasiolek
2003-06-27
This analysis report is one of the technical reports documenting the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN), a biosphere model supporting the total system performance assessment (TSPA) for the geologic repository at Yucca Mountain. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows relationships among the reports developed for biosphere modeling and biosphere abstraction products for the TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (TWP) (BSC 2003 [163602]). Some documents in Figure 1-1 may be under development and not available when this report is issued. This figure provides an understanding of how this report contributes to biosphere modeling in support of the license application (LA), but access to the listed documents is not required to understand the contents of this report. This report is one of the reports that develops input parameter values for the biosphere model. The ''Biosphere Model Report'' (BSC 2003 [160699]) describes the conceptual model, the mathematical model, and the input parameters. The purpose of this analysis is to develop biosphere model parameter values related to radionuclide transport and accumulation in the environment. These parameters support calculations of radionuclide concentrations in the environmental media (e.g., soil, crops, animal products, and air) resulting from a given radionuclide concentration at the source of contamination (i.e., either in groundwater or volcanic ash). The analysis was performed in accordance with the TWP (BSC 2003 [163602]). This analysis develops values of parameters associated with many features, events, and processes (FEPs) applicable to the reference biosphere (DTN: M00303SEPFEPS2.000 [162452]), which are addressed in the biosphere model (BSC 2003 [160699]). The treatment of these FEPs is described in BSC (2003 [160699
Construction of constant-Q viscoelastic model with three parameters
Institute of Scientific and Technical Information of China (English)
SUN Cheng-yu; YIN Xing-yao
2007-01-01
The popularly used viscoelastic models have some shortcomings in describing relationship between quality factor (Q) and frequency, which is not consistent with the observation data. Based on the theory of viscoelasticity, a new approach to construct constant-Q viscoelastic model in given frequency band with three parameters is developed. The designed model describes the frequency-independence feature of quality factor very well, and the effect of viscoelasticity on seismic wave field can be studied relatively accurate in theory with this model. Furthermore, the number of required parameters in this model has been reduced fewer than that of other constant-Q models, this can simplify the solution of the viscoelastic problems to some extent. At last, the accuracy and application range have been analyzed through numerical tests. The effect of viscoelasticity on wave propagation has been briefly illustrated through the change of frequency spectra and waveform in several different viscoelastic models.
Global-scale regionalization of hydrologic model parameters
Beck, Hylke E.; van Dijk, Albert I. J. M.; de Roo, Ad; Miralles, Diego G.; McVicar, Tim R.; Schellekens, Jaap; Bruijnzeel, L. Adrian
2016-05-01
Current state-of-the-art models typically applied at continental to global scales (hereafter called macroscale) tend to use a priori parameters, resulting in suboptimal streamflow (Q) simulation. For the first time, a scheme for regionalization of model parameters at the global scale was developed. We used data from a diverse set of 1787 small-to-medium sized catchments (10-10,000 km2) and the simple conceptual HBV model to set up and test the scheme. Each catchment was calibrated against observed daily Q, after which 674 catchments with high calibration and validation scores, and thus presumably good-quality observed Q and forcing data, were selected to serve as donor catchments. The calibrated parameter sets for the donors were subsequently transferred to 0.5° grid cells with similar climatic and physiographic characteristics, resulting in parameter maps for HBV with global coverage. For each grid cell, we used the 10 most similar donor catchments, rather than the single most similar donor, and averaged the resulting simulated Q, which enhanced model performance. The 1113 catchments not used as donors were used to independently evaluate the scheme. The regionalized parameters outperformed spatially uniform (i.e., averaged calibrated) parameters for 79% of the evaluation catchments. Substantial improvements were evident for all major Köppen-Geiger climate types and even for evaluation catchments > 5000 km distant from the donors. The median improvement was about half of the performance increase achieved through calibration. HBV with regionalized parameters outperformed nine state-of-the-art macroscale models, suggesting these might also benefit from the new regionalization scheme. The produced HBV parameter maps including ancillary data are available via www.gloh2o.org.
Bayesian parameter estimation for nonlinear modelling of biological pathways
Directory of Open Access Journals (Sweden)
Ghasemi Omid
2011-12-01
Full Text Available Abstract Background The availability of temporal measurements on biological experiments has significantly promoted research areas in systems biology. To gain insight into the interaction and regulation of biological systems, mathematical frameworks such as ordinary differential equations have been widely applied to model biological pathways and interpret the temporal data. Hill equations are the preferred formats to represent the reaction rate in differential equation frameworks, due to their simple structures and their capabilities for easy fitting to saturated experimental measurements. However, Hill equations are highly nonlinearly parameterized functions, and parameters in these functions cannot be measured easily. Additionally, because of its high nonlinearity, adaptive parameter estimation algorithms developed for linear parameterized differential equations cannot be applied. Therefore, parameter estimation in nonlinearly parameterized differential equation models for biological pathways is both challenging and rewarding. In this study, we propose a Bayesian parameter estimation algorithm to estimate parameters in nonlinear mathematical models for biological pathways using time series data. Results We used the Runge-Kutta method to transform differential equations to difference equations assuming a known structure of the differential equations. This transformation allowed us to generate predictions dependent on previous states and to apply a Bayesian approach, namely, the Markov chain Monte Carlo (MCMC method. We applied this approach to the biological pathways involved in the left ventricle (LV response to myocardial infarction (MI and verified our algorithm by estimating two parameters in a Hill equation embedded in the nonlinear model. We further evaluated our estimation performance with different parameter settings and signal to noise ratios. Our results demonstrated the effectiveness of the algorithm for both linearly and nonlinearly
Mirror symmetry for two-parameter models, 1
Candelas, Philip; Font, A; Katz, S; Morrison, Douglas Robert Ogston; Candelas, Philip; Ossa, Xenia de la; Font, Anamaria; Katz, Sheldon; Morrison, David R.
1994-01-01
We study, by means of mirror symmetry, the quantum geometry of the K\\"ahler-class parameters of a number of Calabi-Yau manifolds that have $b_{11}=2$. Our main interest lies in the structure of the moduli space and in the loci corresponding to singular models. This structure is considerably richer when there are two parameters than in the various one-parameter models that have been studied hitherto. We describe the intrinsic structure of the point in the (compactification of the) moduli space that corresponds to the large complex structure or classical limit. The instanton expansions are of interest owing to the fact that some of the instantons belong to families with continuous parameters. We compute the Yukawa couplings and their expansions in terms of instantons of genus zero. By making use of recent results of Bershadsky et al. we compute also the instanton numbers for instantons of genus one. For particular values of the parameters the models become birational to certain models with one parameter. The co...
Rock thermal conductivity as key parameter for geothermal numerical models
Di Sipio, Eloisa; Chiesa, Sergio; Destro, Elisa; Galgaro, Antonio; Giaretta, Aurelio; Gola, Gianluca; Manzella, Adele
2013-04-01
The geothermal energy applications are undergoing a rapid development. However, there are still several challenges in the successful exploitation of geothermal energy resources. In particular, a special effort is required to characterize the thermal properties of the ground along with the implementation of efficient thermal energy transfer technologies. This paper focuses on understanding the quantitative contribution that geosciences can receive from the characterization of rock thermal conductivity. The thermal conductivity of materials is one of the main input parameters in geothermal modeling since it directly controls the steady state temperature field. An evaluation of this thermal property is required in several fields, such as Thermo-Hydro-Mechanical multiphysics analysis of frozen soils, designing ground source heat pumps plant, modeling the deep geothermal reservoirs structure, assessing the geothermal potential of subsoil. Aim of this study is to provide original rock thermal conductivity values useful for the evaluation of both low and high enthalpy resources at regional or local scale. To overcome the existing lack of thermal conductivity data of sedimentary, igneous and metamorphic rocks, a series of laboratory measurements has been performed on several samples, collected in outcrop, representative of the main lithologies of the regions included in the VIGOR Project (southern Italy). Thermal properties tests were carried out both in dry and wet conditions, using a C-Therm TCi device, operating following the Modified Transient Plane Source method.Measurements were made at standard laboratory conditions on samples both water saturated and dehydrated with a fan-forced drying oven at 70 ° C for 24 hr, for preserving the mineral assemblage and preventing the change of effective porosity. Subsequently, the samples have been stored in an air-conditioned room while bulk density, solid volume and porosity were detected. The measured thermal conductivity
Do Lumped-Parameter Models Provide the Correct Geometrical Damping?
DEFF Research Database (Denmark)
Andersen, Lars
2007-01-01
This paper concerns the formulation of lumped-parameter models for rigid footings on homogenous or stratified soil with focus on the horizontal sliding and rocking. Such models only contain a few degrees of freedom, which makes them ideal for inclusion in aero-elastic codes for wind turbines...
Muscle parameters for musculoskeletal modelling of the human neck
Borst, J.; Forbes, P.A.; Happee, R.; Veeger, H.E.J.
2011-01-01
Background: To study normal or pathological neuromuscular control, a musculoskeletal model of the neck has great potential but a complete and consistent anatomical dataset which comprises the muscle geometry parameters to construct such a model is not yet available. Methods: A dissection experiment
Do Lumped-Parameter Models Provide the Correct Geometrical Damping?
DEFF Research Database (Denmark)
Andersen, Lars
2007-01-01
This paper concerns the formulation of lumped-parameter models for rigid footings on homogenous or stratified soil with focus on the horizontal sliding and rocking. Such models only contain a few degrees of freedom, which makes them ideal for inclusion in aero-elastic codes for wind turbines...
Multiplicity Control in Structural Equation Modeling: Incorporating Parameter Dependencies
Smith, Carrie E.; Cribbie, Robert A.
2013-01-01
When structural equation modeling (SEM) analyses are conducted, significance tests for all important model relationships (parameters including factor loadings, covariances, etc.) are typically conducted at a specified nominal Type I error rate ([alpha]). Despite the fact that many significance tests are often conducted in SEM, rarely is…
Muscle parameters for musculoskeletal modelling of the human neck
Borst, J.; Forbes, P.A.; Happee, R.; Veeger, H.E.J.
2011-01-01
Background: To study normal or pathological neuromuscular control, a musculoskeletal model of the neck has great potential but a complete and consistent anatomical dataset which comprises the muscle geometry parameters to construct such a model is not yet available. Methods: A dissection experiment
Geometry parameters for musculoskeletal modelling of the shoulder system
Van der Helm, F C; Veeger, DirkJan (H. E. J.); Pronk, G M; Van der Woude, L H; Rozendal, R H
1992-01-01
A dynamical finite-element model of the shoulder mechanism consisting of thorax, clavicula, scapula and humerus is outlined. The parameters needed for the model are obtained in a cadaver experiment consisting of both shoulders of seven cadavers. In this paper, in particular, the derivation of geomet
Precise correction to parameter ρ in the littlest Higgs model
Institute of Scientific and Technical Information of China (English)
Farshid Tabbak; F.Farnoudi
2008-01-01
In this paper tree-level violation of weak isospin parameter,ρ in the flame of the littlest Higgs model is studied.The potentially large deviation from the standard model prediction for the ρ in terms of the littlest Higgs model parameters is calculated.The maximum value for ρ for f ＝ 1 TeV,c ＝ 0.05,c'＝ 0.05and v'= 1.5 GeV is ρ = 1.2973 which means a large enhancement than the SM.
Comparative Analysis of Visco-elastic Models with Variable Parameters
Directory of Open Access Journals (Sweden)
Silviu Nastac
2010-01-01
Full Text Available The paper presents a theoretical comparative study for computational behaviour analysis of vibration isolation elements based on viscous and elastic models with variable parameters. The changing of elastic and viscous parameters can be produced by natural timed evolution demo-tion or by heating developed into the elements during their working cycle. It was supposed both linear and non-linear numerical viscous and elastic models, and their combinations. The results show the impor-tance of numerical model tuning with the real behaviour, as such the characteristics linearity, and the essential parameters for damping and rigidity. Multiple comparisons between linear and non-linear simulation cases dignify the basis of numerical model optimization regarding mathematical complexity vs. results reliability.
Calibration of the Transport Parameters of a Local Problem of Water Quality in Igap\\'o I Lake
Romeiro, Neyva M L; Cirilo, Eliandro R; Natti, Paulo L
2011-01-01
The calibration of a model refers to the process by which one can estimate some parameters by comparisons with observed data. Due to the dynamical nature of the environment, variations between predicted and observed values occur. Thus, the environmental parameters may vary due to random temperature changes, time of discharge flow, time of the day, and other conditions. Such variations can be minimized by identifying and optimizing some parameters of the transport model, like the values of diffusion coefficients in x and y directions and the kinetic parameter that describes the process of removing pollutants. This paper presents results concerning the calibration of transport parameters for two-dimensional problems of water quality (fecal coliform control) at Igap\\'o I Lake, located in Londrina, Paran\\'a, Brazil. Thus, the convection-diffusion-reaction equation, which describes mathematically the process studied in this work, is resolved by a semidiscrete finite element method (SUPG) which combines finite diff...
Improvement of Continuous Hydrologic Models and HMS SMA Parameters Reduction
Rezaeian Zadeh, Mehdi; Zia Hosseinipour, E.; Abghari, Hirad; Nikian, Ashkan; Shaeri Karimi, Sara; Moradzadeh Azar, Foad
2010-05-01
Hydrological models can help us to predict stream flows and associated runoff volumes of rainfall events within a watershed. There are many different reasons why we need to model the rainfall-runoff processes of for a watershed. However, the main reason is the limitation of hydrological measurement techniques and the costs of data collection at a fine scale. Generally, we are not able to measure all that we would like to know about a given hydrological systems. This is very particularly the case for ungauged catchments. Since the ultimate aim of prediction using models is to improve decision-making about a hydrological problem, therefore, having a robust and efficient modeling tool becomes an important factor. Among several hydrologic modeling approaches, continuous simulation has the best predictions because it can model dry and wet conditions during a long-term period. Continuous hydrologic models, unlike event based models, account for a watershed's soil moisture balance over a long-term period and are suitable for simulating daily, monthly, and seasonal streamflows. In this paper, we describe a soil moisture accounting (SMA) algorithm added to the hydrologic modeling system (HEC-HMS) computer program. As is well known in the hydrologic modeling community one of the ways for improving a model utility is the reduction of input parameters. The enhanced model developed in this study is applied to Khosrow Shirin Watershed, located in the north-west part of Fars Province in Iran, a data limited watershed. The HMS SMA algorithm divides the potential path of rainfall onto a watershed into five zones. The results showed that the output of HMS SMA is insensitive with the variation of many parameters such as soil storage and soil percolation rate. The study's objective is to remove insensitive parameters from the model input using Multi-objective sensitivity analysis. Keywords: Continuous Hydrologic Modeling, HMS SMA, Multi-objective sensitivity analysis, SMA Parameters
Modeling Water Pollution of Soil
Directory of Open Access Journals (Sweden)
V. Doležel
2008-01-01
depth of 220–300 m below the terrain. As an alternative, thinner stoppers were considered, but this option was discarded.The aim of this paper is to describe the design of the stoppers applied to separate the two types of water along the contact horizon using Desai’s DSC theory (Distinct State Concept, and generalized plane strain in the multiphase problem of water flow in a porous medium. In addition, a comparison of some results from scale experimental models with numerical solutions was carried out. The intrinsic material properties of stoppers for numerical computations were obtained from physical and chemical laboratory tests. The models were evaluated for the complete underground work, particularly in its final stage of construction.
A software for parameter estimation in dynamic models
Directory of Open Access Journals (Sweden)
M. Yuceer
2008-12-01
Full Text Available A common problem in dynamic systems is to determine parameters in an equation used to represent experimental data. The goal is to determine the values of model parameters that provide the best fit to measured data, generally based on some type of least squares or maximum likelihood criterion. In the most general case, this requires the solution of a nonlinear and frequently non-convex optimization problem. Some of the available software lack in generality, while others do not provide ease of use. A user-interactive parameter estimation software was needed for identifying kinetic parameters. In this work we developed an integration based optimization approach to provide a solution to such problems. For easy implementation of the technique, a parameter estimation software (PARES has been developed in MATLAB environment. When tested with extensive example problems from literature, the suggested approach is proven to provide good agreement between predicted and observed data within relatively less computing time and iterations.
Condition Parameter Modeling for Anomaly Detection in Wind Turbines
Directory of Open Access Journals (Sweden)
Yonglong Yan
2014-05-01
Full Text Available Data collected from the supervisory control and data acquisition (SCADA system, used widely in wind farms to obtain operational and condition information about wind turbines (WTs, is of important significance for anomaly detection in wind turbines. The paper presents a novel model for wind turbine anomaly detection mainly based on SCADA data and a back-propagation neural network (BPNN for automatic selection of the condition parameters. The SCADA data sets are determined through analysis of the cumulative probability distribution of wind speed and the relationship between output power and wind speed. The automatic BPNN-based parameter selection is for reduction of redundant parameters for anomaly detection in wind turbines. Through investigation of cases of WT faults, the validity of the automatic parameter selection-based model for WT anomaly detection is verified.
Parameter Estimation of Photovoltaic Models via Cuckoo Search
Directory of Open Access Journals (Sweden)
Jieming Ma
2013-01-01
Full Text Available Since conventional methods are incapable of estimating the parameters of Photovoltaic (PV models with high accuracy, bioinspired algorithms have attracted significant attention in the last decade. Cuckoo Search (CS is invented based on the inspiration of brood parasitic behavior of some cuckoo species in combination with the Lévy flight behavior. In this paper, a CS-based parameter estimation method is proposed to extract the parameters of single-diode models for commercial PV generators. Simulation results and experimental data show that the CS algorithm is capable of obtaining all the parameters with extremely high accuracy, depicted by a low Root-Mean-Squared-Error (RMSE value. The proposed method outperforms other algorithms applied in this study.
Li, Ning; McLaughlin, Dennis; Kinzelbach, Wolfgang; Li, WenPeng; Dong, XinGuang
2015-10-01
Model uncertainty needs to be quantified to provide objective assessments of the reliability of model predictions and of the risk associated with management decisions that rely on these predictions. This is particularly true in water resource studies that depend on model-based assessments of alternative management strategies. In recent decades, Bayesian data assimilation methods have been widely used in hydrology to assess uncertain model parameters and predictions. In this case study, a particular data assimilation algorithm, the Ensemble Smoother with Multiple Data Assimilation (ESMDA) (Emerick and Reynolds, 2012), is used to derive posterior samples of uncertain model parameters and forecasts for a distributed hydrological model of Yanqi basin, China. This model is constructed using MIKESHE/MIKE11software, which provides for coupling between surface and subsurface processes (DHI, 2011a-d). The random samples in the posterior parameter ensemble are obtained by using measurements to update 50 prior parameter samples generated with a Latin Hypercube Sampling (LHS) procedure. The posterior forecast samples are obtained from model runs that use the corresponding posterior parameter samples. Two iterative sample update methods are considered: one based on an a perturbed observation Kalman filter update and one based on a square root Kalman filter update. These alternatives give nearly the same results and converge in only two iterations. The uncertain parameters considered include hydraulic conductivities, drainage and river leakage factors, van Genuchten soil property parameters, and dispersion coefficients. The results show that the uncertainty in many of the parameters is reduced during the smoother updating process, reflecting information obtained from the observations. Some of the parameters are insensitive and do not benefit from measurement information. The correlation coefficients among certain parameters increase in each iteration, although they generally
Parameter Estimation for Single Diode Models of Photovoltaic Modules
Energy Technology Data Exchange (ETDEWEB)
Hansen, Clifford [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Photovoltaic and Distributed Systems Integration Dept.
2015-03-01
Many popular models for photovoltaic system performance employ a single diode model to compute the I - V curve for a module or string of modules at given irradiance and temperature conditions. A single diode model requires a number of parameters to be estimated from measured I - V curves. Many available parameter estimation methods use only short circuit, o pen circuit and maximum power points for a single I - V curve at standard test conditions together with temperature coefficients determined separately for individual cells. In contrast, module testing frequently records I - V curves over a wide range of irradi ance and temperature conditions which, when available , should also be used to parameterize the performance model. We present a parameter estimation method that makes use of a fu ll range of available I - V curves. We verify the accuracy of the method by recov ering known parameter values from simulated I - V curves . We validate the method by estimating model parameters for a module using outdoor test data and predicting the outdoor performance of the module.
Automatic Determination of the Conic Coronal Mass Ejection Model Parameters
Pulkkinen, A.; Oates, T.; Taktakishvili, A.
2009-01-01
Characterization of the three-dimensional structure of solar transients using incomplete plane of sky data is a difficult problem whose solutions have potential for societal benefit in terms of space weather applications. In this paper transients are characterized in three dimensions by means of conic coronal mass ejection (CME) approximation. A novel method for the automatic determination of cone model parameters from observed halo CMEs is introduced. The method uses both standard image processing techniques to extract the CME mass from white-light coronagraph images and a novel inversion routine providing the final cone parameters. A bootstrap technique is used to provide model parameter distributions. When combined with heliospheric modeling, the cone model parameter distributions will provide direct means for ensemble predictions of transient propagation in the heliosphere. An initial validation of the automatic method is carried by comparison to manually determined cone model parameters. It is shown using 14 halo CME events that there is reasonable agreement, especially between the heliocentric locations of the cones derived with the two methods. It is argued that both the heliocentric locations and the opening half-angles of the automatically determined cones may be more realistic than those obtained from the manual analysis
Accounting for Water Insecurity in Modeling Domestic Water Demand
Galaitsis, S. E.; Huber-lee, A. T.; Vogel, R. M.; Naumova, E.
2013-12-01
Water demand management uses price elasticity estimates to predict consumer demand in relation to water pricing changes, but studies have shown that many additional factors effect water consumption. Development scholars document the need for water security, however, much of the water security literature focuses on broad policies which can influence water demand. Previous domestic water demand studies have not considered how water security can affect a population's consumption behavior. This study is the first to model the influence of water insecurity on water demand. A subjective indicator scale measuring water insecurity among consumers in the Palestinian West Bank is developed and included as a variable to explore how perceptions of control, or lack thereof, impact consumption behavior and resulting estimates of price elasticity. A multivariate regression model demonstrates the significance of a water insecurity variable for data sets encompassing disparate water access. When accounting for insecurity, the R-squaed value improves and the marginal price a household is willing to pay becomes a significant predictor for the household quantity consumption. The model denotes that, with all other variables held equal, a household will buy more water when the users are more water insecure. Though the reasons behind this trend require further study, the findings suggest broad policy implications by demonstrating that water distribution practices in scarcity conditions can promote consumer welfare and efficient water use.
Estimation of the parameters of ETAS models by Simulated Annealing
Lombardi, Anna Maria
2015-01-01
This paper proposes a new algorithm to estimate the maximum likelihood parameters of an Epidemic Type Aftershock Sequences (ETAS) model. It is based on Simulated Annealing, a versatile method that solves problems of global optimization and ensures convergence to a global optimum. The procedure is tested on both simulated and real catalogs. The main conclusion is that the method performs poorly as the size of the catalog decreases because the effect of the correlation of the ETAS parameters is...
CADLIVE optimizer: web-based parameter estimation for dynamic models
Directory of Open Access Journals (Sweden)
Inoue Kentaro
2012-08-01
Full Text Available Abstract Computer simulation has been an important technique to capture the dynamics of biochemical networks. In most networks, however, few kinetic parameters have been measured in vivo because of experimental complexity. We develop a kinetic parameter estimation system, named the CADLIVE Optimizer, which comprises genetic algorithms-based solvers with a graphical user interface. This optimizer is integrated into the CADLIVE Dynamic Simulator to attain efficient simulation for dynamic models.
Oscillating water column structural model
Energy Technology Data Exchange (ETDEWEB)
Copeland, Guild [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bull, Diana L [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Jepsen, Richard Alan [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Gordon, Margaret Ellen [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2014-09-01
An oscillating water column (OWC) wave energy converter is a structure with an opening to the ocean below the free surface, i.e. a structure with a moonpool. Two structural models for a non-axisymmetric terminator design OWC, the Backward Bent Duct Buoy (BBDB) are discussed in this report. The results of this structural model design study are intended to inform experiments and modeling underway in support of the U.S. Department of Energy (DOE) initiated Reference Model Project (RMP). A detailed design developed by Re Vision Consulting used stiffeners and girders to stabilize the structure against the hydrostatic loads experienced by a BBDB device. Additional support plates were added to this structure to account for loads arising from the mooring line attachment points. A simplified structure was designed in a modular fashion. This simplified design allows easy alterations to the buoyancy chambers and uncomplicated analysis of resulting changes in buoyancy.
Reference physiological parameters for pharmacodynamic modeling of liver cancer
Energy Technology Data Exchange (ETDEWEB)
Travis, C.C.; Arms, A.D.
1988-01-01
This document presents a compilation of measured values for physiological parameters used in pharamacodynamic modeling of liver cancer. The physiological parameters include body weight, liver weight, the liver weight/body weight ratio, and number of hepatocytes. Reference values for use in risk assessment are given for each of the physiological parameters based on analyses of valid measurements taken from the literature and other reliable sources. The proposed reference values for rodents include sex-specific measurements for the B6C3F{sub 1}, mice and Fishcer 344/N, Sprague-Dawley, and Wistar rats. Reference values are also provided for humans. 102 refs., 65 tabs.
Uncertainty of Modal Parameters Estimated by ARMA Models
DEFF Research Database (Denmark)
Jensen, Jacob Laigaard; Brincker, Rune; Rytter, Anders
1990-01-01
In this paper the uncertainties of identified modal parameters such as eidenfrequencies and damping ratios are assed. From the measured response of dynamic excited structures the modal parameters may be identified and provide important structural knowledge. However the uncertainty of the parameters...... by simulation study of a lightly damped single degree of freedom system. Identification by ARMA models has been choosen as system identification method. It is concluded that both the sampling interval and number of sampled points may play a significant role with respect to the statistical errors. Furthermore...
X-Parameter Based Modelling of Polar Modulated Power Amplifiers
DEFF Research Database (Denmark)
Wang, Yelin; Nielsen, Troels Studsgaard; Sira, Daniel
2013-01-01
X-parameters are developed as an extension of S-parameters capable of modelling non-linear devices driven by large signals. They are suitable for devices having only radio frequency (RF) and DC ports. In a polar power amplifier (PA), phase and envelope of the input modulated signal are applied...... at separate ports and the envelope port is neither an RF nor a DC port. As a result, X-parameters may fail to characterise the effect of the envelope port excitation and consequently the polar PA. This study introduces a solution to the problem for a commercial polar PA. In this solution, the RF-phase path...
Understanding transport in model water desalination membranes
Chan, Edwin
Polyamide based thin film composites represent the the state-of-the-art nanofiltration and reverse osmosis membranes used in water desalination. The performance of these membranes is enabled by the ultrathin (~100 nm) crosslinked polyamide film in facilitating the selective transport of water over salt ions. While these materials have been refined over the last several decades, understanding the relationships between polyamide structure and membrane performance remains a challenge because of the complex and heterogeneous nature of the polyamide film. In this contribution, we present our approach to addressing this challenge by studying the transport properties of model polyamide membranes synthesized via molecular layer-by-layer (mLbL) assembly. First, we demonstrate that mLbL can successfully construct polyamide membranes with well-defined nanoscale thickness and roughness using a variety of monomer formulations. Next, we present measurement tools for characterizing the network structure and transport of these model polyamide membranes. Specifically, we used X-ray and neutron scattering techniques to characterize their structure as well as a recently-developed indentation based poromechanics approach to extrapolate their water diffusion coefficient. Finally, we illustrate how these measurements can provide insight into the original problem by linking the key polyamide network properties, i.e. water-polyamide interaction parameter and characteristic network mesh size, to the membrane performance.
A Bayesian framework for parameter estimation in dynamical models.
Directory of Open Access Journals (Sweden)
Flávio Codeço Coelho
Full Text Available Mathematical models in biology are powerful tools for the study and exploration of complex dynamics. Nevertheless, bringing theoretical results to an agreement with experimental observations involves acknowledging a great deal of uncertainty intrinsic to our theoretical representation of a real system. Proper handling of such uncertainties is key to the successful usage of models to predict experimental or field observations. This problem has been addressed over the years by many tools for model calibration and parameter estimation. In this article we present a general framework for uncertainty analysis and parameter estimation that is designed to handle uncertainties associated with the modeling of dynamic biological systems while remaining agnostic as to the type of model used. We apply the framework to fit an SIR-like influenza transmission model to 7 years of incidence data in three European countries: Belgium, the Netherlands and Portugal.
Simultaneous estimation of parameters in the bivariate Emax model.
Magnusdottir, Bergrun T; Nyquist, Hans
2015-12-10
In this paper, we explore inference in multi-response, nonlinear models. By multi-response, we mean models with m > 1 response variables and accordingly m relations. Each parameter/explanatory variable may appear in one or more of the relations. We study a system estimation approach for simultaneous computation and inference of the model and (co)variance parameters. For illustration, we fit a bivariate Emax model to diabetes dose-response data. Further, the bivariate Emax model is used in a simulation study that compares the system estimation approach to equation-by-equation estimation. We conclude that overall, the system estimation approach performs better for the bivariate Emax model when there are dependencies among relations. The stronger the dependencies, the more we gain in precision by using system estimation rather than equation-by-equation estimation.
Water Hammer Model of Shock Absorber Throttle Slice
Institute of Scientific and Technical Information of China (English)
CHEN Yi-jie; GU Liang; LEI Sheng-guang; GUAN Ji-fu
2008-01-01
In allusion to easy invalidation of damping valve in vehicle shock absorber caused by the impact from the road surface, the importance of the study of damping valve water hammer pressure is presented. The physical model of damping valve with the circle throttle slice is established. The time for the throttle slice deformation is studied by using the finite software, and the laws that how the structure parameters affect the deformation time are obtained. Combining the theory of water hammer, the water hammer initial and boundary condition of the damping valve is deduced, and the water hammer model of throttle slice is established. The analysis of simulation results indicates that the water hammer pressure amplitude and the amount of water hammer oscillation period can be reduced and the dependability of the valve can be enhanced by modifying the structure parameters and aperture width between slice and valve body.
Linear regression models of floor surface parameters on friction between Neolite and quarry tiles.
Chang, Wen-Ruey; Matz, Simon; Grönqvist, Raoul; Hirvonen, Mikko
2010-01-01
For slips and falls, friction is widely used as an indicator of surface slipperiness. Surface parameters, including surface roughness and waviness, were shown to influence friction by correlating individual surface parameters with the measured friction. A collective input from multiple surface parameters as a predictor of friction, however, could provide a broader perspective on the contributions from all the surface parameters evaluated. The objective of this study was to develop regression models between the surface parameters and measured friction. The dynamic friction was measured using three different mixtures of glycerol and water as contaminants. Various surface roughness and waviness parameters were measured using three different cut-off lengths. The regression models indicate that the selected surface parameters can predict the measured friction coefficient reliably in most of the glycerol concentrations and cut-off lengths evaluated. The results of the regression models were, in general, consistent with those obtained from the correlation between individual surface parameters and the measured friction in eight out of nine conditions evaluated in this experiment. A hierarchical regression model was further developed to evaluate the cumulative contributions of the surface parameters in the final iteration by adding these parameters to the regression model one at a time from the easiest to measure to the most difficult to measure and evaluating their impacts on the adjusted R(2) values. For practical purposes, the surface parameter R(a) alone would account for the majority of the measured friction even if it did not reach a statistically significant level in some of the regression models.
Shape parameter estimate for a glottal model without time position
Degottex, Gilles; Roebel, Axel; Rodet, Xavier
2009-01-01
cote interne IRCAM: Degottex09a; None / None; National audience; From a recorded speech signal, we propose to estimate a shape parameter of a glottal model without estimating his time position. Indeed, the literature usually propose to estimate the time position first (ex. by detecting Glottal Closure Instants). The vocal-tract filter estimate is expressed as a minimum-phase envelope estimation after removing the glottal model and a standard lips radiation model. Since this filter is mainly b...
Light-Front Spin-1 Model: Parameters Dependence
Mello, Clayton S; de Melo, J P B C; Frederico, T
2015-01-01
We study the structure of the $\\rho$-meson within a light-front model with constituent quark degrees of freedom. We calculate electroweak static observables: magnetic and quadrupole moments, decay constant and charge radius. The prescription used to compute the electroweak quantities is free of zero modes, which makes the calculation implicitly covariant. We compare the results of our model with other ones found in the literature. Our model parameters give a decay constant close to the experimental one.
Cosmological Models with Variable Deceleration Parameter in Lyra's Manifold
Pradhan, A; Singh, C B
2006-01-01
FRW models of the universe have been studied in the cosmological theory based on Lyra's manifold. A new class of exact solutions has been obtained by considering a time dependent displacement field for variable deceleration parameter from which three models of the universe are derived (i) exponential (ii) polynomial and (iii) sinusoidal form respectively. The behaviour of these models of the universe are also discussed. Finally some possibilities of further problems and their investigations have been pointed out.
Water-sediment flow models for river reaches sediment related pollution control.
Sil, Briti Sundar; Choudhury, Parthasarathi
2012-07-01
Hybrid water-sediment flow models for river reaches have been for predicting sediment and sediment related pollutions in water courses. The models are developed by combining sediment rating model and the Muskingum model applicable for a reach. The models incorporate sediment concentration and water discharge variables for a river reach; allow defining downstream sediment rating curve in terms of upstream water discharges. The model is useful in generating sediment concentration graph for a station having no water discharge records. The hybrid models provide forecasting forms that can be used to forecast downstream sediment concentration/water discharges 2kx time unit ahead. The forecasting models are useful for applications in real time namely, in the real time management of sediment related pollution in water courses and in issuing flood warning. Integration of sediment rating model and the Muskingum model increases model parameters and nonlinearity requiring efficient estimation technique for parameter identification. To identify parameters in the hybrid models genetic algorithm (GA) based optimization technique can be used. The new model relies on the Muskingum model, obey continuity requirement and the parameters can be used in the Muskingum model with water discharges to estimate/predict downstream water discharge values. The proposed model formulations are demonstrated for simulating and forecasting sediment concentration and water discharges in the Mississippi River Basin, USA. Model parameters are estimated using non-dominated sorting Genetic Algorithm II (NSGA-II). Model results show satisfactory model performances.
Identification of slow molecular order parameters for Markov model construction
Perez-Hernandez, Guillermo; Giorgino, Toni; de Fabritiis, Gianni; Noé, Frank
2013-01-01
A goal in the kinetic characterization of a macromolecular system is the description of its slow relaxation processes, involving (i) identification of the structural changes involved in these processes, and (ii) estimation of the rates or timescales at which these slow processes occur. Most of the approaches to this task, including Markov models, Master-equation models, and kinetic network models, start by discretizing the high-dimensional state space and then characterize relaxation processes in terms of the eigenvectors and eigenvalues of a discrete transition matrix. The practical success of such an approach depends very much on the ability to finely discretize the slow order parameters. How can this task be achieved in a high-dimensional configuration space without relying on subjective guesses of the slow order parameters? In this paper, we use the variational principle of conformation dynamics to derive an optimal way of identifying the "slow subspace" of a large set of prior order parameters - either g...
Solar Model Parameters and Direct Measurements of Solar Neutrino Fluxes
Bandyopadhyay, A; Goswami, S; Petcov, S T; Bandyopadhyay, Abhijit; Choubey, Sandhya; Goswami, Srubabati
2006-01-01
We explore a novel possibility of determining the solar model parameters, which serve as input in the calculations of the solar neutrino fluxes, by exploiting the data from direct measurements of the fluxes. More specifically, we use the rather precise value of the $^8B$ neutrino flux, $\\phi_B$ obtained from the global analysis of the solar neutrino and KamLAND data, to derive constraints on each of the solar model parameters on which $\\phi_B$ depends. We also use more precise values of $^7Be$ and $pp$ fluxes as can be obtained from future prospective data and discuss whether such measurements can help in reducing the uncertainties of one or more input parameters of the Standard Solar Model.
IP-Sat: Impact-Parameter dependent Saturation model; revised
Rezaeian, Amir H; Van de Klundert, Merijn; Venugopalan, Raju
2013-01-01
In this talk, we present a global analysis of available small-x data on inclusive DIS and exclusive diffractive processes, including the latest data from the combined HERA analysis on reduced cross sections within the Impact-Parameter dependent Saturation (IP-Sat) Model. The impact-parameter dependence of dipole amplitude is crucial in order to have a unified description of both inclusive and exclusive diffractive processes. With the parameters of model fixed via a fit to the high-precision reduced cross-section, we compare model predictions to data for the structure functions, the longitudinal structure function, the charm structure function, exclusive vector mesons production and Deeply Virtual Compton Scattering (DVCS). Excellent agreement is obtained for the processes considered at small x in a wide range of Q^2.
QCD-inspired determination of NJL model parameters
Springer, Paul; Rechenberger, Stefan; Rennecke, Fabian
2016-01-01
The QCD phase diagram at finite temperature and density has attracted considerable interest over many decades now, not least because of its relevance for a better understanding of heavy-ion collision experiments. Models provide some insight into the QCD phase structure but usually rely on various parameters. Based on renormalization group arguments, we discuss how the parameters of QCD low-energy models can be determined from the fundamental theory of the strong interaction. We particularly focus on a determination of the temperature dependence of these parameters in this work and comment on the effect of a finite quark chemical potential. We present first results and argue that our findings can be used to improve the predictive power of future model calculations.
SPOTting model parameters using a ready-made Python package
Houska, Tobias; Kraft, Philipp; Breuer, Lutz
2015-04-01
The selection and parameterization of reliable process descriptions in ecological modelling is driven by several uncertainties. The procedure is highly dependent on various criteria, like the used algorithm, the likelihood function selected and the definition of the prior parameter distributions. A wide variety of tools have been developed in the past decades to optimize parameters. Some of the tools are closed source. Due to this, the choice for a specific parameter estimation method is sometimes more dependent on its availability than the performance. A toolbox with a large set of methods can support users in deciding about the most suitable method. Further, it enables to test and compare different methods. We developed the SPOT (Statistical Parameter Optimization Tool), an open source python package containing a comprehensive set of modules, to analyze and optimize parameters of (environmental) models. SPOT comes along with a selected set of algorithms for parameter optimization and uncertainty analyses (Monte Carlo, MC; Latin Hypercube Sampling, LHS; Maximum Likelihood, MLE; Markov Chain Monte Carlo, MCMC; Scuffled Complex Evolution, SCE-UA; Differential Evolution Markov Chain, DE-MCZ), together with several likelihood functions (Bias, (log-) Nash-Sutcliff model efficiency, Correlation Coefficient, Coefficient of Determination, Covariance, (Decomposed-, Relative-, Root-) Mean Squared Error, Mean Absolute Error, Agreement Index) and prior distributions (Binomial, Chi-Square, Dirichlet, Exponential, Laplace, (log-, multivariate-) Normal, Pareto, Poisson, Cauchy, Uniform, Weibull) to sample from. The model-independent structure makes it suitable to analyze a wide range of applications. We apply all algorithms of the SPOT package in three different case studies. Firstly, we investigate the response of the Rosenbrock function, where the MLE algorithm shows its strengths. Secondly, we study the Griewank function, which has a challenging response surface for
Synchronous Generator Model Parameter Estimation Based on Noisy Dynamic Waveforms
Berhausen, Sebastian; Paszek, Stefan
2016-01-01
In recent years, there have occurred system failures in many power systems all over the world. They have resulted in a lack of power supply to a large number of recipients. To minimize the risk of occurrence of power failures, it is necessary to perform multivariate investigations, including simulations, of power system operating conditions. To conduct reliable simulations, the current base of parameters of the models of generating units, containing the models of synchronous generators, is necessary. In the paper, there is presented a method for parameter estimation of a synchronous generator nonlinear model based on the analysis of selected transient waveforms caused by introducing a disturbance (in the form of a pseudorandom signal) in the generator voltage regulation channel. The parameter estimation was performed by minimizing the objective function defined as a mean square error for deviations between the measurement waveforms and the waveforms calculated based on the generator mathematical model. A hybrid algorithm was used for the minimization of the objective function. In the paper, there is described a filter system used for filtering the noisy measurement waveforms. The calculation results of the model of a 44 kW synchronous generator installed on a laboratory stand of the Institute of Electrical Engineering and Computer Science of the Silesian University of Technology are also given. The presented estimation method can be successfully applied to parameter estimation of different models of high-power synchronous generators operating in a power system.
Optimizing Muscle Parameters in Musculoskeletal Modeling Using Monte Carlo Simulations
Hanson, Andrea; Reed, Erik; Cavanagh, Peter
2011-01-01
Astronauts assigned to long-duration missions experience bone and muscle atrophy in the lower limbs. The use of musculoskeletal simulation software has become a useful tool for modeling joint and muscle forces during human activity in reduced gravity as access to direct experimentation is limited. Knowledge of muscle and joint loads can better inform the design of exercise protocols and exercise countermeasure equipment. In this study, the LifeModeler(TM) (San Clemente, CA) biomechanics simulation software was used to model a squat exercise. The initial model using default parameters yielded physiologically reasonable hip-joint forces. However, no activation was predicted in some large muscles such as rectus femoris, which have been shown to be active in 1-g performance of the activity. Parametric testing was conducted using Monte Carlo methods and combinatorial reduction to find a muscle parameter set that more closely matched physiologically observed activation patterns during the squat exercise. Peak hip joint force using the default parameters was 2.96 times body weight (BW) and increased to 3.21 BW in an optimized, feature-selected test case. The rectus femoris was predicted to peak at 60.1% activation following muscle recruitment optimization, compared to 19.2% activation with default parameters. These results indicate the critical role that muscle parameters play in joint force estimation and the need for exploration of the solution space to achieve physiologically realistic muscle activation.
Modeling Source Water Threshold Exceedances with Extreme Value Theory
Rajagopalan, B.; Samson, C.; Summers, R. S.
2016-12-01
Variability in surface water quality, influenced by seasonal and long-term climate changes, can impact drinking water quality and treatment. In particular, temperature and precipitation can impact surface water quality directly or through their influence on streamflow and dilution capacity. Furthermore, they also impact land surface factors, such as soil moisture and vegetation, which can in turn affect surface water quality, in particular, levels of organic matter in surface waters which are of concern. All of these will be exacerbated by anthropogenic climate change. While some source water quality parameters, particularly Total Organic Carbon (TOC) and bromide concentrations, are not directly regulated for drinking water, these parameters are precursors to the formation of disinfection byproducts (DBPs), which are regulated in drinking water distribution systems. These DBPs form when a disinfectant, added to the water to protect public health against microbial pathogens, most commonly chlorine, reacts with dissolved organic matter (DOM), measured as TOC or dissolved organic carbon (DOC), and inorganic precursor materials, such as bromide. Therefore, understanding and modeling the extremes of TOC and Bromide concentrations is of critical interest for drinking water utilities. In this study we develop nonstationary extreme value analysis models for threshold exceedances of source water quality parameters, specifically TOC and bromide concentrations. In this, the threshold exceedances are modeled as Generalized Pareto Distribution (GPD) whose parameters vary as a function of climate and land surface variables - thus, enabling to capture the temporal nonstationarity. We apply these to model threshold exceedance of source water TOC and bromide concentrations at two locations with different climate and find very good performance.
Shanmugam, Palanisamy; Varunan, Theenathayalan; Nagendra Jaiganesh, S. N.; Sahay, Arvind; Chauhan, Prakash
2016-06-01
Prediction of the curve of the absorption coefficient of colored dissolved organic matter (CDOM) and differentiation between marine and terrestrially derived CDOM pools in coastal environments are hampered by a high degree of variability in the composition and concentration of CDOM, uncertainties in retrieved remote sensing reflectance and the weak signal-to-noise ratio of space-borne instruments. In the present study, a hybrid model is presented along with empirical methods to remotely determine the amount and type of CDOM in coastal and inland water environments. A large set of in-situ data collected on several oceanographic cruises and field campaigns from different regional waters was used to develop empirical methods for studying the distribution and dynamics of CDOM, dissolved organic carbon (DOC) and salinity. Our validation analyses demonstrated that the hybrid model is a better descriptor of CDOM absorption spectra compared to the existing models. Additional spectral slope parameters included in the present model to differentiate between terrestrially derived and marine CDOM pools make a substantial improvement over those existing models. Empirical algorithms to derive CDOM, DOC and salinity from remote sensing reflectance data demonstrated success in retrieval of these products with significantly low mean relative percent differences from large in-situ measurements. The performance of these algorithms was further assessed using three hyperspectral HICO images acquired simultaneously with our field measurements in productive coastal and lagoon waters on the southeast part of India. The validation match-ups of CDOM and salinity showed good agreement between HICO retrievals and field observations. Further analyses of these data showed significant temporal changes in CDOM and phytoplankton absorption coefficients with a distinct phase shift between these two products. Healthy phytoplankton cells and macrophytes were recognized to directly contribute to the
Comparing spatial and temporal transferability of hydrological model parameters
Patil, Sopan; Stieglitz, Marc
2015-04-01
Operational use of hydrological models requires the transfer of calibrated parameters either in time (for streamflow forecasting) or space (for prediction at ungauged catchments) or both. Although the effects of spatial and temporal parameter transfer on catchment streamflow predictions have been well studied individually, a direct comparison of these approaches is much less documented. In our view, such comparison is especially pertinent in the context of increasing appeal and popularity of the "trading space for time" approaches that are proposed for assessing the hydrological implications of anthropogenic climate change. Here, we compare three different schemes of parameter transfer, viz., temporal, spatial, and spatiotemporal, using a spatially lumped hydrological model called EXP-HYDRO at 294 catchments across the continental United States. Results show that the temporal parameter transfer scheme performs best, with lowest decline in prediction performance (median decline of 4.2%) as measured using the Kling-Gupta efficiency metric. More interestingly, negligible difference in prediction performance is observed between the spatial and spatiotemporal parameter transfer schemes (median decline of 12.4% and 13.9% respectively). We further demonstrate that the superiority of temporal parameter transfer scheme is preserved even when: (1) spatial distance between donor and receiver catchments is reduced, or (2) temporal lag between calibration and validation periods is increased. Nonetheless, increase in the temporal lag between calibration and validation periods reduces the overall performance gap between the three parameter transfer schemes. Results suggest that spatiotemporal transfer of hydrological model parameters has the potential to be a viable option for climate change related hydrological studies, as envisioned in the "trading space for time" framework. However, further research is still needed to explore the relationship between spatial and temporal
Water losses dynamic modelling in water distribution networks
Puleo, Valeria; Milici, Barbara
2015-12-01
In the last decades, one of the main concerns of the water system managers have been the minimisation of water losses, that frequently reach values of 30% or even 70% of the volume supplying the water distribution network. The economic and social costs associated with water losses in modern water supply systems are rapidly rising to unacceptably high levels. Furthermore, the problem of the water losses assumes more and more importance mainly when periods of water scarcity occur or when not sufficient water supply takes part in areas with fast growth. In the present analysis, a dynamic model was used for estimating real and apparent losses of a real case study. A specific nodal demand model reflecting the user's tank installation and a specific apparent losses module were implemented. The results from the dynamic model were compared with the modelling estimation based on a steady-state approach.
Parameters influencing deposit estimation when using water sensitive papers
Directory of Open Access Journals (Sweden)
Emanuele Cerruto
2013-10-01
Full Text Available The aim of the study was to assess the possibility of using water sensitive papers (WSP to estimate the amount of deposit on the target when varying the spray characteristics. To identify the main quantities influencing the deposit, some simplifying hypotheses were applied to simulate WSP behaviour: log-normal distribution of the diameters of the drops and circular stains randomly placed on the images. A very large number (4704 of images of WSPs were produced by means of simulation. The images were obtained by simulating drops of different arithmetic mean diameter (40-300 μm, different coefficient of variation (0.1-1.5, and different percentage of covered surface (2-100%, not considering overlaps. These images were considered to be effective WSP images and then analysed using image processing software in order to measure the percentage of covered surface, the number of particles, and the area of each particle; the deposit was then calculated. These data were correlated with those used to produce the images, varying the spray characteristics. As far as the drop populations are concerned, a classification based on the volume median diameter only should be avoided, especially in case of high variability. This, in fact, results in classifying sprays with very low arithmetic mean diameter as extremely or ultra coarse. The WSP image analysis shows that the relation between simulated and computed percentage of covered surface is independent of the type of spray, whereas impact density and unitary deposit can be estimated from the computed percentage of covered surface only if the spray characteristics (arithmetic mean and coefficient of variation of the drop diameters are known. These data can be estimated by analysing the particles on the WSP images. The results of a validation test show good agreement between simulated and computed deposits, testified by a high (0.93 coefficient of determination.
Monthly Water Balance Model Hydrology Futures
Bock, Andy; Hay, Lauren E.; Markstrom, Steven; Atkinson, R. Dwight
2016-01-01
A monthly water balance model (MWBM) was driven with precipitation and temperature using a station-based dataset for current conditions (1950 to 2010) and selected statistically-downscaled general circulation models (GCMs) for current and future conditions (1950 to 2099) across the conterminous United States (CONUS) using hydrologic response units from the Geospatial Fabric for National Hydrologic Modeling (http://dx.doi.org/doi:10.5066/F7542KMD). Six MWBM output variables (actual evapotranspiration (AET), potential evapotranspiration (PET), runoff (RO), streamflow (STRM), soil moisture storage (SOIL), and snow water equivalent (SWE)) and the two MWBM input variables (atmospheric temperature (TAVE) and precipitation (PPT)) were summarized for hydrologic response units and aggregated at points of interest on a stream network. Results were then organized into the Monthly Water Balance Hydrology Futures database, an open-access database using netCDF format (http://cida-eros-mows1.er.usgs.gov/thredds/dodsC/nwb_pub/). Methods used to calibrate and parameterize the MWBM are detailed in the Hydrology and Earth System Sciences (HESS) paper "Parameter regionalization of a monthly water balance model for the conterminous United States" by Bock and others (2016). See the discussion paper link in the "Related External Resources" section for access. Supplemental data files related to the plots and data analysis in Bock and others (2016) can be found in the HESS-2015-325.zip folder in the "Attached Files" section. Detailed information on the files and data can be found in the ReadMe.txt contained within the zipped folder. Recommended citation of discussion paper:Bock, A.R., Hay, L.E., McCabe, G.J., Markstrom, S.L., and Atkinson, R.D., 2016, Parameter regionalization of a monthly water balance model for the conterminous United States: Hydrology and Earth System Sciences, v. 20, 2861-2876, doi:10.5194/hess-20-2861-2016, 2016
Clusters of classical water models
Kiss, Péter T.; Baranyai, András
2009-11-01
The properties of clusters can be used as tests of models constructed for molecular simulation of water. We searched for configurations with minimal energies for a small number of molecules. We identified topologically different structures close to the absolute energy minimum of the system by calculating overlap integrals and enumerating hydrogen bonds. Starting from the dimer, we found increasing number of topologically different, low-energy arrangements for the trimer(3), the tetramer(6), the pentamer(6), and the hexamer(9). We studied simple models with polarizable point dipole. These were the BSV model [J. Brodholt et al., Mol. Phys. 86, 149 (1995)], the DC model [L. X. Dang and T. M. Chang, J. Chem. Phys. 106, 8149 (1997)], and the GCP model [P. Paricaud et al., J. Chem. Phys. 122, 244511 (2005)]. As an alternative the SWM4-DP and the SWM4-NDP charge-on-spring models [G. Lamoureux et al., Chem. Phys. Lett. 418, 245 (2006)] were also investigated. To study the impact of polarizability restricted to the plane of the molecule we carried out calculations for the SPC-FQ and TIP4P-FQ models, too [S. W. Rick et al., J. Chem. Phys. 101, 6141 (1994)]. In addition to them, justified by their widespread use even for near critical or surface behavior calculations, we identified clusters for five nonpolarizable models of ambient water, SPC/E [H. J. C. Berendsen et al., J. Phys. Chem. 91, 6269 (1987)], TIP4P [W. L. Jorgensen et al., J. Chem. Phys. 79, 926 (1983)], TIP4P-EW [H. W. Horn et al., J. Chem. Phys. 120, 9665 (2004)], and TIP4P/2005 [J. L. F. Abascal and C. Vega, J. Chem. Phys. 123, 234505 (2005)]. The fifth was a five-site model named TIP5P [M. W. Mahoney and W. L. Jorgensen, J. Chem. Phys. 112, 8910 (2000)]. To see the impact of the vibrations we studied the flexible SPC model. [K. Toukan and A. Rahman, Phys. Rev. B 31, 2643 (1985)]. We evaluated the results comparing them with experimental data and quantum chemical calculations. The position of the negative
Directory of Open Access Journals (Sweden)
Mousong Wu
2016-02-01
Full Text Available Water and energy processes in frozen soils are important for better understanding hydrologic processes and water resources management in cold regions. To investigate the water and energy balance in seasonally frozen soils, CoupModel combined with the generalized likelihood uncertainty estimation (GLUE method was used. Simulation work on water and heat processes in frozen soil in northern China during the 2012/2013 winter was conducted. Ensemble simulations through the Monte Carlo sampling method were generated for uncertainty analysis. Behavioral simulations were selected based on combinations of multiple model performance index criteria with respect to simulated soil water and temperature at four depths (5 cm, 15 cm, 25 cm, and 35 cm. Posterior distributions for parameters related to soil hydraulic, radiation processes, and heat transport indicated that uncertainties in both input and model structures could influence model performance in modeling water and heat processes in seasonally frozen soils. Seasonal courses in water and energy partitioning were obvious during the winter. Within the day-cycle, soil evaporation/condensation and energy distributions were well captured and clarified as an important phenomenon in the dynamics of the energy balance system. The combination of the CoupModel simulations with the uncertainty-based calibration method provides a way of understanding the seasonal courses of hydrology and energy processes in cold regions with limited data. Additional measurements may be used to further reduce the uncertainty of regulating factors during the different stages of freezing–thawing.
Estimation of the parameters of ETAS models by Simulated Annealing
Lombardi, Anna Maria
2015-02-01
This paper proposes a new algorithm to estimate the maximum likelihood parameters of an Epidemic Type Aftershock Sequences (ETAS) model. It is based on Simulated Annealing, a versatile method that solves problems of global optimization and ensures convergence to a global optimum. The procedure is tested on both simulated and real catalogs. The main conclusion is that the method performs poorly as the size of the catalog decreases because the effect of the correlation of the ETAS parameters is more significant. These results give new insights into the ETAS model and the efficiency of the maximum-likelihood method within this context.
J-A Hysteresis Model Parameters Estimation using GA
Directory of Open Access Journals (Sweden)
Bogomir Zidaric
2005-01-01
Full Text Available This paper presents the Jiles and Atherton (J-A hysteresis model parameter estimation for soft magnetic composite (SMC material. The calculation of Jiles and Atherton hysteresis model parameters is based on experimental data and genetic algorithms (GA. Genetic algorithms operate in a given area of possible solutions. Finding the best solution of a problem in wide area of possible solutions is uncertain. A new approach in use of genetic algorithms is proposed to overcome this uncertainty. The basis of this approach is in genetic algorithm built in another genetic algorithm.
A new estimate of the parameters in linear mixed models
Institute of Scientific and Technical Information of China (English)
王松桂; 尹素菊
2002-01-01
In linear mixed models, there are two kinds of unknown parameters: one is the fixed effect, theother is the variance component. In this paper, new estimates of these parameters, called the spectral decom-position estimates, are proposed, Some important statistical properties of the new estimates are established,in particular the linearity of the estimates of the fixed effects with many statistical optimalities. A new methodis applied to two important models which are used in economics, finance, and mechanical fields. All estimatesobtained have good statistical and practical meaning.
Models wagging the dog: are circuits constructed with disparate parameters?
Nowotny, Thomas; Szücs, Attila; Levi, Rafael; Selverston, Allen I
2007-08-01
In a recent article, Prinz, Bucher, and Marder (2004) addressed the fundamental question of whether neural systems are built with a fixed blueprint of tightly controlled parameters or in a way in which properties can vary largely from one individual to another, using a database modeling approach. Here, we examine the main conclusion that neural circuits indeed are built with largely varying parameters in the light of our own experimental and modeling observations. We critically discuss the experimental and theoretical evidence, including the general adequacy of database approaches for questions of this kind, and come to the conclusion that the last word for this fundamental question has not yet been spoken.
Li, Jicun; Wang, Feng
2016-07-01
The effects of decoupling the water-water and water-solute interactions are studied with selected mono-valent ions as the solute. Using the ion-water cross terms developed for the BLYPSP-4F water model, we replaced the water potential with WAIL, TIP4P, and TIP3P without changing the ion-water parameters. When the adaptive force matching (AFM) derived BLYPSP-4F model is replaced by the other AFM derived WAIL model, the difference in ion properties, such as hydration free energies, radial distribution functions, relative diffusion constants, is negligible, demonstrating the feasibility for combining AFM parameters from different sources. Interestingly, when the AFM-derived ion-water cross-terms are used with a non-AFM based water model, only small changes in the ion properties are observed. The final combined models with TIP3P or TIP4P water reproduce the salt hydration free energies within 6% of experiments. The feasibility of combining AFM models with other non-AFM models is of significance since such combinations allow more complex systems to be studied without specific parameterization. In addition, the study suggests an interesting prospect of reusing the cross-terms when a part of a general force field is replaced with a different model. The prevailing practice, which is to re-derive all cross-terms with combining rules, may not have been optimal.
Pradhan, Snigdhendubala; Boernick, Hilmar; Kumar, Pradeep; Mehrotra, Indu
2016-07-15
The correlation between octanol-water partition coefficient (KOW) and the transport of aqueous samples containing single organic compound is well documented. The concept of the KOW of river water containing the mixture of organics was evolved by Pradhan et al. (2015). The present study aims at determining the KOW and sorption parameters of synthetic aqueous samples and river water to finding out the correlation, if any. The laboratory scale columns packed with aquifer materials were fed with synthetic and river water samples. Under the operating conditions, the compounds in the samples did not separate, and all the samples that contain more than one organic compound yielded a single breakthrough curve. Breakthrough curves simulated from sorption isotherms were compared with those from the column runs. The sorption parameters such as retardation factor (Rf), height of mass transfer zone (HMTZ), rate of mass transfer zone (RMTZ), breakpoint column capacity (qb) and maximum column capacity (qx) estimated from column runs, sorption isotherms and models developed by Yoon-Nelson, Bohart-Adam and Thomas were in agreement. The empirical correlations were found between the KOW and sorption parameters. The transport of the organics measured as dissolved organic carbon (DOC) through the aquifer can be predicted from the KOW of the river water and other water samples. The novelty of the study is to measure KOW and to envisage the fate of the DOC of the river water, particularly during riverbank filtration. Statistical analysis of the results revealed a fair agreement between the observed and computed values.
Institute of Scientific and Technical Information of China (English)
Lukas Graber; Diomar Infante; Michael Steurer; William W. Brey
2011-01-01
Careful analysis of transients in shipboard power systems is important to achieve long life times of the com ponents in future all-electric ships. In order to accomplish results with high accuracy, it is recommended to validate cable models as they have significant influence on the amplitude and frequency spectrum of voltage transients. The authors propose comparison of model and measurement using scattering parameters. They can be easily obtained from measurement and simulation and deliver broadband information about the accuracy of the model. The measurement can be performed using a vector network analyzer. The process to extract scattering parameters from simulation models is explained in detail. Three different simulation models of a 5 kV XLPE power cable have been validated. The chosen approach delivers an efficient tool to quickly estimate the quality of a model.
High correlation of double Debye model parameters in skin cancer detection.
Truong, Bao C Q; Tuan, H D; Fitzgerald, Anthony J; Wallace, Vincent P; Nguyen, H T
2014-01-01
The double Debye model can be used to capture the dielectric response of human skin in terahertz regime due to high water content in the tissue. The increased water proportion is widely considered as a biomarker of carcinogenesis, which gives rise of using this model in skin cancer detection. Therefore, the goal of this paper is to provide a specific analysis of the double Debye parameters in terms of non-melanoma skin cancer classification. Pearson correlation is applied to investigate the sensitivity of these parameters and their combinations to the variation in tumor percentage of skin samples. The most sensitive parameters are then assessed by using the receiver operating characteristic (ROC) plot to confirm their potential of classifying tumor from normal skin. Our positive outcomes support further steps to clinical application of terahertz imaging in skin cancer delineation.
Energy Technology Data Exchange (ETDEWEB)
Berlan, F.J.; Garcia-Araya, J.F.; Alvarez, P. [Universidad de Extremadura, Badajoz (Spain). Dept. de Ingenieria Quimica y Energetica
1997-12-31
Urban waste waters were treated with pure ozone or combinations of ozone, hydrogen peroxide and/or UV radiation to study the course of resulting BOD (biological oxygen demand)-time profiles and to propose a kinetic model. BOD-time profiles of chemically treated waste waters show an initial lag period that first order kinetic models cannot describe. A second order kinetic model is then proposed that satisfactorily fits experimental BOD-time profiles, except when hydrogen peroxide has been used. In these cases, BOD-time profiles present the highest lag periods observed. By applying this model, three parameters are determined: the biokinetic constant (k) which is an index of the biological removal rate; the potential amount of biodegradable matter (BOD{sub T}), and the measure of the size of inocula and microbial activities of microorganisms ({lambda}). The model was checked with experimental results of BOD-time profiles corresponding to both untreated and chemically ozonated urban waste waters. Ozonated waste waters showed the highest values of k and BOD{sub T}, which implies an improvement of waste water biodegradability after ozonation. However, values of {lambda} corrsponding to ozonated waste waters presented lower values than those of untreated waste waters. This was due to the lag period observed in the BOD-time profile, which was a consequence of a lack of micro-organism acclimation to ozonated waste waters. The effect of the ozone dose, pH and carbonates during oxonation on COD (chemical oxygen demand) and the above indicated parameters was also studies. The results suggest that ozonolysis, the direct molecular ozone way of reaction, due to its selective character, increases the biodegradability of waste water more than other chemically advancec oxidation processes based on hydroxyl radical reactions. (orig./SR)
Inhalation Exposure Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
M. Wasiolek
2006-06-05
This analysis is one of the technical reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), referred to in this report as the biosphere model. ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. ''Inhalation Exposure Input Parameters for the Biosphere Model'' is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the biosphere model is presented in Figure 1-1 (based on BSC 2006 [DIRS 176938]). This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and how this analysis report contributes to biosphere modeling. This analysis report defines and justifies values of atmospheric mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of the biosphere model to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception. This
Parameter uncertainty, sensitivity, and sediment coupling in bioenergetics-based food web models
Energy Technology Data Exchange (ETDEWEB)
Barron, M.G.; Cacela, D.; Beltman, D. [Hagler Bailly, Boulder, CO (United States)
1995-12-31
A bioenergetics-based food web model was developed and calibrated using measured PCB water and sediment concentrations in two Great Lakes food webs: Green Bay, Michigan and Lake Ontario. The model incorporated functional based trophic levels and sediment, water, and food chain exposures of PCBs to aquatic biota. Sensitivity analysis indicated the parameters with the greatest influence on PCBs in top predators were lipid content of plankton and benthos, planktivore assimilation efficiency, Kow, prey selection, and ambient temperature. Sediment-associated PCBs were estimated to contribute over 90% of PCBs in benthivores and less than 50% in piscivores. Ranges of PCB concentrations in top predators estimated by Monte Carlo simulation incorporating parameter uncertainty were within one order of magnitude of modal values. Model applications include estimation of exceedences of human and ecological thresholds. The results indicate that point estimates from bioenergetics-based food web models have substantial uncertainty that should be considered in regulatory and scientific applications.
Uncertainty of Modal Parameters Estimated by ARMA Models
DEFF Research Database (Denmark)
Jensen, Jakob Laigaard; Brincker, Rune; Rytter, Anders
In this paper the uncertainties of identified modal parameters such as eigenfrequencies and damping ratios are assessed. From the measured response of dynamic excited structures the modal parameters may be identified and provide important structural knowledge. However the uncertainty of the param......In this paper the uncertainties of identified modal parameters such as eigenfrequencies and damping ratios are assessed. From the measured response of dynamic excited structures the modal parameters may be identified and provide important structural knowledge. However the uncertainty...... by a simulation study of a lightly damped single degree of freedom system. Identification by ARMA models has been chosen as system identification method. It is concluded that both the sampling interval and number of sampled points may play a significant role with respect to the statistical errors. Furthermore...
Iterative integral parameter identification of a respiratory mechanics model
Directory of Open Access Journals (Sweden)
Schranz Christoph
2012-07-01
Full Text Available Abstract Background Patient-specific respiratory mechanics models can support the evaluation of optimal lung protective ventilator settings during ventilation therapy. Clinical application requires that the individual’s model parameter values must be identified with information available at the bedside. Multiple linear regression or gradient-based parameter identification methods are highly sensitive to noise and initial parameter estimates. Thus, they are difficult to apply at the bedside to support therapeutic decisions. Methods An iterative integral parameter identification method is applied to a second order respiratory mechanics model. The method is compared to the commonly used regression methods and error-mapping approaches using simulated and clinical data. The clinical potential of the method was evaluated on data from 13 Acute Respiratory Distress Syndrome (ARDS patients. Results The iterative integral method converged to error minima 350 times faster than the Simplex Search Method using simulation data sets and 50 times faster using clinical data sets. Established regression methods reported erroneous results due to sensitivity to noise. In contrast, the iterative integral method was effective independent of initial parameter estimations, and converged successfully in each case tested. Conclusion These investigations reveal that the iterative integral method is beneficial with respect to computing time, operator independence and robustness, and thus applicable at the bedside for this clinical application.
Institute of Scientific and Technical Information of China (English)
WANG Zheng-Ying; SHU Qiao-Sheng; XIE Li-Ya; LIU Zuo-Xin; B.C.SI
2011-01-01
Soil water-retention characteristics at measurement scales are generally different from those at application scales, and there is scale disparity between them and soil physical properties. The relationships between two water-retention parameters,the scaling parameter related to the inverse of the air-entry pressure (αvG, cm-1) and the curve shape factor related to soil pore-size distribution (n) of the van Genuchten water-retention equation, and soil texture (sand, silt, and clay contents)were examined at multiple scales. One hundred twenty-eight undisturbed soil samples were collected from a 640-m transect located in Fuxin, China. Soil water-retention curves were measured and the van Genuchten parameters were obtained by curve fitting. The relationships between the two parameters and soil texture at the observed scale and at multiple scales were evaluated using Pearson correlation and joint multifractal analyses, respectively. The results of Pearson correlation analysis showed that the parameter αvG was significantly correlated with sand, silt, and clay contents at the observed scale. Joint multifractal analyses, however, indicated that the parameter αvG was not correlated with silt and sand contents at multiple scales. The parameter n was positively correlated with clay content at multiple scales. Sand content was significantly correlated with the parameter n at the observed scale but not at multiple scales. Clay contents were strongly correlated to both water-retention parameters because clay content was relatively low in the soil studied, indicating that water retention was dominated by clay content in the field of this study at all scales. These suggested that multiple-scale analyses were necessary to fully grasp the spatial variability of soil water-retention characteristics.
Optical parameters of the Black Sea waters: long term variability and present status
Vladimirov, Vladimir L.; Mankovsky, Viktor I.; Solov'ev, Mark V.; Mishonov, Alexey V.; Besiktepe, Sukru; Ozsoy, Emin
1997-02-01
Seasonal and long-term variability of the Black sea optical parameters are analyzed using valuable data set from the data bases of Marine Hydrophysical Institute and Institute of Marine Sciences. The drastic decrease of the water transparency was observed during 1986-1992. It coincided with the big changes of the spectral distribution of water optical parameters. The main causes of these changes are eutrophication, influence of biological invader Mnemiopsis leidyi on the sea ecosystem, and the natural 11-years cycle.
Estimation of growth parameters using a nonlinear mixed Gompertz model.
Wang, Z; Zuidhof, M J
2004-06-01
In order to maximize the utility of simulation models for decision making, accurate estimation of growth parameters and associated variances is crucial. A mixed Gompertz growth model was used to account for between-bird variation and heterogeneous variance. The mixed model had several advantages over the fixed effects model. The mixed model partitioned BW variation into between- and within-bird variation, and the covariance structure assumed with the random effect accounted for part of the BW correlation across ages in the same individual. The amount of residual variance decreased by over 55% with the mixed model. The mixed model reduced estimation biases that resulted from selective sampling. For analysis of longitudinal growth data, the mixed effects growth model is recommended.
Modelling Biophysical Parameters of Maize Using Landsat 8 Time Series
Dahms, Thorsten; Seissiger, Sylvia; Conrad, Christopher; Borg, Erik
2016-06-01
Open and free access to multi-frequent high-resolution data (e.g. Sentinel - 2) will fortify agricultural applications based on satellite data. The temporal and spatial resolution of these remote sensing datasets directly affects the applicability of remote sensing methods, for instance a robust retrieving of biophysical parameters over the entire growing season with very high geometric resolution. In this study we use machine learning methods to predict biophysical parameters, namely the fraction of absorbed photosynthetic radiation (FPAR), the leaf area index (LAI) and the chlorophyll content, from high resolution remote sensing. 30 Landsat 8 OLI scenes were available in our study region in Mecklenburg-Western Pomerania, Germany. In-situ data were weekly to bi-weekly collected on 18 maize plots throughout the summer season 2015. The study aims at an optimized prediction of biophysical parameters and the identification of the best explaining spectral bands and vegetation indices. For this purpose, we used the entire in-situ dataset from 24.03.2015 to 15.10.2015. Random forest and conditional inference forests were used because of their explicit strong exploratory and predictive character. Variable importance measures allowed for analysing the relation between the biophysical parameters with respect to the spectral response, and the performance of the two approaches over the plant stock evolvement. Classical random forest regression outreached the performance of conditional inference forests, in particular when modelling the biophysical parameters over the entire growing period. For example, modelling biophysical parameters of maize for the entire vegetation period using random forests yielded: FPAR: R² = 0.85; RMSE = 0.11; LAI: R² = 0.64; RMSE = 0.9 and chlorophyll content (SPAD): R² = 0.80; RMSE=4.9. Our results demonstrate the great potential in using machine-learning methods for the interpretation of long-term multi-frequent remote sensing datasets to model
Joint Dynamics Modeling and Parameter Identification for Space Robot Applications
Directory of Open Access Journals (Sweden)
Adenilson R. da Silva
2007-01-01
Full Text Available Long-term mission identification and model validation for in-flight manipulator control system in almost zero gravity with hostile space environment are extremely important for robotic applications. In this paper, a robot joint mathematical model is developed where several nonlinearities have been taken into account. In order to identify all the required system parameters, an integrated identification strategy is derived. This strategy makes use of a robust version of least-squares procedure (LS for getting the initial conditions and a general nonlinear optimization method (MCS—multilevel coordinate search—algorithm to estimate the nonlinear parameters. The approach is applied to the intelligent robot joint (IRJ experiment that was developed at DLR for utilization opportunity on the International Space Station (ISS. The results using real and simulated measurements have shown that the developed algorithm and strategy have remarkable features in identifying all the parameters with good accuracy.
Mathematical Modelling and Parameter Optimization of Pulsating Heat Pipes
Yang, Xin-She; Luan, Tao; Koziel, Slawomir
2014-01-01
Proper heat transfer management is important to key electronic components in microelectronic applications. Pulsating heat pipes (PHP) can be an efficient solution to such heat transfer problems. However, mathematical modelling of a PHP system is still very challenging, due to the complexity and multiphysics nature of the system. In this work, we present a simplified, two-phase heat transfer model, and our analysis shows that it can make good predictions about startup characteristics. Furthermore, by considering parameter estimation as a nonlinear constrained optimization problem, we have used the firefly algorithm to find parameter estimates efficiently. We have also demonstrated that it is possible to obtain good estimates of key parameters using very limited experimental data.
The influences of model parameters on the characteristics of memristors
Institute of Scientific and Technical Information of China (English)
Zhou Jing; Huang Da
2012-01-01
As the fourth passive circuit component,a memristor is a nonlinear resistor that can "remember" the amount of charge passing through it.The characteristic of "remembering" the charge and non-volatility makes memristors great potential candidates in many fields.Nowadays,only a few groups have the ability to fabricate memristors,and most researchers study them by theoretic analysis and simulation.In this paper,we first analyse the theoretical base and characteristics of memristors,then use a simulation program with integrated circuit emphasis as our tool to simulate the theoretical model of memristors and change the parameters in the model to see the influence of each parameter on the characteristics.Our work supplies researchers engaged in memristor-based circuits with advice on how to choose the proper parameters.
Prediction of interest rate using CKLS model with stochastic parameters
Energy Technology Data Exchange (ETDEWEB)
Ying, Khor Chia [Faculty of Computing and Informatics, Multimedia University, Jalan Multimedia, 63100 Cyberjaya, Selangor (Malaysia); Hin, Pooi Ah [Sunway University Business School, No. 5, Jalan Universiti, Bandar Sunway, 47500 Subang Jaya, Selangor (Malaysia)
2014-06-19
The Chan, Karolyi, Longstaff and Sanders (CKLS) model is a popular one-factor model for describing the spot interest rates. In this paper, the four parameters in the CKLS model are regarded as stochastic. The parameter vector φ{sup (j)} of four parameters at the (J+n)-th time point is estimated by the j-th window which is defined as the set consisting of the observed interest rates at the j′-th time point where j≤j′≤j+n. To model the variation of φ{sup (j)}, we assume that φ{sup (j)} depends on φ{sup (j−m)}, φ{sup (j−m+1)},…, φ{sup (j−1)} and the interest rate r{sub j+n} at the (j+n)-th time point via a four-dimensional conditional distribution which is derived from a [4(m+1)+1]-dimensional power-normal distribution. Treating the (j+n)-th time point as the present time point, we find a prediction interval for the future value r{sub j+n+1} of the interest rate at the next time point when the value r{sub j+n} of the interest rate is given. From the above four-dimensional conditional distribution, we also find a prediction interval for the future interest rate r{sub j+n+d} at the next d-th (d≥2) time point. The prediction intervals based on the CKLS model with stochastic parameters are found to have better ability of covering the observed future interest rates when compared with those based on the model with fixed parameters.
Rosing, L. M.
1976-01-01
Physical, chemical and biological water quality data from five sites in the Tennessee River, two in Guntersville Reservoir and three in Wheeler Reservoir were correlated with climatological data for three annual cycles. Two of the annual cycles are for the years prior to the Browns Ferry Nuclear Power Plant operations and one is for the first 14 months of Plant operations. A comparison of the results of the annual cycles indicates that two distinct physical conditions in the reservoirs occur, one during the warm months when the reservoirs are at capacity and one during the colder winter months when the reservoirs have been drawn-down for water storage during the rainy months and for weed control. The wide variations of physical and chemical parameters to which the biological organisms are subjected on an annual basis control the biological organisms and their population levels. A comparison of the parameters of the site below the Power plant indicates that the heated effluent from the plant operating with two of the three reactors has not had any effect on the organisms at this site. Recommendations given include the development of prediction mathematical models (statistical analysis) for the physical and chemical parameters under specific climatological conditions which affect biological organisms. Tabulated data of chemical analysis of water and organism populations studied is given.
Comparison of Parameter Estimation Methods for Transformer Weibull Lifetime Modelling
Institute of Scientific and Technical Information of China (English)
ZHOU Dan; LI Chengrong; WANG Zhongdong
2013-01-01
Two-parameter Weibull distribution is the most widely adopted lifetime model for power transformers.An appropriate parameter estimation method is essential to guarantee the accuracy of a derived Weibull lifetime model.Six popular parameter estimation methods (i.e.the maximum likelihood estimation method,two median rank regression methods including the one regressing X on Y and the other one regressing Y on X,the Kaplan-Meier method,the method based on cumulative hazard plot,and the Li's method) are reviewed and compared in order to find the optimal one that suits transformer's Weibull lifetime modelling.The comparison took several different scenarios into consideration:10 000 sets of lifetime data,each of which had a sampling size of 40 ～ 1 000 and a censoring rate of 90％,were obtained by Monte-Carlo simulations for each scienario.Scale and shape parameters of Weibull distribution estimated by the six methods,as well as their mean value,median value and 90％ confidence band are obtained.The cross comparison of these results reveals that,among the six methods,the maximum likelihood method is the best one,since it could provide the most accurate Weibull parameters,i.e.parameters having the smallest bias in both mean and median values,as well as the shortest length of the 90％ confidence band.The maximum likelihood method is therefore recommended to be used over the other methods in transformer Weibull lifetime modelling.
On the estimation of water pure compound parameters in association theories
DEFF Research Database (Denmark)
Grenner, Andreas; Kontogeorgis, Georgios; Michelsen, Michael Locht;
2007-01-01
Determination of the appropriate number of association sites and estimation of parameters for association (SAFT-type) theories is not a trivial matter. Building further on a recently published manuscript by Clark et al., this work investigates aspects of the parameter estimation for water using two...... different association theories. Their performance for various properties as well as against the results presented earlier is demonstrated....
Calculation of Thermodynamic Parameters for Freundlich and Temkin Isotherm Models
Institute of Scientific and Technical Information of China (English)
ZHANGZENGQIANG; ZHANGYIPING; 等
1999-01-01
Derivation of the Freundlich and Temkin isotherm models from the kinetic adsorption/desorption equations was carried out to calculate their thermodynamic equilibrium constants.The calculation formulase of three thermodynamic parameters,the standard molar Gibbs free energy change,the standard molar enthalpy change and the standard molar entropy change,of isothermal adsorption processes for Freundlich and Temkin isotherm models were deduced according to the relationship between the thermodynamic equilibrium constants and the temperature.
Parameter Estimation for a Computable General Equilibrium Model
DEFF Research Database (Denmark)
Arndt, Channing; Robinson, Sherman; Tarp, Finn
2002-01-01
We introduce a maximum entropy approach to parameter estimation for computable general equilibrium (CGE) models. The approach applies information theory to estimating a system of non-linear simultaneous equations. It has a number of advantages. First, it imposes all general equilibrium constraints...
Parabolic problems with parameters arising in evolution model for phytromediation
Sahmurova, Aida; Shakhmurov, Veli
2012-12-01
The past few decades, efforts have been made to clean sites polluted by heavy metals as chromium. One of the new innovative methods of eradicating metals from soil is phytoremediation. This uses plants to pull metals from the soil through the roots. This work develops a system of differential equations with parameters to model the plant metal interaction of phytoremediation (see [1]).
Improved parameter estimation for hydrological models using weighted object functions
Stein, A.; Zaadnoordijk, W.J.
1999-01-01
This paper discusses the sensitivity of calibration of hydrological model parameters to different objective functions. Several functions are defined with weights depending upon the hydrological background. These are compared with an objective function based upon kriging. Calibration is applied to pi
Parameter Estimation for a Computable General Equilibrium Model
DEFF Research Database (Denmark)
Arndt, Channing; Robinson, Sherman; Tarp, Finn
We introduce a maximum entropy approach to parameter estimation for computable general equilibrium (CGE) models. The approach applies information theory to estimating a system of nonlinear simultaneous equations. It has a number of advantages. First, it imposes all general equilibrium constraints...
PARAMETER ESTIMATION IN LINEAR REGRESSION MODELS FOR LONGITUDINAL CONTAMINATED DATA
Institute of Scientific and Technical Information of China (English)
QianWeimin; LiYumei
2005-01-01
The parameter estimation and the coefficient of contamination for the regression models with repeated measures are studied when its response variables are contaminated by another random variable sequence. Under the suitable conditions it is proved that the estimators which are established in the paper are strongly consistent estimators.
Modeling and simulation of HTS cables for scattering parameter analysis
Bang, Su Sik; Lee, Geon Seok; Kwon, Gu-Young; Lee, Yeong Ho; Chang, Seung Jin; Lee, Chun-Kwon; Sohn, Songho; Park, Kijun; Shin, Yong-June
2016-11-01
Most of modeling and simulation of high temperature superconducting (HTS) cables are inadequate for high frequency analysis since focus of the simulation's frequency is fundamental frequency of the power grid, which does not reflect transient characteristic. However, high frequency analysis is essential process to research the HTS cables transient for protection and diagnosis of the HTS cables. Thus, this paper proposes a new approach for modeling and simulation of HTS cables to derive the scattering parameter (S-parameter), an effective high frequency analysis, for transient wave propagation characteristics in high frequency range. The parameters sweeping method is used to validate the simulation results to the measured data given by a network analyzer (NA). This paper also presents the effects of the cable-to-NA connector in order to minimize the error between the simulated and the measured data under ambient and superconductive conditions. Based on the proposed modeling and simulation technique, S-parameters of long-distance HTS cables can be accurately derived in wide range of frequency. The results of proposed modeling and simulation can yield the characteristics of the HTS cables and will contribute to analyze the HTS cables.
Evaluation of some infiltration models and hydraulic parameters
Energy Technology Data Exchange (ETDEWEB)
Haghighi, F.; Gorji, M.; Shorafa, M.; Sarmadian, F.; Mohammadi, M. H.
2010-07-01
The evaluation of infiltration characteristics and some parameters of infiltration models such as sorptivity and final steady infiltration rate in soils are important in agriculture. The aim of this study was to evaluate some of the most common models used to estimate final soil infiltration rate. The equality of final infiltration rate with saturated hydraulic conductivity (Ks) was also tested. Moreover, values of the estimated sorptivity from the Philips model were compared to estimates by selected pedotransfer functions (PTFs). The infiltration experiments used the doublering method on soils with two different land uses in the Taleghan watershed of Tehran province, Iran, from September to October, 2007. The infiltration models of Kostiakov-Lewis, Philip two-term and Horton were fitted to observed infiltration data. Some parameters of the models and the coefficient of determination goodness of fit were estimated using MATLAB software. The results showed that, based on comparing measured and model-estimated infiltration rate using root mean squared error (RMSE), Hortons model gave the best prediction of final infiltration rate in the experimental area. Laboratory measured Ks values gave significant differences and higher values than estimated final infiltration rates from the selected models. The estimated final infiltration rate was not equal to laboratory measured Ks values in the study area. Moreover, the estimated sorptivity factor by Philips model was significantly different to those estimated by selected PTFs. It is suggested that the applicability of PTFs is limited to specific, similar conditions. (Author) 37 refs.
Agricultural and Environmental Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
K. Rasmuson; K. Rautenstrauch
2004-09-14
This analysis is one of 10 technical reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) (i.e., the biosphere model). It documents development of agricultural and environmental input parameters for the biosphere model, and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for the repository at Yucca Mountain. The ERMYN provides the TSPA with the capability to perform dose assessments. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships between the major activities and their products (the analysis and model reports) that were planned in ''Technical Work Plan for Biosphere Modeling and Expert Support'' (BSC 2004 [DIRS 169573]). The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the ERMYN and its input parameters.
Siemes, K.; Snellen, M.; Simons, D.G.; Hermand, J.P.
2009-01-01
Shallow water naval operations require detailed knowledge of the environmental properties. In addition to parameters such as water depth, knowledge about the sediment properties is of high importance for a wide range of operations. In this context, the MREA BP'07 experiment was carried out in the Me
Estimating model parameters in nonautonomous chaotic systems using synchronization
Yang, Xiaoli; Xu, Wei; Sun, Zhongkui
2007-05-01
In this Letter, a technique is addressed for estimating unknown model parameters of multivariate, in particular, nonautonomous chaotic systems from time series of state variables. This technique uses an adaptive strategy for tracking unknown parameters in addition to a linear feedback coupling for synchronizing systems, and then some general conditions, by means of the periodic version of the LaSalle invariance principle for differential equations, are analytically derived to ensure precise evaluation of unknown parameters and identical synchronization between the concerned experimental system and its corresponding receiver one. Exemplifies are presented by employing a parametrically excited 4D new oscillator and an additionally excited Ueda oscillator. The results of computer simulations reveal that the technique not only can quickly track the desired parameter values but also can rapidly respond to changes in operating parameters. In addition, the technique can be favorably robust against the effect of noise when the experimental system is corrupted by bounded disturbance and the normalized absolute error of parameter estimation grows almost linearly with the cutoff value of noise strength in simulation.
Estimating model parameters in nonautonomous chaotic systems using synchronization
Energy Technology Data Exchange (ETDEWEB)
Yang, Xiaoli [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China)]. E-mail: yangxl205@mail.nwpu.edu.cn; Xu, Wei [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China); Sun, Zhongkui [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China)
2007-05-07
In this Letter, a technique is addressed for estimating unknown model parameters of multivariate, in particular, nonautonomous chaotic systems from time series of state variables. This technique uses an adaptive strategy for tracking unknown parameters in addition to a linear feedback coupling for synchronizing systems, and then some general conditions, by means of the periodic version of the LaSalle invariance principle for differential equations, are analytically derived to ensure precise evaluation of unknown parameters and identical synchronization between the concerned experimental system and its corresponding receiver one. Exemplifies are presented by employing a parametrically excited 4D new oscillator and an additionally excited Ueda oscillator. The results of computer simulations reveal that the technique not only can quickly track the desired parameter values but also can rapidly respond to changes in operating parameters. In addition, the technique can be favorably robust against the effect of noise when the experimental system is corrupted by bounded disturbance and the normalized absolute error of parameter estimation grows almost linearly with the cutoff value of noise strength in simulation.
Gao, Z.; Zhang, K.; Xue, X.; Huang, J.; Hong, Y.
2016-12-01
Floods are among the most common natural disasters with worldwide impacts that cause significant humanitarian and economic negative consequences. The increasing availability of satellite-based precipitation estimates and geospatial datasets with global coverage and improved temporal resolutions has enhanced our capability of forecasting floods and monitoring water resources across the world. This study presents an approach combing physically based and empirical methods for a-priori parameter estimates and a parameter dataset for the Coupled Routing and Excess Storage (CREST) hydrological model at the global scale. This approach takes advantage of geographic information such as topography, land cover, and soil properties to derive the distributed parameter values across the world. The main objective of this study is to evaluate the utility of a-priori parameter estimates to improve the performance of the CREST distributed hydrologic model and enable its prediction at poorly gauged or ungauged catchments. Using the CREST hydrologic model, several typical river basins in different continents were selected to serve as test areas. The results show that the simulated daily stream flows using the parameters derived from geographically based information outperform the results using the lumped parameters. Overall, this early study highlights that a priori parameter estimates for hydrologic model warrants improved model predictive capability in ungauged basins at regional to global scales.
Model and parameter uncertainty in IDF relationships under climate change
Chandra, Rupa; Saha, Ujjwal; Mujumdar, P. P.
2015-05-01
Quantifying distributional behavior of extreme events is crucial in hydrologic designs. Intensity Duration Frequency (IDF) relationships are used extensively in engineering especially in urban hydrology, to obtain return level of extreme rainfall event for a specified return period and duration. Major sources of uncertainty in the IDF relationships are due to insufficient quantity and quality of data leading to parameter uncertainty due to the distribution fitted to the data and uncertainty as a result of using multiple GCMs. It is important to study these uncertainties and propagate them to future for accurate assessment of return levels for future. The objective of this study is to quantify the uncertainties arising from parameters of the distribution fitted to data and the multiple GCM models using Bayesian approach. Posterior distribution of parameters is obtained from Bayes rule and the parameters are transformed to obtain return levels for a specified return period. Markov Chain Monte Carlo (MCMC) method using Metropolis Hastings algorithm is used to obtain the posterior distribution of parameters. Twenty six CMIP5 GCMs along with four RCP scenarios are considered for studying the effects of climate change and to obtain projected IDF relationships for the case study of Bangalore city in India. GCM uncertainty due to the use of multiple GCMs is treated using Reliability Ensemble Averaging (REA) technique along with the parameter uncertainty. Scale invariance theory is employed for obtaining short duration return levels from daily data. It is observed that the uncertainty in short duration rainfall return levels is high when compared to the longer durations. Further it is observed that parameter uncertainty is large compared to the model uncertainty.
Modeling water demand when households have multiple sources of water
Coulibaly, Lassina; Jakus, Paul M.; Keith, John E.
2014-07-01
A significant portion of the world's population lives in areas where public water delivery systems are unreliable and/or deliver poor quality water. In response, people have developed important alternatives to publicly supplied water. To date, most water demand research has been based on single-equation models for a single source of water, with very few studies that have examined water demand from two sources of water (where all nonpublic system water sources have been aggregated into a single demand). This modeling approach leads to two outcomes. First, the demand models do not capture the full range of alternatives, so the true economic relationship among the alternatives is obscured. Second, and more seriously, economic theory predicts that demand for a good becomes more price-elastic as the number of close substitutes increases. If researchers artificially limit the number of alternatives studied to something less than the true number, the price elasticity estimate may be biased downward. This paper examines water demand in a region with near universal access to piped water, but where system reliability and quality is such that many alternative sources of water exist. In extending the demand analysis to four sources of water, we are able to (i) demonstrate why households choose the water sources they do, (ii) provide a richer description of the demand relationships among sources, and (iii) calculate own-price elasticity estimates that are more elastic than those generally found in the literature.
Better Insight Into Water Resources Management With Integrated Hydrodynamic And Water Quality Models
Debele, B.; Srinivasan, R.; Parlange, J.
2004-12-01
Models have long been used in water resources management to guide decision making and improve understanding of the system. Numerous models of different scales -spatial and temporal - are available. Yet, very few models manage to bridge simulations of hydrological and water quality parameters from both upland watershed and riverine system. Most water quality models, such as QUAL2E and EPD-RIV1 concentrate on the riverine system while CE-QUAL-W2 and WASP models focus on larger waterbodies, such as lakes and reservoirs. On the other hand, the original SWAT model, HSPF and other upland watershed hydrological models simulate agricultural (diffuse) pollution sources with limited number of processes incorporated to handle point source pollutions that emanate from industrial sectors. Such limitations, which are common in most hydrodynamic and water quality models undermine better understanding that otherwise could be uncovered by employing integrated hydrological and water quality models for both upland watershed and riverine system. The SWAT model is a well documented and verified hydrological and water quality model that has been developed to simulate the effects of various management scenarios on the health of the environment in terms of water quantity and quality. Recently, the SWAT model has been extended to include the simulation of hydrodynamic and water quality parameters in the river system. The extended SWAT model (ESWAT) has been further extended to run using diurnally varying (hourly) weather data and produce outputs at hourly timescales. This and other improvements in the ESWAT model have been documented in the current work. Besides, the results from two case studies in Texas will be reported.
Directory of Open Access Journals (Sweden)
Guang-zhou Chen
2015-01-01
Full Text Available Parameter identification plays a crucial role for simulating and using model. This paper firstly carried out the sensitivity analysis of the 2-chlorophenol oxidation model in supercritical water using the Monte Carlo method. Then, to address the nonlinearity of the model, two improved differential search (DS algorithms were proposed to carry out the parameter identification of the model. One strategy is to adopt the Latin hypercube sampling method to replace the uniform distribution of initial population; the other is to combine DS with simplex method. The results of sensitivity analysis reveal the sensitivity and the degree of difficulty identified for every model parameter. Furthermore, the posteriori probability distribution of parameters and the collaborative relationship between any two parameters can be obtained. To verify the effectiveness of the improved algorithms, the optimization performance of improved DS in kinetic parameter estimation is studied and compared with that of the basic DS algorithm, differential evolution, artificial bee colony optimization, and quantum-behaved particle swarm optimization. And the experimental results demonstrate that the DS with the Latin hypercube sampling method does not present better performance, while the hybrid methods have the advantages of strong global search ability and local search ability and are more effective than the other algorithms.
Reduced parameter model on trajectory tracking data with applications
Institute of Scientific and Technical Information of China (English)
王正明; 朱炬波
1999-01-01
The data fusion in tracking the same trajectory by multi-measurernent unit (MMU) is considered. Firstly, the reduced parameter model (RPM) of trajectory parameter (TP), system error and random error are presented,and then the RPM on trajectory tracking data (TTD) is obtained, a weighted method on measuring elements (ME) is studied and criteria on selection of ME based on residual and accuracy estimation are put forward. According to RPM,the problem about selection of ME and self-calibration of TTD is thoroughly investigated. The method improves data accuracy in trajectory tracking obviously and gives accuracy evaluation of trajectory tracking system simultaneously.
Parameter Estimation of the Extended Vasiček Model
Rujivan, Sanae
2010-01-01
In this paper, an estimate of the drift and diffusion parameters of the extended Vasiček model is presented. The estimate is based on the method of maximum likelihood. We derive a closed-form expansion for the transition (probability) density of the extended Vasiček process and use the expansion to construct an approximate log-likelihood function of a discretely sampled data of the process. Approximate maximum likelihood estimators (AMLEs) of the parameters are obtained by maximizing the appr...
Prediction of mortality rates using a model with stochastic parameters
Tan, Chon Sern; Pooi, Ah Hin
2016-10-01
Prediction of future mortality rates is crucial to insurance companies because they face longevity risks while providing retirement benefits to a population whose life expectancy is increasing. In the past literature, a time series model based on multivariate power-normal distribution has been applied on mortality data from the United States for the years 1933 till 2000 to forecast the future mortality rates for the years 2001 till 2010. In this paper, a more dynamic approach based on the multivariate time series will be proposed where the model uses stochastic parameters that vary with time. The resulting prediction intervals obtained using the model with stochastic parameters perform better because apart from having good ability in covering the observed future mortality rates, they also tend to have distinctly shorter interval lengths.
Probabilistic Constraint Programming for Parameters Optimisation of Generative Models
Zanin, Massimiliano; Sousa, Pedro A C; Cruz, Jorge
2015-01-01
Complex networks theory has commonly been used for modelling and understanding the interactions taking place between the elements composing complex systems. More recently, the use of generative models has gained momentum, as they allow identifying which forces and mechanisms are responsible for the appearance of given structural properties. In spite of this interest, several problems remain open, one of the most important being the design of robust mechanisms for finding the optimal parameters of a generative model, given a set of real networks. In this contribution, we address this problem by means of Probabilistic Constraint Programming. By using as an example the reconstruction of networks representing brain dynamics, we show how this approach is superior to other solutions, in that it allows a better characterisation of the parameters space, while requiring a significantly lower computational cost.
Mark-recapture models with parameters constant in time.
Jolly, G M
1982-06-01
The Jolly-Seber method, which allows for both death and immigration, is easy to apply but often requires a larger number of parameters to be estimated tha would otherwise be necessary. If (i) survival rate, phi, or (ii) probability of capture, p, or (iii) both phi and p can be assumed constant over the experimental period, models with a reduced number of parameters are desirable. In the present paper, maximum likelihood (ML) solutions for these three situations are derived from the general ML equations of Jolly [1979, in Sampling Biological Populations, R. M. Cormack, G. P. Patil and D. S. Robson (eds), 277-282]. A test is proposed for heterogeneity arising from a breakdown of assumptions in the general Jolly-Seber model. Tests for constancy of phi and p are provided. An example is given, in which these models are fitted to data from a local butterfly population.
Global modelling of river water quality under climate change
van Vliet, Michelle T. H.; Franssen, Wietse H. P.; Yearsley, John R.
2017-04-01
Climate change will pose challenges on the quality of freshwater resources for human use and ecosystems for instance by changing the dilution capacity and by affecting the rate of chemical processes in rivers. Here we assess the impacts of climate change and induced streamflow changes on a selection of water quality parameters for river basins globally. We used the Variable Infiltration Capacity (VIC) model and a newly developed global water quality module for salinity, temperature, dissolved oxygen and biochemical oxygen demand. The modelling framework was validated using observed records of streamflow, water temperature, chloride, electrical conductivity, dissolved oxygen and biochemical oxygen demand for 1981-2010. VIC and the water quality module were then forced with an ensemble of bias-corrected General Circulation Model (GCM) output for the representative concentration pathways RCP2.6 and RCP8.5 to study water quality trends and identify critical regions (hotspots) of water quality deterioration for the 21st century.
Enhancing debris flow modeling parameters integrating Bayesian networks
Graf, C.; Stoffel, M.; Grêt-Regamey, A.
2009-04-01
Applied debris-flow modeling requires suitably constraint input parameter sets. Depending on the used model, there is a series of parameters to define before running the model. Normally, the data base describing the event, the initiation conditions, the flow behavior, the deposition process and mainly the potential range of possible debris flow events in a certain torrent is limited. There are only some scarce places in the world, where we fortunately can find valuable data sets describing event history of debris flow channels delivering information on spatial and temporal distribution of former flow paths and deposition zones. Tree-ring records in combination with detailed geomorphic mapping for instance provide such data sets over a long time span. Considering the significant loss potential associated with debris-flow disasters, it is crucial that decisions made in regard to hazard mitigation are based on a consistent assessment of the risks. This in turn necessitates a proper assessment of the uncertainties involved in the modeling of the debris-flow frequencies and intensities, the possible run out extent, as well as the estimations of the damage potential. In this study, we link a Bayesian network to a Geographic Information System in order to assess debris-flow risk. We identify the major sources of uncertainty and show the potential of Bayesian inference techniques to improve the debris-flow model. We model the flow paths and deposition zones of a highly active debris-flow channel in the Swiss Alps using the numerical 2-D model RAMMS. Because uncertainties in run-out areas cause large changes in risk estimations, we use the data of flow path and deposition zone information of reconstructed debris-flow events derived from dendrogeomorphological analysis covering more than 400 years to update the input parameters of the RAMMS model. The probabilistic model, which consistently incorporates this available information, can serve as a basis for spatial risk
Identification of ecosystem parameters by SDE-modelling
DEFF Research Database (Denmark)
describing interactions between phytoplankton and water-column nitrogen with light as forcing, using data form a Danish estuary covering a 16 years period (1988-2003), and modelling primary production as a random walk, it is demonstrated how non-linear relationships between states can be identified...
SHEARING AND WATER RETENTION BEHAVIOR OF UNSATURATED LOAM WITH MODELING
Kiyohara, Yukoh; Kazama, Motoki
Unsaturated triaxial tests were carried out to study deformation behavior, effective stress path and water retention property of consolidated loam during consolidation and shearing processes. Initial matric suction was set as 0, 50, and 90 kPa, and confining pressures (net normal stresses) were set as 100 kPa. Then shearing processes were done under undrained and drained conditions. We clarified the relation between void ratio and Van Genuchten model parameter by using water retention curve. To predict the unsaturated shearing behavior, a modified Cam Clay model considering void ratio dependent Van Genuchten parameter was proposed. Those numerical test results were agreed well with laboratory tests results.
Directory of Open Access Journals (Sweden)
R. T. Vashi
2015-09-01
Full Text Available Groundwater samples were collected from five talukas of Valsad district for one year (from August 2008 to July 2009 and were analyzed for their physicochemical characteristics. The present investigation is focused on determination of parameters like pH, Colour, Electrical Conductivity (EC, Total Hardness (TH, Calcium (Ca, Magnesium (Mg, Total Alkalinity (TA, Total Dissolved Solids (TDS, Silica, Chloride, Sulphate, Fluoride, Sodium, Chemical Oxygen Demand (COD and metals like Copper (Cu and Manganese (Mn. Correlation coefficients were determined to identify the highly correlated parameters and interrelated water quality parameters. Correlation matrix of Valsad district suggests that EC of groundwater is found to be significantly correlated with eight out of seventeen water quality parameters studied. It may be suggested that the quality of Valsad district can be checked very effectively by controlling EC of water.
Directory of Open Access Journals (Sweden)
N. Rahmanian
2015-01-01
Full Text Available The drinking water quality was investigated in suspected parts of Perak state, Malaysia, to ensure the continuous supply of clean and safe drinking water for the public health protection. In this regard, a detailed physical and chemical analysis of drinking water samples was carried out in different residential and commercial areas of the state. A number of parameters such as pH, turbidity, conductivity, total suspended solids (TSS, total dissolved solids (TDS, and heavy metals such as Cu, Zn, Mg, Fe, Cd, Pb, Cr, As, Hg, and Sn were analysed for each water sample collected during winter and summer periods. The obtained values of each parameter were compared with the standard values set by the World Health Organization (WHO and local standards such as National Drinking Water Quality Standard (NDWQS. The values of each parameter were found to be within the safe limits set by the WHO and NDWQS. Overall, the water from all the locations was found to be safe as drinking water. However, it is also important to investigate other potential water contaminations such as chemicals and microbial and radiological materials for a longer period of time, including human body fluids, in order to assess the overall water quality of Perak state.
Singularity of Some Software Reliability Models and Parameter Estimation Method
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
According to the principle, “The failure data is the basis of software reliability analysis”, we built a software reliability expert system (SRES) by adopting the artificial intelligence technology. By reasoning out the conclusion from the fitting results of failure data of a software project, the SRES can recommend users “the most suitable model” as a software reliability measurement model. We believe that the SRES can overcome the inconsistency in applications of software reliability models well. We report investigation results of singularity and parameter estimation methods of experimental models in SRES.
Parameter Identifiability of Ship Manoeuvring Modeling Using System Identification
Directory of Open Access Journals (Sweden)
Weilin Luo
2016-01-01
Full Text Available To improve the feasibility of system identification in the prediction of ship manoeuvrability, several measures are presented to deal with the parameter identifiability in the parametric modeling of ship manoeuvring motion based on system identification. Drift of nonlinear hydrodynamic coefficients is explained from the point of view of regression analysis. To diminish the multicollinearity in a complicated manoeuvring model, difference method and additional signal method are employed to reconstruct the samples. Moreover, the structure of manoeuvring model is simplified based on correlation analysis. Manoeuvring simulation is performed to demonstrate the validity of the measures proposed.
Directory of Open Access Journals (Sweden)
K. Verbist
2009-06-01
Full Text Available In arid and semi-arid zones runoff harvesting techniques are often applied to increase the water retention and infiltration on steep slopes. Additionally, they act as an erosion control measure to reduce land degradation hazards. Nevertheless, few efforts were observed to quantify the water harvesting processes of these techniques and to evaluate their efficiency. In this study a combination of detailed field measurements and modelling with the HYDRUS-2D software package was used to visualize the effect of an infiltration trench on the soil water content of a bare slope in Northern Chile. Rainfall simulations were combined with high spatial and temporal resolution water content monitoring in order to construct a useful dataset for inverse modelling purposes. Initial estimates of model parameters were provided by detailed infiltration and soil water retention measurements. Four different measurement techniques were used to determine the saturated hydraulic conductivity (K_{sat} independently. Tension infiltrometer measurements proved a good estimator of the K_{sat} value and a proxy for those measured under simulated rainfall, whereas the pressure and constant head well infiltrometer measurements showed larger variability. Six different parameter optimization functions were tested as a combination of soil-water content, water retention and cumulative infiltration data. Infiltration data alone proved insufficient to obtain high model accuracy, due to large scatter on the data set, and water content data were needed to obtain optimized effective parameter sets with small confidence intervals. Correlation between observed soil water content and simulated values was as high as R^{2}=0.93 for ten selected observation points used in the model calibration phase, with overall correlation for the 22 observation points equal to 0.85. Model results indicate that the infiltration trench has a significant effect on
Directory of Open Access Journals (Sweden)
K. Verbist
2009-10-01
Full Text Available In arid and semi-arid zones, runoff harvesting techniques are often applied to increase the water retention and infiltration on steep slopes. Additionally, they act as an erosion control measure to reduce land degradation hazards. Nevertheless, few efforts were observed to quantify the water harvesting processes of these techniques and to evaluate their efficiency. In this study, a combination of detailed field measurements and modelling with the HYDRUS-2D software package was used to visualize the effect of an infiltration trench on the soil water content of a bare slope in northern Chile. Rainfall simulations were combined with high spatial and temporal resolution water content monitoring in order to construct a useful dataset for inverse modelling purposes. Initial estimates of model parameters were provided by detailed infiltration and soil water retention measurements. Four different measurement techniques were used to determine the saturated hydraulic conductivity (K_{sat} independently. The tension infiltrometer measurements proved a good estimator of the K_{sat} value and a proxy for those measured under simulated rainfall, whereas the pressure and constant head well infiltrometer measurements showed larger variability. Six different parameter optimization functions were tested as a combination of soil-water content, water retention and cumulative infiltration data. Infiltration data alone proved insufficient to obtain high model accuracy, due to large scatter on the data set, and water content data were needed to obtain optimized effective parameter sets with small confidence intervals. Correlation between the observed soil water content and the simulated values was as high as R^{2}=0.93 for ten selected observation points used in the model calibration phase, with overall correlation for the 22 observation points equal to 0.85. The model results indicate that the infiltration trench has a
Verbist, K.; Cornelis, W. M.; Gabriels, D.; Alaerts, K.; Soto, G.
2009-10-01
In arid and semi-arid zones, runoff harvesting techniques are often applied to increase the water retention and infiltration on steep slopes. Additionally, they act as an erosion control measure to reduce land degradation hazards. Nevertheless, few efforts were observed to quantify the water harvesting processes of these techniques and to evaluate their efficiency. In this study, a combination of detailed field measurements and modelling with the HYDRUS-2D software package was used to visualize the effect of an infiltration trench on the soil water content of a bare slope in northern Chile. Rainfall simulations were combined with high spatial and temporal resolution water content monitoring in order to construct a useful dataset for inverse modelling purposes. Initial estimates of model parameters were provided by detailed infiltration and soil water retention measurements. Four different measurement techniques were used to determine the saturated hydraulic conductivity (Ksat) independently. The tension infiltrometer measurements proved a good estimator of the Ksat value and a proxy for those measured under simulated rainfall, whereas the pressure and constant head well infiltrometer measurements showed larger variability. Six different parameter optimization functions were tested as a combination of soil-water content, water retention and cumulative infiltration data. Infiltration data alone proved insufficient to obtain high model accuracy, due to large scatter on the data set, and water content data were needed to obtain optimized effective parameter sets with small confidence intervals. Correlation between the observed soil water content and the simulated values was as high as R2=0.93 for ten selected observation points used in the model calibration phase, with overall correlation for the 22 observation points equal to 0.85. The model results indicate that the infiltration trench has a significant effect on soil-water storage, especially at the base of the
Rezaei, Meisam; Seuntjens, Piet; Shahidi, Reihaneh; Joris, Ingeborg; Boënne, Wesley; Cornelis, Wim
2016-04-01
Soil hydraulic parameters, which can be derived from in situ and/or laboratory experiments, are key input parameters for modeling water flow in the vadose zone. In this study, we measured soil hydraulic properties with typical laboratory measurements and field tension infiltration experiments using Wooding's analytical solution and inverse optimization along the vertical direction within two typical podzol profiles with sand texture in a potato field. The objective was to identify proper sets of hydraulic parameters and to evaluate their relevance on hydrological model performance for irrigation management purposes. Tension disc infiltration experiments were carried out at five different depths for both profiles at consecutive negative pressure heads of 12, 6, 3 and 0.1 cm. At the same locations and depths undisturbed samples were taken to determine the water retention curve with hanging water column and pressure extractors and lab saturated hydraulic conductivity with the constant head method. Both approaches allowed to determine the Mualem-van Genuchten (MVG) hydraulic parameters (residual water content θr, saturated water content θs,, shape parameters α and n, and field or lab saturated hydraulic conductivity Kfs and Kls). Results demonstrated horizontal differences and vertical variability of hydraulic properties. Inverse optimization resulted in excellent matches between observed and fitted infiltration rates in combination with final water content at the end of the experiment, θf, using Hydrus 2D/3D. It also resulted in close correspondence of and Kfs with those from Logsdon and Jaynes' (1993) solution of Wooding's equation. The MVG parameters Kfs and α estimated from the inverse solution (θr set to zero), were relatively similar to values from Wooding's solution which were used as initial value and the estimated θs corresponded to (effective) field saturated water content θf. We found the Gardner parameter αG to be related to the optimized van
Hydraulic modelling of drinking water treatment plant operations
Directory of Open Access Journals (Sweden)
K. J. Borger
2008-10-01
Full Text Available For a drinking water treatment plant simulation, water quality models, a hydraulic model, a process-control model, an object model, data management, training and decision-support features and a graphic user interface have been integrated. The integration of a hydraulic model in the simulator is necessary to correctly determine the division of flows over the plant's lanes and, thus, the flow through the individual treatment units, based on valve positions and pump speeds. The flow through a unit is one of the most important parameters in terms of a unit's effectiveness. In the present paper, a new EPAnet library is presented with the typical hydraulic elements for drinking water treatment processes. Using this library, a hydraulic model was set up and validated for the drinking water treatment plant Harderbroek.
Moisture Absorption Model of Composites Considering Water Temperature Effect
Directory of Open Access Journals (Sweden)
HUI Li
2016-11-01
Full Text Available The influence of water temperature on composite moisture absorption parameters was investigated in temperature-controlled water bath. Experiments of carbon fiber/bismaleimide resin composites immersed in water of 60℃, 70℃and 80℃ were developed respectively. According to the moisture content-time curves obtained from the experimental results, the diffusion coefficient and the balanced moisture content of the composites immersed in different water temperature could be calculated. What's more, the effect of water temperature on the diffusion coefficient and the balanced moisture content were discussed too. According to the Arrhenius equation and the law of Fick, a moisture absorption model was proposed to simulate the hygroscopic behaviour of the composite laminates immersed in different water temperature which can predict the absorption rate of water of the composites immersed in distilled water of 95℃ at any time precisely and can calculate how long it will take to reach the specific absorption rate.
Robust linear parameter varying induction motor control with polytopic models
Directory of Open Access Journals (Sweden)
Dalila Khamari
2013-01-01
Full Text Available This paper deals with a robust controller for an induction motor which is represented as a linear parameter varying systems. To do so linear matrix inequality (LMI based approach and robust Lyapunov feedback controller are associated. This new approach is related to the fact that the synthesis of a linear parameter varying (LPV feedback controller for the inner loop take into account rotor resistance and mechanical speed as varying parameter. An LPV flux observer is also synthesized to estimate rotor flux providing reference to cited above regulator. The induction motor is described as a polytopic model because of speed and rotor resistance affine dependence their values can be estimated on line during systems operations. The simulation results are presented to confirm the effectiveness of the proposed approach where robustness stability and high performances have been achieved over the entire operating range of the induction motor.
Minimum information modelling of structural systems with uncertain parameters
Hyland, D. C.
1983-01-01
Work is reviewed wherein the design of active structural control is formulated as the mean-square optimal control of a linear mechanical system with stochastic parameters. In practice, a complete probabilistic description of model parameters can never be provided by empirical determinations, and a suitable design approach must accept very limited a priori data on parameter statistics. In consequence, the mean-square optimization problem is formulated using a complete probability assignment which is made to be consistent with available data but maximally unconstrained otherwise through use of a maximum entropy principle. The ramifications of this approach for both robustness and large dimensionality are illustrated by consideration of the full-state feedback regulation problem.
Parameter estimation in a spatial unit root autoregressive model
Baran, Sándor
2011-01-01
Spatial autoregressive model $X_{k,\\ell}=\\alpha X_{k-1,\\ell}+\\beta X_{k,\\ell-1}+\\gamma X_{k-1,\\ell-1}+\\epsilon_{k,\\ell}$ is investigated in the unit root case, that is when the parameters are on the boundary of the domain of stability that forms a tetrahedron with vertices $(1,1,-1), \\ (1,-1,1),\\ (-1,1,1)$ and $(-1,-1,-1)$. It is shown that the limiting distribution of the least squares estimator of the parameters is normal and the rate of convergence is $n$ when the parameters are in the faces or on the edges of the tetrahedron, while on the vertices the rate is $n^{3/2}$.
Nationwide water availability data for energy-water modeling.
Energy Technology Data Exchange (ETDEWEB)
Tidwell, Vincent Carroll; Zemlick, Katie M.; Klise, Geoffrey Taylor
2013-11-01
The purpose of this effort is to explore where the availability of water could be a limiting factor in the siting of new electric power generation. To support this analysis, water availability is mapped at the county level for the conterminous United States (3109 counties). Five water sources are individually considered, including unappropriated surface water, unappropriated groundwater, appropriated water (western U.S. only), municipal wastewater and brackish groundwater. Also mapped is projected growth in non-thermoelectric consumptive water demand to 2035. Finally, the water availability metrics are accompanied by estimated costs associated with utilizing that particular supply of water. Ultimately these data sets are being developed for use in the National Renewable Energy Laboratories' (NREL) Regional Energy Deployment System (ReEDS) model, designed to investigate the likely deployment of new energy installations in the U.S., subject to a number of constraints, particularly water.
DEVELOPMENT OF WATER CIRCULATION MODEL INCLUDING IRRIGATION
Kotsuki, Shunji; Tanaka, Kenji; Kojiri, Toshiharu; Hamaguchi, Toshio
It is well known that since agricultural water withdrawal has much affect on water circulation system, accurate analysis of river discharge or water balance are difficult with less regard for it. In this study, water circulation model composed of land surface model and distributed runoff model is proposed at 10km 10km resolution. In this model, irrigation water, which is estimated with land surface model, is introduced to river discharge analysis. The model is applied to the Chao Phraya River in Thailand, and reproduced seasonal water balance. Additionally, the discharge on dry season simulated with the model is improved as a result of including irrigation. Since the model, which is basically developed from global data sets, simulated seasonal change of river discharge, it can be suggested that our model has university to other river basins.
A ZeroDimensional Model of a 2nd Generation Planar SOFC Using Calibrated Parameters
Directory of Open Access Journals (Sweden)
Brian Elmegaard
2006-12-01
Full Text Available This paper presents a zero-dimensional mathematical model of a planar 2nd generation coflow SOFC developed for simulation of power systems. The model accounts for the electrochemical oxidation of hydrogen as well as the methane reforming reaction and the water-gas shift reaction. An important part of the paper is the electrochemical sub-model, where experimental data was used to calibrate specific parameters. The SOFC model was implemented in the DNA simulation software which is designed for energy system simulation. The result is an accurate and flexible tool suitable for simulation of many different SOFC-based power systems.
Liu, Y. R.; Li, Y. P.; Huang, G. H.; Zhang, J. L.; Fan, Y. R.
2017-10-01
In this study, a Bayesian-based multilevel factorial analysis (BMFA) method is developed to assess parameter uncertainties and their effects on hydrological model responses. In BMFA, Differential Evolution Adaptive Metropolis (DREAM) algorithm is employed to approximate the posterior distributions of model parameters with Bayesian inference; factorial analysis (FA) technique is used for measuring the specific variations of hydrological responses in terms of posterior distributions to investigate the individual and interactive effects of parameters on model outputs. BMFA is then applied to a case study of the Jinghe River watershed in the Loess Plateau of China to display its validity and applicability. The uncertainties of four sensitive parameters, including soil conservation service runoff curve number to moisture condition II (CN2), soil hydraulic conductivity (SOL_K), plant available water capacity (SOL_AWC), and soil depth (SOL_Z), are investigated. Results reveal that (i) CN2 has positive effect on peak flow, implying that the concentrated rainfall during rainy season can cause infiltration-excess surface flow, which is an considerable contributor to peak flow in this watershed; (ii) SOL_K has positive effect on average flow, implying that the widely distributed cambisols can lead to medium percolation capacity; (iii) the interaction between SOL_AWC and SOL_Z has noticeable effect on the peak flow and their effects are dependent upon each other, which discloses that soil depth can significant influence the processes of plant uptake of soil water in this watershed. Based on the above findings, the significant parameters and the relationship among uncertain parameters can be specified, such that hydrological model's capability for simulating/predicting water resources of the Jinghe River watershed can be improved.
Elhatip, Hatim; Kömür, M. Aydin
2008-01-01
Sustaining the human ecological benefits of surface water requires carefully planned strategies for reducing the cumulative risks posed by diverse human activities. The municipality of Aksaray city plays a key role in developing solutions to surface water management and protection in the central Anatolian part of Turkey. The responsibility to provide drinking water and sewage works, regulate the use of private land and protect public health provides the mandate and authority to take action. The present approach discusses the main sources of contamination and the result of direct wastewater discharges into the Melendiz and Karasu rivers, which recharge the Mamasın dam sites by the use of artificial neural network (ANN) modeling techniques. The present study illustrates the ability to predict and/or approve the output values of previously measured water quality parameters of the recharge and discharge areas at the Mamasin dam site by means of ANN techniques. Using the ANN model is appreciated in such environmental research. Here, the ANN is used for estimating if the field parameters are agreeable to the results of this model or not. The present study simulates a situation in the past by means of ANN. But in case any field measurements of some relative parameters at the outlet point “discharge area” have been missed, it could be possible to predict the approximate output values from the detailed periodical water quality parameters. Because of the high variance and the inherent non-linear relationship of the water quality parameters in time series, it is difficult to produce a reliable model with conventional modeling approaches. In this paper, the ANN modeling technique is used to establish a model for evaluating the change in electrical conductivity (EC) and dissolved oxygen (DO) values in recharge (input) and discharge (output) areas of the dam water under pollution risks. A general ANN modeling scheme is also recommended for the water parameters. The modeling
Modeling Water Quality in Rivers
Directory of Open Access Journals (Sweden)
Liren Yu
2005-01-01
Full Text Available This study reports a PC software, used in a Windows-based environment, which was developed based on the first order reaction of Biological Oxygen Demand (BOD and a modified Streeter and Phelps equation, in order to simulate and determine the variations of Dissolved Oxygen (DO and of the BOD along with the studied river reaches. The software considers many impacts of environmental factors, such as the different type of discharges (concentrated or punctual source, tributary contribution, distributed source, nitrogenous BOD, BOD sedimentation, photosynthetic production and benthic demand of oxygen, and so on. The software has been used to model the DO profile along one river, with the aim to improve the water quality through suitable engineering measure.
Recursive modular modelling methodology for lumped-parameter dynamic systems.
Orsino, Renato Maia Matarazzo
2017-08-01
This paper proposes a novel approach to the modelling of lumped-parameter dynamic systems, based on representing them by hierarchies of mathematical models of increasing complexity instead of a single (complex) model. Exploring the multilevel modularity that these systems typically exhibit, a general recursive modelling methodology is proposed, in order to conciliate the use of the already existing modelling techniques. The general algorithm is based on a fundamental theorem that states the conditions for computing projection operators recursively. Three procedures for these computations are discussed: orthonormalization, use of orthogonal complements and use of generalized inverses. The novel methodology is also applied for the development of a recursive algorithm based on the Udwadia-Kalaba equation, which proves to be identical to the one of a Kalman filter for estimating the state of a static process, given a sequence of noiseless measurements representing the constraints that must be satisfied by the system.
Alp, E.; Yücel, Ö.; Özcan, Z.
2014-12-01
Turkey has been making many legal arrangements for sustainable water management during the harmonization process with the European Union. In order to make cost effective and efficient decisions, monitoring network in Turkey has been expanding. However, due to time and budget constraints, desired number of monitoring campaigns can not be carried. Hence, in this study, independent parameters that can be measured easily and quickly are used to estimate water quality parameters in Lake Mogan and Eymir using linear regression. Nonpoint sources are one of the major pollutant components in Eymir and Mogan lakes. In this paper, a correlation between easily measurable parameters, DO, temperature, electrical conductivity, pH, precipitation and dependent variables, TN, TP, COD, Chl-a, TSS, Total Coliform is investigated. Simple regression analysis is performed for each season in Eymir and Mogan lakes by using SPSS Statistical program using the water quality data collected between 2006-2012. Regression analysis demonstrated significant linear relationship between measured and simulated concentrations for TN (R2=0.86), TP (R2=0.85), TSS (R2=0.91), Chl-a (R2=0.94), COD (R2=0.99), T. Coliform (R2=0.97) which are the best results in each season for Eymir and Mogan Lakes. The overall results of this study shows that by using easily measurable parameters even in ungauged situation the water quality of lakes can be predicted. Moreover, the outputs obtained from the regression equations can be used as an input for water quality models such as phosphorus budget model which is used to calculate the required reduction in the external phosphorus load to Lake Mogan to meet the water quality standards.
Zhou, Liming; Yang, Yuxing; Yuan, Shiying
2006-02-01
A new algorithm, the coordinates transform iterative optimizing method based on the least square curve fitting model, is presented. This arithmetic is used for extracting the bio-impedance model parameters. It is superior to other methods, for example, its speed of the convergence is quicker, and its calculating precision is higher. The objective to extract the model parameters, such as Ri, Re, Cm and alpha, has been realized rapidly and accurately. With the aim at lowering the power consumption, decreasing the price and improving the price-to-performance ratio, a practical bio-impedance measure system with double CPUs has been built. It can be drawn from the preliminary results that the intracellular resistance Ri increased largely with an increase in working load during sitting, which reflects the ischemic change of lower limbs.
Hussain, Faraz; Jha, Sumit K; Jha, Susmit; Langmead, Christopher J
2014-01-01
Stochastic models are increasingly used to study the behaviour of biochemical systems. While the structure of such models is often readily available from first principles, unknown quantitative features of the model are incorporated into the model as parameters. Algorithmic discovery of parameter values from experimentally observed facts remains a challenge for the computational systems biology community. We present a new parameter discovery algorithm that uses simulated annealing, sequential hypothesis testing, and statistical model checking to learn the parameters in a stochastic model. We apply our technique to a model of glucose and insulin metabolism used for in-silico validation of artificial pancreata and demonstrate its effectiveness by developing parallel CUDA-based implementation for parameter synthesis in this model.
Siti Farizwana, M. R.; Mazrura, S.; Zurahanim Fasha, A.; Ahmad Rohi, G.
2010-01-01
The study was to determine the concentration of aluminium (Al) and study the physicochemical parameters (pH, total dissolved solids (TDS), turbidity, and residual chlorine) in drinking water supply in selected palm oil estates in Kota Tinggi, Johor. Water samples were collected from the estates with the private and the public water supplies. The sampling points were at the water source (S), the treatment plant outlet (TPO), and at the nearest houses (H1) and the furthest houses (H2) from the TPO. All estates with private water supply failed to meet the NSDWQ for Al with mean concentration of 0.99 ± 1.52 mg/L. However, Al concentrations in all public water supply estates were well within the limit except for one estate. The pH for all samples complied with the NSDWQ except from the private estates for the drinking water supply with an acidic pH (5.50 ± 0.90). The private water supply showed violated turbidity value in the drinking water samples (14.2 ± 24.1 NTU). Insufficient amount of chlorination was observed in the private water supply estates (0.09 ± 0.30 mg/L). Private water supplies with inefficient water treatment served unsatisfactory drinking water quality to the community which may lead to major health problems. PMID:21461348
Siti Farizwana, M R; Mazrura, S; Zurahanim Fasha, A; Ahmad Rohi, G
2010-01-01
The study was to determine the concentration of aluminium (Al) and study the physicochemical parameters (pH, total dissolved solids (TDS), turbidity, and residual chlorine) in drinking water supply in selected palm oil estates in Kota Tinggi, Johor. Water samples were collected from the estates with the private and the public water supplies. The sampling points were at the water source (S), the treatment plant outlet (TPO), and at the nearest houses (H1) and the furthest houses (H2) from the TPO. All estates with private water supply failed to meet the NSDWQ for Al with mean concentration of 0.99 ± 1.52 mg/L. However, Al concentrations in all public water supply estates were well within the limit except for one estate. The pH for all samples complied with the NSDWQ except from the private estates for the drinking water supply with an acidic pH (5.50 ± 0.90). The private water supply showed violated turbidity value in the drinking water samples (14.2 ± 24.1 NTU). Insufficient amount of chlorination was observed in the private water supply estates (0.09 ± 0.30 mg/L). Private water supplies with inefficient water treatment served unsatisfactory drinking water quality to the community which may lead to major health problems.
Directory of Open Access Journals (Sweden)
M. R. Siti Farizwana
2010-01-01
Full Text Available The study was to determine the concentration of aluminium (Al and study the physicochemical parameters (pH, total dissolved solids (TDS, turbidity, and residual chlorine in drinking water supply in selected palm oil estates in Kota Tinggi, Johor. Water samples were collected from the estates with the private and the public water supplies. The sampling points were at the water source (S, the treatment plant outlet (TPO, and at the nearest houses (H1 and the furthest houses (H2 from the TPO. All estates with private water supply failed to meet the NSDWQ for Al with mean concentration of 0.99 ± 1.52 mg/L. However, Al concentrations in all public water supply estates were well within the limit except for one estate. The pH for all samples complied with the NSDWQ except from the private estates for the drinking water supply with an acidic pH (5.50 ± 0.90. The private water supply showed violated turbidity value in the drinking water samples (14.2 ± 24.1 NTU. Insufficient amount of chlorination was observed in the private water supply estates (0.09 ± 0.30 mg/L. Private water supplies with inefficient water treatment served unsatisfactory drinking water quality to the community which may lead to major health problems.
Propagation channel characterization, parameter estimation, and modeling for wireless communications
Yin, Xuefeng
2016-01-01
Thoroughly covering channel characteristics and parameters, this book provides the knowledge needed to design various wireless systems, such as cellular communication systems, RFID and ad hoc wireless communication systems. It gives a detailed introduction to aspects of channels before presenting the novel estimation and modelling techniques which can be used to achieve accurate models. To systematically guide readers through the topic, the book is organised in three distinct parts. The first part covers the fundamentals of the characterization of propagation channels, including the conventional single-input single-output (SISO) propagation channel characterization as well as its extension to multiple-input multiple-output (MIMO) cases. Part two focuses on channel measurements and channel data post-processing. Wideband channel measurements are introduced, including the equipment, technology and advantages and disadvantages of different data acquisition schemes. The channel parameter estimation methods are ...
Auxiliary Parameter MCMC for Exponential Random Graph Models
Byshkin, Maksym; Stivala, Alex; Mira, Antonietta; Krause, Rolf; Robins, Garry; Lomi, Alessandro
2016-11-01
Exponential random graph models (ERGMs) are a well-established family of statistical models for analyzing social networks. Computational complexity has so far limited the appeal of ERGMs for the analysis of large social networks. Efficient computational methods are highly desirable in order to extend the empirical scope of ERGMs. In this paper we report results of a research project on the development of snowball sampling methods for ERGMs. We propose an auxiliary parameter Markov chain Monte Carlo (MCMC) algorithm for sampling from the relevant probability distributions. The method is designed to decrease the number of allowed network states without worsening the mixing of the Markov chains, and suggests a new approach for the developments of MCMC samplers for ERGMs. We demonstrate the method on both simulated and actual (empirical) network data and show that it reduces CPU time for parameter estimation by an order of magnitude compared to current MCMC methods.
Physicochemical parameters and seasonal variation of coastal water from Balochistan coast, Pakistan
Directory of Open Access Journals (Sweden)
Naeema Elahi
2015-03-01
Full Text Available Objective: To determine common physico-chemical parameters of coastal water. Methods: Physicochemical properties of water were determined according to the standards of the American Public Health Association. Generally, all those parameters were recorded a small variation between stations. The variation in physico-chemical parameters like salinity, temperature, dissolved oxygen and pH at Gwadar (Coastal water of Balochistan were recorded. Results: The range of air temperature of coastal water of Balochistan during 2004 and 2006 varies from 25 ºC to 37 ºC, water temperature ranged from 15.00 ºC to 33.00 ºC, pH ranged from 7.08 to 8.95, salinity ranged from 37.4‰ to 41.3‰ and dissolved oxygen ranged from 5.32 to 8.67 mg/L. Conclusions: Results showed that these parameters of Balochistan coast of Pakistan is not dangerous for marine habitat and the use of these parameters in monitoring programs to assess ecosystem health has the potential to inform the general public and decision-makers about the state of the coastal ecosystems. To save this vital important habitat, the government agencies and scientists should work with proper attention.
Physicochemical parameters and seasonal variation of coastal water from Balochistan coast, Pakistan
Institute of Scientific and Technical Information of China (English)
Naeema Elahi; Quratulan Ahmed; Levent Bat; Farzana Yousuf
2015-01-01
Objective:To determine common physico-chemical parameters of coastal water. Methods:Physicochemical properties of water were determined according to the standards of the American Public Health Association. Generally, all those parameters were recorded a small variation between stations. The variation in physico-chemical parameters like salinity, temperature, dissolved oxygen and pH at Gwadar (Coastal water of Balochistan) were recorded. Results:The range of air temperature of coastal water of Balochistan during 2004 and 2006 varies from 25ºCto 37ºC, water temperature ranged from 15.00ºC to 33.00ºC, pH ranged from 7.08 to 8.95, salinity ranged from 37.4‰ to 41.3‰and dissolved oxygen ranged from 5.32 to 8.67 mg/L. Conclusions:Results showed that these parameters of Balochistan coast of Pakistan is not dangerous for marine habitat and the use of these parameters in monitoring programs to assess ecosystem health has the potential to inform the general public and decision-makers about the state of the coastal ecosystems. To save this vital important habitat, the government agencies and scientists should work with proper attention.
Comparison of anthropometric parameters among Iranian and Spanish water polo players
Directory of Open Access Journals (Sweden)
Pooya Nekooei
2016-06-01
Full Text Available The purpose of this study was to compare the anthropometric parameters between Iranian and Spanish water polo national team players. Material and Methods ― The research was conducted in the physiological laboratory of Isfahan Azad University. Participants who participate in this study were 44 male national water polo players (22 Iranian and 22 Spanish, age 22±2 years old (Mean±SD. For the aim of this study twenty anthropometric parameters that was more important for water polo was measured and analysis. All the parameters were measured base on the international standard of anthropometric parameters (International Society for the Advancement of Kinanthropometry – ISAK. For analysis data, normal distribution of the data was proved by Kolmogorov-Smirnov test and then comparison between two groups was done by t-test. Results ― The results showed a significant difference in seven anthropometric parameters contain body fat percentage (P=0.031, biliocristal breadth (P<0.001, wrist breadth (P<0.001, chest girth (P=0.021, mid-thigh girth (P=0.019, palm length (P<0.001 and height (P=0.032. Conclusion ― Spanish players with relatively higher underlying levels of anthropometric parameters compare to Iranian water polo players had stronger ability to control the ball with the bigger palm and bigger wrist breadth, also they had stronger ability to do water vertical jump, cause of higher value of biliocristal breadth and mid-thigh girth and also stronger throwing the ball because of bigger muscle on their chest part of their body. However, Base on this study, having longer hands, more muscular body than fat and taller stature is an advantage for the players because it is considered to be a useful parameter in water polo.
Determining avalanche modelling input parameters using terrestrial laser scanning technology
2013-01-01
International audience; In dynamic avalanche modelling, data about the volumes and areas of the snow released, mobilized and deposited are key input parameters, as well as the fracture height. The fracture height can sometimes be measured in the field, but it is often difficult to access the starting zone due to difficult or dangerous terrain and avalanche hazards. More complex is determining the areas and volumes of snow involved in an avalanche. Such calculations require high-resolution spa...
Numerical model for thermal parameters in optical materials
Sato, Yoichi; Taira, Takunori
2016-04-01
Thermal parameters of optical materials, such as thermal conductivity, thermal expansion, temperature coefficient of refractive index play a decisive role for the thermal design inside laser cavities. Therefore, numerical value of them with temperature dependence is quite important in order to develop the high intense laser oscillator in which optical materials generate excessive heat across mode volumes both of lasing output and optical pumping. We already proposed a novel model of thermal conductivity in various optical materials. Thermal conductivity is a product of isovolumic specific heat and thermal diffusivity, and independent modeling of these two figures should be required from the viewpoint of a clarification of physical meaning. Our numerical model for thermal conductivity requires one material parameter for specific heat and two parameters for thermal diffusivity in the calculation of each optical material. In this work we report thermal conductivities of various optical materials as Y3Al5O12 (YAG), YVO4 (YVO), GdVO4 (GVO), stoichiometric and congruent LiTaO3, synthetic quartz, YAG ceramics and Y2O3 ceramics. The dependence on Nd3+-doping in laser gain media in YAG, YVO and GVO is also studied. This dependence can be described by only additional three parameters. Temperature dependence of thermal expansion and temperature coefficient of refractive index for YAG, YVO, and GVO: these are also included in this work for convenience. We think our numerical model is quite useful for not only thermal analysis in laser cavities or optical waveguides but also the evaluation of physical properties in various transparent materials.
Land Building Models: Uncertainty in and Sensitivity to Input Parameters
2013-08-01
Louisiana Coastal Area Ecosystem Restoration Projects Study , Vol. 3, Final integrated ERDC/CHL CHETN-VI-44 August 2013 24 feasibility study and... Nourishment Module, Chapter 8. In Coastal Louisiana Ecosystem Assessment and Restoration (CLEAR) Model of Louisiana Coastal Area (LCA) Comprehensive...to Input Parameters by Ty V. Wamsley PURPOSE: The purpose of this Coastal and Hydraulics Engineering Technical Note (CHETN) is to document a
The oblique S parameter in higgsless electroweak models
Rosell, Ignasi
2012-01-01
We present a one-loop calculation of the oblique S parameter within Higgsless models of electroweak symmetry breaking. We have used a general effective Lagrangian with at most two derivatives, implementing the chiral symmetry breaking SU(2)_L x SU(2)_R -> SU(2)_{L+R} with Goldstones, gauge bosons and one multiplet of vector and axial-vector resonances. The estimation is based on the short-distance constraints and the dispersive approach proposed by Peskin and Takeuchi.
A statistical model of proton with no parameter
Zhang, Y; Zhang, Yongjun; Yang, Li-Ming
2001-01-01
In this text, the protons are taken as an ensemble of Fock states. Using detailed balancing principle and equal probability principle, the unpolarized parton distribution of proton is gained through Monte Carlo without any parameter. A new origin of the light flavor sea-quark asymmetry is given here beside known models as Pauli blocking, meson-cloud, chiral-field, chiral-soliton and instantons.
Model of the Stochastic Vacuum and QCD Parameters
Ferreira, E; Ferreira, Erasmo; Pereira, Flávio
1997-01-01
Accounting for the two independent correlation functions of the QCD vacuum, we improve the simple and consistent description given by the model of the stochastic vacuum to the high-energy pp and pbar-p data, with a new determination of parameters of non-perturbative QCD. The increase of the hadronic radii with the energy accounts for the energy dependence of the observables.
Identification of relaxation parameter of a physical model of vein from fluid transient experiment
Directory of Open Access Journals (Sweden)
Hromádka David
2014-03-01
Full Text Available This paper presents a new fluid transient inflation experiment applied on a physical model of vein (short latex tube, 5mm diameter. Aim of experiments is assessment of wall viscous behaviour from attenuated pulsation of the tested sample. Experimental data obtained from dynamic test are compared with numerical simulation and a viscoelastic parameter of Haslach constitutive model is identified. It is verified that the viscoelasticity of wall has a greater impact to the damping of pulsation than the viscosity of water filling the sample and the attached capillary. Volume of sample depends on internal pressure measured by a pressure transducer. The maximum dissipation constitutive model of viscoelastic wall sample was employed for description of viscoelastic behaviour. Frequency of natural oscillation of pressure is determined by inertia of water column within the tested sample and attached capillary and by the tested specimen stiffness. The pressure pulsations are initiated by a sudden pressure drop at water surface.
Nnane, Daniel Ekane; Ebdon, James Edward; Taylor, Huw David
2011-03-01
In many parts of the world, microbial contamination of surface waters used for drinking, recreation, and shellfishery remains a pervasive risk to human health, especially in Less Economically Developed Countries (LEDC). However, the capacity to provide effective management strategies to break the waterborne route to human infection is often thwarted by our inability to identify the source of microbial contamination. Microbial Source Tracking (MST) has potential to improve water quality management in complex river catchments that are either routinely, or intermittently contaminated by faecal material from one or more sources, by attributing faecal loads to their human or non-human sources, and thereby supporting more rational approaches to microbial risk assessment. The River Ouse catchment in southeast England (U.K.) was used as a model with which to investigate the integration and application of a novel and simple MST approach to monitor microbial water quality over one calendar year, thereby encompassing a range of meteorological conditions. A key objective of the work was to develop simple low-cost protocols that could be easily replicated. Bacteriophages (viruses) capable of infecting a human specific strain of Bacteroides GB-124, and their correlation with presumptive Escherichia coli, were used to distinguish sources of faecal pollution. The results reported here suggest that in this river catchment the principal source of faecal pollution in most instances was non-human in origin. During storm events, presumptive E. coli and presumptive intestinal enterococci levels were 1.1-1.2 logs higher than during dry weather conditions, and levels of the faecal indicator organisms (FIOs) were closely associated with increased turbidity levels (presumptive E. coli and turbidity, r = 0.43). Spatio-temporal variation in microbial water quality parameters was accounted for by three principal components (67.6%). Cluster Analysis, reduced the fourteen monitoring sites to six
Digital Repository Service at National Institute of Oceanography (India)
Padma, P.; Sheela, V.S.; Suryakumari, S.; Jayalakshmy, K.V.; Nair, S.M.; Kumar, N.C.
stream_size 64084 stream_content_type text/plain stream_name Water_Qual_Expos_Health_5_197.pdf.txt stream_source_info Water_Qual_Expos_Health_5_197.pdf.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8... Water Qual Expo Health DOI 10.1007/s12403-014-0115-9 ORIGINAL PAPER Assessment of Water Quality of a River-Dominated Estuary with Hydrochemical Parameters: A Statistical Approach P. Padma · V. S. Sheela · S. Suryakumari · K. V. Jayalakshmy · S. M. Nair...
A robust approach for the determination of Gurson model parameters
Directory of Open Access Journals (Sweden)
R. Sepe
2016-07-01
Full Text Available Among the most promising models introduced in recent years, with which it is possible to obtain very useful results for a better understanding of the physical phenomena involved in the macroscopic mechanism of crack propagation, the one proposed by Gurson and Tvergaard links the propagation of a crack to the nucleation, growth and coalescence of micro-voids, which is likely to connect the micromechanical characteristics of the component under examination to crack initiation and propagation up to a macroscopic scale. It must be pointed out that, even if the statistical character of some of the many physical parameters involved in the said model has been put in evidence, no serious attempt has been made insofar to link the corresponding statistic to the experimental and macroscopic results, as for example crack initiation time, material toughness, residual strength of the cracked component (R-Curve, and so on. In this work, such an analysis was carried out in a twofold way: the former concerned the study of the influence exerted by each of the physical parameters on the material toughness, and the latter concerned the use of the Stochastic Design Improvement (SDI technique to perform a “robust” numerical calibration of the model evaluating the nominal values of the physical and correction parameters, which fit a particular experimental result even in the presence of their “natural” variability.
Effects of thermodynamics parameters on mass transfer of volatile pollutants at air-water interface
Directory of Open Access Journals (Sweden)
Li-ping Chen
2015-07-01
Full Text Available A transient three-dimensional coupling model based on the compressible volume of fluid (VOF method was developed to simulate the transport of volatile pollutants at the air-water interface. VOF is a numerical technique for locating and tracking the free surface of water flow. The relationships between Henry’s constant, thermodynamics parameters, and the enlarged topological index were proposed for nonstandard conditions. A series of experiments and numerical simulations were performed to study the transport of benzene and carbinol. The simulation results agreed with the experimental results. Temperature had no effect on mass transfer of pollutants with low transfer free energy and high Henry’s constant. The temporal and spatial distribution of pollutants with high transfer free energy and low Henry’s constant was affected by temperature. The total enthalpy and total transfer free energy increased significantly with temperature, with significant fluctuations at low temperatures. The total enthalpy and total transfer free energy increased steadily without fluctuation at high temperatures.
Kim, Kyung Yong; Lee, Won-Chan
2017-01-01
This article provides a detailed description of three factors (specification of the ability distribution, numerical integration, and frame of reference for the item parameter estimates) that might affect the item parameter estimation of the three-parameter logistic model, and compares five item calibration methods, which are combinations of the…
Iosjpe, M.
2011-10-01
A sensitivity analysis has been carried out on the basis of the local and global sensitivity indexes for selected radionuclides ( 3H, 137Cs, 238Pu, 241Am and 244Cm) and main parameters describing the water-sediment interaction (sediment reworking rate, pore-water turnover rate, sediment distribution coefficient, suspended sediment load in water column, sedimentation rate, molecular diffusion coefficient, surface sediment thickness, porosity of bottom sediment and density of sediment material). Sensitivity analysis has been carried out using a compartment model for dose assessment to man and biota, which includes the processes of advection of radioactivity between compartments, sedimentation, diffusion of radioactivity through pore water in sediments, particle mixing, pore water mixing and a burial process of radioactivity in deep sediment layers. The sensitivity analysis indicates that for the conditions in the Norwegian Current (the Norwegian Sea) particle mixing dominates the transfer of radioactivity between the bottom water and surface sediment compartments. For the conditions in the Ob Bay (the Kara Sea), the sedimentation process has also been found to be significant. The calculated dynamics of the sensitivity indexes demonstrate clearly the complexities encountered when modeling water-sediment interactions. It is also shown that the results can be strongly dependent on the time of analysis. For example, given a specific change of parameters the radionuclide concentration will be either increased or decreased, depending on the temporal interval. Information provided by the sensitivity analysis can contribute to a better understanding of experimental data and might further improve the parameterization process. The obtained results show that water-sediment interactions can play a key role in the marine coastal environment, thus demonstrating the need to further deepen our understanding of them, as well as improve the models describing them.
Information Theoretic Tools for Parameter Fitting in Coarse Grained Models
Kalligiannaki, Evangelia
2015-01-07
We study the application of information theoretic tools for model reduction in the case of systems driven by stochastic dynamics out of equilibrium. The model/dimension reduction is considered by proposing parametrized coarse grained dynamics and finding the optimal parameter set for which the relative entropy rate with respect to the atomistic dynamics is minimized. The minimization problem leads to a generalization of the force matching methods to non equilibrium systems. A multiplicative noise example reveals the importance of the diffusion coefficient in the optimization problem.
Nonlocal order parameters for the 1D Hubbard model.
Montorsi, Arianna; Roncaglia, Marco
2012-12-07
We characterize the Mott-insulator and Luther-Emery phases of the 1D Hubbard model through correlators that measure the parity of spin and charge strings along the chain. These nonlocal quantities order in the corresponding gapped phases and vanish at the critical point U(c)=0, thus configuring as hidden order parameters. The Mott insulator consists of bound doublon-holon pairs, which in the Luther-Emery phase turn into electron pairs with opposite spins, both unbinding at U(c). The behavior of the parity correlators is captured by an effective free spinless fermion model.
Surrogate based approaches to parameter inference in ocean models
Knio, Omar
2016-01-06
This talk discusses the inference of physical parameters using model surrogates. Attention is focused on the use of sampling schemes to build suitable representations of the dependence of the model response on uncertain input data. Non-intrusive spectral projections and regularized regressions are used for this purpose. A Bayesian inference formalism is then applied to update the uncertain inputs based on available measurements or observations. To perform the update, we consider two alternative approaches, based on the application of Markov Chain Monte Carlo methods or of adjoint-based optimization techniques. We outline the implementation of these techniques to infer dependence of wind drag, bottom drag, and internal mixing coefficients.
Energy deposition model for I-125 photon radiation in water
Energy Technology Data Exchange (ETDEWEB)
Fuss, M.C.; Garcia, G. [Instituto de Fisica Fundamental, Consejo Superior de Investigaciones Cientificas (CSIC), Madrid (Spain); Munoz, A.; Oller, J.C. [Centro de Investigaciones Energeticas, Medioambientales y Tecnologicas (CIEMAT), Madrid (Spain); Blanco, F. [Departamento de Fisica Atomica, Molecular y Nuclear, Universidad Complutense de Madrid (Spain); Limao-Vieira, P. [Laboratorio de Colisoes Atomicas e Moleculares, Departamento de Fisica, CEFITEC, FCT-Universidade Nova de Lisboa, Caparica (Portugal); Williart, A.; Garcia, G. [Departamento de Fisica de los Materiales, Universidad Nacional de Educacion a Distancia, Madrid (Spain); Huerga, C.; Tellez, M. [Hospital Universitario La Paz, Madrid (Spain)
2010-10-15
In this study, an electron-tracking Monte Carlo algorithm developed by us is combined with established photon transport models in order to simulate all primary and secondary particle interactions in water for incident photon radiation. As input parameters for secondary electron interactions, electron scattering cross sections by water molecules and experimental energy loss spectra are used. With this simulation, the resulting energy deposition can be modelled at the molecular level, yielding detailed information about localization and type of single collision events. The experimental emission spectrum of I-125 seeds, as used for radiotherapy of different tumours, was used for studying the energy deposition in water when irradiating with this radionuclide. (authors)
Dynamic Water Modeling and Application of Billet Continuous Casting
Institute of Scientific and Technical Information of China (English)
LIU Wen-hong; XIE Zhi; JI Zhen-ping; WANG Biao; LAI Zhao-yi; JIA Guang-lin
2008-01-01
The continuous casting process is used for solidifying molten steel into semi-finished steel. The technology of secondary cooling is extremely important for output of the casting machine and billet quality. A dynamic water model was introduced, including solidification model in the secondary cooling, feedforward control strategy based on continuous temperature measurement in tundish, and feedback control strategy based on surface temperature measurement. The mathematical model of solidification process was developed according to the principle of solidification, and the solidification model was validated by measuring billet shell thickness through shooting nail and sulfur print. Primary water distribution was calculated by the solidification model according to procedure parameters, and it was adjusted by the other two control strategies online. The model was applied on some caster and billet quality was obviously improved, indicating that the dynamic water model is better than conventional ones.
Effects of water quality parameters on boron toxicity to Ceriodaphnia dubia.
Dethloff, Gail M; Stubblefield, William A; Schlekat, Christian E
2009-07-01
The potential modifying effects of certain water quality parameters (e.g., hardness, alkalinity, pH) on the acute toxicity of boron were tested using a freshwater cladoceran, Ceriodaphnia dubia. By comparison, boron acute toxicity was less affected by water quality characteristics than some metals (e.g., copper and silver). Increases in alkalinity over the range tested did not alter toxicity. Increases in water hardness appeared to have an effect with very hard waters (>500 mg/L as CaCO(3)). Decreased pH had a limited influence on boron acute toxicity in laboratory waters. Increasing chloride concentration did not provide a protective effect. Boron acute toxicity was unaffected by sodium concentrations. Median acute lethal concentrations (LC(50)) in natural water samples collected from three field sites were all greater than in reconstituted laboratory waters that matched natural waters in all respects except for dissolved organic carbon. Water effect ratios in these waters ranged from 1.4 to 1.8. In subsequent studies using a commercially available source of natural organic matter, acute toxicity decreased with increased dissolved organic carbon, suggesting, along with the natural water studies, that dissolved organic carbon should be considered further as a modifier of boron toxicity in natural waters where it exceeds 2 mg/L.
Fernández-Pato, Javier; Caviedes-Voullième, Daniel; García-Navarro, Pilar
2016-05-01
One of the most difficult issues in the development of hydrologic models is to find a rigorous source of data and specific parameters to a given problem, on a given location that enable reliable calibration. In this paper, a distributed and physically based model (2D Shallow Water Equations) is used for surface flow and runoff calculations in combination with two infiltration laws (Horton and Green-Ampt) for estimating infiltration in a watershed. This technique offers the capability of assigning a local and time-dependent infiltration rate to each computational cell depending on the available surface water, soil type or vegetation. We investigate how the calibration of parameters is affected by transient distributed Shallow Water model and the complexity of the problem. In the first part of this work, we calibrate the infiltration parameters for both Horton and Green-Ampt models under flat ponded soil conditions. Then, by means of synthetic test cases, we perform a space-distributed sensitivity analysis in order to show that this calibration can be significantly affected by the introduction of topography or rainfall. In the second part, parameter calibration for a real catchment is addressed by comparing the numerical simulations with two different sets of experimental data, corresponding to very different events in terms of the rainfall volume. We show that the initial conditions of the catchment and the rainfall pattern have a special relevance in the quality of the adjustment. Hence, it is shown that the topography of the catchment and the storm characteristics affect the calibration of infiltration parameters.
Comparison of parameter estimation algorithms in hydrological modelling
DEFF Research Database (Denmark)
Blasone, Roberta-Serena; Madsen, Henrik; Rosbjerg, Dan
2006-01-01
Local search methods have been applied successfully in calibration of simple groundwater models, but might fail in locating the optimum for models of increased complexity, due to the more complex shape of the response surface. Global search algorithms have been demonstrated to perform well...... for these types of models, although at a more expensive computational cost. The main purpose of this study is to investigate the performance of a global and a local parameter optimization algorithm, respectively, the Shuffled Complex Evolution (SCE) algorithm and the gradient-based Gauss......-Marquardt-Levenberg algorithm (implemented in the PEST software), when applied to a steady-state and a transient groundwater model. The results show that PEST can have severe problems in locating the global optimum and in being trapped in local regions of attractions. The global SCE procedure is, in general, more effective...
Moolenaar, H.E.; Selten, F.M.
2004-01-01
Climate models contain numerous parameters for which the numeric values are uncertain. In the context of climate simulation and prediction, a relevant question is what range of climate outcomes is possible given the range of parameter uncertainties. Which parameter perturbation changes the climate i
Sensitivity analysis of dimensionless parameters for physical simulation of water-flooding reservoir
Institute of Scientific and Technical Information of China (English)
BAI Yuhu; LI Jiachun; ZHOU Jifu
2005-01-01
A numerical approach to optimize dimensionless parameters of water-flooding porous media flows is proposed based on the analysis of the sensitivity factor defined as the variation ration of a target function with respect to the variation of dimensionless parameters. A complete set of scaling criteria for water-flooding reservoir of five-spot well pattern case is derived from the 3-D governing equations, involving the gravitational force,the capillary force and the compressibility of water, oil and rock. By using this approach,we have estimated the influences of each dimensionless parameter on experimental results, and thus sorting out the dominant ones with larger sensitivity factors ranging from 10-4 to 100.
Parameter and uncertainty estimation for mechanistic, spatially explicit epidemiological models
Finger, Flavio; Schaefli, Bettina; Bertuzzo, Enrico; Mari, Lorenzo; Rinaldo, Andrea
2014-05-01
Epidemiological models can be a crucially important tool for decision-making during disease outbreaks. The range of possible applications spans from real-time forecasting and allocation of health-care resources to testing alternative intervention mechanisms such as vaccines, antibiotics or the improvement of sanitary conditions. Our spatially explicit, mechanistic models for cholera epidemics have been successfully applied to several epidemics including, the one that struck Haiti in late 2010 and is still ongoing. Calibration and parameter estimation of such models represents a major challenge because of properties unusual in traditional geoscientific domains such as hydrology. Firstly, the epidemiological data available might be subject to high uncertainties due to error-prone diagnosis as well as manual (and possibly incomplete) data collection. Secondly, long-term time-series of epidemiological data are often unavailable. Finally, the spatially explicit character of the models requires the comparison of several time-series of model outputs with their real-world counterparts, which calls for an appropriate weighting scheme. It follows that the usual assumption of a homoscedastic Gaussian error distribution, used in combination with classical calibration techniques based on Markov chain Monte Carlo algorithms, is likely to be violated, whereas the construction of an appropriate formal likelihood function seems close to impossible. Alternative calibration methods, which allow for accurate estimation of total model uncertainty, particularly regarding the envisaged use of the models for decision-making, are thus needed. Here we present the most recent developments regarding methods for parameter and uncertainty estimation to be used with our mechanistic, spatially explicit models for cholera epidemics, based on informal measures of goodness of fit.
A review of hydrological/water-quality models
Directory of Open Access Journals (Sweden)
Liangliang GAO,Daoliang LI
2014-12-01
Full Text Available Water quality models are important in predicting the changes in surface water quality for environmental management. A range of water quality models are wildly used, but every model has its advantages and limitations for specific situations. The aim of this review is to provide a guide to researcher for selecting a suitable water quality model. Eight well known water quality models were selected for this review: SWAT, WASP, QUALs, MIKE 11, HSPF, CE-QUAL-W2, ELCOM-CAEDYM and EFDC. Each model is described according to its intended use, development, simulation elements, basic principles and applicability (e.g., for rivers, lakes, and reservoirs and estuaries. Currently, the most important trends for future model development are: (1 combination models─individual models cannot completely solve the complex situations so combined models are needed to obtain the most appropriate results, (2 application of artificial intelligence and mechanistic models combined with non-mechanistic models will provide more accurate results because of the realistic parameters derived from non-mechanistic models, and (3 integration with remote sensing, geographical information and global position systems (3S ─3S can solve problems requiring large amounts of data.
Patil, Dilip A; Deshmukh, Prashant K; Fursule, Ravindra A; Patil, Pravin O
2010-07-01
This study has been carried out to find out the water pollutants and to test the suitability of water for drinking and irrigation purposes in Dhule and surrounding areas in Maharashtra State in India. The analysis was carried out for the parameters pH, DO (dissolved oxygen), BOD (biological oxygen demand), Cl-, NO3-, F-, S(2)-, total alkalinity, total solid, total dissolved solids (TDS), total suspended solids (TSS), total hardness, calcium, magnesium, carbonate and noncarbonate hardness, and concentrations of calcium and magnesium. These parameters were compared against the standards laid down by World Health Organization (WHO) and Indian Council of Medical Research (ICMR) for drinking water quality. High levels of NO(3)-, Cl-, F-, S(2)-, total solid, TDS, TSS, total hardness, magnesium and calcium have been found in the collected samples. From these observations, it has been found that fluoride is present as per the permissible limit (WHO 2003) in some of the villages studied, but both fluoride and nitrate levels are unacceptable in drinking water samples taken from several villages in Dhule. This is a serious problem and, therefore, requires immediate attention. Excess of theses impurities in water causes many diseases in plants and animals. This study has been carried out to find out the water pollutants and to test the suitability of water for drinking and irrigation purposes in Dhule and surrounding areas in Maharashtra.
Order-parameter model for unstable multilane traffic flow
Lubashevsky; Mahnke
2000-11-01
We discuss a phenomenological approach to the description of unstable vehicle motion on multilane highways that explains in a simple way the observed sequence of the "free flow synchronized mode jam" phase transitions as well as the hysteresis in these transitions. We introduce a variable called an order parameter that accounts for possible correlations in the vehicle motion at different lanes. So, it is principally due to the "many-body" effects in the car interaction in contrast to such variables as the mean car density and velocity being actually the zeroth and first moments of the "one-particle" distribution function. Therefore, we regard the order parameter as an additional independent state variable of traffic flow. We assume that these correlations are due to a small group of "fast" drivers and by taking into account the general properties of the driver behavior we formulate a governing equation for the order parameter. In this context we analyze the instability of homogeneous traffic flow that manifested itself in the above-mentioned phase transitions and gave rise to the hysteresis in both of them. Besides, the jam is characterized by the vehicle flows at different lanes which are independent of one another. We specify a certain simplified model in order to study the general features of the car cluster self-formation under the "free flow synchronized motion" phase transition. In particular, we show that the main local parameters of the developed cluster are determined by the state characteristics of vehicle motion only.
Accelerated gravitational wave parameter estimation with reduced order modeling.
Canizares, Priscilla; Field, Scott E; Gair, Jonathan; Raymond, Vivien; Smith, Rory; Tiglio, Manuel
2015-02-20
Inferring the astrophysical parameters of coalescing compact binaries is a key science goal of the upcoming advanced LIGO-Virgo gravitational-wave detector network and, more generally, gravitational-wave astronomy. However, current approaches to parameter estimation for these detectors require computationally expensive algorithms. Therefore, there is a pressing need for new, fast, and accurate Bayesian inference techniques. In this Letter, we demonstrate that a reduced order modeling approach enables rapid parameter estimation to be performed. By implementing a reduced order quadrature scheme within the LIGO Algorithm Library, we show that Bayesian inference on the 9-dimensional parameter space of nonspinning binary neutron star inspirals can be sped up by a factor of ∼30 for the early advanced detectors' configurations (with sensitivities down to around 40 Hz) and ∼70 for sensitivities down to around 20 Hz. This speedup will increase to about 150 as the detectors improve their low-frequency limit to 10 Hz, reducing to hours analyses which could otherwise take months to complete. Although these results focus on interferometric gravitational wave detectors, the techniques are broadly applicable to any experiment where fast Bayesian analysis is desirable.
Reduction of Waste Water in Erhai Lake Based on MIKE21 Hydrodynamic and Water Quality Model
Directory of Open Access Journals (Sweden)
Changjun Zhu
2013-01-01
Full Text Available In order to study the ecological water environment in Erhai Lake, different monitoring sections were set to research the change of hydrodynamics and water quality. According to the measured data, MIKE21 Ecolab, the water quality simulation software developed by DHI, is applied to simulate the water quality in Erhai Lake. The hydrodynamics model coupled with water quality is established by MIKE21FM software to simulate the current situation of Erhai Lake. Then through the comparison with the monitoring data, the model parameters are calibrated and the simulation results are verified. Based on this, water quality is simulated by the two-dimensional hydrodynamics and water quality coupled model. The results indicate that the level of water quality in the north and south of lake is level III, while in the center of lake, the water quality is level II. Finally, the water environment capacity and total emmision reduction of pollutants are filtered to give some guidance for the water resources management and effective utilization in the Erhai Lake.
Santaren, D.; Peylin, P.; Viovy, N.; Ciais, P.
2003-04-01
Global model of Carbone, water, and energy exchanges between the biosphere and the atmosphere are usually validated and calibrated with intensive measurement made over specific ecosystem like those of the fluxnet networks.However the nonlinear dependance between fluxes and model parameters generally complicate the optimization of the major parameters.In this study, we estimate few key parameters of the ORCHIDEE french model,using diurnal variation measurements of latent heat,sensible heat and net CO2 fluxes for 3 weeks over pine forest (Landes, France).The model is forced with the observed climatic forcing: Temperature, income solar radiations,wind velocity norm, air humidity, pressure and precipitations. We will first present the inverse methodology and the problem linkedto the non linearity. The result of the optimization shows correlations within the initial ensemble of parameters which allow us to choose only five parameters determined independently from the observations. Directly related to the net CO2 flux, the maximum rate of carboxylation,Vcmax,and the stomatal conductance, gs, are significantly changed from their apriori estimate for that period. The aerodynamic resistance, the albedo and a parameter linked to maintenance respiration were also modified within their physical range.Overall the model fit to the data was largely improved. Note however that some discrepancies remain for sensible heat flux which would probably require some model improvements for the stocking of energy in the soil. Such work is currently extended in time to account for parameter variations between the season. The application to other ecosystems and with the supplementary data of the Leaf Area Index will be also discussed.
Tillman, Fred D.; Weaver, James W.
Migration of volatile chemicals from the subsurface into overlying buildings is known as vapor intrusion (VI). Under certain circumstances, people living in homes above contaminated soil or ground water may be exposed to harmful levels of these vapors. VI is a particularly difficult pathway to assess, as challenges exist in delineating subsurface contributions to measured indoor-air concentrations as well as in adequate characterization of subsurface parameters necessary to calibrate a predictive flow and transport model. Often, a screening-level model is employed to determine if a potential indoor inhalation exposure pathway exists and, if such a pathway is complete, whether long-term exposure increases the occupants' risk for cancer or other toxic effects to an unacceptable level. A popular screening-level algorithm currently in wide use in the United States, Canada and the UK for making such determinations is the "Johnson and Ettinger" (J&E) model. Concern exists over using the J&E model for deciding whether or not further action is necessary at sites as many parameters are not routinely measured (or are un-measurable). Many screening decisions are then made based on simulations using "best estimate" look-up parameter values. While research exists on the sensitivity of the J&E model to individual parameter uncertainty, little published information is available on the combined effects of multiple uncertain parameters and their effect on screening decisions. This paper presents results of multiple-parameter uncertainty analyses using the J&E model to evaluate risk to humans from VI. Software was developed to produce automated uncertainty analyses of the model. Results indicate an increase in predicted cancer risk from multiple-parameter uncertainty by nearly a factor of 10 compared with single-parameter uncertainty. Additionally, a positive skew in model response to variation of some parameters was noted for both single and multiple parameter uncertainty analyses
Influence of Reaction Parameters on Water Absorbency of Starch Grafted Superabsorbents
Institute of Scientific and Technical Information of China (English)
LI Ming-da; ZHOU Yong-yuan
2002-01-01
Superabsorbents starch grafted sodium polyacrylate was synthesized by inverse suspension polymerization, using toluene as the continuous phase, potassium persulfate as the initiator. The effect of reaction parameters, such as starch pretreatment temperature, neutralization degree of monomer, reaction time and temperature,concentration of initiator, molar ratio of monomer and starch, on