Simultaneous inference for model averaging of derived parameters
DEFF Research Database (Denmark)
Jensen, Signe Marie; Ritz, Christian
2015-01-01
Model averaging is a useful approach for capturing uncertainty due to model selection. Currently, this uncertainty is often quantified by means of approximations that do not easily extend to simultaneous inference. Moreover, in practice there is a need for both model averaging and simultaneous...... inference for derived parameters calculated in an after-fitting step. We propose a method for obtaining asymptotically correct standard errors for one or several model-averaged estimates of derived parameters and for obtaining simultaneous confidence intervals that asymptotically control the family...
Zhang, Hong Mei; Wang, Yue; Fatemi, Mostafa; Insana, Michael F
2017-03-01
Kelvin-Voigt fractional derivative (KVFD) model parameters have been used to describe viscoelastic properties of soft tissues. However, translating model parameters into a concise set of intrinsic mechanical properties related to tissue composition and structure remains challenging. This paper begins by exploring these relationships using a biphasic emulsion materials with known composition. Mechanical properties are measured by analyzing data from two indentation techniques - ramp-stress relaxation and load-unload hysteresis tests. Material composition is predictably correlated with viscoelastic model parameters. Model parameters estimated from the tests reveal that elastic modulus E 0 closely approximates the shear modulus for pure gelatin. Fractional-order parameter α and time constant τ vary monotonically with the volume fraction of the material's fluid component. α characterizes medium fluidity and the rate of energy dissipation, and τ is a viscous time constant. Numerical simulations suggest that the viscous coefficient η is proportional to the energy lost during quasi-static force-displacement cycles, E A . The slope of E A versus η is determined by α and the applied indentation ramp time T r . Experimental measurements from phantom and ex vivo liver data show close agreement with theoretical predictions of the η - E A relation. The relative error is less than 20% for emulsions 22% for liver. We find that KVFD model parameters form a concise features space for biphasic medium characterization that described time-varying mechanical properties.
Kawano, N.; Varquez, A. C. G.; Dong, Y.; Kanda, M.
2016-12-01
Numerical model such as Weather Research and Forecasting model coupled with single-layer Urban Canopy Model (WRF-UCM) is one of the powerful tools to investigate urban heat island. Urban parameters such as average building height (Have), plain area index (λp) and frontal area index (λf), are necessary inputs for the model. In general, these parameters are uniformly assumed in WRF-UCM but this leads to unrealistic urban representation. Distributed urban parameters can also be incorporated into WRF-UCM to consider a detail urban effect. The problem is that distributed building information is not readily available for most megacities especially in developing countries. Furthermore, acquiring real building parameters often require huge amount of time and money. In this study, we investigated the potential of using globally available satellite-captured datasets for the estimation of the parameters, Have, λp, and λf. Global datasets comprised of high spatial resolution population dataset (LandScan by Oak Ridge National Laboratory), nighttime lights (NOAA), and vegetation fraction (NASA). True samples of Have, λp, and λf were acquired from actual building footprints from satellite images and 3D building database of Tokyo, New York, Paris, Melbourne, Istanbul, Jakarta and so on. Regression equations were then derived from the block-averaging of spatial pairs of real parameters and global datasets. Results show that two regression curves to estimate Have and λf from the combination of population and nightlight are necessary depending on the city's level of development. An index which can be used to decide which equation to use for a city is the Gross Domestic Product (GDP). On the other hand, λphas less dependence on GDP but indicated a negative relationship to vegetation fraction. Finally, a simplified but precise approximation of urban parameters through readily-available, high-resolution global datasets and our derived regressions can be utilized to estimate a
Zhang, Hongmei; Wang, Yue; Fatemi, Mostafa; Insana, Michael F.
2017-03-01
Kelvin-Voigt fractional derivative (KVFD) model parameters have been used to describe viscoelastic properties of soft tissues. However, translating model parameters into a concise set of intrinsic mechanical properties related to tissue composition and structure remains challenging. This paper begins by exploring these relationships using a biphasic emulsion materials with known composition. Mechanical properties are measured by analyzing data from two indentation techniques—ramp-stress relaxation and load-unload hysteresis tests. Material composition is predictably correlated with viscoelastic model parameters. Model parameters estimated from the tests reveal that elastic modulus E 0 closely approximates the shear modulus for pure gelatin. Fractional-order parameter α and time constant τ vary monotonically with the volume fraction of the material’s fluid component. α characterizes medium fluidity and the rate of energy dissipation, and τ is a viscous time constant. Numerical simulations suggest that the viscous coefficient η is proportional to the energy lost during quasi-static force-displacement cycles, E A . The slope of E A versus η is determined by α and the applied indentation ramp time T r. Experimental measurements from phantom and ex vivo liver data show close agreement with theoretical predictions of the η -{{E}A} relation. The relative error is less than 20% for emulsions 22% for liver. We find that KVFD model parameters form a concise features space for biphasic medium characterization that described time-varying mechanical properties. The experimental work was carried out at the Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA. Methodological development, including numerical simulation and all data analysis, were carried out at the school of Life Science and Technology, Xi’an JiaoTong University, 710049, China.
Energy Technology Data Exchange (ETDEWEB)
Ye, Sheng; Li, Hongyi; Huang, Maoyi; Ali, Melkamu; Leng, Guoyong; Leung, Lai-Yung R.; Wang, Shaowen; Sivapalan, Murugesu
2014-07-21
Subsurface stormflow is an important component of the rainfall–runoff response, especially in steep terrain. Its contribution to total runoff is, however, poorly represented in the current generation of land surface models. The lack of physical basis of these common parameterizations precludes a priori estimation of the stormflow (i.e. without calibration), which is a major drawback for prediction in ungauged basins, or for use in global land surface models. This paper is aimed at deriving regionalized parameterizations of the storage–discharge relationship relating to subsurface stormflow from a top–down empirical data analysis of streamflow recession curves extracted from 50 eastern United States catchments. Detailed regression analyses were performed between parameters of the empirical storage–discharge relationships and the controlling climate, soil and topographic characteristics. The regression analyses performed on empirical recession curves at catchment scale indicated that the coefficient of the power-law form storage–discharge relationship is closely related to the catchment hydrologic characteristics, which is consistent with the hydraulic theory derived mainly at the hillslope scale. As for the exponent, besides the role of field scale soil hydraulic properties as suggested by hydraulic theory, it is found to be more strongly affected by climate (aridity) at the catchment scale. At a fundamental level these results point to the need for more detailed exploration of the co-dependence of soil, vegetation and topography with climate.
Use of remote sensing derived parameters in a crop model for biomass prediction of hay crop
El Hajj, Mohammad; Baghdadi, Nicolas; Cheviron, Bruno; Belaud, Gilles; Zribi, Mehrez
2016-04-01
Pre-harvest yield forecasting is a critical challenge for producers, especially for large agricultural areas. During previous decades, numerous crop models were developed to predict crop growth and yield at daily time, most often for wheat or maize, and also for grasslands. Crop models require several input parameters that describe soil properties (e.g. field capacity), plant characteristics (e.g. maximal rooting depth) and management options (e.g. sowing dates, irrigation and harvest dates), which are referred to as the soil, plant and management families of parameters. Remote sensing technology has been extensively applied to identify spatially distributed values of some of the accessible parameters in the soil, plant and management families. The aim of this study was to address the feasibility, merits and limitations of forcing remote-sensing-derived parameters (LAI values, harvest and irrigation dates) in the PILOTE crop model, targeting the Total Dry Matter (TDM) of hay crops. Results show that optical images are suitable to feed PILOTE with LAI values without inducing significant errors on the predicted Total Dry Matter (TDM) values (Root Mean Square Error "RMSE" = 0.41 t/ha and Mean Absolute Percentage Error "MAPE" = 22%). Moreover, optical images with revisit times lower than 16 days are adequate to feed PILOTE with remotely sensed harvest dates (RMSE irrigation dates that were estimated from SAR images also enabled reliable model predictions, at least when attaching a random uncertainty of "only" 3 days to the real known irrigation dates. The case of one or several undetected irrigations has also been explored, with the expected conclusion that undetected irrigations significantly affect model predictions only in dry periods. For the tested soil properties and climatic conditions, a maximum underestimation of TDM of approximately 1.55 t/ha (reference TDM of 3.43 t/ha) was observed in the second crop growth cycle when ignoring two irrigations out of four in
Parinussa, R.M.; Meesters, A.G.C.A.; Liu, Y.Y.; Dorigo, W.; Wagner, W.; de Jeu, R.A.M.
2011-01-01
A time-efficient solution to estimate the error of satellite surface soil moisture from the land parameter retrieval model is presented. The errors are estimated using an analytical solution for soil moisture retrievals from this radiative-transfer-based model that derives soil moisture from
Parameter estimation of a pulp digester model with derivative-free optimization strategies
Seiça, João C.; Romanenko, Andrey; Fernandes, Florbela P.; Santos, Lino O.; Fernandes, Natércia C. P.
2017-07-01
The work concerns the parameter estimation in the context of the mechanistic modelling of a pulp digester. The problem is cast as a box bounded nonlinear global optimization problem in order to minimize the mismatch between the model outputs with the experimental data observed at a real pulp and paper plant. MCSFilter and Simulated Annealing global optimization methods were used to solve the optimization problem. While the former took longer to converge to the global minimum, the latter terminated faster at a significantly higher value of the objective function and, thus, failed to find the global solution.
Deriving force field parameters for coordination complexes
DEFF Research Database (Denmark)
Norrby, Per-Ola; Brandt, Peter
2001-01-01
The process of deriving molecular mechanics force fields for coordination complexes is outlined. Force field basics are introduced with an emphasis on special requirements for metal complexes. The review is then focused on how to set up the initial model, define the target, refine the parameters......, and validate the final force field, Alternatives to force field derivation are discussed briefly....
Mathematical models for prediction of rheological parameters in vinasses derived from sugar cane
Chacua, Leidy M.; Ayala, Germán; Rojas, Hernán; Agudelo, Ana C.
2016-04-01
The rheological behaviour of vinasses derived from sugar cane was studied as a function of time (0 and 600 s), soluble solids content (44 and 60 °Brix), temperature (10 and 50°C), and shear rate (0.33 and 1.0 s-1). The results indicated that vinasses were time-independent at 25°C, where shear stress values ranged between 0.01 and 0.08 Pa. Flow curves showed a shear-thinning rheological behaviour in vinasses with a flow behaviour index between 0.69 and 0.89, for temperature between 10 and 20°C. With increasing temperature, the flow behaviour index was modified, reaching values close to 1.0. The Arrhenius model described well the thermal activation of shear stress and the consistency coefficient as a function of temperature. Activation energy from the Arrhenius model ranged between 31 and 45 kJ mol-1. Finally, the consistency coefficient as a function of the soluble solids content and temperature was well fitted using an exponential model (R2 = 0.951), showing that the soluble solids content and temperature have an opposite effect on consistency coefficient values.
DEFF Research Database (Denmark)
Ramin, Elham; Sin, Gürkan; Mikkelsen, Peter Steen
2011-01-01
Uncertainty derived from one of the process models – such as one-dimensional secondary settling tank (SST) models – can impact the output of the other process models, e.g., biokinetic (ASM1), as well as the integrated wastewater treatment plant (WWTP) models. The model structure and parameter...... uncertainty of settler models can therefore propagate, and add to the uncertainties in prediction of any plant performance criteria. Here we present an assessment of the relative significance of secondary settling model performance in WWTP simulations. We perform a global sensitivity analysis (GSA) based....... The outcome of this study contributes to a better understanding of uncertainty in WWTPs, and explicitly demonstrates the significance of secondary settling processes that are crucial elements of model prediction under dry and wet-weather loading conditions....
Saramago, Pedro; Manca, Andrea; Sutton, Alex J
2012-01-01
The evidence base informing economic evaluation models is rarely derived from a single source. Researchers are typically expected to identify and combine available data to inform the estimation of model parameters for a particular decision problem. The absence of clear guidelines on what data can be used and how to effectively synthesize this evidence base under different scenarios inevitably leads to different approaches being used by different modelers. The aim of this article is to produce a taxonomy that can help modelers identify the most appropriate methods to use when synthesizing the available data for a given model parameter. This article developed a taxonomy based on possible scenarios faced by the analyst when dealing with the available evidence. While mainly focusing on clinical effectiveness parameters, this article also discusses strategies relevant to other key input parameters in any economic model (i.e., disease natural history, resource use/costs, and preferences). The taxonomy categorizes the evidence base for health economic modeling according to whether 1) single or multiple data sources are available, 2) individual or aggregate data are available (or both), or 3) individual or multiple decision model parameters are to be estimated from the data. References to examples of the key methodological developments for each entry in the taxonomy together with citations to where such methods have been used in practice are provided throughout. The use of the taxonomy developed in this article hopes to improve the quality of the synthesis of evidence informing decision models by bringing to the attention of health economics modelers recent methodological developments in this field. Copyright © 2012 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
Urban Heat Island Modeling in Conjunction with Satellite-Derived Surface/Soil Parameters.
Hafner, Jan; Kidder, Stanley Q.
1999-04-01
Although it has been studied for over 160 years, the urban heat island (UHI) effect is still not completely understood, yet it is increasingly important. The main purpose of this work is to improve UHI modeling by using AVHRR (Advanced Very High Resolution Radiometer) satellite data to retrieve the surface parameters (albedo, as well as soil thermal and moisture properties). In this study, a hydrostatic three-dimensional mesoscale model was used to perform the numerical modeling. The Carlson technique was applied to retrieve the thermal inertia and moisture availability using the thermal AVHRR channels 4 and 5. The net urban effect was determined as the difference between urban and nonurban simulations, in which urban parameters were replaced by rural parameters.Two winter days were each used for two numerical simulations: a control and an urban-to-rural replacement run. Moisture availability values on the less windy day showed generally a south to north gradient downwind of the city and urban values less than rural values (the urban dry island day). Moisture availability was higher on the windy day, with uniform values in the rural and urban areas (uniform soil moisture day). The only exceptions were variations in the rural hills north of the city and the low rural values under the polluted urban plume downwind of the city.While thermal inertia values showed no urban-rural differences on the uniform soil moisture day, they exhibited larger values over Atlanta than in surrounding rural area on the (less moist) dry island day. Two puzzling facts exist in the data: 1) lack of a north-south thermal inertia gradient on the dry soil day to correspond to its above-mentioned moisture availability gradient and 2) rural thermal inertia values do not change between both days in spite of their large difference in soil moisture. The observed lack of corresponding urban change is expected, as its thermal inertia values depend more on urban building materials than on moisture of
Derivation of potential model for LiAlO2 by simple and effective optimization of model parameters
International Nuclear Information System (INIS)
Tsuchihira, H.; Oda, T.; Tanaka, S.
2009-01-01
Interatomic potentials of LiAlO 2 were constructed by a simple and effective method. In this method, the model function consists of multiple inverse polynomial functions with an exponential truncation function, and parameters in the potential model can be optimized as a solution of simultaneous linear equations. Potential energies obtained by ab initio calculation are used as fitting targets for model parameter optimization. Lattice constants, elastic properties, defect-formation energy, thermal expansions and the melting point were calculated under the constructed potential models. The results showed good agreement with experimental values and ab initio calculation results, which underscores the validity of the presented method.
Directory of Open Access Journals (Sweden)
Anette Hauge
2017-11-01
Full Text Available Abstract Background Abnormalities in the tumor microenvironment are associated with resistance to treatment, aggressive growth, and poor clinical outcome in patients with advanced cervical cancer. The potential of dynamic contrast-enhanced (DCE MRI to assess the microvascular density (MVD, interstitial fluid pressure (IFP, and hypoxic fraction of patient-derived cervical cancer xenografts was investigated in the present study. Methods Four patient-derived xenograft (PDX models of squamous cell carcinoma of the uterine cervix (BK-12, ED-15, HL-16, and LA-19 were subjected to Gd-DOTA-based DCE-MRI using a 7.05 T preclinical scanner. Parametric images of the volume transfer constant (K trans and the fractional distribution volume (v e of the contrast agent were produced by pharmacokinetic analyses utilizing the standard Tofts model. Whole tumor median values of the DCE-MRI parameters were compared with MVD and the fraction of hypoxic tumor tissue, as determined histologically, and IFP, as measured with a Millar catheter. Results Both on the PDX model level and the single tumor level, a significant inverse correlation was found between K trans and hypoxic fraction. The extent of hypoxia was also associated with the fraction of voxels with unphysiological v e values (v e > 1.0. None of the DCE-MRI parameters were related to MVD or IFP. Conclusions DCE-MRI may provide valuable information on the hypoxic fraction of squamous cell carcinoma of the uterine cervix, and thereby facilitate individualized patient management.
Deriving force field parameters for coordination complexes
DEFF Research Database (Denmark)
Norrby, Per-Ola; Brandt, Peter
2001-01-01
The process of deriving molecular mechanics force fields for coordination complexes is outlined. Force field basics are introduced with an emphasis on special requirements for metal complexes. The review is then focused on how to set up the initial model, define the target, refine the parameters...
Lee, Mi Ji; Son, Jeong Pyo; Kim, Suk Jae; Ryoo, Sookyung; Woo, Sook-Young; Cha, Jihoon; Kim, Gyeong-Moon; Chung, Chin-Sang; Lee, Kwang Ho; Bang, Oh Young
2015-10-01
Good collateral flow is an important predictor for favorable responses to recanalization therapy and successful outcomes after acute ischemic stroke. Magnetic resonance perfusion-weighted imaging (MRP) is widely used in patients with stroke. However, it is unclear whether the perfusion parameters and thresholds would predict collateral status. The present study evaluated the relationship between hypoperfusion severity and collateral status to develop a predictive model for good collaterals using MRP parameters. Patients who were eligible for recanalization therapy that underwent both serial diffusion-weighted imaging and serial MRP were enrolled into the study. A collateral flow map derived from MRP source data was generated through automatic postprocessing. Hypoperfusion severity, presented as proportions of every 2-s Tmax strata to the entire hypoperfusion volume (Tmax≥2 s), was compared between patients with good and poor collaterals. Prediction models for good collaterals were developed with each Tmax strata proportion and cerebral blood volumes. Among 66 patients, 53 showed good collaterals based on MRP-based collateral grading. Although no difference was noted in delays within 16 s, more severe Tmax delays (Tmax16-18 s, Tmax18-22 s, Tmax22-24 s, and Tmax>24 s) were associated with poor collaterals. The probability equation model using Tmax strata proportion demonstrated high predictive power in a receiver operating characteristic analysis (area under the curve=0.9303; 95% confidence interval, 0.8682-0.9924). The probability score was negatively correlated with the volume of infarct growth (P=0.030). Collateral status is associated with more severe Tmax delays than previously defined. The present Tmax severity-weighted model can determine good collaterals and subsequent infarct growth. © 2015 American Heart Association, Inc.
Directory of Open Access Journals (Sweden)
Kovačević Strahinja Z.
2013-01-01
Full Text Available In the present paper, the antifungal activity of a series of benzoxazole and oxazolo[ 4,5-b]pyridine derivatives was evaluated against Candida albicans by using quantitative structure-activity relationships chemometric methodology with artificial neural network (ANN regression approach. In vitro antifungal activity of the tested compounds was presented by minimum inhibitory concentration expressed as log(1/cMIC. In silico pharmacokinetic parameters related to absorption, distribution, metabolism and excretion (ADME were calculated for all studied compounds by using PreADMET software. A feedforward back-propagation ANN with gradient descent learning algorithm was applied for modelling of the relationship between ADME descriptors (blood-brain barrier penetration, plasma protein binding, Madin-Darby cell permeability and Caco-2 cell permeability and experimental log(1/cMIC values. A 4-6-1 ANN was developed with the optimum momentum and learning rates of 0.3 and 0.05, respectively. An excellent correlation between experimental antifungal activity and values predicted by the ANN was obtained with a correlation coefficient of 0.9536. [Projekat Ministarstva nauke Republike Srbije, br. 172012 i br. 172014
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)
Energy Technology Data Exchange (ETDEWEB)
Riches, S.F.; Payne, G.S.; Morgan, V.A.; DeSouza, N.M. [Royal Marsden NHS Foundation Trust and Institute of Cancer Research, CRUK and EPSRC Cancer Imaging Centre, Sutton, Surrey (United Kingdom); Dearnaley, D. [Royal Marsden NHS Foundation Trust and Institute of Cancer Research, Department of Urology and Department of Academic Radiotherapy, Sutton, Surrey (United Kingdom); Morgan, S. [The Ottawa Hospital Cancer Centre and the University of Ottawa, Division of Radiation Oncology, Ottawa, Ontario (Canada); Partridge, M. [The Institute of Cancer Research, Section of Radiotherapy and Imaging, Sutton, Surrey (United Kingdom); University of Oxford, The Gray Institute for Radiation Oncology and Biology, Oxford (United Kingdom); Livni, N. [Royal Marsden NHS Foundation Trust Chelsea, Department of Histopathology, London (United Kingdom); Ogden, C. [Royal Marsden NHS Foundation Trust Chelsea, Department of Urology, London (United Kingdom)
2015-05-01
The objectives are determine the optimal combination of MR parameters for discriminating tumour within the prostate using linear discriminant analysis (LDA) and to compare model accuracy with that of an experienced radiologist. Multiparameter MRIs in 24 patients before prostatectomy were acquired. Tumour outlines from whole-mount histology, T{sub 2}-defined peripheral zone (PZ), and central gland (CG) were superimposed onto slice-matched parametric maps. T{sub 2,} Apparent Diffusion Coefficient, initial area under the gadolinium curve, vascular parameters (K{sup trans},K{sub ep},V{sub e}), and (choline+polyamines+creatine)/citrate were compared between tumour and non-tumour tissues. Receiver operating characteristic (ROC) curves determined sensitivity and specificity at spectroscopic voxel resolution and per lesion, and LDA determined the optimal multiparametric model for identifying tumours. Accuracy was compared with an expert observer. Tumours were significantly different from PZ and CG for all parameters (all p < 0.001). Area under the ROC curve for discriminating tumour from non-tumour was significantly greater (p < 0.001) for the multiparametric model than for individual parameters; at 90 % specificity, sensitivity was 41 % (MRSI voxel resolution) and 59 % per lesion. At this specificity, an expert observer achieved 28 % and 49 % sensitivity, respectively. The model was more accurate when parameters from all techniques were included and performed better than an expert observer evaluating these data. (orig.)
Xie, Tian; Chen, Xiao; Fang, Jingqin; Kang, Houyi; Xue, Wei; Tong, Haipeng; Cao, Peng; Wang, Sumei; Yang, Yizeng; Zhang, Weiguo
2017-08-28
Presurgical glioma grading by dynamic contrast-enhanced MRI (DCE-MRI) has unresolved issues. The aim of this study was to investigate the ability of textural features derived from pharmacokinetic model-based or model-free parameter maps of DCE-MRI in discriminating between different grades of gliomas, and their correlation with pathological index. Retrospective. Forty-two adults with brain gliomas. 3.0T, including conventional anatomic sequences and DCE-MRI sequences (variable flip angle T1-weighted imaging and three-dimensional gradient echo volumetric imaging). Regions of interest on the cross-sectional images with maximal tumor lesion. Five commonly used textural features, including Energy, Entropy, Inertia, Correlation, and Inverse Difference Moment (IDM), were generated. All textural features of model-free parameters (initial area under curve [IAUC], maximal signal intensity [Max SI], maximal up-slope [Max Slope]) could effectively differentiate between grade II (n = 15), grade III (n = 13), and grade IV (n = 14) gliomas (P IDM, of four DCE-MRI parameters, including Max SI, Max Slope (model-free parameters), vp (Extended Tofts), and vp (Patlak) could differentiate grade III and IV gliomas (P IDM of Patlak-based K trans and vp could differentiate grade II (n = 15) from III (n = 13) gliomas (P IDM of Extended Tofts- and Patlak-based vp showed highest area under curve in discriminating between grade III and IV gliomas. However, intraclass correlation coefficient (ICC) of these features revealed relatively lower inter-observer agreement. No significant correlation was found between microvascular density and textural features, compared with a moderate correlation found between cellular proliferation index and those features. Textural features of DCE-MRI parameter maps displayed a good ability in glioma grading. 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2017. © 2017 International Society for Magnetic Resonance in Medicine.
International Nuclear Information System (INIS)
Vomvoris, S.; Andrews, R.W.; Lanyon, G.W.; Voborny, O.; Wilson, W.
1996-04-01
Switzerland is one of many nations with nuclear power that is seeking to identify rock types and locations that would be suitable for the underground disposal of nuclear waste. A common challenge among these programs is to provide engineering designers and safety analysts with a reasonably representative hydrogeological input dataset that synthesizes the relevant information from direct field observations as well as inferences and model results derived from those observations. Needed are estimates of the volumetric flux through a volume of rock and the distribution of that flux into discrete pathways between the repository zones and the biosphere. These fluxes are not directly measurable but must be derived based on understandings of the range of plausible hydrogeologic conditions expected at the location investigated. The methodology described in this report utilizes conceptual and numerical models at various scales to derive the input dataset. The methodology incorporates an innovative approach, called the geometric approach, in which field observations and their associated uncertainty, together with a conceptual representation of those features that most significantly affect the groundwater flow regime, were rigorously applied to generate alternative possible realizations of hydrogeologic features in the geosphere. In this approach, the ranges in the output values directly reflect uncertainties in the input values. As a demonstration, the methodology is applied to the derivation of the hydrogeological dataset for the crystalline basement of Northern Switzerland. (author) figs., tabs., refs
Linking Item Response Model Parameters.
van der Linden, Wim J; Barrett, Michelle D
2016-09-01
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 test equating scores on different test forms. This paper argues, however, that the use of item response models does not require any test score equating. Instead, it involves the necessity of parameter linking due to a fundamental problem inherent in the formal nature of these models-their general lack of identifiability. More specifically, item response model parameters need to be linked to adjust for the different effects of the identifiability restrictions used in separate item calibrations. Our main theorems characterize the formal nature of these linking functions for monotone, continuous response models, derive their specific shapes for different parameterizations of the 3PL model, and show how to identify them from the parameter values of the common items or persons in different linking designs.
Energy Technology Data Exchange (ETDEWEB)
Jerome, Neil P.; Miyazaki, Keiko; Collins, David J.; Orton, Matthew R.; D' Arcy, James A.; Leach, Martin O. [Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging, The Institute of Cancer Research, London (United Kingdom); Wallace, Toni; Koh, Dow-Mu [Royal Marsden NHS Foundation Trust, Department of Radiology, Sutton, Surrey (United Kingdom); Moreno, Lucas [The Institute of Cancer Research, Paediatric Drug Development Team, Division of Cancer Therapeutics and Clinical Studies, London (United Kingdom); Hospital Nino Jesus, Madrid (Spain); Royal Marsden NHS Foundation Trust, Paediatric Drug Development Unit, Children and Young People' s Unit, Sutton, Surrey (United Kingdom); Pearson, Andrew D.J.; Marshall, Lynley V.; Carceller, Fernando; Zacharoulis, Stergios [The Institute of Cancer Research, Paediatric Drug Development Team, Division of Cancer Therapeutics and Clinical Studies, London (United Kingdom); Royal Marsden NHS Foundation Trust, Paediatric Drug Development Unit, Children and Young People' s Unit, Sutton, Surrey (United Kingdom)
2017-01-15
To examine repeatability of parameters derived from non-Gaussian diffusion models in data acquired in children with solid tumours. Paediatric patients (<16 years, n = 17) were scanned twice, 24 h apart, using DWI (6 b-values, 0-1000 mm{sup -2} s) at 1.5 T in a prospective study. Tumour ROIs were drawn (3 slices) and all data fitted using IVIM, stretched exponential, and kurtosis models; percentage coefficients of variation (CV) calculated for each parameter at all ROI histogram centiles, including the medians. The values for ADC, D, DDC{sub α}, α, and DDC{sub K} gave CV < 10 % down to the 5th centile, with sharp CV increases below 5th and above 95th centile. K, f, and D* showed increased CV (>30 %) over the histogram. ADC, D, DDC{sub α}, and DDC{sub K} were strongly correlated (ρ > 0.9), DDC{sub α} and α were not correlated (ρ = 0.083). Perfusion- and kurtosis-related parameters displayed larger, more variable CV across the histogram, indicating observed clinical changes outside of D/DDC in these models should be interpreted with caution. Centiles below 5th for all parameters show high CV and are unreliable as diffusion metrics. The stretched exponential model behaved well for both DDC{sub α} and α, making it a strong candidate for modelling multiple-b-value diffusion imaging data. (orig.)
Spegazzini, Nicolas; Siesler, Heinz W; Ozaki, Yukihiro
2012-10-02
A sequential identification approach by two-dimensional (2D) correlation analysis for the identification of a chemical reaction model, activation, and thermodynamic parameters is presented in this paper. The identification task is decomposed into a sequence of subproblems. The first step is the construction of a reaction model with the suggested information by model-free 2D correlation analysis using a novel technique called derivative double 2D correlation spectroscopy (DD2DCOS), which enables one to analyze intensities with nonlinear behavior and overlapped bands. The second step is a model-based 2D correlation analysis where the activation and thermodynamic parameters are estimated by an indirect implicit calibration or a calibration-free approach. In this way, a minimization process for the spectral information by sample-sample 2D correlation spectroscopy and kinetic hard modeling (using ordinary differential equations) of the chemical reaction model is carried out. The sequential identification by 2D correlation analysis is illustrated with reference to the isomeric structure of diphenylurethane synthesized from phenylisocyanate and phenol. The reaction was investigated by FT-IR spectroscopy. The activation and thermodynamic parameters of the isomeric structures of diphenylurethane linked through a hydrogen bonding equilibrium were studied by means of an integration of model-free and model-based 2D correlation analysis called a sequential identification approach. The study determined the enthalpy (ΔH = 15.25 kJ/mol) and entropy (TΔS = 13.20 kJ/mol) of C═O···H hydrogen bonding of diphenylurethane through direct calculation from the differences in the kinetic parameters (δΔ(‡)H, -TδΔ(‡)S) at equilibrium in the chemical reaction system.
Response model parameter linking
Barrett, M.L.D.
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
Srinivas, Nuggehally R; Ahlawat, Preeti; Shaik, Jafar Bhasha
2013-01-01
Ciclesonide, a novel glucocorticosteroid, through a rapid metabolism to desisobutyryl-ciclesonide (des-ciclesonide), provides an effective treatment option for asthma episodes by the inhaled route of administration. The availability of pharmacokinetic parameters (clearance [CL/F]; volume of distribution [Vd/F]; elimination half-life [T(½)]; and elimination rate constant [Kel]) in mice, rats, rabbits, and dogs enabled the prediction of human parameter values for des-ciclesonide using the well-accepted tool of allometry after intravenous administration of ciclesonide. However, as a result of the rapid conversion of ciclesonide, it was possible to perform allometry for the CL parameter only. Simple allometry (CL = 4.781W⁰·⁷⁸⁷⁴; R² = 0.9968) appeared to predict the CL of ciclesonide in close proximity of the observed value (observed: 101.25 L/h versus predicted: 135.62 L/h). In a similar manner, simple allometry predicted the human pharmacokinetic parameters of des-ciclesonide (CL/F, Vd/F, T(½), and Kel) within a two- to threefold range of the observed values. The allometric equations for des-ciclesonide parameter values were: CL/F = 4.8166W⁰·⁴⁹² (R² = 0.8598); Vd/F = 19.052W⁰·⁶³² (R² = 0.9049); T(½) = 3.7598W⁻⁰·¹⁶¹¹(R² = 0.8551); and Kel = 0.1832W⁰·¹⁵⁹⁶ (R² = 0.8632). In conclusion, the data suggested that allometry tool may be amenable for the prediction of the pharmacokinetic parameters of des-ciclesonide despite differences in the conversion rates and bioavailability of the active metabolite in various animal species.
Lee, J. C.; Liu, Z. Y. C.; Shirzaei, M.
2016-12-01
The Chihshang fault lies at the plate suture between the Eurasian and the Philippine Sea plates along the Longitudinal Valley in eastern Taiwan. Here we investigate depth variation of fault frictional parameters derived from the post-seismic slip model of the 2003 Mw 6.5 Chengkung earthquake. Assuming a rate-strengthening friction, we implement an inverse dynamic modeling scheme to estimate the frictional parameter (a-b) and reference friction coefficient (μ*) in depths by taking into account: pre-seismic stress as well as co-seismic and post-seismic coulomb stress changes associated with the 2003 Chengkung earthquake. We investigate two coseismic models by Hsu et al. (2009) and Thomas et al. (2014). Model parameters, including stress gradient, depth dependent a-b and μ*, are determined from fitting the transient post-seismic geodetic signal measured at 12 continuous GPS stations. In our inversion scheme, we apply a non-linear optimization algorithm, Genetic Algorithm (GA), to search for the optimum frictional parameters. Considering the zone with velocity-strengthening frictional properties along Chihshang fault, the optimum a-b is 7-8 × 10-3 along the shallow part of the fault (0-10 km depth) and 1-2 × 10-2 in 22-28 km depth. Optimum solution for μ* is 0.3-0.4 in 0-10 km depth and reaches 0.8 in 22-28 km depth. The optimized stress gradient is 54 MPa/ km. The inferred frictional parameters are consistent with the laboratory measurements on clay-rich fault zone gouges comparable to the Lichi Melange, which is thrust over Holocene alluvial deposits across the Chihshang fault, considering the main rock composition of the Chihshang fault, at least at the upper kilometers level of the fault. Our results can facilitate further studies in particular on seismic cycle and hazard assessment of active faults.
Directory of Open Access Journals (Sweden)
Nelson Pires
2016-07-01
Full Text Available A conceptually simple formulation is proposed for a new empirical sea state bias (SSB model using information retrieved entirely from altimetric data. Nonparametric regression techniques are used, based on penalized smoothing splines adjusted to each predictor and then combined by a Generalized Additive Model. In addition to the significant wave height (SWH and wind speed (U10, a mediator parameter designed by the mean wave period derived from radar altimetry, has proven to improve the model performance in explaining some of the SSB variability, especially in swell ocean regions with medium-high SWH and low U10. A collinear analysis of scaled sea level anomalies (SLA variance differences shows conformity between the proposed model and the established SSB models. The new formulation aims to be a fast, reliable and flexible SSB model, in line with the well-settled SSB corrections, depending exclusively on altimetric information. The suggested method is computationally efficient and capable of generating a stable model with a small training dataset, a useful feature for forthcoming missions.
Parameters and error of a theoretical model
International Nuclear Information System (INIS)
Moeller, P.; Nix, J.R.; Swiatecki, W.
1986-09-01
We propose a definition for the error of a theoretical model of the type whose parameters are determined from adjustment to experimental data. By applying a standard statistical method, the maximum-likelihoodlmethod, we derive expressions for both the parameters of the theoretical model and its error. We investigate the derived equations by solving them for simulated experimental and theoretical quantities generated by use of random number generators. 2 refs., 4 tabs
Gledhill, M.; Gerringa, L.J.A.
2017-01-01
In this study we examine the impact of dissolved metal concentrations on the parameters that are commonly determined from complexometric titrations in seawater. We use the non-ideal competitive adsorption (NICA) model within the framework of the chemical speciation program visual MINTEQ with iron as a model metal. We demonstrate that dissolved iron concentrations effect the determined parameters for a heterogeneous binding site distribution with a fixed concentration of dissolved organic carb...
Trimmel, Heidelinde; Weihs, Philipp; Oswald, Sandro M.; Masson, Valéry; Schoetter, Robert
2017-04-01
Urban settlements are generally known for their high fractions of impermeable surfaces, large heat capacity and low humidity compared to rural areas which results in the well known phenomena of urban heat islands. The urbanized areas are growing which can amplify the intensity and frequency of situations with heat stress. The distribution of the urban heat island is not uniform though, because the urban environment is highly diverse regarding its morphology as building heights, building contiguity and configuration of open spaces and trees vary, which cause changes in the aerodynamic resistance for heat transfers and drag coefficients for momentum. Furthermore cities are characterized by highly variable physical surface properties as albedo, emissivity, heat capacity and thermal conductivity. The distribution of the urban heat island is influenced by these morphological and physical parameters as well as the distribution of unsealed soil and vegetation. These aspects influence the urban climate on micro- and mesoscale. For larger Vienna high resolution vector and raster geodatasets were processed to derive land use surface fractions and building morphology parameters on block scale following the methodology of Cordeau (2016). A dataset of building age and typology was cross checked and extended using satellite visual and thermal bands and linked to a database joining building age and typology with typical physical building parameters obtained from different studies (Berger et al. 2012 and Amtmann M and Altmann-Mavaddat N (2014)) and the OIB (Österreichisches Institut für Bautechnik). Using dominant parameters obtained using this high resolution mainly ground based data sets (building height, built area fraction, unsealed fraction, sky view factor) a local climate zone classification was produced using an algorithm. The threshold values were chosen according to Stewart and Oke (2012). This approach is compared to results obtained with the methodology of Bechtel et
Sanz, E.; Voss, C.I.
2006-01-01
Inverse modeling studies employing data collected from the classic Henry seawater intrusion problem give insight into several important aspects of inverse modeling of seawater intrusion problems and effective measurement strategies for estimation of parameters for seawater intrusion. Despite the simplicity of the Henry problem, it embodies the behavior of a typical seawater intrusion situation in a single aquifer. Data collected from the numerical problem solution are employed without added noise in order to focus on the aspects of inverse modeling strategies dictated by the physics of variable-density flow and solute transport during seawater intrusion. Covariances of model parameters that can be estimated are strongly dependent on the physics. The insights gained from this type of analysis may be directly applied to field problems in the presence of data errors, using standard inverse modeling approaches to deal with uncertainty in data. Covariance analysis of the Henry problem indicates that in order to generally reduce variance of parameter estimates, the ideal places to measure pressure are as far away from the coast as possible, at any depth, and the ideal places to measure concentration are near the bottom of the aquifer between the center of the transition zone and its inland fringe. These observations are located in and near high-sensitivity regions of system parameters, which may be identified in a sensitivity analysis with respect to several parameters. However, both the form of error distribution in the observations and the observation weights impact the spatial sensitivity distributions, and different choices for error distributions or weights can result in significantly different regions of high sensitivity. Thus, in order to design effective sampling networks, the error form and weights must be carefully considered. For the Henry problem, permeability and freshwater inflow can be estimated with low estimation variance from only pressure or only
International Nuclear Information System (INIS)
Galeriu, D; Melintescu, A
2010-01-01
Tritium ( 3 H) is a radioactive isotope of hydrogen that is ubiquitous in environmental and biological systems. Following debate on the human health risk from exposure to tritium, there have been claims that the current biokinetic model recommended by the International Commission on Radiological Protection (ICRP) may underestimate tritium doses. A new generic model for tritium in mammals, based on energy metabolism and body composition, together with all its input data, has been described in a recent paper and successfully tested for farm and laboratory mammals. That model considers only dietary intake of tritium and was extended to humans. This paper presents the latest development of the human model with explicit consideration of brain energy metabolism. Model testing with human experimental data on organically bound tritium (OBT) in urine after tritiated water (HTO) or OBT intakes is presented. Predicted absorbed doses show a moderate increase for OBT intakes compared with doses recommended by the ICRP. Infants have higher tritium retention-a factor of 2 longer than the ICRP estimate. The highest tritium concentration is in adipose tissue, which has a very low radiobiological sensitivity. The ranges of uncertainty in retention and doses are investigated. The advantage of the new model is its ability to be applied to the interpretation of bioassay data.
Model parameter updating using Bayesian networks
Energy Technology Data Exchange (ETDEWEB)
Treml, C. A. (Christine A.); Ross, Timothy J.
2004-01-01
This paper outlines a model parameter updating technique for a new method of model validation using a modified model reference adaptive control (MRAC) framework with Bayesian Networks (BNs). The model parameter updating within this method is generic in the sense that the model/simulation to be validated is treated as a black box. It must have updateable parameters to which its outputs are sensitive, and those outputs must have metrics that can be compared to that of the model reference, i.e., experimental data. Furthermore, no assumptions are made about the statistics of the model parameter uncertainty, only upper and lower bounds need to be specified. This method is designed for situations where a model is not intended to predict a complete point-by-point time domain description of the item/system behavior; rather, there are specific points, features, or events of interest that need to be predicted. These specific points are compared to the model reference derived from actual experimental data. The logic for updating the model parameters to match the model reference is formed via a BN. The nodes of this BN consist of updateable model input parameters and the specific output values or features of interest. Each time the model is executed, the input/output pairs are used to adapt the conditional probabilities of the BN. Each iteration further refines the inferred model parameters to produce the desired model output. After parameter updating is complete and model inputs are inferred, reliabilities for the model output are supplied. Finally, this method is applied to a simulation of a resonance control cooling system for a prototype coupled cavity linac. The results are compared to experimental data.
VLBI-derived troposphere parameters during CONT08
Heinkelmann, R.; Böhm, J.; Bolotin, S.; Engelhardt, G.; Haas, R.; Lanotte, R.; MacMillan, D. S.; Negusini, M.; Skurikhina, E.; Titov, O.; Schuh, H.
2011-07-01
Time-series of zenith wet and total troposphere delays as well as north and east gradients are compared, and zenith total delays ( ZTD) are combined on the level of parameter estimates. Input data sets are provided by ten Analysis Centers (ACs) of the International VLBI Service for Geodesy and Astrometry (IVS) for the CONT08 campaign (12-26 August 2008). The inconsistent usage of meteorological data and models, such as mapping functions, causes systematics among the ACs, and differing parameterizations and constraints add noise to the troposphere parameter estimates. The empirical standard deviation of ZTD among the ACs with regard to an unweighted mean is 4.6 mm. The ratio of the analysis noise to the observation noise assessed by the operator/software impact (OSI) model is about 2.5. These and other effects have to be accounted for to improve the intra-technique combination of VLBI-derived troposphere parameters. While the largest systematics caused by inconsistent usage of meteorological data can be avoided and the application of different mapping functions can be considered by applying empirical corrections, the noise has to be modeled in the stochastic model of intra-technique combination. The application of different stochastic models shows no significant effects on the combined parameters but results in different mean formal errors: the mean formal errors of the combined ZTD are 2.3 mm (unweighted), 4.4 mm (diagonal), 8.6 mm [variance component (VC) estimation], and 8.6 mm (operator/software impact, OSI). On the one hand, the OSI model, i.e. the inclusion of off-diagonal elements in the cofactor-matrix, considers the reapplication of observations yielding a factor of about two for mean formal errors as compared to the diagonal approach. On the other hand, the combination based on VC estimation shows large differences among the VCs and exhibits a comparable scaling of formal errors. Thus, for the combination of troposphere parameters a combination of the two
Sounding-derived parameters associated with large hail and tornadoes in the Netherlands
Groenemeijer, P.H.; van Delden, A.J.|info:eu-repo/dai/nl/072670703
2007-01-01
A study is presented focusing on the potential value of parameters derived from radiosonde data or data from numerical atmospheric models for the forecasting of severe weather associated with convective storms. Parameters have been derived from soundings in the proximity of large hail, tornadoes
Harfi, Thura T; Seo, Jung-Hee; Yasir, Hayder S; Welsh, Nathaniel; Mayer, Susan A; Abraham, Theodore P; George, Richard T; Mittal, Rajat
2017-01-15
To describe the derivation and validation of a novel echocardiographic metric for prediction of left ventricle thrombus (LVT). Computational fluid dynamic modeling using cardiac CT images was used to derive a novel echocardiography-based metric to predict the presence of LVT. We retrospectively reviewed 25 transthoracic echocardiograms showing definite LVT (LVT group). We then randomly selected 25 patients with LVEF ≥55% (Normal EF group) and 25 patients with severe cardiomyopathy (CMP) with LVEF ≤40% without evidence of LVT (CMP group). The E-wave Propagation Index (EPI) was measured as the E-wave velocity time-integral divided by the LV length. An EPI>1 indicates penetration of the mitral jet into the apex whereas an EPIwave propagation index is a novel, easily-obtainable, echocardiographic metric to evaluate apical LV flow. An EPI of less than 1 is an independent predictor of LVT formation. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Martha Gledhill
2017-08-01
Full Text Available In this study we examine the impact of dissolved metal concentrations on the parameters that are commonly determined from complexometric titrations in seawater. We use the non-ideal competitive adsorption (NICA model within the framework of the chemical speciation program visual MINTEQ with iron as a model metal. We demonstrate that dissolved iron concentrations effect the determined parameters for a heterogeneous binding site distribution with a fixed concentration of dissolved organic carbon. The commonly used terms “ligand concentration” and “binding constant” are therefore dependent on metal concentration, so we adopt the terminology suggested by Town and Filella (2000 and use the terms ligand quotient and stability quotient here. The systematic increase in the ligand quotient with dissolved iron concentration likely contributes toward the trend of increasing ligand quotient with dissolved iron concentration observed in field studies, and makes it hard to assign an objective meaning to the parameter. We suggest that calculation of the side reaction coefficient, a parameter that describes the probability that any added metal will be complexed, could be less prone to bias and misinterpretation than calculation of conditional stability and ligand quotients. We explore the impact of experimental design on side reaction coefficients by applying different detection windows, and multiwindow and reverse titration approaches. We identify the method that results in the best estimates of side reaction coefficients over a range of iron concentrations between 0.1 and 1.5 nmol L−1. We find that single window titrations can only reliably estimate side reaction coefficients over a limited range of iron concentrations. Multiwindow titrations provided estimates of side reaction coefficients within the 99% confidence interval of the values calculated directly from the NICA model at all iron concentrations examined here. We recommend that future
Energy Technology Data Exchange (ETDEWEB)
Andersson, Johan; Hermansson, Jan [Golder Grundteknik KB (Sweden); Elert, M.; Gylling, B. [Kemakta Konsult AB, Stockholm (Sweden); Moreno, L [Royal Inst. of Tech., Stockholm (Sweden). Dept. of Chemical Engineering and Technology; Selroos, J.O. [Swedish Nuclear Fuel and Waste Management Co., Stockholm (Sweden)
1998-12-01
This report concerns the selection of flow related transport parameters for the SR 97 safety assessment project. Interrelationships of the parameters controlling migration and matrix diffusion in the far-field and the issue of spatially varying properties along the migration paths are discussed. Available field information on porosity, flow wetted surface and dispersivity from Aberg, Beberg and Ceberg are explored and values and uncertainty ranges to be used in the assessment calculations are suggested. It is shown how to combine results from the hydrogeological modelling of SR 97 with the data estimates in order to produce parameters to the source term and far-field migration codes. Evaluation of migration and matrix diffusion along varying flow paths demonstrates that the assessment relevant parameter for migration modelling of sorbing elements is the `F-quotient`. If averaged along a flow path the F-quotient could alternatively be expressed in terms of the quotient between the `flow wetted surface per volume of rock` times the migration path length and the Darcy velocity, or as the product between water `transit time` and flow wetted surface per volume of water. In a spatially varying flow field the proper means of defining these average properties are not self evident. However, it can be shown that the sum of the F-quotient in a series of segments, where properties are constant within each segment, can be used as an effective F-quotient for the entire migration path. For non-sorbing species the F-quotient is not sufficient to describe transport. Dispersion, modelled as a Peclet number, is far less important than the F-quotient for sorbing species, at least for Peclet numbers larger than 2. The site specific transport relevant information available for the SR 97 sites comprise tracer tests, geological characterisation, hydraulic measurements, and modelling. It appears that the most defensible means of estimating the flow wetted surface per volume of rock would
Cáceres, Lizethly; Escudey, Mauricio; Fuentes, Edwar; Báez, María E
2010-07-15
Metsulfuron-methyl sorption kinetic was studied in Andisol and Ultisol soils in view of their distinctive physical and chemical properties: acidic pH and variable surface charge. Different kinetic models were applied to the experimental results. The pseudo-second-order model fitted sorption kinetics data better than the pseudo-first-order model. The rate constant and the initial rate constant values obtained through this model demonstrated the different behavior of metsulfuron-methyl in both kinds of soils, both parameters being the highest for Andisol. The application of Elovich equation, intraparticle diffusion model and a two-site nonequilibrium model (TSNE) allowed to conclude that: (i) the high organic matter content is the governing factor for Andisols where mass transfer across the boundary layer, and in a lesser degree, intraparticle diffusion were the two processes controlling sorption kinetic and (ii) the mineral composition was more relevant in Ultisols where rate was controlled almost exclusively by intraparticle diffusion into macropores and micropores. The slower sorption rate on Ultisols, the mechanism involved and the lower sorption capacity of this kind of soils must be taken into account to assess leaching behavior of this herbicide. 2010 Elsevier B.V. All rights reserved.
Derivation of global vegetation biophysical parameters from EUMETSAT Polar System
García-Haro, Francisco Javier; Campos-Taberner, Manuel; Muñoz-Marí, Jordi; Laparra, Valero; Camacho, Fernando; Sánchez-Zapero, Jorge; Camps-Valls, Gustau
2018-05-01
This paper presents the algorithm developed in LSA-SAF (Satellite Application Facility for Land Surface Analysis) for the derivation of global vegetation parameters from the AVHRR (Advanced Very High Resolution Radiometer) sensor on board MetOp (Meteorological-Operational) satellites forming the EUMETSAT (European Organization for the Exploitation of Meteorological Satellites) Polar System (EPS). The suite of LSA-SAF EPS vegetation products includes the leaf area index (LAI), the fractional vegetation cover (FVC), and the fraction of absorbed photosynthetically active radiation (FAPAR). LAI, FAPAR, and FVC characterize the structure and the functioning of vegetation and are key parameters for a wide range of land-biosphere applications. The algorithm is based on a hybrid approach that blends the generalization capabilities offered by physical radiative transfer models with the accuracy and computational efficiency of machine learning methods. One major feature is the implementation of multi-output retrieval methods able to jointly and more consistently estimate all the biophysical parameters at the same time. We propose a multi-output Gaussian process regression (GPRmulti), which outperforms other considered methods over PROSAIL (coupling of PROSPECT and SAIL (Scattering by Arbitrary Inclined Leaves) radiative transfer models) EPS simulations. The global EPS products include uncertainty estimates taking into account the uncertainty captured by the retrieval method and input errors propagation. A sensitivity analysis is performed to assess several sources of uncertainties in retrievals and maximize the positive impact of modeling the noise in training simulations. The paper discusses initial validation studies and provides details about the characteristics and overall quality of the products, which can be of interest to assist the successful use of the data by a broad user's community. The consistent generation and distribution of the EPS vegetation products will
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.
Review of the different methods to derive average spacing from resolved resonance parameters sets
International Nuclear Information System (INIS)
Fort, E.; Derrien, H.; Lafond, D.
1979-12-01
The average spacing of resonances is an important parameter for statistical model calculations, especially concerning non fissile nuclei. The different methods to derive this average value from resonance parameters sets have been reviewed and analyzed in order to tentatively detect their respective weaknesses and propose recommendations. Possible improvements are suggested
DEFF Research Database (Denmark)
Rasmussen, Mads Olander; Goettsche, Frank-M.; Diop, Doudou
2011-01-01
A tree survey and an analysis of high resolution satellite data were performed to characterise the woody vegetation within a 10 x 10 km(2) area around a site located close to the town of Dahra in the semiarid northern part of Senegal. The surveyed parameters were tree species, height, tree crown...
Energy Technology Data Exchange (ETDEWEB)
Petersen, G.W.; Day, R.L.; Pollack, J. [Pennsylvania State Univ., University Park, PA (United States). Dept. of Agronomy
1993-12-01
This study concerned an investigation of ecosystem dynamics in several small study sites in the North Slope region of Alaska. The scope of the proposed research is to quantitatively determine spatial interrelationships between landform geometry within these study areas and such ecologically important factors as vegetation type, depth-to-permafrost, hydraulic conductivity and incoming solar radiation. Extrapolation techniques developed and terrain-related data generated as a result of this research will augment R4D Phase II goals which relate to running the General Arctic Simulac (GAS) model (and associated ecosystem models) at different locations on the North Slope. In particular, Penn State has contributed significantly to extrapolation efforts by developing techniques which can be used to initialize conditions for model input either through direct measurement (e.g., slope and aspect) and GIS-based simulation models (e.g., drainage basin characterization). As stated in the R4D Phase II Research Plan, the long-term objectives of this program are: (1) to determine effects and to develop models based on ecosystem disturbances commonly created by energy development so that appropriate, cost-effective measures can be utilized to minimize deleterious disturbances; and (2) to extend the results to other arctic and alpine areas which are important because of likely impact from energy development. It is this second long-term objective which relates most directly to Penn State`s work.
Gledhill, M.; Gerringa, L.J.A.
2017-01-01
In this study we examine the impact of dissolved metal concentrations on the parametersthat are commonly determined from complexometric titrations in seawater. We use thenon-ideal competitive adsorption (NICA) model within the framework of the chemicalspeciation program visual MINTEQ with iron as a
Energy Technology Data Exchange (ETDEWEB)
Belli, M. [Agenzia Nazionale per la Protezione dell' Ambiente, Rome (Italy). Dipt. Stato Ambiente, Controlli e Sistemi Informativi, Unita' Interdipartimentale di Metrologia Ambientale
2000-07-01
During the Chernobyl accident large areas of semi-natural ecosystems were affected by radionuclide deposition. Meadows and forests are typical semi-natural ecosystems. Meadows are used extensively in many countries as pastures for cattle, sheep and goats, while forests are important to man since they provide wood, paper, wild berries, mushrooms, game and recreational areas. Post-Chernobyl investigations have shown that dose to man from semi-natural ecosystems is relatively greater than from agricultural systems and that this dose risk persists for the long-term. Predictive models are essential to take long-term decisions on the management of contaminated environment and to identify key processes controlling the dynamics of radionuclides inside the ecosystems. During the period following the atmospheric fallout due to the nuclear weapons testing, few models for some specific semi-natural environments were developed. The applicability of these models to a wide range of semi-natural ecosystem is questionable, because in these complex systems it is more difficult to identify general key processes and to apply to other sites models developed for one site. Studies carried out since the Chernobyl accident have increased the understanding of radionuclide behaviour in semi-natural ecosystems, especially for boreal forests and middle European meadow systems which have been extensively investigated. Data sets have been obtained which describe the distribution and the cycling of radionuclides (especially {sup 137}Cs and {sup 90}Sr) within these systems. However, predictive modelling has largely been restricted to aggregated transfer factors which provide good contamination estimates, but only for the sites from which data have been obtained directly. There was a need to develop models that can be applied to a broad variety of ecosystems. They are needed for dose estimation, countermeasure implementation and environmental management. They should give reliable estimates of the
International Nuclear Information System (INIS)
Belli, M.
2000-04-01
During the Chernobyl accident large areas of semi-natural ecosystems were affected by radionuclide deposition. Meadows and forests are typical semi-natural ecosystems. Meadows are used extensively in many countries as pastures for cattle, sheep and goats, while forests are important to man since they provide wood, paper, wild berries, mushrooms, game and recreational areas. Post-Chernobyl investigations have shown that dose to man from semi-natural ecosystems is relatively greater than from agricultural systems and that this dose risk persists for the long-term. Predictive models are essential to take long-term decisions on the management of contaminated environment and to identify key processes controlling the dynamics of radionuclides inside the ecosystems. During the period following the atmospheric fallout due to the nuclear weapons testing, few models for some specific semi-natural environments were developed. The applicability of these models to a wide range of semi-natural ecosystem is questionable, because in these complex systems it is more difficult to identify general key processes and to apply to other sites models developed for one site. Studies carried out since the Chernobyl accident have increased the understanding of radionuclide behaviour in semi-natural ecosystems, especially for boreal forests and middle European meadow systems which have been extensively investigated. Data sets have been obtained which describe the distribution and the cycling of radionuclides (especially 137 Cs and 90 Sr) within these systems. However, predictive modelling has largely been restricted to aggregated transfer factors which provide good contamination estimates, but only for the sites from which data have been obtained directly. There was a need to develop models that can be applied to a broad variety of ecosystems. They are needed for dose estimation, countermeasure implementation and environmental management. They should give reliable estimates of the behaviour
Optimization of some electrochemical etching parameters for cellulose derivatives
International Nuclear Information System (INIS)
Chowdhury, Annis; Gammage, R.B.
1978-01-01
Electrochemical etching of fast neutron induced recoil particle tracks in cellulose derivatives and other polymers provides an inexpensive and sensitive means of fast neutron personnel dosimetry. A study of the shape, clarity, and size of the tracks in Transilwrap polycarbonate indicated that the optimum normality of the potassium hydroxide etching solution is 9 N. Optimizations have also been attempted for cellulose nitrate, triacetate, and acetobutyrate with respect to such electrochemical etching parameters as frequency, voltage gradient, and concentration of the etching solution. The measurement of differential leakage currents between the undamaged and the neutron damaged foils aided in the selection of optimum frequencies. (author)
Nienałtowski, Karol; Włodarczyk, Michał; Lipniacki, Tomasz; Komorowski, Michał
2015-09-29
Compared to engineering or physics problems, dynamical models in quantitative biology typically depend on a relatively large number of parameters. Progress in developing mathematics to manipulate such multi-parameter models and so enable their efficient interplay with experiments has been slow. Existing solutions are significantly limited by model size. In order to simplify analysis of multi-parameter models a method for clustering of model parameters is proposed. It is based on a derived statistically meaningful measure of similarity between groups of parameters. The measure quantifies to what extend changes in values of some parameters can be compensated by changes in values of other parameters. The proposed methodology provides a natural mathematical language to precisely communicate and visualise effects resulting from compensatory changes in values of parameters. As a results, a relevant insight into identifiability analysis and experimental planning can be obtained. Analysis of NF-κB and MAPK pathway models shows that highly compensative parameters constitute clusters consistent with the network topology. The method applied to examine an exceptionally rich set of published experiments on the NF-κB dynamics reveals that the experiments jointly ensure identifiability of only 60% of model parameters. The method indicates which further experiments should be performed in order to increase the number of identifiable parameters. We currently lack methods that simplify broadly understood analysis of multi-parameter models. The introduced tools depict mutually compensative effects between parameters to provide insight regarding role of individual parameters, identifiability and experimental design. The method can also find applications in related methodological areas of model simplification and parameters estimation.
Models for estimating photosynthesis parameters from in situ production profiles
Kovač, Žarko; Platt, Trevor; Sathyendranath, Shubha; Antunović, Suzana
2017-12-01
The rate of carbon assimilation in phytoplankton primary production models is mathematically prescribed with photosynthesis irradiance functions, which convert a light flux (energy) into a material flux (carbon). Information on this rate is contained in photosynthesis parameters: the initial slope and the assimilation number. The exactness of parameter values is crucial for precise calculation of primary production. Here we use a model of the daily production profile based on a suite of photosynthesis irradiance functions and extract photosynthesis parameters from in situ measured daily production profiles at the Hawaii Ocean Time-series station Aloha. For each function we recover parameter values, establish parameter distributions and quantify model skill. We observe that the choice of the photosynthesis irradiance function to estimate the photosynthesis parameters affects the magnitudes of parameter values as recovered from in situ profiles. We also tackle the problem of parameter exchange amongst the models and the effect it has on model performance. All models displayed little or no bias prior to parameter exchange, but significant bias following parameter exchange. The best model performance resulted from using optimal parameter values. Model formulation was extended further by accounting for spectral effects and deriving a spectral analytical solution for the daily production profile. The daily production profile was also formulated with time dependent growing biomass governed by a growth equation. The work on parameter recovery was further extended by exploring how to extract photosynthesis parameters from information on watercolumn production. It was demonstrated how to estimate parameter values based on a linearization of the full analytical solution for normalized watercolumn production and from the solution itself, without linearization. The paper complements previous works on photosynthesis irradiance models by analysing the skill and consistency of
Control of the SCOLE configuration using distributed parameter models
Hsiao, Min-Hung; Huang, Jen-Kuang
1994-01-01
A continuum model for the SCOLE configuration has been derived using transfer matrices. Controller designs for distributed parameter systems have been analyzed. Pole-assignment controller design is considered easy to implement but stability is not guaranteed. An explicit transfer function of dynamic controllers has been obtained and no model reduction is required before the controller is realized. One specific LQG controller for continuum models had been derived, but other optimal controllers for more general performances need to be studied.
Visualization and comparison of DEM-derived parameters. Application to volcanic areas
Favalli, Massimiliano; Fornaciai, Alessandro
2017-08-01
Digital Elevation Models (DEMs) are fruitfully used in volcanology as the topographic base for mapping and quantifying volcanic landforms. The increasing availability of free topographic data on the web, decreasing production costs for high-accuracy data and advances in computer technology, has triggered rapid growth of the number of DEM users in the volcanological community. DEMs are often visualized only as hill-shaded maps, and while this is among the major advantages in using them, the possibility of deriving a very large number of parameters from a single grid of elevation data makes DEMs a powerful tool for morphometric analysis. However, many of these parameters have almost the same informative content, and before starting to elaborate topographic data it is recommended to know a-priori what parameters best visualize the investigated landform, and therefore what is necessary and what is redundant. In this work, we review a number of analytical procedures used to parameterize and represent DEMs. A LIDAR-derived DEM matrix acquired over the Valle del Bove valley, on Mt. Etna, is used as test-case elevation data for deriving the parameters. We first review well known parameters such as hill-shading, slope and aspect, curvature, and roughness, before extending the review to some less common parameters such as Sky View Factor (SVF), openness, and Red Relief Image Maps (RRIM). For each parameter a description is given emphasizing how it can be used for identifying and delimiting specific volcanic elements. The analyzed surface parameters are then cross-compared in order to infer which of them is most uncorrelated, and the results are represented in the form of a correlation matrix. Finally, the reviewed DEM-derived parameters and the correlation matrix are used for analyzing the volcanic landforms of two case studies: Michoacán-Guanajuato volcanic field and a phonolitic lava flow at the Island of Tenerife.
TWO-PARAMETER ISOTHERMS OF METHYL ORANGE SORPTION BY PINECONE DERIVED ACTIVATED CARBON
M. R. Samarghandi ، M. Hadi ، S. Moayedi ، F. Barjasteh Askari
2009-01-01
The adsorption of a mono azo dye methyl-orange (MeO) onto granular pinecone derived activated carbon (GPAC), from aqueous solutions, was studied in a batch system. Seven two-parameter isotherm models Langmuir, Freundlich, Dubinin-Radushkevic, Temkin, Halsey, Jovanovic and Hurkins-Jura were used to fit the experimental data. The results revealed that the adsorption isotherm models fitted the data in the order of Jovanovic (X2=1.374) > Langmuir > Dubinin-Radushkevic > Temkin > Freundlich > Hals...
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
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
Linear elastic properties derivation from microstructures representative of transport parameters.
Hoang, Minh Tan; Bonnet, Guy; Tuan Luu, Hoang; Perrot, Camille
2014-06-01
It is shown that three-dimensional periodic unit cells (3D PUC) representative of transport parameters involved in the description of long wavelength acoustic wave propagation and dissipation through real foam samples may also be used as a standpoint to estimate their macroscopic linear elastic properties. Application of the model yields quantitative agreement between numerical homogenization results, available literature data, and experiments. Key contributions of this work include recognizing the importance of membranes and properties of the base material for the physics of elasticity. The results of this paper demonstrate that a 3D PUC may be used to understand and predict not only the sound absorbing properties of porous materials but also their transmission loss, which is critical for sound insulation problems.
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.
International Nuclear Information System (INIS)
Lange, Kyle J.; Anderson, W. Kyle
2010-01-01
The problem of applying sensitivity analysis to a one-dimensional atmospheric radio frequency plasma discharge simulation is considered. A fluid simulation is used to model an atmospheric pressure radio frequency helium discharge with a small nitrogen impurity. Sensitivity derivatives are computed for the peak electron density with respect to physical inputs to the simulation. These derivatives are verified using several different methods to compute sensitivity derivatives. It is then demonstrated how sensitivity derivatives can be used within a design cycle to change these physical inputs so as to increase the peak electron density. It is also shown how sensitivity analysis can be used in conjunction with experimental data to obtain better estimates for rate and transport parameters. Finally, it is described how sensitivity analysis could be used to compute an upper bound on the uncertainty for results from a simulation.
VOYAGER 2 SATURN PLASMA DERIVED ELECTRON PARAMETERS 96 SEC
National Aeronautics and Space Administration — THIS DATA SET CONTAINS ELECTRON PARAMETERS IN THE PLS ENERGY RANGE (10-5950 EV) AT SATURN DURING THE VOYAGER 2 ENCOUNTER. PARAMETERS ARE CALCULATED IN SEVERAL WAYS....
VOYAGER 1 SATURN PLASMA DERIVED ELECTRON PARAMETERS 96 SEC
National Aeronautics and Space Administration — THIS DATA SET CONTAINS ELECTRON PARAMETERS IN THE PLS ENERGY RANGE (10-5950 EV) AT SATURN DURING THE VOYAGER 1 ENCOUNTER. PARAMETERS ARE CALCULATED IN SEVERAL WAYS....
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 form...
Identifying the connective strength between model parameters and performance criteria
Directory of Open Access Journals (Sweden)
B. Guse
2017-11-01
Full Text Available In hydrological models, parameters are used to represent the time-invariant characteristics of catchments and to capture different aspects of hydrological response. Hence, model parameters need to be identified based on their role in controlling the hydrological behaviour. For the identification of meaningful parameter values, multiple and complementary performance criteria are used that compare modelled and measured discharge time series. The reliability of the identification of hydrologically meaningful model parameter values depends on how distinctly a model parameter can be assigned to one of the performance criteria. To investigate this, we introduce the new concept of connective strength between model parameters and performance criteria. The connective strength assesses the intensity in the interrelationship between model parameters and performance criteria in a bijective way. In our analysis of connective strength, model simulations are carried out based on a latin hypercube sampling. Ten performance criteria including Nash–Sutcliffe efficiency (NSE, Kling–Gupta efficiency (KGE and its three components (alpha, beta and r as well as RSR (the ratio of the root mean square error to the standard deviation for different segments of the flow duration curve (FDC are calculated. With a joint analysis of two regression tree (RT approaches, we derive how a model parameter is connected to different performance criteria. At first, RTs are constructed using each performance criterion as the target variable to detect the most relevant model parameters for each performance criterion. Secondly, RTs are constructed using each parameter as the target variable to detect which performance criteria are impacted by changes in the values of one distinct model parameter. Based on this, appropriate performance criteria are identified for each model parameter. In this study, a high bijective connective strength between model parameters and performance criteria
Historic Low Wall Detection via Topographic Parameter Images Derived from Fine-Resolution DEM
Directory of Open Access Journals (Sweden)
Hone-Jay Chu
2017-11-01
Full Text Available Coral walls protect vegetation gardens from strong winds that sweep across Xiji Island, Taiwan Strait for half the year. Topographic parameters based on light detection and ranging (LiDAR-based high-resolution digital elevation model (DEM provide obvious correspondence with the expected form of landscape features. The information on slope, curvature, and openness can help identify the location of landscape features. This study applied the automatic landscape line detection to extract historic vegetable garden wall lines from a LiDAR-derived DEM. The three rapid processes used in this study included the derivation of topographic parameters, line extraction, and aggregation. The rules were extracted from a decision tree to check the line detection from multiple topographic parameters. Results show that wall line detection with multiple topographic parameter images is an alternative means of obtaining essential historic wall feature information. Multiple topographic parameters are highly related to low wall feature identification. Furthermore, the accuracy of wall feature detection is 74% compared with manual interpretation. Thus, this study provides rapid wall detection systems with multiple topographic parameters for further historic landscape management.
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...
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)
Derivation of Dynamic Function Parameters by Area Scanning Techniques
International Nuclear Information System (INIS)
Maclntyre, W.J.; Inkley, S.R.; Roth, E.; Drescher, W.P.; Ishii, Y.
1970-01-01
This paper describes a functional imaging method for the study of organ function or organ blood flow and its application to the evaluation of lung ventilation and perfusion with 133 Xe. The method is based on area scintigraphy with a scintillation camera, data being accumulated on a 1600-channel analyzer as a 40 x 40 element matrix, transferred to magnetic tape and finally processed by a computer. For the evaluation of lung ventilation, the static distribution of 133 Xe in the lungs after inhalation of oxygen- 133 Xe mixture is recorded as a single matrix during a 20-second period of breath holding. For the evaluation of lung perfusion successive matrices are recorded every 2-4 seconds after intravenous injection of a saline solution of 133 Xe so that the washout of 133 Xe from the lungs may be followed as a function of time. Each element of the matrices is initially subjected to a nine-element smoothing routine. The distribution of ventilation is then derived from the matrix for the static distribution of 133 Xe after its administration by inhalation and the distribution of perfusion from the relative slopes of the curves of disappearance of 133 Xe from the various matrix elements after its administration by injection. The results are displayed as a 40 x 40 element matrix of normalized values or alternatively as an isometric projection of a three—dimensional model in which the x and y coordinates give the spatial reference and the z co-ordinate the relative ventilation or perfusion. Typical results obtained by the method are presented and its advantages over methods which evaluate total organ function discussed. (author)
A compact cyclic plasticity model with parameter evolution
DEFF Research Database (Denmark)
Krenk, Steen; Tidemann, L.
2017-01-01
by the Armstrong–Frederick model, contained as a special case of the present model for a particular choice of the shape parameter. In contrast to previous work, where shaping the stress-strain loops is derived from multiple internal stress states, this effect is here represented by a single parameter......The paper presents a compact model for cyclic plasticity based on energy in terms of external and internal variables, and plastic yielding described by kinematic hardening and a flow potential with an additive term controlling the nonlinear cyclic hardening. The model is basically described by five...... parameters: external and internal stiffness, a yield stress and a limiting ultimate stress, and finally a parameter controlling the gradual development of plastic deformation. Calibration against numerous experimental results indicates that typically larger plastic strains develop than predicted...
CHAMP: Changepoint Detection Using Approximate Model Parameters
2014-06-01
form (with independent emissions or otherwise), in which parameter estimates are available via means such as maximum likelihood fit, MCMC , or sample ...counterparts, including the ability to generate a full posterior distribution over changepoint locations and offering a natural way to incorporate prior... sample consensus method. Our modifications also remove a significant restriction on model definition when detecting parameter changes within a single
Exploiting intrinsic fluctuations to identify model parameters.
Zimmer, Christoph; Sahle, Sven; Pahle, Jürgen
2015-04-01
Parameterisation of kinetic models plays a central role in computational systems biology. Besides the lack of experimental data of high enough quality, some of the biggest challenges here are identification issues. Model parameters can be structurally non-identifiable because of functional relationships. Noise in measured data is usually considered to be a nuisance for parameter estimation. However, it turns out that intrinsic fluctuations in particle numbers can make parameters identifiable that were previously non-identifiable. The authors present a method to identify model parameters that are structurally non-identifiable in a deterministic framework. The method takes time course recordings of biochemical systems in steady state or transient state as input. Often a functional relationship between parameters presents itself by a one-dimensional manifold in parameter space containing parameter sets of optimal goodness. Although the system's behaviour cannot be distinguished on this manifold in a deterministic framework it might be distinguishable in a stochastic modelling framework. Their method exploits this by using an objective function that includes a measure for fluctuations in particle numbers. They show on three example models, immigration-death, gene expression and Epo-EpoReceptor interaction, that this resolves the non-identifiability even in the case of measurement noise with known amplitude. The method is applied to partially observed recordings of biochemical systems with measurement noise. It is simple to implement and it is usually very fast to compute. This optimisation can be realised in a classical or Bayesian fashion.
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
Incorporating model parameter uncertainty into inverse treatment planning
International Nuclear Information System (INIS)
Lian Jun; Xing Lei
2004-01-01
Radiobiological treatment planning depends not only on the accuracy of the models describing the dose-response relation of different tumors and normal tissues but also on the accuracy of tissue specific radiobiological parameters in these models. Whereas the general formalism remains the same, different sets of model parameters lead to different solutions and thus critically determine the final plan. Here we describe an inverse planning formalism with inclusion of model parameter uncertainties. This is made possible by using a statistical analysis-based frameset developed by our group. In this formalism, the uncertainties of model parameters, such as the parameter a that describes tissue-specific effect in the equivalent uniform dose (EUD) model, are expressed by probability density function and are included in the dose optimization process. We found that the final solution strongly depends on distribution functions of the model parameters. Considering that currently available models for computing biological effects of radiation are simplistic, and the clinical data used to derive the models are sparse and of questionable quality, the proposed technique provides us with an effective tool to minimize the effect caused by the uncertainties in a statistical sense. With the incorporation of the uncertainties, the technique has potential for us to maximally utilize the available radiobiology knowledge for better IMRT treatment
Morrison, Adrian F; Herbert, John M
2017-06-14
Recently, we introduced an ab initio version of the Frenkel-Davydov exciton model for computing excited-state properties of molecular crystals and aggregates. Within this model, supersystem excited states are approximated as linear combinations of excitations localized on molecular sites, and the electronic Hamiltonian is constructed and diagonalized in a direct-product basis of non-orthogonal configuration state functions computed for isolated fragments. Here, we derive and implement analytic derivative couplings for this model, including nuclear derivatives of the natural transition orbital and symmetric orthogonalization transformations that are part of the approximation. Nuclear derivatives of the exciton Hamiltonian's matrix elements, required in order to compute the nonadiabatic couplings, are equivalent to the "Holstein" and "Peierls" exciton/phonon couplings that are widely discussed in the context of model Hamiltonians for energy and charge transport in organic photovoltaics. As an example, we compute the couplings that modulate triplet exciton transport in crystalline tetracene, which is relevant in the context of carrier diffusion following singlet exciton fission.
VOYAGER 1&2 SATURN IRIS DERIVED NORTH/SOUTH PARAMETERS V1.0
National Aeronautics and Space Administration — The data set contains Saturn atmospheric parameters derived from spectra obtained with the Voyager infrared interferometer spectrometer (IRIS). The data set is...
VOYAGER 1&2 JUPITER IRIS DERIVED NORTH/SOUTH PARAMETERS V1.0
National Aeronautics and Space Administration — The data set contains Jovian atmospheric parameters derived from spectra obtained with the Voyager infrared interferometer spectrometer (IRIS). The data set is...
VG1/VG2 JUPITER IRIS DERIVED GREAT RED SPOT PARAMETERS V1.0
National Aeronautics and Space Administration — The data set contains Jovian atmospheric parameters derived from spectra obtained with the Voyager infrared interferometer spectrometer (IRIS). The data set is...
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......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...
Setting Parameters for Biological Models With ANIMO
Directory of Open Access Journals (Sweden)
Stefano Schivo
2014-03-01
Full Text Available 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 between biological entities in form of a graph, while the parameters determine the speed of occurrence of such interactions. When a mismatch is observed between the behavior of an ANIMO model and experimental data, we want to update the model so that it explains the new data. In general, the topology of a model can be expanded with new (known or hypothetical nodes, and enables it to match experimental data. However, the unrestrained addition of new parts to a model causes two problems: models can become too complex too fast, to the point of being intractable, and too many parts marked as "hypothetical" or "not known" make a model unrealistic. Even if changing the topology is normally the easier task, these problems push us to try a better parameter fit as a first step, and resort to modifying the model topology only as a last resource. In this paper we show the support added in ANIMO to ease the task of expanding the knowledge on biological networks, concentrating in particular on the parameter settings.
Parameters Affecting the Characteristics of Oil Shale-Derived Fuels.
1981-03-01
1976, Flammability, ignition and electrostatic properties of navy fuels derived from coal , tar sands and shale oil, in American Chemical Society: v...Hall, J. M., and Nowack, C. J., 1978, Relation between fuel properties and chemical composition -- 1. jet fuels from coal , shale and tar sands: Fuel...Refining, used to work at Geokinetics and is much more enthusiastic about synthetic fuels from shale than from coal . " Mr. Roane advocates hydrotreating the
Modelling and parameter estimation of dynamic systems
Raol, JR; Singh, J
2004-01-01
Parameter estimation is the process of using observations from a system to develop mathematical models that adequately represent the system dynamics. The assumed model consists of a finite set of parameters, the values of which are calculated using estimation techniques. Most of the techniques that exist are based on least-square minimization of error between the model response and actual system response. However, with the proliferation of high speed digital computers, elegant and innovative techniques like filter error method, H-infinity and Artificial Neural Networks are finding more and mor
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)
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...
Models and parameters for environmental radiological assessments
International Nuclear Information System (INIS)
Miller, C.W.
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
A Note on the Item Information Function of the Four-Parameter Logistic Model
Magis, David
2013-01-01
This article focuses on four-parameter logistic (4PL) model as an extension of the usual three-parameter logistic (3PL) model with an upper asymptote possibly different from 1. For a given item with fixed item parameters, Lord derived the value of the latent ability level that maximizes the item information function under the 3PL model. The…
SP_Ace: a new code to derive stellar parameters and elemental abundances
Boeche, C.; Grebel, E. K.
2016-03-01
Context. Ongoing and future massive spectroscopic surveys will collect large numbers (106-107) of stellar spectra that need to be analyzed. Highly automated software is needed to derive stellar parameters and chemical abundances from these spectra. Aims: We developed a new method of estimating the stellar parameters Teff, log g, [M/H], and elemental abundances. This method was implemented in a new code, SP_Ace (Stellar Parameters And Chemical abundances Estimator). This is a highly automated code suitable for analyzing the spectra of large spectroscopic surveys with low or medium spectral resolution (R = 2000-20 000). Methods: After the astrophysical calibration of the oscillator strengths of 4643 absorption lines covering the wavelength ranges 5212-6860 Å and 8400-8924 Å, we constructed a library that contains the equivalent widths (EW) of these lines for a grid of stellar parameters. The EWs of each line are fit by a polynomial function that describes the EW of the line as a function of the stellar parameters. The coefficients of these polynomial functions are stored in a library called the "GCOG library". SP_Ace, a code written in FORTRAN95, uses the GCOG library to compute the EWs of the lines, constructs models of spectra as a function of the stellar parameters and abundances, and searches for the model that minimizes the χ2 deviation when compared to the observed spectrum. The code has been tested on synthetic and real spectra for a wide range of signal-to-noise and spectral resolutions. Results: SP_Ace derives stellar parameters such as Teff, log g, [M/H], and chemical abundances of up to ten elements for low to medium resolution spectra of FGK-type stars with precision comparable to the one usually obtained with spectra of higher resolution. Systematic errors in stellar parameters and chemical abundances are presented and identified with tests on synthetic and real spectra. Stochastic errors are automatically estimated by the code for all the parameters
Source term modelling parameters for Project-90
International Nuclear Information System (INIS)
Shaw, W.; Smith, G.; Worgan, K.; Hodgkinson, D.; Andersson, K.
1992-04-01
This document summarises the input parameters for the source term modelling within Project-90. In the first place, the parameters relate to the CALIBRE near-field code which was developed for the Swedish Nuclear Power Inspectorate's (SKI) Project-90 reference repository safety assessment exercise. An attempt has been made to give best estimate values and, where appropriate, a range which is related to variations around base cases. It should be noted that the data sets contain amendments to those considered by KBS-3. In particular, a completely new set of inventory data has been incorporated. The information given here does not constitute a complete set of parameter values for all parts of the CALIBRE code. Rather, it gives the key parameter values which are used in the constituent models within CALIBRE and the associated studies. For example, the inventory data acts as an input to the calculation of the oxidant production rates, which influence the generation of a redox front. The same data is also an initial value data set for the radionuclide migration component of CALIBRE. Similarly, the geometrical parameters of the near-field are common to both sub-models. The principal common parameters are gathered here for ease of reference and avoidance of unnecessary duplication and transcription errors. (au)
A tracer diffusion model derived from microstructure
International Nuclear Information System (INIS)
Lehikoinen, Jarmo; Muurinen, Arto; Olin, Markus
2012-01-01
of reference, is shown to be given by the ratio of the effective diffusivity to the apparent diffusivity for an assumed non-interacting solute, such as tritiated water. Finally, the utility of the model and derivation of the model parameters are demonstrated with tracer diffusion data from the open literature for compacted bentonite. (authors)
Evolution of Geometric Sensitivity Derivatives from Computer Aided Design Models
Jones, William T.; Lazzara, David; Haimes, Robert
2010-01-01
The generation of design parameter sensitivity derivatives is required for gradient-based optimization. Such sensitivity derivatives are elusive at best when working with geometry defined within the solid modeling context of Computer-Aided Design (CAD) systems. Solid modeling CAD systems are often proprietary and always complex, thereby necessitating ad hoc procedures to infer parameter sensitivity. A new perspective is presented that makes direct use of the hierarchical associativity of CAD features to trace their evolution and thereby track design parameter sensitivity. In contrast to ad hoc methods, this method provides a more concise procedure following the model design intent and determining the sensitivity of CAD geometry directly to its respective defining parameters.
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...... was applied.Capture zone modelling was conducted on a synthetic stationary 3-dimensional flow problem involving river, surface and groundwater flow. Simulated capture zones were illustrated as likelihood maps and compared with a deterministic capture zones derived from a reference model. The results showed...
Battery failure model derived from flaw theory
Schulman, I.
1981-01-01
A previously derived failure model for battery lifetime is discussed in terms of growth rate of the flaw, distribution of flaw sizes, and number of flaws. Equations are presented for determining the failure model for a nickel cadmium battery.
Advances in Modelling, System Identification and Parameter ...
Indian Academy of Sciences (India)
models determined from flight test data by using parameter estimation methods find extensive use in design/modification of flight control systems, high fidelity flight simulators and evaluation of handling qualitites of aircraft and rotorcraft. R K Mehra et al present new algorithms and results for flutter tests and adaptive notching ...
A lumped parameter model of plasma focus
International Nuclear Information System (INIS)
Gonzalez, Jose H.; Florido, Pablo C.; Bruzzone, H.; Clausse, Alejandro
1999-01-01
A lumped parameter model to estimate neutron emission of a plasma focus (PF) device is developed. The dynamic of the current sheet is calculated using a snowplow model, and the neutron production with the thermal fusion cross section for a deuterium filling gas. The results were contrasted as a function of the filling pressure with experimental measurements of a 3.68 KJ Mather-type PF. (author)
One parameter model potential for noble metals
International Nuclear Information System (INIS)
Idrees, M.; Khwaja, F.A.; Razmi, M.S.K.
1981-08-01
A phenomenological one parameter model potential which includes s-d hybridization and core-core exchange contributions is proposed for noble metals. A number of interesting properties like liquid metal resistivities, band gaps, thermoelectric powers and ion-ion interaction potentials are calculated for Cu, Ag and Au. The results obtained are in better agreement with experiment than the ones predicted by the other model potentials in the literature. (author)
Timuhins, Andrejs; Bethers, Uldis; Bethers, Peteris; Klints, Ilze; Sennikovs, Juris; Frishfelds, Vilnis
2017-04-01
In a changing climate it is essential to estimate its impacts on different economic fields. In our study we tried to create a framework for climate change assessment and climate change impact estimation for the territory of Latvia and to create results which are also understandable for non-scientists (stakeholder, media and public). This approach allowed us to more carefully assess the presentation and interpretation of results and their validation, for public viewing. For the presentation of our work a website was created (www.modlab.lv/klimats) containing two types of documents in a unified framework, meteorological parameter analysis of different easily interpretable derivative values. Both of these include analysis of the current situation as well as illustrate the projection for future time periods. Derivate values are calculated using two data sources: the bias corrected regional climate data and meteorological observation data. Derivative documents contain description of derived value, some interesting facts and conclusions. Additionally, all results may be viewed in temporal and spatial graphs and maps, for different time periods as well as different seasons. Bias correction (Sennikovs and Bethers, 2009) for the control period 1961-1990 is applied to RCM data series. Meteorological observation data of the Latvian Environment, Geology, and Meteorology Agency and ENSEMBLES project daily data of 13 RCM runs for the period 1960-2100 are used. All the documents are prepared in python notebooks, which allow for flexible changes. At the moment following derivative values have been published: forest fire risk index, wind energy, phenology (Degree days), road condition (friction, ice conditions), daily minimal meteorological visibility, headache occurrence rate, firs snow date and meteorological parameter analysis: temperature, precipitation, wind speed, relative humidity, and cloudiness. While creating these products RCM ability to represent the actual climate was
Van Dyke, Michael B.
2013-01-01
Present preliminary work using lumped parameter models to approximate dynamic response of electronic units to random vibration; Derive a general N-DOF model for application to electronic units; Illustrate parametric influence of model parameters; Implication of coupled dynamics for unit/board design; Demonstrate use of model to infer printed wiring board (PWB) dynamics from external chassis test measurement.
Parameter optimization for surface flux transport models
Whitbread, T.; Yeates, A. R.; Muñoz-Jaramillo, A.; Petrie, G. J. D.
2017-11-01
Accurate prediction of solar activity calls for precise calibration of solar cycle models. Consequently we aim to find optimal parameters for models which describe the physical processes on the solar surface, which in turn act as proxies for what occurs in the interior and provide source terms for coronal models. We use a genetic algorithm to optimize surface flux transport models using National Solar Observatory (NSO) magnetogram data for Solar Cycle 23. This is applied to both a 1D model that inserts new magnetic flux in the form of idealized bipolar magnetic regions, and also to a 2D model that assimilates specific shapes of real active regions. The genetic algorithm searches for parameter sets (meridional flow speed and profile, supergranular diffusivity, initial magnetic field, and radial decay time) that produce the best fit between observed and simulated butterfly diagrams, weighted by a latitude-dependent error structure which reflects uncertainty in observations. Due to the easily adaptable nature of the 2D model, the optimization process is repeated for Cycles 21, 22, and 24 in order to analyse cycle-to-cycle variation of the optimal solution. We find that the ranges and optimal solutions for the various regimes are in reasonable agreement with results from the literature, both theoretical and observational. The optimal meridional flow profiles for each regime are almost entirely within observational bounds determined by magnetic feature tracking, with the 2D model being able to accommodate the mean observed profile more successfully. Differences between models appear to be important in deciding values for the diffusive and decay terms. In like fashion, differences in the behaviours of different solar cycles lead to contrasts in parameters defining the meridional flow and initial field strength.
Parameter uncertainty analysis of a biokinetic model of caesium
International Nuclear Information System (INIS)
Li, W.B.; Oeh, U.; Klein, W.; Blanchardon, E.; Puncher, M.; Leggett, R.W.; Breustedt, B.; Nosske, D.; Lopez, M.A.
2015-01-01
Parameter uncertainties for the biokinetic model of caesium (Cs) developed by Leggett et al. were inventoried and evaluated. The methods of parameter uncertainty analysis were used to assess the uncertainties of model predictions with the assumptions of model parameter uncertainties and distributions. Furthermore, the importance of individual model parameters was assessed by means of sensitivity analysis. The calculated uncertainties of model predictions were compared with human data of Cs measured in blood and in the whole body. It was found that propagating the derived uncertainties in model parameter values reproduced the range of bioassay data observed in human subjects at different times after intake. The maximum ranges, expressed as uncertainty factors (UFs) (defined as a square root of ratio between 97.5. and 2.5. percentiles) of blood clearance, whole-body retention and urinary excretion of Cs predicted at earlier time after intake were, respectively: 1.5, 1.0 and 2.5 at the first day; 1.8, 1.1 and 2.4 at Day 10 and 1.8, 2.0 and 1.8 at Day 100; for the late times (1000 d) after intake, the UFs were increased to 43, 24 and 31, respectively. The model parameters of transfer rates between kidneys and blood, muscle and blood and the rate of transfer from kidneys to urinary bladder content are most influential to the blood clearance and to the whole-body retention of Cs. For the urinary excretion, the parameters of transfer rates from urinary bladder content to urine and from kidneys to urinary bladder content impact mostly. The implication and effect on the estimated equivalent and effective doses of the larger uncertainty of 43 in whole-body retention in the later time, say, after Day 500 will be explored in a successive work in the framework of EURADOS. (authors)
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.
Fadly, Romi; Dewi, Citra
2014-01-01
This research aims to compare the 14 transformation parameters between ITRF from computation result using the Helmert 14-parameter models with IERS standard parameters. The transforma- tion parameters are calculated from the coordinates and velocities of ITRF05 to ITRF00 epoch 2000.00, and from ITRF08 to ITRF05 epoch 2005.00 for respectively transformation models. The transformation parameters are compared to the IERS standard parameters, then tested the signifi- cance of the d...
Constant-parameter capture-recapture models
Brownie, C.; Hines, J.E.; Nichols, J.D.
1986-01-01
Jolly (1982, Biometrics 38, 301-321) presented modifications of the Jolly-Seber model for capture-recapture data, which assume constant survival and/or capture rates. Where appropriate, because of the reduced number of parameters, these models lead to more efficient estimators than the Jolly-Seber model. The tests to compare models given by Jolly do not make complete use of the data, and we present here the appropriate modifications, and also indicate how to carry out goodness-of-fit tests which utilize individual capture history information. We also describe analogous models for the case where young and adult animals are tagged. The availability of computer programs to perform the analysis is noted, and examples are given using output from these programs.
Aqueous Electrolytes: Model Parameters and Process Simulation
DEFF Research Database (Denmark)
Thomsen, Kaj
This thesis deals with aqueous electrolyte mixtures. The Extended UNIQUAC model is being used to describe the excess Gibbs energy of such solutions. Extended UNIQUAC parameters for the twelve ions Na+, K+, NH4+, H+, Cl-, NO3-, SO42-, HSO4-, OH-, CO32-, HCO3-, and S2O82- are estimated. A computer ...... program including a steady state process simulator for the design, simulation, and optimization of fractional crystallization processes is presented.......This thesis deals with aqueous electrolyte mixtures. The Extended UNIQUAC model is being used to describe the excess Gibbs energy of such solutions. Extended UNIQUAC parameters for the twelve ions Na+, K+, NH4+, H+, Cl-, NO3-, SO42-, HSO4-, OH-, CO32-, HCO3-, and S2O82- are estimated. A computer...
Large deflection of viscoelastic beams using fractional derivative model
International Nuclear Information System (INIS)
Bahranini, Seyed Masoud Sotoodeh; Eghtesad, Mohammad; Ghavanloo, Esmaeal; Farid, Mehrdad
2013-01-01
This paper deals with large deflection of viscoelastic beams using a fractional derivative model. For this purpose, a nonlinear finite element formulation of viscoelastic beams in conjunction with the fractional derivative constitutive equations has been developed. The four-parameter fractional derivative model has been used to describe the constitutive equations. The deflected configuration for a uniform beam with different boundary conditions and loads is presented. The effect of the order of fractional derivative on the large deflection of the cantilever viscoelastic beam, is investigated after 10, 100, and 1000 hours. The main contribution of this paper is finite element implementation for nonlinear analysis of viscoelastic fractional model using the storage of both strain and stress histories. The validity of the present analysis is confirmed by comparing the results with those found in the literature.
Kougioumtzoglou, Ioannis A.; dos Santos, Ketson R. M.; Comerford, Liam
2017-09-01
Various system identification techniques exist in the literature that can handle non-stationary measured time-histories, or cases of incomplete data, or address systems following a fractional calculus modeling. However, there are not many (if any) techniques that can address all three aforementioned challenges simultaneously in a consistent manner. In this paper, a novel multiple-input/single-output (MISO) system identification technique is developed for parameter identification of nonlinear and time-variant oscillators with fractional derivative terms subject to incomplete non-stationary data. The technique utilizes a representation of the nonlinear restoring forces as a set of parallel linear sub-systems. In this regard, the oscillator is transformed into an equivalent MISO system in the wavelet domain. Next, a recently developed L1-norm minimization procedure based on compressive sensing theory is applied for determining the wavelet coefficients of the available incomplete non-stationary input-output (excitation-response) data. Finally, these wavelet coefficients are utilized to determine appropriately defined time- and frequency-dependent wavelet based frequency response functions and related oscillator parameters. Several linear and nonlinear time-variant systems with fractional derivative elements are used as numerical examples to demonstrate the reliability of the technique even in cases of noise corrupted and incomplete data.
TWO-PARAMETER ISOTHERMS OF METHYL ORANGE SORPTION BY PINECONE DERIVED ACTIVATED CARBON
Directory of Open Access Journals (Sweden)
M. R. Samarghandi ، M. Hadi ، S. Moayedi ، F. Barjasteh Askari
2009-10-01
Full Text Available The adsorption of a mono azo dye methyl-orange (MeO onto granular pinecone derived activated carbon (GPAC, from aqueous solutions, was studied in a batch system. Seven two-parameter isotherm models Langmuir, Freundlich, Dubinin-Radushkevic, Temkin, Halsey, Jovanovic and Hurkins-Jura were used to fit the experimental data. The results revealed that the adsorption isotherm models fitted the data in the order of Jovanovic (X2=1.374 > Langmuir > Dubinin-Radushkevic > Temkin > Freundlich > Halsey > Hurkins-Jura isotherms. Adsorption isotherms modeling showed that the interaction of dye with activated carbon surface is localized monolayer adsorption. A comparison of kinetic models was evaluated for the pseudo-second order, Elovich and Lagergren kinetic models. Lagergren first order model was found to agree well with the experimental data (X2=9.231. In order to determine the best-fit isotherm and kinetic models, two error analysis methods of Residual Mean Square Error and Chi-square statistic (X2 were used to evaluate the data.
Space geodetic techniques for global modeling of ionospheric peak parameters
Alizadeh, M. Mahdi; Schuh, Harald; Schmidt, Michael
The rapid development of new technological systems for navigation, telecommunication, and space missions which transmit signals through the Earth’s upper atmosphere - the ionosphere - makes the necessity of precise, reliable and near real-time models of the ionospheric parameters more crucial. In the last decades space geodetic techniques have turned into a capable tool for measuring ionospheric parameters in terms of Total Electron Content (TEC) or the electron density. Among these systems, the current space geodetic techniques, such as Global Navigation Satellite Systems (GNSS), Low Earth Orbiting (LEO) satellites, satellite altimetry missions, and others have found several applications in a broad range of commercial and scientific fields. This paper aims at the development of a three-dimensional integrated model of the ionosphere, by using various space geodetic techniques and applying a combination procedure for computation of the global model of electron density. In order to model ionosphere in 3D, electron density is represented as a function of maximum electron density (NmF2), and its corresponding height (hmF2). NmF2 and hmF2 are then modeled in longitude, latitude, and height using two sets of spherical harmonic expansions with degree and order 15. To perform the estimation, GNSS input data are simulated in such a way that the true position of the satellites are detected and used, but the STEC values are obtained through a simulation procedure, using the IGS VTEC maps. After simulating the input data, the a priori values required for the estimation procedure are calculated using the IRI-2012 model and also by applying the ray-tracing technique. The estimated results are compared with F2-peak parameters derived from the IRI model to assess the least-square estimation procedure and moreover, to validate the developed maps, the results are compared with the raw F2-peak parameters derived from the Formosat-3/Cosmic data.
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.
Technique for Calculating Solution Derivatives With Respect to Geometry Parameters in a CFD Code
Mathur, Sanjay
2011-01-01
A solution has been developed to the challenges of computation of derivatives with respect to geometry, which is not straightforward because these are not typically direct inputs to the computational fluid dynamics (CFD) solver. To overcome these issues, a procedure has been devised that can be used without having access to the mesh generator, while still being applicable to all types of meshes. The basic approach is inspired by the mesh motion algorithms used to deform the interior mesh nodes in a smooth manner when the surface nodes, for example, are in a fluid structure interaction problem. The general idea is to model the mesh edges and nodes as constituting a spring-mass system. Changes to boundary node locations are propagated to interior nodes by allowing them to assume their new equilibrium positions, for instance, one where the forces on each node are in balance. The main advantage of the technique is that it is independent of the volumetric mesh generator, and can be applied to structured, unstructured, single- and multi-block meshes. It essentially reduces the problem down to defining the surface mesh node derivatives with respect to the geometry parameters of interest. For analytical geometries, this is quite straightforward. In the more general case, one would need to be able to interrogate the underlying parametric CAD (computer aided design) model and to evaluate the derivatives either analytically, or by a finite difference technique. Because the technique is based on a partial differential equation (PDE), it is applicable not only to forward mode problems (where derivatives of all the output quantities are computed with respect to a single input), but it could also be extended to the adjoint problem, either by using an analytical adjoint of the PDE or a discrete analog.
Parameter estimation in nonlinear models for pesticide degradation
International Nuclear Information System (INIS)
Richter, O.; Pestemer, W.; Bunte, D.; Diekkrueger, B.
1991-01-01
A wide class of environmental transfer models is formulated as ordinary or partial differential equations. With the availability of fast computers, the numerical solution of large systems became feasible. The main difficulty in performing a realistic and convincing simulation of the fate of a substance in the biosphere is not the implementation of numerical techniques but rather the incomplete data basis for parameter estimation. Parameter estimation is a synonym for statistical and numerical procedures to derive reasonable numerical values for model parameters from data. The classical method is the familiar linear regression technique which dates back to the 18th century. Because it is easy to handle, linear regression has long been established as a convenient tool for analysing relationships. However, the wide use of linear regression has led to an overemphasis of linear relationships. In nature, most relationships are nonlinear and linearization often gives a poor approximation of reality. Furthermore, pure regression models are not capable to map the dynamics of a process. Therefore, realistic models involve the evolution in time (and space). This leads in a natural way to the formulation of differential equations. To establish the link between data and dynamical models, numerical advanced parameter identification methods have been developed in recent years. This paper demonstrates the application of these techniques to estimation problems in the field of pesticide dynamics. (7 refs., 5 figs., 2 tabs.)
Lumped Parameters Model of a Crescent Pump
Directory of Open Access Journals (Sweden)
Massimo Rundo
2016-10-01
Full Text Available This paper presents the lumped parameters model of an internal gear crescent pump with relief valve, able to estimate the steady-state flow-pressure characteristic and the pressure ripple. The approach is based on the identification of three variable control volumes regardless of the number of gear teeth. The model has been implemented in the commercial environment LMS Amesim with the development of customized components. Specific attention has been paid to the leakage passageways, some of them affected by the deformation of the cover plate under the action of the delivery pressure. The paper reports the finite element method analysis of the cover for the evaluation of the deflection and the validation through a contactless displacement transducer. Another aspect described in this study is represented by the computational fluid dynamics analysis of the relief valve, whose results have been used for tuning the lumped parameters model. Finally, the validation of the entire model of the pump is presented in terms of steady-state flow rate and of pressure oscillations.
Investigation of land use effects on Nash model parameters
Niazi, Faegheh; Fakheri Fard, Ahmad; Nourani, Vahid; Goodrich, David; Gupta, Hoshin
2015-04-01
Flood forecasting is of great importance in hydrologic planning, hydraulic structure design, water resources management and sustainable designs like flood control and management. Nash's instantaneous unit hydrograph is frequently used for simulating hydrological response in natural watersheds. Urban hydrology is gaining more attention due to population increases and associated construction escalation. Rapid development of urban areas affects the hydrologic processes of watersheds by decreasing soil permeability, flood base flow, lag time and increase in flood volume, peak runoff rates and flood frequency. In this study the influence of urbanization on the significant parameters of the Nash model have been investigated. These parameters were calculated using three popular methods (i.e. moment, root mean square error and random sampling data generation), in a small watershed consisting of one natural sub-watershed which drains into a residentially developed sub-watershed in the city of Sierra Vista, Arizona. The results indicated that for all three methods, the lag time, which is product of Nash parameters "K" and "n", in the natural sub-watershed is greater than the developed one. This logically implies more storage and/or attenuation in the natural sub-watershed. The median K and n parameters derived from the three methods using calibration events were tested via a set of verification events. The results indicated that all the three method have acceptable accuracy in hydrograph simulation. The CDF curves and histograms of the parameters clearly show the difference of the Nash parameter values between the natural and developed sub-watersheds. Some specific upper and lower percentile values of the median of the generated parameters (i.e. 10, 20 and 30 %) were analyzed to future investigates the derived parameters. The model was sensitive to variations in the value of the uncertain K and n parameter. Changes in n are smaller than K in both sub-watersheds indicating
Ceriani, Luca; Martelli, Maurizio; Conconi, Annarita; Zinzani, Pier L; Ferreri, Andrés J M; Botto, Barbara; Stelitano, Caterina; Gotti, Manuel; Cabras, Maria G; Rigacci, Luigi; Giovanella, Luca; Zucca, Emanuele; Johnson, Peter W M
2017-08-01
The International Extranodal Lymphoma Study Group-26 study evaluated the prognostic role of 18-fluorodeoxyglucose positron-emission tomography (PET) in primary mediastinal large B-cell lymphoma. We assessed quantitative PET parameters at diagnosis and post-treatment in 100 patients. The end-of-therapy total lesion glycolysis (TLG) was the best individual outcome predictor, but the combination of baseline TLG and end-of-therapy visual analysis with Deauville Score (DS) showed a better positive predictive value. A model in which baseline TLG is combined with interim DS might identify patients with shorter progression-free survival. PET metrics combined with interim DS may allow early risk assessment and warrants further studies. © 2017 John Wiley & Sons Ltd.
A New Five-Parameter Fréchet Model for Extreme Values
Directory of Open Access Journals (Sweden)
Muhammad Ahsan ul Haq
2017-09-01
Full Text Available A new five parameter Fréchet model for Extreme Values was proposed and studied. Various mathematical properties including moments, quantiles, and moment generating function were derived. Incomplete moments and probability weighted moments were also obtained. The maximum likelihood method was used to estimate the model parameters. The flexibility of the derived model was accessed using two real data set applications.
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.
Varentsov, Mikhail; Wouters, Hendrik; Trusilova, Kristina; Samsonov, Timofey; Konstantinov, Pavel
2017-04-01
In this study we present the application of the regional climate model COSMO-CLM to simulate urban heat island (UHI) phenomenon for Moscow megacity, which is the biggest agglomeration in Europe (with modern population of more than 17 million people). Significant differences of Moscow from the cities of Western Europe are related with much more continental climate with higher diurnal and annual temperature variations, and with specific building features such as its high density and almost total predominance of high-rise and low-rise blocks of flats on the private low-rise houses. Because of these building and climate features, the UHI of Moscow megacity is stronger than UHIs of many other cities of the similar size, with a mean intensity is about 2 °C and maximum intensity reaching up to 13 °C (Lokoschenko, 2014). Such a pronounced UHI together with the existence of an extensive observation network (more than 50 weather and air quality monitoring stations and few microwave temperature profilers) within the city and its surrounding make Moscow an especially interesting place for urban climate researches and good testbed for urban canopy models. In our numerical experiments, regional climate model firstly was adapted for investigated region with aim to improve quality of its simulations of rural areas. Then, to take into account urban canopy effects on thermal regime of the urbanized areas, we used two different versions of COSMO-CLM model. First is coupled with TEB (Town Energy Balance) single layer urban canopy model (Trusilova, 2013), and second is extended with bulk urban canopy scheme TERRA_URB using the Semi-empircal URban-canopY dependency parametriation SURY (Wouters et. al, 2016). Numerical experiments with these two versions of the model were run with spatial resolution about 1 km for several summer and winter months. To provide specific parameters, required for urban parameterizations, such as urban fraction, building height and street canyon aspect ratio
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.
Parameter estimation in fractional diffusion models
Kubilius, Kęstutis; Ralchenko, Kostiantyn
2017-01-01
This book is devoted to parameter estimation in diffusion models involving fractional Brownian motion and related processes. For many years now, standard Brownian motion has been (and still remains) a popular model of randomness used to investigate processes in the natural sciences, financial markets, and the economy. The substantial limitation in the use of stochastic diffusion models with Brownian motion is due to the fact that the motion has independent increments, and, therefore, the random noise it generates is “white,” i.e., uncorrelated. However, many processes in the natural sciences, computer networks and financial markets have long-term or short-term dependences, i.e., the correlations of random noise in these processes are non-zero, and slowly or rapidly decrease with time. In particular, models of financial markets demonstrate various kinds of memory and usually this memory is modeled by fractional Brownian diffusion. Therefore, the book constructs diffusion models with memory and provides s...
Estimating model parameters in nonautonomous chaotic systems using synchronization
International Nuclear Information System (INIS)
Yang, Xiaoli; Xu, Wei; Sun, Zhongkui
2007-01-01
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
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.
Model parameters estimation and sensitivity by genetic algorithms
International Nuclear Information System (INIS)
Marseguerra, Marzio; Zio, Enrico; Podofillini, Luca
2003-01-01
In this paper we illustrate the possibility of extracting qualitative information on the importance of the parameters of a model in the course of a Genetic Algorithms (GAs) optimization procedure for the estimation of such parameters. The Genetic Algorithms' search of the optimal solution is performed according to procedures that resemble those of natural selection and genetics: an initial population of alternative solutions evolves within the search space through the four fundamental operations of parent selection, crossover, replacement, and mutation. During the search, the algorithm examines a large amount of solution points which possibly carries relevant information on the underlying model characteristics. A possible utilization of this information amounts to create and update an archive with the set of best solutions found at each generation and then to analyze the evolution of the statistics of the archive along the successive generations. From this analysis one can retrieve information regarding the speed of convergence and stabilization of the different control (decision) variables of the optimization problem. In this work we analyze the evolution strategy followed by a GA in its search for the optimal solution with the aim of extracting information on the importance of the control (decision) variables of the optimization with respect to the sensitivity of the objective function. The study refers to a GA search for optimal estimates of the effective parameters in a lumped nuclear reactor model of literature. The supporting observation is that, as most optimization procedures do, the GA search evolves towards convergence in such a way to stabilize first the most important parameters of the model and later those which influence little the model outputs. In this sense, besides estimating efficiently the parameters values, the optimization approach also allows us to provide a qualitative ranking of their importance in contributing to the model output. The
Moose models with vanishing S parameter
International Nuclear Information System (INIS)
Casalbuoni, R.; De Curtis, S.; Dominici, D.
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 nonlocal 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 the Randall Sundrum metric
Rational Models for Inflation-Linked Derivatives
DEFF Research Database (Denmark)
Dam, Henrik; Macrina, Andrea; Skovmand, David
2018-01-01
We construct models for the pricing and risk management of inflation-linked derivatives. The model is rational in the sense that affine payoffs written on the consumer price index have prices that are rational functions of the state variables. The nominal pricing kernel is constructed in a multip......We construct models for the pricing and risk management of inflation-linked derivatives. The model is rational in the sense that affine payoffs written on the consumer price index have prices that are rational functions of the state variables. The nominal pricing kernel is constructed...... in a multiplicative manner that allows for closed-form pricing of vanilla inflation products suchlike zero-coupon swaps, caps and floors, year-on-year swaps, caps and floors, and the exotic limited price index swap. The model retains the attractive features of a nominal multi-curve interest rate model such as closed...
Schwinger model with higher derivative couplings
Energy Technology Data Exchange (ETDEWEB)
Barcelos-Neto, J.; Natividade, C.P. (Universidade Federal do Rio de Janeiro, RJ (Brazil). Inst. de Fisica)
1991-02-01
We study a version of the Schwinger model where fermion and gauge fields are coupled by means of higher derivatives. We show that, regardless of possible existence of ghosts and non-unitarity, the model is completely soluble and the anomalous axial divergence and the mass generated for the photon field are the same as in the usual model. The confinement of the electric charge is also discussed. (orig.).
Energy Technology Data Exchange (ETDEWEB)
Ashby, J.P.; Rawlings, G.E.; Soto, C.A.; Wood, D.F.; Chorley, D.W.
1979-12-01
A survey of parameters to be considered in the evaluation of sites for deep geologic nuclear waste repositories is presented. As yet, no comprehensive site selection procedure or performance evaluation approach has been adopted. A basis is provided for the development of parameters by discussing both site selection and performance evaluation. Three major groups of parameters are considered in this report: geologic, mining/rock mechanics, and hydrogeologic. For each type, the role of the parameter in the evaluation of repository sites is discussed. The derivation of the parameter by measurement, correlation, inference, or other method is discussed. Geologic parameters define the framework of the repository site and can be used in development of conceptual models and the prediction of long-term performance. Methods for deriving geological parameters include mapping, surveying, drilling, geophysical investigation, and historical and regional analysis. Rock mechanics/mining parameters are essential for the prediction of short-term performance and the development of initial conditions for modeling of long-term performance. Rock mechanics/mapping parameters can be derived by field or laboratory investigation, correlation, and theoretically or empirically based inference. Hydrogeologic parameters are the most important for assessment of long-term radionuclide confinement, since transport throughout the regional hydrogeologic system is the most likely mode of radionuclide escape from geologic repositories. Hydrogeologic parameters can be derived by hydrogeologic mapping and interpretation, hydrogeologic system modeling, field measurements, and lab tests. Procedures used in determination and statistical evaluation of geologic and rock mechanics parameters are discussed.
International Nuclear Information System (INIS)
Ashby, J.P.; Rawlings, G.E.; Soto, C.A.; Wood, D.F.; Chorley, D.W.
1979-12-01
A survey of parameters to be considered in the evaluation of sites for deep geologic nuclear waste repositories is presented. As yet, no comprehensive site selection procedure or performance evaluation approach has been adopted. A basis is provided for the development of parameters by discussing both site selection and performance evaluation. Three major groups of parameters are considered in this report: geologic, mining/rock mechanics, and hydrogeologic. For each type, the role of the parameter in the evaluation of repository sites is discussed. The derivation of the parameter by measurement, correlation, inference, or other method is discussed. Geologic parameters define the framework of the repository site and can be used in development of conceptual models and the prediction of long-term performance. Methods for deriving geological parameters include mapping, surveying, drilling, geophysical investigation, and historical and regional analysis. Rock mechanics/mining parameters are essential for the prediction of short-term performance and the development of initial conditions for modeling of long-term performance. Rock mechanics/mapping parameters can be derived by field or laboratory investigation, correlation, and theoretically or empirically based inference. Hydrogeologic parameters are the most important for assessment of long-term radionuclide confinement, since transport throughout the regional hydrogeologic system is the most likely mode of radionuclide escape from geologic repositories. Hydrogeologic parameters can be derived by hydrogeologic mapping and interpretation, hydrogeologic system modeling, field measurements, and lab tests. Procedures used in determination and statistical evaluation of geologic and rock mechanics parameters are discussed
Modelling Environment Changes for Pricing Weather Derivatives
Directory of Open Access Journals (Sweden)
Kabaivanov Stanimir
2017-12-01
Full Text Available This paper focuses on modelling environment changes in a way that allows to price weather derivatives in a flexible and efficient way. Applications and importance of climate and weather contracts extends beyond financial markets and hedging as they can be used as complementary tools for risk assessment. In addition, option-based approach toward resource management can offer very special insights on rare-events and allow to reuse derivative pricing methods to improve natural resources management. To demonstrate this general concept, we use Monte Carlo and stochastic modelling of temperatures to evaluate weather options. Research results are accompanied by R and Python code.
Khnychenko, L K; Sapronov, N S
2010-01-01
The results obtained on the model of starvation shows that nutritional dropsy led to the significant decrease of glucose, total cholesterol (TCh) and triglycerides (TC), as well as increase of non-estherified fatty acids (NEFA) in blood serum. In the rats with nutritional dropsy after treatment fed with standard diet enriched with soybean protein body weight returned to normal values as well as levels of Glucose, TCh and TC. However, concentration of NEFA remained increased. In the experimental group received additionally taurepar or taurhythman the level of NEFA decreased up to the normal one. It is necessary to mention that taurine derivatives did not change the biochemical parameters in blood of normal non-starved rats. We suppose that these new substances promote reduction of intensity of hyperlipidemic processes. It is known, that during starvation incomplete oxidation of fatty acids leads to acidosis with following destruction of mitochondria membraine. Finding property of taurine derivatives to decrease the concentration of non-estherified fatty acids points at their ability for restoration of tricarboxilic acid's cycle and prevention of accumulation of suboxidized molecules of NEFA and acidosis development.
International Nuclear Information System (INIS)
Mazoyer, B.M.; Huesman, R.H.; Budinger, T.F.; Knittel, B.L.
1986-01-01
Over the past years a major focus of research in physiologic studies employing tracers has been the computer implementation of mathematical methods of kinetic modeling for extracting the desired physiological parameters from tomographically derived data. A study is reported of factors that affect the statistical properties of compartmental model parameters extracted from dynamic positron emission tomography (PET) experiments
Models for setting ATM parameter values
DEFF Research Database (Denmark)
Blaabjerg, Søren; Gravey, A.; Romæuf, L.
1996-01-01
presents approximate methods and discusses their applicability. We then discuss the problem of obtaining traffic characteristic values for a connection that has crossed a series of switching nodes. This problem is particularly relevant for the traffic contract components corresponding to ICIs...... (CDV) tolerance(s). The values taken by these traffic parameters characterize the so-called ''Worst Case Traffic'' that is used by CAC procedures for accepting a new connection and allocating resources to it. Conformance to the negotiated traffic characteristics is defined, at the ingress User...... essential to set traffic characteristic values that are relevant to the considered cell stream, and that ensure that the amount of non-conforming traffic is small. Using a queueing model representation for the GCRA formalism, several methods are available for choosing the traffic characteristics. This paper...
Temperature stochastic modeling and weather derivatives pricing ...
African Journals Online (AJOL)
... over a sufficient period to apply a stochastic process that describes the evolution of the temperature. A numerical example of a swap contract pricing is presented, using an approximation formula as well as Monte Carlo simulations. Keywords: Weather derivatives, temperature stochastic model, Monte Carlo simulation.
Testing Expected Shortfall Models for Derivative Positions
Kerkhof, F.L.J.; Melenberg, B.; Schumacher, J.M.
2003-01-01
In this paper we test several risk management models for computing expected shortfall for one-period hedge errors of hedged derivatives positions.Contrary to value-at-risk, expected shortfall cannot be tested using the standard binomial test, since we need information of the distribution in the
Modelling ocean-colour-derived chlorophyll a
Dutkiewicz, Stephanie; Hickman, Anna E.; Jahn, Oliver
2018-01-01
This article provides a proof of concept for using a biogeochemical/ecosystem/optical model with a radiative transfer component as a laboratory to explore aspects of ocean colour. We focus here on the satellite ocean colour chlorophyll a (Chl a) product provided by the often-used blue/green reflectance ratio algorithm. The model produces output that can be compared directly to the real-world ocean colour remotely sensed reflectance. This model output can then be used to produce an ocean colour satellite-like Chl a product using an algorithm linking the blue versus green reflectance similar to that used for the real world. Given that the model includes complete knowledge of the (model) water constituents, optics and reflectance, we can explore uncertainties and their causes in this proxy for Chl a (called derived Chl a in this paper). We compare the derived Chl a to the actual model Chl a field. In the model we find that the mean absolute bias due to the algorithm is 22 % between derived and actual Chl a. The real-world algorithm is found using concurrent in situ measurement of Chl a and radiometry. We ask whether increased in situ measurements to train the algorithm would improve the algorithm, and find a mixed result. There is a global overall improvement, but at the expense of some regions, especially in lower latitudes where the biases increase. Not surprisingly, we find that region-specific algorithms provide a significant improvement, at least in the annual mean. However, in the model, we find that no matter how the algorithm coefficients are found there can be a temporal mismatch between the derived Chl a and the actual Chl a. These mismatches stem from temporal decoupling between Chl a and other optically important water constituents (such as coloured dissolved organic matter and detrital matter). The degree of decoupling differs regionally and over time. For example, in many highly seasonal regions, the timing of initiation and peak of the spring bloom in
DEFF Research Database (Denmark)
Parshad, Henrik; Frydenvang, Karla Andrea; Liljefors, Tommy
2002-01-01
Twenty two salts of benzylamine and p-substituted benzoic acids were prepared and characterized. The p-substituent was varied with regard to electronic, hydrophobic, and steric effects as well as hydrogen bonding potential. A multivariate data analysis was used to describe the relationship between...... the aqueous solubility of the salts and experimentally determined physicochemical parameters and theoretically derived molecular descriptors. The model, based on all descriptors, gave R(2)=0.86 and Q(2)=0.72. The most significant descriptors exhibiting VIP (variance of importance) values above 1.0 were...... intrinsic dissolution rate, intrinsic solubility of the unionized acids (S(0)), Hansch's hydrophobic parameter, Charton's steric parameter and molecular weight (MW). Statistically good models for predicting solubility of a selected test set were obtained by using simple models consisting of a few...
Dengue human infection model performance parameters.
Endy, Timothy P
2014-06-15
Dengue is a global health problem and of concern to travelers and deploying military personnel with development and licensure of an effective tetravalent dengue vaccine a public health priority. The dengue viruses (DENVs) are mosquito-borne flaviviruses transmitted by infected Aedes mosquitoes. Illness manifests across a clinical spectrum with severe disease characterized by intravascular volume depletion and hemorrhage. DENV illness results from a complex interaction of viral properties and host immune responses. Dengue vaccine development efforts are challenged by immunologic complexity, lack of an adequate animal model of disease, absence of an immune correlate of protection, and only partially informative immunogenicity assays. A dengue human infection model (DHIM) will be an essential tool in developing potential dengue vaccines or antivirals. The potential performance parameters needed for a DHIM to support vaccine or antiviral candidates are discussed. © The Author 2014. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Dimensionality reduction of RKHS model parameters.
Taouali, Okba; Elaissi, Ilyes; Messaoud, Hassani
2015-07-01
This paper proposes a new method to reduce the parameter number of models developed in the Reproducing Kernel Hilbert Space (RKHS). In fact, this number is equal to the number of observations used in the learning phase which is assumed to be high. The proposed method entitled Reduced Kernel Partial Least Square (RKPLS) consists on approximating the retained latent components determined using the Kernel Partial Least Square (KPLS) method by their closest observation vectors. The paper proposes the design and the comparative study of the proposed RKPLS method and the Support Vector Machines on Regression (SVR) technique. The proposed method is applied to identify a nonlinear Process Trainer PT326 which is a physical process available in our laboratory. Moreover as a thermal process with large time response may help record easily effective observations which contribute to model identification. Compared to the SVR technique, the results from the proposed RKPLS method are satisfactory. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Price models for oil derivates in Slovenia
International Nuclear Information System (INIS)
Nemac, F.; Saver, A.
1995-01-01
In Slovenia, a law is currently applied according to which any change in the price of oil derivatives is subject to the Governmental approval. Following the target of getting closer to the European Union, the necessity has arisen of finding ways for the introduction of liberalization or automated approach to price modifications depending on oscillations of oil derivative prices on the world market and the rate of exchange of the American dollar. It is for this reason that at the Agency for Energy Restructuring we made a study for the Ministry of Economic Affairs and Development regarding this issue. We analysed the possible models for the formation of oil derivative prices for Slovenia. Based on the assessment of experiences of primarily the west European countries, we proposed three models for the price formation for Slovenia. In future, it is expected that the Government of the Republic of Slovenia will make a selection of one of the proposed models to be followed by enforcement of price liberalization. The paper presents two representative models for price formation as used in Austria and Portugal. In the continuation the authors analyse the application of three models that they find suitable for the use in Slovenia. (author)
ORA waveform-derived biomechanical parameters to distinguish normal from keratoconic eyes
Directory of Open Access Journals (Sweden)
Allan Luz
2013-04-01
Full Text Available PURPOSE: To evaluate the ability of the Ocular Response Analyzer (ORA; Reichert Ophthalmic Instruments, Buffalo, NY to distinguish between normal and keratoconic eyes, by comparing pressure and waveform signal-derived parameters. METHODS: This retrospective comparative case series study included 112 patients with normal corneas and 41 patients with bilateral keratoconic eyes. One eye from each subject was randomly selected for analysis. Keratoconus diagnosis was based on clinical examinations, including Placido disk-based corneal topography and rotating Scheimpflug corneal tomography. Data from the ORA best waveform score (WS measurements were extracted using ORA software. Corneal hysteresis (CH, corneal resistance factor (CRF, Goldman-correlated intraocular pressure (IOPg, cornea-compensated intraocular pressure (IOPcc, and 37 parameters derived from the waveform signal were analyzed. Differences in the distributions among the groups were assessed using the Mann-Whitney test. Receiver operating characteristic (ROC curves were calculated. RESULTS: Statistically significant differences between keratoconic and normal eyes were found in all parameters (p<0.05 except IOPcc and W1. The area under the ROC curve (AUROC was greater than 0.85 for 11 parameters, including CH (0.852 and CRF (0.895. The parameters related to the area under the waveform peak during the second and first applanations (p2area and p1area had the best performances, with AUROCs of 0.939 and 0.929, respectively. The AUROCs for CRF, p2area, and p1area were significantly greater than that for CH. CONCLUSION: There are significant differences in biomechanical metrics between normal and keratoconic eyes. Compared with the pressure-derived parameters, corneal hysteresis and corneal resistance factor, novel waveform-derived ORA parameters provide better identification of keratoconus.
ORA waveform-derived biomechanical parameters to distinguish normal from keratoconic eyes.
Luz, Allan; Fontes, Bruno Machado; Lopes, Bernardo; Ramos, Isaac; Schor, Paulo; Ambrósio, Renato
2013-01-01
To evaluate the ability of the Ocular Response Analyzer (ORA; Reichert Ophthalmic Instruments, Buffalo, NY) to distinguish between normal and keratoconic eyes, by comparing pressure and waveform signal-derived parameters. This retrospective comparative case series study included 112 patients with normal corneas and 41 patients with bilateral keratoconic eyes. One eye from each subject was randomly selected for analysis. Keratoconus diagnosis was based on clinical examinations, including Placido disk-based corneal topography and rotating Scheimpflug corneal tomography. Data from the ORA best waveform score (WS) measurements were extracted using ORA software. Corneal hysteresis (CH), corneal resistance factor (CRF), Goldman-correlated intraocular pressure (IOPg), cornea-compensated intraocular pressure (IOPcc), and 37 parameters derived from the waveform signal were analyzed. Differences in the distributions among the groups were assessed using the Mann-Whitney test. Receiver operating characteristic (ROC) curves were calculated. Statistically significant differences between keratoconic and normal eyes were found in all parameters (p<0.05) except IOPcc and W1. The area under the ROC curve (AUROC) was greater than 0.85 for 11 parameters, including CH (0.852) and CRF (0.895). The parameters related to the area under the waveform peak during the second and first applanations (p2area and p1area) had the best performances, with AUROCs of 0.939 and 0.929, respectively. The AUROCs for CRF, p2area, and p1area were significantly greater than that for CH. There are significant differences in biomechanical metrics between normal and keratoconic eyes. Compared with the pressure-derived parameters, corneal hysteresis and corneal resistance factor, novel waveform-derived ORA parameters provide better identification of keratoconus.
Derivative processes for modelling metabolic fluxes
Žurauskienė, Justina; Kirk, Paul; Thorne, Thomas; Pinney, John; Stumpf, Michael
2014-01-01
Motivation: One of the challenging questions in modelling biological systems is to characterize the functional forms of the processes that control and orchestrate molecular and cellular phenotypes. Recently proposed methods for the analysis of metabolic pathways, for example, dynamic flux estimation, can only provide estimates of the underlying fluxes at discrete time points but fail to capture the complete temporal behaviour. To describe the dynamic variation of the fluxes, we additionally require the assumption of specific functional forms that can capture the temporal behaviour. However, it also remains unclear how to address the noise which might be present in experimentally measured metabolite concentrations. Results: Here we propose a novel approach to modelling metabolic fluxes: derivative processes that are based on multiple-output Gaussian processes (MGPs), which are a flexible non-parametric Bayesian modelling technique. The main advantages that follow from MGPs approach include the natural non-parametric representation of the fluxes and ability to impute the missing data in between the measurements. Our derivative process approach allows us to model changes in metabolite derivative concentrations and to characterize the temporal behaviour of metabolic fluxes from time course data. Because the derivative of a Gaussian process is itself a Gaussian process, we can readily link metabolite concentrations to metabolic fluxes and vice versa. Here we discuss how this can be implemented in an MGP framework and illustrate its application to simple models, including nitrogen metabolism in Escherichia coli. Availability and implementation: R code is available from the authors upon request. Contact: j.norkunaite@imperial.ac.uk; m.stumpf@imperial.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24578401
QSAR models for antioxidant activity of new coumarin derivatives.
Erzincan, P; Saçan, M T; Yüce-Dursun, B; Danış, Ö; Demir, S; Erdem, S S; Ogan, A
2015-01-01
This study presents 37 new antioxidant coumarin derivatives and strategies for structural modification to improve their antioxidant activities, the main ferric-reducing antioxidant power (FRAP) assay used to evaluate their antioxidant properties and the generation of validated quantitative structure-activity (antioxidant activity) relationship (QSAR) models. In an attempt to generate QSAR models, structures of all coumarin derivatives in the data set were fully optimized by semi-empirical PM6 method using SPARTAN 10 software. Descriptors were calculated by DRAGON 6.0 software. Multiple linear regression (MLR) models were developed with different training/test set combinations using QSARINS 2.2.1 software. Robustness, reliability and predictive power of the models were tested by internal and external validations. Applicability domain of the best two-descriptor model (nTR = 30; r(2) = 0.924; RMSETR = 0.213; nTEST = 7; r(2)ext = 0.887; RMSEext = 0.255; CCCext = 0.939) was determined. Descriptors appeared in the model revealed that complexity, H-bond donor and lipophilic character are important parameters in describing the antioxidant activity. Apart from the compounds in the data set, we also designed 31 new antioxidant coumarin derivatives and predicted their antioxidant activity using the best two-descriptor model. Most of these compounds are promising antioxidants.
Flare parameters inferred from a 3D loop model database
Cuambe, Valente A.; Costa, J. E. R.; Simões, P. J. A.
2018-04-01
We developed a database of pre-calculated flare images and spectra exploring a set of parameters which describe the physical characteristics of coronal loops and accelerated electron distribution. Due to the large number of parameters involved in describing the geometry and the flaring atmosphere in the model used (Costa et al. 2013), we built a large database of models (˜250 000) to facilitate the flare analysis. The geometry and characteristics of non-thermal electrons are defined on a discrete grid with spatial resolution greater than 4 arcsec. The database was constructed based on general properties of known solar flares and convolved with instrumental resolution to replicate the observations from the Nobeyama radio polarimeter (NoRP) spectra and Nobeyama radio-heliograph (NoRH) brightness maps. Observed spectra and brightness distribution maps are easily compared with the modelled spectra and images in the database, indicating a possible range of solutions. The parameter search efficiency in this finite database is discussed. Eight out of ten parameters analysed for one thousand simulated flare searches were recovered with a relative error of less than 20 per cent on average. In addition, from the analysis of the observed correlation between NoRH flare sizes and intensities at 17 GHz, some statistical properties were derived. From these statistics the energy spectral index was found to be δ ˜ 3, with non-thermal electron densities showing a peak distribution ⪅107 cm-3, and Bphotosphere ⪆2000 G. Some bias for larger loops with heights as great as ˜2.6 × 109 cm, and looptop events were noted. An excellent match of the spectrum and the brightness distribution at 17 and 34 GHz of the 2002 May 31 flare, is presented as well.
Behzadi, Hadi; Forghani, Ali
2017-03-01
The relation between electronic properties and corrosion inhibitive performance of three benzothiazole derivatives 1,3-benzothiazol-2-amine (BTA), 6-methyl-1,3-benzothiazol-2-amine (MBTA) and 2-amino-1,3-benzthiazole-6-thiol (TBTA) has been investigated by density functional theory. The electronic properties including EHOMO, ELUMO and related parameters were calculated at the B3LYP/6-311++G(d,p) level. The chemical shielding CS tensors were introduced as important and neglected descriptors to evaluate inhibitive efficiency of corrosion inhibitors. Nuclear independent chemical shift (NICS) components, as an aromaticity criterion, were also investigated as local descriptor. Polarizability and CS descriptors, as second rank tensors, show the best correlations with inhibition efficiencies of studied inhibitors.
Estimating crop net primary production using inventory data and MODIS-derived parameters
Energy Technology Data Exchange (ETDEWEB)
Bandaru, Varaprasad; West, Tristram O.; Ricciuto, Daniel M.; Izaurralde, Roberto C.
2013-06-03
National estimates of spatially-resolved cropland net primary production (NPP) are needed for diagnostic and prognostic modeling of carbon sources, sinks, and net carbon flux. Cropland NPP estimates that correspond with existing cropland cover maps are needed to drive biogeochemical models at the local scale and over national and continental extents. Existing satellite-based NPP products tend to underestimate NPP on croplands. A new Agricultural Inventory-based Light Use Efficiency (AgI-LUE) framework was developed to estimate individual crop biophysical parameters for use in estimating crop-specific NPP. The method is documented here and evaluated for corn and soybean crops in Iowa and Illinois in years 2006 and 2007. The method includes a crop-specific enhanced vegetation index (EVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS), shortwave radiation data estimated using Mountain Climate Simulator (MTCLIM) algorithm and crop-specific LUE per county. The combined aforementioned variables were used to generate spatially-resolved, crop-specific NPP that correspond to the Cropland Data Layer (CDL) land cover product. The modeling framework represented well the gradient of NPP across Iowa and Illinois, and also well represented the difference in NPP between years 2006 and 2007. Average corn and soybean NPP from AgI-LUE was 980 g C m-2 yr-1 and 420 g C m-2 yr-1, respectively. This was 2.4 and 1.1 times higher, respectively, for corn and soybean compared to the MOD17A3 NPP product. Estimated gross primary productivity (GPP) derived from AgI-LUE were in close agreement with eddy flux tower estimates. The combination of new inputs and improved datasets enabled the development of spatially explicit and reliable NPP estimates for individual crops over large regional extents.
International Nuclear Information System (INIS)
Aman, S N A; Latif, Z Abd; Pradhan, B
2014-01-01
Landslide occurrence depends on various interrelating factors which consequently initiate to massive mass of soil and rock debris that move downhill due to the gravity action. LiDAR has come with a progressive approach in mitigating landslide by permitting the formation of more accurate DEM compared to other active space borne and airborne remote sensing techniques. The objective of this research is to assess the susceptibility of landslide in Ulu Klang area by investigating the correlation between past landslide events with geo environmental factors. A high resolution LiDAR DEM was constructed to produce topographic attributes such as slope, curvature and aspect. These data were utilized to derive second deliverables of landslide parameters such as topographic wetness index (TWI), surface area ratio (SAR) and stream power index (SPI) as well as NDVI generated from IKONOS imagery. Subsequently, a probabilistic based frequency ratio model was applied to establish the spatial relationship between the landslide locations and each landslide related factor. Factor ratings were summed up to obtain Landslide Susceptibility Index (LSI) to construct the landslide susceptibility map
Hope, Sarah A; Meredith, Ian T; Tay, David; Cameron, James D
2007-09-01
Arterial transfer functions (TFs) describe the relationship between the pressure waveform at different arterial sites. Generalized TFs are used to reconstruct central aortic waveforms from non-invasively obtained peripheral waveforms and have been promoted as potentially clinically useful. A limitation is the paucity of information on their 'generalizability' with no information existing on the number of subjects required to construct a satisfactory TF, nor is adequate prospective validation available. We therefore investigated the uniformity of radial-aortic TFs and prospectively estimated the capacity of a generalized TF to reconstruct individual central blood pressure parameters. Ninety-three subjects (64 male) were studied by simultaneous radial applanation and high-fidelity (Millar Mikro-tip catheter) direct measurement of central aortic BP during elective coronary procedures. Subjects were prospectively randomized to either a derivation or validation group. Increasing numbers of individual TFs from the derivation group were averaged to form a generalized TF. There was minimal change with greater than 20 TFs averaged. In the validation group, the error in most reconstructed parameters related to the absolute value of the directly measured parameter [systolic blood pressure (SBP) and pulse pressure, Pcentral aortic SBP and pulse pressure (negatively) and time to peak systole (positively) (all PInclusion of more than 20 individual TFs in the construction of a generalized TF does not improve 'generalizability'. There appear to be systematic errors in derived central pressure waveforms and derived aortic augmentation index is inaccurate compared to the directly measured value.
DEFF Research Database (Denmark)
Pauwels, Valentijn; Balenzano, Anna; Satalino, Giuseppe
2009-01-01
that no direct relationships between the remote-sensing observations, more specifically radar backscatter values, and the parameter values can be derived. However, land surface models can provide these relationships. The objective of this paper is to retrieve a number of soil physical model parameters through...... model is, thus, used to determine the relationship between the soil physical parameters and the remote-sensing data. An analysis is then performed, relating the retrieved soil parameters to the soil texture data available over the study area. The results of the study show that there is a potential...
Parameter estimation and analysis of an automotive heavy-duty SCR catalyst model
DEFF Research Database (Denmark)
Åberg, Andreas; Widd, Anders; Abildskov, Jens
2017-01-01
A single channel model for a heavy-duty SCR catalyst was derived based on first principles. The model considered heat and mass transfer between the channel gas phase and the wash coat phase. The parameters of the kinetic model were estimated using bench-scale monolith isothermal data. Validation ...
Kinetic Parameters of Thermal Decomposition Process Analyzed using a Mathematical Model
Nandiyanto, A. B. D.; Ekawati, R.; Wibawa, S. C.
2018-01-01
The purpose of this study was to show a mathematical analysis model for understanding kinetic parameters of thermal decomposition process. The mathematical model was derived based on phenomena happen during the thermal-related reaction. To get the kinetic parameters (i.e. reaction order, activation energy, and Arrhenius constant), the model was combined with the thermal characteristics of material gained from the thermal gravity (TG) and differential thermal analysis (DTA) curves. As an example, the model was used for analyzing the kinetic properties of trinitrotoluene. Interestingly, identical results gained from the present model with current literatures were obtained; in which these were because the present model was derived directly from the analysis of stoichiometrical and thermal analysis of the ideal chemical reaction. Since the present model confirmed to have a good agreement with current theories, further derivation from the present mathematical model can be useful for further development.
Sample Size and Item Parameter Estimation Precision When Utilizing the One-Parameter "Rasch" Model
Custer, Michael
2015-01-01
This study examines the relationship between sample size and item parameter estimation precision when utilizing the one-parameter model. Item parameter estimates are examined relative to "true" values by evaluating the decline in root mean squared deviation (RMSD) and the number of outliers as sample size increases. This occurs across…
Optimizing incomplete sample designs for item response model parameters
van der Linden, Willem J.
Several models for optimizing incomplete sample designs with respect to information on the item parameters are presented. The following cases are considered: (1) known ability parameters; (2) unknown ability parameters; (3) item sets with multiple ability scales; and (4) response models with
Piecewise Model and Parameter Obtainment of Governor Actuator in Turbine
Directory of Open Access Journals (Sweden)
Jie Zhao
2015-01-01
Full Text Available The governor actuators in some heat-engine plants have nonlinear valves. This nonlinearity of valves may lead to the inaccuracy of the opening and closing time constants calculated based on the whole segment fully open and fully close experimental test curves of the valve. An improved mathematical model of the turbine governor actuator is proposed to reflect the nonlinearity of the valve, in which the main and auxiliary piecewise opening and closing time constants instead of the fixed oil motive opening and closing time constants are adopted to describe the characteristics of the actuator. The main opening and closing time constants are obtained from the linear segments of the whole fully open and close curves. The parameters of proportional integral derivative (PID controller are identified based on the small disturbance experimental tests of the valve. Then the auxiliary opening and closing time constants and the piecewise opening and closing valve points are determined by the fully open/close experimental tests. Several testing functions are selected to compare genetic algorithm and particle swarm optimization algorithm (GA-PSO with other basic intelligence algorithms. The effectiveness of the piecewise linear model and its parameters are validated by practical power plant case studies.
Study on Parameters Modeling of Wind Turbines Using SCADA Data
Directory of Open Access Journals (Sweden)
Yonglong YAN
2014-08-01
Full Text Available Taking the advantage of the current massive monitoring data from Supervisory Control and Data Acquisition (SCADA system of wind farm, it is of important significance for anomaly detection, early warning and fault diagnosis to build the data model of state parameters of wind turbines (WTs. The operational conditions and the relationships between the state parameters of wind turbines are complex. It is difficult to establish the model of state parameter accurately, and the modeling method of state parameters of wind turbines considering parameter selection is proposed. Firstly, by analyzing the characteristic of SCADA data, a reasonable range of data and monitoring parameters are chosen. Secondly, neural network algorithm is adapted, and the selection method of input parameters in the model is presented. Generator bearing temperature and cooling air temperature are regarded as target parameters, and the two models are built and input parameters of the models are selected, respectively. Finally, the parameter selection method in this paper and the method using genetic algorithm-partial least square (GA-PLS are analyzed comparatively, and the results show that the proposed methods are correct and effective. Furthermore, the modeling of two parameters illustrate that the method in this paper can applied to other state parameters of wind turbines.
WINKLER'S SINGLE-PARAMETER SUBGRADE MODEL FROM ...
African Journals Online (AJOL)
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SUBGRADE MODELING. Asrat Worku. Department of ... The models give consistently larger stiffness for the Winkler springs as compared to previously proposed similar continuum-based models that ignore the lateral stresses. ...... (ν = 0.25 and E = 40MPa); (b) a medium stiff clay (ν = 0.45 and E = 50MPa). In contrast to this, ...
DEFF Research Database (Denmark)
Pedersen, Leif Toudal; Tonboe, Rasmus T.; Høyer, Jacob
.e. horizontal and vertical polarization at channels between 6 and 89 GHz as a function of a limited set of physical parameters, i.e. atmospheric water vapor, cloud liquid water, wind speed, surface and air temperature. This type of model is ideal for optimal estimation applications because of its limited set...... channels as well as the combination of data from multiple sources such as microwave radiometry, scatterometry and numerical weather prediction. Optimal estimation is data assimilation without a numerical model for retrieving physical parameters from remote sensing using a multitude of available information....... The methodology is observation driven and model innovation is limited to the translation between observation space and physical parameter space Over open water we use a semi-empirical radiative transfer model developed by Meissner & Wentz that estimates the multispectral AMSR brightness temperatures, i...
QSAR MODELING OF ANTIBACTERIAL ACTIVITY OF SOME BENZIMIDAZOLE DERIVATIVES
Directory of Open Access Journals (Sweden)
SANJA O. PODUNAVAC-KUZMANOVIĆ
2011-03-01
Full Text Available A quantitative structure-activity relationship (QSAR study has been carried out for a training set of 12 benzimidazole derivatives to correlate and predict the antibacterial activity of studied compounds against Gram-negative bacteria Pseudomonas aeruginosa. Multiple linear regression was used to select the descriptors and to generate the best prediction model that relates the structural features to inhibitory activity. The predictivity of the model was estimated by cross-validation with the leave-one-out method. Our results suggest a QSAR model based on the following descriptors: parameter of lipophilicity (logP and hydration energy (HE. Good agreement between experimental and predicted inhibitory values, obtained in the validation procedure, indicated the good quality of the generated QSAR model.
Diabatic models with transferrable parameters for generalized chemical reactions
Reimers, Jeffrey R.; McKemmish, Laura K.; McKenzie, Ross H.; Hush, Noel S.
2017-05-01
Diabatic models applied to adiabatic electron-transfer theory yield many equations involving just a few parameters that connect ground-state geometries and vibration frequencies to excited-state transition energies and vibration frequencies to the rate constants for electron-transfer reactions, utilizing properties of the conical-intersection seam linking the ground and excited states through the Pseudo Jahn-Teller effect. We review how such simplicity in basic understanding can also be obtained for general chemical reactions. The key feature that must be recognized is that electron-transfer (or hole transfer) processes typically involve one electron (hole) moving between two orbitals, whereas general reactions typically involve two electrons or even four electrons for processes in aromatic molecules. Each additional moving electron leads to new high-energy but interrelated conical-intersection seams that distort the shape of the critical lowest-energy seam. Recognizing this feature shows how conical-intersection descriptors can be transferred between systems, and how general chemical reactions can be compared using the same set of simple parameters. Mathematical relationships are presented depicting how different conical-intersection seams relate to each other, showing that complex problems can be reduced into an effective interaction between the ground-state and a critical excited state to provide the first semi-quantitative implementation of Shaik’s “twin state” concept. Applications are made (i) demonstrating why the chemistry of the first-row elements is qualitatively so different to that of the second and later rows, (ii) deducing the bond-length alternation in hypothetical cyclohexatriene from the observed UV spectroscopy of benzene, (iii) demonstrating that commonly used procedures for modelling surface hopping based on inclusion of only the first-derivative correction to the Born-Oppenheimer approximation are valid in no region of the chemical
Parameter and State Estimator for State Space Models
Directory of Open Access Journals (Sweden)
Ruifeng Ding
2014-01-01
Full Text Available This paper proposes a parameter and state estimator for canonical state space systems from measured input-output data. The key is to solve the system state from the state equation and to substitute it into the output equation, eliminating the state variables, and the resulting equation contains only the system inputs and outputs, and to derive a least squares parameter identification algorithm. Furthermore, the system states are computed from the estimated parameters and the input-output data. Convergence analysis using the martingale convergence theorem indicates that the parameter estimates converge to their true values. Finally, an illustrative example is provided to show that the proposed algorithm is effective.
Parameter and state estimator for state space models.
Ding, Ruifeng; Zhuang, Linfan
2014-01-01
This paper proposes a parameter and state estimator for canonical state space systems from measured input-output data. The key is to solve the system state from the state equation and to substitute it into the output equation, eliminating the state variables, and the resulting equation contains only the system inputs and outputs, and to derive a least squares parameter identification algorithm. Furthermore, the system states are computed from the estimated parameters and the input-output data. Convergence analysis using the martingale convergence theorem indicates that the parameter estimates converge to their true values. Finally, an illustrative example is provided to show that the proposed algorithm is effective.
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.
Generic NICA-Donnan model parameters for metal-ion binding by humic substances
Milne, C.J.; Kinniburgh, D.G.; Riemsdijk, van W.H.; Tipping, E.
2003-01-01
A total of 171 datasets of literature and experimental data for metal-ion binding by fulvic and humic acids have been digitized and re-analyzed using the NICA-Donnan model. Generic parameter values have been derived that can be used for modeling in the absence of specific metal-ion binding
Deriving a model for influenza epidemics from historical data.
Energy Technology Data Exchange (ETDEWEB)
Ray, Jaideep; Lefantzi, Sophia
2011-09-01
In this report we describe how we create a model for influenza epidemics from historical data collected from both civilian and military societies. We derive the model when the population of the society is unknown but the size of the epidemic is known. Our interest lies in estimating a time-dependent infection rate to within a multiplicative constant. The model form fitted is chosen for its similarity to published models for HIV and plague, enabling application of Bayesian techniques to discriminate among infectious agents during an emerging epidemic. We have developed models for the progression of influenza in human populations. The model is framed as a integral, and predicts the number of people who exhibit symptoms and seek care over a given time-period. The start and end of the time period form the limits of integration. The disease progression model, in turn, contains parameterized models for the incubation period and a time-dependent infection rate. The incubation period model is obtained from literature, and the parameters of the infection rate are fitted from historical data including both military and civilian populations. The calibrated infection rate models display a marked difference in which the 1918 Spanish Influenza pandemic differed from the influenza seasons in the US between 2001-2008 and the progression of H1N1 in Catalunya, Spain. The data for the 1918 pandemic was obtained from military populations, while the rest are country-wide or province-wide data from the twenty-first century. We see that the initial growth of infection in all cases were about the same; however, military populations were able to control the epidemic much faster i.e., the decay of the infection-rate curve is much higher. It is not clear whether this was because of the much higher level of organization present in a military society or the seriousness with which the 1918 pandemic was addressed. Each outbreak to which the influenza model was fitted yields a separate set of
International Nuclear Information System (INIS)
Larson, D.; Bennett, C. L.; Gold, B.; Dunkley, J.; Hinshaw, G.; Kogut, A.; Wollack, E.; Komatsu, E.; Nolta, M. R.; Halpern, M.; Hill, R. S.; Odegard, N.; Weiland, J. L.; Jarosik, N.; Page, L.; Limon, M.; Meyer, S. S.; Smith, K. M.; Spergel, D. N.; Tucker, G. S.
2011-01-01
The WMAP mission has produced sky maps from seven years of observations at L2. We present the angular power spectra derived from the seven-year maps and discuss the cosmological conclusions that can be inferred from WMAP data alone. With the seven-year data, the temperature (TT) spectrum measurement has a signal-to-noise ratio per multipole that exceeds unity for l m h 2 = 0.1334 +0.0056 -0.0055 , and on the epoch of matter-radiation equality, z eq = 3196 +134 -133 . The temperature-polarization (TE) spectrum is detected in the seven-year data with a significance of 20σ, compared to 13σ with the five-year data. We now detect the second dip in the TE spectrum near l ∼ 450 with high confidence. The TB and EB spectra remain consistent with zero, thus demonstrating low systematic errors and foreground residuals in the data. The low-l EE spectrum, a measure of the optical depth due to reionization, is detected at 5.5σ significance when averaged over l = 2-7: l(l + 1)C EE l /(2π) = 0.074 +0.034 -0.025 μK 2 (68% CL). We now detect the high-l, 24 ≤ l ≤ 800, EE spectrum at over 8σ. The BB spectrum, an important probe of gravitational waves from inflation, remains consistent with zero; when averaged over l = 2-7, l(l + 1)C BB l /(2π) 2 (95% CL). The upper limit on tensor modes from polarization data alone is a factor of two lower with the seven-year data than it was using the five-year data. The data remain consistent with the simple ΛCDM model: the best-fit TT spectrum has an effective χ 2 of 1227 for 1170 degrees of freedom, with a probability to exceed of 9.6%. The allowable volume in the six-dimensional space of ΛCDM parameters has been reduced by a factor of 1.5 relative to the five-year volume, while the ΛCDM model that allows for tensor modes and a running scalar spectral index has a factor of three lower volume when fit to the seven-year data. We test the parameter recovery process for bias and find that the scalar spectral index, n s , is biased
On the relationship between NMR-derived amide order parameters and protein backbone entropy changes.
Sharp, Kim A; O'Brien, Evan; Kasinath, Vignesh; Wand, A Joshua
2015-05-01
Molecular dynamics simulations are used to analyze the relationship between NMR-derived squared generalized order parameters of amide NH groups and backbone entropy. Amide order parameters (O(2) NH ) are largely determined by the secondary structure and average values appear unrelated to the overall flexibility of the protein. However, analysis of the more flexible subset (O(2) NH entropy than that reported by the side chain methyl axis order parameters, O(2) axis . A calibration curve for backbone entropy vs. O(2) NH is developed, which accounts for both correlations between amide group motions of different residues, and correlations between backbone and side chain motions. This calibration curve can be used with experimental values of O(2) NH changes obtained by NMR relaxation measurements to extract backbone entropy changes, for example, upon ligand binding. In conjunction with our previous calibration for side chain entropy derived from measured O(2) axis values this provides a prescription for determination of the total protein conformational entropy changes from NMR relaxation measurements. © 2015 Wiley Periodicals, Inc.
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.
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...
Edge Modeling by Two Blur Parameters in Varying Contrasts.
Seo, Suyoung
2018-06-01
This paper presents a method of modeling edge profiles with two blur parameters, and estimating and predicting those edge parameters with varying brightness combinations and camera-to-object distances (COD). First, the validity of the edge model is proven mathematically. Then, it is proven experimentally with edges from a set of images captured for specifically designed target sheets and with edges from natural images. Estimation of the two blur parameters for each observed edge profile is performed with a brute-force method to find parameters that produce global minimum errors. Then, using the estimated blur parameters, actual blur parameters of edges with arbitrary brightness combinations are predicted using a surface interpolation method (i.e., kriging). The predicted surfaces show that the two blur parameters of the proposed edge model depend on both dark-side edge brightness and light-side edge brightness following a certain global trend. This is similar across varying CODs. The proposed edge model is compared with a one-blur parameter edge model using experiments of the root mean squared error for fitting the edge models to each observed edge profile. The comparison results suggest that the proposed edge model has superiority over the one-blur parameter edge model in most cases where edges have varying brightness combinations.
International Nuclear Information System (INIS)
Bonka, H.
1998-01-01
Since due to the nuclear reactor accident in Chernobyl r[ionuclides arrived in the vicinity of Aachen, the enhancement of the local dose rate, the deposition of the different r[ionuclides on ground and vegetation and the transport of the r[ionuclides into the environment were measured. Partly the measurements were continued until today. Very informative time sequences of the specific activity in grass, food, cow's milk, beef, in the different plants, trees, ploughed soil and undisturbed soil, mushrooms, game, in humans etc. resulted. During different private and official journeys in the old Laender of the Federal Republic of Germany surface covering measurements of the 134 Cs and 137 Cs activity deposited on grass land at different places were carried out. These data were implemented into a map on ground contamination in 1986 in Germany, published in 1991 by the Institute for Water, Soil and Air Hygiene of the Federal Public Health Department in Berlin. Transfer factors soil-grass were measured in the whole Federal Republic of Germany analyzing grass samples which were partly taken at the same time. A large amount of r[ioecological parameters could be derived from the different time sequences. These are in particular: The deposition velocity for iodine and particle bound r[ioanuclides on grass and in forests, the rainout coefficient in dependence of the precipitation intensity, the retention factors on grass, the biological half-life time on grass, the transfer factor soil-grass in dependence of time, the transfer factor food-milk during the pasture period and during stable stay, the transfer factor food-beef, the transfer factors in eatable mushrooms, the translocation factor of cesium in cereals etc. A multi-compartment model was developed to calculate the specific Cs activity in cow's milk and beef. The specific activity in milk can be calculated sufficiently exact using a simple single compartment model. The correlation of the specific Cs activity in spruce
Estimation of Parameters in Latent Class Models with Constraints on the Parameters.
Paulson, James A.
This paper reviews the application of the EM Algorithm to marginal maximum likelihood estimation of parameters in the latent class model and extends the algorithm to the case where there are monotone homogeneity constraints on the item parameters. It is shown that the EM algorithm can be used to obtain marginal maximum likelihood estimates of the…
Modeling and Dynamic Properties of a Four-Parameter Zener Model Vibration Isolator
Directory of Open Access Journals (Sweden)
Wen-ku Shi
2016-01-01
Full Text Available To install high-performance isolators in a limited installation space, a novel passive isolator based on the four-parameter Zener model is proposed. The proposed isolator consists of three major parts, namely, connecting structure, sealing construction, and upper and lower cavities, all of which are enclosed by four segments of metal bellows with the same diameter. The equivalent stiffness and damping model of the isolator are derived from the dynamic stiffness of the isolation system. Experiments are conducted, and the experiment error is analyzed. Test results verify the validity of the model. Theoretical analysis and numerical simulation reveal that the stiffness and damping of the isolator have multiple properties with different exciting amplitudes and structural parameters. In consideration of the design of the structural parameter, the effects of exciting amplitude, damp channel diameter, equivalent cylinder diameter of cavities, sum of the stiffness of the bellows at the end of the isolator, and length of damp channel on the dynamic properties of the isolator are discussed comprehensively. A design method based on the parameter sensitivity of the isolator’s design parameter is proposed. Thus, the novel isolator can be practically applied to engineering and provide a significant contribution in the field.
Analysis and validation of severe storm parameters derived from TITAN in Southeast Brazil
Gomes, Ana Maria; Held, Gerhard; Vernini, Rafael; Demetrio Souza, Caio
2014-05-01
The implementation of TITAN (Thundestorm Identification, Tracking and Nowcasting) System at IPMet in December 2005 has provided real-time access to the storm severity parameters derived from radar reflectivity, which are being used to identify and alert of potentially severe storms within the 240 km quantitative ranges of the Bauru and Presidente Prudente S-band radars. The potential of these tools available with the TITAN system is being evaluated by using the hail reports received from voluntary hail observers to cross-check the occurrence of hail within the radar range against the TITAN predictions. Part of the ongoing research at IPMet aims to determine "signatures" in severe events and therefore, as from 2008, an online standard form was introduced, allowing for greater detail on the occurrence of a severe event within the 240 km ranges of both radars. The model for the hail report was based on the one initially deployed by the Alberta Hail Program, in Canada, and also by the Hail Observer Network established by the CSIR (Council for Scientific and Industrial Research), in Pretoria, South Africa, where it was used for more than 25 years. The TITAN system was deployed to obtain the tracking properties of storms for this analysis. A cell was defined by the thresholds of 40 dBZ for the reflectivity and 16 km3 for the volume, observed at least in two consecutive volume scans (15 minutes). Besides tracking and Nowcasting the movement of storm cells, TITAN comprises algorithms that allow the identification of potentially severe storm "signatures", such as the hail metrics, to indicate the probability of hail (POH), based on a combination of radar data and the knowledge of the vertical temperature distribution of the atmosphere. Another two parameters, also related to hail producing storms, called FOKR (Foote-Krauss) index and HMA (Hail Mass Aloft) index is also included. The period from 2008 to 2013 was used to process all available information about storm
Incremental parameter estimation of kinetic metabolic network models
Directory of Open Access Journals (Sweden)
Jia Gengjie
2012-11-01
Full Text Available Abstract Background An efficient and reliable parameter estimation method is essential for the creation of biological models using ordinary differential equation (ODE. Most of the existing estimation methods involve finding the global minimum of data fitting residuals over the entire parameter space simultaneously. Unfortunately, the associated computational requirement often becomes prohibitively high due to the large number of parameters and the lack of complete parameter identifiability (i.e. not all parameters can be uniquely identified. Results In this work, an incremental approach was applied to the parameter estimation of ODE models from concentration time profiles. Particularly, the method was developed to address a commonly encountered circumstance in the modeling of metabolic networks, where the number of metabolic fluxes (reaction rates exceeds that of metabolites (chemical species. Here, the minimization of model residuals was performed over a subset of the parameter space that is associated with the degrees of freedom in the dynamic flux estimation from the concentration time-slopes. The efficacy of this method was demonstrated using two generalized mass action (GMA models, where the method significantly outperformed single-step estimations. In addition, an extension of the estimation method to handle missing data is also presented. Conclusions The proposed incremental estimation method is able to tackle the issue on the lack of complete parameter identifiability and to significantly reduce the computational efforts in estimating model parameters, which will facilitate kinetic modeling of genome-scale cellular metabolism in the future.
An approach to adjustment of relativistic mean field model parameters
Directory of Open Access Journals (Sweden)
Bayram Tuncay
2017-01-01
Full Text Available The Relativistic Mean Field (RMF model with a small number of adjusted parameters is powerful tool for correct predictions of various ground-state nuclear properties of nuclei. Its success for describing nuclear properties of nuclei is directly related with adjustment of its parameters by using experimental data. In the present study, the Artificial Neural Network (ANN method which mimics brain functionality has been employed for improvement of the RMF model parameters. In particular, the understanding capability of the ANN method for relations between the RMF model parameters and their predictions for binding energies (BEs of 58Ni and 208Pb have been found in agreement with the literature values.
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.
Lumped parameter models for the interpretation of environmental tracer data
International Nuclear Information System (INIS)
Maloszewski, P.; Zuber, A.
1996-01-01
Principles of the lumped-parameter approach to the interpretation of environmental tracer data are given. The following models are considered: the piston flow model (PFM), exponential flow model (EM), linear model (LM), combined piston flow and exponential flow model (EPM), combined linear flow and piston flow model (LPM), and dispersion model (DM). The applicability of these models for the interpretation of different tracer data is discussed for a steady state flow approximation. Case studies are given to exemplify the applicability of the lumped-parameter approach. Description of a user-friendly computer program is given. (author). 68 refs, 25 figs, 4 tabs
A test for the parameters of multiple linear regression models ...
African Journals Online (AJOL)
A test for the parameters of multiple linear regression models is developed for conducting tests simultaneously on all the parameters of multiple linear regression models. The test is robust relative to the assumptions of homogeneity of variances and absence of serial correlation of the classical F-test. Under certain null and ...
WATGIS: A GIS-Based Lumped Parameter Water Quality Model
Glenn P. Fernandez; George M. Chescheir; R. Wayne Skaggs; Devendra M. Amatya
2002-01-01
A Geographic Information System (GIS)Âbased, lumped parameter water quality model was developed to estimate the spatial and temporal nitrogenÂloading patterns for lower coastal plain watersheds in eastern North Carolina. The model uses a spatially distributed delivery ratio (DR) parameter to account for nitrogen retention or loss along a drainage network. Delivery...
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.
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.
Characterizing parameter sensitivity and uncertainty for a snow model across hydroclimatic regimes
He, Minxue; Hogue, Terri S.; Franz, Kristie J.; Margulis, Steven A.; Vrugt, Jasper A.
2011-01-01
The National Weather Service (NWS) uses the SNOW17 model to forecast snow accumulation and ablation processes in snow-dominated watersheds nationwide. Successful application of the SNOW17 relies heavily on site-specific estimation of model parameters. The current study undertakes a comprehensive sensitivity and uncertainty analysis of SNOW17 model parameters using forcing and snow water equivalent (SWE) data from 12 sites with differing meteorological and geographic characteristics. The Generalized Sensitivity Analysis and the recently developed Differential Evolution Adaptive Metropolis (DREAM) algorithm are utilized to explore the parameter space and assess model parametric and predictive uncertainty. Results indicate that SNOW17 parameter sensitivity and uncertainty generally varies between sites. Of the six hydroclimatic characteristics studied, only air temperature shows strong correlation with the sensitivity and uncertainty ranges of two parameters, while precipitation is highly correlated with the uncertainty of one parameter. Posterior marginal distributions of two parameters are also shown to be site-dependent in terms of distribution type. The SNOW17 prediction ensembles generated by the DREAM-derived posterior parameter sets contain most of the observed SWE. The proposed uncertainty analysis provides posterior parameter information on parameter uncertainty and distribution types that can serve as a foundation for a data assimilation framework for hydrologic models.
DEFF Research Database (Denmark)
King, Alexander Weider; Agerkvist, Finn T.
2017-01-01
Commonly used models of moving-coil loudspeaker voice coils, which include effects from eddy current losses, are either inaccurate or contain an abundance of parameters, and are difficult to extend to the nonlinear domain. On the contrary, fractional derivative models accurately describe...... order derivative approaches a value of 1, corresponding to an ideal inductance, when the voice coil is completely outside the magnetic system. Finally, the developed model reveals details about the effect of conductive voice coil formers...
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
Brownian motion model with stochastic parameters for asset prices
Ching, Soo Huei; Hin, Pooi Ah
2013-09-01
The Brownian motion model may not be a completely realistic model for asset prices because in real asset prices the drift μ and volatility σ may change over time. Presently we consider a model in which the parameter x = (μ,σ) is such that its value x (t + Δt) at a short time Δt ahead of the present time t depends on the value of the asset price at time t + Δt as well as the present parameter value x(t) and m-1 other parameter values before time t via a conditional distribution. The Malaysian stock prices are used to compare the performance of the Brownian motion model with fixed parameter with that of the model with stochastic parameter.
Mattia, F.; Pauwels, V. R.; Balenzano, A.; Satalino, G.; Skriver, H.; Verhoest, N. E.
2008-12-01
It is widely recognized that Synthetic Aperture Radar (SAR) data are a very valuable source of information for the modeling of the interactions between the land surface and the atmosphere. During the last couple of decades, most of the research on the use of SAR data in hydrologic applications has been focused on the retrieval of land and bio-geophysical parameters (e.g. soil moisture contents). One relatively unexplored issue consists of the optimization of soil hydraulic model parameters, such as for example hydraulic conductivity values, through remote sensing. This is due to the fact that no direct relationships between the remote sensing observations, more specifically radar backscatter values, and the parameter values can be derived. However, land surface models can provide these relationships. The objective of this study is to retrieve a number of soil physical model parameters through a combination of remote sensing and land surface modeling. Spatially distributed and multitemporal SAR-based soil moisture maps are the basis of the study. The surface soil moisture values are used in a parameter estimation procedure based on the Extended Kalman Filter equations. In fact, the land surface model is thus used to determine the relationship between the soil physical parameters and the remote sensing data. An analysis is then performed, relating the retrieved soil parameters to the soil texture data available over the study area. The results of the study show that there is a potential to retrieve soil physical model parameters through a combination of land surface modeling and remote sensing.
Estimation of shape model parameters for 3D surfaces
DEFF Research Database (Denmark)
Erbou, Søren Gylling Hemmingsen; Darkner, Sune; Fripp, Jurgen
2008-01-01
is applied to a database of 3D surfaces from a section of the porcine pelvic bone extracted from 33 CT scans. A leave-one-out validation shows that the parameters of the first 3 modes of the shape model can be predicted with a mean difference within [-0.01,0.02] from the true mean, with a standard deviation......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...... surfaces using distance maps, which enables the estimation of model parameters without the requirement of point correspondence. For applications with acquisition limitations such as speed and cost, this formulation enables the fitting of a statistical shape model to arbitrarily sampled data. The method...
Determination of the Corona model parameters with artificial neural networks
International Nuclear Information System (INIS)
Ahmet, Nayir; Bekir, Karlik; Arif, Hashimov
2005-01-01
Full text : The aim of this study is to calculate new model parameters taking into account the corona of electrical transmission line wires. For this purpose, a neural network modeling proposed for the corona frequent characteristics modeling. Then this model was compared with the other model developed at the Polytechnic Institute of Saint Petersburg. The results of development of the specified corona model for calculation of its influence on the wave processes in multi-wires line and determination of its parameters are submitted. Results of obtained calculation equations are brought for electrical transmission line with allowance for superficial effect in the ground and wires with reference to developed corona model
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
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. ...
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 with absolute values that round to 1.00 were good indicators of extreme parameter correlation, but smaller values were not necessarily good indicators of lack of correlation and resulting unique parameter estimates; (2) the SVD may be more difficult to interpret than parameter...
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.
Using radar-derived parameters to forecast lightning cessation for nonisolated storms
Davey, Matthew J.; Fuelberg, Henry E.
2017-03-01
Lightning impacts operations at the Kennedy Space Center (KSC) and other outdoor venues leading to injuries, inconvenience, and detrimental economic impacts. This research focuses on cases of "nonisolated" lightning which we define as one cell whose flashes have ceased although it is still embedded in weak composite reflectivity (Z ≥ 15 dBZ) with another cell that is still producing flashes. The objective is to determine if any radar-derived parameters provide useful information about the occurrence of lightning cessation in remnant storms. The data set consists of 50 warm season (May-September) nonisolated storms near KSC during 2013. The research utilizes the National Lightning Detection Network, the second generation Lightning Detection and Ranging network, and polarized radar data. These data are merged and analyzed using the Warning Decision Support System-Integrated Information at 1 min intervals. Our approach only considers 62 parameters, most of which are related to the noninductive charging mechanism. They included the presence of graupel at various thermal altitudes, maximum reflectivity of the decaying storm at thermal altitudes, maximum connecting composite reflectivity between the decaying cell and active cell, minutes since the previous flash, and several others. Results showed that none of the parameters reliably indicated lightning cessation for even our restrictive definition of nonisolated storms. Additional research is needed before cessation can be determined operationally with the high degree of accuracy required for safety.
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 variable-parameter nonlinear Muskingum model using excel solver
Kang, Ling; Zhou, Liwei
2018-02-01
Abstract . The Muskingum model is an effective flood routing technology in hydrology and water resources Engineering. With the development of optimization technology, more and more variable-parameter Muskingum models were presented to improve effectiveness of the Muskingum model in recent decades. A variable-parameter nonlinear Muskingum model (NVPNLMM) was proposed in this paper. According to the results of two real and frequently-used case studies by various models, the NVPNLMM could obtain better values of evaluation criteria, which are used to describe the superiority of the estimated outflows and compare the accuracies of flood routing using various models, and the optimal estimated outflows by the NVPNLMM were closer to the observed outflows than the ones by other models.
Modelling decremental ramps using 2- and 3-parameter "critical power" models.
Morton, R Hugh; Billat, Veronique
2013-01-01
The "Critical Power" (CP) model of human bioenergetics provides a valuable way to identify both limits of tolerance to exercise and mechanisms that underpin that tolerance. It applies principally to cycling-based exercise, but with suitable adjustments for analogous units it can be applied to other exercise modalities; in particular to incremental ramp exercise. It has not yet been applied to decremental ramps which put heavy early demand on the anaerobic energy supply system. This paper details cycling-based bioenergetics of decremental ramps using 2- and 3-parameter CP models. It derives equations that, for an individual of known CP model parameters, define those combinations of starting intensity and decremental gradient which will or will not lead to exhaustion before ramping to zero; and equations that predict time to exhaustion on those decremental ramps that will. These are further detailed with suitably chosen numerical and graphical illustrations. These equations can be used for parameter estimation from collected data, or to make predictions when parameters are known.
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......-parameter models with respect to the prediction of the maximum response during excitation and the geometrical damping related to free vibrations of a footing....
Parameter estimation of electricity spot models from futures prices
Aihara, ShinIchi; Bagchi, Arunabha; Imreizeeq, E.S.N.; Walter, E.
We consider a slight perturbation of the Schwartz-Smith model for the electricity futures prices and the resulting modified spot model. Using the martingale property of the modified price under the risk neutral measure, we derive the arbitrage free model for the spot and futures prices. We estimate
Theoretical values of various parameters in the Gummel-Poon model of a bipolar junction transistor
Benumof, R.; Zoutendyk, J.
1986-01-01
Various parameters in the Gummel-Poon model of a bipolar junction transistor are expressed in terms of the basic structure of a transistor. A consistent theoretical approach is used which facilitates an understanding of the foundations and limitations of the derived formulas. The results enable one to predict how changes in the geometry and composition of a transistor would affect performance.
Estimation of root water uptake parameters by inverse modeling with soil water content data
Hupet, F.; Lambot, S.; Feddes, R.A.; Dam, van J.C.; Vanclooster, M.
2003-01-01
In this paper we have tested the feasibility of the inverse modeling approach to derive root water uptake parameters (RWUP) from soil water content data using numerical experiments for three differently textured soils and for an optimal drying period. The RWUP of interest are the rooting depth and
Modelling the flyway of arctic breeding shorebirds; parameter estimation and sensitivity analysis
Ens, B.J.; Schekkerman, H.; Tulp, I.Y.M.; Bauer, S.; Klaassen, M.
2006-01-01
This report describes the derivation of parameter estimates for the model DYNAMIG for an arctic breeding shorebird, the Knot. DYNAMIG predicts the optimal spring migration of birds, like shorebirds and geese, that depend of a chain of discrete sites, to travel between their breeding grounds and
A method for model identification and parameter estimation
International Nuclear Information System (INIS)
Bambach, M; Heinkenschloss, M; Herty, M
2013-01-01
We propose and analyze a new method for the identification of a parameter-dependent model that best describes a given system. This problem arises, for example, in the mathematical modeling of material behavior where several competing constitutive equations are available to describe a given material. In this case, the models are differential equations that arise from the different constitutive equations, and the unknown parameters are coefficients in the constitutive equations. One has to determine the best-suited constitutive equations for a given material and application from experiments. We assume that the true model is one of the N possible parameter-dependent models. To identify the correct model and the corresponding parameters, we can perform experiments, where for each experiment we prescribe an input to the system and observe a part of the system state. Our approach consists of two stages. In the first stage, for each pair of models we determine the experiment, i.e. system input and observation, that best differentiates between the two models, and measure the distance between the two models. Then we conduct N(N − 1) or, depending on the approach taken, N(N − 1)/2 experiments and use the result of the experiments as well as the previously computed model distances to determine the true model. We provide sufficient conditions on the model distances and measurement errors which guarantee that our approach identifies the correct model. Given the model, we identify the corresponding model parameters in the second stage. The problem in the second stage is a standard parameter estimation problem and we use a method suitable for the given application. We illustrate our approach on three examples, including one where the models are elliptic partial differential equations with different parameterized right-hand sides and an example where we identify the constitutive equation in a problem from computational viscoplasticity. (paper)
International Nuclear Information System (INIS)
Bhartia, Mini; Chatterjee, Arun Kumar
2015-01-01
A 2D model for the potential distribution in silicon film is derived for a symmetrical double gate MOSFET in weak inversion. This 2D potential distribution model is used to analytically derive an expression for the subthreshold slope and threshold voltage. A drain current model for lightly doped symmetrical DG MOSFETs is then presented by considering weak and strong inversion regions including short channel effects, series source to drain resistance and channel length modulation parameters. These derived models are compared with the simulation results of the SILVACO (Atlas) tool for different channel lengths and silicon film thicknesses. Lastly, the effect of the fixed oxide charge on the drain current model has been studied through simulation. It is observed that the obtained analytical models of symmetrical double gate MOSFETs are in good agreement with the simulated results for a channel length to silicon film thickness ratio greater than or equal to 2. (paper)
Bhartia, Mini; Chatterjee, Arun Kumar
2015-04-01
A 2D model for the potential distribution in silicon film is derived for a symmetrical double gate MOSFET in weak inversion. This 2D potential distribution model is used to analytically derive an expression for the subthreshold slope and threshold voltage. A drain current model for lightly doped symmetrical DG MOSFETs is then presented by considering weak and strong inversion regions including short channel effects, series source to drain resistance and channel length modulation parameters. These derived models are compared with the simulation results of the SILVACO (Atlas) tool for different channel lengths and silicon film thicknesses. Lastly, the effect of the fixed oxide charge on the drain current model has been studied through simulation. It is observed that the obtained analytical models of symmetrical double gate MOSFETs are in good agreement with the simulated results for a channel length to silicon film thickness ratio greater than or equal to 2.
Energy Technology Data Exchange (ETDEWEB)
Jannik, T.
2013-03-14
The purpose of this report is twofold. The first is to develop a set of behavioral parameters for a reference person specific for the Savannah River Site (SRS) such that the parameters can be used to determine dose to members of the public in compliance with Department of Energy (DOE) Order 458.1 “Radiation Protection of the Public and the Environment.” A reference person is a hypothetical, gender and age aggregation of human physical and physiological characteristics arrived at by international consensus for the purpose of standardizing radiation dose calculations. DOE O 458.1 states that compliance with the annual dose limit of 100 mrem (1 mSv) to a member of the public may be demonstrated by calculating the dose to the maximally exposed individual (MEI) or to a representative person. Historically, for dose compliance, SRS has used the MEI concept, which uses adult dose coefficients and adult male usage parameters. Beginning with the 2012 annual site environmental report, SRS will be using the representative person concept for dose compliance. The dose to a representative person will be based on 1) the SRS-specific reference person usage parameters at the 95th percentile of appropriate national or regional data, which are documented in this report, 2) the reference person (gender and age averaged) ingestion and inhalation dose coefficients provided in DOE Derived Concentration Technical Standard (DOE-STD-1196-2011), and 3) the external dose coefficients provided in the DC_PAK3 toolbox. The second purpose of this report is to develop SRS-specific derived concentration standards (DCSs) for all applicable food ingestion pathways, ground shine, and water submersion. The DCS is the concentration of a particular radionuclide in water, in air, or on the ground that results in a member of the public receiving 100 mrem (1 mSv) effective dose following continuous exposure for one year. In DOE-STD-1196-2011, DCSs were developed for the ingestion of water, inhalation of
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)
A distributed approach for parameters estimation in System Biology models
International Nuclear Information System (INIS)
Mosca, E.; Merelli, I.; Alfieri, R.; Milanesi, L.
2009-01-01
Due to the lack of experimental measurements, biological variability and experimental errors, the value of many parameters of the systems biology mathematical models is yet unknown or uncertain. A possible computational solution is the parameter estimation, that is the identification of the parameter values that determine the best model fitting respect to experimental data. We have developed an environment to distribute each run of the parameter estimation algorithm on a different computational resource. The key feature of the implementation is a relational database that allows the user to swap the candidate solutions among the working nodes during the computations. The comparison of the distributed implementation with the parallel one showed that the presented approach enables a faster and better parameter estimation of systems biology models.
Photometric parameter maps of the Moon derived from LROC WAC images
Sato, H.; Robinson, M. S.; Hapke, B. W.; Denevi, B. W.; Boyd, A. K.
2013-12-01
Spatially resolved photometric parameter maps were computed from 21 months of Lunar Reconnaissance Orbiter Camera (LROC) Wide Angle Camera (WAC) images. Due to a 60° field-of-view (FOV), the WAC achieves nearly global coverage of the Moon each month with more than 50% overlap from orbit-to-orbit. From the repeat observations at various viewing and illumination geometries, we calculated Hapke bidirectional reflectance model parameters [1] for 1°x1° "tiles" from 70°N to 70°S and 0°E to 360°E. About 66,000 WAC images acquired from February 2010 to October 2011 were converted from DN to radiance factor (I/F) though radiometric calibration, partitioned into gridded tiles, and stacked in a time series (tile-by-tile method [2]). Lighting geometries (phase, incidence, emission) were computed using the WAC digital terrain model (100 m/pixel) [3]. The Hapke parameters were obtained by model fitting against I/F within each tile. Among the 9 parameters of the Hapke model, we calculated 3 free parameters (w, b, and hs) by setting constant values for 4 parameters (Bco=0, hc=1, θ, φ=0) and interpolating 2 parameters (c, Bso). In this simplification, we ignored the Coherent Backscatter Opposition Effect (CBOE) to avoid competing CBOE and Shadow Hiding Opposition Effect (SHOE). We also assumed that surface regolith porosity is uniform across the Moon. The roughness parameter (θ) was set to an averaged value from the equator (× 3°N). The Henyey-Greenstein double lobe function (H-G2) parameter (c) was given by the 'hockey stick' relation [4] (negative correlation) between b and c based on laboratory measurements. The amplitude of SHOE (Bso) was given by the correlation between w and Bso at the equator (× 3°N). Single scattering albedo (w) is strongly correlated to the photometrically normalized I/F, as expected. The c shows an inverse trend relative to b due to the 'hockey stick' relation. The parameter c is typically low for the maria (0.08×0.06) relative to the
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...
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 model predictions that persist despite calibrating the models to different calibration data and sample sizes. However, by directly accounting for the 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.
Transformations among CE–CVM model parameters for ...
Indian Academy of Sciences (India)
Unknown
parameters which exclusively represent interactions of the higher order systems. Such a procedure is presen- ted 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.
Transformations among CE–CVM model parameters for ...
Indian Academy of Sciences (India)
... 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.
Prior distributions for item parameters in IRT models
Matteucci, M.; S. Mignani, Prof.; Veldkamp, Bernard P.
2012-01-01
The focus of this article is on the choice of suitable prior distributions for item parameters within item response theory (IRT) models. In particular, the use of empirical prior distributions for item parameters is proposed. Firstly, regression trees are implemented in order to build informative
Checking the new IRI model The bottomside B parameters
Mosert, M; Ezquer, R; Lazo, B; Miro, G
2002-01-01
Electron density profiles obtained at Pruhonice (50.0, 15.0), El Arenosillo (37.1, 353.2) and Havana (23, 278) were used to check the bottom-side B parameters BO (thickness parameter) and B1 (shape parameter) predicted by the new IRI - 2000 version. The electron density profiles were derived from ionograms using the ARP technique. The data base includes daytime and nighttime ionograms recorded under different seasonal and solar activity conditions. Comparisons with IRI predictions were also done. The analysis shows that: a) The parameter B1 given by IRI 2000 reproduces better the observed ARP values than the IRI-90 version and b) The observed BO values are in general well reproduced by both IRI versions: IRI-90 and IRI-2000.
Catchment classification and model parameter transfer with a view to regionalisation
Ley, Rita; Hellebrand, Hugo; Casper, Markus C.
2013-04-01
Physiographic and climatic catchment characteristics are responsible for catchment response behaviour, whereas hydrological model parameters describe catchment properties in such a way to transform input data (here: precipitation, evaporation) to runoff, hence describing the response behaviour of a catchment. In this respect, model parameters can thus be seen as catchment descriptors. A third catchment descriptor is runoff behaviour, depicted by indices derived from event runoff coefficients and Flow Duration Curves. In an ongoing research project founded by the Deutsche Forschungsgemeinschaft (DFG), we investigate the interdependencies of these three catchment descriptors for catchment classification with a view to regionalisation. The study area comprises about 80 meso-scale catchments in western Germany. These catchments are classified by Self Organising Maps (SOM) based on a) runoff behaviour and b) physical and climatic properties. The two classifications show an overlap of about 80% for all catchments and indicate a direct connection between the two descriptors for a majority of the catchments. Next, all catchments are calibrated with a simple and parsimonious conceptual model, stemming from the Superflex model framework. In this study we test the interdependencies between the classification and the calibrated model parameters by parameter transfer within and between the classes established by SOM. The model simulates total discharge, given observed precipitation and pre-estimated potential evaporation. Simulations with a few catchments show encouraging results: all simulations with the calibrated model show a good fit, which is indicated by Nash Sutcliff coefficients of about 0.8. Most of the simulations of runoff time series for catchments with parameter sets belonging to their own class display good performances too, while simulated runoff with model parameter sets from other classes display significant lower performance. This indicates that there is a
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.
Agricultural and Environmental Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
Kaylie Rasmuson; Kurt Rautenstrauch
2003-06-20
This analysis is one of nine technical reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) biosphere model. It documents input parameters for the biosphere model, and supports the use of the model to develop Biosphere Dose Conversion Factors (BDCF). 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 the biosphere Technical Work Plan (TWP, BSC 2003a). It should be noted that some documents identified in Figure 1-1 may be under development and therefore not available at the time this document is issued. The ''Biosphere Model Report'' (BSC 2003b) describes the ERMYN and its input parameters. This analysis report, ANL-MGR-MD-000006, ''Agricultural and Environmental Input Parameters for the Biosphere Model'', is one of the five reports that develop input parameters for the biosphere model. This report defines and justifies values for twelve parameters required in the biosphere model. These parameters are related to use of contaminated groundwater to grow crops. The parameter values recommended in this report are used in the soil, plant, and carbon-14 submodels of the ERMYN.
Optimizing Performance Parameters of Chemically-Derived Graphene/p-Si Heterojunction Solar Cell.
Batra, Kamal; Nayak, Sasmita; Behura, Sanjay K; Jani, Omkar
2015-07-01
Chemically-derived graphene have been synthesized by modified Hummers method and reduced using sodium borohydride. To explore the potential for photovoltaic applications, graphene/p-silicon (Si) heterojunction devices were fabricated using a simple and cost effective technique called spin coating. The SEM analysis shows the formation of graphene oxide (GO) flakes which become smooth after reduction. The absence of oxygen containing functional groups, as observed in FT-IR spectra, reveals the reduction of GO, i.e., reduced graphene oxide (rGO). It was further confirmed by Raman analysis, which shows slight reduction in G-band intensity with respect to D-band. Hall effect measurement confirmed n-type nature of rGO. Therefore, an effort has been made to simu- late rGO/p-Si heterojunction device by using the one-dimensional solar cell capacitance software, considering the experimentally derived parameters. The detail analysis of the effects of Si thickness, graphene thickness and temperature on the performance of the device has been presented.
Resolution dependence of petrophysical parameters derived from X-ray tomography of chalk
Energy Technology Data Exchange (ETDEWEB)
Müter, D.; Sørensen, H. O.; Jha, D.; Harti, R.; Dalby, K. N.; Stipp, S. L. S. [Nano-Science Center, Department of Chemistry, University of Copenhagen, Universitetsparken 5, 2100 Copenhagen Ø (Denmark); Suhonen, H. [European Synchrotron Research Facility, Grenoble (France); Feidenhans' l, R. [Nano-Science Center, Niels Bohr Institute, University of Copenhagen, Universitetsparken 5, 2100 Copenhagen Ø (Denmark); Engstrøm, F. [Mærsk Oil and Gas A/S, Copenhagen K (Denmark)
2014-07-28
X-ray computed tomography data from chalk drill cuttings were taken over a series of voxel dimensions, ranging from 320 to 25 nm. From these data sets, standard petrophysical parameters (porosity, surface area, and permeability) were derived and we examined the effect of the voxel dimension (i.e., image resolution) on these properties. We found that for the higher voxel dimensions, they are severely over or underestimated, whereas for 50 and 25 nm voxel dimension, the resulting values (5%–30% porosity, 0.2–2 m{sup 2}/g specific surface area, and 0.06–0.34 mD permeability) are within the expected range for this type of rock. We compared our results to macroscopic measurements and in the case of surface area, also to measurements using the Brunauer-Emmett-Teller (BET) method and found that independent of the degree of compaction, the results from tomography amount to about 30% of the BET method. Finally, we concluded that at 25 nm voxel dimension, the essential features of the nanoscopic pore network in chalk are captured but better resolution is still needed to derive surface area.
Preliminary study of reasonableness of important parameters used in deriving OILs for PWR accidents
International Nuclear Information System (INIS)
Yongsheng, L.; Shongqi, S.
2004-01-01
Institute of nuclear energy technology, Tsinghua university, Beijing , China ,100084 Body of Abstract: This paper introduced the definition of operational intervention level (OIL) and the derived process of default OILs recommended by IAEA firstly. Then the paper focused on the reasonableness of two parameters, R1 and R2, which is assumed in derived process of default OIL1 and OIL2 in a reactor accident. The values of R1 and R2 were calculated by the calculating program of InterRas. The source item for computing includes the accidents PWR described in Wash-1400 and France severe accident source items, and furthermore the meteorological conditions for computing are classified to three classes, which are D stability class, A stability class, and F stability class with the mixing heights of 400 meters and 4 hour exposure to the plume. The wind speed is 3m/s, 2m/s and 1m/s correspond to the stability classes. The results show that the average values of R1 and R2 in the same accident series and different meteorological conditions derived by the calculating program of InterRas are close to the presumptive values. The results also indicated the rationalization of the default OIL1 and OIL2. On the other hand, the calculating results of different accidents have considerable disparity with the presumptive values in different distances and meteorological conditions, but the mutative trends are very well-regulated on distance and meteorological conditions. So the OILs recommended by IAEA are applicable to some specified conditions. At last the paper introduced the method of revising the default OILs in terms of measurement results. (Author)
Stochastic hyperelastic modeling considering dependency of material parameters
Caylak, Ismail; Penner, Eduard; Dridger, Alex; Mahnken, Rolf
2018-03-01
This paper investigates the uncertainty of a hyperelastic model by treating random material parameters as stochastic variables. For its stochastic discretization a polynomial chaos expansion (PCE) is used. An important aspect in our work is the consideration of stochastic dependencies in the stochastic modeling of Ogden's material model. To this end, artificial experiments are generated using the auto-regressive moving average process based on real experiments. The parameter identification for all data provides statistics of Ogden's material parameters, which are subsequently used for stochastic modeling. Stochastic dependencies are incorporated into the PCE using a Nataf transformation from dependent distributed random variables to independent standard normal distributed ones. The representative numerical example shows that our proposed method adequately takes into account the stochastic dependencies of Ogden's material parameters.
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)
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
Partial sum approaches to mathematical parameters of some growth models
Korkmaz, Mehmet
2016-04-01
Growth model is fitted by evaluating the mathematical parameters, a, b and c. In this study, the method of partial sums were used. For finding the mathematical parameters, firstly three partial sums were used, secondly four partial sums were used, thirdly five partial sums were used and finally N partial sums were used. The purpose of increasing the partial decomposition is to produce a better phase model which gives a better expected value by minimizing error sum of squares in the interval used.
Parameter estimation in stochastic rainfall-runoff models
DEFF Research Database (Denmark)
Jonsdottir, Harpa; Madsen, Henrik; Palsson, Olafur Petur
2006-01-01
A parameter estimation method for stochastic rainfall-runoff models is presented. The model considered in the paper is a conceptual stochastic model, formulated in continuous-discrete state space form. The model is small and a fully automatic optimization is, therefore, possible for estimating all....... 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...
Luminescence model with quantum impact parameter for low energy ions
Cruz-Galindo, H S; Martínez-Davalos, A; Belmont-Moreno, E; Galindo, S
2002-01-01
We have modified an analytical model of induced light production by energetic ions interacting in scintillating materials. The original model is based on the distribution of energy deposited by secondary electrons produced along the ion's track. The range of scattered electrons, and thus the energy distribution, depends on a classical impact parameter between the electron and the ion's track. The only adjustable parameter of the model is the quenching density rho sub q. The modification here presented, consists in proposing a quantum impact parameter that leads to a better fit of the model to the experimental data at low incident ion energies. The light output response of CsI(Tl) detectors to low energy ions (<3 MeV/A) is fitted with the modified model and comparison is made to the original model.
Agricultural and Environmental Input Parameters for the Biosphere Model
International Nuclear Information System (INIS)
K. Rasmuson; K. Rautenstrauch
2004-01-01
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
PARAMETER ESTIMATION AND MODEL SELECTION FOR INDOOR ENVIRONMENTS BASED ON SPARSE OBSERVATIONS
Directory of Open Access Journals (Sweden)
Y. Dehbi
2017-09-01
Full Text Available This paper presents a novel method for the parameter estimation and model selection for the reconstruction of indoor environments based on sparse observations. While most approaches for the reconstruction of indoor models rely on dense observations, we predict scenes of the interior with high accuracy in the absence of indoor measurements. We use a model-based top-down approach and incorporate strong but profound prior knowledge. The latter includes probability density functions for model parameters and sparse observations such as room areas and the building footprint. The floorplan model is characterized by linear and bi-linear relations with discrete and continuous parameters. We focus on the stochastic estimation of model parameters based on a topological model derived by combinatorial reasoning in a first step. A Gauss-Markov model is applied for estimation and simulation of the model parameters. Symmetries are represented and exploited during the estimation process. Background knowledge as well as observations are incorporated in a maximum likelihood estimation and model selection is performed with AIC/BIC. The likelihood is also used for the detection and correction of potential errors in the topological model. Estimation results are presented and discussed.
Parameter Estimation and Model Selection for Indoor Environments Based on Sparse Observations
Dehbi, Y.; Loch-Dehbi, S.; Plümer, L.
2017-09-01
This paper presents a novel method for the parameter estimation and model selection for the reconstruction of indoor environments based on sparse observations. While most approaches for the reconstruction of indoor models rely on dense observations, we predict scenes of the interior with high accuracy in the absence of indoor measurements. We use a model-based top-down approach and incorporate strong but profound prior knowledge. The latter includes probability density functions for model parameters and sparse observations such as room areas and the building footprint. The floorplan model is characterized by linear and bi-linear relations with discrete and continuous parameters. We focus on the stochastic estimation of model parameters based on a topological model derived by combinatorial reasoning in a first step. A Gauss-Markov model is applied for estimation and simulation of the model parameters. Symmetries are represented and exploited during the estimation process. Background knowledge as well as observations are incorporated in a maximum likelihood estimation and model selection is performed with AIC/BIC. The likelihood is also used for the detection and correction of potential errors in the topological model. Estimation results are presented and discussed.
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
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.
Updating parameters of the chicken processing line model
DEFF Research Database (Denmark)
Kurowicka, Dorota; Nauta, Maarten; Jozwiak, Katarzyna
2010-01-01
A mathematical model of chicken processing that quantitatively describes the transmission of Campylobacter on chicken carcasses from slaughter to chicken meat product has been developed in Nauta et al. (2005). This model was quantified with expert judgment. Recent availability of data allows...... updating parameters of the model to better describe processes observed in slaughterhouses. We propose Bayesian updating as a suitable technique to update expert judgment with microbiological data. Berrang and Dickens’s data are used to demonstrate performance of this method in updating parameters...... of the chicken processing line model....
Lumped-Parameter Models for Windturbine Footings on Layered Ground
DEFF Research Database (Denmark)
Andersen, Lars
The design of modern wind turbines is typically based on lifetime analyses using aeroelastic codes. In this regard, the impedance of the foundations must be described accurately without increasing the overall size of the computationalmodel significantly. This may be obtained by the fitting...... of a lumped-parameter model to the results of a rigorous model or experimental results. In this paper, guidelines are given for the formulation of such lumped-parameter models and examples are given in which the models are utilised for the analysis of a wind turbine supported by a surface footing on a layered...
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.
Parameter dependence and outcome dependence in dynamical models for state vector reduction
International Nuclear Information System (INIS)
Ghirardi, G.C.; Grassi, R.; Butterfield, J.; Fleming, G.N.
1993-01-01
The authors apply the distinction between parameter independence and outcome independence to the linear and nonlinear models of a recent nonrelativistic theory of continuous state vector reduction. It is shown that in the nonlinear model there is a set of realizations of the stochastic process that drives the state vector reduction for which parameter independence is violated for parallel spin components in the EPR-Bohm setup. Such a set has an appreciable probability of occurrence (∼ 1/2). On the other hand, the linear model exhibits only extremely small parameter dependence effects. Some specific features of the models are investigated and it is recalled that, as has been pointed out recently, to be able to speak of definite outcomes (or equivalently of possessed objective elements of reality) at finite times, the criteria for their attribution to physical systems must be slightly changed. The concluding section is devoted to a detailed discussion of the difficulties met when attempting to take, as a starting point for the formulation of a relativistic theory, a nonrelativistic scheme which exhibits parameter dependence. Here the authors derive a theorem which identifies the precise sense in which the occurrence of parameter dependence forbids a genuinely relativistic generalization. Finally, the authors show how the appreciable parameter dependence of the nonlinear model gives rise to problems with relativity, while the extremely weak parameter dependence of the linear model does not give rise to any difficulty, provided the appropriate criteria for the attribution of definite outcomes are taken into account. 19 refs
Bayesian parameter estimation in dynamic population model via particle Markov chain Monte Carlo
Directory of Open Access Journals (Sweden)
Meng Gao
2012-12-01
Full Text Available In nature, population dynamics are subject to multiple sources of stochasticity. State-space models (SSMs provide an ideal framework for incorporating both environmental noises and measurement errors into dynamic population models. In this paper, we present a recently developed method, Particle Markov Chain Monte Carlo (Particle MCMC, for parameter estimation in nonlinear SSMs. We use one effective algorithm of Particle MCMC, Particle Gibbs sampling algorithm, to estimate the parameters of a state-space model of population dynamics. The posterior distributions of parameters are derived given the conjugate prior distribution. Numerical simulations showed that the model parameters can be accurately estimated, no matter the deterministic model is stable, periodic or chaotic. Moreover, we fit the model to 16 representative time series from Global Population Dynamics Database (GPDD. It is verified that the results of parameter and state estimation using Particle Gibbs sampling algorithm are satisfactory for a majority of time series. For other time series, the quality of parameter estimation can also be improved, if prior knowledge is constrained. In conclusion, Particle Gibbs sampling algorithm provides a new Bayesian parameter inference method for studying population dynamics.
Improving weather predictability by including land-surface model parameter uncertainty
Orth, Rene; Dutra, Emanuel; Pappenberger, Florian
2016-04-01
The land surface forms an important component of Earth system models and interacts nonlinearly with other parts such as ocean and atmosphere. To capture the complex and heterogenous hydrology of the land surface, land surface models include a large number of parameters impacting the coupling to other components of the Earth system model. Focusing on ECMWF's land-surface model HTESSEL we present in this study a comprehensive parameter sensitivity evaluation using multiple observational datasets in Europe. We select 6 poorly constrained effective parameters (surface runoff effective depth, skin conductivity, minimum stomatal resistance, maximum interception, soil moisture stress function shape, total soil depth) and explore their sensitivity to model outputs such as soil moisture, evapotranspiration and runoff using uncoupled simulations and coupled seasonal forecasts. Additionally we investigate the possibility to construct ensembles from the multiple land surface parameters. In the uncoupled runs we find that minimum stomatal resistance and total soil depth have the most influence on model performance. Forecast skill scores are moreover sensitive to the same parameters as HTESSEL performance in the uncoupled analysis. We demonstrate the robustness of our findings by comparing multiple best performing parameter sets and multiple randomly chosen parameter sets. We find better temperature and precipitation forecast skill with the best-performing parameter perturbations demonstrating representativeness of model performance across uncoupled (and hence less computationally demanding) and coupled settings. Finally, we construct ensemble forecasts from ensemble members derived with different best-performing parameterizations of HTESSEL. This incorporation of parameter uncertainty in the ensemble generation yields an increase in forecast skill, even beyond the skill of the default system. Orth, R., E. Dutra, and F. Pappenberger, 2016: Improving weather predictability by
Deriving minimal models for resource utilization
te Brinke, Steven; Bockisch, Christoph; Bergmans, Lodewijk; Malakuti Khah Olun Abadi, Somayeh; Aksit, Mehmet; Katz, Shmuel
2013-01-01
We show how compact Resource Utilization Models (RUMs) can be extracted from concrete overly-detailed models of systems or sub-systems in order to model energy-aware software. Using the Counterexample-Guided Abstraction Refinement (CEGAR) approach, along with model-checking tools, abstract models
Howard, B J; Wells, C; Barnett, C L
2016-04-01
Under the MODARIA (Modelling and Data for Radiological Impact Assessments Programme of the International Atomic Energy Agency), there has been an initiative to improve the derivation, provenance and transparency of transfer parameter values for radionuclides. The approach taken for animal products is outlined here and the first revised table for goat milk is provided. Data from some references used in TRS 472 were removed and reasons given for removal. Particular efforts were made to improve the number of CR (concentration ratio) values which have some advantages over transfer coefficients. There is little difference in most of the new CR and Fm (transfer coefficient) values for goat milk compared with those in TRS 472. In TRS 472, 21 CR values were reported for goat milk. In the 2015 dataset for goat milk CR values for a further 14 elements are now included. The CR and Fm values for only one element (Co) were removed. Copyright © 2016 Elsevier Ltd. All rights reserved.
Development of new model for high explosives detonation parameters calculation
Directory of Open Access Journals (Sweden)
Jeremić Radun
2012-01-01
Full Text Available The simple semi-empirical model for calculation of detonation pressure and velocity for CHNO explosives has been developed, which is based on experimental values of detonation parameters. Model uses Avakyan’s method for determination of detonation products' chemical composition, and is applicable in wide range of densities. Compared with the well-known Kamlet's method and numerical model of detonation based on BKW EOS, the calculated values from proposed model have significantly better accuracy.
Microphysically Derived Expressions for Rate-and-State Friction Parameters, a, b, and Dc
Chen, Jianye; Niemeijer, A. R.; Spiers, Christopher J.
2017-12-01
Rate-and-state friction (RSF) laws are extensively applied in fault mechanics but have a largely empirical basis reflecting only limited understanding of the underlying physical mechanisms. We recently proposed a microphysical model describing the frictional behavior of a granular fault gouge undergoing deformation in terms of granular flow accompanied by thermally activated creep and intergranular sliding at grain contacts. Numerical solutions reproduced typical experimental results well. Here we extend our model to obtain physically meaningful, analytical expressions for the steady state frictional strength and standard RSF parameters, a, b, and Dc. The frictional strength contains two components, namely, grain boundary friction and friction due to intergranular dilatation. The expressions obtained for a and b linearly reflect the rate dependence of these two terms. Dc scales with slip band thickness and varies only slightly with velocity. The values of a, b, and Dc predicted show quantitative agreement with previous experimental results, and inserting their values into classical RSF laws gives simulated friction behavior that is consistent with the predictions of our numerically implemented model for small departures from steady state. For large velocity steps, the model produces mixed RSF behavior that falls between the Slowness and Slip laws, for example, with an intermediate equivalent slip(-weakening) distance d0. Our model possesses the interesting property not only that a and b are velocity dependent but also that Dc and d0 scale differently from classical RSF models, potentially explaining behaviour seen in many hydrothermal friction experiments and having substantial implications for natural fault friction.
On the performance of fish stock parameters derived from VIT pseudo-cohort analysis
Directory of Open Access Journals (Sweden)
Hans-Joachim Rätz
2010-03-01
Full Text Available The comparison of VIT model results with those of the virtual population analysis assessment of the cod stock in the Skagerrak, North Sea and Eastern Channel established by the International Council for the Exploration of the Sea (ICES reveal that overall trends in fishing mortality and stock size are well captured over a period of three decades (1963-1992. However, the implications of the equilibrium assumption (steady state made by the VIT model are enormous, as it forces strong inter-annual variations in the estimated fishing mortality, especially in years when the age composition shows strong year class effects. Estimated VIT output parameters should be carefully interpreted when the assessed stock suffers from reduction in abundance and high exploitation, as this condition is likely to deviate from steady state. The VIT estimates of the virgin stock biomass appear very variable, extremely high and fairly dependent on annual stock size estimates. Their use in fisheries management as a realistic biological stock biomass reference is not recommended. The VIT estimates of F0.1 and Fmax are found to be in line with the ICES estimates. Therefore, model results should allow qualitative conclusions regarding the status of marine living resources in relation to a target reference of exploitation rate. Quantitative conclusions regarding the assessment of the exploitation status are only recommended when the model is applied to short time series of consecutive annual data and the resulting variation in the estimated stock parameters appears reasonably low. As such, the model results may form the basis for scientifically sound fisheries management advice covering the actual state of the stock as well as medium-term forecasts of catch and biomass under different options.
Environmental Transport Input Parameters for the Biosphere Model
International Nuclear Information System (INIS)
M. Wasiolek
2004-01-01
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 was performed in accordance with the TWP (BSC 2004 [DIRS 169573])
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
Inhalation Exposure Input Parameters for the Biosphere Model
International Nuclear Information System (INIS)
K. Rautenstrauch
2004-01-01
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
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
International Nuclear Information System (INIS)
Wasiolek, M. A.
2003-01-01
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], Section 6.2). Parameter values
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
Parameter determination for singlet oxygen modeling of BPD-mediated PDT
McMillan, Dayton D.; Chen, Daniel; Kim, Michele M.; Liang, Xing; Zhu, Timothy C.
2013-03-01
Photodynamic therapy (PDT) offers a cancer treatment modality capable of providing minimally invasive localized tumor necrosis. To accurately predict PDT treatment outcome based on pre-treatment patient specific parameters, an explicit dosimetry model is used to calculate apparent reacted 1O2 concentration ([1O2]rx) at varied radial distances from the activating light source inserted into tumor tissue and apparent singlet oxygen threshold concentration for necrosis ([1O2]rx, sd) for type-II PDT photosensitizers. Inputs into the model include a number of photosensitizer independent parameters as well as photosensitizer specific photochemical parameters ξ σ, and β. To determine the specific photochemical parameters of benzoporphyrin derivative monoacid A (BPD), mice were treated with BPDPDT with varied light source strengths and treatment times. All photosensitizer independent inputs were assessed pre-treatment and average necrotic radius in treated tissue was determined post-treatment. Using the explicit dosimetry model, BPD specific ξ σ, and β photochemical parameters were determined which estimated necrotic radii similar to those observed in initial BPD-PDT treated mice using an optimization algorithm that minimizes the difference between the model and that of the measurements. Photochemical parameters for BPD are compared with those of other known photosensitizers, such as Photofrin. The determination of these BPD specific photochemical parameters provides necessary data for predictive treatment outcome in clinical BPD-PDT using the explicit dosimetry model.
Sensor placement for calibration of spatially varying model parameters
Nath, Paromita; Hu, Zhen; Mahadevan, Sankaran
2017-08-01
This paper presents a sensor placement optimization framework for the calibration of spatially varying model parameters. To account for the randomness of the calibration parameters over space and across specimens, the spatially varying parameter is represented as a random field. Based on this representation, Bayesian calibration of spatially varying parameter is investigated. To reduce the required computational effort during Bayesian calibration, the original computer simulation model is substituted with Kriging surrogate models based on the singular value decomposition (SVD) of the model response and the Karhunen-Loeve expansion (KLE) of the spatially varying parameters. A sensor placement optimization problem is then formulated based on the Bayesian calibration to maximize the expected information gain measured by the expected Kullback-Leibler (K-L) divergence. The optimization problem needs to evaluate the expected K-L divergence repeatedly which requires repeated calibration of the spatially varying parameter, and this significantly increases the computational effort of solving the optimization problem. To overcome this challenge, an approximation for the posterior distribution is employed within the optimization problem to facilitate the identification of the optimal sensor locations using the simulated annealing algorithm. A heat transfer problem with spatially varying thermal conductivity is used to demonstrate the effectiveness of the proposed method.
Procedures for parameter estimates of computational models for localized failure
Iacono, C.
2007-01-01
In the last years, many computational models have been developed for tensile fracture in concrete. However, their reliability is related to the correct estimate of the model parameters, not all directly measurable during laboratory tests. Hence, the development of inverse procedures is needed, that
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.
Deloule, Francoise
A machine shop design based on the Merise method is derived. The parameters of the physical system are identified and evaluated. Modeling and simulation are used as complementary methods to solve the problems created by the simultaneous variation of a large number of parameters. The specifications of machines and other elements implementing the flexible shop are obtained. A structured process to optimize the utilization of modeling and simulation is presented. It is shown that for given criteria the solution is close to the optimum.
Improving the realism of hydrologic model through multivariate parameter estimation
Rakovec, Oldrich; Kumar, Rohini; Attinger, Sabine; Samaniego, Luis
2017-04-01
Increased availability and quality of near real-time observations should improve understanding of predictive skills of hydrological models. Recent studies have shown the limited capability of river discharge data alone to adequately constrain different components of distributed model parameterizations. In this study, the GRACE satellite-based total water storage (TWS) anomaly is used to complement the discharge data with an aim to improve the fidelity of mesoscale hydrologic model (mHM) through multivariate parameter estimation. The study is conducted in 83 European basins covering a wide range of hydro-climatic regimes. The model parameterization complemented with the TWS anomalies leads to statistically significant improvements in (1) discharge simulations during low-flow period, and (2) evapotranspiration estimates which are evaluated against independent (FLUXNET) data. Overall, there is no significant deterioration in model performance for the discharge simulations when complemented by information from the TWS anomalies. However, considerable changes in the partitioning of precipitation into runoff components are noticed by in-/exclusion of TWS during the parameter estimation. A cross-validation test carried out to assess the transferability and robustness of the calibrated parameters to other locations further confirms the benefit of complementary TWS data. In particular, the evapotranspiration estimates show more robust performance when TWS data are incorporated during the parameter estimation, in comparison with the benchmark model constrained against discharge only. This study highlights the value for incorporating multiple data sources during parameter estimation to improve the overall realism of hydrologic model and its applications over large domains. Rakovec, O., Kumar, R., Attinger, S. and Samaniego, L. (2016): Improving the realism of hydrologic model functioning through multivariate parameter estimation. Water Resour. Res., 52, http://dx.doi.org/10
Ground level enhancement (GLE) energy spectrum parameters model
Qin, G.; Wu, S.
2017-12-01
We study the ground level enhancement (GLE) events in solar cycle 23 with the four energy spectra parameters, the normalization parameter C, low-energy power-law slope γ 1, high-energy power-law slope γ 2, and break energy E0, obtained by Mewaldt et al. 2012 who fit the observations to the double power-law equation. we divide the GLEs into two groups, one with strong acceleration by interplanetary (IP) shocks and another one without strong acceleration according to the condition of solar eruptions. We next fit the four parameters with solar event conditions to get models of the parameters for the two groups of GLEs separately. So that we would establish a model of energy spectrum for GLEs for the future space weather prediction.
Determination of appropriate models and parameters for premixing calculations
Energy Technology Data Exchange (ETDEWEB)
Park, Ik-Kyu; Kim, Jong-Hwan; Min, Beong-Tae; Hong, Seong-Wan
2008-03-15
The purpose of the present work is to use experiments that have been performed at Forschungszentrum Karlsruhe during about the last ten years for determining the most appropriate models and parameters for premixing calculations. The results of a QUEOS experiment are used to fix the parameters concerning heat transfer. The QUEOS experiments are especially suited for this purpose as they have been performed with small hot solid spheres. Therefore the area of heat exchange is known. With the heat transfer parameters fixed in this way, a PREMIX experiment is recalculated. These experiments have been performed with molten alumina (Al{sub 2}O{sub 3}) as a simulant of corium. Its initial temperature is 2600 K. With these experiments the models and parameters for jet and drop break-up are tested.
International Nuclear Information System (INIS)
Amendola, Luca; Campos, Gabriela Camargo; Rosenfeld, Rogerio
2007-01-01
Models where the dark matter component of the Universe interacts with the dark energy field have been proposed as a solution to the cosmic coincidence problem, since in the attractor regime both dark energy and dark matter scale in the same way. In these models the mass of the cold dark matter particles is a function of the dark energy field responsible for the present acceleration of the Universe, and different scenarios can be parametrized by how the mass of the cold dark matter particles evolves with time. In this article we study the impact of a constant coupling δ between dark energy and dark matter on the determination of a redshift dependent dark energy equation of state w DE (z) and on the dark matter density today from SNIa data. We derive an analytical expression for the luminosity distance in this case. In particular, we show that the presence of such a coupling increases the tension between the cosmic microwave background data from the analysis of the shift parameter in models with constant w DE and SNIa data for realistic values of the present dark matter density fraction. Thus, an independent measurement of the present dark matter density can place constraints on models with interacting dark energy
A Derivative Based Estimator for Semiparametric Index Models
Donkers, A.C.D.; Schafgans, M.
2003-01-01
This paper proposes a semiparametric estimator for single- and multiple index models.It provides an extension of the average derivative estimator to the multiple index model setting.The estimator uses the average of the outer product of derivatives and is shown to be root-N consistent and
Remarks on the microscopic derivation of the collective model
International Nuclear Information System (INIS)
Toyoda, T.; Wildermuth, K.
1984-01-01
The rotational part of the phenomenological collective model of Bohr and Mottelson and others is derived microscopically, starting with the Schrodinger equation written in projection form and introducing a new set of 'relative Euler angles'. In order to derive the local Schrodinger equation of the collective model, it is assumed that the intrinsic wave functions give strong peaking properties to the overlapping kernels
Directory of Open Access Journals (Sweden)
G. Heuvelmans
2004-01-01
Full Text Available Operational applications of a hydrological model often require the prediction of stream flow in (future time periods without stream flow observations or in ungauged catchments. Data for a case-specific optimisation of model parameters are not available for such applications, so parameters have to be derived from other catchments or time periods. It has been demonstrated that for applications of the SWAT in Northern Belgium, temporal transfers of the parameters have less influence than spatial transfers on the performance of the model. This study examines the spatial variation in parameter optima in more detail. The aim was to delineate zones wherein model parameters can be transferred without a significant loss of model performance. SWAT was calibrated for 25 catchments that are part of eight larger sub-basins of the Scheldt river basin. Two approaches are discussed for grouping these units in zones with a uniform set of parameters: a single parameter approach considering each parameter separately and a parameter set approach evaluating the parameterisation as a whole. For every catchment, the SWAT model was run with the local parameter optima, with the average parameter values for the entire study region (Flanders, with the zones delineated with the single parameter approach and with the zones obtained by the parameter set approach. Comparison of the model performances of these four parameterisation strategies indicates that both the single parameter and the parameter set zones lead to stream flow predictions that are more accurate than if the entire study region were treated as one single zone. On the other hand, the use of zonal average parameter values results in a considerably worse model fit compared to local parameter optima. Clustering of parameter sets gives a more accurate result than the single parameter approach and is, therefore, the preferred technique for use in the parameterisation of ungauged sub-catchments as part of the
Soil-related Input Parameters for the Biosphere Model
International Nuclear Information System (INIS)
A. J. Smith
2003-01-01
This analysis is one of the technical reports containing documentation of 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. The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A graphical representation of the documentation hierarchy for the ERMYN biosphere model 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 2003 [163602]). It should be noted that some documents identified in Figure 1-1 may be under development at the time this report is issued and therefore not available. This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this report. This report, ''Soil Related Input Parameters for the Biosphere Model'', is one of the five analysis reports that develop input parameters for use in the ERMYN model. This report is the source documentation for the six biosphere parameters identified in Table 1-1. ''The Biosphere Model Report'' (BSC 2003 [160699]) describes in detail the conceptual model as well as the mathematical model and its input parameters. The purpose of this analysis was to develop the biosphere model parameters needed to evaluate doses from pathways associated with the accumulation and depletion of radionuclides in the soil. These parameters support the calculation of radionuclide concentrations in soil from on-going irrigation and ash
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.
Sensor-derived physical activity parameters can predict future falls in people with dementia.
Schwenk, Michael; Hauer, Klaus; Zieschang, Tania; Englert, Stefan; Mohler, Jane; Najafi, Bijan
2014-01-01
There is a need for simple clinical tools that can objectively assess the fall risk in people with dementia. Wearable sensors seem to have the potential for fall prediction; however, there has been limited work performed in this important area. To explore the validity of sensor-derived physical activity (PA) parameters for predicting future falls in people with dementia. To compare sensor-based fall risk assessment with conventional fall risk measures. This was a cohort study of people with confirmed dementia discharged from a geriatric rehabilitation ward. PA was quantified using 24-hour motion-sensor monitoring at the beginning of the study. PA parameters (percentage of walking, standing, sitting, and lying; duration of single walking, standing, and sitting bouts) were extracted using specific algorithms. Conventional assessment included performance-based tests (Timed Up and Go Test, Performance-Oriented Mobility Assessment, 5-chair stand) and questionnaires (cognition, ADL status, fear of falling, depression, previous faller). Outcome measures were fallers (at least one fall in the 3-month follow-up period) versus non-fallers. 77 people were included in the study (age 81.8 ± 6.3; community-dwelling 88%, institutionalized 12%). Surprisingly, fallers and non-fallers did not differ on any conventional assessment (p = 0.069-0.991), except for 'previous faller' (p = 0.006). Interestingly, several PA parameters discriminated between the groups. The 'walking bout average duration', 'longest walking bout duration' and 'walking bout duration variability' were lower in fallers, compared to non-fallers (p = 0.008-0.027). The 'standing bout average duration' was higher in fallers (p = 0.050). Two variables, 'walking bout average duration' [odds ratio (OR) 0.79, p = 0.012] and 'previous faller' (OR 4.44, p = 0.007) were identified as independent predictors for falls. The OR for a 'walking bout average duration' risk and may have higher diagnostic accuracy in persons with
Directory of Open Access Journals (Sweden)
Claudia Kratzenstein
2013-07-01
Full Text Available We investigate the Oneshot Optimization strategy introduced by Hamdi and Griewank for the applicability and efficiency to identify parameters in models of the earth's climate system. Parameters of a box model of the North Atlantic Thermohaline Circulation are optimized with respect to the fit of model output to data given by another model of intermediate complexity. Since the model is run into a steady state by a pseudo time-stepping, efficient techniques are necessary to avoid extensive recomputations or storing when using gradient-based local optimization algorithms. The Oneshot approach simultaneously updates state, adjoint and parameter values. For the required partial derivatives, the algorithmic/automatic differentiation tool TAF was used. Numerical results are compared to results obtained by the BFGS-quasi-Newton method.
Modeling Chinese ionospheric layer parameters based on EOF analysis
Yu, You; Wan, Weixing
2016-04-01
Using 24-ionosonde observations in and around China during the 20th solar cycle, an assimilative model is constructed to map the ionospheric layer parameters (foF2, hmF2, M(3000)F2, and foE) over China based on empirical orthogonal function (EOF) analysis. First, we decompose the background maps from the International Reference Ionosphere model 2007 (IRI-07) into different EOF modes. The obtained EOF modes consist of two factors: the EOF patterns and the corresponding EOF amplitudes. These two factors individually reflect the spatial distributions (e.g., the latitudinal dependence such as the equatorial ionization anomaly structure and the longitude structure with east-west difference) and temporal variations on different time scales (e.g., solar cycle, annual, semiannual, and diurnal variations) of the layer parameters. Then, the EOF patterns and long-term observations of ionosondes are assimilated to get the observed EOF amplitudes, which are further used to construct the Chinese Ionospheric Maps (CIMs) of the layer parameters. In contrast with the IRI-07 model, the mapped CIMs successfully capture the inherent temporal and spatial variations of the ionospheric layer parameters. Finally, comparison of the modeled (EOF and IRI-07 model) and observed values reveals that the EOF model reproduces the observation with smaller root-mean-square errors and higher linear correlation co- efficients. In addition, IRI discrepancy at the low latitude especially for foF2 is effectively removed by EOF model.
Parameters and variables appearing in repository design models
International Nuclear Information System (INIS)
Curtis, R.H.; Wart, R.J.
1983-12-01
This report defines the parameters and variables appearing in repository design models and presents typical values and ranges of values of each. Areas covered by this report include thermal, geomechanical, and coupled stress and flow analyses in rock. Particular emphasis is given to conductivity, radiation, and convection parameters for thermal analysis and elastic constants, failure criteria, creep laws, and joint properties for geomechanical analysis. The data in this report were compiled to help guide the selection of values of parameters and variables to be used in code benchmarking. 102 references, 33 figures, 51 tables
Energy Technology Data Exchange (ETDEWEB)
McDermid, Richard M. [Department of Physics and Astronomy, Macquarie University, Sydney NSW 2109 (Australia); Cappellari, Michele; Bayet, Estelle; Bureau, Martin; Davies, Roger L. [Sub-Department of Astrophysics, Department of Physics, University of Oxford, Denys Wilkinson Building, Keble Road, Oxford, OX1 3RH (United Kingdom); Alatalo, Katherine [Infrared Processing and Analysis Center, California Institute of Technology, Pasadena, CA 91125 (United States); Blitz, Leo [Department of Astronomy, Campbell Hall, University of California, Berkeley, CA 94720 (United States); Bois, Maxime [Observatoire de Paris, LERMA and CNRS, 61 Av. de l' Observatoire, F-75014 Paris (France); Bournaud, Frédéric; Duc, Pierre-Alain [Laboratoire AIM Paris-Saclay, CEA/IRFU/SAp- CNRS-Université Paris Diderot, F-91191 Gif-sur-Yvette Cedex (France); Crocker, Alison F. [Ritter Astrophysical Observatory, University of Toledo, Toledo, OH 43606 (United States); Davis, Timothy A.; De Zeeuw, P. T.; Emsellem, Eric; Kuntschner, Harald [European Southern Observatory, Karl-Schwarzschild-Str. 2, D-85748 Garching (Germany); Khochfar, Sadegh [Institute for Astronomy, University of Edinburgh, Royal Observatory, Edinburgh, EH9 3HJ (United Kingdom); Krajnović, Davor [Leibniz-Institut für Astrophysik Potsdam (AIP), An der Sternwarte 16, D-14482 Potsdam (Germany); Morganti, Raffaella; Oosterloo, Tom [Netherlands Institute for Radio Astronomy (ASTRON), Postbus 2, 7990 AA Dwingeloo (Netherlands); Naab, Thorsten, E-mail: richard.mcdermid@mq.edu.au [Max-Planck-Institut für Astrophysik, Karl-Schwarzschild-Str. 1, D-85741 Garching (Germany); and others
2014-09-10
We report on empirical trends between the dynamically determined stellar initial mass function (IMF) and stellar population properties for a complete, volume-limited sample of 260 early-type galaxies from the ATLAS{sup 3D} project. We study trends between our dynamically derived IMF normalization α{sub dyn} ≡ (M/L){sub stars}/(M/L){sub Salp} and absorption line strengths, and interpret these via single stellar population-equivalent ages, abundance ratios (measured as [α/Fe]), and total metallicity, [Z/H]. We find that old and alpha-enhanced galaxies tend to have on average heavier (Salpeter-like) mass normalization of the IMF, but stellar population does not appear to be a good predictor of the IMF, with a large range of α{sub dyn} at a given population parameter. As a result, we find weak α{sub dyn}-[α/Fe] and α{sub dyn} –Age correlations and no significant α{sub dyn} –[Z/H] correlation. The observed trends appear significantly weaker than those reported in studies that measure the IMF normalization via the low-mass star demographics inferred through stellar spectral analysis.
A fractal derivative constitutive model for three stages in granite creep
Directory of Open Access Journals (Sweden)
R. Wang
Full Text Available In this paper, by replacing the Newtonian dashpot with the fractal dashpot and considering damage effect, a new constitutive model is proposed in terms of time fractal derivative to describe the full creep regions of granite. The analytic solutions of the fractal derivative creep constitutive equation are derived via scaling transform. The conventional triaxial compression creep tests are performed on MTS 815 rock mechanics test system to verify the efficiency of the new model. The granite specimen is taken from Beishan site, the most potential area for the China’s high-level radioactive waste repository. It is shown that the proposed fractal model can characterize the creep behavior of granite especially in accelerating stage which the classical models cannot predict. The parametric sensitivity analysis is also conducted to investigate the effects of model parameters on the creep strain of granite. Keywords: Beishan granite, Fractal derivative, Damage evolution, Scaling transformation
Energy balance and the Malthusian parameter, m, of grazing small rodents : A graphic model.
Stenseth, Nils Chr
1978-01-01
A graphic model based on cost and gain functions is developed for predicting the relative magnitude of the Malthusian parameter, m, for different phenotypes. The analysis is mainly restricted to grazing small rodents. The cost function is derived by depicting the probability of death due to predation, parasitism etc. as a function of time spent outside the nest. The gain function is derived by comparing the energy obtained by digestion, with energy used (or needed) for maintenance metabolism, both when outside and inside the nest.The model is applied for predicting the relative magnitude of the Malthusian parameter of small versus large phenotypes of grazing rodents. Of these, the smaller phenotypes are concluded to have the larger Malthusian parameter. This may not hold true for hunters (granivores and predators). These conclusions are used for reinterpreting the often observed geographical size trend in warm-blooded vertebrates (Bergmann's rule).The model is further applied to the determination of the relative magnitude of the Malthusian parameter for aggresive and docile strategies hypothesized in Chitty's theory for fluctuating populations. Of these, the aggressive strategy is concluded to have the lowest Malthusian parameter. Although not verifying Chitty's theory, these results support the earlier hypothesis that the aggressive strategy may under certain situations have lower survival. Based on the present model, nothing can be said about whether or not a polymorphic population as hypothesized by Chitty will exhibit oscillations.
A lumped parameter, low dimension model of heat exchanger
International Nuclear Information System (INIS)
Kanoh, Hideaki; Furushoo, Junji; Masubuchi, Masami
1980-01-01
This paper reports on the results of investigation of the distributed parameter model, the difference model, and the model of the method of weighted residuals for heat exchangers. By the method of weighted residuals (MWR), the opposite flow heat exchanger system is approximated by low dimension, lumped parameter model. By assuming constant specific heat, constant density, the same form of tube cross-section, the same form of the surface of heat exchange, uniform flow velocity, the linear relation of heat transfer to flow velocity, liquid heat carrier, and the thermal insulation of liquid from outside, fundamental equations are obtained. The experimental apparatus was made of acrylic resin. The response of the temperature at the exit of first liquid to the variation of the flow rate of second liquid was measured and compared with the models. The MWR model shows good approximation for the low frequency region, and as the number of division increases, good approximation spreads to higher frequency region. (Kato, T.)
Dimitrov, Marin
2014-01-01
We coupled a radiative transfer model and a soil hydrologic model (HYDRUS 1D) with an optimization routine to derive soil hydraulic parameters, surface roughness, and soil moisture of a tilled bare soil plot using measured brightness temperatures at 1.4 GHz (L-band), rainfall, and potential soil evaporation. The robustness of the approach was evaluated using five 28-d data sets representing different meteorological conditions. We considered two soil hydraulic property models: the unimodal Mualem-van Genuchten and the bimodal model of Durner. Microwave radiative transfer was modeled by three different approaches: the Fresnel equation with depth-averaged dielectric permittivity of either 2-or 5-cm-thick surface layers and a coherent radiative transfer model (CRTM) that accounts for vertical gradients in dielectric permittivity. Brightness temperatures simulated by the CRTM and the 2-cm-layer Fresnel model fitted well to the measured ones. L-band brightness temperatures are therefore related to the dielectric permittivity and soil moisture in a 2-cm-thick surface layer. The surface roughness parameter that was derived from brightness temperatures using inverse modeling was similar to direct estimates from laser profiler measurements. The laboratory-derived water retention curve was bimodal and could be retrieved consistently for the different periods from brightness temperatures using inverse modeling. A unimodal soil hydraulic property function underestimated the hydraulic conductivity near saturation. Surface soil moisture contents simulated using retrieved soil hydraulic parameters were compared with in situ measurements. Depth-specific calibration relations were essential to derive soil moisture from near-surface installed sensors. © Soil Science Society of America 5585 Guilford Rd., Madison, WI 53711 USA.
SAC-SMA a priori parameter differences and their impact on distributed hydrologic model simulations
Zhang, Ziya; Koren, Victor; Reed, Seann; Smith, Michael; Zhang, Yu; Moreda, Fekadu; Cosgrove, Brian
2012-02-01
SummaryDeriving a priori gridded parameters is an important step in the development and deployment of an operational distributed hydrologic model. Accurate a priori parameters can reduce the manual calibration effort and/or speed up the automatic calibration process, reduce calibration uncertainty, and provide valuable information at ungauged locations. Underpinned by reasonable parameter data sets, distributed hydrologic modeling can help improve water resource and flood and flash flood forecasting capabilities. Initial efforts at the National Weather Service Office of Hydrologic Development (NWS OHD) to derive a priori gridded Sacramento Soil Moisture Accounting (SAC-SMA) model parameters for the conterminous United States (CONUS) were based on a relatively coarse resolution soils property database, the State Soil Geographic Database (STATSGO) (Soil Survey Staff, 2011) and on the assumption of uniform land use and land cover. In an effort to improve the parameters, subsequent work was performed to fully incorporate spatially variable land cover information into the parameter derivation process. Following that, finer-scale soils data (the county-level Soil Survey Geographic Database (SSURGO) ( Soil Survey Staff, 2011a,b), together with the use of variable land cover data, were used to derive a third set of CONUS, a priori gridded parameters. It is anticipated that the second and third parameter sets, which incorporate more physical data, will be more realistic and consistent. Here, we evaluate whether this is actually the case by intercomparing these three sets of a priori parameters along with their associated hydrologic simulations which were generated by applying the National Weather Service Hydrology Laboratory's Research Distributed Hydrologic Model (HL-RDHM) ( Koren et al., 2004) in a continuous fashion with an hourly time step. This model adopts a well-tested conceptual water balance model, SAC-SMA, applied on a regular spatial grid, and links to physically
Directory of Open Access Journals (Sweden)
S. I. Bartsev
2015-06-01
Full Text Available A possible method for experimental determination of parameters of the previously proposed continual mathematical model of soil organic matter transformation is theoretically considered in this paper. The previously proposed by the authors continual model of soil organic matter transformation, based on using the rate of matter transformation as a continual scale of its recalcitrance, describes the transformation process phenomenologically without going into detail of microbiological mechanisms of transformation. Thereby simplicity of the model is achieved. The model is represented in form of one differential equation in firstorder partial derivatives, which has an analytical solution in elementary functions. The model equation contains a small number of empirical parameters which generally characterize environmental conditions where the matter transformation process occurs and initial properties of the plant litter. Given the values of these parameters, it is possible to calculate dynamics of soil organic matter stocks and its distribution over transformation rate. In the present study, possible approaches for determination of the model parameters are considered and a simple method of their experimental measurement is proposed. An experiment of an incubation of chemically homogeneous samples in soil and multiple sequential measurement of the sample mass loss with time is proposed. An equation of time dynamics of mass loss of incubated homogeneous sample is derived from the basic assumption of the presented soil organic matter transformation model. Thus, fitting by the least squares method the parameters of sample mass loss curve calculated according the proposed mass loss dynamics equation allows to determine the parameters of the general equation of soil organic transformation model.
Aydi, E.; Gebran, M.; Monier, R.; Royer, F.; Lobel, A.; Blomme, R.
2014-12-01
This work describes a procedure to derive several fundamental parameters such as the effective temperature, surface gravity, equatorial rotational velocity and microturbulent velocity. In this work, we have written a numerical procedure in Python which finds the best fit between a grid of synthetic spectra and the observed spectra by minimizing a standard chi-square. LTE model atmospheres were calculated using the ATLAS9 code and were used as inputs to the spectrum synthesis code SYNSPEC48 in order to compute a large grid of synthetic Balmer line profiles. This new procedure has been applied to a large number of new observations (GIRAFFE spectra) of B and A stars members of the young open cluster NGC3293. These observations are part of the GAIA ESO Survey. Takeda's procedure was also used to derive rotational velocities and microturbulent velocities. The results have been compared to previous determinations by other authors and are found to agree with them. As a first result, we concluded that using this procedure, an accuracy of ± 200 K could be achieved in effective temperature and ± 0.2 dex in surface gravities.
International Nuclear Information System (INIS)
Howard, B.J.; Wells, C.; Barnett, C.L.
2016-01-01
Under the MODARIA (Modelling and Data for Radiological Impact Assessments Programme of the International Atomic Energy Agency), there has been an initiative to improve the derivation, provenance and transparency of transfer parameter values for radionuclides. The approach taken for animal products is outlined here and the first revised table for goat milk is provided. Data from some references used in TRS 472 were removed and reasons given for removal. Particular efforts were made to improve the number of CR (concentration ratio) values which have some advantages over transfer coefficients. There is little difference in most of the new CR and F m (transfer coefficient) values for goat milk compared with those in TRS 472. In TRS 472, 21 CR values were reported for goat milk. In the 2015 dataset for goat milk CR values for a further 14 elements are now included. The CR and F m values for only one element (Co) were removed. - Highlights: • The derivation, transparency and provenance of animal product transfer values has been improved. • The first revision of one of these tables is reported for goat milk. • The number of reported Concentration ratio (CR) values has considerably increased.
Bellasio, Chandra; Beerling, David J; Griffiths, Howard
2016-06-01
Combined photosynthetic gas exchange and modulated fluorometres are widely used to evaluate physiological characteristics associated with phenotypic and genotypic variation, whether in response to genetic manipulation or resource limitation in natural vegetation or crops. After describing relatively simple experimental procedures, we present the theoretical background to the derivation of photosynthetic parameters, and provide a freely available Excel-based fitting tool (EFT) that will be of use to specialists and non-specialists alike. We use data acquired in concurrent variable fluorescence-gas exchange experiments, where A/Ci and light-response curves have been measured under ambient and low oxygen. From these data, the EFT derives light respiration, initial PSII (photosystem II) photochemical yield, initial quantum yield for CO2 fixation, fraction of incident light harvested by PSII, initial quantum yield for electron transport, electron transport rate, rate of photorespiration, stomatal limitation, Rubisco (ribulose 1·5-bisphosphate carboxylase/oxygenase) rate of carboxylation and oxygenation, Rubisco specificity factor, mesophyll conductance to CO2 diffusion, light and CO2 compensation point, Rubisco apparent Michaelis-Menten constant, and Rubisco CO2 -saturated carboxylation rate. As an example, a complete analysis of gas exchange data on tobacco plants is provided. We also discuss potential measurement problems and pitfalls, and suggest how such empirical data could subsequently be used to parameterize predictive photosynthetic models. © 2015 John Wiley & Sons Ltd.
Energy Technology Data Exchange (ETDEWEB)
Mian, Muhammad Umer, E-mail: umermian@gmail.com; Khir, M. H. Md.; Tang, T. B. [Department of Electrical and Electronic Engineering, Universiti Teknologi PETRONAS, Tronoh, Perak (Malaysia); Dennis, John Ojur [Department of Fundamental & Applied Sciences, Universiti Teknologi PETRONAS, Tronoh, Perak (Malaysia); Riaz, Kashif; Iqbal, Abid [Faculty of Electronics Engineering, GIK Institute of Engineering Sciences and Technology, Topi, Khyber Pakhtunkhaw (Pakistan); Bazaz, Shafaat A. [Department of Computer Science, Center for Advance Studies in Engineering, Islamabad (Pakistan)
2015-07-22
Pre-fabrication, behavioural and performance analysis with computer aided design (CAD) tools is a common and fabrication cost effective practice. In light of this we present a simulation methodology for a dual-mass oscillator based 3 Degree of Freedom (3-DoF) MEMS gyroscope. 3-DoF Gyroscope is modeled through lumped parameter models using equivalent circuit elements. These equivalent circuits consist of elementary components which are counterpart of their respective mechanical components, used to design and fabricate 3-DoF MEMS gyroscope. Complete designing of equivalent circuit model, mathematical modeling and simulation are being presented in this paper. Behaviors of the equivalent lumped models derived for the proposed device design are simulated in MEMSPRO T-SPICE software. Simulations are carried out with the design specifications following design rules of the MetalMUMPS fabrication process. Drive mass resonant frequencies simulated by this technique are 1.59 kHz and 2.05 kHz respectively, which are close to the resonant frequencies found by the analytical formulation of the gyroscope. The lumped equivalent circuit modeling technique proved to be a time efficient modeling technique for the analysis of complex MEMS devices like 3-DoF gyroscopes. The technique proves to be an alternative approach to the complex and time consuming couple field analysis Finite Element Analysis (FEA) previously used.
Mian, Muhammad Umer; Dennis, John Ojur; Khir, M. H. Md.; Riaz, Kashif; Iqbal, Abid; Bazaz, Shafaat A.; Tang, T. B.
2015-07-01
Pre-fabrication, behavioural and performance analysis with computer aided design (CAD) tools is a common and fabrication cost effective practice. In light of this we present a simulation methodology for a dual-mass oscillator based 3 Degree of Freedom (3-DoF) MEMS gyroscope. 3-DoF Gyroscope is modeled through lumped parameter models using equivalent circuit elements. These equivalent circuits consist of elementary components which are counterpart of their respective mechanical components, used to design and fabricate 3-DoF MEMS gyroscope. Complete designing of equivalent circuit model, mathematical modeling and simulation are being presented in this paper. Behaviors of the equivalent lumped models derived for the proposed device design are simulated in MEMSPRO T-SPICE software. Simulations are carried out with the design specifications following design rules of the MetalMUMPS fabrication process. Drive mass resonant frequencies simulated by this technique are 1.59 kHz and 2.05 kHz respectively, which are close to the resonant frequencies found by the analytical formulation of the gyroscope. The lumped equivalent circuit modeling technique proved to be a time efficient modeling technique for the analysis of complex MEMS devices like 3-DoF gyroscopes. The technique proves to be an alternative approach to the complex and time consuming couple field analysis Finite Element Analysis (FEA) previously used.
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
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.
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.
On the role of modeling parameters in IMRT plan optimization
International Nuclear Information System (INIS)
Krause, Michael; Scherrer, Alexander; Thieke, Christian
2008-01-01
The formulation of optimization problems in intensity-modulated radiotherapy (IMRT) planning comprises the choice of various values such as function-specific parameters or constraint bounds. In current inverse planning programs that yield a single treatment plan for each optimization, it is often unclear how strongly these modeling parameters affect the resulting plan. This work investigates the mathematical concepts of elasticity and sensitivity to deal with this problem. An artificial planning case with a horse-shoe formed target with different opening angles surrounding a circular risk structure is studied. As evaluation functions the generalized equivalent uniform dose (EUD) and the average underdosage below and average overdosage beyond certain dose thresholds are used. A single IMRT plan is calculated for an exemplary parameter configuration. The elasticity and sensitivity of each parameter are then calculated without re-optimization, and the results are numerically verified. The results show the following. (1) elasticity can quantify the influence of a modeling parameter on the optimization result in terms of how strongly the objective function value varies under modifications of the parameter value. It also can describe how strongly the geometry of the involved planning structures affects the optimization result. (2) Based on the current parameter settings and corresponding treatment plan, sensitivity analysis can predict the optimization result for modified parameter values without re-optimization, and it can estimate the value intervals in which such predictions are valid. In conclusion, elasticity and sensitivity can provide helpful tools in inverse IMRT planning to identify the most critical parameters of an individual planning problem and to modify their values in an appropriate way
Assessment of Lumped-Parameter Models for Rigid Footings
DEFF Research Database (Denmark)
Andersen, Lars
2010-01-01
The quality of consistent lumped-parameter models of rigid footings is examined. Emphasis is put on the maximum response during excitation and the geometrical damping related to free vibrations. The optimal order of a lumped-parameter model is determined for each degree of freedom, i.e. horizontal...... and vertical translations as well as torsion and rocking, and the necessity of coupling between horizontal sliding and rocking is discussed. Most of the analyses are carried out for hexagonal footings; but in order to generalise the conclusions to a broader variety of footings, comparisons are made...... with the response of circular and square foundations....
Policy advice derived from simulation models
Brenner, T.; Werker, C.
2009-01-01
When advising policy we face the fundamental problem that economic processes are connected with uncertainty and thus policy can err. In this paper we show how the use of simulation models can reduce policy errors. We suggest that policy is best based on socalled abductive simulation models, which
Climate change decision-making: Model & parameter uncertainties explored
Energy Technology Data Exchange (ETDEWEB)
Dowlatabadi, H.; Kandlikar, M.; Linville, C.
1995-12-31
A critical aspect of climate change decision-making is uncertainties in current understanding of the socioeconomic, climatic and biogeochemical processes involved. Decision-making processes are much better informed if these uncertainties are characterized and their implications understood. Quantitative analysis of these uncertainties serve to inform decision makers about the likely outcome of policy initiatives, and help set priorities for research so that outcome ambiguities faced by the decision-makers are reduced. A family of integrated assessment models of climate change have been developed at Carnegie Mellon. These models are distinguished from other integrated assessment efforts in that they were designed from the outset to characterize and propagate parameter, model, value, and decision-rule uncertainties. The most recent of these models is ICAM 2.1. This model includes representation of the processes of demographics, economic activity, emissions, atmospheric chemistry, climate and sea level change and impacts from these changes and policies for emissions mitigation, and adaptation to change. The model has over 800 objects of which about one half are used to represent uncertainty. In this paper we show, that when considering parameter uncertainties, the relative contribution of climatic uncertainties are most important, followed by uncertainties in damage calculations, economic uncertainties and direct aerosol forcing uncertainties. When considering model structure uncertainties we find that the choice of policy is often dominated by model structure choice, rather than parameter uncertainties.
Petersen, Britta; Gernaey, Krist; Devisscher, Martijn; Dochain, Denis; Vanrolleghem, Peter A
2003-07-01
The first step in the estimation of parameters of models applied for data interpretation should always be an investigation of the identifiability of the model parameters. In this study the structural identifiability of the model parameters of Monod-based activated sludge models (ASM) was studied. In an illustrative example it was assumed that respirometric (dissolved oxygen or oxygen uptake rates) and titrimetric (cumulative proton production) measurements were available for the characterisation of nitrification. Two model structures, including the presence and absence of significant growth for description of long- and short-term experiments, respectively, were considered. The structural identifiability was studied via the series expansion methods. It was proven that the autotrophic yield becomes uniquely identifiable when combined respirometric and titrimetric data are assumed for the characterisation of nitrification. The most remarkable result of the study was, however, that the identifiability results could be generalised by applying a set of ASM1 matrix based generalisation rules. It appeared that the identifiable parameter combinations could be predicted directly based on the knowledge of the process model under study (in ASM1-like matrix representation), the measured variables and the biodegradable substrate considered. This generalisation reduces the time-consuming task of deriving the structurally identifiable model parameters significantly and helps the user to obtain these directly without the necessity to go too deeply into the mathematical background of structural identifiability.
Radcliffe, D E; Lin, Z; Risse, L M; Romeis, J J; Jackson, C R
2009-01-01
Lake Allatoona is a large reservoir north of Atlanta, GA, that drains an area of about 2870 km2 scheduled for a phosphorus (P) total maximum daily load (TMDL). The Soil and Water Assessment Tool (SWAT) model has been widely used for watershed-scale modeling of P, but there is little guidance on how to estimate P-related parameters, especially those related to in-stream P processes. In this paper, methods are demonstrated to individually estimate SWAT soil-related P parameters and to collectively estimate P parameters related to stream processes. Stream related parameters were obtained using the nutrient uptake length concept. In a manner similar to experiments conducted by stream ecologists, a small point source is simulated in a headwater sub-basin of the SWAT models, then the in-stream parameter values are adjusted collectively to get an uptake length of P similar to the values measured in the streams in the region. After adjusting the in-stream parameters, the P uptake length estimated in the simulations ranged from 53 to 149 km compared to uptake lengths measured by ecologists in the region of 11 to 85 km. Once the a priori P-related parameter set was developed, the SWAT models of main tributaries to Lake Allatoona were calibrated for daily transport. Models using SWAT P parameters derived from the methods in this paper outperformed models using default parameter values when predicting total P (TP) concentrations in streams during storm events and TP annual loads to Lake Allatoona.
A variable-order fractal derivative model for anomalous diffusion
Directory of Open Access Journals (Sweden)
Liu Xiaoting
2017-01-01
Full Text Available This paper pays attention to develop a variable-order fractal derivative model for anomalous diffusion. Previous investigations have indicated that the medium structure, fractal dimension or porosity may change with time or space during solute transport processes, results in time or spatial dependent anomalous diffusion phenomena. Hereby, this study makes an attempt to introduce a variable-order fractal derivative diffusion model, in which the index of fractal derivative depends on temporal moment or spatial position, to characterize the above mentioned anomalous diffusion (or transport processes. Compared with other models, the main advantages in description and the physical explanation of new model are explored by numerical simulation. Further discussions on the dissimilitude such as computational efficiency, diffusion behavior and heavy tail phenomena of the new model and variable-order fractional derivative model are also offered.
Timmermans, Joris; Gastellu-Etchegorry, Jean Philippe; van der Tol, Christiaan; Verhoef, Wout; Vekerdy, Zoltan; Su, Zhongbo
2017-04-01
Accurate estimation of the radiative transfer (RT) over vegetation is the corner stone of agricultural and hydrological remote sensing applications. Present remote sensing sensors mostly use traditional optical, thermal and microwave observations. However with these traditional observations characterization of the light efficiency and photosynthetic rate can only be accomplished indirectly. A promising new method of observing these processes is by using the fluorescent emitted radiation. This approach was recently highlighted due to the selection of the FLEX sensor as a future Earth Explorer by the European Space agency (ESA). Several modelling activities have been undertaken to better understand the technical feasibilities of this sensor. Within these studies, the SCOPE model has been chosen as the baseline algorithm. This model combines a detailed RT description of the canopy, using a discrete version of the SAIL model, with a description of photosynthetic processes (by use of the Farquhar/Ball-Berry model). Consequently, this model is capable of simulating simultaneously the biophysical processes and jointly the fluorescent, optical and thermal RT. The SAIL model however is a 1D RT model and consequently provides higher uncertainties with increasing vegetation structures. The main objective of this research is to investigate the limitations of the RT model component of the SCOPE model over complex canopies. In particular the aim of this research is to evaluate the validity for increasingly structural complex canopies', on the bidirectional reflectance distribution functions (BRDF) of these canopies. This was accomplished by evaluating the simulated outgoing radiation from SCOPE/SAIL against simulations of the DART 3D RT model. In total nine different scenarios were simulated with the DART RTM with increasing structural complexity, ranging from the simple 'Plot' scenario to the highly complex 'Multiple Crown' scenario. The canopy parameters are retrieved from a
Identifying the effects of parameter uncertainty on the reliability of riverbank stability modelling
Samadi, A.; Amiri-Tokaldany, E.; Darby, S. E.
2009-05-01
Bank retreat is a key process in fluvial dynamics affecting a wide range of physical, ecological and socioeconomic issues in the fluvial environment. To predict the undesirable effects of bank retreat and to inform effective measures to prevent it, a wide range of bank stability models have been presented in the literature. These models typically express bank stability by defining a factor of safety as the ratio of driving and resisting forces acting on the incipient failure block. These forces are affected by a range of controlling factors that include such aspects as the bank profile (bank height and angle), the geotechnical properties of the bank materials, as well as the hydrological status of the riverbanks. In this paper we evaluate the extent to which uncertainties in the parameterization of these controlling factors feed through to influence the reliability of the resulting bank stability estimate. This is achieved by employing a simple model of riverbank stability with respect to planar failure (which is the most common type of bank stability model) in a series of sensitivity tests and Monte Carlo analyses to identify, for each model parameter, the range of values that induce significant changes in the simulated factor of safety. These identified parameter value ranges are compared to empirically derived parameter uncertainties to determine whether they are likely to confound the reliability of the resulting bank stability calculations. Our results show that parameter uncertainties are typically high enough that the likelihood of generating unreliable predictions is typically very high (> ˜ 80% for predictions requiring a precision of < ± 15%). Because parameter uncertainties are derived primarily from the natural variability of the parameters, rather than measurement errors, much more careful attention should be paid to field sampling strategies, such that the parameter uncertainties and consequent prediction unreliabilities can be quantified more
Inhalation Exposure Input Parameters for the Biosphere Model
International Nuclear Information System (INIS)
M. Wasiolek
2006-01-01
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 report is concerned primarily with the
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
Weather Derivatives and Stochastic Modelling of Temperature
Directory of Open Access Journals (Sweden)
Fred Espen Benth
2011-01-01
Full Text Available We propose a continuous-time autoregressive model for the temperature dynamics with volatility being the product of a seasonal function and a stochastic process. We use the Barndorff-Nielsen and Shephard model for the stochastic volatility. The proposed temperature dynamics is flexible enough to model temperature data accurately, and at the same time being analytically tractable. Futures prices for commonly traded contracts at the Chicago Mercantile Exchange on indices like cooling- and heating-degree days and cumulative average temperatures are computed, as well as option prices on them.
Comparison of digital elevation models and relevant derived attributes
Li, Xinchuan; Zhang, Youjing; Jin, Xiuliang; He, Qiaoning; Zhang, Xiuping
2017-10-01
The digital elevation model (DEM) and its derivative attributes are important parameters for evaluating any process using digital terrain analysis. Five freely available global DEM products including Advanced Spaceborne Thermal Emission and Reflection Radiometer-Global Digital Elevation Model version 2 (ASTER GDEM2), Shuttle Radar Topographic Mission version 4.1 (SRTM V4.1), Global Multiresolution Terrain Elevation Data 2010 (GMTED2010), EarthEnv-DEM90, and Global 30 Arc-Second Elevation (GTOPO30) were assessed in this study. The objective of this study was to compare the differences of elevations, slopes, and topographic wetness indices (TWIs) derived from these five DEM products. SRTM V4.1 showed a better accuracy [root mean square error (RMSE)=4.87 m] than ASTER GDEM2 (RMSE=7.08 m) based on ICESat/GLAS (the Ice, Cloud, and land Elevation Satellite/Geoscience Laser Altimeter System) laser altimetry points. ICESat/GLAS data were then selected as the benchmark to rectify the SRTM V4.1 data using the simple kriging (SK) interpolation method. The corrected high-accuracy SRTM V4.1 data (RMSE=1.14 m) were then regarded as the reference data. EarthEnv-DEM90 displayed the best accuracy in the DEM and slope, whereas the TWI accuracy of GMTED2010 was best. The accuracy of topographic attributes was sensitive to the roughness of the terrain. DEM and slope displayed a larger error variance as the elevation increased. DEM was sensitive to the data source and slope was sensitive to the data source and spatial resolution. TWI was influenced by data source and spatial resolution. As the spatial resolution decreased, the differences of topographic attributes tended to decrease.
The level density parameters for fermi gas model
International Nuclear Information System (INIS)
Zuang Youxiang; Wang Cuilan; Zhou Chunmei; Su Zongdi
1986-01-01
Nuclear level densities are crucial ingredient in the statistical models, for instance, in the calculations of the widths, cross sections, emitted particle spectra, etc. for various reaction channels. In this work 667 sets of more reliable and new experimental data are adopted, which include average level spacing D D , radiative capture width Γ γ 0 at neutron binding energy and cumulative level number N 0 at the low excitation energy. They are published during 1973 to 1983. Based on the parameters given by Gilbert-Cameon and Cook the physical quantities mentioned above are calculated. The calculated results have the deviation obviously from experimental values. In order to improve the fitting, the parameters in the G-C formula are adjusted and new set of level density parameters is obsained. The parameters is this work are more suitable to fit new measurements
Parameter Uncertainty for Aircraft Aerodynamic Modeling using Recursive Least Squares
Grauer, Jared A.; Morelli, Eugene A.
2016-01-01
A real-time method was demonstrated for determining accurate uncertainty levels of stability and control derivatives estimated using recursive least squares and time-domain data. The method uses a recursive formulation of the residual autocorrelation to account for colored residuals, which are routinely encountered in aircraft parameter estimation and change the predicted uncertainties. Simulation data and flight test data for a subscale jet transport aircraft were used to demonstrate the approach. Results showed that the corrected uncertainties matched the observed scatter in the parameter estimates, and did so more accurately than conventional uncertainty estimates that assume white residuals. Only small differences were observed between batch estimates and recursive estimates at the end of the maneuver. It was also demonstrated that the autocorrelation could be reduced to a small number of lags to minimize computation and memory storage requirements without significantly degrading the accuracy of predicted uncertainty levels.
Quantification of key parameters for treating contrails in a large scale climate model
Energy Technology Data Exchange (ETDEWEB)
Ponater, M.; Gierens, K. [Deutsche Forschungsanstalt fuer Luft- und Raumfahrt e.V. (DLR), Wessling (Germany). Inst. fuer Physik der Atmosphaere
1997-12-01
The general objective of this project, to determine contrail key parameters with respect to their climate effect, has been approached by three tasks: (1) quantification of microphysical key parameters, (2) development of a contrail coverage parametrization for climate models, and (3) determination of the worldwide coverage with persistent contrails due to present day air traffic. The microphysical key parameters are determined using microphysical box model simulations. The contrail parametrization was achieved by deriving (from aircraft measurements) the instantaneous fluctuations of temperature and relative humidity that occur on spatial scales beyond the resolution of climate models. The global and annual mean coverage by persistent contrails was calculated from ECMWF numerical analyses and from actual air traffic density. It was found to be currently about 0.1%, though the atmosphere has the potential to form persistent contrails over a much larger area. (orig.) 144 figs., 42 tabs., 497 refs.
Choi, Y.; Vadrevu, K. P.; Vay, S. A.; Woo, J.
2006-12-01
North American terrestrial ecosystems are major sources and sinks of carbon. Precise measurement of atmospheric CO2 concentrations plays an important role in the development and testing of carbon cycle models quantifying the influence of terrestrial CO2 exchange on the North American carbon budget. During the summer 2004 Intercontinental Chemical Transport Experiment North America (INTEX-NA) campaign, regional scale in-situ measurements of atmospheric CO2 were made from the NASA DC-8 affording the opportunity to explore how land surface heterogeneity relates to the airborne observations utilizing remote-sensing data products and GIS-based methods. These 1 Hz data reveal the seasonal biospheric uptake of CO2 over portions of the U.S. continent, especially east of 90°W below 2 km, compared to higher mixing ratios over water as well as within the upper troposphere where well-mixed, aged air masses were sampled. In this study, we use several remote sensing derived biophysical parameters from the LANDSAT, NOAA AVHRR, and MODIS sensors to specify spatiotemporal patterns of land use cover and vegetation characteristics for linking the airborne measurements of CO2 data with terrestrial sources of carbon. Also, CO2 flux footprint outputs from a 3-D Lagrangian atmospheric model have been integrated with satellite remote sensing data to infer CO2 variations across heterogeneous landscapes. In examining the landscape mosaic utilizing these available tools, preliminary results suggest that the lowest CO2 mixing ratios observed during INTEX-NA were over agricultural fields in Illinois dominated by corn then secondarily soybean crops. Low CO2 concentrations are attributable to sampling during the peak growing season over such C4 plants as corn having a higher photosynthetic rate via the C4-dicarboxylic acid pathway of carbon fixation compared to C3 plants such as soybeans. In addition to LANDSAT derived land cover data, results from comparisons of the airborne CO2 observations
Derivation of radioecological parameters from the long-term emission of iodine-129. Final report
International Nuclear Information System (INIS)
Michel, R.; Klipsch, K.; Ernst, T.; Gorny, M.; Jakob, D.; Vahlbruch, J.; Synal, H.A.; Schnabel, C.
2004-01-01
In this project, the distribution and behaviour of 129 I and 127 I in the environment and its pathways through the environment to man were comprehensively investigated in order to provide a basis for estimating the radiation exposure to man due to releases of 129 I. To this end, the actual situation in Lower Saxony, Germany, was studied for exemplary regions near to and far from the coast of the North Sea. Accelerator mass spectrometry, radiochemical neutron activation analysis, ion chromatography, and ICP-MS were applied to measure the iodine isotopes, 129 I and P 127 I, in sea-water, air, precipitation, surface and ground waters, soils, plants, animals, foodstuffs, total diet, and human and animal thyroid glands. For air-borne iodine, the speciation as well as the particle size distribution of aerosols was determined. Soil depth profiles were investigated down to depths of 2.5 m in order to study the iodine migration as well as individual surface soil samples to allow for the determination of transfer factors of the iodine isotopes into plants. From the analytical results radioecological parameters for the long-term behaviour of 129 I in the pedo- and biosphere were derived. The iodine isotopes are in severe disequilibrium in the different environmental compartments. The pre-nuclear equilibrium 129 I/ 127 I ratio in the biosphere was determined to be 2.0 x 10 -13 with a geometric standard deviation of 1.39. Today, the environmental isotopic ratios in Northern Germany range from 10 -6 to 10 -10 . The highest ratios are found in North Sea water, the lowest in deep soil samples and ground water. The North Sea appears as the dominant source of air-borne iodine in Northern Germany due to the emissions of European reprocessing plants. The results are discussed with respect to their radiological relevance and in view of the general protection of the environment, i.e. air, water, soil and the biosphere. (orig.)
Links between the charge model and bonded parameter force constants in biomolecular force fields
Cerutti, David S.; Debiec, Karl T.; Case, David A.; Chong, Lillian T.
2017-10-01
The ff15ipq protein force field is a fixed charge model built by automated tools based on the two charge sets of the implicitly polarized charge method: one set (appropriate for vacuum) for deriving bonded parameters and the other (appropriate for aqueous solution) for running simulations. The duality is intended to treat water-induced electronic polarization with an understanding that fitting data for bonded parameters will come from quantum mechanical calculations in the gas phase. In this study, we compare ff15ipq to two alternatives produced with the same fitting software and a further expanded data set but following more conventional methods for tailoring bonded parameters (harmonic angle terms and torsion potentials) to the charge model. First, ff15ipq-Qsolv derives bonded parameters in the context of the ff15ipq solution phase charge set. Second, ff15ipq-Vac takes ff15ipq's bonded parameters and runs simulations with the vacuum phase charge set used to derive those parameters. The IPolQ charge model and associated protocol for deriving bonded parameters are shown to be an incremental improvement over protocols that do not account for the material phases of each source of their fitting data. Both force fields incorporating the polarized charge set depict stable globular proteins and have varying degrees of success modeling the metastability of short (5-19 residues) peptides. In this particular case, ff15ipq-Qsolv increases stability in a number of α -helices, correctly obtaining 70% helical character in the K19 system at 275 K and showing appropriately diminishing content up to 325 K, but overestimating the helical fraction of AAQAA3 by 50% or more, forming long-lived α -helices in simulations of a β -hairpin, and increasing the likelihood that the disordered p53 N-terminal peptide will also form a helix. This may indicate a systematic bias imparted by the ff15ipq-Qsolv parameter development strategy, which has the hallmarks of strategies used to develop
Identifiability and error minimization of receptor model parameters with PET
International Nuclear Information System (INIS)
Delforge, J.; Syrota, A.; Mazoyer, B.M.
1989-01-01
The identifiability problem and the general framework for experimental design optimization are presented. The methodology is applied to the problem of the receptor-ligand model parameter estimation with dynamic positron emission tomography data. The first attempts to identify the model parameters from data obtained with a single tracer injection led to disappointing numerical results. The possibility of improving parameter estimation using a new experimental design combining an injection of the labelled ligand and an injection of the cold ligand (displacement experiment) has been investigated. However, this second protocol led to two very different numerical solutions and it was necessary to demonstrate which solution was biologically valid. This has been possible by using a third protocol including both a displacement and a co-injection experiment. (authors). 16 refs.; 14 figs
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...... PA for simulations. The simulated error vector magnitude (EVM) and adjacent channel power ratio (ACPR) were compared with the measured data to validate the model. The maximum differences between the simulated and measured EVM and ACPR are less than 2% point and 3 dB, respectively....
Parameter sensitivity analysis of a lumped-parameter model of a chain of lymphangions in series.
Jamalian, Samira; Bertram, Christopher D; Richardson, William J; Moore, James E
2013-12-01
Any disruption of the lymphatic system due to trauma or injury can lead to edema. There is no effective cure for lymphedema, partly because predictive knowledge of lymphatic system reactions to interventions is lacking. A well-developed model of the system could greatly improve our understanding of its function. Lymphangions, defined as the vessel segment between two valves, are the individual pumping units. Based on our previous lumped-parameter model of a chain of lymphangions, this study aimed to identify the parameters that affect the system output the most using a sensitivity analysis. The system was highly sensitive to minimum valve resistance, such that variations in this parameter caused an order-of-magnitude change in time-average flow rate for certain values of imposed pressure difference. Average flow rate doubled when contraction frequency was increased within its physiological range. Optimum lymphangion length was found to be some 13-14.5 diameters. A peak of time-average flow rate occurred when transmural pressure was such that the pressure-diameter loop for active contractions was centered near maximum passive vessel compliance. Increasing the number of lymphangions in the chain improved the pumping in the presence of larger adverse pressure differences. For a given pressure difference, the optimal number of lymphangions increased with the total vessel length. These results indicate that further experiments to estimate valve resistance more accurately are necessary. The existence of an optimal value of transmural pressure may provide additional guidelines for increasing pumping in areas affected by edema.
Reimer, Joscha; Piwonski, Jaroslaw; Slawig, Thomas
2016-04-01
The statistical significance of any model-data comparison strongly depends on the quality of the used data and the criterion used to measure the model-to-data misfit. The statistical properties (such as mean values, variances and covariances) of the data should be taken into account by choosing a criterion as, e.g., ordinary, weighted or generalized least squares. Moreover, the criterion can be restricted onto regions or model quantities which are of special interest. This choice influences the quality of the model output (also for not measured quantities) and the results of a parameter estimation or optimization process. We have estimated the parameters of a three-dimensional and time-dependent marine biogeochemical model describing the phosphorus cycle in the ocean. For this purpose, we have developed a statistical model for measurements of phosphate and dissolved organic phosphorus. This statistical model includes variances and correlations varying with time and location of the measurements. We compared the obtained estimations of model output and parameters for different criteria. Another question is if (and which) further measurements would increase the model's quality at all. Using experimental design criteria, the information content of measurements can be quantified. This may refer to the uncertainty in unknown model parameters as well as the uncertainty regarding which model is closer to reality. By (another) optimization, optimal measurement properties such as locations, time instants and quantities to be measured can be identified. We have optimized such properties for additional measurement for the parameter estimation of the marine biogeochemical model. For this purpose, we have quantified the uncertainty in the optimal model parameters and the model output itself regarding the uncertainty in the measurement data using the (Fisher) information matrix. Furthermore, we have calculated the uncertainty reduction by additional measurements depending on time
Silicon Carbide Derived Carbons: Experiments and Modeling
Energy Technology Data Exchange (ETDEWEB)
Kertesz, Miklos [Georgetown University, Washington DC 20057
2011-02-28
The main results of the computational modeling was: 1. Development of a new genealogical algorithm to generate vacancy clusters in diamond starting from monovacancies combined with energy criteria based on TBDFT energetics. The method revealed that for smaller vacancy clusters the energetically optimal shapes are compact but for larger sizes they tend to show graphitized regions. In fact smaller clusters of the size as small as 12 already show signatures of this graphitization. The modeling gives firm basis for the slit-pore modeling of porous carbon materials and explains some of their properties. 2. We discovered small vacancy clusters and their physical characteristics that can be used to spectroscopically identify them. 3. We found low barrier pathways for vacancy migration in diamond-like materials by obtaining for the first time optimized reaction pathways.
Revised models and genetic parameter estimates for production and ...
African Journals Online (AJOL)
Genetic parameters for production and reproduction traits in the Elsenburg Dormer sheep stud were estimated using records of 11743 lambs born between 1943 and 2002. An animal model with direct and maternal additive, maternal permanent and temporary environmental effects was fitted for traits considered traits of the ...
Transformations among CE–CVM model parameters for ...
Indian Academy of Sciences (India)
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 ...
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...
Comparison of parameter estimation algorithms in hydrological modelling
DEFF Research Database (Denmark)
Blasone, Roberta-Serena; Madsen, Henrik; Rosbjerg, Dan
2006-01-01
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...
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...
Constraint on Parameters of Inverse Compton Scattering Model for ...
Indian Academy of Sciences (India)
J. Astrophys. Astr. (2011) 32, 299–300 c Indian Academy of Sciences. Constraint on Parameters of Inverse Compton Scattering Model for PSR B2319+60. H. G. Wang. ∗. & M. Lv. Center for Astrophysics,Guangzhou University, Guangzhou, China. ∗ e-mail: cosmic008@yahoo.com.cn. Abstract. Using the multifrequency radio ...
Inhalation Exposure Input Parameters for the Biosphere Model
International Nuclear Information System (INIS)
M. A. Wasiolek
2003-01-01
This analysis is one of the nine reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2003a) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents a set of 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 a Yucca Mountain repository. This report, ''Inhalation Exposure Input Parameters for the Biosphere Model'', is one of the 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 2003b). It should be noted that some documents identified in Figure 1-1 may be under development at the time this report is issued and therefore not available at that time. This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this analysis report. This analysis report defines and justifies values of mass loading, which is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Measurements of mass loading are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air surrounding crops and concentrations in air inhaled by a receptor. Concentrations in air to which the
Integrating microbial diversity in soil carbon dynamic models parameters
Louis, Benjamin; Menasseri-Aubry, Safya; Leterme, Philippe; Maron, Pierre-Alain; Viaud, Valérie
2015-04-01
Faced with the numerous concerns about soil carbon dynamic, a large quantity of carbon dynamic models has been developed during the last century. These models are mainly in the form of deterministic compartment models with carbon fluxes between compartments represented by ordinary differential equations. Nowadays, lots of them consider the microbial biomass as a compartment of the soil organic matter (carbon quantity). But the amount of microbial carbon is rarely used in the differential equations of the models as a limiting factor. Additionally, microbial diversity and community composition are mostly missing, although last advances in soil microbial analytical methods during the two past decades have shown that these characteristics play also a significant role in soil carbon dynamic. As soil microorganisms are essential drivers of soil carbon dynamic, the question about explicitly integrating their role have become a key issue in soil carbon dynamic models development. Some interesting attempts can be found and are dominated by the incorporation of several compartments of different groups of microbial biomass in terms of functional traits and/or biogeochemical compositions to integrate microbial diversity. However, these models are basically heuristic models in the sense that they are used to test hypotheses through simulations. They have rarely been confronted to real data and thus cannot be used to predict realistic situations. The objective of this work was to empirically integrate microbial diversity in a simple model of carbon dynamic through statistical modelling of the model parameters. This work is based on available experimental results coming from a French National Research Agency program called DIMIMOS. Briefly, 13C-labelled wheat residue has been incorporated into soils with different pedological characteristics and land use history. Then, the soils have been incubated during 104 days and labelled and non-labelled CO2 fluxes have been measured at ten
Inhalation Exposure Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
M. A. Wasiolek
2003-09-24
This analysis is one of the nine reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2003a) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents a set of 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 a Yucca Mountain repository. This report, ''Inhalation Exposure Input Parameters for the Biosphere Model'', is one of the 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 2003b). It should be noted that some documents identified in Figure 1-1 may be under development at the time this report is issued and therefore not available at that time. This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this analysis report. This analysis report defines and justifies values of mass loading, which is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Measurements of mass loading are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air surrounding crops and concentrations in air
DEFF Research Database (Denmark)
King, Alexander Weider; Agerkvist, Finn T.
2017-01-01
Commonly used models of moving-coil loudspeaker voice coils, which include effects from eddy current losses, are either inaccurate or contain an abundance of parameters, and are difficult to extend to the nonlinear domain. On the contrary, fractional derivative models accurately describe the freq......Commonly used models of moving-coil loudspeaker voice coils, which include effects from eddy current losses, are either inaccurate or contain an abundance of parameters, and are difficult to extend to the nonlinear domain. On the contrary, fractional derivative models accurately describe...... the frequency and position dependence of the lossy inductance, with meaningful connections to the underlying physics, while keeping the number of parameters low. These fractional derivatives are also compatible with state-space polynomial methods of modeling nonlinear behavior. It is shown that the fractional...... order derivative approaches a value of 1, corresponding to an ideal inductance, when the voice coil is completely outside the magnetic system. Finally, the developed model reveals details about the effect of conductive voice coil formers...
Wind gust models derived from field data
Gawronski, W.
1995-01-01
Wind data measured during a field experiment were used to verify the analytical model of wind gusts. Good coincidence was observed; the only discrepancy occurred for the azimuth error in the front and back winds, where the simulated errors were smaller than the measured ones. This happened because of the assumption of the spatial coherence of the wind gust model, which generated a symmetric antenna load and, in consequence, a low azimuth servo error. This result indicates a need for upgrading the wind gust model to a spatially incoherent one that will reflect the real gusts in a more accurate manner. In order to design a controller with wind disturbance rejection properties, the wind disturbance should be known at the input to the antenna rate loop model. The second task, therefore, consists of developing a digital filter that simulates the wind gusts at the antenna rate input. This filter matches the spectrum of the measured servo errors. In this scenario, the wind gusts are generated by introducing white noise to the filter input.
Model predictive control of constrained with non linear stochastic parameters systems
Dombrovskii, V.; Obyedko, T.
2011-01-01
In this paper we consider the model predictive control problem of discrete-time systems with non-linear random depended parameters for which only the first and second conditional distribution moments, the conditional autocorrelations and the mutual cross-correlations are known. The open-loop feedback control strategy is derived subject to hard constraints on the control variables. The approach is advantageous because the rich arsenal of methods of non-linear estimation or the results of nonpa...
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.
Soil-Related Input Parameters for the Biosphere Model
International Nuclear Information System (INIS)
Smith, A. J.
2004-01-01
This report presents one of the analyses that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN). The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the details of the conceptual model as well as the mathematical model and the required input parameters. The biosphere model is one of a series of process models supporting the postclosure Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A schematic representation of the documentation flow for the Biosphere input to TSPA is presented in Figure 1-1. This figure shows the evolutionary relationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan for Biosphere Modeling and Expert Support'' (TWP) (BSC 2004 [DIRS 169573]). This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this report. This report, ''Soil-Related Input Parameters for the Biosphere Model'', is one of the five analysis reports that develop input parameters for use in the ERMYN model. This report is the source documentation for the six biosphere parameters identified in Table 1-1. The purpose of this analysis was to develop the biosphere model parameters associated with the accumulation and depletion of radionuclides in the soil. These parameters support the calculation of radionuclide concentrations in soil from on-going irrigation or ash deposition and, as a direct consequence, radionuclide concentration in other environmental media that are affected by radionuclide concentrations in soil. The analysis was performed in accordance with the TWP (BSC 2004 [DIRS 169573]) where the governing procedure was defined as AP-SIII.9Q, ''Scientific Analyses''. This
Soil-Related Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
A. J. Smith
2004-09-09
This report presents one of the analyses that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN). The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the details of the conceptual model as well as the mathematical model and the required input parameters. The biosphere model is one of a series of process models supporting the postclosure Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A schematic representation of the documentation flow for the Biosphere input to TSPA is presented in Figure 1-1. This figure shows the evolutionary relationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan for Biosphere Modeling and Expert Support'' (TWP) (BSC 2004 [DIRS 169573]). This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this report. This report, ''Soil-Related Input Parameters for the Biosphere Model'', is one of the five analysis reports that develop input parameters for use in the ERMYN model. This report is the source documentation for the six biosphere parameters identified in Table 1-1. The purpose of this analysis was to develop the biosphere model parameters associated with the accumulation and depletion of radionuclides in the soil. These parameters support the calculation of radionuclide concentrations in soil from on-going irrigation or ash deposition and, as a direct consequence, radionuclide concentration in other environmental media that are affected by radionuclide concentrations in soil. The analysis was performed in accordance with the TWP (BSC 2004 [DIRS 169573]) where the governing procedure
Bellasio, Chandra; Beerling, David J; Griffiths, Howard
2016-06-01
The higher photosynthetic potential of C4 plants has led to extensive research over the past 50 years, including C4 -dominated natural biomes, crops such as maize, or for evaluating the transfer of C4 traits into C3 lineages. Photosynthetic gas exchange can be measured in air or in a 2% Oxygen mixture using readily available commercial gas exchange and modulated PSII fluorescence systems. Interpretation of these data, however, requires an understanding (or the development) of various modelling approaches, which limit the use by non-specialists. In this paper we present an accessible summary of the theory behind the analysis and derivation of C4 photosynthetic parameters, and provide a freely available Excel Fitting Tool (EFT), making rigorous C4 data analysis accessible to a broader audience. Outputs include those defining C4 photochemical and biochemical efficiency, the rate of photorespiration, bundle sheath conductance to CO2 diffusion and the in vivo biochemical constants for PEP carboxylase. The EFT compares several methodological variants proposed by different investigators, allowing users to choose the level of complexity required to interpret data. We provide a complete analysis of gas exchange data on maize (as a model C4 organism and key global crop) to illustrate the approaches, their analysis and interpretation. © 2015 John Wiley & Sons Ltd. © 2016 John Wiley & Sons Ltd.
Estimation of the Malthusian parameter in an stochastic epidemic model using martingale methods.
Lindenstrand, David; Svensson, Åke
2013-12-01
Data, on the number of infected, gathered from a large epidemic outbreak can be used to estimate parameters related to the strength and speed of the spread. The Malthusian parameter, which determines the initial growth rate of the epidemic is often of crucial interest. Using a simple epidemic SEIR model with known generation time distribution, we define and analyze an estimate, based on martingale methods. We derive asymptotic properties of the estimate and compare them to the results from simulations of the epidemic. The estimate uses all the information contained in the epidemic curve, in contrast to estimates which only use data from the start of the outbreak.
Analysis of waveform-derived ORA parameters in early forms of keratoconus and normal corneas.
Ventura, Bruna V; Machado, Aydano P; Ambrósio, Renato; Ribeiro, Guilherme; Araújo, Luana N; Luz, Allan; Lyra, João Marcelo
2013-09-01
To evaluate the Ocular Response Analyzer (ORA; Reichert Ophthalmic Instruments, Depew, NY) performance in differentiating grades I and II keratoconus from normal corneas using 41 parameters individually and to assess the effect of analyzing all parameters together. This study compared the mean value of 41 ORA parameters in grades I and II keratoconus with healthy age-matched control eyes. Only eyes with a central corneal thickness between 500 and 600 μm were included. The area under the receiver operating characteristic curve was calculated for each of the 41 parameters independently and for all of the parameters together. This study included 136 eyes with normal corneas and 68 eyes with grades I and II keratoconus. When analyzed individually, four ORA parameters (p1area, p1area1, p2area, and p2area1) had an area under the curve greater than 0.900 for discriminating between both groups. The p2area was the parameter that achieved the largest area under the curve individually (0.931). The area under the curve increased to 0.978 when analyzing all parameters together. Alternative ORA parameters are better for differentiating grades I and II keratoconus from normal corneas than the four parameters originally available for ophthalmologists (corneal hysteresis, Goldmann-correlated intraocular pressure, corneal-compensated intraocular pressure, and corneal resistance factor). Although the ORA did not achieve 100% accuracy, the discrimination between these two groups was optimized by combining all parameters. Copyright 2013, SLACK Incorporated.
MODIS-derived Biophysical Parameters for 5-km Land Cover, North America, 2000-2012
National Aeronautics and Space Administration — This data set provides MODIS-derived surface biophysical climatologies of bidirectional distribution function (BRDF), BDRF/albedo, land surface temperature (LST),...
MODIS-derived Biophysical Parameters for 5-km Land Cover, North America, 2000-2012
National Aeronautics and Space Administration — ABSTRACT: This data set provides MODIS-derived surface biophysical climatologies of bidirectional distribution function (BRDF), BDRF/albedo, land surface temperature...
New empirically-derived solar radiation pressure model for GPS satellites
Bar-Sever, Y.; Kuang, D.
2003-04-01
We derive a new and improved GPS solar pressure model by estimating model parameters using least square approximation to four and a half years of GPS precise orbit data. The new solar radiation model for Block IIR satellites provides 90% improvement over to the best pre-launch model, as measured by orbit fits and orbit prediction quality. The new model of Block II/IIA realizes a more modest improvement of the previous JPL empirical model. The empirical model is constructed as a set of Fourier functions of the Earth-Probe-Sun angle, to represent the solar radiation pressure forces in the coordinate system tied to the nominal solar panel surface orientation. The model derivation reveals a number of systematic patterns, some of which can be explained in terms of properties of the GPS attitude control system, and some are yet to be explained. Finally, we will discuss the overall orbit determination improvements using the new models.
Modeling ramp-hold indentation measurements based on Kelvin-Voigt fractional derivative model
Zhang, Hongmei; zhe Zhang, Qing; Ruan, Litao; Duan, Junbo; Wan, Mingxi; Insana, Michael F.
2018-03-01
Interpretation of experimental data from micro- and nano-scale indentation testing is highly dependent on the constitutive model selected to relate measurements to mechanical properties. The Kelvin-Voigt fractional derivative model (KVFD) offers a compact set of viscoelastic features appropriate for characterizing soft biological materials. This paper provides a set of KVFD solutions for converting indentation testing data acquired for different geometries and scales into viscoelastic properties of soft materials. These solutions, which are mostly in closed-form, apply to ramp-hold relaxation, load-unload and ramp-load creep-testing protocols. We report on applications of these model solutions to macro- and nano-indentation testing of hydrogels, gastric cancer cells and ex vivo breast tissue samples using an atomic force microscope (AFM). We also applied KVFD models to clinical ultrasonic breast data using a compression plate as required for elasticity imaging. Together the results show that KVFD models fit a broad range of experimental data with a correlation coefficient typically R 2 > 0.99. For hydrogel samples, estimation of KVFD model parameters from test data using spherical indentation versus plate compression as well as ramp relaxation versus load-unload compression all agree within one standard deviation. Results from measurements made using macro- and nano-scale indentation agree in trend. For gastric cell and ex vivo breast tissue measurements, KVFD moduli are, respectively, 1/3-1/2 and 1/6 of the elasticity modulus found from the Sneddon model. In vivo breast tissue measurements yield model parameters consistent with literature results. The consistency of results found for a broad range of experimental parameters suggest the KVFD model is a reliable tool for exploring intrinsic features of the cell/tissue microenvironments.
Mass balance model parameter transferability on a tropical glacier
Gurgiser, Wolfgang; Mölg, Thomas; Nicholson, Lindsey; Kaser, Georg
2013-04-01
The mass balance and melt water production of glaciers is of particular interest in the Peruvian Andes where glacier melt water has markedly increased water supply during the pronounced dry seasons in recent decades. However, the melt water contribution from glaciers is projected to decrease with appreciable negative impacts on the local society within the coming decades. Understanding mass balance processes on tropical glaciers is a prerequisite for modeling present and future glacier runoff. As a first step towards this aim we applied a process-based surface mass balance model in order to calculate observed ablation at two stakes in the ablation zone of Shallap Glacier (4800 m a.s.l., 9°S) in the Cordillera Blanca, Peru. Under the tropical climate, the snow line migrates very frequently across most of the ablation zone all year round causing large temporal and spatial variations of glacier surface conditions and related ablation. Consequently, pronounced differences between the two chosen stakes and the two years were observed. Hourly records of temperature, humidity, wind speed, short wave incoming radiation, and precipitation are available from an automatic weather station (AWS) on the moraine near the glacier for the hydrological years 2006/07 and 2007/08 while stake readings are available at intervals of between 14 to 64 days. To optimize model parameters, we used 1000 model simulations in which the most sensitive model parameters were varied randomly within their physically meaningful ranges. The modeled surface height change was evaluated against the two stake locations in the lower ablation zone (SH11, 4760m) and in the upper ablation zone (SH22, 4816m), respectively. The optimal parameter set for each point achieved good model skill but if we transfer the best parameter combination from one stake site to the other stake site model errors increases significantly. The same happens if we optimize the model parameters for each year individually and transfer
Investigation of RADTRAN Stop Model input parameters for truck stops
International Nuclear Information System (INIS)
Griego, N.R.; Smith, J.D.; Neuhauser, K.S.
1996-01-01
RADTRAN is a computer code for estimating the risks and consequences as transport of radioactive materials (RAM). RADTRAN was developed and is maintained by Sandia National Laboratories for the US Department of Energy (DOE). For incident-free transportation, the dose to persons exposed while the shipment is stopped is frequently a major percentage of the overall dose. This dose is referred to as Stop Dose and is calculated by the Stop Model. Because stop dose is a significant portion of the overall dose associated with RAM transport, the values used as input for the Stop Model are important. Therefore, an investigation of typical values for RADTRAN Stop Parameters for truck stops was performed. The resulting data from these investigations were analyzed to provide mean values, standard deviations, and histograms. Hence, the mean values can be used when an analyst does not have a basis for selecting other input values for the Stop Model. In addition, the histograms and their characteristics can be used to guide statistical sampling techniques to measure sensitivity of the RADTRAN calculated Stop Dose to the uncertainties in the stop model input parameters. This paper discusses the details and presents the results of the investigation of stop model input parameters at truck stops
Four-parameter analytical local model potential for atoms
International Nuclear Information System (INIS)
Fei, Yu; Jiu-Xun, Sun; Rong-Gang, Tian; Wei, Yang
2009-01-01
Analytical local model potential for modeling the interaction in an atom reduces the computational effort in electronic structure calculations significantly. A new four-parameter analytical local model potential is proposed for atoms Li through Lr, and the values of four parameters are shell-independent and obtained by fitting the results of X a method. At the same time, the energy eigenvalues, the radial wave functions and the total energies of electrons are obtained by solving the radial Schrödinger equation with a new form of potential function by Numerov's numerical method. The results show that our new form of potential function is suitable for high, medium and low Z atoms. A comparison among the new potential function and other analytical potential functions shows the greater flexibility and greater accuracy of the present new potential function. (atomic and molecular physics)
Improving the transferability of hydrological model parameters under changing conditions
Huang, Yingchun; Bárdossy, András
2014-05-01
Hydrological models are widely utilized to describe catchment behaviors with observed hydro-meteorological data. Hydrological process may be considered as non-stationary under the changing climate and land use conditions. An applicable hydrological model should be able to capture the essential features of the target catchment and therefore be transferable to different conditions. At present, many model applications based on the stationary assumptions are not sufficient for predicting further changes or time variability. The aim of this study is to explore new model calibration methods in order to improve the transferability of model parameters. To cope with the instability of model parameters calibrated on catchments in non-stationary conditions, we investigate the idea of simultaneously calibration on streamflow records for the period with dissimilar climate characteristics. In additional, a weather based weighting function is implemented to adjust the calibration period to future trends. For regions with limited data and ungauged basins, the common calibration was applied by using information from similar catchments. Result shows the model performance and transfer quantity could be well improved via common calibration. This model calibration approach will be used to enhance regional water management and flood forecasting capabilities.
Energy Technology Data Exchange (ETDEWEB)
Brauchler, R.; Doetsch, J.; Dietrich, P.; Sauter, M.
2012-01-10
In this study, hydraulic and seismic tomographic measurements were used to derive a site-specific relationship between the geophysical parameter p-wave velocity and the hydraulic parameters, diffusivity and specific storage. Our field study includes diffusivity tomograms derived from hydraulic travel time tomography, specific storage tomograms, derived from hydraulic attenuation tomography, and p-wave velocity tomograms, derived from seismic tomography. The tomographic inversion was performed in all three cases with the SIRT (Simultaneous Iterative Reconstruction Technique) algorithm, using a ray tracing technique with curved trajectories. The experimental set-up was designed such that the p-wave velocity tomogram overlaps the hydraulic tomograms by half. The experiments were performed at a wellcharacterized sand and gravel aquifer, located in the Leine River valley near Göttingen, Germany. Access to the shallow subsurface was provided by direct-push technology. The high spatial resolution of hydraulic and seismic tomography was exploited to derive representative site-specific relationships between the hydraulic and geophysical parameters, based on the area where geophysical and hydraulic tests were performed. The transformation of the p-wave velocities into hydraulic properties was undertaken using a k-means cluster analysis. Results demonstrate that the combination of hydraulic and geophysical tomographic data is a promising approach to improve hydrogeophysical site characterization.
Analyses of precooling parameters for a bottom flooding ECCS rewetting velocity model
International Nuclear Information System (INIS)
Chun, M.H.
1981-01-01
An extension work of the previous paper on the rewetting velocity model is presented. Application of the rewetting velocity model presented elsewhere requires a priori values of phi. In the absence of phi values, film boiling heat transfer coefficient (hsub(df)) and fog-film length (1) data are needed. To provide these informations, a modified Bromley's correlation is first derived and used to obtain hsub(df) values at higher pressure conditions. In addition, the analysis of the precooling parameters, such as phi and 1 is further extended using much more expensive PWR FLECHT data. Thus, the applicable range of the rewetting velocity model is further expanded in this work. (author)
Impulsive synchronization and parameter mismatch of the three-variable autocatalator model
International Nuclear Information System (INIS)
Li, Yang; Liao, Xiaofeng; Li, Chuandong; Huang, Tingwen; Yang, Degang
2007-01-01
The synchronization problems of the three-variable autocatalator model via impulsive control approach are investigated; several theorems on the stability of impulsive control systems are also investigated. These theorems are then used to find the conditions under which the three-variable autocatalator model can be asymptotically controlled to the equilibrium point. This Letter derives some sufficient conditions for the stabilization and synchronization of a three-variable autocatalator model via impulsive control with varying impulsive intervals. Furthermore, we address the chaos quasi-synchronization in the presence of single-parameter mismatch. To illustrate the effectiveness of the new scheme, several numerical examples are given
Directory of Open Access Journals (Sweden)
Dirk Reith
2013-09-01
Full Text Available Molecular modeling is an important subdomain in the field of computational modeling, regarding both scientific and industrial applications. This is because computer simulations on a molecular level are a virtuous instrument to study the impact of microscopic on macroscopic phenomena. Accurate molecular models are indispensable for such simulations in order to predict physical target observables, like density, pressure, diffusion coefficients or energetic properties, quantitatively over a wide range of temperatures. Thereby, molecular interactions are described mathematically by force fields. The mathematical description includes parameters for both intramolecular and intermolecular interactions. While intramolecular force field parameters can be determined by quantum mechanics, the parameterization of the intermolecular part is often tedious. Recently, an empirical procedure, based on the minimization of a loss function between simulated and experimental physical properties, was published by the authors. Thereby, efficient gradient-based numerical optimization algorithms were used. However, empirical force field optimization is inhibited by the two following central issues appearing in molecular simulations: firstly, they are extremely time-consuming, even on modern and high-performance computer clusters, and secondly, simulation data is affected by statistical noise. The latter provokes the fact that an accurate computation of gradients or Hessians is nearly impossible close to a local or global minimum, mainly because the loss function is flat. Therefore, the question arises of whether to apply a derivative-free method approximating the loss function by an appropriate model function. In this paper, a new Sparse Grid-based Optimization Workflow (SpaGrOW is presented, which accomplishes this task robustly and, at the same time, keeps the number of time-consuming simulations relatively small. This is achieved by an efficient sampling procedure
A simple but accurate procedure for solving the five-parameter model
International Nuclear Information System (INIS)
Mares, Oana; Paulescu, Marius; Badescu, Viorel
2015-01-01
Highlights: • A new procedure for extracting the parameters of the one-diode model is proposed. • Only the basic information listed in the datasheet of PV modules are required. • Results demonstrate a simple, robust and accurate procedure. - Abstract: The current–voltage characteristic of a photovoltaic module is typically evaluated by using a model based on the solar cell equivalent circuit. The complexity of the procedure applied for extracting the model parameters depends on data available in manufacture’s datasheet. Since the datasheet is not detailed enough, simplified models have to be used in many cases. This paper proposes a new procedure for extracting the parameters of the one-diode model in standard test conditions, using only the basic data listed by all manufactures in datasheet (short circuit current, open circuit voltage and maximum power point). The procedure is validated by using manufacturers’ data for six commercially crystalline silicon photovoltaic modules. Comparing the computed and measured current–voltage characteristics the determination coefficient is in the range 0.976–0.998. Thus, the proposed procedure represents a feasible tool for solving the five-parameter model applied to crystalline silicon photovoltaic modules. The procedure is described in detail, to guide potential users to derive similar models for other types of photovoltaic modules.
Cancer treatment model with the Caputo-Fabrizio fractional derivative
Ali Dokuyucu, Mustafa; Celik, Ercan; Bulut, Hasan; Mehmet Baskonus, Haci
2018-03-01
In this article, a model for cancer treatment is examined. The model is integrated into the Caputo-Fabrizio fractional derivative first, to examine the existence of the solution. Then, the uniqueness of the solution is investigated and we identified under which conditions the model provides a unique solution.
Finite BRST Mapping in Higher-Derivative Models
Moshin, Pavel Yu.; Upadhyay, Sudhaker; Castro, Ricardo A.
2017-08-01
We continue the study of finite field-dependent BRST (FFBRST) symmetry in the quantum theory of gauge fields. An expression for the Jacobian of path integral measure is presented, depending on a finite field-dependent parameter, and the FFBRST symmetry is then applied to a number of well-established quantum gauge theories in a form which incudes higher-derivative terms. Specifically, we examine the corresponding versions of the Maxwell theory, non-Abelian vector field theory, and gravitation theory. We present a systematic mapping between different forms of gauge-fixing, including those with higher-derivative terms, for which these theories have better renormalization properties. In doing so, we also provide the independence of the S-matrix from a particular gauge-fixing with higher derivatives. Following this method, a higher-derivative quantum action can be constructed for any gauge theory in the FFBRST framework.
EMF 7 model comparisons: key relationships and parameters
Energy Technology Data Exchange (ETDEWEB)
Hickman, B.G.
1983-12-01
A simplified textbook model of aggregate demand and supply interprets the similarities and differences in the price and income responses of the various EMF 7 models to oil and policy shocks. The simplified model is a marriage of Hicks' classic IS-LM formulation of the Keynesian theory of effective demand with a rudimentary model of aggregate supply, combining a structural Phillips curve for wage determination and a markup theory of price determination. The reduced-form income equation from the fix-price IS-LM model is used to define an aggregate demand (AD) locus in P-Y space, showing alternative pairs of the implicit GNP deflator and real GNP which would simultaneously satisfy the saving-investment identity and the condition for money market equilibrium. An aggregate supply (AS) schedule is derived by a similar reduction of relations between output and labor demand, unemployment and wage inflation, and the wage-price-productivity nexus governing markup pricing. Given a particular econometric model it is possible to derive IS and LM curves algebraically. The resulting locuses would show alternative combinations of interest rate and real income which equilibrate real income identity on the IS side and the demand and supply of money on the LM side. By further substitution the reduced form fix-price income relation could be obtained for direct quantification of the AD locus. The AS schedule is obtainable by algebraic reduction of the structural supply side equations.
Modeling extreme events: Sample fraction adaptive choice in parameter estimation
Neves, Manuela; Gomes, Ivette; Figueiredo, Fernanda; Gomes, Dora Prata
2012-09-01
When modeling extreme events there are a few primordial parameters, among which we refer the extreme value index and the extremal index. The extreme value index measures the right tail-weight of the underlying distribution and the extremal index characterizes the degree of local dependence in the extremes of a stationary sequence. Most of the semi-parametric estimators of these parameters show the same type of behaviour: nice asymptotic properties, but a high variance for small values of k, the number of upper order statistics to be used in the estimation, and a high bias for large values of k. This shows a real need for the choice of k. Choosing some well-known estimators of those parameters we revisit the application of a heuristic algorithm for the adaptive choice of k. The procedure is applied to some simulated samples as well as to some real data sets.
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.
Pettey, W B P; Carter, M E; Toth, D J A; Samore, M H; Gundlapalli, A V
2017-07-01
During the recent Ebola crisis in West Africa, individual person-level details of disease onset, transmissions, and outcomes such as survival or death were reported in online news media. We set out to document disease transmission chains for Ebola, with the goal of generating a timely account that could be used for surveillance, mathematical modeling, and public health decision-making. By accessing public web pages only, such as locally produced newspapers and blogs, we created a transmission chain involving two Ebola clusters in West Africa that compared favorably with other published transmission chains, and derived parameters for a mathematical model of Ebola disease transmission that were not statistically different from those derived from published sources. We present a protocol for responsibly gleaning epidemiological facts, transmission model parameters, and useful details from affected communities using mostly indigenously produced sources. After comparing our transmission parameters to published parameters, we discuss additional benefits of our method, such as gaining practical information about the affected community, its infrastructure, politics, and culture. We also briefly compare our method to similar efforts that used mostly non-indigenous online sources to generate epidemiological information.
Model parameter learning using Kullback-Leibler divergence
Lin, Chungwei; Marks, Tim K.; Pajovic, Milutin; Watanabe, Shinji; Tung, Chih-kuan
2018-02-01
In this paper, we address the following problem: For a given set of spin configurations whose probability distribution is of the Boltzmann type, how do we determine the model coupling parameters? We demonstrate that directly minimizing the Kullback-Leibler divergence is an efficient method. We test this method against the Ising and XY models on the one-dimensional (1D) and two-dimensional (2D) lattices, and provide two estimators to quantify the model quality. We apply this method to two types of problems. First, we apply it to the real-space renormalization group (RG). We find that the obtained RG flow is sufficiently good for determining the phase boundary (within 1% of the exact result) and the critical point, but not accurate enough for critical exponents. The proposed method provides a simple way to numerically estimate amplitudes of the interactions typically truncated in the real-space RG procedure. Second, we apply this method to the dynamical system composed of self-propelled particles, where we extract the parameter of a statistical model (a generalized XY model) from a dynamical system described by the Viscek model. We are able to obtain reasonable coupling values corresponding to different noise strengths of the Viscek model. Our method is thus able to provide quantitative analysis of dynamical systems composed of self-propelled particles.
DEFF Research Database (Denmark)
Ferrari, A.; Gutierrez, S.; Sin, Gürkan
2016-01-01
A steady state model for a production scale milk drying process was built to help process understanding and optimization studies. It involves a spray chamber and also internal/external fluid beds. The model was subjected to a comprehensive statistical analysis for quality assurance using...... sensitivity analysis of inputs/parameters, and uncertainty analysis to estimate confidence intervals on parameters and model predictions (error propagation). Variance based sensitivity analysis (Sobol's method) was used to quantify the influence of inputs on the final powder moisture as the model output...... at chamber inlet air (variation > 100%). The sensitivity analysis results suggest exploring improvements in the current control (Proportional Integral Derivative) for moisture content at concentrate chamber feed in order to reduce the output variance. It is also confirmed that humidity control at chamber...
Biosphere modelling for a HLW repository - scenario and parameter variations
International Nuclear Information System (INIS)
Grogan, H.
1985-03-01
In Switzerland high-level radioactive wastes have been considered for disposal in deep-lying crystalline formations. The individual doses to man resulting from radionuclides entering the biosphere via groundwater transport are calculated. The main recipient area modelled, which constitutes the base case, is a broad gravel terrace sited along the south bank of the river Rhine. An alternative recipient region, a small valley with a well, is also modelled. A number of parameter variations are performed in order to ascertain their impact on the doses. Finally two scenario changes are modelled somewhat simplistically, these consider different prevailing climates, namely tundra and a warmer climate than present. In the base case negligibly low doses to man in the long term, resulting from the existence of a HLW repository have been calculated. Cs-135 results in the largest dose (8.4E-7 mrem/y at 6.1E+6 y) while Np-237 gives the largest dose from the actinides (3.6E-8 mrem/y). The response of the model to parameter variations cannot be easily predicted due to non-linear coupling of many of the parameters. However, the calculated doses were negligibly low in all cases as were those resulting from the two scenario variations. (author)
Thermal Model Parameter Identification of a Lithium Battery
Directory of Open Access Journals (Sweden)
Dirk Nissing
2017-01-01
Full Text Available The temperature of a Lithium battery cell is important for its performance, efficiency, safety, and capacity and is influenced by the environmental temperature and by the charging and discharging process itself. Battery Management Systems (BMS take into account this effect. As the temperature at the battery cell is difficult to measure, often the temperature is measured on or nearby the poles of the cell, although the accuracy of predicting the cell temperature with those quantities is limited. Therefore a thermal model of the battery is used in order to calculate and estimate the cell temperature. This paper uses a simple RC-network representation for the thermal model and shows how the thermal parameters are identified using input/output measurements only, where the load current of the battery represents the input while the temperatures at the poles represent the outputs of the measurement. With a single measurement the eight model parameters (thermal resistances, electric contact resistances, and heat capacities can be determined using the method of least-square. Experimental results show that the simple model with the identified parameters fits very accurately to the measurements.
Contaminant transport in aquifers: improving the determination of model parameters
International Nuclear Information System (INIS)
Sabino, C.V.S.; Moreira, R.M.; Lula, Z.L.; Chausson, Y.; Magalhaes, W.F.; Vianna, M.N.
1998-01-01
Parameters conditioning the migration behavior of cesium and mercury are measured with their tracers 137 Cs and 203 Hg in the laboratory, using both batch and column experiments. Batch tests were used to define the sorption isotherm characteristics. Also investigated were the influences of some test parameters, in particular those due to the volume of water to mass of soil ratio (V/m). A provisional relationship between V/m and the distribution coefficient, K d , has been advanced, and a procedure to estimate K d 's valid for environmental values of the ratio V/m has been suggested. Column tests provided the parameters for a transport model. A major problem to be dealt with in such tests is the collimation of the radioactivity probe. Besides mechanically optimizing the collimator, a deconvolution procedure has been suggested and tested, with statistical criteria, to filter off both noise and spurious tracer signals. Correction procedures for the integrating effect introduced by sampling at the exit of columns have also been developed. These techniques may be helpful in increasing the accuracy required in the measurement of parameters conditioning contaminant migration in soils, thus allowing more reliable predictions based on mathematical model applications. (author)
HOM study and parameter calculation of the TESLA cavity model
Zeng, Ri-Hua; Gerigk Frank; Wang Guang-Wei; Wegner Rolf; Liu Rong; Schuh Marcel
2010-01-01
The Superconducting Proton Linac (SPL) is the project for a superconducting, high current H-accelerator at CERN. To find dangerous higher order modes (HOMs) in the SPL superconducting cavities, simulation and analysis for the cavity model using simulation tools are necessary. The. existing TESLA 9-cell cavity geometry data have been used for the initial construction of the models in HFSS. Monopole, dipole and quadrupole modes have been obtained by applying different symmetry boundaries on various cavity models. In calculation, scripting language in HFSS was used to create scripts to automatically calculate the parameters of modes in these cavity models (these scripts are also available in other cavities with different cell numbers and geometric structures). The results calculated automatically are then compared with the values given in the TESLA paper. The optimized cavity model with the minimum error will be taken as the base for further simulation of the SPL cavities.
Progressive Learning of Topic Modeling Parameters: A Visual Analytics Framework.
El-Assady, Mennatallah; Sevastjanova, Rita; Sperrle, Fabian; Keim, Daniel; Collins, Christopher
2018-01-01
Topic modeling algorithms are widely used to analyze the thematic composition of text corpora but remain difficult to interpret and adjust. Addressing these limitations, we present a modular visual analytics framework, tackling the understandability and adaptability of topic models through a user-driven reinforcement learning process which does not require a deep understanding of the underlying topic modeling algorithms. Given a document corpus, our approach initializes two algorithm configurations based on a parameter space analysis that enhances document separability. We abstract the model complexity in an interactive visual workspace for exploring the automatic matching results of two models, investigating topic summaries, analyzing parameter distributions, and reviewing documents. The main contribution of our work is an iterative decision-making technique in which users provide a document-based relevance feedback that allows the framework to converge to a user-endorsed topic distribution. We also report feedback from a two-stage study which shows that our technique results in topic model quality improvements on two independent measures.
The definition of input parameters for modelling of energetic subsystems
Directory of Open Access Journals (Sweden)
Ptacek M.
2013-06-01
Full Text Available This paper is a short review and a basic description of mathematical models of renewable energy sources which present individual investigated subsystems of a system created in Matlab/Simulink. It solves the physical and mathematical relationships of photovoltaic and wind energy sources that are often connected to the distribution networks. The fuel cell technology is much less connected to the distribution networks but it could be promising in the near future. Therefore, the paper informs about a new dynamic model of the low-temperature fuel cell subsystem, and the main input parameters are defined as well. Finally, the main evaluated and achieved graphic results for the suggested parameters and for all the individual subsystems mentioned above are shown.
The definition of input parameters for modelling of energetic subsystems
Ptacek, M.
2013-06-01
This paper is a short review and a basic description of mathematical models of renewable energy sources which present individual investigated subsystems of a system created in Matlab/Simulink. It solves the physical and mathematical relationships of photovoltaic and wind energy sources that are often connected to the distribution networks. The fuel cell technology is much less connected to the distribution networks but it could be promising in the near future. Therefore, the paper informs about a new dynamic model of the low-temperature fuel cell subsystem, and the main input parameters are defined as well. Finally, the main evaluated and achieved graphic results for the suggested parameters and for all the individual subsystems mentioned above are shown.
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 ...
Empirical flow parameters : a tool for hydraulic model validity
Asquith, William H.; Burley, Thomas E.; Cleveland, Theodore G.
2013-01-01
The objectives of this project were (1) To determine and present from existing data in Texas, relations between observed stream flow, topographic slope, mean section velocity, and other hydraulic factors, to produce charts such as Figure 1 and to produce empirical distributions of the various flow parameters to provide a methodology to "check if model results are way off!"; (2) To produce a statistical regional tool to estimate mean velocity or other selected parameters for storm flows or other conditional discharges at ungauged locations (most bridge crossings) in Texas to provide a secondary way to compare such values to a conventional hydraulic modeling approach. (3.) To present ancillary values such as Froude number, stream power, Rosgen channel classification, sinuosity, and other selected characteristics (readily determinable from existing data) to provide additional information to engineers concerned with the hydraulic-soil-foundation component of transportation infrastructure.
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...... be disregarded without significant loss of accuracy. Finally, special attention is drawn to the influence of the skirt stiffness, i.e. whether the embedded part of the caisson is rigid or flexible....
A study of model parameters associated with the urban climate using HCMM data
1981-01-01
Infrared and visible data from the Heat Capacity Mapping Mission (HCMM) satellite were used to study the intensity of the urban heat island, commonly defined as the temperature difference between the center of the city and the surrounding suburban and rural regions, as a function of changes in the season and changes in meteorological conditions in order to derive various parameters which may be used in numerical models for urban climate. The analysis was focused on the city of St. Louis; and in situ data from St. Louis was combined with HCMM data in order to derive the various parameters. The HCMM data were mapped onto a Mercator projection map of the city and ground temperatures were established using data corrected for the effects of atmospheric absorption. The corrected and uncorrected HCMM data were compared to determine the magnitude of the error induced by atmospheric effects.
A Study on Stability of Limit Cycle Walking Model with Feet: Parameter Study
Directory of Open Access Journals (Sweden)
Yonggwon Jeon
2013-01-01
Full Text Available In this paper, two kinds of feet, namely, curved and flat feet, are added to limit cycle walking model to investigate its stability properties. Although both models are already proposed and are investigated, most previous works are focused on efficiency and gait behaviors. Only the stability properties of the simplest walking model conceived Garcia et al. are well defined. Therefore, there is still a need for a precise research on the effect of feet, especially in the view of local stability, bifurcation route to chaos, global stability, falling boundary and energy balance line. Therefore, this article revisits the stability analysis of limit cycle walking model with various foot shape. To analyze the effects of feet, we re-derive the equation of motion of modified models by adding one more parameter of foot shape than the simplest walking model. Also, the falling boundary and energy balance line of modified models are derived to get proper initial conditions for stable walking and to explain global stability. Simulation results show us that the curved feet can enlarge both stable walking range and area of basin of attraction while the case of flat feet depends on foot shape parameter.
Modeling Water Quality Parameters Using Data-driven Methods
Directory of Open Access Journals (Sweden)
Shima Soleimani
2017-02-01
Full Text Available Introduction: Surface water bodies are the most easily available water resources. Increase use and waste water withdrawal of surface water causes drastic changes in surface water quality. Water quality, importance as the most vulnerable and important water supply resources is absolutely clear. Unfortunately, in the recent years because of city population increase, economical improvement, and industrial product increase, entry of pollutants to water bodies has been increased. According to that water quality parameters express physical, chemical, and biological water features. So the importance of water quality monitoring is necessary more than before. Each of various uses of water, such as agriculture, drinking, industry, and aquaculture needs the water with a special quality. In the other hand, the exact estimation of concentration of water quality parameter is significant. Material and Methods: In this research, first two input variable models as selection methods (namely, correlation coefficient and principal component analysis were applied to select the model inputs. Data processing is consisting of three steps, (1 data considering, (2 identification of input data which have efficient on output data, and (3 selecting the training and testing data. Genetic Algorithm-Least Square Support Vector Regression (GA-LSSVR algorithm were developed to model the water quality parameters. In the LSSVR method is assumed that the relationship between input and output variables is nonlinear, but by using a nonlinear mapping relation can create a space which is named feature space in which relationship between input and output variables is defined linear. The developed algorithm is able to gain maximize the accuracy of the LSSVR method with auto LSSVR parameters. Genetic algorithm (GA is one of evolutionary algorithm which automatically can find the optimum coefficient of Least Square Support Vector Regression (LSSVR. The GA-LSSVR algorithm was employed to
A procedure for determining parameters of a simplified ligament model.
Barrett, Jeff M; Callaghan, Jack P
2018-01-03
A previous mathematical model of ligament force-generation treated their behavior as a population of collagen fibres arranged in parallel. When damage was ignored in this model, an expression for ligament force in terms of the deflection, x, effective stiffness, k, mean collagen slack length, μ, and the standard deviation of slack lengths, σ, was obtained. We present a simple three-step method for determining the three model parameters (k, μ, and σ) from force-deflection data: (1) determine the equation of the line in the linear region of this curve, its slope is k and its x -intercept is -μ; (2) interpolate the force-deflection data when x is -μ to obtain F 0 ; (3) calculate σ with the equation σ=2πF 0 /k. Results from this method were in good agreement to those obtained from a least-squares procedure on experimental data - all falling within 6%. Therefore, parameters obtained using the proposed method provide a systematic way of reporting ligament parameters, or for obtaining an initial guess for nonlinear least-squares. Copyright © 2017 Elsevier Ltd. All rights reserved.
Modelling spatial-temporal and coordinative parameters in swimming.
Seifert, L; Chollet, D
2009-07-01
This study modelled the changes in spatial-temporal and coordinative parameters through race paces in the four swimming strokes. The arm and leg phases in simultaneous strokes (butterfly and breaststroke) and the inter-arm phases in alternating strokes (crawl and backstroke) were identified by video analysis to calculate the time gaps between propulsive phases. The relationships among velocity, stroke rate, stroke length and coordination were modelled by polynomial regression. Twelve elite male swimmers swam at four race paces. Quadratic regression modelled the changes in spatial-temporal and coordinative parameters with velocity increases for all four strokes. First, the quadratic regression between coordination and velocity showed changes common to all four strokes. Notably, the time gaps between the key points defining the beginning and end of the stroke phases decreased with increases in velocity, which led to decreases in glide times and increases in the continuity between propulsive phases. Conjointly, the quadratic regression among stroke rate, stroke length and velocity was similar to the changes in coordination, suggesting that these parameters may influence coordination. The main practical application for coaches and scientists is that ineffective time gaps can be distinguished from those that simply reflect an individual swimmer's profile by monitoring the glide times within a stroke cycle. In the case of ineffective time gaps, targeted training could improve the swimmer's management of glide time.
Directory of Open Access Journals (Sweden)
W. Castaings
2009-04-01
Full Text Available Variational methods are widely used for the analysis and control of computationally intensive spatially distributed systems. In particular, the adjoint state method enables a very efficient calculation of the derivatives of an objective function (response function to be analysed or cost function to be optimised with respect to model inputs.
In this contribution, it is shown that the potential of variational methods for distributed catchment scale hydrology should be considered. A distributed flash flood model, coupling kinematic wave overland flow and Green Ampt infiltration, is applied to a small catchment of the Thoré basin and used as a relatively simple (synthetic observations but didactic application case.
It is shown that forward and adjoint sensitivity analysis provide a local but extensive insight on the relation between the assigned model parameters and the simulated hydrological response. Spatially distributed parameter sensitivities can be obtained for a very modest calculation effort (~6 times the computing time of a single model run and the singular value decomposition (SVD of the Jacobian matrix provides an interesting perspective for the analysis of the rainfall-runoff relation.
For the estimation of model parameters, adjoint-based derivatives were found exceedingly efficient in driving a bound-constrained quasi-Newton algorithm. The reference parameter set is retrieved independently from the optimization initial condition when the very common dimension reduction strategy (i.e. scalar multipliers is adopted.
Furthermore, the sensitivity analysis results suggest that most of the variability in this high-dimensional parameter space can be captured with a few orthogonal directions. A parametrization based on the SVD leading singular vectors was found very promising but should be combined with another regularization strategy in order to prevent overfitting.
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…
Directory of Open Access Journals (Sweden)
Tashkova Katerina
2011-10-01
Full Text Available Abstract Background We address the task of parameter estimation in models of the dynamics of biological systems based on ordinary differential equations (ODEs from measured data, where the models are typically non-linear and have many parameters, the measurements are imperfect due to noise, and the studied system can often be only partially observed. A representative task is to estimate the parameters in a model of the dynamics of endocytosis, i.e., endosome maturation, reflected in a cut-out switch transition between the Rab5 and Rab7 domain protein concentrations, from experimental measurements of these concentrations. The general parameter estimation task and the specific instance considered here are challenging optimization problems, calling for the use of advanced meta-heuristic optimization methods, such as evolutionary or swarm-based methods. Results We apply three global-search meta-heuristic algorithms for numerical optimization, i.e., differential ant-stigmergy algorithm (DASA, particle-swarm optimization (PSO, and differential evolution (DE, as well as a local-search derivative-based algorithm 717 (A717 to the task of estimating parameters in ODEs. We evaluate their performance on the considered representative task along a number of metrics, including the quality of reconstructing the system output and the complete dynamics, as well as the speed of convergence, both on real-experimental data and on artificial pseudo-experimental data with varying amounts of noise. We compare the four optimization methods under a range of observation scenarios, where data of different completeness and accuracy of interpretation are given as input. Conclusions Overall, the global meta-heuristic methods (DASA, PSO, and DE clearly and significantly outperform the local derivative-based method (A717. Among the three meta-heuristics, differential evolution (DE performs best in terms of the objective function, i.e., reconstructing the output, and in terms of
2011-01-01
Background We address the task of parameter estimation in models of the dynamics of biological systems based on ordinary differential equations (ODEs) from measured data, where the models are typically non-linear and have many parameters, the measurements are imperfect due to noise, and the studied system can often be only partially observed. A representative task is to estimate the parameters in a model of the dynamics of endocytosis, i.e., endosome maturation, reflected in a cut-out switch transition between the Rab5 and Rab7 domain protein concentrations, from experimental measurements of these concentrations. The general parameter estimation task and the specific instance considered here are challenging optimization problems, calling for the use of advanced meta-heuristic optimization methods, such as evolutionary or swarm-based methods. Results We apply three global-search meta-heuristic algorithms for numerical optimization, i.e., differential ant-stigmergy algorithm (DASA), particle-swarm optimization (PSO), and differential evolution (DE), as well as a local-search derivative-based algorithm 717 (A717) to the task of estimating parameters in ODEs. We evaluate their performance on the considered representative task along a number of metrics, including the quality of reconstructing the system output and the complete dynamics, as well as the speed of convergence, both on real-experimental data and on artificial pseudo-experimental data with varying amounts of noise. We compare the four optimization methods under a range of observation scenarios, where data of different completeness and accuracy of interpretation are given as input. Conclusions Overall, the global meta-heuristic methods (DASA, PSO, and DE) clearly and significantly outperform the local derivative-based method (A717). Among the three meta-heuristics, differential evolution (DE) performs best in terms of the objective function, i.e., reconstructing the output, and in terms of convergence. These
Local sensitivity analysis of a distributed parameters water quality model
International Nuclear Information System (INIS)
Pastres, R.; Franco, D.; Pecenik, G.; Solidoro, C.; Dejak, C.
1997-01-01
A local sensitivity analysis is presented of a 1D water-quality reaction-diffusion model. The model describes the seasonal evolution of one of the deepest channels of the lagoon of Venice, that is affected by nutrient loads from the industrial area and heat emission from a power plant. Its state variables are: water temperature, concentrations of reduced and oxidized nitrogen, Reactive Phosphorous (RP), phytoplankton, and zooplankton densities, Dissolved Oxygen (DO) and Biological Oxygen Demand (BOD). Attention has been focused on the identifiability and the ranking of the parameters related to primary production in different mixing conditions
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.
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.
Testing variational estimation of process parameters and initial conditions of an earth system model
Directory of Open Access Journals (Sweden)
Simon Blessing
2014-03-01
Full Text Available We present a variational assimilation system around a coarse resolution Earth System Model (ESM and apply it for estimating initial conditions and parameters of the model. The system is based on derivative information that is efficiently provided by the ESM's adjoint, which has been generated through automatic differentiation of the model's source code. In our variational approach, the length of the feasible assimilation window is limited by the size of the domain in control space over which the approximation by the derivative is valid. This validity domain is reduced by non-smooth process representations. We show that in this respect the ocean component is less critical than the atmospheric component. We demonstrate how the feasible assimilation window can be extended to several weeks by modifying the implementation of specific process representations and by switching off processes such as precipitation.
Serranti, S; Trella, A; Bonifazi, G; Izquierdo, C Garcia
2018-02-12
In this work the possibility to apply hyperspectral imaging as a fast and non-destructive technique for the monitoring of the production process at pilot plant scale of an innovative biowaste-derived fertilizer was explored. Different mixtures of urban organic waste, farm organic residues, biochar and vegetable active principles were selected and utilized in two different European countries, Italy and Spain, for the production of the innovative fertilizer. The biowaste-derived fertilizer samples were collected from the pilot plant piles at different curing time and acquired by the hyperspectral imaging device. Spectra have been collected in the near infrared wavelength range (1000-1700 nm). Conventional analyses were carried out on the same samples in order to find correlations between the physical-chemical parameters detected at laboratory scale, and the acquired reflectance spectra. The investigated parameters were: pH, electrical conductivity, soluble total organic carbon and soluble total nitrogen. Hyperspectral data were processed adopting chemometric strategies through the application of principal component analysis, for exploratory purposes, and partial least squares analysis to establish correlations between spectral features and measured physical-chemical parameters. Good correlations, with R 2 ranging between 0.85 and 0.96, were obtained for all the investigated parameters. Results showed as the proposed approach, based on hyperspectral imaging, is suitable to be adopted for a rapid and non-destructive monitoring of waste-derived fertilizer production. Copyright © 2018 Elsevier Ltd. All rights reserved.
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
Rosenblatt, Marcus; Timmer, Jens; Kaschek, Daniel
2016-01-01
Ordinary differential equation models have become a wide-spread approach to analyze dynamical systems and understand underlying mechanisms. Model parameters are often unknown and have to be estimated from experimental data, e.g., by maximum-likelihood estimation. In particular, models of biological systems contain a large number of parameters. To reduce the dimensionality of the parameter space, steady-state information is incorporated in the parameter estimation process. For non-linear models, analytical steady-state calculation typically leads to higher-order polynomial equations for which no closed-form solutions can be obtained. This can be circumvented by solving the steady-state equations for kinetic parameters, which results in a linear equation system with comparatively simple solutions. At the same time multiplicity of steady-state solutions is avoided, which otherwise is problematic for optimization. When solved for kinetic parameters, however, steady-state constraints tend to become negative for particular model specifications, thus, generating new types of optimization problems. Here, we present an algorithm based on graph theory that derives non-negative, analytical steady-state expressions by stepwise removal of cyclic dependencies between dynamical variables. The algorithm avoids multiple steady-state solutions by construction. We show that our method is applicable to most common classes of biochemical reaction networks containing inhibition terms, mass-action and Hill-type kinetic equations. Comparing the performance of parameter estimation for different analytical and numerical methods of incorporating steady-state information, we show that our approach is especially well-tailored to guarantee a high success rate of optimization.
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...
Deriving Animal Movement Behaviors Using Movement Parameters Extracted from Location Data
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Maryam Teimouri
2018-02-01
Full Text Available We present a methodology for distinguishing between three types of animal movement behavior (foraging, resting, and walking based on high-frequency tracking data. For each animal we quantify an individual movement path. A movement path is a temporal sequence consisting of the steps through space taken by an animal. By selecting a set of appropriate movement parameters, we develop a method to assess movement behavioral states, reflected by changes in the movement parameters. The two fundamental tasks of our study are segmentation and clustering. By segmentation, we mean the partitioning of the trajectory into segments, which are homogeneous in terms of their movement parameters. By clustering, we mean grouping similar segments together according to their estimated movement parameters. The proposed method is evaluated using field observations (done by humans of movement behavior. We found that on average, our method agreed with the observational data (ground truth at a level of 80.75% ± 5.9% (SE.
Macquart, T.B.M.J.; Bordogna, MT; Lancelot, P.M.G.J.; De Breuker, R.
2016-01-01
The present paper proposes a set of blending constraints expressed in lamination parameter space, applicable during the continuous optimisation of composite structures. Thicknesses and ply orientations of large composite structures are often locally optimised in response to unequal spatial load
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.
Deriving the Dividend Discount Model in the Intermediate Microeconomics Class
Norman, Stephen; Schlaudraff, Jonathan; White, Karianne; Wills, Douglas
2013-01-01
In this article, the authors show that the dividend discount model can be derived using the basic intertemporal consumption model that is introduced in a typical intermediate microeconomics course. This result will be of use to instructors who teach microeconomics to finance students in that it demonstrates the value of utility maximization in…
A review of distributed parameter groundwater management modeling methods
Gorelick, Steven M.
1983-01-01
Models which solve the governing groundwater flow or solute transport equations in conjunction with optimization techniques, such as linear and quadratic programing, are powerful aquifer management tools. Groundwater management models fall in two general categories: hydraulics or policy evaluation and water allocation. Groundwater hydraulic management models enable the determination of optimal locations and pumping rates of numerous wells under a variety of restrictions placed upon local drawdown, hydraulic gradients, and water production targets. Groundwater policy evaluation and allocation models can be used to study the influence upon regional groundwater use of institutional policies such as taxes and quotas. Furthermore, fairly complex groundwater-surface water allocation problems can be handled using system decomposition and multilevel optimization. Experience from the few real world applications of groundwater optimization-management techniques is summarized. Classified separately are methods for groundwater quality management aimed at optimal waste disposal in the subsurface. This classification is composed of steady state and transient management models that determine disposal patterns in such a way that water quality is protected at supply locations. Classes of research missing from the literature are groundwater quality management models involving nonlinear constraints, models which join groundwater hydraulic and quality simulations with political-economic management considerations, and management models that include parameter uncertainty.
Vulnerable Derivatives and Good Deal Bounds: A Structural Model
DEFF Research Database (Denmark)
Murgoci, Agatha
2013-01-01
We price vulnerable derivatives -- i.e. derivatives where the counterparty may default. These are basically the derivatives traded on the over-the-counter (OTC) markets. Default is modeled in a structural framework. The technique employed for pricing is good deal bounds (GDBs). The method imposes...... can be obtained. We provide a link between the objective probability measure and the range of potential risk-neutral measures, which has an intuitive economic meaning. We also provide tight pricing bounds for European calls and show how to extend the call formula to pricing other financial products...
Dos Santos, P Lopes; Deshpande, Sunil; Rivera, Daniel E; Azevedo-Perdicoúlis, T-P; Ramos, J A; Younger, Jarred
2013-12-31
There is good evidence that naltrexone, an opioid antagonist, has a strong neuroprotective role and may be a potential drug for the treatment of fibromyalgia. In previous work, some of the authors used experimental clinical data to identify input-output linear time invariant models that were used to extract useful information about the effect of this drug on fibromyalgia symptoms. Additional factors such as anxiety, stress, mood, and headache, were considered as additive disturbances. However, it seems reasonable to think that these factors do not affect the drug actuation, but only the way in which a participant perceives how the drug actuates on herself. Under this hypothesis the linear time invariant models can be replaced by State-Space Affine Linear Parameter Varying models where the disturbances are seen as a scheduling signal signal only acting at the parameters of the output equation. In this paper a new algorithm for identifying such a model is proposed. This algorithm minimizes a quadratic criterion of the output error. Since the output error is a linear function of some parameters, the Affine Linear Parameter Varying system identification is formulated as a separable nonlinear least squares problem. Likewise other identification algorithms using gradient optimization methods several parameter derivatives are dynamical systems that must be simulated. In order to increase time efficiency a canonical parametrization that minimizes the number of systems to be simulated is chosen. The effectiveness of the algorithm is assessed in a case study where an Affine Parameter Varying Model is identified from the experimental data used in the previous study and compared with the time-invariant model.
Some notes on unobserved parameters (frailties) in reliability modeling
International Nuclear Information System (INIS)
Cha, Ji Hwan; Finkelstein, Maxim
2014-01-01
Unobserved random quantities (frailties) often appear in various reliability problems especially when dealing with the failure rates of items from heterogeneous populations. As the failure rate is a conditional characteristic, the distributions of these random quantities, similar to Bayesian approaches, are updated in accordance with the corresponding survival information. At some instances, apart from a statistical meaning, frailties can have also useful interpretations describing the underlying lifetime model. We discuss and clarify these issues in reliability context and present and analyze several meaningful examples. We consider the proportional hazards model with a random factor; the stress–strength model, where the unobserved strength of a system can be viewed as frailty; a parallel system with a random number of components and, finally, the first passage time problem for the Wiener process with random parameters. - Highlights: • We discuss and clarify the notion of frailty in reliability context and present and analyze several meaningful examples. • The paper provides a new insight and general perspective on reliability models with unobserved parameters. • The main message of the paper is well illustrated by several meaningful examples and emphasized by detailed discussion
International Nuclear Information System (INIS)
Hofer, E.; Hoffman, F.O.
1987-02-01
The uncertainty analysis of model predictions has to discriminate between two fundamentally different types of uncertainty. The presence of stochastic variability (Type 1 uncertainty) necessitates the use of a probabilistic model instead of the much simpler deterministic one. Lack of knowledge (Type 2 uncertainty), however, applies to deterministic as well as to probabilistic model predictions and often dominates over uncertainties of Type 1. The term ''probability'' is interpreted differently in the probabilistic analysis of either type of uncertainty. After these discriminations have been explained the discussion centers on the propagation of parameter uncertainties through the model, the derivation of quantitative uncertainty statements for model predictions and the presentation and interpretation of the results of a Type 2 uncertainty analysis. Various alternative approaches are compared for a very simple deterministic model
Hydrological Modelling and Parameter Identification for Green Roof
Lo, W.; Tung, C.
2012-12-01
Green roofs, a multilayered system covered by plants, can be used to replace traditional concrete roofs as one of various measures to mitigate the increasing stormwater runoff in the urban environment. Moreover, facing the high uncertainty of the climate change, the present engineering method as adaptation may be regarded as improper measurements; reversely, green roofs are unregretful and flexible, and thus are rather important and suitable. The related technology has been developed for several years and the researches evaluating the stormwater reduction performance of green roofs are ongoing prosperously. Many European counties, cities in the U.S., and other local governments incorporate green roof into the stormwater control policy. Therefore, in terms of stormwater management, it is necessary to develop a robust hydrologic model to quantify the efficacy of green roofs over different types of designs and environmental conditions. In this research, a physical based hydrologic model is proposed to simulate water flowing process in the green roof system. In particular, the model adopts the concept of water balance, bringing a relatively simple and intuitive idea. Also, the research compares the two methods in the surface water balance calculation. One is based on Green-Ampt equation, and the other is under the SCS curve number calculation. A green roof experiment is designed to collect weather data and water discharge. Then, the proposed model is verified with these observed data; furthermore, the parameters using in the model are calibrated to find appropriate values in the green roof hydrologic simulation. This research proposes a simple physical based hydrologic model and the measures to determine parameters for the model.
Modelling Technical and Economic Parameters in Selection of Manufacturing Devices
Directory of Open Access Journals (Sweden)
Naqib Daneshjo
2017-11-01
Full Text Available Sustainable science and technology development is also conditioned by continuous development of means of production which have a key role in structure of each production system. Mechanical nature of the means of production is complemented by controlling and electronic devices in context of intelligent industry. A selection of production machines for a technological process or technological project has so far been practically resolved, often only intuitively. With regard to increasing intelligence, the number of variable parameters that have to be considered when choosing a production device is also increasing. It is necessary to use computing techniques and decision making methods according to heuristic methods and more precise methodological procedures during the selection. The authors present an innovative model for optimization of technical and economic parameters in the selection of manufacturing devices for industry 4.0.
Roldán, J. B.; Miranda, E.; González-Cordero, G.; García-Fernández, P.; Romero-Zaliz, R.; González-Rodelas, P.; Aguilera, A. M.; González, M. B.; Jiménez-Molinos, F.
2018-01-01
A multivariate analysis of the parameters that characterize the reset process in Resistive Random Access Memory (RRAM) has been performed. The different correlations obtained can help to shed light on the current components that contribute in the Low Resistance State (LRS) of the technology considered. In addition, a screening method for the Quantum Point Contact (QPC) current component is presented. For this purpose, the second derivative of the current has been obtained using a novel numerical method which allows determining the QPC model parameters. Once the procedure is completed, a whole Resistive Switching (RS) series of thousands of curves is studied by means of a genetic algorithm. The extracted QPC parameter distributions are characterized in depth to get information about the filamentary pathways associated with LRS in the low voltage conduction regime.
Dynamic systems models new methods of parameter and state estimation
2016-01-01
This monograph is an exposition of a novel method for solving inverse problems, a method of parameter estimation for time series data collected from simulations of real experiments. These time series might be generated by measuring the dynamics of aircraft in flight, by the function of a hidden Markov model used in bioinformatics or speech recognition or when analyzing the dynamics of asset pricing provided by the nonlinear models of financial mathematics. Dynamic Systems Models demonstrates the use of algorithms based on polynomial approximation which have weaker requirements than already-popular iterative methods. Specifically, they do not require a first approximation of a root vector and they allow non-differentiable elements in the vector functions being approximated. The text covers all the points necessary for the understanding and use of polynomial approximation from the mathematical fundamentals, through algorithm development to the application of the method in, for instance, aeroplane flight dynamic...
Parameter Estimation for a Class of Lifetime Models
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Xinyang Ji
2014-01-01
Full Text Available Our purpose in this paper is to present a better method of parametric estimation for a bivariate nonlinear regression model, which takes the performance indicator of rubber aging as the dependent variable and time and temperature as the independent variables. We point out that the commonly used two-step method (TSM, which splits the model and estimate parameters separately, has limitation. Instead, we apply the Marquardt’s method (MM to implement parametric estimation directly for the model and compare these two methods of parametric estimation by random simulation. Our results show that MM has better effect of data fitting, more reasonable parametric estimates, and smaller prediction error compared with TSM.
The parameter space of Cubic Galileon models for cosmic acceleration
Bellini, Emilio
2013-01-01
We use recent measurements of the expansion history of the universe to place constraints on the parameter space of cubic Galileon models. This gives strong constraints on the Lagrangian of these models. Most dynamical terms in the Galileon Lagrangian are constraint to be small and the acceleration is effectively provided by a constant term in the scalar potential, thus reducing, effectively, to a LCDM model for current acceleration. The effective equation of state is indistinguishable from that of a cosmological constant w = -1 and the data constraint it to have no temporal variations of more than at the few % level. The energy density of the Galileon can contribute only to about 10% of the acceleration energy density, being the other 90% a cosmological constant term. This demonstrates how useful direct measurements of the expansion history of the universe are at constraining the dynamical nature of dark energy.
McDermid, Richard M.; Cappellari, Michele; Alatalo, Katherine; Bayet, Estelle; Blitz, Leo; Bois, Maxime; Bournaud, Frédéric; Bureau, Martin; Crocker, Alison F.; Davies, Roger L.; Davis, Timothy A.; de Zeeuw, P. T.; Duc, Pierre-Alain; Emsellem, Eric; Khochfar, Sadegh; Krajnović, Davor; Kuntschner, Harald; Morganti, Raffaella; Naab, Thorsten; Oosterloo, Tom; Sarzi, Marc; Scott, Nicholas; Serra, Paolo; Weijmans, Anne-Marie; Young, Lisa M.
We report on empirical trends between the dynamically determined stellar initial mass function (IMF) and stellar population properties for a complete, volume-limited sample of 260 early-type galaxies from the ATLAS3D project. We study trends between our dynamically derived IMF normalization αdyn ≡
State-Space Modelling of Loudspeakers using Fractional Derivatives
DEFF Research Database (Denmark)
King, Alexander Weider; Agerkvist, Finn T.
2015-01-01
This work investigates the use of fractional order derivatives in modeling moving-coil loudspeakers. A fractional order state-space solution is developed, leading the way towards incorporating nonlinearities into a fractional order system. The method is used to calculate the response of a fractio......This work investigates the use of fractional order derivatives in modeling moving-coil loudspeakers. A fractional order state-space solution is developed, leading the way towards incorporating nonlinearities into a fractional order system. The method is used to calculate the response...... of a fractional harmonic oscillator, representing the mechanical part of a loudspeaker, showing the effect of the fractional derivative and its relationship to viscoelasticity. Finally, a loudspeaker model with a fractional order viscoelastic suspension and fractional order voice coil is fit to measurement data...
Parameter Estimation of a Delay Time Model of Wearing Parts Based on Objective Data
Directory of Open Access Journals (Sweden)
Y. Tang
2015-01-01
Full Text Available The wearing parts of a system have a very high failure frequency, making it necessary to carry out continual functional inspections and maintenance to protect the system from unscheduled downtime. This allows for the collection of a large amount of maintenance data. Taking the unique characteristics of the wearing parts into consideration, we establish their respective delay time models in ideal inspection cases and nonideal inspection cases. The model parameters are estimated entirely using the collected maintenance data. Then, a likelihood function of all renewal events is derived based on their occurring probability functions, and the model parameters are calculated with the maximum likelihood function method, which is solved by the CRM. Finally, using two wearing parts from the oil and gas drilling industry as examples—the filter element and the blowout preventer rubber core—the parameters of the distribution function of the initial failure time and the delay time for each example are estimated, and their distribution functions are obtained. Such parameter estimation based on objective data will contribute to the optimization of the reasonable function inspection interval and will also provide some theoretical models to support the integrity management of equipment or systems.
Bodmer, James E; English, Anthony; Brady, Megan; Blackwell, Ken; Haxhinasto, Kari; Fotedar, Sunaina; Borgman, Kurt; Bai, Er-Wei; Moy, Alan B
2005-09-01
Transendothelial impedance across an endothelial monolayer grown on a microelectrode has previously been modeled as a repeating pattern of disks in which the electrical circuit consists of a resistor and capacitor in series. Although this numerical model breaks down barrier function into measurements of cell-cell adhesion, cell-matrix adhesion, and membrane capacitance, such solution parameters can be inaccurate without understanding model stability and error. In this study, we have evaluated modeling stability and error by using a chi(2) evaluation and Levenberg-Marquardt nonlinear least-squares (LM-NLS) method of the real and/or imaginary data in which the experimental measurement is compared with the calculated measurement derived by the model. Modeling stability and error were dependent on current frequency and the type of experimental data modeled. Solution parameters of cell-matrix adhesion were most susceptible to modeling instability. Furthermore, the LM-NLS method displayed frequency-dependent instability of the solution parameters, regardless of whether the real or imaginary data were analyzed. However, the LM-NLS method identified stable and reproducible solution parameters between all types of experimental data when a defined frequency spectrum of the entire data set was selected on the basis of a criterion of minimizing error. The frequency bandwidth that produced stable solution parameters varied greatly among different data types. Thus a numerical model based on characterizing transendothelial impedance as a resistor and capacitor in series and as a repeating pattern of disks is not sufficient to characterize the entire frequency spectrum of experimental transendothelial impedance.
Analysis of Model Parameters for a Polymer Filtration Simulator
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N. Brackett-Rozinsky
2011-01-01
Full Text Available We examine a simulation model for polymer extrusion filters and determine its sensitivity to filter parameters. The simulator is a three-dimensional, time-dependent discretization of a coupled system of nonlinear partial differential equations used to model fluid flow and debris transport, along with statistical relationships that define debris distributions and retention probabilities. The flow of polymer fluid, and suspended debris particles, is tracked to determine how well a filter performs and how long it operates before clogging. A filter may have multiple layers, characterized by thickness, porosity, and average pore diameter. In this work, the thickness of each layer is fixed, while the porosities and pore diameters vary for a two-layer and three-layer study. The effects of porosity and average pore diameter on the measures of filter quality are calculated. For the three layer model, these effects are tested for statistical significance using analysis of variance. Furthermore, the effects of each pair of interacting parameters are considered. This allows the detection of complexity, where in changing two aspects of a filter together may generate results substantially different from what occurs when those same aspects change separately. The principal findings indicate that the first layer of a filter is the most important.
Optimization of Experimental Model Parameter Identification for Energy Storage Systems
Directory of Open Access Journals (Sweden)
Rosario Morello
2013-09-01
Full Text Available The smart grid approach is envisioned to take advantage of all available modern technologies in transforming the current power system to provide benefits to all stakeholders in the fields of efficient energy utilisation and of wide integration of renewable sources. Energy storage systems could help to solve some issues that stem from renewable energy usage in terms of stabilizing the intermittent energy production, power quality and power peak mitigation. With the integration of energy storage systems into the smart grids, their accurate modeling becomes a necessity, in order to gain robust real-time control on the network, in terms of stability and energy supply forecasting. In this framework, this paper proposes a procedure to identify the values of the battery model parameters in order to best fit experimental data and integrate it, along with models of energy sources and electrical loads, in a complete framework which represents a real time smart grid management system. The proposed method is based on a hybrid optimisation technique, which makes combined use of a stochastic and a deterministic algorithm, with low computational burden and can therefore be repeated over time in order to account for parameter variations due to the battery’s age and usage.
Applying Atmospheric Measurements to Constrain Parameters of Terrestrial Source Models
Hyer, E. J.; Kasischke, E. S.; Allen, D. J.
2004-12-01
Quantitative inversions of atmospheric measurements have been widely applied to constrain atmospheric budgets of a range of trace gases. Experiments of this type have revealed persistent discrepancies between 'bottom-up' and 'top-down' estimates of source magnitudes. The most common atmospheric inversion uses the absolute magnitude as the sole parameter for each source, and returns the optimal value of that parameter. In order for atmospheric measurements to be useful for improving 'bottom-up' models of terrestrial sources, information about other properties of the sources must be extracted. As the density and quality of atmospheric trace gas measurements improve, examination of higher-order properties of trace gas sources should become possible. Our model of boreal forest fire emissions is parameterized to permit flexible examination of the key uncertainties in this source. Using output from this model together with the UM CTM, we examined the sensitivity of CO concentration measurements made by the MOPITT instrument to various uncertainties in the boreal source: geographic distribution of burned area, fire type (crown fires vs. surface fires), and fuel consumption in above-ground and ground-layer fuels. Our results indicate that carefully designed inversion experiments have the potential to help constrain not only the absolute magnitudes of terrestrial sources, but also the key uncertainties associated with 'bottom-up' estimates of those sources.
Bayesian parameter estimation for stochastic models of biological cell migration
Dieterich, Peter; Preuss, Roland
2013-08-01
Cell migration plays an essential role under many physiological and patho-physiological conditions. It is of major importance during embryonic development and wound healing. In contrast, it also generates negative effects during inflammation processes, the transmigration of tumors or the formation of metastases. Thus, a reliable quantification and characterization of cell paths could give insight into the dynamics of these processes. Typically stochastic models are applied where parameters are extracted by fitting models to the so-called mean square displacement of the observed cell group. We show that this approach has several disadvantages and problems. Therefore, we propose a simple procedure directly relying on the positions of the cell's trajectory and the covariance matrix of the positions. It is shown that the covariance is identical with the spatial aging correlation function for the supposed linear Gaussian models of Brownian motion with drift and fractional Brownian motion. The technique is applied and illustrated with simulated data showing a reliable parameter estimation from single cell paths.
Application of a free parameter model to plastic scintillation samples
Energy Technology Data Exchange (ETDEWEB)
Tarancon Sanz, Alex, E-mail: alex.tarancon@ub.edu [Departament de Quimica Analitica, Universitat de Barcelona, Diagonal 647, E-08028 Barcelona (Spain); Kossert, Karsten, E-mail: Karsten.Kossert@ptb.de [Physikalisch-Technische Bundesanstalt (PTB), Bundesallee 100, 38116 Braunschweig (Germany)
2011-08-21
In liquid scintillation (LS) counting, the CIEMAT/NIST efficiency tracing method and the triple-to-double coincidence ratio (TDCR) method have proved their worth for reliable activity measurements of a number of radionuclides. In this paper, an extended approach to apply a free-parameter model to samples containing a mixture of solid plastic scintillation microspheres and radioactive aqueous solutions is presented. Several beta-emitting radionuclides were measured in a TDCR system at PTB. For the application of the free parameter model, the energy loss in the aqueous phase must be taken into account, since this portion of the particle energy does not contribute to the creation of scintillation light. The energy deposit in the aqueous phase is determined by means of Monte Carlo calculations applying the PENELOPE software package. To this end, great efforts were made to model the geometry of the samples. Finally, a new geometry parameter was defined, which was determined by means of a tracer radionuclide with known activity. This makes the analysis of experimental TDCR data of other radionuclides possible. The deviations between the determined activity concentrations and reference values were found to be lower than 3%. The outcome of this research work is also important for a better understanding of liquid scintillation counting. In particular the influence of (inverse) micelles, i.e. the aqueous spaces embedded in the organic scintillation cocktail, can be investigated. The new approach makes clear that it is important to take the energy loss in the aqueous phase into account. In particular for radionuclides emitting low-energy electrons (e.g. M-Auger electrons from {sup 125}I), this effect can be very important.
Microbial Communities Model Parameter Calculation for TSPA/SR
Energy Technology Data Exchange (ETDEWEB)
D. Jolley
2001-07-16
This calculation has several purposes. First the calculation reduces the information contained in ''Committed Materials in Repository Drifts'' (BSC 2001a) to useable parameters required as input to MING V1.O (CRWMS M&O 1998, CSCI 30018 V1.O) for calculation of the effects of potential in-drift microbial communities as part of the microbial communities model. The calculation is intended to replace the parameters found in Attachment II of the current In-Drift Microbial Communities Model revision (CRWMS M&O 2000c) with the exception of Section 11-5.3. Second, this calculation provides the information necessary to supercede the following DTN: M09909SPAMING1.003 and replace it with a new qualified dataset (see Table 6.2-1). The purpose of this calculation is to create the revised qualified parameter input for MING that will allow {Delta}G (Gibbs Free Energy) to be corrected for long-term changes to the temperature of the near-field environment. Calculated herein are the quadratic or second order regression relationships that are used in the energy limiting calculations to potential growth of microbial communities in the in-drift geochemical environment. Third, the calculation performs an impact review of a new DTN: M00012MAJIONIS.000 that is intended to replace the currently cited DTN: GS9809083 12322.008 for water chemistry data used in the current ''In-Drift Microbial Communities Model'' revision (CRWMS M&O 2000c). Finally, the calculation updates the material lifetimes reported on Table 32 in section 6.5.2.3 of the ''In-Drift Microbial Communities'' AMR (CRWMS M&O 2000c) based on the inputs reported in BSC (2001a). Changes include adding new specified materials and updating old materials information that has changed.
Microbial Communities Model Parameter Calculation for TSPA/SR
International Nuclear Information System (INIS)
D. Jolley
2001-01-01
This calculation has several purposes. First the calculation reduces the information contained in ''Committed Materials in Repository Drifts'' (BSC 2001a) to useable parameters required as input to MING V1.O (CRWMS M and O 1998, CSCI 30018 V1.O) for calculation of the effects of potential in-drift microbial communities as part of the microbial communities model. The calculation is intended to replace the parameters found in Attachment II of the current In-Drift Microbial Communities Model revision (CRWMS M and O 2000c) with the exception of Section 11-5.3. Second, this calculation provides the information necessary to supercede the following DTN: M09909SPAMING1.003 and replace it with a new qualified dataset (see Table 6.2-1). The purpose of this calculation is to create the revised qualified parameter input for MING that will allow ΔG (Gibbs Free Energy) to be corrected for long-term changes to the temperature of the near-field environment. Calculated herein are the quadratic or second order regression relationships that are used in the energy limiting calculations to potential growth of microbial communities in the in-drift geochemical environment. Third, the calculation performs an impact review of a new DTN: M00012MAJIONIS.000 that is intended to replace the currently cited DTN: GS9809083 12322.008 for water chemistry data used in the current ''In-Drift Microbial Communities Model'' revision (CRWMS M and O 2000c). Finally, the calculation updates the material lifetimes reported on Table 32 in section 6.5.2.3 of the ''In-Drift Microbial Communities'' AMR (CRWMS M and O 2000c) based on the inputs reported in BSC (2001a). Changes include adding new specified materials and updating old materials information that has changed
Dynamic model of cage induction motor with number of rotor bars as parameter
Directory of Open Access Journals (Sweden)
Gojko Joksimović
2017-05-01
Full Text Available A dynamic mathematical model, using number of rotor bars as parameter, is reached for cage induction motors through the use of coupled-circuits and the concept of winding functions. The exact MMFs waveforms are accounted for by the model which is derived in natural frames of reference. By knowing the initial motor parameters for a priori adopted number of stator slots and rotor bars model allows change of rotor bars number what results in new model parameters. During this process, the rated machine power, number of stator slots and stator winding scheme remain the same. Although presented model has a potentially broad application area it is primarily suitable for the analysis of the different stator/rotor slot combination on motor behaviour during the transients or in steady-state regime. The model is significant in its potential to provide analysis of dozen of different number of rotor bars in a few tens of minutes. Numerical example on cage rotor induction motor exemplifies this application, including three variants of number of rotor bars.
Application of Parameter Estimation for Diffusions and Mixture Models
DEFF Research Database (Denmark)
Nolsøe, Kim
error models. This is obtained by constructing an estimating function through projections of some chosen function of Yti+1 onto functions of previous observations Yti ; : : : ; Yt0 . The process of interest Xti+1 is partially observed through a measurement equation Yti+1 = h(Xti+1)+ noice, where h......(:) is restricted to be a polynomial. Through a simulation study we compare for the CIR process the obtained estimator with an estimator derived from utilizing the extended Kalman filter. The simulation study shows that the two estimation methods perform equally well.......The first part of this thesis proposes a method to determine the preferred number of structures, their proportions and the corresponding geometrical shapes of an m-membered ring molecule. This is obtained by formulating a statistical model for the data and constructing an algorithm which samples...
Modelled basic parameters for semi-industrial irradiation plant design
International Nuclear Information System (INIS)
Mangussi, J.
2009-01-01
The basic parameters of an irradiation plant design are the total activity, the product uniformity ratio and the efficiency process. The target density, the minimum dose required and the throughput depends on the use to which the irradiator will be put at. In this work, a model for calculating the specific dose rate at several depths in an infinite homogeneous medium produced by a slab source irradiator is presented. The product minimum dose rate for a set of target thickness is obtained. The design method steps are detailed and an illustrative example is presented. (author)
Lumped-parameter fuel rod model for rapid thermal transients
International Nuclear Information System (INIS)
Perkins, K.R.; Ramshaw, J.D.
1975-07-01
The thermal behavior of fuel rods during simulated accident conditions is extremely sensitive to the heat transfer coefficient which is, in turn, very sensitive to the cladding surface temperature and the fluid conditions. The development of a semianalytical, lumped-parameter fuel rod model which is intended to provide accurate calculations, in a minimum amount of computer time, of the thermal response of fuel rods during a simulated loss-of-coolant accident is described. The results show good agreement with calculations from a comprehensive fuel-rod code (FRAP-T) currently in use at Aerojet Nuclear Company
Taming Many-Parameter BSM Models with Bayesian Neural Networks
Kuchera, M. P.; Karbo, A.; Prosper, H. B.; Sanchez, A.; Taylor, J. Z.
2017-09-01
The search for physics Beyond the Standard Model (BSM) is a major focus of large-scale high energy physics experiments. One method is to look for specific deviations from the Standard Model that are predicted by BSM models. In cases where the model has a large number of free parameters, standard search methods become intractable due to computation time. This talk presents results using Bayesian Neural Networks, a supervised machine learning method, to enable the study of higher-dimensional models. The popular phenomenological Minimal Supersymmetric Standard Model was studied as an example of the feasibility and usefulness of this method. Graphics Processing Units (GPUs) are used to expedite the calculations. Cross-section predictions for 13 TeV proton collisions will be presented. My participation in the Conference Experience for Undergraduates (CEU) in 2004-2006 exposed me to the national and global significance of cutting-edge research. At the 2005 CEU, I presented work from the previous summer's SULI internship at Lawrence Berkeley Laboratory, where I learned to program while working on the Majorana Project. That work inspired me to follow a similar research path, which led me to my current work on computational methods applied to BSM physics.
Bayesian analysis of inflation: Parameter estimation for single field models
International Nuclear Information System (INIS)
Mortonson, Michael J.; Peiris, Hiranya V.; Easther, Richard
2011-01-01
Future astrophysical data sets promise to strengthen constraints on models of inflation, and extracting these constraints requires methods and tools commensurate with the quality of the data. In this paper we describe ModeCode, a new, publicly available code that computes the primordial scalar and tensor power spectra for single-field inflationary models. ModeCode solves the inflationary mode equations numerically, avoiding the slow roll approximation. It is interfaced with CAMB and CosmoMC to compute cosmic microwave background angular power spectra and perform likelihood analysis and parameter estimation. ModeCode is easily extendable to additional models of inflation, and future updates will include Bayesian model comparison. Errors from ModeCode contribute negligibly to the error budget for analyses of data from Planck or other next generation experiments. We constrain representative single-field models (φ n with n=2/3, 1, 2, and 4, natural inflation, and 'hilltop' inflation) using current data, and provide forecasts for Planck. From current data, we obtain weak but nontrivial limits on the post-inflationary physics, which is a significant source of uncertainty in the predictions of inflationary models, while we find that Planck will dramatically improve these constraints. In particular, Planck will link the inflationary dynamics with the post-inflationary growth of the horizon, and thus begin to probe the ''primordial dark ages'' between TeV and grand unified theory scale energies.
Empirically modelled Pc3 activity based on solar wind parameters
Directory of Open Access Journals (Sweden)
B. Heilig
2010-09-01
Full Text Available It is known that under certain solar wind (SW/interplanetary magnetic field (IMF conditions (e.g. high SW speed, low cone angle the occurrence of ground-level Pc3–4 pulsations is more likely. In this paper we demonstrate that in the event of anomalously low SW particle density, Pc3 activity is extremely low regardless of otherwise favourable SW speed and cone angle. We re-investigate the SW control of Pc3 pulsation activity through a statistical analysis and two empirical models with emphasis on the influence of SW density on Pc3 activity. We utilise SW and IMF measurements from the OMNI project and ground-based magnetometer measurements from the MM100 array to relate SW and IMF measurements to the occurrence of Pc3 activity. Multiple linear regression and artificial neural network models are used in iterative processes in order to identify sets of SW-based input parameters, which optimally reproduce a set of Pc3 activity data. The inclusion of SW density in the parameter set significantly improves the models. Not only the density itself, but other density related parameters, such as the dynamic pressure of the SW, or the standoff distance of the magnetopause work equally well in the model. The disappearance of Pc3s during low-density events can have at least four reasons according to the existing upstream wave theory: 1. Pausing the ion-cyclotron resonance that generates the upstream ultra low frequency waves in the absence of protons, 2. Weakening of the bow shock that implies less efficient reflection, 3. The SW becomes sub-Alfvénic and hence it is not able to sweep back the waves propagating upstream with the Alfvén-speed, and 4. The increase of the standoff distance of the magnetopause (and of the bow shock. Although the models cannot account for the lack of Pc3s during intervals when the SW density is extremely low, the resulting sets of optimal model inputs support the generation of mid latitude Pc3 activity predominantly through
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.
Application of regression model on stream water quality parameters
International Nuclear Information System (INIS)
Suleman, M.; Maqbool, F.; Malik, A.H.; Bhatti, Z.A.
2012-01-01
Statistical analysis was conducted to evaluate the effect of solid waste leachate from the open solid waste dumping site of Salhad on the stream water quality. Five sites were selected along the stream. Two sites were selected prior to mixing of leachate with the surface water. One was of leachate and other two sites were affected with leachate. Samples were analyzed for pH, water temperature, electrical conductivity (EC), total dissolved solids (TDS), Biological oxygen demand (BOD), chemical oxygen demand (COD), dissolved oxygen (DO) and total bacterial load (TBL). In this study correlation coefficient r among different water quality parameters of various sites were calculated by using Pearson model and then average of each correlation between two parameters were also calculated, which shows TDS and EC and pH and BOD have significantly increasing r value, while temperature and TDS, temp and EC, DO and BL, DO and COD have decreasing r value. Single factor ANOVA at 5% level of significance was used which shows EC, TDS, TCL and COD were significantly differ among various sites. By the application of these two statistical approaches TDS and EC shows strongly positive correlation because the ions from the dissolved solids in water influence the ability of that water to conduct an electrical current. These two parameters significantly vary among 5 sites which are further confirmed by using linear regression. (author)
International Nuclear Information System (INIS)
Booker, J.A.; Sutherland, D.C.; Howarth, D.M.; Taylor, L.; Tan, P.
2002-01-01
Full text: Xerostomia may be due to salivary dysfunction from a variety of causes and can be clinically variable ranging from halitosis to overt xerostomia. Semi-quantitative indices may be derived from salivary scintigraphy and may aid both clinical diagnosis and response to treatment. The objective of this study was to determine whether semi-quantitative indices were able to distinguish normal from abnormal salivary function and to be clinically useful. 56 consecutive patients with xerostomia (including a subset of 10 patients with clinical Sjogrens syndrome) and 25 healthy volunteers underwent salivary scintigraphy. Semi-quantitative analysis of time activity curves was performed deriving 6 different indices for each of the four major salivary glands. These indices included percent uptake (%UP), uptake ratios(UR),maximum accumulation (MA), pre-stimulatory oral radioactivity index (PRI), post-stimulatory oral radioactivity index (POI) and ejection fraction (EF). The 95% confidence interval around the mean values was used to compare normal volunteers and xerostomia patients. Wide reference limits were obtained for all indices derived from normal volunteers. No significant difference was found between normal volunteers and patients using any of the six indices. UR and EF showed the greatest difference between the groups. Allowing for Type Two (Beta) error, none of the above indices allow patients with xerostomia who have salivary dysfunction to be distinguished from normal subjects. Copyright (2002) The Australian and New Zealand Society of Nuclear Medicine Inc
Lumped-parameter modeling of one-dimensional two-phase flow
International Nuclear Information System (INIS)
Wulff, W.
1978-01-01
An integral or lumped-parameter modeling technique is presented for the analysis of nonequilibrium, nonhomogeneous, one-dimensional two-phase flow. The method is designed to increase computing efficiency over standard finite difference techniques and to describe accurately the motion of flow regime interfaces. Computing efficiency is achieved by converting the partial differential equations of the conservation laws into ordinary differential equations and by introducing profile estimates. Flow regime interfaces are tracked with the aid of kinematic jump conditions. The governing equations are derived, and the method is elucidated on three applications. One application involves a closed-loop transient, the second one involves the dynamics of a liquid level, while the third application deals with the level swelling above a nonhomogeneous two-phase mixture. Comparisons are presented between lumped parameter modeling solutions, solutions from finite difference techniques and analytical solutions. The comparisons show good agreement. The important role of profile functions is discussed
Interpretation of hydraulic conductivity data and parameter evaluation for groundwater flow models
International Nuclear Information System (INIS)
Niemi, A.
1991-01-01
The report reviews recent developments in evaluating effective permeabilities for groundwater flow models, starting from methods of well test interpretation for and proceeding to the principles of parameter estimation. Basic concepts of parameter evaluation as well as expressions derived for effective permeabilities in traditional porous medium are described. Due to the assumptions made, these do often not apply for fractured media. Specific features of fractured medium are discussed, including approaches used determining the size of a possible REV and questions related to the application of stochastic theories. Due to the difficulties encountered when applying traditional deterministic models for fractured media, stochastic and fracture network approaches have been developed. The application of these techniques is still under development, the main questions to be resolved being related to the scarcity of data
Convergence of surface diffusion parameters with model crystal size
Cohen, Jennifer M.; Voter, Arthur F.
1994-07-01
A study of the variation in the calculated quantities for adatom diffusion with respect to the size of the model crystal is presented. The reported quantities include surface diffusion barrier heights, pre-exponential factors, and dynamical correction factors. Embedded atom method (EAM) potentials were used throughout this effort. Both the layer size and the depth of the crystal were found to influence the values of the Arrhenius factors significantly. In particular, exchange type mechanisms required a significantly larger model than standard hopping mechanisms to determine adatom diffusion barriers of equivalent accuracy. The dynamical events that govern the corrections to transition state theory (TST) did not appear to be as sensitive to crystal depth. Suitable criteria for the convergence of the diffusion parameters with regard to the rate properties are illustrated.
An iterative stochastic ensemble method for parameter estimation of subsurface flow models
International Nuclear Information System (INIS)
Elsheikh, Ahmed H.; Wheeler, Mary F.; Hoteit, Ibrahim
2013-01-01
Parameter estimation for subsurface flow models is an essential step for maximizing the value of numerical simulations for future prediction and the development of effective control strategies. We propose the iterative stochastic ensemble method (ISEM) as a general method for parameter estimation based on stochastic estimation of gradients using an ensemble of directional derivatives. ISEM eliminates the need for adjoint coding and deals with the numerical simulator as a blackbox. The proposed method employs directional derivatives within a Gauss–Newton iteration. The update equation in ISEM resembles the update step in ensemble Kalman filter, however the inverse of the output covariance matrix in ISEM is regularized using standard truncated singular value decomposition or Tikhonov regularization. We also investigate the performance of a set of shrinkage based covariance estimators within ISEM. The proposed method is successfully applied on several nonlinear parameter estimation problems for subsurface flow models. The efficiency of the proposed algorithm is demonstrated by the small size of utilized ensembles and in terms of error convergence rates
An iterative stochastic ensemble method for parameter estimation of subsurface flow models
Elsheikh, Ahmed H.
2013-06-01
Parameter estimation for subsurface flow models is an essential step for maximizing the value of numerical simulations for future prediction and the development of effective control strategies. We propose the iterative stochastic ensemble method (ISEM) as a general method for parameter estimation based on stochastic estimation of gradients using an ensemble of directional derivatives. ISEM eliminates the need for adjoint coding and deals with the numerical simulator as a blackbox. The proposed method employs directional derivatives within a Gauss-Newton iteration. The update equation in ISEM resembles the update step in ensemble Kalman filter, however the inverse of the output covariance matrix in ISEM is regularized using standard truncated singular value decomposition or Tikhonov regularization. We also investigate the performance of a set of shrinkage based covariance estimators within ISEM. The proposed method is successfully applied on several nonlinear parameter estimation problems for subsurface flow models. The efficiency of the proposed algorithm is demonstrated by the small size of utilized ensembles and in terms of error convergence rates. © 2013 Elsevier Inc.
Standard model parameters and the search for new physics
International Nuclear Information System (INIS)
Marciano, W.J.
1988-04-01
In these lectures, my aim is to present an up-to-date status report on the standard model and some key tests of electroweak unification. Within that context, I also discuss how and where hints of new physics may emerge. To accomplish those goals, I have organized my presentation as follows: I discuss the standard model parameters with particular emphasis on the gauge coupling constants and vector boson masses. Examples of new physics appendages are also briefly commented on. In addition, because these lectures are intended for students and thus somewhat pedagogical, I have included an appendix on dimensional regularization and a simple computational example that employs that technique. Next, I focus on weak charged current phenomenology. Precision tests of the standard model are described and up-to-date values for the Cabibbo-Kobayashi-Maskawa (CKM) mixing matrix parameters are presented. Constraints implied by those tests for a 4th generation, supersymmetry, extra Z/prime/ bosons, and compositeness are also discussed. I discuss weak neutral current phenomenology and the extraction of sin/sup 2/ /theta//sub W/ from experiment. The results presented there are based on a recently completed global analysis of all existing data. I have chosen to concentrate that discussion on radiative corrections, the effect of a heavy top quark mass, and implications for grand unified theories (GUTS). The potential for further experimental progress is also commented on. I depart from the narrowest version of the standard model and discuss effects of neutrino masses and mixings. I have chosen to concentrate on oscillations, the Mikheyev-Smirnov- Wolfenstein (MSW) effect, and electromagnetic properties of neutrinos. On the latter topic, I will describe some recent work on resonant spin-flavor precession. Finally, I conclude with a prospectus on hopes for the future. 76 refs
Epps, Brenden; Cushman-Roisin, Benoit
2017-11-01
Fluid turbulence is an outstanding unsolved problem in classical physics, despite 120+ years of sustained effort. Given this history, we assert that a new mathematical framework is needed to make a transformative breakthrough. This talk offers one such framework, based upon kinetic theory tied to the statistics of turbulent transport. Starting from the Boltzmann equation and ``Lévy α-stable distributions'', we derive a turbulence model that expresses the turbulent stresses in the form of a fractional derivative, where the fractional order is tied to the transport behavior of the flow. Initial results are presented herein, for the cases of Couette-Poiseuille flow and 2D boundary layers. Among other results, our model is able to reproduce the logarithmic Law of the Wall in shear turbulence.
Directory of Open Access Journals (Sweden)
Banu Boyuk
2014-01-01
Full Text Available Background and Aim. Studies have suggested that brain-derived neurotrophic factor (BDNF plays a role in glucose and lipid metabolism and inflammation. The aim of this study was to evaluate the relationship between serum BDNF levels and various metabolic parameters and inflammatory markers in patients with type 2 diabetes mellitus (T2DM. Materials and Methods. The study included 88 T2DM patients and 33 healthy controls. Fasting blood samples were obtained from the patients and the control group. The serum levels of BDNF were measured with an ELISA kit. The current paper introduces a receiver-operating characteristic (ROC generalization curve to identify cut-off for the BDNF values in type 2 diabetes patients. Results. The serum levels of BDNF were significantly higher in T2DM patients than in the healthy controls (206.81 ± 107.32 pg/mL versus 130.84 ± 59.81 pg/mL; P<0.001. They showed a positive correlation with the homeostasis model assessment of insulin resistance (HOMA-IR (r=0.28; P<0.05, the triglyceride level (r=0.265; P<0.05, and white blood cell (WBC count (r=0.35; P<0.001. In logistic regression analysis, age (P<0.05, body mass index (BMI (P<0.05, C-reactive protein (CRP (P<0.05, and BDNF (P<0.01 were independently associated with T2DM. In ROC curve analysis, BDNF cut-off was 137. Conclusion. The serum BDNF level was higher in patients with T2DM. The BDNF had a cut-off value of 137. The findings suggest that BDNF may contribute to glucose and lipid metabolism and inflammation.
Howard, B J; Wells, C; Barnett, C L; Howard, D C
2017-02-01
Under the International Atomic Energy Agency (IAEA) MODARIA (Modelling and Data for Radiological Impact Assessments) Programme, there has been an initiative to improve the derivation, provenance and transparency of transfer parameter values for radionuclides from feed to animal products that are for human consumption. A description of the revised MODARIA 2016 cow milk dataset is described in this paper. As previously reported for the MODARIA goat milk dataset, quality control has led to the discounting of some references used in IAEA's Technical Report Series (TRS) report 472 (IAEA, 2010). The number of Concentration Ratio (CR) values has been considerably increased by (i) the inclusion of more literature from agricultural studies which particularly enhanced the stable isotope data of both CR and F m and (ii) by estimating dry matter intake from assumed liveweight. In TRS 472, the data for cow milk were 714 transfer coefficient (F m ) values and 254 CR values describing 31 elements and 26 elements respectively. In the MODARIA 2016 cow milk dataset, F m and CR values are now reported for 43 elements based upon 825 data values for F m and 824 for CR. The MODARIA 2016 cow milk dataset F m values are within an order of magnitude of those reported in TRS 472. Slightly bigger changes are seen in the CR values, but the increase in size of the dataset creates greater confidence in them. Data gaps that still remain are identified for elements with isotopes relevant to radiation protection. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
Carey, W.P.; Simon, Andrew
1984-01-01
Simulation of upland-soil erosion by the Precipitation-Runoff Modeling System currently requires the user to estimate two rainfall detachment parameters and three hydraulic detachmment paramenters. One rainfall detachment parameter can be estimated from rainfall simulator tests. A reformulation of the rainfall detachment equation allows the second parameter to be computed directly. The three hydraulic detachment parameters consist of one exponent and two coefficients. The initial value of the exponent is generally set equal to 1.5. The two coefficients are functions of the soil 's resistance to erosion and one of the two also accounts for sediment delivery processes not simulated in the model. Initial estimates of these parameters can be derived from other modeling studies or from published empirical relations. (USGS)
Bansah, S.; Ali, G.; Haque, M. A.; Tang, V.
2017-12-01
The proportion of precipitation that becomes streamflow is a function of internal catchment characteristics - which include geology, landscape characteristics and vegetation - and influence overall storage dynamics. The timing and quantity of water discharged by a catchment are indeed embedded in event hydrographs. Event hydrograph timing parameters, such as the response lag and time of concentration, are important descriptors of how long it takes the catchment to respond to input precipitation and how long it takes the latter to filter through the catchment. However, the extent to which hydrograph timing parameters relate to average response times derived from fitting transfer functions to annual hydrographs is unknown. In this study, we used a gamma transfer function to determine catchment average response times as well as event-specific hydrograph parameters across a network of eight nested watersheds ranging from 0.19 km2 to 74.6 km2 prairie catchments located in south central Manitoba (Canada). Various statistical analyses were then performed to correlate average response times - estimated using the parameters of the fitted gamma transfer function - to event-specific hydrograph parameters. Preliminary results show significant interannual variations in response times and hydrograph timing parameters: the former were in the order of a few hours to days, while the latter ranged from a few days to weeks. Some statistically significant relationships were detected between response times and event-specific hydrograph parameters. Future analyses will involve the comparison of statistical distributions of event-specific hydrograph parameters with that of runoff response times and baseflow transit times in order to quantity catchment storage dynamics across a range of temporal scales.
Directory of Open Access Journals (Sweden)
Shiyuan LIU
2009-05-01
Full Text Available Background and objective The solitary pulmonary nodules (SPNs is one of the most common findings on chest radiographs. The blood flow patterns of the biggest single SPNs level has been studied. This assessment may be only a limited sample of the entire region of interest (ROI and is unrepresentative of the SPNs as a volume. Ideally, SPNs volume perfusion should be measured. The aim of this study is to evaluate the correlation between the quantifiableparameters of SPNs volume perfusion imaging derived with 16-slice spiral CT and 64-slice spiral CT and nodules size. Methods Sixty-five patients with SPNs (diameter≤3 cm; 42 malignant; 12 active inflammatory; 11 benign underwent multi-location dynamic contrast material-enhanced serial CT scanning mode with stable table were performed; The mean values of valid sections were calculated, as the quantifiable parameters of volume SPNs perfusion imaging derived with16-slice spiral CT and 64-slice spiral CT. The correlation between the quantifiable parameters of SPNs volume perfusion imaging derived with 16-slice spiral CT and 64-slice spiral CT and nodules size were assessed by means of linear regression analysis. Results No significant correlations were found between the nodules size and each of the peak height (PHSPN (32.15 Hu±14.55 Hu，ratio of peak height of the SPN to that of the aorta (SPN-to-A ratio(13.20±6.18%, perfusion(PSPN (29.79±19.12 mLmin-1100 g-1 and mean transit time (12.95±6.53 s (r =0.081, P =0.419; r =0.089, P =0.487; r =0.167, P =0.077; r =0.023, P =0.880. Conclusion No significant correlations were found between the quantifiable parameters of SPNs volume perfusion imaging derived with 16-slice spiral CT and 64-slice spiral CT and nodules size.
Modeling and Forecasting Average Temperature for Weather Derivative Pricing
Directory of Open Access Journals (Sweden)
Zhiliang Wang
2015-01-01
Full Text Available The main purpose of this paper is to present a feasible model for the daily average temperature on the area of Zhengzhou and apply it to weather derivatives pricing. We start by exploring the background of weather derivatives market and then use the 62 years of daily historical data to apply the mean-reverting Ornstein-Uhlenbeck process to describe the evolution of the temperature. Finally, Monte Carlo simulations are used to price heating degree day (HDD call option for this city, and the slow convergence of the price of the HDD call can be found through taking 100,000 simulations. The methods of the research will provide a frame work for modeling temperature and pricing weather derivatives in other similar places in China.
Sun, Y.; Hou, Z.; Huang, M.; Tian, F.; Leung, L. Ruby
2013-12-01
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. Both deterministic least-square fitting and stochastic Markov-chain Monte Carlo (MCMC)-Bayesian inversion approaches are evaluated by applying them to CLM4 at selected sites with different climate and soil conditions. 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 sampling-based stochastic inversion approaches provides significant improvements in the model simulations compared to using default CLM4 parameter values, and that as more information comes in, the predictive intervals (ranges of posterior distributions) of the calibrated parameters become narrower. 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 bounds.
Zhou, H. W.; Yi, H. Y.; Mishnaevsky, L.; Wang, R.; Duan, Z. Q.; Chen, Q.
2017-05-01
A modeling approach to time-dependent property of Glass Fiber Reinforced Polymers (GFRP) composites is of special interest for quantitative description of long-term behavior. An electronic creep machine is employed to investigate the time-dependent deformation of four specimens of dog-bond-shaped GFRP composites at various stress level. A negative exponent function based on structural changes is introduced to describe the damage evolution of material properties in the process of creep test. Accordingly, a new creep constitutive equation, referred to fractional derivative Maxwell model, is suggested to characterize the time-dependent behavior of GFRP composites by replacing Newtonian dashpot with the Abel dashpot in the classical Maxwell model. The analytic solution for the fractional derivative Maxwell model is given and the relative parameters are determined. The results estimated by the fractional derivative Maxwell model proposed in the paper are in a good agreement with the experimental data. It is shown that the new creep constitutive model proposed in the paper needs few parameters to represent various time-dependent behaviors.
A Consistent Pricing Model for Index Options and Volatility Derivatives
DEFF Research Database (Denmark)
Kokholm, Thomas
We propose a flexible modeling framework for the joint dynamics of an index and a set of forward variance swap rates written on this index. Our model reproduces various empirically observed properties of variance swap dynamics and enables volatility derivatives and options on the underlying index...... to be priced consistently, while allowing for jumps in volatility and returns. An affine specification using Lévy processes as building blocks leads to analytically tractable pricing formulas for volatility derivatives, such as VIX options, as well as efficient numerical methods for pricing of European options...... on the underlying asset. The model has the convenient feature of decoupling the vanilla skews from spot/volatility correlations and allowing for different conditional correlations in large and small spot/volatility moves. We show that our model can simultaneously fit prices of European options on S&P 500 across...
A Consistent Pricing Model for Index Options and Volatility Derivatives
DEFF Research Database (Denmark)
Cont, Rama; Kokholm, Thomas
2013-01-01
We propose a flexible modeling framework for the joint dynamics of an index and a set of forward variance swap rates written on this index. Our model reproduces various empirically observed properties of variance swap dynamics and enables volatility derivatives and options on the underlying index...... to be priced consistently, while allowing for jumps in volatility and returns. An affine specification using Lévy processes as building blocks leads to analytically tractable pricing formulas for volatility derivatives, such as VIX options, as well as efficient numerical methods for pricing of European options...... on the underlying asset. The model has the convenient feature of decoupling the vanilla skews from spot/volatility correlations and allowing for different conditional correlations in large and small spot/volatility moves. We show that our model can simultaneously fit prices of European options on S&P 500 across...
Modelling of the Blood Plasma Species of Biguanide Derivatives ...
African Journals Online (AJOL)
NJD
Modelling of the Blood Plasma Species of. Biguanide Derivatives Exhibiting Potential as. Diagnostic Radiopharmaceuticals. Judith M. Wagenera*, Midred K. Dithebea, Daniel Moganob, Ignacy Cukrowskib and Jan Rijn Zeevaartc. aRadiochemistry, NECSA, P.O. Box 582, Pretoria 0001, South Africa. bDepartment of ...
Microscopic Derivation of the Ginzburg-Landau Model
DEFF Research Database (Denmark)
Frank, Rupert; Hainzl, Christian; Seiringer, Robert
2014-01-01
We present a summary of our recent rigorous derivation of the celebrated Ginzburg-Landau (GL) theory, starting from the microscopic Bardeen-Cooper-Schrieffer (BCS) model. Close to the critical temperature, GL arises as an effective theory on the macroscopic scale. The relevant scaling limit...
Modelling ocean-colour-derived chlorophyll a
Directory of Open Access Journals (Sweden)
S. Dutkiewicz
2018-01-01
Full Text Available This article provides a proof of concept for using a biogeochemical/ecosystem/optical model with a radiative transfer component as a laboratory to explore aspects of ocean colour. We focus here on the satellite ocean colour chlorophyll a (Chl a product provided by the often-used blue/green reflectance ratio algorithm. The model produces output that can be compared directly to the real-world ocean colour remotely sensed reflectance. This model output can then be used to produce an ocean colour satellite-like Chl a product using an algorithm linking the blue versus green reflectance similar to that used for the real world. Given that the model includes complete knowledge of the (model water constituents, optics and reflectance, we can explore uncertainties and their causes in this proxy for Chl a (called derived Chl a in this paper. We compare the derived Chl a to the actual model Chl a field. In the model we find that the mean absolute bias due to the algorithm is 22 % between derived and actual Chl a. The real-world algorithm is found using concurrent in situ measurement of Chl a and radiometry. We ask whether increased in situ measurements to train the algorithm would improve the algorithm, and find a mixed result. There is a global overall improvement, but at the expense of some regions, especially in lower latitudes where the biases increase. Not surprisingly, we find that region-specific algorithms provide a significant improvement, at least in the annual mean. However, in the model, we find that no matter how the algorithm coefficients are found there can be a temporal mismatch between the derived Chl a and the actual Chl a. These mismatches stem from temporal decoupling between Chl a and other optically important water constituents (such as coloured dissolved organic matter and detrital matter. The degree of decoupling differs regionally and over time. For example, in many highly seasonal regions, the timing of initiation
A Consistent Pricing Model for Index Options and Volatility Derivatives
DEFF Research Database (Denmark)
Kokholm, Thomas
We propose a flexible modeling framework for the joint dynamics of an index and a set of forward variance swap rates written on this index. Our model reproduces various empirically observed properties of variance swap dynamics and enables volatility derivatives and options on the underlying index...... on the underlying asset. The model has the convenient feature of decoupling the vanilla skews from spot/volatility correlations and allowing for different conditional correlations in large and small spot/volatility moves. We show that our model can simultaneously fit prices of European options on S&P 500 across...
Derivation of Output Power of Induction Heater Model
Directory of Open Access Journals (Sweden)
Riyadh K. Chillab
2016-12-01
Full Text Available The work is concerned with the study of the single phase cylindrical induction heating systems and derive equation power. The presented analysis is analytical and a multi-layer model using cylindrical geometry which is used to obtain the theoretical results. To validate the theoretical results, a practical model is constructed, tested and the results are compared with the theoretical ones. Comparison showed that the adopted analytical method is efficient in describing the performance of such induction heater systems
van der Ent, R.; Van Beek, R.; Sutanudjaja, E.; Wang-Erlandsson, L.; Hessels, T.; Bastiaanssen, W.; Bierkens, M. F.
2017-12-01
The storage and dynamics of water in the root zone control many important hydrological processes such as saturation excess overland flow, interflow, recharge, capillary rise, soil evaporation and transpiration. These processes are parameterized in hydrological models or land-surface schemes and the effect on runoff prediction can be large. Root zone parameters in global hydrological models are very uncertain as they cannot be measured directly at the scale on which these models operate. In this paper we calibrate the global hydrological model PCR-GLOBWB using a state-of-the-art ensemble of evaporation fields derived by solving the energy balance for satellite observations. We focus our calibration on the root zone parameters of PCR-GLOBWB and derive spatial patterns of maximum root zone storage. We find these patterns to correspond well with previous research. The parameterization of our model allows for the conversion of maximum root zone storage to root zone depth and we find that these correspond quite well to the point observations where available. We conclude that climate and soil type should be taken into account when regionalizing measured root depth for a certain vegetation type. We equally find that using evaporation rather than discharge better allows for local adjustment of root zone parameters within a basin and thus provides orthogonal data to diagnose and optimize hydrological models and land surface schemes.
Performance Analysis of Different NeQuick Ionospheric Model Parameters
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WANG Ningbo
2017-04-01
Full Text Available Galileo adopts NeQuick model for single-frequency ionospheric delay corrections. For the standard operation of Galileo, NeQuick model is driven by the effective ionization level parameter Az instead of the solar activity level index, and the three broadcast ionospheric coefficients are determined by a second-polynomial through fitting the Az values estimated from globally distributed Galileo Sensor Stations (GSS. In this study, the processing strategies for the estimation of NeQuick ionospheric coefficients are discussed and the characteristics of the NeQuick coefficients are also analyzed. The accuracy of Global Position System (GPS broadcast Klobuchar, original NeQuick2 and fitted NeQuickC as well as Galileo broadcast NeQuickG models is evaluated over the continental and oceanic regions, respectively, in comparison with the ionospheric total electron content (TEC provided by global ionospheric maps (GIM, GPS test stations and JASON-2 altimeter. The results show that NeQuickG can mitigate ionospheric delay by 54.2%~65.8% on a global scale, and NeQuickC can correct for 71.1%~74.2% of the ionospheric delay. NeQuick2 performs at the same level with NeQuickG, which is a bit better than that of GPS broadcast Klobuchar model.
Exploring parameter constraints on quintessential dark energy: The exponential model
International Nuclear Information System (INIS)
Bozek, Brandon; Abrahamse, Augusta; Albrecht, Andreas; Barnard, Michael
2008-01-01
We present an analysis of a scalar field model of dark energy with an exponential potential using the Dark Energy Task Force (DETF) simulated data models. Using Markov Chain Monte Carlo sampling techniques we examine the ability of each simulated data set to constrain the parameter space of the exponential potential for data sets based on a cosmological constant and a specific exponential scalar field model. We compare our results with the constraining power calculated by the DETF using their 'w 0 -w a ' parametrization of the dark energy. We find that respective increases in constraining power from one stage to the next produced by our analysis give results consistent with DETF results. To further investigate the potential impact of future experiments, we also generate simulated data for an exponential model background cosmology which cannot be distinguished from a cosmological constant at DETF 'Stage 2', and show that for this cosmology good DETF Stage 4 data would exclude a cosmological constant by better than 3σ
Higher derivative extensions of 3d Chern-Simons models: conservation laws and stability
Energy Technology Data Exchange (ETDEWEB)
Kaparulin, D.S.; Karataeva, I.Yu.; Lyakhovich, S.L. [Tomsk State University, Physics Faculty, Tomsk (Russian Federation)
2015-11-15
We consider the class of higher derivative 3d vector field models with the field equation operator being a polynomial of the Chern-Simons operator. For the nth-order theory of this type, we provide a general recipe for constructing n-parameter family of conserved second rank tensors. The family includes the canonical energy-momentum tensor, which is unbounded, while there are bounded conserved tensors that provide classical stability of the system for certain combinations of the parameters in the Lagrangian. We also demonstrate the examples of consistent interactions which are compatible with the requirement of stability. (orig.)
International Nuclear Information System (INIS)
Avila Moreno, R.; Barrdahl, R.; Haegg, C.
1995-05-01
The main objective of the present study was to carry out a screening and a sensitivity analysis of the SSI TOOLBOX source term model SOSIM. This model is a part of the SSI TOOLBOX for radiological impact assessment of the Swedish disposal concept for high-level waste KBS-3. The outputs of interest for this purpose were: the total released fraction, the time of total release, the time and value of maximum release rate, the dose rates after direct releases of the biosphere. The source term equations were derived and simple equations and methods were proposed for calculation of these. A literature survey has been performed in order to determine a characteristic variation range and a nominal value for each model parameter. In order to reduce the model uncertainties the authors recommend a change in the initial boundary condition for solution of the diffusion equation for highly soluble nuclides. 13 refs
Mikhailov, E.; Vlasenko, S.; Rose, D.; Pöschl, U.
2013-01-01
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 κm which can be deconvoluted into a dilute hygroscopicity parameter (κm0) 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 κm-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 collected from boreal rural air and from pristine tropical rainforest air (secondary
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
Directory of Open Access Journals (Sweden)
N. Bulygina
2009-06-01
Full Text Available Data scarcity and model over-parameterisation, leading to model equifinality and large prediction uncertainty, are common barriers to effective hydrological modelling. The problem can be alleviated by constraining the prior parameter space using parameter regionalisation. A common basis for regionalisation in the UK is the HOST database which provides estimates of hydrological indices for different soil classifications. In our study, Base Flow Index is estimated from the HOST database and the power of this index for constraining the parameter space is explored. The method is applied to a highly discretised distributed model of a 12.5 km^{2} upland catchment in Wales. To assess probabilistic predictions against flow observations, a probabilistic version of the Nash-Sutcliffe efficiency is derived. For six flow gauges with reliable data, this efficiency ranged between 0.70 and 0.81, and inspection of the results shows that the model explains the data well. Knowledge of how Base Flow Index and interception losses may change under future land use management interventions was then used to further condition the model. Two interventions are considered: afforestation of grazed areas, and soil degradation associated with increased grazing intensity. Afforestation leads to median reduction in modelled runoff volume of 24% over the simulated 3 month period; and a median peak flow reduction ranging from 12 to 15% over the six gauges for the largest simulated event. Uncertainty in all results is low compared to prior uncertainty and it is concluded that using Base Flow Index estimated from HOST is a simple and potentially powerful method of conditioning the parameter space under current and future land management.
Application of multi-parameter chorus and plasmaspheric hiss wave models in radiation belt modeling
Aryan, H.; Kang, S. B.; Balikhin, M. A.; Fok, M. C. H.; Agapitov, O. V.; Komar, C. M.; Kanekal, S. G.; Nagai, T.; Sibeck, D. G.
2017-12-01
Numerical simulation studies of the Earth's radiation belts are important to understand the acceleration and loss of energetic electrons. The Comprehensive Inner Magnetosphere-Ionosphere (CIMI) model along with many other radiation belt models require inputs for pitch angle, energy, and cross diffusion of electrons, due to chorus and plasmaspheric hiss waves. These parameters are calculated using statistical wave distribution models of chorus and plasmaspheric hiss amplitudes. In this study we incorporate recently developed multi-parameter chorus and plasmaspheric hiss wave models based on geomagnetic index and solar wind parameters. We perform CIMI simulations for two geomagnetic storms and compare the flux enhancement of MeV electrons with data from the Van Allen Probes and Akebono satellites. We show that the relativistic electron fluxes calculated with multi-parameter wave models resembles the observations more accurately than the relativistic electron fluxes calculated with single-parameter wave models. This indicates that wave models based on a combination of geomagnetic index and solar wind parameters are more effective as inputs to radiation belt models.
TID Parameters over the Antarctic Peninsula as Derived from TEC Measurements.
Paznukhov, V.; Galushko, V.; Groves, K. M.; Sopin, A.; Yampolski, Y.
2014-12-01
Results of TID analysis from multi-site TEC observations over the Antarctic Peninsula for the period from 2009 to 2012 are presented. Diurnal dependences of the occurrence frequency, and motion velocity and direction probability density distributions are determined for middle-scale traveling ionospheric disturbances (MSTIDs). TID parameters are calculated using dynamic approach to the problem of ionospheric disturbance diagnostics which has been extended to allow for an arbitrary waveform of TEC perturbations. We have also developed a dedicated algorithm to determine the presence of TID disturbances in the TEC records which is based on the correlation analysis. Statistical treatment of the obtained results shows that during daytime the TIDs propagate predominantly in the northern and northeastern directions. In the evening and nocturnal hours the northwestern direction is prevailing, with the characteristic TID velocities range from 10 to 250 m/s. The most probable TID velocities are tens of meters per second, while the mean values are equal to about 100 - 130 m/s. During the daytime the velocities of the ionospheric disturbances are even higher. The work also presents variations of the TID parameters with seasons and geomagnetic conditions and the role of the solar terminator as a possible source of the disturbances is discussed.
CPT Profiling and Laboratory Data Correlations for Deriving of Selected Geotechnical Parameter
Directory of Open Access Journals (Sweden)
Bulko Roman
2015-12-01
Full Text Available Currently, can be seen a new trend in engineering geological survey, where laboratory analysis are replaced by in situ testing methods, which are more efficient and cost effective, and time saving too. A regular engineering geological survey cannot be provided by simple core drillings, macroscopic description (sometimes very subjective, and then geotechnical parameters are established based on indicative standardized values or archive values from previous geotechnical standards. The engineering geological survey is trustworthy if is composed of laboratory and in-situ testing supplemented by indirect methods of testing, [1]. The prevalence of rotary core drilling for obtaining laboratory soil samples from various depths (every 1 to 3 m, cannot be a more enhanced as continues evaluation of strata and properties e.g. by CPT Piezocone (every 1 cm. Core drillings survey generally uses small amounts of soil samples, but this is resulting to a lower representation of the subsoil and underestimation of parameters. Higher amounts of soil samples make laboratory testing time-consuming and results from this testing can be influenced by the storage and processing of the soil samples. Preference for geotechnical surveys with in situ testing is therefore a more suitable option. In situ testing using static and dynamic penetration tests can be used as a supplement or as a replacement for the (traditional methods of surveying.
Visser, A; Moran, J E; Hillegonds, Darren; Singleton, M J; Kulongoski, Justin T; Belitz, Kenneth; Esser, B K
2016-03-15
Key characteristics of California groundwater systems related to aquifer vulnerability, sustainability, recharge locations and mechanisms, and anthropogenic impact on recharge are revealed in a spatial geostatistical analysis of a unique data set of tritium, noble gases and other isotopic analyses unprecedented in size at nearly 4000 samples. The correlation length of key groundwater residence time parameters varies between tens of kilometers ((3)H; age) to the order of a hundred kilometers ((4)Heter; (14)C; (3)Hetrit). The correlation length of parameters related to climate, topography and atmospheric processes is on the order of several hundred kilometers (recharge temperature; δ(18)O). Young groundwater ages that highlight regional recharge areas are located in the eastern San Joaquin Valley, in the southern Santa Clara Valley Basin, in the upper LA basin and along unlined canals carrying Colorado River water, showing that much of the recent recharge in central and southern California is dominated by river recharge and managed aquifer recharge. Modern groundwater is found in wells with the top open intervals below 60 m depth in the southeastern San Joaquin Valley, Santa Clara Valley and Los Angeles basin, as the result of intensive pumping and/or managed aquifer recharge operations. Copyright © 2016 Elsevier Ltd. All rights reserved.
Carrozzo, Marina M; Cannazza, Giuseppe; Battisti, Umberto; Braghiroli, Daniela; Parenti, Carlo
2010-05-05
On-column stopped flow multidimensional HPLC (sfMDHPLC) and dynamic high-performance liquid chromatography were applied to investigate the influence of alkyl substituents at the sulfonamidic and amino moieties of benzothiadiazine 1,1-dioxide derivatives on hydrolysis and enantiomerization rate constants. The data obtained indicate the presence of pyrrolo substituent at the 3,4 positions on benzothiadiazine rings inhibits the hydrolysis, whereas the enantiomerization occurs in acidic medium. Hydrolysis rates are quite similar for the two benzothiadiazines methyl substituted to nitrogen at 2- and 4-positions. Conversely, enantiomerization rate of 4-N-methyl substituted is significantly higher than 2-N-methyl substituted. 2009 Wiley-Liss, Inc.
Temporal and spatial deviation in F2 peak parameters derived from FORMOSAT-3/COSMIC
Kumar, Sanjay; Singh, R. P.; Tan, Eng Leong; Singh, A. K.; Ghodpage, R. N.; Siingh, Devendraa
2016-06-01
The plasma frequency profiles derived from the Constellation of Observing System for Meteorology, Ionosphere and Climate (COSMIC) radio occultation measurements are compared with ground-based ionosonde data during the year 2013. Equatorial and midlatitude five stations located in the Northern and Southern Hemisphere are considered: Jicamarca, Jeju, Darwin, Learmonth, and Juliusruh. The aim is to validate the COSMIC-derived data with ground-based measurements and to estimate the difference in plasma frequency (which represents electron density) and height of F2 layer peak during the daytime/nighttime and during different seasons by comparing the two data sets. Analysis showed that the nighttime data are better correlated than the daytime, and the maximum difference occurs at the equatorial ionospheric anomaly (EIA) station as compared to lower and midlatitude stations during the equinox months. The difference between daytime and nighttime correlations becomes insignificant at midlatitude stations. The statistical analysis of computed errors in foF2 (hmF2) showed Gaussian nature with the most probable error range of ±15% (±10%) at the equatorial and EIA stations, ±9% (±7%) outside the EIA region which reduced to ±8% (±6%) at midlatitude stations. The reduction in error at midlatitudes is attributed to the decrease in latitudinal electron density gradients. Comparing the analyzed data during the three geomagnetic storms and quiet days of the same months, it is observed that the differences are significantly enhanced during storm periods and the magnitude of difference in foF2 increases with the intensity of geomagnetic storm.
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
Ghassoun, Yahya; Löwner, Marc-Oliver
2017-10-01
Total particle number concentration (TNC) was studied in a 1 × 2 km area in Berlin, the capital of Germany by three Land Use Regression models (LUR). The estimation of TNC was established and compared using one 2D-LUR and two 3D-LUR models. All models predict total number concentrations TNC by using urban morphological (2D resp. 3D) and additional semantical parameters. 2D and semantical parameters were derived from Open Street Map data (OSM) whereas 3D parameters were derived from a CityGML-based 3D city model. While the models are capable to depict the spatial variation of TNC across the study area, the two 3D-LUR showed better results than the 2D-LUR. The 2D-LUR model explained 74% of the variance of TNC for the full data set with root mean square error (RMSE) of 4014 cm-3 while the 3D-LUR explained 79% of the variance with an RMSE of 3477 cm-3. The further introduction of a new spatial parameter, the Frontal Area Index (FAI) that represents the dynamic factor wind direction enhanced the 3D-LUR to explain 82% of the variance with RMSE of 3389 cm-3. Furthermore, the semantical parameters (e.g. streets type) played a significant role in all models.
Empirically derived neighbourhood rules for urban land-use modelling
DEFF Research Database (Denmark)
Hansen, Henning Sten
2012-01-01
interaction between neighbouring land uses is an important component in urban cellular automata. Nevertheless, this component is often calibrated through trial-and-error estimation. The aim of this project has been to develop an empirically derived landscape metric supporting cellular-automata-based land......-use modelling. Through access to very detailed urban land-use data it has been possible to derive neighbourhood rules empirically, and test their sensitivity to the land-use classification applied, the regional variability of the rules, and their time variance. The developed methodology can be implemented...
Operational derivation of Boltzmann distribution with Maxwell's demon model.
Hosoya, Akio; Maruyama, Koji; Shikano, Yutaka
2015-11-24
The resolution of the Maxwell's demon paradox linked thermodynamics with information theory through information erasure principle. By considering a demon endowed with a Turing-machine consisting of a memory tape and a processor, we attempt to explore the link towards the foundations of statistical mechanics and to derive results therein in an operational manner. Here, we present a derivation of the Boltzmann distribution in equilibrium as an example, without hypothesizing the principle of maximum entropy. Further, since the model can be applied to non-equilibrium processes, in principle, we demonstrate the dissipation-fluctuation relation to show the possibility in this direction.
Modeling of a three-phase reactor for bitumen-derived gas oil hydrotreating
Directory of Open Access Journals (Sweden)
R. Chacón
2012-03-01
Full Text Available A three-phase reactor model for describing the hydrotreating reactions of bitumen-derived gas oil was developed. The model incorporates the mass-transfer resistance at the gas-liquid and liquid-solid interfaces and a kinetic rate expression based on a Langmuir-Hinshelwood-type model. We derived three correlations for determining the solubility of hydrogen (H2, hydrogen sulfide (H2S and ammonia (NH3 in hydrocarbon mixtures and the calculation of the catalyst effectiveness factor was included. Experimental data taken from the literature were used to determine the kinetic parameters (stoichiometric coefficients, reaction orders, reaction rate and adsorption constants for hydrodesulfuration (HDS and hydrodenitrogenation (HDN and to validate the model under various operating conditions. Finally, we studied the effect of operating conditions such as pressure, temperature, LHSV, H2/feed ratio and the inhibiting effect of H2S on HDS and NH3 on HDN.
Widyaningsih, Purnami; Retno Sari Saputro, Dewi; Nugrahani Putri, Aulia
2017-06-01
GWOLR model combines geographically weighted regression (GWR) and (ordinal logistic reression) OLR models. Its parameter estimation employs maximum likelihood estimation. Such parameter estimation, however, yields difficult-to-solve system of nonlinear equations, and therefore numerical approximation approach is required. The iterative approximation approach, in general, uses Newton-Raphson (NR) method. The NR method has a disadvantage—its Hessian matrix is always the second derivatives of each iteration so it does not always produce converging results. With regard to this matter, NR model is modified by substituting its Hessian matrix into Fisher information matrix, which is termed Fisher scoring (FS). The present research seeks to determine GWOLR model parameter estimation using Fisher scoring method and apply the estimation on data of the level of vulnerability to Dengue Hemorrhagic Fever (DHF) in Semarang. The research concludes that health facilities give the greatest contribution to the probability of the number of DHF sufferers in both villages. Based on the number of the sufferers, IR category of DHF in both villages can be determined.
The electronic disability record: purpose, parameters, and model use case.
Tulu, Bengisu; Horan, Thomas A
2009-01-01
The active engagement of consumers is an important factor in achieving widespread success of health information systems. The disability community represents a major segment of the healthcare arena, with more than 50 million Americans experiencing some form of disability. In keeping with the "consumer-driven" approach to e-health systems, this paper considers the distinctive aspects of electronic and personal health record use by this segment of society. Drawing upon the information shared during two national policy forums on this topic, the authors present the concept of Electronic Disability Records (EDR). The authors outline the purpose and parameters of such records, with specific attention to its ability to organize health and financial data in a manner that can be used to expedite the disability determination process. In doing so, the authors discuss its interaction with Electronic Health Records (EHR) and Personal Health Records (PHR). The authors then draw upon these general parameters to outline a model use case for disability determination and discuss related implications for disability health management. The paper further reports on the subsequent considerations of these and related deliberations by the American Health Information Community (AHIC).
Data-based model and parameter evaluation in dynamic transcriptional regulatory networks.
Cavelier, German; Anastassiou, Dimitris
2004-05-01
Finding the causality and strength of connectivity in transcriptional regulatory networks from time-series data will provide a powerful tool for the analysis of cellular states. Presented here is the design of tools for the evaluation of the network's model structure and parameters. The most effective tools are found to be based on evolution strategies. We evaluate models of increasing complexity, from lumped, algebraic phenomenological models to Hill functions and thermodynamically derived functions. These last functions provide the free energies of binding of transcription factors to their operators, as well as cooperativity energies. Optimization results based on published experimental data from a synthetic network in Escherichia coli are presented. The free energies of binding and cooperativity found by our tools are in the same physiological ranges as those experimentally derived in the bacteriophage lambda system. We also use time-series data from high-density oligonucleotide microarrays of yeast meiotic expression patterns. The algorithm appropriately finds the parameters of pairs of regulated regulatory yeast genes, showing that for related genes an overall reasonable computation effort is sufficient to find the strength and causality of the connectivity of large numbers of them. Copyright 2004 Wiley-Liss, Inc.
Deriving numerical estimates from descriptive information: the computation of earthquake parameters
Directory of Open Access Journals (Sweden)
G. Ferrari
2000-06-01
Full Text Available We describe here how the origin time, the epicenter location, the epicentral intensity and the magnitude of the earthquakes included in the Catalogue of Strong Italian Earthquakes (CFTI3 have been determined from the documentary information available. As the literature lacks widely accepted formal definitions for these parameters in the case of macroseismic data, we developed ad hoc procedures that starting from generally shared qualitative statements give reasonable and stable results which can also be useful for statistical analysis. These procedures use all of the information available in the CFTI3 database as much as possible and make use of "robust" estimators in order to minimize the effects of anomalous data. The resulting parametric catalogue has been examined statistically for completeness showing that the great majority of the Italian earthquakes with moment magnitude larger that 5.5-6.0 of the last four centuries are correctly reported in CFTI3.
Modeling Temperature and Pricing Weather Derivatives Based on Temperature
Directory of Open Access Journals (Sweden)
Birhan Taştan
2017-01-01
Full Text Available This study first proposes a temperature model to calculate the temperature indices upon which temperature-based derivatives are written. The model is designed as a mean-reverting process driven by a Levy process to represent jumps and other features of temperature. Temperature indices are mainly measured as deviations from a base temperature, and, hence, the proposed model includes jumps because they may constitute an important part of this deviation for some locations. The estimated value of a temperature index and its distribution in this model apply an inversion formula to the temperature model. Second, this study develops a pricing process over calculated index values, which returns a customized price for temperature-based derivatives considering that temperature has unique effects on every economic entity. This personalized price is also used to reveal the trading behavior of a hypothesized entity in a temperature-based derivative trade with profit maximization as the objective. Thus, this study presents a new method that does not need to evaluate the risk-aversion behavior of any economic entity.
The S-parameter in Holographic Technicolor Models
Agashe, Kaustubh; Grojean, Christophe; Reece, Matthew
2007-01-01
We study the S parameter, considering especially its sign, in models of electroweak symmetry breaking (EWSB) in extra dimensions, with fermions localized near the UV brane. Such models are conjectured to be dual to 4D strong dynamics triggering EWSB. The motivation for such a study is that a negative value of S can significantly ameliorate the constraints from electroweak precision data on these models, allowing lower mass scales (TeV or below) for the new particles and leading to easier discovery at the LHC. We first extend an earlier proof of S>0 for EWSB by boundary conditions in arbitrary metric to the case of general kinetic functions for the gauge fields or arbitrary kinetic mixing. We then consider EWSB in the bulk by a Higgs VEV showing that S is positive for arbitrary metric and Higgs profile, assuming that the effects from higher-dimensional operators in the 5D theory are sub-leading and can therefore be neglected. For the specific case of AdS_5 with a power law Higgs profile, we also show that S ~ ...
Extracting Structure Parameters of Dimers for Molecular Tunneling Ionization Model
Zhao, Song-Feng; Huang, Fang; Wang, Guo-Li; Zhou, Xiao-Xin
2016-03-01
We determine structure parameters of the highest occupied molecular orbital (HOMO) of 27 dimers for the molecular tunneling ionization (so called MO-ADK) model of Tong et al. [Phys. Rev. A 66 (2002) 033402]. The molecular wave functions with correct asymptotic behavior are obtained by solving the time-independent Schrödinger equation with B-spline functions and molecular potentials which are numerically created using the density functional theory. We examine the alignment-dependent tunneling ionization probabilities from MO-ADK model for several molecules by comparing with the molecular strong-field approximation (MO-SFA) calculations. We show the molecular Perelomov–Popov–Terent'ev (MO-PPT) can successfully give the laser wavelength dependence of ionization rates (or probabilities). Based on the MO-PPT model, two diatomic molecules having valence orbital with antibonding systems (i.e., Cl2, Ne2) show strong ionization suppression when compared with their corresponding closest companion atoms. Supported by National Natural Science Foundation of China under Grant Nos. 11164025, 11264036, 11465016, 11364038, the Specialized Research Fund for the Doctoral Program of Higher Education of China under Grant No. 20116203120001, and the Basic Scientific Research Foundation for Institution of Higher Learning of Gansu Province
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Chakiba, Camille [Department of Medical Oncology, Bergonié Cancer Institute, Bordeaux (France); Cornelis, François [Department of Radiology, Pellegrin Hospital, Bordeaux (France); Descat, Edouard [Department of Radiology, Saint-Augustin Clinic, Bordeaux (France); Gross-Goupil, Marine [Department of Medical Oncology, Bergonié Cancer Institute, Bordeaux (France); Sargos, Paul [Department of Radiotherapy, Bergonié Cancer Institute, Bordeaux (France); Roubaud, Guilhem [Department of Medical Oncology, Bergonié Cancer Institute, Bordeaux (France); Houédé, Nadine, E-mail: nadine.houede@chu-nimes.fr [Department of Medical Oncology, Bergonié Cancer Institute, Bordeaux (France); Department of Medical Oncology, Nimes University Hosptital, Nîmes (France)
2015-06-15
Highlights: • DCE-MRI parameters could be useful biomarker for patients with localized bladder carcinoma. • Rate of relapse is lower for good responders assessed by DCE-MRI. • The use of DCE-MRI parameters may improve the standardization of patients’ selection before surgery. - Abstract: Objectives: To evaluate the performance of dynamic contrast enhanced (DCE) magnetic resonance (MR) imaging to assess the histological response after chemotherapy on bladder carcinoma. Methods: From 2008 to 2010, 12 patients presenting localized urothelial carcinoma of the bladder were prospectively evaluated by DCE-MR imaging before and after two courses of cisplatin-based neoadjuvant chemotherapy. Size and thickness of tumours were measured. Relative enhancement at the arterial (rSI{sub 35s}) and venous phases (rSI{sub 80s}) of each tumour was obtained. Histological response was assessed and outcomes were recorded. Results: Histological examination after neoadjuvant chemotherapy concluded as pathological complete response (pCR) for 6 out of 12 patients. Five patients developed recurrences (4/6 no pCR and 1/6 pCR). Significant differences, between before and after treatment, were found for patients with complete pathological response after chemotherapy for all MR quantitative values. Tumours decreased in size and thickness (both P = 0.03). After treatment, rSI{sub 80s} was significantly different between pCR and non-pCR patients (P = 0.04) with a cut-off value of 40%. For this cut-off, sensitivity, specificity and accuracy were 83.33%. Similar recurrence free survivals were obtained if applying the MR cut-off value or the histopathological findings. Conclusion: Our results suggest that DCE-MR imaging may be a useful biomarker for patients with localized bladder carcinoma, improving selection before surgery.
Miri-Dashe, Timzing; Osawe, Sophia; Tokdung, Monday; Daniel, Monday Tokdung Nenbammun; Daniel, Nenbammun; Choji, Rahila Pam; Mamman, Ille; Deme, Kurt; Damulak, Dapus; Abimiku, Alash'le
2014-01-01
Interpretation of laboratory test results with appropriate diagnostic accuracy requires reference or cutoff values. This study is a comprehensive determination of reference values for hematology and clinical chemistry in apparently healthy voluntary non-remunerated blood donors and pregnant women. Consented clients were clinically screened and counseled before testing for HIV, Hepatitis B, Hepatitis C and Syphilis. Standard national blood donors' questionnaire was administered to consented blood donors. Blood from qualified volunteers was used for measurement of complete hematology and chemistry parameters. Blood samples were analyzed from a total of 383 participants, 124 (32.4%) males, 125 (32.6%) non-pregnant females and 134 pregnant females (35.2%) with a mean age of 31 years. Our results showed that the red blood cells count (RBC), Hemoglobin (HB) and Hematocrit (HCT) had significant gender difference (p = 0.000) but not for total white blood count (p>0.05) which was only significantly higher in pregnant verses non-pregnant women (p = 0.000). Hemoglobin and Hematocrit values were lower in pregnancy (P = 0.000). Platelets were significantly higher in females than men (p = 0.001) but lower in pregnant women (p = .001) with marked difference in gestational period. For clinical chemistry parameters, there was no significant difference for sodium, potassium and chloride (p>0.05) but gender difference exists for Bicarbonate (HCO3), Urea nitrogen, Creatinine as well as the lipids (p0.05). Hematological and Clinical Chemistry reference ranges established in this study showed significant gender differences. Pregnant women also differed from non-pregnant females and during pregnancy. This is the first of such comprehensive study to establish reference values among adult Nigerians and difference observed underscore the need to establish reference values for different populations.
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Timzing Miri-Dashe
Full Text Available BACKGROUND: Interpretation of laboratory test results with appropriate diagnostic accuracy requires reference or cutoff values. This study is a comprehensive determination of reference values for hematology and clinical chemistry in apparently healthy voluntary non-remunerated blood donors and pregnant women. METHODS AND FINDINGS: Consented clients were clinically screened and counseled before testing for HIV, Hepatitis B, Hepatitis C and Syphilis. Standard national blood donors' questionnaire was administered to consented blood donors. Blood from qualified volunteers was used for measurement of complete hematology and chemistry parameters. Blood samples were analyzed from a total of 383 participants, 124 (32.4% males, 125 (32.6% non-pregnant females and 134 pregnant females (35.2% with a mean age of 31 years. Our results showed that the red blood cells count (RBC, Hemoglobin (HB and Hematocrit (HCT had significant gender difference (p = 0.000 but not for total white blood count (p>0.05 which was only significantly higher in pregnant verses non-pregnant women (p = 0.000. Hemoglobin and Hematocrit values were lower in pregnancy (P = 0.000. Platelets were significantly higher in females than men (p = 0.001 but lower in pregnant women (p = .001 with marked difference in gestational period. For clinical chemistry parameters, there was no significant difference for sodium, potassium and chloride (p>0.05 but gender difference exists for Bicarbonate (HCO3, Urea nitrogen, Creatinine as well as the lipids (p0.05. CONCLUSIONS: Hematological and Clinical Chemistry reference ranges established in this study showed significant gender differences. Pregnant women also differed from non-pregnant females and during pregnancy. This is the first of such comprehensive study to establish reference values among adult Nigerians and difference observed underscore the need to establish reference values for different populations.
Sound propagation and absorption in foam - A distributed parameter model.
Manson, L.; Lieberman, S.
1971-01-01
Liquid-base foams are highly effective sound absorbers. A better understanding of the mechanisms of sound absorption in foams was sought by exploration of a mathematical model of bubble pulsation and coupling and the development of a distributed-parameter mechanical analog. A solution by electric-circuit analogy was thus obtained and transmission-line theory was used to relate the physical properties of the foams to the characteristic impedance and propagation constants of the analog transmission line. Comparison of measured physical properties of the foam with values obtained from measured acoustic impedance and propagation constants and the transmission-line theory showed good agreement. We may therefore conclude that the sound propagation and absorption mechanisms in foam are accurately described by the resonant response of individual bubbles coupled to neighboring bubbles.
Wentworth, Mami Tonoe
Uncertainty quantification plays an important role when making predictive estimates of model responses. In this context, uncertainty quantification is defined as quantifying and reducing uncertainties, and the objective is to quantify uncertainties in parameter, model and measurements, and propagate the uncertainties through the model, so that one can make a predictive estimate with quantified uncertainties. Two of the aspects of uncertainty quantification that must be performed prior to propagating uncertainties are model calibration and parameter selection. There are several efficient techniques for these processes; however, the accuracy of these methods are often not verified. This is the motivation for our work, and in this dissertation, we present and illustrate verification frameworks for model calibration and parameter selection in the context of biological and physical models. First, HIV models, developed and improved by [2, 3, 8], describe the viral infection dynamics of an HIV disease. These are also used to make predictive estimates of viral loads and T-cell counts and to construct an optimal control for drug therapy. Estimating input parameters is an essential step prior to uncertainty quantification. However, not all the parameters are identifiable, implying that they cannot be uniquely determined by the observations. These unidentifiable parameters can be partially removed by performing parameter selection, a process in which parameters that have minimal impacts on the model response are determined. We provide verification techniques for Bayesian model calibration and parameter selection for an HIV model. As an example of a physical model, we employ a heat model with experimental measurements presented in [10]. A steady-state heat model represents a prototypical behavior for heat conduction and diffusion process involved in a thermal-hydraulic model, which is a part of nuclear reactor models. We employ this simple heat model to illustrate verification
Pseudo-dynamic source modelling with 1-point and 2-point statistics of earthquake source parameters
Song, S. G.
2013-12-24
Ground motion prediction is an essential element in seismic hazard and risk analysis. Empirical ground motion prediction approaches have been widely used in the community, but efficient simulation-based ground motion prediction methods are needed to complement empirical approaches, especially in the regions with limited data constraints. Recently, dynamic rupture modelling has been successfully adopted in physics-based source and ground motion modelling, but it is still computationally demanding and many input parameters are not well constrained by observational data. Pseudo-dynamic source modelling keeps the form of kinematic modelling with its computational efficiency, but also tries to emulate the physics of source process. In this paper, we develop a statistical framework that governs the finite-fault rupture process with 1-point and 2-point statistics of source parameters in order to quantify the variability of finite source models for future scenario events. We test this method by extracting 1-point and 2-point statistics from dynamically derived source models and simulating a number of rupture scenarios, given target 1-point and 2-point statistics. We propose a new rupture model generator for stochastic source modelling with the covariance matrix constructed from target 2-point statistics, that is, auto- and cross-correlations. Our sensitivity analysis of near-source ground motions to 1-point and 2-point statistics of source parameters provides insights into relations between statistical rupture properties and ground motions. We observe that larger standard deviation and stronger correlation produce stronger peak ground motions in general. The proposed new source modelling approach will contribute to understanding the effect of earthquake source on near-source ground motion characteristics in a more quantitative and systematic way.
Coupled 1D-2D hydrodynamic inundation model for sewer overflow: Influence of modeling parameters
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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.
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.
Modeling and Parameter Estimation of Spacecraft Fuel Slosh with Diaphragms Using Pendulum Analogs
Chatman, Yadira; Gangadharan, Sathya; Schlee, Keith; Ristow, James; Suderman, James; Walker, Charles; Hubert, Carl
2007-01-01
Prediction and control of liquid slosh in moving containers is an important consideration in the design of spacecraft and launch vehicle control systems. Even with modern computing systems, CFD type simulations are not fast enough to allow for large scale Monte Carlo analyses of spacecraft and launch vehicle dynamic behavior with slosh included. It is still desirable to use some type of simplified mechanical analog for the slosh to shorten computation time. Analytic determination of the slosh analog parameters has met with mixed success and is made even more difficult by the introduction of propellant management devices such as elastomeric diaphragms. By subjecting full-sized fuel tanks with actual flight fuel loads to motion similar to that experienced in flight and measuring the forces experienced by the tanks, these parameters can be determined experimentally. Currently, the identification of the model parameters is a laborious trial-and-error process in which the hand-derived equations of motion for the mechanical analog are evaluated and their results compared with the experimental results. This paper will describe efforts by the university component of a team comprised of NASA's Launch Services Program, Embry Riddle Aeronautical University, Southwest Research Institute and Hubert Astronautics to improve the accuracy and efficiency of modeling techniques used to predict these types of motions. Of particular interest is the effect of diaphragms and bladders on the slosh dynamics and how best to model these devices. The previous research was an effort to automate the process of slosh model parameter identification using a MATLAB/SimMechanics-based computer simulation. These results are the first step in applying the same computer estimation to a full-size tank and vehicle propulsion system. The introduction of diaphragms to this experimental set-up will aid in a better and more complete prediction of fuel slosh characteristics and behavior. Automating the
Differential geometry of viscoelastic models with fractional-order derivatives
International Nuclear Information System (INIS)
Yajima, Takahiro; Nagahama, Hiroyuki
2010-01-01
Viscoelastic materials with memory effect are studied based on the fractional rheonomic geometry. The geometric objects are regarded as basic quantities of fractional viscoelastic models, i.e. the metric tensor and torsion tensor are interpreted as the strain and the fractional strain rate, respectively. The generalized viscoelastic equations are expressed by the geometric objects. Especially, the basic constitutive equations such as Voigt and Maxwell models can be derived geometrically from the generalized equation. This leads to the fact that various viscoelastic models can be unified into one geometric expression.
Joint Parameter Estimation for the Two-Wave with Diffuse Power Fading Model
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Jesus Lopez-Fernandez
2016-06-01
Full Text Available Wireless sensor networks deployed within metallic cavities are known to suffer from a very severe fading, even in strong line-of-sight propagation conditions. This behavior is well-captured by the Two-Wave with Diffuse Power (TWDP fading distribution, which shows great fit to field measurements in such scenarios. In this paper, we address the joint estimation of the parameters K and Δ that characterize the TWDP fading model, based on the observation of the received signal envelope. We use a moment-based approach to derive closed-form expressions for the estimators of K and Δ, as well as closed-form expressions for their asymptotic variance. Results show that the estimation error is close to the Cramer-Rao lower bound for a wide range of values of the parameters K and Δ. The performance degradation due to a finite number of observations is also analyzed.
Achleitner, S; Rinderer, M; Kirnbauer, R
2009-01-01
For the Tyrolean part of the river Inn, a hybrid model for flood forecast has been set up and is currently in its test phase. The system is a hybrid system which comprises of a hydraulic 1D model for the river Inn, and the hydrological models HQsim (Rainfall-runoff-discharge model) and the snow and ice melt model SES for modeling the rainfall runoff form non-glaciated and glaciated tributary catchment respectively. Within this paper the focus is put on the hydrological modeling of the totally 49 connected non-glaciated catchments realized with the software HQsim. In the course of model calibration, the identification of the most sensitive parameters is important aiming at an efficient calibration procedure. The indicators used for explaining the parameter sensitivities were chosen specifically for the purpose of flood forecasting. Finally five model parameters could be identified as being sensitive for model calibration when aiming for a well calibrated model for flood conditions. In addition two parameters were identified which are sensitive in situations where the snow line plays an important role.
Clark, D Angus; Nuttall, Amy K; Bowles, Ryan P
2018-01-01
Latent change score models (LCS) are conceptually powerful tools for analyzing longitudinal data (McArdle & Hamagami, 2001). However, applications of these models typically include constraints on key parameters over time. Although practically useful, strict invariance over time in these parameters is unlikely in real data. This study investigates the robustness of LCS when invariance over time is incorrectly imposed on key change-related parameters. Monte Carlo simulation methods were used to explore the impact of misspecification on parameter estimation, predicted trajectories of change, and model fit in the dual change score model, the foundational LCS. When constraints were incorrectly applied, several parameters, most notably the slope (i.e., constant change) factor mean and autoproportion coefficient, were severely and consistently biased, as were regression paths to the slope factor when external predictors of change were included. Standard fit indices indicated that the misspecified models fit well, partly because mean level trajectories over time were accurately captured. Loosening constraint improved the accuracy of parameter estimates, but estimates were more unstable, and models frequently failed to converge. Results suggest that potentially common sources of misspecification in LCS can produce distorted impressions of developmental processes, and that identifying and rectifying the situation is a challenge.
Testing sensitivity of the LISFLOOD subgrid hydraulic model to SAR image derived information
Wood, Melissa; Bates, Paul; Neal, Jeff; Hostache, Renaud; Matgen, Patrick; Chini, Marco; Giustarini, Laura
2013-04-01
There has been much interest in the use of Synthetic Aperture Radar (SAR) images to indirectly estimate flood extent and flood elevation to aid the understanding of fluvial flood inundation processes. SAR remote sensing satellites are capable of all-weather day/night observations that can discriminate between land and smooth open water surfaces over large scales. By combining SAR derived information with 2D hydraulic models and terrain data, the mechanisms of flooding can be better simulated therefore enabling more accurate and reliable flood forecasting. The objective of this study is to test the sensitivity of a LISFLOOD subgrid 2D model to its main parameters (i.e. roughness coefficient, river bathymetry) using SAR derived flood extent maps. Because of SAR imaging techniques and processing steps used to derive the flood information, any SAR-derived flood extent image will contain inherent uncertainty. We therefore use the uncertainty of the SAR information to obtain a range of plausible parameters to test sensitivity of the hydraulic model. LISFLOOD is a distributed 2D model developed at the University of Bristol and designed for use with larger ungauged river catchments. The version used employs a subgrid procedure which allows any size of river channel below that of the grid resolution to be represented. This procedure has been shown to improve hydraulic connectivity within the modelled flooded area and thus improve flood prediction for data sparse areas. A hydrodynamic LISFLOOD subgrid model of the River Severn at Tewkesbury covering a domain area of 50x70km and including the confluence with a major tributary (the River Avon) will be utilised. A complete storm hydrograph will be used as inflow to the model to simulate the full flood event. Surveyed cross section and gauged daily flows are also available for the River Severn. Therefore, the model results using variable parameters can be compared against results obtained from ground observations to further
Validation of mixing heights derived from the operational NWP models at the German weather service
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Fay, B.; Schrodin, R.; Jacobsen, I. [Deutscher Wetterdienst, Offenbach (Germany); Engelbart, D. [Deutscher Wetterdienst, Meteorol. Observ. Lindenberg (Germany)
1997-10-01
NWP models incorporate an ever-increasing number of observations via four-dimensional data assimilation and are capable of providing comprehensive information about the atmosphere both in space and time. They describe not only near surface parameters but also the vertical structure of the atmosphere. They operate daily, are well verified and successfully used as meteorological pre-processors in large-scale dispersion modelling. Applications like ozone forecasts, emission or power plant control calculations require highly resolved, reliable, and routine values of the temporal evolution of the mixing height (MH) which is a critical parameter in determining the mixing and transformation of substances and the resulting pollution levels near the ground. The purpose of development at the German Weather Service is a straightforward mixing height scheme that uses only parameters derived from NWP model variables and thus automatically provides spatial and temporal fields of mixing heights on an operational basis. An universal parameter to describe stability is the Richardson number Ri. Compared to the usual diagnostic or rate equations, the Ri number concept of determining mixing heights has the advantage of using not only surface layer parameters but also regarding the vertical structure of the boundary layer resolved in the NWP models. (au)
Physical property parameter set for modeling ICPP aqueous wastes with ASPEN electrolyte NRTL model
International Nuclear Information System (INIS)
Schindler, R.E.
1996-09-01
The aqueous waste evaporators at the Idaho Chemical Processing Plant (ICPP) are being modeled using ASPEN software. The ASPEN software calculates chemical and vapor-liquid equilibria with activity coefficients calculated using the electrolyte Non-Random Two Liquid (NRTL) model for local excess Gibbs free energies of interactions between ions and molecules in solution. The use of the electrolyte NRTL model requires the determination of empirical parameters for the excess Gibbs free energies of the interactions between species in solution. This report covers the development of a set parameters, from literature data, for the use of the electrolyte NRTL model with the major solutes in the ICPP aqueous wastes
Testing for parameter instability across different modeling frameworks
Calvori, Francesco; Creal, Drew; Koopman, Siem Jan; Lucas, André
2017-01-01
We develop a new parameter instability test that generalizes the seminal ARCHLagrange Multiplier test of Engle (1982) for a constant variance against the alternative of autoregressive conditional heteroskedasticity to settings with nonlinear timevarying parameters and non-Gaussian distributions. We
Statistical osteoporosis models using composite finite elements: a parameter study.
Wolfram, Uwe; Schwen, Lars Ole; Simon, Ulrich; Rumpf, Martin; Wilke, Hans-Joachim
2009-09-18
Osteoporosis is a widely spread disease with severe consequences for patients and high costs for health care systems. The disease is characterised by a loss of bone mass which induces a loss of mechanical performance and structural integrity. It was found that transverse trabeculae are thinned and perforated while vertical trabeculae stay intact. For understanding these phenomena and the mechanisms leading to fractures of trabecular bone due to osteoporosis, numerous researchers employ micro-finite element models. To avoid disadvantages in setting up classical finite element models, composite finite elements (CFE) can be used. The aim of the study is to test the potential of CFE. For that, a parameter study on numerical lattice samples with statistically simulated, simplified osteoporosis is performed. These samples are subjected to compression and shear loading. Results show that the biggest drop of compressive stiffness is reached for transverse isotropic structures losing 32% of the trabeculae (minus 89.8% stiffness). The biggest drop in shear stiffness is found for an isotropic structure also losing 32% of the trabeculae (minus 67.3% stiffness). The study indicates that losing trabeculae leads to a worse drop of macroscopic stiffness than thinning of trabeculae. The results further demonstrate the advantages of CFEs for simulating micro-structured samples.
Coarse-graining for fast dynamics of order parameters in the phase-field model
Jou, D.; Galenko, P. K.
2018-01-01
In standard descriptions, the master equation can be obtained by coarse-graining with the application of the hypothesis of full local thermalization that is equivalent to the local thermodynamic equilibrium. By contrast, fast transformations proceed in the absence of local equilibrium and the master equation must be obtained with the absence of thermalization. In the present work, a non-Markovian master equation leading, in specific cases of relaxation to local thermodynamic equilibrium, to hyperbolic evolution equations for a binary alloy, is derived for a system with two order parameters. One of them is a conserved order parameter related to the atomistic composition, and the other one is a non-conserved order parameter, which is related to phase field. A microscopic basis for phenomenological phase-field models of fast phase transitions, when the transition is so fast that there is not sufficient time to achieve local thermalization between two successive elementary processes in the system, is provided. In a particular case, when the relaxation to local thermalization proceeds by the exponential law, the obtained coarse-grained equations are related to the hyperbolic phase-field model. The solution of the model equations is obtained to demonstrate non-equilibrium phenomenon of solute trapping which appears in rapid growth of dendritic crystals. This article is part of the theme issue `From atomistic interfaces to dendritic patterns'.
Directory of Open Access Journals (Sweden)
Mata-Cabrera Francisco
2013-10-01
Full Text Available Polyetheretherketone (PEEK composite belongs to a group of high performance thermoplastic polymers and is widely used in structural components. To improve the mechanical and tribological properties, short fibers are added as reinforcement to the material. Due to its functional properties and potential applications, it’s impor- tant to investigate the machinability of non-reinforced PEEK (PEEK, PEEK rein- forced with 30% of carbon fibers (PEEK CF30, and reinforced PEEK with 30% glass fibers (PEEK GF30 to determine the optimal conditions for the manufacture of the parts. The present study establishes the relationship between the cutting con- ditions (cutting speed and feed rate and the roughness (Ra , Rt , Rq , Rp , by develop- ing second order mathematical models. The experiments were planned as per full factorial design of experiments and an analysis of variance has been performed to check the adequacy of the models. These state the adequacy of the derived models to obtain predictions for roughness parameters within ranges of parameters that have been investigated during the experiments. The experimental results show that the most influence of the cutting parameters is the feed rate, furthermore, proved that glass fiber reinforcements produce a worse machinability.
International Nuclear Information System (INIS)
Khan, Z.; Nawaz, M.
2013-01-01
Anemia is one of the most common micronutrient deficiency in our community. Nutritional anaemias are caused when there is an inadequate body store of a specific nutrient needed for hemoglobin synthesis. The most common nutrient deficiency is of iron. Therefore, a cross-sectional survey was conducted on the healthy elderly male, aged >= 40 and 77 years (n=60) volunteers in order to assess their blood parameters, such as hemoglobin concentration (Hb), hematocrit (HCT), red blood cell count (RBC), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH) and mean corpuscular hemoglobin concentration (MCHC) for the diagnosis of anemia. The demographic results showed mean values (50.10+-8.79) years for age, 66-68 +- 1.95 inches for height , 71.43 +- 6.43 kg body weight, 98.34+-0.48 degree F body temperature, 124 +- 8.67 systolic blood pressure, 82.17 +- 4.15 diastolic pressure while, The pulse rate was found to be 74.63 +- 7.02/minute. Similarly, mean values for lean body weight (LBW) found to be 49.9+-2.89, ideal body weight (IBW) 60.9 +- 4.49, body surface area (BSA) was 1.8 +- 0.1 m2 whereas, body mass index (BMI) showed mean value 24.9 +- 2.6 kg/m2. More so, overall mean Hb found to be 13.60 g/dl, RBC 4.6 mill/mm3, HCT/PCV 43%, MCV 92.95fl, MCH 29.42 pg and MCHC was found to be 31.73 g/dl. The normal range of Hb for men was 13-17 g/dl and 31.67% of the subjects participated in the study was considered to be anemic showing less Hb than normal range. The volunteers were suggested to improve the dietary habits and to take iron supplements in order to overcome the iron deficiency anemia. (author)
Effects of previous severe exercise on two and three parameter critical power modeling
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Eduardo Kokubun
2007-09-01
Full Text Available The purpose of this study was to apply the two and three-parameter critical power model equations after depletion of a fi xed amount of anaerobic work capacity (AWC, followed by a short rest period. Sixteen subjects underwent: (1 two practice trials for ergometer familiarization to severe exercise; (2 4-5 exercise bouts on different days for the estimation of critical power (CP and AWC using the two and three parameter models; (3 the same procedures as described in stage 2 were repeated after 30 s recovery from 180 s of exercise completed at an intensity that would have elicited exhaustion in around 300 s. The CP2parameter (130-174 W versus 131-170 W and CP3parameter (108 versus 100 W estimated after prior severe exercise followed by a short rest period remained stable compared to the fatigue-free tests. The AWC2parameter was reduced in response to prior severe exercise. The AWC3parameter was not significantly reduced. The correlations between CP2parameter derived from the same equation with and without prior AWC2parameter reduction were strong (r = 0.97-0.99, P ABSTRACT O propósito do presente estudo foi aplicar as equações do modelo de potência crítica de dois e três parâmetros após a depleção de uma quantia fi xa de capacidade de trabalho anaeróbio (AWC, seguido de um período curto de repouso. Dezesseis sujeitos realizaram: (1 duas familiarizações ao exercício severo no cicloergômetro; (2 4-5 exercícios máximos em dias diferentes para a estimativa da CP e AWC por meio dos modelos de dois e três parâmetros; (3 os mesmos procedimentos descritos no #2 foram realizados após 30 s de repouso e de um exercício de 180 s a uma intensidade em que a exaustão provavelmente ocorreria em ~300 s. A CP2parameter (130-174 W versus 131-170 W e CP3parameter (108 versus 100 W estimadas após o exercício prévio severo e seguido por um curto período de repouso permaneceu estável quando comparado às estimativas sem o exercício pr
Shuguang Liua; Pamela Anderson; Guoyi Zhoud; Boone Kauffman; Flint Hughes; David Schimel; Vicente Watson; Joseph. Tosi
2008-01-01
Objectively assessing the performance of a model and deriving model parameter values from observations are critical and challenging in landscape to regional modeling. In this paper, we applied a nonlinear inversion technique to calibrate the ecosystem model CENTURY against carbon (C) and nitrogen (N) stock measurements collected from 39 mature tropical forest sites in...
Relativistic nuclear matter with alternative derivative coupling models
International Nuclear Information System (INIS)
Delfino, A.; Coelho, C.T.; Malheiro, M.
1994-01-01
Effective Lagrangians involving nucleons coupled to scalar and vector fields are investigated within the framework of relativistic mean-field theory. The study presents the traditional Walecka model and different kinds of scalar derivative coupling suggested by Zimanyi and Moszkowski. The incompressibility (presented in an analytical form), scalar potential, and vector potential at the saturation point of nuclear matter are compared for these models. The real optical potential for the models are calculated and one of the models fits well the experimental curve from-50 to 400 MeV while also gives a soft equation of state. By varying the coupling constants and keeping the saturation point of nuclear matter approximately fixed, only the Walecka model presents a first order phase transition of finite temperature at zero density. (author)
Novel Thiazole Derivatives of Medicinal Potential: Synthesis and Modeling
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Nour E. A. Abdel-Sattar
2017-01-01
Full Text Available This paper reports on the synthesis of new thiazole derivatives that could be profitably exploited in medical treatment of tumors. Molecular electronic structures have been modeled within density function theory (DFT framework. Reactivity indices obtained from the frontier orbital energies as well as electrostatic potential energy maps are discussed and correlated with the molecular structure. X-ray crystallographic data of one of the new compounds is measured and used to support and verify the theoretical results.
Assigning probability distributions to input parameters of performance assessment models
International Nuclear Information System (INIS)
Mishra, Srikanta
2002-02-01
This study presents an overview of various approaches for assigning probability distributions to input parameters and/or future states of performance assessment models. Specifically,three broad approaches are discussed for developing input distributions: (a) fitting continuous distributions to data, (b) subjective assessment of probabilities, and (c) Bayesian updating of prior knowledge based on new information. The report begins with a summary of the nature of data and distributions, followed by a discussion of several common theoretical parametric models for characterizing distributions. Next, various techniques are presented for fitting continuous distributions to data. These include probability plotting, method of moments, maximum likelihood estimation and nonlinear least squares analysis. The techniques are demonstrated using data from a recent performance assessment study for the Yucca Mountain project. Goodness of fit techniques are also discussed, followed by an overview of how distribution fitting is accomplished in commercial software packages. The issue of subjective assessment of probabilities is dealt with in terms of the maximum entropy distribution selection approach, as well as some common rules for codifying informal expert judgment. Formal expert elicitation protocols are discussed next, and are based primarily on the guidance provided by the US NRC. The Bayesian framework for updating prior distributions (beliefs) when new information becomes available is discussed. A simple numerical approach is presented for facilitating practical applications of the Bayes theorem. Finally, a systematic framework for assigning distributions is presented: (a) for the situation where enough data are available to define an empirical CDF or fit a parametric model to the data, and (b) to deal with the situation where only a limited amount of information is available
Assigning probability distributions to input parameters of performance assessment models
Energy Technology Data Exchange (ETDEWEB)
Mishra, Srikanta [INTERA Inc., Austin, TX (United States)
2002-02-01
This study presents an overview of various approaches for assigning probability distributions to input parameters and/or future states of performance assessment models. Specifically,three broad approaches are discussed for developing input distributions: (a) fitting continuous distributions to data, (b) subjective assessment of probabilities, and (c) Bayesian updating of prior knowledge based on new information. The report begins with a summary of the nature of data and distributions, followed by a discussion of several common theoretical parametric models for characterizing distributions. Next, various techniques are presented for fitting continuous distributions to data. These include probability plotting, method of moments, maximum likelihood estimation and nonlinear least squares analysis. The techniques are demonstrated using data from a recent performance assessment study for the Yucca Mountain project. Goodness of fit techniques are also discussed, followed by an overview of how distribution fitting is accomplished in commercial software packages. The issue of subjective assessment of probabilities is dealt with in terms of the maximum entropy distribution selection approach, as well as some common rules for codifying informal expert judgment. Formal expert elicitation protocols are discussed next, and are based primarily on the guidance provided by the US NRC. The Bayesian framework for updating prior distributions (beliefs) when new information becomes available is discussed. A simple numerical approach is presented for facilitating practical applications of the Bayes theorem. Finally, a systematic framework for assigning distributions is presented: (a) for the situation where enough data are available to define an empirical CDF or fit a parametric model to the data, and (b) to deal with the situation where only a limited amount of information is available.
MATHEMATICAL MODELING OF FLOW PARAMETERS FOR SINGLE WIND TURBINE
Directory of Open Access Journals (Sweden)
2016-01-01
Full Text Available It is known that on the territory of the Russian Federation the construction of several large wind farms is planned. The tasks connected with design and efficiency evaluation of wind farm work are in demand today. One of the possible directions in design is connected with mathematical modeling. The method of large eddy simulation developed within the direction of computational hydrodynamics allows to reproduce unsteady structure of the flow in details and to determine various integrated values. The calculation of work for single wind turbine installation by means of large eddy simulation and Actuator Line Method along the turbine blade is given in this work. For problem definition the numerical method in the form of a box was considered and the adapted unstructured grid was used.The mathematical model included the main equations of continuity and momentum equations for incompressible fluid. The large-scale vortex structures were calculated by means of integration of the filtered equations. The calculation was carried out with Smagorinsky model for determination of subgrid scale turbulent viscosity. The geometrical parametersof wind turbine were set proceeding from open sources in the Internet.All physical values were defined at center of computational cell. The approximation of items in equations was ex- ecuted with the second order of accuracy for time and space. The equations for coupling velocity and pressure were solved by means of iterative algorithm PIMPLE. The total quantity of the calculated physical values on each time step was equal to 18. So, the resources of a high performance cluster were required.As a result of flow calculation in wake for the three-bladed turbine average and instantaneous values of velocity, pressure, subgrid kinetic energy and turbulent viscosity, components of subgrid stress tensor were worked out. The re- ceived results matched the known results of experiments and numerical simulation, testify the opportunity
HMM filtering and parameter estimation of an electricity spot price model
International Nuclear Information System (INIS)
Erlwein, Christina; Benth, Fred Espen; Mamon, Rogemar
2010-01-01
In this paper we develop a model for electricity spot price dynamics. The spot price is assumed to follow an exponential Ornstein-Uhlenbeck (OU) process with an added compound Poisson process. In this way, the model allows for mean-reversion and possible jumps. All parameters are modulated by a hidden Markov chain in discrete time. They are able to switch between different economic regimes representing the interaction of various factors. Through the application of reference probability technique, adaptive filters are derived, which in turn, provide optimal estimates for the state of the Markov chain and related quantities of the observation process. The EM algorithm is applied to find optimal estimates of the model parameters in terms of the recursive filters. We implement this self-calibrating model on a deseasonalised series of daily spot electricity prices from the Nordic exchange Nord Pool. On the basis of one-step ahead forecasts, we found that the model is able to capture the empirical characteristics of Nord Pool spot prices. (author)
Rigorous theoretical derivation of lumped models to transmission line systems
International Nuclear Information System (INIS)
Zhao Jixiang
2012-01-01
By virtue of the negative electric parameter concept, i.e. negative lumped resistance, inductance, conductance and capacitance (N-RLGC), the lumped equivalent models of transmission line systems, including the circuit model, two-port π-network and T-network, are given. We start from the N-segment-ladder-like equivalent networks composed distributed parameters, and achieve the input impedance in the form of a continued fraction. Utilizing the continued fraction theory, the expressions of input impedance are obtained under three kinds of extreme cases, i.e. the load impedances are equal to zero, infinity and characteri