Error propagation of partial least squares for parameters optimization in NIR modeling

Science.gov (United States)

Du, Chenzhao; Dai, Shengyun; Qiao, Yanjiang; Wu, Zhisheng

2018-03-01

A novel methodology is proposed to determine the error propagation of partial least-square (PLS) for parameters optimization in near-infrared (NIR) modeling. The parameters include spectral pretreatment, latent variables and variable selection. In this paper, an open source dataset (corn) and a complicated dataset (Gardenia) were used to establish PLS models under different modeling parameters. And error propagation of modeling parameters for water quantity in corn and geniposide quantity in Gardenia were presented by both type І and type II error. For example, when variable importance in the projection (VIP), interval partial least square (iPLS) and backward interval partial least square (BiPLS) variable selection algorithms were used for geniposide in Gardenia, compared with synergy interval partial least squares (SiPLS), the error weight varied from 5% to 65%, 55% and 15%. The results demonstrated how and what extent the different modeling parameters affect error propagation of PLS for parameters optimization in NIR modeling. The larger the error weight, the worse the model. Finally, our trials finished a powerful process in developing robust PLS models for corn and Gardenia under the optimal modeling parameters. Furthermore, it could provide a significant guidance for the selection of modeling parameters of other multivariate calibration models.

Error propagation of partial least squares for parameters optimization in NIR modeling.

Science.gov (United States)

Du, Chenzhao; Dai, Shengyun; Qiao, Yanjiang; Wu, Zhisheng

2018-03-05

A novel methodology is proposed to determine the error propagation of partial least-square (PLS) for parameters optimization in near-infrared (NIR) modeling. The parameters include spectral pretreatment, latent variables and variable selection. In this paper, an open source dataset (corn) and a complicated dataset (Gardenia) were used to establish PLS models under different modeling parameters. And error propagation of modeling parameters for water quantity in corn and geniposide quantity in Gardenia were presented by both type І and type II error. For example, when variable importance in the projection (VIP), interval partial least square (iPLS) and backward interval partial least square (BiPLS) variable selection algorithms were used for geniposide in Gardenia, compared with synergy interval partial least squares (SiPLS), the error weight varied from 5% to 65%, 55% and 15%. The results demonstrated how and what extent the different modeling parameters affect error propagation of PLS for parameters optimization in NIR modeling. The larger the error weight, the worse the model. Finally, our trials finished a powerful process in developing robust PLS models for corn and Gardenia under the optimal modeling parameters. Furthermore, it could provide a significant guidance for the selection of modeling parameters of other multivariate calibration models. Copyright © 2017. Published by Elsevier B.V.

Visual imagery and the user model applied to fuel handling at EBR-II

Energy Technology Data Exchange (ETDEWEB)

Brown-VanHoozer, S.A.

1995-06-01

The material presented in this paper is based on two studies involving visual display designs and the user`s perspective model of a system. The studies involved a methodology known as Neuro-Linguistic Programming (NLP), and its use in expanding design choices which included the ``comfort parameters`` and ``perspective reality`` of the user`s model of the world. In developing visual displays for the EBR-II fuel handling system, the focus would be to incorporate the comfort parameters that overlap from each of the representation systems: visual, auditory and kinesthetic then incorporate the comfort parameters of the most prominent group of the population, and last, blend in the other two representational system comfort parameters. The focus of this informal study was to use the techniques of meta-modeling and synesthesia to develop a virtual environment that closely resembled the operator`s perspective of the fuel handling system of Argonne`s Experimental Breeder Reactor - II. An informal study was conducted using NLP as the behavioral model in a v reality (VR) setting.

Stark broadening parameters and transition probabilities of persistent lines of Tl II

Science.gov (United States)

de Andrés-García, I.; Colón, C.; Fernández-Martínez, F.

2018-05-01

The presence of singly ionized thallium in the stellar atmosphere of the chemically peculiar star χ Lupi was reported by Leckrone et al. in 1999 by analysis of its stellar spectrum obtained with the Goddard High Resolution Spectrograph (GHRS) on board the Hubble Space Telescope. Atomic data about the spectral line of 1307.50 Å and about the hyperfine components of the spectral lines of 1321.71 Å and 1908.64 Å were taken from different sources and used to analyse the isotopic abundance of thallium II in the star χ Lupi. From their results the authors concluded that the photosphere of the star presents an anomalous isotopic composition of Tl II. A study of the atomic parameters of Tl II and of the broadening by the Stark effect of its spectral lines (and therefore of the possible overlaps of these lines) can help to clarify the conclusions about the spectral abundance of Tl II in different stars. In this paper we present calculated values of the atomic transition probabilities and Stark broadening parameters for 49 spectral lines of Tl II obtained by using the Cowan code including core polarization effects and the Griem semiempirical approach. Theoretical values of radiative lifetimes for 11 levels (eight with experimental values in the bibliography) are calculated and compared with the experimental values in order to test the quality of our results. Theoretical trends of the Stark width and shift parameters versus the temperature for spectral lines of astrophysical interest are displayed. Trends of our calculated Stark width for the isoelectronic sequence Tl II-Pb III-Bi IV are also displayed.

Equilibrium modeling of mono and binary sorption of Cu(II and Zn(II onto chitosan gel beads

Directory of Open Access Journals (Sweden)

Nastaj Józef

2016-12-01

Full Text Available The objective of the work are in-depth experimental studies of Cu(II and Zn(II ion removal on chitosan gel beads from both one- and two-component water solutions at the temperature of 303 K. The optimal process conditions such as: pH value, dose of sorbent and contact time were determined. Based on the optimal process conditions, equilibrium and kinetic studies were carried out. The maximum sorption capacities equaled: 191.25 mg/g and 142.88 mg/g for Cu(II and Zn(II ions respectively, when the sorbent dose was 10 g/L and the pH of a solution was 5.0 for both heavy metal ions. One-component sorption equilibrium data were successfully presented for six of the most useful three-parameter equilibrium models: Langmuir-Freundlich, Redlich-Peterson, Sips, Koble-Corrigan, Hill and Toth. Extended forms of Langmuir-Freundlich, Koble-Corrigan and Sips models were also well fitted to the two-component equilibrium data obtained for different ratios of concentrations of Cu(II and Zn(II ions (1:1, 1:2, 2:1. Experimental sorption data were described by two kinetic models of the pseudo-first and pseudo-second order. Furthermore, an attempt to explain the mechanisms of the divalent metal ion sorption process on chitosan gel beads was undertaken.

Modeling the distribution of Mg II absorbers around galaxies using background galaxies and quasars

Energy Technology Data Exchange (ETDEWEB)

Bordoloi, R.; Lilly, S. J. [Institute for Astronomy, ETH Zürich, Wolfgang-Pauli-Strasse 27, 8093 Zürich (Switzerland); Kacprzak, G. G. [Swinburne University of Technology, Victoria 3122 (Australia); Churchill, C. W., E-mail: rongmonb@phys.ethz.ch [New Mexico State University, Las Cruces, NM 88003 (United States)

2014-04-01

We present joint constraints on the distribution of Mg II absorption around high redshift galaxies obtained by combining two orthogonal probes, the integrated Mg II absorption seen in stacked background galaxy spectra and the distribution of parent galaxies of individual strong Mg II systems as seen in the spectra of background quasars. We present a suite of models that can be used to predict, for different two- and three-dimensional distributions, how the projected Mg II absorption will depend on a galaxy's apparent inclination, the impact parameter b and the azimuthal angle between the projected vector to the line of sight and the projected minor axis. In general, we find that variations in the absorption strength with azimuthal angles provide much stronger constraints on the intrinsic geometry of the Mg II absorption than the dependence on the inclination of the galaxies. In addition to the clear azimuthal dependence in the integrated Mg II absorption that we reported earlier in Bordoloi et al., we show that strong equivalent width Mg II absorbers (W{sub r} (2796) ≥ 0.3 Å) are also asymmetrically distributed in azimuth around their host galaxies: 72% of the absorbers in Kacprzak et al., and 100% of the close-in absorbers within 35 kpc of the center of their host galaxies, are located within 50° of the host galaxy's projected semi minor axis. It is shown that either composite models consisting of a simple bipolar component plus a spherical or disk component, or a single highly softened bipolar distribution, can well represent the azimuthal dependencies observed in both the stacked spectrum and quasar absorption-line data sets within 40 kpc. Simultaneously fitting both data sets, we find that in the composite model the bipolar cone has an opening angle of ∼100° (i.e., confined to within 50° of the disk axis) and contains about two-thirds of the total Mg II absorption in the system. The single softened cone model has an exponential fall off with

A shot parameter specification subsystem for automated control of PBFA II accelerator shots

International Nuclear Information System (INIS)

Spiller, J.L.

1987-01-01

The author reports on the shot parameter specification subsystem (SPSS), an integral part of the automatic control system developed for the Particle Beam Fusion Accelerator II (PBFA II). This system has been designed to fully utilize the accelerator by tailoring shot parameters to the needs of the experimenters. The SPSS is the key to this flexibility. Automatic systems will be required on many pulsed power machines for the fastest turnaround, the highest reliability, and most cost effective operation. These systems will require the flexibility and the ease of use that is part of the SPSS. The author discusses how the PBFA II control system has proved to be an effective modular system, flexible enough to meet the demands of both the fast track construction of PBFA II and the control needs of Hermes III. This system is expected to meet the demands of most future machine changes

Chemical speciation of Pb(II, Cd(II, Hg(II, Co(II, Ni(II, Cu(II and Zn(II binary complexes of l-methionine in 1,2-propanediol-water mixtures

Directory of Open Access Journals (Sweden)

M. Padma Latha

2007-04-01

Full Text Available Chemical speciation of Pb(II, Cd(II, Hg(II, Co(II, Ni(II, Cu(II and Zn(II complexes of L-methionine in 0.0-60 % v/v 1,2-propanediol-water mixtures maintaining an ionic strength of 0.16 M at 303 K has been studied pH metrically. The active forms of ligand are LH2+, LH and L-. The predominant species detected are ML, MLH, ML2, ML2H, ML2H2 and MLOH. Models containing different numbers of species were refined by using the computer program MINIQUAD 75. The best-fit chemical models were arrived at based on statistical parameters. The trend in variation of complex stability constants with change in the dielectric constant of the medium is explained on the basis of electrostatic and non-electrostatic forces.

Nuclear model parameter testing for nuclear data evaluation (Reference Input Parameter Library: Phase II). Summary report of the third research co-ordination meeting

International Nuclear Information System (INIS)

Herman, M.

2002-04-01

This report summarises the results and recommendations of the third Research Co-ordination Meeting on improving and testing the Reference Input Parameter Library: Phase II. A primary aim of the meeting was to review the achievements of the CRP, to assess the testing of the library and to approve the final contents. Actions were approved that will result in completion of the file and a draft report by the end of February 2002. Full release of the library is scheduled for July 2002. (author)

Nuclear model parameter testing for nuclear data evaluation (Reference Input Parameter Library: Phase II). Summary report of the second research co-ordination meeting

International Nuclear Information System (INIS)

Herman, M.

2000-09-01

This report summarizes the results and recommendations of the Second Research Coordination Meeting on Testing and Improvement of the Reference Input Parameter Library: Phase II. A primary aim of this meeting was to review progress in the CRP work, to review results of testing the library, to establish the RIPL-2 format and to decide on the contents of the library. The actions were agreed with an aim to complete the project by the end of 2001. Separate abstracts were prepared for 10 individual papers

Textural features of dynamic contrast-enhanced MRI derived model-free and model-based parameter maps in glioma grading.

Science.gov (United States)

Xie, Tian; Chen, Xiao; Fang, Jingqin; Kang, Houyi; Xue, Wei; Tong, Haipeng; Cao, Peng; Wang, Sumei; Yang, Yizeng; Zhang, Weiguo

2018-04-01

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 textural features, Entropy and 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 textural features of any DCE-MRI parameter maps could discriminate between subtypes of grade II and III gliomas (P 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 2018;47:1099-1111. © 2017 International Society for Magnetic Resonance in Medicine.

Effect of Cu(II), Cd(II) and Zn(II) on Pb(II) biosorption by algae Gelidium-derived materials.

Science.gov (United States)

Vilar, Vítor J P; Botelho, Cidália M S; Boaventura, Rui A R

2008-06-15

Biosorption of Pb(II), Cu(II), Cd(II) and Zn(II) from binary metal solutions onto the algae Gelidium sesquipedale, an algal industrial waste and a waste-based composite material was investigated at pH 5.3, in a batch system. Binary Pb(II)/Cu(II), Pb(II)/Cd(II) and Pb(II)/Zn(II) solutions have been tested. For the same equilibrium concentrations of both metal ions (1 mmol l(-1)), approximately 66, 85 and 86% of the total uptake capacity of the biosorbents is taken by lead ions in the systems Pb(II)/Cu(II), Pb(II)/Cd(II) and Pb(II)/Zn(II), respectively. Two-metal results were fitted to a discrete and a continuous model, showing the inhibition of the primary metal biosorption by the co-cation. The model parameters suggest that Cd(II) and Zn(II) have the same decreasing effect on the Pb(II) uptake capacity. The uptake of Pb(II) was highly sensitive to the presence of Cu(II). From the discrete model it was possible to obtain the Langmuir affinity constant for Pb(II) biosorption. The presence of the co-cations decreases the apparent affinity of Pb(II). The experimental results were successfully fitted by the continuous model, at different pH values, for each biosorbent. The following sequence for the equilibrium affinity constants was found: Pb>Cu>Cd approximately Zn.

Reliability of a new biokinetic model of zirconium in internal dosimetry: part II, parameter sensitivity analysis.

Science.gov (United States)

Li, Wei Bo; Greiter, Matthias; Oeh, Uwe; Hoeschen, Christoph

2011-12-01

The reliability of biokinetic models is essential for the assessment of internal doses and a radiation risk analysis for the public and occupational workers exposed to radionuclides. In the present study, a method for assessing the reliability of biokinetic models by means of uncertainty and sensitivity analysis was developed. In the first part of the paper, the parameter uncertainty was analyzed for two biokinetic models of zirconium (Zr); one was reported by the International Commission on Radiological Protection (ICRP), and one was developed at the Helmholtz Zentrum München-German Research Center for Environmental Health (HMGU). In the second part of the paper, the parameter uncertainties and distributions of the Zr biokinetic models evaluated in Part I are used as the model inputs for identifying the most influential parameters in the models. Furthermore, the most influential model parameter on the integral of the radioactivity of Zr over 50 y in source organs after ingestion was identified. The results of the systemic HMGU Zr model showed that over the first 10 d, the parameters of transfer rates between blood and other soft tissues have the largest influence on the content of Zr in the blood and the daily urinary excretion; however, after day 1,000, the transfer rate from bone to blood becomes dominant. For the retention in bone, the transfer rate from blood to bone surfaces has the most influence out to the endpoint of the simulation; the transfer rate from blood to the upper larger intestine contributes a lot in the later days; i.e., after day 300. The alimentary tract absorption factor (fA) influences mostly the integral of radioactivity of Zr in most source organs after ingestion.

On 4-degree-of-freedom biodynamic models of seated occupants: Lumped-parameter modeling

Science.gov (United States)

Bai, Xian-Xu; Xu, Shi-Xu; Cheng, Wei; Qian, Li-Jun

2017-08-01

It is useful to develop an effective biodynamic model of seated human occupants to help understand the human vibration exposure to transportation vehicle vibrations and to help design and improve the anti-vibration devices and/or test dummies. This study proposed and demonstrated a methodology for systematically identifying the best configuration or structure of a 4-degree-of-freedom (4DOF) human vibration model and for its parameter identification. First, an equivalent simplification expression for the models was made. Second, all of the possible 23 structural configurations of the models were identified. Third, each of them was calibrated using the frequency response functions recommended in a biodynamic standard. An improved version of non-dominated sorting genetic algorithm (NSGA-II) based on Pareto optimization principle was used to determine the model parameters. Finally, a model evaluation criterion proposed in this study was used to assess the models and to identify the best one, which was based on both the goodness of curve fits and comprehensive goodness of the fits. The identified top configurations were better than those reported in the literature. This methodology may also be extended and used to develop the models with other DOFs.

Progress on Chinese evaluated nuclear parameter library (CENPL) (II)

International Nuclear Information System (INIS)

Su Zhongdi; Ge Zhigang; Zhou Chunmei

1993-01-01

CENPL collected, evaluated and compiled nuclear basic constants and model parameters. CENPL-1 contain six sub-libraries, they are: (1) Atomic masses and characteristic constants for nuclear ground states; (2) discrete level schemes and branch ratios of γ decay; (3) level density parameters; (4) giant dipole resonance parameters for γ-ray strength function (5) fission barrier parameter; (6) optical model parameters. Their progresses are introduced

Study of physicochemical parameters for cadmium (II) and mercury (II) phytoremediation using the specie Eichhornia Crassipes (water hyacinth)

International Nuclear Information System (INIS)

Poma Llantoy, Victor R.; Valderrama Negron, Ana C.

2014-01-01

In this work, the studies were performed to measure the sorption capacity of metal ions Cd (II) and Hg (II) using the specie Eichhornia crassipes (water hyacinth). This study includes assays where the nutrient concentration, the pH and the metal ion concentration were optimized. These tests were carried out at room temperature and with aqueous solutions of Cd (II), Hg (II), in which the samples of Eichhornia crassipes were placed. To confirm the removal of these metals, the waste solutions after the treatment with the Water Hyacinth species were treated using the method APHA 3030-e. However, Eichhornia crassipes samples were treated using the EPA 200.3 method. The concentration of Cd (II) was determined by an ICP-OES spectrometer and Hg (II), by an atomic absorption spectrophotometer. The results showed: Optimal dosage 1 mL of A and 0,5 mL of B, optimum pH 5, optimum concentration of Cd (II) and Hg (II) 5 mg/L for each ion. With these parameters, it was started the removal of 5 mg/L of the metal ions contained in 1 L of solution. Being the percentages of sorption 16,56% for Cd (II) and 15,6% for Hg (II) after a period of 7 days. (author)

Assessing models for parameters of the Ångström-Prescott formula in China

DEFF Research Database (Denmark)

Liu, Xiaoying; Xu, Yinlong; Zhong, Xiuli

2012-01-01

against the calibrated ones. Models 1, 6 and 7 showed an advantage in keeping the physical meaning of their modeled parameters due to the small magnitude of and the use of the relation of (a + b) versus other variables as a constraint, respectively. All models tended to perform best in zone II and poorest...... () (models 1–2), altitude (model 7), altitude and (model 3), altitude, and latitude (model 4), altitude and latitude (model 5) and annual average air temperature (model 6). It was found that model 7 performed best, followed by models 6, 1, 3, 2 and 4. The better performance of models 7 and 6 and the fact....... This also suggests that applicability of a Rs model is not proportional to its complexity. The common feature of the better performing models suggests that accurate modeling of parameter a is more important than that of b. Therefore, priority should be given to parameter models having higher accuracy for a...

Higgs potential in the type II seesaw model

International Nuclear Information System (INIS)

Arhrib, A.; Benbrik, R.; Chabab, M.; Rahili, L.; Ramadan, J.; Moultaka, G.; Peyranere, M. C.

2011-01-01

The standard model Higgs sector, extended by one weak gauge triplet of scalar fields with a very small vacuum expectation value, is a very promising setting to account for neutrino masses through the so-called type II seesaw mechanism. In this paper we consider the general renormalizable doublet/triplet Higgs potential of this model. We perform a detailed study of its main dynamical features that depend on five dimensionless couplings and two mass parameters after spontaneous symmetry breaking, and highlight the implications for the Higgs phenomenology. In particular, we determine (i) the complete set of tree-level unitarity constraints on the couplings of the potential and (ii) the exact tree-level boundedness from below constraints on these couplings, valid for all directions. When combined, these constraints delineate precisely the theoretically allowed parameter space domain within our perturbative approximation. Among the seven physical Higgs states of this model, the mass of the lighter (heavier) CP even state h 0 (H 0 ) will always satisfy a theoretical upper (lower) bound that is reached for a critical value μ c of μ (the mass parameter controlling triple couplings among the doublet/triplet Higgses). Saturating the unitarity bounds, we find an upper bound m h 0 or approx. μ c and μ c . In the first regime the Higgs sector is typically very heavy, and only h 0 that becomes SM-like could be accessible to the LHC. In contrast, in the second regime, somewhat overlooked in the literature, most of the Higgs sector is light. In particular, the heaviest state H 0 becomes SM-like, the lighter states being the CP odd Higgs, the (doubly) charged Higgses, and a decoupled h 0 , possibly leading to a distinctive phenomenology at the colliders.

Modeling Fe II Emission and Revised Fe II (UV) Empirical Templates for the Seyfert 1 Galaxy I Zw 1

Science.gov (United States)

Bruhweiler, F.; Verner, E.

2008-03-01

We use the narrow-lined broad-line region (BLR) of the Seyfert 1 galaxy, I Zw 1, as a laboratory for modeling the ultraviolet (UV) Fe II 2100-3050 Å emission complex. We calculate a grid of Fe II emission spectra representative of BLR clouds and compare them with the observed I Zw 1 spectrum. Our predicted spectrum for log [nH/(cm -3) ] = 11.0, log [ΦH/(cm -2 s-1) ] = 20.5, and ξ/(1 km s-1) = 20, using Cloudy and an 830 level model atom for Fe II with energies up to 14.06 eV, gives a better fit to the UV Fe II emission than models with fewer levels. Our analysis indicates (1) the observed UV Fe II emission must be corrected for an underlying Fe II pseudocontinuum; (2) Fe II emission peaks can be misidentified as that of other ions in active galactic nuclei (AGNs) with narrow-lined BLRs possibly affecting deduced physical parameters; (3) the shape of 4200-4700 Å Fe II emission in I Zw 1 and other AGNs is a relative indicator of narrow-line region (NLR) and BLR Fe II emission; (4) predicted ratios of Lyα, C III], and Fe II emission relative to Mg II λ2800 agree with extinction corrected observed I Zw 1 fluxes, except for C IV λ1549 (5) the sensitivity of Fe II emission strength to microturbulence ξ casts doubt on existing relative Fe/Mg abundances derived from Fe II (UV)/Mg II flux ratios. Our calculated Fe II emission spectra, suitable for BLRs in AGNs, are available at http://iacs.cua.edu/people/verner/FeII. Based on observations made with the NASA/ESA Hubble Space Telescope, obtained at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 05-26555.

Biokinetic modelling development and analysis of arsenic dissolution into the gastrointestinal tract using SAAM II

Science.gov (United States)

Perama, Yasmin Mohd Idris; Siong, Khoo Kok

2018-04-01

A mathematical model comprising 8 compartments were designed to describe the kinetic dissolution of arsenic (As) from water leach purification (WLP) waste samples ingested into the gastrointestinal system. A totally reengineered software system named Simulation, Analysis and Modelling II (SAAM II) was employed to aid in the experimental design and data analysis. As a powerful tool that creates, simulate and analyze data accurately and rapidly, SAAM II computationally creates a system of ordinary differential equations according to the specified compartmental model structure and simulates the solutions based upon the parameter and model inputs provided. The experimental design of in vitro DIN approach was applied to create an artificial gastric and gastrointestinal fluids. These synthetic fluids assay were produced to determine the concentrations of As ingested into the gastrointestinal tract. The model outputs were created based upon the experimental inputs and the recommended fractional transfer rates parameter. As a result, the measured and predicted As concentrations in gastric fluids were much similar against the time of study. In contrast, the concentrations of As in the gastrointestinal fluids were only similar during the first hour and eventually started decreasing until the fifth hours of study between the measured and predicted values. This is due to the loss of As through the fractional transfer rates of q2 compartment to corresponding compartments of q3 and q5 which are involved with excretion and distribution to the whole body, respectively. The model outputs obtained after best fit to the data were influenced significantly by the fractional transfer rates between each compartment. Therefore, a series of compartmental model created with the association of fractional transfer rates parameter with the aid of SAAM II provides better estimation that simulate the kinetic behavior of As ingested into the gastrointestinal system.

Metal-poor dwarf galaxies in the SIGRID galaxy sample. II. The electron temperature-abundance calibration and the parameters that affect it

Energy Technology Data Exchange (ETDEWEB)

Nicholls, David C.; Dopita, Michael A.; Sutherland, Ralph S.; Jerjen, Helmut; Kewley, Lisa J., E-mail: David.Nicholls@anu.edu.au [Research School of Astronomy and Astrophysics, Australian National University, Cotter Rd., Weston ACT 2611 (Australia)

2014-07-20

In this paper, we use the Mappings photoionization code to explore the physical parameters that impact on the measurement of electron temperature and abundance in H II regions. In our previous paper, we presented observations and measurements of physical properties from the spectra of 17 H II regions in 14 isolated dwarf irregular galaxies from the SIGRID sample. Here, we analyze these observations further, together with three additional published data sets. We explore the effects of optical thickness, electron density, ionization parameter, ionization source, and non-equilibrium effects on the relation between electron temperature and metallicity. We present a standard model that fits the observed data remarkably well at metallicities between one-tenth and 1 solar. We investigate the effects of optically thin H II regions, and show that they can have a considerable effect on the measured electron temperature, and that there is evidence that some of the observed objects are optically thin. We look at the role of the ionization parameter and find that lower ionization parameter values give better fits at higher oxygen abundance. We show that higher pressures combined with low optical depth, and also κ electron energy distributions at low κ values, can generate the apparent high electron temperatures in low-metallicity H II regions, and that the former provides the better fit to observations. We examine the effects of these parameters on the strong line diagnostic methods. We extend this to three-dimensional diagnostic grids to confirm how well the observations are described by the grids.

Computational analysis of neutronic parameters for TRIGA Mark-II research reactor using evaluated nuclear data libraries

International Nuclear Information System (INIS)

Uddin, M.N.; Sarker, M.M.; Khan, M.J.H.; Islam, S.M.A.

2010-01-01

The aim of this study is to analyze the neutronic parameters of TRIGA Mark-II research reactor using the chain of NJOY-WIMS-CITATION computer codes based on evaluated nuclear data libraries CENDL-2.2 and JEFF-3.1.1. The nuclear data processing code NJOY99.0 has been employed to generate the 69 group WIMS library for the isotopes of TRIGA core. The cell code WIMSD-5B was used to generate the cross sections in CITATION format and then 3-dimensional diffusion code CITTATION was used to calculate the neutronic parameters of the TRIGA Mark-II research reactor. All the analyses were performed using the 7-group macroscopic cross section library. The CITATION test-runs using different cross section sets based on different models applied in WIMS calculations have shown a strong influence of those models on the final integral parameters. Some of the cells were specially treated with PRIZE options available in WIMSD-5B to take into account the fine structure of the flux gradient in the fuel-reflector interface region. It was observed that two basic parameters, the effective multiplication factor, k eff and the thermal neutron flux, were in good agreement among the calculated results with each other as well as the measured values. The maximum power densities at the hot spot were 1.0446E02 W/cc and 1.0426E02 W/cc for the libraries CENDL-2.2 and JEFF-3.1.1 respectively. The calculated total peaking factors 5.793 and 5.745 were compared to the original SAR value of 5.6325 as well as MCNP result. Consequently, this analysis will be helpful to enhance the neutronic calculations and also be used for the further thermal-hydraulics study of the TRIGA core.

APPLYING TEACHING-LEARNING TO ARTIFICIAL BEE COLONY FOR PARAMETER OPTIMIZATION OF SOFTWARE EFFORT ESTIMATION MODEL

Directory of Open Access Journals (Sweden)

THANH TUNG KHUAT

2017-05-01

Full Text Available Artificial Bee Colony inspired by the foraging behaviour of honey bees is a novel meta-heuristic optimization algorithm in the community of swarm intelligence algorithms. Nevertheless, it is still insufficient in the speed of convergence and the quality of solutions. This paper proposes an approach in order to tackle these downsides by combining the positive aspects of TeachingLearning based optimization and Artificial Bee Colony. The performance of the proposed method is assessed on the software effort estimation problem, which is the complex and important issue in the project management. Software developers often carry out the software estimation in the early stages of the software development life cycle to derive the required cost and schedule for a project. There are a large number of methods for effort estimation in which COCOMO II is one of the most widely used models. However, this model has some restricts because its parameters have not been optimized yet. In this work, therefore, we will present the approach to overcome this limitation of COCOMO II model. The experiments have been conducted on NASA software project dataset and the obtained results indicated that the improvement of parameters provided better estimation capabilities compared to the original COCOMO II model.

Computational analysis of neutronic parameters of CENM TRIGA Mark II research reactor

International Nuclear Information System (INIS)

El Younoussi, C.; El Bakkari, B.; Boulaich, Y.; Riyach, D.; Otmani, S.; Marrhich, I.; Badri, H.; Htet, A.; Nacir, B.; El Bardouni, T.; Boukhal, H.; Zoubair, M.; Ossama, M.; Chakir, E.

2010-01-01

The CENM TRIGA MARK II reactor is part of the National Center for Energy, Sciences and Nuclear Techniques (CNESTEN). It's a standard design 2MW, natural-convection-cooled reactor with a graphite reflector containing 4 beam tubes and a thermal column. The reactor has several applications in different fields as industry, agriculture, medicine, training and education. In the present work a computational study has been carried out in the framework of neutronic parameters studies of the reactor. A detailed MCNP model that include all elements of the core and surrounding structures has been developed to calculate different parameters of the core (The effective multiplication factor, reactivity experiments comprising control rods worth, excess reactivity and shutdown margin). Further calculations have been carried out to calculate the neutron flux profiles at different locations of the reactor core. The cross sections used are processed from the library provided with MCNP5 and based on the ENDF/B-VII with continuous dependence in energy and special treatment of thermal neutrons in lightweight materials. (author)

Full-range stress–strain behaviour of contemporary pipeline steels: Part II. Estimation of model parameters

International Nuclear Information System (INIS)

Hertelé, Stijn; De Waele, Wim; Denys, Rudi; Verstraete, Matthias

2012-01-01

Contemporary pipeline steels with a yield-to-tensile ratio above 0.80 often show two-stages of strain hardening, which cannot be simultaneously described by the standardized Ramberg–Osgood model. A companion paper (Part I) showed that the recently developed UGent model provides more accurate descriptions than the Ramberg–Osgood model, as it succeeds in describing both strain hardening stages. However, it may be challenging to obtain an optimal model fit in absence of full stress–strain data. This paper discusses on how to find suited parameter values for the UGent model, given a set of measurable tensile test characteristics. The proposed methodology shows good results for an extensive set of investigated experimental stress–strain curves. Next to some common tensile test characteristics, the 1.0% proof stress is needed. The authors therefore encourage the acquisition of this stress during tensile tests. - Highlights: ► An analytical procedure estimates UGent model parameters. ► The procedure requires a set of tensile test characteristics. ► The UGent model performs better than the Ramberg–Osgood model. ► Apart from common characteristics, the 1.0% proof stress is required. ► The authors encourage the acquisition of this 1.0% proof stress.

Preparation, spectroscopic, thermal, antihepatotoxicity, hematological parameters and liver antioxidant capacity characterizations of Cd(II), Hg(II), and Pb(II) mononuclear complexes of paracetamol anti-inflammatory drug

Science.gov (United States)

El-Megharbel, Samy M.; Hamza, Reham Z.; Refat, Moamen S.

2014-10-01

Keeping in view that some metal complexes are found to be more potent than their parent drugs, therefore, our present paper aimed to synthesized Cd(II), Hg(II) and Pb(II) complexes of paracetamol (Para) anti-inflammatory drug. Paracetamol complexes with general formula [M(Para)2(H2O)2]·nH2O have been synthesized and characterized on the basis of elemental analysis, conductivity, IR and thermal (TG/DTG), 1H NMR, electronic spectral studies. The conductivity data of these complexes have non-electrolytic nature. Comparative antimicrobial (bacteria and fungi) behaviors and molecular weights of paracetamol with their complexes have been studied. In vivo the antihepatotoxicity effect and some liver function parameters levels (serum total protein, ALT, AST, and LDH) were measured. Hematological parameters and liver antioxidant capacities of both Para and their complexes were performed. The Cd2+ + Para complex was recorded amelioration of antioxidant capacities in liver homogenates compared to other Para complexes treated groups.

Neutrinoless double beta decay in type I+II seesaw models

Energy Technology Data Exchange (ETDEWEB)

Borah, Debasish [Department of Physics, Tezpur University,Tezpur-784028 (India); Dasgupta, Arnab [Institute of Physics, Sachivalaya Marg,Bhubaneshwar-751005 (India)

2015-11-30

We study neutrinoless double beta decay in left-right symmetric extension of the standard model with type I and type II seesaw origin of neutrino masses. Due to the enhanced gauge symmetry as well as extended scalar sector, there are several new physics sources of neutrinoless double beta decay in this model. Ignoring the left-right gauge boson mixing and heavy-light neutrino mixing, we first compute the contributions to neutrinoless double beta decay for type I and type II dominant seesaw separately and compare with the standard light neutrino contributions. We then repeat the exercise by considering the presence of both type I and type II seesaw, having non-negligible contributions to light neutrino masses and show the difference in results from individual seesaw cases. Assuming the new gauge bosons and scalars to be around a TeV, we constrain different parameters of the model including both heavy and light neutrino masses from the requirement of keeping the new physics contribution to neutrinoless double beta decay amplitude below the upper limit set by the GERDA experiment and also satisfying bounds from lepton flavor violation, cosmology and colliders.

IMITATOR II: A Tool for Solving the Good Parameters Problem in Timed Automata

Directory of Open Access Journals (Sweden)

Étienne André

2010-10-01

Full Text Available We present here Imitator II, a new version of Imitator, a tool implementing the "inverse method" for parametric timed automata: given a reference valuation of the parameters, it synthesizes a constraint such that, for any valuation satisfying this constraint, the system behaves the same as under the reference valuation in terms of traces, i.e., alternating sequences of locations and actions. Imitator II also implements the "behavioral cartography algorithm", allowing us to solve the following good parameters problem: find a set of valuations within a given bounded parametric domain for which the system behaves well. We present new features and optimizations of the tool, and give results of applications to various examples of asynchronous circuits and communication protocols.

Low-dose cone-beam CT via raw counts domain low-signal correction schemes: Performance assessment and task-based parameter optimization (Part II. Task-based parameter optimization).

Science.gov (United States)

Gomez-Cardona, Daniel; Hayes, John W; Zhang, Ran; Li, Ke; Cruz-Bastida, Juan Pablo; Chen, Guang-Hong

2018-05-01

Different low-signal correction (LSC) methods have been shown to efficiently reduce noise streaks and noise level in CT to provide acceptable images at low-radiation dose levels. These methods usually result in CT images with highly shift-variant and anisotropic spatial resolution and noise, which makes the parameter optimization process highly nontrivial. The purpose of this work was to develop a local task-based parameter optimization framework for LSC methods. Two well-known LSC methods, the adaptive trimmed mean (ATM) filter and the anisotropic diffusion (AD) filter, were used as examples to demonstrate how to use the task-based framework to optimize filter parameter selection. Two parameters, denoted by the set P, for each LSC method were included in the optimization problem. For the ATM filter, these parameters are the low- and high-signal threshold levels p l and p h ; for the AD filter, the parameters are the exponents δ and γ in the brightness gradient function. The detectability index d' under the non-prewhitening (NPW) mathematical observer model was selected as the metric for parameter optimization. The optimization problem was formulated as an unconstrained optimization problem that consisted of maximizing an objective function d'(P), where i and j correspond to the i-th imaging task and j-th spatial location, respectively. Since there is no explicit mathematical function to describe the dependence of d' on the set of parameters P for each LSC method, the optimization problem was solved via an experimentally measured d' map over a densely sampled parameter space. In this work, three high-contrast-high-frequency discrimination imaging tasks were defined to explore the parameter space of each of the LSC methods: a vertical bar pattern (task I), a horizontal bar pattern (task II), and a multidirectional feature (task III). Two spatial locations were considered for the analysis, a posterior region-of-interest (ROI) located within the noise streaks region

Avalanche weak layer shear fracture parameters from the cohesive crack model

Science.gov (United States)

McClung, David

2014-05-01

Dry slab avalanches release by mode II shear fracture within thin weak layers under cohesive snow slabs. The important fracture parameters include: nominal shear strength, mode II fracture toughness and mode II fracture energy. Alpine snow is not an elastic material unless the rate of deformation is very high. For natural avalanche release, it would not be possible that the fracture parameters can be considered as from classical fracture mechanics from an elastic framework. The strong rate dependence of alpine snow implies that it is a quasi-brittle material (Bažant et al., 2003) with an important size effect on nominal shear strength. Further, the rate of deformation for release of an avalanche is unknown, so it is not possible to calculate the fracture parameters for avalanche release from any model which requires the effective elastic modulus. The cohesive crack model does not require the modulus to be known to estimate the fracture energy. In this paper, the cohesive crack model was used to calculate the mode II fracture energy as a function of a brittleness number and nominal shear strength values calculated from slab avalanche fracture line data (60 with natural triggers; 191 with a mix of triggers). The brittleness number models the ratio of the approximate peak value of shear strength to nominal shear strength. A high brittleness number (> 10) represents large size relative to fracture process zone (FPZ) size and the implications of LEFM (Linear Elastic Fracture Mechanics). A low brittleness number (e.g. 0.1) represents small sample size and primarily plastic response. An intermediate value (e.g. 5) implies non-linear fracture mechanics with intermediate relative size. The calculations also implied effective values for the modulus and the critical shear fracture toughness as functions of the brittleness number. The results showed that the effective mode II fracture energy may vary by two orders of magnitude for alpine snow with median values ranging from 0

Equilibrium and kinetic modelling of Cd(II) biosorption by algae Gelidium and agar extraction algal waste.

Science.gov (United States)

Vilar, Vítor J P; Botelho, Cidália M S; Boaventura, Rui A R

2006-01-01

In this study an industrial algal waste from agar extraction has been used as an inexpensive and effective biosorbent for cadmium (II) removal from aqueous solutions. This biosorbent was compared with the algae Gelidium itself, which is the raw material for agar extraction. Equilibrium data follow both Langmuir and Redlich-Peterson models. The parameters of Langmuir equilibrium model are q(max)=18.0 mgg(-1), b=0.19 mgl(-1) and q(max)=9.7 mgg(-1), b=0.16 mgl(-1), respectively for Gelidium and the algal waste. Kinetic experiments were conducted at initial Cd(II) concentrations in the range 6-91 mgl(-1). Data were fitted to pseudo-first- and second-order Lagergren models. For an initial Cd(II) concentration of 91 mgl(-1) the parameters of the pseudo-first-order Lagergren model are k(1,ads)=0.17 and 0.87 min(-1); q(eq)=16.3 and 8.7 mgg(-1), respectively, for Gelidium and algal waste. Kinetic constants vary with the initial metal concentration. The adsorptive behaviour of biosorbent particles was modelled using a batch reactor mass transfer kinetic model. The model successfully predicts Cd(II) concentration profiles and provides significant insights on the biosorbents performance. The homogeneous diffusivity, D(h), is in the range 0.5-2.2 x10(-8) and 2.1-10.4 x10(-8)cm(2)s(-1), respectively, for Gelidium and algal waste.

Assessing parameter importance of the Common Land Model based on qualitative and quantitative sensitivity analysis

Directory of Open Access Journals (Sweden)

J. Li

2013-08-01

Full Text Available Proper specification of model parameters is critical to the performance of land surface models (LSMs. Due to high dimensionality and parameter interaction, estimating parameters of an LSM is a challenging task. Sensitivity analysis (SA is a tool that can screen out the most influential parameters on model outputs. In this study, we conducted parameter screening for six output fluxes for the Common Land Model: sensible heat, latent heat, upward longwave radiation, net radiation, soil temperature and soil moisture. A total of 40 adjustable parameters were considered. Five qualitative SA methods, including local, sum-of-trees, multivariate adaptive regression splines, delta test and Morris methods, were compared. The proper sampling design and sufficient sample size necessary to effectively screen out the sensitive parameters were examined. We found that there are 2–8 sensitive parameters, depending on the output type, and about 400 samples are adequate to reliably identify the most sensitive parameters. We also employed a revised Sobol' sensitivity method to quantify the importance of all parameters. The total effects of the parameters were used to assess the contribution of each parameter to the total variances of the model outputs. The results confirmed that global SA methods can generally identify the most sensitive parameters effectively, while local SA methods result in type I errors (i.e., sensitive parameters labeled as insensitive or type II errors (i.e., insensitive parameters labeled as sensitive. Finally, we evaluated and confirmed the screening results for their consistency with the physical interpretation of the model parameters.

Model parameter updating using Bayesian networks

International Nuclear Information System (INIS)

Treml, C.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.

Search for non-standard model signatures in the WZ/ZZ final state at CDF Run II

International Nuclear Information System (INIS)

Norman, Matthew

2009-01-01

This thesis discusses a search for non-Standard Model physics in heavy diboson production in the dilepton-dijet final state, using 1.9 fb -1 of data from the CDF Run II detector. New limits are set on the anomalous coupling parameters for ZZ and WZ production based on limiting the production cross-section at high (cflx s). Additionally limits are set on the direct decay of new physics to ZZ andWZ diboson pairs. The nature and parameters of the CDF Run II detector are discussed, as are the influences that it has on the methods of our analysis.

Search for non-standard model signatures in the WZ/ZZ final state at CDF run II

Energy Technology Data Exchange (ETDEWEB)

Norman, Matthew [Univ. of California, San Diego, CA (United States)

2009-01-01

This thesis discusses a search for non-Standard Model physics in heavy diboson production in the dilepton-dijet final state, using 1.9 fb ^-1 of data from the CDF Run II detector. New limits are set on the anomalous coupling parameters for ZZ and WZ production based on limiting the production cross-section at high š. Additionally limits are set on the direct decay of new physics to ZZ andWZ diboson pairs. The nature and parameters of the CDF Run II detector are discussed, as are the influences that it has on the methods of our analysis.

Risk considerations for a long-term open-state of the radioactive waste storage facility Schacht Asse II. Variation of the parameter sets for radio-ecological modeling using the Monte Carlo method

International Nuclear Information System (INIS)

Kueppers, Christian; Ustohalova, Veronika

2013-01-01

The risk considerations for a long-term open-state of the radioactive waste storage facility Schacht Asse II include the following issues: description of radio-ecological models for the radionuclide transport in the covering rock formations and determination of the radiation exposure, parameters of the radio-ecological and their variability, Monte-Carlo method application. The results of the modeling calculations include the group short-living radionuclides, long-living radionuclides, radionuclides in the frame of decay chains and sensitivity analyses with respect to the correlation of input data and results.

Variation of Supergranule Parameters with Solar Cycles: Results from Century-long Kodaikanal Digitized Ca ii K Data

Energy Technology Data Exchange (ETDEWEB)

Chatterjee, Subhamoy; Mandal, Sudip; Banerjee, Dipankar, E-mail: dipu@iiap.res.in [Indian Institute of Astrophysics, Koramangala, Bangalore 560034 (India)

2017-06-01

The Ca ii K spectroheliograms spanning over a century (1907–2007) from Kodaikanal Solar Observatory, India, have recently been digitized and calibrated. Applying a fully automated algorithm (which includes contrast enhancement and the “Watershed method”) to these data, we have identified the supergranules and calculated the associated parameters, such as scale, circularity, and fractal dimension. We have segregated the quiet and active regions and obtained the supergranule parameters separately for these two domains. In this way, we have isolated the effect of large-scale and small-scale magnetic fields on these structures and find a significantly different behavior of the supergranule parameters over solar cycles. These differences indicate intrinsic changes in the physical mechanism behind the generation and evolution of supergranules in the presence of small-scale and large-scale magnetic fields. This also highlights the need for further studies using solar dynamo theory along with magneto-convection models.

Nonlinear Parameter-Varying AeroServoElastic Reduced Order Model for Aerostructural Sensing and Control, Phase II

Data.gov (United States)

National Aeronautics and Space Administration — The overall goal of the project is to develop reliable reduced order modeling technologies to automatically generate parameter-varying (PV), aeroservoelastic (ASE)...

PARAMETER ESTIMATION IN BREAD BAKING MODEL

Directory of Open Access Journals (Sweden)

Hadiyanto Hadiyanto

2012-05-01

Full Text Available Bread product quality is highly dependent to the baking process. A model for the development of product quality, which was obtained by using quantitative and qualitative relationships, was calibrated by experiments at a fixed baking temperature of 200°C alone and in combination with 100 W microwave powers. The model parameters were estimated in a stepwise procedure i.e. first, heat and mass transfer related parameters, then the parameters related to product transformations and finally product quality parameters. There was a fair agreement between the calibrated model results and the experimental data. The results showed that the applied simple qualitative relationships for quality performed above expectation. Furthermore, it was confirmed that the microwave input is most meaningful for the internal product properties and not for the surface properties as crispness and color. The model with adjusted parameters was applied in a quality driven food process design procedure to derive a dynamic operation pattern, which was subsequently tested experimentally to calibrate the model. Despite the limited calibration with fixed operation settings, the model predicted well on the behavior under dynamic convective operation and on combined convective and microwave operation. It was expected that the suitability between model and baking system could be improved further by performing calibration experiments at higher temperature and various microwave power levels.  Abstrak  PERKIRAAN PARAMETER DALAM MODEL UNTUK PROSES BAKING ROTI. Kualitas produk roti sangat tergantung pada proses baking yang digunakan. Suatu model yang telah dikembangkan dengan metode kualitatif dan kuantitaif telah dikalibrasi dengan percobaan pada temperatur 200oC dan dengan kombinasi dengan mikrowave pada 100 Watt. Parameter-parameter model diestimasi dengan prosedur bertahap yaitu pertama, parameter pada model perpindahan masa dan panas, parameter pada model transformasi, dan

Optimisation of NMR dynamic models II. A new methodology for the dual optimisation of the model-free parameters and the Brownian rotational diffusion tensor

International Nuclear Information System (INIS)

D'Auvergne, Edward J.; Gooley, Paul R.

2008-01-01

Finding the dynamics of an entire macromolecule is a complex problem as the model-free parameter values are intricately linked to the Brownian rotational diffusion of the molecule, mathematically through the autocorrelation function of the motion and statistically through model selection. The solution to this problem was formulated using set theory as an element of the universal set U-the union of all model-free spaces (d'Auvergne EJ and Gooley PR (2007) Mol BioSyst 3(7), 483-494). The current procedure commonly used to find the universal solution is to initially estimate the diffusion tensor parameters, to optimise the model-free parameters of numerous models, and then to choose the best model via model selection. The global model is then optimised and the procedure repeated until convergence. In this paper a new methodology is presented which takes a different approach to this diffusion seeded model-free paradigm. Rather than starting with the diffusion tensor this iterative protocol begins by optimising the model-free parameters in the absence of any global model parameters, selecting between all the model-free models, and finally optimising the diffusion tensor. The new model-free optimisation protocol will be validated using synthetic data from Schurr JM et al. (1994) J Magn Reson B 105(3), 211-224 and the relaxation data of the bacteriorhodopsin (1-36)BR fragment from Orekhov VY (1999) J Biomol NMR 14(4), 345-356. To demonstrate the importance of this new procedure the NMR relaxation data of the Olfactory Marker Protein (OMP) of Gitti R et al. (2005) Biochem 44(28), 9673-9679 is reanalysed. The result is that the dynamics for certain secondary structural elements is very different from those originally reported

Adsorption of Pb(II), Cu(II), Cd(II), Zn(II), Ni(II), Fe(II), and As(V) on bacterially produced metal sulfides.

Science.gov (United States)

Jong, Tony; Parry, David L

2004-07-01

The adsorption of Pb(II), Cu(II), Cd(II), Zn(II), Ni(II), Fe(II) and As(V) onto bacterially produced metal sulfide (BPMS) material was investigated using a batch equilibrium method. It was found that the sulfide material had adsorptive properties comparable with those of other adsorbents with respect to the specific uptake of a range of metals and, the levels to which dissolved metal concentrations in solution can be reduced. The percentage of adsorption increased with increasing pH and adsorbent dose, but decreased with increasing initial dissolved metal concentration. The pH of the solution was the most important parameter controlling adsorption of Cd(II), Cu(II), Fe(II), Ni(II), Pb(II), Zn(II), and As(V) by BPMS. The adsorption data were successfully modeled using the Langmuir adsorption isotherm. Desorption experiments showed that the reversibility of adsorption was low, suggesting high-affinity adsorption governed by chemisorption. The mechanism of adsorption for the divalent metals was thought to be the formation of strong, inner-sphere complexes involving surface hydroxyl groups. However, the mechanism for the adsorption of As(V) by BPMS appears to be distinct from that of surface hydroxyl exchange. These results have important implications to the management of metal sulfide sludge produced by bacterial sulfate reduction.

The Adsorption of Cd(II) on Manganese Oxide Investigated by Batch and Modeling Techniques.

Science.gov (United States)

Huang, Xiaoming; Chen, Tianhu; Zou, Xuehua; Zhu, Mulan; Chen, Dong; Pan, Min

2017-09-28

Manganese (Mn) oxide is a ubiquitous metal oxide in sub-environments. The adsorption of Cd(II) on Mn oxide as function of adsorption time, pH, ionic strength, temperature, and initial Cd(II) concentration was investigated by batch techniques. The adsorption kinetics showed that the adsorption of Cd(II) on Mn oxide can be satisfactorily simulated by pseudo-second-order kinetic model with high correlation coefficients (R² > 0.999). The adsorption of Cd(II) on Mn oxide significantly decreased with increasing ionic strength at pH adsorption was independent of ionic strength at pH > 6.0, which indicated that outer-sphere and inner-sphere surface complexation dominated the adsorption of Cd(II) on Mn oxide at pH 6.0, respectively. The maximum adsorption capacity of Mn oxide for Cd(II) calculated from Langmuir model was 104.17 mg/g at pH 6.0 and 298 K. The thermodynamic parameters showed that the adsorption of Cd(II) on Mn oxide was an endothermic and spontaneous process. According to the results of surface complexation modeling, the adsorption of Cd(II) on Mn oxide can be satisfactorily simulated by ion exchange sites (X₂Cd) at low pH and inner-sphere surface complexation sites (SOCd⁺ and (SO)₂CdOH - species) at high pH conditions. The finding presented herein plays an important role in understanding the fate and transport of heavy metals at the water-mineral interface.

The Adsorption of Cd(II) on Manganese Oxide Investigated by Batch and Modeling Techniques

Science.gov (United States)

Huang, Xiaoming; Chen, Tianhu; Zou, Xuehua; Zhu, Mulan; Chen, Dong

2017-01-01

Manganese (Mn) oxide is a ubiquitous metal oxide in sub-environments. The adsorption of Cd(II) on Mn oxide as function of adsorption time, pH, ionic strength, temperature, and initial Cd(II) concentration was investigated by batch techniques. The adsorption kinetics showed that the adsorption of Cd(II) on Mn oxide can be satisfactorily simulated by pseudo-second-order kinetic model with high correlation coefficients (R2 > 0.999). The adsorption of Cd(II) on Mn oxide significantly decreased with increasing ionic strength at pH adsorption was independent of ionic strength at pH > 6.0, which indicated that outer-sphere and inner-sphere surface complexation dominated the adsorption of Cd(II) on Mn oxide at pH 6.0, respectively. The maximum adsorption capacity of Mn oxide for Cd(II) calculated from Langmuir model was 104.17 mg/g at pH 6.0 and 298 K. The thermodynamic parameters showed that the adsorption of Cd(II) on Mn oxide was an endothermic and spontaneous process. According to the results of surface complexation modeling, the adsorption of Cd(II) on Mn oxide can be satisfactorily simulated by ion exchange sites (X2Cd) at low pH and inner-sphere surface complexation sites (SOCd+ and (SO)2CdOH− species) at high pH conditions. The finding presented herein plays an important role in understanding the fate and transport of heavy metals at the water–mineral interface. PMID:28956849

Multi-objective optimization of combustion, performance and emission parameters in a jatropha biodiesel engine using Non-dominated sorting genetic algorithm-II

Science.gov (United States)

Dhingra, Sunil; Bhushan, Gian; Dubey, Kashyap Kumar

2014-03-01

The present work studies and identifies the different variables that affect the output parameters involved in a single cylinder direct injection compression ignition (CI) engine using jatropha biodiesel. Response surface methodology based on Central composite design (CCD) is used to design the experiments. Mathematical models are developed for combustion parameters (Brake specific fuel consumption (BSFC) and peak cylinder pressure (Pmax)), performance parameter brake thermal efficiency (BTE) and emission parameters (CO, NO x , unburnt HC and smoke) using regression techniques. These regression equations are further utilized for simultaneous optimization of combustion (BSFC, Pmax), performance (BTE) and emission (CO, NO x , HC, smoke) parameters. As the objective is to maximize BTE and minimize BSFC, Pmax, CO, NO x , HC, smoke, a multiobjective optimization problem is formulated. Nondominated sorting genetic algorithm-II is used in predicting the Pareto optimal sets of solution. Experiments are performed at suitable optimal solutions for predicting the combustion, performance and emission parameters to check the adequacy of the proposed model. The Pareto optimal sets of solution can be used as guidelines for the end users to select optimal combination of engine output and emission parameters depending upon their own requirements.

Selection of stirling engine parameter and modes of joint operation with the Topaz II

International Nuclear Information System (INIS)

Kirillov, E.Y.; Ogloblin, B.G.; Shalaev, A.I.

1996-01-01

In addition to a high-temperature thermionic conversion cycle, application of a low-temperature machine cycle, such as the Stirling engine, is being considered. To select the optimum mode for joint operation of the Topaz II system and Stirling engine, output electric parameters are obtained as a function of thermal power released in the TFE fuel cores. The hydraulic diagram used for joint operation of the Topaz II and the Stirling engine is considered. Requirements to hydraulic characteristics of the Stirling engine heat exchanges are formulated. Scope of necessary modifications to mount the Stirling Engine on the Topaz II is estimated. copyright 1996 American Institute of Physics

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.

Predictive Modeling of a Paradigm Mechanical Cooling Tower Model: II. Optimal Best-Estimate Results with Reduced Predicted Uncertainties

Directory of Open Access Journals (Sweden)

Ruixian Fang

2016-09-01

Full Text Available This work uses the adjoint sensitivity model of the counter-flow cooling tower derived in the accompanying PART I to obtain the expressions and relative numerical rankings of the sensitivities, to all model parameters, of the following model responses: (i outlet air temperature; (ii outlet water temperature; (iii outlet water mass flow rate; and (iv air outlet relative humidity. These sensitivities are subsequently used within the “predictive modeling for coupled multi-physics systems” (PM_CMPS methodology to obtain explicit formulas for the predicted optimal nominal values for the model responses and parameters, along with reduced predicted standard deviations for the predicted model parameters and responses. These explicit formulas embody the assimilation of experimental data and the “calibration” of the model’s parameters. The results presented in this work demonstrate that the PM_CMPS methodology reduces the predicted standard deviations to values that are smaller than either the computed or the experimentally measured ones, even for responses (e.g., the outlet water flow rate for which no measurements are available. These improvements stem from the global characteristics of the PM_CMPS methodology, which combines all of the available information simultaneously in phase-space, as opposed to combining it sequentially, as in current data assimilation procedures.

Photovoltaic module parameters acquisition model

Energy Technology Data Exchange (ETDEWEB)

Cibira, Gabriel, E-mail: cibira@lm.uniza.sk; Koščová, Marcela, E-mail: mkoscova@lm.uniza.sk

2014-09-01

Highlights: • Photovoltaic five-parameter model is proposed using Matlab{sup ®} and Simulink. • The model acquisits input sparse data matrix from stigmatic measurement. • Computer simulations lead to continuous I–V and P–V characteristics. • Extrapolated I–V and P–V characteristics are in hand. • The model allows us to predict photovoltaics exploitation in different conditions. - Abstract: This paper presents basic procedures for photovoltaic (PV) module parameters acquisition using MATLAB and Simulink modelling. In first step, MATLAB and Simulink theoretical model are set to calculate I–V and P–V characteristics for PV module based on equivalent electrical circuit. Then, limited I–V data string is obtained from examined PV module using standard measurement equipment at standard irradiation and temperature conditions and stated into MATLAB data matrix as a reference model. Next, the theoretical model is optimized to keep-up with the reference model and to learn its basic parameters relations, over sparse data matrix. Finally, PV module parameters are deliverable for acquisition at different realistic irradiation, temperature conditions as well as series resistance. Besides of output power characteristics and efficiency calculation for PV module or system, proposed model validates computing statistical deviation compared to reference model.

Photovoltaic module parameters acquisition model

International Nuclear Information System (INIS)

Cibira, Gabriel; Koščová, Marcela

2014-01-01

Highlights: • Photovoltaic five-parameter model is proposed using Matlab ® and Simulink. • The model acquisits input sparse data matrix from stigmatic measurement. • Computer simulations lead to continuous I–V and P–V characteristics. • Extrapolated I–V and P–V characteristics are in hand. • The model allows us to predict photovoltaics exploitation in different conditions. - Abstract: This paper presents basic procedures for photovoltaic (PV) module parameters acquisition using MATLAB and Simulink modelling. In first step, MATLAB and Simulink theoretical model are set to calculate I–V and P–V characteristics for PV module based on equivalent electrical circuit. Then, limited I–V data string is obtained from examined PV module using standard measurement equipment at standard irradiation and temperature conditions and stated into MATLAB data matrix as a reference model. Next, the theoretical model is optimized to keep-up with the reference model and to learn its basic parameters relations, over sparse data matrix. Finally, PV module parameters are deliverable for acquisition at different realistic irradiation, temperature conditions as well as series resistance. Besides of output power characteristics and efficiency calculation for PV module or system, proposed model validates computing statistical deviation compared to reference model

Spectroscopic properties of a two-dimensional time-dependent Cepheid model. II. Determination of stellar parameters and abundances

Science.gov (United States)

Vasilyev, V.; Ludwig, H.-G.; Freytag, B.; Lemasle, B.; Marconi, M.

2018-03-01

Context. Standard spectroscopic analyses of variable stars are based on hydrostatic 1D model atmospheres. This quasi-static approach has not been theoretically validated. Aim. We aim at investigating the validity of the quasi-static approximation for Cepheid variables. We focus on the spectroscopic determination of the effective temperature Teff, surface gravity log g, microturbulent velocity ξt, and a generic metal abundance log A, here taken as iron. Methods: We calculated a grid of 1D hydrostatic plane-parallel models covering the ranges in effective temperature and gravity that are encountered during the evolution of a 2D time-dependent envelope model of a Cepheid computed with the radiation-hydrodynamics code CO5BOLD. We performed 1D spectral syntheses for artificial iron lines in local thermodynamic equilibrium by varying the microturbulent velocity and abundance. We fit the resulting equivalent widths to corresponding values obtained from our dynamical model for 150 instances in time, covering six pulsational cycles. In addition, we considered 99 instances during the initial non-pulsating stage of the temporal evolution of the 2D model. In the most general case, we treated Teff, log g, ξt, and log A as free parameters, and in two more limited cases, we fixed Teff and log g by independent constraints. We argue analytically that our approach of fitting equivalent widths is closely related to current standard procedures focusing on line-by-line abundances. Results: For the four-parametric case, the stellar parameters are typically underestimated and exhibit a bias in the iron abundance of ≈-0.2 dex. To avoid biases of this type, it is favorable to restrict the spectroscopic analysis to photometric phases ϕph ≈ 0.3…0.65 using additional information to fix the effective temperature and surface gravity. Conclusions: Hydrostatic 1D model atmospheres can provide unbiased estimates of stellar parameters and abundances of Cepheid variables for particular

The Adsorption of Cd(II on Manganese Oxide Investigated by Batch and Modeling Techniques

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Xiaoming Huang

2017-09-01

Full Text Available Manganese (Mn oxide is a ubiquitous metal oxide in sub-environments. The adsorption of Cd(II on Mn oxide as function of adsorption time, pH, ionic strength, temperature, and initial Cd(II concentration was investigated by batch techniques. The adsorption kinetics showed that the adsorption of Cd(II on Mn oxide can be satisfactorily simulated by pseudo-second-order kinetic model with high correlation coefficients (R2 > 0.999. The adsorption of Cd(II on Mn oxide significantly decreased with increasing ionic strength at pH < 5.0, whereas Cd(II adsorption was independent of ionic strength at pH > 6.0, which indicated that outer-sphere and inner-sphere surface complexation dominated the adsorption of Cd(II on Mn oxide at pH < 5.0 and pH > 6.0, respectively. The maximum adsorption capacity of Mn oxide for Cd(II calculated from Langmuir model was 104.17 mg/g at pH 6.0 and 298 K. The thermodynamic parameters showed that the adsorption of Cd(II on Mn oxide was an endothermic and spontaneous process. According to the results of surface complexation modeling, the adsorption of Cd(II on Mn oxide can be satisfactorily simulated by ion exchange sites (X2Cd at low pH and inner-sphere surface complexation sites (SOCd+ and (SO2CdOH− species at high pH conditions. The finding presented herein plays an important role in understanding the fate and transport of heavy metals at the water–mineral interface.

Modeling Type II-P/II-L Supernovae Interacting with Recent Episodic Mass Ejections from Their Presupernova Stars with MESA and SNEC

Science.gov (United States)

Das, Sanskriti; Ray, Alak

2017-12-01

We show how dense, compact, discrete shells of circumstellar gas immediately outside of red supergiants affect the optical light curves of Type II-P/II-L supernovae (SNe), using the example of SN 2013ej. Earlier efforts in the literature had used an artificial circumstellar medium (CSM) stitched to the surface of an evolved star that had not gone through a phase of late-stage heavy mass loss, which, in essence, is the original source of the CSM. In contrast, we allow enhanced mass-loss rate from the modeled star during the 16O and 28Si burning stages and construct the CSM from the resulting mass-loss history in a self-consistent way. Once such evolved pre-SN stars are exploded, we find that the models with early interaction between the shock and the dense CSM reproduce light curves far better than those without that mass loss and, hence, having no nearby dense CSM. The required explosion energy for the progenitors with a dense CSM is reduced by almost a factor of two compared to those without the CSM. Our model, with a more realistic CSM profile and presupernova and explosion parameters, fits observed data much better throughout the rise, plateau, and radioactive tail phases as compared to previous studies. This points to an intermediate class of supernovae between Type II-P/II-L and Type II-n SNe with the characteristics of simultaneous UV and optical peak, slow decline after peak, and a longer plateau.

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

A Shot Parameter Specification Subsystem for automated control of PBFA [Particle Beam Fusion Accelerator] II accelerator shots

International Nuclear Information System (INIS)

Spiller, J.L.

1987-01-01

The Shot Parameter Specification Subsystem (SPSS) is an integral part of the automatic control system developed for the Particle Beam Fusion Accelerator II (PBFA II) by the Control Monitor (C/M) Software Development Team. This system has been designed to fully utilize the accelerator by tailoring shot parameters to the needs of the experimenters. The SPSS is the key to this flexibility. Automatic systems will be required on many pulsed power machines for the fastest turnaround, the highest reliability, and most cost effective operation. These systems will require the flexibility and the ease of use that is part of the SPSS. The PBFA II control system has proved to be an effective modular system, flexible enough to meet the demands of both the fast track construction of PBFA II and the control needs of Hermes III at the Simulation Technology Laboratory. This system is expected to meet the demands of most future machine changes

Equilibrium and kinetic studies of Pb(II, Cd(II and Zn(II sorption by Lagenaria vulgaris shell

Directory of Open Access Journals (Sweden)

Mitić-Stojanović Dragana-Linda

2012-01-01

Full Text Available The sorption of lead, cadmium and zinc ions from aqueous solution by Lagenaria vulgaris shell biosorbent (LVB in batch system was investigated. The effect of relevant parameters such as contact time, biosorbent dosage and initial metal ions concentration was evaluated. The Pb(II, Cd(II and Zn(II sorption equilibrium (when 98% of initial metal ions were sorbed was attained within 15, 20 and 25 min, respectively. The pseudo first, pseudo-second order, Chrastil’s and intra-particle diffusion models were used to describe the kinetic data. The experimental data fitted the pseudo-second order kinetic model and intra-particle diffusion model. Removal efficiency of lead(II, cadmium(II and zinc(II ions rapidly increased with increasing biosorbent dose from 0.5 to 8.0 g dm-3. Optimal biosorbent dose was set to 4.0 g dm-3. An increase in the initial metal concentration increases the sorption capacity. The sorption data of investigated metal ions are fitted to Langmuir, Freundlich and Temkin isotherm models. Langmuir model best fitted the equilibrium data (r2 > 0.99. Maximal sorption capacities of LVB for Pb(II, Cd(II and Zn(II at 25.0±0.5°C were 0.130, 0.103 and 0.098 mM g-1, respectively. The desorption experiments showed that the LVB could be reused for six cycles with a minimum loss of the initial sorption capacity.

Stability Analysis for Li-Ion Battery Model Parameters and State of Charge Estimation by Measurement Uncertainty Consideration

Directory of Open Access Journals (Sweden)

Shifei Yuan

2015-07-01

Full Text Available Accurate estimation of model parameters and state of charge (SoC is crucial for the lithium-ion battery management system (BMS. In this paper, the stability of the model parameters and SoC estimation under measurement uncertainty is evaluated by three different factors: (i sampling periods of 1/0.5/0.1 s; (ii current sensor precisions of ±5/±50/±500 mA; and (iii voltage sensor precisions of ±1/±2.5/±5 mV. Firstly, the numerical model stability analysis and parametric sensitivity analysis for battery model parameters are conducted under sampling frequency of 1–50 Hz. The perturbation analysis is theoretically performed of current/voltage measurement uncertainty on model parameter variation. Secondly, the impact of three different factors on the model parameters and SoC estimation was evaluated with the federal urban driving sequence (FUDS profile. The bias correction recursive least square (CRLS and adaptive extended Kalman filter (AEKF algorithm were adopted to estimate the model parameters and SoC jointly. Finally, the simulation results were compared and some insightful findings were concluded. For the given battery model and parameter estimation algorithm, the sampling period, and current/voltage sampling accuracy presented a non-negligible effect on the estimation results of model parameters. This research revealed the influence of the measurement uncertainty on the model parameter estimation, which will provide the guidelines to select a reasonable sampling period and the current/voltage sensor sampling precisions in engineering applications.

Micellar effect on metal-ligand complexes of Co(II, Ni(II, Cu(II and Zn(II with citric acid

Directory of Open Access Journals (Sweden)

Nageswara Rao Gollapalli

2009-12-01

Full Text Available Chemical speciation of citric acid complexes of Co(II, Ni(II, Cu(II and Zn(II was investigated pH-metrically in 0.0-2.5% anionic, cationic and neutral micellar media. The primary alkalimetric data were pruned with SCPHD program. The existence of different binary species was established from modeling studies using the computer program MINIQUAD75. Alkalimetric titrations were carried out in different relative concentrations (M:L:X = 1:2:5, 1:3:5, 1:5:3 of metal (M to citric acid. The selection of best chemical models was based on statistical parameters and residual analysis. The species detected were MLH, ML2, ML2H and ML2H2. The trend in variation of stability constants with change in mole fraction of the medium is explained on the basis of electrostatic and non-electrostatic forces. Distributions of the species with pH at different compositions of micellar media are also presented.

Parameter Estimation of Partial Differential Equation Models.

Science.gov (United States)

Xun, Xiaolei; Cao, Jiguo; Mallick, Bani; Carroll, Raymond J; Maity, Arnab

2013-01-01

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 present 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 LIDAR data.

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

Science.gov (United States)

Batzias, Dimitris F.; Ifanti, Konstantina

2012-12-01

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

Quality assessment for radiological model parameters

International Nuclear Information System (INIS)

Funtowicz, S.O.

1989-01-01

A prototype framework for representing uncertainties in radiological model parameters is introduced. This follows earlier development in this journal of a corresponding framework for representing uncertainties in radiological data. Refinements and extensions to the earlier framework are needed in order to take account of the additional contextual factors consequent on using data entries to quantify model parameters. The parameter coding can in turn feed in to methods for evaluating uncertainties in calculated model outputs. (author)

Sensitivity Analysis of Uncertainty Parameter based on MARS-LMR Code on SHRT-45R of EBR II

Energy Technology Data Exchange (ETDEWEB)

Kang, Seok-Ju; Kang, Doo-Hyuk; Seo, Jae-Seung [System Engineering and Technology Co., Daejeon (Korea, Republic of); Bae, Sung-Won [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Jeong, Hae-Yong [Sejong University, Seoul (Korea, Republic of)

2016-10-15

In order to assess the uncertainty quantification of the MARS-LMR code, the code has been improved by modifying the source code to accommodate calculation process required for uncertainty quantification. In the present study, a transient of Unprotected Loss of Flow(ULOF) is selected as typical cases of as Anticipated Transient without Scram(ATWS) which belongs to DEC category. The MARS-LMR input generation for EBR II SHRT-45R and execution works are performed by using the PAPIRUS program. The sensitivity analysis is carried out with Uncertainty Parameter of the MARS-LMR code for EBR-II SHRT-45R. Based on the results of sensitivity analysis, dominant parameters with large sensitivity to FoM are picked out. Dominant parameters selected are closely related to the development process of ULOF event.

I. Nuclear and neutron matter calculations with isobars. II. A model calculation of Fermi liquid parameters for liquid 3He

International Nuclear Information System (INIS)

Ainsworth, T.L.

1983-01-01

The Δ(1232) plays an important role in determining the properties of nuclear and neutron matter. The effects of the Δ resonance are incorporated explicitly by using a coupled channel formalism. A method for constraining a lowest order variational calculation, appropriate when nucleon internal degrees of freedom are made explicity, is presented. Different N-N potentials were calculated and fit to phase shift data and deuteron properties. The potentials were constructed to test the relative importance of the Δ resonance on nuclear properties. The symmetry energy and incompressibility of nuclear matter are generally reproduced by this calculation. Neutron matter results lead to appealing neutron star models. Fermi liquid parameters for 3 He are calculated with a model that includes both direct and induced terms. A convenient form of the direct interaction is obtained in terms of the parameters. The form of the direct interaction ensures that the forward scattering sum rule (Pauli principle) is obeyed. The parameters are adjusted to fit the experimentally determined F 0 /sup s/, F 0 /sup a/, and F 1 /sup s/ Landau parameters. Higher order Landau parameters are calculated by the self-consistent solution of the equations; comparison to experiment is good. The model also leads to a preferred value for the effective mass of 3 He. Of the three parameters only one shows any dependence on pressure. An exact sum rule is derived relating this parameter to a specific summation of Landau parameters

Effect of process parameters on removal and recovery of Cd(II) and Cu(II) from electroplating wastewater by fixed-bed column of nano-dimensional titanium (IV) oxide agglomerates

CSIR Research Space (South Africa)

Debnath, S

2014-01-01

Full Text Available Removal performances of Cd(II) and Cu(II) from water was investigated using agglomerated nanoparticle of hydrous titanium(IV) oxide (NTO) packed fixed bed. The parameters varied were the bed depth, flow rate and feed solution concentrations...

Solar photocatalytic removal of Cu(II), Ni(II), Zn(II) and Pb(II): Speciation modeling of metal-citric acid complexes

International Nuclear Information System (INIS)

Kabra, Kavita; Chaudhary, Rubina; Sawhney, R.L.

2008-01-01

The present study is targeted on solar photocatalytic removal of metal ions from wastewater. Photoreductive deposition and dark adsorption of metal ions Cu(II), Ni(II), Pb(II) and Zn(II), using solar energy irradiated TiO 2 , has been investigated. Citric acid has been used as a hole scavenger. Modeling of metal species has been performed and speciation is used as a tool for discussing the photodeposition trends. Ninety-seven percent reductive deposition was obtained for copper. The deposition values of other metals were significantly low [nickel (36.4%), zinc (22.2%) and lead (41.4%)], indicating that the photocatalytic treatment process, using solar energy, was more suitable for wastewater containing Cu(II) ions. In absence of citric acid, the decreasing order deposition was Cu(II) > Ni(II) > Pb(II) > Zn(II), which proves the theoretical thermodynamic predictions about the metals

Verification of MCNP simulation of neutron flux parameters at TRIGA MK II reactor of Malaysia.

Science.gov (United States)

Yavar, A R; Khalafi, H; Kasesaz, Y; Sarmani, S; Yahaya, R; Wood, A K; Khoo, K S

2012-10-01

A 3-D model for 1 MW TRIGA Mark II research reactor was simulated. Neutron flux parameters were calculated using MCNP-4C code and were compared with experimental results obtained by k(0)-INAA and absolute method. The average values of φ(th),φ(epi), and φ(fast) by MCNP code were (2.19±0.03)×10(12) cm(-2)s(-1), (1.26±0.02)×10(11) cm(-2)s(-1) and (3.33±0.02)×10(10) cm(-2)s(-1), respectively. These average values were consistent with the experimental results obtained by k(0)-INAA. The findings show a good agreement between MCNP code results and experimental results. Copyright © 2012 Elsevier Ltd. All rights reserved.

Parameter Estimation of Partial Differential Equation Models

KAUST Repository

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.

Greenland ice sheet model parameters constrained using simulations of the Eemian Interglacial

Directory of Open Access Journals (Sweden)

A. Robinson

2011-04-01

Full Text Available Using a new approach to force an ice sheet model, we performed an ensemble of simulations of the Greenland Ice Sheet evolution during the last two glacial cycles, with emphasis on the Eemian Interglacial. This ensemble was generated by perturbing four key parameters in the coupled regional climate-ice sheet model and by introducing additional uncertainty in the prescribed "background" climate change. The sensitivity of the surface melt model to climate change was determined to be the dominant driver of ice sheet instability, as reflected by simulated ice sheet loss during the Eemian Interglacial period. To eliminate unrealistic parameter combinations, constraints from present-day and paleo information were applied. The constraints include (i the diagnosed present-day surface mass balance partition between surface melting and ice discharge at the margin, (ii the modeled present-day elevation at GRIP; and (iii the modeled elevation reduction at GRIP during the Eemian. Using these three constraints, a total of 360 simulations with 90 different model realizations were filtered down to 46 simulations and 20 model realizations considered valid. The paleo constraint eliminated more sensitive melt parameter values, in agreement with the surface mass balance partition assumption. The constrained simulations resulted in a range of Eemian ice loss of 0.4–4.4 m sea level equivalent, with a more likely range of about 3.7–4.4 m sea level if the GRIP δ¹⁸O isotope record can be considered an accurate proxy for the precipitation-weighted annual mean temperatures.

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.

Stark parameters of some asymmetrical Si II lines

International Nuclear Information System (INIS)

Ferhat, B; Azzouz, Y; Redon, R; Ripert, M; Lesage, A

2012-01-01

Six lines of SiII are experimentally studied in pulsed plasma generated by Nd :Yag laser breakdown on pure solid silicon target. A set of experimental Stark parameters of asymmetrical lines are measured in temperature range from 14 000 K to 18 000 K (using Boltzmann plot). Calculated values of the electron density (using Griem's formula) vary from 1.7 to 6.1 × 10 23 m −3 . Processed spectral lines are 333.982 nm (3s 2 4p -3s 2 6s) and 397.746 nm, 399.177 nm, 399.801 nm, 401.622 nm (3d' 2 F 0 -4f' 4 G) and (3d' 2 F 0 - 4f' 2 G) of astrophysical interest. Asymmetrical line shapes are synthesized by a sum of two semi-Lorentzian distributions. The obtained fit is in good agreement with the measured spectra.

An Investigation on the Sensitivity of the Parameters of Urban Flood Model

Science.gov (United States)

M, A. B.; Lohani, B.; Jain, A.

2015-12-01

Global climatic change has triggered weather patterns which lead to heavy and sudden rainfall in different parts of world. The impact of heavy rainfall is severe especially on urban areas in the form of urban flooding. In order to understand the effect of heavy rainfall induced flooding, it is necessary to model the entire flooding scenario more accurately, which is now becoming possible with the availability of high resolution airborne LiDAR data and other real time observations. However, there is not much understanding on the optimal use of these data and on the effect of other parameters on the performance of the flood model. This study aims at developing understanding on these issues. In view of the above discussion, the aim of this study is to (i) understand that how the use of high resolution LiDAR data improves the performance of urban flood model, and (ii) understand the sensitivity of various hydrological parameters on urban flood modelling. In this study, modelling of flooding in urban areas due to heavy rainfall is carried out considering Indian Institute of Technology (IIT) Kanpur, India as the study site. The existing model MIKE FLOOD, which is accepted by Federal Emergency Management Agency (FEMA), is used along with the high resolution airborne LiDAR data. Once the model is setup it is made to run by changing the parameters such as resolution of Digital Surface Model (DSM), manning's roughness, initial losses, catchment description, concentration time, runoff reduction factor. In order to realize this, the results obtained from the model are compared with the field observations. The parametric study carried out in this work demonstrates that the selection of catchment description plays a very important role in urban flood modelling. Results also show the significant impact of resolution of DSM, initial losses and concentration time on urban flood model. This study will help in understanding the effect of various parameters that should be part of a

Determination of kinetic and equilibrium parameters of the batch adsorption of Mn(II), Co(II), Ni(II) and Cu(II) from aqueous solution by black carrot (Daucus carota L.) residues

International Nuclear Information System (INIS)

Guezel, Fuat; Yakut, Hakan; Topal, Giray

2008-01-01

In this study, the effect of temperature on the adsorption of Mn(II), Ni(II), Co(II) and Cu(II) from aqueous solution by modified carrot residues (MCR) was investigated. The equilibrium contact times of adsorption process for each heavy metals-MCR systems were determined. Kinetic data obtained for each heavy metal by MCR at different temperatures were applied to the Lagergren equation, and adsorption rate constants (k ads ) at these temperatures were determined. These rate constants related to the adsorption of heavy metal by MCR were applied to the Arrhenius equation, and activation energies (E a ) were determined. In addition, the isotherms for adsorption of each heavy metal by MCR at different temperatures were also determined. These isothermal data were applied to linear forms of isotherm equations that they fit the Langmuir adsorption isotherm, and the Langmuir constants (q m and b) were calculated. b constants determined at different temperatures were applied to thermodynamic equations, and thermodynamic parameters such as enthalpy (ΔH), free energy (ΔG), and entropy (ΔS) were calculated and these values show that adsorption of heavy metal on MCR was an endothermic process and process of adsorption was favoured at high temperatures

An integrated approach for the knowledge discovery in computer simulation models with a multi-dimensional parameter space

Energy Technology Data Exchange (ETDEWEB)

Khawli, Toufik Al; Eppelt, Urs; Hermanns, Torsten [RWTH Aachen University, Chair for Nonlinear Dynamics, Steinbachstr. 15, 52047 Aachen (Germany); Gebhardt, Sascha [RWTH Aachen University, Virtual Reality Group, IT Center, Seffenter Weg 23, 52074 Aachen (Germany); Kuhlen, Torsten [Forschungszentrum Jülich GmbH, Institute for Advanced Simulation (IAS), Jülich Supercomputing Centre (JSC), Wilhelm-Johnen-Straße, 52425 Jülich (Germany); Schulz, Wolfgang [Fraunhofer, ILT Laser Technology, Steinbachstr. 15, 52047 Aachen (Germany)

2016-06-08

In production industries, parameter identification, sensitivity analysis and multi-dimensional visualization are vital steps in the planning process for achieving optimal designs and gaining valuable information. Sensitivity analysis and visualization can help in identifying the most-influential parameters and quantify their contribution to the model output, reduce the model complexity, and enhance the understanding of the model behavior. Typically, this requires a large number of simulations, which can be both very expensive and time consuming when the simulation models are numerically complex and the number of parameter inputs increases. There are three main constituent parts in this work. The first part is to substitute the numerical, physical model by an accurate surrogate model, the so-called metamodel. The second part includes a multi-dimensional visualization approach for the visual exploration of metamodels. In the third part, the metamodel is used to provide the two global sensitivity measures: i) the Elementary Effect for screening the parameters, and ii) the variance decomposition method for calculating the Sobol indices that quantify both the main and interaction effects. The application of the proposed approach is illustrated with an industrial application with the goal of optimizing a drilling process using a Gaussian laser beam.

Removal of Ca(II) and Mg(II) from potassium chromate solution on Amberlite IRC 748 synthetic resin by ion exchange

International Nuclear Information System (INIS)

Yu Zhihui; Qi Tao; Qu Jingkui; Wang Lina; Chu Jinglong

2009-01-01

Experimental measurements have been made on the batch ion exchange of Ca(II) and Mg(II) from potassium chromate solution using cation exchanger of Amberlite IRC 748 as K + form. The ion exchange behavior of two alkaline-earth metals on the resin, depending on contact time, pH, temperature and resin dosage was studied. The adsorption isotherms were described by means of the Langmuir and Freundlich isotherms. For Ca(II) ion, the Langmuir model represented the adsorption process better than the Freundlich model. The maximum ion exchange capacity was found to be 47.21 mg g -1 for Ca(II) and 27.70 mg g -1 for Mg(II). The kinetic data were tested using Lagergren-first-order and pseudo-second-order kinetic models. Kinetic data correlated well with the pseudo-second-order kinetic model, indicating that the chemical adsorption was the rate-limiting step. Various thermodynamic parameters such as Gibbs free energy (ΔG o ), enthalpy (ΔH o ) and entropy (ΔS o ) were also calculated. These parameters showed that the ion exchange of Ca(II) and Mg(II) from potassium chromate solution was feasible, spontaneous and endothermic process in nature. The activation energy of ion-exchange (E a ) was determined as 12.34 kJ mol -1 for Ca(II) and 9.865 kJ mol -1 for Mg(II) according to the Arrhenius equation.

Automated parameter estimation for biological models using Bayesian statistical model checking.

Science.gov (United States)

Hussain, Faraz; Langmead, Christopher J; Mi, Qi; Dutta-Moscato, Joyeeta; Vodovotz, Yoram; Jha, Sumit K

2015-01-01

Probabilistic models have gained widespread acceptance in the systems biology community as a useful way to represent complex biological systems. Such models are developed using existing knowledge of the structure and dynamics of the system, experimental observations, and inferences drawn from statistical analysis of empirical data. A key bottleneck in building such models is that some system variables cannot be measured experimentally. These variables are incorporated into the model as numerical parameters. Determining values of these parameters that justify existing experiments and provide reliable predictions when model simulations are performed is a key research problem. Using an agent-based model of the dynamics of acute inflammation, we demonstrate a novel parameter estimation algorithm by discovering the amount and schedule of doses of bacterial lipopolysaccharide that guarantee a set of observed clinical outcomes with high probability. We synthesized values of twenty-eight unknown parameters such that the parameterized model instantiated with these parameter values satisfies four specifications describing the dynamic behavior of the model. We have developed a new algorithmic technique for discovering parameters in complex stochastic models of biological systems given behavioral specifications written in a formal mathematical logic. Our algorithm uses Bayesian model checking, sequential hypothesis testing, and stochastic optimization to automatically synthesize parameters of probabilistic biological models.

Robust and efficient parameter estimation in dynamic models of biological systems.

Science.gov (United States)

Gábor, Attila; Banga, Julio R

2015-10-29

Dynamic modelling provides a systematic framework to understand function in biological systems. Parameter estimation in nonlinear dynamic models remains a very challenging inverse problem due to its nonconvexity and ill-conditioning. Associated issues like overfitting and local solutions are usually not properly addressed in the systems biology literature despite their importance. Here we present a method for robust and efficient parameter estimation which uses two main strategies to surmount the aforementioned difficulties: (i) efficient global optimization to deal with nonconvexity, and (ii) proper regularization methods to handle ill-conditioning. In the case of regularization, we present a detailed critical comparison of methods and guidelines for properly tuning them. Further, we show how regularized estimations ensure the best trade-offs between bias and variance, reducing overfitting, and allowing the incorporation of prior knowledge in a systematic way. We illustrate the performance of the presented method with seven case studies of different nature and increasing complexity, considering several scenarios of data availability, measurement noise and prior knowledge. We show how our method ensures improved estimations with faster and more stable convergence. We also show how the calibrated models are more generalizable. Finally, we give a set of simple guidelines to apply this strategy to a wide variety of calibration problems. Here we provide a parameter estimation strategy which combines efficient global optimization with a regularization scheme. This method is able to calibrate dynamic models in an efficient and robust way, effectively fighting overfitting and allowing the incorporation of prior information.

Anisotropic Bianchi II cosmological models with matter and electromagnetic fields

International Nuclear Information System (INIS)

Soares, D.

1978-01-01

A class of solutions of Einstein-Maxwell equations is presented, which corresponds to anisotropic Bianchi II spatially homogeneous cosmological models with perfect fluid and electromagnetic field. A particular model is examined and shown to be unstable for perturbations of the electromagnetic field strength parameter about a particular value. This value defines a limiar unstable case in which the ratio epsilon, of the fluid density to the e.m. energy density is monotonically increasing with a minimum finite value at the singularity. Beyond this limiar, the model has a matter dominated singularity, and a characteristic stage appears where epsilon has a minimum, at a finite time from the singularity. For large times, the models tend to an exact solution for zero electromagnetic field and fluid with p = (1/5)p. Some cosmological features of the models are calculated, as the effect of anisotropy on matter density and expansion time scale factors, as compared to the corresponding Friedmann model [pt

Reference methodologies for radioactive controlled discharges an activity within the IAEA's Program Environmental Modelling for Radiation Safety II (EMRAS II)

International Nuclear Information System (INIS)

Stocki, T.J.; Bergman, L.; Tellería, D.M.; Proehl, G.; Amado, V.; Curti, A.; Bonchuk, I.; Boyer, P.; Mourlon, C.; Chyly, P.; Heling, R.; Sági, L.; Kliaus, V.; Krajewski, P.; Latouche, G.; Lauria, D.C.; Newsome, L.; Smith, J.

2011-01-01

In January 2009, the IAEA EMRAS II (Environmental Modelling for Radiation Safety II) program was launched. The goal of the program is to develop, compare and test models for the assessment of radiological impacts to the public and the environment due to radionuclides being released or already existing in the environment; to help countries build and harmonize their capabilities; and to model the movement of radionuclides in the environment. Within EMRAS II, nine working groups are active; this paper will focus on the activities of Working Group 1: Reference Methodologies for Controlling Discharges of Routine Releases. Within this working group environmental transfer and dose assessment models are tested under different scenarios by participating countries and the results compared. This process allows each participating country to identify characteristics of their models that need to be refined. The goal of this working group is to identify reference methodologies for the assessment of exposures to the public due to routine discharges of radionuclides to the terrestrial and aquatic environments. Several different models are being applied to estimate the transfer of radionuclides in the environment for various scenarios. The first phase of the project involves a scenario of nuclear power reactor with a coastal location which routinely (continuously) discharges 60Co, 85Kr, 131I, and 137Cs to the atmosphere and 60Co, 137Cs, and 90Sr to the marine environment. In this scenario many of the parameters and characteristics of the representative group were given to the modelers and cannot be altered. Various models have been used by the different participants in this inter-comparison (PC-CREAM, CROM, IMPACT, CLRP POSEIDON, SYMBIOSE and others). This first scenario is to enable a comparison of the radionuclide transport and dose modelling. These scenarios will facilitate the development of reference methodologies for controlled discharges. (authors)

The influence of model parameters on catchment-response

International Nuclear Information System (INIS)

Shah, S.M.S.; Gabriel, H.F.; Khan, A.A.

2002-01-01

This paper deals with the study of influence of influence of conceptual rainfall-runoff model parameters on catchment response (runoff). A conceptual modified watershed yield model is employed to study the effects of model-parameters on catchment-response, i.e. runoff. The model is calibrated, using manual parameter-fitting approach, also known as trial and error parameter-fitting. In all, there are twenty one (21) parameters that control the functioning of the model. A lumped parametric approach is used. The detailed analysis was performed on Ling River near Kahuta, having catchment area of 56 sq. miles. The model includes physical parameters like GWSM, PETS, PGWRO, etc. fitting coefficients like CINF, CGWS, etc. and initial estimates of the surface-water and groundwater storages i.e. srosp and gwsp. Sensitivity analysis offers a good way, without repetititious computations, the proper weight and consideration that must be taken when each of the influencing factor is evaluated. Sensitivity-analysis was performed to evaluate the influence of model-parameters on runoff. The sensitivity and relative contributions of model parameters influencing catchment-response are studied. (author)

Application of Box-Behnken designs in parameters optimization of differential pulse anodic stripping voltammetry for lead(II) determination in two electrolytes.

Science.gov (United States)

Yu, Xiao-Lan; He, Yong

2017-06-05

Box-Behnken design was advantageous to parameters optimization of differential pulse anodic stripping voltammetry (DPASV) for the analysis of lead(II) with its high efficiency and accuracy. Five Box-Behnken designs were designed and conducted in the electrolyte of 0.1 mol/L acetate buffer and 0.1 mol/L HCl without the removal of oxygen. Significant parameters and interactions in each electrolyte were found (P-value Box-Behnken designs in parameters optimization of DPASV for lead(II) determination regardless of the electrolyte kinds.

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...

Complexity, parameter sensitivity and parameter transferability in the modelling of floodplain inundation

Science.gov (United States)

Bates, P. D.; Neal, J. C.; Fewtrell, T. J.

2012-12-01

In this we paper we consider two related questions. First, we address the issue of how much physical complexity is necessary in a model in order to simulate floodplain inundation to within validation data error. This is achieved through development of a single code/multiple physics hydraulic model (LISFLOOD-FP) where different degrees of complexity can be switched on or off. Different configurations of this code are applied to four benchmark test cases, and compared to the results of a number of industry standard models. Second we address the issue of how parameter sensitivity and transferability change with increasing complexity using numerical experiments with models of different physical and geometric intricacy. Hydraulic models are a good example system with which to address such generic modelling questions as: (1) they have a strong physical basis; (2) there is only one set of equations to solve; (3) they require only topography and boundary conditions as input data; and (4) they typically require only a single free parameter, namely boundary friction. In terms of complexity required we show that for the problem of sub-critical floodplain inundation a number of codes of different dimensionality and resolution can be found to fit uncertain model validation data equally well, and that in this situation Occam's razor emerges as a useful logic to guide model selection. We find also find that model skill usually improves more rapidly with increases in model spatial resolution than increases in physical complexity, and that standard approaches to testing hydraulic models against laboratory data or analytical solutions may fail to identify this important fact. Lastly, we find that in benchmark testing studies significant differences can exist between codes with identical numerical solution techniques as a result of auxiliary choices regarding the specifics of model implementation that are frequently unreported by code developers. As a consequence, making sound

Parameter estimation of variable-parameter nonlinear Muskingum model using excel solver

Science.gov (United States)

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.

Assessing the relative importance of parameter and forcing uncertainty and their interactions in conceptual hydrological model simulations

Science.gov (United States)

Mockler, E. M.; Chun, K. P.; Sapriza-Azuri, G.; Bruen, M.; Wheater, H. S.

2016-11-01

Predictions of river flow dynamics provide vital information for many aspects of water management including water resource planning, climate adaptation, and flood and drought assessments. Many of the subjective choices that modellers make including model and criteria selection can have a significant impact on the magnitude and distribution of the output uncertainty. Hydrological modellers are tasked with understanding and minimising the uncertainty surrounding streamflow predictions before communicating the overall uncertainty to decision makers. Parameter uncertainty in conceptual rainfall-runoff models has been widely investigated, and model structural uncertainty and forcing data have been receiving increasing attention. This study aimed to assess uncertainties in streamflow predictions due to forcing data and the identification of behavioural parameter sets in 31 Irish catchments. By combining stochastic rainfall ensembles and multiple parameter sets for three conceptual rainfall-runoff models, an analysis of variance model was used to decompose the total uncertainty in streamflow simulations into contributions from (i) forcing data, (ii) identification of model parameters and (iii) interactions between the two. The analysis illustrates that, for our subjective choices, hydrological model selection had a greater contribution to overall uncertainty, while performance criteria selection influenced the relative intra-annual uncertainties in streamflow predictions. Uncertainties in streamflow predictions due to the method of determining parameters were relatively lower for wetter catchments, and more evenly distributed throughout the year when the Nash-Sutcliffe Efficiency of logarithmic values of flow (lnNSE) was the evaluation criterion.

Estimation of hydrodinamics parameters in a volcanic fractured phreatic aquifer in Costa Rica. Part II. Double porosity model

International Nuclear Information System (INIS)

Macias, Julio; Vargas, Asdrubal

2017-01-01

MIM 1D transport model was successfully applied to simulate the asymmetric behavior observed in three breakthrough curves of tracer tests performed under natural gradient conditions in a phreatic fractured volcanic aquifer. The transport parameters obtained after adjustment with a computer program, suggest that only 50% of the total porosity effectively contributed to the advective-dispersive transport (mobile fraction) and the other 50% behaved as a temporary reservoir for the tracer (immobile fraction). The estimated values of hydraulic properties and MIM model parameters are within the range of values reported by other researchers. It was possible to establish a conceptual and numerical framework to explain the three-tracer tests curves behavior, despite the limitations in quality and quantity of available field information. (author) [es

Anisotropic Bianchi Type-I and Type-II Bulk Viscous String Cosmological Models Coupled with Zero Mass Scalar Field

Science.gov (United States)

Venkateswarlu, R.; Sreenivas, K.

2014-06-01

The LRS Bianchi type-I and type-II string cosmological models are studied when the source for the energy momentum tensor is a bulk viscous stiff fluid containing one dimensional strings together with zero-mass scalar field. We have obtained the solutions of the field equations assuming a functional relationship between metric coefficients when the metric is Bianchi type-I and constant deceleration parameter in case of Bianchi type-II metric. The physical and kinematical properties of the models are discussed in each case. The effects of Viscosity on the physical and kinematical properties are also studied.

EMPIRE-II statistical model code for nuclear reaction calculations

Energy Technology Data Exchange (ETDEWEB)

Herman, M [International Atomic Energy Agency, Vienna (Austria)

2001-12-15

EMPIRE II is a nuclear reaction code, comprising various nuclear models, and designed for calculations in the broad range of energies and incident particles. A projectile can be any nucleon or Heavy Ion. The energy range starts just above the resonance region, in the case of neutron projectile, and extends up to few hundreds of MeV for Heavy Ion induced reactions. The code accounts for the major nuclear reaction mechanisms, such as optical model (SCATB), Multistep Direct (ORION + TRISTAN), NVWY Multistep Compound, and the full featured Hauser-Feshbach model. Heavy Ion fusion cross section can be calculated within the simplified coupled channels approach (CCFUS). A comprehensive library of input parameters covers nuclear masses, optical model parameters, ground state deformations, discrete levels and decay schemes, level densities, fission barriers (BARFIT), moments of inertia (MOMFIT), and {gamma}-ray strength functions. Effects of the dynamic deformation of a fast rotating nucleus can be taken into account in the calculations. The results can be converted into the ENDF-VI format using the accompanying code EMPEND. The package contains the full EXFOR library of experimental data. Relevant EXFOR entries are automatically retrieved during the calculations. Plots comparing experimental results with the calculated ones can be produced using X4TOC4 and PLOTC4 codes linked to the rest of the system through bash-shell (UNIX) scripts. The graphic user interface written in Tcl/Tk is provided. (author)

A Comparative Study on the Sorption Characteristics of Pb(II and Hg(II onto Activated Carbon

Directory of Open Access Journals (Sweden)

N. Muthulakshmi Andal

2010-01-01

Full Text Available Biosorption equilibrium and kinetics of Pb(II and Hg(II on coconut shell carbon (CSC were investigated by batch equilibration method. The effects of pH, adsorbent dosage, contact time, temperature and initial concentration of Pb(II and Hg(II on the activated carbon of coconut shell wastes were studied. Maximum adsorption of Pb(II occurred at pH 4.5 and Hg(II at pH 6. The sorptive mechanism followed the pseudo second order kinetics. The equilibrium data were analysed by Langmuir, Freundlich and Dubinin-Radushkevich isotherm models. The equilibration data fitted well with both Langmuir and Freundlich isotherm model. The Langmuir adsorption capacity for Pb(II was greater than Hg(II. The mean free energy of adsorption calculated from Dubinin-Radushkevich (D-R isotherm model indicated that the adsorption of metal ions was found to be by chemical ion exchange. Thermodynamic parameter showed that the sorption process of Pb(II onto SDC was feasible, spontaneous and endothermic under studied conditions. A comparison was evaluated for the two metals.

Universally sloppy parameter sensitivities in systems biology models.

Directory of Open Access Journals (Sweden)

Ryan N Gutenkunst

2007-10-01

Full Text Available Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a "sloppy" spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.

Universally sloppy parameter sensitivities in systems biology models.

Science.gov (United States)

Gutenkunst, Ryan N; Waterfall, Joshua J; Casey, Fergal P; Brown, Kevin S; Myers, Christopher R; Sethna, James P

2007-10-01

Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a "sloppy" spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.

Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models.

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.

Systematic parameter inference in stochastic mesoscopic modeling

Energy Technology Data Exchange (ETDEWEB)

Lei, Huan; Yang, Xiu [Pacific Northwest National Laboratory, Richland, WA 99352 (United States); Li, Zhen [Division of Applied Mathematics, Brown University, Providence, RI 02912 (United States); Karniadakis, George Em, E-mail: george_karniadakis@brown.edu [Division of Applied Mathematics, Brown University, Providence, RI 02912 (United States)

2017-02-01

We propose a method to efficiently determine the optimal coarse-grained force field in mesoscopic stochastic simulations of Newtonian fluid and polymer melt systems modeled by dissipative particle dynamics (DPD) and energy conserving dissipative particle dynamics (eDPD). The response surfaces of various target properties (viscosity, diffusivity, pressure, etc.) with respect to model parameters are constructed based on the generalized polynomial chaos (gPC) expansion using simulation results on sampling points (e.g., individual parameter sets). To alleviate the computational cost to evaluate the target properties, we employ the compressive sensing method to compute the coefficients of the dominant gPC terms given the prior knowledge that the coefficients are “sparse”. The proposed method shows comparable accuracy with the standard probabilistic collocation method (PCM) while it imposes a much weaker restriction on the number of the simulation samples especially for systems with high dimensional parametric space. Fully access to the response surfaces within the confidence range enables us to infer the optimal force parameters given the desirable values of target properties at the macroscopic scale. Moreover, it enables us to investigate the intrinsic relationship between the model parameters, identify possible degeneracies in the parameter space, and optimize the model by eliminating model redundancies. The proposed method provides an efficient alternative approach for constructing mesoscopic models by inferring model parameters to recover target properties of the physics systems (e.g., from experimental measurements), where those force field parameters and formulation cannot be derived from the microscopic level in a straight forward way.

The "covariation method" for estimating the parameters of the standard Dynamic Energy Budget model II: Properties and preliminary patterns

Science.gov (United States)

Lika, Konstadia; Kearney, Michael R.; Kooijman, Sebastiaan A. L. M.

2011-11-01

The covariation method for estimating the parameters of the standard Dynamic Energy Budget (DEB) model provides a single-step method of accessing all the core DEB parameters from commonly available empirical data. In this study, we assess the robustness of this parameter estimation procedure and analyse the role of pseudo-data using elasticity coefficients. In particular, we compare the performance of Maximum Likelihood (ML) vs. Weighted Least Squares (WLS) approaches and find that the two approaches tend to converge in performance as the number of uni-variate data sets increases, but that WLS is more robust when data sets comprise single points (zero-variate data). The efficiency of the approach is shown to be high, and the prior parameter estimates (pseudo-data) have very little influence if the real data contain information about the parameter values. For instance, the effects of the pseudo-value for the allocation fraction κ is reduced when there is information for both growth and reproduction, that for the energy conductance is reduced when information on age at birth and puberty is given, and the effects of the pseudo-value for the maturity maintenance rate coefficient are insignificant. The estimation of some parameters (e.g., the zoom factor and the shape coefficient) requires little information, while that of others (e.g., maturity maintenance rate, puberty threshold and reproduction efficiency) require data at several food levels. The generality of the standard DEB model, in combination with the estimation of all of its parameters, allows comparison of species on the basis of parameter values. We discuss a number of preliminary patterns emerging from the present collection of parameter estimates across a wide variety of taxa. We make the observation that the estimated value of the fraction κ of mobilised reserve that is allocated to soma is far away from the value that maximises reproduction. We recognise this as the reason why two very different

Benchmarking of copper(II) LFMM parameters for studying amyloid-β peptides.

Science.gov (United States)

Mutter, Shaun T; Deeth, Robert J; Turner, Matthew; Platts, James A

2018-04-01

Ligand field molecular mechanics (LFMM) parameters have been benchmarked for copper (II) bound to the amyloid-β 1-16 peptide fragment. Several density functional theory (DFT) optimised small test models, representative of different possible copper coordination modes, have been used to test the accuracy of the LFMM copper bond lengths and angles, resulting in errors typically less than 0.1 Å and 5°. Ligand field molecular dynamics (LFMD) simulations have been carried out on the copper bound amyloid-β 1-16 peptide and snapshots extracted from the subsequent trajectory. Snapshots have been optimised using DFT and the semi-empirical PM7 method resulting in good agreement against the LFMM calculated geometry. Analysis of substructures within snapshots shows that the larger contribution of geometrical difference, as measured by RMSD, lies within the peptide backbone, arising from differences in DFT and AMBER, and the copper coordination sphere is reproduced well by LFMM. PM7 performs excellently against LFMM with an average RMSD of 0.2 Å over 21 tested snapshots. Further analysis of the LFMD trajectory shows that copper bond lengths and angles have only small deviations from average values, with the exception of a carbonyl moiety from the N-terminus, which can act as a weakly bound fifth ligand.

System modeling and simulation at EBR-II

International Nuclear Information System (INIS)

Dean, E.M.; Lehto, W.K.; Larson, H.A.

1986-01-01

The codes being developed and verified using EBR-II data are the NATDEMO, DSNP and CSYRED. NATDEMO is a variation of the Westinghouse DEMO code coupled to the NATCON code previously used to simulate perturbations of reactor flow and inlet temperature and loss-of-flow transients leading to natural convection in EBR-II. CSYRED uses the Continuous System Modeling Program (CSMP) to simulate the EBR-II core, including power, temperature, control-rod movement reactivity effects and flow and is used primarily to model reactivity induced power transients. The Dynamic Simulator for Nuclear Power Plants (DSNP) allows a whole plant, thermal-hydraulic simulation using specific component and system models called from libraries. It has been used to simulate flow coastdown transients, reactivity insertion events and balance-of-plant perturbations

Kinetic modelling for zinc (II) ions biosorption onto Luffa cylindrica

International Nuclear Information System (INIS)

Oboh, I.; Aluyor, E.; Audu, T.

2015-01-01

The biosorption of Zinc (II) ions onto a biomaterial - Luffa cylindrica has been studied. This biomaterial was characterized by elemental analysis, surface area, pore size distribution, scanning electron microscopy, and the biomaterial before and after sorption, was characterized by Fourier Transform Infra Red (FTIR) spectrometer. The kinetic nonlinear models fitted were Pseudo-first order, Pseudo-second order and Intra-particle diffusion. A comparison of non-linear regression method in selecting the kinetic model was made. Four error functions, namely coefficient of determination (R 2 ), hybrid fractional error function (HYBRID), average relative error (ARE), and sum of the errors squared (ERRSQ), were used to predict the parameters of the kinetic models. The strength of this study is that a biomaterial with wide distribution particularly in the tropical world and which occurs as waste material could be put into effective utilization as a biosorbent to address a crucial environmental problem

Test models for improving filtering with model errors through stochastic parameter estimation

International Nuclear Information System (INIS)

Gershgorin, B.; Harlim, J.; Majda, A.J.

2010-01-01

The filtering skill for turbulent signals from nature is often limited by model errors created by utilizing an imperfect model for filtering. Updating the parameters in the imperfect model through stochastic parameter estimation is one way to increase filtering skill and model performance. Here a suite of stringent test models for filtering with stochastic parameter estimation is developed based on the Stochastic Parameterization Extended Kalman Filter (SPEKF). These new SPEKF-algorithms systematically correct both multiplicative and additive biases and involve exact formulas for propagating the mean and covariance including the parameters in the test model. A comprehensive study is presented of robust parameter regimes for increasing filtering skill through stochastic parameter estimation for turbulent signals as the observation time and observation noise are varied and even when the forcing is incorrectly specified. The results here provide useful guidelines for filtering turbulent signals in more complex systems with significant model errors.

New LUX and PandaX-II results illuminating the simplest Higgs-portal dark matter models

International Nuclear Information System (INIS)

He, Xiao-Gang; Tandean, Jusak

2016-01-01

Direct searches for dark matter (DM) by the LUX and PandaX-II Collaborations employing xenon-based detectors have recently come up with the most stringent limits to date on the spin-independent elastic scattering of DM off nucleons. For Higgs-portal scalar DM models, the new results have precluded any possibility of accommodating low-mass DM as suggested by the DAMA and CDMS II Si experiments utilizing other target materials, even after invoking isospin-violating DM interactions with nucleons. In the simplest model, SM+D, which is the standard model plus a real singlet scalar named darkon acting as the DM candidate, the LUX and PandaX-II limits rule out DM masses roughly from 4 to 450 GeV, except a small range around the resonance point at half of the Higgs mass where the interaction cross-section is near the neutrino-background floor. In the THDM II+D, which is the type-II two-Higgs-doublet model combined with a darkon, the region excluded in the SM+D by the direct searches can be recovered due to suppression of the DM effective interactions with nucleons at some values of the ratios of Higgs couplings to the up and down quarks, making the interactions significantly isospin-violating. However, in either model, if the 125-GeV Higgs boson is the portal between the dark and SM sectors, DM masses less than 50 GeV or so are already ruled out by the LHC constraint on the Higgs invisible decay. In the THDM II+D, if the heavier CP-even Higgs boson is the portal, theoretical restrictions from perturbativity, vacuum stability, and unitarity requirements turn out to be important instead and exclude much of the region below 100 GeV. For larger DM masses, the THDM II+D has plentiful parameter space that corresponds to interaction cross-sections under the neutrino-background floor and therefore is likely to be beyond the reach of future direct searches without directional sensitivity.

Efficacy of the semiempirical sparkle model as compared to ECP ab-initio calculations for the prediction of ligand field parameters of europium (III) complexes

International Nuclear Information System (INIS)

Freire, Ricardo O.; Rocha, Gerd B.; Albuquerque, Rodrigo Q.; Simas, Alfredo M.

2005-01-01

The second version of the sparkle model for the calculation of lanthanide complexes (SMLC II) as well as ab-initio calculations (HF/STO-3G and HF/3-21G) have been used to calculate the geometries of a series of europium (III) complexes with different coordination numbers (CN=7, 8 and 9), ligating atoms (O and N) and ligands (mono, bi and polydentate). The so-called ligand field parameters, Bqk's, have been calculated from both SMLC II and ab-initio optimized structures and compared to the ones calculated from crystallographic data. The results show that the SMLC II model represents a significant improvement over the previous version (SMLC) and has given good results when compared to ab-initio methods, which demand a much higher computational effort. Indeed, ab-initio methods take around a hundred times more computing time than SMLC. As such, our results indicate that our sparkle model can be a very useful and a fast tool when applied to the prediction of both ground state geometries and ligand field parameters of europium (III) complexes

Multi-metals column adsorption of lead(II), cadmium(II) and manganese(II) onto natural bentonite clay.

Science.gov (United States)

Alexander, Jock Asanja; Surajudeen, Abdulsalam; Aliyu, El-Nafaty Usman; Omeiza, Aroke Umar; Zaini, Muhammad Abbas Ahmad

2017-10-01

The present work was aimed at evaluating the multi-metals column adsorption of lead(II), cadmium(II) and manganese(II) ions onto natural bentonite. The bentonite clay adsorbent was characterized for physical and chemical properties using X-ray diffraction, X-ray fluorescence, Brunauer-Emmett-Teller surface area and cation exchange capacity. The column performance was evaluated using adsorbent bed height of 5.0 cm, with varying influent concentrations (10 mg/L and 50 mg/L) and flow rates (1.4 mL/min and 2.4 mL/min). The result shows that the breakthrough time for all metal ions ranged from 50 to 480 minutes. The maximum adsorption capacity was obtained at initial concentration of 10 mg/L and flow rate of 1.4 mL/min, with 2.22 mg/g of lead(II), 1.71 mg/g of cadmium(II) and 0.37 mg/g of manganese(II). The order of metal ions removal by natural bentonite is lead(II) > cadmium(II) > manganese(II). The sorption performance and the dynamic behaviour of the column were predicted using Adams-Bohart, Thomas, and Yoon-Nelson models. The linear regression analysis demonstrated that the Thomas and Yoon-Nelson models fitted well with the column adsorption data for all metal ions. The natural bentonite was effective for the treatment of wastewater laden with multi-metals, and the process parameters obtained from this work can be used at the industrial scale.

Exploiting intrinsic fluctuations to identify model parameters.

Science.gov (United States)

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.

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

ECOCLIMAP-II/Europe: a twofold database of ecosystems and surface parameters at 1-km resolution based on satellite information for use in land surface, meteorological and climate models

Science.gov (United States)

Faroux, S.; Kaptué Tchuenté, A. T.; Roujean, J.-L.; Masson, V.; Martin, E.; Le Moigne, P.

2012-11-01

The overall objective of the present study is to introduce the new ECOCLIMAP-II database for Europe, which is an upgrade for this region of the former initiative, ECOCLIMAP-I, already implemented at global scale. The ECOCLIMAP programme is a dual database at 1-km resolution that includes an ecosystem classification and a coherent set of land surface parameters that are primarily mandatory in meteorological modelling (notably leaf area index and albedo). Hence, the aim of this innovative physiography is to enhance the quality of initialisation and impose some surface attributes within the scope of weather forecasting and climate related studies. The strategy for implementing ECOCLIMAP-II is to depart from prevalent land cover products such as CLC2000 (Corine Land Cover) and GLC2000 (Global Land Cover) by splitting existing classes into new classes that possess a better regional character by virtue of the climatic environment (latitude, proximity to the sea, topography). The leaf area index (LAI) from MODIS and NDVI from SPOT/Vegetation yield the two proxy variables that were considered here in order to perform a multi-year trimmed analysis between 1999 and 2005 using the K-means method. Further, meteorological applications require each land cover type to appear as a partition of fractions of 4 main surface types or tiles (nature, water bodies, sea, urban areas) and, inside the nature tile, fractions of 12 Plant Functional Types (PFTs) representing generic vegetation types - principally broadleaf forest, needleleaf forest, C3 and C4 crops, grassland and bare land - as incorporated by the SVAT model ISBA developed at Météo France. This landscape division also forms the cornerstone of a validation exercise. The new ECOCLIMAP-II can be verified with auxiliary land cover products at very fine and coarse resolutions by means of versatile land occupation nomenclatures.

PARALLEL MEASUREMENT AND MODELING OF TRANSPORT IN THE DARHT II BEAMLINE ON ETA II

International Nuclear Information System (INIS)

Chambers, F W; Raymond, B A; Falabella, S; Lee, B S; Richardson, R A; Weir, J T; Davis, H A; Schultze, M E

2005-01-01

To successfully tune the DARHT II transport beamline requires the close coupling of a model of the beam transport and the measurement of the beam observables as the beam conditions and magnet settings are varied. For the ETA II experiment using the DARHT II beamline components this was achieved using the SUICIDE (Simple User Interface Connecting to an Integrated Data Environment) data analysis environment and the FITS (Fully Integrated Transport Simulation) model. The SUICIDE environment has direct access to the experimental beam transport data at acquisition and the FITS predictions of the transport for immediate comparison. The FITS model is coupled into the control system where it can read magnet current settings for real time modeling. We find this integrated coupling is essential for model verification and the successful development of a tuning aid for the efficient convergence on a useable tune. We show the real time comparisons of simulation and experiment and explore the successes and limitations of this close coupled approach

Comparison of midlatitude ionospheric F region peak parameters and topside Ne profiles from IRI2012 model prediction with ground-based ionosonde and Alouette II observations

Science.gov (United States)

Gordiyenko, G. I.; Yakovets, A. F.

2017-07-01

The ionospheric F2 peak parameters recorded by a ground-based ionosonde at the midlatitude station Alma-Ata [43.25N, 76.92E] were compared with those obtained using the latest version of the IRI model (http://omniweb.gsfc.nasa.gov/vitmo/iri2012_vitmo.html). It was found that for the Alma-Ata (Kazakhstan) location, the IRI2012 model describes well the morphology of seasonal and diurnal variations of the ionospheric critical frequency (foF2) and peak density height (hmF2) monthly medians. The model errors in the median foF2 prediction (percentage deviations between the median foF2 values and their model predictions) were found to vary approximately in the range from about -20% to 34% and showed a stable overestimation in the median foF2 values for daytime in January and July and underestimation for day- and nighttime hours in the equinoctial months. The comparison between the ionosonde hmF2 and IRI results clearly showed that the IRI overestimates the nighttime hmF2 values for March and September months, and the difference is up to 30 km. The daytime Alma-Ata hmF2 data were found to be close to the IRI predictions (deviations are approximately ±10-15 km) in winter and equinoctial months, except in July when the observed hmF2 values were much more (from approximately 50-200 km). The comparison between the Alouette foF2 data and IRI predictions showed mixed results. In particular, the Alouette foF2 data showed a tendency to be overestimated for daytime in winter months similar to the ionosonde data; however, the overestimated foF2 values for nighttime in the autumn equinox were in disagreement with the ionosonde observations. There were large deviations between the observed hmF2 values and their model predictions. The largest deviations were found during winter and summer (up to -90 km). The comparison of the Alouette II electron density profiles with those predicted by the adapted IRI2012 model in the altitude range hmF2 of the satellite position showed a great

Parameter discovery in stochastic biological models using simulated annealing and statistical model checking.

Science.gov (United States)

Hussain, Faraz; Jha, Sumit K; Jha, Susmit; Langmead, Christopher J

2014-01-01

Stochastic models are increasingly used to study the behaviour of biochemical systems. While the structure of such models is often readily available from first principles, unknown quantitative features of the model are incorporated into the model as parameters. Algorithmic discovery of parameter values from experimentally observed facts remains a challenge for the computational systems biology community. We present a new parameter discovery algorithm that uses simulated annealing, sequential hypothesis testing, and statistical model checking to learn the parameters in a stochastic model. We apply our technique to a model of glucose and insulin metabolism used for in-silico validation of artificial pancreata and demonstrate its effectiveness by developing parallel CUDA-based implementation for parameter synthesis in this model.

Establishing statistical models of manufacturing parameters

International Nuclear Information System (INIS)

Senevat, J.; Pape, J.L.; Deshayes, J.F.

1991-01-01

This paper reports on the effect of pilgering and cold-work parameters on contractile strain ratio and mechanical properties that were investigated using a large population of Zircaloy tubes. Statistical models were established between: contractile strain ratio and tooling parameters, mechanical properties (tensile test, creep test) and cold-work parameters, and mechanical properties and stress-relieving temperature

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. ......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 another in which the cointegrating relations are estimated recursively from a likelihood function, where the short-run parameters have been concentrated out. We suggest graphical procedures based on recursively estimated eigenvalues to evaluate the constancy of the long-run parameters in the model...

Edge Modeling by Two Blur Parameters in Varying Contrasts.

Science.gov (United States)

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.

Biosorption kinetics of Cd (II), Cr (III) and Pb (II) in aqueous solutions by olive stone

OpenAIRE

M. Calero; F. Hernáinz; G. Blázquez; M. A. Martín-Lara; G. Tenorio

2009-01-01

A by-product from olive oil production, olive stone, was investigated for the removal of Cd (II), Cr (III) and Pb (II) from aqueous solutions. The kinetics of biosorption are studied, analyzing the effect of the initial concentration of metal and temperature. Pseudo-first-order, pseudo-second-order, Elovich and intraparticle diffusion models have been used to represent the kinetics of the process and obtain the main kinetic parameters. The results show that the pseudo-second order model is th...

Identifyability measures to select the parameters to be estimated in a solid-state fermentation distributed parameter model.

Science.gov (United States)

da Silveira, Christian L; Mazutti, Marcio A; Salau, Nina P G

2016-07-08

Process modeling can lead to of advantages such as helping in process control, reducing process costs and product quality improvement. This work proposes a solid-state fermentation distributed parameter model composed by seven differential equations with seventeen parameters to represent the process. Also, parameters estimation with a parameters identifyability analysis (PIA) is performed to build an accurate model with optimum parameters. Statistical tests were made to verify the model accuracy with the estimated parameters considering different assumptions. The results have shown that the model assuming substrate inhibition better represents the process. It was also shown that eight from the seventeen original model parameters were nonidentifiable and better results were obtained with the removal of these parameters from the estimation procedure. Therefore, PIA can be useful to estimation procedure, since it may reduce the number of parameters that can be evaluated. Further, PIA improved the model results, showing to be an important procedure to be taken. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:905-917, 2016. © 2016 American Institute of Chemical Engineers.

Reactive Transport Modeling of Microbe-mediated Fe (II) Oxidation for Enhanced Oil Recovery

Science.gov (United States)

Surasani, V.; Li, L.

2011-12-01

Microbially Enhanced Oil Recovery (MEOR) aims to improve the recovery of entrapped heavy oil in depleted reservoirs using microbe-based technology. Reservoir ecosystems often contain diverse microbial communities those can interact with subsurface fluids and minerals through a network of nutrients and energy fluxes. Microbe-mediated reactions products include gases, biosurfactants, biopolymers those can alter the properties of oil and interfacial interactions between oil, brine, and rocks. In addition, the produced biomass and mineral precipitates can change the reservoir permeability profile and increase sweeping efficiency. Under subsurface conditions, the injection of nitrate and Fe (II) as the electron acceptor and donor allows bacteria to grow. The reaction products include minerals such as Fe(OH)3 and nitrogen containing gases. These reaction products can have large impact on oil and reservoir properties and can enhance the recovery of trapped oil. This work aims to understand the Fe(II) oxidation by nitrate under conditions relevant to MEOR. Reactive transport modeling is used to simulate the fluid flow, transport, and reactions involved in this process. Here we developed a complex reactive network for microbial mediated nitrate-dependent Fe (II) oxidation that involves both thermodynamic controlled aqueous reactions and kinetic controlled Fe (II) mineral reaction. Reactive transport modeling is used to understand and quantify the coupling between flow, transport, and reaction processes. Our results identify key parameter controls those are important for the alteration of permeability profile under field conditions.

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

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

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...... 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...

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)

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...

A simulation of water pollution model parameter estimation

Science.gov (United States)

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.

Identification of ecosystem parameters by SDE-modelling

DEFF Research Database (Denmark)

Stochastic differential equations (SDEs) for ecosystem modelling have attracted increasing attention during recent years. The modelling has mostly been through simulation experiments in order to analyse how system noise propagates through the ordinary differential equation formulation of ecosystem...... models. Estimation of parameters in SDEs is, however, possible by combining Kalman filter techniques and likelihood estimation. By modelling parameters as random walks it is possible to identify linear as well as non-linear interactions between ecosystem components. By formulating a simple linear SDE...

Spatio-temporal modeling of nonlinear distributed parameter systems

CERN Document Server

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

Models for estimating photosynthesis parameters from in situ production profiles

Science.gov (United States)

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

Kinetic and isotherm modeling of Cd (II) adsorption by L-cysteine functionalized multi-walled carbon nanotubes as adsorbent.

Science.gov (United States)

Taghavi, Mahmoud; Zazouli, Mohammad Ali; Yousefi, Zabihollah; Akbari-adergani, Behrouz

2015-11-01

In this study, multi-walled carbon nanotubes were functionalized by L-cysteine to show the kinetic and isotherm modeling of Cd (II) ions onto L-cysteine functionalized multi-walled carbon nanotubes. The adsorption behavior of Cd (II) ion was studied by varying parameters including dose of L-MWCNTs, contact time, and cadmium concentration. Equilibrium adsorption isotherms and kinetics were also investigated based on Cd (II) adsorption tests. The results showed that an increase in contact time and adsorbent dosage resulted in increase of the adsorption rate. The optimum condition of the Cd (II) removal process was found at pH=7.0, 15 mg/L L-MWCNTs dosage, 6 mg/L cadmium concentration, and contact time of 60 min. The removal percent was equal to 89.56 at optimum condition. Langmuir and Freundlich models were employed to analyze the experimental data. The data showed well fitting with the Langmuir model (R2=0.994) with q max of 43.47 mg/g. Analyzing the kinetic data by the pseudo-first-order and pseudo-second-order equations revealed that the adsorption of cadmium using L-MWSNTs following the pseudo-second-order kinetic model with correlation coefficients (R2) equals to 0.998, 0.992, and 0.998 for 3, 6, and 9 mg/L Cd (II) concentrations, respectively. The experimental data fitted very well with the pseudo-second-order. Overall, treatment of polluted solution to Cd (II) by adsorption process using L-MWCNT can be considered as an effective technology.

GEMSFITS: Code package for optimization of geochemical model parameters and inverse modeling

International Nuclear Information System (INIS)

Miron, George D.; Kulik, Dmitrii A.; Dmytrieva, Svitlana V.; Wagner, Thomas

2015-01-01

Highlights: • Tool for generating consistent parameters against various types of experiments. • Handles a large number of experimental data and parameters (is parallelized). • Has a graphical interface and can perform statistical analysis on the parameters. • Tested on fitting the standard state Gibbs free energies of aqueous Al species. • Example on fitting interaction parameters of mixing models and thermobarometry. - Abstract: GEMSFITS is a new code package for fitting internally consistent input parameters of GEM (Gibbs Energy Minimization) geochemical–thermodynamic models against various types of experimental or geochemical data, and for performing inverse modeling tasks. It consists of the gemsfit2 (parameter optimizer) and gfshell2 (graphical user interface) programs both accessing a NoSQL database, all developed with flexibility, generality, efficiency, and user friendliness in mind. The parameter optimizer gemsfit2 includes the GEMS3K chemical speciation solver ( (http://gems.web.psi.ch/GEMS3K)), which features a comprehensive suite of non-ideal activity- and equation-of-state models of solution phases (aqueous electrolyte, gas and fluid mixtures, solid solutions, (ad)sorption. The gemsfit2 code uses the robust open-source NLopt library for parameter fitting, which provides a selection between several nonlinear optimization algorithms (global, local, gradient-based), and supports large-scale parallelization. The gemsfit2 code can also perform comprehensive statistical analysis of the fitted parameters (basic statistics, sensitivity, Monte Carlo confidence intervals), thus supporting the user with powerful tools for evaluating the quality of the fits and the physical significance of the model parameters. The gfshell2 code provides menu-driven setup of optimization options (data selection, properties to fit and their constraints, measured properties to compare with computed counterparts, and statistics). The practical utility, efficiency, and

Identification of parameters of discrete-continuous models

International Nuclear Information System (INIS)

Cekus, Dawid; Warys, Pawel

2015-01-01

In the paper, the parameters of a discrete-continuous model have been identified on the basis of experimental investigations and formulation of optimization problem. The discrete-continuous model represents a cantilever stepped Timoshenko beam. The mathematical model has been formulated and solved according to the Lagrange multiplier formalism. Optimization has been based on the genetic algorithm. The presented proceeding’s stages make the identification of any parameters of discrete-continuous systems possible

Identification of parameters of discrete-continuous models

Energy Technology Data Exchange (ETDEWEB)

Cekus, Dawid, E-mail: cekus@imipkm.pcz.pl; Warys, Pawel, E-mail: warys@imipkm.pcz.pl [Institute of Mechanics and Machine Design Foundations, Czestochowa University of Technology, Dabrowskiego 73, 42-201 Czestochowa (Poland)

2015-03-10

In the paper, the parameters of a discrete-continuous model have been identified on the basis of experimental investigations and formulation of optimization problem. The discrete-continuous model represents a cantilever stepped Timoshenko beam. The mathematical model has been formulated and solved according to the Lagrange multiplier formalism. Optimization has been based on the genetic algorithm. The presented proceeding’s stages make the identification of any parameters of discrete-continuous systems possible.

Prediction of equilibrium parameters of adsorption of lead (II) ions onto diatomite

Science.gov (United States)

Salman, Taylan; Ardalı, Yüksel; Gamze Turan, N.

2013-04-01

Heavy metals from industrial wastewaters are one of the most important environmental issues to be solved today. Due to their toxicity and nonbiodegradable nature, heavy metals cause environmental and public health problems. Various techniques have been developed to remove heavy metals from aqueous solutions. These include chemical precipitation, reverse osmosis, ion Exchange and adsorption. Among them, adsorption is considered to be a particularly competitive and effective process for the removal of heavy metals from aqueous solutions. There is growing interest in using low cost, commercially available materials for the adsorption of heavy metals. Diatomite is a siliceous sedimentary rock having an amorphous form of silica (SiO2. nH2O) containing a small amount of microcrystalline material. It has unique combination of physical and chemical properties such as high porosity, high permeability, small particle size, large surface area, and low thermal conductivity. In addition, it is available in Turkey and in various locations around the world. Therefore, diatomite has been successfully used as adsorbent for the removal of heavy metals. The aim of the study is to investigate the adsorption properties of diatomite. The equilibrium adsorption data were applied to the Langmuir, Freundlich and Dubinin-Radushkevic (D-R) isotherm models. Adsorption experiments were performed under batch process, using Pb (II) initial concentration, pH of solution and contact time as variables. The results demonstrated that the adsorption of Pb (II) was strongly dependent on pH of solution. The effect of pH on adsorption of Pb(II) on diatomite was conducted by varying pH from 2 to 12 at 20 oC. In the pH range of 2.0-4.0, the adsorption percentage increases slightly as the pH increasing. At pH>4, the adsorption percentage decreases with increasing pH because hydrolysis product and the precipitation begin to play an important role in the sorption of Pb (II). At pH4, the maximum adsorption

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

Agricultural and Environmental Input Parameters for the Biosphere Model

International Nuclear Information System (INIS)

Kaylie Rasmuson; Kurt Rautenstrauch

2003-01-01

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

Verification Techniques for Parameter Selection and Bayesian Model Calibration Presented for an HIV Model

Science.gov (United States)

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

Zener Diode Compact Model Parameter Extraction Using Xyce-Dakota Optimization.

Energy Technology Data Exchange (ETDEWEB)

Buchheit, Thomas E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Wilcox, Ian Zachary [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Sandoval, Andrew J [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Reza, Shahed [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-12-01

This report presents a detailed process for compact model parameter extraction for DC circuit Zener diodes. Following the traditional approach of Zener diode parameter extraction, circuit model representation is defined and then used to capture the different operational regions of a real diode's electrical behavior. The circuit model contains 9 parameters represented by resistors and characteristic diodes as circuit model elements. The process of initial parameter extraction, the identification of parameter values for the circuit model elements, is presented in a way that isolates the dependencies between certain electrical parameters and highlights both the empirical nature of the extraction and portions of the real diode physical behavior which of the parameters are intended to represent. Optimization of the parameters, a necessary part of a robost parameter extraction process, is demonstrated using a 'Xyce-Dakota' workflow, discussed in more detail in the report. Among other realizations during this systematic approach of electrical model parameter extraction, non-physical solutions are possible and can be difficult to avoid because of the interdependencies between the different parameters. The process steps described are fairly general and can be leveraged for other types of semiconductor device model extractions. Also included in the report are recommendations for experiment setups for generating optimum dataset for model extraction and the Parameter Identification and Ranking Table (PIRT) for Zener diodes.

Brownian motion model with stochastic parameters for asset prices

Science.gov (United States)

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.

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.

Deductive multiscale simulation using order parameters

Science.gov (United States)

Ortoleva, Peter J.

2017-05-16

Illustrative embodiments of systems and methods for the deductive multiscale simulation of macromolecules are disclosed. In one illustrative embodiment, a deductive multiscale simulation method may include (i) constructing a set of order parameters that model one or more structural characteristics of a macromolecule, (ii) simulating an ensemble of atomistic configurations for the macromolecule using instantaneous values of the set of order parameters, (iii) simulating thermal-average forces and diffusivities for the ensemble of atomistic configurations, and (iv) evolving the set of order parameters via Langevin dynamics using the thermal-average forces and diffusivities.

Seven-parameter statistical model for BRDF in the UV band.

Science.gov (United States)

Bai, Lu; Wu, Zhensen; Zou, Xiren; Cao, Yunhua

2012-05-21

A new semi-empirical seven-parameter BRDF model is developed in the UV band using experimentally measured data. The model is based on the five-parameter model of Wu and the fourteen-parameter model of Renhorn and Boreman. Surface scatter, bulk scatter and retro-reflection scatter are considered. An optimizing modeling method, the artificial immune network genetic algorithm, is used to fit the BRDF measurement data over a wide range of incident angles. The calculation time and accuracy of the five- and seven-parameter models are compared. After fixing the seven parameters, the model can well describe scattering data in the UV band.

Lumped-parameter Model of a Bucket Foundation

DEFF Research Database (Denmark)

Andersen, Lars; Ibsen, Lars Bo; Liingaard, Morten

2009-01-01

efficient model that can be applied in aero-elastic codes for fast evaluation of the dynamic structural response of wind turbines. The target solutions, utilised for calibration of the lumped-parameter models, are obtained by a coupled finite-element/boundaryelement scheme in the frequency domain......, and the quality of the models are tested in the time and frequency domains. It is found that precise results are achieved by lumped-parameter models with two to four internal degrees of freedom per displacement or rotation of the foundation. Further, coupling between the horizontal sliding and rocking cannot...

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)

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.

Parameter and model uncertainty in a life-table model for fine particles (PM2.5): a statistical modeling study.

Science.gov (United States)

Tainio, Marko; Tuomisto, Jouni T; Hänninen, Otto; Ruuskanen, Juhani; Jantunen, Matti J; Pekkanen, Juha

2007-08-23

The estimation of health impacts involves often uncertain input variables and assumptions which have to be incorporated into the model structure. These uncertainties may have significant effects on the results obtained with model, and, thus, on decision making. Fine particles (PM2.5) are believed to cause major health impacts, and, consequently, uncertainties in their health impact assessment have clear relevance to policy-making. We studied the effects of various uncertain input variables by building a life-table model for fine particles. Life-expectancy of the Helsinki metropolitan area population and the change in life-expectancy due to fine particle exposures were predicted using a life-table model. A number of parameter and model uncertainties were estimated. Sensitivity analysis for input variables was performed by calculating rank-order correlations between input and output variables. The studied model uncertainties were (i) plausibility of mortality outcomes and (ii) lag, and parameter uncertainties (iii) exposure-response coefficients for different mortality outcomes, and (iv) exposure estimates for different age groups. The monetary value of the years-of-life-lost and the relative importance of the uncertainties related to monetary valuation were predicted to compare the relative importance of the monetary valuation on the health effect uncertainties. The magnitude of the health effects costs depended mostly on discount rate, exposure-response coefficient, and plausibility of the cardiopulmonary mortality. Other mortality outcomes (lung cancer, other non-accidental and infant mortality) and lag had only minor impact on the output. The results highlight the importance of the uncertainties associated with cardiopulmonary mortality in the fine particle impact assessment when compared with other uncertainties. When estimating life-expectancy, the estimates used for cardiopulmonary exposure-response coefficient, discount rate, and plausibility require careful

Parameter and model uncertainty in a life-table model for fine particles (PM2.5: a statistical modeling study

Directory of Open Access Journals (Sweden)

Jantunen Matti J

2007-08-01

Full Text Available Abstract Background The estimation of health impacts involves often uncertain input variables and assumptions which have to be incorporated into the model structure. These uncertainties may have significant effects on the results obtained with model, and, thus, on decision making. Fine particles (PM2.5 are believed to cause major health impacts, and, consequently, uncertainties in their health impact assessment have clear relevance to policy-making. We studied the effects of various uncertain input variables by building a life-table model for fine particles. Methods Life-expectancy of the Helsinki metropolitan area population and the change in life-expectancy due to fine particle exposures were predicted using a life-table model. A number of parameter and model uncertainties were estimated. Sensitivity analysis for input variables was performed by calculating rank-order correlations between input and output variables. The studied model uncertainties were (i plausibility of mortality outcomes and (ii lag, and parameter uncertainties (iii exposure-response coefficients for different mortality outcomes, and (iv exposure estimates for different age groups. The monetary value of the years-of-life-lost and the relative importance of the uncertainties related to monetary valuation were predicted to compare the relative importance of the monetary valuation on the health effect uncertainties. Results The magnitude of the health effects costs depended mostly on discount rate, exposure-response coefficient, and plausibility of the cardiopulmonary mortality. Other mortality outcomes (lung cancer, other non-accidental and infant mortality and lag had only minor impact on the output. The results highlight the importance of the uncertainties associated with cardiopulmonary mortality in the fine particle impact assessment when compared with other uncertainties. Conclusion When estimating life-expectancy, the estimates used for cardiopulmonary exposure

The mobilisation model and parameter sensitivity

International Nuclear Information System (INIS)

Blok, B.M.

1993-12-01

In the PRObabillistic Safety Assessment (PROSA) of radioactive waste in a salt repository one of the nuclide release scenario's is the subrosion scenario. A new subrosion model SUBRECN has been developed. In this model the combined effect of a depth-dependent subrosion, glass dissolution, and salt rise has been taken into account. The subrosion model SUBRECN and the implementation of this model in the German computer program EMOS4 is presented. A new computer program PANTER is derived from EMOS4. PANTER models releases of radionuclides via subrosion from a disposal site in a salt pillar into the biosphere. For uncertainty and sensitivity analyses the new subrosion model Latin Hypercube Sampling has been used for determine the different values for the uncertain parameters. The influence of the uncertainty in the parameters on the dose calculations has been investigated by the following sensitivity techniques: Spearman Rank Correlation Coefficients, Partial Rank Correlation Coefficients, Standardised Rank Regression Coefficients, and the Smirnov Test. (orig./HP)

ECOCLIMAP-II/Europe: a twofold database of ecosystems and surface parameters at 1 km resolution based on satellite information for use in land surface, meteorological and climate models

Science.gov (United States)

Faroux, S.; Kaptué Tchuenté, A. T.; Roujean, J.-L.; Masson, V.; Martin, E.; Le Moigne, P.

2013-04-01

The overall objective of the present study is to introduce the new ECOCLIMAP-II database for Europe, which is an upgrade for this region of the former initiative, ECOCLIMAP-I, already implemented at global scale. The ECOCLIMAP programme is a dual database at 1 km resolution that includes an ecosystem classification and a coherent set of land surface parameters that are primarily mandatory in meteorological modelling (notably leaf area index and albedo). Hence, the aim of this innovative physiography is to enhance the quality of initialisation and impose some surface attributes within the scope of weather forecasting and climate related studies. The strategy for implementing ECOCLIMAP-II is to depart from prevalent land cover products such as CLC2000 (Corine Land Cover) and GLC2000 (Global Land Cover) by splitting existing classes into new classes that possess a better regional character by virtue of the climatic environment (latitude, proximity to the sea, topography). The leaf area index (LAI) from MODIS and normalized difference vegetation index (NDVI) from SPOT/Vegetation (a global monitoring system of vegetation) yield the two proxy variables that were considered here in order to perform a multi-year trimmed analysis between 1999 and 2005 using the K-means method. Further, meteorological applications require each land cover type to appear as a partition of fractions of 4 main surface types or tiles (nature, water bodies, sea, urban areas) and, inside the nature tile, fractions of 12 plant functional types (PFTs) representing generic vegetation types - principally broadleaf forest, needleleaf forest, C3 and C4 crops, grassland and bare land - as incorporated by the SVAT model ISBA (Interactions Surface Biosphere Atmosphere) developed at Météo France. This landscape division also forms the cornerstone of a validation exercise. The new ECOCLIMAP-II can be verified with auxiliary land cover products at very fine and coarse resolutions by means of versatile land

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

Diabatic models with transferrable parameters for generalized chemical reactions

International Nuclear Information System (INIS)

Reimers, Jeffrey R; McKemmish, Laura K; McKenzie, Ross H; Hush, Noel S

2017-01-01

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

Models and parameters for environmental radiological assessments

International Nuclear Information System (INIS)

Miller, C.W.

1983-01-01

This article reviews the forthcoming book Models and Parameters for Environmental Radiological Assessments, which presents a unified compilation of models and parameters for assessing the impact on man of radioactive discharges, both routine and accidental, into the environment. Models presented in this book 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. Summaries are presented for each of the transport and dosimetry areas previously for each of the transport and dosimetry areas previously mentioned, and details are available in the literature cited. A chapter of example problems illustrates many of the methodologies presented throughout the text. Models and parameters presented are based on the results of extensive literature reviews and evaluations performed primarily by the staff of the Health and Safety Research Division of Oak Ridge National Laboratory

Parameter Estimation of Nonlinear Models in Forestry.

OpenAIRE

Fekedulegn, Desta; Mac Siúrtáin, Máirtín Pádraig; Colbert, Jim J.

1999-01-01

Partial derivatives of the negative exponential, monomolecular, Mitcherlich, Gompertz, logistic, Chapman-Richards, von Bertalanffy, Weibull and the Richard’s nonlinear growth models are presented. The application of these partial derivatives in estimating the model parameters is illustrated. The parameters are estimated using the Marquardt iterative method of nonlinear regression relating top height to age of Norway spruce (Picea abies L.) from the Bowmont Norway Spruce Thinnin...

Learning about physical parameters: the importance of model discrepancy

International Nuclear Information System (INIS)

Brynjarsdóttir, Jenný; O'Hagan, Anthony

2014-01-01

Science-based simulation models are widely used to predict the behavior of complex physical systems. It is also common to use observations of the physical system to solve the inverse problem, that is, to learn about the values of parameters within the model, a process which is often called calibration. The main goal of calibration is usually to improve the predictive performance of the simulator but the values of the parameters in the model may also be of intrinsic scientific interest in their own right. In order to make appropriate use of observations of the physical system it is important to recognize model discrepancy, the difference between reality and the simulator output. We illustrate through a simple example that an analysis that does not account for model discrepancy may lead to biased and over-confident parameter estimates and predictions. The challenge with incorporating model discrepancy in statistical inverse problems is being confounded with calibration parameters, which will only be resolved with meaningful priors. For our simple example, we model the model-discrepancy via a Gaussian process and demonstrate that through accounting for model discrepancy our prediction within the range of data is correct. However, only with realistic priors on the model discrepancy do we uncover the true parameter values. Through theoretical arguments we show that these findings are typical of the general problem of learning about physical parameters and the underlying physical system using science-based mechanistic models. (paper)

Phase II Contaminant Transport Parameters for the Groundwater Flow and Contaminant Transport Model of Corrective Action Unit 98: Frenchman Flat, Nye County, Nevada, Rev. No.: 0

Energy Technology Data Exchange (ETDEWEB)

DeNovio, Nicole M.; Bryant, Nathan; King, Chrissi B.; Bhark, Eric; Drellack, Sigmund L.; Pickens, John F.; Farnham, Irene; Brooks, Keely M.; Reimus, Paul; Aly, Alaa

2005-04-01

This report documents pertinent transport data and data analyses as part of the Phase II Corrective Action Investigation (CAI) for Frenchman Flat (FF) Corrective Action Unit (CAU) 98. The purpose of this data compilation and related analyses is to provide the primary reference to support parameterization of the Phase II FF CAU transport model.

Wind Farm Decentralized Dynamic Modeling With Parameters

DEFF Research Database (Denmark)

Soltani, Mohsen; Shakeri, Sayyed Mojtaba; Grunnet, Jacob Deleuran

2010-01-01

Development of dynamic wind flow models for wind farms is part of the research in European research FP7 project AEOLUS. The objective of this report is to provide decentralized dynamic wind flow models with parameters. The report presents a structure for decentralized flow models with inputs from...... local models. The results of this report are especially useful, but not limited, to design a decentralized wind farm controller, since in centralized controller design one can also use the model and update it in a central computing node.......Development of dynamic wind flow models for wind farms is part of the research in European research FP7 project AEOLUS. The objective of this report is to provide decentralized dynamic wind flow models with parameters. The report presents a structure for decentralized flow models with inputs from...

Optimizing incomplete sample designs for item response model parameters

NARCIS (Netherlands)

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

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

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

Equilibrium, thermodynamic and kinetic studies for the biosorption of aqueous lead(II), cadmium(II) and nickel(II) ions on Spirulina platensis

Energy Technology Data Exchange (ETDEWEB)

Seker, Ayseguel [Department of Chemistry, Izmir Institute of Technology, Urla 35430, Izmir (Turkey)], E-mail: aysegulseker@iyte.edu.tr; Shahwan, Talal [Department of Chemistry, Izmir Institute of Technology, Urla 35430, Izmir (Turkey)], E-mail: talalshahwan@iyte.edu.tr; Eroglu, Ahmet E. [Department of Chemistry, Izmir Institute of Technology, Urla 35430, Izmir (Turkey)], E-mail: ahmeteroglu@iyte.edu.tr; Yilmaz, Sinan [Department of Chemistry, Izmir Institute of Technology, Urla 35430, Izmir (Turkey)], E-mail: sinanyilmaz@iyte.edu.tr; Demirel, Zeliha [Department of Biology, Ege University, Bornova 35100, Izmir (Turkey)], E-mail: zelihademirel@gmail.com; Dalay, Meltem Conk [Department of Bioengineering, Ege University, Bornova 35100, Izmir (Turkey)], E-mail: meltemconkdalay@gmail.com

2008-06-15

The biosorption of lead(II), cadmium(II) and nickel(II) ions from aqueous solution by Spirulina platensis was studied as a function of time, concentration, temperature, repetitive reactivity, and ionic competition. The kinetic results obeyed well the pseudo second-order model. Freundlich, Dubinin Radushkevich and Temkin isotherm models were applied in describing the equilibrium partition of the ions. Freundlich isotherm was applied to describe the design of a single-stage batch sorption system. According to the thermodynamic parameters such as {delta}G{sup o}, {delta}H{sup o}and {delta}S{sup o} calculated, the sorption process was endothermic and largely driven towards the products. Sorption activities in a three metal ion system were studied which indicated that there is a relative selectivity of the biosorbent towards Pb{sup 2+} ions. The measurements of the repetitive reusability of S. platensis indicated a large capacity towards the three metal ions.

Accident analysis for PRC-II reactor

International Nuclear Information System (INIS)

Wei Yongren; Tang Gang; Wu Qing; Lu Yili; Liu Zhifeng

1997-12-01

The computer codes, calculation models, transient results, sensitivity research, design improvement, and safety evaluation used in accident analysis for PRC-II Reactor (The Second Pulsed Reactor in China) are introduced. PRC-II Reactor is built in big populous city, so the public pay close attention to reactor safety. Consequently, Some hypothetical accidents are analyzed. They include an uncontrolled control rod withdrawal at rated power, a pulse rod ejection at rated power, and loss of coolant accident. Calculation model which completely depict the principle and process for each accident is established and the relevant analysis code is developed. This work also includes comprehensive computing and analyzing transients for each accident of PRC-II Reactor; the influences in the reactor safety of all kind of sensitive parameters; evaluating the function of engineered safety feature. The measures to alleviate the consequence of accident are suggested and taken in the construction design of PRC-II Reactor. The properties of reactor safety are comprehensively evaluated. A new advanced calculation model (True Core Uncovered Model) of LOCA of PRC-II Reactor and the relevant code (MCRLOCA) are first put forward

Application of multi-parameter chorus and plasmaspheric hiss wave models in radiation belt modeling

Science.gov (United States)

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.

Modelling hydrodynamic parameters to predict flow assisted corrosion

International Nuclear Information System (INIS)

Poulson, B.; Greenwell, B.; Chexal, B.; Horowitz, J.

1992-01-01

During the past 15 years, flow assisted corrosion has been a worldwide problem in the power generating industry. The phenomena is complex and depends on environment, material composition, and hydrodynamic factors. Recently, modeling of flow assisted corrosion has become a subject of great importance. A key part of this effort is modeling the hydrodynamic aspects of this issue. This paper examines which hydrodynamic parameter should be used to correlate the occurrence and rate of flow assisted corrosion with physically meaningful parameters, discusses ways of measuring the relevant hydrodynamic parameter, and describes how the hydrodynamic data is incorporated into the predictive model

keV right-handed neutrinos from type II seesaw mechanism in a 3-3-1 model

International Nuclear Information System (INIS)

Cogollo, D.; Diniz, H.; Pires, C.A. de S

2009-01-01

We adapt the type II seesaw mechanism to the framework of the 3-3-1 model with right-handed neutrinos. We emphasize that the mechanism is capable of generating small masses for the left-handed and right-handed neutrinos and the structure of the model allows that both masses arise from the same Yukawa coupling. For typical values of the free parameters of the model we may obtain at least one right-handed neutrino with mass in the keV range. Right-handed neutrino with mass in this range is a viable candidate for the warm component of the dark matter existent in the universe.

Application and optimization of input parameter spaces in mass flow modelling: a case study with r.randomwalk and r.ranger

Science.gov (United States)

Krenn, Julia; Zangerl, Christian; Mergili, Martin

2017-04-01

strategy is best demonstrated for two input parameters, but can be extended arbitrarily. We use a set of small rock avalanches from western Austria, and some larger ones from Canada and New Zealand, to optimize the basal friction coefficient and the mass-to-drag ratio of the two-parameter friction model implemented with r.randomwalk. Thereby we repeat the optimization procedure with conservative and non-conservative assumptions of a set of complementary parameters and with different raster cell sizes. Our preliminary results indicate that the model performance in terms of AUROC achieved with broad parameter spaces is hardly surpassed by the performance achieved with narrow parameter spaces. However, broad spaces may result in very conservative or very non-conservative predictions. Therefore, guiding parameter spaces have to be (i) broad enough to avoid the risk of being off target; and (ii) narrow enough to ensure a reasonable level of conservativeness of the results. The next steps will consist in (i) extending the study to other types of mass flow processes in order to support forward calculations using r.randomwalk; and (ii) in applying the same strategy to the more complex, dynamic model r.avaflow.

About APPLE II Operation

International Nuclear Information System (INIS)

Schmidt, T.; Zimoch, D.

2007-01-01

The operation of an APPLE II based undulator beamline with all its polarization states (linear horizontal and vertical, circular and elliptical, and continous variation of the linear vector) requires an effective description allowing an automated calculation of gap and shift parameter as function of energy and operation mode. The extension of the linear polarization range from 0 to 180 deg. requires 4 shiftable magnet arrrays, permitting use of the APU (adjustable phase undulator) concept. Studies for a pure fixed gap APPLE II for the SLS revealed surprising symmetries between circular and linear polarization modes allowing for simplified operation. A semi-analytical model covering all types of APPLE II and its implementation will be presented

AN ANALYTIC MODEL OF DUSTY, STRATIFIED, SPHERICAL H ii REGIONS

Energy Technology Data Exchange (ETDEWEB)

Rodríguez-Ramírez, J. C.; Raga, A. C. [Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México, Ap. 70-543, 04510 D.F., México (Mexico); Lora, V. [Astronomisches Rechen-Institut, Zentrum für Astronomie der Universität, Mönchhofstr. 12-14, D-69120 Heidelberg (Germany); Cantó, J., E-mail: juan.rodriguez@nucleares.unam.mx [Instituto de Astronomía, Universidad Nacional Autónoma de México, Ap. 70-468, 04510 D. F., México (Mexico)

2016-12-20

We study analytically the effect of radiation pressure (associated with photoionization processes and with dust absorption) on spherical, hydrostatic H ii regions. We consider two basic equations, one for the hydrostatic balance between the radiation-pressure components and the gas pressure, and another for the balance among the recombination rate, the dust absorption, and the ionizing photon rate. Based on appropriate mathematical approximations, we find a simple analytic solution for the density stratification of the nebula, which is defined by specifying the radius of the external boundary, the cross section of dust absorption, and the luminosity of the central star. We compare the analytic solution with numerical integrations of the model equations of Draine, and find a wide range of the physical parameters for which the analytic solution is accurate.

WINKLER'S SINGLE-PARAMETER SUBGRADE MODEL FROM ...

African Journals Online (AJOL)

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Page 1 ... corresponding single-parameter Winkler model presented in this work. Keywords: Heterogeneous subgrade, Reissner's simplified continuum, Shear interaction, Simplified continuum, Winkler ... model in practical applications and its long time familiarity among practical engineers, its usage has endured to this date ...

Insight into model mechanisms through automatic parameter fitting: a new methodological framework for model development.

Science.gov (United States)

Tøndel, Kristin; Niederer, Steven A; Land, Sander; Smith, Nicolas P

2014-05-20

Striking a balance between the degree of model complexity and parameter identifiability, while still producing biologically feasible simulations using modelling is a major challenge in computational biology. While these two elements of model development are closely coupled, parameter fitting from measured data and analysis of model mechanisms have traditionally been performed separately and sequentially. This process produces potential mismatches between model and data complexities that can compromise the ability of computational frameworks to reveal mechanistic insights or predict new behaviour. In this study we address this issue by presenting a generic framework for combined model parameterisation, comparison of model alternatives and analysis of model mechanisms. The presented methodology is based on a combination of multivariate metamodelling (statistical approximation of the input-output relationships of deterministic models) and a systematic zooming into biologically feasible regions of the parameter space by iterative generation of new experimental designs and look-up of simulations in the proximity of the measured data. The parameter fitting pipeline includes an implicit sensitivity analysis and analysis of parameter identifiability, making it suitable for testing hypotheses for model reduction. Using this approach, under-constrained model parameters, as well as the coupling between parameters within the model are identified. The methodology is demonstrated by refitting the parameters of a published model of cardiac cellular mechanics using a combination of measured data and synthetic data from an alternative model of the same system. Using this approach, reduced models with simplified expressions for the tropomyosin/crossbridge kinetics were found by identification of model components that can be omitted without affecting the fit to the parameterising data. Our analysis revealed that model parameters could be constrained to a standard deviation of on

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.

Spike Neural Models Part II: Abstract Neural Models

Directory of Open Access Journals (Sweden)

Johnson, Melissa G.

2018-02-01

Full Text Available Neurons are complex cells that require a lot of time and resources to model completely. In spiking neural networks (SNN though, not all that complexity is required. Therefore simple, abstract models are often used. These models save time, use less computer resources, and are easier to understand. This tutorial presents two such models: Izhikevich's model, which is biologically realistic in the resulting spike trains but not in the parameters, and the Leaky Integrate and Fire (LIF model which is not biologically realistic but does quickly and easily integrate input to produce spikes. Izhikevich's model is based on Hodgkin-Huxley's model but simplified such that it uses only two differentiation equations and four parameters to produce various realistic spike patterns. LIF is based on a standard electrical circuit and contains one equation. Either of these two models, or any of the many other models in literature can be used in a SNN. Choosing a neural model is an important task that depends on the goal of the research and the resources available. Once a model is chosen, network decisions such as connectivity, delay, and sparseness, need to be made. Understanding neural models and how they are incorporated into the network is the first step in creating a SNN.

Retrospective forecast of ETAS model with daily parameters estimate

Science.gov (United States)

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

2016-04-01

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

Parameter identification in multinomial processing tree models

NARCIS (Netherlands)

Schmittmann, V.D.; Dolan, C.V.; Raijmakers, M.E.J.; Batchelder, W.H.

2010-01-01

Multinomial processing tree models form a popular class of statistical models for categorical data that have applications in various areas of psychological research. As in all statistical models, establishing which parameters are identified is necessary for model inference and selection on the basis

Integrating Seasonal Oscillations into Basel II Behavioural Scoring Models

Directory of Open Access Journals (Sweden)

Goran Klepac

2007-09-01

Full Text Available The article introduces a new methodology of temporal influence measurement (seasonal oscillations, temporal patterns for behavioural scoring development purposes. The paper shows how significant temporal variables can be recognised and then integrated into the behavioural scoring models in order to improve model performance. Behavioural scoring models are integral parts of the Basel II standard on Internal Ratings-Based Approaches (IRB. The IRB approach much more precisely reflects individual risk bank profile.A solution of the problem of how to analyze and integrate macroeconomic and microeconomic factors represented in time series into behavioural scorecard models will be shown in the paper by using the REF II model.

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)

Lumped-parameters equivalent circuit for condenser microphones modeling.

Science.gov (United States)

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

2017-10-01

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

Analysis of Modeling Parameters on Threaded Screws.

Energy Technology Data Exchange (ETDEWEB)

Vigil, Miquela S. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Brake, Matthew Robert [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Vangoethem, Douglas [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-06-01

Assembled mechanical systems often contain a large number of bolted connections. These bolted connections (joints) are integral aspects of the load path for structural dynamics, and, consequently, are paramount for calculating a structure's stiffness and energy dissipation prop- erties. However, analysts have not found the optimal method to model appropriately these bolted joints. The complexity of the screw geometry cause issues when generating a mesh of the model. This paper will explore different approaches to model a screw-substrate connec- tion. Model parameters such as mesh continuity, node alignment, wedge angles, and thread to body element size ratios are examined. The results of this study will give analysts a better understanding of the influences of these parameters and will aide in finding the optimal method to model bolted connections.

Parameter Estimates in Differential Equation Models for Chemical Kinetics

Science.gov (United States)

Winkel, Brian

2011-01-01

We discuss the need for devoting time in differential equations courses to modelling and the completion of the modelling process with efforts to estimate the parameters in the models using data. We estimate the parameters present in several differential equation models of chemical reactions of order n, where n = 0, 1, 2, and apply more general…

Carbonate-mediated Fe(II) oxidation in the air-cathode fuel cell: a kinetic model in terms of Fe(II) speciation.

Science.gov (United States)

Song, Wei; Zhai, Lin-Feng; Cui, Yu-Zhi; Sun, Min; Jiang, Yuan

2013-06-06

Due to the high redox activity of Fe(II) and its abundance in natural waters, the electro-oxidation of Fe(II) can be found in many air-cathode fuel cell systems, such as acid mine drainage fuel cells and sediment microbial fuel cells. To deeply understand these iron-related systems, it is essential to elucidate the kinetics and mechanisms involved in the electro-oxidation of Fe(II). This work aims to develop a kinetic model that adequately describes the electro-oxidation process of Fe(II) in air-cathode fuel cells. The speciation of Fe(II) is incorporated into the model, and contributions of individual Fe(II) species to the overall Fe(II) oxidation rate are quantitatively evaluated. The results show that the kinetic model can accurately predict the electro-oxidation rate of Fe(II) in air-cathode fuel cells. FeCO3, Fe(OH)2, and Fe(CO3)2(2-) are the most important species determining the electro-oxidation kinetics of Fe(II). The Fe(II) oxidation rate is primarily controlled by the oxidation of FeCO3 species at low pH, whereas at high pH Fe(OH)2 and Fe(CO3)2(2-) are the dominant species. Solution pH, carbonate concentration, and solution salinity are able to influence the electro-oxidation kinetics of Fe(II) through changing both distribution and kinetic activity of Fe(II) species.

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...

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...

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.

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

Evaluation of CNTs/MnO{sub 2} composite for adsorption of {sup 60}Co(II), {sup 65}Zn(II) and Cd(II) ions from aqueous solutions

Energy Technology Data Exchange (ETDEWEB)

Sharaf El-Deen, Sahar E.A.; Moussa, Saber I.; Mekawy, Zakaria A.; Shehata, Mohamed K.K.; Someda, Hanan H. [Atomic Energy Authority, Inshas (Egypt). Dept. of Nuclear Chemistry; Sadeek, Sadeek A. [Zagazig Univ. (Egypt). Dept. of Chemistry

2017-03-01

CNTs/MnO{sub 2} composite was synthesized by a co-precipitation method after preparation of carbon nanotubes (CNTs) using a chemical oxidation method and was characterized using Fourier transformer infrared (FT-IR), X-ray diffraction (XRD) and scanning electron microscope (SEM). The synthesized CNTs/MnO{sub 2} composite was used as a sorbent for the removal of some radionuclides ({sup 60}Co and {sup 65}Zn-radioisotopes) and Cd (II) ions from aqueous solutions. Different parameters affecting the removal process including pH, contact time and metal ion concentration were investigated. Isotherm and kinetic models were studied. Adsorption data was interpreted in terms of both Freundlich and Langmuir isotherms and indicated that the CNTs/MnO{sub 2} composite complied well with both Langmuir and Freundlich models for {sup 60}Co and Cd(II) ions and with the Freundlich model only for the {sup 65}Zn radioisotope. A pseudo-second-order model was effectively employed to describe the adsorption behavior of {sup 60}Co, {sup 65}Zn and Cd(II) ions. Desorption of {sup 60}Co and {sup 65}Zn and Cd(II) ions from loaded samples was studied using different eluents.

Understanding agent-based models of financial markets: A bottom-up approach based on order parameters and phase diagrams

Science.gov (United States)

Lye, Ribin; Tan, James Peng Lung; Cheong, Siew Ann

2012-11-01

We describe a bottom-up framework, based on the identification of appropriate order parameters and determination of phase diagrams, for understanding progressively refined agent-based models and simulations of financial markets. We illustrate this framework by starting with a deterministic toy model, whereby N independent traders buy and sell M stocks through an order book that acts as a clearing house. The price of a stock increases whenever it is bought and decreases whenever it is sold. Price changes are updated by the order book before the next transaction takes place. In this deterministic model, all traders based their buy decisions on a call utility function, and all their sell decisions on a put utility function. We then make the agent-based model more realistic, by either having a fraction fb of traders buy a random stock on offer, or a fraction fs of traders sell a random stock in their portfolio. Based on our simulations, we find that it is possible to identify useful order parameters from the steady-state price distributions of all three models. Using these order parameters as a guide, we find three phases: (i) the dead market; (ii) the boom market; and (iii) the jammed market in the phase diagram of the deterministic model. Comparing the phase diagrams of the stochastic models against that of the deterministic model, we realize that the primary effect of stochasticity is to eliminate the dead market phase.

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.

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

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.

Improving weather predictability by including land-surface model parameter uncertainty

Science.gov (United States)

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

Parameters-related uncertainty in modeling sugar cane yield with an agro-Land Surface Model

Science.gov (United States)

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

Parameter estimation in large-scale systems biology models: a parallel and self-adaptive cooperative strategy.

Science.gov (United States)

Penas, David R; González, Patricia; Egea, Jose A; Doallo, Ramón; Banga, Julio R

2017-01-21

The development of large-scale kinetic models is one of the current key issues in computational systems biology and bioinformatics. Here we consider the problem of parameter estimation in nonlinear dynamic models. Global optimization methods can be used to solve this type of problems but the associated computational cost is very large. Moreover, many of these methods need the tuning of a number of adjustable search parameters, requiring a number of initial exploratory runs and therefore further increasing the computation times. Here we present a novel parallel method, self-adaptive cooperative enhanced scatter search (saCeSS), to accelerate the solution of this class of problems. The method is based on the scatter search optimization metaheuristic and incorporates several key new mechanisms: (i) asynchronous cooperation between parallel processes, (ii) coarse and fine-grained parallelism, and (iii) self-tuning strategies. The performance and robustness of saCeSS is illustrated by solving a set of challenging parameter estimation problems, including medium and large-scale kinetic models of the bacterium E. coli, bakerés yeast S. cerevisiae, the vinegar fly D. melanogaster, Chinese Hamster Ovary cells, and a generic signal transduction network. The results consistently show that saCeSS is a robust and efficient method, allowing very significant reduction of computation times with respect to several previous state of the art methods (from days to minutes, in several cases) even when only a small number of processors is used. The new parallel cooperative method presented here allows the solution of medium and large scale parameter estimation problems in reasonable computation times and with small hardware requirements. Further, the method includes self-tuning mechanisms which facilitate its use by non-experts. We believe that this new method can play a key role in the development of large-scale and even whole-cell dynamic models.

Dynamic modeling and simulation of EBR-II steam generator system

International Nuclear Information System (INIS)

Berkan, R.C.; Upadhyaya, B.R.

1989-01-01

This paper presents a low order dynamic model of the Experimental breeder Reactor-II (EBR-II) steam generator system. The model development includes the application of energy, mass and momentum balance equations in state-space form. The model also includes a three-element controller for the drum water level control problem. The simulation results for low-level perturbations exhibit the inherently stable characteristics of the steam generator. The predictions of test transients also verify the consistency of this low order model

Hybrid artificial bee colony algorithm for parameter optimization of five-parameter bidirectional reflectance distribution function model.

Science.gov (United States)

Wang, Qianqian; Zhao, Jing; Gong, Yong; Hao, Qun; Peng, Zhong

2017-11-20

A hybrid artificial bee colony (ABC) algorithm inspired by the best-so-far solution and bacterial chemotaxis was introduced to optimize the parameters of the five-parameter bidirectional reflectance distribution function (BRDF) model. To verify the performance of the hybrid ABC algorithm, we measured BRDF of three kinds of samples and simulated the undetermined parameters of the five-parameter BRDF model using the hybrid ABC algorithm and the genetic algorithm, respectively. The experimental results demonstrate that the hybrid ABC algorithm outperforms the genetic algorithm in convergence speed, accuracy, and time efficiency under the same conditions.

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.

Hydrological model parameter dimensionality is a weak measure of prediction uncertainty

Science.gov (United States)

Pande, S.; Arkesteijn, L.; Savenije, H.; Bastidas, L. A.

2015-04-01

This paper shows that instability of hydrological system representation in response to different pieces of information and associated prediction uncertainty is a function of model complexity. After demonstrating the connection between unstable model representation and model complexity, complexity is analyzed in a step by step manner. This is done measuring differences between simulations of a model under different realizations of input forcings. Algorithms are then suggested to estimate model complexity. Model complexities of the two model structures, SAC-SMA (Sacramento Soil Moisture Accounting) and its simplified version SIXPAR (Six Parameter Model), are computed on resampled input data sets from basins that span across the continental US. The model complexities for SIXPAR are estimated for various parameter ranges. It is shown that complexity of SIXPAR increases with lower storage capacity and/or higher recession coefficients. Thus it is argued that a conceptually simple model structure, such as SIXPAR, can be more complex than an intuitively more complex model structure, such as SAC-SMA for certain parameter ranges. We therefore contend that magnitudes of feasible model parameters influence the complexity of the model selection problem just as parameter dimensionality (number of parameters) does and that parameter dimensionality is an incomplete indicator of stability of hydrological model selection and prediction problems.

Parameter identification and global sensitivity analysis of Xin'anjiang model using meta-modeling approach

Directory of Open Access Journals (Sweden)

Xiao-meng Song

2013-01-01

Full Text Available Parameter identification, model calibration, and uncertainty quantification are important steps in the model-building process, and are necessary for obtaining credible results and valuable information. Sensitivity analysis of hydrological model is a key step in model uncertainty quantification, which can identify the dominant parameters, reduce the model calibration uncertainty, and enhance the model optimization efficiency. There are, however, some shortcomings in classical approaches, including the long duration of time and high computation cost required to quantitatively assess the sensitivity of a multiple-parameter hydrological model. For this reason, a two-step statistical evaluation framework using global techniques is presented. It is based on (1 a screening method (Morris for qualitative ranking of parameters, and (2 a variance-based method integrated with a meta-model for quantitative sensitivity analysis, i.e., the Sobol method integrated with the response surface model (RSMSobol. First, the Morris screening method was used to qualitatively identify the parameters' sensitivity, and then ten parameters were selected to quantify the sensitivity indices. Subsequently, the RSMSobol method was used to quantify the sensitivity, i.e., the first-order and total sensitivity indices based on the response surface model (RSM were calculated. The RSMSobol method can not only quantify the sensitivity, but also reduce the computational cost, with good accuracy compared to the classical approaches. This approach will be effective and reliable in the global sensitivity analysis of a complex large-scale distributed hydrological model.

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....

Saturne II synchroton injector parameters operation and control: computerization and optimization

International Nuclear Information System (INIS)

Lagniel, J.M.

1983-01-01

The injector control system has been studied, aiming at the beam quality improvement, the increasing of the versatility, and a better machine availability. It has been choosen to realize the three following functions: - acquisition of the principal parameters of the process, so as to control them quickly and to be warned if one of them is wrong (monitoring); - the control of those parameters, one by one or by families (starting, operating point); - the research of an optimal control (on a model or on the process itself) [fr

Seasonal and spatial variation in broadleaf forest model parameters

Science.gov (United States)

Groenendijk, M.; van der Molen, M. K.; Dolman, A. J.

2009-04-01

Process based, coupled ecosystem carbon, energy and water cycle models are used with the ultimate goal to project the effect of future climate change on the terrestrial carbon cycle. A typical dilemma in such exercises is how much detail the model must be given to describe the observations reasonably realistic while also be general. We use a simple vegetation model (5PM) with five model parameters to study the variability of the parameters. These parameters are derived from the observed carbon and water fluxes from the FLUXNET database. For 15 broadleaf forests the model parameters were derived for different time resolutions. It appears that in general for all forests, the correlation coefficient between observed and simulated carbon and water fluxes improves with a higher parameter time resolution. The quality of the simulations is thus always better when a higher time resolution is used. These results show that annual parameters are not capable of properly describing weather effects on ecosystem fluxes, and that two day time resolution yields the best results. A first indication of the climate constraints can be found by the seasonal variation of the covariance between Jm, which describes the maximum electron transport for photosynthesis, and climate variables. A general seasonality we found is that during winter the covariance with all climate variables is zero. Jm increases rapidly after initial spring warming, resulting in a large covariance with air temperature and global radiation. During summer Jm is less variable, but co-varies negatively with air temperature and vapour pressure deficit and positively with soil water content. A temperature response appears during spring and autumn for broadleaf forests. This shows that an annual model parameter cannot be representative for the entire year. And relations with mean annual temperature are not possible. During summer the photosynthesis parameters are constrained by water availability, soil water content and

Synthesis and properties of complexes of copper(II), nickel(II), cobalt(II) and uranyl ions with 3-(p-tolylsulphonamido)rhodamine

International Nuclear Information System (INIS)

El-Bindary, A.A.; El-Sonbati, A.Z.

2000-01-01

Metal complexes of copper(II), nickel(II), cobalt(II) and uranyl ions with 3-(p-tolylsulphonamido)rhodamine (HL) have been prepared and characterized by chemical and thermal analyses, molar conductivity , magnetic susceptibility measurements, and infrared, electronic and EPR spectra. The visible and EPR spectra indicated that the Cu(II) complex has a tetragonal geometry. From EPR spectrum of the Cu(II) complex,various parameters were calculated. The crystal field parameters of Ni(II) complex were calculated and were found to agree fairly well with the values reported for known square pyramidal complexes. The infrared spectral studies showed a monobasic bidentate behaviour with the oxygen and nitrogen donor system. Thermal stabilities of the complexes are also reported. (author)

A Scheduling Model for the Re-entrant Manufacturing System and Its Optimization by NSGA-II

Directory of Open Access Journals (Sweden)

Masoud Rabbani

2016-11-01

Full Text Available In this study, a two-objective mixed-integer linear programming model (MILP for multi-product re-entrant flow shop scheduling problem has been designed. As a result, two objectives are considered. One of them is maximization of the production rate and the other is the minimization of processing time. The system has m stations and can process several products in a moment. The re-entrant flow shop scheduling problem is well known as NP-hard problem and its complexity has been discussed by several researchers. Given that NSGA-II algorithm is one of the strongest and most applicable algorithm in solving multi-objective optimization problems, it is used to solve this problem. To increase algorithm performance, Taguchi technique is used to design experiments for algorithm’s parameters. Numerical experiments are proposed to show the efficiency and effectiveness of the model. Finally, the results of NSGA-II are compared with SPEA2 algorithm (Strength Pareto Evolutionary Algorithm 2. The experimental results show that the proposed algorithm performs significantly better than the SPEA2.

Temporal variation and scaling of parameters for a monthly hydrologic model

Science.gov (United States)

Deng, Chao; Liu, Pan; Wang, Dingbao; Wang, Weiguang

2018-03-01

The temporal variation of model parameters is affected by the catchment conditions and has a significant impact on hydrological simulation. This study aims to evaluate the seasonality and downscaling of model parameter across time scales based on monthly and mean annual water balance models with a common model framework. Two parameters of the monthly model, i.e., k and m, are assumed to be time-variant at different months. Based on the hydrological data set from 121 MOPEX catchments in the United States, we firstly analyzed the correlation between parameters (k and m) and catchment properties (NDVI and frequency of rainfall events, α). The results show that parameter k is positively correlated with NDVI or α, while the correlation is opposite for parameter m, indicating that precipitation and vegetation affect monthly water balance by controlling temporal variation of parameters k and m. The multiple linear regression is then used to fit the relationship between ε and the means and coefficient of variations of parameters k and m. Based on the empirical equation and the correlations between the time-variant parameters and NDVI, the mean annual parameter ε is downscaled to monthly k and m. The results show that it has lower NSEs than these from model with time-variant k and m being calibrated through SCE-UA, while for several study catchments, it has higher NSEs than that of the model with constant parameters. The proposed method is feasible and provides a useful tool for temporal scaling of model parameter.

An improved state-parameter analysis of ecosystem models using data assimilation

Science.gov (United States)

Chen, M.; Liu, S.; Tieszen, L.L.; Hollinger, D.Y.

2008-01-01

Much of the effort spent in developing data assimilation methods for carbon dynamics analysis has focused on estimating optimal values for either model parameters or state variables. The main weakness of estimating parameter values alone (i.e., without considering state variables) is that all errors from input, output, and model structure are attributed to model parameter uncertainties. On the other hand, the accuracy of estimating state variables may be lowered if the temporal evolution of parameter values is not incorporated. This research develops a smoothed ensemble Kalman filter (SEnKF) by combining ensemble Kalman filter with kernel smoothing technique. SEnKF has following characteristics: (1) to estimate simultaneously the model states and parameters through concatenating unknown parameters and state variables into a joint state vector; (2) to mitigate dramatic, sudden changes of parameter values in parameter sampling and parameter evolution process, and control narrowing of parameter variance which results in filter divergence through adjusting smoothing factor in kernel smoothing algorithm; (3) to assimilate recursively data into the model and thus detect possible time variation of parameters; and (4) to address properly various sources of uncertainties stemming from input, output and parameter uncertainties. The SEnKF is tested by assimilating observed fluxes of carbon dioxide and environmental driving factor data from an AmeriFlux forest station located near Howland, Maine, USA, into a partition eddy flux model. Our analysis demonstrates that model parameters, such as light use efficiency, respiration coefficients, minimum and optimum temperatures for photosynthetic activity, and others, are highly constrained by eddy flux data at daily-to-seasonal time scales. The SEnKF stabilizes parameter values quickly regardless of the initial values of the parameters. Potential ecosystem light use efficiency demonstrates a strong seasonality. Results show that the

Comparison of adsorption of Cd(II and Pb(II ions on pure and chemically modified fly ashes

Directory of Open Access Journals (Sweden)

Sočo Eleonora

2016-06-01

Full Text Available The study investigates chemical modifications of coal fly ash (FA treated with HCl or NH4HCO3 or NaOH or Na2edta, based on the research conducted to examine the behaviour of Cd(II and Pb(II ions adsorbed from water solution on treated fly ash. In laboratory tests, the equilibrium and kinetics were examined applying various temperatures (293 - 333 K and pH (2 - 11 values. The maximum Cd(II and Pb(II ions adsorption capacity obtained at 293 K, pH 9 and mixing time 2 h from the Langmuir model can be grouped in the following order: FA-NaOH > FA-NH4HCO3 > FA > FA-Na2edta > FA-HCl. The morphology of fly ash grains was examined via small-angle X-ray scattering (SAXS and images of scanning electron microscope (SEM. The adsorption kinetics data were well fitted by a pseudo-second-order rate model but showed a very poor fit for the pseudofirst order model. The intra-particle model also revealed that there are two separate stages in the sorption process, i.e. the external diffusion and the inter-particle diffusion. Thermodynamics parameters such as free energy, enthalpy and entropy were also determined. A laboratory test demonstrated that the modified coal fly ash worked well for the Cd(II and Pb(II ion uptake from polluted waters.

Setting Parameters for Biological Models With ANIMO

NARCIS (Netherlands)

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

Constant-parameter capture-recapture models

Science.gov (United States)

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.

Ground level enhancement (GLE) energy spectrum parameters model

Science.gov (United States)

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.

Effect of temperature on equilibrium and thermodynamic parameters of Cd (II) adsorption onto turmeric powder

International Nuclear Information System (INIS)

Qayoom, A.

2012-01-01

Summary: Batch adsorption of Cd (II) onto turmeric powder was conducted as a function of temperature. Nonlinear Langmuir, Freundlich, Dubinin-Radushkevish (D-R) and Temkin equilibrium models were employed. In addition to R 2, five different error functions were used to determine best fit equilibrium isotherm model. It was found that Freundlich isotherm model provided better fit for adsorption data at 298 and 303 K and Langmuir model was suitable for the experimental data obtained at 310 and 313 K. It was found that increase in temperature decreased maximum adsorption capacities, showing that the adsorption of Cd (II) onto turmeric powder is exothermic. Enthalpy values also confirmed the same trend. Entropy values were negative which means that randomness decreased on increasing temperature. Gibbs free energies were non spontaneous at all the temperatures studied. E values were in the range of 2.73-3.23 kJ mol/sup -1/ which indicated that adsorption mechanism is essentially physical. (author)

Parameter Estimation of Spacecraft Fuel Slosh Model

Science.gov (United States)

Gangadharan, Sathya; Sudermann, James; Marlowe, Andrea; Njengam Charles

2004-01-01

Fuel slosh in the upper stages of a spinning spacecraft during launch has been a long standing concern for the success of a space mission. Energy loss through the movement of the liquid fuel in the fuel tank affects the gyroscopic stability of the spacecraft and leads to nutation (wobble) which can cause devastating control issues. The rate at which nutation develops (defined by Nutation Time Constant (NTC can be tedious to calculate and largely inaccurate if done during the early stages of spacecraft design. Pure analytical means of predicting the influence of onboard liquids have generally failed. A strong need exists to identify and model the conditions of resonance between nutation motion and liquid modes and to understand the general characteristics of the liquid motion that causes the problem in spinning spacecraft. A 3-D computerized model of the fuel slosh that accounts for any resonant modes found in the experimental testing will allow for increased accuracy in the overall modeling process. Development of a more accurate model of the fuel slosh currently lies in a more generalized 3-D computerized model incorporating masses, springs and dampers. Parameters describing the model include the inertia tensor of the fuel, spring constants, and damper coefficients. Refinement and understanding the effects of these parameters allow for a more accurate simulation of fuel slosh. The current research will focus on developing models of different complexity and estimating the model parameters that will ultimately provide a more realistic prediction of Nutation Time Constant obtained through simulation.

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

Efficiency of Chitosan for the Removal of Pb (II, Fe (II and Cu (II Ions from Aqueous Solutions

Directory of Open Access Journals (Sweden)

Soheil Sobhanardakani

2014-09-01

Full Text Available Background: Heavy metals have been recognized as harmful environmental pollutant known to produce highly toxic effects on different organs and systems of both humans and animals. The aim of this paper is to evaluate the adsorption potential of chitosan for the removal of Pb(II, Fe(II and Cu(II ions from aqueous solutions. Methods: This study was conducted in laboratory scale. In this paper chitosan has been used as an adsorbent for the removal of Pb(II, Fe(II and Cu(II from aqueous solution. In batch tests, the effects of parameters like pH solution (1.0-8.0, initial metal concentrations (100-1000 mgL-1, contact time (5.0-150 min and adsorbent dose (1.0-7.0 g on the adsorption process were studied. Results: The results showed that the adsorption of Pb(II, Fe(II and Cu(II ions on chitosan strongly depends on pH. The experimental isothermal data were analyzed using the Langmuir and Freundlich equations and it was found that the removal process followed the Langmuir isotherm and maximum adsorption capacity for the adsorption of Pb(II, Fe(II and Cu(II ions by the chitosan were 55.5mg g−1, 71.4 mg g−1 and 59 mg g−1, respectively, under equilibrium conditions at 25±1 ºC. The adsorption process was found to be well described by the pseudo-second-order rate model. Conclusion: The obtained results showed that chitosan is a readily, available, economic adsorbent and was found suitable for removing Pb(II, Fe(II and Cu(II ions from aqueous solution.

Biosorption optimization of lead(II), cadmium(II) and copper(II) using response surface methodology and applicability in isotherms and thermodynamics modeling

International Nuclear Information System (INIS)

Singh, Rajesh; Chadetrik, Rout; Kumar, Rajender; Bishnoi, Kiran; Bhatia, Divya; Kumar, Anil; Bishnoi, Narsi R.; Singh, Namita

2010-01-01

The present study was carried out to optimize the various environmental conditions for biosorption of Pb(II), Cd(II) and Cu(II) by investigating as a function of the initial metal ion concentration, temperature, biosorbent loading and pH using Trichoderma viride as adsorbent. Biosorption of ions from aqueous solution was optimized in a batch system using response surface methodology. The values of R 2 0.9716, 0.9699 and 0.9982 for Pb(II), Cd(II) and Cu(II) ions, respectively, indicated the validity of the model. The thermodynamic properties ΔG o , ΔH o , ΔE o and ΔS o by the metal ions for biosorption were analyzed using the equilibrium constant value obtained from experimental data at different temperatures. The results showed that biosorption of Pb(II) ions by T. viride adsorbent is more endothermic and spontaneous. The study was attempted to offer a better understating of representative biosorption isotherms and thermodynamics with special focuses on binding mechanism for biosorption using the FTIR spectroscopy.

Biosorption optimization of lead(II), cadmium(II) and copper(II) using response surface methodology and applicability in isotherms and thermodynamics modeling

Energy Technology Data Exchange (ETDEWEB)

Singh, Rajesh; Chadetrik, Rout; Kumar, Rajender; Bishnoi, Kiran; Bhatia, Divya; Kumar, Anil [Department of Environmental Science and Engineering, Guru Jambheshwar University of Science and Technology, Hisar 125001, Haryana (India); Bishnoi, Narsi R., E-mail: nrbishnoi@gmail.com [Department of Environmental Science and Engineering, Guru Jambheshwar University of Science and Technology, Hisar 125001, Haryana (India); Singh, Namita [Department of Bio and Nanotechnology, Guru Jambheshwar University of Science and Technology, Hisar 125001, Haryana (India)

2010-02-15

The present study was carried out to optimize the various environmental conditions for biosorption of Pb(II), Cd(II) and Cu(II) by investigating as a function of the initial metal ion concentration, temperature, biosorbent loading and pH using Trichoderma viride as adsorbent. Biosorption of ions from aqueous solution was optimized in a batch system using response surface methodology. The values of R{sup 2} 0.9716, 0.9699 and 0.9982 for Pb(II), Cd(II) and Cu(II) ions, respectively, indicated the validity of the model. The thermodynamic properties {Delta}G{sup o}, {Delta}H{sup o}, {Delta}E{sup o} and {Delta}S{sup o} by the metal ions for biosorption were analyzed using the equilibrium constant value obtained from experimental data at different temperatures. The results showed that biosorption of Pb(II) ions by T. viride adsorbent is more endothermic and spontaneous. The study was attempted to offer a better understating of representative biosorption isotherms and thermodynamics with special focuses on binding mechanism for biosorption using the FTIR spectroscopy.

Thermodynamics of the Cu(II) adsorption on thin vanillin-modified chitosan membranes

International Nuclear Information System (INIS)

Cestari, Antonio R.; Vieira, Eunice F.S.; Mattos, Charlene R.S.

2006-01-01

In this work, low-density vanillin-modified thin chitosan membranes were synthesized and characterized. The membranes were utilized as adsorbent for the removal of Cu(II) from aqueous solutions. The experimental data obtained in batch experiments at different temperatures were fitted to the Langmuir and Freundlich isotherms to obtain the characteristic parameters of each model. The adsorption equilibrium data fitted well with the Langmuir model (average R 2 > 0.99). Interactions thermodynamic parameters (Δ int H, Δ int G, and Δ int S), as well as the interaction thermal effects (Q int ) were determined from T = (298 to 333) K. The thermodynamic parameters, the Dubinin-Radushkevick equation and the comparative values of Δ int H for some Cu(II)-adsorbent interactions suggested that the adsorption of Cu(II) ions to vanillin-chitosan membranes show average results for both the diffusional (endothermic) and chemical bonding (exothermic) processes in relation to the temperature range studied

Computational Analysis of Nuclear Safety Parameters of 3 MW TRIGA Mark-II Research Reactor Based on Evaluated Nuclear Data Libraries JENDL-3.3 and ENDF/B-VII.0

International Nuclear Information System (INIS)

Khan, Jahirul Haque

2013-01-01

The objective of this study is to explain the main nuclear safety parameters of 3 MW TRIGA Mark-II Research Reactor at AERE, Savar, Dhaka, Bangladesh from the viewpoint of reactor safety and also reactor operator. The most important nuclear reactor physics safety parameters are power distribution, power peaking factors, shutdown margin, control rod worth, excess reactivity and fuel temperature reactivity coefficient. These parameters are calculated using the chain of the computer codes the SRAC-PIJ for cell calculation based on neutron transport theory and the SRAC-CITATION for core calculation based on neutron diffusion equation. To achieve this objective the TRIGA model is developed by the 3-D diffusion code SRAC-CITATION based on the group constants that come from the collision probability transport code SRAC-PIJ. In this study the evaluated nuclear data libraries JENDL-3.3 and ENDF/B-VII.0 are used. The calculated most important reactor physics parameters are compared to the safety analysis report (SAR) values as well as earlier published MCNP results (numerically benchmark). It was found that the calculated results show a good agreement between the said libraries. Besides, in most cases the calculated results reveal a reasonable agreement with the SAR values (by General Atomic) as well as the MCNP results. In addition, this analysis can be used as the inputs for thermal-hydraulic calculations of the TRIGA fresh core in the steady state and pulse mode operation. Because of power peaking factors, power distributions and temperature reactivity coefficients are the most important reactor safety parameters for normal operation and transient safety analysis in research as well as in power reactors. They form the basis for technical specifications and limitations for reactor operation such as loading pattern limitations for pulse operation (in TRIGA). Therefore, this analysis will be very important to develop the nuclear safety parameters data of 3 MW TRIGA Mark-II

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.)

Biological parameters for lung cancer in mathematical models of carcinogenesis

International Nuclear Information System (INIS)

Jacob, P.; Jacob, V.

2003-01-01

Applications of the two-step model of carcinogenesis with clonal expansion (TSCE) to lung cancer data are reviewed, including those on atomic bomb survivors from Hiroshima and Nagasaki, British doctors, Colorado Plateau miners, and Chinese tin miners. Different sets of identifiable model parameters are used in the literature. The parameter set which could be determined with the lowest uncertainty consists of the net proliferation rate gamma of intermediate cells, the hazard h 55 at an intermediate age, and the hazard H? at an asymptotically large age. Also, the values of these three parameters obtained in the various studies are more consistent than other identifiable combinations of the biological parameters. Based on representative results for these three parameters, implications for the biological parameters in the TSCE model are derived. (author)

Parameter sensitivity and uncertainty analysis for a storm surge and wave model

Directory of Open Access Journals (Sweden)

L. A. Bastidas

2016-09-01

Full Text Available Development and simulation of synthetic hurricane tracks is a common methodology used to estimate hurricane hazards in the absence of empirical coastal surge and wave observations. Such methods typically rely on numerical models to translate stochastically generated hurricane wind and pressure forcing into coastal surge and wave estimates. The model output uncertainty associated with selection of appropriate model parameters must therefore be addressed. The computational overburden of probabilistic surge hazard estimates is exacerbated by the high dimensionality of numerical surge and wave models. We present a model parameter sensitivity analysis of the Delft3D model for the simulation of hazards posed by Hurricane Bob (1991 utilizing three theoretical wind distributions (NWS23, modified Rankine, and Holland. The sensitive model parameters (of 11 total considered include wind drag, the depth-induced breaking γB, and the bottom roughness. Several parameters show no sensitivity (threshold depth, eddy viscosity, wave triad parameters, and depth-induced breaking αB and can therefore be excluded to reduce the computational overburden of probabilistic surge hazard estimates. The sensitive model parameters also demonstrate a large number of interactions between parameters and a nonlinear model response. While model outputs showed sensitivity to several parameters, the ability of these parameters to act as tuning parameters for calibration is somewhat limited as proper model calibration is strongly reliant on accurate wind and pressure forcing data. A comparison of the model performance with forcings from the different wind models is also presented.

Calibration of discrete element model parameters: soybeans

Science.gov (United States)

Ghodki, Bhupendra M.; Patel, Manish; Namdeo, Rohit; Carpenter, Gopal

2018-05-01

Discrete element method (DEM) simulations are broadly used to get an insight of flow characteristics of granular materials in complex particulate systems. DEM input parameters for a model are the critical prerequisite for an efficient simulation. Thus, the present investigation aims to determine DEM input parameters for Hertz-Mindlin model using soybeans as a granular material. To achieve this aim, widely acceptable calibration approach was used having standard box-type apparatus. Further, qualitative and quantitative findings such as particle profile, height of kernels retaining the acrylic wall, and angle of repose of experiments and numerical simulations were compared to get the parameters. The calibrated set of DEM input parameters includes the following (a) material properties: particle geometric mean diameter (6.24 mm); spherical shape; particle density (1220 kg m^{-3} ), and (b) interaction parameters such as particle-particle: coefficient of restitution (0.17); coefficient of static friction (0.26); coefficient of rolling friction (0.08), and particle-wall: coefficient of restitution (0.35); coefficient of static friction (0.30); coefficient of rolling friction (0.08). The results may adequately be used to simulate particle scale mechanics (grain commingling, flow/motion, forces, etc) of soybeans in post-harvest machinery and devices.

A three-dimensional cohesive sediment transport model with data assimilation: Model development, sensitivity analysis and parameter estimation

Science.gov (United States)

Wang, Daosheng; Cao, Anzhou; Zhang, Jicai; Fan, Daidu; Liu, Yongzhi; Zhang, Yue

2018-06-01

Based on the theory of inverse problems, a three-dimensional sigma-coordinate cohesive sediment transport model with the adjoint data assimilation is developed. In this model, the physical processes of cohesive sediment transport, including deposition, erosion and advection-diffusion, are parameterized by corresponding model parameters. These parameters are usually poorly known and have traditionally been assigned empirically. By assimilating observations into the model, the model parameters can be estimated using the adjoint method; meanwhile, the data misfit between model results and observations can be decreased. The model developed in this work contains numerous parameters; therefore, it is necessary to investigate the parameter sensitivity of the model, which is assessed by calculating a relative sensitivity function and the gradient of the cost function with respect to each parameter. The results of parameter sensitivity analysis indicate that the model is sensitive to the initial conditions, inflow open boundary conditions, suspended sediment settling velocity and resuspension rate, while the model is insensitive to horizontal and vertical diffusivity coefficients. A detailed explanation of the pattern of sensitivity analysis is also given. In ideal twin experiments, constant parameters are estimated by assimilating 'pseudo' observations. The results show that the sensitive parameters are estimated more easily than the insensitive parameters. The conclusions of this work can provide guidance for the practical applications of this model to simulate sediment transport in the study area.

Uncertainty of Modal Parameters Estimated by ARMA Models

DEFF Research Database (Denmark)

Jensen, Jacob Laigaard; Brincker, Rune; Rytter, Anders

1990-01-01

In this paper the uncertainties of identified modal parameters such as eidenfrequencies and damping ratios are assed. From the measured response of dynamic excited structures the modal parameters may be identified and provide important structural knowledge. However the uncertainty of the parameters...... by simulation study of a lightly damped single degree of freedom system. Identification by ARMA models has been choosen as system identification method. It is concluded that both the sampling interval and number of sampled points may play a significant role with respect to the statistical errors. Furthermore......, it is shown that the model errors may also contribute significantly to the uncertainty....

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...

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

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

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

Parameter optimization for surface flux transport models

Science.gov (United States)

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.

Atomistic modeling of structure II gas hydrate mechanics: Compressibility and equations of state

Science.gov (United States)

Vlasic, Thomas M.; Servio, Phillip; Rey, Alejandro D.

2016-08-01

This work uses density functional theory (DFT) to investigate the poorly characterized structure II gas hydrates, for various guests (empty, propane, butane, ethane-methane, propane-methane), at the atomistic scale to determine key structure and mechanical properties such as equilibrium lattice volume and bulk modulus. Several equations of state (EOS) for solids (Murnaghan, Birch-Murnaghan, Vinet, Liu) were fitted to energy-volume curves resulting from structure optimization simulations. These EOS, which can be used to characterize the compressional behaviour of gas hydrates, were evaluated in terms of their robustness. The three-parameter Vinet EOS was found to perform just as well if not better than the four-parameter Liu EOS, over the pressure range in this study. As expected, the Murnaghan EOS proved to be the least robust. Furthermore, the equilibrium lattice volumes were found to increase with guest size, with double-guest hydrates showing a larger increase than single-guest hydrates, which has significant implications for the widely used van der Waals and Platteeuw thermodynamic model for gas hydrates. Also, hydrogen bonds prove to be the most likely factor contributing to the resistance of gas hydrates to compression; bulk modulus was found to increase linearly with hydrogen bond density, resulting in a relationship that could be used predictively to determine the bulk modulus of various structure II gas hydrates. Taken together, these results fill a long existing gap in the material chemical physics of these important clathrates.

Atomistic modeling of structure II gas hydrate mechanics: Compressibility and equations of state

Directory of Open Access Journals (Sweden)

Thomas M. Vlasic

2016-08-01

Full Text Available This work uses density functional theory (DFT to investigate the poorly characterized structure II gas hydrates, for various guests (empty, propane, butane, ethane-methane, propane-methane, at the atomistic scale to determine key structure and mechanical properties such as equilibrium lattice volume and bulk modulus. Several equations of state (EOS for solids (Murnaghan, Birch-Murnaghan, Vinet, Liu were fitted to energy-volume curves resulting from structure optimization simulations. These EOS, which can be used to characterize the compressional behaviour of gas hydrates, were evaluated in terms of their robustness. The three-parameter Vinet EOS was found to perform just as well if not better than the four-parameter Liu EOS, over the pressure range in this study. As expected, the Murnaghan EOS proved to be the least robust. Furthermore, the equilibrium lattice volumes were found to increase with guest size, with double-guest hydrates showing a larger increase than single-guest hydrates, which has significant implications for the widely used van der Waals and Platteeuw thermodynamic model for gas hydrates. Also, hydrogen bonds prove to be the most likely factor contributing to the resistance of gas hydrates to compression; bulk modulus was found to increase linearly with hydrogen bond density, resulting in a relationship that could be used predictively to determine the bulk modulus of various structure II gas hydrates. Taken together, these results fill a long existing gap in the material chemical physics of these important clathrates.

Atomistic modeling of structure II gas hydrate mechanics: Compressibility and equations of state

Energy Technology Data Exchange (ETDEWEB)

Vlasic, Thomas M.; Servio, Phillip; Rey, Alejandro D., E-mail: alejandro.rey@mcgill.ca [Department of Chemical Engineering, McGill University, Montreal H3A 0C5 (Canada)

2016-08-15

This work uses density functional theory (DFT) to investigate the poorly characterized structure II gas hydrates, for various guests (empty, propane, butane, ethane-methane, propane-methane), at the atomistic scale to determine key structure and mechanical properties such as equilibrium lattice volume and bulk modulus. Several equations of state (EOS) for solids (Murnaghan, Birch-Murnaghan, Vinet, Liu) were fitted to energy-volume curves resulting from structure optimization simulations. These EOS, which can be used to characterize the compressional behaviour of gas hydrates, were evaluated in terms of their robustness. The three-parameter Vinet EOS was found to perform just as well if not better than the four-parameter Liu EOS, over the pressure range in this study. As expected, the Murnaghan EOS proved to be the least robust. Furthermore, the equilibrium lattice volumes were found to increase with guest size, with double-guest hydrates showing a larger increase than single-guest hydrates, which has significant implications for the widely used van der Waals and Platteeuw thermodynamic model for gas hydrates. Also, hydrogen bonds prove to be the most likely factor contributing to the resistance of gas hydrates to compression; bulk modulus was found to increase linearly with hydrogen bond density, resulting in a relationship that could be used predictively to determine the bulk modulus of various structure II gas hydrates. Taken together, these results fill a long existing gap in the material chemical physics of these important clathrates.

Global parameter estimation for thermodynamic models of transcriptional regulation.

Science.gov (United States)

Suleimenov, Yerzhan; Ay, Ahmet; Samee, Md Abul Hassan; Dresch, Jacqueline M; Sinha, Saurabh; Arnosti, David N

2013-07-15

Deciphering the mechanisms involved in gene regulation holds the key to understanding the control of central biological processes, including human disease, population variation, and the evolution of morphological innovations. New experimental techniques including whole genome sequencing and transcriptome analysis have enabled comprehensive modeling approaches to study gene regulation. In many cases, it is useful to be able to assign biological significance to the inferred model parameters, but such interpretation should take into account features that affect these parameters, including model construction and sensitivity, the type of fitness calculation, and the effectiveness of parameter estimation. This last point is often neglected, as estimation methods are often selected for historical reasons or for computational ease. Here, we compare the performance of two parameter estimation techniques broadly representative of local and global approaches, namely, a quasi-Newton/Nelder-Mead simplex (QN/NMS) method and a covariance matrix adaptation-evolutionary strategy (CMA-ES) method. The estimation methods were applied to a set of thermodynamic models of gene transcription applied to regulatory elements active in the Drosophila embryo. Measuring overall fit, the global CMA-ES method performed significantly better than the local QN/NMS method on high quality data sets, but this difference was negligible on lower quality data sets with increased noise or on data sets simplified by stringent thresholding. Our results suggest that the choice of parameter estimation technique for evaluation of gene expression models depends both on quality of data, the nature of the models [again, remains to be established] and the aims of the modeling effort. Copyright © 2013 Elsevier Inc. All rights reserved.

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.

Parameters Estimation of Geographically Weighted Ordinal Logistic Regression (GWOLR) Model

Science.gov (United States)

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.

Reflector modelization for neutronic diffusion and parameters identification

International Nuclear Information System (INIS)

Argaud, J.P.

1993-04-01

Physical parameters of neutronic diffusion equations can be adjusted to decrease calculations-measurements errors. The reflector being always difficult to modelize, we choose to elaborate a new reflector model and to use the parameters of this model as adjustment coefficients in the identification procedure. Using theoretical results, and also the physical behaviour of neutronic flux solutions, the reflector model consists then in its replacement by boundary conditions for the diffusion equations on the core only. This theoretical result of non-local operator relations leads then to some discrete approximations by taking into account the multiscaled behaviour, on the core-reflector interface, of neutronic diffusion solutions. The resulting model of this approach is then compared with previous reflector modelizations, and first results indicate that this new model gives the same representation of reflector for the core than previous. (author). 12 refs

Transient dynamic and modeling parameter sensitivity analysis of 1D solid oxide fuel cell model

International Nuclear Information System (INIS)

Huangfu, Yigeng; Gao, Fei; Abbas-Turki, Abdeljalil; Bouquain, David; Miraoui, Abdellatif

2013-01-01

Highlights: • A multiphysics, 1D, dynamic SOFC model is developed. • The presented model is validated experimentally in eight different operating conditions. • Electrochemical and thermal dynamic transient time expressions are given in explicit forms. • Parameter sensitivity is discussed for different semi-empirical parameters in the model. - Abstract: In this paper, a multiphysics solid oxide fuel cell (SOFC) dynamic model is developed by using a one dimensional (1D) modeling approach. The dynamic effects of double layer capacitance on the electrochemical domain and the dynamic effect of thermal capacity on thermal domain are thoroughly considered. The 1D approach allows the model to predict the non-uniform distributions of current density, gas pressure and temperature in SOFC during its operation. The developed model has been experimentally validated, under different conditions of temperature and gas pressure. Based on the proposed model, the explicit time constant expressions for different dynamic phenomena in SOFC have been given and discussed in detail. A parameters sensitivity study has also been performed and discussed by using statistical Multi Parameter Sensitivity Analysis (MPSA) method, in order to investigate the impact of parameters on the modeling accuracy

Coupled 1D-2D hydrodynamic inundation model for sewer overflow: Influence of modeling parameters

Directory of Open Access Journals (Sweden)

Adeniyi Ganiyu Adeogun

2015-10-01

Full Text Available This paper presents outcome of our investigation on the influence of modeling parameters on 1D-2D hydrodynamic inundation model for sewer overflow, developed through coupling of an existing 1D sewer network model (SWMM and 2D inundation model (BREZO. The 1D-2D hydrodynamic model was developed for the purpose of examining flood incidence due to surcharged water on overland surface. The investigation was carried out by performing sensitivity analysis on the developed model. For the sensitivity analysis, modeling parameters, such as mesh resolution Digital Elevation Model (DEM resolution and roughness were considered. The outcome of the study shows the model is sensitive to changes in these parameters. The performance of the model is significantly influenced, by the Manning's friction value, the DEM resolution and the area of the triangular mesh. Also, changes in the aforementioned modeling parameters influence the Flood characteristics, such as the inundation extent, the flow depth and the velocity across the model domain. Keywords: Inundation, DEM, Sensitivity analysis, Model coupling, Flooding

On the validity of evolutionary models with site-specific parameters.

Directory of Open Access Journals (Sweden)

Konrad Scheffler

Full Text Available Evolutionary models that make use of site-specific parameters have recently been criticized on the grounds that parameter estimates obtained under such models can be unreliable and lack theoretical guarantees of convergence. We present a simulation study providing empirical evidence that a simple version of the models in question does exhibit sensible convergence behavior and that additional taxa, despite not being independent of each other, lead to improved parameter estimates. Although it would be desirable to have theoretical guarantees of this, we argue that such guarantees would not be sufficient to justify the use of these models in practice. Instead, we emphasize the importance of taking the variance of parameter estimates into account rather than blindly trusting point estimates - this is standardly done by using the models to construct statistical hypothesis tests, which are then validated empirically via simulation studies.

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.

Pharmacophore Modelling and 4D-QSAR Study of Ruthenium(II) Arene Complexes as Anticancer Agents (Inhibitors) by Electron Conformational- Genetic Algorithm Method.

Science.gov (United States)

Yavuz, Sevtap Caglar; Sabanci, Nazmiye; Saripinar, Emin

2018-01-01

The EC-GA method was employed in this study as a 4D-QSAR method, for the identification of the pharmacophore (Pha) of ruthenium(II) arene complex derivatives and quantitative prediction of activity. The arrangement of the computed geometric and electronic parameters for atoms and bonds of each compound occurring in a matrix is known as the electron-conformational matrix of congruity (ECMC). It contains the data from HF/3-21G level calculations. Compounds were represented by a group of conformers for each compound rather than a single conformation, known as fourth dimension to generate the model. ECMCs were compared within a certain range of tolerance values by using the EMRE program and the responsible pharmacophore group for ruthenium(II) arene complex derivatives was found. For selecting the sub-parameter which had the most effect on activity in the series and the calculation of theoretical activity values, the non-linear least square method and genetic algorithm which are included in the EMRE program were used. In addition, compounds were classified as the training and test set and the accuracy of the models was tested by cross-validation statistically. The model for training and test sets attained by the optimum 10 parameters gave highly satisfactory results with R2 training= 0.817, q 2=0.718 and SEtraining=0.066, q2 ext1 = 0.867, q2 ext2 = 0.849, q2 ext3 =0.895, ccctr = 0.895, ccctest = 0.930 and cccall = 0.905. Since there is no 4D-QSAR research on metal based organic complexes in the literature, this study is original and gives a powerful tool to the design of novel and selective ruthenium(II) arene complexes. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Confocal arthroscopy-based patient-specific constitutive models of cartilaginous tissues - II: prediction of reaction force history of meniscal cartilage specimens.

Science.gov (United States)

Taylor, Zeike A; Kirk, Thomas B; Miller, Karol

2007-10-01

The theoretical framework developed in a companion paper (Part I) is used to derive estimates of mechanical response of two meniscal cartilage specimens. The previously developed framework consisted of a constitutive model capable of incorporating confocal image-derived tissue microstructural data. In the present paper (Part II) fibre and matrix constitutive parameters are first estimated from mechanical testing of a batch of specimens similar to, but independent from those under consideration. Image analysis techniques which allow estimation of tissue microstructural parameters form confocal images are presented. The constitutive model and image-derived structural parameters are then used to predict the reaction force history of the two meniscal specimens subjected to partially confined compression. The predictions are made on the basis of the specimens' individual structural condition as assessed by confocal microscopy and involve no tuning of material parameters. Although the model does not reproduce all features of the experimental curves, as an unfitted estimate of mechanical response the prediction is quite accurate. In light of the obtained results it is judged that more general non-invasive estimation of tissue mechanical properties is possible using the developed framework.

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

Parameter Optimisation for the Behaviour of Elastic Models over Time

DEFF Research Database (Denmark)

Mosegaard, Jesper

2004-01-01

Optimisation of parameters for elastic models is essential for comparison or finding equivalent behaviour of elastic models when parameters cannot simply be transferred or converted. This is the case with a large range of commonly used elastic models. In this paper we present a general method tha...

Recommended direct simulation Monte Carlo collision model parameters for modeling ionized air transport processes

Energy Technology Data Exchange (ETDEWEB)

Swaminathan-Gopalan, Krishnan; Stephani, Kelly A., E-mail: ksteph@illinois.edu [Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801 (United States)

2016-02-15

A systematic approach for calibrating the direct simulation Monte Carlo (DSMC) collision model parameters to achieve consistency in the transport processes is presented. The DSMC collision cross section model parameters are calibrated for high temperature atmospheric conditions by matching the collision integrals from DSMC against ab initio based collision integrals that are currently employed in the Langley Aerothermodynamic Upwind Relaxation Algorithm (LAURA) and Data Parallel Line Relaxation (DPLR) high temperature computational fluid dynamics solvers. The DSMC parameter values are computed for the widely used Variable Hard Sphere (VHS) and the Variable Soft Sphere (VSS) models using the collision-specific pairing approach. The recommended best-fit VHS/VSS parameter values are provided over a temperature range of 1000-20 000 K for a thirteen-species ionized air mixture. Use of the VSS model is necessary to achieve consistency in transport processes of ionized gases. The agreement of the VSS model transport properties with the transport properties as determined by the ab initio collision integral fits was found to be within 6% in the entire temperature range, regardless of the composition of the mixture. The recommended model parameter values can be readily applied to any gas mixture involving binary collisional interactions between the chemical species presented for the specified temperature range.

High value of the radiobiological parameter Dq correlates to expression of the transforming growth factor beta type II receptor in a panel of small cell lung cancer cell lines

DEFF Research Database (Denmark)

Hougaard, S; Krarup, M; Nørgaard, P

1998-01-01

Our panel of SCLC cell lines have previously been examined for their radiobiological characteristics and sensitivity to treatment with TGF beta 1. In this study we examined the possible correlations between radiobiological parameters and the expression of the TGF beta type II receptor (TGF beta......-rII). We have, in other studies, shown that the presence of TGF beta-rII was mandatory for transmitting the growth inhibitory effect of TGF beta. The results showed a statistically significant difference in Dq, i.e. the shoulder width of the survival curve, between cell lines expressing TGF beta......-rII and cell lines which did not express the receptor (P = 0.01). Cell lines expressing TGF beta-rII had a high Dq-value. TGF beta-rII expression did not correlate with any other radiobiological parameters. We suggest that an intact growth inhibitory pathway mediated by the TGF beta-rII may have a significant...

Assessment of structural model and parameter uncertainty with a multi-model system for soil water balance models

Science.gov (United States)

Michalik, Thomas; Multsch, Sebastian; Frede, Hans-Georg; Breuer, Lutz

2016-04-01

Water for agriculture is strongly limited in arid and semi-arid regions and often of low quality in terms of salinity. The application of saline waters for irrigation increases the salt load in the rooting zone and has to be managed by leaching to maintain a healthy soil, i.e. to wash out salts by additional irrigation. Dynamic simulation models are helpful tools to calculate the root zone water fluxes and soil salinity content in order to investigate best management practices. However, there is little information on structural and parameter uncertainty for simulations regarding the water and salt balance of saline irrigation. Hence, we established a multi-model system with four different models (AquaCrop, RZWQM, SWAP, Hydrus1D/UNSATCHEM) to analyze the structural and parameter uncertainty by using the Global Likelihood and Uncertainty Estimation (GLUE) method. Hydrus1D/UNSATCHEM and SWAP were set up with multiple sets of different implemented functions (e.g. matric and osmotic stress for root water uptake) which results in a broad range of different model structures. The simulations were evaluated against soil water and salinity content observations. The posterior distribution of the GLUE analysis gives behavioral parameters sets and reveals uncertainty intervals for parameter uncertainty. Throughout all of the model sets, most parameters accounting for the soil water balance show a low uncertainty, only one or two out of five to six parameters in each model set displays a high uncertainty (e.g. pore-size distribution index in SWAP and Hydrus1D/UNSATCHEM). The differences between the models and model setups reveal the structural uncertainty. The highest structural uncertainty is observed for deep percolation fluxes between the model sets of Hydrus1D/UNSATCHEM (~200 mm) and RZWQM (~500 mm) that are more than twice as high for the latter. The model sets show a high variation in uncertainty intervals for deep percolation as well, with an interquartile range (IQR) of

Two-loop renormalization in the standard model, part II. Renormalization procedures and computational techniques

Energy Technology Data Exchange (ETDEWEB)

Actis, S. [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany); Passarino, G. [Torino Univ. (Italy). Dipt. di Fisica Teorica; INFN, Sezione di Torino (Italy)

2006-12-15

In part I general aspects of the renormalization of a spontaneously broken gauge theory have been introduced. Here, in part II, two-loop renormalization is introduced and discussed within the context of the minimal Standard Model. Therefore, this paper deals with the transition between bare parameters and fields to renormalized ones. The full list of one- and two-loop counterterms is shown and it is proven that, by a suitable extension of the formalism already introduced at the one-loop level, two-point functions suffice in renormalizing the model. The problem of overlapping ultraviolet divergencies is analyzed and it is shown that all counterterms are local and of polynomial nature. The original program of 't Hooft and Veltman is at work. Finite parts are written in a way that allows for a fast and reliable numerical integration with all collinear logarithms extracted analytically. Finite renormalization, the transition between renormalized parameters and physical (pseudo-)observables, are discussed in part III where numerical results, e.g. for the complex poles of the unstable gauge bosons, are shown. An attempt is made to define the running of the electromagnetic coupling constant at the two-loop level. (orig.)

Survey of non-linear hydrodynamic models of type-II Cepheids

Science.gov (United States)

Smolec, R.

2016-03-01

We present a grid of non-linear convective type-II Cepheid models. The dense model grids are computed for 0.6 M⊙ and a range of metallicities ([Fe/H] = -2.0, -1.5, -1.0), and for 0.8 M⊙ ([Fe/H] = -1.5). Two sets of convective parameters are considered. The models cover the full temperature extent of the classical instability strip, but are limited in luminosity; for the most luminous models, violent pulsation leads to the decoupling of the outermost model shell. Hence, our survey reaches only the shortest period RV Tau domain. In the Hertzsprung-Russell diagram, we detect two domains in which period-doubled pulsation is possible. The first extends through the BL Her domain and low-luminosity W Vir domain (pulsation periods ˜2-6.5 d). The second domain extends at higher luminosities (W Vir domain; periods >9.5 d). Some models within these domains display period-4 pulsation. We also detect very narrow domains (˜10 K wide) in which modulation of pulsation is possible. Another interesting phenomenon we detect is double-mode pulsation in the fundamental mode and in the fourth radial overtone. Fourth overtone is a surface mode, trapped in the outer model layers. Single-mode pulsation in the fourth overtone is also possible on the hot side of the classical instability strip. The origin of the above phenomena is discussed. In particular, the role of resonances in driving different pulsation dynamics as well as in shaping the morphology of the radius variation curves is analysed.

Modelling tourists arrival using time varying parameter

Science.gov (United States)

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.

SPOTting model parameters using a ready-made Python package

Science.gov (United States)

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

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

COMPOSITIONS BASED ON PALLADIUM(II AND COPPER(II COMPOUNDS, HALIDE IONS, AND BENTONITE FOR OZONE DECOMPOSITION

Directory of Open Access Journals (Sweden)

T. L. Rakitskaya

2017-05-01

bromide ion. For Cu(II-KBr/N-Bent composition, kinetic and calculation data show that, in the presence of bromide ions, copper(II inhibits the ozone decomposition. For Pd(II-KBr/NBent composition, it has been found that the maximum activity is attained at СPd(II = 1.02·10-5 mol/g. For bimetallic Pd(II- Cu(II-KBr/N-Bent composition, changes in τ0, τ1/2, k1/2, and Q1/2 parameters depending on a Pd(II content are similar to those for monometallic Pd(II-KBr/NBent composition; however, values of the parameters are higher for the monometallic system. Thus, the inhibiting effect of Cu(II is observed even in the presence of palladium(II.

WATGIS: A GIS-Based Lumped Parameter Water Quality Model

Science.gov (United States)

Glenn P. Fernandez; George M. Chescheir; R. Wayne Skaggs; Devendra M. Amatya

2002-01-01

A Geographic Information System (GIS)­based, lumped parameter water quality model was developed to estimate the spatial and temporal nitrogen­loading 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...

Copper(II) complex with 6-methylpyridine-2-carboxyclic acid: Experimental and computational study on the XRD, FT-IR and UV-Vis spectra, refractive index, band gap and NLO parameters.

Science.gov (United States)

Altürk, Sümeyye; Avcı, Davut; Başoğlu, Adil; Tamer, Ömer; Atalay, Yusuf; Dege, Necmi

2018-02-05

Crystal structure of the synthesized copper(II) complex with 6-methylpyridine-2-carboxylic acid, [Cu(6-Mepic) 2 ·H 2 O]·H 2 O, was determined by XRD, FT-IR and UV-Vis spectroscopic techniques. Furthermore, the geometry optimization, harmonic vibration frequencies for the Cu(II) complex were carried out by using Density Functional Theory calculations with HSEh1PBE/6-311G(d,p)/LanL2DZ level. Electronic absorption wavelengths were obtained by using TD-DFT/HSEh1PBE/6-311G(d,p)/LanL2DZ level with CPCM model and major contributions were determined via Swizard/Chemissian program. Additionally, the refractive index, linear optical (LO) and non-nonlinear optical (NLO) parameters of the Cu(II) complex were calculated at HSEh1PBE/6-311G(d,p) level. The experimental and computed small energy gap shows the charge transfer in the Cu(II) complex. Finally, the hyperconjugative interactions and intramolecular charge transfer (ICT) were studied by performing of natural bond orbital (NBO) analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

LMFBR plant parameters

International Nuclear Information System (INIS)

1979-03-01

This document contains up-to-date data on existing or firmly decided prototype or demonstration LMFBR reactors (Table I), on planned commercial size LMFBR according to the present status of design (Table II) and on experimental fast reactors such as BOR-60, DFR, EBR-II, FERMI, FFTF, JOYO, KNK-II, PEC, RAPSODIE-FORTISSIMO (Table III). Only corrected and revised parameters submitted by the countries participating in the IWGFR are included in this document

Surface complexation modeling calculation of Pb(II) adsorption onto the calcined diatomite

Science.gov (United States)

Ma, Shu-Cui; Zhang, Ji-Lin; Sun, De-Hui; Liu, Gui-Xia

2015-12-01

Removal of noxious heavy metal ions (e.g. Pb(II)) by surface adsorption of minerals (e.g. diatomite) is an important means in the environmental aqueous pollution control. Thus, it is very essential to understand the surface adsorptive behavior and mechanism. In this work, the Pb(II) apparent surface complexation reaction equilibrium constants on the calcined diatomite and distributions of Pb(II) surface species were investigated through modeling calculations of Pb(II) based on diffuse double layer model (DLM) with three amphoteric sites. Batch experiments were used to study the adsorption of Pb(II) onto the calcined diatomite as a function of pH (3.0-7.0) and different ionic strengths (0.05 and 0.1 mol L-1 NaCl) under ambient atmosphere. Adsorption of Pb(II) can be well described by Freundlich isotherm models. The apparent surface complexation equilibrium constants (log K) were obtained by fitting the batch experimental data using the PEST 13.0 together with PHREEQC 3.1.2 codes and there is good agreement between measured and predicted data. Distribution of Pb(II) surface species on the diatomite calculated by PHREEQC 3.1.2 program indicates that the impurity cations (e.g. Al3+, Fe3+, etc.) in the diatomite play a leading role in the Pb(II) adsorption and dominant formation of complexes and additional electrostatic interaction are the main adsorption mechanism of Pb(II) on the diatomite under weak acidic conditions.

Modeling of radionuclide transport through rock formations and the resulting radiation exposure of reference persons. Calculations using Asse II parameters

International Nuclear Information System (INIS)

Kueppers, Christian; Ustohalova, Veronika; Steinhoff, Mathias

2012-01-01

The long-term release of radioactivity into the ground water path cannot be excluded for the radioactive waste repository Asse II. The possible radiological consequences were analyzed using a radio-ecological scenario developed by GRS. A second scenario was developed considering the solubility of radionuclides in salt saturated solutions and retarding/retention effects during the radionuclide transport through the cap rock layers. The modeling of possible radiation exposure was based on the lifestyle habits of reference persons. In Germany the calculation procedure for the prediction of radionuclide release from final repositories is not defined by national standards, the used procedures are based on analogue methods from other radiation protection calculations.

Estimations of parameters in Pareto reliability model in the presence of masked data

International Nuclear Information System (INIS)

Sarhan, Ammar M.

2003-01-01

Estimations of parameters included in the individual distributions of the life times of system components in a series system are considered in this paper based on masked system life test data. We consider a series system of two independent components each has a Pareto distributed lifetime. The maximum likelihood and Bayes estimators for the parameters and the values of the reliability of the system's components at a specific time are obtained. Symmetrical triangular prior distributions are assumed for the unknown parameters to be estimated in obtaining the Bayes estimators of these parameters. Large simulation studies are done in order: (i) explain how one can utilize the theoretical results obtained; (ii) compare the maximum likelihood and Bayes estimates obtained of the underlying parameters; and (iii) study the influence of the masking level and the sample size on the accuracy of the estimates obtained

NONLINEAR PLANT PIECEWISE-CONTINUOUS MODEL MATRIX PARAMETERS ESTIMATION

Directory of Open Access Journals (Sweden)

Roman L. Leibov

2017-09-01

Full Text Available This paper presents a nonlinear plant piecewise-continuous model matrix parameters estimation technique using nonlinear model time responses and random search method. One of piecewise-continuous model application areas is defined. The results of proposed approach application for aircraft turbofan engine piecewisecontinuous model formation are presented

On the biosorption, by brown seaweed, Lobophora variegata, of Ni(II) from aqueous solutions: equilibrium and thermodynamic studies.

Science.gov (United States)

Basha, Shaik; Jaiswar, Santlal; Jha, Bhavanath

2010-09-01

The biosorption equilibrium isotherms of Ni(II) onto marine brown algae Lobophora variegata, which was chemically-modified by CaCl(2) were studied and modeled. To predict the biosorption isotherms and to determine the characteristic parameters for process design, twenty-three one-, two-, three-, four- and five-parameter isotherm models were applied to experimental data. The interaction among biosorbed molecules is attractive and biosorption is carried out on energetically different sites and is an endothermic process. The five-parameter Fritz-Schluender model gives the most accurate fit with high regression coefficient, R (2) (0.9911-0.9975) and F-ratio (118.03-179.96), and low standard error, SE (0.0902-0.0.1556) and the residual or sum of square error, SSE (0.0012-0.1789) values to all experimental data in comparison to other models. The biosorption isotherm models fitted the experimental data in the order: Fritz-Schluender (five-parameter) > Freundlich (two-parameter) > Langmuir (two-parameter) > Khan (three-parameter) > Fritz-Schluender (four-parameter). The thermodynamic parameters such as DeltaG (0), DeltaH (0) and DeltaS (0) have been determined, which indicates the sorption of Ni(II) onto L. variegata was spontaneous and endothermic in nature.

A note on modeling of tumor regression for estimation of radiobiological parameters

International Nuclear Information System (INIS)

Zhong, Hualiang; Chetty, Indrin

2014-01-01

Purpose: Accurate calculation of radiobiological parameters is crucial to predicting radiation treatment response. Modeling differences may have a significant impact on derived parameters. In this study, the authors have integrated two existing models with kinetic differential equations to formulate a new tumor regression model for estimation of radiobiological parameters for individual patients. Methods: A system of differential equations that characterizes the birth-and-death process of tumor cells in radiation treatment was analytically solved. The solution of this system was used to construct an iterative model (Z-model). The model consists of three parameters: tumor doubling time T d , half-life of dead cells T r , and cell survival fraction SF D under dose D. The Jacobian determinant of this model was proposed as a constraint to optimize the three parameters for six head and neck cancer patients. The derived parameters were compared with those generated from the two existing models: Chvetsov's model (C-model) and Lim's model (L-model). The C-model and L-model were optimized with the parameter T d fixed. Results: With the Jacobian-constrained Z-model, the mean of the optimized cell survival fractions is 0.43 ± 0.08, and the half-life of dead cells averaged over the six patients is 17.5 ± 3.2 days. The parameters T r and SF D optimized with the Z-model differ by 1.2% and 20.3% from those optimized with the T d -fixed C-model, and by 32.1% and 112.3% from those optimized with the T d -fixed L-model, respectively. Conclusions: The Z-model was analytically constructed from the differential equations of cell populations that describe changes in the number of different tumor cells during the course of radiation treatment. The Jacobian constraints were proposed to optimize the three radiobiological parameters. The generated model and its optimization method may help develop high-quality treatment regimens for individual patients

Taylor expansion of luminosity distance in Szekeres cosmological models: effects of local structures evolution on cosmographic parameters

Energy Technology Data Exchange (ETDEWEB)

Villani, Mattia, E-mail: villani@fi.infn.it [Sezione INFN di Firenze, Polo Scientifico Via Sansone 1, 50019, Sesto Fiorentino (Italy)

2014-06-01

We consider the Goode-Wainwright representation of the Szekeres cosmological models and calculate the Taylor expansion of the luminosity distance in order to study the effects of the inhomogeneities on cosmographic parameters. Without making a particular choice for the arbitrary functions defining the metric, we Taylor expand up to the second order in redshift for Family I and up to the third order for Family II Szekeres metrics under the hypotesis, based on observation, that local structure formation is over. In a conservative fashion, we also allow for the existence of a non null cosmological constant.

On the effect of model parameters on forecast objects

Science.gov (United States)

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

2018-04-01

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

An automatic and effective parameter optimization method for model tuning

Directory of Open Access Journals (Sweden)

T. Zhang

2015-11-01

simulation results show that the optimum combination of these parameters determined using this method is able to improve the model's overall performance by 9 %. The proposed methodology and software framework can be easily applied to other GCMs to speed up the model development process, especially regarding unavoidable comprehensive parameter tuning during the model development stage.

A compact cyclic plasticity model with parameter evolution

DEFF Research Database (Denmark)

Krenk, Steen; Tidemann, L.

2017-01-01

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...

Modeling the World Health Organization Disability Assessment Schedule II using non-parametric item response models.

Science.gov (United States)

Galindo-Garre, Francisca; Hidalgo, María Dolores; Guilera, Georgina; Pino, Oscar; Rojo, J Emilio; Gómez-Benito, Juana

2015-03-01

The World Health Organization Disability Assessment Schedule II (WHO-DAS II) is a multidimensional instrument developed for measuring disability. It comprises six domains (getting around, self-care, getting along with others, life activities and participation in society). The main purpose of this paper is the evaluation of the psychometric properties for each domain of the WHO-DAS II with parametric and non-parametric Item Response Theory (IRT) models. A secondary objective is to assess whether the WHO-DAS II items within each domain form a hierarchy of invariantly ordered severity indicators of disability. A sample of 352 patients with a schizophrenia spectrum disorder is used in this study. The 36 items WHO-DAS II was administered during the consultation. Partial Credit and Mokken scale models are used to study the psychometric properties of the questionnaire. The psychometric properties of the WHO-DAS II scale are satisfactory for all the domains. However, we identify a few items that do not discriminate satisfactorily between different levels of disability and cannot be invariantly ordered in the scale. In conclusion the WHO-DAS II can be used to assess overall disability in patients with schizophrenia, but some domains are too general to assess functionality in these patients because they contain items that are not applicable to this pathology. Copyright © 2014 John Wiley & Sons, Ltd.

Luminescence model with quantum impact parameter for low energy ions

CERN Document Server

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.

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

Two-dimensional numerical modeling and solution of convection heat transfer in turbulent He II

Science.gov (United States)

Zhang, Burt X.; Karr, Gerald R.

1991-01-01

Numerical schemes are employed to investigate heat transfer in the turbulent flow of He II. FEM is used to solve a set of equations governing the heat transfer and hydrodynamics of He II in the turbulent regime. Numerical results are compared with available experimental data and interpreted in terms of conventional heat transfer parameters such as the Prandtl number, the Peclet number, and the Nusselt number. Within the prescribed Reynolds number domain, the Gorter-Mellink thermal counterflow mechanism becomes less significant, and He II acts like an ordinary fluid. The convection heat transfer characteristics of He II in the highly turbulent regime can be successfully described by using the conventional turbulence and heat transfer theories.

Repetitive Identification of Structural Systems Using a Nonlinear Model Parameter Refinement Approach

Directory of Open Access Journals (Sweden)

Jeng-Wen Lin

2009-01-01

Full Text Available This paper proposes a statistical confidence interval based nonlinear model parameter refinement approach for the health monitoring of structural systems subjected to seismic excitations. The developed model refinement approach uses the 95% confidence interval of the estimated structural parameters to determine their statistical significance in a least-squares regression setting. When the parameters' confidence interval covers the zero value, it is statistically sustainable to truncate such parameters. The remaining parameters will repetitively undergo such parameter sifting process for model refinement until all the parameters' statistical significance cannot be further improved. This newly developed model refinement approach is implemented for the series models of multivariable polynomial expansions: the linear, the Taylor series, and the power series model, leading to a more accurate identification as well as a more controllable design for system vibration control. Because the statistical regression based model refinement approach is intrinsically used to process a “batch” of data and obtain an ensemble average estimation such as the structural stiffness, the Kalman filter and one of its extended versions is introduced to the refined power series model for structural health monitoring.

On-line scheme for parameter estimation of nonlinear lithium ion battery equivalent circuit models using the simplified refined instrumental variable method for a modified Wiener continuous-time model

International Nuclear Information System (INIS)

Allafi, Walid; Uddin, Kotub; Zhang, Cheng; Mazuir Raja Ahsan Sha, Raja; Marco, James

2017-01-01

/Lithium-Nickel-Cobalt-Aluminium-Oxide (C 6 /LiNiCoAlO 2 ) lithium-ion cell. A comparison between the results obtained by the proposed method and by nonparametric frequency-based approaches for obtaining the model parameters is presented. It is shown that although both approaches give similar estimates, the advantages of the proposed method are (i) the simplicity by which the algorithm can be employed on-line for updating nonlinear equivalent circuit model (NL-ECM) parameters and (ii) the improved convergence efficiency of the on-line estimation.

Reopen parameter regions in two-Higgs doublet models

Science.gov (United States)

Staub, Florian

2018-01-01

The stability of the electroweak potential is a very important constraint for models of new physics. At the moment, it is standard for Two-Higgs doublet models (THDM), singlet or triplet extensions of the standard model to perform these checks at tree-level. However, these models are often studied in the presence of very large couplings. Therefore, it can be expected that radiative corrections to the potential are important. We study these effects at the example of the THDM type-II and find that loop corrections can revive more than 50% of the phenomenological viable points which are ruled out by the tree-level vacuum stability checks. Similar effects are expected for other extension of the standard model.

MODELING OF FUEL SPRAY CHARACTERISTICS AND DIESEL COMBUSTION CHAMBER PARAMETERS

Directory of Open Access Journals (Sweden)

G. M. Kukharonak

2011-01-01

Full Text Available The computer model for coordination of fuel spray characteristics with diesel combustion chamber parameters has been created in the paper.  The model allows to observe fuel sprays  develоpment in diesel cylinder at any moment of injection, to calculate characteristics of fuel sprays with due account of a shape and dimensions of a combustion chamber, timely to change fuel injection characteristics and supercharging parameters, shape and dimensions of a combustion chamber. Moreover the computer model permits to determine parameters of holes in an injector nozzle that provides the required fuel sprays characteristics at the stage of designing a diesel engine. Combustion chamber parameters for 4ЧН11/12.5 diesel engine have been determined in the paper.

Japanese proposal and contribution for IAEA/CRP on RIPL-II

International Nuclear Information System (INIS)

Fukahori, T.

1999-01-01

The Japanese Nuclear Data Committee (JNDC) organized an evaluating Calculation Support System Working Group (ECSS-WG) to investigate the subjects related to the RIPL-II project. The activities of this working group for validating model parameter and the development of the integrated nuclear data evaluation system (INDES) and its parameter database are briefly presented in this report

Four-parameter model for polarization-resolved rough-surface BRDF.

Science.gov (United States)

Renhorn, Ingmar G E; Hallberg, Tomas; Bergström, David; Boreman, Glenn D

2011-01-17

A modeling procedure is demonstrated, which allows representation of polarization-resolved BRDF data using only four parameters: the real and imaginary parts of an effective refractive index with an added parameter taking grazing incidence absorption into account and an angular-scattering parameter determined from the BRDF measurement of a chosen angle of incidence, preferably close to normal incidence. These parameters allow accurate predictions of s- and p-polarized BRDF for a painted rough surface, over three decades of variation in BRDF magnitude. To characterize any particular surface of interest, the measurements required to determine these four parameters are the directional hemispherical reflectance (DHR) for s- and p-polarized input radiation and the BRDF at a selected angle of incidence. The DHR data describes the angular and polarization dependence, as well as providing the overall normalization constraint. The resulting model conserves energy and fulfills the reciprocity criteria.

Evolving Non-Dominated Parameter Sets for Computational Models from Multiple Experiments

Science.gov (United States)

Lane, Peter C. R.; Gobet, Fernand

2013-03-01

Creating robust, reproducible and optimal computational models is a key challenge for theorists in many sciences. Psychology and cognitive science face particular challenges as large amounts of data are collected and many models are not amenable to analytical techniques for calculating parameter sets. Particular problems are to locate the full range of acceptable model parameters for a given dataset, and to confirm the consistency of model parameters across different datasets. Resolving these problems will provide a better understanding of the behaviour of computational models, and so support the development of general and robust models. In this article, we address these problems using evolutionary algorithms to develop parameters for computational models against multiple sets of experimental data; in particular, we propose the `speciated non-dominated sorting genetic algorithm' for evolving models in several theories. We discuss the problem of developing a model of categorisation using twenty-nine sets of data and models drawn from four different theories. We find that the evolutionary algorithms generate high quality models, adapted to provide a good fit to all available data.

On the relationship between input parameters in two-mass vocal-fold model with acoustical coupling an signal parameters of the glottal flow

NARCIS (Netherlands)

van Hirtum, Annemie; Lopez, Ines; Hirschberg, Abraham; Pelorson, Xavier

2003-01-01

In this paper the sensitivity of the two-mass model with acoustical coupling to the model input-parameters is assessed. The model-output or the glottal volume air flow is characterised by signal-parameters in the time-domain. The influence of changing input-parameters on the signal-parameters is

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...

Oyster Creek cycle 10 nodal model parameter optimization study using PSMS

International Nuclear Information System (INIS)

Dougher, J.D.

1987-01-01

The power shape monitoring system (PSMS) is an on-line core monitoring system that uses a three-dimensional nodal code (NODE-B) to perform nodal power calculations and compute thermal margins. The PSMS contains a parameter optimization function that improves the ability of NODE-B to accurately monitor core power distributions. This functions iterates on the model normalization parameters (albedos and mixing factors) to obtain the best agreement between predicted and measured traversing in-core probe (TIP) reading on a statepoint-by-statepoint basis. Following several statepoint optimization runs, an average set of optimized normalization parameters can be determined and can be implemented into the current or subsequent cycle core model for on-line core monitoring. A statistical analysis of 19 high-power steady-state state-points throughout Oyster Creek cycle 10 operation has shown a consistently poor virgin model performance. The normalization parameters used in the cycle 10 NODE-B model were based on a cycle 8 study, which evaluated only Exxon fuel types. The introduction of General Electric (GE) fuel into cycle 10 (172 assemblies) was a significant fuel/core design change that could have altered the optimum set of normalization parameters. Based on the need to evaluate a potential change in the model normalization parameters for cycle 11 and in an attempt to account for the poor cycle 10 model performance, a parameter optimization study was performed

Determining extreme parameter correlation in ground water models

DEFF Research Database (Denmark)

Hill, Mary Cole; Østerby, Ole

2003-01-01

can go undetected even by experienced modelers. Extreme parameter correlation can be detected using parameter correlation coefficients, but their utility depends on the presence of sufficient, but not excessive, numerical imprecision of the sensitivities, such as round-off error. This work...... investigates the information that can be obtained from parameter correlation coefficients in the presence of different levels of numerical imprecision, and compares it to the information provided by an alternative method called the singular value decomposition (SVD). Results suggest that (1) calculated...... 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...

FISPACT-II: An Advanced Simulation System for Activation, Transmutation and Material Modelling

Energy Technology Data Exchange (ETDEWEB)

Sublet, J.-Ch., E-mail: jean-christophe.sublet@ukaea.uk [United Kingdom Atomic Energy Authority, Culham Science Centre, Abingdon OX14 3DB (United Kingdom); Eastwood, J.W.; Morgan, J.G. [Culham Electromagnetics Ltd, Culham Science Centre, Abingdon OX14 3DB (United Kingdom); Gilbert, M.R.; Fleming, M.; Arter, W. [United Kingdom Atomic Energy Authority, Culham Science Centre, Abingdon OX14 3DB (United Kingdom)

2017-01-15

Fispact-II is a code system and library database for modelling activation-transmutation processes, depletion-burn-up, time dependent inventory and radiation damage source terms caused by nuclear reactions and decays. The Fispact-II code, written in object-style Fortran, follows the evolution of material irradiated by neutrons, alphas, gammas, protons, or deuterons, and provides a wide range of derived radiological output quantities to satisfy most needs for nuclear applications. It can be used with any ENDF-compliant group library data for nuclear reactions, particle-induced and spontaneous fission yields, and radioactive decay (including but not limited to TENDL-2015, ENDF/B-VII.1, JEFF-3.2, JENDL-4.0u, CENDL-3.1 processed into fine-group-structure files, GEFY-5.2 and UKDD-16), as well as resolved and unresolved resonance range probability tables for self-shielding corrections and updated radiological hazard indices. The code has many novel features including: extension of the energy range up to 1 GeV; additional neutron physics including self-shielding effects, temperature dependence, thin and thick target yields; pathway analysis; and sensitivity and uncertainty quantification and propagation using full covariance data. The latest ENDF libraries such as TENDL encompass thousands of target isotopes. Nuclear data libraries for Fispact-II are prepared from these using processing codes PREPRO, NJOY and CALENDF. These data include resonance parameters, cross sections with covariances, probability tables in the resonance ranges, PKA spectra, kerma, dpa, gas and radionuclide production and energy-dependent fission yields, supplemented with all 27 decay types. All such data for the five most important incident particles are provided in evaluated data tables. The Fispact-II simulation software is described in detail in this paper, together with the nuclear data libraries. The Fispact-II system also includes several utility programs for code-use optimisation

Kreditní rizika z pohledu Basel II

OpenAIRE

Čabrada, Jiří

2007-01-01

The thesis "Credit risk from Basel II point of view" deals with new capital concept with main focus on the credit risk. The particular emphasis is laid on the chief issue of Basel II concept i.e. internal models. The thesis quite in detail describes the usage of basel parameters - LGD particularly - in various day-to-day business processes of credit institutions. An individual part of the thesis is devoted to credit risk mitigants and their impacts on the amount of capital requirements. The a...

Time-varying parameter models for catchments with land use change: the importance of model structure

Science.gov (United States)

Pathiraja, Sahani; Anghileri, Daniela; Burlando, Paolo; Sharma, Ashish; Marshall, Lucy; Moradkhani, Hamid

2018-05-01

Rapid population and economic growth in Southeast Asia has been accompanied by extensive land use change with consequent impacts on catchment hydrology. Modeling methodologies capable of handling changing land use conditions are therefore becoming ever more important and are receiving increasing attention from hydrologists. A recently developed data-assimilation-based framework that allows model parameters to vary through time in response to signals of change in observations is considered for a medium-sized catchment (2880 km2) in northern Vietnam experiencing substantial but gradual land cover change. We investigate the efficacy of the method as well as the importance of the chosen model structure in ensuring the success of a time-varying parameter method. The method was used with two lumped daily conceptual models (HBV and HyMOD) that gave good-quality streamflow predictions during pre-change conditions. Although both time-varying parameter models gave improved streamflow predictions under changed conditions compared to the time-invariant parameter model, persistent biases for low flows were apparent in the HyMOD case. It was found that HyMOD was not suited to representing the modified baseflow conditions, resulting in extreme and unrealistic time-varying parameter estimates. This work shows that the chosen model can be critical for ensuring the time-varying parameter framework successfully models streamflow under changing land cover conditions. It can also be used to determine whether land cover changes (and not just meteorological factors) contribute to the observed hydrologic changes in retrospective studies where the lack of a paired control catchment precludes such an assessment.

Time-varying parameter models for catchments with land use change: the importance of model structure

Directory of Open Access Journals (Sweden)

S. Pathiraja

2018-05-01

Full Text Available Rapid population and economic growth in Southeast Asia has been accompanied by extensive land use change with consequent impacts on catchment hydrology. Modeling methodologies capable of handling changing land use conditions are therefore becoming ever more important and are receiving increasing attention from hydrologists. A recently developed data-assimilation-based framework that allows model parameters to vary through time in response to signals of change in observations is considered for a medium-sized catchment (2880 km2 in northern Vietnam experiencing substantial but gradual land cover change. We investigate the efficacy of the method as well as the importance of the chosen model structure in ensuring the success of a time-varying parameter method. The method was used with two lumped daily conceptual models (HBV and HyMOD that gave good-quality streamflow predictions during pre-change conditions. Although both time-varying parameter models gave improved streamflow predictions under changed conditions compared to the time-invariant parameter model, persistent biases for low flows were apparent in the HyMOD case. It was found that HyMOD was not suited to representing the modified baseflow conditions, resulting in extreme and unrealistic time-varying parameter estimates. This work shows that the chosen model can be critical for ensuring the time-varying parameter framework successfully models streamflow under changing land cover conditions. It can also be used to determine whether land cover changes (and not just meteorological factors contribute to the observed hydrologic changes in retrospective studies where the lack of a paired control catchment precludes such an assessment.

Sparticle mass hierarchies, simplified models from SUGRA unification, and benchmarks for LHC Run-II SUSY searches

International Nuclear Information System (INIS)

Francescone, David; Akula, Sujeet; Altunkaynak, Baris; Nath, Pran

2015-01-01

Sparticle mass hierarchies contain significant information regarding the origin and nature of supersymmetry breaking. The hierarchical patterns are severely constrained by electroweak symmetry breaking as well as by the astrophysical and particle physics data. They are further constrained by the Higgs boson mass measurement. The sparticle mass hierarchies can be used to generate simplified models consistent with the high scale models. In this work we consider supergravity models with universal boundary conditions for soft parameters at the unification scale as well as supergravity models with nonuniversalities and delineate the list of sparticle mass hierarchies for the five lightest sparticles. Simplified models can be obtained by a truncation of these, retaining a smaller set of lightest particles. The mass hierarchies and their truncated versions enlarge significantly the list of simplified models currently being used in the literature. Benchmarks for a variety of supergravity unified models appropriate for SUSY searches at future colliders are also presented. The signature analysis of two benchmark models has been carried out and a discussion of the searches needed for their discovery at LHC Run-II is given. An analysis of the spin-independent neutralino-proton cross section exhibiting the Higgs boson mass dependence and the hierarchical patterns is also carried out. It is seen that a knowledge of the spin-independent neutralino-proton cross section and the neutralino mass will narrow down the list of the allowed sparticle mass hierarchies. Thus dark matter experiments along with analyses for the LHC Run-II will provide strong clues to the nature of symmetry breaking at the unification scale.

Los Alamos progress report for RIPL-II

International Nuclear Information System (INIS)

Young, P.G.; Chadwick, M.B.; Moeller, P.

2000-01-01

Since the last RIPL-II CRP meeting, we have developed a code that prepares inputs from the RIPL-I optical model parameter data base for the SCAT2 and ECIS96 computer codes. We have also made limited corrections to the optical model parameter file, and have made minor extensions to the format for optical potentials. We have implemented mass information from the RIPL-I mass library into the ground-state mass/spin/parity file (Tape13) used in GNASH and other codes. Additionally, we have developed software for using the generalized superfluid level density model on SUN computers at LANL, ultimately for use of the RIPL-I level density information in the GNASH code. (author)

Metamodel-based inverse method for parameter identification: elastic-plastic damage model

Science.gov (United States)

Huang, Changwu; El Hami, Abdelkhalak; Radi, Bouchaïb

2017-04-01

This article proposed a metamodel-based inverse method for material parameter identification and applies it to elastic-plastic damage model parameter identification. An elastic-plastic damage model is presented and implemented in numerical simulation. The metamodel-based inverse method is proposed in order to overcome the disadvantage in computational cost of the inverse method. In the metamodel-based inverse method, a Kriging metamodel is constructed based on the experimental design in order to model the relationship between material parameters and the objective function values in the inverse problem, and then the optimization procedure is executed by the use of a metamodel. The applications of the presented material model and proposed parameter identification method in the standard A 2017-T4 tensile test prove that the presented elastic-plastic damage model is adequate to describe the material's mechanical behaviour and that the proposed metamodel-based inverse method not only enhances the efficiency of parameter identification but also gives reliable results.

House thermal model parameter estimation method for Model Predictive Control applications

NARCIS (Netherlands)

van Leeuwen, Richard Pieter; de Wit, J.B.; Fink, J.; Smit, Gerardus Johannes Maria

In this paper we investigate thermal network models with different model orders applied to various Dutch low-energy house types with high and low interior thermal mass and containing floor heating. Parameter estimations are performed by using data from TRNSYS simulations. The paper discusses results

Inverse modeling of hydrologic parameters using surface flux and runoff observations in the Community Land Model

Science.gov (United States)

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.

Lumped parameter models for the interpretation of environmental tracer data

Energy Technology Data Exchange (ETDEWEB)

Maloszewski, P [GSF-Inst. for Hydrology, Oberschleissheim (Germany); Zuber, A [Institute of Nuclear Physics, Cracow (Poland)

1996-10-01

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.

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

Uncertainty in the determination of soil hydraulic parameters and its influence on the performance of two hydrological models of different complexity

Directory of Open Access Journals (Sweden)

G. Baroni

2010-02-01

Full Text Available Data of soil hydraulic properties forms often a limiting factor in unsaturated zone modelling, especially at the larger scales. Investigations for the hydraulic characterization of soils are time-consuming and costly, and the accuracy of the results obtained by the different methodologies is still debated. However, we may wonder how the uncertainty in soil hydraulic parameters relates to the uncertainty of the selected modelling approach. We performed an intensive monitoring study during the cropping season of a 10 ha maize field in Northern Italy. The data were used to: i compare different methods for determining soil hydraulic parameters and ii evaluate the effect of the uncertainty in these parameters on different variables (i.e. evapotranspiration, average water content in the root zone, flux at the bottom boundary of the root zone simulated by two hydrological models of different complexity: SWAP, a widely used model of soil moisture dynamics in unsaturated soils based on Richards equation, and ALHyMUS, a conceptual model of the same dynamics based on a reservoir cascade scheme. We employed five direct and indirect methods to determine soil hydraulic parameters for each horizon of the experimental profile. Two methods were based on a parameter optimization of: a laboratory measured retention and hydraulic conductivity data and b field measured retention and hydraulic conductivity data. The remaining three methods were based on the application of widely used Pedo-Transfer Functions: c Rawls and Brakensiek, d HYPRES, and e ROSETTA. Simulations were performed using meteorological, irrigation and crop data measured at the experimental site during the period June – October 2006. Results showed a wide range of soil hydraulic parameter values generated with the different methods, especially for the saturated hydraulic conductivity K_sat and the shape parameter α of the van Genuchten curve. This is reflected in a variability of

Is there any correlation between model-based perfusion parameters and model-free parameters of time-signal intensity curve on dynamic contrast enhanced MRI in breast cancer patients?

Energy Technology Data Exchange (ETDEWEB)

Yi, Boram; Kang, Doo Kyoung; Kim, Tae Hee [Ajou University School of Medicine, Department of Radiology, Suwon, Gyeonggi-do (Korea, Republic of); Yoon, Dukyong [Ajou University School of Medicine, Department of Biomedical Informatics, Suwon (Korea, Republic of); Jung, Yong Sik; Kim, Ku Sang [Ajou University School of Medicine, Department of Surgery, Suwon (Korea, Republic of); Yim, Hyunee [Ajou University School of Medicine, Department of Pathology, Suwon (Korea, Republic of)

2014-05-15

To find out any correlation between dynamic contrast-enhanced (DCE) model-based parameters and model-free parameters, and evaluate correlations between perfusion parameters with histologic prognostic factors. Model-based parameters (Ktrans, Kep and Ve) of 102 invasive ductal carcinomas were obtained using DCE-MRI and post-processing software. Correlations between model-based and model-free parameters and between perfusion parameters and histologic prognostic factors were analysed. Mean Kep was significantly higher in cancers showing initial rapid enhancement (P = 0.002) and a delayed washout pattern (P = 0.001). Ve was significantly lower in cancers showing a delayed washout pattern (P = 0.015). Kep significantly correlated with time to peak enhancement (TTP) (ρ = -0.33, P < 0.001) and washout slope (ρ = 0.39, P = 0.002). Ve was significantly correlated with TTP (ρ = 0.33, P = 0.002). Mean Kep was higher in tumours with high nuclear grade (P = 0.017). Mean Ve was lower in tumours with high histologic grade (P = 0.005) and in tumours with negative oestrogen receptor status (P = 0.047). TTP was shorter in tumours with negative oestrogen receptor status (P = 0.037). We could acquire general information about the tumour vascular physiology, interstitial space volume and pathologic prognostic factors by analyzing time-signal intensity curve without a complicated acquisition process for the model-based parameters. (orig.)

Dynamics in the Parameter Space of a Neuron Model

Science.gov (United States)

Paulo, C. Rech

2012-06-01

Some two-dimensional parameter-space diagrams are numerically obtained by considering the largest Lyapunov exponent for a four-dimensional thirteen-parameter Hindmarsh—Rose neuron model. Several different parameter planes are considered, and it is shown that depending on the combination of parameters, a typical scenario can be preserved: for some choice of two parameters, the parameter plane presents a comb-shaped chaotic region embedded in a large periodic region. It is also shown that there exist regions close to these comb-shaped chaotic regions, separated by the comb teeth, organizing themselves in period-adding bifurcation cascades.

The Impact of Three Factors on the Recovery of Item Parameters for the Three-Parameter Logistic Model

Science.gov (United States)

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…

Condition Parameter Modeling for Anomaly Detection in Wind Turbines

Directory of Open Access Journals (Sweden)

Yonglong Yan

2014-05-01

Full Text Available Data collected from the supervisory control and data acquisition (SCADA system, used widely in wind farms to obtain operational and condition information about wind turbines (WTs, is of important significance for anomaly detection in wind turbines. The paper presents a novel model for wind turbine anomaly detection mainly based on SCADA data and a back-propagation neural network (BPNN for automatic selection of the condition parameters. The SCADA data sets are determined through analysis of the cumulative probability distribution of wind speed and the relationship between output power and wind speed. The automatic BPNN-based parameter selection is for reduction of redundant parameters for anomaly detection in wind turbines. Through investigation of cases of WT faults, the validity of the automatic parameter selection-based model for WT anomaly detection is verified.

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.

Determination of appropriate models and parameters for premixing calculations

International Nuclear Information System (INIS)

Park, Ik-Kyu; Kim, Jong-Hwan; Min, Beong-Tae; Hong, Seong-Wan

2008-03-01

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 2 O 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

A parameter network and model pyramid for managing technical information flow

International Nuclear Information System (INIS)

Sinnock, S.; Hartman, H.A.

1994-01-01

Prototypes of information management tools have been developed that can help communicate the technical basis for nuclear waste disposal to a broad audience of program scientists and engineers, project managers, and informed observers from stakeholder organizations. These tools include system engineering concepts, parameter networks expressed as influence diagrams, associated model hierarchies, and a relational database. These tools are used to express relationships among data-collection parameters, model input parameters, model output parameters, systems requirements, physical elements of a system description, and functional analysis of the contribution of physical elements and their associated parameters in satisfying the system requirements. By organizing parameters, models, physical elements, functions, and requirements in a visually reviewable network and a relational database the severe communication challenges facing participants in the nuclear waste dialog can be addressed. The network identifies the influences that data collected in the field have on measures of repository suitability, providing a visual, traceable map that clarifies the role of data and models in supporting conclusions about repository suitability. The map allows conclusions to be traced directly to the underlying parameters and models. Uncertainty in these underlying elements can be exposed to open review in the context of the effects uncertainty has on judgements about suitability. A parameter network provides a stage upon which an informed social dialog about the technical merits of a nuclear waste repository can be conducted. The basis for such dialog must be that stage, if decisions about repository suitability are to be based on a repository's ability to meet requirements embodied in laws and regulations governing disposal of nuclear wastes

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)

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

Frequency Domain Multi-parameter Full Waveform Inversion for Acoustic VTI Media

KAUST Repository

Djebbi, Ramzi

2017-05-26

Multi-parameter full waveform inversion (FWI) for transversely isotropic (TI) media with vertical axis of symmetry (VTI) suffers from the trade-off between the parameters. The trade-off results in the leakage of one parameter\\'s update into the other during the inversion. It affects the accuracy and convergence of the inversion. The sensitivity analyses suggested a parameterisation using the horizontal velocity vh, epsilon and eta to reduce the trade-off for surface recorded seismic data.We test the (vh, epsilon, eta) parameterisation for acoustic VTI media using a scattering integral (SI) based inversion. The data is modeled in frequency domain and the model is updated using a preconditioned conjugate gradient method. We applied the method to the VTI Marmousi II model and in the inversion, we keep eta parameter fixed as the background initial model and we invert simultaneously for both vh and epsilon. The results show the suitability of the parameterisation for multi-parameter VTI acoustic inversion as well as the accuracy of the inversion approach.

Uncertainty in dual permeability model parameters for structured soils

Science.gov (United States)

Arora, B.; Mohanty, B. P.; McGuire, J. T.

2012-01-01

Successful application of dual permeability models (DPM) to predict contaminant transport is contingent upon measured or inversely estimated soil hydraulic and solute transport parameters. The difficulty in unique identification of parameters for the additional macropore- and matrix-macropore interface regions, and knowledge about requisite experimental data for DPM has not been resolved to date. Therefore, this study quantifies uncertainty in dual permeability model parameters of experimental soil columns with different macropore distributions (single macropore, and low- and high-density multiple macropores). Uncertainty evaluation is conducted using adaptive Markov chain Monte Carlo (AMCMC) and conventional Metropolis-Hastings (MH) algorithms while assuming 10 out of 17 parameters to be uncertain or random. Results indicate that AMCMC resolves parameter correlations and exhibits fast convergence for all DPM parameters while MH displays large posterior correlations for various parameters. This study demonstrates that the choice of parameter sampling algorithms is paramount in obtaining unique DPM parameters when information on covariance structure is lacking, or else additional information on parameter correlations must be supplied to resolve the problem of equifinality of DPM parameters. This study also highlights the placement and significance of matrix-macropore interface in flow experiments of soil columns with different macropore densities. Histograms for certain soil hydraulic parameters display tri-modal characteristics implying that macropores are drained first followed by the interface region and then by pores of the matrix domain in drainage experiments. Results indicate that hydraulic properties and behavior of the matrix-macropore interface is not only a function of saturated hydraulic conductivity of the macroporematrix interface (Ksa) and macropore tortuosity (lf) but also of other parameters of the matrix and macropore domains.

Simultaneous Parameters Identifiability and Estimation of an E. coli Metabolic Network Model

Directory of Open Access Journals (Sweden)

Kese Pontes Freitas Alberton

2015-01-01

Full Text Available This work proposes a procedure for simultaneous parameters identifiability and estimation in metabolic networks in order to overcome difficulties associated with lack of experimental data and large number of parameters, a common scenario in the modeling of such systems. As case study, the complex real problem of parameters identifiability of the Escherichia coli K-12 W3110 dynamic model was investigated, composed by 18 differential ordinary equations and 35 kinetic rates, containing 125 parameters. With the procedure, model fit was improved for most of the measured metabolites, achieving 58 parameters estimated, including 5 unknown initial conditions. The results indicate that simultaneous parameters identifiability and estimation approach in metabolic networks is appealing, since model fit to the most of measured metabolites was possible even when important measures of intracellular metabolites and good initial estimates of parameters are not available.

Biosorption kinetics of Cd (II, Cr (III and Pb (II in aqueous solutions by olive stone

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M. Calero

2009-06-01

Full Text Available A by-product from olive oil production, olive stone, was investigated for the removal of Cd (II, Cr (III and Pb (II from aqueous solutions. The kinetics of biosorption are studied, analyzing the effect of the initial concentration of metal and temperature. Pseudo-first-order, pseudo-second-order, Elovich and intraparticle diffusion models have been used to represent the kinetics of the process and obtain the main kinetic parameters. The results show that the pseudo-second order model is the one that best describes the biosorption of the three metal ions for all the range of experimental conditions investigated. For the three metal ions, the maximum biosoption capacity and the initial biosorption rate increase when the initial metal concentration rises. However, the kinetic constant decreases when the initial metal concentration increases. The temperature effect on biosorption capacity for Cd (II and Cr (III is less significant; however, for Pb (II the effect of temperature is more important, especially when temperature rises from 25 to 40ºC. The biosorption capacity at mmol/g of olive stone changes in the following order: Cr>Cd>Pb. Thus, for an initial concentration of 220 mg/ℓ, a maximum sorption capacity of 0.079 mmol/g for Cr (III, 0.065 mmol/g for Cd (II and 0.028 mmol/g for Pb (II has been obtained.

Distribution-centric 3-parameter thermodynamic models of partition gas chromatography.

Science.gov (United States)

Blumberg, Leonid M

2017-03-31

If both parameters (the entropy, ΔS, and the enthalpy, ΔH) of the classic van't Hoff model of dependence of distribution coefficients (K) of analytes on temperature (T) are treated as the temperature-independent constants then the accuracy of the model is known to be insufficient for the needed accuracy of retention time prediction. A more accurate 3-parameter Clarke-Glew model offers a way to treat ΔS and ΔH as functions, ΔS(T) and ΔH(T), of T. A known T-centric construction of these functions is based on relating them to the reference values (ΔS ref and ΔH ref ) corresponding to a predetermined reference temperature (T ref ). Choosing a single T ref for all analytes in a complex sample or in a large database might lead to practically irrelevant values of ΔS ref and ΔH ref for those analytes that have too small or too large retention factors at T ref . Breaking all analytes in several subsets each with its own T ref leads to discontinuities in the analyte parameters. These problems are avoided in the K-centric modeling where ΔS(T) and ΔS(T) and other analyte parameters are described in relation to their values corresponding to a predetermined reference distribution coefficient (K Ref ) - the same for all analytes. In this report, the mathematics of the K-centric modeling are described and the properties of several types of K-centric parameters are discussed. It has been shown that the earlier introduced characteristic parameters of the analyte-column interaction (the characteristic temperature, T char , and the characteristic thermal constant, θ char ) are a special chromatographically convenient case of the K-centric parameters. Transformations of T-centric parameters into K-centric ones and vice-versa as well as the transformations of one set of K-centric parameters into another set and vice-versa are described. Copyright © 2017 Elsevier B.V. All rights reserved.

Patient-specific parameter estimation in single-ventricle lumped circulation models under uncertainty

Science.gov (United States)

Schiavazzi, Daniele E.; Baretta, Alessia; Pennati, Giancarlo; Hsia, Tain-Yen; Marsden, Alison L.

2017-01-01

Summary Computational models of cardiovascular physiology can inform clinical decision-making, providing a physically consistent framework to assess vascular pressures and flow distributions, and aiding in treatment planning. In particular, lumped parameter network (LPN) models that make an analogy to electrical circuits offer a fast and surprisingly realistic method to reproduce the circulatory physiology. The complexity of LPN models can vary significantly to account, for example, for cardiac and valve function, respiration, autoregulation, and time-dependent hemodynamics. More complex models provide insight into detailed physiological mechanisms, but their utility is maximized if one can quickly identify patient specific parameters. The clinical utility of LPN models with many parameters will be greatly enhanced by automated parameter identification, particularly if parameter tuning can match non-invasively obtained clinical data. We present a framework for automated tuning of 0D lumped model parameters to match clinical data. We demonstrate the utility of this framework through application to single ventricle pediatric patients with Norwood physiology. Through a combination of local identifiability, Bayesian estimation and maximum a posteriori simplex optimization, we show the ability to automatically determine physiologically consistent point estimates of the parameters and to quantify uncertainty induced by errors and assumptions in the collected clinical data. We show that multi-level estimation, that is, updating the parameter prior information through sub-model analysis, can lead to a significant reduction in the parameter marginal posterior variance. We first consider virtual patient conditions, with clinical targets generated through model solutions, and second application to a cohort of four single-ventricle patients with Norwood physiology. PMID:27155892

Adaptive Parameter Estimation of Person Recognition Model in a Stochastic Human Tracking Process

Science.gov (United States)

Nakanishi, W.; Fuse, T.; Ishikawa, T.

2015-05-01

This paper aims at an estimation of parameters of person recognition models using a sequential Bayesian filtering method. In many human tracking method, any parameters of models used for recognize the same person in successive frames are usually set in advance of human tracking process. In real situation these parameters may change according to situation of observation and difficulty level of human position prediction. Thus in this paper we formulate an adaptive parameter estimation using general state space model. Firstly we explain the way to formulate human tracking in general state space model with their components. Then referring to previous researches, we use Bhattacharyya coefficient to formulate observation model of general state space model, which is corresponding to person recognition model. The observation model in this paper is a function of Bhattacharyya coefficient with one unknown parameter. At last we sequentially estimate this parameter in real dataset with some settings. Results showed that sequential parameter estimation was succeeded and were consistent with observation situations such as occlusions.

Constraining statistical-model parameters using fusion and spallation reactions

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Charity Robert J.

2011-10-01

Full Text Available The de-excitation of compound nuclei has been successfully described for several decades by means of statistical models. However, such models involve a large number of free parameters and ingredients that are often underconstrained by experimental data. We show how the degeneracy of the model ingredients can be partially lifted by studying different entrance channels for de-excitation, which populate different regions of the parameter space of the compound nucleus. Fusion reactions, in particular, play an important role in this strategy because they fix three out of four of the compound-nucleus parameters (mass, charge and total excitation energy. The present work focuses on fission and intermediate-mass-fragment emission cross sections. We prove how equivalent parameter sets for fusion-fission reactions can be resolved using another entrance channel, namely spallation reactions. Intermediate-mass-fragment emission can be constrained in a similar way. An interpretation of the best-fit IMF barriers in terms of the Wigner energies of the nascent fragments is discussed.

Model parameter learning using Kullback-Leibler divergence

Science.gov (United States)

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.

Good Models Gone Bad: Quantifying and Predicting Parameter-Induced Climate Model Simulation Failures

Science.gov (United States)

Lucas, D. D.; Klein, R.; Tannahill, J.; Brandon, S.; Covey, C. C.; Domyancic, D.; Ivanova, D. P.

2012-12-01

Simulations using IPCC-class climate models are subject to fail or crash for a variety of reasons. Statistical analysis of the failures can yield useful insights to better understand and improve the models. During the course of uncertainty quantification (UQ) ensemble simulations to assess the effects of ocean model parameter uncertainties on climate simulations, we experienced a series of simulation failures of the Parallel Ocean Program (POP2). About 8.5% of our POP2 runs failed for numerical reasons at certain combinations of parameter values. We apply support vector machine (SVM) classification from the fields of pattern recognition and machine learning to quantify and predict the probability of failure as a function of the values of 18 POP2 parameters. The SVM classifiers readily predict POP2 failures in an independent validation ensemble, and are subsequently used to determine the causes of the failures via a global sensitivity analysis. Four parameters related to ocean mixing and viscosity are identified as the major sources of POP2 failures. Our method can be used to improve the robustness of complex scientific models to parameter perturbations and to better steer UQ ensembles. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 and was funded by the Uncertainty Quantification Strategic Initiative Laboratory Directed Research and Development Project at LLNL under project tracking code 10-SI-013 (UCRL LLNL-ABS-569112).

Iterative integral parameter identification of a respiratory mechanics model.

Science.gov (United States)

Schranz, Christoph; Docherty, Paul D; Chiew, Yeong Shiong; Möller, Knut; Chase, J Geoffrey

2012-07-18

Patient-specific respiratory mechanics models can support the evaluation of optimal lung protective ventilator settings during ventilation therapy. Clinical application requires that the individual's model parameter values must be identified with information available at the bedside. Multiple linear regression or gradient-based parameter identification methods are highly sensitive to noise and initial parameter estimates. Thus, they are difficult to apply at the bedside to support therapeutic decisions. An iterative integral parameter identification method is applied to a second order respiratory mechanics model. The method is compared to the commonly used regression methods and error-mapping approaches using simulated and clinical data. The clinical potential of the method was evaluated on data from 13 Acute Respiratory Distress Syndrome (ARDS) patients. The iterative integral method converged to error minima 350 times faster than the Simplex Search Method using simulation data sets and 50 times faster using clinical data sets. Established regression methods reported erroneous results due to sensitivity to noise. In contrast, the iterative integral method was effective independent of initial parameter estimations, and converged successfully in each case tested. These investigations reveal that the iterative integral method is beneficial with respect to computing time, operator independence and robustness, and thus applicable at the bedside for this clinical application.

PIO I-II tendencies. Part 2. Improving the pilot modeling

Directory of Open Access Journals (Sweden)

Ioan URSU

2011-03-01

Full Text Available The study is conceived in two parts and aims to get some contributions to the problem ofPIO aircraft susceptibility analysis. Part I, previously published in this journal, highlighted the mainsteps of deriving a complex model of human pilot. The current Part II of the paper considers a properprocedure of the human pilot mathematical model synthesis in order to analyze PIO II typesusceptibility of a VTOL-type aircraft, related to the presence of position and rate-limited actuator.The mathematical tools are those of semi global stability theory developed in recent works.

Morphological and Biomechanical Differences in the Elastase and AngII apoE−/− Rodent Models of Abdominal Aortic Aneurysms

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Evan H. Phillips

2015-01-01

Full Text Available An abdominal aortic aneurysm (AAA is a potentially fatal cardiovascular disease with multifactorial development and progression. Two preclinical models of the disease (elastase perfusion and angiotensin II infusion in apolipoprotein-E-deficient animals have been developed to study the disease during its initiation and progression. To date, most studies have used ex vivo methods to examine disease characteristics such as expanded aortic diameter or analytic methods to look at circulating biomarkers. Herein, we provide evidence from in vivo ultrasound studies of the temporal changes occurring in biomechanical parameters and macromolecules of the aortic wall in each model. We present findings from 28-day studies in elastase-perfused rats and AngII apoE−/− mice. While each model develops AAAs specific to their induction method, they both share characteristics with human aneurysms, such as marked changes in vessel strain and blood flow velocity. Histology and nonlinear microscopy confirmed that both elastin and collagen, both important extracellular matrix molecules, are similarly affected in their levels and spatial distribution. Future studies could make use of the differences between these models in order to investigate mechanisms of disease progression or evaluate potential AAA treatments.

Modelling Zn(II) sorption onto clayey sediments using a multi-site ion-exchange model

International Nuclear Information System (INIS)

Tertre, E.; Beaucaire, C.; Coreau, N.; Juery, A.

2009-01-01

In environmental studies, it is necessary to be able to predict the behaviour of contaminants in more or less complex physico-chemical contexts. The improvement of this prediction partly depends on establishing thermodynamic models that can describe the behaviour of these contaminants and, in particular, the sorption reactions on mineral surfaces. In this way, based on the mass action law, it is possible to use surface complexation models and ion exchange models. Therefore, the aim of this study is (i) to develop an ion-exchange model able to describe the sorption of transition metal onto pure clay minerals and (ii) to test the ability of this approach to predict the sorption of these elements onto natural materials containing clay minerals (i.e. soils/sediments) under various chemical conditions. This study is focused on the behaviour of Zn(II) in the presence of clayey sediments. Considering that clay minerals are cation exchangers containing multiple sorption sites, it is possible to interpret the sorption of Zn(II), as well as competitor cations, by ion-exchange equilibria with the clay minerals. This approach is applied with success to interpret the experimental data obtained previously in the Zn(II)-H + -Na + -montmorillonite system. The authors' research team has already studied the behaviour of Na + , K + , Ca 2+ and Mg 2+ versus pH in terms of ion exchange onto pure montmorillonite, leading to the development of a thermodynamic database including the exchange site concentrations associated with montmorillonite and the selectivity coefficients of Na + , K + , Ca 2+ , Mg 2+ , and Zn 2+ versus H + . In the present study, experimental isotherms of Zn(II) on two different sediments in batch reactors at different pH and ionic strengths, using NaCl and CaSO 4 as electrolytes are reported. Assuming clay minerals are the main ion-exchanging phases, it is possible to predict Zn(II) sorption onto sediments under different experimental conditions, using the previously

Failure analysis of parameter-induced simulation crashes in climate models

Science.gov (United States)

Lucas, D. D.; Klein, R.; Tannahill, J.; Ivanova, D.; Brandon, S.; Domyancic, D.; Zhang, Y.

2013-08-01

Simulations using IPCC (Intergovernmental Panel on Climate Change)-class climate models are subject to fail or crash for a variety of reasons. Quantitative analysis of the failures can yield useful insights to better understand and improve the models. During the course of uncertainty quantification (UQ) ensemble simulations to assess the effects of ocean model parameter uncertainties on climate simulations, we experienced a series of simulation crashes within the Parallel Ocean Program (POP2) component of the Community Climate System Model (CCSM4). About 8.5% of our CCSM4 simulations failed for numerical reasons at combinations of POP2 parameter values. We applied support vector machine (SVM) classification from machine learning to quantify and predict the probability of failure as a function of the values of 18 POP2 parameters. A committee of SVM classifiers readily predicted model failures in an independent validation ensemble, as assessed by the area under the receiver operating characteristic (ROC) curve metric (AUC > 0.96). The causes of the simulation failures were determined through a global sensitivity analysis. Combinations of 8 parameters related to ocean mixing and viscosity from three different POP2 parameterizations were the major sources of the failures. This information can be used to improve POP2 and CCSM4 by incorporating correlations across the relevant parameters. Our method can also be used to quantify, predict, and understand simulation crashes in other complex geoscientific models.

A stochastic optimization model under modeling uncertainty and parameter certainty for groundwater remediation design-Part I. Model development

Energy Technology Data Exchange (ETDEWEB)

He, L., E-mail: li.he@ryerson.ca [Department of Civil Engineering, Faculty of Engineering, Architecture and Science, Ryerson University, 350 Victoria Street, Toronto, Ontario, M5B 2K3 (Canada); Huang, G.H. [Environmental Systems Engineering Program, Faculty of Engineering, University of Regina, Regina, Saskatchewan, S4S 0A2 (Canada); College of Urban Environmental Sciences, Peking University, Beijing 100871 (China); Lu, H.W. [Environmental Systems Engineering Program, Faculty of Engineering, University of Regina, Regina, Saskatchewan, S4S 0A2 (Canada)

2010-04-15

Solving groundwater remediation optimization problems based on proxy simulators can usually yield optimal solutions differing from the 'true' ones of the problem. This study presents a new stochastic optimization model under modeling uncertainty and parameter certainty (SOMUM) and the associated solution method for simultaneously addressing modeling uncertainty associated with simulator residuals and optimizing groundwater remediation processes. This is a new attempt different from the previous modeling efforts. The previous ones focused on addressing uncertainty in physical parameters (i.e. soil porosity) while this one aims to deal with uncertainty in mathematical simulator (arising from model residuals). Compared to the existing modeling approaches (i.e. only parameter uncertainty is considered), the model has the advantages of providing mean-variance analysis for contaminant concentrations, mitigating the effects of modeling uncertainties on optimal remediation strategies, offering confidence level of optimal remediation strategies to system designers, and reducing computational cost in optimization processes.

Single peak parameters technique for simultaneous measurements: Spectrophotometric sequential injection determination of Fe(II) and Fe(III).

Science.gov (United States)

Kozak, J; Paluch, J; Węgrzecka, A; Kozak, M; Wieczorek, M; Kochana, J; Kościelniak, P

2016-02-01

Spectrophotometric sequential injection system (SI) is proposed to automate the method of simultaneous determination of Fe(II) and Fe(III) on the basis of parameters of a single peak. In the developed SI system, sample and mixture of reagents (1,10-phenanthroline and sulfosalicylic acid) are introduced into a vessel, where in an acid environment (pH≅3) appropriate compounds of Fe(II) and Fe(III) with 1,10-phenanthroline and sulfosalicylic acid are formed, respectively. Then, in turn, air, sample, EDTA and sample again, are introduced into a holding coil. After the flow reversal, a segment of air is removed from the system by an additional valve and as EDTA replaces sulfosalicylic acid forming a more stable colorless compound with Fe(III), a complex signal is registered. Measurements are performed at wavelength 530 nm. The absorbance measured at minimum of the negative peak and the area or the absorbance measured at maximum of the signal can be used as measures corresponding to Fe(II) and Fe(III) concentrations, respectively. The time of the peak registration is about 2 min. Two-component calibration has been applied to analysis. Fe(II) and Fe(III) can be determined within the concentration ranges of 0.04-4.00 and 0.1-5.00 mg L(-1), with precision less than 2.8% and 1.7% (RSD), respectively and accuracy better than 7% (RE). The detection limit is 0.04 and 0.09 mg L(-1) for Fe(II) and Fe(III), respectively. The method was applied to analysis of artesian water samples. Copyright © 2015 Elsevier B.V. All rights reserved.

Parameter resolution in two models for cell survival after radiation

International Nuclear Information System (INIS)

Di Cera, E.; Andreasi Bassi, F.; Arcovito, G.

1989-01-01

The resolvability of model parameters for the linear-quadratic and the repair-misrepair models for cell survival after radiation has been studied by Monte Carlo simulations as a function of the number of experimental data points collected in a given dose range and the experimental error. Statistical analysis of the results reveals the range of experimental conditions under which the model parameters can be resolved with sufficient accuracy, and points out some differences in the operational aspects of the two models. (orig.)

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

Science.gov (United States)

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.

A practical approach to parameter estimation applied to model predicting heart rate regulation

DEFF Research Database (Denmark)

Olufsen, Mette; Ottesen, Johnny T.

2013-01-01

Mathematical models have long been used for prediction of dynamics in biological systems. Recently, several efforts have been made to render these models patient specific. One way to do so is to employ techniques to estimate parameters that enable model based prediction of observed quantities....... Knowledge of variation in parameters within and between groups of subjects have potential to provide insight into biological function. Often it is not possible to estimate all parameters in a given model, in particular if the model is complex and the data is sparse. However, it may be possible to estimate...... a subset of model parameters reducing the complexity of the problem. In this study, we compare three methods that allow identification of parameter subsets that can be estimated given a model and a set of data. These methods will be used to estimate patient specific parameters in a model predicting...

Dynamics of a neuron model in different two-dimensional parameter-spaces

International Nuclear Information System (INIS)

Rech, Paulo C.

2011-01-01

We report some two-dimensional parameter-space diagrams numerically obtained for the multi-parameter Hindmarsh-Rose neuron model. Several different parameter planes are considered, and we show that regardless of the combination of parameters, a typical scenario is preserved: for all choice of two parameters, the parameter-space presents a comb-shaped chaotic region immersed in a large periodic region. We also show that exist regions close these chaotic region, separated by the comb teeth, organized themselves in period-adding bifurcation cascades. - Research highlights: → We report parameter-spaces obtained for the Hindmarsh-Rose neuron model. → Regardless of the combination of parameters, a typical scenario is preserved. → The scenario presents a comb-shaped chaotic region immersed in a periodic region. → Periodic regions near the chaotic region are in period-adding bifurcation cascades.

The sensitivity of flowline models of tidewater glaciers to parameter uncertainty

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E. M. Enderlin

2013-10-01

Full Text Available Depth-integrated (1-D flowline models have been widely used to simulate fast-flowing tidewater glaciers and predict change because the continuous grounding line tracking, high horizontal resolution, and physically based calving criterion that are essential to realistic modeling of tidewater glaciers can easily be incorporated into the models while maintaining high computational efficiency. As with all models, the values for parameters describing ice rheology and basal friction must be assumed and/or tuned based on observations. For prognostic studies, these parameters are typically tuned so that the glacier matches observed thickness and speeds at an initial state, to which a perturbation is applied. While it is well know that ice flow models are sensitive to these parameters, the sensitivity of tidewater glacier models has not been systematically investigated. Here we investigate the sensitivity of such flowline models of outlet glacier dynamics to uncertainty in three key parameters that influence a glacier's resistive stress components. We find that, within typical observational uncertainty, similar initial (i.e., steady-state glacier configurations can be produced with substantially different combinations of parameter values, leading to differing transient responses after a perturbation is applied. In cases where the glacier is initially grounded near flotation across a basal over-deepening, as typically observed for rapidly changing glaciers, these differences can be dramatic owing to the threshold of stability imposed by the flotation criterion. The simulated transient response is particularly sensitive to the parameterization of ice rheology: differences in ice temperature of ~ 2 °C can determine whether the glaciers thin to flotation and retreat unstably or remain grounded on a marine shoal. Due to the highly non-linear dependence of tidewater glaciers on model parameters, we recommend that their predictions are accompanied by

Assessment of CREAMS [Chemicals, Runoff, and Erosion from Agricultural Management Systems] and ERHYM-II [Ekalaka Rangeland Hydrology and Yield Model] computer models for simulating soil water movement on the Idaho National Engineering Laboratory

International Nuclear Information System (INIS)

Laundre, J.W.

1990-05-01

The major goal of radioactive waste management is long-term containment of radioactive waste. Long-term containment is dependent on understanding water movement on, into, and through trench caps. Several computer simulation models are available for predicting water movement. Of the several computer models available, CREAMS (Chemicals, Runoff, and Erosion from Agricultural Management Systems) and ERHYM-II (Ekalaka Rangeland Hydrology and Yield Model) were tested for use on the Idaho National Engineering Laboratory (INEL). The models were calibrated, tested for sensitivity, and used to evaluate some basic trench cap designs. Each model was used to postdict soil moisture, evapotranspiration, and runoff of two watersheds for which such data were already available. Sensitivity of the models was tested by adjusting various input parameters from high to low values and then comparing model outputs to those generated from average values. Ten input parameters of the CREAMS model were tested for sensitivity. 17 refs., 23 figs., 20 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 ...

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

On the relationship between input parameters in the two-mass vocal-fold model with acoustical coupling and signal parameters of the glottal flow

NARCIS (Netherlands)

Hirtum, van A.; Lopez Arteaga, I.; Hirschberg, A.; Pelorson, X.

2003-01-01

In this paper the sensitivity of the two-mass model with acoustical coupling to the model input-parameters is assessed. The model-output or the glottal volume air flow is characterised by signal-parameters in the time-domain. The influence of changing input-parameters on the signal-parameters is

Structural information on the coordination compounds formed by manganese(II), cobalt(II), nickel(II), zinc(II), cadmium(II) and mercury(II) thiocyanates with 4-cyanopyridine N-oxide from their magnetic moments, electronic and infrared spectra