WorldWideScience

Sample records for relevant model parameters

  1. Integrating retention soil filters into urban hydrologic models - Relevant processes and important parameters

    Science.gov (United States)

    Bachmann-Machnik, Anna; Meyer, Daniel; Waldhoff, Axel; Fuchs, Stephan; Dittmer, Ulrich

    2018-04-01

    Retention Soil Filters (RSFs), a form of vertical flow constructed wetlands specifically designed for combined sewer overflow (CSO) treatment, have proven to be an effective tool to mitigate negative impacts of CSOs on receiving water bodies. Long-term hydrologic simulations are used to predict the emissions from urban drainage systems during planning of stormwater management measures. So far no universally accepted model for RSF simulation exists. When simulating hydraulics and water quality in RSFs, an appropriate level of detail must be chosen for reasonable balancing between model complexity and model handling, considering the model input's level of uncertainty. The most crucial parameters determining the resultant uncertainties of the integrated sewer system and filter bed model were identified by evaluating a virtual drainage system with a Retention Soil Filter for CSO treatment. To determine reasonable parameter ranges for RSF simulations, data of 207 events from six full-scale RSF plants in Germany were analyzed. Data evaluation shows that even though different plants with varying loading and operation modes were examined, a simple model is sufficient to assess relevant suspended solids (SS), chemical oxygen demand (COD) and NH4 emissions from RSFs. Two conceptual RSF models with different degrees of complexity were assessed. These models were developed based on evaluation of data from full scale RSF plants and column experiments. Incorporated model processes are ammonium adsorption in the filter layer and degradation during subsequent dry weather period, filtration of SS and particulate COD (XCOD) to a constant background concentration and removal of solute COD (SCOD) by a constant removal rate during filter passage as well as sedimentation of SS and XCOD in the filter overflow. XCOD, SS and ammonium loads as well as ammonium concentration peaks are discharged primarily via RSF overflow not passing through the filter bed. Uncertainties of the integrated

  2. Method for extracting relevant electrical parameters from graphene field-effect transistors using a physical model

    International Nuclear Information System (INIS)

    Boscá, A.; Pedrós, J.; Martínez, J.; Calle, F.

    2015-01-01

    Due to its intrinsic high mobility, graphene has proved to be a suitable material for high-speed electronics, where graphene field-effect transistor (GFET) has shown excellent properties. In this work, we present a method for extracting relevant electrical parameters from GFET devices using a simple electrical characterization and a model fitting. With experimental data from the device output characteristics, the method allows to calculate parameters such as the mobility, the contact resistance, and the fixed charge. Differentiated electron and hole mobilities and direct connection with intrinsic material properties are some of the key aspects of this method. Moreover, the method output values can be correlated with several issues during key fabrication steps such as the graphene growth and transfer, the lithographic steps, or the metalization processes, providing a flexible tool for quality control in GFET fabrication, as well as a valuable feedback for improving the material-growth process

  3. Method for extracting relevant electrical parameters from graphene field-effect transistors using a physical model

    Energy Technology Data Exchange (ETDEWEB)

    Boscá, A., E-mail: alberto.bosca@upm.es [Instituto de Sistemas Optoelectrónicos y Microtecnología, Universidad Politécnica de Madrid, Madrid 28040 (Spain); Dpto. de Ingeniería Electrónica, E.T.S.I. de Telecomunicación, Universidad Politécnica de Madrid, Madrid 28040 (Spain); Pedrós, J. [Instituto de Sistemas Optoelectrónicos y Microtecnología, Universidad Politécnica de Madrid, Madrid 28040 (Spain); Campus de Excelencia Internacional, Campus Moncloa UCM-UPM, Madrid 28040 (Spain); Martínez, J. [Instituto de Sistemas Optoelectrónicos y Microtecnología, Universidad Politécnica de Madrid, Madrid 28040 (Spain); Dpto. de Ciencia de Materiales, E.T.S.I de Caminos, Canales y Puertos, Universidad Politécnica de Madrid, Madrid 28040 (Spain); Calle, F. [Instituto de Sistemas Optoelectrónicos y Microtecnología, Universidad Politécnica de Madrid, Madrid 28040 (Spain); Dpto. de Ingeniería Electrónica, E.T.S.I. de Telecomunicación, Universidad Politécnica de Madrid, Madrid 28040 (Spain); Campus de Excelencia Internacional, Campus Moncloa UCM-UPM, Madrid 28040 (Spain)

    2015-01-28

    Due to its intrinsic high mobility, graphene has proved to be a suitable material for high-speed electronics, where graphene field-effect transistor (GFET) has shown excellent properties. In this work, we present a method for extracting relevant electrical parameters from GFET devices using a simple electrical characterization and a model fitting. With experimental data from the device output characteristics, the method allows to calculate parameters such as the mobility, the contact resistance, and the fixed charge. Differentiated electron and hole mobilities and direct connection with intrinsic material properties are some of the key aspects of this method. Moreover, the method output values can be correlated with several issues during key fabrication steps such as the graphene growth and transfer, the lithographic steps, or the metalization processes, providing a flexible tool for quality control in GFET fabrication, as well as a valuable feedback for improving the material-growth process.

  4. Modelling of interplanetary pickup ion fluxes and relevance for LISM parameters

    International Nuclear Information System (INIS)

    Fahr, H.J.; Rucinski, D.

    1989-01-01

    It has been known for many years that neutral interstellar atoms enter the solar system from the upwind side and penetrate deep into the inner heliosphere. Helium atoms, in particular, advance towards very small solar distances before they are ionized and then again convected as He - pickup ions outwards with the solar wind. Since these ions were recently detected in space, we concentrate here on calculations of He + production rates and He + fluxes. It is shown that inside 1 a.u., the He - production is essentially determined both by solar e.u.v. photoionization and by electron impact ionization. We calculate He + production rates as a function of space coordinates, taking into account the core-halo structure of the energy distribution of solar wind electrons and their temperature distribution with distance according to relevant solar wind models. For this purpose, a newly developed program to compute He densities was used. In contrast to the production of H + , the He - production rates are found to be higher on the downwind axis than on the upwind axis by a factor of 5. We also determine partial and total He + ion fluxes as a function of solar distance and longitude. It is interesting to note that only the values for total fluxes agree well with the integrated He + fluxes measured by the SULEICA experiment aboard the AMPTE satellite. This indicates that pickup ions under the influence of the intrinsic MHD wave turbulence in the solar wind change their primary seed distribution function by rapid pitch-angle scattering and subsequent adiabatic cooling. To interpret the He + intensity profile along the orbit of the Earth in terms of LISM helium parameters, we point to the need to take into account carefully electron impact ionization in order to prevent misinterpretations. (author)

  5. Application of all relevant feature selection for failure analysis of parameter-induced simulation crashes in climate models

    Science.gov (United States)

    Paja, W.; Wrzesień, M.; Niemiec, R.; Rudnicki, W. R.

    2015-07-01

    The climate models are extremely complex pieces of software. They reflect best knowledge on physical components of the climate, nevertheless, they contain several parameters, which are too weakly constrained by observations, and can potentially lead to a crash of simulation. Recently a study by Lucas et al. (2013) has shown that machine learning methods can be used for predicting which combinations of parameters can lead to crash of simulation, and hence which processes described by these parameters need refined analyses. In the current study we reanalyse the dataset used in this research using different methodology. We confirm the main conclusion of the original study concerning suitability of machine learning for prediction of crashes. We show, that only three of the eight parameters indicated in the original study as relevant for prediction of the crash are indeed strongly relevant, three other are relevant but redundant, and two are not relevant at all. We also show that the variance due to split of data between training and validation sets has large influence both on accuracy of predictions and relative importance of variables, hence only cross-validated approach can deliver robust prediction of performance and relevance of variables.

  6. Application of all-relevant feature selection for the failure analysis of parameter-induced simulation crashes in climate models

    Science.gov (United States)

    Paja, Wiesław; Wrzesien, Mariusz; Niemiec, Rafał; Rudnicki, Witold R.

    2016-03-01

    Climate models are extremely complex pieces of software. They reflect the best knowledge on the physical components of the climate; nevertheless, they contain several parameters, which are too weakly constrained by observations, and can potentially lead to a simulation crashing. Recently a study by Lucas et al. (2013) has shown that machine learning methods can be used for predicting which combinations of parameters can lead to the simulation crashing and hence which processes described by these parameters need refined analyses. In the current study we reanalyse the data set used in this research using different methodology. We confirm the main conclusion of the original study concerning the suitability of machine learning for the prediction of crashes. We show that only three of the eight parameters indicated in the original study as relevant for prediction of the crash are indeed strongly relevant, three others are relevant but redundant and two are not relevant at all. We also show that the variance due to the split of data between training and validation sets has a large influence both on the accuracy of predictions and on the relative importance of variables; hence only a cross-validated approach can deliver a robust prediction of performance and relevance of variables.

  7. Inverse analyses of effective diffusion parameters relevant for a two-phase moisture model of cementitious materials

    DEFF Research Database (Denmark)

    Addassi, Mouadh; Johannesson, Björn; Wadsö, Lars

    2018-01-01

    Here we present an inverse analyses approach to determining the two-phase moisture transport properties relevant to concrete durability modeling. The purposed moisture transport model was based on a continuum approach with two truly separate equations for the liquid and gas phase being connected...... test, and, (iv) capillary suction test. Mass change over time, as obtained from the drying test, the two different cup test intervals and the capillary suction test, was used to obtain the effective diffusion parameters using the proposed inverse analyses approach. The moisture properties obtained...

  8. Repository environmental parameters and models/methodologies relevant to assessing the performance of high-level waste packages in basalt, tuff, and salt

    Energy Technology Data Exchange (ETDEWEB)

    Claiborne, H.C.; Croff, A.G.; Griess, J.C.; Smith, F.J.

    1987-09-01

    This document provides specifications for models/methodologies that could be employed in determining postclosure repository environmental parameters relevant to the performance of high-level waste packages for the Basalt Waste Isolation Project (BWIP) at Richland, Washington, the tuff at Yucca Mountain by the Nevada Test Site, and the bedded salt in Deaf Smith County, Texas. Guidance is provided on the identify of the relevant repository environmental parameters; the models/methodologies employed to determine the parameters, and the input data base for the models/methodologies. Supporting studies included are an analysis of potential waste package failure modes leading to identification of the relevant repository environmental parameters, an evaluation of the credible range of the repository environmental parameters, and a summary of the review of existing models/methodologies currently employed in determining repository environmental parameters relevant to waste package performance. 327 refs., 26 figs., 19 tabs.

  9. Repository environmental parameters and models/methodologies relevant to assessing the performance of high-level waste packages in basalt, tuff, and salt

    International Nuclear Information System (INIS)

    Claiborne, H.C.; Croff, A.G.; Griess, J.C.; Smith, F.J.

    1987-09-01

    This document provides specifications for models/methodologies that could be employed in determining postclosure repository environmental parameters relevant to the performance of high-level waste packages for the Basalt Waste Isolation Project (BWIP) at Richland, Washington, the tuff at Yucca Mountain by the Nevada Test Site, and the bedded salt in Deaf Smith County, Texas. Guidance is provided on the identify of the relevant repository environmental parameters; the models/methodologies employed to determine the parameters, and the input data base for the models/methodologies. Supporting studies included are an analysis of potential waste package failure modes leading to identification of the relevant repository environmental parameters, an evaluation of the credible range of the repository environmental parameters, and a summary of the review of existing models/methodologies currently employed in determining repository environmental parameters relevant to waste package performance. 327 refs., 26 figs., 19 tabs

  10. Parsimonious relevance models

    NARCIS (Netherlands)

    Meij, E.; Weerkamp, W.; Balog, K.; de Rijke, M.; Myang, S.-H.; Oard, D.W.; Sebastiani, F.; Chua, T.-S.; Leong, M.-K.

    2008-01-01

    We describe a method for applying parsimonious language models to re-estimate the term probabilities assigned by relevance models. We apply our method to six topic sets from test collections in five different genres. Our parsimonious relevance models (i) improve retrieval effectiveness in terms of

  11. A simplified model for predicting malaria entomologic inoculation rates based on entomologic and parasitologic parameters relevant to control.

    Science.gov (United States)

    Killeen, G F; McKenzie, F E; Foy, B D; Schieffelin, C; Billingsley, P F; Beier, J C

    2000-05-01

    Malaria transmission intensity is modeled from the starting perspective of individual vector mosquitoes and is expressed directly as the entomologic inoculation rate (EIR). The potential of individual mosquitoes to transmit malaria during their lifetime is presented graphically as a function of their feeding cycle length and survival, human biting preferences, and the parasite sporogonic incubation period. The EIR is then calculated as the product of 1) the potential of individual vectors to transmit malaria during their lifetime, 2) vector emergence rate relative to human population size, and 3) the infectiousness of the human population to vectors. Thus, impacts on more than one of these parameters will amplify each other's effects. The EIRs transmitted by the dominant vector species at four malaria-endemic sites from Papua New Guinea, Tanzania, and Nigeria were predicted using field measurements of these characteristics together with human biting rate and human reservoir infectiousness. This model predicted EIRs (+/- SD) that are 1.13 +/- 0.37 (range = 0.84-1.59) times those measured in the field. For these four sites, mosquito emergence rate and lifetime transmission potential were more important determinants of the EIR than human reservoir infectiousness. This model and the input parameters from the four sites allow the potential impacts of various control measures on malaria transmission intensity to be tested under a range of endemic conditions. The model has potential applications for the development and implementation of transmission control measures and for public health education.

  12. Neuroprotective effects of riluzole in early phase Parkinson's disease on clinically relevant parameters in the marmoset MPTP model

    NARCIS (Netherlands)

    Verhave, P.S.; Jongsma, M.J.; Berg, R.M. van den; Vanwersch, R.A.P.; Smit, A.B.; Philippens, I.H.C.H.M.

    2012-01-01

    The present study evaluates neuroprotection in a marmoset MPTP (1-methyl-1,2,3,6-tetrahydropyridine) model representing early Parkinson's disease (PD). The anti-glutamatergic compound riluzole is used as a model compound for neuroprotection. The compound is one of the few protective compounds used

  13. A SIMPLIFIED MODEL FOR PREDICTING MALARIA ENTOMOLOGIC INOCULATION RATES BASED ON ENTOMOLOGIC AND PARASITOLOGIC PARAMETERS RELEVANT TO CONTROL

    OpenAIRE

    KILLEEN, GERRY F.; McKENZIE, F. ELLIS; FOY, BRIAN D.; SCHIEFFELIN, CATHERINE; BILLINGSLEY, PETER F.; BEIER, JOHN C.

    2000-01-01

    Malaria transmission intensity is modeled from the starting perspective of individual vector mosquitoes and is expressed directly as the entomologic inoculation rate (EIR). The potential of individual mosquitoes to transmit malaria during their lifetime is presented graphically as a function of their feeding cycle length and survival, human biting preferences, and the parasite sporogonic incubation period. The EIR is then calculated as the product of 1) the potential of individual vectors to ...

  14. Migration of radionuclides with ground water: a discussion of the relevance of the input parameters used in model calculations

    International Nuclear Information System (INIS)

    Jensen, B.S.

    1982-01-01

    It is probably obvious to all, that establishing the scientific basis of geological waste disposal by going deeper and deeper in detail, may fill out the working hours of hundreds of scientists for hundreds of years. Such an endeavor is, however, impossible to attain, and we are forced to define some criteria telling us and others when knowledge and insight is sufficient. In thepresent case of geological disposal one need to be able to predict migration behavior of a series of radionuclides under diverse conditions to ascertain that unacceptable transfer to the biosphere never occurs. We have already collected a huge amount of data concerning migration phenomena, some very useful, oter less so, but we still need investigatoins departing from the simple ideal concepts, which most often have provided modellers with input data to their calculations. I therefore advocate that basic research is pursued to the point where it is possible to put limits on the effect of the lesser known factors on the migration behavior of radionuclides. When such limits have been established, it will be possible to make calculations on the worst cases, which may also occur. Although I personally believe, that these extra investigations will prove additional safety in geological disposal, this fact will convince nobody, only experimental facts will do

  15. Effect of nonlinear void reactivity on bifurcation characteristics of a lumped-parameter model of a BWR: A study relevant to RBMK

    Energy Technology Data Exchange (ETDEWEB)

    Verma, Dinkar, E-mail: dinkar@iitk.ac.in [Nuclear Engineering and Technology Program, Indian Institute of Technology Kanpur, Kanpur 208 016 (India); Kalra, Manjeet Singh, E-mail: drmanjeet.singh@dituniversity.edu.in [DIT University, Dehradun 248 009 (India); Wahi, Pankaj, E-mail: wahi@iitk.ac.in [Department of Mechanical Engineering, Indian Institute of Technology Kanpur, Kanpur 208 016 (India)

    2017-04-15

    Highlights: • A simplified model with nonlinear void reactivity feedback is studied. • Method of multiple scales for nonlinear analysis and oscillation characteristics. • Second order void reactivity dominates in determining system dynamics. • Opposing signs of linear and quadratic void reactivity enhances global safety. - Abstract: In the present work, the effect of nonlinear void reactivity on the dynamics of a simplified lumped-parameter model for a boiling water reactor (BWR) is investigated. A mathematical model of five differential equations comprising of neutronics and thermal-hydraulics encompassing the nonlinearities associated with both the reactivity feedbacks and the heat transfer process has been used. To this end, we have considered parameters relevant to RBMK for which the void reactivity is known to be nonlinear. A nonlinear analysis of the model exploiting the method of multiple time scales (MMTS) predicts the occurrence of the two types of Hopf bifurcation, namely subcritical and supercritical, leading to the evolution of limit cycles for a range of parameters. Numerical simulations have been performed to verify the analytical results obtained by MMTS. The study shows that the nonlinear reactivity has a significant influence on the system dynamics. A parametric study with varying nominal reactor power and operating conditions in coolant channel has also been performed which shows the effect of change in concerned parameter on the boundary between regions of sub- and super-critical Hopf bifurcations in the space constituted by the two coefficients of reactivities viz. the void and the Doppler coefficient of reactivities. In particular, we find that introduction of a negative quadratic term in the void reactivity feedback significantly increases the supercritical region and dominates in determining the system dynamics.

  16. Lumped-parameter models

    Energy Technology Data Exchange (ETDEWEB)

    Ibsen, Lars Bo; Liingaard, M.

    2006-12-15

    A lumped-parameter model represents the frequency dependent soil-structure interaction of a massless foundation placed on or embedded into an unbounded soil domain. In this technical report the steps of establishing a lumped-parameter model are presented. Following sections are included in this report: Static and dynamic formulation, Simple lumped-parameter models and Advanced lumped-parameter models. (au)

  17. Safe structural food bolus in elderly: the relevant parameters

    OpenAIRE

    Vandenberghe-Descamps, Mathilde; Septier, Chantal; Prot, Aurélie; Tournier, Carole; Hennequin, Martine; Vigneau, Evelyne; Feron, Gilles; Labouré, Hélène

    2017-01-01

    Mastication is essential to prepare food into a bolus ready to be swallowed safely, with no choking risk. Based on food bolus properties, a masticatory normative indicator was developed by Woda et al. (2010) to identify impaired masticatory function within good oral health population. The aim of the present study was to identify relevant parameters of bolus' structure to differentiate safe to unsafe bolus among elderly contrasting by their dental status.93 elderly, 58% with at least 7 posteri...

  18. Other relevant numerical modelling papers

    International Nuclear Information System (INIS)

    Chartier, M.

    1989-01-01

    The ocean modelling is a rapidly evolving science and a large number of results have been published. Several categories of papers are of particular interest for this review: the papers published by the international atomic institutions, such as the NEA (for the CRESP or Subseabed Programs), the IAEA (for example the Safety Series, the Technical Report Series or the TECDOC), and the ICRP, and the papers concerned by more fundamental research, which are published in specific scientific literature. This paper aims to list some of the most relevant publications for the CRESP purposes. It means by no way to be exhaustive, but informative on the incontestable progress recently achieved in that field. One should note that some of these papers are so recent that their final version has not yet been published

  19. Modeling of Toxicity-Relevant Electrophilic Reactivity for Guanine with Epoxides: Estimating the Hard and Soft Acids and Bases (HSAB) Parameter as a Predictor.

    Science.gov (United States)

    Zhang, Jing; Wang, Chenchen; Ji, Li; Liu, Weiping

    2016-05-16

    According to the electrophilic theory in toxicology, many chemical carcinogens in the environment and/or their active metabolites are electrophiles that exert their effects by forming covalent bonds with nucleophilic DNA centers. The theory of hard and soft acids and bases (HSAB), which states that a toxic electrophile reacts preferentially with a biological macromolecule that has a similar hardness or softness, clarifies the underlying chemistry involved in this critical event. Epoxides are hard electrophiles that are produced endogenously by the enzymatic oxidation of parent chemicals (e.g., alkenes and PAHs). Epoxide ring opening proceeds through a SN2-type mechanism with hard nucleophile DNA sites as the major facilitators of toxic effects. Thus, the quantitative prediction of chemical reactivity would enable a predictive assessment of the molecular potential to exert electrophile-mediated toxicity. In this study, we calculated the activation energies for reactions between epoxides and the guanine N7 site for a diverse set of epoxides, including aliphatic epoxides, substituted styrene oxides, and PAH epoxides, using a state-of-the-art density functional theory (DFT) method. It is worth noting that these activation energies for diverse epoxides can be further predicted by quantum chemically calculated nucleophilic indices from HSAB theory, which is a less computationally demanding method than the exacting procedure for locating the transition state. More importantly, the good qualitative/quantitative correlations between the chemical reactivity of epoxides and their bioactivity suggest that the developed model based on HSAB theory may aid in the predictive hazard evaluation of epoxides, enabling the early identification of mutagenicity/carcinogenicity-relevant SN2 reactivity.

  20. Nuclear models relevant to evaluation

    International Nuclear Information System (INIS)

    Arthur, E.D.; Chadwick, M.B.; Hale, G.M.; Young, P.G.

    1991-01-01

    The widespread use of nuclear models continues in the creation of data evaluations. The reasons include extension of data evaluations to higher energies, creation of data libraries for isotopic components of natural materials, and production of evaluations for radiative target species. In these cases, experimental data are often sparse or nonexistent. As this trend continues, the nuclear models employed in evaluation work move towards more microscopically-based theoretical methods, prompted in part by the availability of increasingly powerful computational resources. Advances in nuclear models applicable to evaluation will be reviewed. These include advances in optical model theory, microscopic and phenomenological state and level density theory, unified models that consistently describe both equilibrium and nonequilibrium reaction mechanism, and improved methodologies for calculation of prompt radiation from fission. 84 refs., 8 figs

  1. Passage relevance models for genomics search

    Directory of Open Access Journals (Sweden)

    Frieder Ophir

    2009-03-01

    Full Text Available Abstract We present a passage relevance model for integrating syntactic and semantic evidence of biomedical concepts and topics using a probabilistic graphical model. Component models of topics, concepts, terms, and document are represented as potential functions within a Markov Random Field. The probability of a passage being relevant to a biologist's information need is represented as the joint distribution across all potential functions. Relevance model feedback of top ranked passages is used to improve distributional estimates of query concepts and topics in context, and a dimensional indexing strategy is used for efficient aggregation of concept and term statistics. By integrating multiple sources of evidence including dependencies between topics, concepts, and terms, we seek to improve genomics literature passage retrieval precision. Using this model, we are able to demonstrate statistically significant improvements in retrieval precision using a large genomics literature corpus.

  2. Electroconvulsive Therapy In Neuropsychiatry : Relevance Of Seizure Parameters

    Directory of Open Access Journals (Sweden)

    Gangadhar BN

    2000-01-01

    Full Text Available Electroconvulsive therapy (ECT is used to induce therapeutic seizures in various clinical conditions. It is specifically useful in depression, catatonia, patients with high suicidal risk, and those intolerant to drugs. Its beneficial effects surpass its side effects. Memory impairment is benign and transient. Its mechanism of action is unknown, though numerous neurotransmitters and neuroreceptors have been implicated. The standards of ECT practice are well established but still evolving in some particularly in unilateral ECT. Assessment of threshold by formula method may deliver higher stimulus dose compared with titration method. Cerebral seizure during ECT procedure is necessary. Motor (cuff method and EEG seizure monitoring are mandatory. Recent studies have shown some EEG parameters (amplitude, fractal dimension, symmetry, and post ictal suppression to be associated with therapeutic outcome. Besides seizure monitoring, measuring other physiological parameters such as heart rate (HR and blood pressure (BP may be useful indicators of therapeutic response. Use of ECT in neurological conditions as well as its application in psychiatric illnesses associated with neurological disorders has also been reviewed briefly.

  3. Using ANFIS for selection of more relevant parameters to predict dew point temperature

    International Nuclear Information System (INIS)

    Mohammadi, Kasra; Shamshirband, Shahaboddin; Petković, Dalibor; Yee, Por Lip; Mansor, Zulkefli

    2016-01-01

    Highlights: • ANFIS is used to select the most relevant variables for dew point temperature prediction. • Two cities from the central and south central parts of Iran are selected as case studies. • Influence of 5 parameters on dew point temperature is evaluated. • Appropriate selection of input variables has a notable effect on prediction. • Considering the most relevant combination of 2 parameters would be more suitable. - Abstract: In this research work, for the first time, the adaptive neuro fuzzy inference system (ANFIS) is employed to propose an approach for identifying the most significant parameters for prediction of daily dew point temperature (T_d_e_w). The ANFIS process for variable selection is implemented, which includes a number of ways to recognize the parameters offering favorable predictions. According to the physical factors influencing the dew formation, 8 variables of daily minimum, maximum and average air temperatures (T_m_i_n, T_m_a_x and T_a_v_g), relative humidity (R_h), atmospheric pressure (P), water vapor pressure (V_P), sunshine hour (n) and horizontal global solar radiation (H) are considered to investigate their effects on T_d_e_w. The used data include 7 years daily measured data of two Iranian cities located in the central and south central parts of the country. The results indicate that despite climate difference between the considered case studies, for both stations, V_P is the most influential variable while R_h is the least relevant element. Furthermore, the combination of T_m_i_n and V_P is recognized as the most influential set to predict T_d_e_w. The conducted examinations show that there is a remarkable difference between the errors achieved for most and less relevant input parameters, which highlights the importance of appropriate selection of input parameters. The use of more than two inputs may not be advisable and appropriate; thus, considering the most relevant combination of 2 parameters would be more suitable

  4. Towards increased policy relevance in energy modeling

    Energy Technology Data Exchange (ETDEWEB)

    Worrell, Ernst; Ramesohl, Stephan; Boyd, Gale

    2003-07-29

    Historically, most energy models were reasonably equipped to assess the impact of a subsidy or change in taxation, but are often insufficient to assess the impact of more innovative policy instruments. We evaluate the models used to assess future energy use, focusing on industrial energy use. We explore approaches to engineering-economic analysis that could help improve the realism and policy relevance of engineering-economic modeling frameworks. We also explore solutions to strengthen the policy usefulness of engineering-economic analysis that can be built from a framework of multi-disciplinary cooperation. We focus on the so-called ''engineering-economic'' (or ''bottom-up'') models, as they include the amount of detail that is commonly needed to model policy scenarios. We identify research priorities for the modeling framework, technology representation in models, policy evaluation and modeling of decision-making behavior.

  5. 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.

  6. 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

  7. Safety analysis methodology with assessment of the impact of the prediction errors of relevant parameters

    International Nuclear Information System (INIS)

    Galia, A.V.

    2011-01-01

    The best estimate plus uncertainty approach (BEAU) requires the use of extensive resources and therefore it is usually applied for cases in which the available safety margin obtained with a conservative methodology can be questioned. Outside the BEAU methodology, there is not a clear approach on how to deal with the issue of considering the uncertainties resulting from prediction errors in the safety analyses performed for licensing submissions. However, the regulatory document RD-310 mentions that the analysis method shall account for uncertainties in the analysis data and models. A possible approach is presented, that is simple and reasonable, representing just the author's views, to take into account the impact of prediction errors and other uncertainties when performing safety analysis in line with regulatory requirements. The approach proposes taking into account the prediction error of relevant parameters. Relevant parameters would be those plant parameters that are surveyed and are used to initiate the action of a mitigating system or those that are representative of the most challenging phenomena for the integrity of a fission barrier. Examples of the application of the methodology are presented involving a comparison between the results with the new approach and a best estimate calculation during the blowdown phase for two small breaks in a generic CANDU 6 station. The calculations are performed with the CATHENA computer code. (author)

  8. Mathematical Properties Relevant to Geomagnetic Field Modeling

    DEFF Research Database (Denmark)

    Sabaka, Terence J.; Hulot, Gauthier; Olsen, Nils

    2010-01-01

    be directly measured. In this chapter, the mathematical foundation of global (as opposed to regional) geomagnetic field modeling is reviewed, and the spatial modeling of the field in spherical coordinates is focussed. Time can be dealt with as an independent variable and is not explicitly considered......Geomagnetic field modeling consists in converting large numbers of magnetic observations into a linear combination of elementary mathematical functions that best describes those observations.The set of numerical coefficients defining this linear combination is then what one refers.......The relevant elementary mathematical functions are introduced, their properties are reviewed, and how they can be used to describe the magnetic field in a source-free (such as the Earth’s neutral atmosphere) or source-dense (such as the ionosphere) environment is explained. Completeness and uniqueness...

  9. Mathematical Properties Relevant to Geomagnetic Field Modeling

    DEFF Research Database (Denmark)

    Sabaka, Terence J.; Hulot, Gauthier; Olsen, Nils

    2014-01-01

    be directly measured. In this chapter, the mathematical foundation of global (as opposed to regional) geomagnetic field modeling is reviewed, and the spatial modeling of the field in spherical coordinates is focused. Time can be dealt with as an independent variable and is not explicitly considered......Geomagnetic field modeling consists in converting large numbers of magnetic observations into a linear combination of elementary mathematical functions that best describes those observations. The set of numerical coefficients defining this linear combination is then what one refers....... The relevant elementary mathematical functions are introduced, their properties are reviewed, and how they can be used to describe the magnetic field in a source-free (such as the Earth’s neutral atmosphere) or source-dense (such as the ionosphere) environment is explained. Completeness and uniqueness...

  10. [Influence of reverse osmosis concentrate on physicochemical parameters of Sini decoction material system and their relevance].

    Science.gov (United States)

    Jin, Tang-Hui; Zhang, Liu-Hong; Zhu, Hua-Xu; Guo, Li-Wei; Li, Bo; Lu, Ming-Ming

    2014-04-01

    By studying the process of reverse osmosis system for traditional Chinese medicine materials physicochemical parameters affecting the osmotic pressure of its relevance, new compound system reverse osmosis process design methods were explored. Three concentrations materials for high, middle and low were dubbed with Sini decoction as a model drug, and pretreated by 50 thousand relative molecular weight cut-off ultrafiltration membrane. The viscosity, turbidity, conductivity, salinity, TDS, pH value and osmotic pressure of each sample were determined after the reverse osmosis to study the physical and chemical parameters between their respective correlations with the osmotic pressure, and characterized by HPLC chromatograms showing changes before and after the main chemical composition of samples of reverse osmosis. Conductivity-osmotic pressure, salinity-osmotic pressure of the linear correlation coefficient, TDS-osmotic pressure between the three sets of parameters were 0.963 8, 0.932 7, 0.973 7, respectively. Reverse osmosis concentrate and its characteristic spectrum ultrafiltrate HPLC similarity were up to 0. 968 or more, except the low concentrations. There is a significant correlation between the three physicochemical parameters (conductivity, salinity, TDS) and osmotic pressure of each sample system, and there is also significant linear correlation between salinity, conductivity, TDS. The original chemical composition of Sini decoction material concentrate was completely remained after the process of reverse osmosis.

  11. Structural Model Error and Decision Relevancy

    Science.gov (United States)

    Goldsby, M.; Lusk, G.

    2017-12-01

    The extent to which climate models can underwrite specific climate policies has long been a contentious issue. Skeptics frequently deny that climate models are trustworthy in an attempt to undermine climate action, whereas policy makers often desire information that exceeds the capabilities of extant models. While not skeptics, a group of mathematicians and philosophers [Frigg et al. (2014)] recently argued that even tiny differences between the structure of a complex dynamical model and its target system can lead to dramatic predictive errors, possibly resulting in disastrous consequences when policy decisions are based upon those predictions. They call this result the Hawkmoth effect (HME), and seemingly use it to rebuke rightwing proposals to forgo mitigation in favor of adaptation. However, a vigorous debate has emerged between Frigg et al. on one side and another philosopher-mathematician pair [Winsberg and Goodwin (2016)] on the other. On one hand, Frigg et al. argue that their result shifts the burden to climate scientists to demonstrate that their models do not fall prey to the HME. On the other hand, Winsberg and Goodwin suggest that arguments like those asserted by Frigg et al. can be, if taken seriously, "dangerous": they fail to consider the variety of purposes for which models can be used, and thus too hastily undermine large swaths of climate science. They put the burden back on Frigg et al. to show their result has any effect on climate science. This paper seeks to attenuate this debate by establishing an irenic middle position; we find that there is more agreement between sides than it first seems. We distinguish a `decision standard' from a `burden of proof', which helps clarify the contributions to the debate from both sides. In making this distinction, we argue that scientists bear the burden of assessing the consequences of HME, but that the standard Frigg et al. adopt for decision relevancy is too strict.

  12. The estimation of effective doses using measurement of several relevant physical parameters from radon exposures

    International Nuclear Information System (INIS)

    Ridzikova, A; Fronka, A.; Maly, B.; Moucka, L.

    2003-01-01

    In the present investigation, we will be study the dose relevant factors from continual monitoring in real homes into account getting more accurate estimation of 222 Rn the effective dose. The dose relevant parameters include the radon concentration, the equilibrium factor (f), the fraction (fp) of unattached radon decay products and real time occupancy people in home. The result of the measurement are the time courses of radon concentration that are based on estimation effective doses together with assessment of the real time occupancy people indoor. We found out by analysis that year effective dose is lower than effective dose estimated by ICRP recommendation from the integral measurement that included only average radon concentration. Our analysis of estimation effective doses using measurement of several physical parameters was made only in one case and for the better specification is important to measure in different real occupancy houses. (authors)

  13. Models for setting ATM parameter values

    DEFF Research Database (Denmark)

    Blaabjerg, Søren; Gravey, A.; Romæuf, L.

    1996-01-01

    essential to set traffic characteristic values that are relevant to the considered cell stream, and that ensure that the amount of non-conforming traffic is small. Using a queueing model representation for the GCRA formalism, several methods are available for choosing the traffic characteristics. This paper......In ATM networks, a user should negotiate at connection set-up a traffic contract which includes traffic characteristics and requested QoS. The traffic characteristics currently considered are the Peak Cell Rate, the Sustainable Cell Rate, the Intrinsic Burst Tolerance and the Cell Delay Variation...... (CDV) tolerance(s). The values taken by these traffic parameters characterize the so-called ''Worst Case Traffic'' that is used by CAC procedures for accepting a new connection and allocating resources to it. Conformance to the negotiated traffic characteristics is defined, at the ingress User...

  14. 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

  15. Towards policy relevant environmental modeling: contextual validity and pragmatic models

    Science.gov (United States)

    Miles, Scott B.

    2000-01-01

    "What makes for a good model?" In various forms, this question is a question that, undoubtedly, many people, businesses, and institutions ponder with regards to their particular domain of modeling. One particular domain that is wrestling with this question is the multidisciplinary field of environmental modeling. Examples of environmental models range from models of contaminated ground water flow to the economic impact of natural disasters, such as earthquakes. One of the distinguishing claims of the field is the relevancy of environmental modeling to policy and environment-related decision-making in general. A pervasive view by both scientists and decision-makers is that a "good" model is one that is an accurate predictor. Thus, determining whether a model is "accurate" or "correct" is done by comparing model output to empirical observations. The expected outcome of this process, usually referred to as "validation" or "ground truthing," is a stamp on the model in question of "valid" or "not valid" that serves to indicate whether or not the model will be reliable before it is put into service in a decision-making context. In this paper, I begin by elaborating on the prevailing view of model validation and why this view must change. Drawing from concepts coming out of the studies of science and technology, I go on to propose a contextual view of validity that can overcome the problems associated with "ground truthing" models as an indicator of model goodness. The problem of how we talk about and determine model validity has much to do about how we perceive the utility of environmental models. In the remainder of the paper, I argue that we should adopt ideas of pragmatism in judging what makes for a good model and, in turn, developing good models. From such a perspective of model goodness, good environmental models should facilitate communication, convey—not bury or "eliminate"—uncertainties, and, thus, afford the active building of consensus decisions, instead

  16. Are invertebrates relevant models in ageing research?

    DEFF Research Database (Denmark)

    Erdogan, Cihan Suleyman; Hansen, Benni Winding; Vang, Ole

    2016-01-01

    is an evolutionary conserved key protein kinase in the TOR pathway that regulates growth, proliferation and cell metabolism in response to nutrients, growth factors and stress. Comparing the ageing process in invertebrate model organisms with relatively short lifespan with mammals provides valuable information about...... the molecular mechanisms underlying the ageing process faster than mammal systems. Inhibition of the TOR pathway activity via either genetic manipulation or rapamycin increases lifespan profoundly in most invertebrate model organisms. This contribution will review the recent findings in invertebrates concerning...... the TOR pathway and effects of TOR inhibition by rapamycin on lifespan. Besides some contradictory results, the majority points out that rapamycin induces longevity. This suggests that administration of rapamycin in invertebrates is a promising tool for pursuing the scientific puzzle of lifespan...

  17. 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

  18. On relevant boundary perturbations of unitary minimal models

    International Nuclear Information System (INIS)

    Recknagel, A.; Roggenkamp, D.; Schomerus, V.

    2000-01-01

    We consider unitary Virasoro minimal models on the disk with Cardy boundary conditions and discuss deformations by certain relevant boundary operators, analogous to tachyon condensation in string theory. Concentrating on the least relevant boundary field, we can perform a perturbative analysis of renormalization group fixed points. We find that the systems always flow towards stable fixed points which admit no further (non-trivial) relevant perturbations. The new conformal boundary conditions are in general given by superpositions of 'pure' Cardy boundary conditions

  19. Location Criteria Relevant for Sustainability of Social Housing Model

    Directory of Open Access Journals (Sweden)

    Petković-Grozdanović Nataša

    2016-01-01

    Full Text Available Social housing models, which had began to develop during the last century, for their only objective had a need to overcome the housing problems of socially vulnerable categories. However, numerous studies have shown that these social categories, because of their low social status, are highly susceptible to various psychological and sociological problems. On the other hand a low level of quality, which was common for social housing dwellings, has further aggravated these problems by initiating trouble behaviours among tenants, affecting social exclusion and segregation. Contemporary social housing models are therefore conceptualized in a way to provide a positive psycho-sociological impact on their tenants. Therefore the planning approach in social housing should be such to: support important functions in daily life routines; promote tolerance and cooperation; influence on a sense of social order and belonging; affect the socialization of the tenant and their integration into the wider community; and improve social cohesion. Analysis of the influential location parameters of immediate and wider social housing environment strive to define the ones relevant to the life quality of social housing tenants and therefore influence on the sustainability of social housing model.

  20. 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.

  1. 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)

  2. Outcome quality of in-patient cardiac rehabilitation in elderly patients--identification of relevant parameters.

    Science.gov (United States)

    Salzwedel, Annett; Nosper, Manfred; Röhrig, Bernd; Linck-Eleftheriadis, Sigrid; Strandt, Gert; Völler, Heinz

    2014-02-01

    Outcome quality management requires the consecutive registration of defined variables. The aim was to identify relevant parameters in order to objectively assess the in-patient rehabilitation outcome. From February 2009 to June 2010 1253 patients (70.9 ± 7.0 years, 78.1% men) at 12 rehabilitation clinics were enrolled. Items concerning sociodemographic data, the impairment group (surgery, conservative/interventional treatment), cardiovascular risk factors, structural and functional parameters and subjective health were tested in respect of their measurability, sensitivity to change and their propensity to be influenced by rehabilitation. The majority of patients (61.1%) were referred for rehabilitation after cardiac surgery, 38.9% after conservative or interventional treatment for an acute coronary syndrome. Functionally relevant comorbidities were seen in 49.2% (diabetes mellitus, stroke, peripheral artery disease, chronic obstructive lung disease). In three key areas 13 parameters were identified as being sensitive to change and subject to modification by rehabilitation: cardiovascular risk factors (blood pressure, low-density lipoprotein cholesterol, triglycerides), exercise capacity (resting heart rate, maximal exercise capacity, maximal walking distance, heart failure, angina pectoris) and subjective health (IRES-24 (indicators of rehabilitation status): pain, somatic health, psychological well-being and depression as well as anxiety on the Hospital Anxiety and Depression Scale). The outcome of in-patient rehabilitation in elderly patients can be comprehensively assessed by the identification of appropriate key areas, that is, cardiovascular risk factors, exercise capacity and subjective health. This may well serve as a benchmark for internal and external quality management.

  3. 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

  4. 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

  5. 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.

  6. 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.

  7. 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...

  8. A Compositional Relevance Model for Adaptive Information Retrieval

    Science.gov (United States)

    Mathe, Nathalie; Chen, James; Lu, Henry, Jr. (Technical Monitor)

    1994-01-01

    There is a growing need for rapid and effective access to information in large electronic documentation systems. Access can be facilitated if information relevant in the current problem solving context can be automatically supplied to the user. This includes information relevant to particular user profiles, tasks being performed, and problems being solved. However most of this knowledge on contextual relevance is not found within the contents of documents, and current hypermedia tools do not provide any easy mechanism to let users add this knowledge to their documents. We propose a compositional relevance network to automatically acquire the context in which previous information was found relevant. The model records information on the relevance of references based on user feedback for specific queries and contexts. It also generalizes such information to derive relevant references for similar queries and contexts. This model lets users filter information by context of relevance, build personalized views of documents over time, and share their views with other users. It also applies to any type of multimedia information. Compared to other approaches, it is less costly and doesn't require any a priori statistical computation, nor an extended training period. It is currently being implemented into the Computer Integrated Documentation system which enables integration of various technical documents in a hypertext framework.

  9. 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

  10. 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.

  11. 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

  12. Stress and adaptation : Toward ecologically relevant animal models

    NARCIS (Netherlands)

    Koolhaas, Jaap M.; Boer, Sietse F. de; Buwalda, Bauke

    Animal models have contributed considerably to the current understanding of mechanisms underlying the role of stress in health and disease. Despite the progress made already, much more can be made by more carefully exploiting animals' and humans' shared biology, using ecologically relevant models.

  13. Status report [Parameters for calculation of nuclear reactions of relevance to non-energy nuclear applications

    International Nuclear Information System (INIS)

    Koning, A.

    2008-01-01

    Full text: Masses: Adopted Goriely HFB masses in TALYS as theoretical default instead of Moeller. Audi-Wapstra, Moeller and HFB masses tested formally with TALYS. Levels. Adopted latest discrete level update (2006) by Belgya (as sent by Capote) in TALYS. Tested with TALYS. Resonances. Adopted RIPL-2 D0 collection in TALYS. Tested by TALYS. Optical model. Coordinated Optical model segment for RIPL-3. Adopted Soukhovitskii CC potential as default for actinides. Covariances: Confirmed OMP parameter uncertainties from last meeting. Level density. Produced consistent set of level density parameters for CTM, BFM, GSM and HFM. Local models (per nucleus) and global models (systematics). With and without effective collective enhancement. Included and tested with TALYS Gamma-ray strength. Adopted Goriely HFB strength function tables as option (not default) in TALYS. Both formally tested and validated with TALYS. Fission. Adopted Sin-Capote WKB approximation in TALYS as option for fission calculations. Formally tested. RIPL-2/3 validation. Very extensive formal tests and validation procedures with TALYS. MONKEY code for random input files (has found RIPL errors in the past). Automatic comparison with all available EXFOR cross section data (for level density study). Started work on global parameter uncertainties (for covariances). SALTY nuclear data library (final version under construction): - 60 MeV n,g,p,d,t,h,a activation files for 1200 nuclides - 200 MeV n,g,p,d,t,h,a transport files for 250 nuclides RIPL is automatically being used by all TALYS users (and TALYS-related publications). TALYS-1.0 release in December 2007 (delay because of level densities). (author)

  14. 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...

  15. 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.

  16. 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

  17. Some relevant parameters for assessing fire hazards of combustible mine materials using laboratory scale experiments.

    Science.gov (United States)

    Litton, Charles D; Perera, Inoka E; Harteis, Samuel P; Teacoach, Kara A; DeRosa, Maria I; Thomas, Richard A; Smith, Alex C

    2018-04-15

    When combustible materials ignite and burn, the potential for fire growth and flame spread represents an obvious hazard, but during these processes of ignition and flaming, other life hazards present themselves and should be included to ensure an effective overall analysis of the relevant fire hazards. In particular, the gases and smoke produced both during the smoldering stages of fires leading to ignition and during the advanced flaming stages of a developing fire serve to contaminate the surrounding atmosphere, potentially producing elevated levels of toxicity and high levels of smoke obscuration that render the environment untenable. In underground mines, these hazards may be exacerbated by the existing forced ventilation that can carry the gases and smoke to locations far-removed from the fire location. Clearly, materials that require high temperatures (above 1400 K) and that exhibit low mass loss during thermal decomposition, or that require high heat fluxes or heat transfer rates to ignite represent less of a hazard than materials that decompose at low temperatures or ignite at low levels of heat flux. In order to define and quantify some possible parameters that can be used to assess these hazards, small-scale laboratory experiments were conducted in a number of configurations to measure: 1) the toxic gases and smoke produced both during non-flaming and flaming combustion; 2) mass loss rates as a function of temperature to determine ease of thermal decomposition; and 3) mass loss rates and times to ignition as a function of incident heat flux. This paper describes the experiments that were conducted, their results, and the development of a set of parameters that could possibly be used to assess the overall fire hazard of combustible materials using small scale laboratory experiments.

  18. 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

  19. 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...

  20. 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...

  1. 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.

  2. 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.

  3. 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...

  4. 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

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

    African Journals Online (AJOL)

    Preferred Customer

    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 ...

  6. 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)

  7. 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...

  8. 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

  9. 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)

  10. 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)

  11. Relevant criteria for testing the quality of turbulence models

    DEFF Research Database (Denmark)

    Frandsen, Sten Tronæs; Ejsing Jørgensen, Hans; Sørensen, J.D.

    2007-01-01

    Seeking relevant criteria for testing the quality of turbulence models, the scale of turbulence and the gust factor have been estimated from data and compared with predictions from first-order models of these two quantities. It is found that the mean of the measured length scales is approx. 10......% smaller than the IEC model, for wind turbine hub height levels. The mean is only marginally dependent on trends in time series. It is also found that the coefficient of variation of the measured length scales is about 50%. 3sec and 10sec pre-averaging of wind speed data are relevant for MW-size wind...... turbines when seeking wind characteristics that correspond to one blade and the entire rotor, respectively. For heights exceeding 50-60m the gust factor increases with wind speed. For heights larger the 60-80m, present assumptions on the value of the gust factor are significantly conservative, both for 3...

  12. 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.

  13. 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.

  14. How to Select the most Relevant Roughness Parameters of a Surface: Methodology Research Strategy

    Science.gov (United States)

    Bobrovskij, I. N.

    2018-01-01

    In this paper, the foundations for new methodology creation which provides solving problem of surfaces structure new standards parameters huge amount conflicted with necessary actual floors quantity of surfaces structure parameters which is related to measurement complexity decreasing are considered. At the moment, there is no single assessment of the importance of a parameters. The approval of presented methodology for aerospace cluster components surfaces allows to create necessary foundation, to develop scientific estimation of surfaces texture parameters, to obtain material for investigators of chosen technological procedure. The methods necessary for further work, the creation of a fundamental reserve and development as a scientific direction for assessing the significance of microgeometry parameters are selected.

  15. Model comparisons and genetic and environmental parameter ...

    African Journals Online (AJOL)

    arc

    Model comparisons and genetic and environmental parameter estimates of growth and the ... breeding strategies and for accurate breeding value estimation. The objectives ...... Sci. 23, 72-76. Van Wyk, J.B., Fair, M.D. & Cloete, S.W.P., 2003.

  16. The rho-parameter in supersymmetric models

    International Nuclear Information System (INIS)

    Lim, C.S.; Inami, T.; Sakai, N.

    1983-10-01

    The electroweak rho-parameter is examined in a general class of supersymmetric models. Formulae are given for one-loop contributions to Δrho from scalar quarks and leptons, gauge-Higgs fermions and an extra doublet of Higgs scalars. Mass differences between members of isodoublet scalar quarks and leptons are constrained to be less than about 200 GeV. (author)

  17. A lumped parameter model of plasma focus

    International Nuclear Information System (INIS)

    Gonzalez, Jose H.; Florido, Pablo C.; Bruzzone, H.; Clausse, Alejandro

    1999-01-01

    A lumped parameter model to estimate neutron emission of a plasma focus (PF) device is developed. The dynamic of the current sheet is calculated using a snowplow model, and the neutron production with the thermal fusion cross section for a deuterium filling gas. The results were contrasted as a function of the filling pressure with experimental measurements of a 3.68 KJ Mather-type PF. (author)

  18. One parameter model potential for noble metals

    International Nuclear Information System (INIS)

    Idrees, M.; Khwaja, F.A.; Razmi, M.S.K.

    1981-08-01

    A phenomenological one parameter model potential which includes s-d hybridization and core-core exchange contributions is proposed for noble metals. A number of interesting properties like liquid metal resistivities, band gaps, thermoelectric powers and ion-ion interaction potentials are calculated for Cu, Ag and Au. The results obtained are in better agreement with experiment than the ones predicted by the other model potentials in the literature. (author)

  19. 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.

  20. Models of the Economic Growth and their Relevance

    Directory of Open Access Journals (Sweden)

    Nicolae MOROIANU

    2012-06-01

    Full Text Available Until few years ago, the economic growth was something perfect normal, part of an era marked by the transformation speed. Normality itself has been transformed and we currently are influenced by other rules, unknown yet, which should answer the question: “How do we return to the economic growth?” The economic growth and the models aiming to solve this problem concern the economic history even since its beginnings. In this paper we would like to find out what is the relevance that the well-known macroeconomic models still have and which might be their applicability level in a framework created by a black swan event type.

  1. 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.

  2. Macroscale hydrologic modeling of ecologically relevant flow metrics

    Science.gov (United States)

    Wenger, Seth J.; Luce, Charles H.; Hamlet, Alan F.; Isaak, Daniel J.; Neville, Helen M.

    2010-09-01

    Stream hydrology strongly affects the structure of aquatic communities. Changes to air temperature and precipitation driven by increased greenhouse gas concentrations are shifting timing and volume of streamflows potentially affecting these communities. The variable infiltration capacity (VIC) macroscale hydrologic model has been employed at regional scales to describe and forecast hydrologic changes but has been calibrated and applied mainly to large rivers. An important question is how well VIC runoff simulations serve to answer questions about hydrologic changes in smaller streams, which are important habitat for many fish species. To answer this question, we aggregated gridded VIC outputs within the drainage basins of 55 streamflow gages in the Pacific Northwest United States and compared modeled hydrographs and summary metrics to observations. For most streams, several ecologically relevant aspects of the hydrologic regime were accurately modeled, including center of flow timing, mean annual and summer flows and frequency of winter floods. Frequencies of high and low flows in the summer were not well predicted, however. Predictions were worse for sites with strong groundwater influence, and some sites showed errors that may result from limitations in the forcing climate data. Higher resolution (1/16th degree) modeling provided small improvements over lower resolution (1/8th degree). Despite some limitations, the VIC model appears capable of representing several ecologically relevant hydrologic characteristics in streams, making it a useful tool for understanding the effects of hydrology in delimiting species distributions and predicting the potential effects of climate shifts on aquatic organisms.

  3. Bioprinting towards Physiologically Relevant Tissue Models for Pharmaceutics.

    Science.gov (United States)

    Peng, Weijie; Unutmaz, Derya; Ozbolat, Ibrahim T

    2016-09-01

    Improving the ability to predict the efficacy and toxicity of drug candidates earlier in the drug discovery process will speed up the introduction of new drugs into clinics. 3D in vitro systems have significantly advanced the drug screening process as 3D tissue models can closely mimic native tissues and, in some cases, the physiological response to drugs. Among various in vitro systems, bioprinting is a highly promising technology possessing several advantages such as tailored microarchitecture, high-throughput capability, coculture ability, and low risk of cross-contamination. In this opinion article, we discuss the currently available tissue models in pharmaceutics along with their limitations and highlight the possibilities of bioprinting physiologically relevant tissue models, which hold great potential in drug testing, high-throughput screening, and disease modeling. Copyright © 2016 Elsevier Ltd. All rights reserved.

  4. Finding Relevant Parameters for the Thin-film Photovoltaic Cells Production Process with the Application of Data Mining Methods.

    Science.gov (United States)

    Ulaczyk, Jan; Morawiec, Krzysztof; Zabierowski, Paweł; Drobiazg, Tomasz; Barreau, Nicolas

    2017-09-01

    A data mining approach is proposed as a useful tool for the control parameters analysis of the 3-stage CIGSe photovoltaic cell production process, in order to find variables that are the most relevant for cell electric parameters and efficiency. The analysed data set consists of stage duration times, heater power values as well as temperatures for the element sources and the substrate - there are 14 variables per sample in total. The most relevant variables of the process have been found based on the so-called random forest analysis with the application of the Boruta algorithm. 118 CIGSe samples, prepared at Institut des Matériaux Jean Rouxel, were analysed. The results are close to experimental knowledge on the CIGSe cells production process. They bring new evidence to production parameters of new cells and further research. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  5. 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.

  6. Parameters for calculation of nuclear reactions of relevance to non-energy nuclear applications (Reference Input Parameter Library: Phase III). Summary report of the first research coordination meeting

    International Nuclear Information System (INIS)

    Capote Noy, R.

    2004-08-01

    A summary is given of the First Research Coordination Meeting on Parameters for Calculation of Nuclear Reactions of Relevance to Non-Energy Nuclear Applications (Reference Input Parameter Library: Phase III), including a critical review of the RIPL-2 file. The new library should serve as input for theoretical calculations of nuclear reaction data at incident energies up to 200 MeV, as needed for energy and non-energy modern applications of nuclear data. Technical discussions and the resulting work plan of the Coordinated Research Programme are summarized, along with actions and deadlines. Participants' contributions to the RCM are also attached. (author)

  7. Equation of state experiments and theory relevant to planetary modelling

    International Nuclear Information System (INIS)

    Ross, M.; Graboske, H.C. Jr.; Nellis, W.J.

    1981-01-01

    In recent years there have been a number of static and shockwave experiments on the properties of planetary materials. The highest pressure measurements, and the ones most relevant to planetary modelling, have been obtained by shock compression. Of particular interest to the Jovian group are results for H 2 , H 2 O, CH 4 and NH 3 . Although the properties of metallic hydrogen have not been measured, they have been the subject of extensive calculations. In addition recent shock wave experiments on iron report to have detected melting under Earth core conditions. From this data theoretical models have been developed for computing the equations of state of materials used in planetary studies. A compelling feature that has followed from the use of improved material properties is a simplification in the planetary models. (author)

  8. A multiple relevance feedback strategy with positive and negative models.

    Directory of Open Access Journals (Sweden)

    Yunlong Ma

    Full Text Available A commonly used strategy to improve search accuracy is through feedback techniques. Most existing work on feedback relies on positive information, and has been extensively studied in information retrieval. However, when a query topic is difficult and the results from the first-pass retrieval are very poor, it is impossible to extract enough useful terms from a few positive documents. Therefore, the positive feedback strategy is incapable to improve retrieval in this situation. Contrarily, there is a relatively large number of negative documents in the top of the result list, and it has been confirmed that negative feedback strategy is an important and useful way for adapting this scenario by several recent studies. In this paper, we consider a scenario when the search results are so poor that there are at most three relevant documents in the top twenty documents. Then, we conduct a novel study of multiple strategies for relevance feedback using both positive and negative examples from the first-pass retrieval to improve retrieval accuracy for such difficult queries. Experimental results on these TREC collections show that the proposed language model based multiple model feedback method which is generally more effective than both the baseline method and the methods using only positive or negative model.

  9. 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.

  10. Improving the GIS-DRP Approach by Means of DelineatingRunoff Characteristics with New Discharge Relevant Parameters

    Directory of Open Access Journals (Sweden)

    Marco Hümann

    2013-01-01

    Full Text Available At present it is common to use geographic information system (GIS applications to assess runoff generation. One of these GIS-based tools to generate maps of dominant runoff processes is the so called GIS-DRP approach. The tool, which has been developed mainly based on agricultural areas, uses commonly available input data like a digital elevation model (DEM, geological information as well as land use information. The aim of this study is to test, validate and improve this GIS-DRP method for forested and silviculture areas. Hence, soil-hydrologic investigations and several mapping techniques of dominant runoff processes were conducted on 25 test-plots in four forested catchments in Rhineland-Palatinate (Germany and the Grand Duchy of Luxembourg. By comparing the results of the mapping techniques and those of the test plots, weak points in the original GIS-DRP method were detected. Subsequently, it was possible to enhance the GIS-DRP approach by incorporating new discharge relevant parameters like topsoil sealing, extreme weather events and semipermeability of the substratum. Moreover, the improved GIS-DRP approach can be widely used in different landscapes and for different fields of application. The adapted method can now support foresters and decision makers in forestry planning, answer questions concerning the landscape water balance and peripheral water retention or provide extra information for sustainable forest planning in times of a changing climate.

  11. Electro-optical parameters of bond polarizability model for aluminosilicates.

    Science.gov (United States)

    Smirnov, Konstantin S; Bougeard, Daniel; Tandon, Poonam

    2006-04-06

    Electro-optical parameters (EOPs) of bond polarizability model (BPM) for aluminosilicate structures were derived from quantum-chemical DFT calculations of molecular models. The tensor of molecular polarizability and the derivatives of the tensor with respect to the bond length are well reproduced with the BPM, and the EOPs obtained are in a fair agreement with available experimental data. The parameters derived were found to be transferable to larger molecules. This finding suggests that the procedure used can be applied to systems with partially ionic chemical bonds. The transferability of the parameters to periodic systems was tested in molecular dynamics simulation of the polarized Raman spectra of alpha-quartz. It appeared that the molecular Si-O bond EOPs failed to reproduce the intensity of peaks in the spectra. This limitation is due to large values of the longitudinal components of the bond polarizability and its derivative found in the molecular calculations as compared to those obtained from periodic DFT calculations of crystalline silica polymorphs by Umari et al. (Phys. Rev. B 2001, 63, 094305). It is supposed that the electric field of the solid is responsible for the difference of the parameters. Nevertheless, the EOPs obtained can be used as an initial set of parameters for calculations of polarizability related characteristics of relevant systems in the framework of BPM.

  12. Analysis of all dimensionful parameters relevant in gravitational dressing of conformal theories

    International Nuclear Information System (INIS)

    Dorn, H.; Otto, H.J.

    1992-01-01

    Starting from a covariant and background independent definition of normal ordered vertex operators we give an alternative derivation of the KPZ relation between conformal dimensions and their gravitational dressed partners. With our method we are able to study for arbitrary genus the dependence of N-point functions on all dimensionful parameters. Implications for the interpretation of gravitational dressed dimensions are discussed. (orig.)

  13. Mouse models of ageing and their relevance to disease.

    Science.gov (United States)

    Kõks, Sulev; Dogan, Soner; Tuna, Bilge Guvenc; González-Navarro, Herminia; Potter, Paul; Vandenbroucke, Roosmarijn E

    2016-12-01

    Ageing is a process that gradually increases the organism's vulnerability to death. It affects different biological pathways, and the underlying cellular mechanisms are complex. In view of the growing disease burden of ageing populations, increasing efforts are being invested in understanding the pathways and mechanisms of ageing. We review some mouse models commonly used in studies on ageing, highlight the advantages and disadvantages of the different strategies, and discuss their relevance to disease susceptibility. In addition to addressing the genetics and phenotypic analysis of mice, we discuss examples of models of delayed or accelerated ageing and their modulation by caloric restriction. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

  14. The lumped parameter model for fuel pins

    Energy Technology Data Exchange (ETDEWEB)

    Liu, W S [Ontario Hydro, Toronto, ON (Canada)

    1996-12-31

    The use of a lumped fuel-pin model in a thermal-hydraulic code is advantageous because of computational simplicity and efficiency. The model uses an averaging approach over the fuel cross section and makes some simplifying assumptions to describe the transient equations for the averaged fuel, fuel centerline and sheath temperatures. It is shown that by introducing a factor in the effective fuel conductivity, the analytical solution of the mean fuel temperature can be modified to simulate the effects of the flux depression in the heat generation rate and the variation in fuel thermal conductivity. The simplified analytical method used in the transient equation is presented. The accuracy of the lumped parameter model has been compared with the results from the finite difference method. (author). 4 refs., 2 tabs., 4 figs.

  15. Model atmospheres and parameters of central stars of planetary nebulae

    International Nuclear Information System (INIS)

    Patriarchi, P.; Cerruti-sola, M.; Perinotto, M.

    1989-01-01

    Non-LTE hydrogen and helium model atmospheres have been obtained for temperatures and gravities relevant to the central stars of planetary nebulae. Low-resolution and high-resolution observations obtained by the IUE satellite have been used along with optical data to determine Zanstra temperatures of the central stars of NGC 1535, NGC 6210, NGC 7009, IC 418, and IC 4593. Comparison of the observed stellar continuum of these stars with theoretical results allowed further information on the stellar temperature to be derived. The final temperatures are used to calculate accurate stellar parameters. 62 refs

  16. 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

  17. Measurements of relevant parameters in the formation of clathrate hydrates by a novel experimental apparatus

    Energy Technology Data Exchange (ETDEWEB)

    Arca, S.; Di Profio, P.; Germani, R.; Savelli, G. [Perugia Univ., CEMIN, Perugia (Italy). Dept. of Chemistry

    2008-07-01

    There is a growing interest in understanding the thermodynamics and kinetics of clathrate hydrate formation. This paper presented a study that involved the design, construction, calibration, and testing of a new apparatus that could obtain as many parameters as possible in a single formation batch and that could measure unexplored clathrate hydrate parameters. The apparatus was capable of measuring equilibrium phases involving gaseous components. The paper described the conceptual design as well as the chamber, pressure line, temperature control, liquid addition line, and conductometric probe. The paper also discussed data acquisition, stirring, measurement examples, and internal illumination and video monitoring. It was concluded that refining measurements, particularly those concerning kinetic characterizations, is important in order to clarify several uncertain kinetic behaviors of clathrate hydrates. 6 refs., 16 figs.

  18. Modeling of Parameters of Subcritical Assembly SAD

    CERN Document Server

    Petrochenkov, S; Puzynin, I

    2005-01-01

    The accepted conceptual design of the experimental Subcritical Assembly in Dubna (SAD) is based on the MOX core with a nominal unit capacity of 25 kW (thermal). This corresponds to the multiplication coefficient $k_{\\rm eff} =0.95$ and accelerator beam power 1 kW. A subcritical assembly driven with the existing 660 MeV proton accelerator at the Joint Institute for Nuclear Research has been modelled in order to make choice of the optimal parameters for the future experiments. The Monte Carlo method was used to simulate neutron spectra, energy deposition and doses calculations. Some of the calculation results are presented in the paper.

  19. Parameter estimation in fractional diffusion models

    CERN Document Server

    Kubilius, Kęstutis; Ralchenko, Kostiantyn

    2017-01-01

    This book is devoted to parameter estimation in diffusion models involving fractional Brownian motion and related processes. For many years now, standard Brownian motion has been (and still remains) a popular model of randomness used to investigate processes in the natural sciences, financial markets, and the economy. The substantial limitation in the use of stochastic diffusion models with Brownian motion is due to the fact that the motion has independent increments, and, therefore, the random noise it generates is “white,” i.e., uncorrelated. However, many processes in the natural sciences, computer networks and financial markets have long-term or short-term dependences, i.e., the correlations of random noise in these processes are non-zero, and slowly or rapidly decrease with time. In particular, models of financial markets demonstrate various kinds of memory and usually this memory is modeled by fractional Brownian diffusion. Therefore, the book constructs diffusion models with memory and provides s...

  20. Culturally relevant model program to prevent and reduce agricultural injuries.

    Science.gov (United States)

    Helitzer, D L; Hathorn, G; Benally, J; Ortega, C

    2014-07-01

    Limited research has explored pesticide injury prevention among American Indian farmers. In a five-year agricultural intervention, a university-community partnership, including the University of New Mexico School of Medicine, New Mexico State University, Shiprock Area Cooperative Extension Service, and Navajo Nation communities, used a culturally relevant model to introduce and maintain safe use of integrated pest management techniques. We applied the Diffusion of Innovations theory and community-based approaches to tailor health promotion strategies for our intervention. In a longitudinal study with repeated measures, we trained six "model farmers" to be crop management experts in pesticide safety, application, and control. Subsequently, these model farmers worked with 120 farm families randomized into two groups: intervention (Group 1) and delayed intervention (Group 2). Measurements included a walk-through analysis, test of knowledge and attitudes, and yield analysis. Both groups demonstrated improvements in pesticide storage behaviors after training. Test scores regarding safety practices improved significantly: from 57.3 to 72.4 for Group 1 and from 52.6 to 76.3 for Group 2. Group 1 maintained their knowledge and safety practices after the intervention. Attitudes about pesticides and communication of viewpoints changed across the study years. With pesticides and fertilizer, the number of corn ears increased by 56.3% and yield (kg m(-2)) of alfalfa increased by 41.2%. The study combined traditional farming practices with culturally relevant approaches and behavior change theory to affect knowledge, safety practices, attitudes, communication channels, and crop yield. Storage behaviors, use of pesticides and safety and application equipment, and safety practice knowledge changed significantly, as did attitudes about social networking, social support, and the compatibility and relative advantage of pesticides for farms.

  1. Model fit versus biological relevance: Evaluating photosynthesis-temperature models for three tropical seagrass species

    OpenAIRE

    Matthew P. Adams; Catherine J. Collier; Sven Uthicke; Yan X. Ow; Lucas Langlois; Katherine R. O’Brien

    2017-01-01

    When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluat...

  2. Moose models with vanishing S parameter

    International Nuclear Information System (INIS)

    Casalbuoni, R.; De Curtis, S.; Dominici, D.

    2004-01-01

    In the linear moose framework, which naturally emerges in deconstruction models, we show that there is a unique solution for the vanishing of the S parameter at the lowest order in the weak interactions. We consider an effective gauge theory based on K SU(2) gauge groups, K+1 chiral fields, and electroweak groups SU(2) L and U(1) Y at the ends of the chain of the moose. S vanishes when a link in the moose chain is cut. As a consequence one has to introduce a dynamical nonlocal field connecting the two ends of the moose. Then the model acquires an additional custodial symmetry which protects this result. We examine also the possibility of a strong suppression of S through an exponential behavior of the link couplings as suggested by the Randall Sundrum metric

  3. Atlas selection for hippocampus segmentation: Relevance evaluation of three meta-information parameters.

    Science.gov (United States)

    Dill, Vanderson; Klein, Pedro Costa; Franco, Alexandre Rosa; Pinho, Márcio Sarroglia

    2018-04-01

    Current state-of-the-art methods for whole and subfield hippocampus segmentation use pre-segmented templates, also known as atlases, in the pre-processing stages. Typically, the input image is registered to the template, which provides prior information for the segmentation process. Using a single standard atlas increases the difficulty in dealing with individuals who have a brain anatomy that is morphologically different from the atlas, especially in older brains. To increase the segmentation precision in these cases, without any manual intervention, multiple atlases can be used. However, registration to many templates leads to a high computational cost. Researchers have proposed to use an atlas pre-selection technique based on meta-information followed by the selection of an atlas based on image similarity. Unfortunately, this method also presents a high computational cost due to the image-similarity process. Thus, it is desirable to pre-select a smaller number of atlases as long as this does not impact on the segmentation quality. To pick out an atlas that provides the best registration, we evaluate the use of three meta-information parameters (medical condition, age range, and gender) to choose the atlas. In this work, 24 atlases were defined and each is based on the combination of the three meta-information parameters. These atlases were used to segment 352 vol from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Hippocampus segmentation with each of these atlases was evaluated and compared to reference segmentations of the hippocampus, which are available from ADNI. The use of atlas selection by meta-information led to a significant gain in the Dice similarity coefficient, which reached 0.68 ± 0.11, compared to 0.62 ± 0.12 when using only the standard MNI152 atlas. Statistical analysis showed that the three meta-information parameters provided a significant improvement in the segmentation accuracy. Copyright © 2018 Elsevier Ltd

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

    Science.gov (United States)

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

    2018-01-01

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

  5. In Silico Prediction of Toxicokinetic Parameters for Environmentally Relevant Chemicals for Risk-Based Prioritization

    Science.gov (United States)

    Toxicokinetic (TK) models can address an important component of chemical risk assessments by helping bridge the gap between chemical exposure and measured toxicity endpoints. The metabolic clearance rate (CLint) and fraction of a chemical unbound by plasma proteins (Fub) are crit...

  6. On the ""early-time"" evolution of variables relevant to turbulence models for Rayleigh-Taylor instability

    Energy Technology Data Exchange (ETDEWEB)

    Rollin, Bertrand [Los Alamos National Laboratory; Andrews, Malcolm J [Los Alamos National Laboratory

    2010-01-01

    We present our progress toward setting initial conditions in variable density turbulence models. In particular, we concentrate our efforts on the BHR turbulence model for turbulent Rayleigh-Taylor instability. Our approach is to predict profiles of relevant parameters before the fully turbulent regime and use them as initial conditions for the turbulence model. We use an idealized model of the mixing between two interpenetrating fluids to define the initial profiles for the turbulence model parameters. Velocities and volume fractions used in the idealized mixing model are obtained respectively from a set of ordinary differential equations modeling the growth of the Rayleigh-Taylor instability and from an idealization of the density profile in the mixing layer. A comparison between predicted initial profiles for the turbulence model parameters and initial profiles of the parameters obtained from low Atwood number three dimensional simulations show reasonable agreement.

  7. Doses due to tritium releases by NET - data base and relevant parameters on biological tritium behaviour

    International Nuclear Information System (INIS)

    Diabate, S.; Strack, S.

    1990-12-01

    This study gives an overview on the current knowledge about the behaviour of tritium in plants and in food chains in order to evaluate the ingestion pathway modelling of existing computer codes for dose estimations. The tritium uptake and retention by plants standing at the beginning of the food chains is described. The different chemical forms of tritium, which may be released into the atmosphere (HT, HTO and tritiated organics), and incorporation of tritium into organic material of plants are considered. Uptake and metabolism of tritiated compounds in animals and man are reviewed with particular respect to organically bound tritium and its significance for dose estimations. Some basic remarks on tritium toxicity are also included. Furthermore, a choice of computer codes for dose estimations due to chronic or accidental tritium releases has been compared with respect to the ingestion pathway. (orig.) [de

  8. Parameter Estimation of Partial Differential Equation Models

    KAUST Repository

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

    2013-01-01

    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

  9. Determinants of dermal exposure relevant for exposure modelling in regulatory risk assessment.

    Science.gov (United States)

    Marquart, J; Brouwer, D H; Gijsbers, J H J; Links, I H M; Warren, N; van Hemmen, J J

    2003-11-01

    Risk assessment of chemicals requires assessment of the exposure levels of workers. In the absence of adequate specific measured data, models are often used to estimate exposure levels. For dermal exposure only a few models exist, which are not validated externally. In the scope of a large European research programme, an analysis of potential dermal exposure determinants was made based on the available studies and models and on the expert judgement of the authors of this publication. Only a few potential determinants appear to have been studied in depth. Several studies have included clusters of determinants into vaguely defined parameters, such as 'task' or 'cleaning and maintenance of clothing'. Other studies include several highly correlated parameters, such as 'amount of product handled', 'duration of task' and 'area treated', and separation of these parameters to study their individual influence is not possible. However, based on the available information, a number of determinants could clearly be defined as proven or highly plausible determinants of dermal exposure in one or more exposure situation. This information was combined with expert judgement on the scientific plausibility of the influence of parameters that have not been extensively studied and on the possibilities to gather relevant information during a risk assessment process. The result of this effort is a list of determinants relevant for dermal exposure models in the scope of regulatory risk assessment. The determinants have been divided into the major categories 'substance and product characteristics', 'task done by the worker', 'process technique and equipment', 'exposure control measures', 'worker characteristics and habits' and 'area and situation'. To account for the complex nature of the dermal exposure processes, a further subdivision was made into the three major processes 'direct contact', 'surface contact' and 'deposition'.

  10. Hierarchical Bayesian nonparametric mixture models for clustering with variable relevance determination.

    Science.gov (United States)

    Yau, Christopher; Holmes, Chris

    2011-07-01

    We propose a hierarchical Bayesian nonparametric mixture model for clustering when some of the covariates are assumed to be of varying relevance to the clustering problem. This can be thought of as an issue in variable selection for unsupervised learning. We demonstrate that by defining a hierarchical population based nonparametric prior on the cluster locations scaled by the inverse covariance matrices of the likelihood we arrive at a 'sparsity prior' representation which admits a conditionally conjugate prior. This allows us to perform full Gibbs sampling to obtain posterior distributions over parameters of interest including an explicit measure of each covariate's relevance and a distribution over the number of potential clusters present in the data. This also allows for individual cluster specific variable selection. We demonstrate improved inference on a number of canonical problems.

  11. Model fit versus biological relevance: Evaluating photosynthesis-temperature models for three tropical seagrass species.

    Science.gov (United States)

    Adams, Matthew P; Collier, Catherine J; Uthicke, Sven; Ow, Yan X; Langlois, Lucas; O'Brien, Katherine R

    2017-01-04

    When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluated twelve published empirical models for temperature-dependent tropical seagrass photosynthesis, based on two criteria: (1) goodness of fit, and (2) how easily biologically-meaningful parameters can be obtained. All models were formulated in terms of parameters characterising the thermal optimum (T opt ) for maximum photosynthetic rate (P max ). These parameters indicate the upper thermal limits of seagrass photosynthetic capacity, and hence can be used to assess the vulnerability of seagrass to temperature change. Our study exemplifies an approach to model selection which optimises the usefulness of empirical models for both modellers and ecologists alike.

  12. Model fit versus biological relevance: Evaluating photosynthesis-temperature models for three tropical seagrass species

    Science.gov (United States)

    Adams, Matthew P.; Collier, Catherine J.; Uthicke, Sven; Ow, Yan X.; Langlois, Lucas; O'Brien, Katherine R.

    2017-01-01

    When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluated twelve published empirical models for temperature-dependent tropical seagrass photosynthesis, based on two criteria: (1) goodness of fit, and (2) how easily biologically-meaningful parameters can be obtained. All models were formulated in terms of parameters characterising the thermal optimum (Topt) for maximum photosynthetic rate (Pmax). These parameters indicate the upper thermal limits of seagrass photosynthetic capacity, and hence can be used to assess the vulnerability of seagrass to temperature change. Our study exemplifies an approach to model selection which optimises the usefulness of empirical models for both modellers and ecologists alike.

  13. Evaluation of relevant information for optimal reflector modeling through data assimilation procedures

    International Nuclear Information System (INIS)

    Argaud, J.P.; Bouriquet, B.; Clerc, T.; Lucet-Sanchez, F.; Poncot, A.

    2015-01-01

    The goal of this study is to look after the amount of information that is mandatory to get a relevant parameters optimisation by data assimilation for physical models in neutronic diffusion calculations, and to determine what is the best information to reach the optimum of accuracy at the cheapest cost. To evaluate the quality of the optimisation, we study the covariance matrix that represents the accuracy of the optimised parameter. This matrix is a classical output of the data assimilation procedure, and it is the main information about accuracy and sensitivity of the parameter optimal determination. We present some results collected in the field of neutronic simulation for PWR type reactor. We seek to optimise the reflector parameters that characterise the neutronic reflector surrounding the whole reactive core. On the basis of the configuration studies, it has been shown that with data assimilation we can determine a global strategy to optimise the quality of the result with respect to the amount of information provided. The consequence of this is a cost reduction in terms of measurement and/or computing time with respect to the basic approach. Another result is that using multi-campaign data rather data from a unique campaign significantly improves the efficiency of parameters optimisation

  14. Modelling low energy electron and positron tracks in biologically relevant media

    International Nuclear Information System (INIS)

    Blanco, F.; Munoz, A.; Almeida, D.; Ferreira da Silva, F.; Limao-Vieira, P.; Fuss, M.C.; Sanz, A.G.; Garcia, G.

    2013-01-01

    This colloquium describes an approach to incorporate into radiation damage models the effect of low and intermediate energy (0-100 eV) electrons and positrons, slowing down in biologically relevant materials (water and representative biomolecules). The core of the modelling procedure is a C++ computing programme named 'Low Energy Particle Track Simulation (LEPTS)', which is compatible with available general purpose Monte Carlo packages. Input parameters are carefully selected from theoretical and experimental cross section data and energy loss distribution functions. Data sources used for this purpose are reviewed showing examples of electron and positron cross section and energy loss data for interactions with different media of increasing complexity: atoms, molecules, clusters and condense matter. Finally, we show how such a model can be used to develop an effective dosimetric tool at the molecular level (i.e. nanodosimetry). Recent experimental developments to study the fragmentation induced in biologically material by charge transfer from neutrals and negative ions are also included. (authors)

  15. Relevance Theory as model for analysing visual and multimodal communication

    NARCIS (Netherlands)

    Forceville, C.; Machin, D.

    2014-01-01

    Elaborating on my earlier work (Forceville 1996: chapter 5, 2005, 2009; see also Yus 2008), I will here sketch how discussions of visual and multimodal discourse can be embedded in a more general theory of communication and cognition: Sperber and Wilson’s Relevance Theory/RT (Sperber and Wilson

  16. 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

  17. Dietary supplementation of tiger nut alters biochemical parameters relevant to erectile function in l-NAME treated rats.

    Science.gov (United States)

    Olabiyi, Ayodeji A; Carvalho, Fabiano B; Bottari, Nathieli B; Lopes, Thauan F; da Costa, Pauline; Stefanelo, Naiara; Morsch, Vera M; Akindahunsi, Afolabi A; Oboh, Ganiyu; Schetinger, Maria Rosa

    2018-07-01

    Tiger nut tubers have been reportedly used for the treatment of erectile dysfunction (ED) in folk medicine without scientific basis. Hence, this study evaluated the effect of tiger nut on erectile dysfunction by assessing biochemical parameters relevant to ED in male rats by nitric oxide synthase (NOS) inhibitor, Nω-nitro-l-arginine methyl ester hydrochloride (l-NAME) treatment. Rats were divided into five groups (n = 10) each: Control group; l-NAME plus basal diet; l-NAME plus Sildenafil citrate; diet supplemented processed tiger nut (20%) plus l-NAME;diet supplemented raw tiger nut (20%) plus l-NAME. l-NAME pre-treatment (40 mg/kg/day) lasted for 14 days. Arginase, acetycholinesterase (AChE) and adenosine deaminase (ADA) activities as well as nitric oxide levels (NO) in serum, brain and penile tissue were measured. l-NAME increased the activity of arginase, AChE and ADA and reduced NO levels. However, dietary supplementation with tiger nut caused a reduction on the activities of the above enzymes and up regulated nitric oxide levels when compared to the control group. The effect of tiger nut supplemented diet may be said to prevent alterations of the activities of the enzymes relevant in erectile function. Quercetin was revealed to be the most active component of tiger nut tuber by HPLC finger printing. Copyright © 2018. Published by Elsevier Ltd.

  18. 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

  19. A content relevance model for social media health information.

    Science.gov (United States)

    Prybutok, Gayle Linda; Koh, Chang; Prybutok, Victor R

    2014-04-01

    Consumer health informatics includes the development and implementation of Internet-based systems to deliver health risk management information and health intervention applications to the public. The application of consumer health informatics to educational and interventional efforts such as smoking reduction and cessation has garnered attention from both consumers and health researchers in recent years. Scientists believe that smoking avoidance or cessation before the age of 30 years can prevent more than 90% of smoking-related cancers and that individuals who stop smoking fare as well in preventing cancer as those who never start. The goal of this study was to determine factors that were most highly correlated with content relevance for health information provided on the Internet for a study group of 18- to 30-year-old college students. Data analysis showed that the opportunity for convenient entertainment, social interaction, health information-seeking behavior, time spent surfing on the Internet, the importance of available activities on the Internet (particularly e-mail), and perceived site relevance for Internet-based sources of health information were significantly correlated with content relevance for 18- to 30-year-old college students, an educated subset of this population segment.

  20. 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…

  1. Review: To be or not to be an identifiable model. Is this a relevant question in animal science modelling?

    Science.gov (United States)

    Muñoz-Tamayo, R; Puillet, L; Daniel, J B; Sauvant, D; Martin, O; Taghipoor, M; Blavy, P

    2018-04-01

    What is a good (useful) mathematical model in animal science? For models constructed for prediction purposes, the question of model adequacy (usefulness) has been traditionally tackled by statistical analysis applied to observed experimental data relative to model-predicted variables. However, little attention has been paid to analytic tools that exploit the mathematical properties of the model equations. For example, in the context of model calibration, before attempting a numerical estimation of the model parameters, we might want to know if we have any chance of success in estimating a unique best value of the model parameters from available measurements. This question of uniqueness is referred to as structural identifiability; a mathematical property that is defined on the sole basis of the model structure within a hypothetical ideal experiment determined by a setting of model inputs (stimuli) and observable variables (measurements). Structural identifiability analysis applied to dynamic models described by ordinary differential equations (ODEs) is a common practice in control engineering and system identification. This analysis demands mathematical technicalities that are beyond the academic background of animal science, which might explain the lack of pervasiveness of identifiability analysis in animal science modelling. To fill this gap, in this paper we address the analysis of structural identifiability from a practitioner perspective by capitalizing on the use of dedicated software tools. Our objectives are (i) to provide a comprehensive explanation of the structural identifiability notion for the community of animal science modelling, (ii) to assess the relevance of identifiability analysis in animal science modelling and (iii) to motivate the community to use identifiability analysis in the modelling practice (when the identifiability question is relevant). We focus our study on ODE models. By using illustrative examples that include published

  2. 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.

  3. The Relevance of Using Mathematical Models in Macroeconomic Policies Theory

    Directory of Open Access Journals (Sweden)

    Nora Mihail

    2006-11-01

    Full Text Available The article presents a look of the principal’s mathematical models – starting with Theil, Hansen and Tinbergen work – and their results used to analysis and design macroeconomic policies. In modeling field changes are very fast in theoretical aspects of modeling the many problems of macroeconomic policies and in using in practice the different political models elaboration. The article points out the problems of static and dynamic theory used in macro-policies modeling.

  4. The Relevance of Using Mathematical Models in Macroeconomic Policies Theory

    Directory of Open Access Journals (Sweden)

    Nora Mihail

    2006-09-01

    Full Text Available The article presents a look of the principal’s mathematical models – starting with Theil, Hansen and Tinbergen work – and their results used to analysis and design macroeconomic policies. In modeling field changes are very fast in theoretical aspects of modeling the many problems of macroeconomic policies and in using in practice the different political models elaboration. The article points out the problems of static and dynamic theory used in macro-policies modeling.

  5. Surgeon Reported Outcome Measure for Spine Trauma an International Expert Survey Identifying Parameters Relevant for The Outcome of Subaxial Cervical Spine Injuries

    NARCIS (Netherlands)

    Sadiqi, Said; Verlaan, Jorrit Jan; Lehr, A. M.; Dvorak, Marcel F.; Kandziora, Frank; Rajasekaran, S.; Schnake, Klaus J.; Vaccaro, Alexander R.; Oner, F. C.

    2016-01-01

    STUDY DESIGN.: International web-based survey OBJECTIVE.: To identify clinical and radiological parameters that spine surgeons consider most relevant when evaluating clinical and functional outcomes of subaxial cervical spine trauma patients. SUMMARY OF BACKGROUND DATA.: While an outcome instrument

  6. 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

    geochemical relevance of GEMSFITS is demonstrated by examples of typical classes of problems that include fitting of parameters of thermodynamic mixing models, optimization of standard state Gibbs energies of aqueous species and solid-solution end-members, thermobarometry, inverse titrations, and optimization problems that combine several parameter- and property types

  7. Extracting the relevant delays in time series modelling

    DEFF Research Database (Denmark)

    Goutte, Cyril

    1997-01-01

    selection, and more precisely stepwise forward selection. The method is compared to other forward selection schemes, as well as to a nonparametric tests aimed at estimating the embedding dimension of time series. The final application extends these results to the efficient estimation of FIR filters on some......In this contribution, we suggest a convenient way to use generalisation error to extract the relevant delays from a time-varying process, i.e. the delays that lead to the best prediction performance. We design a generalisation-based algorithm that takes its inspiration from traditional variable...

  8. Looking for a relevant potential evapotranspiration model at the watershed scale

    Science.gov (United States)

    Oudin, L.; Hervieu, F.; Michel, C.; Perrin, C.; Anctil, F.; Andréassian, V.

    2003-04-01

    In this paper, we try to identify the most relevant approach to calculate Potential Evapotranspiration (PET) for use in a daily watershed model, to try to bring an answer to the following question: "how can we use commonly available atmospheric parameters to represent the evaporative demand at the catchment scale?". Hydrologists generally see the Penman model as the ideal model regarding to its good adequacy with lysimeter measurements and its physically-based formulation. However, in real-world engineering situations, where meteorological stations are scarce, hydrologists are often constrained to use other PET formulae with less data requirements or/and long-term average of PET values (the rationale being that PET is an inherently conservative variable). We chose to test 28 commonly used PET models coupled with 4 different daily watershed models. For each test, we compare both PET input options: actual data and long-term average data. The comparison is made in terms of streamflow simulation efficiency, over a large sample of 308 watersheds. The watersheds are located in France, Australia and the United States of America and represent varied climates. Strikingly, we find no systematic improvements of the watershed model efficiencies when using actual PET series instead of long-term averages. This suggests either that watershed models may not conveniently use the climatic information contained in PET values or that formulae are only awkward indicators of the real PET which watershed models need.

  9. A Consistent Methodology Based Parameter Estimation for a Lactic Acid Bacteria Fermentation Model

    DEFF Research Database (Denmark)

    Spann, Robert; Roca, Christophe; Kold, David

    2017-01-01

    Lactic acid bacteria are used in many industrial applications, e.g. as starter cultures in the dairy industry or as probiotics, and research on their cell production is highly required. A first principles kinetic model was developed to describe and understand the biological, physical, and chemical...... mechanisms in a lactic acid bacteria fermentation. We present here a consistent approach for a methodology based parameter estimation for a lactic acid fermentation. In the beginning, just an initial knowledge based guess of parameters was available and an initial parameter estimation of the complete set...... of parameters was performed in order to get a good model fit to the data. However, not all parameters are identifiable with the given data set and model structure. Sensitivity, identifiability, and uncertainty analysis were completed and a relevant identifiable subset of parameters was determined for a new...

  10. 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...

  11. 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.

  12. Theoretical Relevance of Neuropsychological Data for Connectionist Modelling

    Directory of Open Access Journals (Sweden)

    Mauricio Iza

    2011-05-01

    Full Text Available The symbolic information-processing paradigm in cognitive psychology has met a growing challenge from neural network models over the past two decades. While neuropsychological
    evidence has been of great utility to theories concerned with information processing, the real question is, whether the less rigid connectionist models provide valid, or enough, information
    concerning complex cognitive structures. In this work, we will discuss the theoretical implications that neuropsychological data posits for modelling cognitive systems.

  13. A review of models relevant to road safety.

    Science.gov (United States)

    Hughes, B P; Newstead, S; Anund, A; Shu, C C; Falkmer, T

    2015-01-01

    It is estimated that more than 1.2 million people die worldwide as a result of road traffic crashes and some 50 million are injured per annum. At present some Western countries' road safety strategies and countermeasures claim to have developed into 'Safe Systems' models to address the effects of road related crashes. Well-constructed models encourage effective strategies to improve road safety. This review aimed to identify and summarise concise descriptions, or 'models' of safety. The review covers information from a wide variety of fields and contexts including transport, occupational safety, food industry, education, construction and health. The information from 2620 candidate references were selected and summarised in 121 examples of different types of model and contents. The language of safety models and systems was found to be inconsistent. Each model provided additional information regarding style, purpose, complexity and diversity. In total, seven types of models were identified. The categorisation of models was done on a high level with a variation of details in each group and without a complete, simple and rational description. The models identified in this review are likely to be adaptable to road safety and some of them have previously been used. None of systems theory, safety management systems, the risk management approach, or safety culture was commonly or thoroughly applied to road safety. It is concluded that these approaches have the potential to reduce road trauma. Copyright © 2014 Elsevier Ltd. All rights reserved.

  14. Resuspension parameters for TRAC dispersion model

    International Nuclear Information System (INIS)

    Langer, G.

    1987-01-01

    Resuspension factors for the wind erosion of soil contaminated with plutonium are necessary to run the Rocky Flats Plant Terrain Responsive Atmospheric Code (TRAC). The model predicts the dispersion and resulting population dose due to accidental plutonium releases

  15. Relevance of a Managerial Decision-Model to Educational Administration.

    Science.gov (United States)

    Lundin, Edward.; Welty, Gordon

    The rational model of classical economic theory assumes that the decision maker has complete information on alternatives and consequences, and that he chooses the alternative that maximizes expected utility. This model does not allow for constraints placed on the decision maker resulting from lack of information, organizational pressures,…

  16. On the empirical relevance of the transient in opinion models

    Energy Technology Data Exchange (ETDEWEB)

    Banisch, Sven, E-mail: sven.banisch@universecity.d [Mathematical Physics, Physics Department, Bielefeld University, 33501 Bielefeld (Germany); Institute for Complexity Science (ICC), 1249-078 Lisbon (Portugal); Araujo, Tanya, E-mail: tanya@iseg.utl.p [Research Unit on Complexity in Economics (UECE), ISEG, TULisbon, 1249-078 Lisbon (Portugal); Institute for Complexity Science (ICC), 1249-078 Lisbon (Portugal)

    2010-07-12

    While the number and variety of models to explain opinion exchange dynamics is huge, attempts to justify the model results using empirical data are relatively rare. As linking to real data is essential for establishing model credibility, this Letter develops an empirical confirmation experiment by which an opinion model is related to real election data. The model is based on a representation of opinions as a vector of k bits. Individuals interact according to the principle that similarity leads to interaction and interaction leads to still more similarity. In the comparison to real data we concentrate on the transient opinion profiles that form during the dynamic process. An artificial election procedure is introduced which allows to relate transient opinion configurations to the electoral performance of candidates for which data are available. The election procedure based on the well-established principle of proximity voting is repeatedly performed during the transient period and remarkable statistical agreement with the empirical data is observed.

  17. On the empirical relevance of the transient in opinion models

    International Nuclear Information System (INIS)

    Banisch, Sven; Araujo, Tanya

    2010-01-01

    While the number and variety of models to explain opinion exchange dynamics is huge, attempts to justify the model results using empirical data are relatively rare. As linking to real data is essential for establishing model credibility, this Letter develops an empirical confirmation experiment by which an opinion model is related to real election data. The model is based on a representation of opinions as a vector of k bits. Individuals interact according to the principle that similarity leads to interaction and interaction leads to still more similarity. In the comparison to real data we concentrate on the transient opinion profiles that form during the dynamic process. An artificial election procedure is introduced which allows to relate transient opinion configurations to the electoral performance of candidates for which data are available. The election procedure based on the well-established principle of proximity voting is repeatedly performed during the transient period and remarkable statistical agreement with the empirical data is observed.

  18. 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.

  19. Quantifying Key Climate Parameter Uncertainties Using an Earth System Model with a Dynamic 3D Ocean

    Science.gov (United States)

    Olson, R.; Sriver, R. L.; Goes, M. P.; Urban, N.; Matthews, D.; Haran, M.; Keller, K.

    2011-12-01

    Climate projections hinge critically on uncertain climate model parameters such as climate sensitivity, vertical ocean diffusivity and anthropogenic sulfate aerosol forcings. Climate sensitivity is defined as the equilibrium global mean temperature response to a doubling of atmospheric CO2 concentrations. Vertical ocean diffusivity parameterizes sub-grid scale ocean vertical mixing processes. These parameters are typically estimated using Intermediate Complexity Earth System Models (EMICs) that lack a full 3D representation of the oceans, thereby neglecting the effects of mixing on ocean dynamics and meridional overturning. We improve on these studies by employing an EMIC with a dynamic 3D ocean model to estimate these parameters. We carry out historical climate simulations with the University of Victoria Earth System Climate Model (UVic ESCM) varying parameters that affect climate sensitivity, vertical ocean mixing, and effects of anthropogenic sulfate aerosols. We use a Bayesian approach whereby the likelihood of each parameter combination depends on how well the model simulates surface air temperature and upper ocean heat content. We use a Gaussian process emulator to interpolate the model output to an arbitrary parameter setting. We use Markov Chain Monte Carlo method to estimate the posterior probability distribution function (pdf) of these parameters. We explore the sensitivity of the results to prior assumptions about the parameters. In addition, we estimate the relative skill of different observations to constrain the parameters. We quantify the uncertainty in parameter estimates stemming from climate variability, model and observational errors. We explore the sensitivity of key decision-relevant climate projections to these parameters. We find that climate sensitivity and vertical ocean diffusivity estimates are consistent with previously published results. The climate sensitivity pdf is strongly affected by the prior assumptions, and by the scaling

  20. Modeling Influenza Transmission Using Environmental Parameters

    Science.gov (United States)

    Soebiyanto, Radina P.; Kiang, Richard K.

    2010-01-01

    Influenza is an acute viral respiratory disease that has significant mortality, morbidity and economic burden worldwide. It infects approximately 5-15% of the world population, and causes 250,000 500,000 deaths each year. The role of environments on influenza is often drawn upon the latitude variability of influenza seasonality pattern. In regions with temperate climate, influenza epidemics exhibit clear seasonal pattern that peak during winter months, but it is not as evident in the tropics. Toward this end, we developed mathematical model and forecasting capabilities for influenza in regions characterized by warm climate Hong Kong (China) and Maricopa County (Arizona, USA). The best model for Hong Kong uses Land Surface Temperature (LST), precipitation and relative humidity as its covariates. Whereas for Maricopa County, we found that weekly influenza cases can be best modelled using mean air temperature as its covariates. Our forecasts can further guides public health organizations in targeting influenza prevention and control measures such as vaccination.

  1. 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.

  2. Perceived Service Quality models: Are They Still Relevant?

    OpenAIRE

    Polyakova, Olga; Mirza, Mohammed T.

    2015-01-01

    This paper reviews the concept of perceived service quality and provides an update to the body of service quality knowledge. It consolidates the pathway of perceived service quality concept, from its emergence to the research model’s development. It also critically reviews service characteristics as prerequisites of perceived service quality conceptualisation. The examination of six perceived service quality models is intended to identify a superior model that could be used by further researc...

  3. 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.

  4. Advances in Modelling, System Identification and Parameter ...

    Indian Academy of Sciences (India)

    Authors show, using numerical simulation for two system functions, the improvement in percentage normalized ... of nonlinear systems. The approach is to use multiple linearizing models fitted along the operating trajectories. ... over emphasized in the light of present day high level of research activity in the field of aerospace ...

  5. Assessing the value relevance of current mandatory business model disclosures

    DEFF Research Database (Denmark)

    Schaper, Stefan; Nielsen, Christian; Simoni, Lorenzo

    the model developed by Ohlson (1995). Our results show no significant association between BM disclosure and share prices. The main reason behind this finding can be associated with the low level of disclosure (i.e. the low number of value drivers disclosed on average) by companies as part of their BM......Recent regulations have introduced the requirement for large companies to disclose information about their business model (BM) in the annual reports. The objective of these disclosures is to allow external users to understand better how companies create, deliver and capture value. This study aims...... reports. Ad-hoc created disclosure indexes are based on the taxonomy of business model (BM) configurations developed by Taran et al. (2016) as well as complemented by a frame of reference based on the nice BM canvas elements from Osterwalder and Pigneur (2010). After the classification of companies...

  6. 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

  7. 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.

  8. relevance of information warfare models to critical infrastructure

    African Journals Online (AJOL)

    ismith

    Critical infrastructure models, strategies and policies should take information ... gain an advantage over a competitor or adversary through the use of one's own .... digital communications system, where the vehicles are analogous to bits or packets, ..... performance degraded, causing an increase in traffic finding a new route.

  9. Automatic Relevance Determination for multi-way models

    DEFF Research Database (Denmark)

    Mørup, Morten; Hansen, Lars Kai

    2009-01-01

    of components of data within the Tucker and CP structure. For the Tucker and CP model the approach performs better than heuristics such as the Bayesian Information Criterion, Akaikes Information Criterion, DIFFIT and the numerical convex hull (NumConvHull) while operating only at the cost of estimating...... is available for download at www.erpwavelab.org....

  10. 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

  11. 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.

  12. Parameters modelling of amaranth grain processing technology

    Science.gov (United States)

    Derkanosova, N. M.; Shelamova, S. A.; Ponomareva, I. N.; Shurshikova, G. V.; Vasilenko, O. A.

    2018-03-01

    The article presents a technique that allows calculating the structure of a multicomponent bakery mixture for the production of enriched products, taking into account the instability of nutrient content, and ensuring the fulfilment of technological requirements and, at the same time considering consumer preferences. The results of modelling and analysis of optimal solutions are given by the example of calculating the structure of a three-component mixture of wheat and rye flour with an enriching component, that is, whole-hulled amaranth flour applied to the technology of bread from a mixture of rye and wheat flour on a liquid leaven.

  13. 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...

  14. 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 ...

  15. 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)

  16. 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...

  17. On the hyperporous non-linear elasticity model for fusion-relevant pebble beds

    International Nuclear Information System (INIS)

    Di Maio, P.A.; Giammusso, R.; Vella, G.

    2010-01-01

    Packed pebble beds are particular granular systems composed of a large amount of small particles, arranged in irregular lattices and surrounded by a gas filling interstitial spaces. Due to their heterogeneous structure, pebble beds have non-linear and strongly coupled thermal and mechanical behaviours whose constitutive models seem limited, being not suitable for fusion-relevant design-oriented applications. Within the framework of the modelling activities promoted for the lithiated ceramics and beryllium pebble beds foreseen in the Helium-Cooled Pebble Bed breeding blanket concept of DEMO, at the Department of Nuclear Engineering of the University of Palermo (DIN) a thermo-mechanical constitutive model has been set-up assuming that pebble beds can be considered as continuous, homogeneous and isotropic media. The present paper deals with the DIN non-linear elasticity constitutive model, based on the assumption that during the reversible straining of a pebble bed its effective logarithmic bulk modulus depends on the equivalent pressure according to a modified power law and its effective Poisson modulus remains constant. In these hypotheses the functional dependence of the effective tangential and secant bed deformation moduli on either the equivalent pressure or the volumetric strain have been derived in a closed analytical form. A procedure has been, then, defined to assess the model parameters for a given pebble bed from its oedometric test results and it has been applied to both polydisperse lithium orthosilicate and single size beryllium pebble beds.

  18. 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.

  19. 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

  20. 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.

  1. Relevant pH and lipase for in vitro models of gastric digestion.

    Science.gov (United States)

    Sams, Laura; Paume, Julie; Giallo, Jacqueline; Carrière, Frédéric

    2016-01-01

    The development of in vitro digestion models relies on the availability of in vivo data such as digestive enzyme levels and pH values recorded in the course of meal digestion. The variations of these parameters along the GI tract are important for designing dynamic digestion models but also static models for which the choice of representative conditions of the gastric and intestinal conditions is critical. Simulating gastric digestion with a static model and a single set of parameters is particularly challenging because the variations in pH and enzyme concentration occurring in the stomach are much broader than those occurring in the small intestine. A review of the literature on this topic reveals that most models of gastric digestion use very low pH values that are not representative of the fed conditions. This is illustrated here by showing the variations in gastric pH as a function of meal gastric emptying instead of time. This representation highlights those pH values that are the most relevant for testing meal digestion in the stomach. Gastric lipolysis is still largely ignored or is performed with microbial lipases. In vivo data on gastric lipase and lipolysis have however been collected in humans and dogs during test meals. The biochemical characterization of gastric lipase has shown that this enzyme is rather unique among lipases: (i) stability and activity in the pH range 2 to 7 with an optimum at pH 4-5.4; (ii) high tensioactivity that allows resistance to bile salts and penetration into phospholipid layers covering TAG droplets; (iii) sn-3 stereospecificity for TAG hydrolysis; and (iv) resistance to pepsin. Most of these properties have been known for more than two decades and should provide a rational basis for the replacement of gastric lipase by other lipases when gastric lipase is not available.

  2. 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

  3. 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)

  4. The hamster flank organ model: Is it relevant to man

    International Nuclear Information System (INIS)

    Franz, T.J.; Lehman, P.A.; Pochi, P.; Odland, G.F.; Olerud, J.

    1989-01-01

    The critical role that androgens play in the etiology of acne has led to a search for topically active antiandrogens and the frequent use of the flank organ of the golden Syrian hamster as an animal model. 17-alpha-propyltestosterone (17-PT) has been identified as having potent antiandrogenic activity in the hamster model, and this report describes its clinical evaluation. Two double-blind placebo controlled studies comparing 4% 17-PT in 80% alcohol versus vehicle alone were conducted. One study examined 17-PT sebosuppressive activity in 20 subjects. The second study examined its efficacy in 44 subjects having mild to moderate acne. A third study measured in vitro percutaneous absorption of 17-PT through hamster flank and monkey skin, and human face skin in-vivo, using radioactive drug. 17-PT was found to be ineffective in reducing either the sebum excretion rate or the number of inflammatory acne lesions. Failure of 17-PT to show clinical activity was not a result of poor percutaneous absorption. Total absorption in man was 7.7% of the dose and only 1.0% in the hamster. The sebaceous gland of hamster flank organ is apparently more sensitive to antiandrogens than the human sebaceous gland

  5. 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)

  6. RF modeling of the ITER-relevant lower hybrid antenna

    International Nuclear Information System (INIS)

    Hillairet, J.; Ceccuzzi, S.; Belo, J.; Marfisi, L.; Artaud, J.F.; Bae, Y.S.; Berger-By, G.; Bernard, J.M.; Cara, Ph.; Cardinali, A.; Castaldo, C.; Cesario, R.; Decker, J.; Delpech, L.; Ekedahl, A.; Garcia, J.; Garibaldi, P.; Goniche, M.; Guilhem, D.; Hoang, G.T.

    2011-01-01

    In the frame of the EFDA task HCD-08-03-01, a 5 GHz Lower Hybrid system which should be able to deliver 20 MW CW on ITER and sustain the expected high heat fluxes has been reviewed. The design and overall dimensions of the key RF elements of the launcher and its subsystem has been updated from the 2001 design in collaboration with ITER organization. Modeling of the LH wave propagation and absorption into the plasma shows that the optimal parallel index must be chosen between 1.9 and 2.0 for the ITER steady-state scenario. The present study has been made with n || = 2.0 but can be adapted for n || = 1.9. Individual components have been studied separately giving confidence on the global RF design of the whole antenna.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. 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

  14. 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.

  15. 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...

  16. 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.

  17. 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...

  18. 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

  19. 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)

  20. 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.

  1. 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)

  2. Online State Space Model Parameter Estimation in Synchronous Machines

    Directory of Open Access Journals (Sweden)

    Z. Gallehdari

    2014-06-01

    The suggested approach is evaluated for a sample synchronous machine model. Estimated parameters are tested for different inputs at different operating conditions. The effect of noise is also considered in this study. Simulation results show that the proposed approach provides good accuracy for parameter estimation.

  3. 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

  4. 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.

  5. 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.

  6. Constructing an everywhere and locally relevant predictive model of the West-African critical zone

    Science.gov (United States)

    Hector, B.; Cohard, J. M.; Pellarin, T.; Maxwell, R. M.; Cappelaere, B.; Demarty, J.; Grippa, M.; Kergoat, L.; Lebel, T.; Mamadou, O.; Mougin, E.; Panthou, G.; Peugeot, C.; Vandervaere, J. P.; Vischel, T.; Vouillamoz, J. M.

    2017-12-01

    Considering water resources and hydrologic hazards, West Africa is among the most vulnerable regions to face both climatic (e.g. with the observed intensification of precipitation) and anthropogenic changes. With +3% of demographic rate, the region experiences rapid land use changes and increased pressure on surface and groundwater resources with observed consequences on the hydrological cycle (water table rise result of the sahelian paradox, increase in flood occurrence, etc.) Managing large hydrosystems (such as transboundary aquifers or rivers basins as the Niger river) requires anticipation of such changes. However, the region significantly lacks observations, for constructing and validating critical zone (CZ) models able to predict future hydrologic regime, but also comprises hydrosystems which encompass strong environmental gradients (e.g. geological, climatic, ecological) with highly different dominating hydrological processes. We address these issues by constructing a high resolution (1 km²) regional scale physically-based model using ParFlow-CLM which allows modeling a wide range of processes without prior knowledge on their relative dominance. Our approach combines multiple scale modeling from local to meso and regional scales within the same theoretical framework. Local and meso-scale models are evaluated thanks to the rich AMMA-CATCH CZ observation database which covers 3 supersites with contrasted environments in Benin (Lat.: 9.8°N), Niger (Lat.: 13.3°N) and Mali (Lat.: 15.3°N). At the regional scale the lack of relevant map of soil hydrodynamic parameters is addressed using remote sensing data assimilation. Our first results show the model's ability to reproduce the known dominant hydrological processes (runoff generation, ET, groundwater recharge…) across the major West-African regions and allow us to conduct virtual experiments to explore the impact of global changes on the hydrosystems. This approach is a first step toward the construction of

  7. Parameter Estimates in Differential Equation Models for Population Growth

    Science.gov (United States)

    Winkel, Brian J.

    2011-01-01

    We estimate the parameters present in several differential equation models of population growth, specifically logistic growth models and two-species competition models. We discuss student-evolved strategies and offer "Mathematica" code for a gradient search approach. We use historical (1930s) data from microbial studies of the Russian biologist,…

  8. 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.

  9. The temporal-relevance temporal-uncertainty model of prospective duration judgment.

    Science.gov (United States)

    Zakay, Dan

    2015-12-15

    A model aimed at explaining prospective duration judgments in real life settings (as well as in the laboratory) is presented. The model is based on the assumption that situational meaning is continuously being extracted by humans' perceptual and cognitive information processing systems. Time is one of the important dimensions of situational meaning. Based on the situational meaning, a value for Temporal Relevance is set. Temporal Relevance reflects the importance of temporal aspects for enabling adaptive behavior in a specific moment in time. When Temporal Relevance is above a certain threshold a prospective duration judgment process is evoked automatically. In addition, a search for relevant temporal information is taking place and its outcomes determine the level of Temporal Uncertainty which reflects the degree of knowledge one has regarding temporal aspects of the task to be performed. The levels of Temporal Relevance and Temporal Uncertainty determine the amount of attentional resources allocated for timing by the executive system. The merit of the model is in connecting timing processes with the ongoing general information processing stream. The model rests on findings in various domains which indicate that cognitive-relevance and self-relevance are powerful determinants of resource allocation policy. The feasibility of the model is demonstrated by analyzing various temporal phenomena. Suggestions for further empirical validation of the model are presented. Copyright © 2015 Elsevier Inc. All rights reserved.

  10. 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.

  11. Agricultural and Environmental Input Parameters for the Biosphere Model

    International Nuclear Information System (INIS)

    K. Rasmuson; K. Rautenstrauch

    2004-01-01

    This analysis is one of 10 technical reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) (i.e., the biosphere model). It documents development of agricultural and environmental input parameters for the biosphere model, and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for the repository at Yucca Mountain. The ERMYN provides the TSPA with the capability to perform dose assessments. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships between the major activities and their products (the analysis and model reports) that were planned in ''Technical Work Plan for Biosphere Modeling and Expert Support'' (BSC 2004 [DIRS 169573]). The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the ERMYN and its input parameters

  12. 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...

  13. 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....

  14. 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.

  15. 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.)

  16. 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...

  17. 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....

  18. 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...

  19. 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...

  20. Objective image quality parameters of relevance in practice, measured for film-screen combinations - a contribution to quality assurance activities

    International Nuclear Information System (INIS)

    Angerstein, W.; Wolf, M.

    1986-01-01

    Objective measurement of the physico-technical parameters determining the image quality is the fastest and most accurate method of quality testing of the systems. The parameters in case of X-ray intensifying screens are imaging quality, servicable life, and mechanical properties. (orig./DG) [de

  1. A User-Centered Approach to Adaptive Hypertext Based on an Information Relevance Model

    Science.gov (United States)

    Mathe, Nathalie; Chen, James

    1994-01-01

    Rapid and effective to information in large electronic documentation systems can be facilitated if information relevant in an individual user's content can be automatically supplied to this user. However most of this knowledge on contextual relevance is not found within the contents of documents, it is rather established incrementally by users during information access. We propose a new model for interactively learning contextual relevance during information retrieval, and incrementally adapting retrieved information to individual user profiles. The model, called a relevance network, records the relevance of references based on user feedback for specific queries and user profiles. It also generalizes such knowledge to later derive relevant references for similar queries and profiles. The relevance network lets users filter information by context of relevance. Compared to other approaches, it does not require any prior knowledge nor training. More importantly, our approach to adaptivity is user-centered. It facilitates acceptance and understanding by users by giving them shared control over the adaptation without disturbing their primary task. Users easily control when to adapt and when to use the adapted system. Lastly, the model is independent of the particular application used to access information, and supports sharing of adaptations among users.

  2. Anatomical masking of pressure footprints based on the Oxford Foot Model: validation and clinical relevance.

    Science.gov (United States)

    Giacomozzi, Claudia; Stebbins, Julie A

    2017-03-01

    Plantar pressure analysis is widely used in the assessment of foot function. In order to assess regional loading, a mask is applied to the footprint to sub-divide it into regions of interest (ROIs). The most common masking method is based on geometric features of the footprint (GM). Footprint masking based on anatomical landmarks of the foot has been implemented more recently, and involves the integration of a 3D motion capture system, plantar pressure measurement device, and a multi-segment foot model. However, thorough validation of anatomical masking (AM) using pathological footprints has not yet been presented. In the present study, an AM method based on the Oxford Foot Model (OFM) was compared to an equivalent GM. Pressure footprints from 20 young healthy subjects (HG) and 20 patients with clubfoot (CF) were anatomically divided into 5 ROIs using a subset of the OFM markers. The same foot regions were also identified by using a standard GM method. Comparisons of intra-subject coefficient of variation (CV) showed that the OFM-based AM was at least as reliable as the GM for all investigated pressure parameters in all foot regions. Clinical relevance of AM was investigated by comparing footprints from HG and CF groups. Contact time, maximum force, force-time integral and contact area proved to be sensitive parameters that were able to distinguish HG and CF groups, using both AM and GM methods However, the AM method revealed statistically significant differences between groups in 75% of measured variables, compared to 62% using a standard GM method, indicating that the AM method is more sensitive for revealing differences between groups. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. 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.

  4. Present status on atomic and molecular data relevant to fusion plasma diagnostics and modeling

    International Nuclear Information System (INIS)

    Tawara, H.

    1997-01-01

    This issue is the collection of the paper presented status on atomic and molecular data relevant to fusion plasma diagnostics and modeling. The 10 of the presented papers are indexed individually. (J.P.N.)

  5. Heavy particle track structure parameters for biophysical modelling

    International Nuclear Information System (INIS)

    Watt, D.E.

    1994-01-01

    Averaged values of physical track structure parameters are important in radiobiology and radiological protection for the expression of damage mechanisms and for quantifying radiation effects. To provide a ready reference, tables of relevant quantities have been compiled for heavy charged particles in liquid water. The full tables will be published elsewhere but here illustrative examples are given of the trends for the most important quantities. In the tables, data are given for 74 types of heavy charged particle ranging from protons to uranium ions at specific energies between 0.1 keV/u and 1 GeV/u. Aggregate effects in liquid water are taken into account implicitly in the calculations. Results are presented for instantaneous particle energies and for averages over the charged particle equilibrium spectrum. The latter are of special relevance to radiation dosimetry. Quality parameters calculated are: β 2 ; z 2 /β 2 ; linear primary ionisation and the mean free path between ionisations; LET; track and dose-restricted LET with 100 eV cut-off; relative variances; delta-ray energies and ranges; ion energies and ranges and kerma factors. Here, the procedures used in the calculations are indicated. Representative results are shown in graphical form. The role of the physical track properties is discussed with regard to optimisation of the design of experiments intended to elucidate biological damage mechanisms in mammalian cells and their relevance to radiological protection. ((orig.))

  6. 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

  7. 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

  8. 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])

  9. 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.

  10. 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

  11. 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

  12. 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

  13. Highly Relevant Mentoring (HRM) as a Faculty Development Model for Web-Based Instruction

    Science.gov (United States)

    Carter, Lorraine; Salyers, Vincent; Page, Aroha; Williams, Lynda; Albl, Liz; Hofsink, Clarence

    2012-01-01

    This paper describes a faculty development model called the highly relevant mentoring (HRM) model; the model includes a framework as well as some practical strategies for meeting the professional development needs of faculty who teach web-based courses. The paper further emphasizes the need for faculty and administrative buy-in for HRM and…

  14. Political economy models and agricultural policy formation : empirical applicability and relevance for the CAP

    NARCIS (Netherlands)

    Zee, van der F.A.

    1997-01-01

    This study explores the relevance and applicability of political economy models for the explanation of agricultural policies. Part I (chapters 4-7) takes a general perspective and evaluates the empirical applicability of voting models and interest group models to agricultural policy

  15. 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

  16. Regionalising Parameters of a Conceptual Rainfall-Runoff Model for ...

    African Journals Online (AJOL)

    IHACRES, a lumped conceptual rainfall-runoff model, was calibrated to six catchments ranging in size from 49km2 to 600 km2 within the upper Tana River basin to obtain a set of model parameters that characterise the hydrological behaviour within the region. Physical catchment attributes indexing topography, soil and ...

  17. Constraint on Parameters of Inverse Compton Scattering Model for ...

    Indian Academy of Sciences (India)

    B2319+60, two parameters of inverse Compton scattering model, the initial Lorentz factor and the factor of energy loss of relativistic particles are constrained. Key words. Pulsar—inverse Compton scattering—emission mechanism. 1. Introduction. Among various kinds of models for pulsar radio emission, the inverse ...

  18. Geometry parameters for musculoskeletal modelling of the shoulder system

    NARCIS (Netherlands)

    Van der Helm, F C; Veeger, DirkJan (H. E. J.); Pronk, G M; Van der Woude, L H; Rozendal, R H

    A dynamical finite-element model of the shoulder mechanism consisting of thorax, clavicula, scapula and humerus is outlined. The parameters needed for the model are obtained in a cadaver experiment consisting of both shoulders of seven cadavers. In this paper, in particular, the derivation of

  19. Rain storm models and the relationship between their parameters

    NARCIS (Netherlands)

    Stol, P.T.

    1977-01-01

    Rainfall interstation correlation functions can be obtained with the aid of analytic rainfall or storm models. Since alternative storm models have different mathematical formulas, comparison should be based on equallity of parameters like storm diameter, mean rainfall amount, storm maximum or total

  20. 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.

  1. A software for parameter estimation in dynamic models

    Directory of Open Access Journals (Sweden)

    M. Yuceer

    2008-12-01

    Full Text Available A common problem in dynamic systems is to determine parameters in an equation used to represent experimental data. The goal is to determine the values of model parameters that provide the best fit to measured data, generally based on some type of least squares or maximum likelihood criterion. In the most general case, this requires the solution of a nonlinear and frequently non-convex optimization problem. Some of the available software lack in generality, while others do not provide ease of use. A user-interactive parameter estimation software was needed for identifying kinetic parameters. In this work we developed an integration based optimization approach to provide a solution to such problems. For easy implementation of the technique, a parameter estimation software (PARES has been developed in MATLAB environment. When tested with extensive example problems from literature, the suggested approach is proven to provide good agreement between predicted and observed data within relatively less computing time and iterations.

  2. 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.

  3. Parameter identification in a nonlinear nuclear reactor model using quasilinearization

    International Nuclear Information System (INIS)

    Barreto, J.M.; Martins Neto, A.F.; Tanomaru, N.

    1980-09-01

    Parameter identification in a nonlinear, lumped parameter, nuclear reactor model is carried out using discrete output power measurements during the transient caused by an external reactivity change. In order to minimize the difference between the model and the reactor power responses, the parameter promt neutron generation time and a parameter in fuel temperature reactivity coefficient equation are adjusted using quasilinearization. The influences of the external reactivity disturbance, the number and frequency of measurements and the measurement noise level on the method accuracy and rate of convergence are analysed through simulation. Procedures for the design of the identification experiments are suggested. The method proved to be very effective for low level noise measurements. (Author) [pt

  4. 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

  5. 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.

  6. 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.

  7. 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

  8. Parameters Optimization and Application to Glutamate Fermentation Model Using SVM

    OpenAIRE

    Zhang, Xiangsheng; Pan, Feng

    2015-01-01

    Aimed at the parameters optimization in support vector machine (SVM) for glutamate fermentation modelling, a new method is developed. It optimizes the SVM parameters via an improved particle swarm optimization (IPSO) algorithm which has better global searching ability. The algorithm includes detecting and handling the local convergence and exhibits strong ability to avoid being trapped in local minima. The material step of the method was shown. Simulation experiments demonstrate the effective...

  9. Parameters Optimization and Application to Glutamate Fermentation Model Using SVM

    Directory of Open Access Journals (Sweden)

    Xiangsheng Zhang

    2015-01-01

    Full Text Available Aimed at the parameters optimization in support vector machine (SVM for glutamate fermentation modelling, a new method is developed. It optimizes the SVM parameters via an improved particle swarm optimization (IPSO algorithm which has better global searching ability. The algorithm includes detecting and handling the local convergence and exhibits strong ability to avoid being trapped in local minima. The material step of the method was shown. Simulation experiments demonstrate the effectiveness of the proposed algorithm.

  10. A Bayesian framework for parameter estimation in dynamical models.

    Directory of Open Access Journals (Sweden)

    Flávio Codeço Coelho

    Full Text Available Mathematical models in biology are powerful tools for the study and exploration of complex dynamics. Nevertheless, bringing theoretical results to an agreement with experimental observations involves acknowledging a great deal of uncertainty intrinsic to our theoretical representation of a real system. Proper handling of such uncertainties is key to the successful usage of models to predict experimental or field observations. This problem has been addressed over the years by many tools for model calibration and parameter estimation. In this article we present a general framework for uncertainty analysis and parameter estimation that is designed to handle uncertainties associated with the modeling of dynamic biological systems while remaining agnostic as to the type of model used. We apply the framework to fit an SIR-like influenza transmission model to 7 years of incidence data in three European countries: Belgium, the Netherlands and Portugal.

  11. A lumped parameter, low dimension model of heat exchanger

    International Nuclear Information System (INIS)

    Kanoh, Hideaki; Furushoo, Junji; Masubuchi, Masami

    1980-01-01

    This paper reports on the results of investigation of the distributed parameter model, the difference model, and the model of the method of weighted residuals for heat exchangers. By the method of weighted residuals (MWR), the opposite flow heat exchanger system is approximated by low dimension, lumped parameter model. By assuming constant specific heat, constant density, the same form of tube cross-section, the same form of the surface of heat exchange, uniform flow velocity, the linear relation of heat transfer to flow velocity, liquid heat carrier, and the thermal insulation of liquid from outside, fundamental equations are obtained. The experimental apparatus was made of acrylic resin. The response of the temperature at the exit of first liquid to the variation of the flow rate of second liquid was measured and compared with the models. The MWR model shows good approximation for the low frequency region, and as the number of division increases, good approximation spreads to higher frequency region. (Kato, T.)

  12. Reservoir theory, groundwater transit time distributions, and lumped parameter models

    International Nuclear Information System (INIS)

    Etcheverry, D.; Perrochet, P.

    1999-01-01

    The relation between groundwater residence times and transit times is given by the reservoir theory. It allows to calculate theoretical transit time distributions in a deterministic way, analytically, or on numerical models. Two analytical solutions validates the piston flow and the exponential model for simple conceptual flow systems. A numerical solution of a hypothetical regional groundwater flow shows that lumped parameter models could be applied in some cases to large-scale, heterogeneous aquifers. (author)

  13. 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

  14. 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.

  15. Synchronous Generator Model Parameter Estimation Based on Noisy Dynamic Waveforms

    Science.gov (United States)

    Berhausen, Sebastian; Paszek, Stefan

    2016-01-01

    In recent years, there have occurred system failures in many power systems all over the world. They have resulted in a lack of power supply to a large number of recipients. To minimize the risk of occurrence of power failures, it is necessary to perform multivariate investigations, including simulations, of power system operating conditions. To conduct reliable simulations, the current base of parameters of the models of generating units, containing the models of synchronous generators, is necessary. In the paper, there is presented a method for parameter estimation of a synchronous generator nonlinear model based on the analysis of selected transient waveforms caused by introducing a disturbance (in the form of a pseudorandom signal) in the generator voltage regulation channel. The parameter estimation was performed by minimizing the objective function defined as a mean square error for deviations between the measurement waveforms and the waveforms calculated based on the generator mathematical model. A hybrid algorithm was used for the minimization of the objective function. In the paper, there is described a filter system used for filtering the noisy measurement waveforms. The calculation results of the model of a 44 kW synchronous generator installed on a laboratory stand of the Institute of Electrical Engineering and Computer Science of the Silesian University of Technology are also given. The presented estimation method can be successfully applied to parameter estimation of different models of high-power synchronous generators operating in a power system.

  16. On the role of modeling parameters in IMRT plan optimization

    International Nuclear Information System (INIS)

    Krause, Michael; Scherrer, Alexander; Thieke, Christian

    2008-01-01

    The formulation of optimization problems in intensity-modulated radiotherapy (IMRT) planning comprises the choice of various values such as function-specific parameters or constraint bounds. In current inverse planning programs that yield a single treatment plan for each optimization, it is often unclear how strongly these modeling parameters affect the resulting plan. This work investigates the mathematical concepts of elasticity and sensitivity to deal with this problem. An artificial planning case with a horse-shoe formed target with different opening angles surrounding a circular risk structure is studied. As evaluation functions the generalized equivalent uniform dose (EUD) and the average underdosage below and average overdosage beyond certain dose thresholds are used. A single IMRT plan is calculated for an exemplary parameter configuration. The elasticity and sensitivity of each parameter are then calculated without re-optimization, and the results are numerically verified. The results show the following. (1) elasticity can quantify the influence of a modeling parameter on the optimization result in terms of how strongly the objective function value varies under modifications of the parameter value. It also can describe how strongly the geometry of the involved planning structures affects the optimization result. (2) Based on the current parameter settings and corresponding treatment plan, sensitivity analysis can predict the optimization result for modified parameter values without re-optimization, and it can estimate the value intervals in which such predictions are valid. In conclusion, elasticity and sensitivity can provide helpful tools in inverse IMRT planning to identify the most critical parameters of an individual planning problem and to modify their values in an appropriate way

  17. DETERMINATION OF RELEVANT FEATURES OF A SCALE MODEL FOR A 55 000 DWT BULK CARRIER NECESSARY TO STUDY THE SHIP MANEUVERABILITY

    Directory of Open Access Journals (Sweden)

    ALECU TOMA

    2016-06-01

    Full Text Available The study method of a ship behavior based on practical tests on scale models is widely used both leading scientists and engineers, architects and researchers in the naval field. In this paper we propose to determine the parameters of a ship handling characteristics relevant to study the 55,000 dwt bulk carrier using a scale model. Scientific background for practical experimentation of this techniques necessary to built a scale model ship consists in applying the principles of similarity or "similitude". The scale model achieved by applying the laws of similarity must allow, through approximations available in certain circumstances, finding relevant parameters needed to simplify and solve the Navier-Stokes equations. These parameters are necessary for modeling the interaction between hull of the real ship and the fluid motion.

  18. 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.

  19. Spatial extrapolation of light use efficiency model parameters to predict gross primary production

    Directory of Open Access Journals (Sweden)

    Karsten Schulz

    2011-12-01

    Full Text Available To capture the spatial and temporal variability of the gross primary production as a key component of the global carbon cycle, the light use efficiency modeling approach in combination with remote sensing data has shown to be well suited. Typically, the model parameters, such as the maximum light use efficiency, are either set to a universal constant or to land class dependent values stored in look-up tables. In this study, we employ the machine learning technique support vector regression to explicitly relate the model parameters of a light use efficiency model calibrated at several FLUXNET sites to site-specific characteristics obtained by meteorological measurements, ecological estimations and remote sensing data. A feature selection algorithm extracts the relevant site characteristics in a cross-validation, and leads to an individual set of characteristic attributes for each parameter. With this set of attributes, the model parameters can be estimated at sites where a parameter calibration is not possible due to the absence of eddy covariance flux measurement data. This will finally allow a spatially continuous model application. The performance of the spatial extrapolation scheme is evaluated with a cross-validation approach, which shows the methodology to be well suited to recapture the variability of gross primary production across the study sites.

  20. 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...

  1. Physically based model for extracting dual permeability parameters using non-Newtonian fluids

    Science.gov (United States)

    Abou Najm, M. R.; Basset, C.; Stewart, R. D.; Hauswirth, S.

    2017-12-01

    Dual permeability models are effective for the assessment of flow and transport in structured soils with two dominant structures. The major challenge to those models remains in the ability to determine appropriate and unique parameters through affordable, simple, and non-destructive methods. This study investigates the use of water and a non-Newtonian fluid in saturated flow experiments to derive physically-based parameters required for improved flow predictions using dual permeability models. We assess the ability of these two fluids to accurately estimate the representative pore sizes in dual-domain soils, by determining the effective pore sizes of macropores and micropores. We developed two sub-models that solve for the effective macropore size assuming either cylindrical (e.g., biological pores) or planar (e.g., shrinkage cracks and fissures) pore geometries, with the micropores assumed to be represented by a single effective radius. Furthermore, the model solves for the percent contribution to flow (wi) corresponding to the representative macro and micro pores. A user-friendly solver was developed to numerically solve the system of equations, given that relevant non-Newtonian viscosity models lack forms conducive to analytical integration. The proposed dual-permeability model is a unique attempt to derive physically based parameters capable of measuring dual hydraulic conductivities, and therefore may be useful in reducing parameter uncertainty and improving hydrologic model predictions.

  2. 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.

  3. 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.

  4. The relevance of non-human primate and rodent malaria models for humans

    OpenAIRE

    Langhorne, Jean; Buffet, Pierre; Galinski, Mary; Good, Michael; Harty, John; Leroy, Didier; Mota, Maria M; Pasini, Erica; Renia, Laurent; Riley, Eleanor; Stins, Monique; Duffy, Patrick

    2011-01-01

    Abstract At the 2010 Keystone Symposium on "Malaria: new approaches to understanding Host-Parasite interactions", an extra scientific session to discuss animal models in malaria research was convened at the request of participants. This was prompted by the concern of investigators that skepticism in the malaria community about the use and relevance of animal models, particularly rodent models of severe malaria, has impacted on funding decisions and publication of research using animal models....

  5. Political economy models and agricultural policy formation : empirical applicability and relevance for the CAP

    OpenAIRE

    Zee, van der, F.A.

    1997-01-01

    This study explores the relevance and applicability of political economy models for the explanation of agricultural policies. Part I (chapters 4-7) takes a general perspective and evaluates the empirical applicability of voting models and interest group models to agricultural policy formation in industrialised market economics. Part II (chapters 8-11) focuses on the empirical applicability of political economy models to agricultural policy formation and agricultural policy developmen...

  6. Deriving amplification factors from simple site parameters using generalized regression neural networks: implications for relevant site proxies

    Science.gov (United States)

    Boudghene Stambouli, Ahmed; Zendagui, Djawad; Bard, Pierre-Yves; Derras, Boumédiène

    2017-07-01

    Most modern seismic codes account for site effects using an amplification factor (AF) that modifies the rock acceleration response spectra in relation to a "site condition proxy," i.e., a parameter related to the velocity profile at the site under consideration. Therefore, for practical purposes, it is interesting to identify the site parameters that best control the frequency-dependent shape of the AF. The goal of the present study is to provide a quantitative assessment of the performance of various site condition proxies to predict the main AF features, including the often used short- and mid-period amplification factors, Fa and Fv, proposed by Borcherdt (in Earthq Spectra 10:617-653, 1994). In this context, the linear, viscoelastic responses of a set of 858 actual soil columns from Japan, the USA, and Europe are computed for a set of 14 real accelerograms with varying frequency contents. The correlation between the corresponding site-specific average amplification factors and several site proxies (considered alone or as multiple combinations) is analyzed using the generalized regression neural network (GRNN). The performance of each site proxy combination is assessed through the variance reduction with respect to the initial amplification factor variability of the 858 profiles. Both the whole period range and specific short- and mid-period ranges associated with the Borcherdt factors Fa and Fv are considered. The actual amplification factor of an arbitrary soil profile is found to be satisfactorily approximated with a limited number of site proxies (4-6). As the usual code practice implies a lower number of site proxies (generally one, sometimes two), a sensitivity analysis is conducted to identify the "best performing" site parameters. The best one is the overall velocity contrast between underlying bedrock and minimum velocity in the soil column. Because these are the most difficult and expensive parameters to measure, especially for thick deposits, other

  7. 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.)

  8. 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.

  9. Higgs boson resonance parameters and the finite temperature phase transition in a chirally invariant Higgs-Yukawa model

    Energy Technology Data Exchange (ETDEWEB)

    Bulava, John; Jansen, Karl [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany). John von Neumann-Inst. fuer Computing NIC; Gerhold, Philip; Kallarackal, Jim; Nagy, Attila [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany). John von Neumann-Inst. fuer Computing NIC; Humbolt-Univ. Berlin (Germany)

    2011-12-15

    We study a chirally invariant Higgs-Yukawa model regulated on a space-time lattice. We calculate Higgs boson resonance parameters and mass bounds for various values of the mass of the degenerate fermion doublet. Also, first results on the phase transition temperature are presented. In general, this model may be relevant for BSM scenarios with a heavy fourth generation of quarks. (orig.)

  10. Functionally relevant climate variables for arid lands: Aclimatic water deficit approach for modelling desert shrub distributions

    Science.gov (United States)

    Thomas E. Dilts; Peter J. Weisberg; Camie M. Dencker; Jeanne C. Chambers

    2015-01-01

    We have three goals. (1) To develop a suite of functionally relevant climate variables for modelling vegetation distribution on arid and semi-arid landscapes of the Great Basin, USA. (2) To compare the predictive power of vegetation distribution models based on mechanistically proximate factors (water deficit variables) and factors that are more mechanistically removed...

  11. Towards Increased Relevance: Context-Adapted Models of the Learning Organization

    Science.gov (United States)

    Örtenblad, Anders

    2015-01-01

    Purpose: The purposes of this paper are to take a closer look at the relevance of the idea of the learning organization for organizations in different generalized organizational contexts; to open up for the existence of multiple, context-adapted models of the learning organization; and to suggest a number of such models.…

  12. Control-relevant modeling and simulation of a SOFC-GT hybrid system

    Directory of Open Access Journals (Sweden)

    Rambabu Kandepu

    2006-07-01

    Full Text Available In this paper, control-relevant models of the most important components in a SOFC-GT hybrid system are described. Dynamic simulations are performed on the overall hybrid system. The model is used to develop a simple control structure, but the simulations show that more elaborate control is needed.

  13. Control-relevant modeling and simulation of a SOFC-GT hybrid system

    OpenAIRE

    Rambabu Kandepu; Lars Imsland; Christoph Stiller; Bjarne A. Foss; Vinay Kariwala

    2006-01-01

    In this paper, control-relevant models of the most important components in a SOFC-GT hybrid system are described. Dynamic simulations are performed on the overall hybrid system. The model is used to develop a simple control structure, but the simulations show that more elaborate control is needed.

  14. 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

  15. 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

  16. The level density parameters for fermi gas model

    International Nuclear Information System (INIS)

    Zuang Youxiang; Wang Cuilan; Zhou Chunmei; Su Zongdi

    1986-01-01

    Nuclear level densities are crucial ingredient in the statistical models, for instance, in the calculations of the widths, cross sections, emitted particle spectra, etc. for various reaction channels. In this work 667 sets of more reliable and new experimental data are adopted, which include average level spacing D D , radiative capture width Γ γ 0 at neutron binding energy and cumulative level number N 0 at the low excitation energy. They are published during 1973 to 1983. Based on the parameters given by Gilbert-Cameon and Cook the physical quantities mentioned above are calculated. The calculated results have the deviation obviously from experimental values. In order to improve the fitting, the parameters in the G-C formula are adjusted and new set of level density parameters is obsained. The parameters is this work are more suitable to fit new measurements

  17. 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.

  18. Iterative integral parameter identification of a respiratory mechanics model

    Directory of Open Access Journals (Sweden)

    Schranz Christoph

    2012-07-01

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

  19. Microwave generation for magnetic fusion energy applications: Task A -- Experimental and numerical study of microwave sources for ECRH incorporating depressed collectors and with ITER-relevant parameters, and Task B -- Theory and modeling of high frequency, high power gyrotron operation. Final report, July 15, 1994--July 14, 1995

    International Nuclear Information System (INIS)

    1995-01-01

    A proof-of-principle short pulse (∼ 100 ns) experiment has successfully demonstrated operation of a sheet-beam FEL amplifier with output power of 250 kW at 86 Ghz and with 24 dB saturated gain and ∼ 3% efficiency. Gain in the linear region was 30 dB. Measured performance parameters were in good agreement with predictions of a multi-mode, time dependence code. Also, a code has been developed to design depressed collectors which will enhance efficiency of ECRH sources (both FELs and gyrotrons). Extensive analytical and theoretical work in support of high power gyrotron development at Varian and MIT, and in support of ITER has been carried out. Specific studies are described. The effect of beam quality on the operation of the 145 GHz gyrotrons at MIT has been characterized using experimentally measured beam velocity distribution functions. The observed performance of these devices is consistent with a 10% RMS perpendicular velocity spread. An extensive study of mode competition in the 110 GHZ experiments at Varian and MIT has been carried out. Design criteria for the suppression of parasitic modes have been given for these experiments. The issues of mode competition and beam quality in the proposed 170 GHz megawatt gyrotrons for ITER have been investigated. Designs of cavities which eliminate unwanted modes have been made, and their sensitivity to beam quality studied. The constraints of lower power density and absence of mode competition coupled with the anticipated beam quality restrict efficiency. Efficiency can be improved by increasing the power density in the wall, improving beam quality, or perhaps by using a more advanced cavity. Studies of the causes of velocity spread in MIG guns have been initiated. Further, the effect of beam cavity misalignment on mode competition has been addressed

  20. MODELLING BIOPHYSICAL PARAMETERS OF MAIZE USING LANDSAT 8 TIME SERIES

    Directory of Open Access Journals (Sweden)

    T. Dahms

    2016-06-01

    Full Text Available Open and free access to multi-frequent high-resolution data (e.g. Sentinel – 2 will fortify agricultural applications based on satellite data. The temporal and spatial resolution of these remote sensing datasets directly affects the applicability of remote sensing methods, for instance a robust retrieving of biophysical parameters over the entire growing season with very high geometric resolution. In this study we use machine learning methods to predict biophysical parameters, namely the fraction of absorbed photosynthetic radiation (FPAR, the leaf area index (LAI and the chlorophyll content, from high resolution remote sensing. 30 Landsat 8 OLI scenes were available in our study region in Mecklenburg-Western Pomerania, Germany. In-situ data were weekly to bi-weekly collected on 18 maize plots throughout the summer season 2015. The study aims at an optimized prediction of biophysical parameters and the identification of the best explaining spectral bands and vegetation indices. For this purpose, we used the entire in-situ dataset from 24.03.2015 to 15.10.2015. Random forest and conditional inference forests were used because of their explicit strong exploratory and predictive character. Variable importance measures allowed for analysing the relation between the biophysical parameters with respect to the spectral response, and the performance of the two approaches over the plant stock evolvement. Classical random forest regression outreached the performance of conditional inference forests, in particular when modelling the biophysical parameters over the entire growing period. For example, modelling biophysical parameters of maize for the entire vegetation period using random forests yielded: FPAR: R² = 0.85; RMSE = 0.11; LAI: R² = 0.64; RMSE = 0.9 and chlorophyll content (SPAD: R² = 0.80; RMSE=4.9. Our results demonstrate the great potential in using machine-learning methods for the interpretation of long-term multi-frequent remote sensing

  1. Modelling Biophysical Parameters of Maize Using Landsat 8 Time Series

    Science.gov (United States)

    Dahms, Thorsten; Seissiger, Sylvia; Conrad, Christopher; Borg, Erik

    2016-06-01

    Open and free access to multi-frequent high-resolution data (e.g. Sentinel - 2) will fortify agricultural applications based on satellite data. The temporal and spatial resolution of these remote sensing datasets directly affects the applicability of remote sensing methods, for instance a robust retrieving of biophysical parameters over the entire growing season with very high geometric resolution. In this study we use machine learning methods to predict biophysical parameters, namely the fraction of absorbed photosynthetic radiation (FPAR), the leaf area index (LAI) and the chlorophyll content, from high resolution remote sensing. 30 Landsat 8 OLI scenes were available in our study region in Mecklenburg-Western Pomerania, Germany. In-situ data were weekly to bi-weekly collected on 18 maize plots throughout the summer season 2015. The study aims at an optimized prediction of biophysical parameters and the identification of the best explaining spectral bands and vegetation indices. For this purpose, we used the entire in-situ dataset from 24.03.2015 to 15.10.2015. Random forest and conditional inference forests were used because of their explicit strong exploratory and predictive character. Variable importance measures allowed for analysing the relation between the biophysical parameters with respect to the spectral response, and the performance of the two approaches over the plant stock evolvement. Classical random forest regression outreached the performance of conditional inference forests, in particular when modelling the biophysical parameters over the entire growing period. For example, modelling biophysical parameters of maize for the entire vegetation period using random forests yielded: FPAR: R² = 0.85; RMSE = 0.11; LAI: R² = 0.64; RMSE = 0.9 and chlorophyll content (SPAD): R² = 0.80; RMSE=4.9. Our results demonstrate the great potential in using machine-learning methods for the interpretation of long-term multi-frequent remote sensing datasets to model

  2. A Peep into the Uncertainty-Complexity-Relevance Modeling Trilemma through Global Sensitivity and Uncertainty Analysis

    Science.gov (United States)

    Munoz-Carpena, R.; Muller, S. J.; Chu, M.; Kiker, G. A.; Perz, S. G.

    2014-12-01

    Model Model complexity resulting from the need to integrate environmental system components cannot be understated. In particular, additional emphasis is urgently needed on rational approaches to guide decision making through uncertainties surrounding the integrated system across decision-relevant scales. However, in spite of the difficulties that the consideration of modeling uncertainty represent for the decision process, it should not be avoided or the value and science behind the models will be undermined. These two issues; i.e., the need for coupled models that can answer the pertinent questions and the need for models that do so with sufficient certainty, are the key indicators of a model's relevance. Model relevance is inextricably linked with model complexity. Although model complexity has advanced greatly in recent years there has been little work to rigorously characterize the threshold of relevance in integrated and complex models. Formally assessing the relevance of the model in the face of increasing complexity would be valuable because there is growing unease among developers and users of complex models about the cumulative effects of various sources of uncertainty on model outputs. In particular, this issue has prompted doubt over whether the considerable effort going into further elaborating complex models will in fact yield the expected payback. New approaches have been proposed recently to evaluate the uncertainty-complexity-relevance modeling trilemma (Muller, Muñoz-Carpena and Kiker, 2011) by incorporating state-of-the-art global sensitivity and uncertainty analysis (GSA/UA) in every step of the model development so as to quantify not only the uncertainty introduced by the addition of new environmental components, but the effect that these new components have over existing components (interactions, non-linear responses). Outputs from the analysis can also be used to quantify system resilience (stability, alternative states, thresholds or tipping

  3. Parameter sensitivity analysis of a lumped-parameter model of a chain of lymphangions in series.

    Science.gov (United States)

    Jamalian, Samira; Bertram, Christopher D; Richardson, William J; Moore, James E

    2013-12-01

    Any disruption of the lymphatic system due to trauma or injury can lead to edema. There is no effective cure for lymphedema, partly because predictive knowledge of lymphatic system reactions to interventions is lacking. A well-developed model of the system could greatly improve our understanding of its function. Lymphangions, defined as the vessel segment between two valves, are the individual pumping units. Based on our previous lumped-parameter model of a chain of lymphangions, this study aimed to identify the parameters that affect the system output the most using a sensitivity analysis. The system was highly sensitive to minimum valve resistance, such that variations in this parameter caused an order-of-magnitude change in time-average flow rate for certain values of imposed pressure difference. Average flow rate doubled when contraction frequency was increased within its physiological range. Optimum lymphangion length was found to be some 13-14.5 diameters. A peak of time-average flow rate occurred when transmural pressure was such that the pressure-diameter loop for active contractions was centered near maximum passive vessel compliance. Increasing the number of lymphangions in the chain improved the pumping in the presence of larger adverse pressure differences. For a given pressure difference, the optimal number of lymphangions increased with the total vessel length. These results indicate that further experiments to estimate valve resistance more accurately are necessary. The existence of an optimal value of transmural pressure may provide additional guidelines for increasing pumping in areas affected by edema.

  4. X-Parameter Based Modelling of Polar Modulated Power Amplifiers

    DEFF Research Database (Denmark)

    Wang, Yelin; Nielsen, Troels Studsgaard; Sira, Daniel

    2013-01-01

    X-parameters are developed as an extension of S-parameters capable of modelling non-linear devices driven by large signals. They are suitable for devices having only radio frequency (RF) and DC ports. In a polar power amplifier (PA), phase and envelope of the input modulated signal are applied...... at separate ports and the envelope port is neither an RF nor a DC port. As a result, X-parameters may fail to characterise the effect of the envelope port excitation and consequently the polar PA. This study introduces a solution to the problem for a commercial polar PA. In this solution, the RF-phase path...... PA for simulations. The simulated error vector magnitude (EVM) and adjacent channel power ratio (ACPR) were compared with the measured data to validate the model. The maximum differences between the simulated and measured EVM and ACPR are less than 2% point and 3 dB, respectively....

  5. Identifiability and error minimization of receptor model parameters with PET

    International Nuclear Information System (INIS)

    Delforge, J.; Syrota, A.; Mazoyer, B.M.

    1989-01-01

    The identifiability problem and the general framework for experimental design optimization are presented. The methodology is applied to the problem of the receptor-ligand model parameter estimation with dynamic positron emission tomography data. The first attempts to identify the model parameters from data obtained with a single tracer injection led to disappointing numerical results. The possibility of improving parameter estimation using a new experimental design combining an injection of the labelled ligand and an injection of the cold ligand (displacement experiment) has been investigated. However, this second protocol led to two very different numerical solutions and it was necessary to demonstrate which solution was biologically valid. This has been possible by using a third protocol including both a displacement and a co-injection experiment. (authors). 16 refs.; 14 figs

  6. Prediction of interest rate using CKLS model with stochastic parameters

    International Nuclear Information System (INIS)

    Ying, Khor Chia; Hin, Pooi Ah

    2014-01-01

    The Chan, Karolyi, Longstaff and Sanders (CKLS) model is a popular one-factor model for describing the spot interest rates. In this paper, the four parameters in the CKLS model are regarded as stochastic. The parameter vector φ (j) of four parameters at the (J+n)-th time point is estimated by the j-th window which is defined as the set consisting of the observed interest rates at the j′-th time point where j≤j′≤j+n. To model the variation of φ (j) , we assume that φ (j) depends on φ (j−m) , φ (j−m+1) ,…, φ (j−1) and the interest rate r j+n at the (j+n)-th time point via a four-dimensional conditional distribution which is derived from a [4(m+1)+1]-dimensional power-normal distribution. Treating the (j+n)-th time point as the present time point, we find a prediction interval for the future value r j+n+1 of the interest rate at the next time point when the value r j+n of the interest rate is given. From the above four-dimensional conditional distribution, we also find a prediction interval for the future interest rate r j+n+d at the next d-th (d≥2) time point. The prediction intervals based on the CKLS model with stochastic parameters are found to have better ability of covering the observed future interest rates when compared with those based on the model with fixed parameters

  7. Prediction of interest rate using CKLS model with stochastic parameters

    Energy Technology Data Exchange (ETDEWEB)

    Ying, Khor Chia [Faculty of Computing and Informatics, Multimedia University, Jalan Multimedia, 63100 Cyberjaya, Selangor (Malaysia); Hin, Pooi Ah [Sunway University Business School, No. 5, Jalan Universiti, Bandar Sunway, 47500 Subang Jaya, Selangor (Malaysia)

    2014-06-19

    The Chan, Karolyi, Longstaff and Sanders (CKLS) model is a popular one-factor model for describing the spot interest rates. In this paper, the four parameters in the CKLS model are regarded as stochastic. The parameter vector φ{sup (j)} of four parameters at the (J+n)-th time point is estimated by the j-th window which is defined as the set consisting of the observed interest rates at the j′-th time point where j≤j′≤j+n. To model the variation of φ{sup (j)}, we assume that φ{sup (j)} depends on φ{sup (j−m)}, φ{sup (j−m+1)},…, φ{sup (j−1)} and the interest rate r{sub j+n} at the (j+n)-th time point via a four-dimensional conditional distribution which is derived from a [4(m+1)+1]-dimensional power-normal distribution. Treating the (j+n)-th time point as the present time point, we find a prediction interval for the future value r{sub j+n+1} of the interest rate at the next time point when the value r{sub j+n} of the interest rate is given. From the above four-dimensional conditional distribution, we also find a prediction interval for the future interest rate r{sub j+n+d} at the next d-th (d≥2) time point. The prediction intervals based on the CKLS model with stochastic parameters are found to have better ability of covering the observed future interest rates when compared with those based on the model with fixed parameters.

  8. Mathematical models to predict rheological parameters of lateritic hydromixtures

    Directory of Open Access Journals (Sweden)

    Gabriel Hernández-Ramírez

    2017-10-01

    Full Text Available The present work had as objective to establish mathematical models that allow the prognosis of the rheological parameters of the lateritic pulp at concentrations of solids from 35% to 48%, temperature of the preheated hydromixture superior to 82 ° C and number of mineral between 3 and 16. Four samples of lateritic pulp were used in the study at different process locations. The results allowed defining that the plastic properties of the lateritic pulp in the conditions of this study conform to the Herschel-Bulkley model for real plastics. In addition, they show that for current operating conditions, even for new situations, UPD mathematical models have a greater ability to predict rheological parameters than least squares mathematical models.

  9. Averaging models: parameters estimation with the R-Average procedure

    Directory of Open Access Journals (Sweden)

    S. Noventa

    2010-01-01

    Full Text Available The Functional Measurement approach, proposed within the theoretical framework of Information Integration Theory (Anderson, 1981, 1982, can be a useful multi-attribute analysis tool. Compared to the majority of statistical models, the averaging model can account for interaction effects without adding complexity. The R-Average method (Vidotto & Vicentini, 2007 can be used to estimate the parameters of these models. By the use of multiple information criteria in the model selection procedure, R-Average allows for the identification of the best subset of parameters that account for the data. After a review of the general method, we present an implementation of the procedure in the framework of R-project, followed by some experiments using a Monte Carlo method.

  10. Revised Parameters for the AMOEBA Polarizable Atomic Multipole Water Model

    Science.gov (United States)

    Pande, Vijay S.; Head-Gordon, Teresa; Ponder, Jay W.

    2016-01-01

    A set of improved parameters for the AMOEBA polarizable atomic multipole water model is developed. The protocol uses an automated procedure, ForceBalance, to adjust model parameters to enforce agreement with ab initio-derived results for water clusters and experimentally obtained data for a variety of liquid phase properties across a broad temperature range. The values reported here for the new AMOEBA14 water model represent a substantial improvement over the previous AMOEBA03 model. The new AMOEBA14 water model accurately predicts the temperature of maximum density and qualitatively matches the experimental density curve across temperatures ranging from 249 K to 373 K. Excellent agreement is observed for the AMOEBA14 model in comparison to a variety of experimental properties as a function of temperature, including the 2nd virial coefficient, enthalpy of vaporization, isothermal compressibility, thermal expansion coefficient and dielectric constant. The viscosity, self-diffusion constant and surface tension are also well reproduced. In comparison to high-level ab initio results for clusters of 2 to 20 water molecules, the AMOEBA14 model yields results similar to the AMOEBA03 and the direct polarization iAMOEBA models. With advances in computing power, calibration data, and optimization techniques, we recommend the use of the AMOEBA14 water model for future studies employing a polarizable water model. PMID:25683601

  11. Relevant parameters in the micro silica selection for the self-flowing ultra-low cement castables production

    International Nuclear Information System (INIS)

    Studart, A.R.; Pandolfelli, V.C.; Rodrigues, J.A.; Vendrasco, S.L.

    1997-01-01

    Self-flowing ultra-low cement castables typically contain a large fraction of the particles, usually fume silica, which increase their flowability and mechanical strength at low temperatures. Fume silicas available in the market differ mainly from their amount of impurities. It is assumed that the content of soluble alkali and free carbon containing in this raw-material affects strongly the processing of self-flowing castable. In this work high alumina castables with gap-sized particle size distribution were prepared to evaluate their flowability, workability and mechanical strength for each sort of fume silica studied. It was observed that the amount of impurities affects both deflocculation and setting time of the castables and their cold and hot mechanical strength. Considerations regarding the physical and chemical characteristics relevant for selecting fume silicas for the production of self-flowing castables are presented and discussed. (author)

  12. Comparisons of criteria in the assessment model parameter optimizations

    International Nuclear Information System (INIS)

    Liu Xinhe; Zhang Yongxing

    1993-01-01

    Three criteria (chi square, relative chi square and correlation coefficient) used in model parameter optimization (MPO) process that aims at significant reduction of prediction uncertainties were discussed and compared to each other with the aid of a well-controlled tracer experiment

  13. Revised models and genetic parameter estimates for production and ...

    African Journals Online (AJOL)

    Genetic parameters for production and reproduction traits in the Elsenburg Dormer sheep stud were estimated using records of 11743 lambs born between 1943 and 2002. An animal model with direct and maternal additive, maternal permanent and temporary environmental effects was fitted for traits considered traits of the ...

  14. Determination of parameters in elasto-plastic models of aluminium.

    NARCIS (Netherlands)

    Meuwissen, M.H.H.; Oomens, C.W.J.; Baaijens, F.P.T.; Petterson, R.; Janssen, J.D.; Sol, H.; Oomens, C.W.J.

    1997-01-01

    A mixed numerical-experimental method is used to determine parameters in elasto-plastic constitutive models. An aluminium plate of non-standard geometry is mounted in a uniaxial tensile testing machine at which some adjustments are made to carry out shear tests. The sample is loaded and the total

  15. Parameter Estimation for a Computable General Equilibrium Model

    DEFF Research Database (Denmark)

    Arndt, Channing; Robinson, Sherman; Tarp, Finn

    2002-01-01

    We introduce a maximum entropy approach to parameter estimation for computable general equilibrium (CGE) models. The approach applies information theory to estimating a system of non-linear simultaneous equations. It has a number of advantages. First, it imposes all general equilibrium constraints...

  16. Parameter Estimation for a Computable General Equilibrium Model

    DEFF Research Database (Denmark)

    Arndt, Channing; Robinson, Sherman; Tarp, Finn

    We introduce a maximum entropy approach to parameter estimation for computable general equilibrium (CGE) models. The approach applies information theory to estimating a system of nonlinear simultaneous equations. It has a number of advantages. First, it imposes all general equilibrium constraints...

  17. Do Lumped-Parameter Models Provide the Correct Geometrical Damping?

    DEFF Research Database (Denmark)

    Andersen, Lars

    response during excitation and the geometrical damping related to free vibrations of a hexagonal footing. The optimal order of a lumped-parameter model is determined for each degree of freedom, i.e. horizontal and vertical translation as well as torsion and rocking. In particular, the necessity of coupling...... between horizontal sliding and rocking is discussed....

  18. Key processes and input parameters for environmental tritium models

    International Nuclear Information System (INIS)

    Bunnenberg, C.; Taschner, M.; Ogram, G.L.

    1994-01-01

    The primary objective of the work reported here is to define key processes and input parameters for mathematical models of environmental tritium behaviour adequate for use in safety analysis and licensing of fusion devices like NET and associated tritium handling facilities. (author). 45 refs., 3 figs

  19. Key processes and input parameters for environmental tritium models

    Energy Technology Data Exchange (ETDEWEB)

    Bunnenberg, C; Taschner, M [Niedersaechsisches Inst. fuer Radiooekologie, Hannover (Germany); Ogram, G L [Ontario Hydro, Toronto, ON (Canada)

    1994-12-31

    The primary objective of the work reported here is to define key processes and input parameters for mathematical models of environmental tritium behaviour adequate for use in safety analysis and licensing of fusion devices like NET and associated tritium handling facilities. (author). 45 refs., 3 figs.

  20. 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

  1. Integrating microbial diversity in soil carbon dynamic models parameters

    Science.gov (United States)

    Louis, Benjamin; Menasseri-Aubry, Safya; Leterme, Philippe; Maron, Pierre-Alain; Viaud, Valérie

    2015-04-01

    Faced with the numerous concerns about soil carbon dynamic, a large quantity of carbon dynamic models has been developed during the last century. These models are mainly in the form of deterministic compartment models with carbon fluxes between compartments represented by ordinary differential equations. Nowadays, lots of them consider the microbial biomass as a compartment of the soil organic matter (carbon quantity). But the amount of microbial carbon is rarely used in the differential equations of the models as a limiting factor. Additionally, microbial diversity and community composition are mostly missing, although last advances in soil microbial analytical methods during the two past decades have shown that these characteristics play also a significant role in soil carbon dynamic. As soil microorganisms are essential drivers of soil carbon dynamic, the question about explicitly integrating their role have become a key issue in soil carbon dynamic models development. Some interesting attempts can be found and are dominated by the incorporation of several compartments of different groups of microbial biomass in terms of functional traits and/or biogeochemical compositions to integrate microbial diversity. However, these models are basically heuristic models in the sense that they are used to test hypotheses through simulations. They have rarely been confronted to real data and thus cannot be used to predict realistic situations. The objective of this work was to empirically integrate microbial diversity in a simple model of carbon dynamic through statistical modelling of the model parameters. This work is based on available experimental results coming from a French National Research Agency program called DIMIMOS. Briefly, 13C-labelled wheat residue has been incorporated into soils with different pedological characteristics and land use history. Then, the soils have been incubated during 104 days and labelled and non-labelled CO2 fluxes have been measured at ten

  2. 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

  3. Male reproductive system parameters in a two-generation reproduction study of ammonium perfluorooctanoate in rats and human relevance.

    Science.gov (United States)

    York, Raymond G; Kennedy, Gerald L; Olsen, Geary W; Butenhoff, John L

    2010-04-30

    Ammonium perfluorooctanoate (ammonium PFOA) is an industrial surfactant that has been used primarily as a processing aid in the manufacture of fluoropolymers. The environmental and metabolic stability of PFOA together with its presence in human blood and long elimination half-life have led to extensive toxicological studies in laboratory animals. Two recent publications based on observations from the Danish general population have reported: (1) a negative association between serum concentrations of PFOA in young adult males and their sperm counts and (2) a positive association among women with time to pregnancy. A two-generation reproduction study in rats was previously published (2004) in which no effects on functional reproduction were observed at doses up to 30mg ammonium PFOA/kg body weight. The article contained the simple statement: "In males, fertility was normal as were all sperm parameters". In order to place the recent human epidemiological data in perspective, herein we provide the detailed male reproductive parameters from that study, including sperm quality and testicular histopathology. Sperm parameters in rats from the two-generation study in all ammonium PFOA treatment groups were unaffected by treatment with ammonium PFOA. These observations reflected the normal fertility observations in these males. No evidence of altered testicular and sperm structure and function was observed in ammonium PFOA-treated rats whose mean group serum PFOA concentrations ranged up to approximately 50,000ng/mL. Given that median serum PFOA in the Danish cohorts was approximately 5ng/mL, it seems unlikely that concentrations observed in the general population, including those recently reported in Danish general population, could be associated causally with a real decrement in sperm number and quality.

  4. The study of influence of relevant physical parameters variations on the estimates of the effective doses of Rn-222

    International Nuclear Information System (INIS)

    Ridzikova, A.; Fronka, A.; Moucka, L.

    2004-01-01

    Based on the analysis of 12 weekly continuous measurements and 4 integral measurements performed in different seasons in actual apartment rooms, bedrooms in particular, we attempted to identify the uncertainties that are involved in the estimation of radiation doses to lung tissues. We found that the parameters of time of residence, concentration, and equilibrium factor can affect substantially the estimate of the overall early effective dose. The weekly averaged concentration measured in one term is not sufficient for a fairly accurate estimate; actually, the equilibrium factor f must also be known and the actual real individual time of residence must be estimated if we want to adopt this approach to the dose estimation

  5. Agricultural and Environmental Input Parameters for the Biosphere Model

    Energy Technology Data Exchange (ETDEWEB)

    K. Rasmuson; K. Rautenstrauch

    2004-09-14

    This analysis is one of 10 technical reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) (i.e., the biosphere model). It documents development of agricultural and environmental input parameters for the biosphere model, and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for the repository at Yucca Mountain. The ERMYN provides the TSPA with the capability to perform dose assessments. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships between the major activities and their products (the analysis and model reports) that were planned in ''Technical Work Plan for Biosphere Modeling and Expert Support'' (BSC 2004 [DIRS 169573]). The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the ERMYN and its input parameters.

  6. Evaluation of some infiltration models and hydraulic parameters

    International Nuclear Information System (INIS)

    Haghighi, F.; Gorji, M.; Shorafa, M.; Sarmadian, F.; Mohammadi, M. H.

    2010-01-01

    The evaluation of infiltration characteristics and some parameters of infiltration models such as sorptivity and final steady infiltration rate in soils are important in agriculture. The aim of this study was to evaluate some of the most common models used to estimate final soil infiltration rate. The equality of final infiltration rate with saturated hydraulic conductivity (Ks) was also tested. Moreover, values of the estimated sorptivity from the Philips model were compared to estimates by selected pedotransfer functions (PTFs). The infiltration experiments used the doublering method on soils with two different land uses in the Taleghan watershed of Tehran province, Iran, from September to October, 2007. The infiltration models of Kostiakov-Lewis, Philip two-term and Horton were fitted to observed infiltration data. Some parameters of the models and the coefficient of determination goodness of fit were estimated using MATLAB software. The results showed that, based on comparing measured and model-estimated infiltration rate using root mean squared error (RMSE), Hortons model gave the best prediction of final infiltration rate in the experimental area. Laboratory measured Ks values gave significant differences and higher values than estimated final infiltration rates from the selected models. The estimated final infiltration rate was not equal to laboratory measured Ks values in the study area. Moreover, the estimated sorptivity factor by Philips model was significantly different to those estimated by selected PTFs. It is suggested that the applicability of PTFs is limited to specific, similar conditions. (Author) 37 refs.

  7. Estimating model parameters in nonautonomous chaotic systems using synchronization

    International Nuclear Information System (INIS)

    Yang, Xiaoli; Xu, Wei; Sun, Zhongkui

    2007-01-01

    In this Letter, a technique is addressed for estimating unknown model parameters of multivariate, in particular, nonautonomous chaotic systems from time series of state variables. This technique uses an adaptive strategy for tracking unknown parameters in addition to a linear feedback coupling for synchronizing systems, and then some general conditions, by means of the periodic version of the LaSalle invariance principle for differential equations, are analytically derived to ensure precise evaluation of unknown parameters and identical synchronization between the concerned experimental system and its corresponding receiver one. Exemplifies are presented by employing a parametrically excited 4D new oscillator and an additionally excited Ueda oscillator. The results of computer simulations reveal that the technique not only can quickly track the desired parameter values but also can rapidly respond to changes in operating parameters. In addition, the technique can be favorably robust against the effect of noise when the experimental system is corrupted by bounded disturbance and the normalized absolute error of parameter estimation grows almost linearly with the cutoff value of noise strength in simulation

  8. 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

  9. 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

  10. Mass balance model parameter transferability on a tropical glacier

    Science.gov (United States)

    Gurgiser, Wolfgang; Mölg, Thomas; Nicholson, Lindsey; Kaser, Georg

    2013-04-01

    The mass balance and melt water production of glaciers is of particular interest in the Peruvian Andes where glacier melt water has markedly increased water supply during the pronounced dry seasons in recent decades. However, the melt water contribution from glaciers is projected to decrease with appreciable negative impacts on the local society within the coming decades. Understanding mass balance processes on tropical glaciers is a prerequisite for modeling present and future glacier runoff. As a first step towards this aim we applied a process-based surface mass balance model in order to calculate observed ablation at two stakes in the ablation zone of Shallap Glacier (4800 m a.s.l., 9°S) in the Cordillera Blanca, Peru. Under the tropical climate, the snow line migrates very frequently across most of the ablation zone all year round causing large temporal and spatial variations of glacier surface conditions and related ablation. Consequently, pronounced differences between the two chosen stakes and the two years were observed. Hourly records of temperature, humidity, wind speed, short wave incoming radiation, and precipitation are available from an automatic weather station (AWS) on the moraine near the glacier for the hydrological years 2006/07 and 2007/08 while stake readings are available at intervals of between 14 to 64 days. To optimize model parameters, we used 1000 model simulations in which the most sensitive model parameters were varied randomly within their physically meaningful ranges. The modeled surface height change was evaluated against the two stake locations in the lower ablation zone (SH11, 4760m) and in the upper ablation zone (SH22, 4816m), respectively. The optimal parameter set for each point achieved good model skill but if we transfer the best parameter combination from one stake site to the other stake site model errors increases significantly. The same happens if we optimize the model parameters for each year individually and transfer

  11. Constraining statistical-model parameters using fusion and spallation reactions

    Directory of Open Access Journals (Sweden)

    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.

  12. In Silico Prediction of Toxicokinetic Parameters for Environmentally Relevant Chemicals with Application to Risk-Based Prioritization

    Science.gov (United States)

    Toxicokinetic (TK) models can help bridge the gap between chemical exposure and measured toxicity endpoints, thereby addressing an important component of chemical risk assessments. The fraction of a chemical unbound by plasma proteins (Fub) and metabolic clearance rate (CLint) ar...

  13. Investigation of RADTRAN Stop Model input parameters for truck stops

    International Nuclear Information System (INIS)

    Griego, N.R.; Smith, J.D.; Neuhauser, K.S.

    1996-01-01

    RADTRAN is a computer code for estimating the risks and consequences as transport of radioactive materials (RAM). RADTRAN was developed and is maintained by Sandia National Laboratories for the US Department of Energy (DOE). For incident-free transportation, the dose to persons exposed while the shipment is stopped is frequently a major percentage of the overall dose. This dose is referred to as Stop Dose and is calculated by the Stop Model. Because stop dose is a significant portion of the overall dose associated with RAM transport, the values used as input for the Stop Model are important. Therefore, an investigation of typical values for RADTRAN Stop Parameters for truck stops was performed. The resulting data from these investigations were analyzed to provide mean values, standard deviations, and histograms. Hence, the mean values can be used when an analyst does not have a basis for selecting other input values for the Stop Model. In addition, the histograms and their characteristics can be used to guide statistical sampling techniques to measure sensitivity of the RADTRAN calculated Stop Dose to the uncertainties in the stop model input parameters. This paper discusses the details and presents the results of the investigation of stop model input parameters at truck stops

  14. Updated climatological model predictions of ionospheric and HF propagation parameters

    International Nuclear Information System (INIS)

    Reilly, M.H.; Rhoads, F.J.; Goodman, J.M.; Singh, M.

    1991-01-01

    The prediction performances of several climatological models, including the ionospheric conductivity and electron density model, RADAR C, and Ionospheric Communications Analysis and Predictions Program, are evaluated for different regions and sunspot number inputs. Particular attention is given to the near-real-time (NRT) predictions associated with single-station updates. It is shown that a dramatic improvement can be obtained by using single-station ionospheric data to update the driving parameters for an ionospheric model for NRT predictions of f(0)F2 and other ionospheric and HF circuit parameters. For middle latitudes, the improvement extends out thousands of kilometers from the update point to points of comparable corrected geomagnetic latitude. 10 refs

  15. Statistical approach for uncertainty quantification of experimental modal model parameters

    DEFF Research Database (Denmark)

    Luczak, M.; Peeters, B.; Kahsin, M.

    2014-01-01

    Composite materials are widely used in manufacture of aerospace and wind energy structural components. These load carrying structures are subjected to dynamic time-varying loading conditions. Robust structural dynamics identification procedure impose tight constraints on the quality of modal models...... represent different complexity levels ranging from coupon, through sub-component up to fully assembled aerospace and wind energy structural components made of composite materials. The proposed method is demonstrated on two application cases of a small and large wind turbine blade........ This paper aims at a systematic approach for uncertainty quantification of the parameters of the modal models estimated from experimentally obtained data. Statistical analysis of modal parameters is implemented to derive an assessment of the entire modal model uncertainty measure. Investigated structures...

  16. Influential input parameters for reflood model of MARS code

    Energy Technology Data Exchange (ETDEWEB)

    Oh, Deog Yeon; Bang, Young Seok [Korea Institute of Nuclear Safety, Daejeon (Korea, Republic of)

    2012-10-15

    Best Estimate (BE) calculation has been more broadly used in nuclear industries and regulations to reduce the significant conservatism for evaluating Loss of Coolant Accident (LOCA). Reflood model has been identified as one of the problems in BE calculation. The objective of the Post BEMUSE Reflood Model Input Uncertainty Methods (PREMIUM) program of OECD/NEA is to make progress the issue of the quantification of the uncertainty of the physical models in system thermal hydraulic codes, by considering an experimental result especially for reflood. It is important to establish a methodology to identify and select the parameters influential to the response of reflood phenomena following Large Break LOCA. For this aspect, a reference calculation and sensitivity analysis to select the dominant influential parameters for FEBA experiment are performed.

  17. Four-parameter analytical local model potential for atoms

    International Nuclear Information System (INIS)

    Fei, Yu; Jiu-Xun, Sun; Rong-Gang, Tian; Wei, Yang

    2009-01-01

    Analytical local model potential for modeling the interaction in an atom reduces the computational effort in electronic structure calculations significantly. A new four-parameter analytical local model potential is proposed for atoms Li through Lr, and the values of four parameters are shell-independent and obtained by fitting the results of X a method. At the same time, the energy eigenvalues, the radial wave functions and the total energies of electrons are obtained by solving the radial Schrödinger equation with a new form of potential function by Numerov's numerical method. The results show that our new form of potential function is suitable for high, medium and low Z atoms. A comparison among the new potential function and other analytical potential functions shows the greater flexibility and greater accuracy of the present new potential function. (atomic and molecular physics)

  18. Application of parameters space analysis tools for empirical model validation

    Energy Technology Data Exchange (ETDEWEB)

    Paloma del Barrio, E. [LEPT-ENSAM UMR 8508, Talence (France); Guyon, G. [Electricite de France, Moret-sur-Loing (France)

    2004-01-01

    A new methodology for empirical model validation has been proposed in the framework of the Task 22 (Building Energy Analysis Tools) of the International Energy Agency. It involves two main steps: checking model validity and diagnosis. Both steps, as well as the underlying methods, have been presented in the first part of the paper. In this part, they are applied for testing modelling hypothesis in the framework of the thermal analysis of an actual building. Sensitivity analysis tools have been first used to identify the parts of the model that can be really tested on the available data. A preliminary diagnosis is then supplied by principal components analysis. Useful information for model behaviour improvement has been finally obtained by optimisation techniques. This example of application shows how model parameters space analysis is a powerful tool for empirical validation. In particular, diagnosis possibilities are largely increased in comparison with residuals analysis techniques. (author)

  19. 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.

  20. A PSO Driven Intelligent Model Updating and Parameter Identification Scheme for Cable-Damper System

    Directory of Open Access Journals (Sweden)

    Danhui Dan

    2015-01-01

    Full Text Available The precise measurement of the cable force is very important for monitoring and evaluating the operation status of cable structures such as cable-stayed bridges. The cable system should be installed with lateral dampers to reduce the vibration, which affects the precise measurement of the cable force and other cable parameters. This paper suggests a cable model updating calculation scheme driven by the particle swarm optimization (PSO algorithm. By establishing a finite element model considering the static geometric nonlinearity and stress-stiffening effect firstly, an automatically finite element method model updating powered by PSO algorithm is proposed, with the aims to identify the cable force and relevant parameters of cable-damper system precisely. Both numerical case studies and full-scale cable tests indicated that, after two rounds of updating process, the algorithm can accurately identify the cable force, moment of inertia, and damping coefficient of the cable-damper system.

  1. 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.

  2. Biosphere modelling for a HLW repository - scenario and parameter variations

    International Nuclear Information System (INIS)

    Grogan, H.

    1985-03-01

    In Switzerland high-level radioactive wastes have been considered for disposal in deep-lying crystalline formations. The individual doses to man resulting from radionuclides entering the biosphere via groundwater transport are calculated. The main recipient area modelled, which constitutes the base case, is a broad gravel terrace sited along the south bank of the river Rhine. An alternative recipient region, a small valley with a well, is also modelled. A number of parameter variations are performed in order to ascertain their impact on the doses. Finally two scenario changes are modelled somewhat simplistically, these consider different prevailing climates, namely tundra and a warmer climate than present. In the base case negligibly low doses to man in the long term, resulting from the existence of a HLW repository have been calculated. Cs-135 results in the largest dose (8.4E-7 mrem/y at 6.1E+6 y) while Np-237 gives the largest dose from the actinides (3.6E-8 mrem/y). The response of the model to parameter variations cannot be easily predicted due to non-linear coupling of many of the parameters. However, the calculated doses were negligibly low in all cases as were those resulting from the two scenario variations. (author)

  3. The LAILAPS search engine: a feature model for relevance ranking in life science databases.

    Science.gov (United States)

    Lange, Matthias; Spies, Karl; Colmsee, Christian; Flemming, Steffen; Klapperstück, Matthias; Scholz, Uwe

    2010-03-25

    Efficient and effective information retrieval in life sciences is one of the most pressing challenge in bioinformatics. The incredible growth of life science databases to a vast network of interconnected information systems is to the same extent a big challenge and a great chance for life science research. The knowledge found in the Web, in particular in life-science databases, are a valuable major resource. In order to bring it to the scientist desktop, it is essential to have well performing search engines. Thereby, not the response time nor the number of results is important. The most crucial factor for millions of query results is the relevance ranking. In this paper, we present a feature model for relevance ranking in life science databases and its implementation in the LAILAPS search engine. Motivated by the observation of user behavior during their inspection of search engine result, we condensed a set of 9 relevance discriminating features. These features are intuitively used by scientists, who briefly screen database entries for potential relevance. The features are both sufficient to estimate the potential relevance, and efficiently quantifiable. The derivation of a relevance prediction function that computes the relevance from this features constitutes a regression problem. To solve this problem, we used artificial neural networks that have been trained with a reference set of relevant database entries for 19 protein queries. Supporting a flexible text index and a simple data import format, this concepts are implemented in the LAILAPS search engine. It can easily be used both as search engine for comprehensive integrated life science databases and for small in-house project databases. LAILAPS is publicly available for SWISSPROT data at http://lailaps.ipk-gatersleben.de.

  4. Contaminant transport in aquifers: improving the determination of model parameters

    International Nuclear Information System (INIS)

    Sabino, C.V.S.; Moreira, R.M.; Lula, Z.L.; Chausson, Y.; Magalhaes, W.F.; Vianna, M.N.

    1998-01-01

    Parameters conditioning the migration behavior of cesium and mercury are measured with their tracers 137 Cs and 203 Hg in the laboratory, using both batch and column experiments. Batch tests were used to define the sorption isotherm characteristics. Also investigated were the influences of some test parameters, in particular those due to the volume of water to mass of soil ratio (V/m). A provisional relationship between V/m and the distribution coefficient, K d , has been advanced, and a procedure to estimate K d 's valid for environmental values of the ratio V/m has been suggested. Column tests provided the parameters for a transport model. A major problem to be dealt with in such tests is the collimation of the radioactivity probe. Besides mechanically optimizing the collimator, a deconvolution procedure has been suggested and tested, with statistical criteria, to filter off both noise and spurious tracer signals. Correction procedures for the integrating effect introduced by sampling at the exit of columns have also been developed. These techniques may be helpful in increasing the accuracy required in the measurement of parameters conditioning contaminant migration in soils, thus allowing more reliable predictions based on mathematical model applications. (author)

  5. On Feature Relevance in Image-Based Prediction Models: An Empirical Study

    DEFF Research Database (Denmark)

    Konukoglu, E.; Ganz, Melanie; Van Leemput, Koen

    2013-01-01

    Determining disease-related variations of the anatomy and function is an important step in better understanding diseases and developing early diagnostic systems. In particular, image-based multivariate prediction models and the “relevant features” they produce are attracting attention from the co...

  6. Stem cell therapy for joint problems using the horse as a clinically relevant animal model

    DEFF Research Database (Denmark)

    Koch, Thomas Gadegaard; Betts, Dean H.

    2007-01-01

    of experimentally induced lesions. The horse lends itself as a good animal model of spontaneous joint disorders that are clinically relevant to similar human disorders. Equine stem cell and tissue engineering studies may be financially feasible to principal investigators and small biotechnology companies...

  7. Consistent robustness analysis (CRA) identifies biologically relevant properties of regulatory network models.

    Science.gov (United States)

    Saithong, Treenut; Painter, Kevin J; Millar, Andrew J

    2010-12-16

    A number of studies have previously demonstrated that "goodness of fit" is insufficient in reliably classifying the credibility of a biological model. Robustness and/or sensitivity analysis is commonly employed as a secondary method for evaluating the suitability of a particular model. The results of such analyses invariably depend on the particular parameter set tested, yet many parameter values for biological models are uncertain. Here, we propose a novel robustness analysis that aims to determine the "common robustness" of the model with multiple, biologically plausible parameter sets, rather than the local robustness for a particular parameter set. Our method is applied to two published models of the Arabidopsis circadian clock (the one-loop [1] and two-loop [2] models). The results reinforce current findings suggesting the greater reliability of the two-loop model and pinpoint the crucial role of TOC1 in the circadian network. Consistent Robustness Analysis can indicate both the relative plausibility of different models and also the critical components and processes controlling each model.

  8. Experimental Models of Vaginal Candidiasis and Their Relevance to Human Candidiasis

    Science.gov (United States)

    Sobel, Jack D.

    2016-01-01

    Vulvovaginal candidiasis (VVC) is a high-incidence disease seriously affecting the quality of life of women worldwide, particularly in its chronic, recurrent forms (RVVC), and with no definitive cure or preventive measure. Experimental studies in currently used rat and mouse models of vaginal candidiasis have generated a large mass of data on pathogenicity determinants and inflammation and immune responses of potential importance for the control of human pathology. However, reflection is necessary about the relevance of these rodent models to RVVC. Here we examine the chemical, biochemical, and biological factors that determine or contrast the forms of the disease in rodent models and in women and highlight the differences between them. We also appeal for approaches to improve or replace the current models in order to enhance their relevance to human infection. PMID:26883592

  9. Propagation channel characterization, parameter estimation, and modeling for wireless communications

    CERN Document Server

    Yin, Xuefeng

    2016-01-01

    Thoroughly covering channel characteristics and parameters, this book provides the knowledge needed to design various wireless systems, such as cellular communication systems, RFID and ad hoc wireless communication systems. It gives a detailed introduction to aspects of channels before presenting the novel estimation and modelling techniques which can be used to achieve accurate models. To systematically guide readers through the topic, the book is organised in three distinct parts. The first part covers the fundamentals of the characterization of propagation channels, including the conventional single-input single-output (SISO) propagation channel characterization as well as its extension to multiple-input multiple-output (MIMO) cases. Part two focuses on channel measurements and channel data post-processing. Wideband channel measurements are introduced, including the equipment, technology and advantages and disadvantages of different data acquisition schemes. The channel parameter estimation methods are ...

  10. Empirical flow parameters : a tool for hydraulic model validity

    Science.gov (United States)

    Asquith, William H.; Burley, Thomas E.; Cleveland, Theodore G.

    2013-01-01

    The objectives of this project were (1) To determine and present from existing data in Texas, relations between observed stream flow, topographic slope, mean section velocity, and other hydraulic factors, to produce charts such as Figure 1 and to produce empirical distributions of the various flow parameters to provide a methodology to "check if model results are way off!"; (2) To produce a statistical regional tool to estimate mean velocity or other selected parameters for storm flows or other conditional discharges at ungauged locations (most bridge crossings) in Texas to provide a secondary way to compare such values to a conventional hydraulic modeling approach. (3.) To present ancillary values such as Froude number, stream power, Rosgen channel classification, sinuosity, and other selected characteristics (readily determinable from existing data) to provide additional information to engineers concerned with the hydraulic-soil-foundation component of transportation infrastructure.

  11. 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.

  12. Correlation between mass transfer coefficient kLa and relevant operating parameters in cylindrical disposable shaken bioreactors on a bench-to-pilot scale.

    Science.gov (United States)

    Klöckner, Wolf; Gacem, Riad; Anderlei, Tibor; Raven, Nicole; Schillberg, Stefan; Lattermann, Clemens; Büchs, Jochen

    2013-12-02

    Among disposable bioreactor systems, cylindrical orbitally shaken bioreactors show important advantages. They provide a well-defined hydrodynamic flow combined with excellent mixing and oxygen transfer for mammalian and plant cell cultivations. Since there is no known universal correlation between the volumetric mass transfer coefficient for oxygen kLa and relevant operating parameters in such bioreactor systems, the aim of this current study is to experimentally determine a universal kLa correlation. A Respiration Activity Monitoring System (RAMOS) was used to measure kLa values in cylindrical disposable shaken bioreactors and Buckingham's π-Theorem was applied to define a dimensionless equation for kLa. In this way, a scale- and volume-independent kLa correlation was developed and validated in bioreactors with volumes from 2 L to 200 L. The final correlation was used to calculate cultivation parameters at different scales to allow a sufficient oxygen supply of tobacco BY-2 cell suspension cultures. The resulting equation can be universally applied to calculate the mass transfer coefficient for any of seven relevant cultivation parameters such as the reactor diameter, the shaking frequency, the filling volume, the viscosity, the oxygen diffusion coefficient, the gravitational acceleration or the shaking diameter within an accuracy range of +/- 30%. To our knowledge, this is the first kLa correlation that has been defined and validated for the cited bioreactor system on a bench-to-pilot scale.

  13. Estimation of Kinetic Parameters in an Automotive SCR Catalyst Model

    DEFF Research Database (Denmark)

    Åberg, Andreas; Widd, Anders; Abildskov, Jens

    2016-01-01

    be used directly for accurate full-scale transient simulations. The model was validated against full-scale data with an engine following the European Transient Cycle. The validation showed that the predictive capability for nitrogen oxides (NOx) was satisfactory. After re-estimation of the adsorption...... and desorption parameters with full-scale transient data, the fit for both NOx and NH3-slip was satisfactory....

  14. Mathematical models to predict rheological parameters of lateritic hydromixtures

    OpenAIRE

    Gabriel Hernández-Ramírez; Arístides A. Legrá-Lobaina; Beatriz Ramírez-Serrano; Liudmila Pérez-García

    2017-01-01

    The present work had as objective to establish mathematical models that allow the prognosis of the rheological parameters of the lateritic pulp at concentrations of solids from 35% to 48%, temperature of the preheated hydromixture superior to 82 ° C and number of mineral between 3 and 16. Four samples of lateritic pulp were used in the study at different process locations. The results allowed defining that the plastic properties of the lateritic pulp in the conditions of this study conform to...

  15. Mathematical properties and parameter estimation for transit compartment pharmacodynamic models.

    Science.gov (United States)

    Yates, James W T

    2008-07-03

    One feature of recent research in pharmacodynamic modelling has been the move towards more mechanistically based model structures. However, in all of these models there are common sub-systems, such as feedback loops and time-delays, whose properties and contribution to the model behaviour merit some mathematical analysis. In this paper a common pharmacodynamic model sub-structure is considered: the linear transit compartment. These models have a number of interesting properties as the length of the cascade chain is increased. In the limiting case a pure time-delay is achieved [Milsum, J.H., 1966. Biological Control Systems Analysis. McGraw-Hill Book Company, New York] and the initial behaviour becoming increasingly sensitive to parameter value perturbation. It is also shown that the modelled drug effect is attenuated, though the duration of action is longer. Through this analysis the range of behaviours that such models are capable of reproducing are characterised. The properties of these models and the experimental requirements are discussed in order to highlight how mathematical analysis prior to experimentation can enhance the utility of mathematical modelling.

  16. Estimation Parameters And Modelling Zero Inflated Negative Binomial

    Directory of Open Access Journals (Sweden)

    Cindy Cahyaning Astuti

    2016-11-01

    Full Text Available Regression analysis is used to determine relationship between one or several response variable (Y with one or several predictor variables (X. Regression model between predictor variables and the Poisson distributed response variable is called Poisson Regression Model. Since, Poisson Regression requires an equality between mean and variance, it is not appropriate to apply this model on overdispersion (variance is higher than mean. Poisson regression model is commonly used to analyze the count data. On the count data type, it is often to encounteredd some observations that have zero value with large proportion of zero value on the response variable (zero Inflation. Poisson regression can be used to analyze count data but it has not been able to solve problem of excess zero value on the response variable. An alternative model which is more suitable for overdispersion data and can solve the problem of excess zero value on the response variable is Zero Inflated Negative Binomial (ZINB. In this research, ZINB is applied on the case of Tetanus Neonatorum in East Java. The aim of this research is to examine the likelihood function and to form an algorithm to estimate the parameter of ZINB and also applying ZINB model in the case of Tetanus Neonatorum in East Java. Maximum Likelihood Estimation (MLE method is used to estimate the parameter on ZINB and the likelihood function is maximized using Expectation Maximization (EM algorithm. Test results of ZINB regression model showed that the predictor variable have a partial significant effect at negative binomial model is the percentage of pregnant women visits and the percentage of maternal health personnel assisted, while the predictor variables that have a partial significant effect at zero inflation model is the percentage of neonatus visits.

  17. COMPREHENSIVE CHECK MEASUREMENT OF KEY PARAMETERS ON MODEL BELT CONVEYOR

    Directory of Open Access Journals (Sweden)

    Vlastimil MONI

    2013-07-01

    Full Text Available Complex measurements of characteristic parameters realised on a long distance model belt conveyor are described. The main objective was to complete and combine the regular measurements of electric power on drives of belt conveyors operated in Czech opencast mines with measurements of other physical quantities and to gain by this way an image of their mutual relations and relations of quantities derived from them. The paper includes a short description and results of the measurements on an experimental model conveyor with a closed material transport way.

  18. Information Theoretic Tools for Parameter Fitting in Coarse Grained Models

    KAUST Repository

    Kalligiannaki, Evangelia

    2015-01-07

    We study the application of information theoretic tools for model reduction in the case of systems driven by stochastic dynamics out of equilibrium. The model/dimension reduction is considered by proposing parametrized coarse grained dynamics and finding the optimal parameter set for which the relative entropy rate with respect to the atomistic dynamics is minimized. The minimization problem leads to a generalization of the force matching methods to non equilibrium systems. A multiplicative noise example reveals the importance of the diffusion coefficient in the optimization problem.

  19. Surrogate based approaches to parameter inference in ocean models

    KAUST Repository

    Knio, Omar

    2016-01-06

    This talk discusses the inference of physical parameters using model surrogates. Attention is focused on the use of sampling schemes to build suitable representations of the dependence of the model response on uncertain input data. Non-intrusive spectral projections and regularized regressions are used for this purpose. A Bayesian inference formalism is then applied to update the uncertain inputs based on available measurements or observations. To perform the update, we consider two alternative approaches, based on the application of Markov Chain Monte Carlo methods or of adjoint-based optimization techniques. We outline the implementation of these techniques to infer dependence of wind drag, bottom drag, and internal mixing coefficients.

  20. Surrogate based approaches to parameter inference in ocean models

    KAUST Repository

    Knio, Omar

    2016-01-01

    This talk discusses the inference of physical parameters using model surrogates. Attention is focused on the use of sampling schemes to build suitable representations of the dependence of the model response on uncertain input data. Non-intrusive spectral projections and regularized regressions are used for this purpose. A Bayesian inference formalism is then applied to update the uncertain inputs based on available measurements or observations. To perform the update, we consider two alternative approaches, based on the application of Markov Chain Monte Carlo methods or of adjoint-based optimization techniques. We outline the implementation of these techniques to infer dependence of wind drag, bottom drag, and internal mixing coefficients.

  1. 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…

  2. Ordinary Mathematical Models in Calculating the Aviation GTE Parameters

    Directory of Open Access Journals (Sweden)

    E. A. Khoreva

    2017-01-01

    Full Text Available The paper presents the analytical review results of the ordinary mathematical models of the operating process used to study aviation GTE parameters and characteristics at all stages of its creation and operation. Considers the mathematical models of the zero and the first level, which are mostly used when solving typical problems in calculating parameters and characteristics of engines.Presents a number of practical problems arising in designing aviation GTE for various applications.The application of mathematical models of the zero-level engine can be quite appropriate when the engine is considered as a component in the aircraft system to estimate its calculated individual flight performance or when modeling the flight cycle of the aircrafts of different purpose.The paper demonstrates that introduction of correction functions into the first-level mathematical models in solving typical problems (influence of the Reynolds number, characteristics deterioration of the units during the overhaul period of engine, as well as influence of the flow inhomogeneity at the inlet because of manufacturing tolerance, etc. enables providing a sufficient engineering estimate accuracy to reflect a realistic operating process in the engine and its elements.

  3. Applicability of genetic algorithms to parameter estimation of economic models

    Directory of Open Access Journals (Sweden)

    Marcel Ševela

    2004-01-01

    Full Text Available The paper concentrates on capability of genetic algorithms for parameter estimation of non-linear economic models. In the paper we test the ability of genetic algorithms to estimate of parameters of demand function for durable goods and simultaneously search for parameters of genetic algorithm that lead to maximum effectiveness of the computation algorithm. The genetic algorithms connect deterministic iterative computation methods with stochastic methods. In the genteic aůgorithm approach each possible solution is represented by one individual, those life and lifes of all generations of individuals run under a few parameter of genetic algorithm. Our simulations resulted in optimal mutation rate of 15% of all bits in chromosomes, optimal elitism rate 20%. We can not set the optimal extend of generation, because it proves positive correlation with effectiveness of genetic algorithm in all range under research, but its impact is degreasing. The used genetic algorithm was sensitive to mutation rate at most, than to extend of generation. The sensitivity to elitism rate is not so strong.

  4. Genetic mouse models relevant to schizophrenia: taking stock and looking forward.

    Science.gov (United States)

    Harrison, Paul J; Pritchett, David; Stumpenhorst, Katharina; Betts, Jill F; Nissen, Wiebke; Schweimer, Judith; Lane, Tracy; Burnet, Philip W J; Lamsa, Karri P; Sharp, Trevor; Bannerman, David M; Tunbridge, Elizabeth M

    2012-03-01

    Genetic mouse models relevant to schizophrenia complement, and have to a large extent supplanted, pharmacological and lesion-based rat models. The main attraction is that they potentially have greater construct validity; however, they share the fundamental limitations of all animal models of psychiatric disorder, and must also be viewed in the context of the uncertain and complex genetic architecture of psychosis. Some of the key issues, including the choice of gene to target, the manner of its manipulation, gene-gene and gene-environment interactions, and phenotypic characterization, are briefly considered in this commentary, illustrated by the relevant papers reported in this special issue. Copyright © 2011 Elsevier Ltd. All rights reserved.

  5. A Review of Distributed Parameter Groundwater Management Modeling Methods

    Science.gov (United States)

    Gorelick, Steven M.

    1983-04-01

    Models which solve the governing groundwater flow or solute transport equations in conjunction with optimization techniques, such as linear and quadratic programing, are powerful aquifer management tools. Groundwater management models fall in two general categories: hydraulics or policy evaluation and water allocation. Groundwater hydraulic management models enable the determination of optimal locations and pumping rates of numerous wells under a variety of restrictions placed upon local drawdown, hydraulic gradients, and water production targets. Groundwater policy evaluation and allocation models can be used to study the influence upon regional groundwater use of institutional policies such as taxes and quotas. Furthermore, fairly complex groundwater-surface water allocation problems can be handled using system decomposition and multilevel optimization. Experience from the few real world applications of groundwater optimization-management techniques is summarized. Classified separately are methods for groundwater quality management aimed at optimal waste disposal in the subsurface. This classification is composed of steady state and transient management models that determine disposal patterns in such a way that water quality is protected at supply locations. Classes of research missing from the literature are groundwater quality management models involving nonlinear constraints, models which join groundwater hydraulic and quality simulations with political-economic management considerations, and management models that include parameter uncertainty.

  6. Parameters of oscillation generation regions in open star cluster models

    Science.gov (United States)

    Danilov, V. M.; Putkov, S. I.

    2017-07-01

    We determine the masses and radii of central regions of open star cluster (OCL) models with small or zero entropy production and estimate the masses of oscillation generation regions in clustermodels based on the data of the phase-space coordinates of stars. The radii of such regions are close to the core radii of the OCL models. We develop a new method for estimating the total OCL masses based on the cluster core mass, the cluster and cluster core radii, and radial distribution of stars. This method yields estimates of dynamical masses of Pleiades, Praesepe, and M67, which agree well with the estimates of the total masses of the corresponding clusters based on proper motions and spectroscopic data for cluster stars.We construct the spectra and dispersion curves of the oscillations of the field of azimuthal velocities v φ in OCL models. Weak, low-amplitude unstable oscillations of v φ develop in cluster models near the cluster core boundary, and weak damped oscillations of v φ often develop at frequencies close to the frequencies of more powerful oscillations, which may reduce the non-stationarity degree in OCL models. We determine the number and parameters of such oscillations near the cores boundaries of cluster models. Such oscillations points to the possible role that gradient instability near the core of cluster models plays in the decrease of the mass of the oscillation generation regions and production of entropy in the cores of OCL models with massive extended cores.

  7. 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.

  8. Developing predictive systems models to address complexity and relevance for ecological risk assessment.

    Science.gov (United States)

    Forbes, Valery E; Calow, Peter

    2013-07-01

    Ecological risk assessments (ERAs) are not used as well as they could be in risk management. Part of the problem is that they often lack ecological relevance; that is, they fail to grasp necessary ecological complexities. Adding realism and complexity can be difficult and costly. We argue that predictive systems models (PSMs) can provide a way of capturing complexity and ecological relevance cost-effectively. However, addressing complexity and ecological relevance is only part of the problem. Ecological risk assessments often fail to meet the needs of risk managers by not providing assessments that relate to protection goals and by expressing risk in ratios that cannot be weighed against the costs of interventions. Once more, PSMs can be designed to provide outputs in terms of value-relevant effects that are modulated against exposure and that can provide a better basis for decision making than arbitrary ratios or threshold values. Recent developments in the modeling and its potential for implementation by risk assessors and risk managers are beginning to demonstrate how PSMs can be practically applied in risk assessment and the advantages that doing so could have. Copyright © 2013 SETAC.

  9. Intertwining personal and reward relevance: evidence from the drift-diffusion model.

    Science.gov (United States)

    Yankouskaya, A; Bührle, R; Lugt, E; Stolte, M; Sui, J

    2018-01-24

    In their seminal paper 'Is our self nothing but reward', Northoff and Hayes (Biol Psychiatry 69(11):1019-1025, Northoff, Hayes, Biological Psychiatry 69(11):1019-1025, 2011) proposed three models of the relationship between self and reward and opened a continuing debate about how these different fields can be linked. To date, none of the proposed models received strong empirical support. The present study tested common and distinct effects of personal relevance and reward values by de-componenting different stages of perceptual decision making using a drift-diffusion approach. We employed a recently developed associative matching paradigm where participants (N = 40) formed mental associations between five geometric shapes and five labels referring personal relevance in the personal task, or five shape-label pairings with different reward values in the reward task and then performed a matching task by indicating whether a displayed shape-label pairing was correct or incorrect. We found that common effects of personal relevance and monetary reward were manifested in the facilitation of behavioural performance for high personal relevance and high reward value as socially important signals. The differential effects between personal and monetary relevance reflected non-decisional time in a perceptual decision process, and task-specific prioritization of stimuli. Our findings support the parallel processing model (Northoff & Hayes, Biol Psychiatry 69(11):1019-1025, Northoff, Hayes, Biological Psychiatry 69(11):1019-1025, 2011) and suggest that self-specific processing occurs in parallel with high reward processing. Limitations and further directions are discussed.

  10. Tension-compression asymmetry modelling: strategies for anisotropy parameters identification.

    Directory of Open Access Journals (Sweden)

    Barros Pedro

    2016-01-01

    Full Text Available This work presents details concerning the strategies and algorithms adopted in the fully implicit FE solver DD3IMP to model the orthotropic behavior of metallic sheets and the procedure for anisotropy parameters identification. The work is focused on the yield criterion developed by Cazacu, Plunkett and Barlat, 2006 [1], which accounts for both tension–compression asymmetry and orthotropic plastic behavior. The anisotropy parameters for a 2090-T3 aluminum alloy are identified accounting, or not, for the tension-compression asymmetry. The numerical simulation of a cup drawing is performed for this material, highlighting the importance of considering tension-compression asymmetry in the prediction of the earing profile, for materials with cubic structure, even if this phenomenon is relatively small.

  11. Parameter Estimation in Stochastic Grey-Box Models

    DEFF Research Database (Denmark)

    Kristensen, Niels Rode; Madsen, Henrik; Jørgensen, Sten Bay

    2004-01-01

    An efficient and flexible parameter estimation scheme for grey-box models in the sense of discretely, partially observed Ito stochastic differential equations with measurement noise is presented along with a corresponding software implementation. The estimation scheme is based on the extended...... Kalman filter and features maximum likelihood as well as maximum a posteriori estimation on multiple independent data sets, including irregularly sampled data sets and data sets with occasional outliers and missing observations. The software implementation is compared to an existing software tool...... and proves to have better performance both in terms of quality of estimates for nonlinear systems with significant diffusion and in terms of reproducibility. In particular, the new tool provides more accurate and more consistent estimates of the parameters of the diffusion term....

  12. Modelling Technical and Economic Parameters in Selection of Manufacturing Devices

    Directory of Open Access Journals (Sweden)

    Naqib Daneshjo

    2017-11-01

    Full Text Available Sustainable science and technology development is also conditioned by continuous development of means of production which have a key role in structure of each production system. Mechanical nature of the means of production is complemented by controlling and electronic devices in context of intelligent industry. A selection of production machines for a technological process or technological project has so far been practically resolved, often only intuitively. With regard to increasing intelligence, the number of variable parameters that have to be considered when choosing a production device is also increasing. It is necessary to use computing techniques and decision making methods according to heuristic methods and more precise methodological procedures during the selection. The authors present an innovative model for optimization of technical and economic parameters in the selection of manufacturing devices for industry 4.0.

  13. The relevance of non-human primate and rodent malaria models for humans

    Directory of Open Access Journals (Sweden)

    Riley Eleanor

    2011-02-01

    Full Text Available Abstract At the 2010 Keystone Symposium on "Malaria: new approaches to understanding Host-Parasite interactions", an extra scientific session to discuss animal models in malaria research was convened at the request of participants. This was prompted by the concern of investigators that skepticism in the malaria community about the use and relevance of animal models, particularly rodent models of severe malaria, has impacted on funding decisions and publication of research using animal models. Several speakers took the opportunity to demonstrate the similarities between findings in rodent models and human severe disease, as well as points of difference. The variety of malaria presentations in the different experimental models parallels the wide diversity of human malaria disease and, therefore, might be viewed as a strength. Many of the key features of human malaria can be replicated in a variety of nonhuman primate models, which are very under-utilized. The importance of animal models in the discovery of new anti-malarial drugs was emphasized. The major conclusions of the session were that experimental and human studies should be more closely linked so that they inform each other, and that there should be wider access to relevant clinical material.

  14. Effects of Mindfulness Practice on Performance-Relevant Parameters and Performance Outcomes in Sports: A Meta-Analytical Review.

    Science.gov (United States)

    Bühlmayer, Lucia; Birrer, Daniel; Röthlin, Philipp; Faude, Oliver; Donath, Lars

    2017-11-01

    Mindfulness as a present-oriented form of mental training affects cognitive processes and is increasingly considered meaningful for sport psychological training approaches. However, few intervention studies have examined the effects of mindfulness practice on physiological and psychological performance surrogates or on performance outcomes in sports. The aim of the present meta-analytical review was to examine the effects of mindfulness practice or mindfulness-based interventions on physiological and psychological performance surrogates and on performance outcomes in sports in athletes over 15 years of age. A structured literature search was conducted in six electronic databases (CINAHL, EMBASE, ISI Web of Knowledge, PsycINFO, MEDLINE and SPORTDiscus). The following search terms were used with Boolean conjunction: (mindful* OR meditat* OR yoga) AND (sport* OR train* OR exercis* OR intervent* OR perform* OR capacity OR skill*) AND (health* OR adult* OR athlete*). Randomized and non-randomized controlled studies that compared mindfulness practice techniques as an intervention with an inactive control or a control that followed another psychological training program in healthy sportive participants were screened for eligibility. Eligibility and study quality [Physiotherapy Evidence Database (PEDro)] scales were independently assessed by two researchers. A third independent researcher was consulted to achieve final consensus in case of disagreement between both researchers. Standardized mean differences (SMDs) were calculated as weighted Hedges' g and served as the main outcomes in comparing mindfulness practice versus control. Statistical analyses were conducted using a random-effects inverse-variance model. Nine trials of fair study quality (mean PEDro score 5.4, standard deviation 1.1) with 290 healthy sportive participants (athletics, cyclists, dart throwers, hammer throwers, hockey players, hurdlers, judo fighters, rugby players, middle-distance runners, long

  15. 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.

  16. Identification of grid model parameters using synchrophasor measurements

    Energy Technology Data Exchange (ETDEWEB)

    Boicea, Valentin; Albu, Mihaela [Politehnica University of Bucharest (Romania)

    2012-07-01

    Presently a critical element of the energy networks is represented by the active distribution grids, where generation intermittency and controllable loads contribute to a stochastic varability of the quantities characterizing the grid operation. The capability of controlling the electrical energy transfer is also limited by the incomplete knowledge of the detailed electrical model of each of the grid components. Asset management in distribution grids has to consider dynamic loads, while high loading of network sections might already have degraded some of the assets. Moreover, in case of functional microgrids, all elements need to be modelled accurately and an appropriate measurement layer enabling online control needs to be deployed. In this paper a method for online identification of the actual parameter values in grid electrical models is proposed. Laboratory results validating the proposed method are presented. (orig.)

  17. Dynamic systems models new methods of parameter and state estimation

    CERN Document Server

    2016-01-01

    This monograph is an exposition of a novel method for solving inverse problems, a method of parameter estimation for time series data collected from simulations of real experiments. These time series might be generated by measuring the dynamics of aircraft in flight, by the function of a hidden Markov model used in bioinformatics or speech recognition or when analyzing the dynamics of asset pricing provided by the nonlinear models of financial mathematics. Dynamic Systems Models demonstrates the use of algorithms based on polynomial approximation which have weaker requirements than already-popular iterative methods. Specifically, they do not require a first approximation of a root vector and they allow non-differentiable elements in the vector functions being approximated. The text covers all the points necessary for the understanding and use of polynomial approximation from the mathematical fundamentals, through algorithm development to the application of the method in, for instance, aeroplane flight dynamic...

  18. Luminescence model with quantum impact parameter for low energies

    International Nuclear Information System (INIS)

    Cruz G, H.S.; Michaelian, K.; Galindo U, S.; Martinez D, A.; Belmont M, E.

    2000-01-01

    The analytical model of induced light production in scintillator materials by energetic ions proposed by Michaelian and Menchaca (M-M) adjusts very well the luminescence substance data in a wide energy interval of the incident ions (10-100 MeV). However at low energies, that is, under to 10 MeV, the experimental deviations of the predictions of M-M model, show that the causes may be certain physical effects, all they important at low energies, which were not considered. We have modified lightly the M-M model using the basic fact that the Quantum mechanics gives to a different limit for the quantum impact parameter instead of the classic approximation. (Author)

  19. Effect of Uncertainty Parameters in Blowdown and Reflood Models for OPR1000 LBLOCA Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Huh, Byung Gil; Jin, Chang Yong; Seul, Kwangwon; Hwang, Taesuk [Korea Institute of Nuclear Safety, Daejeon (Korea, Republic of)

    2014-05-15

    KINS(Korea Institute of Nuclear Safety) has also performed the audit calculation with the KINS Realistic Evaluation Methodology(KINS-REM) to confirm the validity of licensee's calculation. In the BEPU method, it is very important to quantify the code and model uncertainty. It is referred in the following requirement: BE calculations in Regulatory Guide 1.157 - 'the code and models used are acceptable and applicable to the specific facility over the intended operating range and must quantify the uncertainty in the specific application'. In general, the uncertainty of model/code should be obtained through the data comparison with relevant integral- and separate-effect tests at different scales. However, it is not easy to determine these kinds of uncertainty because of the difficulty for evaluating accurately various experiments. Therefore, the expert judgment has been used in many cases even with the limitation that the uncertainty range of important parameters can be wide and inaccurate. In the KINS-REM, six heat transfer parameters in the blowdown phase have been used to consider the uncertainty of models. Recently, MARS-KS code was modified to consider the uncertainty of the five heat transfer parameters in the reflood phase. Accordingly, it is required that the uncertainty range for parameters of reflood models is determined and the effect of these ranges is evaluated. In this study, the large break LOCA (LBLOCA) analysis for OPR1000 was performed to identify the effect of uncertainty parameters in blowdown and reflood models.

  20. Model Predictive Engine Air-Ratio Control Using Online Sequential Relevance Vector Machine

    Directory of Open Access Journals (Sweden)

    Hang-cheong Wong

    2012-01-01

    Full Text Available Engine power, brake-specific fuel consumption, and emissions relate closely to air ratio (i.e., lambda among all the engine variables. An accurate and adaptive model for lambda prediction is essential to effective lambda control for long term. This paper utilizes an emerging technique, relevance vector machine (RVM, to build a reliable time-dependent lambda model which can be continually updated whenever a sample is added to, or removed from, the estimated lambda model. The paper also presents a new model predictive control (MPC algorithm for air-ratio regulation based on RVM. This study shows that the accuracy, training, and updating time of the RVM model are superior to the latest modelling methods, such as diagonal recurrent neural network (DRNN and decremental least-squares support vector machine (DLSSVM. Moreover, the control algorithm has been implemented on a real car to test. Experimental results reveal that the control performance of the proposed relevance vector machine model predictive controller (RVMMPC is also superior to DRNNMPC, support vector machine-based MPC, and conventional proportional-integral (PI controller in production cars. Therefore, the proposed RVMMPC is a promising scheme to replace conventional PI controller for engine air-ratio control.

  1. Optimization of Experimental Model Parameter Identification for Energy Storage Systems

    Directory of Open Access Journals (Sweden)

    Rosario Morello

    2013-09-01

    Full Text Available The smart grid approach is envisioned to take advantage of all available modern technologies in transforming the current power system to provide benefits to all stakeholders in the fields of efficient energy utilisation and of wide integration of renewable sources. Energy storage systems could help to solve some issues that stem from renewable energy usage in terms of stabilizing the intermittent energy production, power quality and power peak mitigation. With the integration of energy storage systems into the smart grids, their accurate modeling becomes a necessity, in order to gain robust real-time control on the network, in terms of stability and energy supply forecasting. In this framework, this paper proposes a procedure to identify the values of the battery model parameters in order to best fit experimental data and integrate it, along with models of energy sources and electrical loads, in a complete framework which represents a real time smart grid management system. The proposed method is based on a hybrid optimisation technique, which makes combined use of a stochastic and a deterministic algorithm, with low computational burden and can therefore be repeated over time in order to account for parameter variations due to the battery’s age and usage.

  2. Bayesian parameter estimation for stochastic models of biological cell migration

    Science.gov (United States)

    Dieterich, Peter; Preuss, Roland

    2013-08-01

    Cell migration plays an essential role under many physiological and patho-physiological conditions. It is of major importance during embryonic development and wound healing. In contrast, it also generates negative effects during inflammation processes, the transmigration of tumors or the formation of metastases. Thus, a reliable quantification and characterization of cell paths could give insight into the dynamics of these processes. Typically stochastic models are applied where parameters are extracted by fitting models to the so-called mean square displacement of the observed cell group. We show that this approach has several disadvantages and problems. Therefore, we propose a simple procedure directly relying on the positions of the cell's trajectory and the covariance matrix of the positions. It is shown that the covariance is identical with the spatial aging correlation function for the supposed linear Gaussian models of Brownian motion with drift and fractional Brownian motion. The technique is applied and illustrated with simulated data showing a reliable parameter estimation from single cell paths.

  3. Model parameters for representative wetland plant functional groups

    Science.gov (United States)

    Williams, Amber S.; Kiniry, James R.; Mushet, David M.; Smith, Loren M.; McMurry, Scott T.; Attebury, Kelly; Lang, Megan; McCarty, Gregory W.; Shaffer, Jill A.; Effland, William R.; Johnson, Mari-Vaughn V.

    2017-01-01

    Wetlands provide a wide variety of ecosystem services including water quality remediation, biodiversity refugia, groundwater recharge, and floodwater storage. Realistic estimation of ecosystem service benefits associated with wetlands requires reasonable simulation of the hydrology of each site and realistic simulation of the upland and wetland plant growth cycles. Objectives of this study were to quantify leaf area index (LAI), light extinction coefficient (k), and plant nitrogen (N), phosphorus (P), and potassium (K) concentrations in natural stands of representative plant species for some major plant functional groups in the United States. Functional groups in this study were based on these parameters and plant growth types to enable process-based modeling. We collected data at four locations representing some of the main wetland regions of the United States. At each site, we collected on-the-ground measurements of fraction of light intercepted, LAI, and dry matter within the 2013–2015 growing seasons. Maximum LAI and k variables showed noticeable variations among sites and years, while overall averages and functional group averages give useful estimates for multisite simulation modeling. Variation within each species gives an indication of what can be expected in such natural ecosystems. For P and K, the concentrations from highest to lowest were spikerush (Eleocharis macrostachya), reed canary grass (Phalaris arundinacea), smartweed (Polygonum spp.), cattail (Typha spp.), and hardstem bulrush (Schoenoplectus acutus). Spikerush had the highest N concentration, followed by smartweed, bulrush, reed canary grass, and then cattail. These parameters will be useful for the actual wetland species measured and for the wetland plant functional groups they represent. These parameters and the associated process-based models offer promise as valuable tools for evaluating environmental benefits of wetlands and for evaluating impacts of various agronomic practices in

  4. Application of a free parameter model to plastic scintillation samples

    Energy Technology Data Exchange (ETDEWEB)

    Tarancon Sanz, Alex, E-mail: alex.tarancon@ub.edu [Departament de Quimica Analitica, Universitat de Barcelona, Diagonal 647, E-08028 Barcelona (Spain); Kossert, Karsten, E-mail: Karsten.Kossert@ptb.de [Physikalisch-Technische Bundesanstalt (PTB), Bundesallee 100, 38116 Braunschweig (Germany)

    2011-08-21

    In liquid scintillation (LS) counting, the CIEMAT/NIST efficiency tracing method and the triple-to-double coincidence ratio (TDCR) method have proved their worth for reliable activity measurements of a number of radionuclides. In this paper, an extended approach to apply a free-parameter model to samples containing a mixture of solid plastic scintillation microspheres and radioactive aqueous solutions is presented. Several beta-emitting radionuclides were measured in a TDCR system at PTB. For the application of the free parameter model, the energy loss in the aqueous phase must be taken into account, since this portion of the particle energy does not contribute to the creation of scintillation light. The energy deposit in the aqueous phase is determined by means of Monte Carlo calculations applying the PENELOPE software package. To this end, great efforts were made to model the geometry of the samples. Finally, a new geometry parameter was defined, which was determined by means of a tracer radionuclide with known activity. This makes the analysis of experimental TDCR data of other radionuclides possible. The deviations between the determined activity concentrations and reference values were found to be lower than 3%. The outcome of this research work is also important for a better understanding of liquid scintillation counting. In particular the influence of (inverse) micelles, i.e. the aqueous spaces embedded in the organic scintillation cocktail, can be investigated. The new approach makes clear that it is important to take the energy loss in the aqueous phase into account. In particular for radionuclides emitting low-energy electrons (e.g. M-Auger electrons from {sup 125}I), this effect can be very important.

  5. 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

  6. Lumped-parameter fuel rod model for rapid thermal transients

    International Nuclear Information System (INIS)

    Perkins, K.R.; Ramshaw, J.D.

    1975-07-01

    The thermal behavior of fuel rods during simulated accident conditions is extremely sensitive to the heat transfer coefficient which is, in turn, very sensitive to the cladding surface temperature and the fluid conditions. The development of a semianalytical, lumped-parameter fuel rod model which is intended to provide accurate calculations, in a minimum amount of computer time, of the thermal response of fuel rods during a simulated loss-of-coolant accident is described. The results show good agreement with calculations from a comprehensive fuel-rod code (FRAP-T) currently in use at Aerojet Nuclear Company

  7. Modelled basic parameters for semi-industrial irradiation plant design

    International Nuclear Information System (INIS)

    Mangussi, J.

    2009-01-01

    The basic parameters of an irradiation plant design are the total activity, the product uniformity ratio and the efficiency process. The target density, the minimum dose required and the throughput depends on the use to which the irradiator will be put at. In this work, a model for calculating the specific dose rate at several depths in an infinite homogeneous medium produced by a slab source irradiator is presented. The product minimum dose rate for a set of target thickness is obtained. The design method steps are detailed and an illustrative example is presented. (author)

  8. Parameter Identification for Nonlinear Circuit Models of Power BAW Resonator

    Directory of Open Access Journals (Sweden)

    CONSTANTINESCU, F.

    2011-02-01

    Full Text Available The large signal operation of the bulk acoustic wave (BAW resonators is characterized by the amplitude-frequency effect and the intermodulation effect. The measurement of these effects, together with that of the small signal frequency characteristic, are used in this paper for the parameter identification of the nonlinear circuit models developed previously by authors. As the resonator has been connected to the measurement bench by wire bonding, the parasitic elements of this connection have been taken into account, being estimated solving some electrical and magnetic field problems.

  9. Systematic Assessment of Neutron and Gamma Backgrounds Relevant to Operational Modeling and Detection Technology Implementation

    Energy Technology Data Exchange (ETDEWEB)

    Archer, Daniel E. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Hornback, Donald Eric [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Johnson, Jeffrey O. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Nicholson, Andrew D. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Patton, Bruce W. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Peplow, Douglas E. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Miller, Thomas Martin [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Ayaz-Maierhafer, Birsen [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2015-01-01

    This report summarizes the findings of a two year effort to systematically assess neutron and gamma backgrounds relevant to operational modeling and detection technology implementation. The first year effort focused on reviewing the origins of background sources and their impact on measured rates in operational scenarios of interest. The second year has focused on the assessment of detector and algorithm performance as they pertain to operational requirements against the various background sources and background levels.

  10. Empirically modelled Pc3 activity based on solar wind parameters

    Directory of Open Access Journals (Sweden)

    B. Heilig

    2010-09-01

    Full Text Available It is known that under certain solar wind (SW/interplanetary magnetic field (IMF conditions (e.g. high SW speed, low cone angle the occurrence of ground-level Pc3–4 pulsations is more likely. In this paper we demonstrate that in the event of anomalously low SW particle density, Pc3 activity is extremely low regardless of otherwise favourable SW speed and cone angle. We re-investigate the SW control of Pc3 pulsation activity through a statistical analysis and two empirical models with emphasis on the influence of SW density on Pc3 activity. We utilise SW and IMF measurements from the OMNI project and ground-based magnetometer measurements from the MM100 array to relate SW and IMF measurements to the occurrence of Pc3 activity. Multiple linear regression and artificial neural network models are used in iterative processes in order to identify sets of SW-based input parameters, which optimally reproduce a set of Pc3 activity data. The inclusion of SW density in the parameter set significantly improves the models. Not only the density itself, but other density related parameters, such as the dynamic pressure of the SW, or the standoff distance of the magnetopause work equally well in the model. The disappearance of Pc3s during low-density events can have at least four reasons according to the existing upstream wave theory: 1. Pausing the ion-cyclotron resonance that generates the upstream ultra low frequency waves in the absence of protons, 2. Weakening of the bow shock that implies less efficient reflection, 3. The SW becomes sub-Alfvénic and hence it is not able to sweep back the waves propagating upstream with the Alfvén-speed, and 4. The increase of the standoff distance of the magnetopause (and of the bow shock. Although the models cannot account for the lack of Pc3s during intervals when the SW density is extremely low, the resulting sets of optimal model inputs support the generation of mid latitude Pc3 activity predominantly through

  11. Modelling of bio-optical parameters of open ocean waters

    Directory of Open Access Journals (Sweden)

    Vadim N. Pelevin

    2001-12-01

    Full Text Available An original method for estimating the concentration of chlorophyll pigments, absorption of yellow substance and absorption of suspended matter without pigments and yellow substance in detritus using spectral diffuse attenuation coefficient for downwelling irradiance and irradiance reflectance data has been applied to sea waters of different types in the open ocean (case 1. Using the effective numerical single parameter classification with the water type optical index m as a parameter over the whole range of the open ocean waters, the calculations have been carried out and the light absorption spectra of sea waters tabulated. These spectra are used to optimize the absorption models and thus to estimate the concentrations of the main admixtures in sea water. The value of m can be determined from direct measurements of the downward irradiance attenuation coefficient at 500 nm or calculated from remote sensing data using the regressions given in the article. The sea water composition can then be readily estimated from the tables given for any open ocean area if that one parameter m characterizing the basin is known.

  12. Application of regression model on stream water quality parameters

    International Nuclear Information System (INIS)

    Suleman, M.; Maqbool, F.; Malik, A.H.; Bhatti, Z.A.

    2012-01-01

    Statistical analysis was conducted to evaluate the effect of solid waste leachate from the open solid waste dumping site of Salhad on the stream water quality. Five sites were selected along the stream. Two sites were selected prior to mixing of leachate with the surface water. One was of leachate and other two sites were affected with leachate. Samples were analyzed for pH, water temperature, electrical conductivity (EC), total dissolved solids (TDS), Biological oxygen demand (BOD), chemical oxygen demand (COD), dissolved oxygen (DO) and total bacterial load (TBL). In this study correlation coefficient r among different water quality parameters of various sites were calculated by using Pearson model and then average of each correlation between two parameters were also calculated, which shows TDS and EC and pH and BOD have significantly increasing r value, while temperature and TDS, temp and EC, DO and BL, DO and COD have decreasing r value. Single factor ANOVA at 5% level of significance was used which shows EC, TDS, TCL and COD were significantly differ among various sites. By the application of these two statistical approaches TDS and EC shows strongly positive correlation because the ions from the dissolved solids in water influence the ability of that water to conduct an electrical current. These two parameters significantly vary among 5 sites which are further confirmed by using linear regression. (author)

  13. Model Parameter Variability for Enhanced Anaerobic Bioremediation of DNAPL Source Zones

    Science.gov (United States)

    Mao, X.; Gerhard, J. I.; Barry, D. A.

    2005-12-01

    modelling parameters typically employed for simulating TCE dechlorination relevant for a range of system conditions (e.g, bioaugmented, high TCE concentrations, etc.). The significance of the obtained variability of parameters is illustrated with one-dimensional simulations of enhanced anaerobic bioremediation of residual TCE DNAPL.

  14. 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.

  15. 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

  16. Hot electron transport modelling in fast ignition relevant targets with non-Spitzer resistivity

    Energy Technology Data Exchange (ETDEWEB)

    Chapman, D A; Hoarty, D J; Swatton, D J R [Plasma Physics Department, AWE, Aldermaston, Reading, Berkshire, RG7 4PR (United Kingdom); Hughes, S J, E-mail: david.chapman@awe.co.u [Computational Physics Group, AWE, Aldermaston, Reading, Berkshire, RG7 4PR (United Kingdom)

    2010-08-01

    The simple Lee-More model for electrical resistivity is implemented in the hybrid fast electron transport code THOR. The model is shown to reproduce experimental data across a wide range of temperatures using a small number of parameters. The effect of this model on the heating of simple Al targets by a short-pulse laser is studied and compared to the predictions of the classical Spitzer-Haerm resistivity. The model is then used in simulations of hot electron transport experiments using buried layer targets.

  17. 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.

  18. Convergence of surface diffusion parameters with model crystal size

    Science.gov (United States)

    Cohen, Jennifer M.; Voter, Arthur F.

    1994-07-01

    A study of the variation in the calculated quantities for adatom diffusion with respect to the size of the model crystal is presented. The reported quantities include surface diffusion barrier heights, pre-exponential factors, and dynamical correction factors. Embedded atom method (EAM) potentials were used throughout this effort. Both the layer size and the depth of the crystal were found to influence the values of the Arrhenius factors significantly. In particular, exchange type mechanisms required a significantly larger model than standard hopping mechanisms to determine adatom diffusion barriers of equivalent accuracy. The dynamical events that govern the corrections to transition state theory (TST) did not appear to be as sensitive to crystal depth. Suitable criteria for the convergence of the diffusion parameters with regard to the rate properties are illustrated.

  19. A distributed parameter wire model for transient electrical discharges

    International Nuclear Information System (INIS)

    Maier, W.B. II; Kadish, A.; Sutherland, C.D.; Robiscoe, R.T.

    1990-01-01

    A model for freely propagating transient electrical discharges, such as lightning and punch-through arcs, is developed in this paper. We describe the electromagnetic fields by Maxwell's equations and we represent the interaction of electric fields with the medium to produce current by ∂J/∂t=ω 2 (E-E*J)/4π, where ω and E* are parameters characteristic of the medium, J≡current density, and J≡J/|J|. We illustrate the properties of this model for small-diameter, guided, cylindrically symmetric discharges. Analytic, numerical, and approximate solutions are given for special cases. The model describes, in a new and comprehensive fashion, certain macroscopic discharge properties, such as threshold behavior, quenching and reignition, path tortuosity, discharge termination with nonzero charge density remaining along the discharge path, and other experimentally observed discharge phenomena. Fields, current densities, and charge densities are quantitatively determined from given boundary and initial conditions. We suggest that many macroscopic discharge properties are properly explained by the model as electromagnetic phenomena, and we discuss extensions of the model to include chemistry, principally ionization and recombination

  20. 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

  1. Theories, models and frameworks used in capacity building interventions relevant to public health: a systematic review.

    Science.gov (United States)

    Bergeron, Kim; Abdi, Samiya; DeCorby, Kara; Mensah, Gloria; Rempel, Benjamin; Manson, Heather

    2017-11-28

    There is limited research on capacity building interventions that include theoretical foundations. The purpose of this systematic review is to identify underlying theories, models and frameworks used to support capacity building interventions relevant to public health practice. The aim is to inform and improve capacity building practices and services offered by public health organizations. Four search strategies were used: 1) electronic database searching; 2) reference lists of included papers; 3) key informant consultation; and 4) grey literature searching. Inclusion and exclusion criteria are outlined with included papers focusing on capacity building, learning plans, professional development plans in combination with tools, resources, processes, procedures, steps, model, framework, guideline, described in a public health or healthcare setting, or non-government, government, or community organizations as they relate to healthcare, and explicitly or implicitly mention a theory, model and/or framework that grounds the type of capacity building approach developed. Quality assessment were performed on all included articles. Data analysis included a process for synthesizing, analyzing and presenting descriptive summaries, categorizing theoretical foundations according to which theory, model and/or framework was used and whether or not the theory, model or framework was implied or explicitly identified. Nineteen articles were included in this review. A total of 28 theories, models and frameworks were identified. Of this number, two theories (Diffusion of Innovations and Transformational Learning), two models (Ecological and Interactive Systems Framework for Dissemination and Implementation) and one framework (Bloom's Taxonomy of Learning) were identified as the most frequently cited. This review identifies specific theories, models and frameworks to support capacity building interventions relevant to public health organizations. It provides public health practitioners

  2. Standard model parameters and the search for new physics

    International Nuclear Information System (INIS)

    Marciano, W.J.

    1988-04-01

    In these lectures, my aim is to present an up-to-date status report on the standard model and some key tests of electroweak unification. Within that context, I also discuss how and where hints of new physics may emerge. To accomplish those goals, I have organized my presentation as follows: I discuss the standard model parameters with particular emphasis on the gauge coupling constants and vector boson masses. Examples of new physics appendages are also briefly commented on. In addition, because these lectures are intended for students and thus somewhat pedagogical, I have included an appendix on dimensional regularization and a simple computational example that employs that technique. Next, I focus on weak charged current phenomenology. Precision tests of the standard model are described and up-to-date values for the Cabibbo-Kobayashi-Maskawa (CKM) mixing matrix parameters are presented. Constraints implied by those tests for a 4th generation, supersymmetry, extra Z/prime/ bosons, and compositeness are also discussed. I discuss weak neutral current phenomenology and the extraction of sin/sup 2/ /theta//sub W/ from experiment. The results presented there are based on a recently completed global analysis of all existing data. I have chosen to concentrate that discussion on radiative corrections, the effect of a heavy top quark mass, and implications for grand unified theories (GUTS). The potential for further experimental progress is also commented on. I depart from the narrowest version of the standard model and discuss effects of neutrino masses and mixings. I have chosen to concentrate on oscillations, the Mikheyev-Smirnov- Wolfenstein (MSW) effect, and electromagnetic properties of neutrinos. On the latter topic, I will describe some recent work on resonant spin-flavor precession. Finally, I conclude with a prospectus on hopes for the future. 76 refs

  3. Technical Note: Using experimentally determined proton spot scanning timing parameters to accurately model beam delivery time.

    Science.gov (United States)

    Shen, Jiajian; Tryggestad, Erik; Younkin, James E; Keole, Sameer R; Furutani, Keith M; Kang, Yixiu; Herman, Michael G; Bues, Martin

    2017-10-01

    To accurately model the beam delivery time (BDT) for a synchrotron-based proton spot scanning system using experimentally determined beam parameters. A model to simulate the proton spot delivery sequences was constructed, and BDT was calculated by summing times for layer switch, spot switch, and spot delivery. Test plans were designed to isolate and quantify the relevant beam parameters in the operation cycle of the proton beam therapy delivery system. These parameters included the layer switch time, magnet preparation and verification time, average beam scanning speeds in x- and y-directions, proton spill rate, and maximum charge and maximum extraction time for each spill. The experimentally determined parameters, as well as the nominal values initially provided by the vendor, served as inputs to the model to predict BDTs for 602 clinical proton beam deliveries. The calculated BDTs (T BDT ) were compared with the BDTs recorded in the treatment delivery log files (T Log ): ∆t = T Log -T BDT . The experimentally determined average layer switch time for all 97 energies was 1.91 s (ranging from 1.9 to 2.0 s for beam energies from 71.3 to 228.8 MeV), average magnet preparation and verification time was 1.93 ms, the average scanning speeds were 5.9 m/s in x-direction and 19.3 m/s in y-direction, the proton spill rate was 8.7 MU/s, and the maximum proton charge available for one acceleration is 2.0 ± 0.4 nC. Some of the measured parameters differed from the nominal values provided by the vendor. The calculated BDTs using experimentally determined parameters matched the recorded BDTs of 602 beam deliveries (∆t = -0.49 ± 1.44 s), which were significantly more accurate than BDTs calculated using nominal timing parameters (∆t = -7.48 ± 6.97 s). An accurate model for BDT prediction was achieved by using the experimentally determined proton beam therapy delivery parameters, which may be useful in modeling the interplay effect and patient throughput. The model may

  4. 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.

  5. Family influences on mania-relevant cognitions and beliefs: a cognitive model of mania and reward.

    Science.gov (United States)

    Chen, Stephen H; Johnson, Sheri L

    2012-07-01

    The present study proposed and tested a cognitive model of mania and reward. Undergraduates (N = 284; 68.4% female; mean age = 20.99 years, standard deviation ± 3.37) completed measures of family goal setting and achievement values, personal reward-related beliefs, cognitive symptoms of mania, and risk for mania. Correlational analyses and structural equation modeling supported two distinct, but related facets of mania-relevant cognition: stably present reward-related beliefs and state-dependent cognitive symptoms in response to success and positive emotion. Results also indicated that family emphasis on achievement and highly ambitious extrinsic goals were associated with these mania-relevant cognitions. Finally, controlling for other factors, cognitive symptoms in response to success and positive emotion were uniquely associated with lifetime propensity towards mania symptoms. Results support the merit of distinguishing between facets of mania-relevant cognition and the importance of the family in shaping both aspects of cognition. © 2012 Wiley Periodicals, Inc.

  6. Performance Analysis of Different NeQuick Ionospheric Model Parameters

    Directory of Open Access Journals (Sweden)

    WANG Ningbo

    2017-04-01

    Full Text Available Galileo adopts NeQuick model for single-frequency ionospheric delay corrections. For the standard operation of Galileo, NeQuick model is driven by the effective ionization level parameter Az instead of the solar activity level index, and the three broadcast ionospheric coefficients are determined by a second-polynomial through fitting the Az values estimated from globally distributed Galileo Sensor Stations (GSS. In this study, the processing strategies for the estimation of NeQuick ionospheric coefficients are discussed and the characteristics of the NeQuick coefficients are also analyzed. The accuracy of Global Position System (GPS broadcast Klobuchar, original NeQuick2 and fitted NeQuickC as well as Galileo broadcast NeQuickG models is evaluated over the continental and oceanic regions, respectively, in comparison with the ionospheric total electron content (TEC provided by global ionospheric maps (GIM, GPS test stations and JASON-2 altimeter. The results show that NeQuickG can mitigate ionospheric delay by 54.2%~65.8% on a global scale, and NeQuickC can correct for 71.1%~74.2% of the ionospheric delay. NeQuick2 performs at the same level with NeQuickG, which is a bit better than that of GPS broadcast Klobuchar model.

  7. Exploring parameter constraints on quintessential dark energy: The exponential model

    International Nuclear Information System (INIS)

    Bozek, Brandon; Abrahamse, Augusta; Albrecht, Andreas; Barnard, Michael

    2008-01-01

    We present an analysis of a scalar field model of dark energy with an exponential potential using the Dark Energy Task Force (DETF) simulated data models. Using Markov Chain Monte Carlo sampling techniques we examine the ability of each simulated data set to constrain the parameter space of the exponential potential for data sets based on a cosmological constant and a specific exponential scalar field model. We compare our results with the constraining power calculated by the DETF using their 'w 0 -w a ' parametrization of the dark energy. We find that respective increases in constraining power from one stage to the next produced by our analysis give results consistent with DETF results. To further investigate the potential impact of future experiments, we also generate simulated data for an exponential model background cosmology which cannot be distinguished from a cosmological constant at DETF 'Stage 2', and show that for this cosmology good DETF Stage 4 data would exclude a cosmological constant by better than 3σ

  8. New Perspectives on Rodent Models of Advanced Paternal Age: Relevance to Autism

    Directory of Open Access Journals (Sweden)

    Claire J Foldi

    2011-06-01

    Full Text Available Offspring of older fathers have an increased risk of various adverse health outcomes, including autism and schizophrenia. With respect to biological mechanisms for this association, there are many more germline cell divisions in the life history of a sperm relative to that of an oocyte. This leads to more opportunities for copy error mutations in germ cells from older fathers. Evidence also suggests that epigenetic patterning in the sperm from older men is altered. Rodent models provide an experimental platform to examine the association between paternal age and brain development. Several rodent models of advanced paternal age (APA have been published with relevance to intermediate phenotypes related to autism. All four published APA models vary in key features creating a lack of consistency with respect to behavioural phenotypes. A consideration of common phenotypes that emerge from these APA-related mouse models may be informative in the exploration of the molecular and neurobiological correlates of APA.

  9. ORBSIM- ESTIMATING GEOPHYSICAL MODEL PARAMETERS FROM PLANETARY GRAVITY DATA

    Science.gov (United States)

    Sjogren, W. L.

    1994-01-01

    The ORBSIM program was developed for the accurate extraction of geophysical model parameters from Doppler radio tracking data acquired from orbiting planetary spacecraft. The model of the proposed planetary structure is used in a numerical integration of the spacecraft along simulated trajectories around the primary body. Using line of sight (LOS) Doppler residuals, ORBSIM applies fast and efficient modelling and optimization procedures which avoid the traditional complex dynamic reduction of data. ORBSIM produces quantitative geophysical results such as size, depth, and mass. ORBSIM has been used extensively to investigate topographic features on the Moon, Mars, and Venus. The program has proven particulary suitable for modelling gravitational anomalies and mascons. The basic observable for spacecraft-based gravity data is the Doppler frequency shift of a transponded radio signal. The time derivative of this signal carries information regarding the gravity field acting on the spacecraft in the LOS direction (the LOS direction being the path between the spacecraft and the receiving station, either Earth or another satellite). There are many dynamic factors taken into account: earth rotation, solar radiation, acceleration from planetary bodies, tracking station time and location adjustments, etc. The actual trajectories of the spacecraft are simulated using least squares fitted to conic motion. The theoretical Doppler readings from the simulated orbits are compared to actual Doppler observations and another least squares adjustment is made. ORBSIM has three modes of operation: trajectory simulation, optimization, and gravity modelling. In all cases, an initial gravity model of curved and/or flat disks, harmonics, and/or a force table are required input. ORBSIM is written in FORTRAN 77 for batch execution and has been implemented on a DEC VAX 11/780 computer operating under VMS. This program was released in 1985.

  10. A flexible, interactive software tool for fitting the parameters of neuronal models.

    Science.gov (United States)

    Friedrich, Péter; Vella, Michael; Gulyás, Attila I; Freund, Tamás F; Káli, Szabolcs

    2014-01-01

    The construction of biologically relevant neuronal models as well as model-based analysis of experimental data often requires the simultaneous fitting of multiple model parameters, so that the behavior of the model in a certain paradigm matches (as closely as possible) the corresponding output of a real neuron according to some predefined criterion. Although the task of model optimization is often computationally hard, and the quality of the results depends heavily on technical issues such as the appropriate choice (and implementation) of cost functions and optimization algorithms, no existing program provides access to the best available methods while also guiding the user through the process effectively. Our software, called Optimizer, implements a modular and extensible framework for the optimization of neuronal models, and also features a graphical interface which makes it easy for even non-expert users to handle many commonly occurring scenarios. Meanwhile, educated users can extend the capabilities of the program and customize it according to their needs with relatively little effort. Optimizer has been developed in Python, takes advantage of open-source Python modules for nonlinear optimization, and interfaces directly with the NEURON simulator to run the models. Other simulators are supported through an external interface. We have tested the program on several different types of problems of varying complexity, using different model classes. As targets, we used simulated traces from the same or a more complex model class, as well as experimental data. We successfully used Optimizer to determine passive parameters and conductance densities in compartmental models, and to fit simple (adaptive exponential integrate-and-fire) neuronal models to complex biological data. Our detailed comparisons show that Optimizer can handle a wider range of problems, and delivers equally good or better performance than any other existing neuronal model fitting tool.

  11. A flexible, interactive software tool for fitting the parameters of neuronal models

    Directory of Open Access Journals (Sweden)

    Péter eFriedrich

    2014-07-01

    Full Text Available The construction of biologically relevant neuronal models as well as model-based analysis of experimental data often requires the simultaneous fitting of multiple model parameters, so that the behavior of the model in a certain paradigm matches (as closely as possible the corresponding output of a real neuron according to some predefined criterion. Although the task of model optimization is often computationally hard, and the quality of the results depends heavily on technical issues such as the appropriate choice (and implementation of cost functions and optimization algorithms, no existing program provides access to the best available methods while also guiding the user through the process effectively. Our software, called Optimizer, implements a modular and extensible framework for the optimization of neuronal models, and also features a graphical interface which makes it easy for even non-expert users to handle many commonly occurring scenarios. Meanwhile, educated users can extend the capabilities of the program and customize it according to their needs with relatively little effort. Optimizer has been developed in Python, takes advantage of open-source Python modules for nonlinear optimization, and interfaces directly with the NEURON simulator to run the models. Other simulators are supported through an external interface. We have tested the program on several different types of problem of varying complexity, using different model classes. As targets, we used simulated traces from the same or a more complex model class, as well as experimental data. We successfully used Optimizer to determine passive parameters and conductance densities in compartmental models, and to fit simple (adaptive exponential integrate-and-fire neuronal models to complex biological data. Our detailed comparisons show that Optimizer can handle a wider range of problems, and delivers equally good or better performance than any other existing neuronal model fitting

  12. Structural characterisation of medically relevant protein assemblies by integrating mass spectrometry with computational modelling.

    Science.gov (United States)

    Politis, Argyris; Schmidt, Carla

    2018-03-20

    Structural mass spectrometry with its various techniques is a powerful tool for the structural elucidation of medically relevant protein assemblies. It delivers information on the composition, stoichiometries, interactions and topologies of these assemblies. Most importantly it can deal with heterogeneous mixtures and assemblies which makes it universal among the conventional structural techniques. In this review we summarise recent advances and challenges in structural mass spectrometric techniques. We describe how the combination of the different mass spectrometry-based methods with computational strategies enable structural models at molecular levels of resolution. These models hold significant potential for helping us in characterizing the function of protein assemblies related to human health and disease. In this review we summarise the techniques of structural mass spectrometry often applied when studying protein-ligand complexes. We exemplify these techniques through recent examples from literature that helped in the understanding of medically relevant protein assemblies. We further provide a detailed introduction into various computational approaches that can be integrated with these mass spectrometric techniques. Last but not least we discuss case studies that integrated mass spectrometry and computational modelling approaches and yielded models of medically important protein assembly states such as fibrils and amyloids. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

  13. Use of an ecologically relevant modelling approach to improve remote sensing-based schistosomiasis risk profiling

    Directory of Open Access Journals (Sweden)

    Yvonne Walz

    2015-11-01

    Full Text Available Schistosomiasis is a widespread water-based disease that puts close to 800 million people at risk of infection with more than 250 million infected, mainly in sub-Saharan Africa. Transmission is governed by the spatial distribution of specific freshwater snails that act as intermediate hosts and the frequency, duration and extent of human bodies exposed to infested water sources during human water contact. Remote sensing data have been utilized for spatially explicit risk profiling of schistosomiasis. Since schistosomiasis risk profiling based on remote sensing data inherits a conceptual drawback if school-based disease prevalence data are directly related to the remote sensing measurements extracted at the location of the school, because the disease transmission usually does not exactly occur at the school, we took the local environment around the schools into account by explicitly linking ecologically relevant environmental information of potential disease transmission sites to survey measurements of disease prevalence. Our models were validated at two sites with different landscapes in Côte d’Ivoire using high- and moderateresolution remote sensing data based on random forest and partial least squares regression. We found that the ecologically relevant modelling approach explained up to 70% of the variation in Schistosoma infection prevalence and performed better compared to a purely pixelbased modelling approach. Furthermore, our study showed that model performance increased as a function of enlarging the school catchment area, confirming the hypothesis that suitable environments for schistosomiasis transmission rarely occur at the location of survey measurements.

  14. 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.

  15. Approaches to highly parameterized inversion: A guide to using PEST for model-parameter and predictive-uncertainty analysis

    Science.gov (United States)

    Doherty, John E.; Hunt, Randall J.; Tonkin, Matthew J.

    2010-01-01

    these highly parameterized modeling contexts. Availability of these utilities is particularly important because, in many cases, a significant proportion of the uncertainty associated with model parameters-and the predictions that depend on them-arises from differences between the complex properties of the real world and the simplified representation of those properties that is expressed by the calibrated model. This report is intended to guide intermediate to advanced modelers in the use of capabilities available with the PEST suite of programs for evaluating model predictive error and uncertainty. A brief theoretical background is presented on sources of parameter and predictive uncertainty and on the means for evaluating this uncertainty. Applications of PEST tools are then discussed for overdetermined and underdetermined problems, both linear and nonlinear. PEST tools for calculating contributions to model predictive uncertainty, as well as optimization of data acquisition for reducing parameter and predictive uncertainty, are presented. The appendixes list the relevant PEST variables, files, and utilities required for the analyses described in the document.

  16. Parameter estimation and hypothesis testing in linear models

    CERN Document Server

    Koch, Karl-Rudolf

    1999-01-01

    The necessity to publish the second edition of this book arose when its third German edition had just been published. This second English edition is there­ fore a translation of the third German edition of Parameter Estimation and Hypothesis Testing in Linear Models, published in 1997. It differs from the first English edition by the addition of a new chapter on robust estimation of parameters and the deletion of the section on discriminant analysis, which has been more completely dealt with by the author in the book Bayesian In­ ference with Geodetic Applications, Springer-Verlag, Berlin Heidelberg New York, 1990. Smaller additions and deletions have been incorporated, to im­ prove the text, to point out new developments or to eliminate errors which became apparent. A few examples have been also added. I thank Springer-Verlag for publishing this second edition and for the assistance in checking the translation, although the responsibility of errors remains with the author. I also want to express my thanks...

  17. 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

  18. 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

  19. Evaluation of the perceptual grouping parameter in the CTVA model

    Directory of Open Access Journals (Sweden)

    Manuel Cortijo

    2005-01-01

    Full Text Available The CODE Theory of Visual Attention (CTVA is a mathematical model explaining the effects of grouping by proximity and distance upon reaction times and accuracy of response with regard to elements in the visual display. The predictions of the theory agree quite acceptably in one and two dimensions (CTVA-2D with the experimental results (reaction times and accuracy of response. The difference between reaction-times for the compatible and incompatible responses, known as the responsecompatibility effect, is also acceptably predicted, except at small distances and high number of distractors. Further results using the same paradigm at even smaller distances have been now obtained, showing greater discrepancies. Then, we have introduced a method to evaluate the strength of sensory evidence (eta parameter, which takes grouping by similarity into account and minimizes these discrepancies.

  20. Filtered selection coupled with support vector machines generate a functionally relevant prediction model for colorectal cancer

    Directory of Open Access Journals (Sweden)

    Gabere MN

    2016-06-01

    Full Text Available Musa Nur Gabere,1 Mohamed Aly Hussein,1 Mohammad Azhar Aziz2 1Department of Bioinformatics, King Abdullah International Medical Research Center/King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia; 2Colorectal Cancer Research Program, Department of Medical Genomics, King Abdullah International Medical Research Center, Riyadh, Saudi Arabia Purpose: There has been considerable interest in using whole-genome expression profiles for the classification of colorectal cancer (CRC. The selection of important features is a crucial step before training a classifier.Methods: In this study, we built a model that uses support vector machine (SVM to classify cancer and normal samples using Affymetrix exon microarray data obtained from 90 samples of 48 patients diagnosed with CRC. From the 22,011 genes, we selected the 20, 30, 50, 100, 200, 300, and 500 genes most relevant to CRC using the minimum-redundancy–maximum-relevance (mRMR technique. With these gene sets, an SVM model was designed using four different kernel types (linear, polynomial, radial basis function [RBF], and sigmoid.Results: The best model, which used 30 genes and RBF kernel, outperformed other combinations; it had an accuracy of 84% for both ten fold and leave-one-out cross validations in discriminating the cancer samples from the normal samples. With this 30 genes set from mRMR, six classifiers were trained using random forest (RF, Bayes net (BN, multilayer perceptron (MLP, naïve Bayes (NB, reduced error pruning tree (REPT, and SVM. Two hybrids, mRMR + SVM and mRMR + BN, were the best models when tested on other datasets, and they achieved a prediction accuracy of 95.27% and 91.99%, respectively, compared to other mRMR hybrid models (mRMR + RF, mRMR + NB, mRMR + REPT, and mRMR + MLP. Ingenuity pathway analysis was used to analyze the functions of the 30 genes selected for this model and their potential association with CRC: CDH3, CEACAM7, CLDN1, IL8, IL6R, MMP1

  1. Decision-relevant evaluation of climate models: A case study of chill hours in California

    Science.gov (United States)

    Jagannathan, K. A.; Jones, A. D.; Kerr, A. C.

    2017-12-01

    The past decade has seen a proliferation of different climate datasets with over 60 climate models currently in use. Comparative evaluation and validation of models can assist practitioners chose the most appropriate models for adaptation planning. However, such assessments are usually conducted for `climate metrics' such as seasonal temperature, while sectoral decisions are often based on `decision-relevant outcome metrics' such as growing degree days or chill hours. Since climate models predict different metrics with varying skill, the goal of this research is to conduct a bottom-up evaluation of model skill for `outcome-based' metrics. Using chill hours (number of hours in winter months where temperature is lesser than 45 deg F) in Fresno, CA as a case, we assess how well different GCMs predict the historical mean and slope of chill hours, and whether and to what extent projections differ based on model selection. We then compare our results with other climate-based evaluations of the region, to identify similarities and differences. For the model skill evaluation, historically observed chill hours were compared with simulations from 27 GCMs (and multiple ensembles). Model skill scores were generated based on a statistical hypothesis test of the comparative assessment. Future projections from RCP 8.5 runs were evaluated, and a simple bias correction was also conducted. Our analysis indicates that model skill in predicting chill hour slope is dependent on its skill in predicting mean chill hours, which results from the non-linear nature of the chill metric. However, there was no clear relationship between the models that performed well for the chill hour metric and those that performed well in other temperature-based evaluations (such winter minimum temperature or diurnal temperature range). Further, contrary to conclusions from other studies, we also found that the multi-model mean or large ensemble mean results may not always be most appropriate for this

  2. Crack propagation rate modelling for 316SS exposed to PWR-relevant conditions

    International Nuclear Information System (INIS)

    Vankeerberghen, M.; Weyns, G.; Gavrilov, S.; Martens, B.; Deconinck, J.

    2009-01-01

    The crack propagation rate of Type 316 stainless steel in boric acid-lithium hydroxide solutions under PWR-relevant conditions was modelled. A film rupture/dissolution/repassivation mechanism is assumed and extended to cold worked materials by including a stress-dependent bare metal dissolution current density. The chemical and electrochemical conditions within the crack are calculated by finite element calculations, an analytical expression is used for the crack-tip strain rate and the crack-tip stress is assumed equal to 2.5 times the yield stress (plane-strain). First the model was calibrated against a literature published data set. Afterwards, the influence of various variables - dissolved hydrogen, boric acid and lithium hydroxide content, stress intensity, crack length, temperature, flow rate - was studied. Finally, other published crack growth rate tests were modelled and the calculated crack growth rates were found to be in reasonable agreement with the reported ones

  3. Examining the Functional Specification of Two-Parameter Model under Location and Scale Parameter Condition

    OpenAIRE

    Nakashima, Takahiro

    2006-01-01

    The functional specification of mean-standard deviation approach is examined under location and scale parameter condition. Firstly, the full set of restrictions imposed on the mean-standard deviation function under the location and scale parameter condition are made clear. Secondly, the examination based on the restrictions mentioned in the previous sentence derives the new properties of the mean-standard deviation function on the applicability of additive separability and the curvature of ex...

  4. 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

  5. Modeling the outflow of liquid with initial supercritical parameters using the relaxation model for condensation

    Directory of Open Access Journals (Sweden)

    Lezhnin Sergey

    2017-01-01

    Full Text Available The two-temperature model of the outflow from a vessel with initial supercritical parameters of medium has been realized. The model uses thermodynamic non-equilibrium relaxation approach to describe phase transitions. Based on a new asymptotic model for computing the relaxation time, the outflow of water with supercritical initial pressure and super- and subcritical temperatures has been calculated.

  6. The relevance of existing health communication models in the email age: An

    Science.gov (United States)

    Fage-Butler, Antoinette Mary; Jensen, Matilde Nisbeth

    2015-01-01

    Email communication is being integrated relatively slowly into doctor–patient communication. Patients have expressed enthusiasm for the medium, while doctors are generally more reluctant. As existing health communication models have characteristically assumed the co-presence of doctor and patient and primarily reflect medical practitioners’ perspectives, their suitability in relation to email communication and patients’ perspectives warrants further investigation. Following a two-step process and using the methodology of the integrative literature review, 29 articles from 2004–2014 are analysed with the aim of investigating the advantages and disadvantages of the medium of email from the patient’s perspective. The findings are compared to the health communication models of biomedicine, patient-centeredness, patient education and patient empowerment to investigate these models’ relevance for doctor–patient email communication. Results show that patients identify numerous advantages with email communication, including improved convenience and access, more detailed informational exchanges, greater reflection opportunities, freedom from the medical gaze and the potential to level out power imbalances, as well as a number of primarily medium-related disadvantages. The findings indicate that email can counteract some of the communicative problems associated with biomedicine and suggest the ongoing relevance of aspects of the models of patient empowerment, patient-centeredness and patient education for email communication.

  7. Relevant Criteria for Testing the Quality of Models for Turbulent Wind Speed Fluctuations

    DEFF Research Database (Denmark)

    Frandsen, Sten Tronæs; Ejsing Jørgensen, Hans; Sørensen, John Dalsgaard

    2008-01-01

    Seeking relevant criteria for testing the quality of turbulence models, the scale of turbulence and the gust factor have been estimated from data and compared with predictions from first-order models of these two quantities. It is found that the mean of the measured length scales is approximately...... 10% smaller than the IEC model for wind turbine hub height levels. The mean is only marginally dependent on trends in time series. It is also found that the coefficient of variation of the measured length scales is about 50%. 3  s and 10  s preaveraging of wind speed data are relevant for megawatt......-size wind turbines when seeking wind characteristics that correspond to one blade and the entire rotor, respectively. For heights exceeding 50-60  m, the gust factor increases with wind speed. For heights larger than 60-80  m, present assumptions on the value of the gust factor are significantly...

  8. 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

  9. Promoting culturally competent chronic pain management using the clinically relevant continuum model.

    Science.gov (United States)

    Monsivais, Diane B

    2011-06-01

    This article reviews the culture of biomedicine and current practices in pain management education, which often merge to create a hostile environment for effective chronic pain care. Areas of cultural tensions in chronic pain frequently involve the struggle to achieve credibility regarding one's complaints of pain (or being believed that the pain is real) and complying with pain medication protocols. The clinically relevant continuum model is presented as a framework allowing providers to approach care from an evidence-based, culturally appropriate (patient centered) perspective that takes into account the highest level of evidence available, provider expertise, and patient preferences and values. Copyright © 2011 Elsevier Inc. All rights reserved.

  10. Pharmacokinetic models relevant to toxicity and metabolism for uranium in humans and animals

    International Nuclear Information System (INIS)

    Wrenn, M.E.; Lipsztein, J.; Bertelli, L.

    1988-01-01

    The aim of this paper is to summarize pharmacokinetic models of uranium metabolism. Fortunately, others have recently reviewed metabolic models of all types, not just pharmacokinetic models. Their papers should be consulted for greater biological detail than is possible here. Improvements in the models since these other papers are noted. Models for assessing the biological consequences of exposure should account for the kinetics of intake by ingestion, inhalation, and injection, and the chemical form of uranium; predict the time dependent concentration in red blood cells, plasma, urine, kidney, bone and other organs (or compartments); and be adaptable to calculating these concentrations for varying regimens of intake. The biological parameters in the models come from metabolic data in humans and animals. Some of these parameters are reasonably well defined. For example, the cumulative urinary excretion at 24 hours post injection of soluble uranium in man is about 70%, the absorbed fraction for soluble uranium ingested by man in drinking water during normal dietary conditions is about 1%, and the half time in the mammalian kidney is several days. 17 refs., 8 figs

  11. Changes of the more relevant PHTS parameters after the cleaning of the steam generators primary side at Embalse nuclear power plant

    International Nuclear Information System (INIS)

    Moreno, Carlos A.; Coutsiers, Ernesto; Acevedo, Paul; Pomerantz, Marcelo E.

    2003-01-01

    During the operation of the plant magnetite deposition occurs at the inner walls of Primary Heat Transport System (PHTS). This deposition is particularly significant at the U-tubes of steam generators. The consequence of this is the deterioration of heat transfer to the Secondary System. In order to minimize this impact, during the annual outage of 2000, the steam generators primary side cleaning by the SIVABLAST technique was carried out. This technique consists in blasting the inner walls with tiny stainless steel balls propelled by air at high pressure. This paper presents the change of the more relevant parameters of PHTS after that cleaning. The parameters analyzed and the main results are the following: 1) Inlet header temperature dropped 4.7 C degrees at full power; 2) Exit quality at the outlet headers decreased from 3,5% to 1,5%; 3) Global PHTS flow in single phase evaluated from: a) In-site instrumentation increased 4,6%; b) Thermalhydraulic code NUCIRC 1.0 increased 3,2%; c) measured flows at the instrumented fuel channels increased 4.4%. (author)

  12. Green roof rainfall-runoff modelling: is the comparison between conceptual and physically based approaches relevant?

    Science.gov (United States)

    Versini, Pierre-Antoine; Tchiguirinskaia, Ioulia; Schertzer, Daniel

    2017-04-01

    Green roofs are commonly considered as efficient tools to mitigate urban runoff as they can store precipitation, and consequently provide retention and detention performances. Designed as a compromise between water holding capacity, weight and hydraulic conductivity, their substrate is usually an artificial media differentiating significantly from a traditional soil. In order to assess green roofs hydrological performances, many models have been developed. Classified into two categories (conceptual and physically based), they are usually applied to reproduce the discharge of a particular monitored green roof considered as homogeneous. Although the resulted simulations could be satisfactory, the question of robustness and consistency of the calibrated parameters is often not addressed. Here, a modeling framework has been developed to assess the efficiency and the robustness of both modelling approaches (conceptual and physically based) in reproducing green roof hydrological behaviour. SWMM and VS2DT models have been used for this purpose. This work also benefits from an experimental setup where several green roofs differentiated by their substrate thickness and vegetation cover are monitored. Based on the data collected for several rainfall events, it has been studied how the calibrated parameters are effectively linked to their physical properties and how they can vary from one green roof configuration to another. Although both models reproduce correctly the observed discharges in most of the cases, their calibrated parameters exhibit a high inconsistency. For a same green roof configuration, these parameters can vary significantly from one rainfall event to another, even if they are supposed to be linked to the green roof characteristics (roughness, residual moisture content for instance). They can also be different from one green roof configuration to another although the implemented substrate is the same. Finally, it appears very difficult to find any

  13. Sensitivity of numerical dispersion modeling to explosive source parameters

    International Nuclear Information System (INIS)

    Baskett, R.L.; Cederwall, R.T.

    1991-01-01

    The calculation of downwind concentrations from non-traditional sources, such as explosions, provides unique challenges to dispersion models. The US Department of Energy has assigned the Atmospheric Release Advisory Capability (ARAC) at the Lawrence Livermore National Laboratory (LLNL) the task of estimating the impact of accidental radiological releases to the atmosphere anywhere in the world. Our experience includes responses to over 25 incidents in the past 16 years, and about 150 exercises a year. Examples of responses to explosive accidents include the 1980 Titan 2 missile fuel explosion near Damascus, Arkansas and the hydrogen gas explosion in the 1986 Chernobyl nuclear power plant accident. Based on judgment and experience, we frequently estimate the source geometry and the amount of toxic material aerosolized as well as its particle size distribution. To expedite our real-time response, we developed some automated algorithms and default assumptions about several potential sources. It is useful to know how well these algorithms perform against real-world measurements and how sensitive our dispersion model is to the potential range of input values. In this paper we present the algorithms we use to simulate explosive events, compare these methods with limited field data measurements, and analyze their sensitivity to input parameters. 14 refs., 7 figs., 2 tabs

  14. Control Relevant Modeling and Design of Scramjet-Powered Hypersonic Vehicles

    Science.gov (United States)

    Dickeson, Jeffrey James

    This report provides an overview of scramjet-powered hypersonic vehicle modeling and control challenges. Such vehicles are characterized by unstable non-minimum phase dynamics with significant coupling and low thrust margins. Recent trends in hypersonic vehicle research are summarized. To illustrate control relevant design issues and tradeoffs, a generic nonlinear 3DOF longitudinal dynamics model capturing aero-elastic-propulsive interactions for wedge-shaped vehicle is used. Limitations of the model are discussed and numerous modifications have been made to address control relevant needs. Two different baseline configurations are examined over a two-stage to orbit ascent trajectory. The report highlights how vehicle level-flight static (trim) and dynamic properties change over the trajectory. Thermal choking constraints are imposed on control system design as a direct consequence of having a finite FER margin. The implication of this state-dependent nonlinear FER margin constraint, the right half plane (RHP) zero, and lightly damped flexible modes, on control system bandwidth (BW) and FPA tracking has been discussed. A control methodology has been proposed that addresses the above dynamics while providing some robustness to modeling uncertainty. Vehicle closure (the ability to fly a trajectory segment subject to constraints) is provided through a proposed vehicle design methodology. The design method attempts to use open loop metrics whenever possible to design the vehicle. The design method is applied to a vehicle/control law closed loop nonlinear simulation for validation. The 3DOF longitudinal modeling results are validated against a newly released NASA 6DOF code.

  15. Black hole algorithm for determining model parameter in self-potential data

    Science.gov (United States)

    Sungkono; Warnana, Dwa Desa

    2018-01-01

    Analysis of self-potential (SP) data is increasingly popular in geophysical method due to its relevance in many cases. However, the inversion of SP data is often highly nonlinear. Consequently, local search algorithms commonly based on gradient approaches have often failed to find the global optimum solution in nonlinear problems. Black hole algorithm (BHA) was proposed as a solution to such problems. As the name suggests, the algorithm was constructed based on the black hole phenomena. This paper investigates the application of BHA to solve inversions of field and synthetic self-potential (SP) data. The inversion results show that BHA accurately determines model parameters and model uncertainty. This indicates that BHA is highly potential as an innovative approach for SP data inversion.

  16. Physical property parameter set for modeling ICPP aqueous wastes with ASPEN electrolyte NRTL model

    International Nuclear Information System (INIS)

    Schindler, R.E.

    1996-09-01

    The aqueous waste evaporators at the Idaho Chemical Processing Plant (ICPP) are being modeled using ASPEN software. The ASPEN software calculates chemical and vapor-liquid equilibria with activity coefficients calculated using the electrolyte Non-Random Two Liquid (NRTL) model for local excess Gibbs free energies of interactions between ions and molecules in solution. The use of the electrolyte NRTL model requires the determination of empirical parameters for the excess Gibbs free energies of the interactions between species in solution. This report covers the development of a set parameters, from literature data, for the use of the electrolyte NRTL model with the major solutes in the ICPP aqueous wastes

  17. Lab-on-a-brane: A novel physiologically relevant planar arterial model to study transendothelial transport

    Science.gov (United States)

    Budhwani, Karim Ismail

    The tremendous quality of life impact notwithstanding, cardiovascular diseases and Cancer add up to over US$ 700bn each year in financial costs alone. Aging and population growth are expected to further expand the problem space while drug research and development remain expensive. However, preclinical costs can be substantially mitigated by substituting animal models with in vitro devices that accurately model human cardiovascular transport. Here we present a novel physiologically relevant lab-on-a-brane that simulates in vivo pressure, flow, strain, and shear waveforms associated with normal and pathological conditions in large and small blood vessels for studying molecular transport across the endothelial monolayer. The device builds upon previously demonstrated integrated microfluidic loop design by: (a) introducing nanoscale pores in the substrate membrane to enable transmembrane molecular transport, (b) transforming the substrate membrane into a nanofibrous matrix for 3D smooth muscle cell (SMC) tissue culture, (c) integrating electrospinning fabrication methods, (d) engineering an invertible sandwich cell culture device architecture, and (e) devising a healthy co-culture mechanism for human arterial endothelial cell (HAEC) monolayer and multiple layers of human smooth muscle cells (HSMC) to accurately mimic arterial anatomy. Structural and mechanical characterization was conducted using confocal microscopy, SEM, stress/strain analysis, and infrared spectroscopy. Transport was characterized using FITC-Dextran hydraulic permeability protocol. Structure and transport characterization successfully demonstrate device viability as a physiologically relevant arterial mimic for testing transendothelial transport. Thus, our lab-on-a-brane provides a highly effective and efficient, yet considerably inexpensive, physiologically relevant alternative for pharmacokinetic evaluation; possibly reducing animals used in pre-clinical testing, clinical trials cost from false

  18. Relevance of Discrecionary Accruals in Ohlson Model: the Case of Mexico

    Directory of Open Access Journals (Sweden)

    Rocío Durán-Vázquez

    2012-01-01

    Full Text Available This study applied the modified Jones´ model (1991 for selected companies of Mexico. This model aims to assess the impact of Discretionary Accrual Information (DAI on financial reporting statements, in order to identify the value relevance of “earnings quality”. We applied methodological criteria of Chung et al (2005 and Mukit & Iskandar (2009. We analyzed financial information of the 35 stock included in the Index of Prices and Quotations (IPC of the Mexican Stock Exchange (BMV for the period 2000 to 2011. 19 companies met the specifications of the model, for 48 quarters of information. The analysis was done in three parts: first, an analysis of the modified Jones´ model under panel data considerations by using fixed effects and adjustments of performing autocorrelation of order 1; second, a correlation analysis between the residuals of the modified Jones´ model and the return of stock price in 3 annual closings years of study: 2007, 2008 and 2009; and third, we incorporated this variable (DAI in the Ohlson model (of the financial and corporate accounting literature and we tested it with panel data analysis, under fixed effects, throughout the study period.

  19. More Realistic Face Model Surface Improves Relevance of Pediatric In-Vitro Aerosol Studies.

    Science.gov (United States)

    Amirav, Israel; Halamish, Asaf; Gorenberg, Miguel; Omar, Hamza; Newhouse, Michael T

    2015-01-01

    Various hard face models are commonly used to evaluate the efficiency of aerosol face masks. Softer more realistic "face" surface materials, like skin, deform upon mask application and should provide more relevant in-vitro tests. Studies that simultaneously take into consideration many of the factors characteristic of the in vivo face are lacking. These include airways, various application forces, comparison of various devices, comparison with a hard-surface model and use of a more representative model face based on large numbers of actual faces. To compare mask to "face" seal and aerosol delivery of two pediatric masks using a soft vs. a hard, appropriately representative, pediatric face model under various applied forces. Two identical face models and upper airways replicas were constructed, the only difference being the suppleness and compressibility of the surface layer of the "face." Integrity of the seal and aerosol delivery of two different masks [AeroChamber (AC) and SootherMask (SM)] were compared using a breath simulator, filter collection and realistic applied forces. The soft "face" significantly increased the delivery efficiency and the sealing characteristics of both masks. Aerosol delivery with the soft "face" was significantly greater for the SM compared to the AC (pmasks was observed with the hard "face." The material and pliability of the model "face" surface has a significant influence on both the seal and delivery efficiency of face masks. This finding should be taken into account during in-vitro aerosol studies.

  20. Linking electricity and water models to assess electricity choices at water-relevant scales

    International Nuclear Information System (INIS)

    Sattler, S; Rogers, J; Macknick, J; Lopez, A; Yates, D; Flores-Lopez, F

    2012-01-01

    Hydrology/water management and electricity generation projections have been modeled separately, but there has been little effort in intentionally and explicitly linking the two sides of the water–energy nexus. This paper describes a platform for assessing power plant cooling water withdrawals and consumption under different electricity pathways at geographic and time scales appropriate for both electricity and hydrology/water management. This platform uses estimates of regional electricity generation by the Regional Energy Deployment System (ReEDS) as input to a hydrologic and water management model—the Water Evaluation and Planning (WEAP) system. In WEAP, this electricity use represents thermoelectric cooling water withdrawals and consumption within the broader, regional water resource context. Here we describe linking the electricity and water models, including translating electricity generation results from ReEDS-relevant geographies to the water-relevant geographies of WEAP. The result of this analysis is water use by the electric sector at the regional watershed level, which is used to examine the water resource implications of these electricity pathways. (letter)

  1. Assigning probability distributions to input parameters of performance assessment models

    Energy Technology Data Exchange (ETDEWEB)

    Mishra, Srikanta [INTERA Inc., Austin, TX (United States)

    2002-02-01

    This study presents an overview of various approaches for assigning probability distributions to input parameters and/or future states of performance assessment models. Specifically,three broad approaches are discussed for developing input distributions: (a) fitting continuous distributions to data, (b) subjective assessment of probabilities, and (c) Bayesian updating of prior knowledge based on new information. The report begins with a summary of the nature of data and distributions, followed by a discussion of several common theoretical parametric models for characterizing distributions. Next, various techniques are presented for fitting continuous distributions to data. These include probability plotting, method of moments, maximum likelihood estimation and nonlinear least squares analysis. The techniques are demonstrated using data from a recent performance assessment study for the Yucca Mountain project. Goodness of fit techniques are also discussed, followed by an overview of how distribution fitting is accomplished in commercial software packages. The issue of subjective assessment of probabilities is dealt with in terms of the maximum entropy distribution selection approach, as well as some common rules for codifying informal expert judgment. Formal expert elicitation protocols are discussed next, and are based primarily on the guidance provided by the US NRC. The Bayesian framework for updating prior distributions (beliefs) when new information becomes available is discussed. A simple numerical approach is presented for facilitating practical applications of the Bayes theorem. Finally, a systematic framework for assigning distributions is presented: (a) for the situation where enough data are available to define an empirical CDF or fit a parametric model to the data, and (b) to deal with the situation where only a limited amount of information is available.

  2. Assigning probability distributions to input parameters of performance assessment models

    International Nuclear Information System (INIS)

    Mishra, Srikanta

    2002-02-01

    This study presents an overview of various approaches for assigning probability distributions to input parameters and/or future states of performance assessment models. Specifically,three broad approaches are discussed for developing input distributions: (a) fitting continuous distributions to data, (b) subjective assessment of probabilities, and (c) Bayesian updating of prior knowledge based on new information. The report begins with a summary of the nature of data and distributions, followed by a discussion of several common theoretical parametric models for characterizing distributions. Next, various techniques are presented for fitting continuous distributions to data. These include probability plotting, method of moments, maximum likelihood estimation and nonlinear least squares analysis. The techniques are demonstrated using data from a recent performance assessment study for the Yucca Mountain project. Goodness of fit techniques are also discussed, followed by an overview of how distribution fitting is accomplished in commercial software packages. The issue of subjective assessment of probabilities is dealt with in terms of the maximum entropy distribution selection approach, as well as some common rules for codifying informal expert judgment. Formal expert elicitation protocols are discussed next, and are based primarily on the guidance provided by the US NRC. The Bayesian framework for updating prior distributions (beliefs) when new information becomes available is discussed. A simple numerical approach is presented for facilitating practical applications of the Bayes theorem. Finally, a systematic framework for assigning distributions is presented: (a) for the situation where enough data are available to define an empirical CDF or fit a parametric model to the data, and (b) to deal with the situation where only a limited amount of information is available

  3. Malaria in pregnancy: the relevance of animal models for vaccine development.

    Science.gov (United States)

    Doritchamou, Justin; Teo, Andrew; Fried, Michal; Duffy, Patrick E

    2017-10-06

    Malaria during pregnancy due to Plasmodium falciparum or P. vivax is a major public health problem in endemic areas, with P. falciparum causing the greatest burden of disease. Increasing resistance of parasites and mosquitoes to existing tools, such as preventive antimalarial treatments and insecticide-treated bed nets respectively, is eroding the partial protection that they offer to pregnant women. Thus, development of effective vaccines against malaria during pregnancy is an urgent priority. Relevant animal models that recapitulate key features of the pathophysiology and immunology of malaria in pregnant women could be used to accelerate vaccine development. This review summarizes available rodent and nonhuman primate models of malaria in pregnancy, and discusses their suitability for studies of biologics intended to prevent or treat malaria in this vulnerable population.

  4. Expanding the scope and relevance of health interventions: Moving beyond clinical trials and behavior change models

    Directory of Open Access Journals (Sweden)

    Khary K. Rigg

    2014-07-01

    Full Text Available An overemphasis on clinical trials and behavior change models has narrowed the knowledge base that can be used to design interventions. The overarching point is that the process of overanalyzing variables is impeding the process of gaining insight into the everyday experiences that shape how people define health and seek treatment. This claim is especially important to health decision-making and behavior change because subtle interpretations often influence the decisions that people make. This manuscript provides a critique of traditional approaches to developing health interventions, and theoretically justifies what and why changes are warranted. The limited scope of these models is also discussed, and an argument is made to adopt a strategy that includes the perceptions of people as necessary for understanding health and health-related decision-making. Three practical strategies are suggested to be used with the more standard approaches to assessing the effectiveness and relevance of health interventions.

  5. Impact relevance and usability of high resolution climate modeling and data

    Energy Technology Data Exchange (ETDEWEB)

    Arnott, James C. [Aspen Global Change Inst., Basalt, CO (United States)

    2016-10-30

    The Aspen Global Change Institute hosted a technical science workshop entitled, “Impact Relevance and Usability of High-Resolution Climate Modeling and Datasets,” on August 2-7, 2015 in Aspen, CO. Kate Calvin (Pacific Northwest National Laboratory), Andrew Jones (Lawrence Berkeley National Laboratory) and Jean-François Lamarque (NCAR) served as co-chairs for the workshop. The meeting included the participation of 29 scientists for a total of 145 participant days. Following the workshop, workshop co-chairs authored a meeting report published in Eos on April 27, 2016. Insights from the workshop directly contributed to the formation of a new DOE-supported project co-led by workshop co-chair Andy Jones. A subset of meeting participants continue to work on a publication on institutional innovations that can support the usability of high resolution modeling, among other sources of climate information.

  6. Short ensembles: An Efficient Method for Discerning Climate-relevant Sensitivities in Atmospheric General Circulation Models

    Energy Technology Data Exchange (ETDEWEB)

    Wan, Hui; Rasch, Philip J.; Zhang, Kai; Qian, Yun; Yan, Huiping; Zhao, Chun

    2014-09-08

    This paper explores the feasibility of an experimentation strategy for investigating sensitivities in fast components of atmospheric general circulation models. The basic idea is to replace the traditional serial-in-time long-term climate integrations by representative ensembles of shorter simulations. The key advantage of the proposed method lies in its efficiency: since fewer days of simulation are needed, the computational cost is less, and because individual realizations are independent and can be integrated simultaneously, the new dimension of parallelism can dramatically reduce the turnaround time in benchmark tests, sensitivities studies, and model tuning exercises. The strategy is not appropriate for exploring sensitivity of all model features, but it is very effective in many situations. Two examples are presented using the Community Atmosphere Model version 5. The first example demonstrates that the method is capable of characterizing the model cloud and precipitation sensitivity to time step length. A nudging technique is also applied to an additional set of simulations to help understand the contribution of physics-dynamics interaction to the detected time step sensitivity. In the second example, multiple empirical parameters related to cloud microphysics and aerosol lifecycle are perturbed simultaneously in order to explore which parameters have the largest impact on the simulated global mean top-of-atmosphere radiation balance. Results show that in both examples, short ensembles are able to correctly reproduce the main signals of model sensitivities revealed by traditional long-term climate simulations for fast processes in the climate system. The efficiency of the ensemble method makes it particularly useful for the development of high-resolution, costly and complex climate models.

  7. Clinical and Neurobiological Relevance of Current Animal Models of Autism Spectrum Disorders

    Science.gov (United States)

    Kim, Ki Chan; Gonzales, Edson Luck; Lázaro, María T.; Choi, Chang Soon; Bahn, Geon Ho; Yoo, Hee Jeong; Shin, Chan Young

    2016-01-01

    Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by social and communication impairments, as well as repetitive and restrictive behaviors. The phenotypic heterogeneity of ASD has made it overwhelmingly difficult to determine the exact etiology and pathophysiology underlying the core symptoms, which are often accompanied by comorbidities such as hyperactivity, seizures, and sensorimotor abnormalities. To our benefit, the advent of animal models has allowed us to assess and test diverse risk factors of ASD, both genetic and environmental, and measure their contribution to the manifestation of autistic symptoms. At a broader scale, rodent models have helped consolidate molecular pathways and unify the neurophysiological mechanisms underlying each one of the various etiologies. This approach will potentially enable the stratification of ASD into clinical, molecular, and neurophenotypic subgroups, further proving their translational utility. It is henceforth paramount to establish a common ground of mechanistic theories from complementing results in preclinical research. In this review, we cluster the ASD animal models into lesion and genetic models and further classify them based on the corresponding environmental, epigenetic and genetic factors. Finally, we summarize the symptoms and neuropathological highlights for each model and make critical comparisons that elucidate their clinical and neurobiological relevance. PMID:27133257

  8. Towards and Effective Financial Management: Relevance of Dividend Discount Model in Stock Price Valuation

    Directory of Open Access Journals (Sweden)

    Ana Mugoša

    2015-06-01

    Full Text Available The aim of this paper is to analyze the relevance of dividend discount model, i.e. its specific form in stock price estimation known as Gordon growth model. The expected dividends can be a measure of cash flows returned to the stockholder. In this context, the model is useful for assessment of how risk factors, such as interest rates and changing inflation rates, affect stock returns. This is especially important in case when investors are value oriented, i.e. when expected dividends are theirmain investing drivers. We compared the estimated with the actual stock price values and tested the statistical significance of price differences in 199 publicly traded European companies for the period2010-2013. Statistical difference between pairs of price series (actual and estimated was tested using Wilcoxon and Kruskal-Wallis tests of median and distribution equality. The hypothesis that Gordon growth model cannot be reliable measure of stock price valuation on European equity market over period of 2010-2013 due to influence of the global financial crisis was rejected with 95% confidence. Gordon growth model has proven to be reliable measure of stock price valuation even over period of strong global financial crisis influence.

  9. Canine intrahepatic vasculature: is a functional anatomic model relevant to the dog?

    Science.gov (United States)

    Hall, Jon L; Mannion, Paddy; Ladlow, Jane F

    2015-01-01

    To clarify canine intrahepatic portal and hepatic venous system anatomy using corrosion casting and advanced imaging and to devise a novel functional anatomic model of the canine liver to investigate whether this could help guide the planning and surgical procedure of partial hepatic lobectomy and interventional radiological procedures. Prospective experimental study. Adult Greyhound cadavers (n = 8). Portal and hepatic vein corrosion casts of healthy livers were assessed using computed tomography (CT). The hepatic lobes have a consistent hilar hepatic and portal vein supply with some variation in the number of intrahepatic branches. For all specimens, 3 surgically resectable areas were identified in the left lateral lobe and 2 surgically resectable areas were identified in the right medial lobe as defined by a functional anatomic model. CT of detailed acrylic casts allowed complex intrahepatic vascular relationships to be investigated and compared with previous studies. Improving understanding of the intrahepatic vascular supply facilitates interpretation of advanced images in clinical patients, the planning and performance of surgical procedures, and may facilitate interventional vascular procedures, such as intravenous embolization of portosystemic shunts. Functional division of the canine liver similar to human models is possible. The left lateral and right medial lobes can be consistently divided into surgically resectable functional areas and partial lobectomies can be performed following a functional model; further study in clinically affected animals would be required to investigate the relevance of this functional model in the dog. © Copyright 2014 by The American College of Veterinary Surgeons.

  10. 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.

  11. Regional and global modeling estimates of policy relevant background ozone over the United States

    Science.gov (United States)

    Emery, Christopher; Jung, Jaegun; Downey, Nicole; Johnson, Jeremiah; Jimenez, Michele; Yarwood, Greg; Morris, Ralph

    2012-02-01

    Policy Relevant Background (PRB) ozone, as defined by the US Environmental Protection Agency (EPA), refers to ozone concentrations that would occur in the absence of all North American anthropogenic emissions. PRB enters into the calculation of health risk benefits, and as the US ozone standard approaches background levels, PRB is increasingly important in determining the feasibility and cost of compliance. As PRB is a hypothetical construct, modeling is a necessary tool. Since 2006 EPA has relied on global modeling to establish PRB for their regulatory analyses. Recent assessments with higher resolution global models exhibit improved agreement with remote observations and modest upward shifts in PRB estimates. This paper shifts the paradigm to a regional model (CAMx) run at 12 km resolution, for which North American boundary conditions were provided by a low-resolution version of the GEOS-Chem global model. We conducted a comprehensive model inter-comparison, from which we elucidate differences in predictive performance against ozone observations and differences in temporal and spatial background variability over the US. In general, CAMx performed better in replicating observations at remote monitoring sites, and performance remained better at higher concentrations. While spring and summer mean PRB predicted by GEOS-Chem ranged 20-45 ppb, CAMx predicted PRB ranged 25-50 ppb and reached well over 60 ppb in the west due to event-oriented phenomena such as stratospheric intrusion and wildfires. CAMx showed a higher correlation between modeled PRB and total observed ozone, which is significant for health risk assessments. A case study during April 2006 suggests that stratospheric exchange of ozone is underestimated in both models on an event basis. We conclude that wildfires, lightning NO x and stratospheric intrusions contribute a significant level of uncertainty in estimating PRB, and that PRB will require careful consideration in the ozone standard setting process.

  12. Importance and variability in processes relevant to environmental tritium ingestion dose models

    International Nuclear Information System (INIS)

    Raskob, W.; Barry, P.

    1997-01-01

    The Aiken List was devised in 1990 to help decide which transport processes should be investigated experimentally so as to derive the greatest improvement in performance of environmental tritium assessment models. Each process was rated high, medium and low on each of two criteria. These were ''Importance'', which rated processes by how much each contributed to ingestion doses, and ''State of Modelling'', which rated the adequacy of the knowledge base on which models were built. Ratings, though unanimous, were, nevertheless, qualitative and subjective opinions. This paper describes how we have tried to quantify the ratings. To do this, we use, as measures of ''Importance'', sensitivities of predicted ingestion doses to changes in values of parameters in mathematical descriptions of individual processes. Measures of ''ModellinStatus'' were taken from a recently completed BIOMOVS study of HTO transport model performance and based either on by how much predicted transport by individual processes differed amongst participating modellers or by the variety of different ways that modellers chose to describe individual processes. The tritium transport model UFOTRI was used, and because environmental transport of HTO varies according to the weather at and after release time, sensitivities were measured in a sample of all conditions likely to arise in central Europe. (Author)

  13. 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

  14. An improved robust model predictive control for linear parameter-varying input-output models

    NARCIS (Netherlands)

    Abbas, H.S.; Hanema, J.; Tóth, R.; Mohammadpour, J.; Meskin, N.

    2018-01-01

    This paper describes a new robust model predictive control (MPC) scheme to control the discrete-time linear parameter-varying input-output models subject to input and output constraints. Closed-loop asymptotic stability is guaranteed by including a quadratic terminal cost and an ellipsoidal terminal

  15. 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.

  16. Towards Measures to Establish the Relevance of Climate Model Output for Decision Support

    Science.gov (United States)

    Clarke, L.; Smith, L. A.

    2007-12-01

    How exactly can decision-support and policy making benefit from the use of multiple climate model experiments in terms of coping with the uncertainties on climate change projections? Climate modelling faces challenges beyond those of weather forecasting or even seasonal forecasting, as with climate we are now (and will probably always be) required to extrapolate to regimes in which we have no relevant forecast-verification archive. This suggests a very different approach from traditional methods of mixing models and skill based weighting to gain profitable probabilistic information when a large forecast-verification archive is in hand. In the case of climate, it may prove more rational to search for agreement between our models (in distribution), the aim being to determine the space and timescales on which, given our current understanding, the details of the simulation models are unimportant. This suggestion and others from Smith (2002, Proc. National Acad. Sci. USA 4 (99): 2487-2492) are interpreted in the light of recent advances. Climate models are large nonlinear dynamical systems which insightfully but imperfectly reflect the evolving weather patterns of the Earth. Their use in policy making and decision support assumes both that they contain sufficient information regarding reality to inform the decision, and that this information can be effectively communicated to the decision makers. There is nothing unique about climate modeling and these constraints, they apply in all cases where scientific modeling is applied to real-word actions (other than, perhaps, the action of improving our models). Starting with the issue of communication, figures from the 2007 IPCC Summary for Policy Makers will be constructively criticized from the perspective of decision makers, specifically those of the energy sector and the insurance/reinsurance sector. More information on basic questions of reliability and robustness would be of significant value when determining how heavily

  17. Parameter and State Estimator for State Space Models

    Directory of Open Access Journals (Sweden)

    Ruifeng Ding

    2014-01-01

    Full Text Available This paper proposes a parameter and state estimator for canonical state space systems from measured input-output data. The key is to solve the system state from the state equation and to substitute it into the output equation, eliminating the state variables, and the resulting equation contains only the system inputs and outputs, and to derive a least squares parameter identification algorithm. Furthermore, the system states are computed from the estimated parameters and the input-output data. Convergence analysis using the martingale convergence theorem indicates that the parameter estimates converge to their true values. Finally, an illustrative example is provided to show that the proposed algorithm is effective.

  18. Assessment of input function distortions on kinetic model parameters in simulated dynamic 82Rb PET perfusion studies

    International Nuclear Information System (INIS)

    Meyer, Carsten; Peligrad, Dragos-Nicolae; Weibrecht, Martin

    2007-01-01

    Cardiac 82 rubidium dynamic PET studies allow quantifying absolute myocardial perfusion by using tracer kinetic modeling. Here, the accurate measurement of the input function, i.e. the tracer concentration in blood plasma, is a major challenge. This measurement is deteriorated by inappropriate temporal sampling, spillover, etc. Such effects may influence the measured input peak value and the measured blood pool clearance. The aim of our study is to evaluate the effect of input function distortions on the myocardial perfusion as estimated by the model. To this end, we simulate noise-free myocardium time activity curves (TACs) with a two-compartment kinetic model. The input function to the model is a generic analytical function. Distortions of this function have been introduced by varying its parameters. Using the distorted input function, the compartment model has been fitted to the simulated myocardium TAC. This analysis has been performed for various sets of model parameters covering a physiologically relevant range. The evaluation shows that ±10% error in the input peak value can easily lead to ±10-25% error in the model parameter K 1 , which relates to myocardial perfusion. Variations in the input function tail are generally less relevant. We conclude that an accurate estimation especially of the plasma input peak is crucial for a reliable kinetic analysis and blood flow estimation

  19. 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.

  20. 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.

  1. From research excellence to brand relevance: A model for higher education reputation building

    Directory of Open Access Journals (Sweden)

    Nina Overton-de Klerk

    2016-05-01

    Full Text Available In this article we propose a novel approach to reputation development at higher education institutions. Global reputation development at higher education institutions is largely driven by research excellence, is predominantly measured by research output, and is predominantly reflected in hierarchical university rankings. The ranking becomes equated with brand equity. We argue that the current approach to reputation development in higher education institutions is modernist and linear. This is strangely out-of-kilter with the complexities of a transforming society in flux, the demands of a diversity of stakeholders, and the drive towards transdisciplinarity, laterality, reflexivity and relevance in science. Good research clearly remains an important ingredient of a university's brand value. However, a case can be made for brand relevance, co-created in collaboration with stakeholders, as an alternative and non-linear way of differentiation. This approach is appropriate in light of challenges in strategic science globally as well as trends and shifts in the emerging paradigm of strategic communication. In applying strategic communication principles to current trends and issues in strategic science and the communication thereof, an alternative model for strategic reputation building at higher education institutions is developed.

  2. Gene Expression Analysis to Assess the Relevance of Rodent Models to Human Lung Injury.

    Science.gov (United States)

    Sweeney, Timothy E; Lofgren, Shane; Khatri, Purvesh; Rogers, Angela J

    2017-08-01

    The relevance of animal models to human diseases is an area of intense scientific debate. The degree to which mouse models of lung injury recapitulate human lung injury has never been assessed. Integrating data from both human and animal expression studies allows for increased statistical power and identification of conserved differential gene expression across organisms and conditions. We sought comprehensive integration of gene expression data in experimental acute lung injury (ALI) in rodents compared with humans. We performed two separate gene expression multicohort analyses to determine differential gene expression in experimental animal and human lung injury. We used correlational and pathway analyses combined with external in vitro gene expression data to identify both potential drivers of underlying inflammation and therapeutic drug candidates. We identified 21 animal lung tissue datasets and three human lung injury bronchoalveolar lavage datasets. We show that the metasignatures of animal and human experimental ALI are significantly correlated despite these widely varying experimental conditions. The gene expression changes among mice and rats across diverse injury models (ozone, ventilator-induced lung injury, LPS) are significantly correlated with human models of lung injury (Pearson r = 0.33-0.45, P human lung injury. Predicted therapeutic targets, peptide ligand signatures, and pathway analyses are also all highly overlapping. Gene expression changes are similar in animal and human experimental ALI, and provide several physiologic and therapeutic insights to the disease.

  3. Relevance of the Lin's and Host hydropedological models to predict grape yield and wine quality

    Directory of Open Access Journals (Sweden)

    E. A. C. Costantini

    2009-09-01

    Full Text Available The adoption of precision agriculture in viticulture could be greatly enhanced by the diffusion of straightforward and easy to be applied hydropedological models, able to predict the spatial variability of available soil water. The Lin's and Host hydropedological models were applied to standard soil series descriptions and hillslope position, to predict the distribution of hydrological functional units in two vineyard and their relevance for grape yield and wine quality. A three-years trial was carried out in Chianti (Central Italy on Sangiovese. The soils of the vineyards differentiated in structure, porosity and related hydropedological characteristics, as well as in salinity. Soil spatial variability was deeply affected by earth movement carried out before vine plantation. Six plots were selected in the different hydrological functional units of the two vineyards, that is, at summit, backslope and footslope morphological positions, to monitor soil hydrology, grape production and wine quality. Plot selection was based upon a cluster analysis of local slope, topographic wetness index (TWI, and cumulative moisture up to the root limiting layer, appreciated by means of a detailed combined geophysical survey. Water content, redox processes and temperature were monitored, as well as yield, phenological phases, and chemical analysis of grapes. The isotopic ratio δ13C was measured in the wine ethanol upon harvesting to evaluate the degree of stress suffered by vines. The grapes in each plot were collected for wine making in small barrels. The wines obtained were analysed and submitted to a blind organoleptic testing.

    The results demonstrated that the combined application of the two hydropedological models can be used for the prevision of the moisture status of soils cultivated with grape during summertime in Mediterranean climate. As correctly foreseen by the models, the amount of mean daily transpirable soil water (TSW during

  4. Uncertainty of Modal Parameters Estimated by ARMA Models

    DEFF Research Database (Denmark)

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

    In this paper the uncertainties of identified modal parameters such as eigenfrequencies and damping ratios are assessed. From the measured response of dynamic excited structures the modal parameters may be identified and provide important structural knowledge. However the uncertainty of the param...

  5. Recalibrating disease parameters for increasing realism in modeling epidemics in closed settings

    Directory of Open Access Journals (Sweden)

    Livio Bioglio

    2016-11-01

    Full Text Available Abstract Background The homogeneous mixing assumption is widely adopted in epidemic modelling for its parsimony and represents the building block of more complex approaches, including very detailed agent-based models. The latter assume homogeneous mixing within schools, workplaces and households, mostly for the lack of detailed information on human contact behaviour within these settings. The recent data availability on high-resolution face-to-face interactions makes it now possible to assess the goodness of this simplified scheme in reproducing relevant aspects of the infection dynamics. Methods We consider empirical contact networks gathered in different contexts, as well as synthetic data obtained through realistic models of contacts in structured populations. We perform stochastic spreading simulations on these contact networks and in populations of the same size under a homogeneous mixing hypothesis. We adjust the epidemiological parameters of the latter in order to fit the prevalence curve of the contact epidemic model. We quantify the agreement by comparing epidemic peak times, peak values, and epidemic sizes. Results Good approximations of the peak times and peak values are obtained with the homogeneous mixing approach, with a median relative difference smaller than 20 % in all cases investigated. Accuracy in reproducing the peak time depends on the setting under study, while for the peak value it is independent of the setting. Recalibration is found to be linear in the epidemic parameters used in the contact data simulations, showing changes across empirical settings but robustness across groups and population sizes. Conclusions An adequate rescaling of the epidemiological parameters can yield a good agreement between the epidemic curves obtained with a real contact network and a homogeneous mixing approach in a population of the same size. The use of such recalibrated homogeneous mixing approximations would enhance the accuracy and

  6. Parameters for the mathematical modelling of Clostridium difficile acquisition and transmission: a systematic review.

    Directory of Open Access Journals (Sweden)

    Eroboghene H Otete

    Full Text Available INTRODUCTION: Mathematical modelling of Clostridium difficile infection dynamics could contribute to the optimisation of strategies for its prevention and control. The objective of this systematic review was to summarise the available literature specifically identifying the quantitative parameters required for a compartmental mathematical model of Clostridium difficile transmission. METHODS: Six electronic healthcare databases were searched and all screening, data extraction and study quality assessments were undertaken in duplicate. Results were synthesised using a narrative approach. RESULTS: Fifty-four studies met the inclusion criteria. Reproduction numbers for hospital based epidemics were described in two studies with a range from 0.55 to 7. Two studies provided consistent data on incubation periods. For 62% of cases, symptoms occurred in less than 4 weeks (3-28 days after infection. Evidence on contact patterns was identified in four studies but with limited data reported for populating a mathematical model. Two studies, including one without clinically apparent donor-recipient pairs, provided information on serial intervals for household or ward contacts, showing transmission intervals of <1 week in ward based contacts compared to up to 2 months for household contacts. Eight studies reported recovery rates of between 75%-100% for patients who had been treated with either metronidazole or vancomycin. Forty-nine studies gave recurrence rates of between 3% and 49% but were limited by varying definitions of recurrence. No study was found which specifically reported force of infection or net reproduction numbers. CONCLUSIONS: There is currently scant literature overtly citing estimates of the parameters required to inform the quantitative modelling of Clostridium difficile transmission. Further high quality studies to investigate transmission parameters are required, including through review of published epidemiological studies where these

  7. Recalibrating disease parameters for increasing realism in modeling epidemics in closed settings.

    Science.gov (United States)

    Bioglio, Livio; Génois, Mathieu; Vestergaard, Christian L; Poletto, Chiara; Barrat, Alain; Colizza, Vittoria

    2016-11-14

    The homogeneous mixing assumption is widely adopted in epidemic modelling for its parsimony and represents the building block of more complex approaches, including very detailed agent-based models. The latter assume homogeneous mixing within schools, workplaces and households, mostly for the lack of detailed information on human contact behaviour within these settings. The recent data availability on high-resolution face-to-face interactions makes it now possible to assess the goodness of this simplified scheme in reproducing relevant aspects of the infection dynamics. We consider empirical contact networks gathered in different contexts, as well as synthetic data obtained through realistic models of contacts in structured populations. We perform stochastic spreading simulations on these contact networks and in populations of the same size under a homogeneous mixing hypothesis. We adjust the epidemiological parameters of the latter in order to fit the prevalence curve of the contact epidemic model. We quantify the agreement by comparing epidemic peak times, peak values, and epidemic sizes. Good approximations of the peak times and peak values are obtained with the homogeneous mixing approach, with a median relative difference smaller than 20 % in all cases investigated. Accuracy in reproducing the peak time depends on the setting under study, while for the peak value it is independent of the setting. Recalibration is found to be linear in the epidemic parameters used in the contact data simulations, showing changes across empirical settings but robustness across groups and population sizes. An adequate rescaling of the epidemiological parameters can yield a good agreement between the epidemic curves obtained with a real contact network and a homogeneous mixing approach in a population of the same size. The use of such recalibrated homogeneous mixing approximations would enhance the accuracy and realism of agent-based simulations and limit the intrinsic biases of

  8. Estimation of biological parameters of marine organisms using linear and nonlinear acoustic scattering model-based inversion methods.

    Science.gov (United States)

    Chu, Dezhang; Lawson, Gareth L; Wiebe, Peter H

    2016-05-01

    The linear inversion commonly used in fisheries and zooplankton acoustics assumes a constant inversion kernel and ignores the uncertainties associated with the shape and behavior of the scattering targets, as well as other relevant animal parameters. Here, errors of the linear inversion due to uncertainty associated with the inversion kernel are quantified. A scattering model-based nonlinear inversion method is presented that takes into account the nonlinearity of the inverse problem and is able to estimate simultaneously animal abundance and the parameters associated with the scattering model inherent to the kernel. It uses sophisticated scattering models to estimate first, the abundance, and second, the relevant shape and behavioral parameters of the target organisms. Numerical simulations demonstrate that the abundance, size, and behavior (tilt angle) parameters of marine animals (fish or zooplankton) can be accurately inferred from the inversion by using multi-frequency acoustic data. The influence of the singularity and uncertainty in the inversion kernel on the inversion results can be mitigated by examining the singular values for linear inverse problems and employing a non-linear inversion involving a scattering model-based kernel.

  9. Short ensembles: an efficient method for discerning climate-relevant sensitivities in atmospheric general circulation models

    Directory of Open Access Journals (Sweden)

    H. Wan

    2014-09-01

    Full Text Available This paper explores the feasibility of an experimentation strategy for investigating sensitivities in fast components of atmospheric general circulation models. The basic idea is to replace the traditional serial-in-time long-term climate integrations by representative ensembles of shorter simulations. The key advantage of the proposed method lies in its efficiency: since fewer days of simulation are needed, the computational cost is less, and because individual realizations are independent and can be integrated simultaneously, the new dimension of parallelism can dramatically reduce the turnaround time in benchmark tests, sensitivities studies, and model tuning exercises. The strategy is not appropriate for exploring sensitivity of all model features, but it is very effective in many situations. Two examples are presented using the Community Atmosphere Model, version 5. In the first example, the method is used to characterize sensitivities of the simulated clouds to time-step length. Results show that 3-day ensembles of 20 to 50 members are sufficient to reproduce the main signals revealed by traditional 5-year simulations. A nudging technique is applied to an additional set of simulations to help understand the contribution of physics–dynamics interaction to the detected time-step sensitivity. In the second example, multiple empirical parameters related to cloud microphysics and aerosol life cycle are perturbed simultaneously in order to find out which parameters have the largest impact on the simulated global mean top-of-atmosphere radiation balance. It turns out that 12-member ensembles of 10-day simulations are able to reveal the same sensitivities as seen in 4-year simulations performed in a previous study. In both cases, the ensemble method reduces the total computational time by a factor of about 15, and the turnaround time by a factor of several hundred. The efficiency of the method makes it particularly useful for the development of

  10. The big seven model of personality and its relevance to personality pathology.

    Science.gov (United States)

    Simms, Leonard J

    2007-02-01

    Proponents of the Big Seven model of personality have suggested that Positive Valence (PV) and Negative Valence (NV) are independent of the Big Five personality dimensions and may be particularly relevant to personality disorder. These hypotheses were tested with 403 undergraduates who completed a Big Seven measure and markers of the Big Five and personality pathology. Results revealed that PV and NV incrementally predicted personality pathology dimensions beyond those predicted by multiple markers of the Big Five. However, factor analyses suggested that PV and NV might be best understood as specific, maladaptive aspects of positive emotionality and low agreeableness, respectively, as opposed to independent factors of personality. Implications for the description of normal and abnormal personality are discussed.

  11. Mitochondrial metabolism in early neural fate and its relevance for neuronal disease modeling.

    Science.gov (United States)

    Lorenz, Carmen; Prigione, Alessandro

    2017-12-01

    Modulation of energy metabolism is emerging as a key aspect associated with cell fate transition. The establishment of a correct metabolic program is particularly relevant for neural cells given their high bioenergetic requirements. Accordingly, diseases of the nervous system commonly involve mitochondrial impairment. Recent studies in animals and in neural derivatives of human pluripotent stem cells (PSCs) highlighted the importance of mitochondrial metabolism for neural fate decisions in health and disease. The mitochondria-based metabolic program of early neurogenesis suggests that PSC-derived neural stem cells (NSCs) may be used for modeling neurological disorders. Understanding how metabolic programming is orchestrated during neural commitment may provide important information for the development of therapies against conditions affecting neural functions, including aging and mitochondrial disorders. Copyright © 2017. Published by Elsevier Ltd.

  12. Thermodynamic curvature for a two-parameter spin model with frustration.

    Science.gov (United States)

    Ruppeiner, George; Bellucci, Stefano

    2015-01-01

    Microscopic models of realistic thermodynamic systems usually involve a number of parameters, not all of equal macroscopic relevance. We examine a decorated (1+3) Ising spin chain containing two microscopic parameters: a stiff parameter K mediating the long-range interactions, and a sloppy J operating within local spin groups. We show that K dominates the macroscopic behavior, with varying J having only a weak effect, except in regions where J brings about transitions between phases through its conditioning of the local spin groups with which K interacts. We calculate the heat capacity C(H), the magnetic susceptibility χ(T), and the thermodynamic curvature R. For large |J/K|, we identify four magnetic phases: ferromagnetic, antiferromagnetic, and two ferrimagnetic, according to the signs of K and J. We argue that for characterizing these phases, the strongest picture is offered by the thermodynamic geometric invariant R, proportional to the correlation length ξ. This picture has correspondences to other cases, such as fluids.

  13. 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

  14. 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

  15. A Note on the Item Information Function of the Four-Parameter Logistic Model

    Science.gov (United States)

    Magis, David

    2013-01-01

    This article focuses on four-parameter logistic (4PL) model as an extension of the usual three-parameter logistic (3PL) model with an upper asymptote possibly different from 1. For a given item with fixed item parameters, Lord derived the value of the latent ability level that maximizes the item information function under the 3PL model. The…

  16. Estimation of Key Parameters of the Coupled Energy and Water Model by Assimilating Land Surface Data

    Science.gov (United States)

    Abdolghafoorian, A.; Farhadi, L.

    2017-12-01

    Accurate estimation of land surface heat and moisture fluxes, as well as root zone soil moisture, is crucial in various hydrological, meteorological, and agricultural applications. Field measurements of these fluxes are costly and cannot be readily scaled to large areas relevant to weather and climate studies. Therefore, there is a need for techniques to make quantitative estimates of heat and moisture fluxes using land surface state observations that are widely available from remote sensing across a range of scale. In this work, we applies the variational data assimilation approach to estimate land surface fluxes and soil moisture profile from the implicit information contained Land Surface Temperature (LST) and Soil Moisture (SM) (hereafter the VDA model). The VDA model is focused on the estimation of three key parameters: 1- neutral bulk heat transfer coefficient (CHN), 2- evaporative fraction from soil and canopy (EF), and 3- saturated hydraulic conductivity (Ksat). CHN and EF regulate the partitioning of available energy between sensible and latent heat fluxes. Ksat is one of the main parameters used in determining infiltration, runoff, groundwater recharge, and in simulating hydrological processes. In this study, a system of coupled parsimonious energy and water model will constrain the estimation of three unknown parameters in the VDA model. The profile of SM (LST) at multiple depths is estimated using moisture diffusion (heat diffusion) equation. In this study, the uncertainties of retrieved unknown parameters and fluxes are estimated from the inverse of Hesian matrix of cost function which is computed using the Lagrangian methodology. Analysis of uncertainty provides valuable information about the accuracy of estimated parameters and their correlation and guide the formulation of a well-posed estimation problem. The results of proposed algorithm are validated with a series of experiments using a synthetic data set generated by the simultaneous heat and

  17. 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).

  18. Relevance of the ICRP biokinetic model for dietary organically bound tritium

    International Nuclear Information System (INIS)

    Trivedi, A.

    1999-10-01

    Ingested dietary tritium can participate in metabolic processes, and become synthesized into organically bound tritium in the tissues and organs. The distribution and retention of the organically bound tritium throughout the body are much different than tritium in the body water. The International Commission on Radiological Protection (ICRP) Publication 56 (1989) has a biokinetic model to calculate dose from the ingestion of organically bound dietary tritium. The model predicts that the dose from the ingestion of organically bound dietary tritium is about 2.3 times higher than from the ingestion of the same activity of tritiated water. Under steady-state conditions, the calculated dose rate (using the first principle approach) from the ingestion of dietary organically bound tritium can be twice that from the ingestion of tritiated water. For an adult, the upper-bound dose estimate for the ingestion of dietary organically bound tritium is estimated to be close to 2.3 times higher than that of tritiated water. Therefore, given the uncertainty in the dose calculation with respect to the actual relevant dose, the ICRP biokinetic model for organically bound tritium is sufficient for dosimetry for adults. (author)

  19. Cadmium toxicity investigated at the physiological and biophysical levels under environmentally relevant conditions using the aquatic model plant Ceratophyllum demersum

    DEFF Research Database (Denmark)

    Andresen, Elisa; Kappel, Sophie; Stärk, Hans-Joachim

    2016-01-01

    Cadmium (Cd) is an important environmental pollutant and is poisonous to most organisms. We aimed to unravel the mechanisms of Cd toxicity in the model water plant Ceratophyllum demersum exposed to low (nM) concentrations of Cd as are present in nature. Experiments were conducted under environmen......Cadmium (Cd) is an important environmental pollutant and is poisonous to most organisms. We aimed to unravel the mechanisms of Cd toxicity in the model water plant Ceratophyllum demersum exposed to low (nM) concentrations of Cd as are present in nature. Experiments were conducted under...... environmentally relevant conditions, including nature-like light and temperature cycles, and a low biomass to water ratio. We measured chlorophyll (Chl) fluorescence kinetics, oxygen exchange, the concentrations of reactive oxygen species and pigments, metal binding to proteins, and the accumulation of starch...... and metals. The inhibition threshold concentration for most parameters was 20 nM. Below this concentration, hardly any stress symptoms were observed. The first site of inhibition was photosynthetic light reactions (the maximal quantum yield of photosystem II (PSII) reaction centre measured as Fv /Fm , light...

  20. Isolated working heart: description of models relevant to radioisotopic and pharmacological assessments

    International Nuclear Information System (INIS)

    Depre, Christophe

    1998-01-01

    Isolated heart preparations are used to study physiological and metabolic parameters of the heart independently of its environment. Several preparations of isolated perfused heart are currently used, mainly the retrograde perfusion system and the working heart model. Both models allow investigations of the metabolic regulation of the heart in various physiological conditions (changes in workload, hormonal influences, substrate competition). These systems may also reproduce different pathological conditions, such as ischemia, reperfusion and hypoxia. Quantitation of metabolic activity can be performed with specific radioactive tracers. Finally, the effects of various drugs on cardiac performance and resistance to ischemia can be studied as well. Heart perfusion also revealed efficient methods to determine the tracer/tracee relation for radioisotopic analogues used with Positron Emission Tomography

  1. MODEL JARINGAN SYARAF TIRUAN UNTUK MEMPREDIKSI PARAMETER KUALITAS TOMAT BERDASARKAN PARAMETER WARNA RGB (An artificial neural network model for predicting tomato quality parameters based on color

    Directory of Open Access Journals (Sweden)

    Rudiati Evi Masithoh

    2013-03-01

    Full Text Available Artificial neural networks (ANN was used to predict the quality parameters of tomato, i.e. Brix, citric acid, total carotene, and vitamin C. ANN was developed from Red Green Blue (RGB image data of tomatoes measured using a developed computer vision system (CVS. Qualitative analysis of tomato compositions were obtained from laboratory experiments. ANN model was based on a feedforward backpropagation network with different training functions, namely gradient descent (traingd, gradient descent with the resilient backpropagation (trainrp, Broyden, Fletcher, Goldfrab and Shanno (BFGS quasi-Newton (trainbfg, as well as Levenberg Marquardt (trainlm.  The network structure using logsig and linear (purelin activation function at the hidden and output layer, respectively, and using  the trainlm as a training function resulted in the best performance. Correlation coefficient (r of training and validation process were 0.97 - 0.99 and 0.92 - 0.99, whereas the MAE values ​​ranged from 0.01 to 0.23 and 0.03 to 0.59, respectively. Keywords: Artificial neural network, trainlm, tomato, RGB   Jaringan syaraf tiruan (JST digunakan untuk memprediksi parameter kualitas tomat, yaitu Brix, asam sitrat, karoten total, dan vitamin C. JST dikembangkan dari data Red Green Blue (RGB  citra tomat yang diukur menggunakan computer vision system. Data kualitas tomat diperoleh dari analisis di laboratorium. Struktur model JST didasarkan pada jaringan feedforward backpropagation dengan berbagai fungsi pelatihan, yaitu gradient descent (traingd, gradient descent dengan resilient backpropagation (trainrp, Broyden, Fletcher, Goldfrab dan Shanno (BFGS quasi-Newton (trainbfg, serta Levenberg Marquardt (trainlm. Fungsi pelatihan yang terbaik adalah menggunakan trainlm, serta pada struktur jaringan digunakan fungsi aktivasi logsig pada lapisan tersembunyi dan linier (purelin pada lapisan keluaran. dengan 1000 epoch. Nilai koefisien korelasi (r pada tahap pelatihan dan validasi

  2. Connecting Global to Local Parameters in Barred Galaxy Models

    Indian Academy of Sciences (India)

    R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

    Key words. Galaxies: barred—orbits—global and local parameters. .... series near the stable Lagrange point L1, which coincides with the origin. Doing so, .... Toomre, A. 1981, In: The Structure and Evolution of Normal Galaxies, (eds) S. M. Fall,.

  3. Checking the new IRI model: The bottomside B parameters

    International Nuclear Information System (INIS)

    Mosert, M.; Buresova, D.; Miro, G.; Lazo, B.; Ezquer, R.

    2003-01-01

    Electron density profiles obtained at Pruhonice (50.0, 15.0), El Arenosillo (37.1, 353.2) and Havana (23, 278) were used to check the bottom-side B parameters BO (thickness parameter) and B1 (shape parameter) predicted by the new IRI - 2000 version. The electron density profiles were derived from ionograms using the ARP technique. The data base includes daytime and nighttime ionograms recorded under different seasonal and solar activity conditions. Comparisons with IRI predictions were also done. The analysis shows that: a) The parameter B1 given by IRI 2000 reproduces better the observed ARP values than the IRI-90 version and b) The observed BO values are in general well reproduced by both IRI versions: IRI-90 and IRI-2000. (author)

  4. Checking the new IRI model The bottomside B parameters

    CERN Document Server

    Mosert, M; Ezquer, R; Lazo, B; Miro, G

    2002-01-01

    Electron density profiles obtained at Pruhonice (50.0, 15.0), El Arenosillo (37.1, 353.2) and Havana (23, 278) were used to check the bottom-side B parameters BO (thickness parameter) and B1 (shape parameter) predicted by the new IRI - 2000 version. The electron density profiles were derived from ionograms using the ARP technique. The data base includes daytime and nighttime ionograms recorded under different seasonal and solar activity conditions. Comparisons with IRI predictions were also done. The analysis shows that: a) The parameter B1 given by IRI 2000 reproduces better the observed ARP values than the IRI-90 version and b) The observed BO values are in general well reproduced by both IRI versions: IRI-90 and IRI-2000.

  5. Multi-scale modeling of diffusion-controlled reactions in polymers: renormalisation of reactivity parameters.

    Science.gov (United States)

    Everaers, Ralf; Rosa, Angelo

    2012-01-07

    The quantitative description of polymeric systems requires hierarchical modeling schemes, which bridge the gap between the atomic scale, relevant to chemical or biomolecular reactions, and the macromolecular scale, where the longest relaxation modes occur. Here, we use the formalism for diffusion-controlled reactions in polymers developed by Wilemski, Fixman, and Doi to discuss the renormalisation of the reactivity parameters in polymer models with varying spatial resolution. In particular, we show that the adjustments are independent of chain length. As a consequence, it is possible to match reactions times between descriptions with different resolution for relatively short reference chains and to use the coarse-grained model to make quantitative predictions for longer chains. We illustrate our results by a detailed discussion of the classical problem of chain cyclization in the Rouse model, which offers the simplest example of a multi-scale descriptions, if we consider differently discretized Rouse models for the same physical system. Moreover, we are able to explore different combinations of compact and non-compact diffusion in the local and large-scale dynamics by varying the embedding dimension.

  6. Using genetic algorithms to calibrate the user-defined parameters of IIST model for SBLOCA analysis

    International Nuclear Information System (INIS)

    Tsai, Chiung-Wen; Shih, Chunkuan; Wang, Jong-Rong

    2014-01-01

    Highlights: • The genetic algorithm is proposed to search the user-defined parameters of important correlations. • The TRACE IIST model was employed as a case study to demonstrate the capability of GAs. • The multi-objective optimization strategy was incorporated to evaluate multi objective functions simultaneously. - Abstract: The thermal–hydraulic system codes, i.e., TRACE, have been designed to predict, investigate, and simulate nuclear reactor transients and accidents. Implementing relevant correlations, these codes are able to represent important phenomena such as two-phase flow, critical flow, and countercurrent flow. Furthermore, the thermal–hydraulic system codes permit users to modify the coefficients corresponding to the correlations, providing a certain degree of freedom to calibrate the numerical results, i.e., peak cladding temperature. These coefficients are known as user-defined parameters (UDPs). Practically, defining a series of UDPs is complex, highly relied on expert opinions and engineering experiences. This study proposes another approach – the genetic algorithms (GAs), providing rigorous procedures and mitigating human judgments and mistakes, to calibrate the UDPs of important correlations for a 2% small break loss of coolant accident (SBLOCA). The TRACE IIST model was employed as a case study to demonstrate the capability of GAs. The UDPs were evolved by GAs to reduce the deviations between TRACE results and IIST experimental data

  7. Inventory parameters

    CERN Document Server

    Sharma, Sanjay

    2017-01-01

    This book provides a detailed overview of various parameters/factors involved in inventory analysis. It especially focuses on the assessment and modeling of basic inventory parameters, namely demand, procurement cost, cycle time, ordering cost, inventory carrying cost, inventory stock, stock out level, and stock out cost. In the context of economic lot size, it provides equations related to the optimum values. It also discusses why the optimum lot size and optimum total relevant cost are considered to be key decision variables, and uses numerous examples to explain each of these inventory parameters separately. Lastly, it provides detailed information on parameter estimation for different sectors/products. Written in a simple and lucid style, it offers a valuable resource for a broad readership, especially Master of Business Administration (MBA) students.

  8. The LXCat project: Electron scattering cross sections and swarm parameters for low temperature plasma modeling

    International Nuclear Information System (INIS)

    Pancheshnyi, S.; Biagi, S.; Bordage, M.C.; Hagelaar, G.J.M.; Morgan, W.L.; Phelps, A.V.; Pitchford, L.C.

    2012-01-01

    -wide effort aimed at collecting, evaluating, and sharing data relevant to modeling low temperature plasmas. To illustrate the utility of LXCat in this context, we compare electron swarm parameters in argon calculated using the different compilations of cross sections presently available on LXCat. These compilations include quite different groupings of excited states, yet lead to swarm parameters in good agreement. LXCat is available at (http://www.lxcat.laplace.univ-tlse.fr).

  9. Relevance of the c-statistic when evaluating risk-adjustment models in surgery.

    Science.gov (United States)

    Merkow, Ryan P; Hall, Bruce L; Cohen, Mark E; Dimick, Justin B; Wang, Edward; Chow, Warren B; Ko, Clifford Y; Bilimoria, Karl Y

    2012-05-01

    The measurement of hospital quality based on outcomes requires risk adjustment. The c-statistic is a popular tool used to judge model performance, but can be limited, particularly when evaluating specific operations in focused populations. Our objectives were to examine the interpretation and relevance of the c-statistic when used in models with increasingly similar case mix and to consider an alternative perspective on model calibration based on a graphical depiction of model fit. From the American College of Surgeons National Surgical Quality Improvement Program (2008-2009), patients were identified who underwent a general surgery procedure, and procedure groups were increasingly restricted: colorectal-all, colorectal-elective cases only, and colorectal-elective cancer cases only. Mortality and serious morbidity outcomes were evaluated using logistic regression-based risk adjustment, and model c-statistics and calibration curves were used to compare model performance. During the study period, 323,427 general, 47,605 colorectal-all, 39,860 colorectal-elective, and 21,680 colorectal cancer patients were studied. Mortality ranged from 1.0% in general surgery to 4.1% in the colorectal-all group, and serious morbidity ranged from 3.9% in general surgery to 12.4% in the colorectal-all procedural group. As case mix was restricted, c-statistics progressively declined from the general to the colorectal cancer surgery cohorts for both mortality and serious morbidity (mortality: 0.949 to 0.866; serious morbidity: 0.861 to 0.668). Calibration was evaluated graphically by examining predicted vs observed number of events over risk deciles. For both mortality and serious morbidity, there was no qualitative difference in calibration identified between the procedure groups. In the present study, we demonstrate how the c-statistic can become less informative and, in certain circumstances, can lead to incorrect model-based conclusions, as case mix is restricted and patients become

  10. Modelling of nonhomogeneous atmosphere in NPP containment using lumped-parameter model based on CFD calculations

    International Nuclear Information System (INIS)

    Ivo, Kljenak; Miroslav, Babic; Borut, Mavko

    2007-01-01

    The possibility of simulating adequately the flow circulation within a nuclear power plant containment using a lumped-parameter code is considered. An experiment on atmosphere mixing and stratification, which was performed in the containment experimental facility TOSQAN at IRSN (Institute of Radioprotection and Nuclear Safety) in Saclay (France), was simulated with the CFD (Computational Fluid Dynamics) code CFX4 and the lumped-parameter code CONTAIN. During some phases of the experiment, steady states were achieved by keeping the boundary conditions constant. Two steady states during which natural convection was the dominant gas flow mechanism were simulated independently. The nodalization of the lumped-parameter model was based on the flow pattern, simulated with the CFD code. The simulation with the lumped-parameter code predicted basically the same flow circulation patterns within the experimental vessel as the simulation with the CFD code did. (authors)

  11. Development of two phase turbulent mixing model for subchannel analysis relevant to BWR

    International Nuclear Information System (INIS)

    Sharma, M.P.; Nayak, A.K.; Kannan, Umasankari

    2014-01-01

    A two phase flow model is presented, which predicts both liquid and gas phase turbulent mixing rate between adjacent subchannels of reactor rod bundles. The model presented here is for slug churn flow regime, which is dominant as compared to the other regimes like bubbly flow and annular flow regimes, since turbulent mixing rate is the highest in slug churn flow regime. In this paper, we have defined new dimensionless parameters i.e. liquid mixing number and gas mixing number for two phase turbulent mixing. The liquid mixing number is a function of mixture Reynolds number whereas the gas phase mixing number is a function of both mixture Reynolds number and volumetric fraction of gas. The effect of pressure, geometrical influence of subchannel is also included in this model. The present model has been tested against low pressure and temperature air-water and high pressure and temperature steam-water experimental data found that it shows good agreement with available experimental data. (author)

  12. Quantifying the relevance of adaptive thermal comfort models in moderate thermal climate zones

    Energy Technology Data Exchange (ETDEWEB)

    Hoof, Joost van; Hensen, Jan L.M. [Faculty of Architecture, Building and Planning, Technische Universiteit Eindhoven, Vertigo 6.18, P.O. Box 513, 5600 MB Eindhoven (Netherlands)

    2007-01-15

    Standards governing thermal comfort evaluation are on a constant cycle of revision and public review. One of the main topics being discussed in the latest round was the introduction of an adaptive thermal comfort model, which now forms an optional part of ASHRAE Standard 55. Also on a national level, adaptive thermal comfort guidelines come into being, such as in the Netherlands. This paper discusses two implementations of the adaptive comfort model in terms of usability and energy use for moderate maritime climate zones by means of literature study, a case study comprising temperature measurements, and building performance simulation. It is concluded that for moderate climate zones the adaptive model is only applicable during summer months, and can reduce energy for naturally conditioned buildings. However, the adaptive thermal comfort model has very limited application potential for such climates. Additionally we suggest a temperature parameter with a gradual course to replace the mean monthly outdoor air temperature to avoid step changes in optimum comfort temperatures. (author)

  13. A conscious mouse model of gastric ileus using clinically relevant endpoints

    Directory of Open Access Journals (Sweden)

    Shao Yuanlin

    2005-06-01

    Full Text Available Abstract Background Gastric ileus is an unsolved clinical problem and current treatment is limited to supportive measures. Models of ileus using anesthetized animals, muscle strips or isolated smooth muscle cells do not adequately reproduce the clinical situation. Thus, previous studies using these techniques have not led to a clear understanding of the pathophysiology of ileus. The feasibility of using food intake and fecal output as simple, clinically relevant endpoints for monitoring ileus in a conscious mouse model was evaluated by assessing the severity and time course of various insults known to cause ileus. Methods Delayed food intake and fecal output associated with ileus was monitored after intraperitoneal injection of endotoxin, laparotomy with bowel manipulation, thermal injury or cerulein induced acute pancreatitis. The correlation of decreased food intake after endotoxin injection with gastric ileus was validated by measuring gastric emptying. The effect of endotoxin on general activity level and feeding behavior was also determined. Small bowel transit was measured using a phenol red marker. Results Each insult resulted in a transient and comparable decrease in food intake and fecal output consistent with the clinical picture of ileus. The endpoints were highly sensitive to small changes in low doses of endotoxin, the extent of bowel manipulation, and cerulein dose. The delay in food intake directly correlated with delayed gastric emptying. Changes in general activity and feeding behavior were insufficient to explain decreased food intake. Intestinal transit remained unchanged at the times measured. Conclusion Food intake and fecal output are sensitive markers of gastric dysfunction in four experimental models of ileus. In the mouse, delayed gastric emptying appears to be the major cause of the anorexic effect associated with ileus. Gastric dysfunction is more important than small bowel dysfunction in this model. Recovery of

  14. Differential Effectiveness of Clinically-Relevant Analgesics in a Rat Model of Chemotherapy-Induced Mucositis.

    Directory of Open Access Journals (Sweden)

    Alexandra L Whittaker

    Full Text Available Chemotherapy-induced intestinal mucositis is characterized by pain and a pro-inflammatory tissue response. Rat models are frequently used in mucositis disease investigations yet little is known about the presence of pain in these animals, the ability of analgesics to ameliorate the condition, or the effect that analgesic administration may have on study outcomes. This study investigated different classes of analgesics with the aim of determining their analgesic effects and impact on research outcomes of interest in a rat model of mucositis. Female DA rats were allocated to 8 groups to include saline and chemotherapy controls (n = 8. Analgesics included opioid derivatives (buprenorphine; 0.05mg/kg and tramadol 12.5mg/kg and NSAID (carprofen; 15mg/kg in combination with either saline or 5-Fluorouracil (5-FU; 150mg/kg. Research outcome measures included daily clinical parameters, pain score and gut histology. Myeloperoxidase assay was performed to determine gut inflammation. At the dosages employed, all agents had an analgesic effect based on behavioural pain scores. Jejunal myeloperoxidase activity was significantly reduced by buprenorphine and tramadol in comparison to 5-FU control animals (53%, p = 0.0004 and 58%, p = 0.0001. Carprofen had no ameliorating effect on myeloperoxidase levels. None of the agents reduced the histological damage caused by 5-FU administration although tramadol tended to increase villus length even when administered to healthy animals. These data provide evidence that carprofen offers potential as an analgesic in this animal model due to its pain-relieving efficacy and minimal effect on measured parameters. This study also supports further investigation into the mechanism and utility of opioid agents in the treatment of chemotherapy-induced mucositis.

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

    Science.gov (United States)

    He, L; Huang, G H; Lu, H W

    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. 2009 Elsevier B.V. All rights reserved.

  16. 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.

  17. Translational relevance of rodent models of hypothalamic-pituitary-adrenal function and stressors in adolescence

    Directory of Open Access Journals (Sweden)

    Cheryl M. McCormick

    2017-02-01

    Full Text Available Elevations in glucocorticoids that result from environmental stressors can have programming effects on brain structure and function when the exposure occurs during sensitive periods that involve heightened neural development. In recent years, adolescence has gained increasing attention as another sensitive period of development, a period in which pubertal transitions may increase the vulnerability to stressors. There are similarities in physical and behavioural development between humans and rats, and rats have been used effectively as an animal model of adolescence and the unique plasticity of this period of ontogeny. This review focuses on benefits and challenges of rats as a model for translational research on hypothalamic-pituitary-adrenal (HPA function and stressors in adolescence, highlighting important parallels and contrasts between adolescent rats and humans, and we review the main stress procedures that are used in investigating HPA stress responses and their consequences in adolescence in rats. We conclude that a greater focus on timing of puberty as a factor in research in adolescent rats may increase the translational relevance of the findings.

  18. Upper Limb Immobilisation: A Neural Plasticity Model with Relevance to Poststroke Motor Rehabilitation

    Directory of Open Access Journals (Sweden)

    Leonardo Furlan

    2016-01-01

    Full Text Available Advances in our understanding of the neural plasticity that occurs after hemiparetic stroke have contributed to the formulation of theories of poststroke motor recovery. These theories, in turn, have underpinned contemporary motor rehabilitation strategies for treating motor deficits after stroke, such as upper limb hemiparesis. However, a relative drawback has been that, in general, these strategies are most compatible with the recovery profiles of relatively high-functioning stroke survivors and therefore do not easily translate into benefit to those individuals sustaining low-functioning upper limb hemiparesis, who otherwise have poorer residual function. For these individuals, alternative motor rehabilitation strategies are currently needed. In this paper, we will review upper limb immobilisation studies that have been conducted with healthy adult humans and animals. Then, we will discuss how the findings from these studies could inspire the creation of a neural plasticity model that is likely to be of particular relevance to the context of motor rehabilitation after stroke. For instance, as will be elaborated, such model could contribute to the development of alternative motor rehabilitation strategies for treating poststroke upper limb hemiparesis. The implications of the findings from those immobilisation studies for contemporary motor rehabilitation strategies will also be discussed and perspectives for future research in this arena will be provided as well.

  19. Modeling systems relevant to the biodiesel production using the CPA equation of state

    DEFF Research Database (Denmark)

    Tsivintzelis, Ioannis; Ali, Shahid; Kontogeorgis, Georgios

    2016-01-01

    In this study, CPA parameters for heavy esters, glycerides, organic acids, and glycerol are presented, together with trends of these parameters against the van der Waals volume. Such trends allow the prediction of parameters for compounds for which data are not available. Pure fluid parameters we...

  20. 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.

  1. New trends in parameter identification for mathematical models

    CERN Document Server

    Leitão, Antonio; Zubelli, Jorge

    2018-01-01

    The Proceedings volume contains 16 contributions to the IMPA conference “New Trends in Parameter Identification for Mathematical Models”, Rio de Janeiro, Oct 30 – Nov 3, 2017, integrating the “Chemnitz Symposium on Inverse Problems on Tour”.  This conference is part of the “Thematic Program on Parameter Identification in Mathematical Models” organized  at IMPA in October and November 2017. One goal is to foster the scientific collaboration between mathematicians and engineers from the Brazialian, European and Asian communities. Main topics are iterative and variational regularization methods in Hilbert and Banach spaces for the stable approximate solution of ill-posed inverse problems, novel methods for parameter identification in partial differential equations, problems of tomography ,  solution of coupled conduction-radiation problems at high temperatures, and the statistical solution of inverse problems with applications in physics.

  2. Models of Stress in Nonhuman Primates and Their Relevance for Human Psychopathology and Endocrine Dysfunction

    Science.gov (United States)

    Meyer, Jerrold S.; Hamel, Amanda F.

    2014-01-01

    Stressful life events have been linked to the onset of severe psychopathology and endocrine dysfunction in many patients. Moreover, vulnerability to the later development of such disorders can be increased by stress or adversity during development (e.g., childhood neglect, abuse, or trauma). This review discusses the methodological features and results of various models of stress in nonhuman primates in the context of their potential relevance for human psychopathology and endocrine dysfunction, particularly mood disorders and dysregulation of the hypothalamic-pituitary-adrenocortical (HPA) system. Such models have typically examined the effects of stress on the animals' behavior, endocrine function (primarily the HPA and hypothalamic-pituitary-gonadal systems), and, in some cases, immune status. Manipulations such as relocation and/or removal of an animal from its current social group or, alternatively, formation of a new social group can have adverse effects on all of these outcome measures that may be either transient or more persistent depending on the species, sex, and other experimental conditions. Social primates may also experience significant stress associated with their rank in the group's dominance hierarchy. Finally, stress during prenatal development or during the early postnatal period may have long-lasting neurobiological and endocrine effects that manifest in an altered ability to cope behaviorally and physiologically with later challenges. Whereas early exposure to severe stress usually results in deficient coping abilities, certain kinds of milder stressors can promote subsequent resilience in the animal. We conclude that studies of stress in nonhuman primates can model many features of stress exposure in human populations and that such studies can play a valuable role in helping to elucidate the mechanisms underlying the role of stress in human psychopathology and endocrine dysfunction. PMID:25225311

  3. Models of stress in nonhuman primates and their relevance for human psychopathology and endocrine dysfunction.

    Science.gov (United States)

    Meyer, Jerrold S; Hamel, Amanda F

    2014-01-01

    Stressful life events have been linked to the onset of severe psychopathology and endocrine dysfunction in many patients. Moreover, vulnerability to the later development of such disorders can be increased by stress or adversity during development (e.g., childhood neglect, abuse, or trauma). This review discusses the methodological features and results of various models of stress in nonhuman primates in the context of their potential relevance for human psychopathology and endocrine dysfunction, particularly mood disorders and dysregulation of the hypothalamic-pituitary-adrenocortical (HPA) system. Such models have typically examined the effects of stress on the animals' behavior, endocrine function (primarily the HPA and hypothalamic-pituitary-gonadal systems), and, in some cases, immune status. Manipulations such as relocation and/or removal of an animal from its current social group or, alternatively, formation of a new social group can have adverse effects on all of these outcome measures that may be either transient or more persistent depending on the species, sex, and other experimental conditions. Social primates may also experience significant stress associated with their rank in the group's dominance hierarchy. Finally, stress during prenatal development or during the early postnatal period may have long-lasting neurobiological and endocrine effects that manifest in an altered ability to cope behaviorally and physiologically with later challenges. Whereas early exposure to severe stress usually results in deficient coping abilities, certain kinds of milder stressors can promote subsequent resilience in the animal. We conclude that studies of stress in nonhuman primates can model many features of stress exposure in human populations and that such studies can play a valuable role in helping to elucidate the mechanisms underlying the role of stress in human psychopathology and endocrine dysfunction. © The Author 2014. Published by Oxford University Press on

  4. Retrieval-time properties of the Little-Hopfield model and their physiological relevance

    International Nuclear Information System (INIS)

    Risau-Gusman, Sebastian; Idiart, Marco A.P.

    2005-01-01

    We perform an extensive numerical investigation on the retrieval dynamics of the synchronous Hopfield model, also known as Little-Hopfield model, up to sizes of 2 18 neurons. Our results correct and extend much of the early simulations on the model. We find that the average convergence time has a power law behavior for a wide range of system sizes, whose exponent depends both on the network loading and the initial overlap with the memory to be retrieved. Surprisingly, we also find that the variance of the convergence time grows as fast as its average, making it a non-self-averaging quantity. Based on the simulation data we differentiate between two definitions for memory retrieval time, one that is mathematically strict, τ c , the number of updates needed to reach the attractor whose properties we just described, and a second definition correspondent to the time τ η when the network stabilizes within a tolerance threshold η such that the difference of two consecutive overlaps with a stored memory is smaller that η. We show that the scaling relationships between τ c and τ η and the typical network parameters as the memory load α or the size of the network N vary greatly, being τ η relatively insensitive to system sizes and loading. We propose τ η as the physiological realistic measure for the typical attractor network response

  5. Measurement of track opening contours of oblique incident 4He and 7Li-ions in CR-39: Relevance for calculation of track formation parameters

    International Nuclear Information System (INIS)

    Hermsdorf, D.; Reichelt, U.

    2010-01-01

    Solid State Nuclear Track Detectors (SSNTD) irradiated in realistic radiation fields exhibits after chemical etching very complex track images resulting from different species of particles and their energy spectra and randomly distributed angles of incidence or emission. Reading out such an etched detector surface with a light microscope, quite different track opening contours are observed. Beside the number of tracks, typically their major and minor axes are measured. In this work following problems arising from such experimental situations will be investigated: ·the measurement of track contour parameters for oblique incident 4 He and 7 Li-ions of different energies and angles in CR-39 detectors ·the theoretical description of the angular variation of both axes. ·the possibility to extract physical and spectroscopic information from major and minor track axes. This analysis is based on an intensive experimental program and the comprehensive study of theoretical models available for description of track revealing processes in CR-39.

  6. 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.

  7. 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.

  8. Importance of hydrological parameters in contaminant transport modeling in a terrestrial environment

    International Nuclear Information System (INIS)

    Tsuduki, Katsunori; Matsunaga, Takeshi

    2007-01-01

    A grid type multi-layered distributed parameter model for calculating discharge in a watershed was described. Model verification with our field observation resulted in different sets of hydrological parameter values, all of which reproduced the observed discharge. The effect of those varied hydrological parameters on contaminant transport calculation was examined and discussed by simulation of event water transfer. (author)

  9. Cognitive Models of Risky Choice: Parameter Stability and Predictive Accuracy of Prospect Theory

    Science.gov (United States)

    Glockner, Andreas; Pachur, Thorsten

    2012-01-01

    In the behavioral sciences, a popular approach to describe and predict behavior is cognitive modeling with adjustable parameters (i.e., which can be fitted to data). Modeling with adjustable parameters allows, among other things, measuring differences between people. At the same time, parameter estimation also bears the risk of overfitting. Are…

  10. Maintaining the clinical relevance of animal models in translational studies of post-traumatic stress disorder.

    Science.gov (United States)

    Cohen, Hagit; Matar, Michael A; Zohar, Joseph

    2014-01-01

    The diagnosis of Post-Traumatic Stress Disorder (PTSD) is conditional on directly experiencing or witnessing a significantly threatening event and the presence of a certain minimal number of symptoms from each of four symptom clusters (re-experiencing, avoidance, negative cognition and mood, and hyperarousal) at least one month after the event (DSM 5) (American Psychiatric Association 2013). Only a proportion of the population exposed develops symptoms fulfilling the criteria. The individual heterogeneity in responses of stress-exposed animals suggested that adapting clearly defined and reliably reproducible "diagnostic", i.e. behavioral, criteria for animal responses would augment the clinical validity of the analysis of study data. We designed cut-off (inclusion/exclusion) behavioral criteria (CBC) which classify study subjects as being severely, minimally or partially affected by the stress paradigm, to be applied retrospectively in the analysis of behavioral data. Behavioral response classification enables the researcher to correlate (retrospectively) specific anatomic, bio-molecular and physiological parameters with the degree and pattern of the individual behavioral response, and also introduces "prevalence rates" as a valid study-parameter. The cumulative results of our studies indicate that, by classifying the data from individual subjects according to their response patterns, the animal study can more readily be translated into clinical "follow-up" studies and back again. This article will discuss the concept of the model and its background, and present a selection of studies employing and examining the model, alongside the underlying translational rationale of each. © The Author 2014. Published by Oxford University Press on behalf of the Institute for Laboratory Animal Research. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  11. Parameter Selection and Performance Analysis of Mobile Terminal Models Based on Unity3D

    Institute of Scientific and Technical Information of China (English)

    KONG Li-feng; ZHAO Hai-ying; XU Guang-mei

    2014-01-01

    Mobile platform is now widely seen as a promising multimedia service with a favorable user group and market prospect. To study the influence of mobile terminal models on the quality of scene roaming, a parameter setting platform of mobile terminal models is established to select the parameter selection and performance index on different mobile platforms in this paper. This test platform is established based on model optimality principle, analyzing the performance curve of mobile terminals in different scene models and then deducing the external parameter of model establishment. Simulation results prove that the established test platform is able to analyze the parameter and performance matching list of a mobile terminal model.

  12. Lumped Parameter Modeling for Rapid Vibration Response Prototyping and Test Correlation for Electronic Units

    Science.gov (United States)

    Van Dyke, Michael B.

    2013-01-01

    Present preliminary work using lumped parameter models to approximate dynamic response of electronic units to random vibration; Derive a general N-DOF model for application to electronic units; Illustrate parametric influence of model parameters; Implication of coupled dynamics for unit/board design; Demonstrate use of model to infer printed wiring board (PWB) dynamics from external chassis test measurement.

  13. MODELING OF THE BASIC PARAMETERS OF ECONOMIC STABILITY (BY THE EXAMPLE OF JSC “BOGUCHAROVO”

    Directory of Open Access Journals (Sweden)

    N. A. Serebriakova

    2014-01-01

    Full Text Available Summary. The article describes the author's vision of the process of management of economic stability of the enterprise by means of simulation of the main parameters of its activity and justified the relevance of the theme of the study. Studied theoretical and methodical bases of economic stability of the enterprise in accordance with the Russian development of a market economy, as well as practical recommendations on modeling of the main parameters of the economic sustainability of the organization. Currently, management of economic stability is one of the most important factors of functioning and development of the enterprises in conditions of the global financial crisis. The relevance of this trend is increasing in line with the increasing complexity of economic ties, changing external environment. A comprehensive approach to the development of the most appropriate variants of the mechanism of management of economic sustainability taking into account the experience of developed countries, industry and sector of factors of external environment can become the basis for developing a common long-term economic development strategy of the enterprise. Problems of economic stability of enterprises caused by the fact that normally carried out in a changing environment operational measures allow for a short time to keep the state of the enterprise is stable, but not change the situation radically. That is, they are associated, on the one hand, with a lack of vision of development of the enterprises, with another - the narrowness of the approach applied to the diagnosis of the existing situation and forecasting of changes in external factors.

  14. 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...

  15. Biologically effective dose distribution based on the linear quadratic model and its clinical relevance

    International Nuclear Information System (INIS)

    Lee, Steve P.; Leu, Min Y.; Smathers, James B.; McBride, William H.; Parker, Robert G.; Withers, H. Rodney

    1995-01-01

    Purpose: Radiotherapy plans based on physical dose distributions do not necessarily entirely reflect the biological effects under various fractionation schemes. Over the past decade, the linear-quadratic (LQ) model has emerged as a convenient tool to quantify biological effects for radiotherapy. In this work, we set out to construct a mechanism to display biologically oriented dose distribution based on the LQ model. Methods and Materials: A computer program that converts a physical dose distribution calculated by a commercially available treatment planning system to a biologically effective dose (BED) distribution has been developed and verified against theoretical calculations. This software accepts a user's input of biological parameters for each structure of interest (linear and quadratic dose-response and repopulation kinetic parameters), as well as treatment scheme factors (number of fractions, fractional dose, and treatment time). It then presents a two-dimensional BED display in conjunction with anatomical structures. Furthermore, to facilitate clinicians' intuitive comparison with conventional fractionation regimen, a conversion of BED to normalized isoeffective dose (NID) is also allowed. Results: Two sample cases serve to illustrate the application of our tool in clinical practice. (a) For an orthogonal wedged pair of x-ray beams treating a maxillary sinus tumor, the biological effect at the ipsilateral mandible can be quantified, thus illustrates the so-called 'double-trouble' effects very well. (b) For a typical four-field, evenly weighted prostate treatment using 10 MV x-rays, physical dosimetry predicts a comparable dose at the femoral necks between an alternate two-fields/day and four-fields/day schups. However, our BED display reveals an approximate 21% higher BED for the two-fields/day scheme. This excessive dose to the femoral necks can be eliminated if the treatment is delivered with a 3:2 (anterio-posterior/posterio-anterior (AP

  16. Three-dimensional FEM model of FBGs in PANDA fibers with experimentally determined model parameters

    Science.gov (United States)

    Lindner, Markus; Hopf, Barbara; Koch, Alexander W.; Roths, Johannes

    2017-04-01

    A 3D-FEM model has been developed to improve the understanding of multi-parameter sensing with Bragg gratings in attached or embedded polarization maintaining fibers. The material properties of the fiber, especially Young's modulus and Poisson's ratio of the fiber's stress applying parts, are crucial for accurate simulations, but are usually not provided by the manufacturers. A methodology is presented to determine the unknown parameters by using experimental characterizations of the fiber and iterative FEM simulations. The resulting 3D-Model is capable of describing the change in birefringence of the free fiber when exposed to longitudinal strain. In future studies the 3D-FEM model will be employed to study the interaction of PANDA fibers with the surrounding materials in which they are embedded.

  17. Cisplatin Resistant Spheroids Model Clinically Relevant Survival Mechanisms in Ovarian Tumors.

    Directory of Open Access Journals (Sweden)

    Winyoo Chowanadisai

    Full Text Available The majority of ovarian tumors eventually recur in a drug resistant form. Using cisplatin sensitive and resistant cell lines assembled into 3D spheroids we profiled gene expression and identified candidate mechanisms and biological pathways associated with cisplatin resistance. OVCAR-8 human ovarian carcinoma cells were exposed to sub-lethal concentrations of cisplatin to create a matched cisplatin-resistant cell line, OVCAR-8R. Genome-wide gene expression profiling of sensitive and resistant ovarian cancer spheroids identified 3,331 significantly differentially expressed probesets coding for 3,139 distinct protein-coding genes (Fc >2, FDR < 0.05 (S2 Table. Despite significant expression changes in some transporters including MDR1, cisplatin resistance was not associated with differences in intracellular cisplatin concentration. Cisplatin resistant cells were significantly enriched for a mesenchymal gene expression signature. OVCAR-8R resistance derived gene sets were significantly more biased to patients with shorter survival. From the most differentially expressed genes, we derived a 17-gene expression signature that identifies ovarian cancer patients with shorter overall survival in three independent datasets. We propose that the use of cisplatin resistant cell lines in 3D spheroid models is a viable approach to gain insight into resistance mechanisms relevant to ovarian tumors in patients. Our data support the emerging concept that ovarian cancers can acquire drug resistance through an epithelial-to-mesenchymal transition.

  18. Automatic Query Generation and Query Relevance Measurement for Unsupervised Language Model Adaptation of Speech Recognition

    Directory of Open Access Journals (Sweden)

    Suzuki Motoyuki

    2009-01-01

    Full Text Available Abstract We are developing a method of Web-based unsupervised language model adaptation for recognition of spoken documents. The proposed method chooses keywords from the preliminary recognition result and retrieves Web documents using the chosen keywords. A problem is that the selected keywords tend to contain misrecognized words. The proposed method introduces two new ideas for avoiding the effects of keywords derived from misrecognized words. The first idea is to compose multiple queries from selected keyword candidates so that the misrecognized words and correct words do not fall into one query. The second idea is that the number of Web documents downloaded for each query is determined according to the "query relevance." Combining these two ideas, we can alleviate bad effect of misrecognized keywords by decreasing the number of downloaded Web documents from queries that contain misrecognized keywords. Finally, we examine a method of determining the number of iterative adaptations based on the recognition likelihood. Experiments have shown that the proposed stopping criterion can determine almost the optimum number of iterations. In the final experiment, the word accuracy without adaptation (55.29% was improved to 60.38%, which was 1.13 point better than the result of the conventional unsupervised adaptation method (59.25%.

  19. Automatic Query Generation and Query Relevance Measurement for Unsupervised Language Model Adaptation of Speech Recognition

    Directory of Open Access Journals (Sweden)

    Akinori Ito

    2009-01-01

    Full Text Available We are developing a method of Web-based unsupervised language model adaptation for recognition of spoken documents. The proposed method chooses keywords from the preliminary recognition result and retrieves Web documents using the chosen keywords. A problem is that the selected keywords tend to contain misrecognized words. The proposed method introduces two new ideas for avoiding the effects of keywords derived from misrecognized words. The first idea is to compose multiple queries from selected keyword candidates so that the misrecognized words and correct words do not fall into one query. The second idea is that the number of Web documents downloaded for each query is determined according to the “query relevance.” Combining these two ideas, we can alleviate bad effect of misrecognized keywords by decreasing the number of downloaded Web documents from queries that contain misrecognized keywords. Finally, we examine a method of determining the number of iterative adaptations based on the recognition likelihood. Experiments have shown that the proposed stopping criterion can determine almost the optimum number of iterations. In the final experiment, the word accuracy without adaptation (55.29% was improved to 60.38%, which was 1.13 point better than the result of the conventional unsupervised adaptation method (59.25%.

  20. Risk-adjusted Outcomes of Clinically Relevant Pancreatic Fistula Following Pancreatoduodenectomy: A Model for Performance Evaluation.

    Science.gov (United States)

    McMillan, Matthew T; Soi, Sameer; Asbun, Horacio J; Ball, Chad G; Bassi, Claudio; Beane, Joal D; Behrman, Stephen W; Berger, Adam C; Bloomston, Mark; Callery, Mark P; Christein, John D; Dixon, Elijah; Drebin, Jeffrey A; Castillo, Carlos Fernandez-Del; Fisher, William E; Fong, Zhi Ven; House, Michael G; Hughes, Steven J; Kent, Tara S; Kunstman, John W; Malleo, Giuseppe; Miller, Benjamin C; Salem, Ronald R; Soares, Kevin; Valero, Vicente; Wolfgang, Christopher L; Vollmer, Charles M

    2016-08-01

    To evaluate surgical performance in pancreatoduodenectomy using clinically relevant postoperative pancreatic fistula (CR-POPF) occurrence as a quality indicator. Accurate assessment of surgeon and institutional performance requires (1) standardized definitions for the outcome of interest and (2) a comprehensive risk-adjustment process to control for differences in patient risk. This multinational, retrospective study of 4301 pancreatoduodenectomies involved 55 surgeons at 15 institutions. Risk for CR-POPF was assessed using the previously validated Fistula Risk Score, and pancreatic fistulas were stratified by International Study Group criteria. CR-POPF variability was evaluated and hierarchical regression analysis assessed individual surgeon and institutional performance. There was considerable variability in both CR-POPF risk and occurrence. Factors increasing the risk for CR-POPF development included increasing Fistula Risk Score (odds ratio 1.49 per point, P ratio 3.30, P performance outliers were identified at the surgeon and institutional levels. Of the top 10 surgeons (≥15 cases) for nonrisk-adjusted performance, only 6 remained in this high-performing category following risk adjustment. This analysis of pancreatic fistulas following pancreatoduodenectomy demonstrates considerable variability in both the risk and occurrence of CR-POPF among surgeons and institutions. Disparities in patient risk between providers reinforce the need for comprehensive, risk-adjusted modeling when assessing performance based on procedure-specific complications. Furthermore, beyond inherent patient risk factors, surgical decision-making influences fistula outcomes.

  1. Using language models to identify relevant new information in inpatient clinical notes.

    Science.gov (United States)

    Zhang, Rui; Pakhomov, Serguei V; Lee, Janet T; Melton, Genevieve B

    2014-01-01

    Redundant information in clinical notes within electronic health record (EHR) systems is ubiquitous and may negatively impact the use of these notes by clinicians, and, potentially, the efficiency of patient care delivery. Automated methods to identify redundant versus relevant new information may provide a valuable tool for clinicians to better synthesize patient information and navigate to clinically important details. In this study, we investigated the use of language models for identification of new information in inpatient notes, and evaluated our methods using expert-derived reference standards. The best method achieved precision of 0.743, recall of 0.832 and F1-measure of 0.784. The average proportion of redundant information was similar between inpatient and outpatient progress notes (76.6% (SD=17.3%) and 76.7% (SD=14.0%), respectively). Advanced practice providers tended to have higher rates of redundancy in their notes compared to physicians. Future investigation includes the addition of semantic components and visualization of new information.

  2. THM-coupled modeling of selected processes in argillaceous rock relevant to rock mechanics

    International Nuclear Information System (INIS)

    Czaikowski, Oliver

    2012-01-01

    Scientific investigations in European countries other than Germany concentrate not only on granite formations (Switzerland, Sweden) but also on argillaceous rock formations (France, Switzerland, Belgium) to assess their suitability as host and barrier rock for the final storage of radioactive waste. In Germany, rock salt has been under thorough study as a host rock over the past few decades. According to a study by the German Federal Institute for Geosciences and Natural Resources, however, not only salt deposits but also argillaceous rock deposits are available at relevant depths and of extensions in space which make final storage of high-level radioactive waste basically possible in Germany. Equally qualified findings about the suitability/unsuitability of non-saline rock formations require fundamental studies to be conducted nationally because of the comparatively low level of knowledge. The article presents basic analyses of coupled mechanical and hydraulic properties of argillaceous rock formations as host rock for a repository. The interaction of various processes is explained on the basis of knowledge derived from laboratory studies, and open problems are deduced. For modeling coupled processes, a simplified analytical computation method is proposed and compared with the results of numerical simulations, and the limits to its application are outlined. (orig.)

  3. 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.

  4. Information Theoretic Tools for Parameter Fitting in Coarse Grained Models

    KAUST Repository

    Kalligiannaki, Evangelia; Harmandaris, Vagelis; Katsoulakis, Markos A.; Plechac, Petr

    2015-01-01

    We study the application of information theoretic tools for model reduction in the case of systems driven by stochastic dynamics out of equilibrium. The model/dimension reduction is considered by proposing parametrized coarse grained dynamics

  5. Kinetic models and parameters estimation study of biomass and ...

    African Journals Online (AJOL)

    compaq

    2017-01-11

    Jan 11, 2017 ... Unstructured models were proposed using the logistic equation for growth, the ... analysis of variance (ANOVA) was also used to validate the proposed models. ... production but their choice depends on the cost and the.

  6. Numerical Modeling of Piezoelectric Transducers Using Physical Parameters

    NARCIS (Netherlands)

    Cappon, H.; Keesman, K.J.

    2012-01-01

    Design of ultrasonic equipment is frequently facilitated with numerical models. These numerical models, however, need a calibration step, because usually not all characteristics of the materials used are known. Characterization of material properties combined with numerical simulations and

  7. Parameter sensitivity and identifiability for a biogeochemical model of hypoxia in the northern Gulf of Mexico

    Science.gov (United States)

    Local sensitivity analyses and identifiable parameter subsets were used to describe numerical constraints of a hypoxia model for bottom waters of the northern Gulf of Mexico. The sensitivity of state variables differed considerably with parameter changes, although most variables ...

  8. Reduced order modeling and parameter identification of a building energy system model through an optimization routine

    International Nuclear Information System (INIS)

    Harish, V.S.K.V.; Kumar, Arun

    2016-01-01

    Highlights: • A BES model based on 1st principles is developed and solved numerically. • Parameters of lumped capacitance model are fitted using the proposed optimization routine. • Validations are showed for different types of building construction elements. • Step response excitations for outdoor air temperature and relative humidity are analyzed. - Abstract: Different control techniques together with intelligent building technology (Building Automation Systems) are used to improve energy efficiency of buildings. In almost all control projects, it is crucial to have building energy models with high computational efficiency in order to design and tune the controllers and simulate their performance. In this paper, a set of partial differential equations are formulated accounting for energy flow within the building space. These equations are then solved as conventional finite difference equations using Crank–Nicholson scheme. Such a model of a higher order is regarded as a benchmark model. An optimization algorithm has been developed, depicted through a flowchart, which minimizes the sum squared error between the step responses of the numerical and the optimal model. Optimal model of the construction element is nothing but a RC-network model with the values of Rs and Cs estimated using the non-linear time invariant constrained optimization routine. The model is validated with comparing the step responses with other two RC-network models whose parameter values are selected based on a certain criteria. Validations are showed for different types of building construction elements viz., low, medium and heavy thermal capacity elements. Simulation results show that the optimal model closely follow the step responses of the numerical model as compared to the responses of other two models.

  9. Radiation-Induced Leukemia at Doses Relevant to Radiation Therapy: Modeling Mechanisms and Estimating Risks

    Science.gov (United States)

    Shuryak, Igor; Sachs, Rainer K.; Hlatky, Lynn; Mark P. Little; Hahnfeldt, Philip; Brenner, David J.

    2006-01-01

    Because many cancer patients are diagnosed earlier and live longer than in the past, second cancers induced by radiation therapy have become a clinically significant issue. An earlier biologically based model that was designed to estimate risks of high-dose radiation induced solid cancers included initiation of stem cells to a premalignant state, inactivation of stem cells at high radiation doses, and proliferation of stem cells during cellular repopulation after inactivation. This earlier model predicted the risks of solid tumors induced by radiation therapy but overestimated the corresponding leukemia risks. Methods: To extend the model to radiation-induced leukemias, we analyzed in addition to cellular initiation, inactivation, and proliferation a repopulation mechanism specific to the hematopoietic system: long-range migration through the blood stream of hematopoietic stem cells (HSCs) from distant locations. Parameters for the model were derived from HSC biologic data in the literature and from leukemia risks among atomic bomb survivors v^ ho were subjected to much lower radiation doses. Results: Proliferating HSCs that migrate from sites distant from the high-dose region include few preleukemic HSCs, thus decreasing the high-dose leukemia risk. The extended model for leukemia provides risk estimates that are consistent with epidemiologic data for leukemia risk associated with radiation therapy over a wide dose range. For example, when applied to an earlier case-control study of 110000 women undergoing radiotherapy for uterine cancer, the model predicted an excess relative risk (ERR) of 1.9 for leukemia among women who received a large inhomogeneous fractionated external beam dose to the bone marrow (mean = 14.9 Gy), consistent with the measured ERR (2.0, 95% confidence interval [CI] = 0.2 to 6.4; from 3.6 cases expected and 11 cases observed). As a corresponding example for brachytherapy, the predicted ERR of 0.80 among women who received an inhomogeneous low

  10. Classical algorithms for automated parameter-search methods in compartmental neural models - A critical survey based on simulations using neuron

    International Nuclear Information System (INIS)

    Mutihac, R.; Mutihac, R.C.; Cicuttin, A.

    2001-09-01

    Parameter-search methods are problem-sensitive. All methods depend on some meta-parameters of their own, which must be determined experimentally in advance. A better choice of these intrinsic parameters for a certain parameter-search method may improve its performance. Moreover, there are various implementations of the same method, which may also affect its performance. The choice of the matching (error) function has a great impact on the search process in terms of finding the optimal parameter set and minimizing the computational cost. An initial assessment of the matching function ability to distinguish between good and bad models is recommended, before launching exhaustive computations. However, different runs of a parameter search method may result in the same optimal parameter set or in different parameter sets (the model is insufficiently constrained to accurately characterize the real system). Robustness of the parameter set is expressed by the extent to which small perturbations in the parameter values are not affecting the best solution. A parameter set that is not robust is unlikely to be physiologically relevant. Robustness can also be defined as the stability of the optimal parameter set to small variations of the inputs. When trying to estimate things like the minimum, or the least-squares optimal parameters of a nonlinear system, the existence of multiple local minima can cause problems with the determination of the global optimum. Techniques such as Newton's method, the Simplex method and Least-squares Linear Taylor Differential correction technique can be useful provided that one is lucky enough to start sufficiently close to the global minimum. All these methods suffer from the inability to distinguish a local minimum from a global one because they follow the local gradients towards the minimum, even if some methods are resetting the search direction when it is likely to get stuck in presumably a local minimum. Deterministic methods based on

  11. Assessing the Impact of Model Parameter Uncertainty in Simulating Grass Biomass Using a Hybrid Carbon Allocation Strategy

    Science.gov (United States)

    Reyes, J. J.; Adam, J. C.; Tague, C.

    2016-12-01

    Grasslands play an important role in agricultural production as forage for livestock; they also provide a diverse set of ecosystem services including soil carbon (C) storage. The partitioning of C between above and belowground plant compartments (i.e. allocation) is influenced by both plant characteristics and environmental conditions. The objectives of this study are to 1) develop and evaluate a hybrid C allocation strategy suitable for grasslands, and 2) apply this strategy to examine the importance of various parameters related to biogeochemical cycling, photosynthesis, allocation, and soil water drainage on above and belowground biomass. We include allocation as an important process in quantifying the model parameter uncertainty, which identifies the most influential parameters and what processes may require further refinement. For this, we use the Regional Hydro-ecologic Simulation System, a mechanistic model that simulates coupled water and biogeochemical processes. A Latin hypercube sampling scheme was used to develop parameter sets for calibration and evaluation of allocation strategies, as well as parameter uncertainty analysis. We developed the hybrid allocation strategy to integrate both growth-based and resource-limited allocation mechanisms. When evaluating the new strategy simultaneously for above and belowground biomass, it produced a larger number of less biased parameter sets: 16% more compared to resource-limited and 9% more compared to growth-based. This also demonstrates its flexible application across diverse plant types and environmental conditions. We found that higher parameter importance corresponded to sub- or supra-optimal resource availability (i.e. water, nutrients) and temperature ranges (i.e. too hot or cold). For example, photosynthesis-related parameters were more important at sites warmer than the theoretical optimal growth temperature. Therefore, larger values of parameter importance indicate greater relative sensitivity in

  12. Parameter estimation for LLDPE gas-phase reactor models

    Directory of Open Access Journals (Sweden)

    G. A. Neumann

    2007-06-01

    Full Text Available Product development and advanced control applications require models with good predictive capability. However, in some cases it is not possible to obtain good quality phenomenological models due to the lack of data or the presence of important unmeasured effects. The use of empirical models requires less investment in modeling, but implies the need for larger amounts of experimental data to generate models with good predictive capability. In this work, nonlinear phenomenological and empirical models were compared with respect to their capability to predict the melt index and polymer yield of a low-density polyethylene production process consisting of two fluidized bed reactors connected in series. To adjust the phenomenological model, the optimization algorithms based on the flexible polyhedron method of Nelder and Mead showed the best efficiency. To adjust the empirical model, the PLS model was more appropriate for polymer yield, and the melt index needed more nonlinearity like the QPLS models. In the comparison between these two types of models better results were obtained for the empirical models.

  13. Parameter estimation of electricity spot models from futures prices

    NARCIS (Netherlands)

    Aihara, ShinIchi; Bagchi, Arunabha; Imreizeeq, E.S.N.; Walter, E.

    We consider a slight perturbation of the Schwartz-Smith model for the electricity futures prices and the resulting modified spot model. Using the martingale property of the modified price under the risk neutral measure, we derive the arbitrage free model for the spot and futures prices. We estimate

  14. New clinically relevant, orthotopic mouse models of human chondrosarcoma with spontaneous metastasis

    Directory of Open Access Journals (Sweden)

    Dass Crispin R

    2010-06-01

    Full Text Available Abstract Background Chondrosarcoma responds poorly to adjuvant therapy and new, clinically relevant animal models are required to test targeted therapy. Methods Two human chondrosarcoma cell lines, JJ012 and FS090, were evaluated for proliferation, colony formation, invasion, angiogenesis and osteoclastogenesis. Cell lines were also investigated for VEGF, MMP-2, MMP-9, and RECK expression. JJ012 and FS090 were injected separately into the mouse tibia intramedullary canal or tibial periosteum. Animal limbs were measured, and x-rayed for evidence of tumour take and progression. Tibias and lungs were harvested to determine the presence of tumour and lung metastases. Results JJ012 demonstrated significantly higher proliferative capacity, invasion, and colony formation in collagen I gel. JJ012 conditioned medium stimulated endothelial tube formation and osteoclastogenesis with a greater potency than FS090 conditioned medium, perhaps related to the effects of VEGF and MMP-9. In vivo, tumours formed in intratibial and periosteal groups injected with JJ012, however no mice injected with FS090 developed tumours. JJ012 periosteal tumours grew to 3 times the non-injected limb size by 7 weeks, whereas intratibial injected limbs required 10 weeks to achieve a similar tumour size. Sectioned tumour tissue demonstrated features of grade III chondrosarcoma. All JJ012 periosteal tumours (5/5 resulted in lung micro-metastase