Data analysis and approximate models model choice, location-scale, analysis of variance, nonparametric regression and image analysis

CERN Document Server

Davies, Patrick Laurie

2014-01-01

Introduction IntroductionApproximate Models Notation Two Modes of Statistical AnalysisTowards One Mode of Analysis Approximation, Randomness, Chaos, Determinism ApproximationA Concept of Approximation Approximation Approximating a Data Set by a Model Approximation Regions Functionals and EquivarianceRegularization and Optimality Metrics and DiscrepanciesStrong and Weak Topologies On Being (almost) Honest Simulations and Tables Degree of Approximation and p-values ScalesStability of Analysis The Choice of En(α, P) Independence Procedures, Approximation and VaguenessDiscrete Models The Empirical Density Metrics and Discrepancies The Total Variation Metric The Kullback-Leibler and Chi-Squared Discrepancies The Po(λ) ModelThe b(k, p) and nb(k, p) Models The Flying Bomb Data The Student Study Times Data OutliersOutliers, Data Analysis and Models Breakdown Points and Equivariance Identifying Outliers and Breakdown Outliers in Multivariate Data Outliers in Linear Regression Outliers in Structured Data The Location...

ModelMate - A graphical user interface for model analysis

Science.gov (United States)

Banta, Edward R.

2011-01-01

ModelMate is a graphical user interface designed to facilitate use of model-analysis programs with models. This initial version of ModelMate supports one model-analysis program, UCODE_2005, and one model software program, MODFLOW-2005. ModelMate can be used to prepare input files for UCODE_2005, run UCODE_2005, and display analysis results. A link to the GW_Chart graphing program facilitates visual interpretation of results. ModelMate includes capabilities for organizing directories used with the parallel-processing capabilities of UCODE_2005 and for maintaining files in those directories to be identical to a set of files in a master directory. ModelMate can be used on its own or in conjunction with ModelMuse, a graphical user interface for MODFLOW-2005 and PHAST.

Models of Economic Analysis

OpenAIRE

Adrian Ioana; Tiberiu Socaciu

2013-01-01

The article presents specific aspects of management and models for economic analysis. Thus, we present the main types of economic analysis: statistical analysis, dynamic analysis, static analysis, mathematical analysis, psychological analysis. Also we present the main object of the analysis: the technological activity analysis of a company, the analysis of the production costs, the economic activity analysis of a company, the analysis of equipment, the analysis of labor productivity, the anal...

Survival analysis models and applications

CERN Document Server

Liu, Xian

2012-01-01

Survival analysis concerns sequential occurrences of events governed by probabilistic laws.  Recent decades have witnessed many applications of survival analysis in various disciplines. This book introduces both classic survival models and theories along with newly developed techniques. Readers will learn how to perform analysis of survival data by following numerous empirical illustrations in SAS. Survival Analysis: Models and Applications: Presents basic techniques before leading onto some of the most advanced topics in survival analysis.Assumes only a minimal knowledge of SAS whilst enablin

Multiscale Signal Analysis and Modeling

CERN Document Server

Zayed, Ahmed

2013-01-01

Multiscale Signal Analysis and Modeling presents recent advances in multiscale analysis and modeling using wavelets and other systems. This book also presents applications in digital signal processing using sampling theory and techniques from various function spaces, filter design, feature extraction and classification, signal and image representation/transmission, coding, nonparametric statistical signal processing, and statistical learning theory. This book also: Discusses recently developed signal modeling techniques, such as the multiscale method for complex time series modeling, multiscale positive density estimations, Bayesian Shrinkage Strategies, and algorithms for data adaptive statistics Introduces new sampling algorithms for multidimensional signal processing Provides comprehensive coverage of wavelets with presentations on waveform design and modeling, wavelet analysis of ECG signals and wavelet filters Reviews features extraction and classification algorithms for multiscale signal and image proce...

Hypersonic - Model Analysis as a Service

DEFF Research Database (Denmark)

Acretoaie, Vlad; Störrle, Harald

2014-01-01

Hypersonic is a Cloud-based tool that proposes a new approach to the deployment of model analysis facilities. It is implemented as a RESTful Web service API o_ering analysis features such as model clone detection. This approach allows the migration of resource intensive analysis algorithms from...

Sensitivity analysis approaches applied to systems biology models.

Science.gov (United States)

Zi, Z

2011-11-01

With the rising application of systems biology, sensitivity analysis methods have been widely applied to study the biological systems, including metabolic networks, signalling pathways and genetic circuits. Sensitivity analysis can provide valuable insights about how robust the biological responses are with respect to the changes of biological parameters and which model inputs are the key factors that affect the model outputs. In addition, sensitivity analysis is valuable for guiding experimental analysis, model reduction and parameter estimation. Local and global sensitivity analysis approaches are the two types of sensitivity analysis that are commonly applied in systems biology. Local sensitivity analysis is a classic method that studies the impact of small perturbations on the model outputs. On the other hand, global sensitivity analysis approaches have been applied to understand how the model outputs are affected by large variations of the model input parameters. In this review, the author introduces the basic concepts of sensitivity analysis approaches applied to systems biology models. Moreover, the author discusses the advantages and disadvantages of different sensitivity analysis methods, how to choose a proper sensitivity analysis approach, the available sensitivity analysis tools for systems biology models and the caveats in the interpretation of sensitivity analysis results.

Statistical Modelling of Wind Proles - Data Analysis and Modelling

DEFF Research Database (Denmark)

Jónsson, Tryggvi; Pinson, Pierre

The aim of the analysis presented in this document is to investigate whether statistical models can be used to make very short-term predictions of wind profiles.......The aim of the analysis presented in this document is to investigate whether statistical models can be used to make very short-term predictions of wind profiles....

Stochastic modeling analysis and simulation

CERN Document Server

Nelson, Barry L

1995-01-01

A coherent introduction to the techniques for modeling dynamic stochastic systems, this volume also offers a guide to the mathematical, numerical, and simulation tools of systems analysis. Suitable for advanced undergraduates and graduate-level industrial engineers and management science majors, it proposes modeling systems in terms of their simulation, regardless of whether simulation is employed for analysis. Beginning with a view of the conditions that permit a mathematical-numerical analysis, the text explores Poisson and renewal processes, Markov chains in discrete and continuous time, se

[Model-based biofuels system analysis: a review].

Science.gov (United States)

Chang, Shiyan; Zhang, Xiliang; Zhao, Lili; Ou, Xunmin

2011-03-01

Model-based system analysis is an important tool for evaluating the potential and impacts of biofuels, and for drafting biofuels technology roadmaps and targets. The broad reach of the biofuels supply chain requires that biofuels system analyses span a range of disciplines, including agriculture/forestry, energy, economics, and the environment. Here we reviewed various models developed for or applied to modeling biofuels, and presented a critical analysis of Agriculture/Forestry System Models, Energy System Models, Integrated Assessment Models, Micro-level Cost, Energy and Emission Calculation Models, and Specific Macro-level Biofuel Models. We focused on the models' strengths, weaknesses, and applicability, facilitating the selection of a suitable type of model for specific issues. Such an analysis was a prerequisite for future biofuels system modeling, and represented a valuable resource for researchers and policy makers.

ROCK PROPERTIES MODEL ANALYSIS MODEL REPORT

International Nuclear Information System (INIS)

Clinton Lum

2002-01-01

The purpose of this Analysis and Model Report (AMR) is to document Rock Properties Model (RPM) 3.1 with regard to input data, model methods, assumptions, uncertainties and limitations of model results, and qualification status of the model. The report also documents the differences between the current and previous versions and validation of the model. The rock properties models are intended principally for use as input to numerical physical-process modeling, such as of ground-water flow and/or radionuclide transport. The constraints, caveats, and limitations associated with this model are discussed in the appropriate text sections that follow. This work was conducted in accordance with the following planning documents: WA-0344, ''3-D Rock Properties Modeling for FY 1998'' (SNL 1997, WA-0358), ''3-D Rock Properties Modeling for FY 1999'' (SNL 1999), and the technical development plan, Rock Properties Model Version 3.1, (CRWMS MandO 1999c). The Interim Change Notice (ICNs), ICN 02 and ICN 03, of this AMR were prepared as part of activities being conducted under the Technical Work Plan, TWP-NBS-GS-000003, ''Technical Work Plan for the Integrated Site Model, Process Model Report, Revision 01'' (CRWMS MandO 2000b). The purpose of ICN 03 is to record changes in data input status due to data qualification and verification activities. These work plans describe the scope, objectives, tasks, methodology, and implementing procedures for model construction. The constraints, caveats, and limitations associated with this model are discussed in the appropriate text sections that follow. The work scope for this activity consists of the following: (1) Conversion of the input data (laboratory measured porosity data, x-ray diffraction mineralogy, petrophysical calculations of bound water, and petrophysical calculations of porosity) for each borehole into stratigraphic coordinates; (2) Re-sampling and merging of data sets; (3) Development of geostatistical simulations of porosity; (4

Intercity Travel Demand Analysis Model

Directory of Open Access Journals (Sweden)

Ming Lu

2014-01-01

Full Text Available It is well known that intercity travel is an important component of travel demand which belongs to short distance corridor travel. The conventional four-step method is no longer suitable for short distance corridor travel demand analysis for the time spent on urban traffic has a great impact on traveler's main mode choice. To solve this problem, the author studied the existing intercity travel demand analysis model, then improved it based on the study, and finally established a combined model of main mode choice and access mode choice. At last, an integrated multilevel nested logit model structure system was built. The model system includes trip generation, destination choice, and mode-route choice based on multinomial logit model, and it achieved linkage and feedback of each part through logsum variable. This model was applied in Shenzhen intercity railway passenger demand forecast in 2010 as a case study. As a result, the forecast results were consistent with the actuality. The model's correctness and feasibility were verified.

Meta-analysis a structural equation modeling approach

CERN Document Server

Cheung, Mike W-L

2015-01-01

Presents a novel approach to conducting meta-analysis using structural equation modeling. Structural equation modeling (SEM) and meta-analysis are two powerful statistical methods in the educational, social, behavioral, and medical sciences. They are often treated as two unrelated topics in the literature. This book presents a unified framework on analyzing meta-analytic data within the SEM framework, and illustrates how to conduct meta-analysis using the metaSEM package in the R statistical environment. Meta-Analysis: A Structural Equation Modeling Approach begins by introducing the impo

Integrating model checking with HiP-HOPS in model-based safety analysis

International Nuclear Information System (INIS)

Sharvia, Septavera; Papadopoulos, Yiannis

2015-01-01

The ability to perform an effective and robust safety analysis on the design of modern safety–critical systems is crucial. Model-based safety analysis (MBSA) has been introduced in recent years to support the assessment of complex system design by focusing on the system model as the central artefact, and by automating the synthesis and analysis of failure-extended models. Model checking and failure logic synthesis and analysis (FLSA) are two prominent MBSA paradigms. Extensive research has placed emphasis on the development of these techniques, but discussion on their integration remains limited. In this paper, we propose a technique in which model checking and Hierarchically Performed Hazard Origin and Propagation Studies (HiP-HOPS) – an advanced FLSA technique – can be applied synergistically with benefit for the MBSA process. The application of the technique is illustrated through an example of a brake-by-wire system. - Highlights: • We propose technique to integrate HiP-HOPS and model checking. • State machines can be systematically constructed from HiP-HOPS. • The strengths of different MBSA techniques are combined. • Demonstrated through modeling and analysis of brake-by-wire system. • Root cause analysis is automated and system dynamic behaviors analyzed and verified

A catalog of automated analysis methods for enterprise models.

Science.gov (United States)

Florez, Hector; Sánchez, Mario; Villalobos, Jorge

2016-01-01

Enterprise models are created for documenting and communicating the structure and state of Business and Information Technologies elements of an enterprise. After models are completed, they are mainly used to support analysis. Model analysis is an activity typically based on human skills and due to the size and complexity of the models, this process can be complicated and omissions or miscalculations are very likely. This situation has fostered the research of automated analysis methods, for supporting analysts in enterprise analysis processes. By reviewing the literature, we found several analysis methods; nevertheless, they are based on specific situations and different metamodels; then, some analysis methods might not be applicable to all enterprise models. This paper presents the work of compilation (literature review), classification, structuring, and characterization of automated analysis methods for enterprise models, expressing them in a standardized modeling language. In addition, we have implemented the analysis methods in our modeling tool.

Intercity Travel Demand Analysis Model

OpenAIRE

Ming Lu; Hai Zhu; Xia Luo; Lei Lei

2014-01-01

It is well known that intercity travel is an important component of travel demand which belongs to short distance corridor travel. The conventional four-step method is no longer suitable for short distance corridor travel demand analysis for the time spent on urban traffic has a great impact on traveler's main mode choice. To solve this problem, the author studied the existing intercity travel demand analysis model, then improved it based on the study, and finally established a combined model...

Uncertainty analysis of environmental models

International Nuclear Information System (INIS)

Monte, L.

1990-01-01

In the present paper an evaluation of the output uncertainty of an environmental model for assessing the transfer of 137 Cs and 131 I in the human food chain are carried out on the basis of a statistical analysis of data reported by the literature. The uncertainty analysis offers the oppotunity of obtaining some remarkable information about the uncertainty of models predicting the migration of non radioactive substances in the environment mainly in relation to the dry and wet deposition

Simulation modeling and analysis with Arena

CERN Document Server

Altiok, Tayfur

2007-01-01

Simulation Modeling and Analysis with Arena is a highly readable textbook which treats the essentials of the Monte Carlo discrete-event simulation methodology, and does so in the context of a popular Arena simulation environment.” It treats simulation modeling as an in-vitro laboratory that facilitates the understanding of complex systems and experimentation with what-if scenarios in order to estimate their performance metrics. The book contains chapters on the simulation modeling methodology and the underpinnings of discrete-event systems, as well as the relevant underlying probability, statistics, stochastic processes, input analysis, model validation and output analysis. All simulation-related concepts are illustrated in numerous Arena examples, encompassing production lines, manufacturing and inventory systems, transportation systems, and computer information systems in networked settings.· Introduces the concept of discrete event Monte Carlo simulation, the most commonly used methodology for modeli...

Sensitivity Analysis of Simulation Models

NARCIS (Netherlands)

Kleijnen, J.P.C.

2009-01-01

This contribution presents an overview of sensitivity analysis of simulation models, including the estimation of gradients. It covers classic designs and their corresponding (meta)models; namely, resolution-III designs including fractional-factorial two-level designs for first-order polynomial

Vibrational Fingerprints of Low-Lying PtnP2n (n = 1–5) Cluster Structures from Global Optimization Based on Density Functional Theory Potential Energy Surfaces

KAUST Repository

Jedidi, Abdesslem; Li, Rui; Fornasiero, Paolo; Cavallo, Luigi; Carbonniere, Philippe

2015-01-01

Vibrational fingerprints of small PtnP2n (n = 1–5) clusters were computed from their low-lying structures located from a global exploration of their DFT potential energy surfaces with the GSAM code. Five DFT methods were assessed from the CCSD(T) wavenumbers of PtP2 species and CCSD relative energies of Pt2P4 structures. The eight first PtnP2n isomers found are reported. The vibrational computations reveal (i) the absence of clear signatures made by overtone or combination bands due to very weak mechanical and electrical anharmonicities and (ii) some significant and recurrent vibrational fingerprints in correlation with the different PP bonding situations in the PtnP2n structures.

Vibrational Fingerprints of Low-Lying PtnP2n (n = 1–5) Cluster Structures from Global Optimization Based on Density Functional Theory Potential Energy Surfaces

KAUST Repository

Jedidi, Abdesslem

2015-11-13

Vibrational fingerprints of small PtnP2n (n = 1–5) clusters were computed from their low-lying structures located from a global exploration of their DFT potential energy surfaces with the GSAM code. Five DFT methods were assessed from the CCSD(T) wavenumbers of PtP2 species and CCSD relative energies of Pt2P4 structures. The eight first PtnP2n isomers found are reported. The vibrational computations reveal (i) the absence of clear signatures made by overtone or combination bands due to very weak mechanical and electrical anharmonicities and (ii) some significant and recurrent vibrational fingerprints in correlation with the different PP bonding situations in the PtnP2n structures.

Reliability analysis and operator modelling

International Nuclear Information System (INIS)

Hollnagel, Erik

1996-01-01

The paper considers the state of operator modelling in reliability analysis. Operator models are needed in reliability analysis because operators are needed in process control systems. HRA methods must therefore be able to account both for human performance variability and for the dynamics of the interaction. A selected set of first generation HRA approaches is briefly described in terms of the operator model they use, their classification principle, and the actual method they propose. In addition, two examples of second generation methods are also considered. It is concluded that first generation HRA methods generally have very simplistic operator models, either referring to the time-reliability relationship or to elementary information processing concepts. It is argued that second generation HRA methods must recognise that cognition is embedded in a context, and be able to account for that in the way human reliability is analysed and assessed

Modeling and Analysis of Wrinkled Membranes: An Overview

Science.gov (United States)

Yang, B.; Ding, H.; Lou, M.; Fang, H.; Broduer, Steve (Technical Monitor)

2001-01-01

Thin-film membranes are basic elements of a variety of space inflatable/deployable structures. Wrinkling degrades the performance and reliability of these membrane structures, and hence has been a topic of continued interest. Wrinkling analysis of membranes for general geometry and arbitrary boundary conditions is quite challenging. The objective of this presentation is two-fold. Firstly, the existing models of wrinkled membranes and related numerical solution methods are reviewed. The important issues to be discussed are the capability of a membrane model to characterize taut, wrinkled and slack states of membranes in a consistent and physically reasonable manner; the ability of a wrinkling analysis method to predict the formation and growth of wrinkled regions, and to determine out-of-plane deformation and wrinkled waves; the convergence of a numerical solution method for wrinkling analysis; and the compatibility of a wrinkling analysis with general-purpose finite element codes. According to this review, several opening issues in modeling and analysis of wrinkled membranes that are to be addressed in future research are summarized, The second objective of this presentation is to discuss a newly developed membrane model of two viable parameters (2-VP model) and associated parametric finite element method (PFEM) for wrinkling analysis are introduced. The innovations and advantages of the proposed membrane model and PFEM-based wrinkling analysis are: (1) Via a unified stress-strain relation; the 2-VP model treat the taut, wrinkled, and slack states of membranes consistently; (2) The PFEM-based wrinkling analysis has guaranteed convergence; (3) The 2-VP model along with PFEM is capable of predicting membrane out-of-plane deformations; and (4) The PFEM can be integrated into any existing finite element code. Preliminary numerical examples are also included in this presentation to demonstrate the 2-VP model and PFEM-based wrinkling analysis approach.

Hierarchical modeling and analysis for spatial data

CERN Document Server

Banerjee, Sudipto; Gelfand, Alan E

2003-01-01

Among the many uses of hierarchical modeling, their application to the statistical analysis of spatial and spatio-temporal data from areas such as epidemiology And environmental science has proven particularly fruitful. Yet to date, the few books that address the subject have been either too narrowly focused on specific aspects of spatial analysis, or written at a level often inaccessible to those lacking a strong background in mathematical statistics.Hierarchical Modeling and Analysis for Spatial Data is the first accessible, self-contained treatment of hierarchical methods, modeling, and dat

Evaluation of Thermal Margin Analysis Models for SMART

International Nuclear Information System (INIS)

Seo, Kyong Won; Kwon, Hyuk; Hwang, Dae Hyun

2011-01-01

Thermal margin of SMART would be analyzed by three different methods. The first method is subchannel analysis by MATRA-S code and it would be a reference data for the other two methods. The second method is an on-line few channel analysis by FAST code that would be integrated into SCOPS/SCOMS. The last one is a single channel module analysis by safety analysis. Several thermal margin analysis models for SMART reactor core by subchannel analysis were setup and tested. We adopted a strategy of single stage analysis for thermal analysis of SMART reactor core. The model should represent characteristics of the SMART reactor core including hot channel. The model should be simple as possible to be evaluated within reasonable time and cost

Domain specific modeling and analysis

NARCIS (Netherlands)

Jacob, Joost Ferdinand

2008-01-01

It is desirable to model software systems in such a way that analysis of the systems, and tool development for such analysis, is readily possible and feasible in the context of large scientific research projects. This thesis emphasizes the methodology that serves as a basis for such developments.

Using structural equation modeling for network meta-analysis.

Science.gov (United States)

Tu, Yu-Kang; Wu, Yun-Chun

2017-07-14

Network meta-analysis overcomes the limitations of traditional pair-wise meta-analysis by incorporating all available evidence into a general statistical framework for simultaneous comparisons of several treatments. Currently, network meta-analyses are undertaken either within the Bayesian hierarchical linear models or frequentist generalized linear mixed models. Structural equation modeling (SEM) is a statistical method originally developed for modeling causal relations among observed and latent variables. As random effect is explicitly modeled as a latent variable in SEM, it is very flexible for analysts to specify complex random effect structure and to make linear and nonlinear constraints on parameters. The aim of this article is to show how to undertake a network meta-analysis within the statistical framework of SEM. We used an example dataset to demonstrate the standard fixed and random effect network meta-analysis models can be easily implemented in SEM. It contains results of 26 studies that directly compared three treatment groups A, B and C for prevention of first bleeding in patients with liver cirrhosis. We also showed that a new approach to network meta-analysis based on the technique of unrestricted weighted least squares (UWLS) method can also be undertaken using SEM. For both the fixed and random effect network meta-analysis, SEM yielded similar coefficients and confidence intervals to those reported in the previous literature. The point estimates of two UWLS models were identical to those in the fixed effect model but the confidence intervals were greater. This is consistent with results from the traditional pairwise meta-analyses. Comparing to UWLS model with common variance adjusted factor, UWLS model with unique variance adjusted factor has greater confidence intervals when the heterogeneity was larger in the pairwise comparison. The UWLS model with unique variance adjusted factor reflects the difference in heterogeneity within each comparison

Multivariate analysis: models and method

International Nuclear Information System (INIS)

Sanz Perucha, J.

1990-01-01

Data treatment techniques are increasingly used since computer methods result of wider access. Multivariate analysis consists of a group of statistic methods that are applied to study objects or samples characterized by multiple values. A final goal is decision making. The paper describes the models and methods of multivariate analysis

Dynamic Chest Image Analysis: Model-Based Perfusion Analysis in Dynamic Pulmonary Imaging

Directory of Open Access Journals (Sweden)

Kiuru Aaro

2003-01-01

Full Text Available The "Dynamic Chest Image Analysis" project aims to develop model-based computer analysis and visualization methods for showing focal and general abnormalities of lung ventilation and perfusion based on a sequence of digital chest fluoroscopy frames collected with the dynamic pulmonary imaging technique. We have proposed and evaluated a multiresolutional method with an explicit ventilation model for ventilation analysis. This paper presents a new model-based method for pulmonary perfusion analysis. According to perfusion properties, we first devise a novel mathematical function to form a perfusion model. A simple yet accurate approach is further introduced to extract cardiac systolic and diastolic phases from the heart, so that this cardiac information may be utilized to accelerate the perfusion analysis and improve its sensitivity in detecting pulmonary perfusion abnormalities. This makes perfusion analysis not only fast but also robust in computation; consequently, perfusion analysis becomes computationally feasible without using contrast media. Our clinical case studies with 52 patients show that this technique is effective for pulmonary embolism even without using contrast media, demonstrating consistent correlations with computed tomography (CT and nuclear medicine (NM studies. This fluoroscopical examination takes only about 2 seconds for perfusion study with only low radiation dose to patient, involving no preparation, no radioactive isotopes, and no contrast media.

TIME SERIES ANALYSIS USING A UNIQUE MODEL OF TRANSFORMATION

Directory of Open Access Journals (Sweden)

Goran Klepac

2007-12-01

Full Text Available REFII1 model is an authorial mathematical model for time series data mining. The main purpose of that model is to automate time series analysis, through a unique transformation model of time series. An advantage of this approach of time series analysis is the linkage of different methods for time series analysis, linking traditional data mining tools in time series, and constructing new algorithms for analyzing time series. It is worth mentioning that REFII model is not a closed system, which means that we have a finite set of methods. At first, this is a model for transformation of values of time series, which prepares data used by different sets of methods based on the same model of transformation in a domain of problem space. REFII model gives a new approach in time series analysis based on a unique model of transformation, which is a base for all kind of time series analysis. The advantage of REFII model is its possible application in many different areas such as finance, medicine, voice recognition, face recognition and text mining.

Applied research in uncertainty modeling and analysis

CERN Document Server

Ayyub, Bilal

2005-01-01

Uncertainty has been a concern to engineers, managers, and scientists for many years. For a long time uncertainty has been considered synonymous with random, stochastic, statistic, or probabilistic. Since the early sixties views on uncertainty have become more heterogeneous. In the past forty years numerous tools that model uncertainty, above and beyond statistics, have been proposed by several engineers and scientists. The tool/method to model uncertainty in a specific context should really be chosen by considering the features of the phenomenon under consideration, not independent of what is known about the system and what causes uncertainty. In this fascinating overview of the field, the authors provide broad coverage of uncertainty analysis/modeling and its application. Applied Research in Uncertainty Modeling and Analysis presents the perspectives of various researchers and practitioners on uncertainty analysis and modeling outside their own fields and domain expertise. Rather than focusing explicitly on...

A global sensitivity analysis approach for morphogenesis models

KAUST Repository

Boas, Sonja E. M.

2015-11-21

Background Morphogenesis is a developmental process in which cells organize into shapes and patterns. Complex, non-linear and multi-factorial models with images as output are commonly used to study morphogenesis. It is difficult to understand the relation between the uncertainty in the input and the output of such ‘black-box’ models, giving rise to the need for sensitivity analysis tools. In this paper, we introduce a workflow for a global sensitivity analysis approach to study the impact of single parameters and the interactions between them on the output of morphogenesis models. Results To demonstrate the workflow, we used a published, well-studied model of vascular morphogenesis. The parameters of this cellular Potts model (CPM) represent cell properties and behaviors that drive the mechanisms of angiogenic sprouting. The global sensitivity analysis correctly identified the dominant parameters in the model, consistent with previous studies. Additionally, the analysis provided information on the relative impact of single parameters and of interactions between them. This is very relevant because interactions of parameters impede the experimental verification of the predicted effect of single parameters. The parameter interactions, although of low impact, provided also new insights in the mechanisms of in silico sprouting. Finally, the analysis indicated that the model could be reduced by one parameter. Conclusions We propose global sensitivity analysis as an alternative approach to study the mechanisms of morphogenesis. Comparison of the ranking of the impact of the model parameters to knowledge derived from experimental data and from manipulation experiments can help to falsify models and to find the operand mechanisms in morphogenesis. The workflow is applicable to all ‘black-box’ models, including high-throughput in vitro models in which output measures are affected by a set of experimental perturbations.

A global sensitivity analysis approach for morphogenesis models.

Science.gov (United States)

Boas, Sonja E M; Navarro Jimenez, Maria I; Merks, Roeland M H; Blom, Joke G

2015-11-21

Morphogenesis is a developmental process in which cells organize into shapes and patterns. Complex, non-linear and multi-factorial models with images as output are commonly used to study morphogenesis. It is difficult to understand the relation between the uncertainty in the input and the output of such 'black-box' models, giving rise to the need for sensitivity analysis tools. In this paper, we introduce a workflow for a global sensitivity analysis approach to study the impact of single parameters and the interactions between them on the output of morphogenesis models. To demonstrate the workflow, we used a published, well-studied model of vascular morphogenesis. The parameters of this cellular Potts model (CPM) represent cell properties and behaviors that drive the mechanisms of angiogenic sprouting. The global sensitivity analysis correctly identified the dominant parameters in the model, consistent with previous studies. Additionally, the analysis provided information on the relative impact of single parameters and of interactions between them. This is very relevant because interactions of parameters impede the experimental verification of the predicted effect of single parameters. The parameter interactions, although of low impact, provided also new insights in the mechanisms of in silico sprouting. Finally, the analysis indicated that the model could be reduced by one parameter. We propose global sensitivity analysis as an alternative approach to study the mechanisms of morphogenesis. Comparison of the ranking of the impact of the model parameters to knowledge derived from experimental data and from manipulation experiments can help to falsify models and to find the operand mechanisms in morphogenesis. The workflow is applicable to all 'black-box' models, including high-throughput in vitro models in which output measures are affected by a set of experimental perturbations.

Experimental Design for Sensitivity Analysis of Simulation Models

NARCIS (Netherlands)

Kleijnen, J.P.C.

2001-01-01

This introductory tutorial gives a survey on the use of statistical designs for what if-or sensitivity analysis in simulation.This analysis uses regression analysis to approximate the input/output transformation that is implied by the simulation model; the resulting regression model is also known as

FAME, the Flux Analysis and Modeling Environment

Directory of Open Access Journals (Sweden)

Boele Joost

2012-01-01

Full Text Available Abstract Background The creation and modification of genome-scale metabolic models is a task that requires specialized software tools. While these are available, subsequently running or visualizing a model often relies on disjoint code, which adds additional actions to the analysis routine and, in our experience, renders these applications suboptimal for routine use by (systems biologists. Results The Flux Analysis and Modeling Environment (FAME is the first web-based modeling tool that combines the tasks of creating, editing, running, and analyzing/visualizing stoichiometric models into a single program. Analysis results can be automatically superimposed on familiar KEGG-like maps. FAME is written in PHP and uses the Python-based PySCeS-CBM for its linear solving capabilities. It comes with a comprehensive manual and a quick-start tutorial, and can be accessed online at http://f-a-m-e.org/. Conclusions With FAME, we present the community with an open source, user-friendly, web-based "one stop shop" for stoichiometric modeling. We expect the application will be of substantial use to investigators and educators alike.

Representing Uncertainty on Model Analysis Plots

Science.gov (United States)

Smith, Trevor I.

2016-01-01

Model analysis provides a mechanism for representing student learning as measured by standard multiple-choice surveys. The model plot contains information regarding both how likely students in a particular class are to choose the correct answer and how likely they are to choose an answer consistent with a well-documented conceptual model.…

Comparing model-based and model-free analysis methods for QUASAR arterial spin labeling perfusion quantification.

Science.gov (United States)

Chappell, Michael A; Woolrich, Mark W; Petersen, Esben T; Golay, Xavier; Payne, Stephen J

2013-05-01

Amongst the various implementations of arterial spin labeling MRI methods for quantifying cerebral perfusion, the QUASAR method is unique. By using a combination of labeling with and without flow suppression gradients, the QUASAR method offers the separation of macrovascular and tissue signals. This permits local arterial input functions to be defined and "model-free" analysis, using numerical deconvolution, to be used. However, it remains unclear whether arterial spin labeling data are best treated using model-free or model-based analysis. This work provides a critical comparison of these two approaches for QUASAR arterial spin labeling in the healthy brain. An existing two-component (arterial and tissue) model was extended to the mixed flow suppression scheme of QUASAR to provide an optimal model-based analysis. The model-based analysis was extended to incorporate dispersion of the labeled bolus, generally regarded as the major source of discrepancy between the two analysis approaches. Model-free and model-based analyses were compared for perfusion quantification including absolute measurements, uncertainty estimation, and spatial variation in cerebral blood flow estimates. Major sources of discrepancies between model-free and model-based analysis were attributed to the effects of dispersion and the degree to which the two methods can separate macrovascular and tissue signal. Copyright © 2012 Wiley Periodicals, Inc.

ANALYSIS AND MODELING OF GENEVA MECHANISM

Directory of Open Access Journals (Sweden)

HARAGA Georgeta

2015-06-01

Full Text Available The paper presents some aspects theoretical and practical based on the finite element analysis and modelling of Geneva mechanism with four slots, using the CATIA graphic program. This type of mechanism is an example of intermittent gearing that translates a continuous rotation into an intermittent rotary motion. It consists of alternate periods of motion and rest without reversing direction. In this paper, some design parameters with specify a Geneva mechanism will be defined precisely such as number of driving cranks, number of slots, wheel diameter, pin diameter, etc. Finite element analysis (FEA can be used for creating a finite element model (preprocessing and visualizing the analysis results (postprocessing, and use other solvers for processing.

Model Performance Evaluation and Scenario Analysis (MPESA)

Science.gov (United States)

Model Performance Evaluation and Scenario Analysis (MPESA) assesses the performance with which models predict time series data. The tool was developed Hydrological Simulation Program-Fortran (HSPF) and the Stormwater Management Model (SWMM)

Development of Wolsong Unit 2 Containment Analysis Model

Energy Technology Data Exchange (ETDEWEB)

Hoon, Choi [Korea Hydro and Nuclear Power Co., Ltd., Daejeon (Korea, Republic of); Jin, Ko Bong; Chan, Park Young [Hanbat National Univ., Daejeon (Korea, Republic of)

2014-05-15

To be prepared for the full scope safety analysis of Wolsong unit 2 with modified fuel, input decks for the various objectives, which can be read by GOTHIC 7.2b(QA), are developed and tested for the steady state simulation. A detailed nodalization of 39 control volumes and 92 flow paths is constructed to determine the differential pressure across internal walls or hydrogen concentration and distribution inside containment. A lumped model with 15 control volumes and 74 flow paths has also been developed to reduce the computer run time for the assessments in which the analysis results are not sensitive to detailed thermal hydraulic distribution inside containment such as peak pressure, pressure dependent signal and radionuclide release. The input data files provide simplified representations of the geometric layout of the containment building (volumes, dimensions, flow paths, doors, panels, etc.) and the performance characteristics of the various containment subsystems. The parameter values are based on best estimate or design values for that parameter. The analysis values are determined by conservatism depending on the analysis objective and may be different for various analysis objectives. Basic input decks of Wolsong unit 2 were developed for the various analysis purposes with GOTHIC 7.2b(QA). Depend on the analysis objective, two types of models are prepared. Detailed model models each confined room in the containment as a separate node. All of the geometric data are based on the drawings of Wolsong unit 2. Developed containment models are simulating the steady state well to the designated initial condition. These base models will be used for Wolsong unit 2 in case of safety analysis of full scope is needed.

Model Selection in Data Analysis Competitions

DEFF Research Database (Denmark)

Wind, David Kofoed; Winther, Ole

2014-01-01

The use of data analysis competitions for selecting the most appropriate model for a problem is a recent innovation in the field of predictive machine learning. Two of the most well-known examples of this trend was the Netflix Competition and recently the competitions hosted on the online platform...... performers from Kaggle and use previous personal experiences from competing in Kaggle competitions. The stated hypotheses about feature engineering, ensembling, overfitting, model complexity and evaluation metrics give indications and guidelines on how to select a proper model for performing well...... Kaggle. In this paper, we will state and try to verify a set of qualitative hypotheses about predictive modelling, both in general and in the scope of data analysis competitions. To verify our hypotheses we will look at previous competitions and their outcomes, use qualitative interviews with top...

Model Based Analysis and Test Generation for Flight Software

Science.gov (United States)

Pasareanu, Corina S.; Schumann, Johann M.; Mehlitz, Peter C.; Lowry, Mike R.; Karsai, Gabor; Nine, Harmon; Neema, Sandeep

2009-01-01

We describe a framework for model-based analysis and test case generation in the context of a heterogeneous model-based development paradigm that uses and combines Math- Works and UML 2.0 models and the associated code generation tools. This paradigm poses novel challenges to analysis and test case generation that, to the best of our knowledge, have not been addressed before. The framework is based on a common intermediate representation for different modeling formalisms and leverages and extends model checking and symbolic execution tools for model analysis and test case generation, respectively. We discuss the application of our framework to software models for a NASA flight mission.

SDI CFD MODELING ANALYSIS

Energy Technology Data Exchange (ETDEWEB)

Lee, S.

2011-05-05

The Savannah River Remediation (SRR) Organization requested that Savannah River National Laboratory (SRNL) develop a Computational Fluid Dynamics (CFD) method to mix and blend the miscible contents of the blend tanks to ensure the contents are properly blended before they are transferred from the blend tank; such as, Tank 50H, to the Salt Waste Processing Facility (SWPF) feed tank. The work described here consists of two modeling areas. They are the mixing modeling analysis during miscible liquid blending operation, and the flow pattern analysis during transfer operation of the blended liquid. The transient CFD governing equations consisting of three momentum equations, one mass balance, two turbulence transport equations for kinetic energy and dissipation rate, and one species transport were solved by an iterative technique until the species concentrations of tank fluid were in equilibrium. The steady-state flow solutions for the entire tank fluid were used for flow pattern analysis, for velocity scaling analysis, and the initial conditions for transient blending calculations. A series of the modeling calculations were performed to estimate the blending times for various jet flow conditions, and to investigate the impact of the cooling coils on the blending time of the tank contents. The modeling results were benchmarked against the pilot scale test results. All of the flow and mixing models were performed with the nozzles installed at the mid-elevation, and parallel to the tank wall. From the CFD modeling calculations, the main results are summarized as follows: (1) The benchmark analyses for the CFD flow velocity and blending models demonstrate their consistency with Engineering Development Laboratory (EDL) and literature test results in terms of local velocity measurements and experimental observations. Thus, an application of the established criterion to SRS full scale tank will provide a better, physically-based estimate of the required mixing time, and

Perturbation analysis of nonlinear matrix population models

Directory of Open Access Journals (Sweden)

Hal Caswell

2008-03-01

Full Text Available Perturbation analysis examines the response of a model to changes in its parameters. It is commonly applied to population growth rates calculated from linear models, but there has been no general approach to the analysis of nonlinear models. Nonlinearities in demographic models may arise due to density-dependence, frequency-dependence (in 2-sex models, feedback through the environment or the economy, and recruitment subsidy due to immigration, or from the scaling inherent in calculations of proportional population structure. This paper uses matrix calculus to derive the sensitivity and elasticity of equilibria, cycles, ratios (e.g. dependency ratios, age averages and variances, temporal averages and variances, life expectancies, and population growth rates, for both age-classified and stage-classified models. Examples are presented, applying the results to both human and non-human populations.

Vibrational Fingerprints of Low-Lying Pt(n)P(2n) (n = 1-5) Cluster Structures from Global Optimization Based on Density Functional Theory Potential Energy Surfaces.

Science.gov (United States)

Jedidi, Abdesslem; Li, Rui; Fornasiero, Paolo; Cavallo, Luigi; Carbonniere, Philippe

2015-12-03

Vibrational fingerprints of small Pt(n)P(2n) (n = 1-5) clusters were computed from their low-lying structures located from a global exploration of their DFT potential energy surfaces with the GSAM code. Five DFT methods were assessed from the CCSD(T) wavenumbers of PtP2 species and CCSD relative energies of Pt2P4 structures. The eight first Pt(n)P(2n) isomers found are reported. The vibrational computations reveal (i) the absence of clear signatures made by overtone or combination bands due to very weak mechanical and electrical anharmonicities and (ii) some significant and recurrent vibrational fingerprints in correlation with the different PP bonding situations in the Pt(n)P(2n) structures.

Global sensitivity analysis of computer models with functional inputs

International Nuclear Information System (INIS)

Iooss, Bertrand; Ribatet, Mathieu

2009-01-01

Global sensitivity analysis is used to quantify the influence of uncertain model inputs on the response variability of a numerical model. The common quantitative methods are appropriate with computer codes having scalar model inputs. This paper aims at illustrating different variance-based sensitivity analysis techniques, based on the so-called Sobol's indices, when some model inputs are functional, such as stochastic processes or random spatial fields. In this work, we focus on large cpu time computer codes which need a preliminary metamodeling step before performing the sensitivity analysis. We propose the use of the joint modeling approach, i.e., modeling simultaneously the mean and the dispersion of the code outputs using two interlinked generalized linear models (GLMs) or generalized additive models (GAMs). The 'mean model' allows to estimate the sensitivity indices of each scalar model inputs, while the 'dispersion model' allows to derive the total sensitivity index of the functional model inputs. The proposed approach is compared to some classical sensitivity analysis methodologies on an analytical function. Lastly, the new methodology is applied to an industrial computer code that simulates the nuclear fuel irradiation.

Horizontal crash testing and analysis of model flatrols

International Nuclear Information System (INIS)

Dowler, H.J.; Soanes, T.P.T.

1985-01-01

To assess the behaviour of a full scale flask and flatrol during a proposed demonstration impact into a tunnel abutment, a mathematical modelling technique was developed and validated. The work was performed at quarter scale and comprised of both scale model tests and mathematical analysis in one and two dimensions. Good agreement between model test results of the 26.8m/s (60 mph) abutment impacts and the mathematical analysis, validated the modelling techniques. The modelling method may be used with confidence to predict the outcome of the proposed full scale demonstration. (author)

Economic analysis model for total energy and economic systems

International Nuclear Information System (INIS)

Shoji, Katsuhiko; Yasukawa, Shigeru; Sato, Osamu

1980-09-01

This report describes framing an economic analysis model developed as a tool of total energy systems. To prospect and analyze future energy systems, it is important to analyze the relation between energy system and economic structure. We prepared an economic analysis model which was suited for this purpose. Our model marks that we can analyze in more detail energy related matters than other economic ones, and can forecast long-term economic progress rather than short-term economic fluctuation. From view point of economics, our model is longterm multi-sectoral economic analysis model of open Leontief type. Our model gave us appropriate results for fitting test and forecasting estimation. (author)

Applied data analysis and modeling for energy engineers and scientists

CERN Document Server

Reddy, T Agami

2011-01-01

""Applied Data Analysis and Modeling for Energy Engineers and Scientists"" discusses mathematical models, data analysis, and decision analysis in modeling. The approach taken in this volume focuses on the modeling and analysis of thermal systems in an engineering environment, while also covering a number of other critical areas. Other material covered includes the tools that researchers and engineering professionals will need in order to explore different analysis methods, use critical assessment skills and reach sound engineering conclusions. The book also covers process and system design and

Application of Statistical Model in Wastewater Treatment Process Modeling Using Data Analysis

Directory of Open Access Journals (Sweden)

Alireza Raygan Shirazinezhad

2015-06-01

Full Text Available Background: Wastewater treatment includes very complex and interrelated physical, chemical and biological processes which using data analysis techniques can be rigorously modeled by a non-complex mathematical calculation models. Materials and Methods: In this study, data on wastewater treatment processes from water and wastewater company of Kohgiluyeh and Boyer Ahmad were used. A total of 3306 data for COD, TSS, PH and turbidity were collected, then analyzed by SPSS-16 software (descriptive statistics and data analysis IBM SPSS Modeler 14.2, through 9 algorithm. Results: According to the results on logistic regression algorithms, neural networks, Bayesian networks, discriminant analysis, decision tree C5, tree C & R, CHAID, QUEST and SVM had accuracy precision of 90.16, 94.17, 81.37, 70.48, 97.89, 96.56, 96.46, 96.84 and 88.92, respectively. Discussion and conclusion: The C5 algorithm as the best and most applicable algorithms for modeling of wastewater treatment processes were chosen carefully with accuracy of 97.899 and the most influential variables in this model were PH, COD, TSS and turbidity.

Interactive Visual Analysis within Dynamic Ocean Models

Science.gov (United States)

Butkiewicz, T.

2012-12-01

The many observation and simulation based ocean models available today can provide crucial insights for all fields of marine research and can serve as valuable references when planning data collection missions. However, the increasing size and complexity of these models makes leveraging their contents difficult for end users. Through a combination of data visualization techniques, interactive analysis tools, and new hardware technologies, the data within these models can be made more accessible to domain scientists. We present an interactive system that supports exploratory visual analysis within large-scale ocean flow models. The currents and eddies within the models are illustrated using effective, particle-based flow visualization techniques. Stereoscopic displays and rendering methods are employed to ensure that the user can correctly perceive the complex 3D structures of depth-dependent flow patterns. Interactive analysis tools are provided which allow the user to experiment through the introduction of their customizable virtual dye particles into the models to explore regions of interest. A multi-touch interface provides natural, efficient interaction, with custom multi-touch gestures simplifying the otherwise challenging tasks of navigating and positioning tools within a 3D environment. We demonstrate the potential applications of our visual analysis environment with two examples of real-world significance: Firstly, an example of using customized particles with physics-based behaviors to simulate pollutant release scenarios, including predicting the oil plume path for the 2010 Deepwater Horizon oil spill disaster. Secondly, an interactive tool for plotting and revising proposed autonomous underwater vehicle mission pathlines with respect to the surrounding flow patterns predicted by the model; as these survey vessels have extremely limited energy budgets, designing more efficient paths allows for greater survey areas.

Modeling issues in nuclear plant fire risk analysis

International Nuclear Information System (INIS)

Siu, N.

1989-01-01

This paper discusses various issues associated with current models for analyzing the risk due to fires in nuclear power plants. Particular emphasis is placed on the fire growth and suppression models, these being unique to the fire portion of the overall risk analysis. Potentially significant modeling improvements are identified; also discussed are a variety of modeling issues where improvements will help the credibility of the analysis, without necessarily changing the computed risk significantly. The mechanistic modeling of fire initiation is identified as a particularly promising improvement for reducing the uncertainties in the predicted risk. 17 refs., 5 figs. 2 tabs

Models as Tools of Analysis of a Network Organisation

Directory of Open Access Journals (Sweden)

Wojciech Pająk

2013-06-01

Full Text Available The paper presents models which may be applied as tools of analysis of a network organisation. The starting point of the discussion is defining the following terms: supply chain and network organisation. Further parts of the paper present basic assumptions analysis of a network organisation. Then the study characterises the best known models utilised in analysis of a network organisation. The purpose of the article is to define the notion and the essence of network organizations and to present the models used for their analysis.

Sensitivity Analysis of Launch Vehicle Debris Risk Model

Science.gov (United States)

Gee, Ken; Lawrence, Scott L.

2010-01-01

As part of an analysis of the loss of crew risk associated with an ascent abort system for a manned launch vehicle, a model was developed to predict the impact risk of the debris resulting from an explosion of the launch vehicle on the crew module. The model consisted of a debris catalog describing the number, size and imparted velocity of each piece of debris, a method to compute the trajectories of the debris and a method to calculate the impact risk given the abort trajectory of the crew module. The model provided a point estimate of the strike probability as a function of the debris catalog, the time of abort and the delay time between the abort and destruction of the launch vehicle. A study was conducted to determine the sensitivity of the strike probability to the various model input parameters and to develop a response surface model for use in the sensitivity analysis of the overall ascent abort risk model. The results of the sensitivity analysis and the response surface model are presented in this paper.

Modeling, Analysis, and Optimization Issues for Large Space Structures

Science.gov (United States)

Pinson, L. D. (Compiler); Amos, A. K. (Compiler); Venkayya, V. B. (Compiler)

1983-01-01

Topics concerning the modeling, analysis, and optimization of large space structures are discussed including structure-control interaction, structural and structural dynamics modeling, thermal analysis, testing, and design.

The uncertainty analysis of model results a practical guide

CERN Document Server

Hofer, Eduard

2018-01-01

This book is a practical guide to the uncertainty analysis of computer model applications. Used in many areas, such as engineering, ecology and economics, computer models are subject to various uncertainties at the level of model formulations, parameter values and input data. Naturally, it would be advantageous to know the combined effect of these uncertainties on the model results as well as whether the state of knowledge should be improved in order to reduce the uncertainty of the results most effectively. The book supports decision-makers, model developers and users in their argumentation for an uncertainty analysis and assists them in the interpretation of the analysis results.

A Conceptual Model for Multidimensional Analysis of Documents

Science.gov (United States)

Ravat, Franck; Teste, Olivier; Tournier, Ronan; Zurlfluh, Gilles

Data warehousing and OLAP are mainly used for the analysis of transactional data. Nowadays, with the evolution of Internet, and the development of semi-structured data exchange format (such as XML), it is possible to consider entire fragments of data such as documents as analysis sources. As a consequence, an adapted multidimensional analysis framework needs to be provided. In this paper, we introduce an OLAP multidimensional conceptual model without facts. This model is based on the unique concept of dimensions and is adapted for multidimensional document analysis. We also provide a set of manipulation operations.

Evaluation of Cost Models and Needs & Gaps Analysis

DEFF Research Database (Denmark)

Kejser, Ulla Bøgvad

2014-01-01

they breakdown costs. This is followed by an in depth analysis of stakeholders’ needs for financial information derived from the 4C project stakeholder consultation.The stakeholders’ needs analysis indicated that models should:• support accounting, but more importantly they should enable budgeting• be able......his report ’D3.1—Evaluation of Cost Models and Needs & Gaps Analysis’ provides an analysis of existing research related to the economics of digital curation and cost & benefit modelling. It reports upon the investigation of how well current models and tools meet stakeholders’ needs for calculating...... andcomparing financial information. Based on this evaluation, it aims to point out gaps that need to be bridged in order to increase the uptake of cost & benefit modelling and good practices that will enable costing and comparison of the costs of alternative scenarios—which in turn provides a starting point...

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)

A Bayesian Nonparametric Meta-Analysis Model

Science.gov (United States)

Karabatsos, George; Talbott, Elizabeth; Walker, Stephen G.

2015-01-01

In a meta-analysis, it is important to specify a model that adequately describes the effect-size distribution of the underlying population of studies. The conventional normal fixed-effect and normal random-effects models assume a normal effect-size population distribution, conditionally on parameters and covariates. For estimating the mean overall…

Personalization of models with many model parameters: an efficient sensitivity analysis approach.

Science.gov (United States)

Donders, W P; Huberts, W; van de Vosse, F N; Delhaas, T

2015-10-01

Uncertainty quantification and global sensitivity analysis are indispensable for patient-specific applications of models that enhance diagnosis or aid decision-making. Variance-based sensitivity analysis methods, which apportion each fraction of the output uncertainty (variance) to the effects of individual input parameters or their interactions, are considered the gold standard. The variance portions are called the Sobol sensitivity indices and can be estimated by a Monte Carlo (MC) approach (e.g., Saltelli's method [1]) or by employing a metamodel (e.g., the (generalized) polynomial chaos expansion (gPCE) [2, 3]). All these methods require a large number of model evaluations when estimating the Sobol sensitivity indices for models with many parameters [4]. To reduce the computational cost, we introduce a two-step approach. In the first step, a subset of important parameters is identified for each output of interest using the screening method of Morris [5]. In the second step, a quantitative variance-based sensitivity analysis is performed using gPCE. Efficient sampling strategies are introduced to minimize the number of model runs required to obtain the sensitivity indices for models considering multiple outputs. The approach is tested using a model that was developed for predicting post-operative flows after creation of a vascular access for renal failure patients. We compare the sensitivity indices obtained with the novel two-step approach with those obtained from a reference analysis that applies Saltelli's MC method. The two-step approach was found to yield accurate estimates of the sensitivity indices at two orders of magnitude lower computational cost. Copyright © 2015 John Wiley & Sons, Ltd.

Integration of Design and Control through Model Analysis

DEFF Research Database (Denmark)

Russel, Boris Mariboe; Henriksen, Jens Peter; Jørgensen, Sten Bay

2002-01-01

A systematic computer aided analysis of the process model is proposed as a pre-solution step for integration of design and control problems. The process model equations are classified in terms of balance equations, constitutive equations and conditional equations. Analysis of the phenomena models...... (structure selection) issues for the integrated problems are considered. (C) 2002 Elsevier Science Ltd. All rights reserved....... representing the constitutive equations identify the relationships between the important process and design variables, which help to understand, define and address some of the issues related to integration of design and control. Furthermore, the analysis is able to identify a set of process (control) variables...

Representing uncertainty on model analysis plots

Directory of Open Access Journals (Sweden)

Trevor I. Smith

2016-09-01

Full Text Available Model analysis provides a mechanism for representing student learning as measured by standard multiple-choice surveys. The model plot contains information regarding both how likely students in a particular class are to choose the correct answer and how likely they are to choose an answer consistent with a well-documented conceptual model. Unfortunately, Bao’s original presentation of the model plot did not include a way to represent uncertainty in these measurements. I present details of a method to add error bars to model plots by expanding the work of Sommer and Lindell. I also provide a template for generating model plots with error bars.

Moderation analysis using a two-level regression model.

Science.gov (United States)

Yuan, Ke-Hai; Cheng, Ying; Maxwell, Scott

2014-10-01

Moderation analysis is widely used in social and behavioral research. The most commonly used model for moderation analysis is moderated multiple regression (MMR) in which the explanatory variables of the regression model include product terms, and the model is typically estimated by least squares (LS). This paper argues for a two-level regression model in which the regression coefficients of a criterion variable on predictors are further regressed on moderator variables. An algorithm for estimating the parameters of the two-level model by normal-distribution-based maximum likelihood (NML) is developed. Formulas for the standard errors (SEs) of the parameter estimates are provided and studied. Results indicate that, when heteroscedasticity exists, NML with the two-level model gives more efficient and more accurate parameter estimates than the LS analysis of the MMR model. When error variances are homoscedastic, NML with the two-level model leads to essentially the same results as LS with the MMR model. Most importantly, the two-level regression model permits estimating the percentage of variance of each regression coefficient that is due to moderator variables. When applied to data from General Social Surveys 1991, NML with the two-level model identified a significant moderation effect of race on the regression of job prestige on years of education while LS with the MMR model did not. An R package is also developed and documented to facilitate the application of the two-level model.

Cryogenic Fuel Tank Draining Analysis Model

Science.gov (United States)

Greer, Donald

1999-01-01

One of the technological challenges in designing advanced hypersonic aircraft and the next generation of spacecraft is developing reusable flight-weight cryogenic fuel tanks. As an aid in the design and analysis of these cryogenic tanks, a computational fluid dynamics (CFD) model has been developed specifically for the analysis of flow in a cryogenic fuel tank. This model employs the full set of Navier-Stokes equations, except that viscous dissipation is neglected in the energy equation. An explicit finite difference technique in two-dimensional generalized coordinates, approximated to second-order accuracy in both space and time is used. The stiffness resulting from the low Mach number is resolved by using artificial compressibility. The model simulates the transient, two-dimensional draining of a fuel tank cross section. To calculate the slosh wave dynamics the interface between the ullage gas and liquid fuel is modeled as a free surface. Then, experimental data for free convection inside a horizontal cylinder are compared with model results. Finally, cryogenic tank draining calculations are performed with three different wall heat fluxes to demonstrate the effect of wall heat flux on the internal tank flow field.

Adaptive streaming applications : analysis and implementation models

NARCIS (Netherlands)

Zhai, Jiali Teddy

2015-01-01

This thesis presents a highly automated design framework, called DaedalusRT, and several novel techniques. As the foundation of the DaedalusRT design framework, two types of dataflow Models-of-Computation (MoC) are used, one as timing analysis model and another one as the implementation model. The

MSSV Modeling for Wolsong-1 Safety Analysis

Energy Technology Data Exchange (ETDEWEB)

Moon, Bok Ja; Choi, Chul Jin; Kim, Seoung Rae [KEPCO EandC, Daejeon (Korea, Republic of)

2010-10-15

The main steam safety valves (MSSVs) are installed on the main steam line to prevent the overpressurization of the system. MSSVs are held in closed position by spring force and the valves pop open by internal force when the main steam pressure increases to open set pressure. If the overpressure condition is relieved, the valves begin to close. For the safety analysis of anticipated accident condition, the safety systems are modeled conservatively to simulate the accident condition more severe. MSSVs are also modeled conservatively for the analysis of over-pressurization accidents. In this paper, the pressure transient is analyzed at over-pressurization condition to evaluate the conservatism for MSSV models

Sensitivity analysis of Takagi-Sugeno-Kang rainfall-runoff fuzzy models

Directory of Open Access Journals (Sweden)

A. P. Jacquin

2009-01-01

Full Text Available This paper is concerned with the sensitivity analysis of the model parameters of the Takagi-Sugeno-Kang fuzzy rainfall-runoff models previously developed by the authors. These models are classified in two types of fuzzy models, where the first type is intended to account for the effect of changes in catchment wetness and the second type incorporates seasonality as a source of non-linearity. The sensitivity analysis is performed using two global sensitivity analysis methods, namely Regional Sensitivity Analysis and Sobol's variance decomposition. The data of six catchments from different geographical locations and sizes are used in the sensitivity analysis. The sensitivity of the model parameters is analysed in terms of several measures of goodness of fit, assessing the model performance from different points of view. These measures include the Nash-Sutcliffe criteria, volumetric errors and peak errors. The results show that the sensitivity of the model parameters depends on both the catchment type and the measure used to assess the model performance.

Automated Techniques for the Qualitative Analysis of Ecological Models: Continuous Models

Directory of Open Access Journals (Sweden)

Lynn van Coller

1997-06-01

Full Text Available The mathematics required for a detailed analysis of the behavior of a model can be formidable. In this paper, I demonstrate how various computer packages can aid qualitative analyses by implementing techniques from dynamical systems theory. Because computer software is used to obtain the results, the techniques can be used by nonmathematicians as well as mathematicians. In-depth analyses of complicated models that were previously very difficult to study can now be done. Because the paper is intended as an introduction to applying the techniques to ecological models, I have included an appendix describing some of the ideas and terminology. A second appendix shows how the techniques can be applied to a fairly simple predator-prey model and establishes the reliability of the computer software. The main body of the paper discusses a ratio-dependent model. The new techniques highlight some limitations of isocline analyses in this three-dimensional setting and show that the model is structurally unstable. Another appendix describes a larger model of a sheep-pasture-hyrax-lynx system. Dynamical systems techniques are compared with a traditional sensitivity analysis and are found to give more information. As a result, an incomplete relationship in the model is highlighted. I also discuss the resilience of these models to both parameter and population perturbations.

Modelling pesticides volatilisation in greenhouses: Sensitivity analysis of a modified PEARL model.

Science.gov (United States)

Houbraken, Michael; Doan Ngoc, Kim; van den Berg, Frederik; Spanoghe, Pieter

2017-12-01

The application of the existing PEARL model was extended to include estimations of the concentration of crop protection products in greenhouse (indoor) air due to volatilisation from the plant surface. The model was modified to include the processes of ventilation of the greenhouse air to the outside atmosphere and transformation in the air. A sensitivity analysis of the model was performed by varying selected input parameters on a one-by-one basis and comparing the model outputs with the outputs of the reference scenarios. The sensitivity analysis indicates that - in addition to vapour pressure - the model had the highest ratio of variation for the rate ventilation rate and thickness of the boundary layer on the day of application. On the days after application, competing processes, degradation and uptake in the plant, becomes more important. Copyright © 2017 Elsevier B.V. All rights reserved.

Sensitivity Analysis in Sequential Decision Models.

Science.gov (United States)

Chen, Qiushi; Ayer, Turgay; Chhatwal, Jagpreet

2017-02-01

Sequential decision problems are frequently encountered in medical decision making, which are commonly solved using Markov decision processes (MDPs). Modeling guidelines recommend conducting sensitivity analyses in decision-analytic models to assess the robustness of the model results against the uncertainty in model parameters. However, standard methods of conducting sensitivity analyses cannot be directly applied to sequential decision problems because this would require evaluating all possible decision sequences, typically in the order of trillions, which is not practically feasible. As a result, most MDP-based modeling studies do not examine confidence in their recommended policies. In this study, we provide an approach to estimate uncertainty and confidence in the results of sequential decision models. First, we provide a probabilistic univariate method to identify the most sensitive parameters in MDPs. Second, we present a probabilistic multivariate approach to estimate the overall confidence in the recommended optimal policy considering joint uncertainty in the model parameters. We provide a graphical representation, which we call a policy acceptability curve, to summarize the confidence in the optimal policy by incorporating stakeholders' willingness to accept the base case policy. For a cost-effectiveness analysis, we provide an approach to construct a cost-effectiveness acceptability frontier, which shows the most cost-effective policy as well as the confidence in that for a given willingness to pay threshold. We demonstrate our approach using a simple MDP case study. We developed a method to conduct sensitivity analysis in sequential decision models, which could increase the credibility of these models among stakeholders.

Model reduction using a posteriori analysis

KAUST Repository

Whiteley, Jonathan P.

2010-05-01

Mathematical models in biology and physiology are often represented by large systems of non-linear ordinary differential equations. In many cases, an observed behaviour may be written as a linear functional of the solution of this system of equations. A technique is presented in this study for automatically identifying key terms in the system of equations that are responsible for a given linear functional of the solution. This technique is underpinned by ideas drawn from a posteriori error analysis. This concept has been used in finite element analysis to identify regions of the computational domain and components of the solution where a fine computational mesh should be used to ensure accuracy of the numerical solution. We use this concept to identify regions of the computational domain and components of the solution where accurate representation of the mathematical model is required for accuracy of the functional of interest. The technique presented is demonstrated by application to a model problem, and then to automatically deduce known results from a cell-level cardiac electrophysiology model. © 2010 Elsevier Inc.

Model reduction using a posteriori analysis

KAUST Repository

Whiteley, Jonathan P.

2010-01-01

Mathematical models in biology and physiology are often represented by large systems of non-linear ordinary differential equations. In many cases, an observed behaviour may be written as a linear functional of the solution of this system of equations. A technique is presented in this study for automatically identifying key terms in the system of equations that are responsible for a given linear functional of the solution. This technique is underpinned by ideas drawn from a posteriori error analysis. This concept has been used in finite element analysis to identify regions of the computational domain and components of the solution where a fine computational mesh should be used to ensure accuracy of the numerical solution. We use this concept to identify regions of the computational domain and components of the solution where accurate representation of the mathematical model is required for accuracy of the functional of interest. The technique presented is demonstrated by application to a model problem, and then to automatically deduce known results from a cell-level cardiac electrophysiology model. © 2010 Elsevier Inc.

Model parameter uncertainty analysis for annual field-scale P loss model

Science.gov (United States)

Phosphorous (P) loss models are important tools for developing and evaluating conservation practices aimed at reducing P losses from agricultural fields. All P loss models, however, have an inherent amount of uncertainty associated with them. In this study, we conducted an uncertainty analysis with ...

Development of Test-Analysis Models (TAM) for correlation of dynamic test and analysis results

Science.gov (United States)

Angelucci, Filippo; Javeed, Mehzad; Mcgowan, Paul

1992-01-01

The primary objective of structural analysis of aerospace applications is to obtain a verified finite element model (FEM). The verified FEM can be used for loads analysis, evaluate structural modifications, or design control systems. Verification of the FEM is generally obtained as the result of correlating test and FEM models. A test analysis model (TAM) is very useful in the correlation process. A TAM is essentially a FEM reduced to the size of the test model, which attempts to preserve the dynamic characteristics of the original FEM in the analysis range of interest. Numerous methods for generating TAMs have been developed in the literature. The major emphasis of this paper is a description of the procedures necessary for creation of the TAM and the correlation of the reduced models with the FEM or the test results. Herein, three methods are discussed, namely Guyan, Improved Reduced System (IRS), and Hybrid. Also included are the procedures for performing these analyses using MSC/NASTRAN. Finally, application of the TAM process is demonstrated with an experimental test configuration of a ten bay cantilevered truss structure.

SBKF Modeling and Analysis Plan: Buckling Analysis of Compression-Loaded Orthogrid and Isogrid Cylinders

Science.gov (United States)

Lovejoy, Andrew E.; Hilburger, Mark W.

2013-01-01

This document outlines a Modeling and Analysis Plan (MAP) to be followed by the SBKF analysts. It includes instructions on modeling and analysis formulation and execution, model verification and validation, identifying sources of error and uncertainty, and documentation. The goal of this MAP is to provide a standardized procedure that ensures uniformity and quality of the results produced by the project and corresponding documentation.

Renewable Energy and Efficiency Modeling Analysis Partnership (REMAP): An Analysis of How Different Energy Models Addressed a Common High Renewable Energy Penetration Scenario in 2025

Energy Technology Data Exchange (ETDEWEB)

Blair, N.; Jenkin, T.; Milford, J.; Short, W.; Sullivan, P.; Evans, D.; Lieberman, E.; Goldstein, G.; Wright, E.; Jayaraman, K. R.; Venkatesh, B.; Kleiman, G.; Namovicz, C.; Smith, B.; Palmer, K.; Wiser, R.; Wood, F.

2009-09-01

Energy system modeling can be intentionally or unintentionally misused by decision-makers. This report describes how both can be minimized through careful use of models and thorough understanding of their underlying approaches and assumptions. The analysis summarized here assesses the impact that model and data choices have on forecasting energy systems by comparing seven different electric-sector models. This analysis was coordinated by the Renewable Energy and Efficiency Modeling Analysis Partnership (REMAP), a collaboration among governmental, academic, and nongovernmental participants.

Robust Linear Models for Cis-eQTL Analysis.

Science.gov (United States)

Rantalainen, Mattias; Lindgren, Cecilia M; Holmes, Christopher C

2015-01-01

Expression Quantitative Trait Loci (eQTL) analysis enables characterisation of functional genetic variation influencing expression levels of individual genes. In outbread populations, including humans, eQTLs are commonly analysed using the conventional linear model, adjusting for relevant covariates, assuming an allelic dosage model and a Gaussian error term. However, gene expression data generally have noise that induces heavy-tailed errors relative to the Gaussian distribution and often include atypical observations, or outliers. Such departures from modelling assumptions can lead to an increased rate of type II errors (false negatives), and to some extent also type I errors (false positives). Careful model checking can reduce the risk of type-I errors but often not type II errors, since it is generally too time-consuming to carefully check all models with a non-significant effect in large-scale and genome-wide studies. Here we propose the application of a robust linear model for eQTL analysis to reduce adverse effects of deviations from the assumption of Gaussian residuals. We present results from a simulation study as well as results from the analysis of real eQTL data sets. Our findings suggest that in many situations robust models have the potential to provide more reliable eQTL results compared to conventional linear models, particularly in respect to reducing type II errors due to non-Gaussian noise. Post-genomic data, such as that generated in genome-wide eQTL studies, are often noisy and frequently contain atypical observations. Robust statistical models have the potential to provide more reliable results and increased statistical power under non-Gaussian conditions. The results presented here suggest that robust models should be considered routinely alongside other commonly used methodologies for eQTL analysis.

Verification and Validation of FAARR Model and Data Envelopment Analysis Models for United States Army Recruiting

National Research Council Canada - National Science Library

Piskator, Gene

1998-01-01

...) model and to develop a Data Envelopment Analysis (DEA) modeling strategy. First, the FAARR model was verified using a simulation of a known production function and validated using sensitivity analysis and ex-post forecasts...

Derivation of Continuum Models from An Agent-based Cancer Model: Optimization and Sensitivity Analysis.

Science.gov (United States)

Voulgarelis, Dimitrios; Velayudhan, Ajoy; Smith, Frank

2017-01-01

Agent-based models provide a formidable tool for exploring complex and emergent behaviour of biological systems as well as accurate results but with the drawback of needing a lot of computational power and time for subsequent analysis. On the other hand, equation-based models can more easily be used for complex analysis in a much shorter timescale. This paper formulates an ordinary differential equations and stochastic differential equations model to capture the behaviour of an existing agent-based model of tumour cell reprogramming and applies it to optimization of possible treatment as well as dosage sensitivity analysis. For certain values of the parameter space a close match between the equation-based and agent-based models is achieved. The need for division of labour between the two approaches is explored. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Model-based safety analysis of a control system using Simulink and Simscape extended models

Directory of Open Access Journals (Sweden)

Shao Nian

2017-01-01

Full Text Available The aircraft or system safety assessment process is an integral part of the overall aircraft development cycle. It is usually characterized by a very high timely and financial effort and can become a critical design driver in certain cases. Therefore, an increasing demand of effective methods to assist the safety assessment process arises within the aerospace community. One approach is the utilization of model-based technology, which is already well-established in the system development, for safety assessment purposes. This paper mainly describes a new tool for Model-Based Safety Analysis. A formal model for an example system is generated and enriched with extended models. Then, system safety analyses are performed on the model with the assistance of automation tools and compared to the results of a manual analysis. The objective of this paper is to improve the increasingly complex aircraft systems development process. This paper develops a new model-based analysis tool in Simulink/Simscape environment.

A Hierarchical Visualization Analysis Model of Power Big Data

Science.gov (United States)

Li, Yongjie; Wang, Zheng; Hao, Yang

2018-01-01

Based on the conception of integrating VR scene and power big data analysis, a hierarchical visualization analysis model of power big data is proposed, in which levels are designed, targeting at different abstract modules like transaction, engine, computation, control and store. The regularly departed modules of power data storing, data mining and analysis, data visualization are integrated into one platform by this model. It provides a visual analysis solution for the power big data.

Traffic analysis toolbox volume XI : weather and traffic analysis, modeling and simulation.

Science.gov (United States)

2010-12-01

This document presents a weather module for the traffic analysis tools program. It provides traffic engineers, transportation modelers and decisions makers with a guide that can incorporate weather impacts into transportation system analysis and mode...

Bayesian analysis of CCDM models

Science.gov (United States)

Jesus, J. F.; Valentim, R.; Andrade-Oliveira, F.

2017-09-01

Creation of Cold Dark Matter (CCDM), in the context of Einstein Field Equations, produces a negative pressure term which can be used to explain the accelerated expansion of the Universe. In this work we tested six different spatially flat models for matter creation using statistical criteria, in light of SNe Ia data: Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and Bayesian Evidence (BE). These criteria allow to compare models considering goodness of fit and number of free parameters, penalizing excess of complexity. We find that JO model is slightly favoured over LJO/ΛCDM model, however, neither of these, nor Γ = 3αH0 model can be discarded from the current analysis. Three other scenarios are discarded either because poor fitting or because of the excess of free parameters. A method of increasing Bayesian evidence through reparameterization in order to reducing parameter degeneracy is also developed.

Bayesian analysis of CCDM models

Energy Technology Data Exchange (ETDEWEB)

Jesus, J.F. [Universidade Estadual Paulista (Unesp), Câmpus Experimental de Itapeva, Rua Geraldo Alckmin 519, Vila N. Sra. de Fátima, Itapeva, SP, 18409-010 Brazil (Brazil); Valentim, R. [Departamento de Física, Instituto de Ciências Ambientais, Químicas e Farmacêuticas—ICAQF, Universidade Federal de São Paulo (UNIFESP), Unidade José Alencar, Rua São Nicolau No. 210, Diadema, SP, 09913-030 Brazil (Brazil); Andrade-Oliveira, F., E-mail: jfjesus@itapeva.unesp.br, E-mail: valentim.rodolfo@unifesp.br, E-mail: felipe.oliveira@port.ac.uk [Institute of Cosmology and Gravitation—University of Portsmouth, Burnaby Road, Portsmouth, PO1 3FX United Kingdom (United Kingdom)

2017-09-01

Creation of Cold Dark Matter (CCDM), in the context of Einstein Field Equations, produces a negative pressure term which can be used to explain the accelerated expansion of the Universe. In this work we tested six different spatially flat models for matter creation using statistical criteria, in light of SNe Ia data: Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and Bayesian Evidence (BE). These criteria allow to compare models considering goodness of fit and number of free parameters, penalizing excess of complexity. We find that JO model is slightly favoured over LJO/ΛCDM model, however, neither of these, nor Γ = 3α H {sub 0} model can be discarded from the current analysis. Three other scenarios are discarded either because poor fitting or because of the excess of free parameters. A method of increasing Bayesian evidence through reparameterization in order to reducing parameter degeneracy is also developed.

Energy Systems Modelling Research and Analysis

DEFF Research Database (Denmark)

Møller Andersen, Frits; Alberg Østergaard, Poul

2015-01-01

This editorial introduces the seventh volume of the International Journal of Sustainable Energy Planning and Management. The volume presents part of the outcome of the project Energy Systems Modelling Research and Analysis (ENSYMORA) funded by the Danish Innovation Fund. The project carried out b...... by 11 university and industry partners has improved the basis for decision-making within energy planning and energy scenario making by providing new and improved tools and methods for energy systems analyses.......This editorial introduces the seventh volume of the International Journal of Sustainable Energy Planning and Management. The volume presents part of the outcome of the project Energy Systems Modelling Research and Analysis (ENSYMORA) funded by the Danish Innovation Fund. The project carried out...

Parametric Analysis of Flexible Logic Control Model

Directory of Open Access Journals (Sweden)

Lihua Fu

2013-01-01

Full Text Available Based on deep analysis about the essential relation between two input variables of normal two-dimensional fuzzy controller, we used universal combinatorial operation model to describe the logic relationship and gave a flexible logic control method to realize the effective control for complex system. In practical control application, how to determine the general correlation coefficient of flexible logic control model is a problem for further studies. First, the conventional universal combinatorial operation model has been limited in the interval [0,1]. Consequently, this paper studies a kind of universal combinatorial operation model based on the interval [a,b]. And some important theorems are given and proved, which provide a foundation for the flexible logic control method. For dealing reasonably with the complex relations of every factor in complex system, a kind of universal combinatorial operation model with unequal weights is put forward. Then, this paper has carried out the parametric analysis of flexible logic control model. And some research results have been given, which have important directive to determine the values of the general correlation coefficients in practical control application.

International Space Station Model Correlation Analysis

Science.gov (United States)

Laible, Michael R.; Fitzpatrick, Kristin; Hodge, Jennifer; Grygier, Michael

2018-01-01

This paper summarizes the on-orbit structural dynamic data and the related modal analysis, model validation and correlation performed for the International Space Station (ISS) configuration ISS Stage ULF7, 2015 Dedicated Thruster Firing (DTF). The objective of this analysis is to validate and correlate the analytical models used to calculate the ISS internal dynamic loads and compare the 2015 DTF with previous tests. During the ISS configurations under consideration, on-orbit dynamic measurements were collected using the three main ISS instrumentation systems; Internal Wireless Instrumentation System (IWIS), External Wireless Instrumentation System (EWIS) and the Structural Dynamic Measurement System (SDMS). The measurements were recorded during several nominal on-orbit DTF tests on August 18, 2015. Experimental modal analyses were performed on the measured data to extract modal parameters including frequency, damping, and mode shape information. Correlation and comparisons between test and analytical frequencies and mode shapes were performed to assess the accuracy of the analytical models for the configurations under consideration. These mode shapes were also compared to earlier tests. Based on the frequency comparisons, the accuracy of the mathematical models is assessed and model refinement recommendations are given. In particular, results of the first fundamental mode will be discussed, nonlinear results will be shown, and accelerometer placement will be assessed.

Systems thinking, the Swiss Cheese Model and accident analysis: a comparative systemic analysis of the Grayrigg train derailment using the ATSB, AcciMap and STAMP models.

Science.gov (United States)

Underwood, Peter; Waterson, Patrick

2014-07-01

The Swiss Cheese Model (SCM) is the most popular accident causation model and is widely used throughout various industries. A debate exists in the research literature over whether the SCM remains a viable tool for accident analysis. Critics of the model suggest that it provides a sequential, oversimplified view of accidents. Conversely, proponents suggest that it embodies the concepts of systems theory, as per the contemporary systemic analysis techniques. The aim of this paper was to consider whether the SCM can provide a systems thinking approach and remain a viable option for accident analysis. To achieve this, the train derailment at Grayrigg was analysed with an SCM-based model (the ATSB accident investigation model) and two systemic accident analysis methods (AcciMap and STAMP). The analysis outputs and usage of the techniques were compared. The findings of the study showed that each model applied the systems thinking approach. However, the ATSB model and AcciMap graphically presented their findings in a more succinct manner, whereas STAMP more clearly embodied the concepts of systems theory. The study suggests that, whilst the selection of an analysis method is subject to trade-offs that practitioners and researchers must make, the SCM remains a viable model for accident analysis. Copyright © 2013 Elsevier Ltd. All rights reserved.

Dynamical analysis of a PWR internals using super-elements in an integrated 3-D model model. Part 2: dynamical tests and seismic analysis

International Nuclear Information System (INIS)

Jesus Miranda, C.A. de.

1992-01-01

The results of the test analysis (frequencies) for the isolated super-elements and for the developed 3-D model of the internals core support structures of a PWR research reactor are presented. Once certified of the model effectiveness for this type of analysis the seismic spectral analysis was performed. From the results can be seen that the structures are rigid for this load, isolated or together with the other in the 3-D model, and there are no impacts among them during the earthquake (OBE). (author)

Evaluation of RCAS Inflow Models for Wind Turbine Analysis

Energy Technology Data Exchange (ETDEWEB)

Tangler, J.; Bir, G.

2004-02-01

The finite element structural modeling in the Rotorcraft Comprehensive Analysis System (RCAS) provides a state-of-the-art approach to aeroelastic analysis. This, coupled with its ability to model all turbine components, results in a methodology that can simulate complex system interactions characteristic of large wind. In addition, RCAS is uniquely capable of modeling advanced control algorithms and the resulting dynamic responses.

Topic Modeling in Sentiment Analysis: A Systematic Review

Directory of Open Access Journals (Sweden)

Toqir Ahmad Rana

2016-06-01

Full Text Available With the expansion and acceptance of Word Wide Web, sentiment analysis has become progressively popular research area in information retrieval and web data analysis. Due to the huge amount of user-generated contents over blogs, forums, social media, etc., sentiment analysis has attracted researchers both in academia and industry, since it deals with the extraction of opinions and sentiments. In this paper, we have presented a review of topic modeling, especially LDA-based techniques, in sentiment analysis. We have presented a detailed analysis of diverse approaches and techniques, and compared the accuracy of different systems among them. The results of different approaches have been summarized, analyzed and presented in a sophisticated fashion. This is the really effort to explore different topic modeling techniques in the capacity of sentiment analysis and imparting a comprehensive comparison among them.

Analytic uncertainty and sensitivity analysis of models with input correlations

Science.gov (United States)

Zhu, Yueying; Wang, Qiuping A.; Li, Wei; Cai, Xu

2018-03-01

Probabilistic uncertainty analysis is a common means of evaluating mathematical models. In mathematical modeling, the uncertainty in input variables is specified through distribution laws. Its contribution to the uncertainty in model response is usually analyzed by assuming that input variables are independent of each other. However, correlated parameters are often happened in practical applications. In the present paper, an analytic method is built for the uncertainty and sensitivity analysis of models in the presence of input correlations. With the method, it is straightforward to identify the importance of the independence and correlations of input variables in determining the model response. This allows one to decide whether or not the input correlations should be considered in practice. Numerical examples suggest the effectiveness and validation of our analytic method in the analysis of general models. A practical application of the method is also proposed to the uncertainty and sensitivity analysis of a deterministic HIV model.

Two sustainable energy system analysis models

DEFF Research Database (Denmark)

Lund, Henrik; Goran Krajacic, Neven Duic; da Graca Carvalho, Maria

2005-01-01

This paper presents a comparative study of two energy system analysis models both designed with the purpose of analysing electricity systems with a substantial share of fluctuating renewable energy....

Sensitivity Analysis for Urban Drainage Modeling Using Mutual Information

Directory of Open Access Journals (Sweden)

Chuanqi Li

2014-11-01

Full Text Available The intention of this paper is to evaluate the sensitivity of the Storm Water Management Model (SWMM output to its input parameters. A global parameter sensitivity analysis is conducted in order to determine which parameters mostly affect the model simulation results. Two different methods of sensitivity analysis are applied in this study. The first one is the partial rank correlation coefficient (PRCC which measures nonlinear but monotonic relationships between model inputs and outputs. The second one is based on the mutual information which provides a general measure of the strength of the non-monotonic association between two variables. Both methods are based on the Latin Hypercube Sampling (LHS of the parameter space, and thus the same datasets can be used to obtain both measures of sensitivity. The utility of the PRCC and the mutual information analysis methods are illustrated by analyzing a complex SWMM model. The sensitivity analysis revealed that only a few key input variables are contributing significantly to the model outputs; PRCCs and mutual information are calculated and used to determine and rank the importance of these key parameters. This study shows that the partial rank correlation coefficient and mutual information analysis can be considered effective methods for assessing the sensitivity of the SWMM model to the uncertainty in its input parameters.

A sensitivity analysis of the WIPP disposal room model: Phase 1

Energy Technology Data Exchange (ETDEWEB)

Labreche, D.A.; Beikmann, M.A. [RE/SPEC, Inc., Albuquerque, NM (United States); Osnes, J.D. [RE/SPEC, Inc., Rapid City, SD (United States); Butcher, B.M. [Sandia National Labs., Albuquerque, NM (United States)

1995-07-01

The WIPP Disposal Room Model (DRM) is a numerical model with three major components constitutive models of TRU waste, crushed salt backfill, and intact halite -- and several secondary components, including air gap elements, slidelines, and assumptions on symmetry and geometry. A sensitivity analysis of the Disposal Room Model was initiated on two of the three major components (waste and backfill models) and on several secondary components as a group. The immediate goal of this component sensitivity analysis (Phase I) was to sort (rank) model parameters in terms of their relative importance to model response so that a Monte Carlo analysis on a reduced set of DRM parameters could be performed under Phase II. The goal of the Phase II analysis will be to develop a probabilistic definition of a disposal room porosity surface (porosity, gas volume, time) that could be used in WIPP Performance Assessment analyses. This report documents a literature survey which quantifies the relative importance of the secondary room components to room closure, a differential analysis of the creep consolidation model and definition of a follow-up Monte Carlo analysis of the model, and an analysis and refitting of the waste component data on which a volumetric plasticity model of TRU drum waste is based. A summary, evaluation of progress, and recommendations for future work conclude the report.

Personalization of models with many model parameters : an efficient sensitivity analysis approach

NARCIS (Netherlands)

Donders, W.P.; Huberts, W.; van de Vosse, F.N.; Delhaas, T.

2015-01-01

Uncertainty quantification and global sensitivity analysis are indispensable for patient-specific applications of models that enhance diagnosis or aid decision-making. Variance-based sensitivity analysis methods, which apportion each fraction of the output uncertainty (variance) to the effects of

Credit Risk Evaluation : Modeling - Analysis - Management

OpenAIRE

Wehrspohn, Uwe

2002-01-01

An analysis and further development of the building blocks of modern credit risk management: -Definitions of default -Estimation of default probabilities -Exposures -Recovery Rates -Pricing -Concepts of portfolio dependence -Time horizons for risk calculations -Quantification of portfolio risk -Estimation of risk measures -Portfolio analysis and portfolio improvement -Evaluation and comparison of credit risk models -Analytic portfolio loss distributions The thesis contributes to the evaluatio...

Modeling and analysis of cell membrane systems with probabilistic model checking

Science.gov (United States)

2011-01-01

Background Recently there has been a growing interest in the application of Probabilistic Model Checking (PMC) for the formal specification of biological systems. PMC is able to exhaustively explore all states of a stochastic model and can provide valuable insight into its behavior which are more difficult to see using only traditional methods for system analysis such as deterministic and stochastic simulation. In this work we propose a stochastic modeling for the description and analysis of sodium-potassium exchange pump. The sodium-potassium pump is a membrane transport system presents in all animal cell and capable of moving sodium and potassium ions against their concentration gradient. Results We present a quantitative formal specification of the pump mechanism in the PRISM language, taking into consideration a discrete chemistry approach and the Law of Mass Action aspects. We also present an analysis of the system using quantitative properties in order to verify the pump reversibility and understand the pump behavior using trend labels for the transition rates of the pump reactions. Conclusions Probabilistic model checking can be used along with other well established approaches such as simulation and differential equations to better understand pump behavior. Using PMC we can determine if specific events happen such as the potassium outside the cell ends in all model traces. We can also have a more detailed perspective on its behavior such as determining its reversibility and why its normal operation becomes slow over time. This knowledge can be used to direct experimental research and make it more efficient, leading to faster and more accurate scientific discoveries. PMID:22369714

Sensitivity analysis technique for application to deterministic models

International Nuclear Information System (INIS)

Ishigami, T.; Cazzoli, E.; Khatib-Rahbar, M.; Unwin, S.D.

1987-01-01

The characterization of sever accident source terms for light water reactors should include consideration of uncertainties. An important element of any uncertainty analysis is an evaluation of the sensitivity of the output probability distributions reflecting source term uncertainties to assumptions regarding the input probability distributions. Historically, response surface methods (RSMs) were developed to replace physical models using, for example, regression techniques, with simplified models for example, regression techniques, with simplified models for extensive calculations. The purpose of this paper is to present a new method for sensitivity analysis that does not utilize RSM, but instead relies directly on the results obtained from the original computer code calculations. The merits of this approach are demonstrated by application of the proposed method to the suppression pool aerosol removal code (SPARC), and the results are compared with those obtained by sensitivity analysis with (a) the code itself, (b) a regression model, and (c) Iman's method

Dynamic data analysis modeling data with differential equations

CERN Document Server

Ramsay, James

2017-01-01

This text focuses on the use of smoothing methods for developing and estimating differential equations following recent developments in functional data analysis and building on techniques described in Ramsay and Silverman (2005) Functional Data Analysis. The central concept of a dynamical system as a buffer that translates sudden changes in input into smooth controlled output responses has led to applications of previously analyzed data, opening up entirely new opportunities for dynamical systems. The technical level has been kept low so that those with little or no exposure to differential equations as modeling objects can be brought into this data analysis landscape. There are already many texts on the mathematical properties of ordinary differential equations, or dynamic models, and there is a large literature distributed over many fields on models for real world processes consisting of differential equations. However, a researcher interested in fitting such a model to data, or a statistician interested in...

Three-dimensional model analysis and processing

CERN Document Server

Yu, Faxin; Luo, Hao; Wang, Pinghui

2011-01-01

This book focuses on five hot research directions in 3D model analysis and processing in computer science:  compression, feature extraction, content-based retrieval, irreversible watermarking and reversible watermarking.

Aircraft/Air Traffic Management Functional Analysis Model: Technical Description. 2.0

Science.gov (United States)

Etheridge, Melvin; Plugge, Joana; Retina, Nusrat

1998-01-01

The Aircraft/Air Traffic Management Functional Analysis Model, Version 2.0 (FAM 2.0), is a discrete event simulation model designed to support analysis of alternative concepts in air traffic management and control. FAM 2.0 was developed by the Logistics Management Institute (LMI) under a National Aeronautics and Space Administration (NASA) contract. This document provides a technical description of FAM 2.0 and its computer files to enable the modeler and programmer to make enhancements or modifications to the model. Those interested in a guide for using the model in analysis should consult the companion document, Aircraft/Air Traffic Management Functional Analysis Model, Version 2.0 Users Manual.

Similar words analysis based on POS-CBOW language model

Directory of Open Access Journals (Sweden)

Dongru RUAN

2015-10-01

Full Text Available Similar words analysis is one of the important aspects in the field of natural language processing, and it has important research and application values in text classification, machine translation and information recommendation. Focusing on the features of Sina Weibo's short text, this paper presents a language model named as POS-CBOW, which is a kind of continuous bag-of-words language model with the filtering layer and part-of-speech tagging layer. The proposed approach can adjust the word vectors' similarity according to the cosine similarity and the word vectors' part-of-speech metrics. It can also filter those similar words set on the base of the statistical analysis model. The experimental result shows that the similar words analysis algorithm based on the proposed POS-CBOW language model is better than that based on the traditional CBOW language model.

FAME, the flux analysis and modelling environment

NARCIS (Netherlands)

Boele, J.; Olivier, B.G.; Teusink, B.

2012-01-01

Background: The creation and modification of genome-scale metabolic models is a task that requires specialized software tools. While these are available, subsequently running or visualizing a model often relies on disjoint code, which adds additional actions to the analysis routine and, in our

How Many Separable Sources? Model Selection In Independent Components Analysis

DEFF Research Database (Denmark)

Woods, Roger P.; Hansen, Lars Kai; Strother, Stephen

2015-01-01

among potential model categories with differing numbers of Gaussian components. Based on simulation studies, the assumptions and approximations underlying the Akaike Information Criterion do not hold in this setting, even with a very large number of observations. Cross-validation is a suitable, though....../Principal Components Analysis (mixed ICA/PCA) model described here accommodates one or more Gaussian components in the independent components analysis model and uses principal components analysis to characterize contributions from this inseparable Gaussian subspace. Information theory can then be used to select from...... might otherwise be questionable. Failure of the Akaike Information Criterion in model selection also has relevance in traditional independent components analysis where all sources are assumed non-Gaussian....

Comparative Analysis of Investment Decision Models

Directory of Open Access Journals (Sweden)

Ieva Kekytė

2017-06-01

Full Text Available Rapid development of financial markets resulted new challenges for both investors and investment issues. This increased demand for innovative, modern investment and portfolio management decisions adequate for market conditions. Financial market receives special attention, creating new models, includes financial risk management and investment decision support systems.Researchers recognize the need to deal with financial problems using models consistent with the reality and based on sophisticated quantitative analysis technique. Thus, role mathematical modeling in finance becomes important. This article deals with various investments decision-making models, which include forecasting, optimization, stochatic processes, artificial intelligence, etc., and become useful tools for investment decisions.

Perturbation analysis for Monte Carlo continuous cross section models

International Nuclear Information System (INIS)

Kennedy, Chris B.; Abdel-Khalik, Hany S.

2011-01-01

Sensitivity analysis, including both its forward and adjoint applications, collectively referred to hereinafter as Perturbation Analysis (PA), is an essential tool to complete Uncertainty Quantification (UQ) and Data Assimilation (DA). PA-assisted UQ and DA have traditionally been carried out for reactor analysis problems using deterministic as opposed to stochastic models for radiation transport. This is because PA requires many model executions to quantify how variations in input data, primarily cross sections, affect variations in model's responses, e.g. detectors readings, flux distribution, multiplication factor, etc. Although stochastic models are often sought for their higher accuracy, their repeated execution is at best computationally expensive and in reality intractable for typical reactor analysis problems involving many input data and output responses. Deterministic methods however achieve computational efficiency needed to carry out the PA analysis by reducing problem dimensionality via various spatial and energy homogenization assumptions. This however introduces modeling error components into the PA results which propagate to the following UQ and DA analyses. The introduced errors are problem specific and therefore are expected to limit the applicability of UQ and DA analyses to reactor systems that satisfy the introduced assumptions. This manuscript introduces a new method to complete PA employing a continuous cross section stochastic model and performed in a computationally efficient manner. If successful, the modeling error components introduced by deterministic methods could be eliminated, thereby allowing for wider applicability of DA and UQ results. Two MCNP models demonstrate the application of the new method - a Critical Pu Sphere (Jezebel), a Pu Fast Metal Array (Russian BR-1). The PA is completed for reaction rate densities, reaction rate ratios, and the multiplication factor. (author)

Bayesian Sensitivity Analysis of a Nonlinear Dynamic Factor Analysis Model with Nonparametric Prior and Possible Nonignorable Missingness.

Science.gov (United States)

Tang, Niansheng; Chow, Sy-Miin; Ibrahim, Joseph G; Zhu, Hongtu

2017-12-01

Many psychological concepts are unobserved and usually represented as latent factors apprehended through multiple observed indicators. When multiple-subject multivariate time series data are available, dynamic factor analysis models with random effects offer one way of modeling patterns of within- and between-person variations by combining factor analysis and time series analysis at the factor level. Using the Dirichlet process (DP) as a nonparametric prior for individual-specific time series parameters further allows the distributional forms of these parameters to deviate from commonly imposed (e.g., normal or other symmetric) functional forms, arising as a result of these parameters' restricted ranges. Given the complexity of such models, a thorough sensitivity analysis is critical but computationally prohibitive. We propose a Bayesian local influence method that allows for simultaneous sensitivity analysis of multiple modeling components within a single fitting of the model of choice. Five illustrations and an empirical example are provided to demonstrate the utility of the proposed approach in facilitating the detection of outlying cases and common sources of misspecification in dynamic factor analysis models, as well as identification of modeling components that are sensitive to changes in the DP prior specification.

Modeling and analysis of stochastic systems

CERN Document Server

Kulkarni, Vidyadhar G

2011-01-01

Based on the author's more than 25 years of teaching experience, Modeling and Analysis of Stochastic Systems, Second Edition covers the most important classes of stochastic processes used in the modeling of diverse systems, from supply chains and inventory systems to genetics and biological systems. For each class of stochastic process, the text includes its definition, characterization, applications, transient and limiting behavior, first passage times, and cost/reward models. Along with reorganizing the material, this edition revises and adds new exercises and examples. New to the second edi

Independent Component Analysis in Multimedia Modeling

DEFF Research Database (Denmark)

Larsen, Jan

2003-01-01

largely refers to text, images/video, audio and combinations of such data. We review a number of applications within single and combined media with the hope that this might provide inspiration for further research in this area. Finally, we provide a detailed presentation of our own recent work on modeling......Modeling of multimedia and multimodal data becomes increasingly important with the digitalization of the world. The objective of this paper is to demonstrate the potential of independent component analysis and blind sources separation methods for modeling and understanding of multimedia data, which...

Modeling and Analysis of Component Faults and Reliability

DEFF Research Database (Denmark)

Le Guilly, Thibaut; Olsen, Petur; Ravn, Anders Peter

2016-01-01

This chapter presents a process to design and validate models of reactive systems in the form of communicating timed automata. The models are extended with faults associated with probabilities of occurrence. This enables a fault tree analysis of the system using minimal cut sets that are automati......This chapter presents a process to design and validate models of reactive systems in the form of communicating timed automata. The models are extended with faults associated with probabilities of occurrence. This enables a fault tree analysis of the system using minimal cut sets...... that are automatically generated. The stochastic information on the faults is used to estimate the reliability of the fault affected system. The reliability is given with respect to properties of the system state space. We illustrate the process on a concrete example using the Uppaal model checker for validating...... the ideal system model and the fault modeling. Then the statistical version of the tool, UppaalSMC, is used to find reliability estimates....

Coping with Complexity Model Reduction and Data Analysis

CERN Document Server

Gorban, Alexander N

2011-01-01

This volume contains the extended version of selected talks given at the international research workshop 'Coping with Complexity: Model Reduction and Data Analysis', Ambleside, UK, August 31 - September 4, 2009. This book is deliberately broad in scope and aims at promoting new ideas and methodological perspectives. The topics of the chapters range from theoretical analysis of complex and multiscale mathematical models to applications in e.g., fluid dynamics and chemical kinetics.

Sensitivity analysis and optimization of system dynamics models : Regression analysis and statistical design of experiments

NARCIS (Netherlands)

Kleijnen, J.P.C.

1995-01-01

This tutorial discusses what-if analysis and optimization of System Dynamics models. These problems are solved, using the statistical techniques of regression analysis and design of experiments (DOE). These issues are illustrated by applying the statistical techniques to a System Dynamics model for

Modeling time-to-event (survival) data using classification tree analysis.

Science.gov (United States)

Linden, Ariel; Yarnold, Paul R

2017-12-01

Time to the occurrence of an event is often studied in health research. Survival analysis differs from other designs in that follow-up times for individuals who do not experience the event by the end of the study (called censored) are accounted for in the analysis. Cox regression is the standard method for analysing censored data, but the assumptions required of these models are easily violated. In this paper, we introduce classification tree analysis (CTA) as a flexible alternative for modelling censored data. Classification tree analysis is a "decision-tree"-like classification model that provides parsimonious, transparent (ie, easy to visually display and interpret) decision rules that maximize predictive accuracy, derives exact P values via permutation tests, and evaluates model cross-generalizability. Using empirical data, we identify all statistically valid, reproducible, longitudinally consistent, and cross-generalizable CTA survival models and then compare their predictive accuracy to estimates derived via Cox regression and an unadjusted naïve model. Model performance is assessed using integrated Brier scores and a comparison between estimated survival curves. The Cox regression model best predicts average incidence of the outcome over time, whereas CTA survival models best predict either relatively high, or low, incidence of the outcome over time. Classification tree analysis survival models offer many advantages over Cox regression, such as explicit maximization of predictive accuracy, parsimony, statistical robustness, and transparency. Therefore, researchers interested in accurate prognoses and clear decision rules should consider developing models using the CTA-survival framework. © 2017 John Wiley & Sons, Ltd.

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.

Bayesian nonparametric meta-analysis using Polya tree mixture models.

Science.gov (United States)

Branscum, Adam J; Hanson, Timothy E

2008-09-01

Summary. A common goal in meta-analysis is estimation of a single effect measure using data from several studies that are each designed to address the same scientific inquiry. Because studies are typically conducted in geographically disperse locations, recent developments in the statistical analysis of meta-analytic data involve the use of random effects models that account for study-to-study variability attributable to differences in environments, demographics, genetics, and other sources that lead to heterogeneity in populations. Stemming from asymptotic theory, study-specific summary statistics are modeled according to normal distributions with means representing latent true effect measures. A parametric approach subsequently models these latent measures using a normal distribution, which is strictly a convenient modeling assumption absent of theoretical justification. To eliminate the influence of overly restrictive parametric models on inferences, we consider a broader class of random effects distributions. We develop a novel hierarchical Bayesian nonparametric Polya tree mixture (PTM) model. We present methodology for testing the PTM versus a normal random effects model. These methods provide researchers a straightforward approach for conducting a sensitivity analysis of the normality assumption for random effects. An application involving meta-analysis of epidemiologic studies designed to characterize the association between alcohol consumption and breast cancer is presented, which together with results from simulated data highlight the performance of PTMs in the presence of nonnormality of effect measures in the source population.

Hidden-Markov-Model Analysis Of Telemanipulator Data

Science.gov (United States)

Hannaford, Blake; Lee, Paul

1991-01-01

Mathematical model and procedure based on hidden-Markov-model concept undergoing development for use in analysis and prediction of outputs of force and torque sensors of telerobotic manipulators. In model, overall task broken down into subgoals, and transition probabilities encode ease with which operator completes each subgoal. Process portion of model encodes task-sequence/subgoal structure, and probability-density functions for forces and torques associated with each state of manipulation encode sensor signals that one expects to observe at subgoal. Parameters of model constructed from engineering knowledge of task.

How Many Separable Sources? Model Selection In Independent Components Analysis

Science.gov (United States)

Woods, Roger P.; Hansen, Lars Kai; Strother, Stephen

2015-01-01

Unlike mixtures consisting solely of non-Gaussian sources, mixtures including two or more Gaussian components cannot be separated using standard independent components analysis methods that are based on higher order statistics and independent observations. The mixed Independent Components Analysis/Principal Components Analysis (mixed ICA/PCA) model described here accommodates one or more Gaussian components in the independent components analysis model and uses principal components analysis to characterize contributions from this inseparable Gaussian subspace. Information theory can then be used to select from among potential model categories with differing numbers of Gaussian components. Based on simulation studies, the assumptions and approximations underlying the Akaike Information Criterion do not hold in this setting, even with a very large number of observations. Cross-validation is a suitable, though computationally intensive alternative for model selection. Application of the algorithm is illustrated using Fisher's iris data set and Howells' craniometric data set. Mixed ICA/PCA is of potential interest in any field of scientific investigation where the authenticity of blindly separated non-Gaussian sources might otherwise be questionable. Failure of the Akaike Information Criterion in model selection also has relevance in traditional independent components analysis where all sources are assumed non-Gaussian. PMID:25811988

Sensitivity analysis practices: Strategies for model-based inference

Energy Technology Data Exchange (ETDEWEB)

Saltelli, Andrea [Institute for the Protection and Security of the Citizen (IPSC), European Commission, Joint Research Centre, TP 361, 21020 Ispra (Vatican City State, Holy See,) (Italy)]. E-mail: andrea.saltelli@jrc.it; Ratto, Marco [Institute for the Protection and Security of the Citizen (IPSC), European Commission, Joint Research Centre, TP 361, 21020 Ispra (VA) (Italy); Tarantola, Stefano [Institute for the Protection and Security of the Citizen (IPSC), European Commission, Joint Research Centre, TP 361, 21020 Ispra (VA) (Italy); Campolongo, Francesca [Institute for the Protection and Security of the Citizen (IPSC), European Commission, Joint Research Centre, TP 361, 21020 Ispra (VA) (Italy)

2006-10-15

Fourteen years after Science's review of sensitivity analysis (SA) methods in 1989 (System analysis at molecular scale, by H. Rabitz) we search Science Online to identify and then review all recent articles having 'sensitivity analysis' as a keyword. In spite of the considerable developments which have taken place in this discipline, of the good practices which have emerged, and of existing guidelines for SA issued on both sides of the Atlantic, we could not find in our review other than very primitive SA tools, based on 'one-factor-at-a-time' (OAT) approaches. In the context of model corroboration or falsification, we demonstrate that this use of OAT methods is illicit and unjustified, unless the model under analysis is proved to be linear. We show that available good practices, such as variance based measures and others, are able to overcome OAT shortcomings and easy to implement. These methods also allow the concept of factors importance to be defined rigorously, thus making the factors importance ranking univocal. We analyse the requirements of SA in the context of modelling, and present best available practices on the basis of an elementary model. We also point the reader to available recipes for a rigorous SA.

Sensitivity analysis practices: Strategies for model-based inference

International Nuclear Information System (INIS)

Saltelli, Andrea; Ratto, Marco; Tarantola, Stefano; Campolongo, Francesca

2006-01-01

Fourteen years after Science's review of sensitivity analysis (SA) methods in 1989 (System analysis at molecular scale, by H. Rabitz) we search Science Online to identify and then review all recent articles having 'sensitivity analysis' as a keyword. In spite of the considerable developments which have taken place in this discipline, of the good practices which have emerged, and of existing guidelines for SA issued on both sides of the Atlantic, we could not find in our review other than very primitive SA tools, based on 'one-factor-at-a-time' (OAT) approaches. In the context of model corroboration or falsification, we demonstrate that this use of OAT methods is illicit and unjustified, unless the model under analysis is proved to be linear. We show that available good practices, such as variance based measures and others, are able to overcome OAT shortcomings and easy to implement. These methods also allow the concept of factors importance to be defined rigorously, thus making the factors importance ranking univocal. We analyse the requirements of SA in the context of modelling, and present best available practices on the basis of an elementary model. We also point the reader to available recipes for a rigorous SA

Ignalina NPP Safety Analysis: Models and Results

International Nuclear Information System (INIS)

Uspuras, E.

1999-01-01

Research directions, linked to safety assessment of the Ignalina NPP, of the scientific safety analysis group are presented: Thermal-hydraulic analysis of accidents and operational transients; Thermal-hydraulic assessment of Ignalina NPP Accident Localization System and other compartments; Structural analysis of plant components, piping and other parts of Main Circulation Circuit; Assessment of RBMK-1500 reactor core and other. Models and main works carried out last year are described. (author)

Automatic differentiation algorithms in model analysis

NARCIS (Netherlands)

Huiskes, M.J.

2002-01-01

Title: Automatic differentiation algorithms in model analysis
Author: M.J. Huiskes
Date: 19 March, 2002

In this thesis automatic differentiation algorithms and derivative-based methods

Model parameter uncertainty analysis for an annual field-scale phosphorus loss model

Science.gov (United States)

Phosphorous (P) loss models are important tools for developing and evaluating conservation practices aimed at reducing P losses from agricultural fields. All P loss models, however, have an inherent amount of uncertainty associated with them. In this study, we conducted an uncertainty analysis with ...

Integrated dynamic modeling and management system mission analysis

Energy Technology Data Exchange (ETDEWEB)

Lee, A.K.

1994-12-28

This document summarizes the mission analysis performed on the Integrated Dynamic Modeling and Management System (IDMMS). The IDMMS will be developed to provide the modeling and analysis capability required to understand the TWRS system behavior in terms of the identified TWRS performance measures. The IDMMS will be used to demonstrate in a verified and validated manner the satisfactory performance of the TWRS system configuration and assurance that the requirements have been satisfied.

Integrated dynamic modeling and management system mission analysis

International Nuclear Information System (INIS)

Lee, A.K.

1994-01-01

This document summarizes the mission analysis performed on the Integrated Dynamic Modeling and Management System (IDMMS). The IDMMS will be developed to provide the modeling and analysis capability required to understand the TWRS system behavior in terms of the identified TWRS performance measures. The IDMMS will be used to demonstrate in a verified and validated manner the satisfactory performance of the TWRS system configuration and assurance that the requirements have been satisfied

Trojan detection model based on network behavior analysis

International Nuclear Information System (INIS)

Liu Junrong; Liu Baoxu; Wang Wenjin

2012-01-01

Based on the analysis of existing Trojan detection technology, this paper presents a Trojan detection model based on network behavior analysis. First of all, we abstract description of the Trojan network behavior, then according to certain rules to establish the characteristic behavior library, and then use the support vector machine algorithm to determine whether a Trojan invasion. Finally, through the intrusion detection experiments, shows that this model can effectively detect Trojans. (authors)

A hierarchical analysis of terrestrial ecosystem model Biome-BGC: Equilibrium analysis and model calibration

Energy Technology Data Exchange (ETDEWEB)

Thornton, Peter E [ORNL; Wang, Weile [ORNL; Law, Beverly E. [Oregon State University; Nemani, Ramakrishna R [NASA Ames Research Center

2009-01-01

The increasing complexity of ecosystem models represents a major difficulty in tuning model parameters and analyzing simulated results. To address this problem, this study develops a hierarchical scheme that simplifies the Biome-BGC model into three functionally cascaded tiers and analyzes them sequentially. The first-tier model focuses on leaf-level ecophysiological processes; it simulates evapotranspiration and photosynthesis with prescribed leaf area index (LAI). The restriction on LAI is then lifted in the following two model tiers, which analyze how carbon and nitrogen is cycled at the whole-plant level (the second tier) and in all litter/soil pools (the third tier) to dynamically support the prescribed canopy. In particular, this study analyzes the steady state of these two model tiers by a set of equilibrium equations that are derived from Biome-BGC algorithms and are based on the principle of mass balance. Instead of spinning-up the model for thousands of climate years, these equations are able to estimate carbon/nitrogen stocks and fluxes of the target (steady-state) ecosystem directly from the results obtained by the first-tier model. The model hierarchy is examined with model experiments at four AmeriFlux sites. The results indicate that the proposed scheme can effectively calibrate Biome-BGC to simulate observed fluxes of evapotranspiration and photosynthesis; and the carbon/nitrogen stocks estimated by the equilibrium analysis approach are highly consistent with the results of model simulations. Therefore, the scheme developed in this study may serve as a practical guide to calibrate/analyze Biome-BGC; it also provides an efficient way to solve the problem of model spin-up, especially for applications over large regions. The same methodology may help analyze other similar ecosystem models as well.

Prior Sensitivity Analysis in Default Bayesian Structural Equation Modeling.

Science.gov (United States)

van Erp, Sara; Mulder, Joris; Oberski, Daniel L

2017-11-27

Bayesian structural equation modeling (BSEM) has recently gained popularity because it enables researchers to fit complex models and solve some of the issues often encountered in classical maximum likelihood estimation, such as nonconvergence and inadmissible solutions. An important component of any Bayesian analysis is the prior distribution of the unknown model parameters. Often, researchers rely on default priors, which are constructed in an automatic fashion without requiring substantive prior information. However, the prior can have a serious influence on the estimation of the model parameters, which affects the mean squared error, bias, coverage rates, and quantiles of the estimates. In this article, we investigate the performance of three different default priors: noninformative improper priors, vague proper priors, and empirical Bayes priors-with the latter being novel in the BSEM literature. Based on a simulation study, we find that these three default BSEM methods may perform very differently, especially with small samples. A careful prior sensitivity analysis is therefore needed when performing a default BSEM analysis. For this purpose, we provide a practical step-by-step guide for practitioners to conducting a prior sensitivity analysis in default BSEM. Our recommendations are illustrated using a well-known case study from the structural equation modeling literature, and all code for conducting the prior sensitivity analysis is available in the online supplemental materials. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Global plastic models for computerized structural analysis

International Nuclear Information System (INIS)

Roche, R.L.; Hoffmann, A.

1977-01-01

In many types of structures, it is possible to use generalized stresses (like membrane forces, bending moment, torsion moment...) to define a yield surface for a part of the structure. Analysis can be achieved by using the HILL's principle and a hardening rule. The whole formulation is said 'Global Plastic Model'. Two different global models are used in the CEASEMT system for structural analysis, one for shell analysis and the other for piping analysis (in plastic or creep field). In shell analysis the generalized stresses chosen are the membrane forces and bending (including torsion) moments. There is only one yield condition for a normal to the middle surface and no integration along the thickness is required. In piping analysis, the choice of generalized stresses is bending moments, torsional moment, hoop stress and tension stress. There is only a set of stresses for a cross section and no integration over the cross section area is needed. Connected strains are axis curvature, torsion, uniform strains. The definition of the yield surface is the most important item. A practical way is to use a diagonal quadratic function of the stress components. But the coefficients are depending of the shape of the pipe element, especially for curved segments. Indications will be given on the yield functions used. Some examples of applications in structural analysis are added to the text

MMA, A Computer Code for Multi-Model Analysis

Science.gov (United States)

Poeter, Eileen P.; Hill, Mary C.

2007-01-01

This report documents the Multi-Model Analysis (MMA) computer code. MMA can be used to evaluate results from alternative models of a single system using the same set of observations for all models. As long as the observations, the observation weighting, and system being represented are the same, the models can differ in nearly any way imaginable. For example, they may include different processes, different simulation software, different temporal definitions (for example, steady-state and transient models could be considered), and so on. The multiple models need to be calibrated by nonlinear regression. Calibration of the individual models needs to be completed before application of MMA. MMA can be used to rank models and calculate posterior model probabilities. These can be used to (1) determine the relative importance of the characteristics embodied in the alternative models, (2) calculate model-averaged parameter estimates and predictions, and (3) quantify the uncertainty of parameter estimates and predictions in a way that integrates the variations represented by the alternative models. There is a lack of consensus on what model analysis methods are best, so MMA provides four default methods. Two are based on Kullback-Leibler information, and use the AIC (Akaike Information Criterion) or AICc (second-order-bias-corrected AIC) model discrimination criteria. The other two default methods are the BIC (Bayesian Information Criterion) and the KIC (Kashyap Information Criterion) model discrimination criteria. Use of the KIC criterion is equivalent to using the maximum-likelihood Bayesian model averaging (MLBMA) method. AIC, AICc, and BIC can be derived from Frequentist or Bayesian arguments. The default methods based on Kullback-Leibler information have a number of theoretical advantages, including that they tend to favor more complicated models as more data become available than do the other methods, which makes sense in many situations. Many applications of MMA will

Guideliness for system modeling: fault tree [analysis

Energy Technology Data Exchange (ETDEWEB)

Lee, Yoon Hwan; Yang, Joon Eon; Kang, Dae Il; Hwang, Mee Jeong

2004-07-01

This document, the guidelines for system modeling related to Fault Tree Analysis(FTA), is intended to provide the guidelines with the analyzer to construct the fault trees in the level of the capability category II of ASME PRA standard. Especially, they are to provide the essential and basic guidelines and the related contents to be used in support of revising the Ulchin 3 and 4 PSA model for risk monitor within the capability category II of ASME PRA standard. Normally the main objective of system analysis is to assess the reliability of system modeled by Event Tree Analysis (ETA). A variety of analytical techniques can be used for the system analysis, however, FTA method is used in this procedures guide. FTA is the method used for representing the failure logic of plant systems deductively using AND, OR or NOT gates. The fault tree should reflect all possible failure modes that may contribute to the system unavailability. This should include contributions due to the mechanical failures of the components, Common Cause Failures (CCFs), human errors and outages for testing and maintenance. This document identifies and describes the definitions and the general procedures of FTA and the essential and basic guidelines for reving the fault trees. Accordingly, the guidelines for FTA will be capable to guide the FTA to the level of the capability category II of ASME PRA standard.

Guideliness for system modeling: fault tree [analysis

International Nuclear Information System (INIS)

Lee, Yoon Hwan; Yang, Joon Eon; Kang, Dae Il; Hwang, Mee Jeong

2004-07-01

This document, the guidelines for system modeling related to Fault Tree Analysis(FTA), is intended to provide the guidelines with the analyzer to construct the fault trees in the level of the capability category II of ASME PRA standard. Especially, they are to provide the essential and basic guidelines and the related contents to be used in support of revising the Ulchin 3 and 4 PSA model for risk monitor within the capability category II of ASME PRA standard. Normally the main objective of system analysis is to assess the reliability of system modeled by Event Tree Analysis (ETA). A variety of analytical techniques can be used for the system analysis, however, FTA method is used in this procedures guide. FTA is the method used for representing the failure logic of plant systems deductively using AND, OR or NOT gates. The fault tree should reflect all possible failure modes that may contribute to the system unavailability. This should include contributions due to the mechanical failures of the components, Common Cause Failures (CCFs), human errors and outages for testing and maintenance. This document identifies and describes the definitions and the general procedures of FTA and the essential and basic guidelines for reving the fault trees. Accordingly, the guidelines for FTA will be capable to guide the FTA to the level of the capability category II of ASME PRA standard

Urban Sprawl Analysis and Modeling in Asmara, Eritrea

Directory of Open Access Journals (Sweden)

Mussie G. Tewolde

2011-09-01

Full Text Available The extension of urban perimeter markedly cuts available productive land. Hence, studies in urban sprawl analysis and modeling play an important role to ensure sustainable urban development. The urbanization pattern of the Greater Asmara Area (GAA, the capital of Eritrea, was studied. Satellite images and geospatial tools were employed to analyze the spatiotemporal urban landuse changes. Object-Based Image Analysis (OBIA, Landuse Cover Change (LUCC analysis and urban sprawl analysis using Shannon Entropy were carried out. The Land Change Modeler (LCM was used to develop a model of urban growth. The Multi-layer Perceptron Neural Network was employed to model the transition potential maps with an accuracy of 85.9% and these were used as an input for the ‘actual’ urban modeling with Markov chains. Model validation was assessed and a scenario of urban land use change of the GAA up to year 2020 was presented. The result of the study indicated that the built-up area has tripled in size (increased by 4,441 ha between 1989 and 2009. Specially, after year 2000 urban sprawl in GAA caused large scale encroachment on high potential agricultural lands and plantation cover. The scenario for year 2020 shows an increase of the built-up areas by 1,484 ha (25% which may cause further loss. The study indicated that the land allocation system in the GAA overrode the landuse plan, which caused the loss of agricultural land and plantation cover. The recommended policy options might support decision makers to resolve further loss of agricultural land and plantation cover and to achieve sustainable urban development planning in the GAA.

Conceptual models for waste tank mechanistic analysis

International Nuclear Information System (INIS)

Allemann, R.T.; Antoniak, Z.I.; Eyler, L.L.; Liljegren, L.M.; Roberts, J.S.

1992-02-01

Pacific Northwest Laboratory (PNL) is conducting a study for Westinghouse Hanford Company (Westinghouse Hanford), a contractor for the US Department of Energy (DOE). The purpose of the work is to study possible mechanisms and fluid dynamics contributing to the periodic release of gases from double-shell waste storage tanks at the Hanford Site in Richland, Washington. This interim report emphasizing the modeling work follows two other interim reports, Mechanistic Analysis of Double-Shell Tank Gas Release Progress Report -- November 1990 and Collection and Analysis of Existing Data for Waste Tank Mechanistic Analysis Progress Report -- December 1990, that emphasized data correlation and mechanisms. The approach in this study has been to assemble and compile data that are pertinent to the mechanisms, analyze the data, evaluate physical properties and parameters, evaluate hypothetical mechanisms, and develop mathematical models of mechanisms

Online Statistical Modeling (Regression Analysis) for Independent Responses

Science.gov (United States)

Made Tirta, I.; Anggraeni, Dian; Pandutama, Martinus

2017-06-01

Regression analysis (statistical analmodelling) are among statistical methods which are frequently needed in analyzing quantitative data, especially to model relationship between response and explanatory variables. Nowadays, statistical models have been developed into various directions to model various type and complex relationship of data. Rich varieties of advanced and recent statistical modelling are mostly available on open source software (one of them is R). However, these advanced statistical modelling, are not very friendly to novice R users, since they are based on programming script or command line interface. Our research aims to developed web interface (based on R and shiny), so that most recent and advanced statistical modelling are readily available, accessible and applicable on web. We have previously made interface in the form of e-tutorial for several modern and advanced statistical modelling on R especially for independent responses (including linear models/LM, generalized linier models/GLM, generalized additive model/GAM and generalized additive model for location scale and shape/GAMLSS). In this research we unified them in the form of data analysis, including model using Computer Intensive Statistics (Bootstrap and Markov Chain Monte Carlo/ MCMC). All are readily accessible on our online Virtual Statistics Laboratory. The web (interface) make the statistical modeling becomes easier to apply and easier to compare them in order to find the most appropriate model for the data.

Environmental modeling and health risk analysis (ACTS/RISK)

National Research Council Canada - National Science Library

Aral, M. M

2010-01-01

... presents a review of the topics of exposure and health risk analysis. The Analytical Contaminant Transport Analysis System (ACTS) and Health RISK Analysis (RISK) software tools are an integral part of the book and provide computational platforms for all the models discussed herein. The most recent versions of these two softwa...

Cost-effectiveness Analysis in R Using a Multi-state Modeling Survival Analysis Framework: A Tutorial.

Science.gov (United States)

Williams, Claire; Lewsey, James D; Briggs, Andrew H; Mackay, Daniel F

2017-05-01

This tutorial provides a step-by-step guide to performing cost-effectiveness analysis using a multi-state modeling approach. Alongside the tutorial, we provide easy-to-use functions in the statistics package R. We argue that this multi-state modeling approach using a package such as R has advantages over approaches where models are built in a spreadsheet package. In particular, using a syntax-based approach means there is a written record of what was done and the calculations are transparent. Reproducing the analysis is straightforward as the syntax just needs to be run again. The approach can be thought of as an alternative way to build a Markov decision-analytic model, which also has the option to use a state-arrival extended approach. In the state-arrival extended multi-state model, a covariate that represents patients' history is included, allowing the Markov property to be tested. We illustrate the building of multi-state survival models, making predictions from the models and assessing fits. We then proceed to perform a cost-effectiveness analysis, including deterministic and probabilistic sensitivity analyses. Finally, we show how to create 2 common methods of visualizing the results-namely, cost-effectiveness planes and cost-effectiveness acceptability curves. The analysis is implemented entirely within R. It is based on adaptions to functions in the existing R package mstate to accommodate parametric multi-state modeling that facilitates extrapolation of survival curves.

A Requirements Analysis Model Based on QFD

Institute of Scientific and Technical Information of China (English)

TANG Zhi-wei; Nelson K.H.Tang

2004-01-01

The enterprise resource planning (ERP) system has emerged to offer an integrated IT solution and more and more enterprises are increasing by adopting this system and regarding it as an important innovation. However, there is already evidence of high failure risks in ERP project implementation, one major reason is poor analysis of the requirements for system implementation. In this paper, the importance of requirements analysis for ERP project implementation is highlighted, and a requirements analysis model by applying quality function deployment (QFD) is presented, which will support to conduct requirements analysis for ERP project.

ISAC: A tool for aeroservoelastic modeling and analysis

Science.gov (United States)

Adams, William M., Jr.; Hoadley, Sherwood Tiffany

1993-01-01

The capabilities of the Interaction of Structures, Aerodynamics, and Controls (ISAC) system of program modules is discussed. The major modeling, analysis, and data management components of ISAC are identified. Equations of motion are displayed for a Laplace-domain representation of the unsteady aerodynamic forces. Options for approximating a frequency-domain representation of unsteady aerodynamic forces with rational functions of the Laplace variable are shown. Linear time invariant state-space equations of motion that result are discussed. Model generation and analyses of stability and dynamic response characteristics are shown for an aeroelastic vehicle which illustrates some of the capabilities of ISAC as a modeling and analysis tool for aeroelastic applications.

Neutrosophic Logic for Mental Model Elicitation and Analysis

Directory of Open Access Journals (Sweden)

Karina Pérez-Teruel

2014-03-01

Full Text Available Mental models are personal, internal representations of external reality that people use to interact with the world around them. They are useful in multiple situations such as muticriteria decision making, knowledge management, complex system learning and analysis. In this paper a framework for mental models elicitation and analysis based on neutrosophic Logic is presented. An illustrative example is provided to show the applicability of the proposal. The paper ends with conclusion future research directions.

Model based process-product design and analysis

DEFF Research Database (Denmark)

Gani, Rafiqul

This paper gives a perspective on modelling and the important role it has within product-process design and analysis. Different modelling issues related to development and application of systematic model-based solution approaches for product-process design is discussed and the need for a hybrid...... model-based framework is highlighted. This framework should be able to manage knowledge-data, models, and associated methods and tools integrated with design work-flows and data-flows for specific product-process design problems. In particular, the framework needs to manage models of different types......, forms and complexity, together with their associated parameters. An example of a model-based system for design of chemicals based formulated products is also given....

Inverse Analysis and Modeling for Tunneling Thrust on Shield Machine

Directory of Open Access Journals (Sweden)

Qian Zhang

2013-01-01

Full Text Available With the rapid development of sensor and detection technologies, measured data analysis plays an increasingly important role in the design and control of heavy engineering equipment. The paper proposed a method for inverse analysis and modeling based on mass on-site measured data, in which dimensional analysis and data mining techniques were combined. The method was applied to the modeling of the tunneling thrust on shield machines and an explicit expression for thrust prediction was established. Combined with on-site data from a tunneling project in China, the inverse identification of model coefficients was carried out using the multiple regression method. The model residual was analyzed by statistical methods. By comparing the on-site data and the model predicted results in the other two projects with different tunneling conditions, the feasibility of the model was discussed. The work may provide a scientific basis for the rational design and control of shield tunneling machines and also a new way for mass on-site data analysis of complex engineering systems with nonlinear, multivariable, time-varying characteristics.

Bayesian Sensitivity Analysis of Statistical Models with Missing Data.

Science.gov (United States)

Zhu, Hongtu; Ibrahim, Joseph G; Tang, Niansheng

2014-04-01

Methods for handling missing data depend strongly on the mechanism that generated the missing values, such as missing completely at random (MCAR) or missing at random (MAR), as well as other distributional and modeling assumptions at various stages. It is well known that the resulting estimates and tests may be sensitive to these assumptions as well as to outlying observations. In this paper, we introduce various perturbations to modeling assumptions and individual observations, and then develop a formal sensitivity analysis to assess these perturbations in the Bayesian analysis of statistical models with missing data. We develop a geometric framework, called the Bayesian perturbation manifold, to characterize the intrinsic structure of these perturbations. We propose several intrinsic influence measures to perform sensitivity analysis and quantify the effect of various perturbations to statistical models. We use the proposed sensitivity analysis procedure to systematically investigate the tenability of the non-ignorable missing at random (NMAR) assumption. Simulation studies are conducted to evaluate our methods, and a dataset is analyzed to illustrate the use of our diagnostic measures.

Computer Models for IRIS Control System Transient Analysis

International Nuclear Information System (INIS)

Gary D Storrick; Bojan Petrovic; Luca Oriani

2007-01-01

This report presents results of the Westinghouse work performed under Task 3 of this Financial Assistance Award and it satisfies a Level 2 Milestone for the project. Task 3 of the collaborative effort between ORNL, Brazil and Westinghouse for the International Nuclear Energy Research Initiative entitled 'Development of Advanced Instrumentation and Control for an Integrated Primary System Reactor' focuses on developing computer models for transient analysis. This report summarizes the work performed under Task 3 on developing control system models. The present state of the IRIS plant design--such as the lack of a detailed secondary system or I and C system designs--makes finalizing models impossible at this time. However, this did not prevent making considerable progress. Westinghouse has several working models in use to further the IRIS design. We expect to continue modifying the models to incorporate the latest design information until the final IRIS unit becomes operational. Section 1.2 outlines the scope of this report. Section 2 describes the approaches we are using for non-safety transient models. It describes the need for non-safety transient analysis and the model characteristics needed to support those analyses. Section 3 presents the RELAP5 model. This is the highest-fidelity model used for benchmark evaluations. However, it is prohibitively slow for routine evaluations and additional lower-fidelity models have been developed. Section 4 discusses the current Matlab/Simulink model. This is a low-fidelity, high-speed model used to quickly evaluate and compare competing control and protection concepts. Section 5 describes the Modelica models developed by POLIMI and Westinghouse. The object-oriented Modelica language provides convenient mechanisms for developing models at several levels of detail. We have used this to develop a high-fidelity model for detailed analyses and a faster-running simplified model to help speed the I and C development process. Section

Analysis on the crime model using dynamical approach

Science.gov (United States)

Mohammad, Fazliza; Roslan, Ummu'Atiqah Mohd

2017-08-01

A research is carried out to analyze a dynamical model of the spread crime system. A Simplified 2-Dimensional Model is used in this research. The objectives of this research are to investigate the stability of the model of the spread crime, to summarize the stability by using a bifurcation analysis and to study the relationship of basic reproduction number, R0 with the parameter in the model. Our results for stability of equilibrium points shows that we have two types of stability, which are asymptotically stable and saddle node. While the result for bifurcation analysis shows that the number of criminally active and incarcerated increases as we increase the value of a parameter in the model. The result for the relationship of R0 with the parameter shows that as the parameter increases, R0 increase too, and the rate of crime increase too.

Critical analysis of algebraic collective models

International Nuclear Information System (INIS)

Moshinsky, M.

1986-01-01

The author shall understand by algebraic collective models all those based on specific Lie algebras, whether the latter are suggested through simple shell model considerations like in the case of the Interacting Boson Approximation (IBA), or have a detailed microscopic foundation like the symplectic model. To analyze these models critically, it is convenient to take a simple conceptual example of them in which all steps can be implemented analytically or through elementary numerical analysis. In this note he takes as an example the symplectic model in a two dimensional space i.e. based on a sp(4,R) Lie algebra, and show how through its complete discussion we can get a clearer understanding of the structure of algebraic collective models of nuclei. In particular he discusses the association of Hamiltonians, related to maximal subalgebras of our basic Lie algebra, with specific types of spectra, and the connections between spectra and shapes

Performance analysis and dynamic modeling of a single-spool turbojet engine

Science.gov (United States)

Andrei, Irina-Carmen; Toader, Adrian; Stroe, Gabriela; Frunzulica, Florin

2017-01-01

The purposes of modeling and simulation of a turbojet engine are the steady state analysis and transient analysis. From the steady state analysis, which consists in the investigation of the operating, equilibrium regimes and it is based on appropriate modeling describing the operation of a turbojet engine at design and off-design regimes, results the performance analysis, concluded by the engine's operational maps (i.e. the altitude map, velocity map and speed map) and the engine's universal map. The mathematical model that allows the calculation of the design and off-design performances, in case of a single spool turbojet is detailed. An in house code was developed, its calibration was done for the J85 turbojet engine as the test case. The dynamic modeling of the turbojet engine is obtained from the energy balance equations for compressor, combustor and turbine, as the engine's main parts. The transient analysis, which is based on appropriate modeling of engine and its main parts, expresses the dynamic behavior of the turbojet engine, and further, provides details regarding the engine's control. The aim of the dynamic analysis is to determine a control program for the turbojet, based on the results provided by performance analysis. In case of the single-spool turbojet engine, with fixed nozzle geometry, the thrust is controlled by one parameter, which is the fuel flow rate. The design and management of the aircraft engine controls are based on the results of the transient analysis. The construction of the design model is complex, since it is based on both steady-state and transient analysis, further allowing the flight path cycle analysis and optimizations. This paper presents numerical simulations for a single-spool turbojet engine (J85 as test case), with appropriate modeling for steady-state and dynamic analysis.

Model-based human reliability analysis: prospects and requirements

International Nuclear Information System (INIS)

Mosleh, A.; Chang, Y.H.

2004-01-01

Major limitations of the conventional methods for human reliability analysis (HRA), particularly those developed for operator response analysis in probabilistic safety assessments (PSA) of nuclear power plants, are summarized as a motivation for the need and a basis for developing requirements for the next generation HRA methods. It is argued that a model-based approach that provides explicit cognitive causal links between operator behaviors and directly or indirectly measurable causal factors should be at the core of the advanced methods. An example of such causal model is briefly reviewed, where due to the model complexity and input requirements can only be currently implemented in a dynamic PSA environment. The computer simulation code developed for this purpose is also described briefly, together with current limitations in the models, data, and the computer implementation

Discussion of OECD LWR Uncertainty Analysis in Modelling Benchmark

International Nuclear Information System (INIS)

Ivanov, K.; Avramova, M.; Royer, E.; Gillford, J.

2013-01-01

The demand for best estimate calculations in nuclear reactor design and safety evaluations has increased in recent years. Uncertainty quantification has been highlighted as part of the best estimate calculations. The modelling aspects of uncertainty and sensitivity analysis are to be further developed and validated on scientific grounds in support of their performance and application to multi-physics reactor simulations. The Organization for Economic Co-operation and Development (OECD) / Nuclear Energy Agency (NEA) Nuclear Science Committee (NSC) has endorsed the creation of an Expert Group on Uncertainty Analysis in Modelling (EGUAM). Within the framework of activities of EGUAM/NSC the OECD/NEA initiated the Benchmark for Uncertainty Analysis in Modelling for Design, Operation, and Safety Analysis of Light Water Reactor (OECD LWR UAM benchmark). The general objective of the benchmark is to propagate the predictive uncertainties of code results through complex coupled multi-physics and multi-scale simulations. The benchmark is divided into three phases with Phase I highlighting the uncertainty propagation in stand-alone neutronics calculations, while Phase II and III are focused on uncertainty analysis of reactor core and system respectively. This paper discusses the progress made in Phase I calculations, the Specifications for Phase II and the incoming challenges in defining Phase 3 exercises. The challenges of applying uncertainty quantification to complex code systems, in particular the time-dependent coupled physics models are the large computational burden and the utilization of non-linear models (expected due to the physics coupling). (authors)

Three dimensional mathematical model of tooth for finite element analysis

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Puškar Tatjana

2010-01-01

Full Text Available Introduction. The mathematical model of the abutment tooth is the starting point of the finite element analysis of stress and deformation of dental structures. The simplest and easiest way is to form a model according to the literature data of dimensions and morphological characteristics of teeth. Our method is based on forming 3D models using standard geometrical forms (objects in programmes for solid modeling. Objective. Forming the mathematical model of abutment of the second upper premolar for finite element analysis of stress and deformation of dental structures. Methods. The abutment tooth has a form of a complex geometric object. It is suitable for modeling in programs for solid modeling SolidWorks. After analyzing the literature data about the morphological characteristics of teeth, we started the modeling dividing the tooth (complex geometric body into simple geometric bodies (cylinder, cone, pyramid,.... Connecting simple geometric bodies together or substricting bodies from the basic body, we formed complex geometric body, tooth. The model is then transferred into Abaqus, a computational programme for finite element analysis. Transferring the data was done by standard file format for transferring 3D models ACIS SAT. Results. Using the programme for solid modeling SolidWorks, we developed three models of abutment of the second maxillary premolar: the model of the intact abutment, the model of the endodontically treated tooth with two remaining cavity walls and the model of the endodontically treated tooth with two remaining walls and inserted post. Conclusion Mathematical models of the abutment made according to the literature data are very similar with the real abutment and the simplifications are minimal. These models enable calculations of stress and deformation of the dental structures. The finite element analysis provides useful information in understanding biomechanical problems and gives guidance for clinical research.

Integrative Analysis of Metabolic Models – from Structure to Dynamics

Energy Technology Data Exchange (ETDEWEB)

Hartmann, Anja, E-mail: hartmann@ipk-gatersleben.de [Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben (Germany); Schreiber, Falk [Monash University, Melbourne, VIC (Australia); Martin-Luther-University Halle-Wittenberg, Halle (Germany)

2015-01-26

The characterization of biological systems with respect to their behavior and functionality based on versatile biochemical interactions is a major challenge. To understand these complex mechanisms at systems level modeling approaches are investigated. Different modeling formalisms allow metabolic models to be analyzed depending on the question to be solved, the biochemical knowledge and the availability of experimental data. Here, we describe a method for an integrative analysis of the structure and dynamics represented by qualitative and quantitative metabolic models. Using various formalisms, the metabolic model is analyzed from different perspectives. Determined structural and dynamic properties are visualized in the context of the metabolic model. Interaction techniques allow the exploration and visual analysis thereby leading to a broader understanding of the behavior and functionality of the underlying biological system. The System Biology Metabolic Model Framework (SBM{sup 2} – Framework) implements the developed method and, as an example, is applied for the integrative analysis of the crop plant potato.

ADAM: analysis of discrete models of biological systems using computer algebra.

Science.gov (United States)

Hinkelmann, Franziska; Brandon, Madison; Guang, Bonny; McNeill, Rustin; Blekherman, Grigoriy; Veliz-Cuba, Alan; Laubenbacher, Reinhard

2011-07-20

Many biological systems are modeled qualitatively with discrete models, such as probabilistic Boolean networks, logical models, Petri nets, and agent-based models, to gain a better understanding of them. The computational complexity to analyze the complete dynamics of these models grows exponentially in the number of variables, which impedes working with complex models. There exist software tools to analyze discrete models, but they either lack the algorithmic functionality to analyze complex models deterministically or they are inaccessible to many users as they require understanding the underlying algorithm and implementation, do not have a graphical user interface, or are hard to install. Efficient analysis methods that are accessible to modelers and easy to use are needed. We propose a method for efficiently identifying attractors and introduce the web-based tool Analysis of Dynamic Algebraic Models (ADAM), which provides this and other analysis methods for discrete models. ADAM converts several discrete model types automatically into polynomial dynamical systems and analyzes their dynamics using tools from computer algebra. Specifically, we propose a method to identify attractors of a discrete model that is equivalent to solving a system of polynomial equations, a long-studied problem in computer algebra. Based on extensive experimentation with both discrete models arising in systems biology and randomly generated networks, we found that the algebraic algorithms presented in this manuscript are fast for systems with the structure maintained by most biological systems, namely sparseness and robustness. For a large set of published complex discrete models, ADAM identified the attractors in less than one second. Discrete modeling techniques are a useful tool for analyzing complex biological systems and there is a need in the biological community for accessible efficient analysis tools. ADAM provides analysis methods based on mathematical algorithms as a web

LBLOCA sensitivity analysis using meta models

International Nuclear Information System (INIS)

Villamizar, M.; Sanchez-Saez, F.; Villanueva, J.F.; Carlos, S.; Sanchez, A.I.; Martorell, S.

2014-01-01

This paper presents an approach to perform the sensitivity analysis of the results of simulation of thermal hydraulic codes within a BEPU approach. Sensitivity analysis is based on the computation of Sobol' indices that makes use of a meta model, It presents also an application to a Large-Break Loss of Coolant Accident, LBLOCA, in the cold leg of a pressurized water reactor, PWR, addressing the results of the BEMUSE program and using the thermal-hydraulic code TRACE. (authors)

Formal Modeling and Analysis of Timed Systems

DEFF Research Database (Denmark)

Larsen, Kim Guldstrand; Niebert, Peter

This book constitutes the thoroughly refereed post-proceedings of the First International Workshop on Formal Modeling and Analysis of Timed Systems, FORMATS 2003, held in Marseille, France in September 2003. The 19 revised full papers presented together with an invited paper and the abstracts of ...... systems, discrete time systems, timed languages, and real-time operating systems....... of two invited talks were carefully selected from 36 submissions during two rounds of reviewing and improvement. All current aspects of formal method for modeling and analyzing timed systems are addressed; among the timed systems dealt with are timed automata, timed Petri nets, max-plus algebras, real-time......This book constitutes the thoroughly refereed post-proceedings of the First International Workshop on Formal Modeling and Analysis of Timed Systems, FORMATS 2003, held in Marseille, France in September 2003. The 19 revised full papers presented together with an invited paper and the abstracts...

Failure Propagation Modeling and Analysis via System Interfaces

Directory of Open Access Journals (Sweden)

Lin Zhao

2016-01-01

Full Text Available Safety-critical systems must be shown to be acceptably safe to deploy and use in their operational environment. One of the key concerns of developing safety-critical systems is to understand how the system behaves in the presence of failures, regardless of whether that failure is triggered by the external environment or caused by internal errors. Safety assessment at the early stages of system development involves analysis of potential failures and their consequences. Increasingly, for complex systems, model-based safety assessment is becoming more widely used. In this paper we propose an approach for safety analysis based on system interface models. By extending interaction models on the system interface level with failure modes as well as relevant portions of the physical system to be controlled, automated support could be provided for much of the failure analysis. We focus on fault modeling and on how to compute minimal cut sets. Particularly, we explore state space reconstruction strategy and bounded searching technique to reduce the number of states that need to be analyzed, which remarkably improves the efficiency of cut sets searching algorithm.

Sensitivity and uncertainty analysis of the PATHWAY radionuclide transport model

International Nuclear Information System (INIS)

Otis, M.D.

1983-01-01

Procedures were developed for the uncertainty and sensitivity analysis of a dynamic model of radionuclide transport through human food chains. Uncertainty in model predictions was estimated by propagation of parameter uncertainties using a Monte Carlo simulation technique. Sensitivity of model predictions to individual parameters was investigated using the partial correlation coefficient of each parameter with model output. Random values produced for the uncertainty analysis were used in the correlation analysis for sensitivity. These procedures were applied to the PATHWAY model which predicts concentrations of radionuclides in foods grown in Nevada and Utah and exposed to fallout during the period of atmospheric nuclear weapons testing in Nevada. Concentrations and time-integrated concentrations of iodine-131, cesium-136, and cesium-137 in milk and other foods were investigated. 9 figs., 13 tabs

Bayesian meta-analysis models for microarray data: a comparative study

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Song Joon J

2007-03-01

Full Text Available Abstract Background With the growing abundance of microarray data, statistical methods are increasingly needed to integrate results across studies. Two common approaches for meta-analysis of microarrays include either combining gene expression measures across studies or combining summaries such as p-values, probabilities or ranks. Here, we compare two Bayesian meta-analysis models that are analogous to these methods. Results Two Bayesian meta-analysis models for microarray data have recently been introduced. The first model combines standardized gene expression measures across studies into an overall mean, accounting for inter-study variability, while the second combines probabilities of differential expression without combining expression values. Both models produce the gene-specific posterior probability of differential expression, which is the basis for inference. Since the standardized expression integration model includes inter-study variability, it may improve accuracy of results versus the probability integration model. However, due to the small number of studies typical in microarray meta-analyses, the variability between studies is challenging to estimate. The probability integration model eliminates the need to model variability between studies, and thus its implementation is more straightforward. We found in simulations of two and five studies that combining probabilities outperformed combining standardized gene expression measures for three comparison values: the percent of true discovered genes in meta-analysis versus individual studies; the percent of true genes omitted in meta-analysis versus separate studies, and the number of true discovered genes for fixed levels of Bayesian false discovery. We identified similar results when pooling two independent studies of Bacillus subtilis. We assumed that each study was produced from the same microarray platform with only two conditions: a treatment and control, and that the data sets

Biomechanical Analysis and Evaluation Technology Using Human Multi-Body Dynamic Model

Energy Technology Data Exchange (ETDEWEB)

Kim, Yoon Hyuk; Shin, June Ho; Khurelbaatar, Tsolmonbaatar [Kyung Hee University, Yongin (Korea, Republic of)

2011-10-15

This paper presents the biomechanical analysis and evaluation technology of musculoskeletal system by multi-body human dynamic model and 3-D motion capture data. First, medical image based geometric model and material properties of tissue were used to develop the human dynamic model and 3-D motion capture data based motion analysis techniques were develop to quantify the in-vivo joint kinematics, joint moment, joint force, and muscle force. Walking and push-up motion was investigated using the developed model. The present model and technologies would be useful to apply the biomechanical analysis and evaluation of human activities.

Assessing Heterogeneity for Factor Analysis Model with Continuous and Ordinal Outcomes

Directory of Open Access Journals (Sweden)

Ye-Mao Xia

2016-01-01

Full Text Available Factor analysis models with continuous and ordinal responses are a useful tool for assessing relations between the latent variables and mixed observed responses. These models have been successfully applied to many different fields, including behavioral, educational, and social-psychological sciences. However, within the Bayesian analysis framework, most developments are constrained within parametric families, of which the particular distributions are specified for the parameters of interest. This leads to difficulty in dealing with outliers and/or distribution deviations. In this paper, we propose a Bayesian semiparametric modeling for factor analysis model with continuous and ordinal variables. A truncated stick-breaking prior is used to model the distributions of the intercept and/or covariance structural parameters. Bayesian posterior analysis is carried out through the simulation-based method. Blocked Gibbs sampler is implemented to draw observations from the complicated posterior. For model selection, the logarithm of pseudomarginal likelihood is developed to compare the competing models. Empirical results are presented to illustrate the application of the methodology.

Illustrating a Model-Game-Model Paradigm for Using Human Wargames in Analysis

Science.gov (United States)

2017-02-01

example, a risk -taking model with glorious objectives may give little weight to worst-case possibilities; a risk - averse model concerned primarily with... framing than with details. How can an analytic process that includes gaming contribute? Figure 1 uses the metaphor of learning a game such as chess when...strategies. We might then do some analysis and report tentative conclusions, including suggestions on how to frame mental models, but we would also want

Verify Super Double-Heterogeneous Spherical Lattice Model for Equilibrium Fuel Cycle Analysis AND HTR Spherical Super Lattice Model for Equilibrium Fuel Cycle Analysis

International Nuclear Information System (INIS)

Gray S. Chang

2005-01-01

The currently being developed advanced High Temperature gas-cooled Reactors (HTR) is able to achieve a simplification of safety through reliance on innovative features and passive systems. One of the innovative features in these HTRs is reliance on ceramic-coated fuel particles to retain the fission products even under extreme accident conditions. Traditionally, the effect of the random fuel kernel distribution in the fuel pebble/block is addressed through the use of the Dancoff correction factor in the resonance treatment. However, the Dancoff correction factor is a function of burnup and fuel kernel packing factor, which requires that the Dancoff correction factor be updated during Equilibrium Fuel Cycle (EqFC) analysis. An advanced KbK-sph model and whole pebble super lattice model (PSLM), which can address and update the burnup dependent Dancoff effect during the EqFC analysis. The pebble homogeneous lattice model (HLM) is verified by the burnup characteristics with the double-heterogeneous KbK-sph lattice model results. This study summarizes and compares the KbK-sph lattice model and HLM burnup analyzed results. Finally, we discuss the Monte-Carlo coupling with a fuel depletion and buildup code--ORIGEN-2 as a fuel burnup analysis tool and its PSLM calculated results for the HTR EqFC burnup analysis

Electromagnetic modeling method for eddy current signal analysis

International Nuclear Information System (INIS)

Lee, D. H.; Jung, H. K.; Cheong, Y. M.; Lee, Y. S.; Huh, H.; Yang, D. J.

2004-10-01

An electromagnetic modeling method for eddy current signal analysis is necessary before an experiment is performed. Electromagnetic modeling methods consists of the analytical method and the numerical method. Also, the numerical methods can be divided by Finite Element Method(FEM), Boundary Element Method(BEM) and Volume Integral Method(VIM). Each modeling method has some merits and demerits. Therefore, the suitable modeling method can be chosen by considering the characteristics of each modeling. This report explains the principle and application of each modeling method and shows the comparison modeling programs

Discrete Discriminant analysis based on tree-structured graphical models

DEFF Research Database (Denmark)

Perez de la Cruz, Gonzalo; Eslava, Guillermina

The purpose of this paper is to illustrate the potential use of discriminant analysis based on tree{structured graphical models for discrete variables. This is done by comparing its empirical performance using estimated error rates for real and simulated data. The results show that discriminant a...... analysis based on tree{structured graphical models is a simple nonlinear method competitive with, and sometimes superior to, other well{known linear methods like those assuming mutual independence between variables and linear logistic regression.......The purpose of this paper is to illustrate the potential use of discriminant analysis based on tree{structured graphical models for discrete variables. This is done by comparing its empirical performance using estimated error rates for real and simulated data. The results show that discriminant...

Structure and sensitivity analysis of individual-based predator–prey models

International Nuclear Information System (INIS)

Imron, Muhammad Ali; Gergs, Andre; Berger, Uta

2012-01-01

The expensive computational cost of sensitivity analyses has hampered the use of these techniques for analysing individual-based models in ecology. A relatively cheap computational cost, referred to as the Morris method, was chosen to assess the relative effects of all parameters on the model’s outputs and to gain insights into predator–prey systems. Structure and results of the sensitivity analysis of the Sumatran tiger model – the Panthera Population Persistence (PPP) and the Notonecta foraging model (NFM) – were compared. Both models are based on a general predation cycle and designed to understand the mechanisms behind the predator–prey interaction being considered. However, the models differ significantly in their complexity and the details of the processes involved. In the sensitivity analysis, parameters that directly contribute to the number of prey items killed were found to be most influential. These were the growth rate of prey and the hunting radius of tigers in the PPP model as well as attack rate parameters and encounter distance of backswimmers in the NFM model. Analysis of distances in both of the models revealed further similarities in the sensitivity of the two individual-based models. The findings highlight the applicability and importance of sensitivity analyses in general, and screening design methods in particular, during early development of ecological individual-based models. Comparison of model structures and sensitivity analyses provides a first step for the derivation of general rules in the design of predator–prey models for both practical conservation and conceptual understanding. - Highlights: ► Structure of predation processes is similar in tiger and backswimmer model. ► The two individual-based models (IBM) differ in space formulations. ► In both models foraging distance is among the sensitive parameters. ► Morris method is applicable for the sensitivity analysis even of complex IBMs.

Information-theoretic analysis of the dynamics of an executable biological model.

Directory of Open Access Journals (Sweden)

Avital Sadot

Full Text Available To facilitate analysis and understanding of biological systems, large-scale data are often integrated into models using a variety of mathematical and computational approaches. Such models describe the dynamics of the biological system and can be used to study the changes in the state of the system over time. For many model classes, such as discrete or continuous dynamical systems, there exist appropriate frameworks and tools for analyzing system dynamics. However, the heterogeneous information that encodes and bridges molecular and cellular dynamics, inherent to fine-grained molecular simulation models, presents significant challenges to the study of system dynamics. In this paper, we present an algorithmic information theory based approach for the analysis and interpretation of the dynamics of such executable models of biological systems. We apply a normalized compression distance (NCD analysis to the state representations of a model that simulates the immune decision making and immune cell behavior. We show that this analysis successfully captures the essential information in the dynamics of the system, which results from a variety of events including proliferation, differentiation, or perturbations such as gene knock-outs. We demonstrate that this approach can be used for the analysis of executable models, regardless of the modeling framework, and for making experimentally quantifiable predictions.

Economic and Power System Modeling and Analysis | Water Power | NREL

Science.gov (United States)

Economic and Power System Modeling and Analysis Economic and Power System Modeling and Analysis technologies, their possible deployment scenarios, and the economic impacts of this deployment. As a research approaches used to estimate direct and indirect economic impacts of offshore renewable energy projects

Modeling and Analysis of Space Based Transceivers

Science.gov (United States)

Moore, Michael S.; Price, Jeremy C.; Abbott, Ben; Liebetreu, John; Reinhart, Richard C.; Kacpura, Thomas J.

2007-01-01

This paper presents the tool chain, methodology, and initial results of a study to provide a thorough, objective, and quantitative analysis of the design alternatives for space Software Defined Radio (SDR) transceivers. The approach taken was to develop a set of models and tools for describing communications requirements, the algorithm resource requirements, the available hardware, and the alternative software architectures, and generate analysis data necessary to compare alternative designs. The Space Transceiver Analysis Tool (STAT) was developed to help users identify and select representative designs, calculate the analysis data, and perform a comparative analysis of the representative designs. The tool allows the design space to be searched quickly while permitting incremental refinement in regions of higher payoff.

Versatile Micromechanics Model for Multiscale Analysis of Composite Structures

Science.gov (United States)

Kwon, Y. W.; Park, M. S.

2013-08-01

A general-purpose micromechanics model was developed so that the model could be applied to various composite materials such as reinforced by particles, long fibers and short fibers as well as those containing micro voids. Additionally, the model can be used with hierarchical composite materials. The micromechanics model can be used to compute effective material properties like elastic moduli, shear moduli, Poisson's ratios, and coefficients of thermal expansion for the various composite materials. The model can also calculate the strains and stresses at the constituent material level such as fibers, particles, and whiskers from the composite level stresses and strains. The model was implemented into ABAQUS using the UMAT option for multiscale analysis. An extensive set of examples are presented to demonstrate the reliability and accuracy of the developed micromechanics model for different kinds of composite materials. Another set of examples is provided to study the multiscale analysis of composite structures.

European Climate - Energy Security Nexus. A model based scenario analysis

International Nuclear Information System (INIS)

Criqui, Patrick; Mima, Silvana

2011-01-01

In this research, we have provided an overview of the climate-security nexus in the European sector through a model based scenario analysis with POLES model. The analysis underline that under stringent climate policies, Europe take advantage of a double dividend in its capacity to develop a new cleaner energy model and in lower vulnerability to potential shocks on the international energy markets. (authors)

Properties of autoregressive model in reactor noise analysis, 1

International Nuclear Information System (INIS)

Yamada, Sumasu; Kishida, Kuniharu; Bekki, Keisuke.

1987-01-01

Under appropriate conditions, stochastic processes are described by the ARMA model, however, the AR model is popularly used in reactor noise analysis. Hence, the properties of AR model as an approximate representation of the ARMA model should be made clear. Here, convergence of AR-parameters and PSD of AR model were studied through numerical analysis on specific examples such as the neutron noise in subcritical reactors, and it was found that : (1) The convergence of AR-parameters and AR model PSD is governed by the ''zero nearest to the unit circle in the complex plane'' (μ -1 ,|μ| M . (3) The AR model of the neutron noise of subcritical reactors needs a large model order because of an ARMA-zero very close to unity corresponding to the decay constant of the 6-th group of delayed neutron precursors. (4) In applying AR model for system identification, much attention has to be paid to a priori unknown error as an approximate representation of the ARMA model in addition to the statistical errors. (author)

Fuel-Coolant-Interaction modeling and analysis work for the High Flux Isotope Reactor Safety Analysis Report

International Nuclear Information System (INIS)

Taleyarkhan, R.P.; Georgevich, V.; Nestor, C.W.; Chang, S.J.; Freels, J.; Gat, U.; Lepard, B.L.; Gwaltney, R.C.; Luttrell, C.; Kirkpatrick, J.

1993-07-01

A brief historical background and a description of short- and long-term task plan development for effective closure of this important safety issue for the HFIR are given. Short-term aspects deal with Fuel-Coolant-Interaction (FCI) issues experimentation, modeling, and analysis for the flow-blockage-induced steam explosion events in direct support of the SAR. Long-term aspects deal with addressing FCI issues resulting from other accidents in conjunction with issues dealing with aluminum ignition, which can result in an order of magnitude increase in overall energetics. Problem formulation, modeling, and computer code simulation for the various phases of steam explosions are described. The evaluation of core melt initiation propagation, and melt superheat are described. Core melt initiation and propagation have been studied using simple conservative models as well as from modeling and analysis using RELAP5. Core debris coolability, heatup, and melting/freezing aspects have been studied by use of the two-dimensional melting/freezing analysis code 2DKO, which was also benchmarked with MELCOR code predictions. Descriptions are provided for the HM, BH, FCIMOD, and CTH computer codes that have been implemented for studying steam explosion energetics from the standpoint of evaluating bounding loads by thermodynamic models or best-estimate loads from one- and two-dimensional simulations of steam explosion energetics. Vessel failure modeling and analysis was conducted using the principles of probabilistic fracture mechanics in conjunction with ADINA code calculations. Top head bolts failure modeling has also been conducted where the failure criterion was based upon stresses in the bolts exceeding the material yield stress for a given time duration. Missile transport modeling and analysis was conducted by setting up a one-dimensional mathematical model that accounts for viscous dissipation, virtual mass effects, and material inertia

Visual modeling in an analysis of multidimensional data

Science.gov (United States)

Zakharova, A. A.; Vekhter, E. V.; Shklyar, A. V.; Pak, A. J.

2018-01-01

The article proposes an approach to solve visualization problems and the subsequent analysis of multidimensional data. Requirements to the properties of visual models, which were created to solve analysis problems, are described. As a perspective direction for the development of visual analysis tools for multidimensional and voluminous data, there was suggested an active use of factors of subjective perception and dynamic visualization. Practical results of solving the problem of multidimensional data analysis are shown using the example of a visual model of empirical data on the current state of studying processes of obtaining silicon carbide by an electric arc method. There are several results of solving this problem. At first, an idea of possibilities of determining the strategy for the development of the domain, secondly, the reliability of the published data on this subject, and changes in the areas of attention of researchers over time.

The application of sensitivity analysis to models of large scale physiological systems

Science.gov (United States)

Leonard, J. I.

1974-01-01

A survey of the literature of sensitivity analysis as it applies to biological systems is reported as well as a brief development of sensitivity theory. A simple population model and a more complex thermoregulatory model illustrate the investigatory techniques and interpretation of parameter sensitivity analysis. The role of sensitivity analysis in validating and verifying models, and in identifying relative parameter influence in estimating errors in model behavior due to uncertainty in input data is presented. This analysis is valuable to the simulationist and the experimentalist in allocating resources for data collection. A method for reducing highly complex, nonlinear models to simple linear algebraic models that could be useful for making rapid, first order calculations of system behavior is presented.

Business Models For SMEs In Bandung: Swot Analysis

Directory of Open Access Journals (Sweden)

Senen Machmud

2014-04-01

Full Text Available The main objective of this study is to find the model business for small and medium-sized enterprises (SMEs with management strategy and business strategy approach. This research to help researchers, owners of SMEs and government in developing a framework for management strategy and business strategy on how the best result of business models. This study is valuable considering the limited among of empirical work previously done on the topic in question. The result of management strategies is internal and external factor analysis than analysis with strength, weakness, opportunities, and treatment (SWOT.

Supplementary Material for: A global sensitivity analysis approach for morphogenesis models

KAUST Repository

Boas, Sonja

2015-01-01

Abstract Background Morphogenesis is a developmental process in which cells organize into shapes and patterns. Complex, non-linear and multi-factorial models with images as output are commonly used to study morphogenesis. It is difficult to understand the relation between the uncertainty in the input and the output of such ‘black-box’ models, giving rise to the need for sensitivity analysis tools. In this paper, we introduce a workflow for a global sensitivity analysis approach to study the impact of single parameters and the interactions between them on the output of morphogenesis models. Results To demonstrate the workflow, we used a published, well-studied model of vascular morphogenesis. The parameters of this cellular Potts model (CPM) represent cell properties and behaviors that drive the mechanisms of angiogenic sprouting. The global sensitivity analysis correctly identified the dominant parameters in the model, consistent with previous studies. Additionally, the analysis provided information on the relative impact of single parameters and of interactions between them. This is very relevant because interactions of parameters impede the experimental verification of the predicted effect of single parameters. The parameter interactions, although of low impact, provided also new insights in the mechanisms of in silico sprouting. Finally, the analysis indicated that the model could be reduced by one parameter. Conclusions We propose global sensitivity analysis as an alternative approach to study the mechanisms of morphogenesis. Comparison of the ranking of the impact of the model parameters to knowledge derived from experimental data and from manipulation experiments can help to falsify models and to find the operand mechanisms in morphogenesis. The workflow is applicable to all ‘black-box’ models, including high-throughput in vitro models in which output measures are affected by a set of experimental perturbations.

Application of autoregressive moving average model in reactor noise analysis

International Nuclear Information System (INIS)

Tran Dinh Tri

1993-01-01

The application of an autoregressive (AR) model to estimating noise measurements has achieved many successes in reactor noise analysis in the last ten years. The physical processes that take place in the nuclear reactor, however, are described by an autoregressive moving average (ARMA) model rather than by an AR model. Consequently more correct results could be obtained by applying the ARMA model instead of the AR model to reactor noise analysis. In this paper the system of the generalised Yule-Walker equations is derived from the equation of an ARMA model, then a method for its solution is given. Numerical results show the applications of the method proposed. (author)

Dynamic sensitivity analysis of long running landslide models through basis set expansion and meta-modelling

Science.gov (United States)

Rohmer, Jeremy

2016-04-01

Predicting the temporal evolution of landslides is typically supported by numerical modelling. Dynamic sensitivity analysis aims at assessing the influence of the landslide properties on the time-dependent predictions (e.g., time series of landslide displacements). Yet two major difficulties arise: 1. Global sensitivity analysis require running the landslide model a high number of times (> 1000), which may become impracticable when the landslide model has a high computation time cost (> several hours); 2. Landslide model outputs are not scalar, but function of time, i.e. they are n-dimensional vectors with n usually ranging from 100 to 1000. In this article, I explore the use of a basis set expansion, such as principal component analysis, to reduce the output dimensionality to a few components, each of them being interpreted as a dominant mode of variation in the overall structure of the temporal evolution. The computationally intensive calculation of the Sobol' indices for each of these components are then achieved through meta-modelling, i.e. by replacing the landslide model by a "costless-to-evaluate" approximation (e.g., a projection pursuit regression model). The methodology combining "basis set expansion - meta-model - Sobol' indices" is then applied to the La Frasse landslide to investigate the dynamic sensitivity analysis of the surface horizontal displacements to the slip surface properties during the pore pressure changes. I show how to extract information on the sensitivity of each main modes of temporal behaviour using a limited number (a few tens) of long running simulations. In particular, I identify the parameters, which trigger the occurrence of a turning point marking a shift between a regime of low values of landslide displacements and one of high values.

Apply Functional Modelling to Consequence Analysis in Supervision Systems

DEFF Research Database (Denmark)

Zhang, Xinxin; Lind, Morten; Gola, Giulio

2013-01-01

This paper will first present the purpose and goals of applying functional modelling approach to consequence analysis by adopting Multilevel Flow Modelling (MFM). MFM Models describe a complex system in multiple abstraction levels in both means-end dimension and whole-part dimension. It contains...... consequence analysis to practical or online applications in supervision systems. It will also suggest a multiagent solution as the integration architecture for developing tools to facilitate the utilization results of functional consequence analysis. Finally a prototype of the multiagent reasoning system...... causal relations between functions and goals. A rule base system can be developed to trace the causal relations and perform consequence propagations. This paper will illustrate how to use MFM for consequence reasoning by using rule base technology and describe the challenges for integrating functional...

Dual-use tools and systematics-aware analysis workflows in the ATLAS Run-II analysis model

CERN Document Server

FARRELL, Steven; The ATLAS collaboration

2015-01-01

The ATLAS analysis model has been overhauled for the upcoming run of data collection in 2015 at 13 TeV. One key component of this upgrade was the Event Data Model (EDM), which now allows for greater flexibility in the choice of analysis software framework and provides powerful new features that can be exploited by analysis software tools. A second key component of the upgrade is the introduction of a dual-use tool technology, which provides abstract interfaces for analysis software tools to run in either the Athena framework or a ROOT-based framework. The tool interfaces, including a new interface for handling systematic uncertainties, have been standardized for the development of improved analysis workflows and consolidation of high-level analysis tools. This presentation will cover the details of the dual-use tool functionality, the systematics interface, and how these features fit into a centrally supported analysis environment.

Dual-use tools and systematics-aware analysis workflows in the ATLAS Run-2 analysis model

CERN Document Server

FARRELL, Steven; The ATLAS collaboration; Calafiura, Paolo; Delsart, Pierre-Antoine; Elsing, Markus; Koeneke, Karsten; Krasznahorkay, Attila; Krumnack, Nils; Lancon, Eric; Lavrijsen, Wim; Laycock, Paul; Lei, Xiaowen; Strandberg, Sara Kristina; Verkerke, Wouter; Vivarelli, Iacopo; Woudstra, Martin

2015-01-01

The ATLAS analysis model has been overhauled for the upcoming run of data collection in 2015 at 13 TeV. One key component of this upgrade was the Event Data Model (EDM), which now allows for greater flexibility in the choice of analysis software framework and provides powerful new features that can be exploited by analysis software tools. A second key component of the upgrade is the introduction of a dual-use tool technology, which provides abstract interfaces for analysis software tools to run in either the Athena framework or a ROOT-based framework. The tool interfaces, including a new interface for handling systematic uncertainties, have been standardized for the development of improved analysis workflows and consolidation of high-level analysis tools. This paper will cover the details of the dual-use tool functionality, the systematics interface, and how these features fit into a centrally supported analysis environment.

Global Sensitivity Analysis of Environmental Models: Convergence, Robustness and Validation

Science.gov (United States)

Sarrazin, Fanny; Pianosi, Francesca; Khorashadi Zadeh, Farkhondeh; Van Griensven, Ann; Wagener, Thorsten

2015-04-01

Global Sensitivity Analysis aims to characterize the impact that variations in model input factors (e.g. the parameters) have on the model output (e.g. simulated streamflow). In sampling-based Global Sensitivity Analysis, the sample size has to be chosen carefully in order to obtain reliable sensitivity estimates while spending computational resources efficiently. Furthermore, insensitive parameters are typically identified through the definition of a screening threshold: the theoretical value of their sensitivity index is zero but in a sampling-base framework they regularly take non-zero values. There is little guidance available for these two steps in environmental modelling though. The objective of the present study is to support modellers in making appropriate choices, regarding both sample size and screening threshold, so that a robust sensitivity analysis can be implemented. We performed sensitivity analysis for the parameters of three hydrological models with increasing level of complexity (Hymod, HBV and SWAT), and tested three widely used sensitivity analysis methods (Elementary Effect Test or method of Morris, Regional Sensitivity Analysis, and Variance-Based Sensitivity Analysis). We defined criteria based on a bootstrap approach to assess three different types of convergence: the convergence of the value of the sensitivity indices, of the ranking (the ordering among the parameters) and of the screening (the identification of the insensitive parameters). We investigated the screening threshold through the definition of a validation procedure. The results showed that full convergence of the value of the sensitivity indices is not necessarily needed to rank or to screen the model input factors. Furthermore, typical values of the sample sizes that are reported in the literature can be well below the sample sizes that actually ensure convergence of ranking and screening.

Multiway modeling and analysis in stem cell systems biology

Directory of Open Access Journals (Sweden)

Vandenberg Scott L

2008-07-01

Full Text Available Abstract Background Systems biology refers to multidisciplinary approaches designed to uncover emergent properties of biological systems. Stem cells are an attractive target for this analysis, due to their broad therapeutic potential. A central theme of systems biology is the use of computational modeling to reconstruct complex systems from a wealth of reductionist, molecular data (e.g., gene/protein expression, signal transduction activity, metabolic activity, etc.. A number of deterministic, probabilistic, and statistical learning models are used to understand sophisticated cellular behaviors such as protein expression during cellular differentiation and the activity of signaling networks. However, many of these models are bimodal i.e., they only consider row-column relationships. In contrast, multiway modeling techniques (also known as tensor models can analyze multimodal data, which capture much more information about complex behaviors such as cell differentiation. In particular, tensors can be very powerful tools for modeling the dynamic activity of biological networks over time. Here, we review the application of systems biology to stem cells and illustrate application of tensor analysis to model collagen-induced osteogenic differentiation of human mesenchymal stem cells. Results We applied Tucker1, Tucker3, and Parallel Factor Analysis (PARAFAC models to identify protein/gene expression patterns during extracellular matrix-induced osteogenic differentiation of human mesenchymal stem cells. In one case, we organized our data into a tensor of type protein/gene locus link × gene ontology category × osteogenic stimulant, and found that our cells expressed two distinct, stimulus-dependent sets of functionally related genes as they underwent osteogenic differentiation. In a second case, we organized DNA microarray data in a three-way tensor of gene IDs × osteogenic stimulus × replicates, and found that application of tensile strain to a

Causal Analysis for Performance Modeling of Computer Programs

Directory of Open Access Journals (Sweden)

Jan Lemeire

2007-01-01

Full Text Available Causal modeling and the accompanying learning algorithms provide useful extensions for in-depth statistical investigation and automation of performance modeling. We enlarged the scope of existing causal structure learning algorithms by using the form-free information-theoretic concept of mutual information and by introducing the complexity criterion for selecting direct relations among equivalent relations. The underlying probability distribution of experimental data is estimated by kernel density estimation. We then reported on the benefits of a dependency analysis and the decompositional capacities of causal models. Useful qualitative models, providing insight into the role of every performance factor, were inferred from experimental data. This paper reports on the results for a LU decomposition algorithm and on the study of the parameter sensitivity of the Kakadu implementation of the JPEG-2000 standard. Next, the analysis was used to search for generic performance characteristics of the applications.

Operations and Modeling Analysis

Science.gov (United States)

Ebeling, Charles

2005-01-01

The Reliability and Maintainability Analysis Tool (RMAT) provides NASA the capability to estimate reliability and maintainability (R&M) parameters and operational support requirements for proposed space vehicles based upon relationships established from both aircraft and Shuttle R&M data. RMAT has matured both in its underlying database and in its level of sophistication in extrapolating this historical data to satisfy proposed mission requirements, maintenance concepts and policies, and type of vehicle (i.e. ranging from aircraft like to shuttle like). However, a companion analyses tool, the Logistics Cost Model (LCM) has not reached the same level of maturity as RMAT due, in large part, to nonexistent or outdated cost estimating relationships and underlying cost databases, and it's almost exclusive dependence on Shuttle operations and logistics cost input parameters. As a result, the full capability of the RMAT/LCM suite of analysis tools to take a conceptual vehicle and derive its operations and support requirements along with the resulting operating and support costs has not been realized.

Integration of Design and Control Through Model Analysis

DEFF Research Database (Denmark)

Russel, Boris Mariboe; Henriksen, Jens Peter; Jørgensen, Sten Bay

2000-01-01

of the phenomena models representing the process model identify the relationships between the important process and design variables, which help to understand, define and address some of the issues related to integration of design and control issues. The model analysis is highlighted through examples involving...... processes with mass and/or energy recycle. (C) 2000 Elsevier Science Ltd. All rights reserved....

Numerical modeling techniques for flood analysis

Science.gov (United States)

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

2016-12-01

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

Model extension and improvement for simulator-based software safety analysis

Energy Technology Data Exchange (ETDEWEB)

Huang, H.-W. [Department of Engineering and System Science, National Tsing Hua University (NTHU), 101 Section 2 Kuang Fu Road, Hsinchu, Taiwan (China) and Institute of Nuclear Energy Research (INER), No. 1000 Wenhua Road, Chiaan Village, Longtan Township, Taoyuan County 32546, Taiwan (China)]. E-mail: hwhwang@iner.gov.tw; Shih Chunkuan [Department of Engineering and System Science, National Tsing Hua University (NTHU), 101 Section 2 Kuang Fu Road, Hsinchu, Taiwan (China); Yih Swu [Department of Computer Science and Information Engineering, Ching Yun University, 229 Chien-Hsin Road, Jung-Li, Taoyuan County 320, Taiwan (China); Chen, M.-H. [Institute of Nuclear Energy Research (INER), No. 1000Wenhua Road, Chiaan Village, Longtan Township, Taoyuan County 32546, Taiwan (China); Lin, J.-M. [Taiwan Power Company (TPC), 242 Roosevelt Road, Section 3, Taipei 100, Taiwan (China)

2007-05-15

One of the major concerns when employing digital I and C system in nuclear power plant is digital system may introduce new failure mode, which differs with previous analog I and C system. Various techniques are under developing to analyze the hazard originated from software faults in digital systems. Preliminary hazard analysis, failure modes and effects analysis, and fault tree analysis are the most extensive used techniques. However, these techniques are static analysis methods, cannot perform dynamic analysis and the interactions among systems. This research utilizes 'simulator/plant model testing' technique classified in (IEEE Std 7-4.3.2-2003, 2003. IEEE Standard for Digital Computers in Safety Systems of Nuclear Power Generating Stations) to identify hazards which might be induced by nuclear I and C software defects. The recirculation flow system, control rod system, feedwater system, steam line model, dynamic power-core flow map, and related control systems of PCTran-ABWR model were successfully extended and improved. The benchmark against ABWR SAR proves this modified model is capable to accomplish dynamic system level software safety analysis and better than the static methods. This improved plant simulation can then further be applied to hazard analysis for operator/digital I and C interface interaction failure study, and the hardware-in-the-loop fault injection study.

Modeling human reliability analysis using MIDAS

International Nuclear Information System (INIS)

Boring, R. L.

2006-01-01

This paper documents current efforts to infuse human reliability analysis (HRA) into human performance simulation. The Idaho National Laboratory is teamed with NASA Ames Research Center to bridge the SPAR-H HRA method with NASA's Man-machine Integration Design and Analysis System (MIDAS) for use in simulating and modeling the human contribution to risk in nuclear power plant control room operations. It is anticipated that the union of MIDAS and SPAR-H will pave the path for cost-effective, timely, and valid simulated control room operators for studying current and next generation control room configurations. This paper highlights considerations for creating the dynamic HRA framework necessary for simulation, including event dependency and granularity. This paper also highlights how the SPAR-H performance shaping factors can be modeled in MIDAS across static, dynamic, and initiator conditions common to control room scenarios. This paper concludes with a discussion of the relationship of the workload factors currently in MIDAS and the performance shaping factors in SPAR-H. (authors)

Building Information Modeling (BIM) for Indoor Environmental Performance Analysis

DEFF Research Database (Denmark)

The report is a part of a research assignment carried out by students in the 5ETCS course “Project Byggeri – [entitled as: Building Information Modeling (BIM) – Modeling & Analysis]”, during the 3rd semester of master degree in Civil and Architectural Engineering, Department of Engineering, Aarhus...... University. This includes seven papers describing BIM for Sustainability, concentrating specifically on individual topics regarding to Indoor Environment Performance Analysis....

Numerical equilibrium analysis for structured consumer resource models

NARCIS (Netherlands)

de Roos, A.M.; Diekmann, O.; Getto, P.; Kirkilionis, M.A.

2010-01-01

In this paper, we present methods for a numerical equilibrium and stability analysis for models of a size structured population competing for an unstructured re- source. We concentrate on cases where two model parameters are free, and thus existence boundaries for equilibria and stability boundaries

Numerical equilibrium analysis for structured consumer resource models

NARCIS (Netherlands)

de Roos, A.M.; Diekmann, O.; Getto, P.; Kirkilionis, M.A.

2010-01-01

In this paper, we present methods for a numerical equilibrium and stability analysis for models of a size structured population competing for an unstructured resource. We concentrate on cases where two model parameters are free, and thus existence boundaries for equilibria and stability boundaries

MATHEMATICAL RISK ANALYSIS: VIA NICHOLAS RISK MODEL AND BAYESIAN ANALYSIS

Directory of Open Access Journals (Sweden)

Anass BAYAGA

2010-07-01

Full Text Available The objective of this second part of a two-phased study was to explorethe predictive power of quantitative risk analysis (QRA method andprocess within Higher Education Institution (HEI. The method and process investigated the use impact analysis via Nicholas risk model and Bayesian analysis, with a sample of hundred (100 risk analysts in a historically black South African University in the greater Eastern Cape Province.The first findings supported and confirmed previous literature (KingIII report, 2009: Nicholas and Steyn, 2008: Stoney, 2007: COSA, 2004 that there was a direct relationship between risk factor, its likelihood and impact, certiris paribus. The second finding in relation to either controlling the likelihood or the impact of occurrence of risk (Nicholas risk model was that to have a brighter risk reward, it was important to control the likelihood ofoccurrence of risks as compared with its impact so to have a direct effect on entire University. On the Bayesian analysis, thus third finding, the impact of risk should be predicted along three aspects. These aspects included the human impact (decisions made, the property impact (students and infrastructural based and the business impact. Lastly, the study revealed that although in most business cases, where as business cycles considerably vary dependingon the industry and or the institution, this study revealed that, most impacts in HEI (University was within the period of one academic.The recommendation was that application of quantitative risk analysisshould be related to current legislative framework that affects HEI.

a finite element model for the analysis of bridge decks

African Journals Online (AJOL)

Dr Obe

A FINITE ELEMENT MODEL FOR THE ANALYSIS OF BRIDGE DECKS. NIGERIAN JOURNAL OF TECHNOLOGY, VOL. 27 NO.1, MARCH 2008. 59. (a) Beam-plate system. (b) T-beam structural model. Fig. 1 Beam-plate structure idealisations. The matrix displacement method of analysis is used. The continuum structure is.

Thermodynamic modeling of transcription: sensitivity analysis differentiates biological mechanism from mathematical model-induced effects.

Science.gov (United States)

Dresch, Jacqueline M; Liu, Xiaozhou; Arnosti, David N; Ay, Ahmet

2010-10-24

Quantitative models of gene expression generate parameter values that can shed light on biological features such as transcription factor activity, cooperativity, and local effects of repressors. An important element in such investigations is sensitivity analysis, which determines how strongly a model's output reacts to variations in parameter values. Parameters of low sensitivity may not be accurately estimated, leading to unwarranted conclusions. Low sensitivity may reflect the nature of the biological data, or it may be a result of the model structure. Here, we focus on the analysis of thermodynamic models, which have been used extensively to analyze gene transcription. Extracted parameter values have been interpreted biologically, but until now little attention has been given to parameter sensitivity in this context. We apply local and global sensitivity analyses to two recent transcriptional models to determine the sensitivity of individual parameters. We show that in one case, values for repressor efficiencies are very sensitive, while values for protein cooperativities are not, and provide insights on why these differential sensitivities stem from both biological effects and the structure of the applied models. In a second case, we demonstrate that parameters that were thought to prove the system's dependence on activator-activator cooperativity are relatively insensitive. We show that there are numerous parameter sets that do not satisfy the relationships proferred as the optimal solutions, indicating that structural differences between the two types of transcriptional enhancers analyzed may not be as simple as altered activator cooperativity. Our results emphasize the need for sensitivity analysis to examine model construction and forms of biological data used for modeling transcriptional processes, in order to determine the significance of estimated parameter values for thermodynamic models. Knowledge of parameter sensitivities can provide the necessary

Molecular structure based property modeling: Development/ improvement of property models through a systematic property-data-model analysis

DEFF Research Database (Denmark)

Hukkerikar, Amol Shivajirao; Sarup, Bent; Sin, Gürkan

2013-01-01

models. To make the property-data-model analysis fast and efficient, an approach based on the “molecular structure similarity criteria” to identify molecules (mono-functional, bi-functional, etc.) containing specified set of structural parameters (that is, groups) is employed. The method has been applied...

Ventilation Model and Analysis Report

International Nuclear Information System (INIS)

Chipman, V.

2003-01-01

This model and analysis report develops, validates, and implements a conceptual model for heat transfer in and around a ventilated emplacement drift. This conceptual model includes thermal radiation between the waste package and the drift wall, convection from the waste package and drift wall surfaces into the flowing air, and conduction in the surrounding host rock. These heat transfer processes are coupled and vary both temporally and spatially, so numerical and analytical methods are used to implement the mathematical equations which describe the conceptual model. These numerical and analytical methods predict the transient response of the system, at the drift scale, in terms of spatially varying temperatures and ventilation efficiencies. The ventilation efficiency describes the effectiveness of the ventilation process in removing radionuclide decay heat from the drift environment. An alternative conceptual model is also developed which evaluates the influence of water and water vapor mass transport on the ventilation efficiency. These effects are described using analytical methods which bound the contribution of latent heat to the system, quantify the effects of varying degrees of host rock saturation (and hence host rock thermal conductivity) on the ventilation efficiency, and evaluate the effects of vapor and enhanced vapor diffusion on the host rock thermal conductivity

Sensitivity Analysis of a Simplified Fire Dynamic Model

DEFF Research Database (Denmark)

Sørensen, Lars Schiøtt; Nielsen, Anker

2015-01-01

This paper discusses a method for performing a sensitivity analysis of parameters used in a simplified fire model for temperature estimates in the upper smoke layer during a fire. The results from the sensitivity analysis can be used when individual parameters affecting fire safety are assessed...

Turbulent diffusion modelling for windflow and dispersion analysis

International Nuclear Information System (INIS)

Bartzis, J.G.

1988-01-01

The need for simple but reliable models for turbulent diffusion for windflow and atmospheric dispersion analysis is a necessity today if one takes into consideration the relatively high demand in computer time and costs for such an analysis, arising mainly from the often large solution domains needed, the terrain complexity and the transient nature of the phenomena. In the accident consequence assessment often there is a need for a relatively large number of cases to be analysed increasing further the computer time and costs. Within the framework of searching for relatively simple and universal eddy viscosity/diffusivity models, a new three dimensional non isotropic model is proposed applicable to any domain complexity and any atmospheric stability conditions. The model utilizes the transport equation for turbulent kinetic energy but introduces a new approach in effective length scale estimation based on the flow global characteristics and local atmospheric stability. The model is discussed in detail and predictions are given for flow field and boundary layer thickness. The results are compared with experimental data with satisfactory results

Improved hydrogen combustion model for multi-compartment analysis

International Nuclear Information System (INIS)

Ogino, Masao; Hashimoto, Takashi

2000-01-01

NUPEC has been improving a hydrogen combustion model in MELCOR code for severe accident analysis. In the proposed combustion model, the flame velocity in a node was predicted using six different flame front shapes of fireball, prism, bubble, spherical jet, plane jet, and parallelepiped. A verification study of the proposed model was carried out using the NUPEC large-scale combustion test results following the previous work in which the GRS/Battelle multi-compartment combustion test results had been used. The selected test cases for the study were the premixed test and the scenario-oriented test which simulated the severe accident sequences of an actual plant. The improved MELCOR code replaced by the proposed model could predict sufficiently both results of the premixed test and the scenario-oriented test of NUPEC large-scale test. The improved MELCOR code was confirmed to simulate the combustion behavior in the multi-compartment containment vessel during a severe accident with acceptable degree of accuracy. Application of the new model to the LWR severe accident analysis will be continued. (author)

Model Based Analysis of Insider Threats

DEFF Research Database (Denmark)

Chen, Taolue; Han, Tingting; Kammueller, Florian

2016-01-01

In order to detect malicious insider attacks it is important to model and analyse infrastructures and policies of organisations and the insiders acting within them. We extend formal approaches that allow modelling such scenarios by quantitative aspects to enable a precise analysis of security...... designs. Our framework enables evaluating the risks of an insider attack to happen quantitatively. The framework first identifies an insider's intention to perform an inside attack, using Bayesian networks, and in a second phase computes the probability of success for an inside attack by this actor, using...

Multi-terminal direct-current grids modeling, analysis, and control

CERN Document Server

Chaudhuri, Nilanjan; Majumder, Rajat; Yazdani, Amirnaser

2014-01-01

A comprehensive modeling, analysis, and control design framework for multi-terminal direct current (MTDC) grids is presented together with their interaction with the surrounding AC networks and the impact on overall stability. The first book of its kind on the topic of multi-terminal DC (MTDC) grids  Presents a comprehensive modeling framework for MTDC grids which is compatible with the standard AC system modeling for stability studies Includes modal analysis and study of the interactions between the MTDC grid and the surrounding AC systems Addresses the problems of autonomous power sharing an

Distribution system modeling and analysis

CERN Document Server

Kersting, William H

2001-01-01

For decades, distribution engineers did not have the sophisticated tools developed for analyzing transmission systems-often they had only their instincts. Things have changed, and we now have computer programs that allow engineers to simulate, analyze, and optimize distribution systems. Powerful as these programs are, however, without a real understanding of the operating characteristics of a distribution system, engineers using the programs can easily make serious errors in their designs and operating procedures. Distribution System Modeling and Analysis helps prevent those errors. It gives readers a basic understanding of the modeling and operating characteristics of the major components of a distribution system. One by one, the author develops and analyzes each component as a stand-alone element, then puts them all together to analyze a distribution system comprising the various shunt and series devices for power-flow and short-circuit studies. He includes the derivation of all models and includes many num...

ANALYSIS MODEL FOR INVENTORY MANAGEMENT

Directory of Open Access Journals (Sweden)

CAMELIA BURJA

2010-01-01

Full Text Available The inventory represents an essential component for the assets of the enterprise and the economic analysis gives them special importance because their accurate management determines the achievement of the activity object and the financial results. The efficient management of inventory requires ensuring an optimum level for them, which will guarantee the normal functioning of the activity with minimum inventory expenses and funds which are immobilised. The paper presents an analysis model for inventory management based on their rotation speed and the correlation with the sales volume illustrated in an adequate study. The highlighting of the influence factors on the efficient inventory management ensures the useful information needed to justify managerial decisions, which will lead to a balancedfinancial position and to increased company performance.

Analysis of nonlinear systems using ARMA [autoregressive moving average] models

International Nuclear Information System (INIS)

Hunter, N.F. Jr.

1990-01-01

While many vibration systems exhibit primarily linear behavior, a significant percentage of the systems encountered in vibration and model testing are mildly to severely nonlinear. Analysis methods for such nonlinear systems are not yet well developed and the response of such systems is not accurately predicted by linear models. Nonlinear ARMA (autoregressive moving average) models are one method for the analysis and response prediction of nonlinear vibratory systems. In this paper we review the background of linear and nonlinear ARMA models, and illustrate the application of these models to nonlinear vibration systems. We conclude by summarizing the advantages and disadvantages of ARMA models and emphasizing prospects for future development. 14 refs., 11 figs

Monte Carlo Analysis of Reservoir Models Using Seismic Data and Geostatistical Models

Science.gov (United States)

Zunino, A.; Mosegaard, K.; Lange, K.; Melnikova, Y.; Hansen, T. M.

2013-12-01

We present a study on the analysis of petroleum reservoir models consistent with seismic data and geostatistical constraints performed on a synthetic reservoir model. Our aim is to invert directly for structure and rock bulk properties of the target reservoir zone. To infer the rock facies, porosity and oil saturation seismology alone is not sufficient but a rock physics model must be taken into account, which links the unknown properties to the elastic parameters. We then combine a rock physics model with a simple convolutional approach for seismic waves to invert the "measured" seismograms. To solve this inverse problem, we employ a Markov chain Monte Carlo (MCMC) method, because it offers the possibility to handle non-linearity, complex and multi-step forward models and provides realistic estimates of uncertainties. However, for large data sets the MCMC method may be impractical because of a very high computational demand. To face this challenge one strategy is to feed the algorithm with realistic models, hence relying on proper prior information. To address this problem, we utilize an algorithm drawn from geostatistics to generate geologically plausible models which represent samples of the prior distribution. The geostatistical algorithm learns the multiple-point statistics from prototype models (in the form of training images), then generates thousands of different models which are accepted or rejected by a Metropolis sampler. To further reduce the computation time we parallelize the software and run it on multi-core machines. The solution of the inverse problem is then represented by a collection of reservoir models in terms of facies, porosity and oil saturation, which constitute samples of the posterior distribution. We are finally able to produce probability maps of the properties we are interested in by performing statistical analysis on the collection of solutions.

Generalized linear models with random effects unified analysis via H-likelihood

CERN Document Server

Lee, Youngjo; Pawitan, Yudi

2006-01-01

Since their introduction in 1972, generalized linear models (GLMs) have proven useful in the generalization of classical normal models. Presenting methods for fitting GLMs with random effects to data, Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood explores a wide range of applications, including combining information over trials (meta-analysis), analysis of frailty models for survival data, genetic epidemiology, and analysis of spatial and temporal models with correlated errors.Written by pioneering authorities in the field, this reference provides an introduction to various theories and examines likelihood inference and GLMs. The authors show how to extend the class of GLMs while retaining as much simplicity as possible. By maximizing and deriving other quantities from h-likelihood, they also demonstrate how to use a single algorithm for all members of the class, resulting in a faster algorithm as compared to existing alternatives. Complementing theory with examples, many of...

Review and analysis of biomass gasification models

DEFF Research Database (Denmark)

Puig Arnavat, Maria; Bruno, Joan Carles; Coronas, Alberto

2010-01-01

, and the design, simulation, optimisation and process analysis of gasifiers have been carried out. This paper presents and analyses several gasification models based on thermodynamic equilibrium, kinetics and artificial neural networks. The thermodynamic models are found to be a useful tool for preliminary...... comparison and for process studies on the influence of the most important fuel and process parameters. They have the advantage of being independent of gasifier design, but they cannot give highly accurate results for all cases. The kinetic-based models are computationally more intensive but give accurate...

Modeling and Performance Analysis of Manufacturing Systems in ...

African Journals Online (AJOL)

Modeling and Performance Analysis of Manufacturing Systems in Footwear Industry. ... researcher to experiment with different variables and controls the manufacturing process ... In this study Arena simulation software is employed to model and measure ... for Authors · for Policy Makers · about Open Access · Journal Quality.

Aspects of uncertainty analysis in accident consequence modeling

International Nuclear Information System (INIS)

Travis, C.C.; Hoffman, F.O.

1981-01-01

Mathematical models are frequently used to determine probable dose to man from an accidental release of radionuclides by a nuclear facility. With increased emphasis on the accuracy of these models, the incorporation of uncertainty analysis has become one of the most crucial and sensitive components in evaluating the significance of model predictions. In the present paper, we address three aspects of uncertainty in models used to assess the radiological impact to humans: uncertainties resulting from the natural variability in human biological parameters; the propagation of parameter variability by mathematical models; and comparison of model predictions to observational data

Global sensitivity analysis of DRAINMOD-FOREST, an integrated forest ecosystem model

Science.gov (United States)

Shiying Tian; Mohamed A. Youssef; Devendra M. Amatya; Eric D. Vance

2014-01-01

Global sensitivity analysis is a useful tool to understand process-based ecosystem models by identifying key parameters and processes controlling model predictions. This study reported a comprehensive global sensitivity analysis for DRAINMOD-FOREST, an integrated model for simulating water, carbon (C), and nitrogen (N) cycles and plant growth in lowland forests. The...

Analysis of a Model for Computer Virus Transmission

Directory of Open Access Journals (Sweden)

Peng Qin

2015-01-01

Full Text Available Computer viruses remain a significant threat to computer networks. In this paper, the incorporation of new computers to the network and the removing of old computers from the network are considered. Meanwhile, the computers are equipped with antivirus software on the computer network. The computer virus model is established. Through the analysis of the model, disease-free and endemic equilibrium points are calculated. The stability conditions of the equilibria are derived. To illustrate our theoretical analysis, some numerical simulations are also included. The results provide a theoretical basis to control the spread of computer virus.

Multidisciplinary Product Decomposition and Analysis Based on Design Structure Matrix Modeling

DEFF Research Database (Denmark)

Habib, Tufail

2014-01-01

Design structure matrix (DSM) modeling in complex system design supports to define physical and logical configuration of subsystems, components, and their relationships. This modeling includes product decomposition, identification of interfaces, and structure analysis to increase the architectural...... interactions across subsystems and components. For this purpose, Cambridge advanced modeler (CAM) software tool is used to develop the system matrix. The analysis of the product (printer) architecture includes clustering, partitioning as well as structure analysis of the system. The DSM analysis is helpful...... understanding of the system. Since product architecture has broad implications in relation to product life cycle issues, in this paper, mechatronic product is decomposed into subsystems and components, and then, DSM model is developed to examine the extent of modularity in the system and to manage multiple...

Advances in power system modelling, control and stability analysis

CERN Document Server

Milano, Federico

2016-01-01

Advances in Power System Modelling, Control and Stability Analysis captures the variety of new methodologies and technologies that are changing the way modern electric power systems are modelled, simulated and operated.

The genetic analysis of repeated measures I: Simplex models

NARCIS (Netherlands)

Molenaar, P.C.M.; Boomsma, D.I.

1987-01-01

Extends the simplex model to a model that may be used for the genetic and environmental analysis of covariance (ANCOVA) structures. This "double" simplex structure can be specified as a linear structural relationships model. It is shown that data that give rise to a simplex correlation structure,

Generalized structured component analysis a component-based approach to structural equation modeling

CERN Document Server

Hwang, Heungsun

2014-01-01

Winner of the 2015 Sugiyama Meiko Award (Publication Award) of the Behaviormetric Society of Japan Developed by the authors, generalized structured component analysis is an alternative to two longstanding approaches to structural equation modeling: covariance structure analysis and partial least squares path modeling. Generalized structured component analysis allows researchers to evaluate the adequacy of a model as a whole, compare a model to alternative specifications, and conduct complex analyses in a straightforward manner. Generalized Structured Component Analysis: A Component-Based Approach to Structural Equation Modeling provides a detailed account of this novel statistical methodology and its various extensions. The authors present the theoretical underpinnings of generalized structured component analysis and demonstrate how it can be applied to various empirical examples. The book enables quantitative methodologists, applied researchers, and practitioners to grasp the basic concepts behind this new a...

[Analysis of the stability and adaptability of near infrared spectra qualitative analysis model].

Science.gov (United States)

Cao, Wu; Li, Wei-jun; Wang, Ping; Zhang, Li-ping

2014-06-01

The stability and adaptability of model of near infrared spectra qualitative analysis were studied. Method of separate modeling can significantly improve the stability and adaptability of model; but its ability of improving adaptability of model is limited. Method of joint modeling can not only improve the adaptability of the model, but also the stability of model, at the same time, compared to separate modeling, the method can shorten the modeling time, reduce the modeling workload; extend the term of validity of model, and improve the modeling efficiency. The experiment of model adaptability shows that, the correct recognition rate of separate modeling method is relatively low, which can not meet the requirements of application, and joint modeling method can reach the correct recognition rate of 90%, and significantly enhances the recognition effect. The experiment of model stability shows that, the identification results of model by joint modeling are better than the model by separate modeling, and has good application value.

Data Analysis A Model Comparison Approach, Second Edition

CERN Document Server

Judd, Charles M; Ryan, Carey S

2008-01-01

This completely rewritten classic text features many new examples, insights and topics including mediational, categorical, and multilevel models. Substantially reorganized, this edition provides a briefer, more streamlined examination of data analysis. Noted for its model-comparison approach and unified framework based on the general linear model, the book provides readers with a greater understanding of a variety of statistical procedures. This consistent framework, including consistent vocabulary and notation, is used throughout to develop fewer but more powerful model building techniques. T

System model for analysis of the mirror fusion-fission reactor

International Nuclear Information System (INIS)

Bender, D.J.; Carlson, G.A.

1977-01-01

This report describes a system model for the mirror fusion-fission reactor. In this model we include a reactor description as well as analyses of capital cost and blanket fuel management. In addition, we provide an economic analysis evaluating the cost of producing the two hybrid products, fissile fuel and electricity. We also furnish the results of a limited parametric analysis of the modeled reactor, illustrating the technological and economic implications of varying some important reactor design parameters

Application of adversarial risk analysis model in pricing strategies with remanufacturing

Directory of Open Access Journals (Sweden)

Liurui Deng

2015-01-01

Full Text Available Purpose: Purpose: This paper mainly focus on the application of adversarial risk analysis (ARA in pricing strategy with remanufacturing. We hope to obtain more realistic results than classical model. Moreover, we also wish that our research improve the development of ARA in pricing strategy of manufacturing or remanufacturing. Approach: In order to gain more actual research, combining adversarial risk analysis, we explore the pricing strategy with remanufacturing based on Stackelberg model. Especially, we build OEM’s 1-order ARA model and further study on manufacturers and remanufacturers’ pricing strategy. Findings: We find the OEM’s 1-order ARA model for the OEM’s product cost C. Besides, we get according manufacturers and remanufacturers’ pricing strategies. Besides, the pricing strategies based on 1-order ARA model have advantage over than the classical model regardless of OEMs and remanufacturers. Research implications: The research on application of ARA imply that we can get more actual results with this kind of modern risk analysis method and ARA can be extensively in pricing strategies of supply chain. Value: Our research improves the application of ARA in remanufacturing industry. Meanwhile, inspired by this analysis, we can also create different ARA models for different parameters. Furthermore, some results and analysis methods can be applied to other pricing strategies of supply chain.

A comparative analysis of reactor lower head debris cooling models employed in the existing severe accident analysis codes

International Nuclear Information System (INIS)

Ahn, K.I.; Kim, D.H.; Kim, S.B.; Kim, H.D.

1998-08-01

MELCOR and MAAP4 are the representative severe accident analysis codes which have been developed for the integral analysis of the phenomenological reactor lower head corium cooling behavior. Main objectives of the present study is to identify merits and disadvantages of each relevant model through the comparative analysis of the lower plenum corium cooling models employed in these two codes. The final results will be utilized for the development of LILAC phenomenological models and for the continuous improvement of the existing MELCOR reactor lower head models, which are currently being performed at the KAERI. For these purposes, first, nine reference models are selected featuring the lower head corium behavior based on the existing experimental evidences and related models. Then main features of the selected models have been critically analyzed, and finally merits and disadvantages of each corresponding model have been summarized in the view point of realistic corium behavior and reasonable modeling. Being on these evidences, summarized and presented the potential improvements for developing more advanced models. The present study has been focused on the qualitative comparison of each model and so more detailed quantitative analysis is strongly required to obtain the final conclusions for their merits and disadvantages. In addition, in order to compensate the limitations of the current model, required further studies relating closely the detailed mechanistic models with the molten material movement and heat transfer based on phase-change in the porous medium, to the existing simple models. (author). 36 refs

Domain Endurants: An Analysis and Description Process Model

DEFF Research Database (Denmark)

Bjørner, Dines

2014-01-01

We present a summary, Sect. 2, of a structure of domain analysis and description concepts: techniques and tools. And we link, in Sect. 3, these concepts, embodied in domain analysis prompts and domain description prompts, in a model of how a diligent domain analyser cum describer would use them. We...

Single-channel model for steady thermal-hydraulic analysis in nuclear reactor

International Nuclear Information System (INIS)

Zhang Xiaoying; Huang Yuanyuan

2010-01-01

This article established a single-channel model for steady analysis in the reactor and an example of thermal-hydraulic analysis was made by using this model, including the Maximum heat flux density of fuel element, enthalpy, Coolant flow, various kinds of pressure drop, enthalpy increase in average tube and thermal tube. I also got the Coolant temperature distribution and the fuel element temperature distribution and analysis of the final result. The results show that some relevant parameters which we got in this paper are well coincide with the actual operating parameters. It is also show that the single-channel model can be used to the steady thermal-hydraulic analysis. (authors)

Session 6: Dynamic Modeling and Systems Analysis

Science.gov (United States)

Csank, Jeffrey; Chapman, Jeffryes; May, Ryan

2013-01-01

These presentations cover some of the ongoing work in dynamic modeling and dynamic systems analysis. The first presentation discusses dynamic systems analysis and how to integrate dynamic performance information into the systems analysis. The ability to evaluate the dynamic performance of an engine design may allow tradeoffs between the dynamic performance and operability of a design resulting in a more efficient engine design. The second presentation discusses the Toolbox for Modeling and Analysis of Thermodynamic Systems (T-MATS). T-MATS is a Simulation system with a library containing the basic building blocks that can be used to create dynamic Thermodynamic Systems. Some of the key features include Turbo machinery components, such as turbines, compressors, etc., and basic control system blocks. T-MAT is written in the Matlab-Simulink environment and is open source software. The third presentation focuses on getting additional performance from the engine by allowing the limit regulators only to be active when a limit is danger of being violated. Typical aircraft engine control architecture is based on MINMAX scheme, which is designed to keep engine operating within prescribed mechanical/operational safety limits. Using a conditionally active min-max limit regulator scheme, additional performance can be gained by disabling non-relevant limit regulators

Modeling and analysis of advanced binary cycles

Energy Technology Data Exchange (ETDEWEB)

Gawlik, K.

1997-12-31

A computer model (Cycle Analysis Simulation Tool, CAST) and a methodology have been developed to perform value analysis for small, low- to moderate-temperature binary geothermal power plants. The value analysis method allows for incremental changes in the levelized electricity cost (LEC) to be determined between a baseline plant and a modified plant. Thermodynamic cycle analyses and component sizing are carried out in the model followed by economic analysis which provides LEC results. The emphasis of the present work is on evaluating the effect of mixed working fluids instead of pure fluids on the LEC of a geothermal binary plant that uses a simple Organic Rankine Cycle. Four resources were studied spanning the range of 265{degrees}F to 375{degrees}F. A variety of isobutane and propane based mixtures, in addition to pure fluids, were used as working fluids. This study shows that the use of propane mixtures at a 265{degrees}F resource can reduce the LEC by 24% when compared to a base case value that utilizes commercial isobutane as its working fluid. The cost savings drop to 6% for a 375{degrees}F resource, where an isobutane mixture is favored. Supercritical cycles were found to have the lowest cost at all resources.

Techniques to extract physical modes in model-independent analysis of rings

International Nuclear Information System (INIS)

Wang, C.-X.

2004-01-01

A basic goal of Model-Independent Analysis is to extract the physical modes underlying the beam histories collected at a large number of beam position monitors so that beam dynamics and machine properties can be deduced independent of specific machine models. Here we discuss techniques to achieve this goal, especially the Principal Component Analysis and the Independent Component Analysis.

Stochastic modeling of friction force and vibration analysis of a mechanical system using the model

International Nuclear Information System (INIS)

Kang, Won Seok; Choi, Chan Kyu; Yoo, Hong Hee

2015-01-01

The squeal noise generated from a disk brake or chatter occurred in a machine tool primarily results from friction-induced vibration. Since friction-induced vibration is usually accompanied by abrasion and lifespan reduction of mechanical parts, it is necessary to develop a reliable analysis model by which friction-induced vibration phenomena can be accurately analyzed. The original Coulomb's friction model or the modified Coulomb friction model employed in most commercial programs employs deterministic friction coefficients. However, observing friction phenomena between two contact surfaces, one may observe that friction coefficients keep changing due to the unevenness of contact surface, temperature, lubrication and humidity. Therefore, in this study, friction coefficients are modeled as random parameters that keep changing during the motion of a mechanical system undergoing friction force. The integrity of the proposed stochastic friction model was validated by comparing the analysis results obtained by the proposed model with experimental results.

Regression analysis of a chemical reaction fouling model

International Nuclear Information System (INIS)

Vasak, F.; Epstein, N.

1996-01-01

A previously reported mathematical model for the initial chemical reaction fouling of a heated tube is critically examined in the light of the experimental data for which it was developed. A regression analysis of the model with respect to that data shows that the reference point upon which the two adjustable parameters of the model were originally based was well chosen, albeit fortuitously. (author). 3 refs., 2 tabs., 2 figs

Corneal modeling for analysis of photorefractive keratectomy

Science.gov (United States)

Della Vecchia, Michael A.; Lamkin-Kennard, Kathleen

1997-05-01

Procedurally, excimer photorefractive keratectomy is based on the refractive correction of composite spherical and cylindrical ophthalmic errors of the entire eye. These refractive errors are inputted for correction at the corneal plane and for the properly controlled duration and location of laser energy. Topography is usually taken to correspondingly monitor spherical and cylindrical corneorefractive errors. While a corneal topographer provides surface morphologic information, the keratorefractive photoablation is based on the patient's spherical and cylindrical spectacle correction. Topography is at present not directly part of the procedural deterministic parameters. Examination of how corneal curvature at each of the keratometric reference loci affect the shape of the resultant corneal photoablated surface may enhance the accuracy of the desired correction. The objective of this study was to develop a methodology to utilize corneal topography for construction of models depicting pre- and post-operative keratomorphology for analysis of photorefractive keratectomy. Multiple types of models were developed then recreated in optical design software for examination of focal lengths and other optical characteristics. The corneal models were developed using data extracted from the TMS I corneal modeling system (Computed Anatomy, New York, NY). The TMS I does not allow for manipulation of data or differentiation of pre- and post-operative surfaces within its platform, thus models needed to be created for analysis. The data were imported into Matlab where 3D models, surface meshes, and contour plots were created. The data used to generate the models were pre- and post-operative curvatures, heights from the corneal apes, and x-y positions at 6400 locations on the corneal surface. Outlying non-contributory points were eliminated through statistical operations. Pre- and post- operative models were analyzed to obtain the resultant changes in the corneal surfaces during PRK

A random effects meta-analysis model with Box-Cox transformation.

Science.gov (United States)

Yamaguchi, Yusuke; Maruo, Kazushi; Partlett, Christopher; Riley, Richard D

2017-07-19

In a random effects meta-analysis model, true treatment effects for each study are routinely assumed to follow a normal distribution. However, normality is a restrictive assumption and the misspecification of the random effects distribution may result in a misleading estimate of overall mean for the treatment effect, an inappropriate quantification of heterogeneity across studies and a wrongly symmetric prediction interval. We focus on problems caused by an inappropriate normality assumption of the random effects distribution, and propose a novel random effects meta-analysis model where a Box-Cox transformation is applied to the observed treatment effect estimates. The proposed model aims to normalise an overall distribution of observed treatment effect estimates, which is sum of the within-study sampling distributions and the random effects distribution. When sampling distributions are approximately normal, non-normality in the overall distribution will be mainly due to the random effects distribution, especially when the between-study variation is large relative to the within-study variation. The Box-Cox transformation addresses this flexibly according to the observed departure from normality. We use a Bayesian approach for estimating parameters in the proposed model, and suggest summarising the meta-analysis results by an overall median, an interquartile range and a prediction interval. The model can be applied for any kind of variables once the treatment effect estimate is defined from the variable. A simulation study suggested that when the overall distribution of treatment effect estimates are skewed, the overall mean and conventional I 2 from the normal random effects model could be inappropriate summaries, and the proposed model helped reduce this issue. We illustrated the proposed model using two examples, which revealed some important differences on summary results, heterogeneity measures and prediction intervals from the normal random effects model. The

A random effects meta-analysis model with Box-Cox transformation

Directory of Open Access Journals (Sweden)

Yusuke Yamaguchi

2017-07-01

Full Text Available Abstract Background In a random effects meta-analysis model, true treatment effects for each study are routinely assumed to follow a normal distribution. However, normality is a restrictive assumption and the misspecification of the random effects distribution may result in a misleading estimate of overall mean for the treatment effect, an inappropriate quantification of heterogeneity across studies and a wrongly symmetric prediction interval. Methods We focus on problems caused by an inappropriate normality assumption of the random effects distribution, and propose a novel random effects meta-analysis model where a Box-Cox transformation is applied to the observed treatment effect estimates. The proposed model aims to normalise an overall distribution of observed treatment effect estimates, which is sum of the within-study sampling distributions and the random effects distribution. When sampling distributions are approximately normal, non-normality in the overall distribution will be mainly due to the random effects distribution, especially when the between-study variation is large relative to the within-study variation. The Box-Cox transformation addresses this flexibly according to the observed departure from normality. We use a Bayesian approach for estimating parameters in the proposed model, and suggest summarising the meta-analysis results by an overall median, an interquartile range and a prediction interval. The model can be applied for any kind of variables once the treatment effect estimate is defined from the variable. Results A simulation study suggested that when the overall distribution of treatment effect estimates are skewed, the overall mean and conventional I 2 from the normal random effects model could be inappropriate summaries, and the proposed model helped reduce this issue. We illustrated the proposed model using two examples, which revealed some important differences on summary results, heterogeneity measures and

Development of the tube bundle structure for fluid-structure interaction analysis model

International Nuclear Information System (INIS)

Yoon, Kyung Ho; Kim, Jae Yong

2010-02-01

Tube bundle structures within a Boiler or heat exchanger are laid the fluid-structure, thermal-structure and fluid-thermal-structure coupled boundary condition. In these complicated boundary conditions, Fluid-structure interaction (FSI) occurs when fluid flow causes deformation of the structure. This deformation, in turn, changes the boundary conditions for the fluid flow. The structural analysis discipline, and then independently analyzed each other. However, the fluid dynamic force effect the behavior of the structure, and the vibration amplitude of the structure to fluid. FSI analysis model was separately created fluid and structure model, and then defined the fsi boundary condition, and simultaneously analyzed in one domain. The analysis results were compared with those of the experimental method for validating the analysis model. Flow-induced vibration test was executed with single rod configuration. The vibration amplitudes of a fuel rod were measured by the laser vibro-meter system in x and y-direction. The analyses results were not closely with the test data, but the trend was very similar with the test result. In fsi coupled analysis case, the turbulent model was very important with the reliability of the accuracy of the analysis model. Therefore, the analysis model will be needed to further study

Image analysis and modeling in medical image computing. Recent developments and advances.

Science.gov (United States)

Handels, H; Deserno, T M; Meinzer, H-P; Tolxdorff, T

2012-01-01

Medical image computing is of growing importance in medical diagnostics and image-guided therapy. Nowadays, image analysis systems integrating advanced image computing methods are used in practice e.g. to extract quantitative image parameters or to support the surgeon during a navigated intervention. However, the grade of automation, accuracy, reproducibility and robustness of medical image computing methods has to be increased to meet the requirements in clinical routine. In the focus theme, recent developments and advances in the field of modeling and model-based image analysis are described. The introduction of models in the image analysis process enables improvements of image analysis algorithms in terms of automation, accuracy, reproducibility and robustness. Furthermore, model-based image computing techniques open up new perspectives for prediction of organ changes and risk analysis of patients. Selected contributions are assembled to present latest advances in the field. The authors were invited to present their recent work and results based on their outstanding contributions to the Conference on Medical Image Computing BVM 2011 held at the University of Lübeck, Germany. All manuscripts had to pass a comprehensive peer review. Modeling approaches and model-based image analysis methods showing new trends and perspectives in model-based medical image computing are described. Complex models are used in different medical applications and medical images like radiographic images, dual-energy CT images, MR images, diffusion tensor images as well as microscopic images are analyzed. The applications emphasize the high potential and the wide application range of these methods. The use of model-based image analysis methods can improve segmentation quality as well as the accuracy and reproducibility of quantitative image analysis. Furthermore, image-based models enable new insights and can lead to a deeper understanding of complex dynamic mechanisms in the human body

Fault Tree Analysis with Temporal Gates and Model Checking Technique for Qualitative System Safety Analysis

International Nuclear Information System (INIS)

Koh, Kwang Yong; Seong, Poong Hyun

2010-01-01

Fault tree analysis (FTA) has suffered from several drawbacks such that it uses only static gates and hence can not capture dynamic behaviors of the complex system precisely, and it is in lack of rigorous semantics, and reasoning process which is to check whether basic events really cause top events is done manually and hence very labor-intensive and time-consuming for the complex systems while it has been one of the most widely used safety analysis technique in nuclear industry. Although several attempts have been made to overcome this problem, they can not still do absolute or actual time modeling because they adapt relative time concept and can capture only sequential behaviors of the system. In this work, to resolve the problems, FTA and model checking are integrated to provide formal, automated and qualitative assistance to informal and/or quantitative safety analysis. Our approach proposes to build a formal model of the system together with fault trees. We introduce several temporal gates based on timed computational tree logic (TCTL) to capture absolute time behaviors of the system and to give concrete semantics to fault tree gates to reduce errors during the analysis, and use model checking technique to automate the reasoning process of FTA

Global sensitivity analysis for models with spatially dependent outputs

International Nuclear Information System (INIS)

Iooss, B.; Marrel, A.; Jullien, M.; Laurent, B.

2011-01-01

The global sensitivity analysis of a complex numerical model often calls for the estimation of variance-based importance measures, named Sobol' indices. Meta-model-based techniques have been developed in order to replace the CPU time-expensive computer code with an inexpensive mathematical function, which predicts the computer code output. The common meta-model-based sensitivity analysis methods are well suited for computer codes with scalar outputs. However, in the environmental domain, as in many areas of application, the numerical model outputs are often spatial maps, which may also vary with time. In this paper, we introduce an innovative method to obtain a spatial map of Sobol' indices with a minimal number of numerical model computations. It is based upon the functional decomposition of the spatial output onto a wavelet basis and the meta-modeling of the wavelet coefficients by the Gaussian process. An analytical example is presented to clarify the various steps of our methodology. This technique is then applied to a real hydrogeological case: for each model input variable, a spatial map of Sobol' indices is thus obtained. (authors)

Discretization model for nonlinear dynamic analysis of three dimensional structures

International Nuclear Information System (INIS)

Hayashi, Y.

1982-12-01

A discretization model for nonlinear dynamic analysis of three dimensional structures is presented. The discretization is achieved through a three dimensional spring-mass system and the dynamic response obtained by direct integration of the equations of motion using central diferences. First the viability of the model is verified through the analysis of homogeneous linear structures and then its performance in the analysis of structures subjected to impulsive or impact loads, taking into account both geometrical and physical nonlinearities is evaluated. (Author) [pt

Urban Saturated Power Load Analysis Based on a Novel Combined Forecasting Model

Directory of Open Access Journals (Sweden)

Huiru Zhao

2015-03-01

Full Text Available Analysis of urban saturated power loads is helpful to coordinate urban power grid construction and economic social development. There are two different kinds of forecasting models: the logistic curve model focuses on the growth law of the data itself, while the multi-dimensional forecasting model considers several influencing factors as the input variables. To improve forecasting performance, a novel combined forecasting model for saturated power load analysis was proposed in this paper, which combined the above two models. Meanwhile, the weights of these two models in the combined forecasting model were optimized by employing a fruit fly optimization algorithm. Using Hubei Province as the example, the effectiveness of the proposed combined forecasting model was verified, demonstrating a higher forecasting accuracy. The analysis result shows that the power load of Hubei Province will reach saturation in 2039, and the annual maximum power load will reach about 78,630 MW. The results obtained from this proposed hybrid urban saturated power load analysis model can serve as a reference for sustainable development for urban power grids, regional economies, and society at large.

Operational modal analysis modeling, Bayesian inference, uncertainty laws

CERN Document Server

Au, Siu-Kui

2017-01-01

This book presents operational modal analysis (OMA), employing a coherent and comprehensive Bayesian framework for modal identification and covering stochastic modeling, theoretical formulations, computational algorithms, and practical applications. Mathematical similarities and philosophical differences between Bayesian and classical statistical approaches to system identification are discussed, allowing their mathematical tools to be shared and their results correctly interpreted. Many chapters can be used as lecture notes for the general topic they cover beyond the OMA context. After an introductory chapter (1), Chapters 2–7 present the general theory of stochastic modeling and analysis of ambient vibrations. Readers are first introduced to the spectral analysis of deterministic time series (2) and structural dynamics (3), which do not require the use of probability concepts. The concepts and techniques in these chapters are subsequently extended to a probabilistic context in Chapter 4 (on stochastic pro...

Modeling Toolkit and Workbook for Defense Analysis Students

National Research Council Canada - National Science Library

Riden, Chad A; Drake, Douglass M

2006-01-01

.... Topics covered include difference equations, systems of difference equations, Lanchester equations, graphical analysis, proportionality, geometric similarity, model fitting, Monte Carlo simulation...

Sensitivity analysis of an Advanced Gas-cooled Reactor control rod model

International Nuclear Information System (INIS)

Scott, M.; Green, P.L.; O’Driscoll, D.; Worden, K.; Sims, N.D.

2016-01-01

Highlights: • A model was made of the AGR control rod mechanism. • The aim was to better understand the performance when shutting down the reactor. • The model showed good agreement with test data. • Sensitivity analysis was carried out. • The results demonstrated the robustness of the system. - Abstract: A model has been made of the primary shutdown system of an Advanced Gas-cooled Reactor nuclear power station. The aim of this paper is to explore the use of sensitivity analysis techniques on this model. The two motivations for performing sensitivity analysis are to quantify how much individual uncertain parameters are responsible for the model output uncertainty, and to make predictions about what could happen if one or several parameters were to change. Global sensitivity analysis techniques were used based on Gaussian process emulation; the software package GEM-SA was used to calculate the main effects, the main effect index and the total sensitivity index for each parameter and these were compared to local sensitivity analysis results. The results suggest that the system performance is resistant to adverse changes in several parameters at once.

Preditive Models And Health Sciences: A Brief Analysis

Directory of Open Access Journals (Sweden)

Jair Sales Paulino, Msc

2017-07-01

Full Text Available Background: Predictive Models are an important tool in event predicting and health planning. Despite this, there are few works focusing this area. Thus, the analysis of the real benefits of these models in Health Sciences is necessary to be performed. Results: Predictive techniques largely evolved in second half of XX century. The development of AR, MA, ARMA, ARIMA and SARIMA models, through Box-Jenkins methodology, constitute a robust conjunct of mechanisms able to help in solution of epidemiological modeling problems, mainly in Health Sciences, once it allows to evaluate individual characteristics of living beings and its correlation with pathologies in the same space-time. Nevertheless, AR, MA and ARMA does not have tendency in seasonality, which weakens the analysis. Conclusions: To predict the natural history of endemic/epidemic and its health-disease processes in a determined population is a sine que non condition to its adequate management in Public Health context and in adoption of affirmative measures concerning health promotion. Thus, the predictive models, with emphasis in ARIMA, SARIMA, Artificial Neural Networks and Formalism of Copulas are alternatives that can be feasible.

Comparative Distributions of Hazard Modeling Analysis

Directory of Open Access Journals (Sweden)

Rana Abdul Wajid

2006-07-01

Full Text Available In this paper we present the comparison among the distributions used in hazard analysis. Simulation technique has been used to study the behavior of hazard distribution modules. The fundamentals of Hazard issues are discussed using failure criteria. We present the flexibility of the hazard modeling distribution that approaches to different distributions.

A cognitive-pragmatic model for translation-shift analysis in ...

African Journals Online (AJOL)

A cognitive-pragmatic model for translation-shift analysis in descriptive case ... This model responds to the tendency of descriptive studies to analyse all translation shifts under the same rubric of neutrality. ... AJOL African Journals Online.

Analysis of organizational culture with social network models

OpenAIRE

Titov, S.

2015-01-01

Organizational culture is nowadays an object of numerous scientific papers. However, only marginal part of existing research attempts to use the formal models of organizational cultures. The lack of organizational culture models significantly limits the further research in this area and restricts the application of the theory to practice of organizational culture change projects. The article consists of general views on potential application of network models and social network analysis to th...

Data Envelopment Analysis (DEA) Model in Operation Management

Science.gov (United States)

Malik, Meilisa; Efendi, Syahril; Zarlis, Muhammad

2018-01-01

Quality management is an effective system in operation management to develops, maintains, and improves quality from groups of companies that allow marketing, production, and service at the most economycal level as well as ensuring customer satisfication. Many companies are practicing quality management to improve their bussiness performance. One of performance measurement is through measurement of efficiency. One of the tools can be used to assess efficiency of companies performance is Data Envelopment Analysis (DEA). The aim of this paper is using Data Envelopment Analysis (DEA) model to assess efficiency of quality management. In this paper will be explained CCR, BCC, and SBM models to assess efficiency of quality management.

Mathematical models of ABE fermentation: review and analysis.

Science.gov (United States)

Mayank, Rahul; Ranjan, Amrita; Moholkar, Vijayanand S

2013-12-01

Among different liquid biofuels that have emerged in the recent past, biobutanol produced via fermentation processes is of special interest due to very similar properties to that of gasoline. For an effective design, scale-up, and optimization of the acetone-butanol-ethanol (ABE) fermentation process, it is necessary to have insight into the micro- and macro-mechanisms of the process. The mathematical models for ABE fermentation are efficient tools for this purpose, which have evolved from simple stoichiometric fermentation equations in the 1980s to the recent sophisticated and elaborate kinetic models based on metabolic pathways. In this article, we have reviewed the literature published in the area of mathematical modeling of the ABE fermentation. We have tried to present an analysis of these models in terms of their potency in describing the overall physiology of the process, design features, mode of operation along with comparison and validation with experimental results. In addition, we have also highlighted important facets of these models such as metabolic pathways, basic kinetics of different metabolites, biomass growth, inhibition modeling and other additional features such as cell retention and immobilized cultures. Our review also covers the mathematical modeling of the downstream processing of ABE fermentation, i.e. recovery and purification of solvents through flash distillation, liquid-liquid extraction, and pervaporation. We believe that this review will be a useful source of information and analysis on mathematical models for ABE fermentation for both the appropriate scientific and engineering communities.

Conformational analysis of lignin models

International Nuclear Information System (INIS)

Santos, Helio F. dos

2001-01-01

The conformational equilibrium for two 5,5' biphenyl lignin models have been analyzed using a quantum mechanical semiempirical method. The gas phase and solution structures are discussed based on the NMR and X-ray experimental data. The results obtained showed that the observed conformations are solvent-dependent, being the geometries and the thermodynamic properties correlated with the experimental information. This study shows how a systematic theoretical conformational analysis can help to understand chemical processes at a molecular level. (author)

Analysis of the resolution processes of three modeling tasks

Directory of Open Access Journals (Sweden)

Cèsar Gallart Palau

2017-08-01

Full Text Available In this paper we present a comparative analysis of the resolution process of three modeling tasks performed by secondary education students (13-14 years, designed from three different points of view: The Modelling-eliciting Activities, the LEMA project, and the Realistic Mathematical Problems. The purpose of this analysis is to obtain a methodological characterization of them in order to provide to secondary education teachers a proper selection and sequencing of tasks for their implementation in the classroom.

Predictive models for monitoring and analysis of the total zooplankton

Directory of Open Access Journals (Sweden)

Obradović Milica

2014-01-01

Full Text Available In recent years, modeling and prediction of total zooplankton abundance have been performed by various tools and techniques, among which data mining tools have been less frequent. The purpose of this paper is to automatically determine the dependency degree and the influence of physical, chemical and biological parameters on the total zooplankton abundance, through design of the specific data mining models. For this purpose, the analysis of key influencers was used. The analysis is based on the data obtained from the SeLaR information system - specifically, the data from the two reservoirs (Gruža and Grošnica with different morphometric characteristics and trophic state. The data is transformed into optimal structure for data analysis, upon which, data mining model based on the Naïve Bayes algorithm is constructed. The results of the analysis imply that in both reservoirs, parameters of groups and species of zooplankton have the greatest influence on the total zooplankton abundance. If these inputs (group and zooplankton species are left out, differences in the impact of physical, chemical and other biological parameters in dependences of reservoirs can be noted. In the Grošnica reservoir, analysis showed that the temporal dimension (months, nitrates, water temperature, chemical oxygen demand, chlorophyll and chlorides, had the key influence with strong relative impact. In the Gruža reservoir, key influence parameters for total zooplankton are: spatial dimension (location, water temperature and physiological groups of bacteria. The results show that the presented data mining model is usable on any kind of aquatic ecosystem and can also serve for the detection of inputs which could be the basis for the future analysis and modeling.

Uncertainty analysis and validation of environmental models. The empirically based uncertainty analysis

International Nuclear Information System (INIS)

Monte, Luigi; Hakanson, Lars; Bergstroem, Ulla; Brittain, John; Heling, Rudie

1996-01-01

The principles of Empirically Based Uncertainty Analysis (EBUA) are described. EBUA is based on the evaluation of 'performance indices' that express the level of agreement between the model and sets of empirical independent data collected in different experimental circumstances. Some of these indices may be used to evaluate the confidence limits of the model output. The method is based on the statistical analysis of the distribution of the index values and on the quantitative relationship of these values with the ratio 'experimental data/model output'. Some performance indices are described in the present paper. Among these, the so-called 'functional distance' (d) between the logarithm of model output and the logarithm of the experimental data, defined as d 2 =Σ n 1 ( ln M i - ln O i ) 2 /n where M i is the i-th experimental value, O i the corresponding model evaluation and n the number of the couplets 'experimental value, predicted value', is an important tool for the EBUA method. From the statistical distribution of this performance index, it is possible to infer the characteristics of the distribution of the ratio 'experimental data/model output' and, consequently to evaluate the confidence limits for the model predictions. This method was applied to calculate the uncertainty level of a model developed to predict the migration of radiocaesium in lacustrine systems. Unfortunately, performance indices are affected by the uncertainty of the experimental data used in validation. Indeed, measurement results of environmental levels of contamination are generally associated with large uncertainty due to the measurement and sampling techniques and to the large variability in space and time of the measured quantities. It is demonstrated that this non-desired effect, in some circumstances, may be corrected by means of simple formulae

Validation of statistical models for creep rupture by parametric analysis

Energy Technology Data Exchange (ETDEWEB)

Bolton, J., E-mail: john.bolton@uwclub.net [65, Fisher Ave., Rugby, Warks CV22 5HW (United Kingdom)

2012-01-15

Statistical analysis is an efficient method for the optimisation of any candidate mathematical model of creep rupture data, and for the comparative ranking of competing models. However, when a series of candidate models has been examined and the best of the series has been identified, there is no statistical criterion to determine whether a yet more accurate model might be devised. Hence there remains some uncertainty that the best of any series examined is sufficiently accurate to be considered reliable as a basis for extrapolation. This paper proposes that models should be validated primarily by parametric graphical comparison to rupture data and rupture gradient data. It proposes that no mathematical model should be considered reliable for extrapolation unless the visible divergence between model and data is so small as to leave no apparent scope for further reduction. This study is based on the data for a 12% Cr alloy steel used in BS PD6605:1998 to exemplify its recommended statistical analysis procedure. The models considered in this paper include a) a relatively simple model, b) the PD6605 recommended model and c) a more accurate model of somewhat greater complexity. - Highlights: Black-Right-Pointing-Pointer The paper discusses the validation of creep rupture models derived from statistical analysis. Black-Right-Pointing-Pointer It demonstrates that models can be satisfactorily validated by a visual-graphic comparison of models to data. Black-Right-Pointing-Pointer The method proposed utilises test data both as conventional rupture stress and as rupture stress gradient. Black-Right-Pointing-Pointer The approach is shown to be more reliable than a well-established and widely used method (BS PD6605).

Beta-binomial model for meta-analysis of odds ratios.

Science.gov (United States)

Bakbergenuly, Ilyas; Kulinskaya, Elena

2017-05-20

In meta-analysis of odds ratios (ORs), heterogeneity between the studies is usually modelled via the additive random effects model (REM). An alternative, multiplicative REM for ORs uses overdispersion. The multiplicative factor in this overdispersion model (ODM) can be interpreted as an intra-class correlation (ICC) parameter. This model naturally arises when the probabilities of an event in one or both arms of a comparative study are themselves beta-distributed, resulting in beta-binomial distributions. We propose two new estimators of the ICC for meta-analysis in this setting. One is based on the inverted Breslow-Day test, and the other on the improved gamma approximation by Kulinskaya and Dollinger (2015, p. 26) to the distribution of Cochran's Q. The performance of these and several other estimators of ICC on bias and coverage is studied by simulation. Additionally, the Mantel-Haenszel approach to estimation of ORs is extended to the beta-binomial model, and we study performance of various ICC estimators when used in the Mantel-Haenszel or the inverse-variance method to combine ORs in meta-analysis. The results of the simulations show that the improved gamma-based estimator of ICC is superior for small sample sizes, and the Breslow-Day-based estimator is the best for n⩾100. The Mantel-Haenszel-based estimator of OR is very biased and is not recommended. The inverse-variance approach is also somewhat biased for ORs≠1, but this bias is not very large in practical settings. Developed methods and R programs, provided in the Web Appendix, make the beta-binomial model a feasible alternative to the standard REM for meta-analysis of ORs. © 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

A new tool for accelerator system modeling and analysis

International Nuclear Information System (INIS)

Gillespie, G.H.; Hill, B.W.; Jameson, R.A.

1994-01-01

A novel computer code is being developed to generate system level designs of radiofrequency ion accelerators. The goal of the Accelerator System Model (ASM) code is to create a modeling and analysis tool that is easy to use, automates many of the initial design calculations, supports trade studies used in assessing alternate designs and yet is flexible enough to incorporate new technology concepts as they emerge. Hardware engineering parameters and beam dynamics are modeled at comparable levels of fidelity. Existing scaling models of accelerator subsystems were sued to produce a prototype of ASM (version 1.0) working within the Shell for Particle Accelerator Related Codes (SPARC) graphical user interface. A small user group has been testing and evaluating the prototype for about a year. Several enhancements and improvements are now being developed. The current version (1.1) of ASM is briefly described and an example of the modeling and analysis capabilities is illustrated

Integrated modeling and analysis methodology for precision pointing applications

Science.gov (United States)

Gutierrez, Homero L.

2002-07-01

Space-based optical systems that perform tasks such as laser communications, Earth imaging, and astronomical observations require precise line-of-sight (LOS) pointing. A general approach is described for integrated modeling and analysis of these types of systems within the MATLAB/Simulink environment. The approach can be applied during all stages of program development, from early conceptual design studies to hardware implementation phases. The main objective is to predict the dynamic pointing performance subject to anticipated disturbances and noise sources. Secondary objectives include assessing the control stability, levying subsystem requirements, supporting pointing error budgets, and performing trade studies. The integrated model resides in Simulink, and several MATLAB graphical user interfaces (GUI"s) allow the user to configure the model, select analysis options, run analyses, and process the results. A convenient parameter naming and storage scheme, as well as model conditioning and reduction tools and run-time enhancements, are incorporated into the framework. This enables the proposed architecture to accommodate models of realistic complexity.

Static aeroelastic analysis including geometric nonlinearities based on reduced order model

Directory of Open Access Journals (Sweden)

Changchuan Xie

2017-04-01

Full Text Available This paper describes a method proposed for modeling large deflection of aircraft in nonlinear aeroelastic analysis by developing reduced order model (ROM. The method is applied for solving the static aeroelastic and static aeroelastic trim problems of flexible aircraft containing geometric nonlinearities; meanwhile, the non-planar effects of aerodynamics and follower force effect have been considered. ROMs are computational inexpensive mathematical representations compared to traditional nonlinear finite element method (FEM especially in aeroelastic solutions. The approach for structure modeling presented here is on the basis of combined modal/finite element (MFE method that characterizes the stiffness nonlinearities and we apply that structure modeling method as ROM to aeroelastic analysis. Moreover, the non-planar aerodynamic force is computed by the non-planar vortex lattice method (VLM. Structure and aerodynamics can be coupled with the surface spline method. The results show that both of the static aeroelastic analysis and trim analysis of aircraft based on structure ROM can achieve a good agreement compared to analysis based on the FEM and experimental result.

User Defined Data in the New Analysis Model of the BaBar Experiment

Energy Technology Data Exchange (ETDEWEB)

De Nardo, G.

2005-04-06

The BaBar experiment has recently revised its Analysis Model. One of the key ingredient of BaBar new Analysis Model is the support of the capability to add to the Event Store user defined data, which can be the output of complex computations performed at an advanced stage of a physics analysis, and are associated to analysis objects. In order to provide flexibility and extensibility with respect to object types, template generic programming has been adopted. In this way the model is non-intrusive with respect to reconstruction and analysis objects it manages, not requiring changes in their interfaces and implementations. Technological details are hidden as much as possible to the user, providing a simple interface. In this paper we present some of the limitations of the old model and how they are addressed by the new Analysis Model.

Integrating acoustic analysis in the architectural design process using parametric modelling

DEFF Research Database (Denmark)

Peters, Brady

2011-01-01

This paper discusses how parametric modeling techniques can be used to provide architectural designers with a better understanding of the acoustic performance of their designs and provide acoustic engineers with models that can be analyzed using computational acoustic analysis software. Architects......, acoustic performance can inform the geometry and material logic of the design. In this way, the architectural design and the acoustic analysis model become linked....

Comparative analysis of calculation models of railway subgrade

Directory of Open Access Journals (Sweden)

I.O. Sviatko

2013-08-01

Full Text Available Purpose. In transport engineering structures design, the primary task is to determine the parameters of foundation soil and nuances of its work under loads. It is very important to determine the parameters of shear resistance and the parameters, determining the development of deep deformations in foundation soils, while calculating the soil subgrade - upper track structure interaction. Search for generalized numerical modeling methods of embankment foundation soil work that include not only the analysis of the foundation stress state but also of its deformed one. Methodology. The analysis of existing modern and classical methods of numerical simulation of soil samples under static load was made. Findings. According to traditional methods of analysis of ground masses work, limitation and the qualitative estimation of subgrade deformations is possible only indirectly, through the estimation of stress and comparison of received values with the boundary ones. Originality. A new computational model was proposed in which it will be applied not only classical approach analysis of the soil subgrade stress state, but deformed state will be also taken into account. Practical value. The analysis showed that for accurate analysis of ground masses work it is necessary to develop a generalized methodology for analyzing of the rolling stock - railway subgrade interaction, which will use not only the classical approach of analyzing the soil subgrade stress state, but also take into account its deformed one.

Modeling and Analysis of Reentrant Manufacturing Systems: Micro- and Macroperspectives

Directory of Open Access Journals (Sweden)

Fenglan He

2011-01-01

Full Text Available In order to obtain the better analysis of the multiple reentrant manufacturing systems (MRMSs, their modeling and analysis from both micro- and macroperspectives are considered. First, this paper presents the discrete event simulation models for MRMS and the corresponding algorithms are developed. In order to describe MRMS more accurately, then a modified continuum model is proposed. This continuum model takes into account the re-entrant degree of products, and its effectiveness is verified through numerical experiments. Finally, based on the discrete event simulation and the modified continuum models, a numerical example is used to analyze the MRMS. The changes in the WIP levels and outflux are also analyzed in details for multiple re-entrant supply chain networks. Meanwhile, some interesting observations are discussed.

Statistical models and methods for reliability and survival analysis

CERN Document Server

Couallier, Vincent; Huber-Carol, Catherine; Mesbah, Mounir; Huber -Carol, Catherine; Limnios, Nikolaos; Gerville-Reache, Leo

2013-01-01

Statistical Models and Methods for Reliability and Survival Analysis brings together contributions by specialists in statistical theory as they discuss their applications providing up-to-date developments in methods used in survival analysis, statistical goodness of fit, stochastic processes for system reliability, amongst others. Many of these are related to the work of Professor M. Nikulin in statistics over the past 30 years. The authors gather together various contributions with a broad array of techniques and results, divided into three parts - Statistical Models and Methods, Statistical

Linear mixed-effects modeling approach to FMRI group analysis.

Science.gov (United States)

Chen, Gang; Saad, Ziad S; Britton, Jennifer C; Pine, Daniel S; Cox, Robert W

2013-06-01

Conventional group analysis is usually performed with Student-type t-test, regression, or standard AN(C)OVA in which the variance-covariance matrix is presumed to have a simple structure. Some correction approaches are adopted when assumptions about the covariance structure is violated. However, as experiments are designed with different degrees of sophistication, these traditional methods can become cumbersome, or even be unable to handle the situation at hand. For example, most current FMRI software packages have difficulty analyzing the following scenarios at group level: (1) taking within-subject variability into account when there are effect estimates from multiple runs or sessions; (2) continuous explanatory variables (covariates) modeling in the presence of a within-subject (repeated measures) factor, multiple subject-grouping (between-subjects) factors, or the mixture of both; (3) subject-specific adjustments in covariate modeling; (4) group analysis with estimation of hemodynamic response (HDR) function by multiple basis functions; (5) various cases of missing data in longitudinal studies; and (6) group studies involving family members or twins. Here we present a linear mixed-effects modeling (LME) methodology that extends the conventional group analysis approach to analyze many complicated cases, including the six prototypes delineated above, whose analyses would be otherwise either difficult or unfeasible under traditional frameworks such as AN(C)OVA and general linear model (GLM). In addition, the strength of the LME framework lies in its flexibility to model and estimate the variance-covariance structures for both random effects and residuals. The intraclass correlation (ICC) values can be easily obtained with an LME model with crossed random effects, even at the presence of confounding fixed effects. The simulations of one prototypical scenario indicate that the LME modeling keeps a balance between the control for false positives and the sensitivity

TIPPtool: Compositional Specification and Analysis of Markovian Performance Models

NARCIS (Netherlands)

Hermanns, H.; Halbwachs, N.; Peled, D.; Mertsiotakis, V.; Siegle, M.

1999-01-01

In this short paper we briefly describe a tool which is based on a Markovian stochastic process algebra. The tool offers both model specification and quantitative model analysis in a compositional fashion, wrapped in a userfriendly graphical front-end.

Modelling optimization involving different types of elements in finite element analysis

International Nuclear Information System (INIS)

Wai, C M; Rivai, Ahmad; Bapokutty, Omar

2013-01-01

Finite elements are used to express the mechanical behaviour of a structure in finite element analysis. Therefore, the selection of the elements determines the quality of the analysis. The aim of this paper is to compare and contrast 1D element, 2D element, and 3D element used in finite element analysis. A simple case study was carried out on a standard W460x74 I-beam. The I-beam was modelled and analyzed statically with 1D elements, 2D elements and 3D elements. The results for the three separate finite element models were compared in terms of stresses, deformation and displacement of the I-beam. All three finite element models yield satisfactory results with acceptable errors. The advantages and limitations of these elements are discussed. 1D elements offer simplicity although lacking in their ability to model complicated geometry. 2D elements and 3D elements provide more detail yet sophisticated results which require more time and computer memory in the modelling process. It is also found that the choice of element in finite element analysis is influence by a few factors such as the geometry of the structure, desired analysis results, and the capability of the computer

Human Modeling for Ground Processing Human Factors Engineering Analysis

Science.gov (United States)

Stambolian, Damon B.; Lawrence, Brad A.; Stelges, Katrine S.; Steady, Marie-Jeanne O.; Ridgwell, Lora C.; Mills, Robert E.; Henderson, Gena; Tran, Donald; Barth, Tim

2011-01-01

There have been many advancements and accomplishments over the last few years using human modeling for human factors engineering analysis for design of spacecraft. The key methods used for this are motion capture and computer generated human models. The focus of this paper is to explain the human modeling currently used at Kennedy Space Center (KSC), and to explain the future plans for human modeling for future spacecraft designs

Interpretation of medical images by model guided analysis

International Nuclear Information System (INIS)

Karssemeijer, N.

1989-01-01

Progress in the development of digital pictorial information systems stimulates a growing interest in the use of image analysis techniques in medicine. Especially when precise quantitative information is required the use of fast and reproducable computer analysis may be more appropriate than relying on visual judgement only. Such quantitative information can be valuable, for instance, in diagnostics or in irradiation therapy planning. As medical images are mostly recorded in a prescribed way, human anatomy guarantees a common image structure for each particular type of exam. In this thesis it is investigated how to make use of this a priori knowledge to guide image analysis. For that purpose models are developed which are suited to capture common image structure. The first part of this study is devoted to an analysis of nuclear medicine images of myocardial perfusion. In ch. 2 a model of these images is designed in order to represent characteristic image properties. It is shown that for these relatively simple images a compact symbolic description can be achieved, without significant loss of diagnostically importance of several image properties. Possibilities for automatic interpretation of more complex images is investigated in the following chapters. The central topic is segmentation of organs. Two methods are proposed and tested on a set of abdominal X-ray CT scans. Ch. 3 describes a serial approach based on a semantic network and the use of search areas. Relational constraints are used to guide the image processing and to classify detected image segments. In teh ch.'s 4 and 5 a more general parallel approach is utilized, based on a markov random field image model. A stochastic model used to represent prior knowledge about the spatial arrangement of organs is implemented as an external field. (author). 66 refs.; 27 figs.; 6 tabs

Uncertainty analysis of hydrological modeling in a tropical area using different algorithms

Science.gov (United States)

Rafiei Emam, Ammar; Kappas, Martin; Fassnacht, Steven; Linh, Nguyen Hoang Khanh

2018-01-01

Hydrological modeling outputs are subject to uncertainty resulting from different sources of errors (e.g., error in input data, model structure, and model parameters), making quantification of uncertainty in hydrological modeling imperative and meant to improve reliability of modeling results. The uncertainty analysis must solve difficulties in calibration of hydrological models, which further increase in areas with data scarcity. The purpose of this study is to apply four uncertainty analysis algorithms to a semi-distributed hydrological model, quantifying different source of uncertainties (especially parameter uncertainty) and evaluate their performance. In this study, the Soil and Water Assessment Tools (SWAT) eco-hydrological model was implemented for the watershed in the center of Vietnam. The sensitivity of parameters was analyzed, and the model was calibrated. The uncertainty analysis for the hydrological model was conducted based on four algorithms: Generalized Likelihood Uncertainty Estimation (GLUE), Sequential Uncertainty Fitting (SUFI), Parameter Solution method (ParaSol) and Particle Swarm Optimization (PSO). The performance of the algorithms was compared using P-factor and Rfactor, coefficient of determination (R 2), the Nash Sutcliffe coefficient of efficiency (NSE) and Percent Bias (PBIAS). The results showed the high performance of SUFI and PSO with P-factor>0.83, R-factor 0.91, NSE>0.89, and 0.18analysis. Indeed, the uncertainty analysis must be accounted when the outcomes of the model use for policy or management decisions.

Image decomposition as a tool for validating stress analysis models

Directory of Open Access Journals (Sweden)

Mottershead J.

2010-06-01

Full Text Available It is good practice to validate analytical and numerical models used in stress analysis for engineering design by comparison with measurements obtained from real components either in-service or in the laboratory. In reality, this critical step is often neglected or reduced to placing a single strain gage at the predicted hot-spot of stress. Modern techniques of optical analysis allow full-field maps of displacement, strain and, or stress to be obtained from real components with relative ease and at modest cost. However, validations continued to be performed only at predicted and, or observed hot-spots and most of the wealth of data is ignored. It is proposed that image decomposition methods, commonly employed in techniques such as fingerprinting and iris recognition, can be employed to validate stress analysis models by comparing all of the key features in the data from the experiment and the model. Image decomposition techniques such as Zernike moments and Fourier transforms have been used to decompose full-field distributions for strain generated from optical techniques such as digital image correlation and thermoelastic stress analysis as well as from analytical and numerical models by treating the strain distributions as images. The result of the decomposition is 101 to 102 image descriptors instead of the 105 or 106 pixels in the original data. As a consequence, it is relatively easy to make a statistical comparison of the image descriptors from the experiment and from the analytical/numerical model and to provide a quantitative assessment of the stress analysis.

Three-Dimensional Assembly Tolerance Analysis Based on the Jacobian-Torsor Statistical Model

Directory of Open Access Journals (Sweden)

Peng Heping

2017-01-01

Full Text Available The unified Jacobian-Torsor model has been developed for deterministic (worst case tolerance analysis. This paper presents a comprehensive model for performing statistical tolerance analysis by integrating the unified Jacobian-Torsor model and Monte Carlo simulation. In this model, an assembly is sub-divided into surfaces, the Small Displacements Torsor (SDT parameters are used to express the relative position between any two surfaces of the assembly. Then, 3D dimension-chain can be created by using a surface graph of the assembly and the unified Jacobian-Torsor model is developed based on the effect of each functional element on the whole functional requirements of products. Finally, Monte Carlo simulation is implemented for the statistical tolerance analysis. A numerical example is given to demonstrate the capability of the proposed method in handling three-dimensional assembly tolerance analysis.

Semiparametric mixed-effects analysis of PK/PD models using differential equations.

Science.gov (United States)

Wang, Yi; Eskridge, Kent M; Zhang, Shunpu

2008-08-01

Motivated by the use of semiparametric nonlinear mixed-effects modeling on longitudinal data, we develop a new semiparametric modeling approach to address potential structural model misspecification for population pharmacokinetic/pharmacodynamic (PK/PD) analysis. Specifically, we use a set of ordinary differential equations (ODEs) with form dx/dt = A(t)x + B(t) where B(t) is a nonparametric function that is estimated using penalized splines. The inclusion of a nonparametric function in the ODEs makes identification of structural model misspecification feasible by quantifying the model uncertainty and provides flexibility for accommodating possible structural model deficiencies. The resulting model will be implemented in a nonlinear mixed-effects modeling setup for population analysis. We illustrate the method with an application to cefamandole data and evaluate its performance through simulations.

Pressurized water reactor system model for control system design and analysis

International Nuclear Information System (INIS)

Cooper, K.F.; Cain, J.T.

1975-01-01

Satisfactory operation of present generation Pressurized Water Reactor (PWR) Nuclear Power systems requires that several independent and interactive control systems be designed. Since it is not practical to use an actual PWR system as a design tool, a mathematical model of the system must be developed as a design and analysis tool. The model presented has been developed to be used as an aid in applying optimal control theory to design and implement new control systems for PWR plants. To be applicable, the model developed must represent the PWR system in its normal operating range. For safety analysis the operating conditions of the system are usually abnormal and, therefore, the system modeling requirements are different from those for control system design and analysis

Analysis of GRI North American Regional Gas Supply-Demand Model

International Nuclear Information System (INIS)

Nesbitt, D.M.; Singh, J.; Pine, G.D.; Kline, D.; Barron, M.; Cheung, P.D.

1989-01-01

This paper summarizes the results from the GRI North American Regional Gas Supply-Demand Model using the four scenarios defined for the Energy Modeling Forum Number 9 (EMF-9) described in EMF-9 Working Paper 9.4 (1987). The analysis is designed both to showcase the GRI North American Regional model as well as to infer meaningful results about the North American natural gas system. The focus of the analysis is not R ampersand D per se; R ampersand D analysis using the model is conducted regularly by GRI and described elsewhere. Rather, the objective is to analyze some of the major uncertainties in the North American gas market, uncertainties that potentially affect all players including GRI. In particular, the authors seek to quantify the overall economic environment in which production, transmission, distribution, consumption, and R ampersand D decisions will be made and how different that overall environment might be under alternative assumptions. An attendant objective of this analysis has been to enlist economists from a range of organizations (producers, regulators, GRI, and consultants) to carefully scrutinize the GRI North American Regional model and results. In particular, the coauthors were assembled from diverse organizations to review and evaluate model outputs, applying their particular experience and perspective. The four EMF-9 scenarios upon which this paper is based are described in detail later in this document. Briefly, scenario one represents a world with a surfeit of gas and a relatively high oil price projection; scenario two considers a lower oil price forecast; scenario three assumes a pessimistic outlook for the gas resource base with the same oil prices as scenario one; and scenario four examines a higher level of demand for gas in the North American gas market. An important objective of this analysis is to illustrate the predictive power of multi-scenario comparisons (as contrasted with detailed analysis of any individual scenario)

Simplified model for DNB analysis

International Nuclear Information System (INIS)

Silva Filho, E.

1979-08-01

In a pressurized water nuclear reactor (PWR), the power of operation is restricted by the possibility of the occurrence of the departure from nucleate boiling called DNB (Departure from Nucleate Boiling) in the hottest channel of the core. The present work proposes a simplified model that analyses the thermal-hydraulic conditions of the coolant in the hottest channel of PWRs with the objective to evaluate BNB in this channel. For this the coupling between the hot channel and typical nominal channels assumed imposing the existence of a cross flow between these channels in a way that a uniforme pressure axial distribution results along the channels. The model is applied for Angra-I reactor and the results are compared with those of Final Safety Analysis Report (FSAR) obtained by Westinghouse through the THINC program, beeing considered satisfactory (Author) [pt

Urban drainage models - making uncertainty analysis simple

DEFF Research Database (Denmark)

Vezzaro, Luca; Mikkelsen, Peter Steen; Deletic, Ana

2012-01-01

in each measured/observed datapoint; an issue which is commonly overlook in the uncertainty analysis of urban drainage models. This comparison allows the user to intuitively estimate the optimum number of simulations required to conduct uncertainty analyses. The output of the method includes parameter......There is increasing awareness about uncertainties in modelling of urban drainage systems and, as such, many new methods for uncertainty analyses have been developed. Despite this, all available methods have limitations which restrict their widespread application among practitioners. Here...

Credible baseline analysis for multi-model public policy studies

Energy Technology Data Exchange (ETDEWEB)

Parikh, S.C.; Gass, S.I.

1981-01-01

The nature of public decision-making and resource allocation is such that many complex interactions can best be examined and understood by quantitative analysis. Most organizations do not possess the totality of models and needed analytical skills to perform detailed and systematic quantitative analysis. Hence, the need for coordinated, multi-organization studies that support public decision-making has grown in recent years. This trend is expected not only to continue, but to increase. This paper describes the authors' views on the process of multi-model analysis based on their participation in an analytical exercise, the ORNL/MITRE Study. One of the authors was the exercise coordinator. During the study, the authors were concerned with the issue of measuring and conveying credibility of the analysis. This work led them to identify several key determinants, described in this paper, that could be used to develop a rating of credibility.

Computer-aided-engineering system for modeling and analysis of ECLSS integration testing

Science.gov (United States)

Sepahban, Sonbol

1987-01-01

The accurate modeling and analysis of two-phase fluid networks found in environmental control and life support systems is presently undertaken by computer-aided engineering (CAE) techniques whose generalized fluid dynamics package can solve arbitrary flow networks. The CAE system for integrated test bed modeling and analysis will also furnish interfaces and subsystem/test-article mathematical models. Three-dimensional diagrams of the test bed are generated by the system after performing the requisite simulation and analysis.

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.

Joint Analysis of Binomial and Continuous Traits with a Recursive Model

DEFF Research Database (Denmark)

Varona, Louis; Sorensen, Daniel

2014-01-01

This work presents a model for the joint analysis of a binomial and a Gaussian trait using a recursive parametrization that leads to a computationally efficient implementation. The model is illustrated in an analysis of mortality and litter size in two breeds of Danish pigs, Landrace and Yorkshir...

Modelling and analysis of global coal markets

International Nuclear Information System (INIS)

Trueby, Johannes

2013-01-01

The thesis comprises four interrelated essays featuring modelling and analysis of coal markets. Each of the four essays has a dedicated chapter in this thesis. Chapters 2 to 4 have, from a topical perspective, a backward-looking focus and deal with explaining recent market outcomes in the international coal trade. The findings of those essays may serve as guidance for assessing current coal market outcomes as well as expected market outcomes in the near to medium-term future. Chapter 5 has a forward-looking focus and builds a bridge between explaining recent market outcomes and projecting long-term market equilibria. Chapter 2, Strategic Behaviour in International Metallurgical Coal Markets, deals with market conduct of large exporters in the market of coals used in steel-making in the period 2008 to 2010. In this essay I analyse whether prices and trade-flows in the international market for metallurgical coals were subject to non-competitive conduct in the period 2008 to 2010. To do so, I develop mathematical programming models - a Stackelberg model, two varieties of a Cournot model, and a perfect competition model - for computing spatial equilibria in international resource markets. Results are analysed with various statistical measures to assess the prediction accuracy of the models. The results show that real market equilibria cannot be reproduced with a competitive model. However, real market outcomes can be accurately simulated with the non-competitive models, suggesting that market equilibria in the international metallurgical coal trade were subject to the strategic behaviour of coal exporters. Chapter 3 and chapter 4 deal with market power issues in the steam coal trade in the period 2006 to 2008. Steam coals are typically used to produce steam either for electricity generation or for heating purposes. In Chapter 3 we analyse market behaviour of key exporting countries in the steam coal trade. This chapter features the essay Market Structure Scenarios in

Modelling and analysis of global coal markets

Energy Technology Data Exchange (ETDEWEB)

Trueby, Johannes

2013-01-17

The thesis comprises four interrelated essays featuring modelling and analysis of coal markets. Each of the four essays has a dedicated chapter in this thesis. Chapters 2 to 4 have, from a topical perspective, a backward-looking focus and deal with explaining recent market outcomes in the international coal trade. The findings of those essays may serve as guidance for assessing current coal market outcomes as well as expected market outcomes in the near to medium-term future. Chapter 5 has a forward-looking focus and builds a bridge between explaining recent market outcomes and projecting long-term market equilibria. Chapter 2, Strategic Behaviour in International Metallurgical Coal Markets, deals with market conduct of large exporters in the market of coals used in steel-making in the period 2008 to 2010. In this essay I analyse whether prices and trade-flows in the international market for metallurgical coals were subject to non-competitive conduct in the period 2008 to 2010. To do so, I develop mathematical programming models - a Stackelberg model, two varieties of a Cournot model, and a perfect competition model - for computing spatial equilibria in international resource markets. Results are analysed with various statistical measures to assess the prediction accuracy of the models. The results show that real market equilibria cannot be reproduced with a competitive model. However, real market outcomes can be accurately simulated with the non-competitive models, suggesting that market equilibria in the international metallurgical coal trade were subject to the strategic behaviour of coal exporters. Chapter 3 and chapter 4 deal with market power issues in the steam coal trade in the period 2006 to 2008. Steam coals are typically used to produce steam either for electricity generation or for heating purposes. In Chapter 3 we analyse market behaviour of key exporting countries in the steam coal trade. This chapter features the essay Market Structure Scenarios in

Time Aquatic Resources Modeling and Analysis Program (STARMAP)

Data.gov (United States)

Federal Laboratory Consortium — Colorado State University has received funding from the U.S. Environmental Protection Agency (EPA) for its Space-Time Aquatic Resources Modeling and Analysis Program...

3D face modeling, analysis and recognition

CERN Document Server

Daoudi, Mohamed; Veltkamp, Remco

2013-01-01

3D Face Modeling, Analysis and Recognition presents methodologies for analyzing shapes of facial surfaces, develops computational tools for analyzing 3D face data, and illustrates them using state-of-the-art applications. The methodologies chosen are based on efficient representations, metrics, comparisons, and classifications of features that are especially relevant in the context of 3D measurements of human faces. These frameworks have a long-term utility in face analysis, taking into account the anticipated improvements in data collection, data storage, processing speeds, and application s

Ferrofluids: Modeling, numerical analysis, and scientific computation

Science.gov (United States)

Tomas, Ignacio

This dissertation presents some developments in the Numerical Analysis of Partial Differential Equations (PDEs) describing the behavior of ferrofluids. The most widely accepted PDE model for ferrofluids is the Micropolar model proposed by R.E. Rosensweig. The Micropolar Navier-Stokes Equations (MNSE) is a subsystem of PDEs within the Rosensweig model. Being a simplified version of the much bigger system of PDEs proposed by Rosensweig, the MNSE are a natural starting point of this thesis. The MNSE couple linear velocity u, angular velocity w, and pressure p. We propose and analyze a first-order semi-implicit fully-discrete scheme for the MNSE, which decouples the computation of the linear and angular velocities, is unconditionally stable and delivers optimal convergence rates under assumptions analogous to those used for the Navier-Stokes equations. Moving onto the much more complex Rosensweig's model, we provide a definition (approximation) for the effective magnetizing field h, and explain the assumptions behind this definition. Unlike previous definitions available in the literature, this new definition is able to accommodate the effect of external magnetic fields. Using this definition we setup the system of PDEs coupling linear velocity u, pressure p, angular velocity w, magnetization m, and magnetic potential ϕ We show that this system is energy-stable and devise a numerical scheme that mimics the same stability property. We prove that solutions of the numerical scheme always exist and, under certain simplifying assumptions, that the discrete solutions converge. A notable outcome of the analysis of the numerical scheme for the Rosensweig's model is the choice of finite element spaces that allow the construction of an energy-stable scheme. Finally, with the lessons learned from Rosensweig's model, we develop a diffuse-interface model describing the behavior of two-phase ferrofluid flows and present an energy-stable numerical scheme for this model. For a

MODELLING AND SIMULATION MATTERS UPON THE STATIC ANALYSIS OF A BUILDING

Directory of Open Access Journals (Sweden)

DUTA Alina

2017-05-01

Full Text Available The present paper puts forward a method applied to determine the static analysis and the stress of a two-level building, via an analysis with finite elements for building construction domain. Prior to this, we shall deal with a strategic issue, i.e. the achievement of a model with finite elements to validate the best approximation for the building structure. The method endorsed comes to replace the mathematical model, which is more complicated. However, a central issue that has to be dealt with before determining the displacements and the stress analysis is the achievement of the model with finite elements, as the best approximation of the building structure.

Modelling and Analysis of Smart Grid: A Stochastic Model Checking Case Study

DEFF Research Database (Denmark)

Yuksel, Ender; Zhu, Huibiao; Nielson, Hanne Riis

2012-01-01

that require novel methods and applications. In this context, an important issue is the verification of certain quantitative properties of the system. In this paper, we consider a specific Chinese Smart Grid implementation as a case study and address the verification problem for performance and energy......Cyber-physical systems integrate information and communication technology functions to the physical elements of a system for monitoring and controlling purposes. The conversion of traditional power grid into a smart grid, a fundamental example of a cyber-physical system, raises a number of issues...... consumption. We employ stochastic model checking approach and present our modelling and analysis study using PRISM model checker....

Mathematical Model and Stability Analysis of Inverter-Based Distributed Generator

Directory of Open Access Journals (Sweden)

Alireza Khadem Abbasi

2013-01-01

Full Text Available This paper presents a mathematical (small-signal model of an electronically interfaced distributed generator (DG by considering the effect of voltage and frequency variations of the prime source. Dynamic equations are found by linearization about an operating point. In this study, the dynamic of DC part of the interface is included in the model. The stability analysis shows with proper selection of system parameters; the system is stable during steady-state and dynamic situations, and oscillatory modes are well damped. The proposed model is useful to study stability analysis of a standalone DG or a Microgrid.

3D space analysis of dental models

Science.gov (United States)

Chuah, Joon H.; Ong, Sim Heng; Kondo, Toshiaki; Foong, Kelvin W. C.; Yong, Than F.

2001-05-01

Space analysis is an important procedure by orthodontists to determine the amount of space available and required for teeth alignment during treatment planning. Traditional manual methods of space analysis are tedious and often inaccurate. Computer-based space analysis methods that work on 2D images have been reported. However, as the space problems in the dental arch exist in all three planes of space, a full 3D analysis of the problems is necessary. This paper describes a visualization and measurement system that analyses 3D images of dental plaster models. Algorithms were developed to determine dental arches. The system is able to record the depths of the Curve of Spee, and quantify space liabilities arising from a non-planar Curve of Spee, malalignment and overjet. Furthermore, the difference between total arch space available and the space required to arrange the teeth in ideal occlusion can be accurately computed. The system for 3D space analysis of the dental arch is an accurate, comprehensive, rapid and repeatable method of space analysis to facilitate proper orthodontic diagnosis and treatment planning.

Global plastic models for computerized structural analysis

International Nuclear Information System (INIS)

Roche, R.; Hoffmann, A.

1977-01-01

Two different global models are used in the CEASEMT system for structural analysis, one for the shells analysis and the other for piping analysis (in plastic or creep field). In shell analysis the generalized stresses choosed are the membrane forces Nsub(ij) and bending (including torsion) moments Msub(ij). There is only one yield condition for a normal (to the middle surface) and no integration along the thickness is required. In piping analysis, the choice of generalized stresses is: bending moments, torsional moments, Hoop stress and tension stress. There is only a set of stresses for a cross section and non integration over the cross section area is needed. Connected strains are axis curvature, torsion, uniform strains. The definition of the yield surface is the most important item. A practical way is to use a diagonal quadratic fonction of the stress components. But the coefficients are depending of the shape of the pipe element, especially for curved segments. Indications will be given on the yield fonctions used. Some examples of applications in structural analysis are added to the text [fr

The physical and mathematical model of dynamic economic analysis and assessment for NPP

International Nuclear Information System (INIS)

Xu Jiming

1992-01-01

A set physical and mathematical model of dynamic economic analysis referring to international general sub-item and account of investment and constant money levelized model and combining current economic analysis method in China for nuclear power plant was established. The model can be used in economic analysis not only for nuclear power plant but also for coal-fired power plant and can satisfy demand of doing economic analysis and assessment for nuclear power plant and conventional power plant

Model-based gene set analysis for Bioconductor.

Science.gov (United States)

Bauer, Sebastian; Robinson, Peter N; Gagneur, Julien

2011-07-01

Gene Ontology and other forms of gene-category analysis play a major role in the evaluation of high-throughput experiments in molecular biology. Single-category enrichment analysis procedures such as Fisher's exact test tend to flag large numbers of redundant categories as significant, which can complicate interpretation. We have recently developed an approach called model-based gene set analysis (MGSA), that substantially reduces the number of redundant categories returned by the gene-category analysis. In this work, we present the Bioconductor package mgsa, which makes the MGSA algorithm available to users of the R language. Our package provides a simple and flexible application programming interface for applying the approach. The mgsa package has been made available as part of Bioconductor 2.8. It is released under the conditions of the Artistic license 2.0. peter.robinson@charite.de; julien.gagneur@embl.de.

Finite element modelling for fatigue stress analysis of large suspension bridges

Science.gov (United States)

Chan, Tommy H. T.; Guo, L.; Li, Z. X.

2003-03-01

Fatigue is an important failure mode for large suspension bridges under traffic loadings. However, large suspension bridges have so many attributes that it is difficult to analyze their fatigue damage using experimental measurement methods. Numerical simulation is a feasible method of studying such fatigue damage. In British standards, the finite element method is recommended as a rigorous method for steel bridge fatigue analysis. This paper aims at developing a finite element (FE) model of a large suspension steel bridge for fatigue stress analysis. As a case study, a FE model of the Tsing Ma Bridge is presented. The verification of the model is carried out with the help of the measured bridge modal characteristics and the online data measured by the structural health monitoring system installed on the bridge. The results show that the constructed FE model is efficient for bridge dynamic analysis. Global structural analyses using the developed FE model are presented to determine the components of the nominal stress generated by railway loadings and some typical highway loadings. The critical locations in the bridge main span are also identified with the numerical results of the global FE stress analysis. Local stress analysis of a typical weld connection is carried out to obtain the hot-spot stresses in the region. These results provide a basis for evaluating fatigue damage and predicting the remaining life of the bridge.

Representing the Past by Solid Modeling + Golden Ratio Analysis

Science.gov (United States)

Ding, Suining

2008-01-01

This paper describes the procedures of reconstructing ancient architecture using solid modeling with geometric analysis, especially the Golden Ratio analysis. In the past the recovery and reconstruction of ruins required bringing together fragments of evidence and vast amount of measurements from archaeological site. Although researchers and…

NMR and modelling techniques in structural and conformation analysis

Energy Technology Data Exchange (ETDEWEB)

Abraham, R J [Liverpool Univ. (United Kingdom)

1994-12-31

The use of Lanthanide Induced Shifts (L.I.S.) and modelling techniques in conformational analysis is presented. The use of Co{sup III} porphyrins as shift reagents is discussed, with examples of their use in the conformational analysis of some heterocyclic amines. (author) 13 refs., 9 figs.

Frequency-Zooming ARMA Modeling for Analysis of Noisy String Instrument Tones

Directory of Open Access Journals (Sweden)

Paulo A. A. Esquef

2003-09-01

Full Text Available This paper addresses model-based analysis of string instrument sounds. In particular, it reviews the application of autoregressive (AR modeling to sound analysis/synthesis purposes. Moreover, a frequency-zooming autoregressive moving average (FZ-ARMA modeling scheme is described. The performance of the FZ-ARMA method on modeling the modal behavior of isolated groups of resonance frequencies is evaluated for both synthetic and real string instrument tones immersed in background noise. We demonstrate that the FZ-ARMA modeling is a robust tool to estimate the decay time and frequency of partials of noisy tones. Finally, we discuss the use of the method in synthesis of string instrument sounds.

Modelling and analysis of real-time and hybrid systems

Energy Technology Data Exchange (ETDEWEB)

Olivero, A

1994-09-29

This work deals with the modelling and analysis of real-time and hybrid systems. We first present the timed-graphs as model for the real-time systems and we recall the basic notions of the analysis of real-time systems. We describe the temporal properties on the timed-graphs using TCTL formulas. We consider two methods for property verification: in one hand we study the symbolic model-checking (based on backward analysis) and in the other hand we propose a verification method derived of the construction of the simulation graph (based on forward analysis). Both methods have been implemented within the KRONOS verification tool. Their application for the automatic verification on several real-time systems confirms the practical interest of our approach. In a second part we study the hybrid systems, systems combining discrete components with continuous ones. As in the general case the analysis of this king of systems is not decidable, we identify two sub-classes of hybrid systems and we give a construction based method for the generation of a timed-graph from an element into the sub-classes. We prove that in one case the timed-graph obtained is bi-similar with the considered system and that there exists a simulation in the other case. These relationships allow the application of the described technics on the hybrid systems into the defined sub-classes. (authors). 60 refs., 43 figs., 8 tabs., 2 annexes.

Modeling individual differences in randomized experiments using growth models: Recommendations for design, statistical analysis and reporting of results of internet interventions

Directory of Open Access Journals (Sweden)

Hugo Hesser

2015-05-01

Full Text Available Growth models (also known as linear mixed effects models, multilevel models, and random coefficients models have the capability of studying change at the group as well as the individual level. In addition, these methods have documented advantages over traditional data analytic approaches in the analysis of repeated-measures data. These advantages include, but are not limited to, the ability to incorporate time-varying predictors, handle dependence among repeated observations in a very flexible manner, and to provide accurate estimates with missing data under fairly unrestrictive missing data assumptions. The flexibility of the growth curve modeling approach to the analysis of change makes it the preferred choice in the evaluation of direct, indirect and moderated intervention effects. Although offering many benefits, growth models present challenges in terms of design, analysis and reporting of results. This paper provides a nontechnical overview of growth models in the analysis of change in randomized experiments and advocates for their use in the field of internet interventions. Practical recommendations for design, analysis and reporting of results from growth models are provided.

Sparse Principal Component Analysis in Medical Shape Modeling

DEFF Research Database (Denmark)

Sjöstrand, Karl; Stegmann, Mikkel Bille; Larsen, Rasmus

2006-01-01

Principal component analysis (PCA) is a widely used tool in medical image analysis for data reduction, model building, and data understanding and exploration. While PCA is a holistic approach where each new variable is a linear combination of all original variables, sparse PCA (SPCA) aims...... analysis in medicine. Results for three different data sets are given in relation to standard PCA and sparse PCA by simple thresholding of sufficiently small loadings. Focus is on a recent algorithm for computing sparse principal components, but a review of other approaches is supplied as well. The SPCA...

Analysis of deterministic cyclic gene regulatory network models with delays

CERN Document Server

Ahsen, Mehmet Eren; Niculescu, Silviu-Iulian

2015-01-01

This brief examines a deterministic, ODE-based model for gene regulatory networks (GRN) that incorporates nonlinearities and time-delayed feedback. An introductory chapter provides some insights into molecular biology and GRNs. The mathematical tools necessary for studying the GRN model are then reviewed, in particular Hill functions and Schwarzian derivatives. One chapter is devoted to the analysis of GRNs under negative feedback with time delays and a special case of a homogenous GRN is considered. Asymptotic stability analysis of GRNs under positive feedback is then considered in a separate chapter, in which conditions leading to bi-stability are derived. Graduate and advanced undergraduate students and researchers in control engineering, applied mathematics, systems biology and synthetic biology will find this brief to be a clear and concise introduction to the modeling and analysis of GRNs.

An effective convolutional neural network model for Chinese sentiment analysis

Science.gov (United States)

Zhang, Yu; Chen, Mengdong; Liu, Lianzhong; Wang, Yadong

2017-06-01

Nowadays microblog is getting more and more popular. People are increasingly accustomed to expressing their opinions on Twitter, Facebook and Sina Weibo. Sentiment analysis of microblog has received significant attention, both in academia and in industry. So far, Chinese microblog exploration still needs lots of further work. In recent years CNN has also been used to deal with NLP tasks, and already achieved good results. However, these methods ignore the effective use of a large number of existing sentimental resources. For this purpose, we propose a Lexicon-based Sentiment Convolutional Neural Networks (LSCNN) model focus on Weibo's sentiment analysis, which combines two CNNs, trained individually base on sentiment features and word embedding, at the fully connected hidden layer. The experimental results show that our model outperforms the CNN model only with word embedding features on microblog sentiment analysis task.

Multifunctional Collaborative Modeling and Analysis Methods in Engineering Science

Science.gov (United States)

Ransom, Jonathan B.; Broduer, Steve (Technical Monitor)

2001-01-01

Engineers are challenged to produce better designs in less time and for less cost. Hence, to investigate novel and revolutionary design concepts, accurate, high-fidelity results must be assimilated rapidly into the design, analysis, and simulation process. This assimilation should consider diverse mathematical modeling and multi-discipline interactions necessitated by concepts exploiting advanced materials and structures. Integrated high-fidelity methods with diverse engineering applications provide the enabling technologies to assimilate these high-fidelity, multi-disciplinary results rapidly at an early stage in the design. These integrated methods must be multifunctional, collaborative, and applicable to the general field of engineering science and mechanics. Multifunctional methodologies and analysis procedures are formulated for interfacing diverse subdomain idealizations including multi-fidelity modeling methods and multi-discipline analysis methods. These methods, based on the method of weighted residuals, ensure accurate compatibility of primary and secondary variables across the subdomain interfaces. Methods are developed using diverse mathematical modeling (i.e., finite difference and finite element methods) and multi-fidelity modeling among the subdomains. Several benchmark scalar-field and vector-field problems in engineering science are presented with extensions to multidisciplinary problems. Results for all problems presented are in overall good agreement with the exact analytical solution or the reference numerical solution. Based on the results, the integrated modeling approach using the finite element method for multi-fidelity discretization among the subdomains is identified as most robust. The multiple-method approach is advantageous when interfacing diverse disciplines in which each of the method's strengths are utilized. The multifunctional methodology presented provides an effective mechanism by which domains with diverse idealizations are

Sensitivity analysis of the terrestrial food chain model FOOD III

International Nuclear Information System (INIS)

Zach, Reto.

1980-10-01

As a first step in constructing a terrestrial food chain model suitable for long-term waste management situations, a numerical sensitivity analysis of FOOD III was carried out to identify important model parameters. The analysis involved 42 radionuclides, four pathways, 14 food types, 93 parameters and three percentages of parameter variation. We also investigated the importance of radionuclides, pathways and food types. The analysis involved a simple contamination model to render results from individual pathways comparable. The analysis showed that radionuclides vary greatly in their dose contribution to each of the four pathways, but relative contributions to each pathway are very similar. Man's and animals' drinking water pathways are much more important than the leaf and root pathways. However, this result depends on the contamination model used. All the pathways contain unimportant food types. Considering the number of parameters involved, FOOD III has too many different food types. Many of the parameters of the leaf and root pathway are important. However, this is true for only a few of the parameters of animals' drinking water pathway, and for neither of the two parameters of mans' drinking water pathway. The radiological decay constant increases the variability of these results. The dose factor is consistently the most important variable, and it explains most of the variability of radionuclide doses within pathways. Consideration of the variability of dose factors is important in contemporary as well as long-term waste management assessment models, if realistic estimates are to be made. (auth)

DMFC performance and methanol cross-over: Experimental analysis and model validation

Energy Technology Data Exchange (ETDEWEB)

Casalegno, A.; Marchesi, R. [Dipartimento di Energia, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milano (Italy)

2008-10-15

A combined experimental and modelling approach is proposed to analyze methanol cross-over and its effect on DMFC performance. The experimental analysis is performed in order to allow an accurate investigation of methanol cross-over influence on DMFC performance, hence measurements were characterized in terms of uncertainty and reproducibility. The findings suggest that methanol cross-over is mainly determined by diffusion transport and affects cell performance partly via methanol electro-oxidation at the cathode. The modelling analysis is carried out to further investigate methanol cross-over phenomenon. A simple model evaluates the effectiveness of two proposed interpretations regarding methanol cross-over and its effects. The model is validated using the experimental data gathered. Both the experimental analysis and the proposed and validated model allow a substantial step forward in the understanding of the main phenomena associated with methanol cross-over. The findings confirm the possibility to reduce methanol cross-over by optimizing anode feeding. (author)

Predicate Argument Structure Analysis for Use Case Description Modeling

Science.gov (United States)

Takeuchi, Hironori; Nakamura, Taiga; Yamaguchi, Takahira

In a large software system development project, many documents are prepared and updated frequently. In such a situation, support is needed for looking through these documents easily to identify inconsistencies and to maintain traceability. In this research, we focus on the requirements documents such as use cases and consider how to create models from the use case descriptions in unformatted text. In the model construction, we propose a few semantic constraints based on the features of the use cases and use them for a predicate argument structure analysis to assign semantic labels to actors and actions. With this approach, we show that we can assign semantic labels without enhancing any existing general lexical resources such as case frame dictionaries and design a less language-dependent model construction architecture. By using the constructed model, we consider a system for quality analysis of the use cases and automated test case generation to keep the traceability between document sets. We evaluated the reuse of the existing use cases and generated test case steps automatically with the proposed prototype system from real-world use cases in the development of a system using a packaged application. Based on the evaluation, we show how to construct models with high precision from English and Japanese use case data. Also, we could generate good test cases for about 90% of the real use cases through the manual improvement of the descriptions based on the feedback from the quality analysis system.

Economic Modeling and Analysis of Educational Vouchers

Science.gov (United States)

Epple, Dennis; Romano, Richard

2012-01-01

The analysis of educational vouchers has evolved from market-based analogies to models that incorporate distinctive features of the educational environment. These distinctive features include peer effects, scope for private school pricing and admissions based on student characteristics, the linkage of household residential and school choices in…

Power system stability modelling, analysis and control

CERN Document Server

Sallam, Abdelhay A

2015-01-01

This book provides a comprehensive treatment of the subject from both a physical and mathematical perspective and covers a range of topics including modelling, computation of load flow in the transmission grid, stability analysis under both steady-state and disturbed conditions, and appropriate controls to enhance stability.

Advances in statistical models for data analysis

CERN Document Server

Minerva, Tommaso; Vichi, Maurizio

2015-01-01

This edited volume focuses on recent research results in classification, multivariate statistics and machine learning and highlights advances in statistical models for data analysis. The volume provides both methodological developments and contributions to a wide range of application areas such as economics, marketing, education, social sciences and environment. The papers in this volume were first presented at the 9th biannual meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, held in September 2013 at the University of Modena and Reggio Emilia, Italy.

Precise Model Analysis for 3-phase High Power Converter using the Harmonic State Space Modeling

DEFF Research Database (Denmark)

Kwon, Jun Bum; Wang, Xiongfei; Blaabjerg, Frede

2015-01-01

This paper presents about the generalized multi-frequency modeling and analysis methodology, which can be used in control loop design and stability analysis. In terms of the switching frequency of high power converter, there can be harmonics interruption if the voltage source converter has a low...... switching frequency ratio or multi-sampling frequency. The range of the control bandwidth can include the switching component. Thus, the systems become unstable. This paper applies the Harmonic State Space (HSS) Modeling method in order to find out the transfer function for each harmonics terms...

A Mathematical Model for Analysis on Ships Collision Avoidance ...

African Journals Online (AJOL)

This study develops a mathematical model for analysis on collision avoidance of ships. The obtained model provides information on the quantitative effect of the ship's engine's response and the applied reversing force on separation distance and stopping abilities of the ships. Appropriate evasive maneuvers require the ...

Deterministic sensitivity and uncertainty analysis for large-scale computer models

International Nuclear Information System (INIS)

Worley, B.A.; Pin, F.G.; Oblow, E.M.; Maerker, R.E.; Horwedel, J.E.; Wright, R.Q.

1988-01-01

This paper presents a comprehensive approach to sensitivity and uncertainty analysis of large-scale computer models that is analytic (deterministic) in principle and that is firmly based on the model equations. The theory and application of two systems based upon computer calculus, GRESS and ADGEN, are discussed relative to their role in calculating model derivatives and sensitivities without a prohibitive initial manpower investment. Storage and computational requirements for these two systems are compared for a gradient-enhanced version of the PRESTO-II computer model. A Deterministic Uncertainty Analysis (DUA) method that retains the characteristics of analytically computing result uncertainties based upon parameter probability distributions is then introduced and results from recent studies are shown. 29 refs., 4 figs., 1 tab

Analysis and optimization of dynamic model of eccentric shaft grinder

Science.gov (United States)

Gao, Yangjie; Han, Qiushi; Li, Qiguang; Peng, Baoying

2018-04-01

Eccentric shaft servo grinder is the core equipment in the process chain of machining eccentric shaft. The establishment of the movement model and the determination of the kinematic relation of the-axis in the grinding process directly affect the quality of the grinding process, and there are many error factors in grinding, and it is very important to analyze the influence of these factors on the work piece quality. The three-dimensional model of eccentric shaft grinder is drawn by Pro/E three-dimensional drawing software, the model is imported into ANSYS Workbench Finite element analysis software, and the finite element analysis is carried out, and then the variation and parameters of each component of the bed are obtained by the modal analysis result. The natural frequencies and formations of the first six steps of the eccentric shaft grinder are obtained by modal analysis, and the weak links of the parts of the grinder are found out, and a reference improvement method is proposed for the design of the eccentric shaft grinder in the future.

ANALYSIS MODEL FOR RETURN ON CAPITAL EMPLOYED

Directory of Open Access Journals (Sweden)

BURJA CAMELIA

2013-02-01

Full Text Available At the microeconomic level, the appreciation of the capitals’ profitability is a very complex action which is ofinterest for stakeholders. This study has as main purpose to extend the traditional analysis model for the capitals’profitability, based on the ratio “Return on capital employed”. In line with it the objectives of this work aim theidentification of factors that exert an influence on the capital’s profitability utilized by a company and the measurementof their contribution in the manifestation of the phenomenon. The proposed analysis model is validated on the use caseof a representative company from the agricultural sector. The results obtained reveal that in a company there are somefactors which can act positively on the capitals’ profitability: capital turnover, sales efficiency, increase the share ofsales in the total revenues, improvement of the expenses’ efficiency. The findings are useful both for the decisionmakingfactors in substantiating the economic strategies and for the capital owners who are interested in efficiency oftheir investments.

Analyzing Multiple-Choice Questions by Model Analysis and Item Response Curves

Science.gov (United States)

Wattanakasiwich, P.; Ananta, S.

2010-07-01

In physics education research, the main goal is to improve physics teaching so that most students understand physics conceptually and be able to apply concepts in solving problems. Therefore many multiple-choice instruments were developed to probe students' conceptual understanding in various topics. Two techniques including model analysis and item response curves were used to analyze students' responses from Force and Motion Conceptual Evaluation (FMCE). For this study FMCE data from more than 1000 students at Chiang Mai University were collected over the past three years. With model analysis, we can obtain students' alternative knowledge and the probabilities for students to use such knowledge in a range of equivalent contexts. The model analysis consists of two algorithms—concentration factor and model estimation. This paper only presents results from using the model estimation algorithm to obtain a model plot. The plot helps to identify a class model state whether it is in the misconception region or not. Item response curve (IRC) derived from item response theory is a plot between percentages of students selecting a particular choice versus their total score. Pros and cons of both techniques are compared and discussed.

Integrated Exoplanet Modeling with the GSFC Exoplanet Modeling & Analysis Center (EMAC)

Science.gov (United States)

Mandell, Avi M.; Hostetter, Carl; Pulkkinen, Antti; Domagal-Goldman, Shawn David

2018-01-01

Our ability to characterize the atmospheres of extrasolar planets will be revolutionized by JWST, WFIRST and future ground- and space-based telescopes. In preparation, the exoplanet community must develop an integrated suite of tools with which we can comprehensively predict and analyze observations of exoplanets, in order to characterize the planetary environments and ultimately search them for signs of habitability and life.The GSFC Exoplanet Modeling and Analysis Center (EMAC) will be a web-accessible high-performance computing platform with science support for modelers and software developers to host and integrate their scientific software tools, with the goal of leveraging the scientific contributions from the entire exoplanet community to improve our interpretations of future exoplanet discoveries. Our suite of models will include stellar models, models for star-planet interactions, atmospheric models, planet system science models, telescope models, instrument models, and finally models for retrieving signals from observational data. By integrating this suite of models, the community will be able to self-consistently calculate the emergent spectra from the planet whether from emission, scattering, or in transmission, and use these simulations to model the performance of current and new telescopes and their instrumentation.The EMAC infrastructure will not only provide a repository for planetary and exoplanetary community models, modeling tools and intermodal comparisons, but it will include a "run-on-demand" portal with each software tool hosted on a separate virtual machine. The EMAC system will eventually include a means of running or “checking in” new model simulations that are in accordance with the community-derived standards. Additionally, the results of intermodal comparisons will be used to produce open source publications that quantify the model comparisons and provide an overview of community consensus on model uncertainties on the climates of

System Reliability Analysis Capability and Surrogate Model Application in RAVEN

Energy Technology Data Exchange (ETDEWEB)

Rabiti, Cristian [Idaho National Lab. (INL), Idaho Falls, ID (United States); Alfonsi, Andrea [Idaho National Lab. (INL), Idaho Falls, ID (United States); Huang, Dongli [Idaho National Lab. (INL), Idaho Falls, ID (United States); Gleicher, Frederick [Idaho National Lab. (INL), Idaho Falls, ID (United States); Wang, Bei [Idaho National Lab. (INL), Idaho Falls, ID (United States); Adbel-Khalik, Hany S. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Pascucci, Valerio [Idaho National Lab. (INL), Idaho Falls, ID (United States); Smith, Curtis L. [Idaho National Lab. (INL), Idaho Falls, ID (United States)

2015-11-01

This report collect the effort performed to improve the reliability analysis capabilities of the RAVEN code and explore new opportunity in the usage of surrogate model by extending the current RAVEN capabilities to multi physics surrogate models and construction of surrogate models for high dimensionality fields.

A flammability and combustion model for integrated accident analysis

International Nuclear Information System (INIS)

Plys, M.G.; Astleford, R.D.; Epstein, M.

1988-01-01

A model for flammability characteristics and combustion of hydrogen and carbon monoxide mixtures is presented for application to severe accident analysis of Advanced Light Water Reactors (ALWR's). Flammability of general mixtures for thermodynamic conditions anticipated during a severe accident is quantified with a new correlation technique applied to data for several fuel and inertant mixtures and using accepted methods for combining these data. Combustion behavior is quantified by a mechanistic model consisting of a continuity and momentum balance for the burned gases, and considering an uncertainty parameter to match the idealized process to experiment. Benchmarks against experiment demonstrate the validity of this approach for a single recommended value of the flame flux multiplier parameter. The models presented here are equally applicable to analysis of current LWR's. 21 refs., 16 figs., 6 tabs

Micropollutants throughout an integrated urban drainage model: Sensitivity and uncertainty analysis

Science.gov (United States)

Mannina, Giorgio; Cosenza, Alida; Viviani, Gaspare

2017-11-01

The paper presents the sensitivity and uncertainty analysis of an integrated urban drainage model which includes micropollutants. Specifically, a bespoke integrated model developed in previous studies has been modified in order to include the micropollutant assessment (namely, sulfamethoxazole - SMX). The model takes into account also the interactions between the three components of the system: sewer system (SS), wastewater treatment plant (WWTP) and receiving water body (RWB). The analysis has been applied to an experimental catchment nearby Palermo (Italy): the Nocella catchment. Overall, five scenarios, each characterized by different uncertainty combinations of sub-systems (i.e., SS, WWTP and RWB), have been considered applying, for the sensitivity analysis, the Extended-FAST method in order to select the key factors affecting the RWB quality and to design a reliable/useful experimental campaign. Results have demonstrated that sensitivity analysis is a powerful tool for increasing operator confidence in the modelling results. The approach adopted here can be used for blocking some non-identifiable factors, thus wisely modifying the structure of the model and reducing the related uncertainty. The model factors related to the SS have been found to be the most relevant factors affecting the SMX modeling in the RWB when all model factors (scenario 1) or model factors of SS (scenarios 2 and 3) are varied. If the only factors related to the WWTP are changed (scenarios 4 and 5), the SMX concentration in the RWB is mainly influenced (till to 95% influence of the total variance for SSMX,max) by the aerobic sorption coefficient. A progressive uncertainty reduction from the upstream to downstream was found for the soluble fraction of SMX in the RWB.

Distributed resistance model for the analysis of wire-wrapped rod bundles

International Nuclear Information System (INIS)

Ha, K. S.; Jung, H. Y.; Kwon, Y. M.; Jang, W. P.; Lee, Y. B.

2003-01-01

A partial flow blockage within a fuel assembly in liquid metal reactor may result in localized boiling or a failure of the fuel cladding. Thus, the precise analysis for the phenomenon is required for a safe design of LMR. MATRA-LMR code developed by KAERI models the flow distribution in an assembly by using the wire forcing function to consider the effects of wire-wrap spacers, which is important to the analysis for flow blockage. However, the wire forcing function does not have the capabilities of analysis when the flow blockage is occurred. And thus this model was altered to the distributed resistance model and the validation calculation was carried out against to the experiment of FFM 2A

Landsat analysis of tropical forest succession employing a terrain model

Science.gov (United States)

Barringer, T. H.; Robinson, V. B.; Coiner, J. C.; Bruce, R. C.

1980-01-01

Landsat multispectral scanner (MSS) data have yielded a dual classification of rain forest and shadow in an analysis of a semi-deciduous forest on Mindonoro Island, Philippines. Both a spatial terrain model, using a fifth side polynomial trend surface analysis for quantitatively estimating the general spatial variation in the data set, and a spectral terrain model, based on the MSS data, have been set up. A discriminant analysis, using both sets of data, has suggested that shadowing effects may be due primarily to local variations in the spectral regions and can therefore be compensated for through the decomposition of the spatial variation in both elevation and MSS data.

Liquidity and liquidity cost vs. bank profitability. A model analysis attempt

OpenAIRE

Boguslaw Guzik

2008-01-01

The author suggests a “model” of relations between liquidity, costs of liquidity and basic or empirical profitability. The first part of the article present the idea of the model analysis. The author makes an effort to explain the frequent empirical paradox – when an increase of liquidity is accompanied by an increase in profitability. The second part present the model analysis in more detail. The author refers to the economic and econometrical model formation. He suggests using the bank prof...

Analysis and Comparison of Typical Models within Distribution Network Design

DEFF Research Database (Denmark)

Jørgensen, Hans Jacob; Larsen, Allan; Madsen, Oli B.G.

This paper investigates the characteristics of typical optimisation models within Distribution Network Design. During the paper fourteen models known from the literature will be thoroughly analysed. Through this analysis a schematic approach to categorisation of distribution network design models...... for educational purposes. Furthermore, the paper can be seen as a practical introduction to network design modelling as well as a being an art manual or recipe when constructing such a model....

Dynamical system analysis of interacting models

Science.gov (United States)

Carneiro, S.; Borges, H. A.

2018-01-01

We perform a dynamical system analysis of a cosmological model with linear dependence between the vacuum density and the Hubble parameter, with constant-rate creation of dark matter. We show that the de Sitter spacetime is an asymptotically stable critical point, future limit of any expanding solution. Our analysis also shows that the Minkowski spacetime is an unstable critical point, which eventually collapses to a singularity. In this way, such a prescription for the vacuum decay not only predicts the correct future de Sitter limit, but also forbids the existence of a stable Minkowski universe. We also study the effect of matter creation on the growth of structures and their peculiar velocities, showing that it is inside the current errors of redshift space distortions observations.

Application of linearized model to the stability analysis of the pressurized water reactor

International Nuclear Information System (INIS)

Li Haipeng; Huang Xiaojin; Zhang Liangju

2008-01-01

A Linear Time-Invariant model of the Pressurized Water Reactor is formulated through the linearization of the nonlinear model. The model simulation results show that the linearized model agrees well with the nonlinear model under small perturbation. Based upon the Lyapunov's First Method, the linearized model is applied to the stability analysis of the Pressurized Water Reactor. The calculation results show that the methodology of linearization to stability analysis is conveniently feasible. (authors)

Bayesian Analysis of Multidimensional Item Response Theory Models: A Discussion and Illustration of Three Response Style Models

Science.gov (United States)

Leventhal, Brian C.; Stone, Clement A.

2018-01-01

Interest in Bayesian analysis of item response theory (IRT) models has grown tremendously due to the appeal of the paradigm among psychometricians, advantages of these methods when analyzing complex models, and availability of general-purpose software. Possible models include models which reflect multidimensionality due to designed test structure,…

An analysis of urban collisions using an artificial intelligence model.

Science.gov (United States)

Mussone, L; Ferrari, A; Oneta, M

1999-11-01

Traditional studies on road accidents estimate the effect of variables (such as vehicular flows, road geometry, vehicular characteristics), and the calculation of the number of accidents. A descriptive statistical analysis of the accidents (those used in the model) over the period 1992-1995 is proposed. The paper describes an alternative method based on the use of artificial neural networks (ANN) in order to work out a model that relates to the analysis of vehicular accidents in Milan. The degree of danger of urban intersections using different scenarios is quantified by the ANN model. Methodology is the first result, which allows us to tackle the modelling of urban vehicular accidents by the innovative use of ANN. Other results deal with model outputs: intersection complexity may determine a higher accident index depending on the regulation of intersection. The highest index for running over of pedestrian occurs at non-signalised intersections at night-time.

An introduction to queueing theory modeling and analysis in applications

CERN Document Server

Bhat, U Narayan

2015-01-01

This introductory textbook is designed for a one-semester course on queueing theory that does not require a course on stochastic processes as a prerequisite. By integrating the necessary background on stochastic processes with the analysis of models, the work provides a sound foundational introduction to the modeling and analysis of queueing systems for a wide interdisciplinary audience of students in mathematics, statistics, and applied disciplines such as computer science, operations research, and engineering. This edition includes additional topics in methodology and applications. Key features: • An introductory chapter including a historical account of the growth of queueing theory in more than 100 years. • A modeling-based approach with emphasis on identification of models. • Rigorous treatment of the foundations of basic models commonly used in applications with appropriate references for advanced topics. • Applications in manufacturing and, computer and communication systems. • A chapter on ...

The Run 2 ATLAS Analysis Event Data Model

CERN Document Server

SNYDER, S; The ATLAS collaboration; NOWAK, M; EIFERT, T; BUCKLEY, A; ELSING, M; GILLBERG, D; MOYSE, E; KOENEKE, K; KRASZNAHORKAY, A

2014-01-01

During the LHC's first Long Shutdown (LS1) ATLAS set out to establish a new analysis model, based on the experience gained during Run 1. A key component of this is a new Event Data Model (EDM), called the xAOD. This format, which is now in production, provides the following features: A separation of the EDM into interface classes that the user code directly interacts with, and data storage classes that hold the payload data. The user sees an Array of Structs (AoS) interface, while the data is stored in a Struct of Arrays (SoA) format in memory, thus making it possible to efficiently auto-vectorise reconstruction code. A simple way of augmenting and reducing the information saved for different data objects. This makes it possible to easily decorate objects with new properties during data analysis, and to remove properties that the analysis does not need. A persistent file format that can be explored directly with ROOT, either with or without loading any additional libraries. This allows fast interactive naviga...

Modeling, Analysis, Simulation, and Synthesis of Biomolecular Networks

National Research Council Canada - National Science Library

Ruben, Harvey; Kumar, Vijay; Sokolsky, Oleg

2006-01-01

...) a first example of reachability analysis applied to a biomolecular system (lactose induction), 4) a model of tetracycline resistance that discriminates between two possible mechanisms for tetracycline diffusion through the cell membrane, and 5...

Variance-based sensitivity analysis for wastewater treatment plant modelling.

Science.gov (United States)

Cosenza, Alida; Mannina, Giorgio; Vanrolleghem, Peter A; Neumann, Marc B

2014-02-01

Global sensitivity analysis (GSA) is a valuable tool to support the use of mathematical models that characterise technical or natural systems. In the field of wastewater modelling, most of the recent applications of GSA use either regression-based methods, which require close to linear relationships between the model outputs and model factors, or screening methods, which only yield qualitative results. However, due to the characteristics of membrane bioreactors (MBR) (non-linear kinetics, complexity, etc.) there is an interest to adequately quantify the effects of non-linearity and interactions. This can be achieved with variance-based sensitivity analysis methods. In this paper, the Extended Fourier Amplitude Sensitivity Testing (Extended-FAST) method is applied to an integrated activated sludge model (ASM2d) for an MBR system including microbial product formation and physical separation processes. Twenty-one model outputs located throughout the different sections of the bioreactor and 79 model factors are considered. Significant interactions among the model factors are found. Contrary to previous GSA studies for ASM models, we find the relationship between variables and factors to be non-linear and non-additive. By analysing the pattern of the variance decomposition along the plant, the model factors having the highest variance contributions were identified. This study demonstrates the usefulness of variance-based methods in membrane bioreactor modelling where, due to the presence of membranes and different operating conditions than those typically found in conventional activated sludge systems, several highly non-linear effects are present. Further, the obtained results highlight the relevant role played by the modelling approach for MBR taking into account simultaneously biological and physical processes. © 2013.

The case for repeatable analysis with energy economy optimization models

International Nuclear Information System (INIS)

DeCarolis, Joseph F.; Hunter, Kevin; Sreepathi, Sarat

2012-01-01

Energy economy optimization (EEO) models employ formal search techniques to explore the future decision space over several decades in order to deliver policy-relevant insights. EEO models are a critical tool for decision-makers who must make near-term decisions with long-term effects in the face of large future uncertainties. While the number of model-based analyses proliferates, insufficient attention is paid to transparency in model development and application. Given the complex, data-intensive nature of EEO models and the general lack of access to source code and data, many of the assumptions underlying model-based analysis are hidden from external observers. This paper discusses the simplifications and subjective judgments involved in the model building process, which cannot be fully articulated in journal papers, reports, or model documentation. In addition, we argue that for all practical purposes, EEO model-based insights cannot be validated through comparison to real world outcomes. As a result, modelers are left without credible metrics to assess a model's ability to deliver reliable insight. We assert that EEO models should be discoverable through interrogation of publicly available source code and data. In addition, third parties should be able to run a specific model instance in order to independently verify published results. Yet a review of twelve EEO models suggests that in most cases, replication of model results is currently impossible. We provide several recommendations to help develop and sustain a software framework for repeatable model analysis.

Analysis of MUF data using arima models

International Nuclear Information System (INIS)

Downing, D.J.; Pike, D.H.; Morrison, G.W.

1978-01-01

An introduction to Box-Jenkins time series analysis is presented. It is shown how the models presented by Box-Jenkins can be applied to material unaccounted for (MUF) data to detect losses. For the constant loss case an optimal estimate of the loss is found and its probability of detection found

Determining Predictor Importance in Hierarchical Linear Models Using Dominance Analysis

Science.gov (United States)

Luo, Wen; Azen, Razia

2013-01-01

Dominance analysis (DA) is a method used to evaluate the relative importance of predictors that was originally proposed for linear regression models. This article proposes an extension of DA that allows researchers to determine the relative importance of predictors in hierarchical linear models (HLM). Commonly used measures of model adequacy in…

Model Uncertainty and Robustness: A Computational Framework for Multimodel Analysis

Science.gov (United States)

Young, Cristobal; Holsteen, Katherine

2017-01-01

Model uncertainty is pervasive in social science. A key question is how robust empirical results are to sensible changes in model specification. We present a new approach and applied statistical software for computational multimodel analysis. Our approach proceeds in two steps: First, we estimate the modeling distribution of estimates across all…

PeTTSy: a computational tool for perturbation analysis of complex systems biology models.

Science.gov (United States)

Domijan, Mirela; Brown, Paul E; Shulgin, Boris V; Rand, David A

2016-03-10

Over the last decade sensitivity analysis techniques have been shown to be very useful to analyse complex and high dimensional Systems Biology models. However, many of the currently available toolboxes have either used parameter sampling, been focused on a restricted set of model observables of interest, studied optimisation of a objective function, or have not dealt with multiple simultaneous model parameter changes where the changes can be permanent or temporary. Here we introduce our new, freely downloadable toolbox, PeTTSy (Perturbation Theory Toolbox for Systems). PeTTSy is a package for MATLAB which implements a wide array of techniques for the perturbation theory and sensitivity analysis of large and complex ordinary differential equation (ODE) based models. PeTTSy is a comprehensive modelling framework that introduces a number of new approaches and that fully addresses analysis of oscillatory systems. It examines sensitivity analysis of the models to perturbations of parameters, where the perturbation timing, strength, length and overall shape can be controlled by the user. This can be done in a system-global setting, namely, the user can determine how many parameters to perturb, by how much and for how long. PeTTSy also offers the user the ability to explore the effect of the parameter perturbations on many different types of outputs: period, phase (timing of peak) and model solutions. PeTTSy can be employed on a wide range of mathematical models including free-running and forced oscillators and signalling systems. To enable experimental optimisation using the Fisher Information Matrix it efficiently allows one to combine multiple variants of a model (i.e. a model with multiple experimental conditions) in order to determine the value of new experiments. It is especially useful in the analysis of large and complex models involving many variables and parameters. PeTTSy is a comprehensive tool for analysing large and complex models of regulatory and

Modeling and analysis on ring-type piezoelectric transformers.

Science.gov (United States)

Ho, Shine-Tzong

2007-11-01

This paper presents an electromechanical model for a ring-type piezoelectric transformer (PT). To establish this model, vibration characteristics of the piezoelectric ring with free boundary conditions are analyzed in advance. Based on the vibration analysis of the piezoelectric ring, the operating frequency and vibration mode of the PT are chosen. Then, electromechanical equations of motion for the PT are derived based on Hamilton's principle, which can be used to simulate the coupled electromechanical system for the transformer. Such as voltage stepup ratio, input impedance, output impedance, input power, output power, and efficiency are calculated by the equations. The optimal load resistance and the maximum efficiency for the PT will be presented in this paper. Experiments also were conducted to verify the theoretical analysis, and a good agreement was obtained.

Preliminary analysis of a 1:4 scale prestressed concrete containment vessel model

International Nuclear Information System (INIS)

Dameron, R.A.; Rashid, Y.R.; Luk, V.K.; Hessheimer, M.F.

1997-01-01

Sandia National Laboratories is conducting a research program to investigate the integrity of nuclear containment structures. As part of the program Sandia will construct an instrumented 1:4 scale model of a prestressed concrete containment vessel (PCCV) for pressurized water reactors (PWR), which will be pressure tested up to its ultimate capacity. One of the key program objectives is to develop validated methods to predict the structural performance of containment vessels when subjected to beyond design basis loadings. Analytical prediction of structural performance requires a stepwise, systematic approach that addresses all potential failure modes. The analysis effort includes two and three-dimensional nonlinear finite element analyses of the PCCV test model to evaluate its structural performance under very high internal pressurization. Such analyses have been performed using the nonlinear concrete constitutive model, ANACAP-U, in conjunction with the ABAQUS general purpose finite element code. The analysis effort is carried out in three phases: preliminary analysis; pretest prediction; and post-test data interpretation and analysis evaluation. The preliminary analysis phase serves to provide instrumentation support and identify candidate failure modes. The associated tasks include the preliminary prediction of failure pressure and probable failure locations and the development of models to be used in the detailed failure analyses. This paper describes the modeling approaches and some of the results obtained in the first phase of the analysis effort

The concept of validation of numerical models for consequence analysis

International Nuclear Information System (INIS)

Borg, Audun; Paulsen Husted, Bjarne; Njå, Ove

2014-01-01

Numerical models such as computational fluid dynamics (CFD) models are increasingly used in life safety studies and other types of analyses to calculate the effects of fire and explosions. The validity of these models is usually established by benchmark testing. This is done to quantitatively measure the agreement between the predictions provided by the model and the real world represented by observations in experiments. This approach assumes that all variables in the real world relevant for the specific study are adequately measured in the experiments and in the predictions made by the model. In this paper the various definitions of validation for CFD models used for hazard prediction are investigated to assess their implication for consequence analysis in a design phase. In other words, how is uncertainty in the prediction of future events reflected in the validation process? The sources of uncertainty are viewed from the perspective of the safety engineer. An example of the use of a CFD model is included to illustrate the assumptions the analyst must make and how these affect the prediction made by the model. The assessments presented in this paper are based on a review of standards and best practice guides for CFD modeling and the documentation from two existing CFD programs. Our main thrust has been to assess how validation work is performed and communicated in practice. We conclude that the concept of validation adopted for numerical models is adequate in terms of model performance. However, it does not address the main sources of uncertainty from the perspective of the safety engineer. Uncertainty in the input quantities describing future events, which are determined by the model user, outweighs the inaccuracies in the model as reported in validation studies. - Highlights: • Examine the basic concept of validation applied to models for consequence analysis. • Review standards and guides for validation of numerical models. • Comparison of the validation

Functional linear models for association analysis of quantitative traits.

Science.gov (United States)

Fan, Ruzong; Wang, Yifan; Mills, James L; Wilson, Alexander F; Bailey-Wilson, Joan E; Xiong, Momiao

2013-11-01

Functional linear models are developed in this paper for testing associations between quantitative traits and genetic variants, which can be rare variants or common variants or the combination of the two. By treating multiple genetic variants of an individual in a human population as a realization of a stochastic process, the genome of an individual in a chromosome region is a continuum of sequence data rather than discrete observations. The genome of an individual is viewed as a stochastic function that contains both linkage and linkage disequilibrium (LD) information of the genetic markers. By using techniques of functional data analysis, both fixed and mixed effect functional linear models are built to test the association between quantitative traits and genetic variants adjusting for covariates. After extensive simulation analysis, it is shown that the F-distributed tests of the proposed fixed effect functional linear models have higher power than that of sequence kernel association test (SKAT) and its optimal unified test (SKAT-O) for three scenarios in most cases: (1) the causal variants are all rare, (2) the causal variants are both rare and common, and (3) the causal variants are common. The superior performance of the fixed effect functional linear models is most likely due to its optimal utilization of both genetic linkage and LD information of multiple genetic variants in a genome and similarity among different individuals, while SKAT and SKAT-O only model the similarities and pairwise LD but do not model linkage and higher order LD information sufficiently. In addition, the proposed fixed effect models generate accurate type I error rates in simulation studies. We also show that the functional kernel score tests of the proposed mixed effect functional linear models are preferable in candidate gene analysis and small sample problems. The methods are applied to analyze three biochemical traits in data from the Trinity Students Study. © 2013 WILEY

Development of interpretation models for PFN uranium log analysis

International Nuclear Information System (INIS)

Barnard, R.W.

1980-11-01

This report presents the models for interpretation of borehole logs for the PFN (Prompt Fission Neutron) uranium logging system. Two models have been developed, the counts-ratio model and the counts/dieaway model. Both are empirically developed, but can be related to the theoretical bases for PFN analysis. The models try to correct for the effects of external factors (such as probe or formation parameters) in the calculation of uranium grade. The theoretical bases and calculational techniques for estimating uranium concentration from raw PFN data and other parameters are discussed. Examples and discussions of borehole logs are included

Rotor-Flying Manipulator: Modeling, Analysis, and Control

Directory of Open Access Journals (Sweden)

Bin Yang

2014-01-01

Full Text Available Equipping multijoint manipulators on a mobile robot is a typical redesign scheme to make the latter be able to actively influence the surroundings and has been extensively used for many ground robots, underwater robots, and space robotic systems. However, the rotor-flying robot (RFR is difficult to be made such redesign. This is mainly because the motion of the manipulator will bring heavy coupling between itself and the RFR system, which makes the system model highly complicated and the controller design difficult. Thus, in this paper, the modeling, analysis, and control of the combined system, called rotor-flying multijoint manipulator (RF-MJM, are conducted. Firstly, the detailed dynamics model is constructed and analyzed. Subsequently, a full-state feedback linear quadratic regulator (LQR controller is designed through obtaining linearized model near steady state. Finally, simulations are conducted and the results are analyzed to show the basic control performance.

Net energy analysis in a Ramsey–Hotelling growth model

International Nuclear Information System (INIS)

Macías, Arturo; Matilla-García, Mariano

2015-01-01

This article presents a dynamic growth model with energy as an input in the production function. The available stock of energy resources is ordered by a quality parameter based on energy accounting: the “Energy Return on Energy Invested” (EROI). In our knowledge this is the first paper where EROI fits in a neoclassical growth model (with individual utility maximization and market equilibrium), establishing the economic use of “net energy analysis” on a firmer theoretical ground. All necessary concepts to link neoclassical economics and EROI are discussed before their use in the model, and a comparative static analysis of the steady states of a simplified version of the model is presented. - Highlights: • A neoclassical growth model with EROI (“Energy Return on Energy Invested”) is shown • All concepts linking neoclassical economics and net energy analysis are discussed • Any EROI decline can be compensated increasing gross activity in the energy sector. • The economic impact of EROI depends on some non-energy cost in the energy sector. • Comparative steady-state statics for different EROI levels is performed and discussed. • Policy implications are suggested.

Formal Analysis of BPMN Models Using Event-B

Science.gov (United States)

Bryans, Jeremy W.; Wei, Wei

The use of business process models has gone far beyond documentation purposes. In the development of business applications, they can play the role of an artifact on which high level properties can be verified and design errors can be revealed in an effort to reduce overhead at later software development and diagnosis stages. This paper demonstrates how formal verification may add value to the specification, design and development of business process models in an industrial setting. The analysis of these models is achieved via an algorithmic translation from the de-facto standard business process modeling language BPMN to Event-B, a widely used formal language supported by the Rodin platform which offers a range of simulation and verification technologies.

Mathematical Modelling Research in Turkey: A Content Analysis Study

Science.gov (United States)

Çelik, H. Coskun

2017-01-01

The aim of the present study was to examine the mathematical modelling studies done between 2004 and 2015 in Turkey and to reveal their tendencies. Forty-nine studies were selected using purposeful sampling based on the term, "mathematical modelling" with Higher Education Academic Search Engine. They were analyzed with content analysis.…

Stability analysis for a general age-dependent vaccination model

International Nuclear Information System (INIS)

El Doma, M.

1995-05-01

An SIR epidemic model of a general age-dependent vaccination model is investigated when the fertility, mortality and removal rates depends on age. We give threshold criteria of the existence of equilibriums and perform stability analysis. Furthermore a critical vaccination coverage that is sufficient to eradicate the disease is determined. (author). 12 refs

Multi-model analysis of terrestrial carbon cycles in Japan: limitations and implications of model calibration using eddy flux observations

Directory of Open Access Journals (Sweden)

K. Ichii

2010-07-01

Full Text Available Terrestrial biosphere models show large differences when simulating carbon and water cycles, and reducing these differences is a priority for developing more accurate estimates of the condition of terrestrial ecosystems and future climate change. To reduce uncertainties and improve the understanding of their carbon budgets, we investigated the utility of the eddy flux datasets to improve model simulations and reduce variabilities among multi-model outputs of terrestrial biosphere models in Japan. Using 9 terrestrial biosphere models (Support Vector Machine – based regressions, TOPS, CASA, VISIT, Biome-BGC, DAYCENT, SEIB, LPJ, and TRIFFID, we conducted two simulations: (1 point simulations at four eddy flux sites in Japan and (2 spatial simulations for Japan with a default model (based on original settings and a modified model (based on model parameter tuning using eddy flux data. Generally, models using default model settings showed large deviations in model outputs from observation with large model-by-model variability. However, after we calibrated the model parameters using eddy flux data (GPP, RE and NEP, most models successfully simulated seasonal variations in the carbon cycle, with less variability among models. We also found that interannual variations in the carbon cycle are mostly consistent among models and observations. Spatial analysis also showed a large reduction in the variability among model outputs. This study demonstrated that careful validation and calibration of models with available eddy flux data reduced model-by-model differences. Yet, site history, analysis of model structure changes, and more objective procedure of model calibration should be included in the further analysis.

Multi-model analysis of terrestrial carbon cycles in Japan: limitations and implications of model calibration using eddy flux observations

Science.gov (United States)

Ichii, K.; Suzuki, T.; Kato, T.; Ito, A.; Hajima, T.; Ueyama, M.; Sasai, T.; Hirata, R.; Saigusa, N.; Ohtani, Y.; Takagi, K.

2010-07-01

Terrestrial biosphere models show large differences when simulating carbon and water cycles, and reducing these differences is a priority for developing more accurate estimates of the condition of terrestrial ecosystems and future climate change. To reduce uncertainties and improve the understanding of their carbon budgets, we investigated the utility of the eddy flux datasets to improve model simulations and reduce variabilities among multi-model outputs of terrestrial biosphere models in Japan. Using 9 terrestrial biosphere models (Support Vector Machine - based regressions, TOPS, CASA, VISIT, Biome-BGC, DAYCENT, SEIB, LPJ, and TRIFFID), we conducted two simulations: (1) point simulations at four eddy flux sites in Japan and (2) spatial simulations for Japan with a default model (based on original settings) and a modified model (based on model parameter tuning using eddy flux data). Generally, models using default model settings showed large deviations in model outputs from observation with large model-by-model variability. However, after we calibrated the model parameters using eddy flux data (GPP, RE and NEP), most models successfully simulated seasonal variations in the carbon cycle, with less variability among models. We also found that interannual variations in the carbon cycle are mostly consistent among models and observations. Spatial analysis also showed a large reduction in the variability among model outputs. This study demonstrated that careful validation and calibration of models with available eddy flux data reduced model-by-model differences. Yet, site history, analysis of model structure changes, and more objective procedure of model calibration should be included in the further analysis.

A sensitivity analysis of a radiological assessment model for Arctic waters

DEFF Research Database (Denmark)

Nielsen, S.P.

1998-01-01

A model based on compartment analysis has been developed to simulate the dispersion of radionuclides in Arctic waters for an assessment of doses to man. The model predicts concentrations of radionuclides in the marine environment and doses to man from a range of exposure pathways. A parameter sen...... scavenging, water-sediment interaction, biological uptake, ice transport and fish migration. Two independent evaluations of the release of radioactivity from dumped nuclear waste in the Kara Sea have been used as source terms for the dose calculations.......A model based on compartment analysis has been developed to simulate the dispersion of radionuclides in Arctic waters for an assessment of doses to man. The model predicts concentrations of radionuclides in the marine environment and doses to man from a range of exposure pathways. A parameter...... sensitivity analysis has identified components of the model that are potentially important contributors to the predictive accuracy of doses to individuals of critical groups as well as to the world population. The components investigated include features associated with water transport and mixing, particle...

A Costing Analysis for Decision Making Grid Model in Failure-Based Maintenance

Directory of Open Access Journals (Sweden)

Burhanuddin M. A.

2011-01-01

Full Text Available Background. In current economic downturn, industries have to set good control on production cost, to maintain their profit margin. Maintenance department as an imperative unit in industries should attain all maintenance data, process information instantaneously, and subsequently transform it into a useful decision. Then act on the alternative to reduce production cost. Decision Making Grid model is used to identify strategies for maintenance decision. However, the model has limitation as it consider two factors only, that is, downtime and frequency of failures. We consider third factor, cost, in this study for failure-based maintenance. The objective of this paper is to introduce the formulae to estimate maintenance cost. Methods. Fish bone analysis conducted with Ishikawa model and Decision Making Grid methods are used in this study to reveal some underlying risk factors that delay failure-based maintenance. The goal of the study is to estimate the risk factor that is, repair cost to fit in the Decision Making Grid model. Decision Making grid model consider two variables, frequency of failure and downtime in the analysis. This paper introduces third variable, repair cost for Decision Making Grid model. This approaches give better result to categorize the machines, reduce cost, and boost the earning for the manufacturing plant. Results. We collected data from one of the food processing factories in Malaysia. From our empirical result, Machine C, Machine D, Machine F, and Machine I must be in the Decision Making Grid model even though their frequency of failures and downtime are less than Machine B and Machine N, based on the costing analysis. The case study and experimental results show that the cost analysis in Decision Making Grid model gives more promising strategies in failure-based maintenance. Conclusions. The improvement of Decision Making Grid model for decision analysis with costing analysis is our contribution in this paper for

A comprehensive probabilistic analysis model of oil pipelines network based on Bayesian network

Science.gov (United States)

Zhang, C.; Qin, T. X.; Jiang, B.; Huang, C.

2018-02-01

Oil pipelines network is one of the most important facilities of energy transportation. But oil pipelines network accident may result in serious disasters. Some analysis models for these accidents have been established mainly based on three methods, including event-tree, accident simulation and Bayesian network. Among these methods, Bayesian network is suitable for probabilistic analysis. But not all the important influencing factors are considered and the deployment rule of the factors has not been established. This paper proposed a probabilistic analysis model of oil pipelines network based on Bayesian network. Most of the important influencing factors, including the key environment condition and emergency response are considered in this model. Moreover, the paper also introduces a deployment rule for these factors. The model can be used in probabilistic analysis and sensitive analysis of oil pipelines network accident.

Capital Cost Optimization for Prefabrication: A Factor Analysis Evaluation Model

Directory of Open Access Journals (Sweden)

Hong Xue

2018-01-01

Full Text Available High capital cost is a significant hindrance to the promotion of prefabrication. In order to optimize cost management and reduce capital cost, this study aims to explore the latent factors and factor analysis evaluation model. Semi-structured interviews were conducted to explore potential variables and then questionnaire survey was employed to collect professionals’ views on their effects. After data collection, exploratory factor analysis was adopted to explore the latent factors. Seven latent factors were identified, including “Management Index”, “Construction Dissipation Index”, “Productivity Index”, “Design Efficiency Index”, “Transport Dissipation Index”, “Material increment Index” and “Depreciation amortization Index”. With these latent factors, a factor analysis evaluation model (FAEM, divided into factor analysis model (FAM and comprehensive evaluation model (CEM, was established. The FAM was used to explore the effect of observed variables on the high capital cost of prefabrication, while the CEM was used to evaluate comprehensive cost management level on prefabrication projects. Case studies were conducted to verify the models. The results revealed that collaborative management had a positive effect on capital cost of prefabrication. Material increment costs and labor costs had significant impacts on production cost. This study demonstrated the potential of on-site management and standardization design to reduce capital cost. Hence, collaborative management is necessary for cost management of prefabrication. Innovation and detailed design were needed to improve cost performance. The new form of precast component factories can be explored to reduce transportation cost. Meanwhile, targeted strategies can be adopted for different prefabrication projects. The findings optimized the capital cost and improved the cost performance through providing an evaluation and optimization model, which helps managers to

Bifurcation analysis of parametrically excited bipolar disorder model

Science.gov (United States)

Nana, Laurent

2009-02-01

Bipolar II disorder is characterized by alternating hypomanic and major depressive episode. We model the periodic mood variations of a bipolar II patient with a negatively damped harmonic oscillator. The medications administrated to the patient are modeled via a forcing function that is capable of stabilizing the mood variations and of varying their amplitude. We analyze analytically, using perturbation method, the amplitude and stability of limit cycles and check this analysis with numerical simulations.

Model-based schedulability analysis of safety critical hard real-time Java programs

DEFF Research Database (Denmark)

Bøgholm, Thomas; Kragh-Hansen, Henrik; Olsen, Petur

2008-01-01

verifiable by the Uppaal model checker [23]. Schedulability analysis is reduced to a simple reachability question, checking for deadlock freedom. Model-based schedulability analysis has been developed by Amnell et al. [2], but has so far only been applied to high level specifications, not actual...

EXPOSURE ANALYSIS MODELING SYSTEM (EXAMS): USER MANUAL AND SYSTEM DOCUMENTATION

Science.gov (United States)

The Exposure Analysis Modeling System, first published in 1982 (EPA-600/3-82-023), provides interactive computer software for formulating aquatic ecosystem models and rapidly evaluating the fate, transport, and exposure concentrations of synthetic organic chemicals - pesticides, ...

Earth System Model Development and Analysis using FRE-Curator and Live Access Servers: On-demand analysis of climate model output with data provenance.

Science.gov (United States)

Radhakrishnan, A.; Balaji, V.; Schweitzer, R.; Nikonov, S.; O'Brien, K.; Vahlenkamp, H.; Burger, E. F.

2016-12-01

There are distinct phases in the development cycle of an Earth system model. During the model development phase, scientists make changes to code and parameters and require rapid access to results for evaluation. During the production phase, scientists may make an ensemble of runs with different settings, and produce large quantities of output, that must be further analyzed and quality controlled for scientific papers and submission to international projects such as the Climate Model Intercomparison Project (CMIP). During this phase, provenance is a key concern:being able to track back from outputs to inputs. We will discuss one of the paths taken at GFDL in delivering tools across this lifecycle, offering on-demand analysis of data by integrating the use of GFDL's in-house FRE-Curator, Unidata's THREDDS and NOAA PMEL's Live Access Servers (LAS).Experience over this lifecycle suggests that a major difficulty in developing analysis capabilities is only partially the scientific content, but often devoted to answering the questions "where is the data?" and "how do I get to it?". "FRE-Curator" is the name of a database-centric paradigm used at NOAA GFDL to ingest information about the model runs into an RDBMS (Curator database). The components of FRE-Curator are integrated into Flexible Runtime Environment workflow and can be invoked during climate model simulation. The front end to FRE-Curator, known as the Model Development Database Interface (MDBI) provides an in-house web-based access to GFDL experiments: metadata, analysis output and more. In order to provide on-demand visualization, MDBI uses Live Access Servers which is a highly configurable web server designed to provide flexible access to geo-referenced scientific data, that makes use of OPeNDAP. Model output saved in GFDL's tape archive, the size of the database and experiments, continuous model development initiatives with more dynamic configurations add complexity and challenges in providing an on

Comparison of transient PCRV model test results with analysis

International Nuclear Information System (INIS)

Marchertas, A.H.; Belytschko, T.B.

1979-01-01

Comparisons are made of transient data derived from simple models of a reactor containment vessel with analytical solutions. This effort is a part of the ongoing process of development and testing of the DYNAPCON computer code. The test results used in these comparisons were obtained from scaled models of the British sodium cooled fast breeder program. The test structure is a scaled model of a cylindrically shaped reactor containment vessel made of concrete. This concrete vessel is prestressed axially by holddown bolts spanning the top and bottom slabs along the cylindrical walls, and is also prestressed circumferentially by a number of cables wrapped around the vessel. For test purposes this containment vessel is partially filled with water, which comes in direct contact with the vessel walls. The explosive charge is immersed in the pool of water and is centrally suspended from the top of the vessel. The load history was obtained from an ICECO analysis, using the equations of state for the source and the water. A detailed check of this solution was made to assure that the derived loading did provide the correct input. The DYNAPCON code was then used for the analysis of the prestressed concrete containment model. This analysis required the simulation of prestressing and the response of the model to the applied transient load. The calculations correctly predict the magnitudes of displacements of the PCRV model. In addition, the displacement time histories obtained from the calculations reproduce the general features of the experimental records: the period elongation and amplitude increase as compared to an elastic solution, and also the absence of permanent displacement. However, the period still underestimates the experiment, while the amplitude is generally somewhat large

Multivariate Analysis and Modeling of Sediment Pollution Using Neural Network Models and Geostatistics

Science.gov (United States)

Golay, Jean; Kanevski, Mikhaïl

2013-04-01

The present research deals with the exploration and modeling of a complex dataset of 200 measurement points of sediment pollution by heavy metals in Lake Geneva. The fundamental idea was to use multivariate Artificial Neural Networks (ANN) along with geostatistical models and tools in order to improve the accuracy and the interpretability of data modeling. The results obtained with ANN were compared to those of traditional geostatistical algorithms like ordinary (co)kriging and (co)kriging with an external drift. Exploratory data analysis highlighted a great variety of relationships (i.e. linear, non-linear, independence) between the 11 variables of the dataset (i.e. Cadmium, Mercury, Zinc, Copper, Titanium, Chromium, Vanadium and Nickel as well as the spatial coordinates of the measurement points and their depth). Then, exploratory spatial data analysis (i.e. anisotropic variography, local spatial correlations and moving window statistics) was carried out. It was shown that the different phenomena to be modeled were characterized by high spatial anisotropies, complex spatial correlation structures and heteroscedasticity. A feature selection procedure based on General Regression Neural Networks (GRNN) was also applied to create subsets of variables enabling to improve the predictions during the modeling phase. The basic modeling was conducted using a Multilayer Perceptron (MLP) which is a workhorse of ANN. MLP models are robust and highly flexible tools which can incorporate in a nonlinear manner different kind of high-dimensional information. In the present research, the input layer was made of either two (spatial coordinates) or three neurons (when depth as auxiliary information could possibly capture an underlying trend) and the output layer was composed of one (univariate MLP) to eight neurons corresponding to the heavy metals of the dataset (multivariate MLP). MLP models with three input neurons can be referred to as Artificial Neural Networks with EXternal

Hydrochemical analysis of groundwater using a tree-based model

Science.gov (United States)

Litaor, M. Iggy; Brielmann, H.; Reichmann, O.; Shenker, M.

2010-06-01

SummaryHydrochemical indices are commonly used to ascertain aquifer characteristics, salinity problems, anthropogenic inputs and resource management, among others. This study was conducted to test the applicability of a binary decision tree model to aquifer evaluation using hydrochemical indices as input. The main advantage of the tree-based model compared to other commonly used statistical procedures such as cluster and factor analyses is the ability to classify groundwater samples with assigned probability and the reduction of a large data set into a few significant variables without creating new factors. We tested the model using data sets collected from headwater springs of the Jordan River, Israel. The model evaluation consisted of several levels of complexity, from simple separation between the calcium-magnesium-bicarbonate water type of karstic aquifers to the more challenging separation of calcium-sodium-bicarbonate water type flowing through perched and regional basaltic aquifers. In all cases, the model assigned measures for goodness of fit in the form of misclassification errors and singled out the most significant variable in the analysis. The model proceeded through a sequence of partitions providing insight into different possible pathways and changing lithology. The model results were extremely useful in constraining the interpretation of geological heterogeneity and constructing a conceptual flow model for a given aquifer. The tree model clearly identified the hydrochemical indices that were excluded from the analysis, thus providing information that can lead to a decrease in the number of routinely analyzed variables and a significant reduction in laboratory cost.

Uncertainty modeling in vibration, control and fuzzy analysis of structural systems

CERN Document Server

Halder, Achintya; Ayyub, Bilal M

1997-01-01

This book gives an overview of the current state of uncertainty modeling in vibration, control, and fuzzy analysis of structural and mechanical systems. It is a coherent compendium written by leading experts and offers the reader a sampling of exciting research areas in several fast-growing branches in this field. Uncertainty modeling and analysis are becoming an integral part of system definition and modeling in many fields. The book consists of ten chapters that report the work of researchers, scientists and engineers on theoretical developments and diversified applications in engineering sy

Modeling and analysis of doubly fed induction generator wind energy systems

CERN Document Server

Fan, Lingling

2015-01-01

Wind Energy Systems: Modeling, Analysis and Control with DFIG provides key information on machine/converter modelling strategies based on space vectors, complex vector, and further frequency-domain variables. It includes applications that focus on wind energy grid integration, with analysis and control explanations with examples. For those working in the field of wind energy integration examining the potential risk of stability is key, this edition looks at how wind energy is modelled, what kind of control systems are adopted, how it interacts with the grid, as well as suitable study

A New Dynamic Model for Nuclear Fuel Cycle System Analysis

International Nuclear Information System (INIS)

Choi, Sungyeol; Ko, Won Il

2014-01-01

The evaluation of mass flow is a complex process where numerous parameters and their complex interaction are involved. Given that many nuclear power countries have light and heavy water reactors and associated fuel cycle technologies, the mass flow analysis has to consider a dynamic transition from the open fuel cycle to other cycles over decades or a century. Although an equilibrium analysis provides insight concerning the end-states of fuel cycle transitions, it cannot answer when we need specific management options, whether the current plan can deliver these options when needed, and how fast the equilibrium can be achieved. As a pilot application, the government brought several experts together to conduct preliminary evaluations for nuclear fuel cycle options in 2010. According to Table 1, they concluded that the closed nuclear fuel cycle has long-term advantages over the open fuel cycle. However, it is still necessary to assess these options in depth and to optimize transition paths of these long-term options with advanced dynamic fuel cycle models. A dynamic simulation model for nuclear fuel cycle systems was developed and its dynamic mass flow analysis capability was validated against the results of existing models. This model can reflects a complex combination of various fuel cycle processes and reactor types, from once-through to multiple recycling, within a single nuclear fuel cycle system. For the open fuel cycle, the results of the developed model are well matched with the results of other models

Gentrification and models for real estate analysis

Directory of Open Access Journals (Sweden)

Gianfranco Brusa

2013-08-01

Full Text Available This research propose a deep analysis of Milanese real estate market, based on data supplied by three real estate organizations; gentrification appears in some neighborhoods, such as Tortona, Porta Genova, Bovisa, Isola Garibaldi: the latest is the subject of the final analysis, by surveying of physical and social state of the area. The survey takes place in two periods (2003 and 2009 to compare the evolution of gentrification. The results of surveys has been employed in a simulation by multi-agent system model, to foresee long term evolution of the phenomenon. These neighborhood micro-indicators allow to put in evidence actual trends, conditioning a local real estate market, which can translate themselves in phenomena such as gentrification. In present analysis, the employ of cellular automata models applied to a neighborhood in Milan (Isola Garibaldi produced the dynamic simulation of gentrification trend during a very long time: the cyclical phenomenon (one loop holds a period of twenty – thirty years appears sometimes during a theoretical time of 100 – 120 – 150 years. Simulation of long period scenarios by multi-agent systems and cellular automata provides estimator with powerful tool, without limits in implementing it, able to support him in appraisal judge. It stands also to reason that such a tool can sustain urban planning and related evaluation processes.

Exploratory Modelling of Financial Reporting and Analysis Practices in Small Growth Enterprises

OpenAIRE

Richard G. P. McMahon; Leslie G. Davies; Nicholas M. Bluhm

1994-01-01

This paper reports an exploratory study of statistical modelling of historical financial reporting and analysis in a sample of small growth enterprises. The study sought to identify those factors that determine whether particular financial reporting and analysis practices are undertaken, and to represent these explanatory factors in expressions that reflect their relative and combined influence. Dichotomous logistic regression is employed to model financial analysis and polytomous logistic re...

Floquet stability analysis of the longitudinal dynamics of two hovering model insects

Science.gov (United States)

Wu, Jiang Hao; Sun, Mao

2012-01-01

Because of the periodically varying aerodynamic and inertial forces of the flapping wings, a hovering or constant-speed flying insect is a cyclically forcing system, and, generally, the flight is not in a fixed-point equilibrium, but in a cyclic-motion equilibrium. Current stability theory of insect flight is based on the averaged model and treats the flight as a fixed-point equilibrium. In the present study, we treated the flight as a cyclic-motion equilibrium and used the Floquet theory to analyse the longitudinal stability of insect flight. Two hovering model insects were considered—a dronefly and a hawkmoth. The former had relatively high wingbeat frequency and small wing-mass to body-mass ratio, and hence very small amplitude of body oscillation; while the latter had relatively low wingbeat frequency and large wing-mass to body-mass ratio, and hence relatively large amplitude of body oscillation. For comparison, analysis using the averaged-model theory (fixed-point stability analysis) was also made. Results of both the cyclic-motion stability analysis and the fixed-point stability analysis were tested by numerical simulation using complete equations of motion coupled with the Navier–Stokes equations. The Floquet theory (cyclic-motion stability analysis) agreed well with the simulation for both the model dronefly and the model hawkmoth; but the averaged-model theory gave good results only for the dronefly. Thus, for an insect with relatively large body oscillation at wingbeat frequency, cyclic-motion stability analysis is required, and for their control analysis, the existing well-developed control theories for systems of fixed-point equilibrium are no longer applicable and new methods that take the cyclic variation of the flight dynamics into account are needed. PMID:22491980

Modeling Analysis For Grout Hopper Waste Tank

International Nuclear Information System (INIS)

Lee, S.

2012-01-01

The Saltstone facility at Savannah River Site (SRS) has a grout hopper tank to provide agitator stirring of the Saltstone feed materials. The tank has about 300 gallon capacity to provide a larger working volume for the grout nuclear waste slurry to be held in case of a process upset, and it is equipped with a mechanical agitator, which is intended to keep the grout in motion and agitated so that it won't start to set up. The primary objective of the work was to evaluate the flow performance for mechanical agitators to prevent vortex pull-through for an adequate stirring of the feed materials and to estimate an agitator speed which provides acceptable flow performance with a 45 o pitched four-blade agitator. In addition, the power consumption required for the agitator operation was estimated. The modeling calculations were performed by taking two steps of the Computational Fluid Dynamics (CFD) modeling approach. As a first step, a simple single-stage agitator model with 45 o pitched propeller blades was developed for the initial scoping analysis of the flow pattern behaviors for a range of different operating conditions. Based on the initial phase-1 results, the phase-2 model with a two-stage agitator was developed for the final performance evaluations. A series of sensitivity calculations for different designs of agitators and operating conditions have been performed to investigate the impact of key parameters on the grout hydraulic performance in a 300-gallon hopper tank. For the analysis, viscous shear was modeled by using the Bingham plastic approximation. Steady state analyses with a two-equation turbulence model were performed. All analyses were based on three-dimensional results. Recommended operational guidance was developed by using the basic concept that local shear rate profiles and flow patterns can be used as a measure of hydraulic performance and spatial stirring. Flow patterns were estimated by a Lagrangian integration technique along the flow paths