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Sample records for dynamic reliability models

  1. Creation and Reliability Analysis of Vehicle Dynamic Weighing Model

    Directory of Open Access Journals (Sweden)

    Zhi-Ling XU

    2014-08-01

    Full Text Available In this paper, it is modeled by using ADAMS to portable axle load meter of dynamic weighing system, controlling a single variable simulation weighing process, getting the simulation weighing data under the different speed and weight; simultaneously using portable weighing system with the same parameters to achieve the actual measurement, comparative analysis the simulation results under the same conditions, at 30 km/h or less, the simulation value and the measured value do not differ by more than 5 %, it is not only to verify the reliability of dynamic weighing model, but also to create possible for improving algorithm study efficiency by using dynamic weighing model simulation.

  2. An integrated approach to human reliability analysis -- decision analytic dynamic reliability model

    International Nuclear Information System (INIS)

    Holmberg, J.; Hukki, K.; Norros, L.; Pulkkinen, U.; Pyy, P.

    1999-01-01

    The reliability of human operators in process control is sensitive to the context. In many contemporary human reliability analysis (HRA) methods, this is not sufficiently taken into account. The aim of this article is that integration between probabilistic and psychological approaches in human reliability should be attempted. This is achieved first, by adopting such methods that adequately reflect the essential features of the process control activity, and secondly, by carrying out an interactive HRA process. Description of the activity context, probabilistic modeling, and psychological analysis form an iterative interdisciplinary sequence of analysis in which the results of one sub-task maybe input to another. The analysis of the context is carried out first with the help of a common set of conceptual tools. The resulting descriptions of the context promote the probabilistic modeling, through which new results regarding the probabilistic dynamics can be achieved. These can be incorporated in the context descriptions used as reference in the psychological analysis of actual performance. The results also provide new knowledge of the constraints of activity, by providing information of the premises of the operator's actions. Finally, the stochastic marked point process model gives a tool, by which psychological methodology may be interpreted and utilized for reliability analysis

  3. Modeling cognition dynamics and its application to human reliability analysis

    International Nuclear Information System (INIS)

    Mosleh, A.; Smidts, C.; Shen, S.H.

    1996-01-01

    For the past two decades, a number of approaches have been proposed for the identification and estimation of the likelihood of human errors, particularly for use in the risk and reliability studies of nuclear power plants. Despite the wide-spread use of the most popular among these methods, their fundamental weaknesses are widely recognized, and the treatment of human reliability has been considered as one of the soft spots of risk studies of large technological systems. To alleviate the situation, new efforts have focused on the development of human reliability models based on a more fundamental understanding of operator response and its cognitive aspects

  4. Modeling of seismic hazards for dynamic reliability analysis

    International Nuclear Information System (INIS)

    Mizutani, M.; Fukushima, S.; Akao, Y.; Katukura, H.

    1993-01-01

    This paper investigates the appropriate indices of seismic hazard curves (SHCs) for seismic reliability analysis. In the most seismic reliability analyses of structures, the seismic hazards are defined in the form of the SHCs of peak ground accelerations (PGAs). Usually PGAs play a significant role in characterizing ground motions. However, PGA is not always a suitable index of seismic motions. When random vibration theory developed in the frequency domain is employed to obtain statistics of responses, it is more convenient for the implementation of dynamic reliability analysis (DRA) to utilize an index which can be determined in the frequency domain. In this paper, we summarize relationships among the indices which characterize ground motions. The relationships between the indices and the magnitude M are arranged as well. In this consideration, duration time plays an important role in relating two distinct class, i.e. energy class and power class. Fourier and energy spectra are involved in the energy class, and power and response spectra and PGAs are involved in the power class. These relationships are also investigated by using ground motion records. Through these investigations, we have shown the efficiency of employing the total energy as an index of SHCs, which can be determined in the time and frequency domains and has less variance than the other indices. In addition, we have proposed the procedure of DRA based on total energy. (author)

  5. Human Performance Modeling for Dynamic Human Reliability Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Boring, Ronald Laurids [Idaho National Laboratory; Joe, Jeffrey Clark [Idaho National Laboratory; Mandelli, Diego [Idaho National Laboratory

    2015-08-01

    Part of the U.S. Department of Energy’s (DOE’s) Light Water Reac- tor Sustainability (LWRS) Program, the Risk-Informed Safety Margin Charac- terization (RISMC) Pathway develops approaches to estimating and managing safety margins. RISMC simulations pair deterministic plant physics models with probabilistic risk models. As human interactions are an essential element of plant risk, it is necessary to integrate human actions into the RISMC risk framework. In this paper, we review simulation based and non simulation based human reliability analysis (HRA) methods. This paper summarizes the founda- tional information needed to develop a feasible approach to modeling human in- teractions in RISMC simulations.

  6. Dynamic reliability modeling of three-state networks

    OpenAIRE

    Ashrafi, S.; Asadi, M.

    2014-01-01

    This paper is an investigation into the reliability and stochastic properties of three-state networks. We consider a single-step network consisting of n links and we assume that the links are subject to failure. We assume that the network can be in three states, up (K = 2), partial performance (K = 1), and down (K = 0). Using the concept of the two-dimensional signature, we study the residual lifetimes of the networks under different scenarios on the states and the number of...

  7. Adjoint sensitivity analysis of dynamic reliability models based on Markov chains - II: Application to IFMIF reliability assessment

    Energy Technology Data Exchange (ETDEWEB)

    Cacuci, D. G. [Commiss Energy Atom, Direct Energy Nucl, Saclay, (France); Cacuci, D. G.; Balan, I. [Univ Karlsruhe, Inst Nucl Technol and Reactor Safetly, Karlsruhe, (Germany); Ionescu-Bujor, M. [Forschungszentrum Karlsruhe, Fus Program, D-76021 Karlsruhe, (Germany)

    2008-07-01

    In Part II of this work, the adjoint sensitivity analysis procedure developed in Part I is applied to perform sensitivity analysis of several dynamic reliability models of systems of increasing complexity, culminating with the consideration of the International Fusion Materials Irradiation Facility (IFMIF) accelerator system. Section II presents the main steps of a procedure for the automated generation of Markov chains for reliability analysis, including the abstraction of the physical system, construction of the Markov chain, and the generation and solution of the ensuing set of differential equations; all of these steps have been implemented in a stand-alone computer code system called QUEFT/MARKOMAG-S/MCADJSEN. This code system has been applied to sensitivity analysis of dynamic reliability measures for a paradigm '2-out-of-3' system comprising five components and also to a comprehensive dynamic reliability analysis of the IFMIF accelerator system facilities for the average availability and, respectively, the system's availability at the final mission time. The QUEFT/MARKOMAG-S/MCADJSEN has been used to efficiently compute sensitivities to 186 failure and repair rates characterizing components and subsystems of the first-level fault tree of the IFMIF accelerator system. (authors)

  8. Adjoint sensitivity analysis of dynamic reliability models based on Markov chains - II: Application to IFMIF reliability assessment

    International Nuclear Information System (INIS)

    Cacuci, D. G.; Cacuci, D. G.; Balan, I.; Ionescu-Bujor, M.

    2008-01-01

    In Part II of this work, the adjoint sensitivity analysis procedure developed in Part I is applied to perform sensitivity analysis of several dynamic reliability models of systems of increasing complexity, culminating with the consideration of the International Fusion Materials Irradiation Facility (IFMIF) accelerator system. Section II presents the main steps of a procedure for the automated generation of Markov chains for reliability analysis, including the abstraction of the physical system, construction of the Markov chain, and the generation and solution of the ensuing set of differential equations; all of these steps have been implemented in a stand-alone computer code system called QUEFT/MARKOMAG-S/MCADJSEN. This code system has been applied to sensitivity analysis of dynamic reliability measures for a paradigm '2-out-of-3' system comprising five components and also to a comprehensive dynamic reliability analysis of the IFMIF accelerator system facilities for the average availability and, respectively, the system's availability at the final mission time. The QUEFT/MARKOMAG-S/MCADJSEN has been used to efficiently compute sensitivities to 186 failure and repair rates characterizing components and subsystems of the first-level fault tree of the IFMIF accelerator system. (authors)

  9. A Structural Reliability Business Process Modelling with System Dynamics Simulation

    OpenAIRE

    Lam, C. Y.; Chan, S. L.; Ip, W. H.

    2010-01-01

    Business activity flow analysis enables organizations to manage structured business processes, and can thus help them to improve performance. The six types of business activities identified here (i.e., SOA, SEA, MEA, SPA, MSA and FIA) are correlated and interact with one another, and the decisions from any business activity form feedback loops with previous and succeeding activities, thus allowing the business process to be modelled and simulated. For instance, for any company that is eager t...

  10. Adjoint sensitivity analysis of dynamic reliability models based on Markov chains - I: Theory

    International Nuclear Information System (INIS)

    Cacuci, D. G.; Cacuci, D. G.; Ionescu-Bujor, M.

    2008-01-01

    The development of the adjoint sensitivity analysis procedure (ASAP) for generic dynamic reliability models based on Markov chains is presented, together with applications of this procedure to the analysis of several systems of increasing complexity. The general theory is presented in Part I of this work and is accompanied by a paradigm application to the dynamic reliability analysis of a simple binary component, namely a pump functioning on an 'up/down' cycle until it fails irreparably. This paradigm example admits a closed form analytical solution, which permits a clear illustration of the main characteristics of the ASAP for Markov chains. In particular, it is shown that the ASAP for Markov chains presents outstanding computational advantages over other procedures currently in use for sensitivity and uncertainty analysis of the dynamic reliability of large-scale systems. This conclusion is further underscored by the large-scale applications presented in Part II. (authors)

  11. Adjoint sensitivity analysis of dynamic reliability models based on Markov chains - I: Theory

    Energy Technology Data Exchange (ETDEWEB)

    Cacuci, D. G. [Commiss Energy Atom, Direct Energy Nucl, Saclay, (France); Cacuci, D. G. [Univ Karlsruhe, Inst Nucl Technol and Reactor Safety, D-76021 Karlsruhe, (Germany); Ionescu-Bujor, M. [Forschungszentrum Karlsruhe, Fus Program, D-76021 Karlsruhe, (Germany)

    2008-07-01

    The development of the adjoint sensitivity analysis procedure (ASAP) for generic dynamic reliability models based on Markov chains is presented, together with applications of this procedure to the analysis of several systems of increasing complexity. The general theory is presented in Part I of this work and is accompanied by a paradigm application to the dynamic reliability analysis of a simple binary component, namely a pump functioning on an 'up/down' cycle until it fails irreparably. This paradigm example admits a closed form analytical solution, which permits a clear illustration of the main characteristics of the ASAP for Markov chains. In particular, it is shown that the ASAP for Markov chains presents outstanding computational advantages over other procedures currently in use for sensitivity and uncertainty analysis of the dynamic reliability of large-scale systems. This conclusion is further underscored by the large-scale applications presented in Part II. (authors)

  12. Development of Markov model of emergency diesel generator for dynamic reliability analysis

    Energy Technology Data Exchange (ETDEWEB)

    Jin, Young Ho; Choi, Sun Yeong; Yang, Joon Eon [Korea Atomic Energy Research Institute, Taejon (Korea)

    1999-02-01

    The EDG (Emergency Diesal Generator) of nuclear power plant is one of the most important equipments in mitigating accidents. The FT (Fault Tree) method is widely used to assess the reliability of safety systems like an EDG in nuclear power plant. This method, however, has limitations in modeling dynamic features of safety systems exactly. We, hence, have developed a Markov model to represent the stochastic process of dynamic systems whose states change as time moves on. The Markov model enables us to develop a dynamic reliability model of EDG. This model can represent all possible states of EDG comparing to the FRANTIC code developed by U.S. NRC for the reliability analysis of standby systems. to access the regulation policy for test interval, we performed two simulations based on the generic data and plant specific data of YGN 3, respectively by using the developed model. We also estimate the effects of various repair rates and the fractions of starting failures by demand shock to the reliability of EDG. And finally, Aging effect is analyzed. (author). 23 refs., 19 figs., 9 tabs.

  13. Reliability modelling and analysis of a multi-state element based on a dynamic Bayesian network

    Science.gov (United States)

    Li, Zhiqiang; Xu, Tingxue; Gu, Junyuan; Dong, Qi; Fu, Linyu

    2018-04-01

    This paper presents a quantitative reliability modelling and analysis method for multi-state elements based on a combination of the Markov process and a dynamic Bayesian network (DBN), taking perfect repair, imperfect repair and condition-based maintenance (CBM) into consideration. The Markov models of elements without repair and under CBM are established, and an absorbing set is introduced to determine the reliability of the repairable element. According to the state-transition relations between the states determined by the Markov process, a DBN model is built. In addition, its parameters for series and parallel systems, namely, conditional probability tables, can be calculated by referring to the conditional degradation probabilities. Finally, the power of a control unit in a failure model is used as an example. A dynamic fault tree (DFT) is translated into a Bayesian network model, and subsequently extended to a DBN. The results show the state probabilities of an element and the system without repair, with perfect and imperfect repair, and under CBM, with an absorbing set plotted by differential equations and verified. Through referring forward, the reliability value of the control unit is determined in different kinds of modes. Finally, weak nodes are noted in the control unit.

  14. Modeling and simulation of a controlled steam generator in the context of dynamic reliability using a Stochastic Hybrid Automaton

    International Nuclear Information System (INIS)

    Babykina, Génia; Brînzei, Nicolae; Aubry, Jean-François; Deleuze, Gilles

    2016-01-01

    The paper proposes a modeling framework to support Monte Carlo simulations of the behavior of a complex industrial system. The aim is to analyze the system dependability in the presence of random events, described by any type of probability distributions. Continuous dynamic evolutions of physical parameters are taken into account by a system of differential equations. Dynamic reliability is chosen as theoretical framework. Based on finite state automata theory, the formal model is built by parallel composition of elementary sub-models using a bottom-up approach. Considerations of a stochastic nature lead to a model called the Stochastic Hybrid Automaton. The Scilab/Scicos open source environment is used for implementation. The case study is carried out on an example of a steam generator of a nuclear power plant. The behavior of the system is studied by exploring its trajectories. Possible system trajectories are analyzed both empirically, using the results of Monte Carlo simulations, and analytically, using the formal system model. The obtained results are show to be relevant. The Stochastic Hybrid Automaton appears to be a suitable tool to address the dynamic reliability problem and to model real systems of high complexity; the bottom-up design provides precision and coherency of the system model. - Highlights: • A part of a nuclear power plant is modeled in the context of dynamic reliability. • Stochastic Hybrid Automaton is used as an input model for Monte Carlo simulations. • The model is formally built using a bottom-up approach. • The behavior of the system is analyzed empirically and analytically. • A formally built SHA shows to be a suitable tool to approach dynamic reliability.

  15. Linear and evolutionary polynomial regression models to forecast coastal dynamics: Comparison and reliability assessment

    Science.gov (United States)

    Bruno, Delia Evelina; Barca, Emanuele; Goncalves, Rodrigo Mikosz; de Araujo Queiroz, Heithor Alexandre; Berardi, Luigi; Passarella, Giuseppe

    2018-01-01

    In this paper, the Evolutionary Polynomial Regression data modelling strategy has been applied to study small scale, short-term coastal morphodynamics, given its capability for treating a wide database of known information, non-linearly. Simple linear and multilinear regression models were also applied to achieve a balance between the computational load and reliability of estimations of the three models. In fact, even though it is easy to imagine that the more complex the model, the more the prediction improves, sometimes a "slight" worsening of estimations can be accepted in exchange for the time saved in data organization and computational load. The models' outcomes were validated through a detailed statistical, error analysis, which revealed a slightly better estimation of the polynomial model with respect to the multilinear model, as expected. On the other hand, even though the data organization was identical for the two models, the multilinear one required a simpler simulation setting and a faster run time. Finally, the most reliable evolutionary polynomial regression model was used in order to make some conjecture about the uncertainty increase with the extension of extrapolation time of the estimation. The overlapping rate between the confidence band of the mean of the known coast position and the prediction band of the estimated position can be a good index of the weakness in producing reliable estimations when the extrapolation time increases too much. The proposed models and tests have been applied to a coastal sector located nearby Torre Colimena in the Apulia region, south Italy.

  16. Improvement of level-1 PSA computer code package - Modeling and analysis for dynamic reliability of nuclear power plants

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Chang Hoon; Baek, Sang Yeup; Shin, In Sup; Moon, Shin Myung; Moon, Jae Phil; Koo, Hoon Young; Kim, Ju Shin [Seoul National University, Seoul (Korea, Republic of); Hong, Jung Sik [Seoul National Polytechnology University, Seoul (Korea, Republic of); Lim, Tae Jin [Soongsil University, Seoul (Korea, Republic of)

    1996-08-01

    The objective of this project is to develop a methodology of the dynamic reliability analysis for NPP. The first year`s research was focused on developing a procedure for analyzing failure data of running components and a simulator for estimating the reliability of series-parallel structures. The second year`s research was concentrated on estimating the lifetime distribution and PM effect of a component from its failure data in various cases, and the lifetime distribution of a system with a particular structure. Computer codes for performing these jobs were also developed. The objectives of the third year`s research is to develop models for analyzing special failure types (CCFs, Standby redundant structure) that were nor considered in the first two years, and to complete a methodology of the dynamic reliability analysis for nuclear power plants. The analysis of failure data of components and related researches for supporting the simulator must be preceded for providing proper input to the simulator. Thus this research is divided into three major parts. 1. Analysis of the time dependent life distribution and the PM effect. 2. Development of a simulator for system reliability analysis. 3. Related researches for supporting the simulator : accelerated simulation analytic approach using PH-type distribution, analysis for dynamic repair effects. 154 refs., 5 tabs., 87 figs. (author)

  17. Dynamic reliability of digital-based transmitters

    Energy Technology Data Exchange (ETDEWEB)

    Brissaud, Florent, E-mail: florent.brissaud.2007@utt.f [Institut National de l' Environnement Industriel et des Risques (INERIS), Parc Technologique Alata, BP 2, 60550 Verneuil-en-Halatte (France) and Universite de Technologie de Troyes - UTT, Institut Charles Delaunay - ICD and UMR CNRS 6279 STMR, 12 rue Marie Curie, BP 2060, 10010 Troyes Cedex (France); Smidts, Carol [Ohio State University (OSU), Nuclear Engineering Program, Department of Mechanical Engineering, Scott Laboratory, 201 W 19th Ave, Columbus OH 43210 (United States); Barros, Anne; Berenguer, Christophe [Universite de Technologie de Troyes (UTT), Institut Charles Delaunay (ICD) and UMR CNRS 6279 STMR, 12 rue Marie Curie, BP 2060, 10010 Troyes Cedex (France)

    2011-07-15

    Dynamic reliability explicitly handles the interactions between the stochastic behaviour of system components and the deterministic behaviour of process variables. While dynamic reliability provides a more efficient and realistic way to perform probabilistic risk assessment than 'static' approaches, its industrial level applications are still limited. Factors contributing to this situation are the inherent complexity of the theory and the lack of a generic platform. More recently the increased use of digital-based systems has also introduced additional modelling challenges related to specific interactions between system components. Typical examples are the 'intelligent transmitters' which are able to exchange information, and to perform internal data processing and advanced functionalities. To make a contribution to solving these challenges, the mathematical framework of dynamic reliability is extended to handle the data and information which are processed and exchanged between systems components. Stochastic deviations that may affect system properties are also introduced to enhance the modelling of failures. A formalized Petri net approach is then presented to perform the corresponding reliability analyses using numerical methods. Following this formalism, a versatile model for the dynamic reliability modelling of digital-based transmitters is proposed. Finally the framework's flexibility and effectiveness is demonstrated on a substantial case study involving a simplified model of a nuclear fast reactor.

  18. A dynamic simulation model for assessing the overall impact of incentive policies on power system reliability, costs and environment

    International Nuclear Information System (INIS)

    Ibanez-Lopez, A.S.; Martinez-Val, J.M.; Moratilla-Soria, B.Y.

    2017-01-01

    The liberalization of power markets has entailed dramatic changes in power system planning worldwide. The inception of new alternative technologies, smart grids and distributed generation and storage is expected to make system planning even more challenging. Government policies still play a major role in the evolution of a country's power generation mix, even in those countries with liberalized markets. This paper presents a System Dynamics model aimed at assessing the overall technical, economic and environmental impact of renewable energy incentives and capacity payment policies. The model has been used to simulate Spain's power industry in order to assess the impact of electric power policies with the goal of getting insights regarding how to achieve an optimum power generation mix. The main conclusions of the present paper are (i) the necessity of specific regulatory actions in Spain in order to keep adequate reliability levels, avoid price spikes and boom and bust investment cycles as well as to deploy specific technologies, (ii) the fact that capacity payments are a better instrument for keeping adequate reserve margins and avoiding power price spikes than renewable energy incentives and (iii) the evidence that both instruments entail additional system costs over the base case scenario. - Highlights: • A System Dynamics model of Spain's power generation mix is proposed. • The overall policy impact on system costs, environment and reliability is assessed. • Current policies are not enough to keep adequate reliability levels. • Capacity payments are an adequate instrument for guaranteeing system reliability. • RES incentives do not solve reliability issues and entail greater system costs.

  19. 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

  20. Trust in the CODA model: Opinion dynamics and the reliability of other agents

    Energy Technology Data Exchange (ETDEWEB)

    Martins, André C.R., E-mail: amartins@usp.br

    2013-11-08

    A model for the joint evolution of opinions and how much the agents trust each other is presented, using the framework of the Continuous Opinions and Discrete Actions (CODA) model. Instead of a fixed probability that the other agents will decide in the favor of the best choice, each agent considers that other agents might be one of two types: trustworthy or untrustworthy. Each agent its opinion and also the probability for each one of the other agents it interacts with being trustworthy. The dynamics of opinions and the evolution of the trust between the agents are studied. Clear evidences of the existence of two phases, one with strong polarization and the other tending to agreement, are observed. The transition shows signs of being a first-order transition. This happens despite the fact that the trust network evolves much slower than the opinion on the central issue.

  1. Trust in the CODA model: Opinion dynamics and the reliability of other agents

    International Nuclear Information System (INIS)

    Martins, André C.R.

    2013-01-01

    A model for the joint evolution of opinions and how much the agents trust each other is presented, using the framework of the Continuous Opinions and Discrete Actions (CODA) model. Instead of a fixed probability that the other agents will decide in the favor of the best choice, each agent considers that other agents might be one of two types: trustworthy or untrustworthy. Each agent its opinion and also the probability for each one of the other agents it interacts with being trustworthy. The dynamics of opinions and the evolution of the trust between the agents are studied. Clear evidences of the existence of two phases, one with strong polarization and the other tending to agreement, are observed. The transition shows signs of being a first-order transition. This happens despite the fact that the trust network evolves much slower than the opinion on the central issue.

  2. Prime implicants in dynamic reliability analysis

    International Nuclear Information System (INIS)

    Tyrväinen, Tero

    2016-01-01

    This paper develops an improved definition of a prime implicant for the needs of dynamic reliability analysis. Reliability analyses often aim to identify minimal cut sets or prime implicants, which are minimal conditions that cause an undesired top event, such as a system's failure. Dynamic reliability analysis methods take the time-dependent behaviour of a system into account. This means that the state of a component can change in the analysed time frame and prime implicants can include the failure of a component at different time points. There can also be dynamic constraints on a component's behaviour. For example, a component can be non-repairable in the given time frame. If a non-repairable component needs to be failed at a certain time point to cause the top event, we consider that the condition that it is failed at the latest possible time point is minimal, and the condition in which it fails earlier non-minimal. The traditional definition of a prime implicant does not account for this type of time-related minimality. In this paper, a new definition is introduced and illustrated using a dynamic flowgraph methodology model. - Highlights: • A new definition of a prime implicant is developed for dynamic reliability analysis. • The new definition takes time-related minimality into account. • The new definition is needed in dynamic flowgraph methodology. • Results can be represented by a smaller number of prime implicants.

  3. Proposed reliability cost model

    Science.gov (United States)

    Delionback, L. M.

    1973-01-01

    The research investigations which were involved in the study include: cost analysis/allocation, reliability and product assurance, forecasting methodology, systems analysis, and model-building. This is a classic example of an interdisciplinary problem, since the model-building requirements include the need for understanding and communication between technical disciplines on one hand, and the financial/accounting skill categories on the other. The systems approach is utilized within this context to establish a clearer and more objective relationship between reliability assurance and the subcategories (or subelements) that provide, or reenforce, the reliability assurance for a system. Subcategories are further subdivided as illustrated by a tree diagram. The reliability assurance elements can be seen to be potential alternative strategies, or approaches, depending on the specific goals/objectives of the trade studies. The scope was limited to the establishment of a proposed reliability cost-model format. The model format/approach is dependent upon the use of a series of subsystem-oriented CER's and sometimes possible CTR's, in devising a suitable cost-effective policy.

  4. Reliable dynamics in Boolean and continuous networks

    International Nuclear Information System (INIS)

    Ackermann, Eva; Drossel, Barbara; Peixoto, Tiago P

    2012-01-01

    We investigate the dynamical behavior of a model of robust gene regulatory networks which possess ‘entirely reliable’ trajectories. In a Boolean representation, these trajectories are characterized by being insensitive to the order in which the nodes are updated, i.e. they always go through the same sequence of states. The Boolean model for gene activity is compared with a continuous description in terms of differential equations for the concentrations of mRNA and proteins. We found that entirely reliable Boolean trajectories can be reproduced perfectly in the continuous model when realistic Hill coefficients are used. We investigate to what extent this high correspondence between Boolean and continuous trajectories depends on the extent of reliability of the Boolean trajectories, and we identify simple criteria that enable the faithful reproduction of the Boolean dynamics in the continuous description. (paper)

  5. Travel time reliability modeling.

    Science.gov (United States)

    2011-07-01

    This report includes three papers as follows: : 1. Guo F., Rakha H., and Park S. (2010), "A Multi-state Travel Time Reliability Model," : Transportation Research Record: Journal of the Transportation Research Board, n 2188, : pp. 46-54. : 2. Park S.,...

  6. Reliability and Model Fit

    Science.gov (United States)

    Stanley, Leanne M.; Edwards, Michael C.

    2016-01-01

    The purpose of this article is to highlight the distinction between the reliability of test scores and the fit of psychometric measurement models, reminding readers why it is important to consider both when evaluating whether test scores are valid for a proposed interpretation and/or use. It is often the case that an investigator judges both the…

  7. Reliability models for Space Station power system

    Science.gov (United States)

    Singh, C.; Patton, A. D.; Kim, Y.; Wagner, H.

    1987-01-01

    This paper presents a methodology for the reliability evaluation of Space Station power system. The two options considered are the photovoltaic system and the solar dynamic system. Reliability models for both of these options are described along with the methodology for calculating the reliability indices.

  8. Supply chain reliability modelling

    Directory of Open Access Journals (Sweden)

    Eugen Zaitsev

    2012-03-01

    Full Text Available Background: Today it is virtually impossible to operate alone on the international level in the logistics business. This promotes the establishment and development of new integrated business entities - logistic operators. However, such cooperation within a supply chain creates also many problems related to the supply chain reliability as well as the optimization of the supplies planning. The aim of this paper was to develop and formulate the mathematical model and algorithms to find the optimum plan of supplies by using economic criterion and the model for the probability evaluating of non-failure operation of supply chain. Methods: The mathematical model and algorithms to find the optimum plan of supplies were developed and formulated by using economic criterion and the model for the probability evaluating of non-failure operation of supply chain. Results and conclusions: The problem of ensuring failure-free performance of goods supply channel analyzed in the paper is characteristic of distributed network systems that make active use of business process outsourcing technologies. The complex planning problem occurring in such systems that requires taking into account the consumer's requirements for failure-free performance in terms of supply volumes and correctness can be reduced to a relatively simple linear programming problem through logical analysis of the structures. The sequence of the operations, which should be taken into account during the process of the supply planning with the supplier's functional reliability, was presented.

  9. Sensitivity case study in dynamic reliability

    International Nuclear Information System (INIS)

    Kopustinskas, V.

    2001-01-01

    Recent trends in the risk assessments of the complex industrial plants show increased interest in dynamical models arising from the coupling of the probabilistic and deterministic approaches. Conventionally used static system models, represented by the fault/event trees can not reflect dynamic behaviour of the system and complex interaction between the process variables, components and human actions. The nature of the most complex industrial systems, like nuclear power plants (NPP) suggests that Markov type stochastic differential equations (SDEs) consisting of jump and drift components can be successfully used to represent and analyze the phenomena. This paper discuss possible applications of the SDEs in reliability problems. In particular, Accident Localization System (ALS) of the Ignalina NPP was analyzed as a benchmark for further investigations in this area. (author)

  10. Hot Spot Temperature and Grey Target Theory-Based Dynamic Modelling for Reliability Assessment of Transformer Oil-Paper Insulation Systems: A Practical Case Study

    Directory of Open Access Journals (Sweden)

    Lefeng Cheng

    2018-01-01

    Full Text Available This paper develops a novel dynamic correction method for the reliability assessment of large oil-immersed power transformers. First, with the transformer oil-paper insulation system (TOPIS as the target of evaluation and the winding hot spot temperature (HST as the core point, an HST-based static ageing failure model is built according to the Weibull distribution and Arrhenius reaction law, in order to describe the transformer ageing process and calculate the winding HST for obtaining the failure rate and life expectancy of TOPIS. A grey target theory based dynamic correction model is then developed, combined with the data of Dissolved Gas Analysis (DGA in power transformer oil, in order to dynamically modify the life expectancy calculated by the built static model, such that the corresponding relationship between the state grade and life expectancy correction coefficient of TOPIS can be built. Furthermore, the life expectancy loss recovery factor is introduced to correct the life expectancy of TOPIS again. Lastly, a practical case study of an operating transformer has been undertaken, in which the failure rate curve after introducing dynamic corrections can be obtained for the reliability assessment of this transformer. The curve shows a better ability of tracking the actual reliability level of transformer, thus verifying the validity of the proposed method and providing a new way for transformer reliability assessment. This contribution presents a novel model for the reliability assessment of TOPIS, in which the DGA data, as a source of information for the dynamic correction, is processed based on the grey target theory, thus the internal faults of power transformer can be diagnosed accurately as well as its life expectancy updated in time, ensuring that the dynamic assessment values can commendably track and reflect the actual operation state of the power transformers.

  11. Reliability of dynamic systems under limited information.

    Energy Technology Data Exchange (ETDEWEB)

    Field, Richard V., Jr. (.,; .); Grigoriu, Mircea

    2006-09-01

    A method is developed for reliability analysis of dynamic systems under limited information. The available information includes one or more samples of the system output; any known information on features of the output can be used if available. The method is based on the theory of non-Gaussian translation processes and is shown to be particularly suitable for problems of practical interest. For illustration, we apply the proposed method to a series of simple example problems and compare with results given by traditional statistical estimators in order to establish the accuracy of the method. It is demonstrated that the method delivers accurate results for the case of linear and nonlinear dynamic systems, and can be applied to analyze experimental data and/or mathematical model outputs. Two complex applications of direct interest to Sandia are also considered. First, we apply the proposed method to assess design reliability of a MEMS inertial switch. Second, we consider re-entry body (RB) component vibration response during normal re-entry, where the objective is to estimate the time-dependent probability of component failure. This last application is directly relevant to re-entry random vibration analysis at Sandia, and may provide insights on test-based and/or model-based qualification of weapon components for random vibration environments.

  12. Power transformer reliability modelling

    NARCIS (Netherlands)

    Schijndel, van A.

    2010-01-01

    Problem description Electrical power grids serve to transport and distribute electrical power with high reliability and availability at acceptable costs and risks. These grids play a crucial though preferably invisible role in supplying sufficient power in a convenient form. Today’s society has

  13. Role of network dynamics in shaping spike timing reliability

    International Nuclear Information System (INIS)

    Bazhenov, Maxim; Rulkov, Nikolai F.; Fellous, Jean-Marc; Timofeev, Igor

    2005-01-01

    We study the reliability of cortical neuron responses to periodically modulated synaptic stimuli. Simple map-based models of two different types of cortical neurons are constructed to replicate the intrinsic resonances of reliability found in experimental data and to explore the effects of those resonance properties on collective behavior in a cortical network model containing excitatory and inhibitory cells. We show that network interactions can enhance the frequency range of reliable responses and that the latter can be controlled by the strength of synaptic connections. The underlying dynamical mechanisms of reliability enhancement are discussed

  14. Reliability Overhaul Model

    Science.gov (United States)

    1989-08-01

    Random variables for the conditional exponential distribution are generated using the inverse transform method. C1) Generate U - UCO,i) (2) Set s - A ln...e - [(x+s - 7)/ n] 0 + [Cx-T)/n]0 c. Random variables from the conditional weibull distribution are generated using the inverse transform method. C1...using a standard normal transformation and the inverse transform method. B - 3 APPENDIX 3 DISTRIBUTIONS SUPPORTED BY THE MODEL (1) Generate Y - PCX S

  15. Embedded Sensors and Controls to Improve Component Performance and Reliability - System Dynamics Modeling and Control System Design

    Energy Technology Data Exchange (ETDEWEB)

    Melin, Alexander M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Kisner, Roger A. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Fugate, David L. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2013-10-01

    This report documents the current status of the modeling, control design, and embedded control research for the magnetic bearing canned rotor pump being used as a demonstration platform for deeply integrating instrumentation and controls (I{\\&}C) into nuclear power plant components. This pump is a highly inter-connected thermo/electro/mechanical system that requires an active control system to operate. Magnetic bearings are inherently unstable system and without active, moment by moment control, the rotor would contact fixed surfaces in the pump causing physical damage. This report details the modeling of the pump rotordynamics, fluid forces, electromagnetic properties of the protective cans, active magnetic bearings, power electronics, and interactions between different dynamical models. The system stability of the unforced and controlled rotor are investigated analytically. Additionally, controllers are designed using proportional derivative (PD) control, proportional integral derivative (PID) control, voltage control, and linear quadratic regulator (LQR) control. Finally, a design optimization problem that joins the electrical, mechanical, magnetic, and control system design into one problem to balance the opposing needs of various design criteria using the embedded system approach is presented.

  16. Reliability Modeling of Wind Turbines

    DEFF Research Database (Denmark)

    Kostandyan, Erik

    Cost reductions for offshore wind turbines are a substantial requirement in order to make offshore wind energy more competitive compared to other energy supply methods. During the 20 – 25 years of wind turbines useful life, Operation & Maintenance costs are typically estimated to be a quarter...... for Operation & Maintenance planning. Concentrating efforts on development of such models, this research is focused on reliability modeling of Wind Turbine critical subsystems (especially the power converter system). For reliability assessment of these components, structural reliability methods are applied...... to one third of the total cost of energy. Reduction of Operation & Maintenance costs will result in significant cost savings and result in cheaper electricity production. Operation & Maintenance processes mainly involve actions related to replacements or repair. Identifying the right times when...

  17. Proposed Reliability/Cost Model

    Science.gov (United States)

    Delionback, L. M.

    1982-01-01

    New technique estimates cost of improvement in reliability for complex system. Model format/approach is dependent upon use of subsystem cost-estimating relationships (CER's) in devising cost-effective policy. Proposed methodology should have application in broad range of engineering management decisions.

  18. Reliability in the Rasch Model

    Czech Academy of Sciences Publication Activity Database

    Martinková, Patrícia; Zvára, K.

    2007-01-01

    Roč. 43, č. 3 (2007), s. 315-326 ISSN 0023-5954 R&D Projects: GA MŠk(CZ) 1M06014 Institutional research plan: CEZ:AV0Z10300504 Keywords : Cronbach's alpha * Rasch model * reliability Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.552, year: 2007 http://dml.cz/handle/10338.dmlcz/135776

  19. Multinomial-exponential reliability function: a software reliability model

    International Nuclear Information System (INIS)

    Saiz de Bustamante, Amalio; Saiz de Bustamante, Barbara

    2003-01-01

    The multinomial-exponential reliability function (MERF) was developed during a detailed study of the software failure/correction processes. Later on MERF was approximated by a much simpler exponential reliability function (EARF), which keeps most of MERF mathematical properties, so the two functions together makes up a single reliability model. The reliability model MERF/EARF considers the software failure process as a non-homogeneous Poisson process (NHPP), and the repair (correction) process, a multinomial distribution. The model supposes that both processes are statistically independent. The paper discusses the model's theoretical basis, its mathematical properties and its application to software reliability. Nevertheless it is foreseen model applications to inspection and maintenance of physical systems. The paper includes a complete numerical example of the model application to a software reliability analysis

  20. Development of reliable pavement models.

    Science.gov (United States)

    2011-05-01

    The current report proposes a framework for estimating the reliability of a given pavement structure as analyzed by : the Mechanistic-Empirical Pavement Design Guide (MEPDG). The methodology proposes using a previously fit : response surface, in plac...

  1. Software reliability models for critical applications

    Energy Technology Data Exchange (ETDEWEB)

    Pham, H.; Pham, M.

    1991-12-01

    This report presents the results of the first phase of the ongoing EG&G Idaho, Inc. Software Reliability Research Program. The program is studying the existing software reliability models and proposes a state-of-the-art software reliability model that is relevant to the nuclear reactor control environment. This report consists of three parts: (1) summaries of the literature review of existing software reliability and fault tolerant software reliability models and their related issues, (2) proposed technique for software reliability enhancement, and (3) general discussion and future research. The development of this proposed state-of-the-art software reliability model will be performed in the second place. 407 refs., 4 figs., 2 tabs.

  2. Software reliability models for critical applications

    Energy Technology Data Exchange (ETDEWEB)

    Pham, H.; Pham, M.

    1991-12-01

    This report presents the results of the first phase of the ongoing EG G Idaho, Inc. Software Reliability Research Program. The program is studying the existing software reliability models and proposes a state-of-the-art software reliability model that is relevant to the nuclear reactor control environment. This report consists of three parts: (1) summaries of the literature review of existing software reliability and fault tolerant software reliability models and their related issues, (2) proposed technique for software reliability enhancement, and (3) general discussion and future research. The development of this proposed state-of-the-art software reliability model will be performed in the second place. 407 refs., 4 figs., 2 tabs.

  3. A double-loop adaptive sampling approach for sensitivity-free dynamic reliability analysis

    International Nuclear Information System (INIS)

    Wang, Zequn; Wang, Pingfeng

    2015-01-01

    Dynamic reliability measures reliability of an engineered system considering time-variant operation condition and component deterioration. Due to high computational costs, conducting dynamic reliability analysis at an early system design stage remains challenging. This paper presents a confidence-based meta-modeling approach, referred to as double-loop adaptive sampling (DLAS), for efficient sensitivity-free dynamic reliability analysis. The DLAS builds a Gaussian process (GP) model sequentially to approximate extreme system responses over time, so that Monte Carlo simulation (MCS) can be employed directly to estimate dynamic reliability. A generic confidence measure is developed to evaluate the accuracy of dynamic reliability estimation while using the MCS approach based on developed GP models. A double-loop adaptive sampling scheme is developed to efficiently update the GP model in a sequential manner, by considering system input variables and time concurrently in two sampling loops. The model updating process using the developed sampling scheme can be terminated once the user defined confidence target is satisfied. The developed DLAS approach eliminates computationally expensive sensitivity analysis process, thus substantially improves the efficiency of dynamic reliability analysis. Three case studies are used to demonstrate the efficacy of DLAS for dynamic reliability analysis. - Highlights: • Developed a novel adaptive sampling approach for dynamic reliability analysis. • POD Developed a new metric to quantify the accuracy of dynamic reliability estimation. • Developed a new sequential sampling scheme to efficiently update surrogate models. • Three case studies were used to demonstrate the efficacy of the new approach. • Case study results showed substantially enhanced efficiency with high accuracy

  4. Improvement of the reliability graph with general gates to analyze the reliability of dynamic systems that have various operation modes

    Energy Technology Data Exchange (ETDEWEB)

    Shin, Seung Ki [Div. of Research Reactor System Design, Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); No, Young Gyu; Seong, Poong Hyun [Dept. of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon (Korea, Republic of)

    2016-04-15

    The safety of nuclear power plants is analyzed by a probabilistic risk assessment, and the fault tree analysis is the most widely used method for a risk assessment with the event tree analysis. One of the well-known disadvantages of the fault tree is that drawing a fault tree for a complex system is a very cumbersome task. Thus, several graphical modeling methods have been proposed for the convenient and intuitive modeling of complex systems. In this paper, the reliability graph with general gates (RGGG) method, one of the intuitive graphical modeling methods based on Bayesian networks, is improved for the reliability analyses of dynamic systems that have various operation modes with time. A reliability matrix is proposed and it is explained how to utilize the reliability matrix in the RGGG for various cases of operation mode changes. The proposed RGGG with a reliability matrix provides a convenient and intuitive modeling of various operation modes of complex systems, and can also be utilized with dynamic nodes that analyze the failure sequences of subcomponents. The combinatorial use of a reliability matrix with dynamic nodes is illustrated through an application to a shutdown cooling system in a nuclear power plant.

  5. Improvement of the reliability graph with general gates to analyze the reliability of dynamic systems that have various operation modes

    International Nuclear Information System (INIS)

    Shin, Seung Ki; No, Young Gyu; Seong, Poong Hyun

    2016-01-01

    The safety of nuclear power plants is analyzed by a probabilistic risk assessment, and the fault tree analysis is the most widely used method for a risk assessment with the event tree analysis. One of the well-known disadvantages of the fault tree is that drawing a fault tree for a complex system is a very cumbersome task. Thus, several graphical modeling methods have been proposed for the convenient and intuitive modeling of complex systems. In this paper, the reliability graph with general gates (RGGG) method, one of the intuitive graphical modeling methods based on Bayesian networks, is improved for the reliability analyses of dynamic systems that have various operation modes with time. A reliability matrix is proposed and it is explained how to utilize the reliability matrix in the RGGG for various cases of operation mode changes. The proposed RGGG with a reliability matrix provides a convenient and intuitive modeling of various operation modes of complex systems, and can also be utilized with dynamic nodes that analyze the failure sequences of subcomponents. The combinatorial use of a reliability matrix with dynamic nodes is illustrated through an application to a shutdown cooling system in a nuclear power plant

  6. Reliability and continuous regeneration model

    Directory of Open Access Journals (Sweden)

    Anna Pavlisková

    2006-06-01

    Full Text Available The failure-free function of an object is very important for the service. This leads to the interest in the determination of the object reliability and failure intensity. The reliability of an element is defined by the theory of probability.The element durability T is a continuous random variate with the probability density f. The failure intensity (tλ is a very important reliability characteristics of the element. Often it is an increasing function, which corresponds to the element ageing. We disposed of the data about a belt conveyor failures recorded during the period of 90 months. The given ses behaves according to the normal distribution. By using a mathematical analysis and matematical statistics, we found the failure intensity function (tλ. The function (tλ increases almost linearly.

  7. Review of various dynamic modeling methods and development of an intuitive modeling method for dynamic systems

    International Nuclear Information System (INIS)

    Shin, Seung Ki; Seong, Poong Hyun

    2008-01-01

    Conventional static reliability analysis methods are inadequate for modeling dynamic interactions between components of a system. Various techniques such as dynamic fault tree, dynamic Bayesian networks, and dynamic reliability block diagrams have been proposed for modeling dynamic systems based on improvement of the conventional modeling methods. In this paper, we review these methods briefly and introduce dynamic nodes to the existing Reliability Graph with General Gates (RGGG) as an intuitive modeling method to model dynamic systems. For a quantitative analysis, we use a discrete-time method to convert an RGGG to an equivalent Bayesian network and develop a software tool for generation of probability tables

  8. Reliability analysis for dynamic configurations of systems with three failure modes

    International Nuclear Information System (INIS)

    Pham, Hoang

    1999-01-01

    Analytical models for computing the reliability of dynamic configurations of systems, such as majority and k-out-of-n, assuming that units and systems are subject to three types of failures: stuck-at-0, stuck-at-1, and stuck-at-x are presented in this paper. Formulas for determining the optimal design policies that maximize the reliability of dynamic k-out-of-n configurations subject to three types of failures are defined. The comparisons of the reliability modeling functions are also obtained. The optimum system size and threshold value k that minimize the expected cost of dynamic k-out-of-n configurations are also determined

  9. 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)

  10. A dynamic discretization method for reliability inference in Dynamic Bayesian Networks

    International Nuclear Information System (INIS)

    Zhu, Jiandao; Collette, Matthew

    2015-01-01

    The material and modeling parameters that drive structural reliability analysis for marine structures are subject to a significant uncertainty. This is especially true when time-dependent degradation mechanisms such as structural fatigue cracking are considered. Through inspection and monitoring, information such as crack location and size can be obtained to improve these parameters and the corresponding reliability estimates. Dynamic Bayesian Networks (DBNs) are a powerful and flexible tool to model dynamic system behavior and update reliability and uncertainty analysis with life cycle data for problems such as fatigue cracking. However, a central challenge in using DBNs is the need to discretize certain types of continuous random variables to perform network inference while still accurately tracking low-probability failure events. Most existing discretization methods focus on getting the overall shape of the distribution correct, with less emphasis on the tail region. Therefore, a novel scheme is presented specifically to estimate the likelihood of low-probability failure events. The scheme is an iterative algorithm which dynamically partitions the discretization intervals at each iteration. Through applications to two stochastic crack-growth example problems, the algorithm is shown to be robust and accurate. Comparisons are presented between the proposed approach and existing methods for the discretization problem. - Highlights: • A dynamic discretization method is developed for low-probability events in DBNs. • The method is compared to existing approaches on two crack growth problems. • The method is shown to improve on existing methods for low-probability events

  11. Reliability Analysis of Dynamic Stability in Waves

    DEFF Research Database (Denmark)

    Søborg, Anders Veldt

    2004-01-01

    exhibit sufficient characteristics with respect to slope at zero heel (GM value), maximum leverarm, positive range of stability and area below the leverarm curve. The rule-based requirements to calm water leverarm curves are entirely based on experience obtained from vessels in operation and recorded......The assessment of a ship's intact stability is traditionally based on a semi-empirical deterministic concept that evaluates the characteristics of ship's calm water restoring leverarm curves. Today the ship is considered safe with respect to dynamic stability if its calm water leverarm curves...... accidents in the past. The rules therefore only leaves little room for evaluation and improvement of safety of a ship's dynamic stability. A few studies have evaluated the probability of ship stability loss in waves using Monte Carlo simulations. However, since this probability may be in the order of 10...

  12. Reliability Modeling of Double Beam Bridge Crane

    Science.gov (United States)

    Han, Zhu; Tong, Yifei; Luan, Jiahui; Xiangdong, Li

    2018-05-01

    This paper briefly described the structure of double beam bridge crane and the basic parameters of double beam bridge crane are defined. According to the structure and system division of double beam bridge crane, the reliability architecture of double beam bridge crane system is proposed, and the reliability mathematical model is constructed.

  13. Reliable Approximation of Long Relaxation Timescales in Molecular Dynamics

    Directory of Open Access Journals (Sweden)

    Wei Zhang

    2017-07-01

    Full Text Available Many interesting rare events in molecular systems, like ligand association, protein folding or conformational changes, occur on timescales that often are not accessible by direct numerical simulation. Therefore, rare event approximation approaches like interface sampling, Markov state model building, or advanced reaction coordinate-based free energy estimation have attracted huge attention recently. In this article we analyze the reliability of such approaches. How precise is an estimate of long relaxation timescales of molecular systems resulting from various forms of rare event approximation methods? Our results give a theoretical answer to this question by relating it with the transfer operator approach to molecular dynamics. By doing so we also allow for understanding deep connections between the different approaches.

  14. Reliability Modeling of Wind Turbines

    DEFF Research Database (Denmark)

    Kostandyan, Erik

    Cost reductions for offshore wind turbines are a substantial requirement in order to make offshore wind energy more competitive compared to other energy supply methods. During the 20 – 25 years of wind turbines useful life, Operation & Maintenance costs are typically estimated to be a quarter...... and uncertainties are quantified. Further, estimation of annual failure probability for structural components taking into account possible faults in electrical or mechanical systems is considered. For a representative structural failure mode, a probabilistic model is developed that incorporates grid loss failures...

  15. Reliability modeling of an engineered barrier system

    International Nuclear Information System (INIS)

    Ananda, M.M.A.; Singh, A.K.; Flueck, J.A.

    1993-01-01

    The Weibull distribution is widely used in reliability literature as a distribution of time to failure, as it allows for both increasing failure rate (IFR) and decreasing failure rate (DFR) models. It has also been used to develop models for an engineered barrier system (EBS), which is known to be one of the key components in a deep geological repository for high level radioactive waste (HLW). The EBS failure time can more realistically be modelled by an IFR distribution, since the failure rate for the EBS is not expected to decrease with time. In this paper, we use an IFR distribution to develop a reliability model for the EBS

  16. Reliability modeling of an engineered barrier system

    International Nuclear Information System (INIS)

    Ananda, M.M.A.; Singh, A.K.; Flueck, J.A.

    1993-01-01

    The Weibull distribution is widely used in reliability literature as a distribution of time to failure, as it allows for both increasing failure rate (IFR) and decreasing failure rate (DFR) models. It has also been used to develop models for an engineered barrier system (EBS), which is known to be one of the key components in a deep geological repository for high level radioactive waste (HLW). The EBS failure time can more realistically be modelled by an IFR distribution, since the failure rate for the EBS is not expected to decrease with time. In this paper, an IFR distribution is used to develop a reliability model for the EBS

  17. Evaluation of mobile ad hoc network reliability using propagation-based link reliability model

    International Nuclear Information System (INIS)

    Padmavathy, N.; Chaturvedi, Sanjay K.

    2013-01-01

    A wireless mobile ad hoc network (MANET) is a collection of solely independent nodes (that can move randomly around the area of deployment) making the topology highly dynamic; nodes communicate with each other by forming a single hop/multi-hop network and maintain connectivity in decentralized manner. MANET is modelled using geometric random graphs rather than random graphs because the link existence in MANET is a function of the geometric distance between the nodes and the transmission range of the nodes. Among many factors that contribute to the MANET reliability, the reliability of these networks also depends on the robustness of the link between the mobile nodes of the network. Recently, the reliability of such networks has been evaluated for imperfect nodes (transceivers) with binary model of communication links based on the transmission range of the mobile nodes and the distance between them. However, in reality, the probability of successful communication decreases as the signal strength deteriorates due to noise, fading or interference effects even up to the nodes' transmission range. Hence, in this paper, using a propagation-based link reliability model rather than a binary-model with nodes following a known failure distribution to evaluate the network reliability (2TR m , ATR m and AoTR m ) of MANET through Monte Carlo Simulation is proposed. The method is illustrated with an application and some imperative results are also presented

  18. Towards a reliable animal model of migraine

    DEFF Research Database (Denmark)

    Olesen, Jes; Jansen-Olesen, Inger

    2012-01-01

    The pharmaceutical industry shows a decreasing interest in the development of drugs for migraine. One of the reasons for this could be the lack of reliable animal models for studying the effect of acute and prophylactic migraine drugs. The infusion of glyceryl trinitrate (GTN) is the best validated...... and most studied human migraine model. Several attempts have been made to transfer this model to animals. The different variants of this model are discussed as well as other recent models....

  19. Space Vehicle Reliability Modeling in DIORAMA

    Energy Technology Data Exchange (ETDEWEB)

    Tornga, Shawn Robert [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-07-12

    When modeling system performance of space based detection systems it is important to consider spacecraft reliability. As space vehicles age the components become prone to failure for a variety of reasons such as radiation damage. Additionally, some vehicles may lose the ability to maneuver once they exhaust fuel supplies. Typically failure is divided into two categories: engineering mistakes and technology surprise. This document will report on a method of simulating space vehicle reliability in the DIORAMA framework.

  20. The DYLAM approach for the dynamic reliability analysis of systems

    International Nuclear Information System (INIS)

    Cojazzi, Giacomo

    1996-01-01

    In many real systems, failures occurring to the components, control failures and human interventions often interact with the physical system evolution in such a way that a simple reliability analysis, de-coupled from process dynamics, is very difficult or even impossible. In the last ten years many dynamic reliability approaches have been proposed to properly assess the reliability of these systems characterized by dynamic interactions. The DYLAM methodology, now implemented in its latest version, DYLAM-3, offers a powerful tool for integrating deterministic and failure events. This paper describes the main features of the DYLAM-3 code with reference to the classic fault-tree and event-tree techniques. Some aspects connected to the practical problems underlying dynamic event-trees are also discussed. A simple system, already analyzed with other dynamic methods is used as a reference for the numerical applications. The same system is also studied with a time-dependent fault-tree approach in order to show some features of dynamic methods vs classical techniques. Examples including stochastic failures, without and with repair, failures on demand and time dependent failure rates give an extensive overview of DYLAM-3 capabilities

  1. Modeling of system reliability Petri nets with aging tokens

    International Nuclear Information System (INIS)

    Volovoi, V.

    2004-01-01

    The paper addresses the dynamic modeling of degrading and repairable complex systems. Emphasis is placed on the convenience of modeling for the end user, with special attention being paid to the modeling part of a problem, which is considered to be decoupled from the choice of solution algorithms. Depending on the nature of the problem, these solution algorithms can include discrete event simulation or numerical solution of the differential equations that govern underlying stochastic processes. Such modularity allows a focus on the needs of system reliability modeling and tailoring of the modeling formalism accordingly. To this end, several salient features are chosen from the multitude of existing extensions of Petri nets, and a new concept of aging tokens (tokens with memory) is introduced. The resulting framework provides for flexible and transparent graphical modeling with excellent representational power that is particularly suited for system reliability modeling with non-exponentially distributed firing times. The new framework is compared with existing Petri-net approaches and other system reliability modeling techniques such as reliability block diagrams and fault trees. The relative differences are emphasized and illustrated with several examples, including modeling of load sharing, imperfect repair of pooled items, multiphase missions, and damage-tolerant maintenance. Finally, a simple implementation of the framework using discrete event simulation is described

  2. Overcoming some limitations of imprecise reliability models

    DEFF Research Database (Denmark)

    Kozine, Igor; Krymsky, Victor

    2011-01-01

    The application of imprecise reliability models is often hindered by the rapid growth in imprecision that occurs when many components constitute a system and by the fact that time to failure is bounded from above. The latter results in the necessity to explicitly introduce an upper bound on time ...

  3. Evaluating the reliability of multi-body mechanisms: A method considering the uncertainties of dynamic performance

    International Nuclear Information System (INIS)

    Wu, Jianing; Yan, Shaoze; Zuo, Ming J.

    2016-01-01

    Mechanism reliability is defined as the ability of a certain mechanism to maintain output accuracy under specified conditions. Mechanism reliability is generally assessed by the classical direct probability method (DPM) derived from the first order second moment (FOSM) method. The DPM relies strongly on the analytical form of the dynamic solution so it is not applicable to multi-body mechanisms that have only numerical solutions. In this paper, an indirect probability model (IPM) is proposed for mechanism reliability evaluation of multi-body mechanisms. IPM combines the dynamic equation, degradation function and Kaplan–Meier estimator to evaluate mechanism reliability comprehensively. Furthermore, to reduce the amount of computation in practical applications, the IPM is simplified into the indirect probability step model (IPSM). A case study of a crank–slider mechanism with clearance is investigated. Results show that relative errors between the theoretical and experimental results of mechanism reliability are less than 5%, demonstrating the effectiveness of the proposed method. - Highlights: • An indirect probability model (IPM) is proposed for mechanism reliability evaluation. • The dynamic equation, degradation function and Kaplan–Meier estimator are used. • Then the simplified form of indirect probability model is proposed. • The experimental results agree well with the predicted results.

  4. Reliable RANSAC Using a Novel Preprocessing Model

    Directory of Open Access Journals (Sweden)

    Xiaoyan Wang

    2013-01-01

    Full Text Available Geometric assumption and verification with RANSAC has become a crucial step for corresponding to local features due to its wide applications in biomedical feature analysis and vision computing. However, conventional RANSAC is very time-consuming due to redundant sampling times, especially dealing with the case of numerous matching pairs. This paper presents a novel preprocessing model to explore a reduced set with reliable correspondences from initial matching dataset. Both geometric model generation and verification are carried out on this reduced set, which leads to considerable speedups. Afterwards, this paper proposes a reliable RANSAC framework using preprocessing model, which was implemented and verified using Harris and SIFT features, respectively. Compared with traditional RANSAC, experimental results show that our method is more efficient.

  5. Investigating the Intersession Reliability of Dynamic Brain-State Properties.

    Science.gov (United States)

    Smith, Derek M; Zhao, Yrian; Keilholz, Shella D; Schumacher, Eric H

    2018-06-01

    Dynamic functional connectivity metrics have much to offer to the neuroscience of individual differences of cognition. Yet, despite the recent expansion in dynamic connectivity research, limited resources have been devoted to the study of the reliability of these connectivity measures. To address this, resting-state functional magnetic resonance imaging data from 100 Human Connectome Project subjects were compared across 2 scan days. Brain states (i.e., patterns of coactivity across regions) were identified by classifying each time frame using k means clustering. This was done with and without global signal regression (GSR). Multiple gauges of reliability indicated consistency in the brain-state properties across days and GSR attenuated the reliability of the brain states. Changes in the brain-state properties across the course of the scan were investigated as well. The results demonstrate that summary metrics describing the clustering of individual time frames have adequate test/retest reliability, and thus, these patterns of brain activation may hold promise for individual-difference research.

  6. Dynamic Scheduling for Cloud Reliability using Transportation Problem

    OpenAIRE

    P. Balasubramanie; S. K. Senthil Kumar

    2012-01-01

    Problem statement: Cloud is purely a dynamic environment and the existing task scheduling algorithms are mostly static and considered various parameters like time, cost, make span, speed, scalability, throughput, resource utilization, scheduling success rate and so on. Available scheduling algorithms are mostly heuristic in nature and more complex, time consuming and does not consider reliability and availability of the cloud computing environment. Therefore there is a need to implement a sch...

  7. Photovoltaic Reliability Performance Model v 2.0

    Energy Technology Data Exchange (ETDEWEB)

    2016-12-16

    PV-RPM is intended to address more “real world” situations by coupling a photovoltaic system performance model with a reliability model so that inverters, modules, combiner boxes, etc. can experience failures and be repaired (or left unrepaired). The model can also include other effects, such as module output degradation over time or disruptions such as electrical grid outages. In addition, PV-RPM is a dynamic probabilistic model that can be used to run many realizations (i.e., possible future outcomes) of a system’s performance using probability distributions to represent uncertain parameter inputs.

  8. Bring Your Own Device - Providing Reliable Model of Data Access

    Directory of Open Access Journals (Sweden)

    Stąpór Paweł

    2016-10-01

    Full Text Available The article presents a model of Bring Your Own Device (BYOD as a model network, which provides the user reliable access to network resources. BYOD is a model dynamically developing, which can be applied in many areas. Research network has been launched in order to carry out the test, in which as a service of BYOD model Work Folders service was used. This service allows the user to synchronize files between the device and the server. An access to the network is completed through the wireless communication by the 802.11n standard. Obtained results are shown and analyzed in this article.

  9. Design and reliability analysis of DP-3 dynamic positioning control architecture

    Science.gov (United States)

    Wang, Fang; Wan, Lei; Jiang, Da-Peng; Xu, Yu-Ru

    2011-12-01

    As the exploration and exploitation of oil and gas proliferate throughout deepwater area, the requirements on the reliability of dynamic positioning system become increasingly stringent. The control objective ensuring safety operation at deep water will not be met by a single controller for dynamic positioning. In order to increase the availability and reliability of dynamic positioning control system, the triple redundancy hardware and software control architectures were designed and developed according to the safe specifications of DP-3 classification notation for dynamically positioned ships and rigs. The hardware redundant configuration takes the form of triple-redundant hot standby configuration including three identical operator stations and three real-time control computers which connect each other through dual networks. The function of motion control and redundancy management of control computers were implemented by software on the real-time operating system VxWorks. The software realization of task loose synchronization, majority voting and fault detection were presented in details. A hierarchical software architecture was planed during the development of software, consisting of application layer, real-time layer and physical layer. The behavior of the DP-3 dynamic positioning control system was modeled by a Markov model to analyze its reliability. The effects of variation in parameters on the reliability measures were investigated. The time domain dynamic simulation was carried out on a deepwater drilling rig to prove the feasibility of the proposed control architecture.

  10. Centralized Bayesian reliability modelling with sensor networks

    Czech Academy of Sciences Publication Activity Database

    Dedecius, Kamil; Sečkárová, Vladimíra

    2013-01-01

    Roč. 19, č. 5 (2013), s. 471-482 ISSN 1387-3954 R&D Projects: GA MŠk 7D12004 Grant - others:GA MŠk(CZ) SVV-265315 Keywords : Bayesian modelling * Sensor network * Reliability Subject RIV: BD - Theory of Information Impact factor: 0.984, year: 2013 http://library.utia.cas.cz/separaty/2013/AS/dedecius-0392551.pdf

  11. Stochastic models in reliability and maintenance

    CERN Document Server

    2002-01-01

    Our daily lives can be maintained by the high-technology systems. Computer systems are typical examples of such systems. We can enjoy our modern lives by using many computer systems. Much more importantly, we have to maintain such systems without failure, but cannot predict when such systems will fail and how to fix such systems without delay. A stochastic process is a set of outcomes of a random experiment indexed by time, and is one of the key tools needed to analyze the future behavior quantitatively. Reliability and maintainability technologies are of great interest and importance to the maintenance of such systems. Many mathematical models have been and will be proposed to describe reliability and maintainability systems by using the stochastic processes. The theme of this book is "Stochastic Models in Reliability and Main­ tainability. " This book consists of 12 chapters on the theme above from the different viewpoints of stochastic modeling. Chapter 1 is devoted to "Renewal Processes," under which cla...

  12. Modeling dynamic swarms

    KAUST Repository

    Ghanem, Bernard; Ahuja, Narendra

    2013-01-01

    This paper proposes the problem of modeling video sequences of dynamic swarms (DSs). We define a DS as a large layout of stochastically repetitive spatial configurations of dynamic objects (swarm elements) whose motions exhibit local spatiotemporal

  13. Measurement-based reliability/performability models

    Science.gov (United States)

    Hsueh, Mei-Chen

    1987-01-01

    Measurement-based models based on real error-data collected on a multiprocessor system are described. Model development from the raw error-data to the estimation of cumulative reward is also described. A workload/reliability model is developed based on low-level error and resource usage data collected on an IBM 3081 system during its normal operation in order to evaluate the resource usage/error/recovery process in a large mainframe system. Thus, both normal and erroneous behavior of the system are modeled. The results provide an understanding of the different types of errors and recovery processes. The measured data show that the holding times in key operational and error states are not simple exponentials and that a semi-Markov process is necessary to model the system behavior. A sensitivity analysis is performed to investigate the significance of using a semi-Markov process, as opposed to a Markov process, to model the measured system.

  14. Dynamic Reliability Analysis of Gear Transmission System of Wind Turbine in Consideration of Randomness of Loadings and Parameters

    Directory of Open Access Journals (Sweden)

    Lei Wang

    2014-01-01

    Full Text Available A dynamic model of gear transmission system of wind turbine is built with consideration of randomness of loads and parameters. The dynamic response of the system is obtained using the theory of random sampling and the Runge-Kutta method. According to rain flow counting principle, the dynamic meshing forces are converted into a series of luffing fatigue load spectra. The amplitude and frequency of the equivalent stress are obtained using equivalent method of Geber quadratic curve. Moreover, the dynamic reliability model of components and system is built according to the theory of probability of cumulative fatigue damage. The system reliability with the random variation of parameters is calculated and the influence of random parameters on dynamic reliability of components is analyzed. In the end, the results of the proposed method are compared with that of Monte Carlo method. This paper can be instrumental in the design of wind turbine gear transmission system with more advantageous dynamic reliability.

  15. Imperfect Preventive Maintenance Model Study Based On Reliability Limitation

    Directory of Open Access Journals (Sweden)

    Zhou Qian

    2016-01-01

    Full Text Available Effective maintenance is crucial for equipment performance in industry. Imperfect maintenance conform to actual failure process. Taking the dynamic preventive maintenance cost into account, the preventive maintenance model was constructed by using age reduction factor. The model regards the minimization of repair cost rate as final target. It use allowed smallest reliability as the replacement condition. Equipment life was assumed to follow two parameters Weibull distribution since it was one of the most commonly adopted distributions to fit cumulative failure problems. Eventually the example verifies the rationality and benefits of the model.

  16. Bayesian methodology for reliability model acceptance

    International Nuclear Information System (INIS)

    Zhang Ruoxue; Mahadevan, Sankaran

    2003-01-01

    This paper develops a methodology to assess the reliability computation model validity using the concept of Bayesian hypothesis testing, by comparing the model prediction and experimental observation, when there is only one computational model available to evaluate system behavior. Time-independent and time-dependent problems are investigated, with consideration of both cases: with and without statistical uncertainty in the model. The case of time-independent failure probability prediction with no statistical uncertainty is a straightforward application of Bayesian hypothesis testing. However, for the life prediction (time-dependent reliability) problem, a new methodology is developed in this paper to make the same Bayesian hypothesis testing concept applicable. With the existence of statistical uncertainty in the model, in addition to the application of a predictor estimator of the Bayes factor, the uncertainty in the Bayes factor is explicitly quantified through treating it as a random variable and calculating the probability that it exceeds a specified value. The developed method provides a rational criterion to decision-makers for the acceptance or rejection of the computational model

  17. Data Used in Quantified Reliability Models

    Science.gov (United States)

    DeMott, Diana; Kleinhammer, Roger K.; Kahn, C. J.

    2014-01-01

    Data is the crux to developing quantitative risk and reliability models, without the data there is no quantification. The means to find and identify reliability data or failure numbers to quantify fault tree models during conceptual and design phases is often the quagmire that precludes early decision makers consideration of potential risk drivers that will influence design. The analyst tasked with addressing a system or product reliability depends on the availability of data. But, where is does that data come from and what does it really apply to? Commercial industries, government agencies, and other international sources might have available data similar to what you are looking for. In general, internal and external technical reports and data based on similar and dissimilar equipment is often the first and only place checked. A common philosophy is "I have a number - that is good enough". But, is it? Have you ever considered the difference in reported data from various federal datasets and technical reports when compared to similar sources from national and/or international datasets? Just how well does your data compare? Understanding how the reported data was derived, and interpreting the information and details associated with the data is as important as the data itself.

  18. Dynamic decision-making for reliability and maintenance analysis of manufacturing systems based on failure effects

    Science.gov (United States)

    Zhang, Ding; Zhang, Yingjie

    2017-09-01

    A framework for reliability and maintenance analysis of job shop manufacturing systems is proposed in this paper. An efficient preventive maintenance (PM) policy in terms of failure effects analysis (FEA) is proposed. Subsequently, reliability evaluation and component importance measure based on FEA are performed under the PM policy. A job shop manufacturing system is applied to validate the reliability evaluation and dynamic maintenance policy. Obtained results are compared with existed methods and the effectiveness is validated. Some vague understandings for issues such as network modelling, vulnerabilities identification, the evaluation criteria of repairable systems, as well as PM policy during manufacturing system reliability analysis are elaborated. This framework can help for reliability optimisation and rational maintenance resources allocation of job shop manufacturing systems.

  19. RADYBAN: A tool for reliability analysis of dynamic fault trees through conversion into dynamic Bayesian networks

    International Nuclear Information System (INIS)

    Montani, S.; Portinale, L.; Bobbio, A.; Codetta-Raiteri, D.

    2008-01-01

    In this paper, we present RADYBAN (Reliability Analysis with DYnamic BAyesian Networks), a software tool which allows to analyze a dynamic fault tree relying on its conversion into a dynamic Bayesian network. The tool implements a modular algorithm for automatically translating a dynamic fault tree into the corresponding dynamic Bayesian network and exploits classical algorithms for the inference on dynamic Bayesian networks, in order to compute reliability measures. After having described the basic features of the tool, we show how it operates on a real world example and we compare the unreliability results it generates with those returned by other methodologies, in order to verify the correctness and the consistency of the results obtained

  20. Dynamic reliability networks with self-healing units

    International Nuclear Information System (INIS)

    Jenab, K.; Seyed Hosseini, S.M.; Dhillon, B.S.

    2008-01-01

    This paper presents an analytical approach for dynamic reliability networks used for the failure limit strategy in maintenance optimization. The proposed approach utilizes the moment generating function (MGF) and the flow-graph concept to depict the functional and reliability diagrams of the system comprised of series, parallel or mix configuration of self-healing units. The self-healing unit is featured by the embedded failure detection and recovery mechanisms presented by self-loop in flow-graph networks. The newly developed analytical approach provides the probability of the system failure and time-to-failure data i.e., mean and standard deviation time-to-failure used for maintenance optimization

  1. Dynamic Latent Classification Model

    DEFF Research Database (Denmark)

    Zhong, Shengtong; Martínez, Ana M.; Nielsen, Thomas Dyhre

    as possible. Motivated by this problem setting, we propose a generative model for dynamic classification in continuous domains. At each time point the model can be seen as combining a naive Bayes model with a mixture of factor analyzers (FA). The latent variables of the FA are used to capture the dynamics...

  2. Equivalent Dynamic Models.

    Science.gov (United States)

    Molenaar, Peter C M

    2017-01-01

    Equivalences of two classes of dynamic models for weakly stationary multivariate time series are discussed: dynamic factor models and autoregressive models. It is shown that exploratory dynamic factor models can be rotated, yielding an infinite set of equivalent solutions for any observed series. It also is shown that dynamic factor models with lagged factor loadings are not equivalent to the currently popular state-space models, and that restriction of attention to the latter type of models may yield invalid results. The known equivalent vector autoregressive model types, standard and structural, are given a new interpretation in which they are conceived of as the extremes of an innovating type of hybrid vector autoregressive models. It is shown that consideration of hybrid models solves many problems, in particular with Granger causality testing.

  3. Reliability and Correlation of Static and Dynamic Foot Arch Measurement in a Healthy Pediatric Population.

    Science.gov (United States)

    Scholz, Timo; Zech, Astrid; Wegscheider, Karl; Lezius, Susanne; Braumann, Klaus-Michael; Sehner, Susanne; Hollander, Karsten

    2017-09-01

    Measurement of the medial longitudinal foot arch in children is a controversial topic, as there are many different methods without a definite standard procedure. The purpose of this study was to 1) investigate intraday and interrater reliability regarding dynamic arch index and static arch height, 2) explore the correlation between both arch indices, and 3) examine the variation of the medial longitudinal arch at two different times of the day. Eighty-six children (mean ± SD age, 8.9 ± 1.9 years) participated in the study. Dynamic footprint data were captured with a pedobarographic platform. For static arch measurements, a specially constructed caliper was used to assess heel-to-toe length and dorsum height. A mixed model was established to determine reliability and variation. Reliability was found to be excellent for the static arch height index in sitting (intraday, 0.90; interrater, 0.80) and standing positions (0.88 and 0.85) and for the dynamic arch index (both 1.00). There was poor correlation between static and dynamic assessment of the medial longitudinal arch (standing dynamic arch index, r = -0.138; sitting dynamic arch index, r = -0.070). Static measurements were found to be significantly influenced by the time of day (P body mass index (P mind. For clinical purposes, static and dynamic arch data should be interpreted separately.

  4. Dynamic reliability assessment and prediction for repairable systems with interval-censored data

    International Nuclear Information System (INIS)

    Peng, Yizhen; Wang, Yu; Zi, YanYang; Tsui, Kwok-Leung; Zhang, Chuhua

    2017-01-01

    The ‘Test, Analyze and Fix’ process is widely applied to improve the reliability of a repairable system. In this process, dynamic reliability assessment for the system has been paid a great deal of attention. Due to instrument malfunctions, staff omissions and imperfect inspection strategies, field reliability data are often subject to interval censoring, making dynamic reliability assessment become a difficult task. Most traditional methods assume this kind of data as multiple normal distributed variables or the missing mechanism as missing at random, which may cause a large bias in parameter estimation. This paper proposes a novel method to evaluate and predict the dynamic reliability of a repairable system subject to interval-censored problem. First, a multiple imputation strategy based on the assumption that the reliability growth trend follows a nonhomogeneous Poisson process is developed to derive the distributions of missing data. Second, a new order statistic model that can transfer the dependent variables into independent variables is developed to simplify the imputation procedure. The unknown parameters of the model are iteratively inferred by the Monte Carlo expectation maximization (MCEM) algorithm. Finally, to verify the effectiveness of the proposed method, a simulation and a real case study for gas pipeline compressor system are implemented. - Highlights: • A new multiple imputation strategy was developed to derive the PDF of missing data. • A new order statistic model was developed to simplify the imputation procedure. • The parameters of the order statistic model were iteratively inferred by MCEM. • A real cases study was conducted to verify the effectiveness of the proposed method.

  5. [Measurements of blood velocities using duplex sonography in carotid artery stents: analysis of reliability in an in-vitro model and computational fluid dynamics (CFD)].

    Science.gov (United States)

    Schönwald, U G; Jorczyk, U; Kipfmüller, B

    2011-01-01

    Stents are commonly used for the treatment of occlusive artery diseases in carotid arteries. Today, there is a controversial discussion as to whether duplex sonography (DS) displays blood velocities (BV) that are too high in stented areas. The goal of this study was to evaluate the effect of stenting on DS with respect to BV in artificial carotid arteries. The results of computational fluid dynamics (CFD) were also used for the comparison. To analyze BV using DS, a phantom with a constant flow (70 cm/s) was created. Three different types of stents for carotid arteries were selected. The phantom fluid consisted of 67 % water and 33 % glycerol. All BV measurements were carried out on the last third of the stents. Furthermore, all test runs were simulated using CFD. All measurements were statistically analyzed. DS-derived BV values increased significantly after the placement of the Palmaz Genesis stent (77.6 ± 4.92 cm/sec, p = 0.03). A higher increase in BV values was registered when using the Precise RX stent (80.1 ± 2.01 cm/sec, p CFD simulations showed similar results. Stents have a significant impact on BV, but no effect on DS. The main factor of the blood flow acceleration is the material thickness of the stents. Therefore, different stents need different velocity criteria. Furthermore, the results of computational fluid dynamics prove that CFD can be used to simulate BV in stented silicone tubes. © Georg Thieme Verlag KG Stuttgart · New York.

  6. An integrated methodology for the dynamic performance and reliability evaluation of fault-tolerant systems

    International Nuclear Information System (INIS)

    Dominguez-Garcia, Alejandro D.; Kassakian, John G.; Schindall, Joel E.; Zinchuk, Jeffrey J.

    2008-01-01

    We propose an integrated methodology for the reliability and dynamic performance analysis of fault-tolerant systems. This methodology uses a behavioral model of the system dynamics, similar to the ones used by control engineers to design the control system, but also incorporates artifacts to model the failure behavior of each component. These artifacts include component failure modes (and associated failure rates) and how those failure modes affect the dynamic behavior of the component. The methodology bases the system evaluation on the analysis of the dynamics of the different configurations the system can reach after component failures occur. For each of the possible system configurations, a performance evaluation of its dynamic behavior is carried out to check whether its properties, e.g., accuracy, overshoot, or settling time, which are called performance metrics, meet system requirements. Markov chains are used to model the stochastic process associated with the different configurations that a system can adopt when failures occur. This methodology not only enables an integrated framework for evaluating dynamic performance and reliability of fault-tolerant systems, but also enables a method for guiding the system design process, and further optimization. To illustrate the methodology, we present a case-study of a lateral-directional flight control system for a fighter aircraft

  7. Models for Dynamic Applications

    DEFF Research Database (Denmark)

    Sales-Cruz, Mauricio; Morales Rodriguez, Ricardo; Heitzig, Martina

    2011-01-01

    This chapter covers aspects of the dynamic modelling and simulation of several complex operations that include a controlled blending tank, a direct methanol fuel cell that incorporates a multiscale model, a fluidised bed reactor, a standard chemical reactor and finally a polymerisation reactor...... be applied to formulate, analyse and solve these dynamic problems and how in the case of the fuel cell problem the model consists of coupledmeso and micro scale models. It is shown how data flows are handled between the models and how the solution is obtained within the modelling environment....

  8. Dynamic k-out-of-n system reliability with component partnership

    International Nuclear Information System (INIS)

    Coit, David W.; Chatwattanasiri, Nida; Wattanapongsakorn, Naruemon; Konak, Abdullah

    2015-01-01

    This paper describes a new k-out-of-n system reliability model that is appropriate for certain design problems when the minimum number of required components, k, changes dynamically in response to failures to maximize the utility of the available collection of functioning components. This new model shares some distinct similarities with weighted k-out-of-n models and for some problems they produce the same result. However, there are subtle and distinct differences, and in practice, there are some complex applications have not been properly explained or modeled by traditional or extended k-out-of-n system models. For this application, components are arranged in a k-out-of-n configuration of heterogeneous components with different performance levels. Component performance is indicated by a component-specific component partnership level; the fewer partners required to operate successfully implies higher performance. The components can work collectively with partners at the same level to maintain system reliability, or they can create a partnership group with components at higher performance levels which serve as replacements to provide the necessary number of working components. When components fail, the dynamic k-out-of-n configuration maintains reliability of the system with changing k by having components create partnerships with other components at the same level or above. To demonstrate the model, a system replacement maintenance policy based on a replacement interval variable is applied to an example system to obtain the optimal replacement time. - Highlights: • A new k-out-of-n system reliability model is presented. • Components can form partnerships with other components. • The new k-out-of-n model is presented with a dynamic or changing k. • The new model is for systems with components that must work together in a group

  9. 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

  10. Dynamic term structure models

    DEFF Research Database (Denmark)

    Andreasen, Martin Møller; Meldrum, Andrew

    This paper studies whether dynamic term structure models for US nominal bond yields should enforce the zero lower bound by a quadratic policy rate or a shadow rate specification. We address the question by estimating quadratic term structure models (QTSMs) and shadow rate models with at most four...

  11. Are there reliable constitutive laws for dynamic friction?

    Science.gov (United States)

    Woodhouse, Jim; Putelat, Thibaut; McKay, Andrew

    2015-09-28

    Structural vibration controlled by interfacial friction is widespread, ranging from friction dampers in gas turbines to the motion of violin strings. To predict, control or prevent such vibration, a constitutive description of frictional interactions is inevitably required. A variety of friction models are discussed to assess their scope and validity, in the light of constraints provided by different experimental observations. Three contrasting case studies are used to illustrate how predicted behaviour can be extremely sensitive to the choice of frictional constitutive model, and to explore possible experimental paths to discriminate between and calibrate dynamic friction models over the full parameter range needed for real applications. © 2015 The Author(s).

  12. Reliability physics and engineering time-to-failure modeling

    CERN Document Server

    McPherson, J W

    2013-01-01

    Reliability Physics and Engineering provides critically important information that is needed for designing and building reliable cost-effective products. Key features include:  ·       Materials/Device Degradation ·       Degradation Kinetics ·       Time-To-Failure Modeling ·       Statistical Tools ·       Failure-Rate Modeling ·       Accelerated Testing ·       Ramp-To-Failure Testing ·       Important Failure Mechanisms for Integrated Circuits ·       Important Failure Mechanisms for  Mechanical Components ·       Conversion of Dynamic  Stresses into Static Equivalents ·       Small Design Changes Producing Major Reliability Improvements ·       Screening Methods ·       Heat Generation and Dissipation ·       Sampling Plans and Confidence Intervals This textbook includes numerous example problems with solutions. Also, exercise problems along with the answers are included at the end of each chapter. Relia...

  13. Reliability of complex systems under dynamic conditions: A Bayesian multivariate degradation perspective

    International Nuclear Information System (INIS)

    Peng, Weiwen; Li, Yan-Feng; Mi, Jinhua; Yu, Le; Huang, Hong-Zhong

    2016-01-01

    Degradation analysis is critical to reliability assessment and operational management of complex systems. Two types of assumptions are often adopted for degradation analysis: (1) single degradation indicator and (2) constant external factors. However, modern complex systems are generally characterized as multiple functional and suffered from multiple failure modes due to dynamic operating conditions. In this paper, Bayesian degradation analysis of complex systems with multiple degradation indicators under dynamic conditions is investigated. Three practical engineering-driven issues are addressed: (1) to model various combinations of degradation indicators, a generalized multivariate hybrid degradation process model is proposed, which subsumes both monotonic and non-monotonic degradation processes models as special cases, (2) to study effects of external factors, two types of dynamic covariates are incorporated jointly, which include both environmental conditions and operating profiles, and (3) to facilitate degradation based reliability analysis, a serial of Bayesian strategy is constructed, which covers parameter estimation, factor-related degradation prediction, and unit-specific remaining useful life assessment. Finally, degradation analysis of a type of heavy machine tools is presented to demonstrate the application and performance of the proposed method. A comparison of the proposed model with a traditional model is studied as well in the example. - Highlights: • A generalized multivariate hybrid degradation process model is introduced. • Various types of dependent degradation processes can be modeled coherently. • The effects of environmental conditions and operating profiles are investigated. • Unit-specific RUL assessment is implemented through a two-step Bayesian method.

  14. Spatiotemporal Dynamics and Reliable Computations in Recurrent Spiking Neural Networks

    Science.gov (United States)

    Pyle, Ryan; Rosenbaum, Robert

    2017-01-01

    Randomly connected networks of excitatory and inhibitory spiking neurons provide a parsimonious model of neural variability, but are notoriously unreliable for performing computations. We show that this difficulty is overcome by incorporating the well-documented dependence of connection probability on distance. Spatially extended spiking networks exhibit symmetry-breaking bifurcations and generate spatiotemporal patterns that can be trained to perform dynamical computations under a reservoir computing framework.

  15. Spatiotemporal Dynamics and Reliable Computations in Recurrent Spiking Neural Networks.

    Science.gov (United States)

    Pyle, Ryan; Rosenbaum, Robert

    2017-01-06

    Randomly connected networks of excitatory and inhibitory spiking neurons provide a parsimonious model of neural variability, but are notoriously unreliable for performing computations. We show that this difficulty is overcome by incorporating the well-documented dependence of connection probability on distance. Spatially extended spiking networks exhibit symmetry-breaking bifurcations and generate spatiotemporal patterns that can be trained to perform dynamical computations under a reservoir computing framework.

  16. Human reliability data collection and modelling

    International Nuclear Information System (INIS)

    1991-09-01

    The main purpose of this document is to review and outline the current state-of-the-art of the Human Reliability Assessment (HRA) used for quantitative assessment of nuclear power plants safe and economical operation. Another objective is to consider Human Performance Indicators (HPI) which can alert plant manager and regulator to departures from states of normal and acceptable operation. These two objectives are met in the three sections of this report. The first objective has been divided into two areas, based on the location of the human actions being considered. That is, the modelling and data collection associated with control room actions are addressed first in chapter 1 while actions outside the control room (including maintenance) are addressed in chapter 2. Both chapters 1 and 2 present a brief outline of the current status of HRA for these areas, and major outstanding issues. Chapter 3 discusses HPI. Such performance indicators can signal, at various levels, changes in factors which influence human performance. The final section of this report consists of papers presented by the participants of the Technical Committee Meeting. A separate abstract was prepared for each of these papers. Refs, figs and tabs

  17. System reliability time-dependent models

    International Nuclear Information System (INIS)

    Debernardo, H.D.

    1991-06-01

    A probabilistic methodology for safety system technical specification evaluation was developed. The method for Surveillance Test Interval (S.T.I.) evaluation basically means an optimization of S.T.I. of most important system's periodically tested components. For Allowed Outage Time (A.O.T.) calculations, the method uses system reliability time-dependent models (A computer code called FRANTIC III). A new approximation, which was called Independent Minimal Cut Sets (A.C.I.), to compute system unavailability was also developed. This approximation is better than Rare Event Approximation (A.E.R.) and the extra computing cost is neglectible. A.C.I. was joined to FRANTIC III to replace A.E.R. on future applications. The case study evaluations verified that this methodology provides a useful probabilistic assessment of surveillance test intervals and allowed outage times for many plant components. The studied system is a typical configuration of nuclear power plant safety systems (two of three logic). Because of the good results, these procedures will be used by the Argentine nuclear regulatory authorities in evaluation of technical specification of Atucha I and Embalse nuclear power plant safety systems. (Author) [es

  18. Dynamic accelerator modeling

    International Nuclear Information System (INIS)

    Nishimura, Hiroshi.

    1993-05-01

    Object-Oriented Programming has been used extensively to model the LBL Advanced Light Source 1.5 GeV electron storage ring. This paper is on the present status of the class library construction with emphasis on a dynamic modeling

  19. Dynamic panel data models

    NARCIS (Netherlands)

    Bun, M.J.G.; Sarafidis, V.

    2013-01-01

    This Chapter reviews the recent literature on dynamic panel data models with a short time span and a large cross-section. Throughout the discussion we considerlinear models with additional endogenous covariates. First we give a broad overview of available inference methods placing emphasis on GMM.

  20. Reliability

    OpenAIRE

    Condon, David; Revelle, William

    2017-01-01

    Separating the signal in a test from the irrelevant noise is a challenge for all measurement. Low test reliability limits test validity, attenuates important relationships, and can lead to regression artifacts. Multiple approaches to the assessment and improvement of reliability are discussed. The advantages and disadvantages of several different approaches to reliability are considered. Practical advice on how to assess reliability using open source software is provided.

  1. Simple and reliable procedure for the evaluation of short-term dynamic processes in power systems

    Energy Technology Data Exchange (ETDEWEB)

    Popovic, D P

    1986-10-01

    An efficient approach is presented to the solution of the short-term dynamics model in power systems. It consists of an adequate algebraic treatment of the original system of nonlinear differential equations, using linearization, decomposition and Cauchy's formula. The simple difference equations obtained in this way are incorporated into a model of the electrical network, which is of a low order compared to the ones usually used. Newton's method is applied to the model formed in this way, which leads to a simple and reliable iterative procedure. The characteristics of the procedure developed are demonstrated on examples of transient stability analysis of real power systems. 12 refs.

  2. Modeling dynamic swarms

    KAUST Repository

    Ghanem, Bernard

    2013-01-01

    This paper proposes the problem of modeling video sequences of dynamic swarms (DSs). We define a DS as a large layout of stochastically repetitive spatial configurations of dynamic objects (swarm elements) whose motions exhibit local spatiotemporal interdependency and stationarity, i.e., the motions are similar in any small spatiotemporal neighborhood. Examples of DS abound in nature, e.g., herds of animals and flocks of birds. To capture the local spatiotemporal properties of the DS, we present a probabilistic model that learns both the spatial layout of swarm elements (based on low-level image segmentation) and their joint dynamics that are modeled as linear transformations. To this end, a spatiotemporal neighborhood is associated with each swarm element, in which local stationarity is enforced both spatially and temporally. We assume that the prior on the swarm dynamics is distributed according to an MRF in both space and time. Embedding this model in a MAP framework, we iterate between learning the spatial layout of the swarm and its dynamics. We learn the swarm transformations using ICM, which iterates between estimating these transformations and updating their distribution in the spatiotemporal neighborhoods. We demonstrate the validity of our method by conducting experiments on real and synthetic video sequences. Real sequences of birds, geese, robot swarms, and pedestrians evaluate the applicability of our model to real world data. © 2012 Elsevier Inc. All rights reserved.

  3. Structural hybrid reliability index and its convergent solving method based on random–fuzzy–interval reliability model

    OpenAIRE

    Hai An; Ling Zhou; Hui Sun

    2016-01-01

    Aiming to resolve the problems of a variety of uncertainty variables that coexist in the engineering structure reliability analysis, a new hybrid reliability index to evaluate structural hybrid reliability, based on the random–fuzzy–interval model, is proposed in this article. The convergent solving method is also presented. First, the truncated probability reliability model, the fuzzy random reliability model, and the non-probabilistic interval reliability model are introduced. Then, the new...

  4. Usage models in reliability assessment of software-based systems

    Energy Technology Data Exchange (ETDEWEB)

    Haapanen, P.; Pulkkinen, U. [VTT Automation, Espoo (Finland); Korhonen, J. [VTT Electronics, Espoo (Finland)

    1997-04-01

    This volume in the OHA-project report series deals with the statistical reliability assessment of software based systems on the basis of dynamic test results and qualitative evidence from the system design process. Other reports to be published later on in the OHA-project report series will handle the diversity requirements in safety critical software-based systems, generation of test data from operational profiles and handling of programmable automation in plant PSA-studies. In this report the issues related to the statistical testing and especially automated test case generation are considered. The goal is to find an efficient method for building usage models for the generation of statistically significant set of test cases and to gather practical experiences from this method by applying it in a case study. The scope of the study also includes the tool support for the method, as the models may grow quite large and complex. (32 refs., 30 figs.).

  5. Usage models in reliability assessment of software-based systems

    International Nuclear Information System (INIS)

    Haapanen, P.; Pulkkinen, U.; Korhonen, J.

    1997-04-01

    This volume in the OHA-project report series deals with the statistical reliability assessment of software based systems on the basis of dynamic test results and qualitative evidence from the system design process. Other reports to be published later on in the OHA-project report series will handle the diversity requirements in safety critical software-based systems, generation of test data from operational profiles and handling of programmable automation in plant PSA-studies. In this report the issues related to the statistical testing and especially automated test case generation are considered. The goal is to find an efficient method for building usage models for the generation of statistically significant set of test cases and to gather practical experiences from this method by applying it in a case study. The scope of the study also includes the tool support for the method, as the models may grow quite large and complex. (32 refs., 30 figs.)

  6. Building and integrating reliability models in a Reliability-Centered-Maintenance approach

    International Nuclear Information System (INIS)

    Verite, B.; Villain, B.; Venturini, V.; Hugonnard, S.; Bryla, P.

    1998-03-01

    Electricite de France (EDF) has recently developed its OMF-Structures method, designed to optimize preventive maintenance of passive structures such as pipes and support, based on risk. In particular, reliability performances of components need to be determined; it is a two-step process, consisting of a qualitative sort followed by a quantitative evaluation, involving two types of models. Initially, degradation models are widely used to exclude some components from the field of preventive maintenance. The reliability of the remaining components is then evaluated by means of quantitative reliability models. The results are then included in a risk indicator that is used to directly optimize preventive maintenance tasks. (author)

  7. Reliability Model of Power Transformer with ONAN Cooling

    OpenAIRE

    M. Sefidgaran; M. Mirzaie; A. Ebrahimzadeh

    2010-01-01

    Reliability of a power system is considerably influenced by its equipments. Power transformers are one of the most critical and expensive equipments of a power system and their proper functions are vital for the substations and utilities. Therefore, reliability model of power transformer is very important in the risk assessment of the engineering systems. This model shows the characteristics and functions of a transformer in the power system. In this paper the reliability model...

  8. Corruption dynamics model

    Science.gov (United States)

    Malafeyev, O. A.; Nemnyugin, S. A.; Rylow, D.; Kolpak, E. P.; Awasthi, Achal

    2017-07-01

    The corruption dynamics is analyzed by means of the lattice model which is similar to the three-dimensional Ising model. Agents placed at nodes of the corrupt network periodically choose to perfom or not to perform the act of corruption at gain or loss while making decisions based on the process history. The gain value and its dynamics are defined by means of the Markov stochastic process modelling with parameters established in accordance with the influence of external and individual factors on the agent's gain. The model is formulated algorithmically and is studied by means of the computer simulation. Numerical results are obtained which demonstrate asymptotic behaviour of the corruption network under various conditions.

  9. Adaptive numerical modeling of dynamic crack propagation

    International Nuclear Information System (INIS)

    Adouani, H.; Tie, B.; Berdin, C.; Aubry, D.

    2006-01-01

    We propose an adaptive numerical strategy that aims at developing reliable and efficient numerical tools to model dynamic crack propagation and crack arrest. We use the cohesive zone theory as behavior of interface-type elements to model crack. Since the crack path is generally unknown beforehand, adaptive meshing is proposed to model the dynamic crack propagation. The dynamic study requires the development of specific solvers for time integration. As both geometry and finite element mesh of the studied structure evolve in time during transient analysis, the stability behavior of dynamic solver becomes a major concern. For this purpose, we use the space-time discontinuous Galerkin finite element method, well-known to provide a natural framework to manage meshes that evolve in time. As an important result, we prove that the space-time discontinuous Galerkin solver is unconditionally stable, when the dynamic crack propagation is modeled by the cohesive zone theory, which is highly non-linear. (authors)

  10. DYNAMIC LOAD DAMPER MODELING

    Directory of Open Access Journals (Sweden)

    Loktev Aleksey Alekseevich

    2013-01-01

    Full Text Available The authors present their findings associated with their modeling of a dynamic load damper. According to the authors, the damper is to be installed onto a structure or its element that may be exposed to impact, vibration or any other dynamic loading. The damper is composed of paralleled or consecutively connected viscous and elastic elements. The authors study the influence of viscosity and elasticity parameters of the damper produced onto the regular displacement of points of the structure to be protected and onto the regular acceleration transmitted immediately from the damper to the elements positioned below it.

  11. Characterizing and Modeling Citation Dynamics

    Science.gov (United States)

    Eom, Young-Ho; Fortunato, Santo

    2011-01-01

    Citation distributions are crucial for the analysis and modeling of the activity of scientists. We investigated bibliometric data of papers published in journals of the American Physical Society, searching for the type of function which best describes the observed citation distributions. We used the goodness of fit with Kolmogorov-Smirnov statistics for three classes of functions: log-normal, simple power law and shifted power law. The shifted power law turns out to be the most reliable hypothesis for all citation networks we derived, which correspond to different time spans. We find that citation dynamics is characterized by bursts, usually occurring within a few years since publication of a paper, and the burst size spans several orders of magnitude. We also investigated the microscopic mechanisms for the evolution of citation networks, by proposing a linear preferential attachment with time dependent initial attractiveness. The model successfully reproduces the empirical citation distributions and accounts for the presence of citation bursts as well. PMID:21966387

  12. Exact combinatorial reliability analysis of dynamic systems with sequence-dependent failures

    International Nuclear Information System (INIS)

    Xing Liudong; Shrestha, Akhilesh; Dai Yuanshun

    2011-01-01

    Many real-life fault-tolerant systems are subjected to sequence-dependent failure behavior, in which the order in which the fault events occur is important to the system reliability. Such systems can be modeled by dynamic fault trees (DFT) with priority-AND (pAND) gates. Existing approaches for the reliability analysis of systems subjected to sequence-dependent failures are typically state-space-based, simulation-based or inclusion-exclusion-based methods. Those methods either suffer from the state-space explosion problem or require long computation time especially when results with high degree of accuracy are desired. In this paper, an analytical method based on sequential binary decision diagrams is proposed. The proposed approach can analyze the exact reliability of non-repairable dynamic systems subjected to the sequence-dependent failure behavior. Also, the proposed approach is combinatorial and is applicable for analyzing systems with any arbitrary component time-to-failure distributions. The application and advantages of the proposed approach are illustrated through analysis of several examples. - Highlights: → We analyze the sequence-dependent failure behavior using combinatorial models. → The method has no limitation on the type of time-to-failure distributions. → The method is analytical and based on sequential binary decision diagrams (SBDD). → The method is computationally more efficient than existing methods.

  13. Dynamic reliability and risk assessment of the accident localization system of the Ignalina NPP RBMK-1500 reactor

    International Nuclear Information System (INIS)

    Kopustinskas, V.; Augutis, J.; Rimkevicius, S.

    2005-01-01

    The paper presents reliability and risk analysis of the RBMK-1500 reactor accident localization system (ALS) (confinement), which prevents radioactive releases to the environment. Reliability of the system was estimated and compared by two methods: the conventional fault tree method and an innovative dynamic reliability model, based on stochastic differential equations. Frequency of radioactive release through ALS was also estimated. The results of the study indicate that conventional fault tree modeling techniques in this case apply high degree of conservatism in the system reliability estimates. One of the purposes of the ALS reliability study was to demonstrate advantages of the dynamic reliability analysis against the conventional fault/event tree methods. The Markovian framework to deal with dynamic aspects of system behavior is presented. Although not analyzed in detail, the framework is also capable of accounting for non-constant component failure rates. Computational methods are proposed to solve stochastic differential equations, including analytical solution, which is possible only for relatively small and simple systems. Other numerical methods, like Monte Carlo and numerical schemes of differential equations are analyzed and compared. The study is finalized with concluding remarks regarding both the studied system reliability and computational methods used

  14. Rich Interfaces for Dependability: Compositional Methods for Dynamic Fault Trees and Arcade models

    NARCIS (Netherlands)

    Boudali, H.; Crouzen, Pepijn; Haverkort, Boudewijn R.H.M.; Kuntz, G.W.M.; Stoelinga, Mariëlle Ida Antoinette

    This paper discusses two behavioural interfaces for reliability analysis: dynamic fault trees, which model the system reliability in terms of the reliability of its components and Arcade, which models the system reliability at an architectural level. For both formalisms, the reliability is analyzed

  15. Time domain series system definition and gear set reliability modeling

    International Nuclear Information System (INIS)

    Xie, Liyang; Wu, Ningxiang; Qian, Wenxue

    2016-01-01

    Time-dependent multi-configuration is a typical feature for mechanical systems such as gear trains and chain drives. As a series system, a gear train is distinct from a traditional series system, such as a chain, in load transmission path, system-component relationship, system functioning manner, as well as time-dependent system configuration. Firstly, the present paper defines time-domain series system to which the traditional series system reliability model is not adequate. Then, system specific reliability modeling technique is proposed for gear sets, including component (tooth) and subsystem (tooth-pair) load history description, material priori/posterior strength expression, time-dependent and system specific load-strength interference analysis, as well as statistically dependent failure events treatment. Consequently, several system reliability models are developed for gear sets with different tooth numbers in the scenario of tooth root material ultimate tensile strength failure. The application of the models is discussed in the last part, and the differences between the system specific reliability model and the traditional series system reliability model are illustrated by virtue of several numerical examples. - Highlights: • A new type of series system, i.e. time-domain multi-configuration series system is defined, that is of great significance to reliability modeling. • Multi-level statistical analysis based reliability modeling method is presented for gear transmission system. • Several system specific reliability models are established for gear set reliability estimation. • The differences between the traditional series system reliability model and the new model are illustrated.

  16. Models on reliability of non-destructive testing

    International Nuclear Information System (INIS)

    Simola, K.; Pulkkinen, U.

    1998-01-01

    The reliability of ultrasonic inspections has been studied in e.g. international PISC (Programme for the Inspection of Steel Components) exercises. These exercises have produced a large amount of information on the effect of various factors on the reliability of inspections. The information obtained from reliability experiments are used to model the dependency of flaw detection probability on various factors and to evaluate the performance of inspection equipment, including the sizing accuracy. The information from experiments is utilised in a most effective way when mathematical models are applied. Here, some statistical models for reliability of non-destructive tests are introduced. In order to demonstrate the use of inspection reliability models, they have been applied to the inspection results of intergranular stress corrosion cracking (IGSCC) type flaws in PISC III exercise (PISC 1995). The models are applied to both flaw detection frequency data of all inspection teams and to flaw sizing data of one participating team. (author)

  17. Dynamic wake meandering modeling

    Energy Technology Data Exchange (ETDEWEB)

    Larsen, Gunner C.; Aagaard Madsen, H.; Bingoel, F. (and others)

    2007-06-15

    We present a consistent, physically based theory for the wake meandering phenomenon, which we consider of crucial importance for the overall description of wind turbine loadings in wind farms. In its present version the model is confined to single wake situations. The model philosophy does, however, have the potential to include also mutual wake interaction phenomenons. The basic conjecture behind the dynamic wake meandering model is that wake transportation in the atmospheric boundary layer is driven by the large scale lateral- and vertical turbulence components. Based on this conjecture a stochastic model of the downstream wake meandering is formulated. In addition to the kinematic formulation of the dynamics of the 'meandering frame of reference', models characterizing the mean wake deficit as well as the added wake turbulence, described in the meandering frame of reference, are an integrated part the model complex. For design applications, the computational efficiency of wake deficit prediction is a key issue. Two computationally low cost models are developed for this purpose. The character of the added wake turbulence, generated by the up-stream turbine in the form of shed and trailed vorticity, has been approached by analytical as well as by numerical studies. The dynamic wake meandering philosophy has been verified by comparing model predictions with extensive full-scale measurements. These comparisons have demonstrated good agreement, both qualitatively and quantitatively, concerning both flow characteristics and turbine load characteristics. Contrary to previous attempts to model wake loading, the dynamic wake meandering approach opens for a unifying description in the sense that turbine power and load aspects can be treated simultaneously. This capability is a direct and attractive consequence of the model being based on the underlying physical process, and it potentially opens for optimization of wind farm topology, of wind farm operation as

  18. Reliability modelling and simulation of switched linear system ...

    African Journals Online (AJOL)

    Reliability modelling and simulation of switched linear system control using temporal databases. ... design of fault-tolerant real-time switching systems control and modelling embedded micro-schedulers for complex systems maintenance.

  19. A possibilistic uncertainty model in classical reliability theory

    International Nuclear Information System (INIS)

    De Cooman, G.; Capelle, B.

    1994-01-01

    The authors argue that a possibilistic uncertainty model can be used to represent linguistic uncertainty about the states of a system and of its components. Furthermore, the basic properties of the application of this model to classical reliability theory are studied. The notion of the possibilistic reliability of a system or a component is defined. Based on the concept of a binary structure function, the important notion of a possibilistic function is introduced. It allows to calculate the possibilistic reliability of a system in terms of the possibilistic reliabilities of its components

  20. Dynamical chiral bag model

    International Nuclear Information System (INIS)

    Colanero, K.; Chu, M.-C.

    2002-01-01

    We study a dynamical chiral bag model, in which massless fermions are confined within an impenetrable but movable bag coupled to meson fields. The self-consistent motion of the bag is obtained by solving the equations of motion exactly assuming spherical symmetry. When the bag interacts with an external meson wave we find three different kinds of resonances: fermionic, geometric, and σ resonances. We discuss the phenomenological implications of our results

  1. Model for macroevolutionary dynamics.

    Science.gov (United States)

    Maruvka, Yosef E; Shnerb, Nadav M; Kessler, David A; Ricklefs, Robert E

    2013-07-02

    The highly skewed distribution of species among genera, although challenging to macroevolutionists, provides an opportunity to understand the dynamics of diversification, including species formation, extinction, and morphological evolution. Early models were based on either the work by Yule [Yule GU (1925) Philos Trans R Soc Lond B Biol Sci 213:21-87], which neglects extinction, or a simple birth-death (speciation-extinction) process. Here, we extend the more recent development of a generic, neutral speciation-extinction (of species)-origination (of genera; SEO) model for macroevolutionary dynamics of taxon diversification. Simulations show that deviations from the homogeneity assumptions in the model can be detected in species-per-genus distributions. The SEO model fits observed species-per-genus distributions well for class-to-kingdom-sized taxonomic groups. The model's predictions for the appearance times (the time of the first existing species) of the taxonomic groups also approximately match estimates based on molecular inference and fossil records. Unlike estimates based on analyses of phylogenetic reconstruction, fitted extinction rates for large clades are close to speciation rates, consistent with high rates of species turnover and the relatively slow change in diversity observed in the fossil record. Finally, the SEO model generally supports the consistency of generic boundaries based on morphological differences between species and provides a comparator for rates of lineage splitting and morphological evolution.

  2. A dynamic particle filter-support vector regression method for reliability prediction

    International Nuclear Information System (INIS)

    Wei, Zhao; Tao, Tao; ZhuoShu, Ding; Zio, Enrico

    2013-01-01

    Support vector regression (SVR) has been applied to time series prediction and some works have demonstrated the feasibility of its use to forecast system reliability. For accuracy of reliability forecasting, the selection of SVR's parameters is important. The existing research works on SVR's parameters selection divide the example dataset into training and test subsets, and tune the parameters on the training data. However, these fixed parameters can lead to poor prediction capabilities if the data of the test subset differ significantly from those of training. Differently, the novel method proposed in this paper uses particle filtering to estimate the SVR model parameters according to the whole measurement sequence up to the last observation instance. By treating the SVR training model as the observation equation of a particle filter, our method allows updating the SVR model parameters dynamically when a new observation comes. Because of the adaptability of the parameters to dynamic data pattern, the new PF–SVR method has superior prediction performance over that of standard SVR. Four application results show that PF–SVR is more robust than SVR to the decrease of the number of training data and the change of initial SVR parameter values. Also, even if there are trends in the test data different from those in the training data, the method can capture the changes, correct the SVR parameters and obtain good predictions. -- Highlights: •A dynamic PF–SVR method is proposed to predict the system reliability. •The method can adjust the SVR parameters according to the change of data. •The method is robust to the size of training data and initial parameter values. •Some cases based on both artificial and real data are studied. •PF–SVR shows superior prediction performance over standard SVR

  3. Development of a Conservative Model Validation Approach for Reliable Analysis

    Science.gov (United States)

    2015-01-01

    CIE 2015 August 2-5, 2015, Boston, Massachusetts, USA [DRAFT] DETC2015-46982 DEVELOPMENT OF A CONSERVATIVE MODEL VALIDATION APPROACH FOR RELIABLE...obtain a conservative simulation model for reliable design even with limited experimental data. Very little research has taken into account the...3, the proposed conservative model validation is briefly compared to the conventional model validation approach. Section 4 describes how to account

  4. RETRAN dynamic slip model

    International Nuclear Information System (INIS)

    McFadden, J.H.; Paulsen, M.P.; Gose, G.C.

    1981-01-01

    Thermal-hydraulic codes in general use for system calculations are based on extensive analyses of loss-of-coolant accidents following the postulated rupture of a large coolant pipe. In this study, time-dependent equation for the slip velocity in a two-phase flow condition has been incorporated into the RETRAN-02 computer code. This model addition was undertaken to remove a limitation in RETRAN-01 associated with the homogeneous equilibrium mixture model. The dynamic slip equation was derived from a set of two-fluid conservation equations. 18 refs

  5. Developing Fast and Reliable Flood Models

    DEFF Research Database (Denmark)

    Thrysøe, Cecilie; Toke, Jens; Borup, Morten

    2016-01-01

    . A surrogate model is set up for a case study area in Aarhus, Denmark, to replace a MIKE FLOOD model. The drainage surrogates are able to reproduce the MIKE URBAN results for a set of rain inputs. The coupled drainage-surface surrogate model lacks details in the surface description which reduces its overall...... accuracy. The model shows no instability, hence larger time steps can be applied, which reduces the computational time by more than a factor 1400. In conclusion, surrogate models show great potential for usage in urban water modelling....

  6. Contact dynamics math model

    Science.gov (United States)

    Glaese, John R.; Tobbe, Patrick A.

    1986-01-01

    The Space Station Mechanism Test Bed consists of a hydraulically driven, computer controlled six degree of freedom (DOF) motion system with which docking, berthing, and other mechanisms can be evaluated. Measured contact forces and moments are provided to the simulation host computer to enable representation of orbital contact dynamics. This report describes the development of a generalized math model which represents the relative motion between two rigid orbiting vehicles. The model allows motion in six DOF for each body, with no vehicle size limitation. The rotational and translational equations of motion are derived. The method used to transform the forces and moments from the sensor location to the vehicles' centers of mass is also explained. Two math models of docking mechanisms, a simple translational spring and the Remote Manipulator System end effector, are presented along with simulation results. The translational spring model is used in an attempt to verify the simulation with compensated hardware in the loop results.

  7. Quantitative dynamic reliability evaluation of AP1000 passive safety systems by using FMEA and GO-FLOW methodology

    International Nuclear Information System (INIS)

    Hashim Muhammad; Yoshikawa, Hidekazu; Matsuoka, Takeshi; Yang Ming

    2014-01-01

    The passive safety systems utilized in advanced pressurized water reactor (PWR) design such as AP1000 should be more reliable than that of active safety systems of conventional PWR by less possible opportunities of hardware failures and human errors (less human intervention). The objectives of present study are to evaluate the dynamic reliability of AP1000 plant in order to check the effectiveness of passive safety systems by comparing the reliability-related issues with that of active safety systems in the event of the big accidents. How should the dynamic reliability of passive safety systems properly evaluated? And then what will be the comparison of reliability results of AP1000 passive safety systems with the active safety systems of conventional PWR. For this purpose, a single loop model of AP1000 passive core cooling system (PXS) and passive containment cooling system (PCCS) are assumed separately for quantitative reliability evaluation. The transient behaviors of these passive safety systems are taken under the large break loss-of-coolant accident in the cold leg. The analysis is made by utilizing the qualitative method failure mode and effect analysis in order to identify the potential failure mode and success-oriented reliability analysis tool called GO-FLOW for quantitative reliability evaluation. The GO-FLOW analysis has been conducted separately for PXS and PCCS systems under the same accident. The analysis results show that reliability of AP1000 passive safety systems (PXS and PCCS) is increased due to redundancies and diversity of passive safety subsystems and components, and four stages automatic depressurization system is the key subsystem for successful actuation of PXS and PCCS system. The reliability results of PCCS system of AP1000 are more reliable than that of the containment spray system of conventional PWR. And also GO-FLOW method can be utilized for reliability evaluation of passive safety systems. (author)

  8. Experiment research on cognition reliability model of nuclear power plant

    International Nuclear Information System (INIS)

    Zhao Bingquan; Fang Xiang

    1999-01-01

    The objective of the paper is to improve the reliability of operation on real nuclear power plant of operators through the simulation research to the cognition reliability of nuclear power plant operators. The research method of the paper is to make use of simulator of nuclear power plant as research platform, to take present international research model of reliability of human cognition based on three-parameter Weibull distribution for reference, to develop and get the research model of Chinese nuclear power plant operators based on two-parameter Weibull distribution. By making use of two-parameter Weibull distribution research model of cognition reliability, the experiments about the cognition reliability of nuclear power plant operators have been done. Compared with the results of other countries such USA and Hungary, the same results can be obtained, which can do good to the safety operation of nuclear power plant

  9. An interval-valued reliability model with bounded failure rates

    DEFF Research Database (Denmark)

    Kozine, Igor; Krymsky, Victor

    2012-01-01

    The approach to deriving interval-valued reliability measures described in this paper is distinctive from other imprecise reliability models in that it overcomes the issue of having to impose an upper bound on time to failure. It rests on the presupposition that a constant interval-valued failure...... rate is known possibly along with other reliability measures, precise or imprecise. The Lagrange method is used to solve the constrained optimization problem to derive new reliability measures of interest. The obtained results call for an exponential-wise approximation of failure probability density...

  10. Reliability Estimation of Aero-engine Based on Mixed Weibull Distribution Model

    Science.gov (United States)

    Yuan, Zhongda; Deng, Junxiang; Wang, Dawei

    2018-02-01

    Aero-engine is a complex mechanical electronic system, based on analysis of reliability of mechanical electronic system, Weibull distribution model has an irreplaceable role. Till now, only two-parameter Weibull distribution model and three-parameter Weibull distribution are widely used. Due to diversity of engine failure modes, there is a big error with single Weibull distribution model. By contrast, a variety of engine failure modes can be taken into account with mixed Weibull distribution model, so it is a good statistical analysis model. Except the concept of dynamic weight coefficient, in order to make reliability estimation result more accurately, three-parameter correlation coefficient optimization method is applied to enhance Weibull distribution model, thus precision of mixed distribution reliability model is improved greatly. All of these are advantageous to popularize Weibull distribution model in engineering applications.

  11. Analytical modeling of nuclear power station operator reliability

    International Nuclear Information System (INIS)

    Sabri, Z.A.; Husseiny, A.A.

    1979-01-01

    The operator-plant interface is a critical component of power stations which requires the formulation of mathematical models to be applied in plant reliability analysis. The human model introduced here is based on cybernetic interactions and allows for use of available data from psychological experiments, hot and cold training and normal operation. The operator model is identified and integrated in the control and protection systems. The availability and reliability are given for different segments of the operator task and for specific periods of the operator life: namely, training, operation and vigilance or near retirement periods. The results can be easily and directly incorporated in system reliability analysis. (author)

  12. Reliability modeling of Clinch River breeder reactor electrical shutdown systems

    International Nuclear Information System (INIS)

    Schatz, R.A.; Duetsch, K.L.

    1974-01-01

    The initial simulation of the probabilistic properties of the Clinch River Breeder Reactor Plant (CRBRP) electrical shutdown systems is described. A model of the reliability (and availability) of the systems is presented utilizing Success State and continuous-time, discrete state Markov modeling techniques as significant elements of an overall reliability assessment process capable of demonstrating the achievement of program goals. This model is examined for its sensitivity to safe/unsafe failure rates, sybsystem redundant configurations, test and repair intervals, monitoring by reactor operators; and the control exercised over system reliability by design modifications and the selection of system operating characteristics. (U.S.)

  13. Modeling and Forecasting (Un)Reliable Realized Covariances for More Reliable Financial Decisions

    DEFF Research Database (Denmark)

    Bollerslev, Tim; Patton, Andrew J.; Quaedvlieg, Rogier

    We propose a new framework for modeling and forecasting common financial risks based on (un)reliable realized covariance measures constructed from high-frequency intraday data. Our new approach explicitly incorporates the effect of measurement errors and time-varying attenuation biases into the c......We propose a new framework for modeling and forecasting common financial risks based on (un)reliable realized covariance measures constructed from high-frequency intraday data. Our new approach explicitly incorporates the effect of measurement errors and time-varying attenuation biases...

  14. Models for Battery Reliability and Lifetime

    Energy Technology Data Exchange (ETDEWEB)

    Smith, K.; Wood, E.; Santhanagopalan, S.; Kim, G. H.; Neubauer, J.; Pesaran, A.

    2014-03-01

    Models describing battery degradation physics are needed to more accurately understand how battery usage and next-generation battery designs can be optimized for performance and lifetime. Such lifetime models may also reduce the cost of battery aging experiments and shorten the time required to validate battery lifetime. Models for chemical degradation and mechanical stress are reviewed. Experimental analysis of aging data from a commercial iron-phosphate lithium-ion (Li-ion) cell elucidates the relative importance of several mechanical stress-induced degradation mechanisms.

  15. RELIABILITY MODELING BASED ON INCOMPLETE DATA: OIL PUMP APPLICATION

    Directory of Open Access Journals (Sweden)

    Ahmed HAFAIFA

    2014-07-01

    Full Text Available The reliability analysis for industrial maintenance is now increasingly demanded by the industrialists in the world. Indeed, the modern manufacturing facilities are equipped by data acquisition and monitoring system, these systems generates a large volume of data. These data can be used to infer future decisions affecting the health facilities. These data can be used to infer future decisions affecting the state of the exploited equipment. However, in most practical cases the data used in reliability modelling are incomplete or not reliable. In this context, to analyze the reliability of an oil pump, this work proposes to examine and treat the incomplete, incorrect or aberrant data to the reliability modeling of an oil pump. The objective of this paper is to propose a suitable methodology for replacing the incomplete data using a regression method.

  16. The general dynamic model

    DEFF Research Database (Denmark)

    Borregaard, Michael K.; Matthews, Thomas J.; Whittaker, Robert James

    2016-01-01

    Aim: Island biogeography focuses on understanding the processes that underlie a set of well-described patterns on islands, but it lacks a unified theoretical framework for integrating these processes. The recently proposed general dynamic model (GDM) of oceanic island biogeography offers a step...... towards this goal. Here, we present an analysis of causality within the GDM and investigate its potential for the further development of island biogeographical theory. Further, we extend the GDM to include subduction-based island arcs and continental fragment islands. Location: A conceptual analysis...... of evolutionary processes in simulations derived from the mechanistic assumptions of the GDM corresponded broadly to those initially suggested, with the exception of trends in extinction rates. Expanding the model to incorporate different scenarios of island ontogeny and isolation revealed a sensitivity...

  17. MODELING HUMAN RELIABILITY ANALYSIS USING MIDAS

    Energy Technology Data Exchange (ETDEWEB)

    Ronald L. Boring; Donald D. Dudenhoeffer; Bruce P. Hallbert; Brian F. Gore

    2006-05-01

    This paper summarizes an emerging collaboration between Idaho National Laboratory and NASA Ames Research Center regarding the utilization of high-fidelity MIDAS simulations for modeling control room crew performance at nuclear power plants. The key envisioned uses for MIDAS-based control room simulations are: (i) the estimation of human error with novel control room equipment and configurations, (ii) the investigative determination of risk significance in recreating past event scenarios involving control room operating crews, and (iii) the certification of novel staffing levels in control rooms. It is proposed that MIDAS serves as a key component for the effective modeling of risk in next generation control rooms.

  18. Plant and control system reliability and risk model

    International Nuclear Information System (INIS)

    Niemelae, I.M.

    1986-01-01

    A new reliability modelling technique for control systems and plants is demonstrated. It is based on modified boolean algebra and it has been automated into an efficient computer code called RELVEC. The code is useful for getting an overall view of the reliability parameters or for an in-depth reliability analysis, which is essential in risk analysis, where the model must be capable of answering to specific questions like: 'What is the probability of this temperature limiter to provide a false alarm', or 'what is the probability of air pressure in this subsystem to drop below lower limit'. (orig./DG)

  19. Dynamic Self-Adaptive Reliability Control for Electric-Hydraulic Systems

    Directory of Open Access Journals (Sweden)

    Yi Wan

    2015-02-01

    Full Text Available The high-speed electric-hydraulic proportional control is a new development of the hydraulic control technique with high reliability, low cost, efficient energy, and easy maintenance; it is widely used in industrial manufacturing and production. However, there are still some unresolved challenges, the most notable being the requirements of high stability and real-time by the classical control algorithm due to its high nonlinear characteristics. We propose a dynamic self-adaptive mixed control method based on the least squares support vector machine (LSSVM and the genetic algorithm for high-speed electric-hydraulic proportional control systems in this paper; LSSVM is used to identify and adjust online a nonlinear electric-hydraulic proportional system, and the genetic algorithm is used to optimize the control law of the controlled system and dynamic self-adaptive internal model control and predictive control are implemented by using the mixed intelligent method. The internal model and the inverse control model are online adjusted together. At the same time, a time-dependent Hankel matrix is constructed based on sample data; thus finite dimensional solution can be optimized on finite dimensional space. The results of simulation experiments show that the dynamic characteristics are greatly improved by the mixed intelligent control strategy, and good tracking and high stability are met in condition of high frequency response.

  20. Improving Reliability of Embedded Systems through Dynamic Memory Manager Optimization using Grammatical Evolution

    OpenAIRE

    Colmenar, J. Manuel; Risco-Martin, Jose L.; Atienza Alonso, David; Garnica, Oscar; Hidalgo, Jose I.; Lanchares, Juan

    2010-01-01

    Technology scaling has offered advantages to embedded systems, such as increased performance, more available memory and reduced energy consumption. However, scaling also brings a number of problems like reliability degradation mechanisms. The intensive activity of devices and high operating temperatures are key factors for reliability degradation in latest technology nodes. Focusing on embedded systems, the memory is prone to suffer reliability problems due to the intensive use of dynamic mem...

  1. Quantitative metal magnetic memory reliability modeling for welded joints

    Science.gov (United States)

    Xing, Haiyan; Dang, Yongbin; Wang, Ben; Leng, Jiancheng

    2016-03-01

    Metal magnetic memory(MMM) testing has been widely used to detect welded joints. However, load levels, environmental magnetic field, and measurement noises make the MMM data dispersive and bring difficulty to quantitative evaluation. In order to promote the development of quantitative MMM reliability assessment, a new MMM model is presented for welded joints. Steel Q235 welded specimens are tested along the longitudinal and horizontal lines by TSC-2M-8 instrument in the tensile fatigue experiments. The X-ray testing is carried out synchronously to verify the MMM results. It is found that MMM testing can detect the hidden crack earlier than X-ray testing. Moreover, the MMM gradient vector sum K vs is sensitive to the damage degree, especially at early and hidden damage stages. Considering the dispersion of MMM data, the K vs statistical law is investigated, which shows that K vs obeys Gaussian distribution. So K vs is the suitable MMM parameter to establish reliability model of welded joints. At last, the original quantitative MMM reliability model is first presented based on the improved stress strength interference theory. It is shown that the reliability degree R gradually decreases with the decreasing of the residual life ratio T, and the maximal error between prediction reliability degree R 1 and verification reliability degree R 2 is 9.15%. This presented method provides a novel tool of reliability testing and evaluating in practical engineering for welded joints.

  2. Tracking reliability for space cabin-borne equipment in development by Crow model.

    Science.gov (United States)

    Chen, J D; Jiao, S J; Sun, H L

    2001-12-01

    Objective. To study and track the reliability growth of manned spaceflight cabin-borne equipment in the course of its development. Method. A new technique of reliability growth estimation and prediction, which is composed of the Crow model and test data conversion (TDC) method was used. Result. The estimation and prediction value of the reliability growth conformed to its expectations. Conclusion. The method could dynamically estimate and predict the reliability of the equipment by making full use of various test information in the course of its development. It offered not only a possibility of tracking the equipment reliability growth, but also the reference for quality control in manned spaceflight cabin-borne equipment design and development process.

  3. Dynamic Linear Models with R

    CERN Document Server

    Campagnoli, Patrizia; Petris, Giovanni

    2009-01-01

    State space models have gained tremendous popularity in as disparate fields as engineering, economics, genetics and ecology. Introducing general state space models, this book focuses on dynamic linear models, emphasizing their Bayesian analysis. It illustrates the fundamental steps needed to use dynamic linear models in practice, using R package.

  4. Software reliability growth model for safety systems of nuclear reactor

    International Nuclear Information System (INIS)

    Thirugnana Murthy, D.; Murali, N.; Sridevi, T.; Satya Murty, S.A.V.; Velusamy, K.

    2014-01-01

    The demand for complex software systems has increased more rapidly than the ability to design, implement, test, and maintain them, and the reliability of software systems has become a major concern for our, modern society.Software failures have impaired several high visibility programs in space, telecommunications, defense and health industries. Besides the costs involved, it setback the projects. The ways of quantifying it and using it for improvement and control of the software development and maintenance process. This paper discusses need for systematic approaches for measuring and assuring software reliability which is a major share of project development resources. It covers the reliability models with the concern on 'Reliability Growth'. It includes data collection on reliability, statistical estimation and prediction, metrics and attributes of product architecture, design, software development, and the operational environment. Besides its use for operational decisions like deployment, it includes guiding software architecture, development, testing and verification and validation. (author)

  5. A Reliability Based Model for Wind Turbine Selection

    Directory of Open Access Journals (Sweden)

    A.K. Rajeevan

    2013-06-01

    Full Text Available A wind turbine generator output at a specific site depends on many factors, particularly cut- in, rated and cut-out wind speed parameters. Hence power output varies from turbine to turbine. The objective of this paper is to develop a mathematical relationship between reliability and wind power generation. The analytical computation of monthly wind power is obtained from weibull statistical model using cubic mean cube root of wind speed. Reliability calculation is based on failure probability analysis. There are many different types of wind turbinescommercially available in the market. From reliability point of view, to get optimum reliability in power generation, it is desirable to select a wind turbine generator which is best suited for a site. The mathematical relationship developed in this paper can be used for site-matching turbine selection in reliability point of view.

  6. GIS and dynamic phenomena modeling

    Czech Academy of Sciences Publication Activity Database

    Klimešová, Dana

    2006-01-01

    Roč. 4, č. 4 (2006), s. 11-15 ISSN 0139-570X Institutional research plan: CEZ:AV0Z10750506 Keywords : dynamic modelling * temporal analysis * dynamics evaluation * temporal space Subject RIV: BC - Control Systems Theory

  7. A Survey of Software Reliability Modeling and Estimation

    Science.gov (United States)

    1983-09-01

    considered include: the Jelinski-Moranda Model, the ,Geometric Model,’ and Musa’s Model. A Monte -Carlo study of the behavior of the ’V"’"*least squares...ceedings Number 261, 1979, pp. 34-1, 34-11. IoelAmrit, AGieboSSukert, Alan and Goel, Ararat , "A Guidebookfor Software Reliability Assessment, 1980

  8. Power plant reliability calculation with Markov chain models

    International Nuclear Information System (INIS)

    Senegacnik, A.; Tuma, M.

    1998-01-01

    In the paper power plant operation is modelled using continuous time Markov chains with discrete state space. The model is used to compute the power plant reliability and the importance and influence of individual states, as well as the transition probabilities between states. For comparison the model is fitted to data for coal and nuclear power plants recorded over several years. (orig.) [de

  9. 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.

  10. Methods for Calculating Frequency of Maintenance of Complex Information Security System Based on Dynamics of Its Reliability

    Science.gov (United States)

    Varlataya, S. K.; Evdokimov, V. E.; Urzov, A. Y.

    2017-11-01

    This article describes a process of calculating a certain complex information security system (CISS) reliability using the example of the technospheric security management model as well as ability to determine the frequency of its maintenance using the system reliability parameter which allows one to assess man-made risks and to forecast natural and man-made emergencies. The relevance of this article is explained by the fact the CISS reliability is closely related to information security (IS) risks. Since reliability (or resiliency) is a probabilistic characteristic of the system showing the possibility of its failure (and as a consequence - threats to the protected information assets emergence), it is seen as a component of the overall IS risk in the system. As it is known, there is a certain acceptable level of IS risk assigned by experts for a particular information system; in case of reliability being a risk-forming factor maintaining an acceptable risk level should be carried out by the routine analysis of the condition of CISS and its elements and their timely service. The article presents a reliability parameter calculation for the CISS with a mixed type of element connection, a formula of the dynamics of such system reliability is written. The chart of CISS reliability change is a S-shaped curve which can be divided into 3 periods: almost invariable high level of reliability, uniform reliability reduction, almost invariable low level of reliability. Setting the minimum acceptable level of reliability, the graph (or formula) can be used to determine the period of time during which the system would meet requirements. Ideally, this period should not be longer than the first period of the graph. Thus, the proposed method of calculating the CISS maintenance frequency helps to solve a voluminous and critical task of the information assets risk management.

  11. Reliability-based Dynamic Network Design with Stochastic Networks

    NARCIS (Netherlands)

    Li, H.

    2009-01-01

    Transportation systems are stochastic and dynamic systems. The road capacities and the travel demand are fluctuating from time to time within a day and at the same time from day to day. For road users, the travel time and travel costs experienced over time and space are stochastic, thus desire

  12. A simulation model for reliability evaluation of Space Station power systems

    Science.gov (United States)

    Singh, C.; Patton, A. D.; Kumar, Mudit; Wagner, H.

    1988-01-01

    A detailed simulation model for the hybrid Space Station power system is presented which allows photovoltaic and solar dynamic power sources to be mixed in varying proportions. The model considers the dependence of reliability and storage characteristics during the sun and eclipse periods, and makes it possible to model the charging and discharging of the energy storage modules in a relatively accurate manner on a continuous basis.

  13. Maximum Entropy Discrimination Poisson Regression for Software Reliability Modeling.

    Science.gov (United States)

    Chatzis, Sotirios P; Andreou, Andreas S

    2015-11-01

    Reliably predicting software defects is one of the most significant tasks in software engineering. Two of the major components of modern software reliability modeling approaches are: 1) extraction of salient features for software system representation, based on appropriately designed software metrics and 2) development of intricate regression models for count data, to allow effective software reliability data modeling and prediction. Surprisingly, research in the latter frontier of count data regression modeling has been rather limited. More specifically, a lack of simple and efficient algorithms for posterior computation has made the Bayesian approaches appear unattractive, and thus underdeveloped in the context of software reliability modeling. In this paper, we try to address these issues by introducing a novel Bayesian regression model for count data, based on the concept of max-margin data modeling, effected in the context of a fully Bayesian model treatment with simple and efficient posterior distribution updates. Our novel approach yields a more discriminative learning technique, making more effective use of our training data during model inference. In addition, it allows of better handling uncertainty in the modeled data, which can be a significant problem when the training data are limited. We derive elegant inference algorithms for our model under the mean-field paradigm and exhibit its effectiveness using the publicly available benchmark data sets.

  14. Estimation of some stochastic models used in reliability engineering

    International Nuclear Information System (INIS)

    Huovinen, T.

    1989-04-01

    The work aims to study the estimation of some stochastic models used in reliability engineering. In reliability engineering continuous probability distributions have been used as models for the lifetime of technical components. We consider here the following distributions: exponential, 2-mixture exponential, conditional exponential, Weibull, lognormal and gamma. Maximum likelihood method is used to estimate distributions from observed data which may be either complete or censored. We consider models based on homogeneous Poisson processes such as gamma-poisson and lognormal-poisson models for analysis of failure intensity. We study also a beta-binomial model for analysis of failure probability. The estimators of the parameters for three models are estimated by the matching moments method and in the case of gamma-poisson and beta-binomial models also by maximum likelihood method. A great deal of mathematical or statistical problems that arise in reliability engineering can be solved by utilizing point processes. Here we consider the statistical analysis of non-homogeneous Poisson processes to describe the failing phenomena of a set of components with a Weibull intensity function. We use the method of maximum likelihood to estimate the parameters of the Weibull model. A common cause failure can seriously reduce the reliability of a system. We consider a binomial failure rate (BFR) model as an application of the marked point processes for modelling common cause failure in a system. The parameters of the binomial failure rate model are estimated with the maximum likelihood method

  15. RELIABLE DYNAMIC SOURCE ROUTING PROTOCOL (RDSRP FOR ENERGY HARVESTING WIRELESS SENSOR NETWORKS

    Directory of Open Access Journals (Sweden)

    B. Narasimhan

    2015-03-01

    Full Text Available Wireless sensor networks (WSNs carry noteworthy pros over traditional communication. Though, unkind and composite environments fake great challenges in the reliability of WSN communications. It is more vital to develop a reliable unipath dynamic source routing protocol (RDSRPl for WSN to provide better quality of service (QoS in energy harvesting wireless sensor networks (EH-WSN. This paper proposes a dynamic source routing approach for attaining the most reliable route in EH-WSNs. Performance evaluation is carried out using NS-2 and throughput and packet delivery ratio are chosen as the metrics.

  16. Reliability model for common mode failures in redundant safety systems

    International Nuclear Information System (INIS)

    Fleming, K.N.

    1974-12-01

    A method is presented for computing the reliability of redundant safety systems, considering both independent and common mode type failures. The model developed for the computation is a simple extension of classical reliability theory. The feasibility of the method is demonstrated with the use of an example. The probability of failure of a typical diesel-generator emergency power system is computed based on data obtained from U. S. diesel-generator operating experience. The results are compared with reliability predictions based on the assumption that all failures are independent. The comparison shows a significant increase in the probability of redundant system failure, when common failure modes are considered. (U.S.)

  17. Characterizing and modeling citation dynamics.

    Directory of Open Access Journals (Sweden)

    Young-Ho Eom

    Full Text Available Citation distributions are crucial for the analysis and modeling of the activity of scientists. We investigated bibliometric data of papers published in journals of the American Physical Society, searching for the type of function which best describes the observed citation distributions. We used the goodness of fit with Kolmogorov-Smirnov statistics for three classes of functions: log-normal, simple power law and shifted power law. The shifted power law turns out to be the most reliable hypothesis for all citation networks we derived, which correspond to different time spans. We find that citation dynamics is characterized by bursts, usually occurring within a few years since publication of a paper, and the burst size spans several orders of magnitude. We also investigated the microscopic mechanisms for the evolution of citation networks, by proposing a linear preferential attachment with time dependent initial attractiveness. The model successfully reproduces the empirical citation distributions and accounts for the presence of citation bursts as well.

  18. New application of dynamic reliability assessment of the mid-loop operation

    International Nuclear Information System (INIS)

    Moosung, Jae; Goon Cherl Park; Chang Hyun Chung

    1995-01-01

    This paper presents a new approach for assessing the dynamic reliability in a complex system such as a nuclear power plant. The method is applied to a dynamic analysis of the potential accident sequences that may occur during mid-loop operation

  19. Modelling dynamic roughness during floods

    NARCIS (Netherlands)

    Paarlberg, Andries; Dohmen-Janssen, Catarine M.; Hulscher, Suzanne J.M.H.; Termes, A.P.P.

    2007-01-01

    In this paper, we present a dynamic roughness model to predict water levels during floods. Hysteresis effects of dune development are explicitly included. It is shown that differences between the new dynamic roughness model, and models where the roughness coefficient is calibrated, are most

  20. Modeling Sensor Reliability in Fault Diagnosis Based on Evidence Theory

    Directory of Open Access Journals (Sweden)

    Kaijuan Yuan

    2016-01-01

    Full Text Available Sensor data fusion plays an important role in fault diagnosis. Dempster–Shafer (D-R evidence theory is widely used in fault diagnosis, since it is efficient to combine evidence from different sensors. However, under the situation where the evidence highly conflicts, it may obtain a counterintuitive result. To address the issue, a new method is proposed in this paper. Not only the statistic sensor reliability, but also the dynamic sensor reliability are taken into consideration. The evidence distance function and the belief entropy are combined to obtain the dynamic reliability of each sensor report. A weighted averaging method is adopted to modify the conflict evidence by assigning different weights to evidence according to sensor reliability. The proposed method has better performance in conflict management and fault diagnosis due to the fact that the information volume of each sensor report is taken into consideration. An application in fault diagnosis based on sensor fusion is illustrated to show the efficiency of the proposed method. The results show that the proposed method improves the accuracy of fault diagnosis from 81.19% to 89.48% compared to the existing methods.

  1. Learning reliable manipulation strategies without initial physical models

    Science.gov (United States)

    Christiansen, Alan D.; Mason, Matthew T.; Mitchell, Tom M.

    1990-01-01

    A description is given of a robot, possessing limited sensory and effectory capabilities but no initial model of the effects of its actions on the world, that acquires such a model through exploration, practice, and observation. By acquiring an increasingly correct model of its actions, it generates increasingly successful plans to achieve its goals. In an apparently nondeterministic world, achieving reliability requires the identification of reliable actions and a preference for using such actions. Furthermore, by selecting its training actions carefully, the robot can significantly improve its learning rate.

  2. Using LISREL to Evaluate Measurement Models and Scale Reliability.

    Science.gov (United States)

    Fleishman, John; Benson, Jeri

    1987-01-01

    LISREL program was used to examine measurement model assumptions and to assess reliability of Coopersmith Self-Esteem Inventory for Children, Form B. Data on 722 third-sixth graders from over 70 schools in large urban school district were used. LISREL program assessed (1) nature of basic measurement model for scale, (2) scale invariance across…

  3. Travel Time Reliability for Urban Networks : Modelling and Empirics

    NARCIS (Netherlands)

    Zheng, F.; Liu, Xiaobo; van Zuylen, H.J.; Li, Jie; Lu, Chao

    2017-01-01

    The importance of travel time reliability in traffic management, control, and network design has received a lot of attention in the past decade. In this paper, a network travel time distribution model based on the Johnson curve system is proposed. The model is applied to field travel time data

  4. Reliability model of SNS linac (spallation neutron source-ORNL)

    International Nuclear Information System (INIS)

    Pitigoi, A.; Fernandez, P.

    2015-01-01

    A reliability model of SNS LINAC (Spallation Neutron Source at Oak Ridge National Laboratory) has been developed using risk spectrum reliability analysis software and the analysis of the accelerator system's reliability has been performed. The analysis results have been evaluated by comparing them with the SNS operational data. This paper presents the main results and conclusions focusing on the definition of design weaknesses and provides recommendations to improve reliability of the MYRRHA ( linear accelerator. The reliability results show that the most affected SNS LINAC parts/systems are: 1) SCL (superconducting linac), front-end systems: IS, LEBT (low-energy beam transport line), MEBT (medium-energy beam transport line), diagnostics and controls; 2) RF systems (especially the SCL RF system); 3) power supplies and PS controllers. These results are in line with the records in the SNS logbook. The reliability issue that needs to be enforced in the linac design is the redundancy of the systems, subsystems and components most affected by failures. For compensation purposes, there is a need for intelligent fail-over redundancy implementation in controllers. Enough diagnostics has to be implemented to allow reliable functioning of the redundant solutions and to ensure the compensation function

  5. Models for reliability and management of NDT data

    International Nuclear Information System (INIS)

    Simola, K.

    1997-01-01

    In this paper the reliability of NDT measurements was approached from three directions. We have modelled the flaw sizing performance, the probability of flaw detection, and developed models to update the knowledge of true flaw size based on sequential measurement results and flaw sizing reliability model. In discussed models the measured flaw characteristics (depth, length) are assumed to be simple functions of the true characteristics and random noise corresponding to measurement errors, and the models are based on logarithmic transforms. Models for Bayesian updating of the flaw size distributions were developed. Using these models, it is possible to take into account the prior information of the flaw size and combine it with the measured results. A Bayesian approach could contribute e. g. to the definition of an appropriate combination of practical assessments and technical justifications in NDT system qualifications, as expressed by the European regulatory bodies

  6. Transparent reliability model for fault-tolerant safety systems

    International Nuclear Information System (INIS)

    Bodsberg, Lars; Hokstad, Per

    1997-01-01

    A reliability model is presented which may serve as a tool for identification of cost-effective configurations and operating philosophies of computer-based process safety systems. The main merit of the model is the explicit relationship in the mathematical formulas between failure cause and the means used to improve system reliability such as self-test, redundancy, preventive maintenance and corrective maintenance. A component failure taxonomy has been developed which allows the analyst to treat hardware failures, human failures, and software failures of automatic systems in an integrated manner. Furthermore, the taxonomy distinguishes between failures due to excessive environmental stresses and failures initiated by humans during engineering and operation. Attention has been given to develop a transparent model which provides predictions which are in good agreement with observed system performance, and which is applicable for non-experts in the field of reliability

  7. Field programmable gate array reliability analysis using the dynamic flow graph methodology

    Energy Technology Data Exchange (ETDEWEB)

    McNelles, Phillip; Lu, Lixuan [Faculty of Energy Systems and Nuclear Science, University of Ontario Institute of Technology (UOIT), Ontario (Canada)

    2016-10-15

    Field programmable gate array (FPGA)-based systems are thought to be a practical option to replace certain obsolete instrumentation and control systems in nuclear power plants. An FPGA is a type of integrated circuit, which is programmed after being manufactured. FPGAs have some advantages over other electronic technologies, such as analog circuits, microprocessors, and Programmable Logic Controllers (PLCs), for nuclear instrumentation and control, and safety system applications. However, safety-related issues for FPGA-based systems remain to be verified. Owing to this, modeling FPGA-based systems for safety assessment has now become an important point of research. One potential methodology is the dynamic flowgraph methodology (DFM). It has been used for modeling software/hardware interactions in modern control systems. In this paper, FPGA logic was analyzed using DFM. Four aspects of FPGAs are investigated: the 'IEEE 1164 standard', registers (D flip-flops), configurable logic blocks, and an FPGA-based signal compensator. The ModelSim simulations confirmed that DFM was able to accurately model those four FPGA properties, proving that DFM has the potential to be used in the modeling of FPGA-based systems. Furthermore, advantages of DFM over traditional reliability analysis methods and FPGA simulators are presented, along with a discussion of potential issues with using DFM for FPGA-based system modeling.

  8. A discrete-time Bayesian network reliability modeling and analysis framework

    International Nuclear Information System (INIS)

    Boudali, H.; Dugan, J.B.

    2005-01-01

    Dependability tools are becoming an indispensable tool for modeling and analyzing (critical) systems. However the growing complexity of such systems calls for increasing sophistication of these tools. Dependability tools need to not only capture the complex dynamic behavior of the system components, but they must be also easy to use, intuitive, and computationally efficient. In general, current tools have a number of shortcomings including lack of modeling power, incapacity to efficiently handle general component failure distributions, and ineffectiveness in solving large models that exhibit complex dependencies between their components. We propose a novel reliability modeling and analysis framework based on the Bayesian network (BN) formalism. The overall approach is to investigate timed Bayesian networks and to find a suitable reliability framework for dynamic systems. We have applied our methodology to two example systems and preliminary results are promising. We have defined a discrete-time BN reliability formalism and demonstrated its capabilities from a modeling and analysis point of view. This research shows that a BN based reliability formalism is a powerful potential solution to modeling and analyzing various kinds of system components behaviors and interactions. Moreover, being based on the BN formalism, the framework is easy to use and intuitive for non-experts, and provides a basis for more advanced and useful analyses such as system diagnosis

  9. 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

  10. Fuse Modeling for Reliability Study of Power Electronic Circuits

    DEFF Research Database (Denmark)

    Bahman, Amir Sajjad; Iannuzzo, Francesco; Blaabjerg, Frede

    2017-01-01

    This paper describes a comprehensive modeling approach on reliability of fuses used in power electronic circuits. When fuses are subjected to current pulses, cyclic temperature stress is introduced to the fuse element and will wear out the component. Furthermore, the fuse may be used in a large......, and rated voltage/current are opposed to shift in time to effect early breaking during the normal operation of the circuit. Therefore, in such cases, a reliable protection required for the other circuit components will not be achieved. The thermo-mechanical models, fatigue analysis and thermo...

  11. Structural hybrid reliability index and its convergent solving method based on random–fuzzy–interval reliability model

    Directory of Open Access Journals (Sweden)

    Hai An

    2016-08-01

    Full Text Available Aiming to resolve the problems of a variety of uncertainty variables that coexist in the engineering structure reliability analysis, a new hybrid reliability index to evaluate structural hybrid reliability, based on the random–fuzzy–interval model, is proposed in this article. The convergent solving method is also presented. First, the truncated probability reliability model, the fuzzy random reliability model, and the non-probabilistic interval reliability model are introduced. Then, the new hybrid reliability index definition is presented based on the random–fuzzy–interval model. Furthermore, the calculation flowchart of the hybrid reliability index is presented and it is solved using the modified limit-step length iterative algorithm, which ensures convergence. And the validity of convergent algorithm for the hybrid reliability model is verified through the calculation examples in literature. In the end, a numerical example is demonstrated to show that the hybrid reliability index is applicable for the wear reliability assessment of mechanisms, where truncated random variables, fuzzy random variables, and interval variables coexist. The demonstration also shows the good convergence of the iterative algorithm proposed in this article.

  12. Average inactivity time model, associated orderings and reliability properties

    Science.gov (United States)

    Kayid, M.; Izadkhah, S.; Abouammoh, A. M.

    2018-02-01

    In this paper, we introduce and study a new model called 'average inactivity time model'. This new model is specifically applicable to handle the heterogeneity of the time of the failure of a system in which some inactive items exist. We provide some bounds for the mean average inactivity time of a lifespan unit. In addition, we discuss some dependence structures between the average variable and the mixing variable in the model when original random variable possesses some aging behaviors. Based on the conception of the new model, we introduce and study a new stochastic order. Finally, to illustrate the concept of the model, some interesting reliability problems are reserved.

  13. Hybrid dynamics for currency modeling

    OpenAIRE

    Theodosopoulos, Ted; Trifunovic, Alex

    2006-01-01

    We present a simple hybrid dynamical model as a tool to investigate behavioral strategies based on trend following. The multiplicative symbolic dynamics are generated using a lognormal diffusion model for the at-the-money implied volatility term structure. Thus, are model exploits information from derivative markets to obtain qualititative properties of the return distribution for the underlier. We apply our model to the JPY-USD exchange rate and the corresponding 1mo., 3mo., 6mo. and 1yr. im...

  14. A model for assessing human cognitive reliability in PRA studies

    International Nuclear Information System (INIS)

    Hannaman, G.W.; Spurgin, A.J.; Lukic, Y.

    1985-01-01

    This paper summarizes the status of a research project sponsored by EPRI as part of the Probabilistic Risk Assessment (PRA) technology improvement program and conducted by NUS Corporation to develop a model of Human Cognitive Reliability (HCR). The model was synthesized from features identified in a review of existing models. The model development was based on the hypothesis that the key factors affecting crew response times are separable. The inputs to the model consist of key parameters the values of which can be determined by PRA analysts for each accident situation being assessed. The output is a set of curves which represent the probability of control room crew non-response as a function of time for different conditions affecting their performance. The non-response probability is then a contributor to the overall non-success of operating crews to achieve a functional objective identified in the PRA study. Simulator data and some small scale tests were utilized to illustrate the calibration of interim HCR model coefficients for different types of cognitive processing since the data were sparse. The model can potentially help PRA analysts make human reliability assessments more explicit. The model incorporates concepts from psychological models of human cognitive behavior, information from current collections of human reliability data sources and crew response time data from simulator training exercises

  15. Reliability and mass analysis of dynamic power conversion systems with parallel or standby redundancy

    Science.gov (United States)

    Juhasz, Albert J.; Bloomfield, Harvey S.

    1987-01-01

    A combinatorial reliability approach was used to identify potential dynamic power conversion systems for space mission applications. A reliability and mass analysis was also performed, specifically for a 100-kWe nuclear Brayton power conversion system with parallel redundancy. Although this study was done for a reactor outlet temperature of 1100 K, preliminary system mass estimates are also included for reactor outlet temperatures ranging up to 1500 K.

  16. Reliability and mass analysis of dynamic power conversion systems with parallel of standby redundancy

    Science.gov (United States)

    Juhasz, A. J.; Bloomfield, H. S.

    1985-01-01

    A combinatorial reliability approach is used to identify potential dynamic power conversion systems for space mission applications. A reliability and mass analysis is also performed, specifically for a 100 kWe nuclear Brayton power conversion system with parallel redundancy. Although this study is done for a reactor outlet temperature of 1100K, preliminary system mass estimates are also included for reactor outlet temperatures ranging up to 1500 K.

  17. The reliability of the Adelaide in-shoe foot model.

    Science.gov (United States)

    Bishop, Chris; Hillier, Susan; Thewlis, Dominic

    2017-07-01

    Understanding the biomechanics of the foot is essential for many areas of research and clinical practice such as orthotic interventions and footwear development. Despite the widespread attention paid to the biomechanics of the foot during gait, what largely remains unknown is how the foot moves inside the shoe. This study investigated the reliability of the Adelaide In-Shoe Foot Model, which was designed to quantify in-shoe foot kinematics and kinetics during walking. Intra-rater reliability was assessed in 30 participants over five walking trials whilst wearing shoes during two data collection sessions, separated by one week. Sufficient reliability for use was interpreted as a coefficient of multiple correlation and intra-class correlation coefficient of >0.61. Inter-rater reliability was investigated separately in a second sample of 10 adults by two researchers with experience in applying markers for the purpose of motion analysis. The results indicated good consistency in waveform estimation for most kinematic and kinetic data, as well as good inter-and intra-rater reliability. The exception is the peak medial ground reaction force, the minimum abduction angle and the peak abduction/adduction external hindfoot joint moments which resulted in less than acceptable repeatability. Based on our results, the Adelaide in-shoe foot model can be used with confidence for 24 commonly measured biomechanical variables during shod walking. Copyright © 2017 Elsevier B.V. All rights reserved.

  18. Modeling of humidity-related reliability in enclosures with electronics

    DEFF Research Database (Denmark)

    Hygum, Morten Arnfeldt; Popok, Vladimir

    2015-01-01

    Reliability of electronics that operate outdoor is strongly affected by environmental factors such as temperature and humidity. Fluctuations of these parameters can lead to water condensation inside enclosures. Therefore, modelling of humidity distribution in a container with air and freely exposed...

  19. Models of Information Security Highly Reliable Computing Systems

    Directory of Open Access Journals (Sweden)

    Vsevolod Ozirisovich Chukanov

    2016-03-01

    Full Text Available Methods of the combined reservation are considered. The models of reliability of systems considering parameters of restoration and prevention of blocks of system are described. Ratios for average quantity prevention and an availability quotient of blocks of system are given.

  20. SIERRA - A 3-D device simulator for reliability modeling

    Science.gov (United States)

    Chern, Jue-Hsien; Arledge, Lawrence A., Jr.; Yang, Ping; Maeda, John T.

    1989-05-01

    SIERRA is a three-dimensional general-purpose semiconductor-device simulation program which serves as a foundation for investigating integrated-circuit (IC) device and reliability issues. This program solves the Poisson and continuity equations in silicon under dc, transient, and small-signal conditions. Executing on a vector/parallel minisupercomputer, SIERRA utilizes a matrix solver which uses an incomplete LU (ILU) preconditioned conjugate gradient square (CGS, BCG) method. The ILU-CGS method provides a good compromise between memory size and convergence rate. The authors have observed a 5x to 7x speedup over standard direct methods in simulations of transient problems containing highly coupled Poisson and continuity equations such as those found in reliability-oriented simulations. The application of SIERRA to parasitic CMOS latchup and dynamic random-access memory single-event-upset studies is described.

  1. An architectural model for software reliability quantification: sources of data

    International Nuclear Information System (INIS)

    Smidts, C.; Sova, D.

    1999-01-01

    Software reliability assessment models in use today treat software as a monolithic block. An aversion towards 'atomic' models seems to exist. These models appear to add complexity to the modeling, to the data collection and seem intrinsically difficult to generalize. In 1997, we introduced an architecturally based software reliability model called FASRE. The model is based on an architecture derived from the requirements which captures both functional and nonfunctional requirements and on a generic classification of functions, attributes and failure modes. The model focuses on evaluation of failure mode probabilities and uses a Bayesian quantification framework. Failure mode probabilities of functions and attributes are propagated to the system level using fault trees. It can incorporate any type of prior information such as results of developers' testing, historical information on a specific functionality and its attributes, and, is ideally suited for reusable software. By building an architecture and deriving its potential failure modes, the model forces early appraisal and understanding of the weaknesses of the software, allows reliability analysis of the structure of the system, provides assessments at a functional level as well as at a systems' level. In order to quantify the probability of failure (or the probability of success) of a specific element of our architecture, data are needed. The term element of the architecture is used here in its broadest sense to mean a single failure mode or a higher level of abstraction such as a function. The paper surveys the potential sources of software reliability data available during software development. Next the mechanisms for incorporating these sources of relevant data to the FASRE model are identified

  2. Stochastic Differential Equation-Based Flexible Software Reliability Growth Model

    Directory of Open Access Journals (Sweden)

    P. K. Kapur

    2009-01-01

    Full Text Available Several software reliability growth models (SRGMs have been developed by software developers in tracking and measuring the growth of reliability. As the size of software system is large and the number of faults detected during the testing phase becomes large, so the change of the number of faults that are detected and removed through each debugging becomes sufficiently small compared with the initial fault content at the beginning of the testing phase. In such a situation, we can model the software fault detection process as a stochastic process with continuous state space. In this paper, we propose a new software reliability growth model based on Itô type of stochastic differential equation. We consider an SDE-based generalized Erlang model with logistic error detection function. The model is estimated and validated on real-life data sets cited in literature to show its flexibility. The proposed model integrated with the concept of stochastic differential equation performs comparatively better than the existing NHPP-based models.

  3. Modular reliability modeling of the TJNAF personnel safety system

    International Nuclear Information System (INIS)

    Cinnamon, J.; Mahoney, K.

    1997-01-01

    A reliability model for the Thomas Jefferson National Accelerator Facility (formerly CEBAF) personnel safety system has been developed. The model, which was implemented using an Excel spreadsheet, allows simulation of all or parts of the system. Modularity os the model's implementation allows rapid open-quotes what if open-quotes case studies to simulate change in safety system parameters such as redundancy, diversity, and failure rates. Particular emphasis is given to the prediction of failure modes which would result in the failure of both of the redundant safety interlock systems. In addition to the calculation of the predicted reliability of the safety system, the model also calculates availability of the same system. Such calculations allow the user to make tradeoff studies between reliability and availability, and to target resources to improving those parts of the system which would most benefit from redesign or upgrade. The model includes calculated, manufacturer's data, and Jefferson Lab field data. This paper describes the model, methods used, and comparison of calculated to actual data for the Jefferson Lab personnel safety system. Examples are given to illustrate the model's utility and ease of use

  4. 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....

  5. Reliability modeling and analysis of smart power systems

    CERN Document Server

    Karki, Rajesh; Verma, Ajit Kumar

    2014-01-01

    The volume presents the research work in understanding, modeling and quantifying the risks associated with different ways of implementing smart grid technology in power systems in order to plan and operate a modern power system with an acceptable level of reliability. Power systems throughout the world are undergoing significant changes creating new challenges to system planning and operation in order to provide reliable and efficient use of electrical energy. The appropriate use of smart grid technology is an important drive in mitigating these problems and requires considerable research acti

  6. Computer Modelling of Dynamic Processes

    Directory of Open Access Journals (Sweden)

    B. Rybakin

    2000-10-01

    Full Text Available Results of numerical modeling of dynamic problems are summed in the article up. These problems are characteristic for various areas of human activity, in particular for problem solving in ecology. The following problems are considered in the present work: computer modeling of dynamic effects on elastic-plastic bodies, calculation and determination of performances of gas streams in gas cleaning equipment, modeling of biogas formation processes.

  7. A general graphical user interface for automatic reliability modeling

    Science.gov (United States)

    Liceaga, Carlos A.; Siewiorek, Daniel P.

    1991-01-01

    Reported here is a general Graphical User Interface (GUI) for automatic reliability modeling of Processor Memory Switch (PMS) structures using a Markov model. This GUI is based on a hierarchy of windows. One window has graphical editing capabilities for specifying the system's communication structure, hierarchy, reconfiguration capabilities, and requirements. Other windows have field texts, popup menus, and buttons for specifying parameters and selecting actions. An example application of the GUI is given.

  8. NHPP-Based Software Reliability Models Using Equilibrium Distribution

    Science.gov (United States)

    Xiao, Xiao; Okamura, Hiroyuki; Dohi, Tadashi

    Non-homogeneous Poisson processes (NHPPs) have gained much popularity in actual software testing phases to estimate the software reliability, the number of remaining faults in software and the software release timing. In this paper, we propose a new modeling approach for the NHPP-based software reliability models (SRMs) to describe the stochastic behavior of software fault-detection processes. The fundamental idea is to apply the equilibrium distribution to the fault-detection time distribution in NHPP-based modeling. We also develop efficient parameter estimation procedures for the proposed NHPP-based SRMs. Through numerical experiments, it can be concluded that the proposed NHPP-based SRMs outperform the existing ones in many data sets from the perspective of goodness-of-fit and prediction performance.

  9. Structural reliability in context of statistical uncertainties and modelling discrepancies

    International Nuclear Information System (INIS)

    Pendola, Maurice

    2000-01-01

    Structural reliability methods have been largely improved during the last years and have showed their ability to deal with uncertainties during the design stage or to optimize the functioning and the maintenance of industrial installations. They are based on a mechanical modeling of the structural behavior according to the considered failure modes and on a probabilistic representation of input parameters of this modeling. In practice, only limited statistical information is available to build the probabilistic representation and different sophistication levels of the mechanical modeling may be introduced. Thus, besides the physical randomness, other uncertainties occur in such analyses. The aim of this work is triple: 1. at first, to propose a methodology able to characterize the statistical uncertainties due to the limited number of data in order to take them into account in the reliability analyses. The obtained reliability index measures the confidence in the structure considering the statistical information available. 2. Then, to show a methodology leading to reliability results evaluated from a particular mechanical modeling but by using a less sophisticated one. The objective is then to decrease the computational efforts required by the reference modeling. 3. Finally, to propose partial safety factors that are evolving as a function of the number of statistical data available and as a function of the sophistication level of the mechanical modeling that is used. The concepts are illustrated in the case of a welded pipe and in the case of a natural draught cooling tower. The results show the interest of the methodologies in an industrial context. [fr

  10. Reliability assessment of competing risks with generalized mixed shock models

    International Nuclear Information System (INIS)

    Rafiee, Koosha; Feng, Qianmei; Coit, David W.

    2017-01-01

    This paper investigates reliability modeling for systems subject to dependent competing risks considering the impact from a new generalized mixed shock model. Two dependent competing risks are soft failure due to a degradation process, and hard failure due to random shocks. The shock process contains fatal shocks that can cause hard failure instantaneously, and nonfatal shocks that impact the system in three different ways: 1) damaging the unit by immediately increasing the degradation level, 2) speeding up the deterioration by accelerating the degradation rate, and 3) weakening the unit strength by reducing the hard failure threshold. While the first impact from nonfatal shocks comes from each individual shock, the other two impacts are realized when the condition for a new generalized mixed shock model is satisfied. Unlike most existing mixed shock models that consider a combination of two shock patterns, our new generalized mixed shock model includes three classic shock patterns. According to the proposed generalized mixed shock model, the degradation rate and the hard failure threshold can simultaneously shift multiple times, whenever the condition for one of these three shock patterns is satisfied. An example using micro-electro-mechanical systems devices illustrates the effectiveness of the proposed approach with sensitivity analysis. - Highlights: • A rich reliability model for systems subject to dependent failures is proposed. • The degradation rate and the hard failure threshold can shift simultaneously. • The shift is triggered by a new generalized mixed shock model. • The shift can occur multiple times under the generalized mixed shock model.

  11. Structural dynamic modifications via models

    Indian Academy of Sciences (India)

    The study shows that as many as half of the matrix ... the dynamicist's analytical modelling skill which would appear both in the numerator as. Figure 2. ..... Brandon J A 1990 Strategies for structural dynamic modification (New York: John Wiley).

  12. Dynamic programming models and applications

    CERN Document Server

    Denardo, Eric V

    2003-01-01

    Introduction to sequential decision processes covers use of dynamic programming in studying models of resource allocation, methods for approximating solutions of control problems in continuous time, production control, more. 1982 edition.

  13. Dynamical models of the Galaxy

    Directory of Open Access Journals (Sweden)

    McMillan P.J.

    2012-02-01

    Full Text Available I discuss the importance of dynamical models for exploiting survey data, focusing on the advantages of “torus” models. I summarize a number of applications of these models to the study of the Milky Way, including the determination of the peculiar Solar velocity and investigation of the Hyades moving group.

  14. Testing the reliability of ice-cream cone model

    Science.gov (United States)

    Pan, Zonghao; Shen, Chenglong; Wang, Chuanbing; Liu, Kai; Xue, Xianghui; Wang, Yuming; Wang, Shui

    2015-04-01

    Coronal Mass Ejections (CME)'s properties are important to not only the physical scene itself but space-weather prediction. Several models (such as cone model, GCS model, and so on) have been raised to get rid of the projection effects within the properties observed by spacecraft. According to SOHO/ LASCO observations, we obtain the 'real' 3D parameters of all the FFHCMEs (front-side full halo Coronal Mass Ejections) within the 24th solar cycle till July 2012, by the ice-cream cone model. Considering that the method to obtain 3D parameters from the CME observations by multi-satellite and multi-angle has higher accuracy, we use the GCS model to obtain the real propagation parameters of these CMEs in 3D space and compare the results with which by ice-cream cone model. Then we could discuss the reliability of the ice-cream cone model.

  15. An integrated model for reliability estimation of digital nuclear protection system based on fault tree and software control flow methodologies

    International Nuclear Information System (INIS)

    Kim, Man Cheol; Seong, Poong Hyun

    2000-01-01

    In the nuclear industry, the difficulty of proving the reliabilities of digital systems prohibits the widespread use of digital systems in various nuclear application such as plant protection system. Even though there exist a few models which are used to estimate the reliabilities of digital systems, we develop a new integrated model which is more realistic than the existing models. We divide the process of estimating the reliability of a digital system into two phases, a high-level phase and a low-level phase, and the boundary of two phases is the reliabilities of subsystems. We apply software control flow method to the low-level phase and fault tree analysis to the high-level phase. The application of the model to Dynamic Safety System(DDS) shows that the estimated reliability of the system is quite reasonable and realistic

  16. An integrated model for reliability estimation of digital nuclear protection system based on fault tree and software control flow methodologies

    International Nuclear Information System (INIS)

    Kim, Man Cheol; Seong, Poong Hyun

    2000-01-01

    In nuclear industry, the difficulty of proving the reliabilities of digital systems prohibits the widespread use of digital systems in various nuclear application such as plant protection system. Even though there exist a few models which are used to estimate the reliabilities of digital systems, we develop a new integrated model which is more realistic than the existing models. We divide the process of estimating the reliability of a digital system into two phases, a high-level phase and a low-level phase, and the boundary of two phases is the reliabilities of subsystems. We apply software control flow method to the low-level phase and fault tree analysis to the high-level phase. The application of the model of dynamic safety system (DSS) shows that the estimated reliability of the system is quite reasonable and realistic. (author)

  17. Modelling and estimating degradation processes with application in structural reliability

    International Nuclear Information System (INIS)

    Chiquet, J.

    2007-06-01

    The characteristic level of degradation of a given structure is modeled through a stochastic process called the degradation process. The random evolution of the degradation process is governed by a differential system with Markovian environment. We put the associated reliability framework by considering the failure of the structure once the degradation process reaches a critical threshold. A closed form solution of the reliability function is obtained thanks to Markov renewal theory. Then, we build an estimation methodology for the parameters of the stochastic processes involved. The estimation methods and the theoretical results, as well as the associated numerical algorithms, are validated on simulated data sets. Our method is applied to the modelling of a real degradation mechanism, known as crack growth, for which an experimental data set is considered. (authors)

  18. Stochastic quasi-gradient based optimization algorithms for dynamic reliability applications

    International Nuclear Information System (INIS)

    Bourgeois, F.; Labeau, P.E.

    2001-01-01

    On one hand, PSA results are increasingly used in decision making, system management and optimization of system design. On the other hand, when severe accidental transients are considered, dynamic reliability appears appropriate to account for the complex interaction between the transitions between hardware configurations, the operator behavior and the dynamic evolution of the system. This paper presents an exploratory work in which the estimation of the system unreliability in a dynamic context is coupled with an optimization algorithm to determine the 'best' safety policy. Because some reliability parameters are likely to be distributed, the cost function to be minimized turns out to be a random variable. Stochastic programming techniques are therefore envisioned to determine an optimal strategy. Monte Carlo simulation is used at all stages of the computations, from the estimation of the system unreliability to that of the stochastic quasi-gradient. The optimization algorithm is illustrated on a HNO 3 supply system

  19. Incorporation of Markov reliability models for digital instrumentation and control systems into existing PRAs

    International Nuclear Information System (INIS)

    Bucci, P.; Mangan, L. A.; Kirschenbaum, J.; Mandelli, D.; Aldemir, T.; Arndt, S. A.

    2006-01-01

    Markov models have the ability to capture the statistical dependence between failure events that can arise in the presence of complex dynamic interactions between components of digital instrumentation and control systems. One obstacle to the use of such models in an existing probabilistic risk assessment (PRA) is that most of the currently available PRA software is based on the static event-tree/fault-tree methodology which often cannot represent such interactions. We present an approach to the integration of Markov reliability models into existing PRAs by describing the Markov model of a digital steam generator feedwater level control system, how dynamic event trees (DETs) can be generated from the model, and how the DETs can be incorporated into an existing PRA with the SAPHIRE software. (authors)

  20. RETRAN dynamic slip model

    International Nuclear Information System (INIS)

    McFadden, J.H.; Paulsen, M.P.; Gose, G.C.

    1981-01-01

    A time dependent equation for the slip velocity in a two-phase flow condition has been incorporated into a developmental version of the RETRAN computer code. This model addition has been undertaken to remove a limitation in RETRAN-01 associated with the homogeneous equilibrium mixture model. In this paper, the development of the slip model is summarized and the corresponding constitutive equations are discussed. Comparisons of RETRAN analyses with steady-state void fraction data and data from the Semiscale S-02-6 small break test are also presented

  1. Fuzzy Goal Programming Approach in Selective Maintenance Reliability Model

    Directory of Open Access Journals (Sweden)

    Neha Gupta

    2013-12-01

    Full Text Available 800x600 In the present paper, we have considered the allocation problem of repairable components for a parallel-series system as a multi-objective optimization problem and have discussed two different models. In first model the reliability of subsystems are considered as different objectives. In second model the cost and time spent on repairing the components are considered as two different objectives. These two models is formulated as multi-objective Nonlinear Programming Problem (MONLPP and a Fuzzy goal programming method is used to work out the compromise allocation in multi-objective selective maintenance reliability model in which we define the membership functions of each objective function and then transform membership functions into equivalent linear membership functions by first order Taylor series and finally by forming a fuzzy goal programming model obtain a desired compromise allocation of maintenance components. A numerical example is also worked out to illustrate the computational details of the method.  Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4

  2. Modeling Propellant Tank Dynamics

    Data.gov (United States)

    National Aeronautics and Space Administration — The main objective of my work will be to develop accurate models of self-pressurizing propellant tanks for use in designing hybrid rockets. The first key goal is to...

  3. Software reliability growth models with normal failure time distributions

    International Nuclear Information System (INIS)

    Okamura, Hiroyuki; Dohi, Tadashi; Osaki, Shunji

    2013-01-01

    This paper proposes software reliability growth models (SRGM) where the software failure time follows a normal distribution. The proposed model is mathematically tractable and has sufficient ability of fitting to the software failure data. In particular, we consider the parameter estimation algorithm for the SRGM with normal distribution. The developed algorithm is based on an EM (expectation-maximization) algorithm and is quite simple for implementation as software application. Numerical experiment is devoted to investigating the fitting ability of the SRGMs with normal distribution through 16 types of failure time data collected in real software projects

  4. Reliability modelling - PETROBRAS 2010 integrated gas supply chain

    Energy Technology Data Exchange (ETDEWEB)

    Faertes, Denise; Heil, Luciana; Saker, Leonardo; Vieira, Flavia; Risi, Francisco; Domingues, Joaquim; Alvarenga, Tobias; Carvalho, Eduardo; Mussel, Patricia

    2010-09-15

    The purpose of this paper is to present the innovative reliability modeling of Petrobras 2010 integrated gas supply chain. The model represents a challenge in terms of complexity and software robustness. It was jointly developed by PETROBRAS Gas and Power Department and Det Norske Veritas. It was carried out with the objective of evaluating security of supply of 2010 gas network design that was conceived to connect Brazilian Northeast and Southeast regions. To provide best in class analysis, state of the art software was used to quantify the availability and the efficiency of the overall network and its individual components.

  5. Evaluating the reliability of predictions made using environmental transfer models

    International Nuclear Information System (INIS)

    1989-01-01

    The development and application of mathematical models for predicting the consequences of releases of radionuclides into the environment from normal operations in the nuclear fuel cycle and in hypothetical accident conditions has increased dramatically in the last two decades. This Safety Practice publication has been prepared to provide guidance on the available methods for evaluating the reliability of environmental transfer model predictions. It provides a practical introduction of the subject and a particular emphasis has been given to worked examples in the text. It is intended to supplement existing IAEA publications on environmental assessment methodology. 60 refs, 17 figs, 12 tabs

  6. Modelling group dynamic animal movement

    DEFF Research Database (Denmark)

    Langrock, Roland; Hopcraft, J. Grant C.; Blackwell, Paul G.

    2014-01-01

    makes its movement decisions relative to the group centroid. The basic idea is framed within the flexible class of hidden Markov models, extending previous work on modelling animal movement by means of multi-state random walks. While in simulation experiments parameter estimators exhibit some bias......, to date, practical statistical methods which can include group dynamics in animal movement models have been lacking. We consider a flexible modelling framework that distinguishes a group-level model, describing the movement of the group's centre, and an individual-level model, such that each individual......Group dynamic movement is a fundamental aspect of many species' movements. The need to adequately model individuals' interactions with other group members has been recognised, particularly in order to differentiate the role of social forces in individual movement from environmental factors. However...

  7. Power Electronic Packaging Design, Assembly Process, Reliability and Modeling

    CERN Document Server

    Liu, Yong

    2012-01-01

    Power Electronic Packaging presents an in-depth overview of power electronic packaging design, assembly,reliability and modeling. Since there is a drastic difference between IC fabrication and power electronic packaging, the book systematically introduces typical power electronic packaging design, assembly, reliability and failure analysis and material selection so readers can clearly understand each task's unique characteristics. Power electronic packaging is one of the fastest growing segments in the power electronic industry, due to the rapid growth of power integrated circuit (IC) fabrication, especially for applications like portable, consumer, home, computing and automotive electronics. This book also covers how advances in both semiconductor content and power advanced package design have helped cause advances in power device capability in recent years. The author extrapolates the most recent trends in the book's areas of focus to highlight where further improvement in materials and techniques can d...

  8. Modeling Internet Topology Dynamics

    NARCIS (Netherlands)

    Haddadi, H.; Uhlig, S.; Moore, A.; Mortier, R.; Rio, M.

    Despite the large number of papers on network topology modeling and inference, there still exists ambiguity about the real nature of the Internet AS and router level topology. While recent findings have illustrated the inaccuracies in maps inferred from BGP peering and traceroute measurements,

  9. Generative Models of Conformational Dynamics

    OpenAIRE

    Langmead, Christopher James

    2014-01-01

    Atomistic simulations of the conformational dynamics of proteins can be performed using either Molecular Dynamics or Monte Carlo procedures. The ensembles of three-dimensional structures produced during simulation can be analyzed in a number of ways to elucidate the thermodynamic and kinetic properties of the system. The goal of this chapter is to review both traditional and emerging methods for learning generative models from atomistic simulation data. Here, the term ‘generative’ refers to a...

  10. ITER Dynamic Tritium Inventory Modeling Code

    International Nuclear Information System (INIS)

    Cristescu, Ioana-R.; Doerr, L.; Busigin, A.; Murdoch, D.

    2005-01-01

    A tool for tritium inventory evaluation within each sub-system of the Fuel Cycle of ITER is vital, with respect to both the process of licensing ITER and also for operation. It is very likely that measurements of total tritium inventories may not be possible for all sub-systems, however tritium accounting may be achieved by modeling its hold-up within each sub-system and by validating these models in real-time against the monitored flows and tritium streams between the systems. To get reliable results, an accurate dynamic modeling of the tritium content in each sub-system is necessary. In order to optimize the configuration and operation of the ITER fuel cycle, a dynamic fuel cycle model was developed progressively in the decade up to 2000-2001. As the design for some sub-systems from the fuel cycle (i.e. Vacuum pumping, Neutral Beam Injectors (NBI)) have substantially progressed meanwhile, a new code developed under a different platform to incorporate these modifications has been developed. The new code is taking over the models and algorithms for some subsystems, such as Isotope Separation System (ISS); where simplified models have been previously considered, more detailed have been introduced, as for the Water Detritiation System (WDS). To reflect all these changes, the new code developed inside EU participating team was nominated TRIMO (Tritium Inventory Modeling), to emphasize the use of the code on assessing the tritium inventory within ITER

  11. Vehicle dynamics modeling and simulation

    CERN Document Server

    Schramm, Dieter; Bardini, Roberto

    2014-01-01

    The authors examine in detail the fundamentals and mathematical descriptions of the dynamics of automobiles. In this context different levels of complexity will be presented, starting with basic single-track models up to complex three-dimensional multi-body models. A particular focus is on the process of establishing mathematical models on the basis of real cars and the validation of simulation results. The methods presented are explained in detail by means of selected application scenarios.

  12. Stochastic process corrosion growth models for pipeline reliability

    International Nuclear Information System (INIS)

    Bazán, Felipe Alexander Vargas; Beck, André Teófilo

    2013-01-01

    Highlights: •Novel non-linear stochastic process corrosion growth model is proposed. •Corrosion rate modeled as random Poisson pulses. •Time to corrosion initiation and inherent time-variability properly represented. •Continuous corrosion growth histories obtained. •Model is shown to precisely fit actual corrosion data at two time points. -- Abstract: Linear random variable corrosion models are extensively employed in reliability analysis of pipelines. However, linear models grossly neglect well-known characteristics of the corrosion process. Herein, a non-linear model is proposed, where corrosion rate is represented as a Poisson square wave process. The resulting model represents inherent time-variability of corrosion growth, produces continuous growth and leads to mean growth at less-than-one power of time. Different corrosion models are adjusted to the same set of actual corrosion data for two inspections. The proposed non-linear random process corrosion growth model leads to the best fit to the data, while better representing problem physics

  13. Do downscaled general circulation models reliably simulate historical climatic conditions?

    Science.gov (United States)

    Bock, Andrew R.; Hay, Lauren E.; McCabe, Gregory J.; Markstrom, Steven L.; Atkinson, R. Dwight

    2018-01-01

    The accuracy of statistically downscaled (SD) general circulation model (GCM) simulations of monthly surface climate for historical conditions (1950–2005) was assessed for the conterminous United States (CONUS). The SD monthly precipitation (PPT) and temperature (TAVE) from 95 GCMs from phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5) were used as inputs to a monthly water balance model (MWBM). Distributions of MWBM input (PPT and TAVE) and output [runoff (RUN)] variables derived from gridded station data (GSD) and historical SD climate were compared using the Kolmogorov–Smirnov (KS) test For all three variables considered, the KS test results showed that variables simulated using CMIP5 generally are more reliable than those derived from CMIP3, likely due to improvements in PPT simulations. At most locations across the CONUS, the largest differences between GSD and SD PPT and RUN occurred in the lowest part of the distributions (i.e., low-flow RUN and low-magnitude PPT). Results indicate that for the majority of the CONUS, there are downscaled GCMs that can reliably simulate historical climatic conditions. But, in some geographic locations, none of the SD GCMs replicated historical conditions for two of the three variables (PPT and RUN) based on the KS test, with a significance level of 0.05. In these locations, improved GCM simulations of PPT are needed to more reliably estimate components of the hydrologic cycle. Simple metrics and statistical tests, such as those described here, can provide an initial set of criteria to help simplify GCM selection.

  14. Containing Terrorism: A Dynamic Model

    Directory of Open Access Journals (Sweden)

    Giti Zahedzadeh

    2017-06-01

    Full Text Available The strategic interplay between counterterror measures and terror activity is complex. Herein, we propose a dynamic model to depict this interaction. The model generates stylized prognoses: (i under conditions of inefficient counterterror measures, terror groups enjoy longer period of activity but only if recruitment into terror groups remains low; high recruitment shortens the period of terror activity (ii highly efficient counterterror measures effectively contain terror activity, but only if recruitment remains low. Thus, highly efficient counterterror measures can effectively contain terrorism if recruitment remains restrained. We conclude that the trajectory of the dynamics between counterterror measures and terror activity is heavily altered by recruitment.

  15. Using the Weibull distribution reliability, modeling and inference

    CERN Document Server

    McCool, John I

    2012-01-01

    Understand and utilize the latest developments in Weibull inferential methods While the Weibull distribution is widely used in science and engineering, most engineers do not have the necessary statistical training to implement the methodology effectively. Using the Weibull Distribution: Reliability, Modeling, and Inference fills a gap in the current literature on the topic, introducing a self-contained presentation of the probabilistic basis for the methodology while providing powerful techniques for extracting information from data. The author explains the use of the Weibull distribution

  16. Understanding software faults and their role in software reliability modeling

    Science.gov (United States)

    Munson, John C.

    1994-01-01

    This study is a direct result of an on-going project to model the reliability of a large real-time control avionics system. In previous modeling efforts with this system, hardware reliability models were applied in modeling the reliability behavior of this system. In an attempt to enhance the performance of the adapted reliability models, certain software attributes were introduced in these models to control for differences between programs and also sequential executions of the same program. As the basic nature of the software attributes that affect software reliability become better understood in the modeling process, this information begins to have important implications on the software development process. A significant problem arises when raw attribute measures are to be used in statistical models as predictors, for example, of measures of software quality. This is because many of the metrics are highly correlated. Consider the two attributes: lines of code, LOC, and number of program statements, Stmts. In this case, it is quite obvious that a program with a high value of LOC probably will also have a relatively high value of Stmts. In the case of low level languages, such as assembly language programs, there might be a one-to-one relationship between the statement count and the lines of code. When there is a complete absence of linear relationship among the metrics, they are said to be orthogonal or uncorrelated. Usually the lack of orthogonality is not serious enough to affect a statistical analysis. However, for the purposes of some statistical analysis such as multiple regression, the software metrics are so strongly interrelated that the regression results may be ambiguous and possibly even misleading. Typically, it is difficult to estimate the unique effects of individual software metrics in the regression equation. The estimated values of the coefficients are very sensitive to slight changes in the data and to the addition or deletion of variables in the

  17. Dynamic thermo-hydraulic model of district cooling networks

    International Nuclear Information System (INIS)

    Oppelt, Thomas; Urbaneck, Thorsten; Gross, Ulrich; Platzer, Bernd

    2016-01-01

    Highlights: • A dynamic thermo-hydraulic model for district cooling networks is presented. • The thermal modelling is based on water segment tracking (Lagrangian approach). • Thus, numerical errors and balance inaccuracies are avoided. • Verification and validation studies proved the reliability of the model. - Abstract: In the present paper, the dynamic thermo-hydraulic model ISENA is presented which can be applied for answering different questions occurring in design and operation of district cooling networks—e.g. related to economic and energy efficiency. The network model consists of a quasistatic hydraulic model and a transient thermal model based on tracking water segments through the whole network (Lagrangian method). Applying this approach, numerical errors and balance inaccuracies can be avoided which leads to a higher quality of results compared to other network models. Verification and validation calculations are presented in order to show that ISENA provides reliable results and is suitable for practical application.

  18. Advanced RESTART method for the estimation of the probability of failure of highly reliable hybrid dynamic systems

    International Nuclear Information System (INIS)

    Turati, Pietro; Pedroni, Nicola; Zio, Enrico

    2016-01-01

    The efficient estimation of system reliability characteristics is of paramount importance for many engineering applications. Real world system reliability modeling calls for the capability of treating systems that are: i) dynamic, ii) complex, iii) hybrid and iv) highly reliable. Advanced Monte Carlo (MC) methods offer a way to solve these types of problems, which are feasible according to the potentially high computational costs. In this paper, the REpetitive Simulation Trials After Reaching Thresholds (RESTART) method is employed, extending it to hybrid systems for the first time (to the authors’ knowledge). The estimation accuracy and precision of RESTART highly depend on the choice of the Importance Function (IF) indicating how close the system is to failure: in this respect, proper IFs are here originally proposed to improve the performance of RESTART for the analysis of hybrid systems. The resulting overall simulation approach is applied to estimate the probability of failure of the control system of a liquid hold-up tank and of a pump-valve subsystem subject to degradation induced by fatigue. The results are compared to those obtained by standard MC simulation and by RESTART with classical IFs available in the literature. The comparison shows the improvement in the performance obtained by our approach. - Highlights: • We consider the issue of estimating small failure probabilities in dynamic systems. • We employ the RESTART method to estimate the failure probabilities. • New Importance Functions (IFs) are introduced to increase the method performance. • We adopt two dynamic, hybrid, highly reliable systems as case studies. • A comparison with literature IFs proves the effectiveness of the new IFs.

  19. Reliable low precision simulations in land surface models

    Science.gov (United States)

    Dawson, Andrew; Düben, Peter D.; MacLeod, David A.; Palmer, Tim N.

    2017-12-01

    Weather and climate models must continue to increase in both resolution and complexity in order that forecasts become more accurate and reliable. Moving to lower numerical precision may be an essential tool for coping with the demand for ever increasing model complexity in addition to increasing computing resources. However, there have been some concerns in the weather and climate modelling community over the suitability of lower precision for climate models, particularly for representing processes that change very slowly over long time-scales. These processes are difficult to represent using low precision due to time increments being systematically rounded to zero. Idealised simulations are used to demonstrate that a model of deep soil heat diffusion that fails when run in single precision can be modified to work correctly using low precision, by splitting up the model into a small higher precision part and a low precision part. This strategy retains the computational benefits of reduced precision whilst preserving accuracy. This same technique is also applied to a full complexity land surface model, resulting in rounding errors that are significantly smaller than initial condition and parameter uncertainties. Although lower precision will present some problems for the weather and climate modelling community, many of the problems can likely be overcome using a straightforward and physically motivated application of reduced precision.

  20. A dynamical model of terrorism

    Directory of Open Access Journals (Sweden)

    Firdaus Udwadia

    2006-01-01

    Full Text Available This paper develops a dynamical model of terrorism. We consider the population in a given region as being made up of three primary components: terrorists, those susceptible to both terrorist and pacifist propaganda, and nonsusceptibles, or pacifists. The dynamical behavior of these three populations is studied using a model that incorporates the effects of both direct military/police intervention to reduce the terrorist population, and nonviolent, persuasive intervention to influence the susceptibles to become pacifists. The paper proposes a new paradigm for studying terrorism, and looks at the long-term dynamical evolution in time of these three population components when such interventions are carried out. Many important features—some intuitive, others not nearly so—of the nature of terrorism emerge from the dynamical model proposed, and they lead to several important policy implications for the management of terrorism. The different circumstances in which nonviolent intervention and/or military/police intervention may be beneficial, and the specific conditions under which each mode of intervention, or a combination of both, may be useful, are obtained. The novelty of the model presented herein is that it deals with the time evolution of terrorist activity. It appears to be one of the few models that can be tested, evaluated, and improved upon, through the use of actual field data.

  1. A model for nuclear research reactor dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Barati, Ramin, E-mail: Barati.ramin@aut.ac.ir; Setayeshi, Saeed, E-mail: setayesh@aut.ac.ir

    2013-09-15

    Highlights: • A thirty-fourth order model is used to simulate the dynamics of a research reactor. • We consider delayed neutrons fraction as a function of time. • Variable fuel and temperature reactivity coefficients are used. • WIMS, BORGES and CITVAP codes are used for initial condition calculations. • Results are in agreement with experimental data rather than common codes. -- Abstract: In this paper, a useful thirty-fourth order model is presented to simulate the kinetics and dynamics of a research reactor core. The model considers relevant physical phenomena that govern the core such as reactor kinetics, reactivity feedbacks due to coolant and fuel temperatures (Doppler effects) with variable reactivity coefficients, xenon, samarium, boron concentration, fuel burn up and thermal hydraulics. WIMS and CITVAP codes are used to extract neutron cross sections and calculate the initial neuron flux respectively. The purpose is to present a model with results similar to reality as much as possible with reducing common simplifications in reactor modeling to be used in different analyses such as reactor control, functional reliability and safety. The model predictions are qualified by comparing with experimental data, detailed simulations of reactivity insertion transients, and steady state for Tehran research reactor reported in the literature and satisfactory results have been obtained.

  2. The validity and reliability of a dynamic neuromuscular stabilization-heel sliding test for core stability.

    Science.gov (United States)

    Cha, Young Joo; Lee, Jae Jin; Kim, Do Hyun; You, Joshua Sung H

    2017-10-23

    Core stabilization plays an important role in the regulation of postural stability. To overcome shortcomings associated with pain and severe core instability during conventional core stabilization tests, we recently developed the dynamic neuromuscular stabilization-based heel sliding (DNS-HS) test. The purpose of this study was to establish the criterion validity and test-retest reliability of the novel DNS-HS test. Twenty young adults with core instability completed both the bilateral straight leg lowering test (BSLLT) and DNS-HS test for the criterion validity study and repeated the DNS-HS test for the test-retest reliability study. Criterion validity was determined by comparing hip joint angle data that were obtained from BSLLT and DNS-HS measures. The test-retest reliability was determined by comparing hip joint angle data. Criterion validity was (ICC2,3) = 0.700 (preliability was (ICC3,3) = 0.953 (pvalidity data demonstrated a good relationship between the gold standard BSLLT and DNS-HS core stability measures. Test-retest reliability data suggests that DNS-HS core stability was a reliable test for core stability. Clinically, the DNS-HS test is useful to objectively quantify core instability and allow early detection and evaluation.

  3. Generative Models of Conformational Dynamics

    Science.gov (United States)

    Langmead, Christopher James

    2014-01-01

    Atomistic simulations of the conformational dynamics of proteins can be performed using either Molecular Dynamics or Monte Carlo procedures. The ensembles of three-dimensional structures produced during simulation can be analyzed in a number of ways to elucidate the thermodynamic and kinetic properties of the system. The goal of this chapter is to review both traditional and emerging methods for learning generative models from atomistic simulation data. Here, the term ‘generative’ refers to a model of the joint probability distribution over the behaviors of the constituent atoms. In the context of molecular modeling, generative models reveal the correlation structure between the atoms, and may be used to predict how the system will respond to structural perturbations. We begin by discussing traditional methods, which produce multivariate Gaussian models. We then discuss GAMELAN (GrAphical Models of Energy LANdscapes), which produces generative models of complex, non-Gaussian conformational dynamics (e.g., allostery, binding, folding, etc) from long timescale simulation data. PMID:24446358

  4. Reliable critical sized defect rodent model for cleft palate research.

    Science.gov (United States)

    Mostafa, Nesrine Z; Doschak, Michael R; Major, Paul W; Talwar, Reena

    2014-12-01

    Suitable animal models are necessary to test the efficacy of new bone grafting therapies in cleft palate surgery. Rodent models of cleft palate are available but have limitations. This study compared and modified mid-palate cleft (MPC) and alveolar cleft (AC) models to determine the most reliable and reproducible model for bone grafting studies. Published MPC model (9 × 5 × 3 mm(3)) lacked sufficient information for tested rats. Our initial studies utilizing AC model (7 × 4 × 3 mm(3)) in 8 and 16 weeks old Sprague Dawley (SD) rats revealed injury to adjacent structures. After comparing anteroposterior and transverse maxillary dimensions in 16 weeks old SD and Wistar rats, virtual planning was performed to modify MPC and AC defects dimensions, taking the adjacent structures into consideration. Modified MPC (7 × 2.5 × 1 mm(3)) and AC (5 × 2.5 × 1 mm(3)) defects were employed in 16 weeks old Wistar rats and healing was monitored by micro-computed tomography and histology. Maxillary dimensions in SD and Wistar rats were not significantly different. Preoperative virtual planning enhanced postoperative surgical outcomes. Bone healing occurred at defect margin leaving central bone void confirming the critical size nature of the modified MPC and AC defects. Presented modifications for MPC and AC models created clinically relevant and reproducible defects. Copyright © 2014 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.

  5. Benchmarking novel approaches for modelling species range dynamics.

    Science.gov (United States)

    Zurell, Damaris; Thuiller, Wilfried; Pagel, Jörn; Cabral, Juliano S; Münkemüller, Tamara; Gravel, Dominique; Dullinger, Stefan; Normand, Signe; Schiffers, Katja H; Moore, Kara A; Zimmermann, Niklaus E

    2016-08-01

    Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species' range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process-based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process-based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species' response to climate change but also emphasize several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches

  6. Experimental Modeling of Dynamic Systems

    DEFF Research Database (Denmark)

    Knudsen, Morten Haack

    2006-01-01

    An engineering course, Simulation and Experimental Modeling, has been developed that is based on a method for direct estimation of physical parameters in dynamic systems. Compared with classical system identification, the method appears to be easier to understand, apply, and combine with physical...

  7. Handbook of electrical power system dynamics modeling, stability, and control

    CERN Document Server

    Eremia, Mircea

    2013-01-01

    Complete guidance for understanding electrical power system dynamics and blackouts This handbook offers a comprehensive and up-to-date treatment of power system dynamics. Addressing the full range of topics, from the fundamentals to the latest technologies in modeling, stability, and control, Handbook of Electrical Power System Dynamics provides engineers with hands-on guidance for understanding the phenomena leading to blackouts so they can design the most appropriate solutions for a cost-effective and reliable operation. Focusing on system dynamics, the book details

  8. Reliability model for offshore wind farms; Paalidelighedsmodel for havvindmoelleparker

    Energy Technology Data Exchange (ETDEWEB)

    Christensen, P.; Lundtang Paulsen, J.; Lybech Toegersen, M.; Krogh, T. [Risoe National Lab., Roskilde (Denmark); Raben, N.; Donovan, M.H.; Joergensen, L. [SEAS (Denmark); Winther-Jensen, M.

    2002-05-01

    A method for the prediction of the mean availability for an offshore windfarm has been developed. Factors comprised are the reliability of the single turbine, the strategy for preventive maintenance the climate, the number of repair teams, and the type of boats available for transport. The mean availability is defined as the sum of the fractions of time, where each turbine is available for production. The project has been carried out together with SEAS Wind Technique, and their site Roedsand has been chosen as the example of the work. A climate model has been created based on actual site measurements. The prediction of the availability is done with a Monte Carlo-simulation. Software was developed for the preparation of the climate model from weather measurements as well as for the Monte carlo-simulation. Three examples have been simulated, one with guessed parametres, and the other two with parameters more close to the Roedsand case. (au)

  9. Scalable Joint Models for Reliable Uncertainty-Aware Event Prediction.

    Science.gov (United States)

    Soleimani, Hossein; Hensman, James; Saria, Suchi

    2017-08-21

    Missing data and noisy observations pose significant challenges for reliably predicting events from irregularly sampled multivariate time series (longitudinal) data. Imputation methods, which are typically used for completing the data prior to event prediction, lack a principled mechanism to account for the uncertainty due to missingness. Alternatively, state-of-the-art joint modeling techniques can be used for jointly modeling the longitudinal and event data and compute event probabilities conditioned on the longitudinal observations. These approaches, however, make strong parametric assumptions and do not easily scale to multivariate signals with many observations. Our proposed approach consists of several key innovations. First, we develop a flexible and scalable joint model based upon sparse multiple-output Gaussian processes. Unlike state-of-the-art joint models, the proposed model can explain highly challenging structure including non-Gaussian noise while scaling to large data. Second, we derive an optimal policy for predicting events using the distribution of the event occurrence estimated by the joint model. The derived policy trades-off the cost of a delayed detection versus incorrect assessments and abstains from making decisions when the estimated event probability does not satisfy the derived confidence criteria. Experiments on a large dataset show that the proposed framework significantly outperforms state-of-the-art techniques in event prediction.

  10. reliability reliability

    African Journals Online (AJOL)

    eobe

    Corresponding author, Tel: +234-703. RELIABILITY .... V , , given by the code of practice. However, checks must .... an optimization procedure over the failure domain F corresponding .... of Concrete Members based on Utility Theory,. Technical ...

  11. Reliability assessment using degradation models: bayesian and classical approaches

    Directory of Open Access Journals (Sweden)

    Marta Afonso Freitas

    2010-04-01

    Full Text Available Traditionally, reliability assessment of devices has been based on (accelerated life tests. However, for highly reliable products, little information about reliability is provided by life tests in which few or no failures are typically observed. Since most failures arise from a degradation mechanism at work for which there are characteristics that degrade over time, one alternative is monitor the device for a period of time and assess its reliability from the changes in performance (degradation observed during that period. The goal of this article is to illustrate how degradation data can be modeled and analyzed by using "classical" and Bayesian approaches. Four methods of data analysis based on classical inference are presented. Next we show how Bayesian methods can also be used to provide a natural approach to analyzing degradation data. The approaches are applied to a real data set regarding train wheels degradation.Tradicionalmente, o acesso à confiabilidade de dispositivos tem sido baseado em testes de vida (acelerados. Entretanto, para produtos altamente confiáveis, pouca informação a respeito de sua confiabilidade é fornecida por testes de vida no quais poucas ou nenhumas falhas são observadas. Uma vez que boa parte das falhas é induzida por mecanismos de degradação, uma alternativa é monitorar o dispositivo por um período de tempo e acessar sua confiabilidade através das mudanças em desempenho (degradação observadas durante aquele período. O objetivo deste artigo é ilustrar como dados de degradação podem ser modelados e analisados utilizando-se abordagens "clássicas" e Bayesiana. Quatro métodos de análise de dados baseados em inferência clássica são apresentados. A seguir, mostramos como os métodos Bayesianos podem também ser aplicados para proporcionar uma abordagem natural à análise de dados de degradação. As abordagens são aplicadas a um banco de dados real relacionado à degradação de rodas de trens.

  12. Business model dynamics and innovation

    DEFF Research Database (Denmark)

    Cavalcante, Sergio Andre; Kesting, Peter; Ulhøi, John Parm

    2011-01-01

    the impact of specific changes to a firm's business model. Such a tool would be particularly useful in identifying path dependencies and resistance at the process level, and would therefore allow a firm's management to take focused action on this in advance. Originality/value – The paper makes two main...... and specifies four different types of business model change: business model creation, extension, revision, and termination. Each type of business model change is associated with specific challenges. Practical implications – The proposed typology can serve as a basis for developing a management tool to evaluate......Purpose – This paper aims to discuss the need to dynamize the existing conceptualization of business model, and proposes a new typology to distinguish different types of business model change. Design/methodology/approach – The paper integrates basic insights of innovation, business process...

  13. On whole Abelian model dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Chauca, J.; Doria, R. [CBPF, Rio de Janeiro (Brazil); Aprendanet, Petropolis, 25600 (Brazil)

    2012-09-24

    Physics challenge is to determine the objects dynamics. However, there are two ways for deciphering the part. The first one is to search for the ultimate constituents; the second one is to understand its behaviour in whole terms. Therefore, the parts can be defined either from elementary constituents or as whole functions. Historically, science has been moving through the first aspect, however, quarks confinement and complexity are interrupting this usual approach. These relevant facts are supporting for a systemic vision be introduced. Our effort here is to study on the whole meaning through gauge theory. Consider a systemic dynamics oriented through the U(1) - systemic gauge parameter which function is to collect a fields set {l_brace}A{sub {mu}I}{r_brace}. Derive the corresponding whole gauge invariant Lagrangian, equations of motion, Bianchi identities, Noether relationships, charges and Ward-Takahashi equations. Whole Lorentz force and BRST symmetry are also studied. These expressions bring new interpretations further than the usual abelian model. They are generating a systemic system governed by 2N+ 10 classical equations plus Ward-Takahashi identities. A whole dynamics based on the notions of directive and circumstance is producing a set determinism where the parts dynamics are inserted in the whole evolution. A dynamics based on state, collective and individual equations with a systemic interdependence.

  14. A Dialogue about MCQs, Reliability, and Item Response Modelling

    Science.gov (United States)

    Wright, Daniel B.; Skagerberg, Elin M.

    2006-01-01

    Multiple choice questions (MCQs) are becoming more common in UK psychology departments and the need to assess their reliability is apparent. Having examined the reliability of MCQs in our department we faced many questions from colleagues about why we were examining reliability, what it was that we were doing, and what should be reported when…

  15. Relating structure and dynamics in organisation models

    NARCIS (Netherlands)

    Jonkers, C.M.; Treur, J.

    2002-01-01

    To understand how an organisational structure relates to dynamics is an interesting fundamental challenge in the area of social modelling. Specifications of organisational structure usually have a diagrammatic form that abstracts from more detailed dynamics. Dynamic properties of agent systems,

  16. Validated Loads Prediction Models for Offshore Wind Turbines for Enhanced Component Reliability

    DEFF Research Database (Denmark)

    Koukoura, Christina

    To improve the reliability of offshore wind turbines, accurate prediction of their response is required. Therefore, validation of models with site measurements is imperative. In the present thesis a 3.6MW pitch regulated-variable speed offshore wind turbine on a monopole foundation is built...... are used for the modification of the sub-structure/foundation design for possible material savings. First, the background of offshore wind engineering, including wind-wave conditions, support structure, blade loading and wind turbine dynamics are presented. Second, a detailed description of the site...

  17. Modelling MIZ dynamics in a global model

    Science.gov (United States)

    Rynders, Stefanie; Aksenov, Yevgeny; Feltham, Daniel; Nurser, George; Naveira Garabato, Alberto

    2016-04-01

    Exposure of large, previously ice-covered areas of the Arctic Ocean to the wind and surface ocean waves results in the Arctic pack ice cover becoming more fragmented and mobile, with large regions of ice cover evolving into the Marginal Ice Zone (MIZ). The need for better climate predictions, along with growing economic activity in the Polar Oceans, necessitates climate and forecasting models that can simulate fragmented sea ice with a greater fidelity. Current models are not fully fit for the purpose, since they neither model surface ocean waves in the MIZ, nor account for the effect of floe fragmentation on drag, nor include sea ice rheology that represents both the now thinner pack ice and MIZ ice dynamics. All these processes affect the momentum transfer to the ocean. We present initial results from a global ocean model NEMO (Nucleus for European Modelling of the Ocean) coupled to the Los Alamos sea ice model CICE. The model setup implements a novel rheological formulation for sea ice dynamics, accounting for ice floe collisions, thus offering a seamless framework for pack ice and MIZ simulations. The effect of surface waves on ice motion is included through wave pressure and the turbulent kinetic energy of ice floes. In the multidecadal model integrations we examine MIZ and basin scale sea ice and oceanic responses to the changes in ice dynamics. We analyse model sensitivities and attribute them to key sea ice and ocean dynamical mechanisms. The results suggest that the effect of the new ice rheology is confined to the MIZ. However with the current increase in summer MIZ area, which is projected to continue and may become the dominant type of sea ice in the Arctic, we argue that the effects of the combined sea ice rheology will be noticeable in large areas of the Arctic Ocean, affecting sea ice and ocean. With this study we assert that to make more accurate sea ice predictions in the changing Arctic, models need to include MIZ dynamics and physics.

  18. Modeling human intention formation for human reliability assessment

    International Nuclear Information System (INIS)

    Woods, D.D.; Roth, E.M.; Pople, H. Jr.

    1988-01-01

    This paper describes a dynamic simulation capability for modeling how people form intentions to act in nuclear power plant emergency situations. This modeling tool, Cognitive Environment Simulation or CES, was developed based on techniques from artificial intelligence. It simulates the cognitive processes that determine situation assessment and intention formation. It can be used to investigate analytically what situations and factors lead to intention failures, what actions follow from intention failures (e.g. errors of omission, errors of commission, common mode errors), the ability to recover from errors or additional machine failures, and the effects of changes in the NPP person machine system. One application of the CES modeling environment is to enhance the measurement of the human contribution to risk in probabilistic risk assessment studies. (author)

  19. Numerical Model based Reliability Estimation of Selective Laser Melting Process

    DEFF Research Database (Denmark)

    Mohanty, Sankhya; Hattel, Jesper Henri

    2014-01-01

    Selective laser melting is developing into a standard manufacturing technology with applications in various sectors. However, the process is still far from being at par with conventional processes such as welding and casting, the primary reason of which is the unreliability of the process. While...... of the selective laser melting process. A validated 3D finite-volume alternating-direction-implicit numerical technique is used to model the selective laser melting process, and is calibrated against results from single track formation experiments. Correlation coefficients are determined for process input...... parameters such as laser power, speed, beam profile, etc. Subsequently, uncertainties in the processing parameters are utilized to predict a range for the various outputs, using a Monte Carlo method based uncertainty analysis methodology, and the reliability of the process is established....

  20. Cognitive modelling: a basic complement of human reliability analysis

    International Nuclear Information System (INIS)

    Bersini, U.; Cacciabue, P.C.; Mancini, G.

    1988-01-01

    In this paper the issues identified in modelling humans and machines are discussed in the perspective of the consideration of human errors managing complex plants during incidental as well as normal conditions. The dichotomy between the use of a cognitive versus a behaviouristic model approach is discussed and the complementarity aspects rather than the differences of the two methods are identified. A cognitive model based on a hierarchical goal-oriented approach and driven by fuzzy logic methodology is presented as the counterpart to the 'classical' THERP methodology for studying human errors. Such a cognitive model is discussed at length and its fundamental components, i.e. the High Level Decision Making and the Low Level Decision Making models, are reviewed. Finally, the inadequacy of the 'classical' THERP methodology to deal with cognitive errors is discussed on the basis of a simple test case. For the same case the cognitive model is then applied showing the flexibility and adequacy of the model to dynamic configuration with time-dependent failures of components and with consequent need for changing of strategy during the transient itself. (author)

  1. Approaches to determining the reliability of a multimodal three-dimensional dynamic signature

    Directory of Open Access Journals (Sweden)

    Yury E. Kozlov

    2018-03-01

    Full Text Available The market of modern mobile applications has increasingly strict requirements for the authentication system reliability. This article examines an authentication method using a multimodal three-dimensional dynamic signature (MTDS, that can be used both as a main and additional method of user authentication in mobile applications. It is based on the use of gesture in the air performed by two independent mobile devices as an identifier. The MTDS method has certain advantages over currently used biometric methods, including fingerprint authentication, face recognition and voice recognition. A multimodal three-dimensional dynamic signature allows quickly changing an authentication gesture, as well as concealing the authentication procedure using gestures that do not attract attention. Despite all its advantages, the MTDS method has certain limitations, the main one is building functionally dynamic complex (FDC skills required for accurate repeating an authentication gesture. To correctly create MTDS need to have a system for assessing the reliability of gestures. Approaches to the solution of this task are grouped in this article according to methods of their implementation. Two of the approaches can be implemented only with the use of a server as a centralized MTDS processing center and one approach can be implemented using smartphone's own computing resources. The final part of the article provides data of testing one of these methods on a template performing the MTDS authentication.

  2. Reliability and responsiveness of dynamic contrast-enhanced magnetic resonance imaging in rheumatoid arthritis

    DEFF Research Database (Denmark)

    Axelsen, M.B.; Poggenborg, R.P.; Stoltenberg, M.

    2013-01-01

    intraarticular injection with 80 mg methylprednisolone. Using semi-automated image processing software, DCE-MRI parameters, including the initial rate of enhancement (IRE) and maximal enhancement (ME), were generated for three regions of interest (ROIs): ‘Whole slice’, ‘Quick ROI’, and ‘Precise ROI......Objectives: To investigate the responsiveness to treatment and the reliability of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in rheumatoid arthritis (RA) knee joints. Methods: DCE-MRI was performed in 12 clinically active RA knee joints before and 1, 7, 30, and 180 days after......’. The smallest detectable difference (SDD), the smallest detectable change (SDC), and intra- and inter-reader intraclass correlation coefficients (ICCs) were used to assess the reliability of DCE-MRI. Responsiveness to treatment was assessed by the standardized response mean (SRM). Results: In all patients...

  3. Social Dynamics Modeling and Inference

    Science.gov (United States)

    2018-03-29

    the experiment(s)/ theory and equipment or analyses. Development of innovative theoretical model and methodologies with experimental verifications...information. The methodology based on communication and information theory (thanks to leave at MIT supported by this research) is described in [J1], [C2...a dynamic system [C1] and as a social learning mechanism in details [J4]. Furthermore, by incentive seeding and rewiring connections, information

  4. Modeling high-Power Accelerators Reliability-SNS LINAC (SNS-ORNL); MAX LINAC (MYRRHA)

    International Nuclear Information System (INIS)

    Pitigoi, A. E.; Fernandez Ramos, P.

    2013-01-01

    Improving reliability has recently become a very important objective in the field of particle accelerators. The particle accelerators in operation are constantly undergoing modifications, and improvements are implemented using new technologies, more reliable components or redundant schemes (to obtain more reliability, strength, more power, etc.) A reliability model of SNS (Spallation Neutron Source) LINAC has been developed within MAX project and analysis of the accelerator systems reliability has been performed within the MAX project, using the Risk Spectrum reliability analysis software. The analysis results have been evaluated by comparison with the SNS operational data. Results and conclusions are presented in this paper, oriented to identify design weaknesses and provide recommendations for improving reliability of MYRRHA linear accelerator. The SNS reliability model developed for the MAX preliminary design phase indicates possible avenues for further investigation that could be needed to improve the reliability of the high-power accelerators, in view of the future reliability targets of ADS accelerators.

  5. Evaluating North American Electric Grid Reliability Using the Barabasi-Albert Network Model

    OpenAIRE

    Chassin, David P.; Posse, Christian

    2004-01-01

    The reliability of electric transmission systems is examined using a scale-free model of network structure and failure propagation. The topologies of the North American eastern and western electric networks are analyzed to estimate their reliability based on the Barabasi-Albert network model. A commonly used power system reliability index is computed using a simple failure propagation model. The results are compared to the values of power system reliability indices previously obtained using s...

  6. Testing substellar models with dynamical mass measurements

    Directory of Open Access Journals (Sweden)

    Liu M.C.

    2011-07-01

    Full Text Available We have been using Keck laser guide star adaptive optics to monitor the orbits of ultracool binaries, providing dynamical masses at lower luminosities and temperatures than previously available and enabling strong tests of theoretical models. We have identified three specific problems with theory: (1 We find that model color–magnitude diagrams cannot be reliably used to infer masses as they do not accurately reproduce the colors of ultracool dwarfs of known mass. (2 Effective temperatures inferred from evolutionary model radii are typically inconsistent with temperatures derived from fitting atmospheric models to observed spectra by 100–300 K. (3 For the only known pair of field brown dwarfs with a precise mass (3% and age determination (≈25%, the measured luminosities are ~2–3× higher than predicted by model cooling rates (i.e., masses inferred from Lbol and age are 20–30% larger than measured. To make progress in understanding the observed discrepancies, more mass measurements spanning a wide range of luminosity, temperature, and age are needed, along with more accurate age determinations (e.g., via asteroseismology for primary stars with brown dwarf binary companions. Also, resolved optical and infrared spectroscopy are needed to measure lithium depletion and to characterize the atmospheres of binary components in order to better assess model deficiencies.

  7. Response and reliability analysis of nonlinear uncertain dynamical structures by the probability density evolution method

    DEFF Research Database (Denmark)

    Nielsen, Søren R. K.; Peng, Yongbo; Sichani, Mahdi Teimouri

    2016-01-01

    The paper deals with the response and reliability analysis of hysteretic or geometric nonlinear uncertain dynamical systems of arbitrary dimensionality driven by stochastic processes. The approach is based on the probability density evolution method proposed by Li and Chen (Stochastic dynamics...... of structures, 1st edn. Wiley, London, 2009; Probab Eng Mech 20(1):33–44, 2005), which circumvents the dimensional curse of traditional methods for the determination of non-stationary probability densities based on Markov process assumptions and the numerical solution of the related Fokker–Planck and Kolmogorov......–Feller equations. The main obstacle of the method is that a multi-dimensional convolution integral needs to be carried out over the sample space of a set of basic random variables, for which reason the number of these need to be relatively low. In order to handle this problem an approach is suggested, which...

  8. Design Protocols and Analytical Strategies that Incorporate Structural Reliability Models

    Science.gov (United States)

    Duffy, Stephen F.

    1997-01-01

    Al single crystal turbine blade material; map a simplistic failure strength envelope of the material; develop a statistically based reliability computer algorithm, verify the reliability model and computer algorithm, and model stator vanes for rig tests. Thus establishing design protocols that enable the engineer to analyze and predict the mechanical behavior of ceramic composites and intermetallics would mitigate the prototype (trial and error) approach currently used by the engineering community. The primary objective of the research effort supported by this short term grant is the continued creation of enabling technologies for the macroanalysis of components fabricated from ceramic composites and intermetallic material systems. The creation of enabling technologies aids in shortening the product development cycle of components fabricated from the new high technology materials.

  9. Girsanov's transformation based variance reduced Monte Carlo simulation schemes for reliability estimation in nonlinear stochastic dynamics

    Science.gov (United States)

    Kanjilal, Oindrila; Manohar, C. S.

    2017-07-01

    The study considers the problem of simulation based time variant reliability analysis of nonlinear randomly excited dynamical systems. Attention is focused on importance sampling strategies based on the application of Girsanov's transformation method. Controls which minimize the distance function, as in the first order reliability method (FORM), are shown to minimize a bound on the sampling variance of the estimator for the probability of failure. Two schemes based on the application of calculus of variations for selecting control signals are proposed: the first obtains the control force as the solution of a two-point nonlinear boundary value problem, and, the second explores the application of the Volterra series in characterizing the controls. The relative merits of these schemes, vis-à-vis the method based on ideas from the FORM, are discussed. Illustrative examples, involving archetypal single degree of freedom (dof) nonlinear oscillators, and a multi-degree of freedom nonlinear dynamical system, are presented. The credentials of the proposed procedures are established by comparing the solutions with pertinent results from direct Monte Carlo simulations.

  10. DYNAMIC MODELLING OF VIBRATIONS ASSISTED DRILLING

    Directory of Open Access Journals (Sweden)

    Mathieu LADONNE

    2015-05-01

    Full Text Available The number of multi-materials staking configurations for aeronautical structures is increasing, with the evolution of composite and metallic materials. For drilling the fastening holes, the processes of Vibration Assisted Drilling (VAD expand rapidly, as it permits to improve reliability of drilling operations on multilayer structures. Among these processes of VAD, the solution with forced vibrations added to conventional feed to create a discontinuous cutting is the more developed in industry. The back and forth movement allows to improve the evacuation of chips by breaking it. This technology introduces two new operating parameters, the frequency and the amplitude of the oscillation. To optimize the process, the choice of those parameters requires first to model precisely the operation cutting and dynamics. In this paper, a kinematic modelling of the process is firstly proposed. The limits of the model are analysed through comparison between simulations and measurements. The proposed model is used to develop a cutting force model that allows foreseeing the operating conditions which ensure good chips breaking and tool life improvement.

  11. Multiscale modeling of pedestrian dynamics

    CERN Document Server

    Cristiani, Emiliano; Tosin, Andrea

    2014-01-01

    This book presents mathematical models and numerical simulations of crowd dynamics. The core topic is the development of a new multiscale paradigm, which bridges the microscopic and macroscopic scales taking the most from each of them for capturing the relevant clues of complexity of crowds. The background idea is indeed that most of the complex trends exhibited by crowds are due to an intrinsic interplay between individual and collective behaviors. The modeling approach promoted in this book pursues actively this intuition and profits from it for designing general mathematical structures susceptible of application also in fields different from the inspiring original one. The book considers also the two most traditional points of view: the microscopic one, in which pedestrians are tracked individually, and the macroscopic one, in which pedestrians are assimilated to a continuum. Selected existing models are critically analyzed. The work is addressed to researchers and graduate students.

  12. Impact of Loss Synchronization on Reliable High Speed Networks: A Model Based Simulation

    Directory of Open Access Journals (Sweden)

    Suman Kumar

    2014-01-01

    Full Text Available Contemporary nature of network evolution demands for simulation models which are flexible, scalable, and easily implementable. In this paper, we propose a fluid based model for performance analysis of reliable high speed networks. In particular, this paper aims to study the dynamic relationship between congestion control algorithms and queue management schemes, in order to develop a better understanding of the causal linkages between the two. We propose a loss synchronization module which is user configurable. We validate our model through simulations under controlled settings. Also, we present a performance analysis to provide insights into two important issues concerning 10 Gbps high speed networks: (i impact of bottleneck buffer size on the performance of 10 Gbps high speed network and (ii impact of level of loss synchronization on link utilization-fairness tradeoffs. The practical impact of the proposed work is to provide design guidelines along with a powerful simulation tool to protocol designers and network developers.

  13. Approach for an integral power transformer reliability model

    NARCIS (Netherlands)

    Schijndel, van A.; Wouters, P.A.A.F.; Steennis, E.F.; Wetzer, J.M.

    2012-01-01

    In electrical power transmission and distribution networks power transformers represent a crucial group of assets both in terms of reliability and investments. In order to safeguard the required quality at acceptable costs, decisions must be based on a reliable forecast of future behaviour. The aim

  14. Wireless Channel Modeling Perspectives for Ultra-Reliable Communications

    DEFF Research Database (Denmark)

    Eggers, Patrick Claus F.; Popovski, Petar

    2018-01-01

    Ultra-Reliable Communication (URC) is one of the distinctive features of the upcoming 5G wireless communication. The level of reliability, going down to packet error rates (PER) of $10^{-9}$, should be sufficiently convincing in order to remove cables in an industrial setting or provide remote co...

  15. The FFA dynamic stall model. The Beddoes-Leishman dynamic stall model modified for lead-lag oscillations

    Energy Technology Data Exchange (ETDEWEB)

    Bjoerck, A. [FFA, The Aeronautical Research Institute of Sweden, Bromma (Sweden)

    1997-08-01

    For calculations of the dynamics of wind turbines the inclusion of a dynamic stall model is necessary in order to obtain reliable results at high winds. For blade vibrations in the lead-lag motion the velocity relative to the blade will vary in time. In the present paper modifications to the Beddoes-Leishman model is presented in order to improve the model for calculations of cases with a varying relative velocity. Comparisons with measurement are also shown and the influence on the calculated aerodynamic damping by the modifications are investigated. (au)

  16. Modeling Manufacturing Impacts on Aging and Reliability of Polyurethane Foams

    Energy Technology Data Exchange (ETDEWEB)

    Rao, Rekha R.; Roberts, Christine Cardinal; Mondy, Lisa Ann; Soehnel, Melissa Marie; Johnson, Kyle; Lorenzo, Henry T.

    2016-10-01

    Polyurethane is a complex multiphase material that evolves from a viscous liquid to a system of percolating bubbles, which are created via a CO2 generating reaction. The continuous phase polymerizes to a solid during the foaming process generating heat. Foams introduced into a mold increase their volume up to tenfold, and the dynamics of the expansion process may lead to voids and will produce gradients in density and degree of polymerization. These inhomogeneities can lead to structural stability issues upon aging. For instance, structural components in weapon systems have been shown to change shape as they age depending on their molding history, which can threaten critical tolerances. The purpose of this project is to develop a Cradle-to-Grave multiphysics model, which allows us to predict the material properties of foam from its birth through aging in the stockpile, where its dimensional stability is important.

  17. Reliability of multi-model and structurally different single-model ensembles

    Energy Technology Data Exchange (ETDEWEB)

    Yokohata, Tokuta [National Institute for Environmental Studies, Center for Global Environmental Research, Tsukuba, Ibaraki (Japan); Annan, James D.; Hargreaves, Julia C. [Japan Agency for Marine-Earth Science and Technology, Research Institute for Global Change, Yokohama, Kanagawa (Japan); Collins, Matthew [University of Exeter, College of Engineering, Mathematics and Physical Sciences, Exeter (United Kingdom); Jackson, Charles S.; Tobis, Michael [The University of Texas at Austin, Institute of Geophysics, 10100 Burnet Rd., ROC-196, Mail Code R2200, Austin, TX (United States); Webb, Mark J. [Met Office Hadley Centre, Exeter (United Kingdom)

    2012-08-15

    The performance of several state-of-the-art climate model ensembles, including two multi-model ensembles (MMEs) and four structurally different (perturbed parameter) single model ensembles (SMEs), are investigated for the first time using the rank histogram approach. In this method, the reliability of a model ensemble is evaluated from the point of view of whether the observations can be regarded as being sampled from the ensemble. Our analysis reveals that, in the MMEs, the climate variables we investigated are broadly reliable on the global scale, with a tendency towards overdispersion. On the other hand, in the SMEs, the reliability differs depending on the ensemble and variable field considered. In general, the mean state and historical trend of surface air temperature, and mean state of precipitation are reliable in the SMEs. However, variables such as sea level pressure or top-of-atmosphere clear-sky shortwave radiation do not cover a sufficiently wide range in some. It is not possible to assess whether this is a fundamental feature of SMEs generated with particular model, or a consequence of the algorithm used to select and perturb the values of the parameters. As under-dispersion is a potentially more serious issue when using ensembles to make projections, we recommend the application of rank histograms to assess reliability when designing and running perturbed physics SMEs. (orig.)

  18. Models and data requirements for human reliability analysis

    International Nuclear Information System (INIS)

    1989-03-01

    It has been widely recognised for many years that the safety of the nuclear power generation depends heavily on the human factors related to plant operation. This has been confirmed by the accidents at Three Mile Island and Chernobyl. Both these cases revealed how human actions can defeat engineered safeguards and the need for special operator training to cover the possibility of unexpected plant conditions. The importance of the human factor also stands out in the analysis of abnormal events and insights from probabilistic safety assessments (PSA's), which reveal a large proportion of cases having their origin in faulty operator performance. A consultants' meeting, organized jointly by the International Atomic Energy Agency (IAEA) and the International Institute for Applied Systems Analysis (IIASA) was held at IIASA in Laxenburg, Austria, December 7-11, 1987, with the aim of reviewing existing models used in Probabilistic Safety Assessment (PSA) for Human Reliability Analysis (HRA) and of identifying the data required. The report collects both the contributions offered by the members of the Expert Task Force and the findings of the extensive discussions that took place during the meeting. Refs, figs and tabs

  19. Evaluating system behavior through Dynamic Master Logic Diagram (DMLD) modeling

    International Nuclear Information System (INIS)

    Hu, Y.-S.; Modarres, Mohammad

    1999-01-01

    In this paper, the Dynamic Master Logic Diagram (DMLD) is introduced for representing full-scale time-dependent behavior and uncertain behavior of complex physical systems. Conceptually, the DMLD allows one to decompose a complex system hierarchically to model and to represent: (1) partial success/failure of the system, (2) full-scale logical, physical and fuzzy connectivity relations, (3) probabilistic, resolutional or linguistic uncertainty, (4) multiple-state system dynamics, and (5) floating threshold and transition effects. To demonstrate the technique, examples of using DMLD to model, to diagnose and to control dynamic behavior of a system are presented. A DMLD-based expert system building tool, called Dynamic Reliability Expert System (DREXs), is introduced to automate the DMLD modeling process

  20. Integrating software reliability concepts into risk and reliability modeling of digital instrumentation and control systems used in nuclear power plants

    International Nuclear Information System (INIS)

    Arndt, S. A.

    2006-01-01

    As software-based digital systems are becoming more and more common in all aspects of industrial process control, including the nuclear power industry, it is vital that the current state of the art in quality, reliability, and safety analysis be advanced to support the quantitative review of these systems. Several research groups throughout the world are working on the development and assessment of software-based digital system reliability methods and their applications in the nuclear power, aerospace, transportation, and defense industries. However, these groups are hampered by the fact that software experts and probabilistic safety assessment experts view reliability engineering very differently. This paper discusses the characteristics of a common vocabulary and modeling framework. (authors)

  1. MATHEMATICAL MODEL FOR RIVERBOAT DYNAMICS

    Directory of Open Access Journals (Sweden)

    Aleksander Grm

    2017-01-01

    Full Text Available Present work describes a simple dynamical model for riverboat motion based on the square drag law. Air and water interactions with the boat are determined from aerodynamic coefficients. CFX simulations were performed with fully developed turbulent flow to determine boat aerodynamic coefficients for an arbitrary angle of attack for the air and water portions separately. The effect of wave resistance is negligible compared to other forces. Boat movement analysis considers only two-dimensional motion, therefore only six aerodynamics coefficients are required. The proposed model is solved and used to determine the critical environmental parameters (wind and current under which river navigation can be conducted safely. Boat simulator was tested in a single area on the Ljubljanica river and estimated critical wind velocity.

  2. CoDCon Dynamic Modeling.

    Energy Technology Data Exchange (ETDEWEB)

    Cipiti, Benjamin B. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-03-01

    The Co-Decontamination (CoDCon) Demonstration project is designed to test the separation of a mixed U and Pu product from dissolved spent nuclear fuel. The primary purpose of the project is to quantify the accuracy and precision to which a U/Pu mass ratio can be achieved without removing a pure Pu product. The system includes an on-line monitoring system using spectroscopy to monitor the ratios throughout the process. A dynamic model of the CoDCon flowsheet and on-line monitoring system was developed in order to expand the range of scenarios that can be examined for process control and determine overall measurement uncertainty. The model development and initial results are presented here.

  3. Modeling the dynamics of choice.

    Science.gov (United States)

    Baum, William M; Davison, Michael

    2009-06-01

    A simple linear-operator model both describes and predicts the dynamics of choice that may underlie the matching relation. We measured inter-food choice within components of a schedule that presented seven different pairs of concurrent variable-interval schedules for 12 food deliveries each with no signals indicating which pair was in force. This measure of local choice was accurately described and predicted as obtained reinforcer sequences shifted it to favor one alternative or the other. The effect of a changeover delay was reflected in one parameter, the asymptote, whereas the effect of a difference in overall rate of food delivery was reflected in the other parameter, rate of approach to the asymptote. The model takes choice as a primary dependent variable, not derived by comparison between alternatives-an approach that agrees with the molar view of behaviour.

  4. The Quadrotor Dynamic Modeling and Indoor Target Tracking Control Method

    Directory of Open Access Journals (Sweden)

    Dewei Zhang

    2014-01-01

    Full Text Available A reliable nonlinear dynamic model of the quadrotor is presented. The nonlinear dynamic model includes actuator dynamic and aerodynamic effect. Since the rotors run near a constant hovering speed, the dynamic model is simplified at hovering operating point. Based on the simplified nonlinear dynamic model, the PID controllers with feedback linearization and feedforward control are proposed using the backstepping method. These controllers are used to control both the attitude and position of the quadrotor. A fully custom quadrotor is developed to verify the correctness of the dynamic model and control algorithms. The attitude of the quadrotor is measured by inertia measurement unit (IMU. The position of the quadrotor in a GPS-denied environment, especially indoor environment, is estimated from the downward camera and ultrasonic sensor measurements. The validity and effectiveness of the proposed dynamic model and control algorithms are demonstrated by experimental results. It is shown that the vehicle achieves robust vision-based hovering and moving target tracking control.

  5. Science-Based Simulation Model of Human Performance for Human Reliability Analysis

    International Nuclear Information System (INIS)

    Kelly, Dana L.; Boring, Ronald L.; Mosleh, Ali; Smidts, Carol

    2011-01-01

    Human reliability analysis (HRA), a component of an integrated probabilistic risk assessment (PRA), is the means by which the human contribution to risk is assessed, both qualitatively and quantitatively. However, among the literally dozens of HRA methods that have been developed, most cannot fully model and quantify the types of errors that occurred at Three Mile Island. Furthermore, all of the methods lack a solid empirical basis, relying heavily on expert judgment or empirical results derived in non-reactor domains. Finally, all of the methods are essentially static, and are thus unable to capture the dynamics of an accident in progress. The objective of this work is to begin exploring a dynamic simulation approach to HRA, one whose models have a basis in psychological theories of human performance, and whose quantitative estimates have an empirical basis. This paper highlights a plan to formalize collaboration among the Idaho National Laboratory (INL), the University of Maryland, and The Ohio State University (OSU) to continue development of a simulation model initially formulated at the University of Maryland. Initial work will focus on enhancing the underlying human performance models with the most recent psychological research, and on planning follow-on studies to establish an empirical basis for the model, based on simulator experiments to be carried out at the INL and at the OSU.

  6. Dynamical modeling of tidal streams

    International Nuclear Information System (INIS)

    Bovy, Jo

    2014-01-01

    I present a new framework for modeling the dynamics of tidal streams. The framework consists of simple models for the initial action-angle distribution of tidal debris, which can be straightforwardly evolved forward in time. Taking advantage of the essentially one-dimensional nature of tidal streams, the transformation to position-velocity coordinates can be linearized and interpolated near a small number of points along the stream, thus allowing for efficient computations of a stream's properties in observable quantities. I illustrate how to calculate the stream's average location (its 'track') in different coordinate systems, how to quickly estimate the dispersion around its track, and how to draw mock stream data. As a generative model, this framework allows one to compute the full probability distribution function and marginalize over or condition it on certain phase-space dimensions as well as convolve it with observational uncertainties. This will be instrumental in proper data analysis of stream data. In addition to providing a computationally efficient practical tool for modeling the dynamics of tidal streams, the action-angle nature of the framework helps elucidate how the observed width of the stream relates to the velocity dispersion or mass of the progenitor, and how the progenitors of 'orphan' streams could be located. The practical usefulness of the proposed framework crucially depends on the ability to calculate action-angle variables for any orbit in any gravitational potential. A novel method for calculating actions, frequencies, and angles in any static potential using a single orbit integration is described in the Appendix.

  7. Dynamic modeling and simulation of power transformer maintenance costs

    Directory of Open Access Journals (Sweden)

    Ristić Olga

    2016-01-01

    Full Text Available The paper presents the dynamic model of maintenance costs of the power transformer functional components. Reliability is modeled combining the exponential and Weibull's distribution. The simulation was performed with the aim of corrective maintenance and installation of the continuous monitoring system of the most critical components. Simulation Dynamic System (SDS method and VENSIM PLE software was used to simulate the cost. In this way, significant savings in maintenance costs will be achieved with a small initial investment. [Projekat Ministarstva nauke Republike Srbije, br. III 41025 i br. OI 171007

  8. Reliability Analysis of Wireless Sensor Networks Using Markovian Model

    Directory of Open Access Journals (Sweden)

    Jin Zhu

    2012-01-01

    Full Text Available This paper investigates reliability analysis of wireless sensor networks whose topology is switching among possible connections which are governed by a Markovian chain. We give the quantized relations between network topology, data acquisition rate, nodes' calculation ability, and network reliability. By applying Lyapunov method, sufficient conditions of network reliability are proposed for such topology switching networks with constant or varying data acquisition rate. With the conditions satisfied, the quantity of data transported over wireless network node will not exceed node capacity such that reliability is ensured. Our theoretical work helps to provide a deeper understanding of real-world wireless sensor networks, which may find its application in the fields of network design and topology control.

  9. Modeling, implementation, and validation of arterial travel time reliability : [summary].

    Science.gov (United States)

    2013-11-01

    Travel time reliability (TTR) has been proposed as : a better measure of a facilitys performance than : a statistical measure like peak hour demand. TTR : is based on more information about average traffic : flows and longer time periods, thus inc...

  10. Modeling, implementation, and validation of arterial travel time reliability.

    Science.gov (United States)

    2013-11-01

    Previous research funded by Florida Department of Transportation (FDOT) developed a method for estimating : travel time reliability for arterials. This method was not initially implemented or validated using field data. This : project evaluated and r...

  11. Study of redundant Models in reliability prediction of HXMT's HES

    International Nuclear Information System (INIS)

    Wang Jinming; Liu Congzhan; Zhang Zhi; Ji Jianfeng

    2010-01-01

    Two redundant equipment structures of HXMT's HES are proposed firstly, the block backup and dual system cold-redundancy. Then prediction of the reliability is made by using parts count method. Research of comparison and analysis is also performed on the two proposals. A conclusion is drawn that a higher reliability and longer service life could be offered by taking a redundant equipment structure of block backup. (authors)

  12. Dynamical Models for Computer Viruses Propagation

    Directory of Open Access Journals (Sweden)

    José R. C. Piqueira

    2008-01-01

    Full Text Available Nowadays, digital computer systems and networks are the main engineering tools, being used in planning, design, operation, and control of all sizes of building, transportation, machinery, business, and life maintaining devices. Consequently, computer viruses became one of the most important sources of uncertainty, contributing to decrease the reliability of vital activities. A lot of antivirus programs have been developed, but they are limited to detecting and removing infections, based on previous knowledge of the virus code. In spite of having good adaptation capability, these programs work just as vaccines against diseases and are not able to prevent new infections based on the network state. Here, a trial on modeling computer viruses propagation dynamics relates it to other notable events occurring in the network permitting to establish preventive policies in the network management. Data from three different viruses are collected in the Internet and two different identification techniques, autoregressive and Fourier analyses, are applied showing that it is possible to forecast the dynamics of a new virus propagation by using the data collected from other viruses that formerly infected the network.

  13. Parameter estimation of component reliability models in PSA model of Krsko NPP

    International Nuclear Information System (INIS)

    Jordan Cizelj, R.; Vrbanic, I.

    2001-01-01

    In the paper, the uncertainty analysis of component reliability models for independent failures is shown. The present approach for parameter estimation of component reliability models in NPP Krsko is presented. Mathematical approaches for different types of uncertainty analyses are introduced and used in accordance with some predisposed requirements. Results of the uncertainty analyses are shown in an example for time-related components. As the most appropriate uncertainty analysis proved the Bayesian estimation with the numerical estimation of a posterior, which can be approximated with some appropriate probability distribution, in this paper with lognormal distribution.(author)

  14. Reliability model analysis and primary experimental evaluation of laser triggered pulse trigger

    International Nuclear Information System (INIS)

    Chen Debiao; Yang Xinglin; Li Yuan; Li Jin

    2012-01-01

    High performance pulse trigger can enhance performance and stability of the PPS. It is necessary to evaluate the reliability of the LTGS pulse trigger, so we establish the reliability analysis model of this pulse trigger based on CARMES software, the reliability evaluation is accord with the statistical results. (authors)

  15. 78 FR 45447 - Revisions to Modeling, Data, and Analysis Reliability Standard

    Science.gov (United States)

    2013-07-29

    ...; Order No. 782] Revisions to Modeling, Data, and Analysis Reliability Standard AGENCY: Federal Energy... Analysis (MOD) Reliability Standard MOD- 028-2, submitted to the Commission for approval by the North... Organization. The Commission finds that the proposed Reliability Standard represents an improvement over the...

  16. Dynamic analysis and reliability assessment of structures with uncertain-but-bounded parameters under stochastic process excitations

    International Nuclear Information System (INIS)

    Do, Duy Minh; Gao, Wei; Song, Chongmin; Tangaramvong, Sawekchai

    2014-01-01

    This paper presents the non-deterministic dynamic analysis and reliability assessment of structures with uncertain-but-bounded parameters under stochastic process excitations. Random ground acceleration from earthquake motion is adopted to illustrate the stochastic process force. The exact change ranges of natural frequencies, random vibration displacement and stress responses of structures are investigated under the interval analysis framework. Formulations for structural reliability are developed considering the safe boundary and structural random vibration responses as interval parameters. An improved particle swarm optimization algorithm, namely randomised lower sequence initialized high-order nonlinear particle swarm optimization algorithm, is employed to capture the better bounds of structural dynamic characteristics, random vibration responses and reliability. Three numerical examples are used to demonstrate the presented method for interval random vibration analysis and reliability assessment of structures. The accuracy of the results obtained by the presented method is verified by the randomised Quasi-Monte Carlo simulation method (QMCSM) and direct Monte Carlo simulation method (MCSM). - Highlights: • Interval uncertainty is introduced into structural random vibration responses. • Interval dynamic reliability assessments of structures are implemented. • Boundaries of structural dynamic response and reliability are achieved

  17. Computer Model to Estimate Reliability Engineering for Air Conditioning Systems

    International Nuclear Information System (INIS)

    Afrah Al-Bossly, A.; El-Berry, A.; El-Berry, A.

    2012-01-01

    Reliability engineering is used to predict the performance and optimize design and maintenance of air conditioning systems. Air conditioning systems are expose to a number of failures. The failures of an air conditioner such as turn on, loss of air conditioner cooling capacity, reduced air conditioning output temperatures, loss of cool air supply and loss of air flow entirely can be due to a variety of problems with one or more components of an air conditioner or air conditioning system. Forecasting for system failure rates are very important for maintenance. This paper focused on the reliability of the air conditioning systems. Statistical distributions that were commonly applied in reliability settings: the standard (2 parameter) Weibull and Gamma distributions. After distributions parameters had been estimated, reliability estimations and predictions were used for evaluations. To evaluate good operating condition in a building, the reliability of the air conditioning system that supplies conditioned air to the several The company's departments. This air conditioning system is divided into two, namely the main chilled water system and the ten air handling systems that serves the ten departments. In a chilled-water system the air conditioner cools water down to 40-45 degree F (4-7 degree C). The chilled water is distributed throughout the building in a piping system and connected to air condition cooling units wherever needed. Data analysis has been done with support a computer aided reliability software, this is due to the Weibull and Gamma distributions indicated that the reliability for the systems equal to 86.012% and 77.7% respectively. A comparison between the two important families of distribution functions, namely, the Weibull and Gamma families was studied. It was found that Weibull method performed for decision making.

  18. Improved resolution and reliability in dynamic PET using Bayesian regularization of MRTM2

    DEFF Research Database (Denmark)

    Agn, Mikael; Svarer, Claus; Frokjaer, Vibe G.

    2014-01-01

    This paper presents a mathematical model that regularizes dynamic PET data by using a Bayesian framework. We base the model on the well known two-parameter multilinear reference tissue method MRTM2 and regularize on the assumption that spatially close regions have similar parameters. The developed...... model is compared to the conventional approach of improving the low signal-to-noise ratio of PET data, i.e., spatial filtering of each time frame independently by a Gaussian kernel. We show that the model handles high levels of noise better than the conventional approach, while at the same time...

  19. A dynamic programming algorithm for the buffer allocation problem in homogeneous asymptotically reliable serial production lines

    Directory of Open Access Journals (Sweden)

    Diamantidis A. C.

    2004-01-01

    Full Text Available In this study, the buffer allocation problem (BAP in homogeneous, asymptotically reliable serial production lines is considered. A known aggregation method, given by Lim, Meerkov, and Top (1990, for the performance evaluation (i.e., estimation of throughput of this type of production lines when the buffer allocation is known, is used as an evaluative method in conjunction with a newly developed dynamic programming (DP algorithm for the BAP. The proposed algorithm is applied to production lines where the number of machines is varying from four up to a hundred machines. The proposed algorithm is fast because it reduces the volume of computations by rejecting allocations that do not lead to maximization of the line's throughput. Numerical results are also given for large production lines.

  20. Reliability and Minimum Detectable Change of Temporal-Spatial, Kinematic, and Dynamic Stability Measures during Perturbed Gait.

    Directory of Open Access Journals (Sweden)

    Christopher A Rábago

    Full Text Available Temporal-spatial, kinematic variability, and dynamic stability measures collected during perturbation-based assessment paradigms are often used to identify dysfunction associated with gait instability. However, it remains unclear which measures are most reliable for detecting and tracking responses to perturbations. This study systematically determined the between-session reliability and minimum detectable change values of temporal-spatial, kinematic variability, and dynamic stability measures during three types of perturbed gait. Twenty young healthy adults completed two identical testing sessions two weeks apart, comprised of an unperturbed and three perturbed (cognitive, physical, and visual walking conditions in a virtual reality environment. Within each session, perturbation responses were compared to unperturbed walking using paired t-tests. Between-session reliability and minimum detectable change values were also calculated for each measure and condition. All temporal-spatial, kinematic variability and dynamic stability measures demonstrated fair to excellent between-session reliability. Minimal detectable change values, normalized to mean values ranged from 1-50%. Step width mean and variability measures demonstrated the greatest response to perturbations with excellent between-session reliability and low minimum detectable change values. Orbital stability measures demonstrated specificity to perturbation direction and sensitivity with excellent between-session reliability and low minimum detectable change values. We observed substantially greater between-session reliability and lower minimum detectable change values for local stability measures than previously described which may be the result of averaging across trials within a session and using velocity versus acceleration data for reconstruction of state spaces. Across all perturbation types, temporal-spatial, orbital and local measures were the most reliable measures with the

  1. Possibilities and limitations of applying software reliability growth models to safety-critical software

    International Nuclear Information System (INIS)

    Kim, Man Cheol; Jang, Seung Cheol; Ha, Jae Joo

    2007-01-01

    It is generally known that software reliability growth models such as the Jelinski-Moranda model and the Goel-Okumoto's Non-Homogeneous Poisson Process (NHPP) model cannot be applied to safety-critical software due to a lack of software failure data. In this paper, by applying two of the most widely known software reliability growth models to sample software failure data, we demonstrate the possibility of using the software reliability growth models to prove the high reliability of safety-critical software. The high sensitivity of a piece of software's reliability to software failure data, as well as a lack of sufficient software failure data, is also identified as a possible limitation when applying the software reliability growth models to safety-critical software

  2. System Dynamics Modelling for a Balanced Scorecard

    DEFF Research Database (Denmark)

    Nielsen, Steen; Nielsen, Erland Hejn

    2008-01-01

    /methodology/approach - We use a case study model to develop time or dynamic dimensions by using a System Dynamics modelling (SDM) approach. The model includes five perspectives and a number of financial and non-financial measures. All indicators are defined and related to a coherent number of different cause...... have a major influence on other indicators and profit and may be impossible to predict without using a dynamic model. Practical implications - The model may be used as the first step in quantifying the cause-and-effect relationships of an integrated BSC model. Using the System Dynamics model provides......Purpose - To construct a dynamic model/framework inspired by a case study based on an international company. As described by the theory, one of the main difficulties of BSC is to foresee the time lag dimension of different types of indicators and their combined dynamic effects. Design...

  3. Reliability of corneal dynamic scheimpflug analyser measurements in virgin and post-PRK eyes.

    Directory of Open Access Journals (Sweden)

    Xiangjun Chen

    Full Text Available PURPOSE: To determine the measurement reliability of CorVis ST, a dynamic Scheimpflug analyser, in virgin and post-photorefractive keratectomy (PRK eyes and compare the results between these two groups. METHODS: Forty virgin eyes and 42 post-PRK eyes underwent CorVis ST measurements performed by two technicians. Repeatability was evaluated by comparing three consecutive measurements by technician A. Reproducibility was determined by comparing the first measurement by technician A with one performed by technician B. Intraobserver and interobserver intraclass correlation coefficients (ICCs were calculated. Univariate analysis of covariance (ANCOVA was used to compare measured parameters between virgin and post-PRK eyes. RESULTS: The intraocular pressure (IOP, central corneal thickness (CCT and 1st applanation time demonstrated good intraobserver repeatability and interobserver reproducibility (ICC ≧ 0.90 in virgin and post-PRK eyes. The deformation amplitude showed a good or close to good repeatability and reproducibility in both groups (ICC ≧ 0.88. The CCT correlated positively with 1st applanation time (r = 0.437 and 0.483, respectively, p<0.05 and negatively with deformation amplitude (r = -0.384 and -0.375, respectively, p<0.05 in both groups. Compared to post-PRK eyes, virgin eyes showed longer 1st applanation time (7.29 ± 0.21 vs. 6.96 ± 0.17 ms, p<0.05 and lower deformation amplitude (1.06 ± 0.07 vs. 1.17 ± 0.08 mm, p < 0.05. CONCLUSIONS: CorVis ST demonstrated reliable measurements for CCT, IOP, and 1st applanation time, as well as relatively reliable measurement for deformation amplitude in both virgin and post-PRK eyes. There were differences in 1st applanation time and deformation amplitude between virgin and post-PRK eyes, which may reflect corneal biomechanical changes occurring after the surgery in the latter.

  4. An adaptive cubature formula for efficient reliability assessment of nonlinear structural dynamic systems

    Science.gov (United States)

    Xu, Jun; Kong, Fan

    2018-05-01

    Extreme value distribution (EVD) evaluation is a critical topic in reliability analysis of nonlinear structural dynamic systems. In this paper, a new method is proposed to obtain the EVD. The maximum entropy method (MEM) with fractional moments as constraints is employed to derive the entire range of EVD. Then, an adaptive cubature formula is proposed for fractional moments assessment involved in MEM, which is closely related to the efficiency and accuracy for reliability analysis. Three point sets, which include a total of 2d2 + 1 integration points in the dimension d, are generated in the proposed formula. In this regard, the efficiency of the proposed formula is ensured. Besides, a "free" parameter is introduced, which makes the proposed formula adaptive with the dimension. The "free" parameter is determined by arranging one point set adjacent to the boundary of the hyper-sphere which contains the bulk of total probability. In this regard, the tail distribution may be better reproduced and the fractional moments could be evaluated with accuracy. Finally, the proposed method is applied to a ten-storey shear frame structure under seismic excitations, which exhibits strong nonlinearity. The numerical results demonstrate the efficacy of the proposed method.

  5. Competing risk models in reliability systems, a Weibull distribution model with Bayesian analysis approach

    International Nuclear Information System (INIS)

    Iskandar, Ismed; Gondokaryono, Yudi Satria

    2016-01-01

    In reliability theory, the most important problem is to determine the reliability of a complex system from the reliability of its components. The weakness of most reliability theories is that the systems are described and explained as simply functioning or failed. In many real situations, the failures may be from many causes depending upon the age and the environment of the system and its components. Another problem in reliability theory is one of estimating the parameters of the assumed failure models. The estimation may be based on data collected over censored or uncensored life tests. In many reliability problems, the failure data are simply quantitatively inadequate, especially in engineering design and maintenance system. The Bayesian analyses are more beneficial than the classical one in such cases. The Bayesian estimation analyses allow us to combine past knowledge or experience in the form of an apriori distribution with life test data to make inferences of the parameter of interest. In this paper, we have investigated the application of the Bayesian estimation analyses to competing risk systems. The cases are limited to the models with independent causes of failure by using the Weibull distribution as our model. A simulation is conducted for this distribution with the objectives of verifying the models and the estimators and investigating the performance of the estimators for varying sample size. The simulation data are analyzed by using Bayesian and the maximum likelihood analyses. The simulation results show that the change of the true of parameter relatively to another will change the value of standard deviation in an opposite direction. For a perfect information on the prior distribution, the estimation methods of the Bayesian analyses are better than those of the maximum likelihood. The sensitivity analyses show some amount of sensitivity over the shifts of the prior locations. They also show the robustness of the Bayesian analysis within the range

  6. Conceptual Software Reliability Prediction Models for Nuclear Power Plant Safety Systems

    International Nuclear Information System (INIS)

    Johnson, G.; Lawrence, D.; Yu, H.

    2000-01-01

    The objective of this project is to develop a method to predict the potential reliability of software to be used in a digital system instrumentation and control system. The reliability prediction is to make use of existing measures of software reliability such as those described in IEEE Std 982 and 982.2. This prediction must be of sufficient accuracy to provide a value for uncertainty that could be used in a nuclear power plant probabilistic risk assessment (PRA). For the purposes of the project, reliability was defined to be the probability that the digital system will successfully perform its intended safety function (for the distribution of conditions under which it is expected to respond) upon demand with no unintended functions that might affect system safety. The ultimate objective is to use the identified measures to develop a method for predicting the potential quantitative reliability of a digital system. The reliability prediction models proposed in this report are conceptual in nature. That is, possible prediction techniques are proposed and trial models are built, but in order to become a useful tool for predicting reliability, the models must be tested, modified according to the results, and validated. Using methods outlined by this project, models could be constructed to develop reliability estimates for elements of software systems. This would require careful review and refinement of the models, development of model parameters from actual experience data or expert elicitation, and careful validation. By combining these reliability estimates (generated from the validated models for the constituent parts) in structural software models, the reliability of the software system could then be predicted. Modeling digital system reliability will also require that methods be developed for combining reliability estimates for hardware and software. System structural models must also be developed in order to predict system reliability based upon the reliability

  7. Probabilistic risk assessment for a loss of coolant accident in McMaster Nuclear Reactor and application of reliability physics model for modeling human reliability

    Science.gov (United States)

    Ha, Taesung

    A probabilistic risk assessment (PRA) was conducted for a loss of coolant accident, (LOCA) in the McMaster Nuclear Reactor (MNR). A level 1 PRA was completed including event sequence modeling, system modeling, and quantification. To support the quantification of the accident sequence identified, data analysis using the Bayesian method and human reliability analysis (HRA) using the accident sequence evaluation procedure (ASEP) approach were performed. Since human performance in research reactors is significantly different from that in power reactors, a time-oriented HRA model (reliability physics model) was applied for the human error probability (HEP) estimation of the core relocation. This model is based on two competing random variables: phenomenological time and performance time. The response surface and direct Monte Carlo simulation with Latin Hypercube sampling were applied for estimating the phenomenological time, whereas the performance time was obtained from interviews with operators. An appropriate probability distribution for the phenomenological time was assigned by statistical goodness-of-fit tests. The human error probability (HEP) for the core relocation was estimated from these two competing quantities: phenomenological time and operators' performance time. The sensitivity of each probability distribution in human reliability estimation was investigated. In order to quantify the uncertainty in the predicted HEPs, a Bayesian approach was selected due to its capability of incorporating uncertainties in model itself and the parameters in that model. The HEP from the current time-oriented model was compared with that from the ASEP approach. Both results were used to evaluate the sensitivity of alternative huinan reliability modeling for the manual core relocation in the LOCA risk model. This exercise demonstrated the applicability of a reliability physics model supplemented with a. Bayesian approach for modeling human reliability and its potential

  8. Designing dynamically "signature business model" that support durable competitive advantage

    OpenAIRE

    Čirjevskis, Andrejs

    2016-01-01

    Purpose/Research question: The paper provides an empirical research of the Samsung case. In particular, we study the case by adopting three frameworks: dynamic capabilities (DC, examined by using the sensing/seizing/transforming approach), business model (BM, examined by using the BM canvas), and customer value proposition (CVP), examined by using the PERFA ((Performance, Ease of use, Reliability, Flexibility, and Affectivity) framework. The aim is to demonstrate that three frameworks success...

  9. Supply reliability and dynamic safety analysis of an alternative energy supply chain

    DEFF Research Database (Denmark)

    Herbert-Hansen, Zaza Nadja Lee; Markert, Frank; Jacobsen, Peter

    2016-01-01

    This paper focuses on the integration of risk and supply chain modelling by means of analysing a case concerning a Hydrogen Refuelling Station in Berlin. It presents a framework that can analyse an energy supply chain and at the same time enables easy reporting and presentation of various results...... by utilizing Dis-crete Event Simulation (DES). The industrial implication of this work is to provide practitioners with an anal-ysis framework for improved decision support. The novelty of this paper is the approach to model a supply chain together with a dynamically modelled event tree-based approach...

  10. Modeling and reliability analysis of three phase z-source AC-AC converter

    Directory of Open Access Journals (Sweden)

    Prasad Hanuman

    2017-12-01

    Full Text Available This paper presents the small signal modeling using the state space averaging technique and reliability analysis of a three-phase z-source ac-ac converter. By controlling the shoot-through duty ratio, it can operate in buck-boost mode and maintain desired output voltage during voltage sag and surge condition. It has faster dynamic response and higher efficiency as compared to the traditional voltage regulator. Small signal analysis derives different control transfer functions and this leads to design a suitable controller for a closed loop system during supply voltage variation. The closed loop system of the converter with a PID controller eliminates the transients in output voltage and provides steady state regulated output. The proposed model designed in the RT-LAB and executed in a field programming gate array (FPGA-based real-time digital simulator at a fixedtime step of 10 μs and a constant switching frequency of 10 kHz. The simulator was developed using very high speed integrated circuit hardware description language (VHDL, making it versatile and moveable. Hardware-in-the-loop (HIL simulation results are presented to justify the MATLAB simulation results during supply voltage variation of the three phase z-source ac-ac converter. The reliability analysis has been applied to the converter to find out the failure rate of its different components.

  11. High effective inverse dynamics modelling for dual-arm robot

    Science.gov (United States)

    Shen, Haoyu; Liu, Yanli; Wu, Hongtao

    2018-05-01

    To deal with the problem of inverse dynamics modelling for dual arm robot, a recursive inverse dynamics modelling method based on decoupled natural orthogonal complement is presented. In this model, the concepts and methods of Decoupled Natural Orthogonal Complement matrices are used to eliminate the constraint forces in the Newton-Euler kinematic equations, and the screws is used to express the kinematic and dynamics variables. On this basis, the paper has developed a special simulation program with symbol software of Mathematica and conducted a simulation research on the a dual-arm robot. Simulation results show that the proposed method based on decoupled natural orthogonal complement can save an enormous amount of CPU time that was spent in computing compared with the recursive Newton-Euler kinematic equations and the results is correct and reasonable, which can verify the reliability and efficiency of the method.

  12. Supply based on demand dynamical model

    Science.gov (United States)

    Levi, Asaf; Sabuco, Juan; Sanjuán, Miguel A. F.

    2018-04-01

    We propose and numerically analyze a simple dynamical model that describes the firm behaviors under uncertainty of demand. Iterating this simple model and varying some parameter values, we observe a wide variety of market dynamics such as equilibria, periodic, and chaotic behaviors. Interestingly, the model is also able to reproduce market collapses.

  13. Opinion dynamics model based on quantum formalism

    Energy Technology Data Exchange (ETDEWEB)

    Artawan, I. Nengah, E-mail: nengahartawan@gmail.com [Theoretical Physics Division, Department of Physics, Udayana University (Indonesia); Trisnawati, N. L. P., E-mail: nlptrisnawati@gmail.com [Biophysics, Department of Physics, Udayana University (Indonesia)

    2016-03-11

    Opinion dynamics model based on quantum formalism is proposed. The core of the quantum formalism is on the half spin dynamics system. In this research the implicit time evolution operators are derived. The analogy between the model with Deffuant dan Sznajd models is discussed.

  14. Prediction Models for Dynamic Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Aman, Saima; Frincu, Marc; Chelmis, Charalampos; Noor, Muhammad; Simmhan, Yogesh; Prasanna, Viktor K.

    2015-11-02

    As Smart Grids move closer to dynamic curtailment programs, Demand Response (DR) events will become necessary not only on fixed time intervals and weekdays predetermined by static policies, but also during changing decision periods and weekends to react to real-time demand signals. Unique challenges arise in this context vis-a-vis demand prediction and curtailment estimation and the transformation of such tasks into an automated, efficient dynamic demand response (D2R) process. While existing work has concentrated on increasing the accuracy of prediction models for DR, there is a lack of studies for prediction models for D2R, which we address in this paper. Our first contribution is the formal definition of D2R, and the description of its challenges and requirements. Our second contribution is a feasibility analysis of very-short-term prediction of electricity consumption for D2R over a diverse, large-scale dataset that includes both small residential customers and large buildings. Our third, and major contribution is a set of insights into the predictability of electricity consumption in the context of D2R. Specifically, we focus on prediction models that can operate at a very small data granularity (here 15-min intervals), for both weekdays and weekends - all conditions that characterize scenarios for D2R. We find that short-term time series and simple averaging models used by Independent Service Operators and utilities achieve superior prediction accuracy. We also observe that workdays are more predictable than weekends and holiday. Also, smaller customers have large variation in consumption and are less predictable than larger buildings. Key implications of our findings are that better models are required for small customers and for non-workdays, both of which are critical for D2R. Also, prediction models require just few days’ worth of data indicating that small amounts of

  15. Relating structure and dynamics in organisation models

    NARCIS (Netherlands)

    Jonker, C.M.; Treur, J.

    2003-01-01

    To understand how an organisational structure relates to dynamics is an interesting fundamental challenge in the area of social modelling. Specifications of organisational structure usually have a diagrammatic form that abstracts from more detailed dynamics. Dynamic properties of agent systems, on

  16. Identifying the effects of parameter uncertainty on the reliability of riverbank stability modelling

    Science.gov (United States)

    Samadi, A.; Amiri-Tokaldany, E.; Darby, S. E.

    2009-05-01

    Bank retreat is a key process in fluvial dynamics affecting a wide range of physical, ecological and socioeconomic issues in the fluvial environment. To predict the undesirable effects of bank retreat and to inform effective measures to prevent it, a wide range of bank stability models have been presented in the literature. These models typically express bank stability by defining a factor of safety as the ratio of driving and resisting forces acting on the incipient failure block. These forces are affected by a range of controlling factors that include such aspects as the bank profile (bank height and angle), the geotechnical properties of the bank materials, as well as the hydrological status of the riverbanks. In this paper we evaluate the extent to which uncertainties in the parameterization of these controlling factors feed through to influence the reliability of the resulting bank stability estimate. This is achieved by employing a simple model of riverbank stability with respect to planar failure (which is the most common type of bank stability model) in a series of sensitivity tests and Monte Carlo analyses to identify, for each model parameter, the range of values that induce significant changes in the simulated factor of safety. These identified parameter value ranges are compared to empirically derived parameter uncertainties to determine whether they are likely to confound the reliability of the resulting bank stability calculations. Our results show that parameter uncertainties are typically high enough that the likelihood of generating unreliable predictions is typically very high (> ˜ 80% for predictions requiring a precision of < ± 15%). Because parameter uncertainties are derived primarily from the natural variability of the parameters, rather than measurement errors, much more careful attention should be paid to field sampling strategies, such that the parameter uncertainties and consequent prediction unreliabilities can be quantified more

  17. Model-free inference of direct network interactions from nonlinear collective dynamics.

    Science.gov (United States)

    Casadiego, Jose; Nitzan, Mor; Hallerberg, Sarah; Timme, Marc

    2017-12-19

    The topology of interactions in network dynamical systems fundamentally underlies their function. Accelerating technological progress creates massively available data about collective nonlinear dynamics in physical, biological, and technological systems. Detecting direct interaction patterns from those dynamics still constitutes a major open problem. In particular, current nonlinear dynamics approaches mostly require to know a priori a model of the (often high dimensional) system dynamics. Here we develop a model-independent framework for inferring direct interactions solely from recording the nonlinear collective dynamics generated. Introducing an explicit dependency matrix in combination with a block-orthogonal regression algorithm, the approach works reliably across many dynamical regimes, including transient dynamics toward steady states, periodic and non-periodic dynamics, and chaos. Together with its capabilities to reveal network (two point) as well as hypernetwork (e.g., three point) interactions, this framework may thus open up nonlinear dynamics options of inferring direct interaction patterns across systems where no model is known.

  18. Sensitivity of Reliability Estimates in Partially Damaged RC Structures subject to Earthquakes, using Reduced Hysteretic Models

    DEFF Research Database (Denmark)

    Iwankiewicz, R.; Nielsen, Søren R. K.; Skjærbæk, P. S.

    The subject of the paper is the investigation of the sensitivity of structural reliability estimation by a reduced hysteretic model for a reinforced concrete frame under an earthquake excitation.......The subject of the paper is the investigation of the sensitivity of structural reliability estimation by a reduced hysteretic model for a reinforced concrete frame under an earthquake excitation....

  19. Intra- and interobserver reliability of gray scale/dynamic range evaluation of ultrasonography using a standardized phantom

    International Nuclear Information System (INIS)

    Lee, Song; Choi, Joon Il; Park, Michael Yong; Yeo, Dong Myung; Byun, Jae Young; Jung, Seung Eun; Rha, Sung Eun; Oh, Soon Nam; Lee, Young Joon

    2014-01-01

    To evaluate intra- and interobserver reliability of the gray scale/dynamic range of the phantom image evaluation of ultrasonography using a standardized phantom, and to assess the effect of interactive education on the reliability. Three radiologists (a resident, and two board-certified radiologists with 2 and 7 years of experience in evaluating ultrasound phantom images) performed the gray scale/dynamic range test for an ultrasound machine using a standardized phantom. They scored the number of visible cylindrical structures of varying degrees of brightness and made a pass or fail decision. First, they scored 49 phantom images twice from a 2010 survey with limited knowledge of phantom images. After this, the radiologists underwent two hours of interactive education for the phantom images and scored another 91 phantom images from a 2011 survey twice. Intra- and interobserver reliability before and after the interactive education session were analyzed using K analyses. Before education, the K-value for intraobserver reliability for the radiologist with 7 years of experience, 2 years of experience, and the resident was 0.386, 0.469, and 0.465, respectively. After education, the K-values were improved (0.823, 0.611, and 0.711, respectively). For interobserver reliability, the K-value was also better after the education for the 3 participants (0.067, 0.002, and 0.547 before education; 0.635, 0.667, and 0.616 after education, respectively). The intra- and interobserver reliability of the gray scale/dynamic range was fair to substantial. Interactive education can improve reliability. For more reliable results, double- checking of phantom images by multiple reviewers is recommended.

  20. Possibilities and Limitations of Applying Software Reliability Growth Models to Safety- Critical Software

    International Nuclear Information System (INIS)

    Kim, Man Cheol; Jang, Seung Cheol; Ha, Jae Joo

    2006-01-01

    As digital systems are gradually introduced to nuclear power plants (NPPs), the need of quantitatively analyzing the reliability of the digital systems is also increasing. Kang and Sung identified (1) software reliability, (2) common-cause failures (CCFs), and (3) fault coverage as the three most critical factors in the reliability analysis of digital systems. For the estimation of the safety-critical software (the software that is used in safety-critical digital systems), the use of Bayesian Belief Networks (BBNs) seems to be most widely used. The use of BBNs in reliability estimation of safety-critical software is basically a process of indirectly assigning a reliability based on various observed information and experts' opinions. When software testing results or software failure histories are available, we can use a process of directly estimating the reliability of the software using various software reliability growth models such as Jelinski- Moranda model and Goel-Okumoto's nonhomogeneous Poisson process (NHPP) model. Even though it is generally known that software reliability growth models cannot be applied to safety-critical software due to small number of expected failure data from the testing of safety-critical software, we try to find possibilities and corresponding limitations of applying software reliability growth models to safety critical software

  1. Comparison of Model Reliabilities from Single-Step and Bivariate Blending Methods

    DEFF Research Database (Denmark)

    Taskinen, Matti; Mäntysaari, Esa; Lidauer, Martin

    2013-01-01

    Model based reliabilities in genetic evaluation are compared between three methods: animal model BLUP, single-step BLUP, and bivariate blending after genomic BLUP. The original bivariate blending is revised in this work to better account animal models. The study data is extracted from...... be calculated. Model reliabilities by the single-step and the bivariate blending methods were higher than by animal model due to genomic information. Compared to the single-step method, the bivariate blending method reliability estimates were, in general, lower. Computationally bivariate blending method was......, on the other hand, lighter than the single-step method....

  2. Using Model Replication to Improve the Reliability of Agent-Based Models

    Science.gov (United States)

    Zhong, Wei; Kim, Yushim

    The basic presupposition of model replication activities for a computational model such as an agent-based model (ABM) is that, as a robust and reliable tool, it must be replicable in other computing settings. This assumption has recently gained attention in the community of artificial society and simulation due to the challenges of model verification and validation. Illustrating the replication of an ABM representing fraudulent behavior in a public service delivery system originally developed in the Java-based MASON toolkit for NetLogo by a different author, this paper exemplifies how model replication exercises provide unique opportunities for model verification and validation process. At the same time, it helps accumulate best practices and patterns of model replication and contributes to the agenda of developing a standard methodological protocol for agent-based social simulation.

  3. Procedure for Application of Software Reliability Growth Models to NPP PSA

    International Nuclear Information System (INIS)

    Son, Han Seong; Kang, Hyun Gook; Chang, Seung Cheol

    2009-01-01

    As the use of software increases at nuclear power plants (NPPs), the necessity for including software reliability and/or safety into the NPP Probabilistic Safety Assessment (PSA) rises. This work proposes an application procedure of software reliability growth models (RGMs), which are most widely used to quantify software reliability, to NPP PSA. Through the proposed procedure, it can be determined if a software reliability growth model can be applied to the NPP PSA before its real application. The procedure proposed in this work is expected to be very helpful for incorporating software into NPP PSA

  4. Time-dependent reliability analysis of nuclear reactor operators using probabilistic network models

    International Nuclear Information System (INIS)

    Oka, Y.; Miyata, K.; Kodaira, H.; Murakami, S.; Kondo, S.; Togo, Y.

    1987-01-01

    Human factors are very important for the reliability of a nuclear power plant. Human behavior has essentially a time-dependent nature. The details of thinking and decision making processes are important for detailed analysis of human reliability. They have, however, not been well considered by the conventional methods of human reliability analysis. The present paper describes the models for the time-dependent and detailed human reliability analysis. Recovery by an operator is taken into account and two-operators models are also presented

  5. Dynamic modelling of nuclear steam generators

    International Nuclear Information System (INIS)

    Kerlin, T.W.; Katz, E.M.; Freels, J.; Thakkar, J.

    1980-01-01

    Moving boundary, nodal models with dynamic energy balances, dynamic mass balances, quasi-static momentum balances, and an equivalent single channel approach have been developed for steam generators used in nuclear power plants. The model for the U-tube recirculation type steam generator is described and comparisons are made of responses from models of different complexity; non-linear versus linear, high-order versus low order, detailed modeling of the control system versus a simple control assumption. The results of dynamic tests on nuclear power systems show that when this steam generator model is included in a system simulation there is good agreement with actual plant performance. (author)

  6. Dynamic Airspace Managment - Models and Algorithms

    OpenAIRE

    Cheng, Peng; Geng, Rui

    2010-01-01

    This chapter investigates the models and algorithms for implementing the concept of Dynamic Airspace Management. Three models are discussed. First two models are about how to use or adjust air route dynamically in order to speed up air traffic flow and reduce delay. The third model gives a way to dynamically generate the optimal sector configuration for an air traffic control center to both balance the controller’s workload and save control resources. The first model, called the Dynami...

  7. Wind Farm Decentralized Dynamic Modeling With Parameters

    DEFF Research Database (Denmark)

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

    2010-01-01

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

  8. System dynamics modelling of situation awareness

    CSIR Research Space (South Africa)

    Oosthuizen, R

    2015-11-01

    Full Text Available . The feedback loops and delays in the Command and Control system also contribute to the complex dynamic behavior. This paper will build on existing situation awareness models to develop a System Dynamics model to support a qualitative investigation through...

  9. Reliability of corneal dynamic scheimpflug analyser measurements in virgin and post-PRK eyes.

    Science.gov (United States)

    Chen, Xiangjun; Stojanovic, Aleksandar; Hua, Yanjun; Eidet, Jon Roger; Hu, Di; Wang, Jingting; Utheim, Tor Paaske

    2014-01-01

    To determine the measurement reliability of CorVis ST, a dynamic Scheimpflug analyser, in virgin and post-photorefractive keratectomy (PRK) eyes and compare the results between these two groups. Forty virgin eyes and 42 post-PRK eyes underwent CorVis ST measurements performed by two technicians. Repeatability was evaluated by comparing three consecutive measurements by technician A. Reproducibility was determined by comparing the first measurement by technician A with one performed by technician B. Intraobserver and interobserver intraclass correlation coefficients (ICCs) were calculated. Univariate analysis of covariance (ANCOVA) was used to compare measured parameters between virgin and post-PRK eyes. The intraocular pressure (IOP), central corneal thickness (CCT) and 1st applanation time demonstrated good intraobserver repeatability and interobserver reproducibility (ICC ≧ 0.90) in virgin and post-PRK eyes. The deformation amplitude showed a good or close to good repeatability and reproducibility in both groups (ICC ≧ 0.88). The CCT correlated positively with 1st applanation time (r = 0.437 and 0.483, respectively, pPRK eyes, virgin eyes showed longer 1st applanation time (7.29 ± 0.21 vs. 6.96 ± 0.17 ms, pPRK eyes. There were differences in 1st applanation time and deformation amplitude between virgin and post-PRK eyes, which may reflect corneal biomechanical changes occurring after the surgery in the latter.

  10. Impact of Climate Change on Natural Snow Reliability, Snowmaking Capacities, and Wind Conditions of Ski Resorts in Northeast Turkey: A Dynamical Downscaling Approach

    Directory of Open Access Journals (Sweden)

    Osman Cenk Demiroglu

    2016-04-01

    Full Text Available Many ski resorts worldwide are going through deteriorating snow cover conditions due to anthropogenic warming trends. As the natural and the artificially supported, i.e., technical, snow reliability of ski resorts diminish, the industry approaches a deadlock. For this reason, impact assessment studies have become vital for understanding vulnerability of ski tourism. This study considers three resorts at one of the rapidly emerging ski destinations, Northeast Turkey, for snow reliability analyses. Initially one global circulation model is dynamically downscaled by using the regional climate model RegCM4.4 for 1971–2000 and 2021–2050 periods along the RCP4.5 greenhouse gas concentration pathway. Next, the projected climate outputs are converted into indicators of natural snow reliability, snowmaking capacity, and wind conditions. The results show an overall decline in the frequencies of naturally snow reliable days and snowmaking capacities between the two periods. Despite the decrease, only the lower altitudes of one ski resort would face the risk of losing natural snow reliability and snowmaking could still compensate for forming the base layer before the critical New Year’s week. On the other hand, adverse high wind conditions improve as to reduce the number of lift closure days at all resorts. Overall, this particular region seems to be relatively resilient against climate change.

  11. An Agent Model Integrating an Adaptive Model for Environmental Dynamics

    NARCIS (Netherlands)

    Treur, J.; Umair, M.

    2011-01-01

    The environments in which agents are used often may be described by dynamical models, e.g., in the form of a set of differential equations. In this paper, an agent model is proposed that can perform model-based reasoning about the environment, based on a numerical (dynamical system) model of the

  12. Hydration dynamics near a model protein surface

    International Nuclear Information System (INIS)

    Russo, Daniela; Hura, Greg; Head-Gordon, Teresa

    2003-01-01

    The evolution of water dynamics from dilute to very high concentration solutions of a prototypical hydrophobic amino acid with its polar backbone, N-acetyl-leucine-methylamide (NALMA), is studied by quasi-elastic neutron scattering and molecular dynamics simulation for both the completely deuterated and completely hydrogenated leucine monomer. We observe several unexpected features in the dynamics of these biological solutions under ambient conditions. The NALMA dynamics shows evidence of de Gennes narrowing, an indication of coherent long timescale structural relaxation dynamics. The translational water dynamics are analyzed in a first approximation with a jump diffusion model. At the highest solute concentrations, the hydration water dynamics is significantly suppressed and characterized by a long residential time and a slow diffusion coefficient. The analysis of the more dilute concentration solutions takes into account the results of the 2.0M solution as a model of the first hydration shell. Subtracting the first hydration layer based on the 2.0M spectra, the translational diffusion dynamics is still suppressed, although the rotational relaxation time and residential time are converged to bulk-water values. Molecular dynamics analysis shows spatially heterogeneous dynamics at high concentration that becomes homogeneous at more dilute concentrations. We discuss the hydration dynamics results of this model protein system in the context of glassy systems, protein function, and protein-protein interfaces

  13. Theory model and experiment research about the cognition reliability of nuclear power plant operators

    International Nuclear Information System (INIS)

    Fang Xiang; Zhao Bingquan

    2000-01-01

    In order to improve the reliability of NPP operation, the simulation research on the reliability of nuclear power plant operators is needed. Making use of simulator of nuclear power plant as research platform, and taking the present international reliability research model-human cognition reliability for reference, the part of the model is modified according to the actual status of Chinese nuclear power plant operators and the research model of Chinese nuclear power plant operators obtained based on two-parameter Weibull distribution. Experiments about the reliability of nuclear power plant operators are carried out using the two-parameter Weibull distribution research model. Compared with those in the world, the same results are achieved. The research would be beneficial to the operation safety of nuclear power plant

  14. Stochastic modeling for reliability shocks, burn-in and heterogeneous populations

    CERN Document Server

    Finkelstein, Maxim

    2013-01-01

    Focusing on shocks modeling, burn-in and heterogeneous populations, Stochastic Modeling for Reliability naturally combines these three topics in the unified stochastic framework and presents numerous practical examples that illustrate recent theoretical findings of the authors.  The populations of manufactured items in industry are usually heterogeneous. However, the conventional reliability analysis is performed under the implicit assumption of homogeneity, which can result in distortion of the corresponding reliability indices and various misconceptions. Stochastic Modeling for Reliability fills this gap and presents the basics and further developments of reliability theory for heterogeneous populations. Specifically, the authors consider burn-in as a method of elimination of ‘weak’ items from heterogeneous populations. The real life objects are operating in a changing environment. One of the ways to model an impact of this environment is via the external shocks occurring in accordance with some stocha...

  15. Research on cognitive reliability model for main control room considering human factors in nuclear power plants

    International Nuclear Information System (INIS)

    Jiang Jianjun; Zhang Li; Wang Yiqun; Zhang Kun; Peng Yuyuan; Zhou Cheng

    2012-01-01

    Facing the shortcomings of the traditional cognitive factors and cognitive model, this paper presents a Bayesian networks cognitive reliability model by taking the main control room as a reference background and human factors as the key points. The model mainly analyzes the cognitive reliability affected by the human factors, and for the cognitive node and influence factors corresponding to cognitive node, a series of methods and function formulas to compute the node cognitive reliability is proposed. The model and corresponding methods can be applied to the evaluation of cognitive process for the nuclear power plant operators and have a certain significance for the prevention of safety accidents in nuclear power plants. (authors)

  16. Model case IRS-RWE for the determination of reliability data in practical operation

    Energy Technology Data Exchange (ETDEWEB)

    Hoemke, P; Krause, H

    1975-11-01

    Reliability und availability analyses are carried out to assess the safety of nuclear power plants. The paper deals in the first part with the requirement of accuracy for the input data of such analyses and in the second part with the prototype data collection of reliability data 'Model case IRS-RWE'. The objectives and the structure of the data collection are described. The present results show that the estimation of reliability data in power plants is possible and gives reasonable results.

  17. Estimating the Parameters of Software Reliability Growth Models Using the Grey Wolf Optimization Algorithm

    OpenAIRE

    Alaa F. Sheta; Amal Abdel-Raouf

    2016-01-01

    In this age of technology, building quality software is essential to competing in the business market. One of the major principles required for any quality and business software product for value fulfillment is reliability. Estimating software reliability early during the software development life cycle saves time and money as it prevents spending larger sums fixing a defective software product after deployment. The Software Reliability Growth Model (SRGM) can be used to predict the number of...

  18. A new model for reliability optimization of series-parallel systems with non-homogeneous components

    International Nuclear Information System (INIS)

    Feizabadi, Mohammad; Jahromi, Abdolhamid Eshraghniaye

    2017-01-01

    In discussions related to reliability optimization using redundancy allocation, one of the structures that has attracted the attention of many researchers, is series-parallel structure. In models previously presented for reliability optimization of series-parallel systems, there is a restricting assumption based on which all components of a subsystem must be homogeneous. This constraint limits system designers in selecting components and prevents achieving higher levels of reliability. In this paper, a new model is proposed for reliability optimization of series-parallel systems, which makes possible the use of non-homogeneous components in each subsystem. As a result of this flexibility, the process of supplying system components will be easier. To solve the proposed model, since the redundancy allocation problem (RAP) belongs to the NP-hard class of optimization problems, a genetic algorithm (GA) is developed. The computational results of the designed GA are indicative of high performance of the proposed model in increasing system reliability and decreasing costs. - Highlights: • In this paper, a new model is proposed for reliability optimization of series-parallel systems. • In the previous models, there is a restricting assumption based on which all components of a subsystem must be homogeneous. • The presented model provides a possibility for the subsystems’ components to be non- homogeneous in the required conditions. • The computational results demonstrate the high performance of the proposed model in improving reliability and reducing costs.

  19. Forecasting house prices in the 50 states using Dynamic Model Averaging and Dynamic Model Selection

    DEFF Research Database (Denmark)

    Bork, Lasse; Møller, Stig Vinther

    2015-01-01

    We examine house price forecastability across the 50 states using Dynamic Model Averaging and Dynamic Model Selection, which allow for model change and parameter shifts. By allowing the entire forecasting model to change over time and across locations, the forecasting accuracy improves substantia......We examine house price forecastability across the 50 states using Dynamic Model Averaging and Dynamic Model Selection, which allow for model change and parameter shifts. By allowing the entire forecasting model to change over time and across locations, the forecasting accuracy improves...

  20. Uncertainty propagation through dynamic models of assemblies of mechanical structures

    International Nuclear Information System (INIS)

    Daouk, Sami

    2016-01-01

    When studying the behaviour of mechanical systems, mathematical models and structural parameters are usually considered deterministic. Return on experience shows however that these elements are uncertain in most cases, due to natural variability or lack of knowledge. Therefore, quantifying the quality and reliability of the numerical model of an industrial assembly remains a major question in low-frequency dynamics. The purpose of this thesis is to improve the vibratory design of bolted assemblies through setting up a dynamic connector model that takes account of different types and sources of uncertainty on stiffness parameters, in a simple, efficient and exploitable in industrial context. This work has been carried out in the framework of the SICODYN project, led by EDF R and D, that aims to characterise and quantify, numerically and experimentally, the uncertainties in the dynamic behaviour of bolted industrial assemblies. Comparative studies of several numerical methods of uncertainty propagation demonstrate the advantage of using the Lack-Of-Knowledge theory. An experimental characterisation of uncertainties in bolted structures is performed on a dynamic test rig and on an industrial assembly. The propagation of many small and large uncertainties through different dynamic models of mechanical assemblies leads to the assessment of the efficiency of the Lack-Of-Knowledge theory and its applicability in an industrial environment. (author)

  1. Reliability-cost models for the power switching devices of wind power converters

    DEFF Research Database (Denmark)

    Ma, Ke; Blaabjerg, Frede

    2012-01-01

    In order to satisfy the growing reliability requirements for the wind power converters with more cost-effective solution, the target of this paper is to establish a new reliability-cost model which can connect the relationship between reliability performances and corresponding semiconductor cost...... temperature mean value Tm and fluctuation amplitude ΔTj of power devices, are presented. With the proposed reliability-cost model, it is possible to enable future reliability-oriented design of the power switching devices for wind power converters, and also an evaluation benchmark for different wind power...... for power switching devices. First the conduction loss, switching loss as well as thermal impedance models of power switching devices (IGBT module) are related to the semiconductor chip number information respectively. Afterwards simplified analytical solutions, which can directly extract the junction...

  2. Evaluation of Validity and Reliability for Hierarchical Scales Using Latent Variable Modeling

    Science.gov (United States)

    Raykov, Tenko; Marcoulides, George A.

    2012-01-01

    A latent variable modeling method is outlined, which accomplishes estimation of criterion validity and reliability for a multicomponent measuring instrument with hierarchical structure. The approach provides point and interval estimates for the scale criterion validity and reliability coefficients, and can also be used for testing composite or…

  3. Reliability Based Optimal Design of Vertical Breakwaters Modelled as a Series System Failure

    DEFF Research Database (Denmark)

    Christiani, E.; Burcharth, H. F.; Sørensen, John Dalsgaard

    1996-01-01

    Reliability based design of monolithic vertical breakwaters is considered. Probabilistic models of important failure modes such as sliding and rupture failure in the rubble mound and the subsoil are described. Characterisation of the relevant stochastic parameters are presented, and relevant design...... variables are identified and an optimal system reliability formulation is presented. An illustrative example is given....

  4. Model correction factor method for reliability problems involving integrals of non-Gaussian random fields

    DEFF Research Database (Denmark)

    Franchin, P.; Ditlevsen, Ove Dalager; Kiureghian, Armen Der

    2002-01-01

    The model correction factor method (MCFM) is used in conjunction with the first-order reliability method (FORM) to solve structural reliability problems involving integrals of non-Gaussian random fields. The approach replaces the limit-state function with an idealized one, in which the integrals ...

  5. Reliability Models Applied to a System of Power Converters in Particle Accelerators

    OpenAIRE

    Siemaszko, D; Speiser, M; Pittet, S

    2012-01-01

    Several reliability models are studied when applied to a power system containing a large number of power converters. A methodology is proposed and illustrated in the case study of a novel linear particle accelerator designed for reaching high energies. The proposed methods result in the prediction of both reliability and availability of the considered system for optimisation purposes.

  6. Modeling and Quantification of Team Performance in Human Reliability Analysis for Probabilistic Risk Assessment

    Energy Technology Data Exchange (ETDEWEB)

    Jeffrey C. JOe; Ronald L. Boring

    2014-06-01

    Probabilistic Risk Assessment (PRA) and Human Reliability Assessment (HRA) are important technical contributors to the United States (U.S.) Nuclear Regulatory Commission’s (NRC) risk-informed and performance based approach to regulating U.S. commercial nuclear activities. Furthermore, all currently operating commercial NPPs in the U.S. are required by federal regulation to be staffed with crews of operators. Yet, aspects of team performance are underspecified in most HRA methods that are widely used in the nuclear industry. There are a variety of "emergent" team cognition and teamwork errors (e.g., communication errors) that are 1) distinct from individual human errors, and 2) important to understand from a PRA perspective. The lack of robust models or quantification of team performance is an issue that affects the accuracy and validity of HRA methods and models, leading to significant uncertainty in estimating HEPs. This paper describes research that has the objective to model and quantify team dynamics and teamwork within NPP control room crews for risk informed applications, thereby improving the technical basis of HRA, which improves the risk-informed approach the NRC uses to regulate the U.S. commercial nuclear industry.

  7. Modeling Gas Dynamics in California Sea Lions

    Science.gov (United States)

    2015-09-30

    W. and Fahlman, A. (2009). Could beaked whales get the bends?. Effect of diving behaviour and physiology on modelled gas exchange for three species...1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Modeling Gas Dynamics in California Sea Lions Andreas...to update a current gas dynamics model with recently acquired data for respiratory compliance (P-V), and body compartment size estimates in

  8. A Dynamic Model of Sustainment Investment

    Science.gov (United States)

    2015-02-01

    Sustainment System Dynamics Model 11 Figure 7: Core Structure of Sustainment Work 12 Figure 8: Bandwagon Effect Loop 13 Figure 9: Limits to Growth Loop 14...Dynamics Model sustainment capacity sustainment performance gap Bandwagon Effect R1 Limits to Growth B1 S Work Smarter B3 Work Bigger B2 desired...which is of concern primarily when using the model as a vehicle for research. Figure 8 depicts a reinforcing loop called the “ Bandwagon Effect

  9. Modeling the Dynamic Digestive System Microbiome†

    OpenAIRE

    Estes, Anne M.

    2015-01-01

    Modeling the Dynamic Digestive System Microbiome” is a hands-on activity designed to demonstrate the dynamics of microbiome ecology using dried pasta and beans to model disturbance events in the human digestive system microbiome. This exercise demonstrates how microbiome diversity is influenced by: 1) niche availability and habitat space and 2) a major disturbance event, such as antibiotic use. Students use a pictorial key to examine prepared models of digestive system microbiomes to determi...

  10. Analysis of Statistical Distributions Used for Modeling Reliability and Failure Rate of Temperature Alarm Circuit

    International Nuclear Information System (INIS)

    EI-Shanshoury, G.I.

    2011-01-01

    Several statistical distributions are used to model various reliability and maintainability parameters. The applied distribution depends on the' nature of the data being analyzed. The presented paper deals with analysis of some statistical distributions used in reliability to reach the best fit of distribution analysis. The calculations rely on circuit quantity parameters obtained by using Relex 2009 computer program. The statistical analysis of ten different distributions indicated that Weibull distribution gives the best fit distribution for modeling the reliability of the data set of Temperature Alarm Circuit (TAC). However, the Exponential distribution is found to be the best fit distribution for modeling the failure rate

  11. Reliability Modeling of Electromechanical System with Meta-Action Chain Methodology

    Directory of Open Access Journals (Sweden)

    Genbao Zhang

    2018-01-01

    Full Text Available To establish a more flexible and accurate reliability model, the reliability modeling and solving algorithm based on the meta-action chain thought are used in this thesis. Instead of estimating the reliability of the whole system only in the standard operating mode, this dissertation adopts the structure chain and the operating action chain for the system reliability modeling. The failure information and structure information for each component are integrated into the model to overcome the given factors applied in the traditional modeling. In the industrial application, there may be different operating modes for a multicomponent system. The meta-action chain methodology can estimate the system reliability under different operating modes by modeling the components with varieties of failure sensitivities. This approach has been identified by computing some electromechanical system cases. The results indicate that the process could improve the system reliability estimation. It is an effective tool to solve the reliability estimation problem in the system under various operating modes.

  12. A reliability-based approach of fastest routes planning in dynamic traffic network under emergency management situation

    Directory of Open Access Journals (Sweden)

    Ye Sun

    2011-12-01

    Full Text Available In order to establish an available emergency management system, it is important to conduct effective evacuation with reliable and real time optimal route plans. This paper aims at creating a route finding strategy by considering the time dependent factors as well as uncertainties that may be encountered during the emergency management system. To combine dynamic features with the level of reliability in the process of fastest route planning, the speed distribution of typical intercity roads is studied in depth, and the strategy of modifying real time speed to a more reliable value based on speed distribution is proposed. Two algorithms of route planning have been developed to find three optimal routes with the shortest travel time and the reliability of 0.9. In order to validate the new strategy, experimental implementation of the route planning method is conducted based on road speed information acquired by field study. The results show that the proposed strategy might provide more reliable routes in dynamic traffic networks by conservatively treating roads with large speed discretion or with relative extreme real speed value.

  13. Reliability and reference values of two clinical measurements of dynamic and static knee position in healthy children

    DEFF Research Database (Denmark)

    Ortqvist, Maria; Moström, Eva B; Roos, Ewa M.

    2011-01-01

    PURPOSE: The purposes of this study were to evaluate reliability of the Single-limb mini squat test (a dynamic measure of medio-lateral knee position) and the Quadriceps-angle (Q-angle) (a static measure of medio-lateral knee position), present paediatric reference values of the Q......-angle measurements was found. Reference values for the Q-angle (mean 13.5° (1.9)-15.3° (2.8)) varies with age and gender. No associations were found between dynamic and static measures. CONCLUSIONS: The Single-limb mini squat test showed a moderate reliability and the Q-angle showed a fair to moderate reliability......-angle, and evaluate the association between the tests. METHODS: Two hundred and forty-six healthy children (9-16 years) were included (intra/inter-rater reliability for Q-angle (n = 37/85) and for Single-limb mini squat test (n = 33/28)). Dynamic medio-lateral knee position was assessed by the Single-limb mini squat...

  14. Reliable Viscosity Calculation from Equilibrium Molecular Dynamics Simulations: A Time Decomposition Method.

    Science.gov (United States)

    Zhang, Yong; Otani, Akihito; Maginn, Edward J

    2015-08-11

    Equilibrium molecular dynamics is often used in conjunction with a Green-Kubo integral of the pressure tensor autocorrelation function to compute the shear viscosity of fluids. This approach is computationally expensive and is subject to a large amount of variability because the plateau region of the Green-Kubo integral is difficult to identify unambiguously. Here, we propose a time decomposition approach for computing the shear viscosity using the Green-Kubo formalism. Instead of one long trajectory, multiple independent trajectories are run and the Green-Kubo relation is applied to each trajectory. The averaged running integral as a function of time is fit to a double-exponential function with a weighting function derived from the standard deviation of the running integrals. Such a weighting function minimizes the uncertainty of the estimated shear viscosity and provides an objective means of estimating the viscosity. While the formal Green-Kubo integral requires an integration to infinite time, we suggest an integration cutoff time tcut, which can be determined by the relative values of the running integral and the corresponding standard deviation. This approach for computing the shear viscosity can be easily automated and used in computational screening studies where human judgment and intervention in the data analysis are impractical. The method has been applied to the calculation of the shear viscosity of a relatively low-viscosity liquid, ethanol, and relatively high-viscosity ionic liquid, 1-n-butyl-3-methylimidazolium bis(trifluoromethane-sulfonyl)imide ([BMIM][Tf2N]), over a range of temperatures. These test cases show that the method is robust and yields reproducible and reliable shear viscosity values.

  15. Development of an Environment for Software Reliability Model Selection

    Science.gov (United States)

    1992-09-01

    now is directed to other related problems such as tools for model selection, multiversion programming, and software fault tolerance modeling... multiversion programming, 7. Hlardware can be repaired by spare modules, which is not. the case for software, 2-6 N. Preventive maintenance is very important

  16. Fatigue reliability and effective turbulence models in wind farms

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Frandsen, Sten Tronæs; Tarp-Johansen, N.J.

    2007-01-01

    behind wind turbines can imply a significant reduction in the fatigue lifetime of wind turbines placed in wakes. In this paper the design code model in the wind turbine code IEC 61400-1 (2005) is evaluated from a probabilistic point of view, including the importance of modeling the SN-curve by linear...

  17. Powering stochastic reliability models by discrete event simulation

    DEFF Research Database (Denmark)

    Kozine, Igor; Wang, Xiaoyun

    2012-01-01

    it difficult to find a solution to the problem. The power of modern computers and recent developments in discrete-event simulation (DES) software enable to diminish some of the drawbacks of stochastic models. In this paper we describe the insights we have gained based on using both Markov and DES models...

  18. A Novel OBDD-Based Reliability Evaluation Algorithm for Wireless Sensor Networks on the Multicast Model

    Directory of Open Access Journals (Sweden)

    Zongshuai Yan

    2015-01-01

    Full Text Available The two-terminal reliability calculation for wireless sensor networks (WSNs is a #P-hard problem. The reliability calculation of WSNs on the multicast model provides an even worse combinatorial explosion of node states with respect to the calculation of WSNs on the unicast model; many real WSNs require the multicast model to deliver information. This research first provides a formal definition for the WSN on the multicast model. Next, a symbolic OBDD_Multicast algorithm is proposed to evaluate the reliability of WSNs on the multicast model. Furthermore, our research on OBDD_Multicast construction avoids the problem of invalid expansion, which reduces the number of subnetworks by identifying the redundant paths of two adjacent nodes and s-t unconnected paths. Experiments show that the OBDD_Multicast both reduces the complexity of the WSN reliability analysis and has a lower running time than Xing’s OBDD- (ordered binary decision diagram- based algorithm.

  19. Wind Farm Reliability Modelling Using Bayesian Networks and Semi-Markov Processes

    Directory of Open Access Journals (Sweden)

    Robert Adam Sobolewski

    2015-09-01

    Full Text Available Technical reliability plays an important role among factors affecting the power output of a wind farm. The reliability is determined by an internal collection grid topology and reliability of its electrical components, e.g. generators, transformers, cables, switch breakers, protective relays, and busbars. A wind farm reliability’s quantitative measure can be the probability distribution of combinations of operating and failed states of the farm’s wind turbines. The operating state of a wind turbine is its ability to generate power and to transfer it to an external power grid, which means the availability of the wind turbine and other equipment necessary for the power transfer to the external grid. This measure can be used for quantitative analysis of the impact of various wind farm topologies and the reliability of individual farm components on the farm reliability, and for determining the expected farm output power with consideration of the reliability. This knowledge may be useful in an analysis of power generation reliability in power systems. The paper presents probabilistic models that quantify the wind farm reliability taking into account the above-mentioned technical factors. To formulate the reliability models Bayesian networks and semi-Markov processes were used. Using Bayesian networks the wind farm structural reliability was mapped, as well as quantitative characteristics describing equipment reliability. To determine the characteristics semi-Markov processes were used. The paper presents an example calculation of: (i probability distribution of the combination of both operating and failed states of four wind turbines included in the wind farm, and (ii expected wind farm output power with consideration of its reliability.

  20. Differential equation models for sharp threshold dynamics.

    Science.gov (United States)

    Schramm, Harrison C; Dimitrov, Nedialko B

    2014-01-01

    We develop an extension to differential equation models of dynamical systems to allow us to analyze probabilistic threshold dynamics that fundamentally and globally change system behavior. We apply our novel modeling approach to two cases of interest: a model of infectious disease modified for malware where a detection event drastically changes dynamics by introducing a new class in competition with the original infection; and the Lanchester model of armed conflict, where the loss of a key capability drastically changes the effectiveness of one of the sides. We derive and demonstrate a step-by-step, repeatable method for applying our novel modeling approach to an arbitrary system, and we compare the resulting differential equations to simulations of the system's random progression. Our work leads to a simple and easily implemented method for analyzing probabilistic threshold dynamics using differential equations. Published by Elsevier Inc.

  1. Large eddy simulation of spanwise rotating turbulent channel flow with dynamic variants of eddy viscosity model

    Science.gov (United States)

    Jiang, Zhou; Xia, Zhenhua; Shi, Yipeng; Chen, Shiyi

    2018-04-01

    A fully developed spanwise rotating turbulent channel flow has been numerically investigated utilizing large-eddy simulation. Our focus is to assess the performances of the dynamic variants of eddy viscosity models, including dynamic Vreman's model (DVM), dynamic wall adapting local eddy viscosity (DWALE) model, dynamic σ (Dσ ) model, and the dynamic volumetric strain-stretching (DVSS) model, in this canonical flow. The results with dynamic Smagorinsky model (DSM) and direct numerical simulations (DNS) are used as references. Our results show that the DVM has a wrong asymptotic behavior in the near wall region, while the other three models can correctly predict it. In the high rotation case, the DWALE can get reliable mean velocity profile, but the turbulence intensities in the wall-normal and spanwise directions show clear deviations from DNS data. DVSS exhibits poor predictions on both the mean velocity profile and turbulence intensities. In all three cases, Dσ performs the best.

  2. Construction of a reliable model pyranometer for irradiance ...

    African Journals Online (AJOL)

    USER

    2010-03-22

    Mar 22, 2010 ... hour, latitude and cloud cover are the most widely or commonly used ... models in the Nigerian environment include that of Burari and Sambo .... influence the stability of the assembly (reducing its phase ... earth's surface.

  3. Reliability and safety engineering

    CERN Document Server

    Verma, Ajit Kumar; Karanki, Durga Rao

    2016-01-01

    Reliability and safety are core issues that must be addressed throughout the life cycle of engineering systems. Reliability and Safety Engineering presents an overview of the basic concepts, together with simple and practical illustrations. The authors present reliability terminology in various engineering fields, viz.,electronics engineering, software engineering, mechanical engineering, structural engineering and power systems engineering. The book describes the latest applications in the area of probabilistic safety assessment, such as technical specification optimization, risk monitoring and risk informed in-service inspection. Reliability and safety studies must, inevitably, deal with uncertainty, so the book includes uncertainty propagation methods: Monte Carlo simulation, fuzzy arithmetic, Dempster-Shafer theory and probability bounds. Reliability and Safety Engineering also highlights advances in system reliability and safety assessment including dynamic system modeling and uncertainty management. Cas...

  4. Nonlinear dynamic phenomena in the beer model

    DEFF Research Database (Denmark)

    Mosekilde, Erik; Laugesen, Jakob Lund

    2007-01-01

    The production-distribution system or "beer game" is one of the most well-known system dynamics models. Notorious for the complex dynamics it produces, the beer game has been used for nearly five decades to illustrate how structure generates behavior and to explore human decision making. Here we...

  5. Phone Routing using the Dynamic Memory Model

    DEFF Research Database (Denmark)

    Bendtsen, Claus Nicolaj; Krink, Thiemo

    2002-01-01

    In earlier studies a genetic algorithm (GA) extended with the dynamic memory model has shown remarkable performance on real-world-like problems. In this paper we experiment with routing in communication networks and show that the dynamic memory GA performs remarkable well compared to ant colony...

  6. Intra- and interrater reliability and agreement of the Danish version of the Dynamic Gait Index in older people with balance impairments

    DEFF Research Database (Denmark)

    Jønsson, Line R; Kristensen, Morten; Tibaek, Sigrid

    2011-01-01

    To examine the intrarater and interrater reliability and agreement of the Danish version of the Dynamic Gait Index (DGI) in hospitalized and community-dwelling older people with balance impairments.......To examine the intrarater and interrater reliability and agreement of the Danish version of the Dynamic Gait Index (DGI) in hospitalized and community-dwelling older people with balance impairments....

  7. Dynamic queuing transmission model for dynamic network loading

    DEFF Research Database (Denmark)

    Raovic, Nevena; Nielsen, Otto Anker; Prato, Carlo Giacomo

    2017-01-01

    and allowing for the representation of multiple vehicle classes, queue spillbacks and shock waves. The model assumes that a link is split into a moving part plus a queuing part, and p that traffic dynamics are given by a triangular fundamental diagram. A case-study is investigated and the DQTM is compared...

  8. Software reliability

    CERN Document Server

    Bendell, A

    1986-01-01

    Software Reliability reviews some fundamental issues of software reliability as well as the techniques, models, and metrics used to predict the reliability of software. Topics covered include fault avoidance, fault removal, and fault tolerance, along with statistical methods for the objective assessment of predictive accuracy. Development cost models and life-cycle cost models are also discussed. This book is divided into eight sections and begins with a chapter on adaptive modeling used to predict software reliability, followed by a discussion on failure rate in software reliability growth mo

  9. Charge transport models for reliability engineering of semiconductor devices

    International Nuclear Information System (INIS)

    Bina, M.

    2014-01-01

    The simulation of semiconductor devices is important for the assessment of device lifetimes before production. In this context, this work investigates the influence of the charge carrier transport model on the accuracy of bias temperature instability and hot-carrier degradation models in MOS devices. For this purpose, a four-state defect model based on a non-radiative multi phonon (NMP) theory is implemented to study the bias temperature instability. However, the doping concentrations typically used in nano-scale devices correspond to only a small number of dopants in the channel, leading to fluctuations of the electrostatic potential. Thus, the granularity of the doping cannot be ignored in these devices. To study the bias temperature instability in the presence of fluctuations of the electrostatic potential, the advanced drift diffusion device simulator Minimos-NT is employed. In a first effort to understand the bias temperature instability in p-channel MOSFETs at elevated temperatures, data from direct-current-current-voltage measurements is successfully reproduced using a four-state defect model. Differences between the four-state defect model and the commonly employed trapping model from Shockley, Read and Hall (SRH) have been investigated showing that the SRH model is incapable of reproducing the measurement data. This is in good agreement with the literature, where it has been extensively shown that a model based on SRH theory cannot reproduce the characteristic time constants found in BTI recovery traces. Upon inspection of recorded recovery traces after bias temperature stress in n-channel MOSFETs it is found that the gate current is strongly correlated with the drain current (recovery trace). Using a random discrete dopant model and non-equilibrium greens functions it is shown that direct tunnelling cannot explain the magnitude of the gate current reduction. Instead it is found that trap-assisted tunnelling, modelled using NMP theory, is the cause of this

  10. Reliability modeling of digital component in plant protection system with various fault-tolerant techniques

    International Nuclear Information System (INIS)

    Kim, Bo Gyung; Kang, Hyun Gook; Kim, Hee Eun; Lee, Seung Jun; Seong, Poong Hyun

    2013-01-01

    Highlights: • Integrated fault coverage is introduced for reflecting characteristics of fault-tolerant techniques in the reliability model of digital protection system in NPPs. • The integrated fault coverage considers the process of fault-tolerant techniques from detection to fail-safe generation process. • With integrated fault coverage, the unavailability of repairable component of DPS can be estimated. • The new developed reliability model can reveal the effects of fault-tolerant techniques explicitly for risk analysis. • The reliability model makes it possible to confirm changes of unavailability according to variation of diverse factors. - Abstract: With the improvement of digital technologies, digital protection system (DPS) has more multiple sophisticated fault-tolerant techniques (FTTs), in order to increase fault detection and to help the system safely perform the required functions in spite of the possible presence of faults. Fault detection coverage is vital factor of FTT in reliability. However, the fault detection coverage is insufficient to reflect the effects of various FTTs in reliability model. To reflect characteristics of FTTs in the reliability model, integrated fault coverage is introduced. The integrated fault coverage considers the process of FTT from detection to fail-safe generation process. A model has been developed to estimate the unavailability of repairable component of DPS using the integrated fault coverage. The new developed model can quantify unavailability according to a diversity of conditions. Sensitivity studies are performed to ascertain important variables which affect the integrated fault coverage and unavailability

  11. BUILDING MODEL ANALYSIS APPLICATIONS WITH THE JOINT UNIVERSAL PARAMETER IDENTIFICATION AND EVALUATION OF RELIABILITY (JUPITER) API

    Science.gov (United States)

    The open-source, public domain JUPITER (Joint Universal Parameter IdenTification and Evaluation of Reliability) API (Application Programming Interface) provides conventions and Fortran-90 modules to develop applications (computer programs) for analyzing process models. The input ...

  12. Reliability Assessment of IGBT Modules Modeled as Systems with Correlated Components

    DEFF Research Database (Denmark)

    Kostandyan, Erik; Sørensen, John Dalsgaard

    2013-01-01

    configuration. The estimated system reliability by the proposed method is a conservative estimate. Application of the suggested method could be extended for reliability estimation of systems composing of welding joints, bolts, bearings, etc. The reliability model incorporates the correlation between...... was applied for the systems failure functions estimation. It is desired to compare the results with the true system failure function, which is possible to estimate using simulation techniques. Theoretical model development should be applied for the further research. One of the directions for it might...... be modeling the system based on the Sequential Order Statistics, by considering the failure of the minimum (weakest component) at each loading level. The proposed idea to represent the system by the independent components could also be used for modeling reliability by Sequential Order Statistics....

  13. Reliability Modeling Development and Its Applications for Ceramic Capacitors with Base-Metal Electrodes (BMEs)

    Science.gov (United States)

    Liu, Donhang

    2014-01-01

    This presentation includes a summary of NEPP-funded deliverables for the Base-Metal Electrodes (BMEs) capacitor task, development of a general reliability model for BME capacitors, and a summary and future work.

  14. Modeling Nonstationary Emotion Dynamics in Dyads using a Time-Varying Vector-Autoregressive Model.

    Science.gov (United States)

    Bringmann, Laura F; Ferrer, Emilio; Hamaker, Ellen L; Borsboom, Denny; Tuerlinckx, Francis

    2018-01-01

    Emotion dynamics are likely to arise in an interpersonal context. Standard methods to study emotions in interpersonal interaction are limited because stationarity is assumed. This means that the dynamics, for example, time-lagged relations, are invariant across time periods. However, this is generally an unrealistic assumption. Whether caused by an external (e.g., divorce) or an internal (e.g., rumination) event, emotion dynamics are prone to change. The semi-parametric time-varying vector-autoregressive (TV-VAR) model is based on well-studied generalized additive models, implemented in the software R. The TV-VAR can explicitly model changes in temporal dependency without pre-existing knowledge about the nature of change. A simulation study is presented, showing that the TV-VAR model is superior to the standard time-invariant VAR model when the dynamics change over time. The TV-VAR model is applied to empirical data on daily feelings of positive affect (PA) from a single couple. Our analyses indicate reliable changes in the male's emotion dynamics over time, but not in the female's-which were not predicted by her own affect or that of her partner. This application illustrates the usefulness of using a TV-VAR model to detect changes in the dynamics in a system.

  15. Microstructural Modeling of Brittle Materials for Enhanced Performance and Reliability.

    Energy Technology Data Exchange (ETDEWEB)

    Teague, Melissa Christine [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Teague, Melissa Christine [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Rodgers, Theron [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Rodgers, Theron [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Grutzik, Scott Joseph [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Grutzik, Scott Joseph [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Meserole, Stephen [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Meserole, Stephen [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-08-01

    Brittle failure is often influenced by difficult to measure and variable microstructure-scale stresses. Recent advances in photoluminescence spectroscopy (PLS), including improved confocal laser measurement and rapid spectroscopic data collection have established the potential to map stresses with microscale spatial resolution (%3C2 microns). Advanced PLS was successfully used to investigate both residual and externally applied stresses in polycrystalline alumina at the microstructure scale. The measured average stresses matched those estimated from beam theory to within one standard deviation, validating the technique. Modeling the residual stresses within the microstructure produced general agreement in comparison with the experimentally measured results. Microstructure scale modeling is primed to take advantage of advanced PLS to enable its refinement and validation, eventually enabling microstructure modeling to become a predictive tool for brittle materials.

  16. Some dynamical aspects of interacting quintessence model

    Indian Academy of Sciences (India)

    Binayak S Choudhury

    2018-03-16

    Mar 16, 2018 ... Accelerated expansion of the Universe; quintessence; dynamical system; Friedmann–Lemaitre–. Robertson–Walker ... accepted theoretical model. One of the .... Thus, quintessence loses its self-strength and gives dark matter.

  17. Modeling of truck's braking dynamics with ABS

    Directory of Open Access Journals (Sweden)

    Maxym DYACHUK

    2014-09-01

    Full Text Available In the article some questions of ABS simulation on the basis of plane vehicle's dynamics and automatic modeling are considered. The author's algorithm of ABS modulators control is presented.

  18. Modelling Reliability of Supply and Infrastructural Dependency in Energy Distribution Systems

    OpenAIRE

    Helseth, Arild

    2008-01-01

    This thesis presents methods and models for assessing reliability of supply and infrastructural dependency in energy distribution systems with multiple energy carriers. The three energy carriers of electric power, natural gas and district heating are considered. Models and methods for assessing reliability of supply in electric power systems are well documented, frequently applied in the industry and continuously being subject to research and improvement. On the contrary, there are compar...

  19. An analytical model for computation of reliability of waste management facilities with intermediate storages

    International Nuclear Information System (INIS)

    Kallweit, A.; Schumacher, F.

    1977-01-01

    A high reliability is called for waste management facilities within the fuel cycle of nuclear power stations which can be fulfilled by providing intermediate storage facilities and reserve capacities. In this report a model based on the theory of Markov processes is described which allows computation of reliability characteristics of waste management facilities containing intermediate storage facilities. The application of the model is demonstrated by an example. (orig.) [de

  20. Parametric and semiparametric models with applications to reliability, survival analysis, and quality of life

    CERN Document Server

    Nikulin, M; Mesbah, M; Limnios, N

    2004-01-01

    Parametric and semiparametric models are tools with a wide range of applications to reliability, survival analysis, and quality of life. This self-contained volume examines these tools in survey articles written by experts currently working on the development and evaluation of models and methods. While a number of chapters deal with general theory, several explore more specific connections and recent results in "real-world" reliability theory, survival analysis, and related fields.

  1. Appraisal and Reliability of Variable Engagement Model Prediction ...

    African Journals Online (AJOL)

    The variable engagement model based on the stress - crack opening displacement relationship and, which describes the behaviour of randomly oriented steel fibres composite subjected to uniaxial tension has been evaluated so as to determine the safety indices associated when the fibres are subjected to pullout and with ...

  2. Multi-state reliability for coolant pump based on dependent competitive failure model

    International Nuclear Information System (INIS)

    Shang Yanlong; Cai Qi; Zhao Xinwen; Chen Ling

    2013-01-01

    By taking into account the effect of degradation due to internal vibration and external shocks. and based on service environment and degradation mechanism of nuclear power plant coolant pump, a multi-state reliability model of coolant pump was proposed for the system that involves competitive failure process between shocks and degradation. Using this model, degradation state probability and system reliability were obtained under the consideration of internal vibration and external shocks for the degraded coolant pump. It provided an effective method to reliability analysis for coolant pump in nuclear power plant based on operating environment. The results can provide a decision making basis for design changing and maintenance optimization. (authors)

  3. Reliability Evaluation for the Surface to Air Missile Weapon Based on Cloud Model

    Directory of Open Access Journals (Sweden)

    Deng Jianjun

    2015-01-01

    Full Text Available The fuzziness and randomness is integrated by using digital characteristics, such as Expected value, Entropy and Hyper entropy. The cloud model adapted to reliability evaluation is put forward based on the concept of the surface to air missile weapon. The cloud scale of the qualitative evaluation is constructed, and the quantitative variable and the qualitative variable in the system reliability evaluation are corresponded. The practical calculation result shows that it is more effective to analyze the reliability of the surface to air missile weapon by this way. The practical calculation result also reflects the model expressed by cloud theory is more consistent with the human thinking style of uncertainty.

  4. Modeling reliability measurement of interface on information system: Towards the forensic of rules

    Science.gov (United States)

    Nasution, M. K. M.; Sitompul, Darwin; Harahap, Marwan

    2018-02-01

    Today almost all machines depend on the software. As a software and hardware system depends also on the rules that are the procedures for its use. If the procedure or program can be reliably characterized by involving the concept of graph, logic, and probability, then regulatory strength can also be measured accordingly. Therefore, this paper initiates an enumeration model to measure the reliability of interfaces based on the case of information systems supported by the rules of use by the relevant agencies. An enumeration model is obtained based on software reliability calculation.

  5. Dynamic Models of Insurgent Activity

    Science.gov (United States)

    2014-05-19

    one dimension that has recently been studied in the computer science community. The model involves movement with a speed proportional to a “fear...more realistic model of human locomotion. The movement of the criminal agents follows a biased Levy flight with step sizes distributed according to a...power-law distribution. The biased Brownian motion of the original model is then derived as a special case. Starting with an agent-based model, we

  6. Stochastic population dynamic models as probability networks

    Science.gov (United States)

    M.E. and D.C. Lee. Borsuk

    2009-01-01

    The dynamics of a population and its response to environmental change depend on the balance of birth, death and age-at-maturity, and there have been many attempts to mathematically model populations based on these characteristics. Historically, most of these models were deterministic, meaning that the results were strictly determined by the equations of the model and...

  7. Reliability prediction system based on the failure rate model for electronic components

    International Nuclear Information System (INIS)

    Lee, Seung Woo; Lee, Hwa Ki

    2008-01-01

    Although many methodologies for predicting the reliability of electronic components have been developed, their reliability might be subjective according to a particular set of circumstances, and therefore it is not easy to quantify their reliability. Among the reliability prediction methods are the statistical analysis based method, the similarity analysis method based on an external failure rate database, and the method based on the physics-of-failure model. In this study, we developed a system by which the reliability of electronic components can be predicted by creating a system for the statistical analysis method of predicting reliability most easily. The failure rate models that were applied are MILHDBK- 217F N2, PRISM, and Telcordia (Bellcore), and these were compared with the general purpose system in order to validate the effectiveness of the developed system. Being able to predict the reliability of electronic components from the stage of design, the system that we have developed is expected to contribute to enhancing the reliability of electronic components

  8. Model uncertainty and multimodel inference in reliability estimation within a longitudinal framework.

    Science.gov (United States)

    Alonso, Ariel; Laenen, Annouschka

    2013-05-01

    Laenen, Alonso, and Molenberghs (2007) and Laenen, Alonso, Molenberghs, and Vangeneugden (2009) proposed a method to assess the reliability of rating scales in a longitudinal context. The methodology is based on hierarchical linear models, and reliability coefficients are derived from the corresponding covariance matrices. However, finding a good parsimonious model to describe complex longitudinal data is a challenging task. Frequently, several models fit the data equally well, raising the problem of model selection uncertainty. When model uncertainty is high one may resort to model averaging, where inferences are based not on one but on an entire set of models. We explored the use of different model building strategies, including model averaging, in reliability estimation. We found that the approach introduced by Laenen et al. (2007, 2009) combined with some of these strategies may yield meaningful results in the presence of high model selection uncertainty and when all models are misspecified, in so far as some of them manage to capture the most salient features of the data. Nonetheless, when all models omit prominent regularities in the data, misleading results may be obtained. The main ideas are further illustrated on a case study in which the reliability of the Hamilton Anxiety Rating Scale is estimated. Importantly, the ambit of model selection uncertainty and model averaging transcends the specific setting studied in the paper and may be of interest in other areas of psychometrics. © 2012 The British Psychological Society.

  9. Quantification of Wave Model Uncertainties Used for Probabilistic Reliability Assessments of Wave Energy Converters

    DEFF Research Database (Denmark)

    Ambühl, Simon; Kofoed, Jens Peter; Sørensen, John Dalsgaard

    2015-01-01

    Wave models used for site assessments are subjected to model uncertainties, which need to be quantified when using wave model results for probabilistic reliability assessments. This paper focuses on determination of wave model uncertainties. Four different wave models are considered, and validation...... data are collected from published scientific research. The bias and the root-mean-square error, as well as the scatter index, are considered for the significant wave height as well as the mean zero-crossing wave period. Based on an illustrative generic example, this paper presents how the quantified...... uncertainties can be implemented in probabilistic reliability assessments....

  10. Determination of Wave Model Uncertainties used for Probabilistic Reliability Assessments of Wave Energy Devices

    DEFF Research Database (Denmark)

    Ambühl, Simon; Kofoed, Jens Peter; Sørensen, John Dalsgaard

    2014-01-01

    Wave models used for site assessments are subject to model uncertainties, which need to be quantified when using wave model results for probabilistic reliability assessments. This paper focuses on determination of wave model uncertainties. Considered are four different wave models and validation...... data is collected from published scientific research. The bias, the root-mean-square error as well as the scatter index are considered for the significant wave height as well as the mean zero-crossing wave period. Based on an illustrative generic example it is shown how the estimated uncertainties can...... be implemented in probabilistic reliability assessments....

  11. On new cautious structural reliability models in the framework of imprecise probabilities

    DEFF Research Database (Denmark)

    Utkin, Lev; Kozine, Igor

    2010-01-01

    measures when the number of events of interest or observations is very small. The main feature of the models is that prior ignorance is not modelled by a fixed single prior distribution, but by a class of priors which is defined by upper and lower probabilities that can converge as statistical data......New imprecise structural reliability models are described in this paper. They are developed based on the imprecise Bayesian inference and are imprecise Dirichlet, imprecise negative binomial, gamma-exponential and normal models. The models are applied to computing cautious structural reliability...

  12. Bond graph modeling of nuclear reactor dynamics

    International Nuclear Information System (INIS)

    Tylee, J.L.

    1981-01-01

    A tenth-order linear model of a pressurized water reactor (PWR) is developed using bond graph techniques. The model describes the nuclear heat generation process and the transfer of this heat to the reactor coolant. Comparisons between the calculated model response and test data from a small-scale PWR show the model to be an adequate representation of the actual plant dynamics. Possible application of the model in an advanced plant diagnostic system is discussed

  13. Swarm Intelligence for Urban Dynamics Modelling

    International Nuclear Information System (INIS)

    Ghnemat, Rawan; Bertelle, Cyrille; Duchamp, Gerard H. E.

    2009-01-01

    In this paper, we propose swarm intelligence algorithms to deal with dynamical and spatial organization emergence. The goal is to model and simulate the developement of spatial centers using multi-criteria. We combine a decentralized approach based on emergent clustering mixed with spatial constraints or attractions. We propose an extension of the ant nest building algorithm with multi-center and adaptive process. Typically, this model is suitable to analyse and simulate urban dynamics like gentrification or the dynamics of the cultural equipment in urban area.

  14. Swarm Intelligence for Urban Dynamics Modelling

    Science.gov (United States)

    Ghnemat, Rawan; Bertelle, Cyrille; Duchamp, Gérard H. E.

    2009-04-01

    In this paper, we propose swarm intelligence algorithms to deal with dynamical and spatial organization emergence. The goal is to model and simulate the developement of spatial centers using multi-criteria. We combine a decentralized approach based on emergent clustering mixed with spatial constraints or attractions. We propose an extension of the ant nest building algorithm with multi-center and adaptive process. Typically, this model is suitable to analyse and simulate urban dynamics like gentrification or the dynamics of the cultural equipment in urban area.

  15. Understanding and Modeling Teams As Dynamical Systems

    Science.gov (United States)

    Gorman, Jamie C.; Dunbar, Terri A.; Grimm, David; Gipson, Christina L.

    2017-01-01

    By its very nature, much of teamwork is distributed across, and not stored within, interdependent people working toward a common goal. In this light, we advocate a systems perspective on teamwork that is based on general coordination principles that are not limited to cognitive, motor, and physiological levels of explanation within the individual. In this article, we present a framework for understanding and modeling teams as dynamical systems and review our empirical findings on teams as dynamical systems. We proceed by (a) considering the question of why study teams as dynamical systems, (b) considering the meaning of dynamical systems concepts (attractors; perturbation; synchronization; fractals) in the context of teams, (c) describe empirical studies of team coordination dynamics at the perceptual-motor, cognitive-behavioral, and cognitive-neurophysiological levels of analysis, and (d) consider the theoretical and practical implications of this approach, including new kinds of explanations of human performance and real-time analysis and performance modeling. Throughout our discussion of the topics we consider how to describe teamwork using equations and/or modeling techniques that describe the dynamics. Finally, we consider what dynamical equations and models do and do not tell us about human performance in teams and suggest future research directions in this area. PMID:28744231

  16. A General Reliability Model for Ni-BaTiO3-Based Multilayer Ceramic Capacitors

    Science.gov (United States)

    Liu, Donhang

    2014-01-01

    The evaluation of multilayer ceramic capacitors (MLCCs) with Ni electrode and BaTiO3 dielectric material for potential space project applications requires an in-depth understanding of their reliability. A general reliability model for Ni-BaTiO3 MLCC is developed and discussed. The model consists of three parts: a statistical distribution; an acceleration function that describes how a capacitor's reliability life responds to the external stresses, and an empirical function that defines contribution of the structural and constructional characteristics of a multilayer capacitor device, such as the number of dielectric layers N, dielectric thickness d, average grain size, and capacitor chip size A. Application examples are also discussed based on the proposed reliability model for Ni-BaTiO3 MLCCs.

  17. Dynamical models of spiral galaxies

    International Nuclear Information System (INIS)

    Grosbol, P.

    1990-01-01

    The effects of changing the basic parameters of rotation curve steepness, amount of bulge, and pitch angle of the imposed spiral pattern in the galactic model of Contoupolos and Grosbel (1986) are investigated. The general conclusions of the model are confirmed and shown to be insensitive to the specific choice of parameters for the galactic potential. The exact amplitude at which the nonlinear effects at the 4:1 resonance become important do, however, depend on the model

  18. Energy Balance Models and Planetary Dynamics

    Science.gov (United States)

    Domagal-Goldman, Shawn

    2012-01-01

    We know that planetary dynamics can have a significant affect on the climate of planets. Planetary dynamics dominate the glacial-interglacial periods on Earth, leaving a significant imprint on the geological record. They have also been demonstrated to have a driving influence on the climates of other planets in our solar system. We should therefore expect th.ere to be similar relationships on extrasolar planets. Here we describe a simple energy balance model that can predict the growth and thickness of glaciers, and their feedbacks on climate. We will also describe model changes that we have made to include planetary dynamics effects. This is the model we will use at the start of our collaboration to handle the influence of dynamics on climate.

  19. Validating clustering of molecular dynamics simulations using polymer models

    Directory of Open Access Journals (Sweden)

    Phillips Joshua L

    2011-11-01

    Full Text Available Abstract Background Molecular dynamics (MD simulation is a powerful technique for sampling the meta-stable and transitional conformations of proteins and other biomolecules. Computational data clustering has emerged as a useful, automated technique for extracting conformational states from MD simulation data. Despite extensive application, relatively little work has been done to determine if the clustering algorithms are actually extracting useful information. A primary goal of this paper therefore is to provide such an understanding through a detailed analysis of data clustering applied to a series of increasingly complex biopolymer models. Results We develop a novel series of models using basic polymer theory that have intuitive, clearly-defined dynamics and exhibit the essential properties that we are seeking to identify in MD simulations of real biomolecules. We then apply spectral clustering, an algorithm particularly well-suited for clustering polymer structures, to our models and MD simulations of several intrinsically disordered proteins. Clustering results for the polymer models provide clear evidence that the meta-stable and transitional conformations are detected by the algorithm. The results for the polymer models also help guide the analysis of the disordered protein simulations by comparing and contrasting the statistical properties of the extracted clusters. Conclusions We have developed a framework for validating the performance and utility of clustering algorithms for studying molecular biopolymer simulations that utilizes several analytic and dynamic polymer models which exhibit well-behaved dynamics including: meta-stable states, transition states, helical structures, and stochastic dynamics. We show that spectral clustering is robust to anomalies introduced by structural alignment and that different structural classes of intrinsically disordered proteins can be reliably discriminated from the clustering results. To our

  20. Stirling Engine Dynamic System Modeling

    Science.gov (United States)

    Nakis, Christopher G.

    2004-01-01

    The Thermo-Mechanical systems branch at the Glenn Research Center focuses a large amount time on Stirling engines. These engines will be used on missions where solar power is inefficient, especially in deep space. I work with Tim Regan and Ed Lewandowski who are currently developing and validating a mathematical model for the Stirling engines. This model incorporates all aspects of the system including, mechanical, electrical and thermodynamic components. Modeling is done through Simplorer, a program capable of running simulations of the model. Once created and then proven to be accurate, a model is used for developing new ideas for engine design. My largest specific project involves varying key parameters in the model and quantifying the results. This can all be done relatively trouble-free with the help of Simplorer. Once the model is complete, Simplorer will do all the necessary calculations. The more complicated part of this project is determining which parameters to vary. Finding key parameters depends on the potential for a value to be independently altered in the design. For example, a change in one dimension may lead to a proportional change to the rest of the model, and no real progress is made. Also, the ability for a changed value to have a substantial impact on the outputs of the system is important. Results will be condensed into graphs and tables with the purpose of better communication and understanding of the data. With the changing of these parameters, a more optimal design can be created without having to purchase or build any models. Also, hours and hours of results can be simulated in minutes. In the long run, using mathematical models can save time and money. Along with this project, I have many other smaller assignments throughout the summer. My main goal is to assist in the processes of model development, validation and testing.

  1. Brand Equity Evolution: a System Dynamics Model

    Directory of Open Access Journals (Sweden)

    Edson Crescitelli

    2009-04-01

    Full Text Available One of the greatest challenges in brand management lies in monitoring brand equity over time. This paper aimsto present a simulation model able to represent this evolution. The model was drawn on brand equity concepts developed by Aaker and Joachimsthaler (2000, using the system dynamics methodology. The use ofcomputational dynamic models aims to create new sources of information able to sensitize academics and managers alike to the dynamic implications of their brand management. As a result, an easily implementable model was generated, capable of executing continuous scenario simulations by surveying casual relations among the variables that explain brand equity. Moreover, the existence of a number of system modeling tools will allow extensive application of the concepts used in this study in practical situations, both in professional and educational settings

  2. Discrete dynamic modeling of cellular signaling networks.

    Science.gov (United States)

    Albert, Réka; Wang, Rui-Sheng

    2009-01-01

    Understanding signal transduction in cellular systems is a central issue in systems biology. Numerous experiments from different laboratories generate an abundance of individual components and causal interactions mediating environmental and developmental signals. However, for many signal transduction systems there is insufficient information on the overall structure and the molecular mechanisms involved in the signaling network. Moreover, lack of kinetic and temporal information makes it difficult to construct quantitative models of signal transduction pathways. Discrete dynamic modeling, combined with network analysis, provides an effective way to integrate fragmentary knowledge of regulatory interactions into a predictive mathematical model which is able to describe the time evolution of the system without the requirement for kinetic parameters. This chapter introduces the fundamental concepts of discrete dynamic modeling, particularly focusing on Boolean dynamic models. We describe this method step-by-step in the context of cellular signaling networks. Several variants of Boolean dynamic models including threshold Boolean networks and piecewise linear systems are also covered, followed by two examples of successful application of discrete dynamic modeling in cell biology.

  3. Dynamic Modelling with "MLE-Energy Dynamic" for Primary School

    Science.gov (United States)

    Giliberti, Enrico; Corni, Federico

    During the recent years simulation and modelling are growing instances in science education. In primary school, however, the main use of software is the simulation, due to the lack of modelling software tools specially designed to fit/accomplish the needs of primary education. In particular primary school teachers need to use simulation in a framework that is both consistent and simple enough to be understandable by children [2]. One of the possible area to approach modelling is about the construction of the concept of energy, in particular for what concerns the relations among substance, potential, power [3]. Following the previous initial research results with this approach [2], and with the static version of the software MLE Energy [1], we suggest the design and the experimentation of a dynamic modelling software—MLE dynamic-capable to represent dynamically the relations occurring when two substance-like quantities exchange energy, modifying their potential. By means of this software the user can graphically choose the dependent and independent variables and leave the other parameters fixed. The software has been initially evaluated, during a course of science education with a group of primary school teachers-to-be, to test the ability of the software to improve teachers' way of thinking in terms of substance-like quantities and their effects (graphical representation of the extensive, intensive variables and their mutual relations); moreover, the software has been tested with a group of primary school teachers, asking their opinion about the software didactical relevance in the class work.

  4. Assessing Reliability of Cellulose Hydrolysis Models to Support Biofuel Process Design – Identifiability and Uncertainty Analysis

    DEFF Research Database (Denmark)

    Sin, Gürkan; Meyer, Anne S.; Gernaey, Krist

    2010-01-01

    The reliability of cellulose hydrolysis models is studied using the NREL model. An identifiability analysis revealed that only 6 out of 26 parameters are identifiable from the available data (typical hydrolysis experiments). Attempting to identify a higher number of parameters (as done in the ori......The reliability of cellulose hydrolysis models is studied using the NREL model. An identifiability analysis revealed that only 6 out of 26 parameters are identifiable from the available data (typical hydrolysis experiments). Attempting to identify a higher number of parameters (as done...

  5. Use of measurement theory for operationalization and quantification of psychological constructs in systems dynamics modelling

    Science.gov (United States)

    Fitkov-Norris, Elena; Yeghiazarian, Ara

    2016-11-01

    The analytical tools available to social scientists have traditionally been adapted from tools originally designed for analysis of natural science phenomena. This article discusses the applicability of systems dynamics - a qualitative based modelling approach, as a possible analysis and simulation tool that bridges the gap between social and natural sciences. After a brief overview of the systems dynamics modelling methodology, the advantages as well as limiting factors of systems dynamics to the potential applications in the field of social sciences and human interactions are discussed. The issues arise with regards to operationalization and quantification of latent constructs at the simulation building stage of the systems dynamics methodology and measurement theory is proposed as a ready and waiting solution to the problem of dynamic model calibration, with a view of improving simulation model reliability and validity and encouraging the development of standardised, modular system dynamics models that can be used in social science research.

  6. Dynamics of the standard model

    CERN Document Server

    Donoghue, John F; Holstein, Barry R

    2014-01-01

    Describing the fundamental theory of particle physics and its applications, this book provides a detailed account of the Standard Model, focusing on techniques that can produce information about real observed phenomena. The book begins with a pedagogic account of the Standard Model, introducing essential techniques such as effective field theory and path integral methods. It then focuses on the use of the Standard Model in the calculation of physical properties of particles. Rigorous methods are emphasized, but other useful models are also described. This second edition has been updated to include recent theoretical and experimental advances, such as the discovery of the Higgs boson. A new chapter is devoted to the theoretical and experimental understanding of neutrinos, and major advances in CP violation and electroweak physics have been given a modern treatment. This book is valuable to graduate students and researchers in particle physics, nuclear physics and related fields.

  7. Forecasting with Dynamic Regression Models

    CERN Document Server

    Pankratz, Alan

    2012-01-01

    One of the most widely used tools in statistical forecasting, single equation regression models is examined here. A companion to the author's earlier work, Forecasting with Univariate Box-Jenkins Models: Concepts and Cases, the present text pulls together recent time series ideas and gives special attention to possible intertemporal patterns, distributed lag responses of output to input series and the auto correlation patterns of regression disturbance. It also includes six case studies.

  8. IMPROVEMENT OF MATHEMATICAL MODELS FOR ESTIMATION OF TRAIN DYNAMICS

    Directory of Open Access Journals (Sweden)

    L. V. Ursulyak

    2017-12-01

    Full Text Available Purpose. Using scientific publications the paper analyzes the mathematical models developed in Ukraine, CIS countries and abroad for theoretical studies of train dynamics and also shows the urgency of their further improvement. Methodology. Information base of the research was official full-text and abstract databases, scientific works of domestic and foreign scientists, professional periodicals, materials of scientific and practical conferences, methodological materials of ministries and departments. Analysis of publications on existing mathematical models used to solve a wide range of problems associated with the train dynamics study shows the expediency of their application. Findings. The results of these studies were used in: 1 design of new types of draft gears and air distributors; 2 development of methods for controlling the movement of conventional and connected trains; 3 creation of appropriate process flow diagrams; 4 development of energy-saving methods of train driving; 5 revision of the Construction Codes and Regulations (SNiP ΙΙ-39.76; 6 when selecting the parameters of the autonomous automatic control system, created in DNURT, for an auxiliary locomotive that is part of a connected train; 7 when creating computer simulators for the training of locomotive drivers; 8 assessment of the vehicle dynamic indices characterizing traffic safety. Scientists around the world conduct numerical experiments related to estimation of train dynamics using mathematical models that need to be constantly improved. Originality. The authors presented the main theoretical postulates that allowed them to develop the existing mathematical models for solving problems related to the train dynamics. The analysis of scientific articles published in Ukraine, CIS countries and abroad allows us to determine the most relevant areas of application of mathematical models. Practicalvalue. The practical value of the results obtained lies in the scientific validity

  9. Dynamic Modelling Of A SCARA Robot

    Science.gov (United States)

    Turiel, J. Perez; Calleja, R. Grossi; Diez, V. Gutierrez

    1987-10-01

    This paper describes a method for modelling industrial robots that considers dynamic approach to manipulation systems motion generation, obtaining the complete dynamic model for the mechanic part of the robot and taking into account the dynamic effect of actuators acting at the joints. For a four degree of freedom SCARA robot we obtain the dynamic model for the basic (minimal) configuration, that is, the three degrees of freedom that allow us to place the robot end effector in a desired point, using the Lagrange Method to obtain the dynamic equations in matrix form. The manipulator is considered to be a set of rigid bodies inter-connected by joints in the form of simple kinematic pairs. Then, the state space model is obtained for the actuators that move the robot joints, uniting the models of the single actuators, that is, two DC permanent magnet servomotors and an electrohydraulic actuator. Finally, using a computer simulation program written in FORTRAN language, we can compute the matrices of the complete model.

  10. Dynamic modeling of IGCC power plants

    International Nuclear Information System (INIS)

    Casella, F.; Colonna, P.

    2012-01-01

    Integrated Gasification Combined Cycle (IGCC) power plants are an effective option to reduce emissions and implement carbon-dioxide sequestration. The combination of a very complex fuel-processing plant and a combined cycle power station leads to challenging problems as far as dynamic operation is concerned. Dynamic performance is extremely relevant because recent developments in the electricity market push toward an ever more flexible and varying operation of power plants. A dynamic model of the entire system and models of its sub-systems are indispensable tools in order to perform computer simulations aimed at process and control design. This paper presents the development of the lumped-parameters dynamic model of an entrained-flow gasifier, with special emphasis on the modeling approach. The model is implemented into software by means of the Modelica language and validated by comparison with one set of data related to the steady operation of the gasifier of the Buggenum power station in the Netherlands. Furthermore, in order to demonstrate the potential of the proposed modeling approach and the use of simulation for control design purposes, a complete model of an exemplary IGCC power plant, including its control system, has been developed, by re-using existing models of combined cycle plant components; the results of a load dispatch ramp simulation are presented and shortly discussed. - Highlights: ► The acausal dynamic model of an entrained gasifier has been developed. ► The model can be used to perform system optimization and control studies. ► The model has been validated using field data. ► Model use is illustrated with an example showing the transient of an IGCC plant.

  11. Automated adaptive inference of phenomenological dynamical models

    Science.gov (United States)

    Daniels, Bryan

    Understanding the dynamics of biochemical systems can seem impossibly complicated at the microscopic level: detailed properties of every molecular species, including those that have not yet been discovered, could be important for producing macroscopic behavior. The profusion of data in this area has raised the hope that microscopic dynamics might be recovered in an automated search over possible models, yet the combinatorial growth of this space has limited these techniques to systems that contain only a few interacting species. We take a different approach inspired by coarse-grained, phenomenological models in physics. Akin to a Taylor series producing Hooke's Law, forgoing microscopic accuracy allows us to constrain the search over dynamical models to a single dimension. This makes it feasible to infer dynamics with very limited data, including cases in which important dynamical variables are unobserved. We name our method Sir Isaac after its ability to infer the dynamical structure of the law of gravitation given simulated planetary motion data. Applying the method to output from a microscopically complicated but macroscopically simple biological signaling model, it is able to adapt the level of detail to the amount of available data. Finally, using nematode behavioral time series data, the method discovers an effective switch between behavioral attractors after the application of a painful stimulus.

  12. A Stochastic Reliability Model for Application in a Multidisciplinary Optimization of a Low Pressure Turbine Blade Made of Titanium Aluminide

    Directory of Open Access Journals (Sweden)

    Christian Dresbach

    Full Text Available Abstract Currently, there are a lot of research activities dealing with gamma titanium aluminide (γ-TiAl alloys as new materials for low pressure turbine (LPT blades. Even though the scatter in mechanical properties of such intermetallic alloys is more distinctive as in conventional metallic alloys, stochastic investigations on γ -TiAl alloys are very rare. For this reason, we analyzed the scatter in static and dynamic mechanical properties of the cast alloy Ti-48Al-2Cr-2Nb. It was found that this alloy shows a size effect in strength which is less pronounced than the size effect of brittle materials. A weakest-link approach is enhanced for describing a scalable size effect under multiaxial stress states and implemented in a post processing tool for reliability analysis of real components. The presented approach is a first applicable reliability model for semi-brittle materials. The developed reliability tool was integrated into a multidisciplinary optimization of the geometry of a LPT blade. Some processes of the optimization were distributed in a wide area network, so that specialized tools for each discipline could be employed. The optimization results show that it is possible to increase the aerodynamic efficiency and the structural mechanics reliability at the same time, while ensuring the blade can be manufactured in an investment casting process.

  13. Maintenance personnel performance simulation (MAPPS): a model for predicting maintenance performance reliability in nuclear power plants

    International Nuclear Information System (INIS)

    Knee, H.E.; Krois, P.A.; Haas, P.M.; Siegel, A.I.; Ryan, T.G.

    1983-01-01

    The NRC has developed a structured, quantitative, predictive methodology in the form of a computerized simulation model for assessing maintainer task performance. Objective of the overall program is to develop, validate, and disseminate a practical, useful, and acceptable methodology for the quantitative assessment of NPP maintenance personnel reliability. The program was organized into four phases: (1) scoping study, (2) model development, (3) model evaluation, and (4) model dissemination. The program is currently nearing completion of Phase 2 - Model Development

  14. On reliability and maintenance modelling of ageing equipment in electric power systems

    International Nuclear Information System (INIS)

    Lindquist, Tommie

    2008-04-01

    Maintenance optimisation is essential to achieve cost-efficiency, availability and reliability of supply in electric power systems. The process of maintenance optimisation requires information about the costs of preventive and corrective maintenance, as well as the costs of failures borne by both electricity suppliers and customers. To calculate expected costs, information is needed about equipment reliability characteristics and the way in which maintenance affects equipment reliability. The aim of this Ph.D. work has been to develop equipment reliability models taking the effect of maintenance into account. The research has focussed on the interrelated areas of condition estimation, reliability modelling and maintenance modelling, which have been investigated in a number of case studies. In the area of condition estimation two methods to quantitatively estimate the condition of disconnector contacts have been developed, which utilise results from infrared thermography inspections and contact resistance measurements. The accuracy of these methods were investigated in two case studies. Reliability models have been developed and implemented for SF6 circuit-breakers, disconnector contacts and XLPE cables in three separate case studies. These models were formulated using both empirical and physical modelling approaches. To improve confidence in such models a Bayesian statistical method incorporating information from the equipment design process was also developed. This method was illustrated in a case study of SF6 circuit-breaker operating rods. Methods for quantifying the effect of maintenance on equipment condition and reliability have been investigated in case studies on disconnector contacts and SF6 circuit-breakers. The input required by these methods are condition measurements and historical failure and maintenance data, respectively. This research has demonstrated that the effect of maintenance on power system equipment may be quantified using available data

  15. A Tutorial on Nonlinear Time-Series Data Mining in Engineering Asset Health and Reliability Prediction: Concepts, Models, and Algorithms

    Directory of Open Access Journals (Sweden)

    Ming Dong

    2010-01-01

    Full Text Available The primary objective of engineering asset management is to optimize assets service delivery potential and to minimize the related risks and costs over their entire life through the development and application of asset health and usage management in which the health and reliability prediction plays an important role. In real-life situations where an engineering asset operates under dynamic operational and environmental conditions, the lifetime of an engineering asset is generally described as monitored nonlinear time-series data and subject to high levels of uncertainty and unpredictability. It has been proved that application of data mining techniques is very useful for extracting relevant features which can be used as parameters for assets diagnosis and prognosis. In this paper, a tutorial on nonlinear time-series data mining in engineering asset health and reliability prediction is given. Besides that an overview on health and reliability prediction techniques for engineering assets is covered, this tutorial will focus on concepts, models, algorithms, and applications of hidden Markov models (HMMs and hidden semi-Markov models (HSMMs in engineering asset health prognosis, which are representatives of recent engineering asset health prediction techniques.

  16. Damage Model for Reliability Assessment of Solder Joints in Wind Turbines

    DEFF Research Database (Denmark)

    Kostandyan, Erik; Sørensen, John Dalsgaard

    2012-01-01

    environmental factors. Reliability assessment for such type of products conventionally is performed by classical reliability techniques based on test data. Usually conventional reliability approaches are time and resource consuming activities. Thus in this paper we choose a physics of failure approach to define...... damage model by Miner’s rule. Our attention is focused on crack propagation in solder joints of electrical components due to the temperature loadings. Based on the proposed method it is described how to find the damage level for a given temperature loading profile. The proposed method is discussed...

  17. The model case IRS-RWE for the determination of reliability data in practical operation

    International Nuclear Information System (INIS)

    Hoemke, P.; Krause, H.

    1975-11-01

    Reliability und availability analyses are carried out to assess the safety of nuclear power plants. This paper deals in the first part with the requirement of accuracy for the input data of such analyses and in the second part with the prototype data collection of reliability data 'Model case IRS-RWE'. The objectives and the structure of the data collection will be described. The present results show that the estimation of reliability data in power plants is possible and gives reasonable results. (orig.) [de

  18. Investigation of reliability indicators of information analysis systems based on Markov’s absorbing chain model

    Science.gov (United States)

    Gilmanshin, I. R.; Kirpichnikov, A. P.

    2017-09-01

    In the result of study of the algorithm of the functioning of the early detection module of excessive losses, it is proven the ability to model it by using absorbing Markov chains. The particular interest is in the study of probability characteristics of early detection module functioning algorithm of losses in order to identify the relationship of indicators of reliability of individual elements, or the probability of occurrence of certain events and the likelihood of transmission of reliable information. The identified relations during the analysis allow to set thresholds reliability characteristics of the system components.

  19. Maintenance overtime policies in reliability theory models with random working cycles

    CERN Document Server

    Nakagawa, Toshio

    2015-01-01

    This book introduces a new concept of replacement in maintenance and reliability theory. Replacement overtime, where replacement occurs at the first completion of a working cycle over a planned time, is a new research topic in maintenance theory and also serves to provide a fresh optimization technique in reliability engineering. In comparing replacement overtime with standard and random replacement techniques theoretically and numerically, 'Maintenance Overtime Policies in Reliability Theory' highlights the key benefits to be gained by adopting this new approach and shows how they can be applied to inspection policies, parallel systems and cumulative damage models. Utilizing the latest research in replacement overtime by internationally recognized experts, readers are introduced to new topics and methods, and learn how to practically apply this knowledge to actual reliability models. This book will serve as an essential guide to a new subject of study for graduate students and researchers and also provides a...

  20. Reliable software systems via chains of object models with provably correct behavior

    International Nuclear Information System (INIS)

    Yakhnis, A.; Yakhnis, V.

    1996-01-01

    This work addresses specification and design of reliable safety-critical systems, such as nuclear reactor control systems. Reliability concerns are addressed in complimentary fashion by different fields. Reliability engineers build software reliability models, etc. Safety engineers focus on prevention of potential harmful effects of systems on environment. Software/hardware correctness engineers focus on production of reliable systems on the basis of mathematical proofs. The authors think that correctness may be a crucial guiding issue in the development of reliable safety-critical systems. However, purely formal approaches are not adequate for the task, because they neglect the connection with the informal customer requirements. They alleviate that as follows. First, on the basis of the requirements, they build a model of the system interactions with the environment, where the system is viewed as a black box. They will provide foundations for automated tools which will (a) demonstrate to the customer that all of the scenarios of system behavior are presented in the model, (b) uncover scenarios not present in the requirements, and (c) uncover inconsistent scenarios. The developers will work with the customer until the black box model will not possess scenarios (b) and (c) above. Second, the authors will build a chain of several increasingly detailed models, where the first model is the black box model and the last model serves to automatically generated proved executable code. The behavior of each model will be proved to conform to the behavior of the previous one. They build each model as a cluster of interactive concurrent objects, thus they allow both top-down and bottom-up development

  1. Review of Dynamic Modeling and Simulation of Large Scale Belt Conveyor System

    Science.gov (United States)

    He, Qing; Li, Hong

    Belt conveyor is one of the most important devices to transport bulk-solid material for long distance. Dynamic analysis is the key to decide whether the design is rational in technique, safe and reliable in running, feasible in economy. It is very important to study dynamic properties, improve efficiency and productivity, guarantee conveyor safe, reliable and stable running. The dynamic researches and applications of large scale belt conveyor are discussed. The main research topics, the state-of-the-art of dynamic researches on belt conveyor are analyzed. The main future works focus on dynamic analysis, modeling and simulation of main components and whole system, nonlinear modeling, simulation and vibration analysis of large scale conveyor system.

  2. Online Learning of Industrial Manipulators' Dynamics Models

    DEFF Research Database (Denmark)

    Polydoros, Athanasios

    2017-01-01

    , it was compared with multiple other state-of-the-art machine learning algorithms. Moreover, the thesis presents the application of the proposed learning method on robot control for achieving trajectory execution while learning the inverse dynamics models  on-the-fly . Also it is presented the application...... of the dynamics models. Those mainly derive from physics-based methods and thus they are based on physical properties which are hard to be calculated.  In this thesis, is presented, a novel online machine learning approach  which is able to model both inverse and forward dynamics models of industrial manipulators....... The proposed method belongs to the class of deep learning and exploits the concepts of self-organization, recurrent neural networks and iterative multivariate Bayesian regression. It has been evaluated on multiple datasets captured from industrial robots while they were performing various tasks. Also...

  3. Dynamic optimization deterministic and stochastic models

    CERN Document Server

    Hinderer, Karl; Stieglitz, Michael

    2016-01-01

    This book explores discrete-time dynamic optimization and provides a detailed introduction to both deterministic and stochastic models. Covering problems with finite and infinite horizon, as well as Markov renewal programs, Bayesian control models and partially observable processes, the book focuses on the precise modelling of applications in a variety of areas, including operations research, computer science, mathematics, statistics, engineering, economics and finance. Dynamic Optimization is a carefully presented textbook which starts with discrete-time deterministic dynamic optimization problems, providing readers with the tools for sequential decision-making, before proceeding to the more complicated stochastic models. The authors present complete and simple proofs and illustrate the main results with numerous examples and exercises (without solutions). With relevant material covered in four appendices, this book is completely self-contained.

  4. Dynamic modeling of the INAPRO aquaponic system

    NARCIS (Netherlands)

    Karimanzira, Divas; Keesman, Karel J.; Kloas, Werner; Baganz, Daniela; Rauschenbach, Thomas

    2016-01-01

    The use of modeling techniques to analyze aquaponics systems is demonstrated with an example of dynamic modeling for the production of Nile tilapia (Oreochromis niloticus) and tomatoes (Solanum lycopersicon) using the innovative double recirculating aquaponic system ASTAF-PRO. For the management

  5. Dynamic spatial panels : models, methods, and inferences

    NARCIS (Netherlands)

    Elhorst, J. Paul

    This paper provides a survey of the existing literature on the specification and estimation of dynamic spatial panel data models, a collection of models for spatial panels extended to include one or more of the following variables and/or error terms: a dependent variable lagged in time, a dependent

  6. A Discrete Dynamical Model of Signed Partitions

    Directory of Open Access Journals (Sweden)

    G. Chiaselotti

    2013-01-01

    Full Text Available We use a discrete dynamical model with three evolution rules in order to analyze the structure of a partially ordered set of signed integer partitions whose main properties are actually not known. This model is related to the study of some extremal combinatorial sum problems.

  7. Dynamic Factor Models for the Volatility Surface

    DEFF Research Database (Denmark)

    van der Wel, Michel; Ozturk, Sait R.; Dijk, Dick van

    The implied volatility surface is the collection of volatilities implied by option contracts for different strike prices and time-to-maturity. We study factor models to capture the dynamics of this three-dimensional implied volatility surface. Three model types are considered to examine desirable...

  8. Reliability analysis and prediction of mixed mode load using Markov Chain Model

    International Nuclear Information System (INIS)

    Nikabdullah, N.; Singh, S. S. K.; Alebrahim, R.; Azizi, M. A.; K, Elwaleed A.; Noorani, M. S. M.

    2014-01-01

    The aim of this paper is to present the reliability analysis and prediction of mixed mode loading by using a simple two state Markov Chain Model for an automotive crankshaft. The reliability analysis and prediction for any automotive component or structure is important for analyzing and measuring the failure to increase the design life, eliminate or reduce the likelihood of failures and safety risk. The mechanical failures of the crankshaft are due of high bending and torsion stress concentration from high cycle and low rotating bending and torsional stress. The Markov Chain was used to model the two states based on the probability of failure due to bending and torsion stress. In most investigations it revealed that bending stress is much serve than torsional stress, therefore the probability criteria for the bending state would be higher compared to the torsion state. A statistical comparison between the developed Markov Chain Model and field data was done to observe the percentage of error. The reliability analysis and prediction was derived and illustrated from the Markov Chain Model were shown in the Weibull probability and cumulative distribution function, hazard rate and reliability curve and the bathtub curve. It can be concluded that Markov Chain Model has the ability to generate near similar data with minimal percentage of error and for a practical application; the proposed model provides a good accuracy in determining the reliability for the crankshaft under mixed mode loading

  9. Dynamical modeling of surface tension

    International Nuclear Information System (INIS)

    Brackbill, J.U.; Kothe, D.B.

    1996-01-01

    In a recent review it is said that free-surface flows ''represent some of the difficult remaining challenges in computational fluid dynamics''. There has been progress with the development of new approaches to treating interfaces, such as the level-set method and the improvement of older methods such as the VOF method. A common theme of many of the new developments has been the regularization of discontinuities at the interface. One example of this approach is the continuum surface force (CSF) formulation for surface tension, which replaces the surface stress given by Laplace's equation by an equivalent volume force. Here, we describe how CSF might be made more useful. Specifically, we consider a derivation of the CSF equations from a minimization of surface energy as outlined by Jacqmin. This reformulation suggests that if one eliminates the computation of curvature in terms of a unit normal vector, parasitic currents may be eliminated For this reformulation to work, it is necessary that transition region thickness be controlled. Various means for this, in addition to the one discussed by Jacqmin are discussed

  10. 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

  11. Analyzing dynamic fault trees derived from model-based system architectures

    International Nuclear Information System (INIS)

    Dehlinger, Josh; Dugan, Joanne Bechta

    2008-01-01

    Dependability-critical systems, such as digital instrumentation and control systems in nuclear power plants, necessitate engineering techniques and tools to provide assurances of their safety and reliability. Determining system reliability at the architectural design phase is important since it may guide design decisions and provide crucial information for trade-off analysis and estimating system cost. Despite this, reliability and system engineering remain separate disciplines and engineering processes by which the dependability analysis results may not represent the designed system. In this article we provide an overview and application of our approach to build architecture-based, dynamic system models for dependability-critical systems and then automatically generate Dynamic Fault Trees (DFT) for comprehensive, toolsupported reliability analysis. Specifically, we use the Architectural Analysis and Design Language (AADL) to model the structural, behavioral and failure aspects of the system in a composite architecture model. From the AADL model, we seek to derive the DFT(s) and use Galileo's automated reliability analyses to estimate system reliability. This approach alleviates the dependability engineering - systems engineering knowledge expertise gap, integrates the dependability and system engineering design and development processes and enables a more formal, automated and consistent DFT construction. We illustrate this work using an example based on a dynamic digital feed-water control system for a nuclear reactor

  12. Mesoscale Models of Fluid Dynamics

    Science.gov (United States)

    Boghosian, Bruce M.; Hadjiconstantinou, Nicolas G.

    During the last half century, enormous progress has been made in the field of computational materials modeling, to the extent that in many cases computational approaches are used in a predictive fashion. Despite this progress, modeling of general hydrodynamic behavior remains a challenging task. One of the main challenges stems from the fact that hydrodynamics manifests itself over a very wide range of length and time scales. On one end of the spectrum, one finds the fluid's "internal" scale characteristic of its molecular structure (in the absence of quantum effects, which we omit in this chapter). On the other end, the "outer" scale is set by the characteristic sizes of the problem's domain. The resulting scale separation or lack thereof as well as the existence of intermediate scales are key to determining the optimal approach. Successful treatments require a judicious choice of the level of description which is a delicate balancing act between the conflicting requirements of fidelity and manageable computational cost: a coarse description typically requires models for underlying processes occuring at smaller length and time scales; on the other hand, a fine-scale model will incur a significantly larger computational cost.

  13. Modelling biased human trust dynamics

    NARCIS (Netherlands)

    Hoogendoorn, M.; Jaffry, S.W.; Maanen, P.P. van; Treur, J.

    2013-01-01

    Abstract. Within human trust related behaviour, according to the literature from the domains of Psychology and Social Sciences often non-rational behaviour can be observed. Current trust models that have been developed typically do not incorporate non-rational elements in the trust formation

  14. Dynamic model for a boiling water reactor

    International Nuclear Information System (INIS)

    Muscettola, M.

    1963-07-01

    A theoretical formulation is derived for the dynamics of a boiling water reactor of the pressure tube and forced circulation type. Attention is concentrated on neutron kinetics, fuel element heat transfer dynamics, and the primary circuit - that is the boiling channel, riser, steam drum, downcomer and recirculating pump of a conventional La Mont loop. Models for the steam and feedwater plant are not derived. (author)

  15. On modeling human reliability in space flights - Redundancy and recovery operations

    Science.gov (United States)

    Aarset, M.; Wright, J. F.

    The reliability of humans is of paramount importance to the safety of space flight systems. This paper describes why 'back-up' operators might not be the best solution, and in some cases, might even degrade system reliability. The problem associated with human redundancy calls for special treatment in reliability analyses. The concept of Standby Redundancy is adopted, and psychological and mathematical models are introduced to improve the way such problems can be estimated and handled. In the past, human reliability has practically been neglected in most reliability analyses, and, when included, the humans have been modeled as a component and treated numerically the way technical components are. This approach is not wrong in itself, but it may lead to systematic errors if too simple analogies from the technical domain are used in the modeling of human behavior. In this paper redundancy in a man-machine system will be addressed. It will be shown how simplification from the technical domain, when applied to human components of a system, may give non-conservative estimates of system reliability.

  16. Predicting Flow Breakdown Probability and Duration in Stochastic Network Models: Impact on Travel Time Reliability

    Energy Technology Data Exchange (ETDEWEB)

    Dong, Jing [ORNL; Mahmassani, Hani S. [Northwestern University, Evanston

    2011-01-01

    This paper proposes a methodology to produce random flow breakdown endogenously in a mesoscopic operational model, by capturing breakdown probability and duration. Based on previous research findings that probability of flow breakdown can be represented as a function of flow rate and the duration can be characterized by a hazard model. By generating random flow breakdown at various levels and capturing the traffic characteristics at the onset of the breakdown, the stochastic network simulation model provides a tool for evaluating travel time variability. The proposed model can be used for (1) providing reliability related traveler information; (2) designing ITS (intelligent transportation systems) strategies to improve reliability; and (3) evaluating reliability-related performance measures of the system.

  17. Structural reliability analysis under evidence theory using the active learning kriging model

    Science.gov (United States)

    Yang, Xufeng; Liu, Yongshou; Ma, Panke

    2017-11-01

    Structural reliability analysis under evidence theory is investigated. It is rigorously proved that a surrogate model providing only correct sign prediction of the performance function can meet the accuracy requirement of evidence-theory-based reliability analysis. Accordingly, a method based on the active learning kriging model which only correctly predicts the sign of the performance function is proposed. Interval Monte Carlo simulation and a modified optimization method based on Karush-Kuhn-Tucker conditions are introduced to make the method more efficient in estimating the bounds of failure probability based on the kriging model. Four examples are investigated to demonstrate the efficiency and accuracy of the proposed method.

  18. A dynamical model for multifragmentation

    International Nuclear Information System (INIS)

    Ngo, H.; Ighezou, F.Z.; Ngo, C.

    1999-01-01

    The surface multifragmentation of highly excited (compression and thermal excitation) 208 Pb is investigated with a finite temperature spherical TDHF approximation coupled to a restructured aggregation model. This approach is discussed in terms of the data available from ALADIN collaboration at GSI on gold ion induced reactions on C, Al and Cu targets at 600 MeV/u excitation energy. The calculation showed that the slowest fragments originate in the nuclear volume while the smaller, faster fragments are emitted from surface

  19. Nonlinear Dynamic Models in Advanced Life Support

    Science.gov (United States)

    Jones, Harry

    2002-01-01

    To facilitate analysis, ALS systems are often assumed to be linear and time invariant, but they usually have important nonlinear and dynamic aspects. Nonlinear dynamic behavior can be caused by time varying inputs, changes in system parameters, nonlinear system functions, closed loop feedback delays, and limits on buffer storage or processing rates. Dynamic models are usually cataloged according to the number of state variables. The simplest dynamic models are linear, using only integration, multiplication, addition, and subtraction of the state variables. A general linear model with only two state variables can produce all the possible dynamic behavior of linear systems with many state variables, including stability, oscillation, or exponential growth and decay. Linear systems can be described using mathematical analysis. Nonlinear dynamics can be fully explored only by computer simulations of models. Unexpected behavior is produced by simple models having only two or three state variables with simple mathematical relations between them. Closed loop feedback delays are a major source of system instability. Exceeding limits on buffer storage or processing rates forces systems to change operating mode. Different equilibrium points may be reached from different initial conditions. Instead of one stable equilibrium point, the system may have several equilibrium points, oscillate at different frequencies, or even behave chaotically, depending on the system inputs and initial conditions. The frequency spectrum of an output oscillation may contain harmonics and the sums and differences of input frequencies, but it may also contain a stable limit cycle oscillation not related to input frequencies. We must investigate the nonlinear dynamic aspects of advanced life support systems to understand and counter undesirable behavior.

  20. Dynamic model updating based on strain mode shape and natural frequency using hybrid pattern search technique

    Science.gov (United States)

    Guo, Ning; Yang, Zhichun; Wang, Le; Ouyang, Yan; Zhang, Xinping

    2018-05-01

    Aiming at providing a precise dynamic structural finite element (FE) model for dynamic strength evaluation in addition to dynamic analysis. A dynamic FE model updating method is presented to correct the uncertain parameters of the FE model of a structure using strain mode shapes and natural frequencies. The strain mode shape, which is sensitive to local changes in structure, is used instead of the displacement mode for enhancing model updating. The coordinate strain modal assurance criterion is developed to evaluate the correlation level at each coordinate over the experimental and the analytical strain mode shapes. Moreover, the natural frequencies which provide the global information of the structure are used to guarantee the accuracy of modal properties of the global model. Then, the weighted summation of the natural frequency residual and the coordinate strain modal assurance criterion residual is used as the objective function in the proposed dynamic FE model updating procedure. The hybrid genetic/pattern-search optimization algorithm is adopted to perform the dynamic FE model updating procedure. Numerical simulation and model updating experiment for a clamped-clamped beam are performed to validate the feasibility and effectiveness of the present method. The results show that the proposed method can be used to update the uncertain parameters with good robustness. And the updated dynamic FE model of the beam structure, which can correctly predict both the natural frequencies and the local dynamic strains, is reliable for the following dynamic analysis and dynamic strength evaluation.

  1. Stochastic models and reliability parameter estimation applicable to nuclear power plant safety

    International Nuclear Information System (INIS)

    Mitra, S.P.

    1979-01-01

    A set of stochastic models and related estimation schemes for reliability parameters are developed. The models are applicable for evaluating reliability of nuclear power plant systems. Reliability information is extracted from model parameters which are estimated from the type and nature of failure data that is generally available or could be compiled in nuclear power plants. Principally, two aspects of nuclear power plant reliability have been investigated: (1) The statistical treatment of inplant component and system failure data; (2) The analysis and evaluation of common mode failures. The model inputs are failure data which have been classified as either the time type of failure data or the demand type of failure data. Failures of components and systems in nuclear power plant are, in general, rare events.This gives rise to sparse failure data. Estimation schemes for treating sparse data, whenever necessary, have been considered. The following five problems have been studied: 1) Distribution of sparse failure rate component data. 2) Failure rate inference and reliability prediction from time type of failure data. 3) Analyses of demand type of failure data. 4) Common mode failure model applicable to time type of failure data. 5) Estimation of common mode failures from 'near-miss' demand type of failure data

  2. Designing the database for a reliability aware Model-Based System Engineering process

    International Nuclear Information System (INIS)

    Cressent, Robin; David, Pierre; Idasiak, Vincent; Kratz, Frederic

    2013-01-01

    This article outlines the need for a reliability database to implement model-based description of components failure modes and dysfunctional behaviors. We detail the requirements such a database should honor and describe our own solution: the Dysfunctional Behavior Database (DBD). Through the description of its meta-model, the benefits of integrating the DBD in the system design process is highlighted. The main advantages depicted are the possibility to manage feedback knowledge at various granularity and semantic levels and to ease drastically the interactions between system engineering activities and reliability studies. The compliance of the DBD with other reliability database such as FIDES is presented and illustrated. - Highlights: ► Model-Based System Engineering is more and more used in the industry. ► It results in a need for a reliability database able to deal with model-based description of dysfunctional behavior. ► The Dysfunctional Behavior Database aims to fulfill that need. ► It helps dealing with feedback management thanks to its structured meta-model. ► The DBD can profit from other reliability database such as FIDES.

  3. System Dynamics Modeling of Multipurpose Reservoir Operation

    Directory of Open Access Journals (Sweden)

    Ebrahim Momeni

    2006-03-01

    Full Text Available System dynamics, a feedback – based object – oriented simulation approach, not only represents complex dynamic systemic systems in a realistic way but also allows the involvement of end users in model development to increase their confidence in modeling process. The increased speed of model development, the possibility of group model development, the effective communication of model results, and the trust developed in the model due to user participation are the main strengths of this approach. The ease of model modification in response to changes in the system and the ability to perform sensitivity analysis make this approach more attractive compared with systems analysis techniques for modeling water management systems. In this study, a system dynamics model was developed for the Zayandehrud basin in central Iran. This model contains river basin, dam reservoir, plains, irrigation systems, and groundwater. Current operation rule is conjunctive use of ground and surface water. Allocation factor for each irrigation system is computed based on the feedback from groundwater storage in its zone. Deficit water is extracted from groundwater.The results show that applying better rules can not only satisfy all demands such as Gawkhuni swamp environmental demand, but it can also  prevent groundwater level drawdown in future.

  4. Instrumented static and dynamic balance assessment after stroke using Wii Balance Boards: reliability and association with clinical tests.

    Science.gov (United States)

    Bower, Kelly J; McGinley, Jennifer L; Miller, Kimberly J; Clark, Ross A

    2014-01-01

    The Wii Balance Board (WBB) is a globally accessible device that shows promise as a clinically useful balance assessment tool. Although the WBB has been found to be comparable to a laboratory-grade force platform for obtaining centre of pressure data, it has not been comprehensively studied in clinical populations. The aim of this study was to investigate the measurement properties of tests utilising the WBB in people after stroke. Thirty individuals who were more than three months post-stroke and able to stand unsupported were recruited from a single outpatient rehabilitation facility. Participants performed standardised assessments incorporating the WBB and customised software (static stance with eyes open and closed, static weight-bearing asymmetry, dynamic mediolateral weight shifting and dynamic sit-to-stand) in addition to commonly employed clinical tests (10 Metre Walk Test, Timed Up and Go, Step Test and Functional Reach) on two testing occasions one week apart. Test-retest reliability and construct validity of the WBB tests were investigated. All WBB-based outcomes were found to be highly reliable between testing occasions (ICC  = 0.82 to 0.98). Correlations were poor to moderate between WBB variables and clinical tests, with the strongest associations observed between task-related activities, such as WBB mediolateral weight shifting and the Step Test. The WBB, used with customised software, is a reliable and potentially useful tool for the assessment of balance and weight-bearing asymmetry following stroke. Future research is recommended to further investigate validity and responsiveness.

  5. Value-Added Models for Teacher Preparation Programs: Validity and Reliability Threats, and a Manageable Alternative

    Science.gov (United States)

    Brady, Michael P.; Heiser, Lawrence A.; McCormick, Jazarae K.; Forgan, James

    2016-01-01

    High-stakes standardized student assessments are increasingly used in value-added evaluation models to connect teacher performance to P-12 student learning. These assessments are also being used to evaluate teacher preparation programs, despite validity and reliability threats. A more rational model linking student performance to candidates who…

  6. An adaptive neuro fuzzy model for estimating the reliability of component-based software systems

    Directory of Open Access Journals (Sweden)

    Kirti Tyagi

    2014-01-01

    Full Text Available Although many algorithms and techniques have been developed for estimating the reliability of component-based software systems (CBSSs, much more research is needed. Accurate estimation of the reliability of a CBSS is difficult because it depends on two factors: component reliability and glue code reliability. Moreover, reliability is a real-world phenomenon with many associated real-time problems. Soft computing techniques can help to solve problems whose solutions are uncertain or unpredictable. A number of soft computing approaches for estimating CBSS reliability have been proposed. These techniques learn from the past and capture existing patterns in data. The two basic elements of soft computing are neural networks and fuzzy logic. In this paper, we propose a model for estimating CBSS reliability, known as an adaptive neuro fuzzy inference system (ANFIS, that is based on these two basic elements of soft computing, and we compare its performance with that of a plain FIS (fuzzy inference system for different data sets.

  7. Life cycle reliability assessment of new products—A Bayesian model updating approach

    International Nuclear Information System (INIS)

    Peng, Weiwen; Huang, Hong-Zhong; Li, Yanfeng; Zuo, Ming J.; Xie, Min

    2013-01-01

    The rapidly increasing pace and continuously evolving reliability requirements of new products have made life cycle reliability assessment of new products an imperative yet difficult work. While much work has been done to separately estimate reliability of new products in specific stages, a gap exists in carrying out life cycle reliability assessment throughout all life cycle stages. We present a Bayesian model updating approach (BMUA) for life cycle reliability assessment of new products. Novel features of this approach are the development of Bayesian information toolkits by separately including “reliability improvement factor” and “information fusion factor”, which allow the integration of subjective information in a specific life cycle stage and the transition of integrated information between adjacent life cycle stages. They lead to the unique characteristics of the BMUA in which information generated throughout life cycle stages are integrated coherently. To illustrate the approach, an application to the life cycle reliability assessment of a newly developed Gantry Machining Center is shown

  8. Modeling and identification in structural dynamics

    OpenAIRE

    Jayakumar, Paramsothy

    1987-01-01

    Analytical modeling of structures subjected to ground motions is an important aspect of fully dynamic earthquake-resistant design. In general, linear models are only sufficient to represent structural responses resulting from earthquake motions of small amplitudes. However, the response of structures during strong ground motions is highly nonlinear and hysteretic. System identification is an effective tool for developing analytical models from experimental data. Testing of full-scale prot...

  9. Feature Extraction for Structural Dynamics Model Validation

    Energy Technology Data Exchange (ETDEWEB)

    Farrar, Charles [Los Alamos National Laboratory; Nishio, Mayuko [Yokohama University; Hemez, Francois [Los Alamos National Laboratory; Stull, Chris [Los Alamos National Laboratory; Park, Gyuhae [Chonnam Univesity; Cornwell, Phil [Rose-Hulman Institute of Technology; Figueiredo, Eloi [Universidade Lusófona; Luscher, D. J. [Los Alamos National Laboratory; Worden, Keith [University of Sheffield

    2016-01-13

    As structural dynamics becomes increasingly non-modal, stochastic and nonlinear, finite element model-updating technology must adopt the broader notions of model validation and uncertainty quantification. For example, particular re-sampling procedures must be implemented to propagate uncertainty through a forward calculation, and non-modal features must be defined to analyze nonlinear data sets. The latter topic is the focus of this report, but first, some more general comments regarding the concept of model validation will be discussed.

  10. Record Dynamics and the Parking Lot Model for granular dynamics

    Science.gov (United States)

    Sibani, Paolo; Boettcher, Stefan

    Also known for its application to granular compaction (E. Ben-Naim et al., Physica D, 1998), the Parking Lot Model (PLM) describes the random parking of identical cars in a strip with no marked bays. In the thermally activated version considered, cars can be removed at an energy cost and, in thermal equilibrium, their average density increases as temperature decreases. However, equilibration at high density becomes exceedingly slow and the system enters an aging regime induced by a kinematic constraint, the fact that parked cars may not overlap. As parking an extra car reduces the available free space,the next parking event is even harder to achieve. Records in the number of parked cars mark the salient features of the dynamics and are shown to be well described by the log-Poisson statistics known from other glassy systems with record dynamics. Clusters of cars whose positions must be rearranged to make the next insertion possible have a length scale which grows logarithmically with age, while their life-time grows exponentially with size. The implications for a recent cluster model of colloidal dynamics,(S. Boettcher and P. Sibani, J. Phys.: Cond. Matter, 2011 N. Becker et al., J. Phys.: Cond. Matter, 2014) are discussed. Support rom the Villum Foundation is gratefully acknowledged.

  11. Proof-of-Concept Demonstrations for Computation-Based Human Reliability Analysis. Modeling Operator Performance During Flooding Scenarios

    International Nuclear Information System (INIS)

    Joe, Jeffrey Clark; Boring, Ronald Laurids; Herberger, Sarah Elizabeth Marie; Mandelli, Diego; Smith, Curtis Lee

    2015-01-01

    The United States (U.S.) Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) program has the overall objective to help sustain the existing commercial nuclear power plants (NPPs). To accomplish this program objective, there are multiple LWRS 'pathways,' or research and development (R&D) focus areas. One LWRS focus area is called the Risk-Informed Safety Margin and Characterization (RISMC) pathway. Initial efforts under this pathway to combine probabilistic and plant multi-physics models to quantify safety margins and support business decisions also included HRA, but in a somewhat simplified manner. HRA experts at Idaho National Laboratory (INL) have been collaborating with other experts to develop a computational HRA approach, called the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER), for inclusion into the RISMC framework. The basic premise of this research is to leverage applicable computational techniques, namely simulation and modeling, to develop and then, using RAVEN as a controller, seamlessly integrate virtual operator models (HUNTER) with 1) the dynamic computational MOOSE runtime environment that includes a full-scope plant model, and 2) the RISMC framework PRA models already in use. The HUNTER computational HRA approach is a hybrid approach that leverages past work from cognitive psychology, human performance modeling, and HRA, but it is also a significant departure from existing static and even dynamic HRA methods. This report is divided into five chapters that cover the development of an external flooding event test case and associated statistical modeling considerations.

  12. Proof-of-Concept Demonstrations for Computation-Based Human Reliability Analysis. Modeling Operator Performance During Flooding Scenarios

    Energy Technology Data Exchange (ETDEWEB)

    Joe, Jeffrey Clark [Idaho National Lab. (INL), Idaho Falls, ID (United States); Boring, Ronald Laurids [Idaho National Lab. (INL), Idaho Falls, ID (United States); Herberger, Sarah Elizabeth Marie [Idaho National Lab. (INL), Idaho Falls, ID (United States); Mandelli, Diego [Idaho National Lab. (INL), Idaho Falls, ID (United States); Smith, Curtis Lee [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2015-09-01

    The United States (U.S.) Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) program has the overall objective to help sustain the existing commercial nuclear power plants (NPPs). To accomplish this program objective, there are multiple LWRS “pathways,” or research and development (R&D) focus areas. One LWRS focus area is called the Risk-Informed Safety Margin and Characterization (RISMC) pathway. Initial efforts under this pathway to combine probabilistic and plant multi-physics models to quantify safety margins and support business decisions also included HRA, but in a somewhat simplified manner. HRA experts at Idaho National Laboratory (INL) have been collaborating with other experts to develop a computational HRA approach, called the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER), for inclusion into the RISMC framework. The basic premise of this research is to leverage applicable computational techniques, namely simulation and modeling, to develop and then, using RAVEN as a controller, seamlessly integrate virtual operator models (HUNTER) with 1) the dynamic computational MOOSE runtime environment that includes a full-scope plant model, and 2) the RISMC framework PRA models already in use. The HUNTER computational HRA approach is a hybrid approach that leverages past work from cognitive psychology, human performance modeling, and HRA, but it is also a significant departure from existing static and even dynamic HRA methods. This report is divided into five chapters that cover the development of an external flooding event test case and associated statistical modeling considerations.

  13. Dynamic control of the lumbopelvic complex; lack of reliability of established test procedures

    DEFF Research Database (Denmark)

    Henriksen, Marius; Lund, Hans; Bliddal, Henning

    2007-01-01

    used in order to account for learning effects. Intraclass correlation coefficients were low for the sitting (0.54) and supported standing positions (0.36). In the standing position, a significant difference between test and retest was observed (P = 0.003) and further reliability analysis was therefore...

  14. Modeling the dynamics of dissent

    Science.gov (United States)

    Lee, Eun; Holme, Petter; Lee, Sang Hoon

    2017-11-01

    We investigate the formation of opinion against authority in an authoritarian society composed of agents with different levels of authority. We explore a ;dissenting; opinion, held by lower-ranking, obedient, or less authoritative people, spreading in an environment of an ;affirmative; opinion held by authoritative leaders. A real-world example would be a corrupt society where people revolt against such leaders, but it can be applied to more general situations. In our model, agents can change their opinion depending on their authority relative to their neighbors and their own confidence level. In addition, with a certain probability, agents can override the affirmative opinion to take the dissenting opinion of a neighbor. Based on analytic derivation and numerical simulations, we observe that both the network structure and heterogeneity in authority, and their correlation, significantly affect the possibility of the dissenting opinion to spread through the population. In particular, the dissenting opinion is suppressed when the authority distribution is very heterogeneous and there exists a positive correlation between the authority and the number of neighbors of people (degree). Except for such an extreme case, though, spreading of the dissenting opinion takes place when people have the tendency to override the authority to hold the dissenting opinion, but the dissenting opinion can take a long time to spread to the entire society, depending on the model parameters. We argue that the internal social structure of agents sets the scale of the time to reach consensus, based on the analysis of the underlying structural properties of opinion spreading.

  15. Modeling Dynamic Regulatory Processes in Stroke

    Science.gov (United States)

    McDermott, Jason E.; Jarman, Kenneth; Taylor, Ronald; Lancaster, Mary; Shankaran, Harish; Vartanian, Keri B.; Stevens, Susan L.; Stenzel-Poore, Mary P.; Sanfilippo, Antonio

    2012-01-01

    The ability to examine the behavior of biological systems in silico has the potential to greatly accelerate the pace of discovery in diseases, such as stroke, where in vivo analysis is time intensive and costly. In this paper we describe an approach for in silico examination of responses of the blood transcriptome to neuroprotective agents and subsequent stroke through the development of dynamic models of the regulatory processes observed in the experimental gene expression data. First, we identified functional gene clusters from these data. Next, we derived ordinary differential equations (ODEs) from the data relating these functional clusters to each other in terms of their regulatory influence on one another. Dynamic models were developed by coupling these ODEs into a model that simulates the expression of regulated functional clusters. By changing the magnitude of gene expression in the initial input state it was possible to assess the behavior of the networks through time under varying conditions since the dynamic model only requires an initial starting state, and does not require measurement of regulatory influences at each time point in order to make accurate predictions. We discuss the implications of our models on neuroprotection in stroke, explore the limitations of the approach, and report that an optimized dynamic model can provide accurate predictions of overall system behavior under several different neuroprotective paradigms. PMID:23071432

  16. Business Cases for Microgrids: Modeling Interactions of Technology Choice, Reliability, Cost, and Benefit

    Science.gov (United States)

    Hanna, Ryan

    Distributed energy resources (DERs), and increasingly microgrids, are becoming an integral part of modern distribution systems. Interest in microgrids--which are insular and autonomous power networks embedded within the bulk grid--stems largely from the vast array of flexibilities and benefits they can offer stakeholders. Managed well, they can improve grid reliability and resiliency, increase end-use energy efficiency by coupling electric and thermal loads, reduce transmission losses by generating power locally, and may reduce system-wide emissions, among many others. Whether these public benefits are realized, however, depends on whether private firms see a "business case", or private value, in investing. To this end, firms need models that evaluate costs, benefits, risks, and assumptions that underlie decisions to invest. The objectives of this dissertation are to assess the business case for microgrids that provide what industry analysts forecast as two primary drivers of market growth--that of providing energy services (similar to an electric utility) as well as reliability service to customers within. Prototypical first adopters are modeled--using an existing model to analyze energy services and a new model that couples that analysis with one of reliability--to explore interactions between technology choice, reliability, costs, and benefits. The new model has a bi-level hierarchy; it uses heuristic optimization to select and size DERs and analytical optimization to schedule them. It further embeds Monte Carlo simulation to evaluate reliability as well as regression models for customer damage functions to monetize reliability. It provides least-cost microgrid configurations for utility customers who seek to reduce interruption and operating costs. Lastly, the model is used to explore the impact of such adoption on system-wide greenhouse gas emissions in California. Results indicate that there are, at present, co-benefits for emissions reductions when customers

  17. Coupling population dynamics with earth system models: the POPEM model.

    Science.gov (United States)

    Navarro, Andrés; Moreno, Raúl; Jiménez-Alcázar, Alfonso; Tapiador, Francisco J

    2017-09-16

    Precise modeling of CO 2 emissions is important for environmental research. This paper presents a new model of human population dynamics that can be embedded into ESMs (Earth System Models) to improve climate modeling. Through a system dynamics approach, we develop a cohort-component model that successfully simulates historical population dynamics with fine spatial resolution (about 1°×1°). The population projections are used to improve the estimates of CO 2 emissions, thus transcending the bulk approach of existing models and allowing more realistic non-linear effects to feature in the simulations. The module, dubbed POPEM (from Population Parameterization for Earth Models), is compared with current emission inventories and validated against UN aggregated data. Finally, it is shown that the module can be used to advance toward fully coupling the social and natural components of the Earth system, an emerging research path for environmental science and pollution research.

  18. Reliability Measure Model for Assistive Care Loop Framework Using Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Venki Balasubramanian

    2010-01-01

    Full Text Available Body area wireless sensor networks (BAWSNs are time-critical systems that rely on the collective data of a group of sensor nodes. Reliable data received at the sink is based on the collective data provided by all the source sensor nodes and not on individual data. Unlike conventional reliability, the definition of retransmission is inapplicable in a BAWSN and would only lead to an elapsed data arrival that is not acceptable for time-critical application. Time-driven applications require high data reliability to maintain detection and responses. Hence, the transmission reliability for the BAWSN should be based on the critical time. In this paper, we develop a theoretical model to measure a BAWSN's transmission reliability, based on the critical time. The proposed model is evaluated through simulation and then compared with the experimental results conducted in our existing Active Care Loop Framework (ACLF. We further show the effect of the sink buffer in transmission reliability after a detailed study of various other co-existing parameters.

  19. Reliability modeling of digital RPS with consideration of undetected software faults

    Energy Technology Data Exchange (ETDEWEB)

    Khalaquzzaman, M.; Lee, Seung Jun; Jung, Won Dea [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Kim, Man Cheol [Chung Ang Univ., Seoul (Korea, Republic of)

    2013-10-15

    This paper provides overview of different software reliability methodologies and proposes a technic for estimating the reliability of RPS with consideration of undetected software faults. Software reliability analysis of safety critical software has been challenging despite spending a huge effort for developing large number of software reliability models, and no consensus yet to attain on an appropriate modeling methodology. However, it is realized that the combined application of BBN based SDLC fault prediction method and random black-box testing of software would provide better ground for reliability estimation of safety critical software. Digitalizing the reactor protection system of nuclear power plant has been initiated several decades ago and now full digitalization has been adopted in the new generation of NPPs around the world because digital I and C systems have many better technical features like easier configurability and maintainability over analog I and C systems. Digital I and C systems are also drift-free and incorporation of new features is much easier. Rules and regulation for safe operation of NPPs are established and has been being practiced by the operators as well as regulators of NPPs to ensure safety. The failure mechanism of hardware and analog systems well understood and the risk analysis methods for these components and systems are well established. However, digitalization of I and C system in NPP introduces some crisis and uncertainty in reliability analysis methods of the digital systems/components because software failure mechanisms are still unclear.

  20. Dynamical properties of the Rabi model

    International Nuclear Information System (INIS)

    Hu, Binglu; Zhou, Huili; Chen, Shujie; Xianlong, Gao; Wang, Kelin

    2017-01-01

    We study the dynamical properties of the quantum Rabi model using a systematic expansion method. Based on the observation that the parity symmetry of the Rabi model is kept during evolution of the states, we decompose the initial state and the time-dependent one into positive and negative parity parts expanded by superposition of the coherent states. The evolutions of the corresponding positive and the negative parities are obtained, in which the expansion coefficients in the dynamical equations are known from the derived recurrence relation. (paper)

  1. A multi-state reliability evaluation model for P2P networks

    International Nuclear Information System (INIS)

    Fan Hehong; Sun Xiaohan

    2010-01-01

    The appearance of new service types and the convergence tendency of the communication networks have endowed the networks more and more P2P (peer to peer) properties. These networks can be more robust and tolerant for a series of non-perfect operational states due to the non-deterministic server-client distributions. Thus a reliability model taking into account of the multi-state and non-deterministic server-client distribution properties is needed for appropriate evaluation of the networks. In this paper, two new performance measures are defined to quantify the overall and local states of the networks. A new time-evolving state-transition Monte Carlo (TEST-MC) simulation model is presented for the reliability analysis of P2P networks in multiple states. The results show that the model is not only valid for estimating the traditional binary-state network reliability parameters, but also adequate for acquiring the parameters in a series of non-perfect operational states, with good efficiencies, especially for highly reliable networks. Furthermore, the model is versatile for the reliability and maintainability analyses in that both the links and the nodes can be failure-prone with arbitrary life distributions, and various maintainability schemes can be applied.

  2. Modelling of nuclear power plant control and instrumentation elements for automatic disturbance and reliability analysis

    International Nuclear Information System (INIS)

    Hollo, E.

    1985-08-01

    Present Final Report summarizes results of R/D work done within IAEA-VEIKI (Institute for Electrical Power Research, Budapest, Hungary) Research Contract No. 3210 during 3 years' period of 01.08.1982 - 31.08.1985. Chapter 1 lists main research objectives of the project. Main results obtained are summarized in Chapters 2 and 3. Outcomes from development of failure modelling methodologies and their application for C/I components of WWER-440 units are as follows (Chapter 2): improvement of available ''failure mode and effect analysis'' methods and mini-fault tree structures usable for automatic disturbance (DAS) and reliability (RAS) analysis; general classification and determination of functional failure modes of WWER-440 NPP C/I components; set up of logic models for motor operated control valves and rod control/drive mechanism. Results of development of methods and their application for reliability modelling of NPP components and systems cover (Chapter 3): development of an algorithm (computer code COMPREL) for component-related failure and reliability parameter calculation; reliability analysis of PAKS II NPP diesel system; definition of functional requirements for reliability data bank (RDB) in WWER-440 units. Determination of RDB input/output data structure and data manipulation services. Methods used are a-priori failure mode and effect analysis, combined fault tree/event tree modelling technique, structural computer programming, probability theory application to nuclear field

  3. Modeling Optimal Scheduling for Pumping System to Minimize Operation Cost and Enhance Operation Reliability

    Directory of Open Access Journals (Sweden)

    Yin Luo

    2012-01-01

    Full Text Available Traditional pump scheduling models neglect the operation reliability which directly relates with the unscheduled maintenance cost and the wear cost during the operation. Just for this, based on the assumption that the vibration directly relates with the operation reliability and the degree of wear, it could express the operation reliability as the normalization of the vibration level. The characteristic of the vibration with the operation point was studied, it could be concluded that idealized flow versus vibration plot should be a distinct bathtub shape. There is a narrow sweet spot (80 to 100 percent BEP to obtain low vibration levels in this shape, and the vibration also follows similar law with the square of the rotation speed without resonance phenomena. Then, the operation reliability could be modeled as the function of the capacity and rotation speed of the pump and add this function to the traditional model to form the new. And contrast with the tradition method, the result shown that the new model could fix the result produced by the traditional, make the pump operate in low vibration, then the operation reliability could increase and the maintenance cost could decrease.

  4. Reliability Analysis of Sealing Structure of Electromechanical System Based on Kriging Model

    Science.gov (United States)

    Zhang, F.; Wang, Y. M.; Chen, R. W.; Deng, W. W.; Gao, Y.

    2018-05-01

    The sealing performance of aircraft electromechanical system has a great influence on flight safety, and the reliability of its typical seal structure is analyzed by researcher. In this paper, we regard reciprocating seal structure as a research object to study structural reliability. Having been based on the finite element numerical simulation method, the contact stress between the rubber sealing ring and the cylinder wall is calculated, and the relationship between the contact stress and the pressure of the hydraulic medium is built, and the friction force on different working conditions are compared. Through the co-simulation, the adaptive Kriging model obtained by EFF learning mechanism is used to describe the failure probability of the seal ring, so as to evaluate the reliability of the sealing structure. This article proposes a new idea of numerical evaluation for the reliability analysis of sealing structure, and also provides a theoretical basis for the optimal design of sealing structure.

  5. Dynamic Equivalent Modeling of a Grid-Tied Microgrid Based on Characteristic Model and Measurement Data

    Directory of Open Access Journals (Sweden)

    Changchun Cai

    2017-11-01

    Full Text Available Microgrids can significantly improve the utilization of distributed generation (DG and the reliability of the power supply. However, in the grid-tied operational mode, the interaction between the microgrid and the distribution network cannot be ignored. The paper proposes an equivalent modeling method for the microgrid under grid-tied mode based on a characteristic model. It can simplify the microgrid model in the numerical simulation of the distribution network. The proposed equivalent model can present the dynamic response of a microgrid but not miss any of its primary characteristics. The characteristic model is represented by a low-order time-varying differential equation with the same characteristics of the original microgrid system. During the modeling process, the voltage and the power exchanged between the microgrid and distribution network are collected as the training data for the identification of model parameters. A recursive damped least squares algorithm (RDLS is used for the parameter identification. A microgrid system containing different DGs is built to test the proposed modeling method in DIgSILENT, and the results show that the proposed dynamic equivalent modeling method is effective and the characteristic model can present the dynamic behaviors of the detailed model of a microgrid.

  6. [Reliability study in the measurement of the cusp inclination angle of a chairside digital model].

    Science.gov (United States)

    Xinggang, Liu; Xiaoxian, Chen

    2018-02-01

    This study aims to evaluate the reliability of the software Picpick in the measurement of the cusp inclination angle of a digital model. Twenty-one trimmed models were used as experimental objects. The chairside digital impression was then used for the acquisition of 3D digital models, and the software Picpick was employed for the measurement of the cusp inclination of these models. The measurements were repeated three times, and the results were compared with a gold standard, which was a manually measured experimental model cusp angle. The intraclass correlation coefficient (ICC) was calculated. The paired t test value of the two measurement methods was 0.91. The ICCs between the two measurement methods and three repeated measurements were greater than 0.9. The digital model achieved a smaller coefficient of variation (9.9%). The software Picpick is reliable in measuring the cusp inclination of a digital model.

  7. Bayesian Hierarchical Scale Mixtures of Log-Normal Models for Inference in Reliability with Stochastic Constraint

    Directory of Open Access Journals (Sweden)

    Hea-Jung Kim

    2017-06-01

    Full Text Available This paper develops Bayesian inference in reliability of a class of scale mixtures of log-normal failure time (SMLNFT models with stochastic (or uncertain constraint in their reliability measures. The class is comprehensive and includes existing failure time (FT models (such as log-normal, log-Cauchy, and log-logistic FT models as well as new models that are robust in terms of heavy-tailed FT observations. Since classical frequency approaches to reliability analysis based on the SMLNFT model with stochastic constraint are intractable, the Bayesian method is pursued utilizing a Markov chain Monte Carlo (MCMC sampling based approach. This paper introduces a two-stage maximum entropy (MaxEnt prior, which elicits a priori uncertain constraint and develops Bayesian hierarchical SMLNFT model by using the prior. The paper also proposes an MCMC method for Bayesian inference in the SMLNFT model reliability and calls attention to properties of the MaxEnt prior that are useful for method development. Finally, two data sets are used to illustrate how the proposed methodology works.

  8. Reliability modeling of degradation of products with multiple performance characteristics based on gamma processes

    International Nuclear Information System (INIS)

    Pan Zhengqiang; Balakrishnan, Narayanaswamy

    2011-01-01

    Many highly reliable products usually have complex structure, with their reliability being evaluated by two or more performance characteristics. In certain physical situations, the degradation of these performance characteristics would be always positive and strictly increasing. In such a case, the gamma process is usually considered as a degradation process due to its independent and non-negative increments properties. In this paper, we suppose that a product has two dependent performance characteristics and that their degradation can be modeled by gamma processes. For such a bivariate degradation involving two performance characteristics, we propose to use a bivariate Birnbaum-Saunders distribution and its marginal distributions to approximate the reliability function. Inferential method for the corresponding model parameters is then developed. Finally, for an illustration of the proposed model and method, a numerical example about fatigue cracks is discussed and some computational results are presented.

  9. Inter-arch digital model vs. manual cast measurements: Accuracy and reliability.

    Science.gov (United States)

    Kiviahde, Heikki; Bukovac, Lea; Jussila, Päivi; Pesonen, Paula; Sipilä, Kirsi; Raustia, Aune; Pirttiniemi, Pertti

    2017-06-28

    The purpose of this study was to evaluate the accuracy and reliability of inter-arch measurements using digital dental models and conventional dental casts. Thirty sets of dental casts with permanent dentition were examined. Manual measurements were done with a digital caliper directly on the dental casts, and digital measurements were made on 3D models by two independent examiners. Intra-class correlation coefficients (ICC), a paired sample t-test or Wilcoxon signed-rank test, and Bland-Altman plots were used to evaluate intra- and inter-examiner error and to determine the accuracy and reliability of the measurements. The ICC values were generally good for manual and excellent for digital measurements. The Bland-Altman plots of all the measurements showed good agreement between the manual and digital methods and excellent inter-examiner agreement using the digital method. Inter-arch occlusal measurements on digital models are accurate and reliable and are superior to manual measurements.

  10. Comparative analysis among deterministic and stochastic collision damage models for oil tanker and bulk carrier reliability

    Directory of Open Access Journals (Sweden)

    A. Campanile

    2018-01-01

    Full Text Available The incidence of collision damage models on oil tanker and bulk carrier reliability is investigated considering the IACS deterministic model against GOALDS/IMO database statistics for collision events, substantiating the probabilistic model. Statistical properties of hull girder residual strength are determined by Monte Carlo simulation, based on random generation of damage dimensions and a modified form of incremental-iterative method, to account for neutral axis rotation and equilibrium of horizontal bending moment, due to cross-section asymmetry after collision events. Reliability analysis is performed, to investigate the incidence of collision penetration depth and height statistical properties on hull girder sagging/hogging failure probabilities. Besides, the incidence of corrosion on hull girder residual strength and reliability is also discussed, focussing on gross, hull girder net and local net scantlings, respectively. The ISSC double hull oil tanker and single side bulk carrier, assumed as test cases in the ISSC 2012 report, are taken as reference ships.

  11. Dynamic Modeling of ThermoFluid Systems

    DEFF Research Database (Denmark)

    Jensen, Jakob Munch

    2003-01-01

    The objective of the present study has been to developed dynamic models for two-phase flow in pipes (evaporation and condensation). Special attention has been given to modeling evaporators for refrigeration plant particular dry-expansion evaporators. Models of different complexity have been...... formulated. The different models deviate with respect to the detail¿s included and calculation time in connection with simulation. The models have been implemented in a new library named ThermoTwoPhase to the programming language Modelica. A test rig has been built with an evaporator instrumented in a way...

  12. Research on nonlinear stochastic dynamical price model

    International Nuclear Information System (INIS)

    Li Jiaorui; Xu Wei; Xie Wenxian; Ren Zhengzheng

    2008-01-01

    In consideration of many uncertain factors existing in economic system, nonlinear stochastic dynamical price model which is subjected to Gaussian white noise excitation is proposed based on deterministic model. One-dimensional averaged Ito stochastic differential equation for the model is derived by using the stochastic averaging method, and applied to investigate the stability of the trivial solution and the first-passage failure of the stochastic price model. The stochastic price model and the methods presented in this paper are verified by numerical studies

  13. Modelling environmental dynamics. Advances in goematic solutions

    Energy Technology Data Exchange (ETDEWEB)

    Paegelow, Martin [Toulouse-2 Univ., 31 (France). GEODE UMR 5602 CNRS; Camacho Olmedo, Maria Teresa (eds.) [Granada Univ (Spain). Dpto. de Analisis Geografico Regional y Geografia Fisica

    2008-07-01

    Modelling environmental dynamics is critical to understanding and predicting the evolution of the environment in response to the large number of influences including urbanisation, climate change and deforestation. Simulation and modelling provide support for decision making in environmental management. The first chapter introduces terminology and provides an overview of methodological modelling approaches which may be applied to environmental and complex dynamics. Based on this introduction this book illustrates various models applied to a large variety of themes: deforestation in tropical regions, fire risk, natural reforestation in European mountains, agriculture, biodiversity, urbanism, climate change and land management for decision support, etc. These case studies, provided by a large international spectrum of researchers and presented in a uniform structure, focus particularly on methods and model validation so that this book is not only aimed at researchers and graduates but also at professionals. (orig.)

  14. Modeling emotional dynamics : currency versus field.

    Energy Technology Data Exchange (ETDEWEB)

    Sallach, D .L.; Decision and Information Sciences; Univ. of Chicago

    2008-08-01

    Randall Collins has introduced a simplified model of emotional dynamics in which emotional energy, heightened and focused by interaction rituals, serves as a common denominator for social exchange: a generic form of currency, except that it is active in a far broader range of social transactions. While the scope of this theory is attractive, the specifics of the model remain unconvincing. After a critical assessment of the currency theory of emotion, a field model of emotion is introduced that adds expressiveness by locating emotional valence within its cognitive context, thereby creating an integrated orientation field. The result is a model which claims less in the way of motivational specificity, but is more satisfactory in modeling the dynamic interaction between cognitive and emotional orientations at both individual and social levels.

  15. Modeling initial contact dynamics during ambulation with dynamic simulation.

    Science.gov (United States)

    Meyer, Andrew R; Wang, Mei; Smith, Peter A; Harris, Gerald F

    2007-04-01

    Ankle-foot orthoses are frequently used interventions to correct pathological gait. Their effects on the kinematics and kinetics of the proximal joints are of great interest when prescribing ankle-foot orthoses to specific patient groups. Mathematical Dynamic Model (MADYMO) is developed to simulate motor vehicle crash situations and analyze tissue injuries of the occupants based multibody dynamic theories. Joint kinetics output from an inverse model were perturbed and input to the forward model to examine the effects of changes in the internal sagittal ankle moment on knee and hip kinematics following heel strike. Increasing the internal ankle moment (augmentation, equivalent to gastroc-soleus contraction) produced less pronounced changes in kinematic results at the hip, knee and ankle than decreasing the moment (attenuation, equivalent to gastroc-soleus relaxation). Altering the internal ankle moment produced two distinctly different kinematic curve morphologies at the hip. Decreased internal ankle moments increased hip flexion, peaking at roughly 8% of the gait cycle. Increasing internal ankle moments decreased hip flexion to a lesser degree, and approached normal at the same point in the gait cycle. Increasing the internal ankle moment produced relatively small, well-behaved extension-biased kinematic results at the knee. Decreasing the internal ankle moment produced more substantial changes in knee kinematics towards flexion that increased with perturbation magnitude. Curve morphologies were similar to those at the hip. Immediately following heel strike, kinematic results at the ankle showed movement in the direction of the internal moment perturbation. Increased internal moments resulted in kinematic patterns that rapidly approach normal after initial differences. When the internal ankle moment was decreased, differences from normal were much greater and did not rapidly decrease. This study shows that MADYMO can be successfully applied to accomplish forward

  16. A depth semi-averaged model for coastal dynamics

    Science.gov (United States)

    Antuono, M.; Colicchio, G.; Lugni, C.; Greco, M.; Brocchini, M.

    2017-05-01

    The present work extends the semi-integrated method proposed by Antuono and Brocchini ["Beyond Boussinesq-type equations: Semi-integrated models for coastal dynamics," Phys. Fluids 25(1), 016603 (2013)], which comprises a subset of depth-averaged equations (similar to Boussinesq-like models) and a Poisson equation that accounts for vertical dynamics. Here, the subset of depth-averaged equations has been reshaped in a conservative-like form and both the Poisson equation formulations proposed by Antuono and Brocchini ["Beyond Boussinesq-type equations: Semi-integrated models for coastal dynamics," Phys. Fluids 25(1), 016603 (2013)] are investigated: the former uses the vertical velocity component (formulation A) and the latter a specific depth semi-averaged variable, ϒ (formulation B). Our analyses reveal that formulation A is prone to instabilities as wave nonlinearity increases. On the contrary, formulation B allows an accurate, robust numerical implementation. Test cases derived from the scientific literature on Boussinesq-type models—i.e., solitary and Stokes wave analytical solutions for linear dispersion and nonlinear evolution and experimental data for shoaling properties—are used to assess the proposed solution strategy. It is found that the present method gives reliable predictions of wave propagation in shallow to intermediate waters, in terms of both semi-averaged variables and conservation properties.

  17. ARA and ARI imperfect repair models: Estimation, goodness-of-fit and reliability prediction

    International Nuclear Information System (INIS)

    Toledo, Maria Luíza Guerra de; Freitas, Marta A.; Colosimo, Enrico A.; Gilardoni, Gustavo L.

    2015-01-01

    An appropriate maintenance policy is essential to reduce expenses and risks related to equipment failures. A fundamental aspect to be considered when specifying such policies is to be able to predict the reliability of the systems under study, based on a well fitted model. In this paper, the classes of models Arithmetic Reduction of Age and Arithmetic Reduction of Intensity are explored. Likelihood functions for such models are derived, and a graphical method is proposed for model selection. A real data set involving failures in trucks used by a Brazilian mining is analyzed considering models with different memories. Parameters, namely, shape and scale for Power Law Process, and the efficiency of repair were estimated for the best fitted model. Estimation of model parameters allowed us to derive reliability estimators to predict the behavior of the failure process. These results are a valuable information for the mining company and can be used to support decision making regarding preventive maintenance policy. - Highlights: • Likelihood functions for imperfect repair models are derived. • A goodness-of-fit technique is proposed as a tool for model selection. • Failures in trucks owned by a Brazilian mining are modeled. • Estimation allowed deriving reliability predictors to forecast the future failure process of the trucks

  18. An overview of erosion corrosion models and reliability assessment for corrosion defects in piping system

    International Nuclear Information System (INIS)

    Srividya, A.; Suresh, H.N.; Verma, A.K.; Gopika, V.; Santosh

    2006-01-01

    Piping systems are part of passive structural elements in power plants. The analysis of the piping systems and their quantification in terms of failure probability is of utmost importance. The piping systems may fail due to various degradation mechanisms like thermal fatigue, erosion-corrosion, stress corrosion cracking and vibration fatigue. On examination of previous results, erosion corrosion was more prevalent and wall thinning is a time dependent phenomenon. The paper is intended to consolidate the work done by various investigators on erosion corrosion in estimating the erosion corrosion rate and reliability predictions. A comparison of various erosion corrosion models is made. The reliability predictions based on remaining strength of corroded pipelines by wall thinning is also attempted. Variables in the limit state functions are modelled using normal distributions and Reliability assessment is carried out using some of the existing failure pressure models. A steady state corrosion rate is assumed to estimate the corrosion defect and First Order Reliability Method (FORM) is used to find the probability of failure associated with corrosion defects over time using the software for Component Reliability evaluation (COMREL). (author)

  19. Efficient surrogate models for reliability analysis of systems with multiple failure modes

    International Nuclear Information System (INIS)

    Bichon, Barron J.; McFarland, John M.; Mahadevan, Sankaran

    2011-01-01

    Despite many advances in the field of computational reliability analysis, the efficient estimation of the reliability of a system with multiple failure modes remains a persistent challenge. Various sampling and analytical methods are available, but they typically require accepting a tradeoff between accuracy and computational efficiency. In this work, a surrogate-based approach is presented that simultaneously addresses the issues of accuracy, efficiency, and unimportant failure modes. The method is based on the creation of Gaussian process surrogate models that are required to be locally accurate only in the regions of the component limit states that contribute to system failure. This approach to constructing surrogate models is demonstrated to be both an efficient and accurate method for system-level reliability analysis. - Highlights: → Extends efficient global reliability analysis to systems with multiple failure modes. → Constructs locally accurate Gaussian process models of each response. → Highly efficient and accurate method for assessing system reliability. → Effectiveness is demonstrated on several test problems from the literature.

  20. A Stochastic Model for Malaria Transmission Dynamics

    Directory of Open Access Journals (Sweden)

    Rachel Waema Mbogo

    2018-01-01

    Full Text Available Malaria is one of the three most dangerous infectious diseases worldwide (along with HIV/AIDS and tuberculosis. In this paper we compare the disease dynamics of the deterministic and stochastic models in order to determine the effect of randomness in malaria transmission dynamics. Relationships between the basic reproduction number for malaria transmission dynamics between humans and mosquitoes and the extinction thresholds of corresponding continuous-time Markov chain models are derived under certain assumptions. The stochastic model is formulated using the continuous-time discrete state Galton-Watson branching process (CTDSGWbp. The reproduction number of deterministic models is an essential quantity to predict whether an epidemic will spread or die out. Thresholds for disease extinction from stochastic models contribute crucial knowledge on disease control and elimination and mitigation of infectious diseases. Analytical and numerical results show some significant differences in model predictions between the stochastic and deterministic models. In particular, we find that malaria outbreak is more likely if the disease is introduced by infected mosquitoes as opposed to infected humans. These insights demonstrate the importance of a policy or intervention focusing on controlling the infected mosquito population if the control of malaria is to be realized.

  1. Modeling biological pathway dynamics with timed automata.

    Science.gov (United States)

    Schivo, Stefano; Scholma, Jetse; Wanders, Brend; Urquidi Camacho, Ricardo A; van der Vet, Paul E; Karperien, Marcel; Langerak, Rom; van de Pol, Jaco; Post, Janine N

    2014-05-01

    Living cells are constantly subjected to a plethora of environmental stimuli that require integration into an appropriate cellular response. This integration takes place through signal transduction events that form tightly interconnected networks. The understanding of these networks requires capturing their dynamics through computational support and models. ANIMO (analysis of Networks with Interactive Modeling) is a tool that enables the construction and exploration of executable models of biological networks, helping to derive hypotheses and to plan wet-lab experiments. The tool is based on the formalism of Timed Automata, which can be analyzed via the UPPAAL model checker. Thanks to Timed Automata, we can provide a formal semantics for the domain-specific language used to represent signaling networks. This enforces precision and uniformity in the definition of signaling pathways, contributing to the integration of isolated signaling events into complex network models. We propose an approach to discretization of reaction kinetics that allows us to efficiently use UPPAAL as the computational engine to explore the dynamic behavior of the network of interest. A user-friendly interface hides the use of Timed Automata from the user, while keeping the expressive power intact. Abstraction to single-parameter kinetics speeds up construction of models that remain faithful enough to provide meaningful insight. The resulting dynamic behavior of the network components is displayed graphically, allowing for an intuitive and interactive modeling experience.

  2. Validity and Reliability of Dynamic Visual Acuity (DVA) Measurement During Walking

    Science.gov (United States)

    Deshpande, Nandini; Peters, Brian T.; Bloomberg, Jacob J.

    2014-01-01

    DVA is primarily subserved by the vestibulo-ocular reflex mechanism. Individuals with vestibular hypofunction commonly experience highly debilitating illusory movement or blurring of visual images during daily activities possibly, due to impaired DVA. Even without pathologies, gradual age-related morphological deterioration is evident in all components of the vestibular system. We examined the construct validity to detect age-related differences and test-retest reliability of DVA measurements performed during walking. METHODS: Healthy adults were recruited into 3 groups: 1. young (20-39years, n=18), 2. middle-aged (40-59years, n=14), and 3. older adults (60-80years, n=15). Randomly selected seven participants from each group (n=21) participated in retesting. Participants were excluded if they had a history of vestibular or neuromuscular pathologies, dizziness/vertigo or >1 falls in the past year. Older persons with MMSE scores reliability. RESULTS: The three age groups were not different in their height, weight and normal walking speed (p>0.05). The post hoc analyses for DVA measurements demonstrated that each group was significantly different from the other two groups for Near as well as FarDVA (preliability. FarDVA at 0.8 m/s and 1.0 m/s demonstrated good test-retest reliability (ICCs 0.71 and 0.77, respectively).

  3. Intra-observer reliability and agreement of manual and digital orthodontic model analysis.

    Science.gov (United States)

    Koretsi, Vasiliki; Tingelhoff, Linda; Proff, Peter; Kirschneck, Christian

    2018-01-23

    Digital orthodontic model analysis is gaining acceptance in orthodontics, but its reliability is dependent on the digitalisation hardware and software used. We thus investigated intra-observer reliability and agreement / conformity of a particular digital model analysis work-flow in relation to traditional manual plaster model analysis. Forty-eight plaster casts of the upper/lower dentition were collected. Virtual models were obtained with orthoX®scan (Dentaurum) and analysed with ivoris®analyze3D (Computer konkret). Manual model analyses were done with a dial caliper (0.1 mm). Common parameters were measured on each plaster cast and its virtual counterpart five times each by an experienced observer. We assessed intra-observer reliability within method (ICC), agreement/conformity between methods (Bland-Altman analyses and Lin's concordance correlation), and changing bias (regression analyses). Intra-observer reliability was substantial within each method (ICC ≥ 0.7), except for five manual outcomes (12.8 per cent). Bias between methods was statistically significant, but less than 0.5 mm for 87.2 per cent of the outcomes. In general, larger tooth sizes were measured digitally. Total difference maxilla and mandible had wide limits of agreement (-3.25/6.15 and -2.31/4.57 mm), but bias between methods was mostly smaller than intra-observer variation within each method with substantial conformity of manual and digital measurements in general. No changing bias was detected. Although both work-flows were reliable, the investigated digital work-flow proved to be more reliable and yielded on average larger tooth sizes. Averaged differences between methods were within 0.5 mm for directly measured outcomes but wide ranges are expected for some computed space parameters due to cumulative error. © The Author 2017. Published by Oxford University Press on behalf of the European Orthodontic Society. All rights reserved. For permissions, please email: journals.permissions@oup.com

  4. Dynamic Model Averaging in Large Model Spaces Using Dynamic Occam’s Window*

    Science.gov (United States)

    Onorante, Luca; Raftery, Adrian E.

    2015-01-01

    Bayesian model averaging has become a widely used approach to accounting for uncertainty about the structural form of the model generating the data. When data arrive sequentially and the generating model can change over time, Dynamic Model Averaging (DMA) extends model averaging to deal with this situation. Often in macroeconomics, however, many candidate explanatory variables are available and the number of possible models becomes too large for DMA to be applied in its original form. We propose a new method for this situation which allows us to perform DMA without considering the whole model space, but using a subset of models and dynamically optimizing the choice of models at each point in time. This yields a dynamic form of Occam’s window. We evaluate the method in the context of the problem of nowcasting GDP in the Euro area. We find that its forecasting performance compares well with that of other methods. PMID:26917859

  5. Dynamic Model Averaging in Large Model Spaces Using Dynamic Occam's Window.

    Science.gov (United States)

    Onorante, Luca; Raftery, Adrian E

    2016-01-01

    Bayesian model averaging has become a widely used approach to accounting for uncertainty about the structural form of the model generating the data. When data arrive sequentially and the generating model can change over time, Dynamic Model Averaging (DMA) extends model averaging to deal with this situation. Often in macroeconomics, however, many candidate explanatory variables are available and the number of possible models becomes too large for DMA to be applied in its original form. We propose a new method for this situation which allows us to perform DMA without considering the whole model space, but using a subset of models and dynamically optimizing the choice of models at each point in time. This yields a dynamic form of Occam's window. We evaluate the method in the context of the problem of nowcasting GDP in the Euro area. We find that its forecasting performance compares well with that of other methods.

  6. On the mathematical modeling of soccer dynamics

    Science.gov (United States)

    Machado, J. A. Tenreiro; Lopes, António M.

    2017-12-01

    This paper addresses the modeling and dynamical analysis of soccer teams. Two modeling perspectives based on the concepts of fractional calculus are adopted. In the first, the power law behavior and fractional-order integration are explored. In the second, a league season is interpreted in the light of a system where the teams are represented by objects (particles) that evolve in time and interact (collide) at successive rounds with dynamics driven by the outcomes of the matches. The two proposed models embed implicitly details of players and coaches, or strategical and tactical maneuvers during the matches. Therefore, the scale of observation focuses on the teams behavior in the scope of the observed variables. Data characterizing two European soccer leagues in the season 2015-2016 are adopted and processed. The model leads to the emergence of patterns that are analyzed and interpreted.

  7. BWR stability using a reducing dynamical model

    International Nuclear Information System (INIS)

    Ballestrin Bolea, J. M.; Blazquez Martinez, J. B.

    1990-01-01

    BWR stability can be treated with reduced order dynamical models. When the parameters of the model came from dynamical models. When the parameters of the model came from experimental data, the predictions are accurate. In this work an alternative derivation for the void fraction equation is made, but remarking the physical structure of the parameters. As the poles of power/reactivity transfer function are related with the parameters, the measurement of the poles by other techniques such as noise analysis will lead to the parameters, but the system of equations is non-linear. Simple parametric calculation of decay ratio are performed, showing why BWRs become unstable when they are operated at low flow and high power. (Author)

  8. Modelling the Dynamics of Emotional Awareness

    NARCIS (Netherlands)

    Thilakarathne, D.J.; Treur, J.; Schaub, T.

    2014-01-01

    In this paper, based on literature from Cognitive and Affective Neuroscience, a computational agent model is introduced incorporating the role of emotional awareness states in the dynamics of action generation. More specifically, it covers both automatic, unconscious (bottom-up) and more cognitive

  9. Object Oriented Modelling and Dynamical Simulation

    DEFF Research Database (Denmark)

    Wagner, Falko Jens; Poulsen, Mikael Zebbelin

    1998-01-01

    This report with appendix describes the work done in master project at DTU.The goal of the project was to develop a concept for simulation of dynamical systems based on object oriented methods.The result was a library of C++-classes, for use when both building componentbased models and when...

  10. Modeling the population dynamics of Pacific yew.

    Science.gov (United States)

    Richard T. Busing; Thomas A. Spies

    1995-01-01

    A study of Pacific yew (Taxus brevifolia Nutt.) population dynamics in the mountains of western Oregon and Washington was based on a combination of long-term population data and computer modeling. Rates of growth and mortality were low in mature and old-growth forest stands. Diameter growth at breast height ranged from 0 to 3 centimeters per decade...

  11. CFTSIM-ITER dynamic fuel cycle model

    International Nuclear Information System (INIS)

    Busigin, A.; Gierszewski, P.

    1998-01-01

    Dynamic system models have been developed for specific tritium systems with considerable detail and for integrated fuel cycles with lesser detail (e.g. D. Holland, B. Merrill, Analysis of tritium migration and deposition in fusion reactor systems, Proceedings of the Ninth Symposium Eng. Problems of Fusion Research (1981); M.A. Abdou, E. Vold, C. Gung, M. Youssef, K. Shin, DT fuel self-sufficiency in fusion reactors, Fusion Technol. (1986); G. Spannagel, P. Gierszewski, Dynamic tritium inventory of a NET/ITER fuel cycle with lithium salt solution blanket, Fusion Eng. Des. (1991); W. Kuan, M.A. Abdou, R.S. Willms, Dynamic simulation of a proposed ITER tritium processing system, Fusion Technol. (1995)). In order to provide a tool to understand and optimize the behavior of the ITER fuel cycle, a dynamic fuel cycle model called CFTSIM is under development. The CFTSIM code incorporates more detailed ITER models, specifically for the important isotope separation system, and also has an easier-to-use graphical interface. This paper provides an overview of CFTSIM Version 1.0. The models included are those with significant and varying tritium inventories over a test campaign: fueling, plasma and first wall, pumping, fuel cleanup, isotope separation and storage. An illustration of the results is shown. (orig.)

  12. The quantum Rabi model: solution and dynamics

    International Nuclear Information System (INIS)

    Xie, Qiongtao; Zhong, Honghua; Lee, Chaohong; Batchelor, Murray T

    2017-01-01

    This article presents a review of recent developments on various aspects of the quantum Rabi model. Particular emphasis is given on the exact analytic solution obtained in terms of confluent Heun functions. The analytic solutions for various generalisations of the quantum Rabi model are also discussed. Results are also reviewed on the level statistics and the dynamics of the quantum Rabi model. The article concludes with an introductory overview of several experimental realisations of the quantum Rabi model. An outlook towards future developments is also given. (topical review)

  13. A complete dynamic model of primary sedimentation.

    Science.gov (United States)

    Paraskevas, P; Kolokithas, G; Lekkas, T

    1993-11-01

    A dynamic mathematical model for the primary clarifier of a wastewater treatment plant is described, which is represented by a general tanks-in-series model, to simulate insufficient mixing. The model quantifies successfully the diurnal response of both the suspended and dissolved species. It is general enough, so that the values of the parameters can be replaced with those applicable to a specific case. The model was verified through data from the Biological Centre of Metamorfosi, in Athens, Greece, and can be used to assist in the design of new plants or in the analysis and output predictions of existing ones.

  14. Dynamic Modeling of CDS Index Tranche Spreads

    DEFF Research Database (Denmark)

    Dorn, Jochen

    This paper provides a Market Model which implies a dynamics for standardized CDS index tranche spreads, i.e. tranches which securitise CDS index series and dispose of predefined subordination. This model is useful for pricing options on tranches with future Issue Dates as well as for modeling...... options on structured credit derivatives. With the upcoming regulation of the CDS market in perspective, the model presented here is also an attempt to face the effects on pricing approaches provoked by an eventual Clearing Chamber . It becomes also possible to calibrate Index Tranche Options with bespoke...... tenors/tranche subordination to market data obtained by more liquid Index Tranche Options with standard characteristics....

  15. Uncertainty and its propagation in dynamics models

    International Nuclear Information System (INIS)

    Devooght, J.

    1994-01-01

    The purpose of this paper is to bring together some characteristics due to uncertainty when we deal with dynamic models and therefore to propagation of uncertainty. The respective role of uncertainty and inaccuracy is examined. A mathematical formalism based on Chapman-Kolmogorov equation allows to define a open-quotes subdynamicsclose quotes where the evolution equation takes the uncertainty into account. The problem of choosing or combining models is examined through a loss function associated to a decision

  16. Modeling reliability of power systems substations by using stochastic automata networks

    International Nuclear Information System (INIS)

    Šnipas, Mindaugas; Radziukynas, Virginijus; Valakevičius, Eimutis

    2017-01-01

    In this paper, stochastic automata networks (SANs) formalism to model reliability of power systems substations is applied. The proposed strategy allows reducing the size of state space of Markov chain model and simplifying system specification. Two case studies of standard configurations of substations are considered in detail. SAN models with different assumptions were created. SAN approach is compared with exact reliability calculation by using a minimal path set method. Modeling results showed that total independence of automata can be assumed for relatively small power systems substations with reliable equipment. In this case, the implementation of Markov chain model by a using SAN method is a relatively easy task. - Highlights: • We present the methodology to apply stochastic automata network formalism to create Markov chain models of power systems. • The stochastic automata network approach is combined with minimal path sets and structural functions. • Two models of substation configurations with different model assumptions are presented to illustrate the proposed methodology. • Modeling results of system with independent automata and functional transition rates are similar. • The conditions when total independence of automata can be assumed are addressed.

  17. Reliable gain-scheduled control of discrete-time systems and its application to CSTR model

    Science.gov (United States)

    Sakthivel, R.; Selvi, S.; Mathiyalagan, K.; Shi, Y.

    2016-10-01

    This paper is focused on reliable gain-scheduled controller design for a class of discrete-time systems with randomly occurring nonlinearities and actuator fault. Further, the nonlinearity in the system model is assumed to occur randomly according to a Bernoulli distribution with measurable time-varying probability in real time. The main purpose of this paper is to design a gain-scheduled controller by implementing a probability-dependent Lyapunov function and linear matrix inequality (LMI) approach such that the closed-loop discrete-time system is stochastically stable for all admissible randomly occurring nonlinearities. The existence conditions for the reliable controller is formulated in terms of LMI constraints. Finally, the proposed reliable gain-scheduled control scheme is applied on continuously stirred tank reactor model to demonstrate the effectiveness and applicability of the proposed design technique.

  18. Study on reliability analysis based on multilevel flow models and fault tree method

    International Nuclear Information System (INIS)

    Chen Qiang; Yang Ming

    2014-01-01

    Multilevel flow models (MFM) and fault tree method describe the system knowledge in different forms, so the two methods express an equivalent logic of the system reliability under the same boundary conditions and assumptions. Based on this and combined with the characteristics of MFM, a method mapping MFM to fault tree was put forward, thus providing a way to establish fault tree rapidly and realizing qualitative reliability analysis based on MFM. Taking the safety injection system of pressurized water reactor nuclear power plant as an example, its MFM was established and its reliability was analyzed qualitatively. The analysis result shows that the logic of mapping MFM to fault tree is correct. The MFM is easily understood, created and modified. Compared with the traditional fault tree analysis, the workload is greatly reduced and the modeling time is saved. (authors)

  19. Reliability of Coulomb stress changes inferred from correlated uncertainties of finite-fault source models

    KAUST Repository

    Woessner, J.

    2012-07-14

    Static stress transfer is one physical mechanism to explain triggered seismicity. Coseismic stress-change calculations strongly depend on the parameterization of the causative finite-fault source model. These models are uncertain due to uncertainties in input data, model assumptions, and modeling procedures. However, fault model uncertainties have usually been ignored in stress-triggering studies and have not been propagated to assess the reliability of Coulomb failure stress change (ΔCFS) calculations. We show how these uncertainties can be used to provide confidence intervals for co-seismic ΔCFS-values. We demonstrate this for the MW = 5.9 June 2000 Kleifarvatn earthquake in southwest Iceland and systematically map these uncertainties. A set of 2500 candidate source models from the full posterior fault-parameter distribution was used to compute 2500 ΔCFS maps. We assess the reliability of the ΔCFS-values from the coefficient of variation (CV) and deem ΔCFS-values to be reliable where they are at least twice as large as the standard deviation (CV ≤ 0.5). Unreliable ΔCFS-values are found near the causative fault and between lobes of positive and negative stress change, where a small change in fault strike causes ΔCFS-values to change sign. The most reliable ΔCFS-values are found away from the source fault in the middle of positive and negative ΔCFS-lobes, a likely general pattern. Using the reliability criterion, our results support the static stress-triggering hypothesis. Nevertheless, our analysis also suggests that results from previous stress-triggering studies not considering source model uncertainties may have lead to a biased interpretation of the importance of static stress-triggering.

  20. Dynamic multibody modeling for tethered space elevators

    Science.gov (United States)

    Williams, Paul

    2009-08-01

    This paper presents a fundamental modeling strategy for dealing with powered and propelled bodies moving along space tethers. The tether is divided into a large number of discrete masses, which are connected by viscoelastic springs. The tether is subject to the full range of forces expected in Earth orbit in a relatively simple manner. Two different models of the elevator dynamics are presented. In order to capture the effect of the elevator moving along the tether, the elevator dynamics are included as a separate body in both models. One model treats the elevator's motion dynamically, where propulsive and friction forces are applied to the elevator body. The second model treats the elevator's motion kinematically, where the distance along the tether is determined by adjusting the lengths of tether on either side of the elevator. The tether model is used to determine optimal configurations for the space elevator. A modal analysis of two different configurations is presented which show that the fundamental mode of oscillation is a pendular one around the anchor point with a period on the order of 160 h for the in-plane motion, and 24 h for the out-of-plane motion. Numerical simulation results of the effects of the elevator moving along the cable are presented for different travel velocities and different elevator masses.

  1. Sepsis progression and outcome: a dynamical model

    Directory of Open Access Journals (Sweden)

    Gessler Damian DG

    2006-02-01

    Full Text Available Abstract Background Sepsis (bloodstream infection is the leading cause of death in non-surgical intensive care units. It is diagnosed in 750,000 US patients per annum, and has high mortality. Current understanding of sepsis is predominately observational and correlational, with only a partial and incomplete understanding of the physiological dynamics underlying the syndrome. There exists a need for dynamical models of sepsis progression, based upon basic physiologic principles, which could eventually guide hourly treatment decisions. Results We present an initial mathematical model of sepsis, based on metabolic rate theory that links basic vascular and immunological dynamics. The model includes the rate of vascular circulation, a surrogate for the metabolic rate that is mechanistically associated with disease progression. We use the mass-specific rate of blood circulation (SRBC, a correlate of the body mass index, to build a differential equation model of circulation, infection, organ damage, and recovery. This introduces a vascular component into an infectious disease model that describes the interaction between a pathogen and the adaptive immune system. Conclusion The model predicts that deviations from normal SRBC correlate with disease progression and adverse outcome. We compare the predictions with population mortality data from cardiovascular disease and cancer and show that deviations from normal SRBC correlate with higher mortality rates.

  2. Mineral vein dynamics modeling (FRACS). Phase 1

    Energy Technology Data Exchange (ETDEWEB)

    Urai, J.; Virgo, S.; Arndt, M. [RWTH Aachen (Germany). Geologie-Endogene Dynamik] [and others

    2013-07-15

    The Mineral Vein Dynamics Modeling group ''FRACS'' is a team of 7 research groups from the Universities of Mainz, Aachen, Tuebingen, Karlsruhe, Bayreuth, ETH Zuerich and Glasgow working on an understanding of the dynamic development of fracturing, fluid flow and fracture sealing. World-class field laboratories, especially carbonate sequences from the Oman Mountains are studied and classified. State of the art numerical programs are written, expanded and used to simulate the dynamic interaction of fracturing, flow and resealing and the results are compared with the natural examples. Newest analytical technologies including laser scanning, high resolution X-ray microtomography, fluid inclusion and isotope analysis are performed to understand and compare the results of simulations with natural examples. A new statistical program was developed to classify the natural fracture and vein systems and compare them with dynamic numerical simulations and analytical models. The results of the first project phase are extremely promising. Most of the numerical models have been developed up to the stage where they can be used to simulate the natural examples. The models allow a definition of the first proxies for high fluid pressure and tectonic stresses. It was found out that the Oman Mountains are a complex and very dynamic system that constantly fractures and reseals from the scale of small veins up to the scale of large normal and strike slip faults. The numerical simulations also indicate that the permeability of such systems is not a constant but that the system adjusts to the driving force, for ex-ample high fluid pressure. When the system reseals fast a fluctuating behavior can be observed in the models where the system constantly fractures and reseals, which is in accordance with the observation of the natural laboratory.

  3. The application of cognitive models to the evaluation and prediction of human reliability

    International Nuclear Information System (INIS)

    Embrey, D.E.; Reason, J.T.

    1986-01-01

    The first section of the paper provides a brief overview of a number of important principles relevant to human reliability modeling that have emerged from cognitive models, and presents a synthesis of these approaches in the form of a Generic Error Modeling System (GEMS). The next section illustrates the application of GEMS to some well known nuclear power plant (NPP) incidents in which human error was a major contributor. The way in which design recommendations can emerge from analyses of this type is illustrated. The third section describes the use of cognitive models in the classification of human errors for prediction and data collection purposes. The final section addresses the predictive modeling of human error as part of human reliability assessment in Probabilistic Risk Assessment

  4. A hybrid reliability algorithm using PSO-optimized Kriging model and adaptive importance sampling

    Science.gov (United States)

    Tong, Cao; Gong, Haili

    2018-03-01

    This paper aims to reduce the computational cost of reliability analysis. A new hybrid algorithm is proposed based on PSO-optimized Kriging model and adaptive importance sampling method. Firstly, the particle swarm optimization algorithm (PSO) is used to optimize the parameters of Kriging model. A typical function is fitted to validate improvement by comparing results of PSO-optimized Kriging model with those of the original Kriging model. Secondly, a hybrid algorithm for reliability analysis combined optimized Kriging model and adaptive importance sampling is proposed. Two cases from literatures are given to validate the efficiency and correctness. The proposed method is proved to be more efficient due to its application of small number of sample points according to comparison results.

  5. Development of web-based reliability data analysis algorithm model and its application

    International Nuclear Information System (INIS)

    Hwang, Seok-Won; Oh, Ji-Yong; Moosung-Jae

    2010-01-01

    For this study, a database model of plant reliability was developed for the effective acquisition and management of plant-specific data that can be used in various applications of plant programs as well as in Probabilistic Safety Assessment (PSA). Through the development of a web-based reliability data analysis algorithm, this approach systematically gathers specific plant data such as component failure history, maintenance history, and shift diary. First, for the application of the developed algorithm, this study reestablished the raw data types, data deposition procedures and features of the Enterprise Resource Planning (ERP) system process. The component codes and system codes were standardized to make statistical analysis between different types of plants possible. This standardization contributes to the establishment of a flexible database model that allows the customization of reliability data for the various applications depending on component types and systems. In addition, this approach makes it possible for users to perform trend analyses and data comparisons for the significant plant components and systems. The validation of the algorithm is performed through a comparison of the importance measure value (Fussel-Vesely) of the mathematical calculation and that of the algorithm application. The development of a reliability database algorithm is one of the best approaches for providing systemic management of plant-specific reliability data with transparency and continuity. This proposed algorithm reinforces the relationships between raw data and application results so that it can provide a comprehensive database that offers everything from basic plant-related data to final customized data.

  6. A Review of the Progress with Statistical Models of Passive Component Reliability

    Directory of Open Access Journals (Sweden)

    Bengt O.Y. Lydell

    2017-03-01

    Full Text Available During the past 25 years, in the context of probabilistic safety assessment, efforts have been directed towards establishment of comprehensive pipe failure event databases as a foundation for exploratory research to better understand how to effectively organize a piping reliability analysis task. The focused pipe failure database development efforts have progressed well with the development of piping reliability analysis frameworks that utilize the full body of service experience data, fracture mechanics analysis insights, expert elicitation results that are rolled into an integrated and risk-informed approach to the estimation of piping reliability parameters with full recognition of the embedded uncertainties. The discussion in this paper builds on a major collection of operating experience data (more than 11,000 pipe failure records and the associated lessons learned from data analysis and data applications spanning three decades. The piping reliability analysis lessons learned have been obtained from the derivation of pipe leak and rupture frequencies for corrosion resistant piping in a raw water environment, loss-of-coolant-accident frequencies given degradation mitigation, high-energy pipe break analysis, moderate-energy pipe break analysis, and numerous plant-specific applications of a statistical piping reliability model framework. Conclusions are presented regarding the feasibility of determining and incorporating aging effects into probabilistic safety assessment models.

  7. A review of the progress with statistical models of passive component reliability

    Energy Technology Data Exchange (ETDEWEB)

    Lydell, Bengt O. Y. [Sigma-Phase Inc., Vail (United States)

    2017-03-15

    During the past 25 years, in the context of probabilistic safety assessment, efforts have been directed towards establishment of comprehensive pipe failure event databases as a foundation for exploratory research to better understand how to effectively organize a piping reliability analysis task. The focused pipe failure database development efforts have progressed well with the development of piping reliability analysis frameworks that utilize the full body of service experience data, fracture mechanics analysis insights, expert elicitation results that are rolled into an integrated and risk-informed approach to the estimation of piping reliability parameters with full recognition of the embedded uncertainties. The discussion in this paper builds on a major collection of operating experience data (more than 11,000 pipe failure records) and the associated lessons learned from data analysis and data applications spanning three decades. The piping reliability analysis lessons learned have been obtained from the derivation of pipe leak and rupture frequencies for corrosion resistant piping in a raw water environment, loss-of-coolant-accident frequencies given degradation mitigation, high-energy pipe break analysis, moderate-energy pipe break analysis, and numerous plant-specific applications of a statistical piping reliability model framework. Conclusions are presented regarding the feasibility of determining and incorporating aging effects into probabilistic safety assessment models.

  8. Development of web-based reliability data analysis algorithm model and its application

    Energy Technology Data Exchange (ETDEWEB)

    Hwang, Seok-Won, E-mail: swhwang@khnp.co.k [Korea Hydro and Nuclear Power Co. Ltd., Jang-Dong 25-1, Yuseong-Gu, 305-343 Daejeon (Korea, Republic of); Oh, Ji-Yong [Korea Hydro and Nuclear Power Co. Ltd., Jang-Dong 25-1, Yuseong-Gu, 305-343 Daejeon (Korea, Republic of); Moosung-Jae [Department of Nuclear Engineering Hanyang University 17 Haengdang, Sungdong, Seoul (Korea, Republic of)

    2010-02-15

    For this study, a database model of plant reliability was developed for the effective acquisition and management of plant-specific data that can be used in various applications of plant programs as well as in Probabilistic Safety Assessment (PSA). Through the development of a web-based reliability data analysis algorithm, this approach systematically gathers specific plant data such as component failure history, maintenance history, and shift diary. First, for the application of the developed algorithm, this study reestablished the raw data types, data deposition procedures and features of the Enterprise Resource Planning (ERP) system process. The component codes and system codes were standardized to make statistical analysis between different types of plants possible. This standardization contributes to the establishment of a flexible database model that allows the customization of reliability data for the various applications depending on component types and systems. In addition, this approach makes it possible for users to perform trend analyses and data comparisons for the significant plant components and systems. The validation of the algorithm is performed through a comparison of the importance measure value (Fussel-Vesely) of the mathematical calculation and that of the algorithm application. The development of a reliability database algorithm is one of the best approaches for providing systemic management of plant-specific reliability data with transparency and continuity. This proposed algorithm reinforces the relationships between raw data and application results so that it can provide a comprehensive database that offers everything from basic plant-related data to final customized data.

  9. Reliability model for helicopter main gearbox lubrication system using influence diagrams

    International Nuclear Information System (INIS)

    Rashid, H.S.J.; Place, C.S.; Mba, D.; Keong, R.L.C.; Healey, A.; Kleine-Beek, W.; Romano, M.

    2015-01-01

    The loss of oil from a helicopter main gearbox (MGB) leads to increased friction between components, a rise in component surface temperatures, and subsequent mechanical failure of gearbox components. A number of significant helicopter accidents have been caused due to such loss of lubrication. This paper presents a model to assess the reliability of helicopter MGB lubricating systems. Safety risk modeling was conducted for MGB oil system related accidents in order to analyse key failure mechanisms and the contributory factors. Thus, the dominant failure modes for lubrication systems and key contributing components were identified. The Influence Diagram (ID) approach was then employed to investigate reliability issues of the MGB lubrication systems at the level of primary causal factors, thus systematically investigating a complex context of events, conditions, and influences that are direct triggers of the helicopter MGB lubrication system failures. The interrelationships between MGB lubrication system failure types were thus identified, and the influence of each of these factors on the overall MGB lubrication system reliability was assessed. This paper highlights parts of the HELMGOP project, sponsored by the European Aviation Safety Agency to improve helicopter main gearbox reliability. - Highlights: • We investigated methods to optimize helicopter MGB oil system run-dry capability. • Used Influence Diagram to assess design and maintenance factors of MGB oil system. • Factors influencing overall MGB lubrication system reliability were identified. • This globally influences current and future helicopter MGB designs

  10. A review of the progress with statistical models of passive component reliability

    International Nuclear Information System (INIS)

    Lydell, Bengt O. Y.

    2017-01-01

    During the past 25 years, in the context of probabilistic safety assessment, efforts have been directed towards establishment of comprehensive pipe failure event databases as a foundation for exploratory research to better understand how to effectively organize a piping reliability analysis task. The focused pipe failure database development efforts have progressed well with the development of piping reliability analysis frameworks that utilize the full body of service experience data, fracture mechanics analysis insights, expert elicitation results that are rolled into an integrated and risk-informed approach to the estimation of piping reliability parameters with full recognition of the embedded uncertainties. The discussion in this paper builds on a major collection of operating experience data (more than 11,000 pipe failure records) and the associated lessons learned from data analysis and data applications spanning three decades. The piping reliability analysis lessons learned have been obtained from the derivation of pipe leak and rupture frequencies for corrosion resistant piping in a raw water environment, loss-of-coolant-accident frequencies given degradation mitigation, high-energy pipe break analysis, moderate-energy pipe break analysis, and numerous plant-specific applications of a statistical piping reliability model framework. Conclusions are presented regarding the feasibility of determining and incorporating aging effects into probabilistic safety assessment models

  11. Direct modeling for computational fluid dynamics

    Science.gov (United States)

    Xu, Kun

    2015-06-01

    All fluid dynamic equations are valid under their modeling scales, such as the particle mean free path and mean collision time scale of the Boltzmann equation and the hydrodynamic scale of the Navier-Stokes (NS) equations. The current computational fluid dynamics (CFD) focuses on the numerical solution of partial differential equations (PDEs), and its aim is to get the accurate solution of these governing equations. Under such a CFD practice, it is hard to develop a unified scheme that covers flow physics from kinetic to hydrodynamic scales continuously because there is no such governing equation which could make a smooth transition from the Boltzmann to the NS modeling. The study of fluid dynamics needs to go beyond the traditional numerical partial differential equations. The emerging engineering applications, such as air-vehicle design for near-space flight and flow and heat transfer in micro-devices, do require further expansion of the concept of gas dynamics to a larger domain of physical reality, rather than the traditional distinguishable governing equations. At the current stage, the non-equilibrium flow physics has not yet been well explored or clearly understood due to the lack of appropriate tools. Unfortunately, under the current numerical PDE approach, it is hard to develop such a meaningful tool due to the absence of valid PDEs. In order to construct multiscale and multiphysics simulation methods similar to the modeling process of constructing the Boltzmann or the NS governing equations, the development of a numerical algorithm should be based on the first principle of physical modeling. In this paper, instead of following the traditional numerical PDE path, we introduce direct modeling as a principle for CFD algorithm development. Since all computations are conducted in a discretized space with limited cell resolution, the flow physics to be modeled has to be done in the mesh size and time step scales. Here, the CFD is more or less a direct

  12. Quasi-dynamic model for an organic Rankine cycle

    International Nuclear Information System (INIS)

    Bamgbopa, Musbaudeen O.; Uzgoren, Eray

    2013-01-01

    Highlights: • Study presents a simplified transient modeling approach for an ORC under variable heat input. • The ORC model is presented as a synthesis of its models of its sub-components. • The model is compared to benchmark numerical simulations and experimental data at different stages. - Abstract: When considering solar based thermal energy input to an organic Rankine cycle (ORC), intermittent nature of the heat input does not only adversely affect the power output but also it may prevent ORC to operate under steady state conditions. In order to identify reliability and efficiency of such systems, this paper presents a simplified transient modeling approach for an ORC operating under variable heat input. The approach considers that response of the system to heat input variations is mainly dictated by the evaporator. Consequently, overall system is assembled using dynamic models for the heat exchangers (evaporator and condenser) and static models of the pump and the expander. In addition, pressure drop within heat exchangers is neglected. The model is compared to benchmark numerical and experimental data showing that the underlying assumptions are reasonable for cases where thermal input varies in time. Furthermore, the model is studied on another configuration and mass flow rates of both the working fluid and hot water and hot water’s inlet temperature to the ORC unit are shown to have direct influence on the system’s response

  13. Towards an efficient multiphysics model for nuclear reactor dynamics

    Directory of Open Access Journals (Sweden)

    Obaidurrahman K.

    2015-01-01

    Full Text Available Availability of fast computer resources nowadays has facilitated more in-depth modeling of complex engineering systems which involve strong multiphysics interactions. This multiphysics modeling is an important necessity in nuclear reactor safety studies where efforts are being made worldwide to combine the knowledge from all associated disciplines at one place to accomplish the most realistic simulation of involved phenomenon. On these lines coupled modeling of nuclear reactor neutron kinetics, fuel heat transfer and coolant transport is a regular practice nowadays for transient analysis of reactor core. However optimization between modeling accuracy and computational economy has always been a challenging task to ensure the adequate degree of reliability in such extensive numerical exercises. Complex reactor core modeling involves estimation of evolving 3-D core thermal state, which in turn demands an expensive multichannel based detailed core thermal hydraulics model. A novel approach of power weighted coupling between core neutronics and thermal hydraulics presented in this work aims to reduce the bulk of core thermal calculations in core dynamics modeling to a significant extent without compromising accuracy of computation. Coupled core model has been validated against a series of international benchmarks. Accuracy and computational efficiency of the proposed multiphysics model has been demonstrated by analyzing a reactivity initiated transient.

  14. New concepts for dynamic plant uptake models

    DEFF Research Database (Denmark)

    Rein, Arno; Legind, Charlotte Nielsen; Trapp, Stefan

    2011-01-01

    Models for the prediction of chemical uptake into plants are widely applied tools for human and wildlife exposure assessment, pesticide design and for environmental biotechnology such as phytoremediation. Steady-state considerations are often applied, because they are simple and have a small data...... need. However, often the emission pattern is non-steady. Examples are pesticide spraying, or the application of manure and sewage sludge on agricultural fields. In these scenarios, steady-state solutions are not valid, and dynamic simulation is required. We compared different approaches for dynamic...

  15. Statistical models of petrol engines vehicles dynamics

    Science.gov (United States)

    Ilie, C. O.; Marinescu, M.; Alexa, O.; Vilău, R.; Grosu, D.

    2017-10-01

    This paper focuses on studying statistical models of vehicles dynamics. It was design and perform a one year testing program. There were used many same type cars with gasoline engines and different mileage. Experimental data were collected of onboard sensors and those on the engine test stand. A database containing data of 64th tests was created. Several mathematical modelling were developed using database and the system identification method. Each modelling is a SISO or a MISO linear predictive ARMAX (AutoRegressive-Moving-Average with eXogenous inputs) model. It represents a differential equation with constant coefficients. It were made 64th equations for each dependency like engine torque as output and engine’s load and intake manifold pressure, as inputs. There were obtained strings with 64 values for each type of model. The final models were obtained using average values of the coefficients. The accuracy of models was assessed.

  16. Improved radiograph measurement inter-observer reliability by use of statistical shape models

    Energy Technology Data Exchange (ETDEWEB)

    Pegg, E.C., E-mail: elise.pegg@ndorms.ox.ac.uk [University of Oxford, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Nuffield Orthopaedic Centre, Windmill Road, Oxford OX3 7LD (United Kingdom); Mellon, S.J., E-mail: stephen.mellon@ndorms.ox.ac.uk [University of Oxford, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Nuffield Orthopaedic Centre, Windmill Road, Oxford OX3 7LD (United Kingdom); Salmon, G. [University of Oxford, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Nuffield Orthopaedic Centre, Windmill Road, Oxford OX3 7LD (United Kingdom); Alvand, A., E-mail: abtin.alvand@ndorms.ox.ac.uk [University of Oxford, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Nuffield Orthopaedic Centre, Windmill Road, Oxford OX3 7LD (United Kingdom); Pandit, H., E-mail: hemant.pandit@ndorms.ox.ac.uk [University of Oxford, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Nuffield Orthopaedic Centre, Windmill Road, Oxford OX3 7LD (United Kingdom); Murray, D.W., E-mail: david.murray@ndorms.ox.ac.uk [University of Oxford, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Nuffield Orthopaedic Centre, Windmill Road, Oxford OX3 7LD (United Kingdom); Gill, H.S., E-mail: richie.gill@ndorms.ox.ac.uk [University of Oxford, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Nuffield Orthopaedic Centre, Windmill Road, Oxford OX3 7LD (United Kingdom)

    2012-10-15

    Pre- and post-operative radiographs of patients undergoing joint arthroplasty are often examined for a variety of purposes including preoperative planning and patient assessment. This work examines the feasibility of using active shape models (ASM) to semi-automate measurements from post-operative radiographs for the specific case of the Oxford™ Unicompartmental Knee. Measurements of the proximal tibia and the position of the tibial tray were made using the ASM model and manually. Data were obtained by four observers and one observer took four sets of measurements to allow assessment of the inter- and intra-observer reliability, respectively. The parameters measured were the tibial tray angle, the tray overhang, the tray size, the sagittal cut position, the resection level and the tibial width. Results demonstrated improved reliability (average of 27% and 11.2% increase for intra- and inter-reliability, respectively) and equivalent accuracy (p > 0.05 for compared data values) for all of the measurements using the ASM model, with the exception of the tray overhang (p = 0.0001). Less time (15 s) was required to take measurements using the ASM model compared with manual measurements, which was significant. These encouraging results indicate that semi-automated measurement techniques could improve the reliability of radiographic measurements.

  17. Improved radiograph measurement inter-observer reliability by use of statistical shape models

    International Nuclear Information System (INIS)

    Pegg, E.C.; Mellon, S.J.; Salmon, G.; Alvand, A.; Pandit, H.; Murray, D.W.; Gill, H.S.

    2012-01-01

    Pre- and post-operative radiographs of patients undergoing joint arthroplasty are often examined for a variety of purposes including preoperative planning and patient assessment. This work examines the feasibility of using active shape models (ASM) to semi-automate measurements from post-operative radiographs for the specific case of the Oxford™ Unicompartmental Knee. Measurements of the proximal tibia and the position of the tibial tray were made using the ASM model and manually. Data were obtained by four observers and one observer took four sets of measurements to allow assessment of the inter- and intra-observer reliability, respectively. The parameters measured were the tibial tray angle, the tray overhang, the tray size, the sagittal cut position, the resection level and the tibial width. Results demonstrated improved reliability (average of 27% and 11.2% increase for intra- and inter-reliability, respectively) and equivalent accuracy (p > 0.05 for compared data values) for all of the measurements using the ASM model, with the exception of the tray overhang (p = 0.0001). Less time (15 s) was required to take measurements using the ASM model compared with manual measurements, which was significant. These encouraging results indicate that semi-automated measurement techniques could improve the reliability of radiographic measurements

  18. Reliability Analysis of an Extended Shock Model and Its Optimization Application in a Production Line

    Directory of Open Access Journals (Sweden)

    Renbin Liu

    2014-01-01

    some important reliability indices are derived, such as availability, failure frequency, mean vacation period, mean renewal cycle, mean startup period, and replacement frequency. Finally, a production line controlled by two cold-standby computers is modeled to present numerical illustration and its optimal part-time job policy at a maximum profit.

  19. Role of frameworks, models, data, and judgment in human reliability analysis

    Energy Technology Data Exchange (ETDEWEB)

    Hannaman, G W

    1986-05-01

    Many advancements in the methods for treating human interactions in PRA studies have occurred in the last decade. These advancements appear to increase the capability of PRAs to extend beyond just the assessment of the human's importance to safety. However, variations in the application of these advanced models, data, and judgements in recent PRAs make quantitative comparisons among studies extremely difficult. This uncertainty in the analysis diminishes the usefulness of the PRA study for upgrading procedures, enhancing traning, simulator design, technical specification guidance, and for aid in designing the man-machine interface. Hence, there is a need for a framework to guide analysts in incorporating human interactions into the PRA systems analyses so that future users of a PRA study will have a clear understanding of the approaches, models, data, and assumptions which were employed in the initial study. This paper describes the role of the systematic human action reliability procedure (SHARP) in providing a road map through the complex terrain of human reliability that promises to improve the reproducibility of such analysis in the areas of selecting the models, data, representations, and assumptions. Also described is the role that a human cognitive reliability model can have in collecting data from simulators and helping analysts assign human reliability parameters in a PRA study. Use of these systematic approaches to perform or upgrade existing PRAs promises to make PRA studies more useful as risk management tools.

  20. Assessing the Reliability of Curriculum-Based Measurement: An Application of Latent Growth Modeling

    Science.gov (United States)

    Yeo, Seungsoo; Kim, Dong-Il; Branum-Martin, Lee; Wayman, Miya Miura; Espin, Christine A.

    2012-01-01

    The purpose of this study was to demonstrate the use of Latent Growth Modeling (LGM) as a method for estimating reliability of Curriculum-Based Measurement (CBM) progress-monitoring data. The LGM approach permits the error associated with each measure to differ at each time point, thus providing an alternative method for examining of the…