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

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.

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)

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

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.

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)

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.

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.

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)

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.

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.

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.

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.

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

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

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

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

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

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

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.

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.

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.

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

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.

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

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

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

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

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.

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)

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.

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

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.

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)

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.

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.

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.

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.

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.

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.

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.

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

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.

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.

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.

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

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.

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)

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

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...

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

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.

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

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.

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...

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)

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...

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.

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)

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

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.

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...

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

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)

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)

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...

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...

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

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.

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

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.

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.

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

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)

Proceedings of the SRESA national conference on reliability and safety engineering

International Nuclear Information System (INIS)

Varde, P.V.; Vaishnavi, P.; Sujatha, S.; Valarmathi, A.

2014-01-01

The objective of this conference was to provide a forum for technical discussions on recent developments in the area of risk based approach and Prognostic Health Management of critical systems in decision making. The reliability and safety engineering methods are concerned with the way which the product fails, and the effects of failure is to understand how a product works and assures acceptable levels of safety. The reliability engineering addresses all the anticipated and possibly unanticipated causes of failure to ensure the occurrence of failure is prevented or minimized. The topics discussed in the conference were: Reliability in Engineering Design, Safety Assessment and Management, Reliability analysis and Assessment , Stochastic Petri nets for reliability Modeling, Dynamic Reliability, Reliability Prediction, Hardware Reliability, Software Reliability in Safety Critical Issues, Probabilistic Safety Assessment, Risk Informed Approach, Dynamic Models for Reliability Analysis, Reliability based Design and Analysis, Prognostics and Health Management, Remaining Useful Life (RUL), Human Reliability Modeling, Risk Based Applications, Hazard and Operability Study (HAZOP), Reliability in Network Security and Quality Assurance and Management etc. The papers relevant to INIS are indexed separately

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.

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

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...

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.)

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.,...

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.

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.

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.

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...

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...

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...

Agent autonomy approach to probabilistic physics-of-failure modeling of complex dynamic systems with interacting failure mechanisms

Science.gov (United States)

Gromek, Katherine Emily

A novel computational and inference framework of the physics-of-failure (PoF) reliability modeling for complex dynamic systems has been established in this research. The PoF-based reliability models are used to perform a real time simulation of system failure processes, so that the system level reliability modeling would constitute inferences from checking the status of component level reliability at any given time. The "agent autonomy" concept is applied as a solution method for the system-level probabilistic PoF-based (i.e. PPoF-based) modeling. This concept originated from artificial intelligence (AI) as a leading intelligent computational inference in modeling of multi agents systems (MAS). The concept of agent autonomy in the context of reliability modeling was first proposed by M. Azarkhail [1], where a fundamentally new idea of system representation by autonomous intelligent agents for the purpose of reliability modeling was introduced. Contribution of the current work lies in the further development of the agent anatomy concept, particularly the refined agent classification within the scope of the PoF-based system reliability modeling, new approaches to the learning and the autonomy properties of the intelligent agents, and modeling interacting failure mechanisms within the dynamic engineering system. The autonomous property of intelligent agents is defined as agent's ability to self-activate, deactivate or completely redefine their role in the analysis. This property of agents and the ability to model interacting failure mechanisms of the system elements makes the agent autonomy fundamentally different from all existing methods of probabilistic PoF-based reliability modeling. 1. Azarkhail, M., "Agent Autonomy Approach to Physics-Based Reliability Modeling of Structures and Mechanical Systems", PhD thesis, University of Maryland, College Park, 2007.

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

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...

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.

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.

Overview of system reliability analyses for PSA

International Nuclear Information System (INIS)

Matsuoka, Takeshi

2012-01-01

Overall explanations are given for many matters relating to system reliability analysis. Systems engineering, Operations research, Industrial engineering, Quality control are briefly explained. Many system reliability analysis methods including advanced methods are introduced. Discussions are given for FMEA, reliability block diagram, Markov model, Petri net, Bayesian network, goal tree success tree, dynamic flow graph methodology, cell-to-cell mapping technique, the GO-FLOW and others. (author)

Integration of Human Reliability Analysis Models into the Simulation-Based Framework for the Risk-Informed Safety Margin Characterization Toolkit

International Nuclear Information System (INIS)

Boring, Ronald; Mandelli, Diego; Rasmussen, Martin; Ulrich, Thomas; Groth, Katrina; Smith, Curtis

2016-01-01

This report presents an application of a computation-based human reliability analysis (HRA) framework called the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER). HUNTER has been developed not as a standalone HRA method but rather as framework that ties together different HRA methods to model dynamic risk of human activities as part of an overall probabilistic risk assessment (PRA). While we have adopted particular methods to build an initial model, the HUNTER framework is meant to be intrinsically flexible to new pieces that achieve particular modeling goals. In the present report, the HUNTER implementation has the following goals: • Integration with a high fidelity thermal-hydraulic model capable of modeling nuclear power plant behaviors and transients • Consideration of a PRA context • Incorporation of a solid psychological basis for operator performance • Demonstration of a functional dynamic model of a plant upset condition and appropriate operator response This report outlines these efforts and presents the case study of a station blackout scenario to demonstrate the various modules developed to date under the HUNTER research umbrella.

Integration of Human Reliability Analysis Models into the Simulation-Based Framework for the Risk-Informed Safety Margin Characterization Toolkit

Energy Technology Data Exchange (ETDEWEB)

Boring, Ronald [Idaho National Lab. (INL), Idaho Falls, ID (United States); Mandelli, Diego [Idaho National Lab. (INL), Idaho Falls, ID (United States); Rasmussen, Martin [Norwegian Univ. of Science and Technology, Trondheim (Norway). Social Research; Herberger, Sarah [Idaho National Lab. (INL), Idaho Falls, ID (United States); Ulrich, Thomas [Idaho National Lab. (INL), Idaho Falls, ID (United States); Groth, Katrina [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Smith, Curtis [Idaho National Lab. (INL), Idaho Falls, ID (United States)

2016-06-01

This report presents an application of a computation-based human reliability analysis (HRA) framework called the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER). HUNTER has been developed not as a standalone HRA method but rather as framework that ties together different HRA methods to model dynamic risk of human activities as part of an overall probabilistic risk assessment (PRA). While we have adopted particular methods to build an initial model, the HUNTER framework is meant to be intrinsically flexible to new pieces that achieve particular modeling goals. In the present report, the HUNTER implementation has the following goals: • Integration with a high fidelity thermal-hydraulic model capable of modeling nuclear power plant behaviors and transients • Consideration of a PRA context • Incorporation of a solid psychological basis for operator performance • Demonstration of a functional dynamic model of a plant upset condition and appropriate operator response This report outlines these efforts and presents the case study of a station blackout scenario to demonstrate the various modules developed to date under the HUNTER research umbrella.

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.

A Review: Passive System Reliability Analysis – Accomplishments and Unresolved Issues

Energy Technology Data Exchange (ETDEWEB)

Nayak, Arun Kumar, E-mail: arunths@barc.gov.in [Reactor Engineering Division, Reactor Design and Development Group, Bhabha Atomic Research Centre, Mumbai (India); Chandrakar, Amit [Homi Bhabha National Institute, Mumbai (India); Vinod, Gopika [Reactor Safety Division, Reactor Design and Development Group, Bhabha Atomic Research Centre, Mumbai (India)

2014-10-10

Reliability assessment of passive safety systems is one of the important issues, since safety of advanced nuclear reactors rely on several passive features. In this context, a few methodologies such as reliability evaluation of passive safety system (REPAS), reliability methods for passive safety functions (RMPS), and analysis of passive systems reliability (APSRA) have been developed in the past. These methodologies have been used to assess reliability of various passive safety systems. While these methodologies have certain features in common, but they differ in considering certain issues; for example, treatment of model uncertainties, deviation of geometric, and process parameters from their nominal values. This paper presents the state of the art on passive system reliability assessment methodologies, the accomplishments, and remaining issues. In this review, three critical issues pertaining to passive systems performance and reliability have been identified. The first issue is applicability of best estimate codes and model uncertainty. The best estimate codes based phenomenological simulations of natural convection passive systems could have significant amount of uncertainties, these uncertainties must be incorporated in appropriate manner in the performance and reliability analysis of such systems. The second issue is the treatment of dynamic failure characteristics of components of passive systems. REPAS, RMPS, and APSRA methodologies do not consider dynamic failures of components or process, which may have strong influence on the failure of passive systems. The influence of dynamic failure characteristics of components on system failure probability is presented with the help of a dynamic reliability methodology based on Monte Carlo simulation. The analysis of a benchmark problem of Hold-up tank shows the error in failure probability estimation by not considering the dynamism of components. It is thus suggested that dynamic reliability methodologies must be

KINEMATICS AND DYNAMICS MODELS OF CYLINDRICAL ROLLER BEARING OF RAILWAY TRANSPORT

Directory of Open Access Journals (Sweden)

A. V. Gaydamaka

2014-05-01

Full Text Available Purpose. Lack of kinematics models and imperfection of the known dynamics models of the roller bearings of railway rolling stock axle-boxes do not allow designing the optimal structure of bearing cages, providing the required service life and reliability of bearing units of wheel sets for cars and locomotives. The studies of kinematics and dynamics of roller bearings of axle boxes for cars and locomotives and modeling of their parts interaction to create the analytical method of bearing cages calculation are necessary. Methodology. This purpose has been achieved due to the modeling of kinematics of the ideal (without gaps and real (taking account the gaps, manufacturing and installation errors bearings, substantiation of the transfer mechanism of motion from the rollers to bearing cage, modeling the dynamics of rolling, research of interaction forces of the rollers with bearing cage. Findings. It is established that the kinematics of ideal bearing is determined by the contact deformations of the rollers and rings, when the kinematics of real bearing depends mainly on the side gaps in the windows of the bearing cage. On the basis of studies of the real bearing kinematics the dynamics models of the rollers and bearing cage interaction were constructed. The conducted studies of kinematics and dynamics of rolling bearings have changed our view of them as of the planetary mechanism, explained the reason of bearing cage loading, and confirmed the possibility of destruction during operation. Originality. It was first proposed a mechanism for motion transfer from the rollers to the bearing cage of roller bearings, consisting in that the side gap in the bearing cage window is reduced gradually multiple of the number of rollers of radial loading area according to the bearing cage motion. The models of roller bearing dynamics, which allow calculating the interaction forces of parts for all modes of operation, were improved. Practical value. Use of the

Reliable control using the primary and dual Youla parameterizations

DEFF Research Database (Denmark)

Niemann, Hans Henrik; Stoustrup, J.

2002-01-01

Different aspects of modeling faults in dynamic systems are considered in connection with reliable control (RC). The fault models include models with additive faults, multiplicative faults and structural changes in the models due to faults in the systems. These descriptions are considered...... in connection with reliable control and feedback control with fault rejection. The main emphasis is on fault modeling. A number of fault diagnosis problems, reliable control problems, and feedback control with fault rejection problems are formulated/considered, again, mainly from a fault modeling point of view....... Reliability is introduced by means of the (primary) Youla parameterization of all stabilizing controllers, where an additional loop is closed around a diagnostic signal. In order to quantify the level of reliability, the dual Youla parameterization is introduced which can be used to analyze how large faults...

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.

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.

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)

Reliability assessment of complex electromechanical systems under epistemic uncertainty

International Nuclear Information System (INIS)

Mi, Jinhua; Li, Yan-Feng; Yang, Yuan-Jian; Peng, Weiwen; Huang, Hong-Zhong

2016-01-01

The appearance of macro-engineering and mega-project have led to the increasing complexity of modern electromechanical systems (EMSs). The complexity of the system structure and failure mechanism makes it more difficult for reliability assessment of these systems. Uncertainty, dynamic and nonlinearity characteristics always exist in engineering systems due to the complexity introduced by the changing environments, lack of data and random interference. This paper presents a comprehensive study on the reliability assessment of complex systems. In view of the dynamic characteristics within the system, it makes use of the advantages of the dynamic fault tree (DFT) for characterizing system behaviors. The lifetime of system units can be expressed as bounded closed intervals by incorporating field failures, test data and design expertize. Then the coefficient of variation (COV) method is employed to estimate the parameters of life distributions. An extended probability-box (P-Box) is proposed to convey the present of epistemic uncertainty induced by the incomplete information about the data. By mapping the DFT into an equivalent Bayesian network (BN), relevant reliability parameters and indexes have been calculated. Furthermore, the Monte Carlo (MC) simulation method is utilized to compute the DFT model with consideration of system replacement policy. The results show that this integrated approach is more flexible and effective for assessing the reliability of complex dynamic systems. - Highlights: • A comprehensive study on the reliability assessment of complex system is presented. • An extended probability-box is proposed to convey the present of epistemic uncertainty. • The dynamic fault tree model is built. • Bayesian network and Monte Carlo simulation methods are used. • The reliability assessment of a complex electromechanical system is performed.

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…

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

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

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....

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.

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.

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.

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...

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.

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

Optimal blood glucose level control using dynamic programming based on minimal Bergman model

Science.gov (United States)

Rettian Anggita Sari, Maria; Hartono

2018-03-01

The purpose of this article is to simulate the glucose dynamic and the insulin kinetic of diabetic patient. The model used in this research is a non-linear Minimal Bergman model. Optimal control theory is then applied to formulate the problem in order to determine the optimal dose of insulin in the treatment of diabetes mellitus such that the glucose level is in the normal range for some specific time range. The optimization problem is solved using dynamic programming. The result shows that dynamic programming is quite reliable to represent the interaction between glucose and insulin levels in diabetes mellitus patient.

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.

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.).

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.)

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

A consensus approach for estimating the predictive accuracy of dynamic models in biology.

Science.gov (United States)

Villaverde, Alejandro F; Bongard, Sophia; Mauch, Klaus; Müller, Dirk; Balsa-Canto, Eva; Schmid, Joachim; Banga, Julio R

2015-04-01

Mathematical models that predict the complex dynamic behaviour of cellular networks are fundamental in systems biology, and provide an important basis for biomedical and biotechnological applications. However, obtaining reliable predictions from large-scale dynamic models is commonly a challenging task due to lack of identifiability. The present work addresses this challenge by presenting a methodology for obtaining high-confidence predictions from dynamic models using time-series data. First, to preserve the complex behaviour of the network while reducing the number of estimated parameters, model parameters are combined in sets of meta-parameters, which are obtained from correlations between biochemical reaction rates and between concentrations of the chemical species. Next, an ensemble of models with different parameterizations is constructed and calibrated. Finally, the ensemble is used for assessing the reliability of model predictions by defining a measure of convergence of model outputs (consensus) that is used as an indicator of confidence. We report results of computational tests carried out on a metabolic model of Chinese Hamster Ovary (CHO) cells, which are used for recombinant protein production. Using noisy simulated data, we find that the aggregated ensemble predictions are on average more accurate than the predictions of individual ensemble models. Furthermore, ensemble predictions with high consensus are statistically more accurate than ensemble predictions with large variance. The procedure provides quantitative estimates of the confidence in model predictions and enables the analysis of sufficiently complex networks as required for practical applications. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

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)

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.

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)

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

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.

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...

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.

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.

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.

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.

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

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.

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.

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

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.

Development Of Dynamic Probabilistic Safety Assessment: The Accident Dynamic Simulator (ADS) Tool

International Nuclear Information System (INIS)

Chang, Y.H.; Mosleh, A.; Dang, V.N.

2003-01-01

The development of a dynamic methodology for Probabilistic Safety Assessment (PSA) addresses the complex interactions between the behaviour of technical systems and personnel response in the evolution of accident scenarios. This paper introduces the discrete dynamic event tree, a framework for dynamic PSA, and its implementation in the Accident Dynamic Simulator (ADS) tool. Dynamic event tree tools generate and quantify accident scenarios through coupled simulation models of the plant physical processes, its automatic systems, the equipment reliability, and the human response. The current research on the framework, the ADS tool, and on Human Reliability Analysis issues within dynamic PSA, is discussed. (author)

Development Of Dynamic Probabilistic Safety Assessment: The Accident Dynamic Simulator (ADS) Tool

Energy Technology Data Exchange (ETDEWEB)

Chang, Y.H.; Mosleh, A.; Dang, V.N

2003-03-01

The development of a dynamic methodology for Probabilistic Safety Assessment (PSA) addresses the complex interactions between the behaviour of technical systems and personnel response in the evolution of accident scenarios. This paper introduces the discrete dynamic event tree, a framework for dynamic PSA, and its implementation in the Accident Dynamic Simulator (ADS) tool. Dynamic event tree tools generate and quantify accident scenarios through coupled simulation models of the plant physical processes, its automatic systems, the equipment reliability, and the human response. The current research on the framework, the ADS tool, and on Human Reliability Analysis issues within dynamic PSA, is discussed. (author)

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.

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

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.

Multivariate performance reliability prediction in real-time

International Nuclear Information System (INIS)

Lu, S.; Lu, H.; Kolarik, W.J.

2001-01-01

This paper presents a technique for predicting system performance reliability in real-time considering multiple failure modes. The technique includes on-line multivariate monitoring and forecasting of selected performance measures and conditional performance reliability estimates. The performance measures across time are treated as a multivariate time series. A state-space approach is used to model the multivariate time series. Recursive forecasting is performed by adopting Kalman filtering. The predicted mean vectors and covariance matrix of performance measures are used for the assessment of system survival/reliability with respect to the conditional performance reliability. The technique and modeling protocol discussed in this paper provide a means to forecast and evaluate the performance of an individual system in a dynamic environment in real-time. The paper also presents an example to demonstrate the technique

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.

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.

On-Line Junction Temperature Monitoring of Switching Devices with Dynamic Compact Thermal Models Extracted with Model Order Reduction

Directory of Open Access Journals (Sweden)

Fabio Di Napoli

2017-02-01

Full Text Available Residual lifetime estimation has gained a key point among the techniques that improve the reliability and the efficiency of power converters. The main cause of failures are the junction temperature cycles exhibited by switching devices during their normal operation; therefore, reliable power converter lifetime estimation requires the knowledge of the junction temperature time profile. Since on-line dynamic temperature measurements are extremely difficult, in this work an innovative real-time monitoring strategy is proposed, which is capable of estimating the junction temperature profile from the measurement of the dissipated powers through an accurate and compact thermal model of the whole power module. The equations of this model can be easily implemented inside a FPGA, exploiting the control architecture already present in modern power converters. Experimental results on an IGBT power module demonstrate the reliability of the proposed method.

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.

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.

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

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

A reliability-risk modelling of nuclear rad-waste facilities

International Nuclear Information System (INIS)

Lehmann, P.H.; El-Bassioni, A.A.

1975-01-01

Rad-waste disposal systems of nuclear power sites are designed and operated to collect, delay, contain, and concentrate radioactive wastes from reactor plant processes such that on-site and off-site exposures to radiation are well below permissible limits. To assist the designer in achieving minimum release/exposure goals, a computerized reliability-risk model has been developed to simulate the rad-waste system. The objectives of the model are to furnish a practical tool for quantifying the effects of changes in system configuration, operation, and equipment, and for the identification of weak segments in the system design. Primarily, the model comprises a marriage of system analysis, reliability analysis, and release-risk assessment. Provisions have been included in the model to permit the optimization of the system design subject to constraints on cost and rad-releases. The system analysis phase involves the preparation of a physical and functional description of the rad-waste facility accompanied by the formation of a system tree diagram. The reliability analysis phase embodies the formulation of appropriate reliability models and the collection of model parameters. Release-risk assessment constitutes the analytical basis whereupon further system and reliability analyses may be warranted. Release-risk represents the potential for release of radioactivity and is defined as the product of an element's unreliability at time, t, and the radioactivity available for release in time interval, Δt. A computer code (RARISK) has been written to simulate the tree diagram of the rad-waste system. Reliability and release-risk results have been generated for cases which examined the process flow paths of typical rad-waste systems, the effects of repair and standby, the variations of equipment failure and repair rates, and changes in system configurations. The essential feature of this model is that a complex system like the rad-waste facility can be easily decomposed into its

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....

Reliability analysis using network simulation

International Nuclear Information System (INIS)

Engi, D.

1985-01-01

The models that can be used to provide estimates of the reliability of nuclear power systems operate at many different levels of sophistication. The least-sophisticated models treat failure processes that entail only time-independent phenomena (such as demand failure). More advanced models treat processes that also include time-dependent phenomena such as run failure and possibly repair. However, many of these dynamic models are deficient in some respects because they either disregard the time-dependent phenomena that cannot be expressed in closed-form analytic terms or because they treat these phenomena in quasi-static terms. The next level of modeling requires a dynamic approach that incorporates not only procedures for treating all significant time-dependent phenomena but also procedures for treating these phenomena when they are conditionally linked or characterized by arbitrarily selected probability distributions. The level of sophistication that is required is provided by a dynamic, Monte Carlo modeling approach. A computer code that uses a dynamic, Monte Carlo modeling approach is Q-GERT (Graphical Evaluation and Review Technique - with Queueing), and the present study had demonstrated the feasibility of using Q-GERT for modeling time-dependent, unconditionally and conditionally linked phenomena that are characterized by arbitrarily selected probability distributions

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

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

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.

Quantification of intervertebral displacement with a novel MRI-based modeling technique: Assessing measurement bias and reliability with a porcine spine model.

Science.gov (United States)

Mahato, Niladri K; Montuelle, Stephane; Goubeaux, Craig; Cotton, John; Williams, Susan; Thomas, James; Clark, Brian C

2017-05-01

The purpose of this study was to develop a novel magnetic resonance imaging (MRI)-based modeling technique for measuring intervertebral displacements. Here, we present the measurement bias and reliability of the developmental work using a porcine spine model. Porcine lumbar vertebral segments were fitted in a custom-built apparatus placed within an externally calibrated imaging volume of an open-MRI scanner. The apparatus allowed movement of the vertebrae through pre-assigned magnitudes of sagittal and coronal translation and rotation. The induced displacements were imaged with static (T 1 ) and fast dynamic (2D HYCE S) pulse sequences. These images were imported into animation software, in which these images formed a background 'scene'. Three-dimensional models of vertebrae were created using static axial scans from the specimen and then transferred into the animation environment. In the animation environment, the user manually moved the models (rotoscoping) to perform model-to-'scene' matching to fit the models to their image silhouettes and assigned anatomical joint axes to the motion-segments. The animation protocol quantified the experimental translation and rotation displacements between the vertebral models. Accuracy of the technique was calculated as 'bias' using a linear mixed effects model, average percentage error and root mean square errors. Between-session reliability was examined by computing intra-class correlation coefficients (ICC) and the coefficient of variations (CV). For translation trials, a constant bias (β 0 ) of 0.35 (±0.11) mm was detected for the 2D HYCE S sequence (p=0.01). The model did not demonstrate significant additional bias with each mm increase in experimental translation (β 1 Displacement=0.01mm; p=0.69). Using the T 1 sequence for the same assessments did not significantly change the bias (p>0.05). ICC values for the T 1 and 2D HYCE S pulse sequences were 0.98 and 0.97, respectively. For rotation trials, a constant bias (�

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.

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

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...

Modeling of human operator dynamics in simple manual control utilizing time series analysis. [tracking (position)

Science.gov (United States)

Agarwal, G. C.; Osafo-Charles, F.; Oneill, W. D.; Gottlieb, G. L.

1982-01-01

Time series analysis is applied to model human operator dynamics in pursuit and compensatory tracking modes. The normalized residual criterion is used as a one-step analytical tool to encompass the processes of identification, estimation, and diagnostic checking. A parameter constraining technique is introduced to develop more reliable models of human operator dynamics. The human operator is adequately modeled by a second order dynamic system both in pursuit and compensatory tracking modes. In comparing the data sampling rates, 100 msec between samples is adequate and is shown to provide better results than 200 msec sampling. The residual power spectrum and eigenvalue analysis show that the human operator is not a generator of periodic characteristics.

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.

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.)

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...

A Research Roadmap for Computation-Based Human Reliability Analysis

Energy Technology Data Exchange (ETDEWEB)

Boring, Ronald [Idaho National Lab. (INL), Idaho Falls, ID (United States); Mandelli, Diego [Idaho National Lab. (INL), Idaho Falls, ID (United States); Joe, Jeffrey [Idaho National Lab. (INL), Idaho Falls, ID (United States); Smith, Curtis [Idaho National Lab. (INL), Idaho Falls, ID (United States); Groth, Katrina [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-08-01

The United States (U.S.) Department of Energy (DOE) is sponsoring research through the Light Water Reactor Sustainability (LWRS) program to extend the life of the currently operating fleet of commercial nuclear power plants. The Risk Informed Safety Margin Characterization (RISMC) research pathway within LWRS looks at ways to maintain and improve the safety margins of these plants. The RISMC pathway includes significant developments in the area of thermalhydraulics code modeling and the development of tools to facilitate dynamic probabilistic risk assessment (PRA). PRA is primarily concerned with the risk of hardware systems at the plant; yet, hardware reliability is often secondary in overall risk significance to human errors that can trigger or compound undesirable events at the plant. This report highlights ongoing efforts to develop a computation-based approach to human reliability analysis (HRA). This computation-based approach differs from existing static and dynamic HRA approaches in that it: (i) interfaces with a dynamic computation engine that includes a full scope plant model, and (ii) interfaces with a PRA software toolset. The computation-based HRA approach presented in this report is called the Human Unimodels for Nuclear Technology to Enhance Reliability (HUNTER) and incorporates in a hybrid fashion elements of existing HRA methods to interface with new computational tools developed under the RISMC pathway. The goal of this research effort is to model human performance more accurately than existing approaches, thereby minimizing modeling uncertainty found in current plant risk models.

A Research Roadmap for Computation-Based Human Reliability Analysis

International Nuclear Information System (INIS)

Boring, Ronald; Mandelli, Diego; Joe, Jeffrey; Smith, Curtis; Groth, Katrina

2015-01-01

The United States (U.S.) Department of Energy (DOE) is sponsoring research through the Light Water Reactor Sustainability (LWRS) program to extend the life of the currently operating fleet of commercial nuclear power plants. The Risk Informed Safety Margin Characterization (RISMC) research pathway within LWRS looks at ways to maintain and improve the safety margins of these plants. The RISMC pathway includes significant developments in the area of thermalhydraulics code modeling and the development of tools to facilitate dynamic probabilistic risk assessment (PRA). PRA is primarily concerned with the risk of hardware systems at the plant; yet, hardware reliability is often secondary in overall risk significance to human errors that can trigger or compound undesirable events at the plant. This report highlights ongoing efforts to develop a computation-based approach to human reliability analysis (HRA). This computation-based approach differs from existing static and dynamic HRA approaches in that it: (i) interfaces with a dynamic computation engine that includes a full scope plant model, and (ii) interfaces with a PRA software toolset. The computation-based HRA approach presented in this report is called the Human Unimodels for Nuclear Technology to Enhance Reliability (HUNTER) and incorporates in a hybrid fashion elements of existing HRA methods to interface with new computational tools developed under the RISMC pathway. The goal of this research effort is to model human performance more accurately than existing approaches, thereby minimizing modeling uncertainty found in current plant risk models.

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

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.

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

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....

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.

Modeling capillary bridge dynamics and crack healing between surfaces of nanoscale roughness

Science.gov (United States)

Soylemez, Emrecan; de Boer, Maarten P.

2017-12-01

Capillary bridge formation between adjacent surfaces in humid environments is a ubiquitous phenomenon. It strongly influences tribological performance with respect to adhesion, friction and wear. Only a few studies, however, assess effects due to capillary dynamics. Here we focus on how capillary bridge evolution influences crack healing rates. Experimental results indicated a logarithmic decrease in average crack healing velocity as the energy release rate increases. Our objective is to model that trend. We assume that capillary dynamics involve two mechanisms: capillary bridge growth and subsequently nucleation followed by growth. We show that by incorporating interface roughness details and the presence of an adsorbed water layer, the behavior of capillary force dynamics can be understood quantitatively. We identify three important regimes that control the healing process, namely bridge growth, combined bridge growth and nucleation, and finally bridge nucleation. To fully capture the results, however, the theoretical model for nucleation time required an empirical modification. Our model enables significant insight into capillary bridge dynamics, with a goal of attaining a predictive capability for this important microelectromechanical systems (MEMS) reliability failure mechanism.

Cognitive modeling and dynamic probabilistic simulation of operating crew response to complex system accidents

International Nuclear Information System (INIS)

Chang, Y.H.J.; Mosleh, A.

2007-01-01

This is the last in a series of five papers that discuss the Information Decision and Action in Crew (IDAC) context for human reliability analysis (HRA) and example application. The model is developed to probabilistically predict the responses of the control room operating crew in nuclear power plants during an accident, for use in probabilistic risk assessments (PRA). The operator response spectrum includes cognitive, emotional, and physical activities during the course of an accident. This paper describes a dynamic PRA computer simulation program, accident dynamics simulator (ADS), developed in part to implement the IDAC model. This paper also provides a detailed example of implementing a simpler version of IDAC, compared with the IDAC model discussed in the first four papers of this series, to demonstrate the practicality of integrating a detailed cognitive HRA model within a dynamic PRA framework

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.

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.

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

A system dynamics model for tritium cycle of pulsed fusion reactor

International Nuclear Information System (INIS)

Zhu, Zuolong; Nie, Baojie; Chen, Dehong

2017-01-01

As great challenges and uncertainty exist in achieving steady plasma burning, pulsed plasma burning may be a potential scenario for fusion engineering test reactor, even for fusion DEMOnstration reactor. In order to analyze dynamic tritium inventory and tritium self-sufficiency for pulsed fusion systems, a system dynamics model of tritium cycle was developed on the basis of earlier version of Tritium Analysis program for fusion System (TAS). The model was verified with TRIMO, which was developed by KIT in Germany. Tritium self-sufficiency and dynamic tritium inventory assessment were performed for a typical fusion engineering test reactor. The verification results show that the system dynamics model can be used for tritium cycle analysis of pulsed fusion reactor with sufficient reliability. The assessment results of tritium self-sufficiency indicate that the fusion reactor might only need several hundred gram tritium to startup if achieved high efficient tritium handling ability (Referred ITER: 1 h). And the initial tritium startup inventory in pulsed fusion reactor is determined by the combined influence of pulse length, burn availability, and tritium recycle time. Meanwhile, tritium self-sufficiency can be achieved under the defined condition.

A system dynamics model for tritium cycle of pulsed fusion reactor

Energy Technology Data Exchange (ETDEWEB)

Zhu, Zuolong; Nie, Baojie [Key Laboratory of Neutronics and Radiation Safety, Institute of Nuclear Energy Safety Technology, Chinese Academy of Sciences, Hefei, Anhui, 230031 (China); University of Science and Technology of China, Hefei, Anhui, 230027 (China); Chen, Dehong, E-mail: dehong.chen@fds.org.cn [Key Laboratory of Neutronics and Radiation Safety, Institute of Nuclear Energy Safety Technology, Chinese Academy of Sciences, Hefei, Anhui, 230031 (China)

2017-05-15

As great challenges and uncertainty exist in achieving steady plasma burning, pulsed plasma burning may be a potential scenario for fusion engineering test reactor, even for fusion DEMOnstration reactor. In order to analyze dynamic tritium inventory and tritium self-sufficiency for pulsed fusion systems, a system dynamics model of tritium cycle was developed on the basis of earlier version of Tritium Analysis program for fusion System (TAS). The model was verified with TRIMO, which was developed by KIT in Germany. Tritium self-sufficiency and dynamic tritium inventory assessment were performed for a typical fusion engineering test reactor. The verification results show that the system dynamics model can be used for tritium cycle analysis of pulsed fusion reactor with sufficient reliability. The assessment results of tritium self-sufficiency indicate that the fusion reactor might only need several hundred gram tritium to startup if achieved high efficient tritium handling ability (Referred ITER: 1 h). And the initial tritium startup inventory in pulsed fusion reactor is determined by the combined influence of pulse length, burn availability, and tritium recycle time. Meanwhile, tritium self-sufficiency can be achieved under the defined condition.

Reliability Characteristics of Power Plants

Directory of Open Access Journals (Sweden)

Zbynek Martinek

2017-01-01

Full Text Available This paper describes the phenomenon of reliability of power plants. It gives an explanation of the terms connected with this topic as their proper understanding is important for understanding the relations and equations which model the possible real situations. The reliability phenomenon is analysed using both the exponential distribution and the Weibull distribution. The results of our analysis are specific equations giving information about the characteristics of the power plants, the mean time of operations and the probability of failure-free operation. Equations solved for the Weibull distribution respect the failures as well as the actual operating hours. Thanks to our results, we are able to create a model of dynamic reliability for prediction of future states. It can be useful for improving the current situation of the unit as well as for creating the optimal plan of maintenance and thus have an impact on the overall economics of the operation of these power plants.

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...

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....

Dynamic flowgraph modeling of process and control systems of a nuclear-based hydrogen production plant

Energy Technology Data Exchange (ETDEWEB)

Al-Dabbagh, Ahmad W. [Faculty of Engineering and Applied Science, University of Ontario Institute of Technology, 2000 Simcoe Street North, Oshawa, Ontario (Canada); Lu, Lixuan [Faculty of Energy Systems and Nuclear Science, Faculty of Engineering and Applied Science, University of Ontario Institute of Technology, 2000 Simcoe Street North, Oshawa, Ontario (Canada)

2010-09-15

Modeling and analysis of system reliability facilitate the identification of areas of potential improvement. The Dynamic Flowgraph Methodology (DFM) is an emerging discrete modeling framework that allows for capturing time dependent behaviour, switching logic and multi-state representation of system components. The objective of this research is to demonstrate the process of dynamic flowgraph modeling of a nuclear-based hydrogen production plant with the copper-chlorine (Cu-Cl) cycle. Modeling of the thermochemical process of the Cu-Cl cycle in conjunction with a networked control system proposed for monitoring and control of the process is provided. This forms the basis for future component selection. (author)

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....

Network reliability assessment using a cellular automata approach

International Nuclear Information System (INIS)

Rocco S, Claudio M.; Moreno, Jose Ali

2002-01-01

Two cellular automata (CA) models that evaluate the s-t connectedness and shortest path in a network are presented. CA based algorithms enhance the performance of classical algorithms, since they allow a more reliable and straightforward parallel implementation resulting in a dynamic network evaluation, where changes in the connectivity and/or link costs can readily be incorporated avoiding recalculation from scratch. The paper also demonstrates how these algorithms can be applied for network reliability evaluation (based on Monte-Carlo approach) and for finding s-t path with maximal reliability

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

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.

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)

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.

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.

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.

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

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.

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.

Modeling structured population dynamics using data from unmarked individuals

Science.gov (United States)

Grant, Evan H. Campbell; Zipkin, Elise; Thorson, James T.; See, Kevin; Lynch, Heather J.; Kanno, Yoichiro; Chandler, Richard; Letcher, Benjamin H.; Royle, J. Andrew

2014-01-01

The study of population dynamics requires unbiased, precise estimates of abundance and vital rates that account for the demographic structure inherent in all wildlife and plant populations. Traditionally, these estimates have only been available through approaches that rely on intensive mark–recapture data. We extended recently developed N-mixture models to demonstrate how demographic parameters and abundance can be estimated for structured populations using only stage-structured count data. Our modeling framework can be used to make reliable inferences on abundance as well as recruitment, immigration, stage-specific survival, and detection rates during sampling. We present a range of simulations to illustrate the data requirements, including the number of years and locations necessary for accurate and precise parameter estimates. We apply our modeling framework to a population of northern dusky salamanders (Desmognathus fuscus) in the mid-Atlantic region (USA) and find that the population is unexpectedly declining. Our approach represents a valuable advance in the estimation of population dynamics using multistate data from unmarked individuals and should additionally be useful in the development of integrated models that combine data from intensive (e.g., mark–recapture) and extensive (e.g., counts) data sources.

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.

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.

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.

Efficient finite element modelling for the investigation of the dynamic behaviour of a structure with bolted joints

Science.gov (United States)

Omar, R.; Rani, M. N. Abdul; Yunus, M. A.; Mirza, W. I. I. Wan Iskandar; Zin, M. S. Mohd

2018-04-01

A simple structure with bolted joints consists of the structural components, bolts and nuts. There are several methods to model the structures with bolted joints, however there is no reliable, efficient and economic modelling methods that can accurately predict its dynamics behaviour. Explained in this paper is an investigation that was conducted to obtain an appropriate modelling method for bolted joints. This was carried out by evaluating four different finite element (FE) models of the assembled plates and bolts namely the solid plates-bolts model, plates without bolt model, hybrid plates-bolts model and simplified plates-bolts model. FE modal analysis was conducted for all four initial FE models of the bolted joints. Results of the FE modal analysis were compared with the experimental modal analysis (EMA) results. EMA was performed to extract the natural frequencies and mode shapes of the test physical structure with bolted joints. Evaluation was made by comparing the number of nodes, number of elements, elapsed computer processing unit (CPU) time, and the total percentage of errors of each initial FE model when compared with EMA result. The evaluation showed that the simplified plates-bolts model could most accurately predict the dynamic behaviour of the structure with bolted joints. This study proved that the reliable, efficient and economic modelling of bolted joints, mainly the representation of the bolting, has played a crucial element in ensuring the accuracy of the dynamic behaviour prediction.

When the Jeans Do Not Fit: How Stellar Feedback Drives Stellar Kinematics and Complicates Dynamical Modeling in Low-mass Galaxies

Energy Technology Data Exchange (ETDEWEB)

El-Badry, Kareem; Quataert, Eliot [Department of Astronomy, University of California, Berkeley, CA (United States); Wetzel, Andrew R.; Hopkins, Philip F. [TAPIR, California Institute of Technology, Pasadena, CA (United States); Geha, Marla [Department of Astronomy, Yale University, New Haven, CT (United States); Kereš, Dusan; Chan, T. K. [Department of Physics, Center for Astrophysics and Space Sciences, University of California at San Diego, La Jolla (United States); Faucher-Giguère, Claude-André, E-mail: kelbadry@berkeley.edu [Department of Physics and Astronomy and CIERA, Northwestern University, Evanston, IL (United States)

2017-02-01

In low-mass galaxies, stellar feedback can drive gas outflows that generate non-equilibrium fluctuations in the gravitational potential. Using cosmological zoom-in baryonic simulations from the Feedback in Realistic Environments project, we investigate how these fluctuations affect stellar kinematics and the reliability of Jeans dynamical modeling in low-mass galaxies. We find that stellar velocity dispersion and anisotropy profiles fluctuate significantly over the course of galaxies’ starburst cycles. We therefore predict an observable correlation between star formation rate and stellar kinematics: dwarf galaxies with higher recent star formation rates should have systemically higher stellar velocity dispersions. This prediction provides an observational test of the role of stellar feedback in regulating both stellar and dark-matter densities in dwarf galaxies. We find that Jeans modeling, which treats galaxies as virialized systems in dynamical equilibrium, overestimates a galaxy’s dynamical mass during periods of post-starburst gas outflow and underestimates it during periods of net inflow. Short-timescale potential fluctuations lead to typical errors of ∼20% in dynamical mass estimates, even if full three-dimensional stellar kinematics—including the orbital anisotropy—are known exactly. When orbital anisotropy is not known a priori, typical mass errors arising from non-equilibrium fluctuations in the potential are larger than those arising from the mass-anisotropy degeneracy. However, Jeans modeling alone cannot reliably constrain the orbital anisotropy, and problematically, it often favors anisotropy models that do not reflect the true profile. If galaxies completely lose their gas and cease forming stars, fluctuations in the potential subside, and Jeans modeling becomes much more reliable.

When the Jeans Do Not Fit: How Stellar Feedback Drives Stellar Kinematics and Complicates Dynamical Modeling in Low-mass Galaxies

International Nuclear Information System (INIS)

El-Badry, Kareem; Quataert, Eliot; Wetzel, Andrew R.; Hopkins, Philip F.; Geha, Marla; Kereš, Dusan; Chan, T. K.; Faucher-Giguère, Claude-André

2017-01-01

In low-mass galaxies, stellar feedback can drive gas outflows that generate non-equilibrium fluctuations in the gravitational potential. Using cosmological zoom-in baryonic simulations from the Feedback in Realistic Environments project, we investigate how these fluctuations affect stellar kinematics and the reliability of Jeans dynamical modeling in low-mass galaxies. We find that stellar velocity dispersion and anisotropy profiles fluctuate significantly over the course of galaxies’ starburst cycles. We therefore predict an observable correlation between star formation rate and stellar kinematics: dwarf galaxies with higher recent star formation rates should have systemically higher stellar velocity dispersions. This prediction provides an observational test of the role of stellar feedback in regulating both stellar and dark-matter densities in dwarf galaxies. We find that Jeans modeling, which treats galaxies as virialized systems in dynamical equilibrium, overestimates a galaxy’s dynamical mass during periods of post-starburst gas outflow and underestimates it during periods of net inflow. Short-timescale potential fluctuations lead to typical errors of ∼20% in dynamical mass estimates, even if full three-dimensional stellar kinematics—including the orbital anisotropy—are known exactly. When orbital anisotropy is not known a priori, typical mass errors arising from non-equilibrium fluctuations in the potential are larger than those arising from the mass-anisotropy degeneracy. However, Jeans modeling alone cannot reliably constrain the orbital anisotropy, and problematically, it often favors anisotropy models that do not reflect the true profile. If galaxies completely lose their gas and cease forming stars, fluctuations in the potential subside, and Jeans modeling becomes much more reliable.

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

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

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.

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.

Verification of experimental modal modeling using HDR (Heissdampfreaktor) dynamic test data

International Nuclear Information System (INIS)

Srinivasan, M.G.; Kot, C.A.; Hsieh, B.J.

1983-01-01

Experimental modal modeling involves the determination of the modal parameters of the model of a structure from recorded input-output data from dynamic tests. Though commercial modal analysis algorithms are being widely used in many industries their ability to identify a set of reliable modal parameters of an as-built nuclear power plant structure has not been systematically verified. This paper describes the effort to verify MODAL-PLUS, a widely used modal analysis code, using recorded data from the dynamic tests performed on the reactor building of the Heissdampfreaktor, situated near Frankfurt, Federal Republic of Germany. In the series of dynamic tests on HDR in 1979, the reactor building was subjected to forced vibrations from different types and levels of dynamic excitations. Two sets of HDR containment building input-output data were chosen for MODAL-PLUS analyses. To reduce the influence of nonlinear behavior on the results, these sets were chosen so that the levels of excitation are relatively low and about the same in the two sets. The attempted verification was only partially successful in that only one modal model, with a limited range of validity, could be synthesized and in that the goodness of fit could be verified only in this limited range

Optimization of reliability centered predictive maintenance scheme for inertial navigation system

International Nuclear Information System (INIS)

Jiang, Xiuhong; Duan, Fuhai; Tian, Heng; Wei, Xuedong

2015-01-01

The goal of this study is to propose a reliability centered predictive maintenance scheme for a complex structure Inertial Navigation System (INS) with several redundant components. GO Methodology is applied to build the INS reliability analysis model—GO chart. Components Remaining Useful Life (RUL) and system reliability are updated dynamically based on the combination of components lifetime distribution function, stress samples, and the system GO chart. Considering the redundant design in INS, maintenance time is based not only on components RUL, but also (and mainly) on the timing of when system reliability fails to meet the set threshold. The definition of components maintenance priority balances three factors: components importance to system, risk degree, and detection difficulty. Maintenance Priority Number (MPN) is introduced, which may provide quantitative maintenance priority results for all components. A maintenance unit time cost model is built based on components MPN, components RUL predictive model and maintenance intervals for the optimization of maintenance scope. The proposed scheme can be applied to serve as the reference for INS maintenance. Finally, three numerical examples prove the proposed predictive maintenance scheme is feasible and effective. - Highlights: • A dynamic PdM with a rolling horizon is proposed for INS with redundant components. • GO Methodology is applied to build the system reliability analysis model. • A concept of MPN is proposed to quantify the maintenance sequence of components. • An optimization model is built to select the optimal group of maintenance components. • The optimization goal is minimizing the cost of maintaining system reliability

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...

A Topology Control Strategy with Reliability Assurance for Satellite Cluster Networks in Earth Observation.

Science.gov (United States)

Chen, Qing; Zhang, Jinxiu; Hu, Ze

2017-02-23

This article investigates the dynamic topology control problemof satellite cluster networks (SCNs) in Earth observation (EO) missions by applying a novel metric of stability for inter-satellite links (ISLs). The properties of the periodicity and predictability of satellites' relative position are involved in the link cost metric which is to give a selection criterion for choosing the most reliable data routing paths. Also, a cooperative work model with reliability is proposed for the situation of emergency EO missions. Based on the link cost metric and the proposed reliability model, a reliability assurance topology control algorithm and its corresponding dynamic topology control (RAT) strategy are established to maximize the stability of data transmission in the SCNs. The SCNs scenario is tested through some numeric simulations of the topology stability of average topology lifetime and average packet loss rate. Simulation results show that the proposed reliable strategy applied in SCNs significantly improves the data transmission performance and prolongs the average topology lifetime.

A Topology Control Strategy with Reliability Assurance for Satellite Cluster Networks in Earth Observation

Directory of Open Access Journals (Sweden)

Qing Chen

2017-02-01

Full Text Available This article investigates the dynamic topology control problemof satellite cluster networks (SCNs in Earth observation (EO missions by applying a novel metric of stability for inter-satellite links (ISLs. The properties of the periodicity and predictability of satellites’ relative position are involved in the link cost metric which is to give a selection criterion for choosing the most reliable data routing paths. Also, a cooperative work model with reliability is proposed for the situation of emergency EO missions. Based on the link cost metric and the proposed reliability model, a reliability assurance topology control algorithm and its corresponding dynamic topology control (RAT strategy are established to maximize the stability of data transmission in the SCNs. The SCNs scenario is tested through some numeric simulations of the topology stability of average topology lifetime and average packet loss rate. Simulation results show that the proposed reliable strategy applied in SCNs significantly improves the data transmission performance and prolongs the average topology lifetime.

Dynamic modeling and sensitivity analysis of solar thermal energy conversion systems

Science.gov (United States)

Hamilton, C. L.

1977-01-01

Since the energy input to solar thermal conversion systems is both time variant and probabilistic, it is unlikely that simple steady-state methods for estimating lifetime performance will provide satisfactory results. The work described here uses dynamic modeling to begin identifying what must be known about input radiation and system dynamic characteristics to estimate performance reliably. Daily operation of two conceptual solar energy systems was simulated under varying operating strategies with time-dependent radiation intensity ranging from smooth input of several magnitudes to input of constant total energy whose intensity oscillated with periods from 1/4 hour to 6 hours. Integrated daily system output and efficiency were functions of both level and dynamic characteristics of insolation. Sensitivity of output to changes in total input was greater than one.

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.

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

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...

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.

Unavailability Analysis of Dynamic Systems of which the Configuration Changes with Time

International Nuclear Information System (INIS)

Shin, Seung Ki; Seong, Poong Hyun

2011-01-01

A dynamic system has a state at any given time which can be represented by a point in an appropriate state space and it is much more difficult to estimate the reliability or availability than a static system. As the classic fault tree cannot be used to model the time requirements, dynamic fault tree methods have been developed for the analysis of dynamic systems. They are time-dependent fault trees, so they can capture the dynamic behaviors of the system failure mechanisms. There exist two types of dynamic fault trees to analyze various dynamic properties of the system failure mechanisms. One dynamic fault tree handles failure mechanisms composed of sequence-dependent events using dynamic gates and the other one handles failure mechanisms of which the system configuration changes with time using house event matrix. In this paper, the second dynamic failure mechanism is assessed using a reliability graph with general gates (RGGG) which is an extended reliability graph model and allows more intuitive modeling of target systems compared to the fault tree. In order for the RGGG method to analyze such dynamic failure mechanism, a novel concept of reliability matrix for the RGGG is introduced and Bayesian Networks are used to quantify the modeled RGGG. The proposed method provides much easier way to model dynamic systems and understand the actual structure of the system compared to the dynamic fault tree with house events

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...

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

Future of structural reliability methodology in nuclear power plant technology

Energy Technology Data Exchange (ETDEWEB)

Schueeller, G I [Technische Univ. Muenchen (Germany, F.R.); Kafka, P [Gesellschaft fuer Reaktorsicherheit m.b.H. (GRS), Garching (Germany, F.R.)

1978-10-01

This paper presents the authors' personal view as to which areas of structural reliability in nuclear power plant design need most urgently to be advanced. Aspects of simulation modeling, design rules, codification and specification of reliability, system analysis, probabilistic structural dynamics, rare events and particularly the interaction of systems and structural reliability are discussed. As an example, some considerations of the interaction effects between the protective systems and the pressure vessel are stated. The paper concludes with recommendation for further research.

Reliability importance analysis of Markovian systems at steady state using perturbation analysis

Energy Technology Data Exchange (ETDEWEB)

Phuc Do Van [Institut Charles Delaunay - FRE CNRS 2848, Systems Modeling and Dependability Group, Universite de technologie de Troyes, 12, rue Marie Curie, BP 2060-10010 Troyes cedex (France); Barros, Anne [Institut Charles Delaunay - FRE CNRS 2848, Systems Modeling and Dependability Group, Universite de technologie de Troyes, 12, rue Marie Curie, BP 2060-10010 Troyes cedex (France)], E-mail: anne.barros@utt.fr; Berenguer, Christophe [Institut Charles Delaunay - FRE CNRS 2848, Systems Modeling and Dependability Group, Universite de technologie de Troyes, 12, rue Marie Curie, BP 2060-10010 Troyes cedex (France)

2008-11-15

Sensitivity analysis has been primarily defined for static systems, i.e. systems described by combinatorial reliability models (fault or event trees). Several structural and probabilistic measures have been proposed to assess the components importance. For dynamic systems including inter-component and functional dependencies (cold spare, shared load, shared resources, etc.), and described by Markov models or, more generally, by discrete events dynamic systems models, the problem of sensitivity analysis remains widely open. In this paper, the perturbation method is used to estimate an importance factor, called multi-directional sensitivity measure, in the framework of Markovian systems. Some numerical examples are introduced to show why this method offers a promising tool for steady-state sensitivity analysis of Markov processes in reliability studies.

Reliability importance analysis of Markovian systems at steady state using perturbation analysis

International Nuclear Information System (INIS)

Phuc Do Van; Barros, Anne; Berenguer, Christophe

2008-01-01

Sensitivity analysis has been primarily defined for static systems, i.e. systems described by combinatorial reliability models (fault or event trees). Several structural and probabilistic measures have been proposed to assess the components importance. For dynamic systems including inter-component and functional dependencies (cold spare, shared load, shared resources, etc.), and described by Markov models or, more generally, by discrete events dynamic systems models, the problem of sensitivity analysis remains widely open. In this paper, the perturbation method is used to estimate an importance factor, called multi-directional sensitivity measure, in the framework of Markovian systems. Some numerical examples are introduced to show why this method offers a promising tool for steady-state sensitivity analysis of Markov processes in reliability studies

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

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...

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.

An improved cellular automata model for train operation simulation with dynamic acceleration

Science.gov (United States)

Li, Wen-Jun; Nie, Lei

2018-03-01

Urban rail transit plays an important role in the urban public traffic because of its advantages of fast speed, large transport capacity, high safety, reliability and low pollution. This study proposes an improved cellular automaton (CA) model by considering the dynamic characteristic of the train acceleration to analyze the energy consumption and train running time. Constructing an effective model for calculating energy consumption to aid train operation improvement is the basis for studying and analyzing energy-saving measures for urban rail transit system operation.

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

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.

Multi-valley effective mass theory for device-level modeling of open quantum dynamics

Science.gov (United States)

Jacobson, N. Tobias; Baczewski, Andrew D.; Frees, Adam; Gamble, John King; Montano, Ines; Moussa, Jonathan E.; Muller, Richard P.; Nielsen, Erik

2015-03-01

Simple models for semiconductor-based quantum information processors can provide useful qualitative descriptions of device behavior. However, as experimental implementations have matured, more specific guidance from theory has become necessary, particularly in the form of quantitatively reliable yet computationally efficient modeling. Besides modeling static device properties, improved characterization of noisy gate operations requires a more sophisticated description of device dynamics. Making use of recent developments in multi-valley effective mass theory, we discuss device-level simulations of the open system quantum dynamics of a qubit interacting with phonons and other noise sources. Sandia is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the US Department of Energy National Nuclear Security Administration under Contract No. DE-AC04-94AL85000.

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

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...

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

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

A software prototype for assessing the reliability of a concrete bridge superstructure subjected to chloride-induced reinforcement corrosion

DEFF Research Database (Denmark)

Schneider, Ronald; Thöns, Sebastian; Fischer, Johannes

2014-01-01

state of the box girder and a structural model for evaluating the overall system reliability. The condition model is based on a dynamic Bayesian network (DBN) model which considers the spatial variation of the corrosion process. Inspection data are included in the calculation of the system reliability...

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.

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

System Reliability Engineering

International Nuclear Information System (INIS)

Lim, Tae Jin

2005-02-01

This book tells of reliability engineering, which includes quality and reliability, reliability data, importance of reliability engineering, reliability and measure, the poisson process like goodness of fit test and the poisson arrival model, reliability estimation like exponential distribution, reliability of systems, availability, preventive maintenance such as replacement policies, minimal repair policy, shock models, spares, group maintenance and periodic inspection, analysis of common cause failure, and analysis model of repair effect.

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.

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

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

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.

Modelling Anopheles gambiae s.s. Population Dynamics with Temperature- and Age-Dependent Survival

Directory of Open Access Journals (Sweden)

Céline Christiansen-Jucht

2015-05-01

Full Text Available Climate change and global warming are emerging as important threats to human health, particularly through the potential increase in vector- and water-borne diseases. Environmental variables are known to affect substantially the population dynamics and abundance of the poikilothermic vectors of disease, but the exact extent of this sensitivity is not well established. Focusing on malaria and its main vector in Africa, Anopheles gambiae sensu stricto, we present a set of novel mathematical models of climate-driven mosquito population dynamics motivated by experimental data suggesting that in An. gambiae, mortality is temperature and age dependent. We compared the performance of these models to that of a “standard” model ignoring age dependence. We used a longitudinal dataset of vector abundance over 36 months in sub-Saharan Africa for comparison between models that incorporate age dependence and one that does not, and observe that age-dependent models consistently fitted the data better than the reference model. This highlights that including age dependence in the vector component of mosquito-borne disease models may be important to predict more reliably disease transmission dynamics. Further data and studies are needed to enable improved fitting, leading to more accurate and informative model predictions for the An. gambiae malaria vector as well as for other disease vectors.

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

Cracked rotors. A survey on static and dynamic behaviour including modelling and diagnosis

Energy Technology Data Exchange (ETDEWEB)

Bachschmid, Nicolo; Pennacchi, Paolo; Tanzi, Ezio [Politecnico di Milano (Italy). Dept. of Mechanical Engineering

2010-07-01

Cracks can develop in rotating shafts and can propagate to relevant depths without affecting consistently the normal operating conditions of the shaft. In order to avoid catastrophic failures, accurate vibration analyses have to be performed for crack detection. The identification of the crack location and depth is possible by means of a model based diagnostic approach, provided that the model of the crack and the model of the cracked shaft dynamical behavior are accurate and reliable. This monograph shows the typical dynamical behavior of cracked shafts and presents tests for detecting cracks. The book describes how to model cracks, how to simulate the dynamical behavior of cracked shaft, and compares the corresponding numerical with experimental results. All effects of cracks on the vibrations of rotating shafts are analyzed, and some results of a numerical sensitivity analysis of the vibrations to the presence and severity of the crack are shown. Finally the book describes some crack identification procedures and shows some results in model based crack identification in position and depth. The book is useful for higher university courses in mechanical and energetic engineering, but also for skilled technical people employed in power generation industries. (orig.)

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.

A New Model of Stopping Sight Distance of Curve Braking Based on Vehicle Dynamics

Directory of Open Access Journals (Sweden)

Rong-xia Xia

2016-01-01

Full Text Available Compared with straight-line braking, cornering brake has longer braking distance and poorer stability. Therefore, drivers are more prone to making mistakes. The braking process and the dynamics of vehicles in emergency situations on curves were analyzed. A biaxial four-wheel vehicle was simplified to a single model. Considering the braking process, dynamics, force distribution, and stability, a stopping sight distance of the curve braking calculation model was built. Then a driver-vehicle-road simulation platform was built using multibody dynamic software. The vehicle test of brake-in-turn was realized in this platform. The comparison of experimental and calculated values verified the reliability of the computational model. Eventually, the experimental values and calculated values were compared with the stopping sight distance recommended by the Highway Route Design Specification (JTGD20-2006; the current specification of stopping sight distance does not apply to cornering brake sight distance requirements. In this paper, the general values and limits of the curve stopping sight distance are presented.

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 ...

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

Modeling long-term dynamics of electricity markets

International Nuclear Information System (INIS)

Olsina, Fernando; Garces, Francisco; Haubrich, H.-J.

2006-01-01

In the last decade, many countries have restructured their electricity industries by introducing competition in their power generation sectors. Although some restructuring has been regarded as successful, the short experience accumulated with liberalized power markets does not allow making any founded assertion about their long-term behavior. Long-term prices and long-term supply reliability are now center of interest. This concerns firms considering investments in generation capacity and regulatory authorities interested in assuring the long-term supply adequacy and the stability of power markets. In order to gain significant insight into the long-term behavior of liberalized power markets, in this paper, a simulation model based on system dynamics is proposed and the underlying mathematical formulations extensively discussed. Unlike classical market models based on the assumption that market outcomes replicate the results of a centrally made optimization, the approach presented here focuses on replicating the system structure of power markets and the logic of relationships among system components in order to derive its dynamical response. The simulations suggest that there might be serious problems to adjust early enough the generation capacity necessary to maintain stable reserve margins, and consequently, stable long-term price levels. Because of feedback loops embedded in the structure of power markets and the existence of some time lags, the long-term market development might exhibit a quite volatile behavior. By varying some exogenous inputs, a sensitivity analysis is carried out to assess the influence of these factors on the long-run market dynamics

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

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.

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

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

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).

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.

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

Photoinduced charge-order melting dynamics in a one-dimensional interacting Holstein model

Science.gov (United States)

Hashimoto, Hiroshi; Ishihara, Sumio

2017-07-01

Transient quantum dynamics in an interacting fermion-phonon system are investigated with a focus on a charge order (CO) melting after a short optical-pulse irradiation and the roles of the quantum phonons in the transient dynamics. A spinless-fermion model in a one-dimensional chain coupled with local phonons is analyzed numerically. The infinite time-evolving block decimation algorithm is adopted as a reliable numerical method for one-dimensional quantum many-body systems. Numerical results for the photoinduced CO melting dynamics without phonons are well interpreted by the soliton picture for the CO domains. This interpretation is confirmed by numerical simulation of an artificial local excitation and the classical soliton model. In the case of large phonon frequencies corresponding to the antiadiabatic condition, CO melting is induced by propagations of the polaronic solitons with the renormalized soliton velocity. On the other hand, in the case of small phonon frequencies corresponding to the adiabatic condition, the first stage of the CO melting dynamics occurs due to the energy transfer from the fermionic to phononic systems, and the second stage is brought about by the soliton motions around the bottom of the soliton band. The analyses provide a standard reference for photoinduced CO melting dynamics in one-dimensional many-body quantum systems.

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.

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

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...

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

Automated chemical kinetic modeling via hybrid reactive molecular dynamics and quantum chemistry simulations.

Science.gov (United States)

Döntgen, Malte; Schmalz, Felix; Kopp, Wassja A; Kröger, Leif C; Leonhard, Kai

2018-06-13

An automated scheme for obtaining chemical kinetic models from scratch using reactive molecular dynamics and quantum chemistry simulations is presented. This methodology combines the phase space sampling of reactive molecular dynamics with the thermochemistry and kinetics prediction capabilities of quantum mechanics. This scheme provides the NASA polynomial and modified Arrhenius equation parameters for all species and reactions that are observed during the simulation and supplies them in the ChemKin format. The ab initio level of theory for predictions is easily exchangeable and the presently used G3MP2 level of theory is found to reliably reproduce hydrogen and methane oxidation thermochemistry and kinetics data. Chemical kinetic models obtained with this approach are ready-to-use for, e.g., ignition delay time simulations, as shown for hydrogen combustion. The presented extension of the ChemTraYzer approach can be used as a basis for methodologically advancing chemical kinetic modeling schemes and as a black-box approach to generate chemical kinetic models.

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

Dynamics of aesthetic appreciation

Science.gov (United States)

Carbon, Claus-Christian

2012-03-01

Aesthetic appreciation is a complex cognitive processing with inherent aspects of cold as well as hot cognition. Research from the last decades of empirical has shown that evaluations of aesthetic appreciation are highly reliable. Most frequently, facial attractiveness was used as the corner case for investigating aesthetic appreciation. Evaluating facial attractiveness shows indeed high internal consistencies and impressively high inter-rater reliabilities, even across cultures. Although this indicates general and stable mechanisms underlying aesthetic appreciation, it is also obvious that our taste for specific objects changes dynamically. Aesthetic appreciation on artificial object categories, such as fashion, design or art is inherently very dynamic. Gaining insights into the cognitive mechanisms that trigger and enable corresponding changes of aesthetic appreciation is of particular interest for research as this will provide possibilities to modeling aesthetic appreciation for longer durations and from a dynamic perspective. The present paper refers to a recent two-step model ("the dynamical two-step-model of aesthetic appreciation"), dynamically adapting itself, which accounts for typical dynamics of aesthetic appreciation found in different research areas such as art history, philosophy and psychology. The first step assumes singular creative sources creating and establishing innovative material towards which, in a second step, people adapt by integrating it into their visual habits. This inherently leads to dynamic changes of the beholders' aesthetic appreciation.

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...

Advantages of a Dynamic RGGG Method in Qualitative and Quantitative Analysis

International Nuclear Information System (INIS)

Shin, Seung Ki; Seong, Poong Hyun

2009-01-01

Various researches have been conducted in order to analyze dynamic interactions among components and process variables in nuclear power plants which cannot be handled by static reliability analysis methods such as conventional fault tree and event tree techniques. A dynamic reliability graph with general gates (RGGG) method was proposed for an intuitive modeling of dynamic systems and it enables one to easily analyze huge and complex systems. In this paper, advantages of the dynamic RGGG method are assessed through two stages: system modeling and quantitative analysis. And then a software tool for dynamic RGGG method is introduced and an application to a real dynamic system is accompanied

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)

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

Numerical modeling of local scour around hydraulic structure in sandy beds by dynamic mesh method

Science.gov (United States)

Fan, Fei; Liang, Bingchen; Bai, Yuchuan; Zhu, Zhixia; Zhu, Yanjun

2017-10-01

Local scour, a non-negligible factor in hydraulic engineering, endangers the safety of hydraulic structures. In this work, a numerical model for simulating local scour was constructed, based on the open source code computational fluid dynamics model OpenFOAM. We consider both the bedload and suspended load sediment transport in the scour model and adopt the dynamic mesh method to simulate the evolution of the bed elevation. We use the finite area method to project data between the three-dimensional flow model and the two-dimensional (2D) scour model. We also improved the 2D sand slide method and added it to the scour model to correct the bed bathymetry when the bed slope angle exceeds the angle of repose. Moreover, to validate our scour model, we conducted and compared the results of three experiments with those of the developed model. The validation results show that our developed model can reliably simulate local scour.

Data-driven reverse engineering of signaling pathways using ensembles of dynamic models.

Directory of Open Access Journals (Sweden)

David Henriques

2017-02-01

Full Text Available Despite significant efforts and remarkable progress, the inference of signaling networks from experimental data remains very challenging. The problem is particularly difficult when the objective is to obtain a dynamic model capable of predicting the effect of novel perturbations not considered during model training. The problem is ill-posed due to the nonlinear nature of these systems, the fact that only a fraction of the involved proteins and their post-translational modifications can be measured, and limitations on the technologies used for growing cells in vitro, perturbing them, and measuring their variations. As a consequence, there is a pervasive lack of identifiability. To overcome these issues, we present a methodology called SELDOM (enSEmbLe of Dynamic lOgic-based Models, which builds an ensemble of logic-based dynamic models, trains them to experimental data, and combines their individual simulations into an ensemble prediction. It also includes a model reduction step to prune spurious interactions and mitigate overfitting. SELDOM is a data-driven method, in the sense that it does not require any prior knowledge of the system: the interaction networks that act as scaffolds for the dynamic models are inferred from data using mutual information. We have tested SELDOM on a number of experimental and in silico signal transduction case-studies, including the recent HPN-DREAM breast cancer challenge. We found that its performance is highly competitive compared to state-of-the-art methods for the purpose of recovering network topology. More importantly, the utility of SELDOM goes beyond basic network inference (i.e. uncovering static interaction networks: it builds dynamic (based on ordinary differential equation models, which can be used for mechanistic interpretations and reliable dynamic predictions in new experimental conditions (i.e. not used in the training. For this task, SELDOM's ensemble prediction is not only consistently better

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.

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

An application of the ESD framework to the probabilistic risk assessment of dynamic systems

International Nuclear Information System (INIS)

Swaminathan, S.; Smidts, Carol

2000-01-01

Dynamic reliability is the probabilistic study of man-machine-software systems affected by an underlying physical process. The theory of probabilistic dynamics established that dynamic reliability methodologies are essentially semi-Markovian frameworks and can be expressed by an extension of the Chapman-Kolmogorov equation. The mathematical complexity associated with the assessment of dynamic systems' behaviour can be rather overwhelming for real life size systems. This is due to the fact that dynamic methodologies emphasize a component based representation rather than the sequence based representation used in the traditional Event Tree/Fault Tree framework or in the original Event Sequence Diagram (ESD) Framework. An extension of the ESD framework was proposed that facilitates capture of dynamic situations. The modeling framework is composed of events, gates, conditions, competitions and constraints which express many of the dynamic situations encountered in the evolution of accidents. The following paper illustrates an application of this extended ESD framework on a complex dynamic application. The problem at hand is an extension of a problem extensively studied in the validation of dynamic reliability algorithms, a simplified model of the fast reactor Europa. A discussion on how ESDs can help in guiding dynamic reliability simulations as well as aggregating and binning the numerous scenarios generated by dynamic reliability algorithms is provided.(author)

A 2-D process-based model for suspended sediment dynamics: a first step towards ecological modeling

Science.gov (United States)

Achete, F. M.; van der Wegen, M.; Roelvink, D.; Jaffe, B.

2015-06-01

In estuaries suspended sediment concentration (SSC) is one of the most important contributors to turbidity, which influences habitat conditions and ecological functions of the system. Sediment dynamics differs depending on sediment supply and hydrodynamic forcing conditions that vary over space and over time. A robust sediment transport model is a first step in developing a chain of models enabling simulations of contaminants, phytoplankton and habitat conditions. This works aims to determine turbidity levels in the complex-geometry delta of the San Francisco estuary using a process-based approach (Delft3D Flexible Mesh software). Our approach includes a detailed calibration against measured SSC levels, a sensitivity analysis on model parameters and the determination of a yearly sediment budget as well as an assessment of model results in terms of turbidity levels for a single year, water year (WY) 2011. Model results show that our process-based approach is a valuable tool in assessing sediment dynamics and their related ecological parameters over a range of spatial and temporal scales. The model may act as the base model for a chain of ecological models assessing the impact of climate change and management scenarios. Here we present a modeling approach that, with limited data, produces reliable predictions and can be useful for estuaries without a large amount of processes data.

A 2-D process-based model for suspended sediment dynamics: A first step towards ecological modeling

Science.gov (United States)

Achete, F. M.; van der Wegen, M.; Roelvink, D.; Jaffe, B.

2015-01-01

In estuaries suspended sediment concentration (SSC) is one of the most important contributors to turbidity, which influences habitat conditions and ecological functions of the system. Sediment dynamics differs depending on sediment supply and hydrodynamic forcing conditions that vary over space and over time. A robust sediment transport model is a first step in developing a chain of models enabling simulations of contaminants, phytoplankton and habitat conditions. This works aims to determine turbidity levels in the complex-geometry delta of the San Francisco estuary using a process-based approach (Delft3D Flexible Mesh software). Our approach includes a detailed calibration against measured SSC levels, a sensitivity analysis on model parameters and the determination of a yearly sediment budget as well as an assessment of model results in terms of turbidity levels for a single year, water year (WY) 2011. Model results show that our process-based approach is a valuable tool in assessing sediment dynamics and their related ecological parameters over a range of spatial and temporal scales. The model may act as the base model for a chain of ecological models assessing the impact of climate change and management scenarios. Here we present a modeling approach that, with limited data, produces reliable predictions and can be useful for estuaries without a large amount of processes data.

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...

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...

Modeling the influence of polls on elections: a population dynamics approach

Energy Technology Data Exchange (ETDEWEB)

Hyman, James M [Los Alamos National Laboratory; Restrepo, Juan M [UNIV OF ARIZONA; Rael, Rosalyn C [UNIV OF ARIZONA

2009-01-01

We propose a population dynamics model for quantifying the effects of polling data on the outcome of multi-party elections decided by a majority-rule voting process. We divide the population into two groups: committed voters impervious to polling data, and susceptible voters whose decision to vote is influenced by data, depending on its reliability. This population-based approach to modeling the process sidesteps the problem of upscaling models based upon the choices made by individuals. We find releasing poll data is not advantageous to leading candidates, but it can be exploited by those closely trailing. The analysis identifies the particular type of voting impetus at play in different stages of an election and could help strategists optimize their influence on susceptible voters.

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.

New modelling strategy for IRIS dynamic response simulation

International Nuclear Information System (INIS)

Cammi, A.; Ricotti, M. E.; Casella, F.; Schiavo, F.

2004-01-01

The pressurized light water cooled, medium power (1000 MWt) IRIS (International Reactor Innovative and Secure) has been under development for four years by an international consortium of over 21 organizations from ten countries. The plant conceptual design was completed in 2001 and the preliminary design is nearing completion. The pre-application licensing process with NRC started in October, 2002 and IRIS is one of the designs considered by US utilities as part of the ESP (Early Site Permit) process. In this paper the development of an adequate modeling and simulation tool for Dynamics and Control tasks is presented. The key features of the developed simulator are: a) Modularity: the system model is built by connecting the models of its components, which are written independently of their boundary conditions; b) Openness: the code of each component model is clearly readable and close to the original equations and easily customised by the experienced user; c) Efficiency: the simulation code is fast; d) Tool support: the simulation tool is based on reliable, tested and well-documented software. To achieve these objectives, the Modelica language was used as a basis for the development of the simulator. The Modelica language is the results of recent advances in the field of object-oriented, multi-physics, dynamic system modelling. The language definition is open-source and it has already been successfully adopted in several industrial fields. To provide the required capabilities for the analysis, specific models for nuclear reactor components have been developed, to be applied for the dynamic simulation of the IRIS integral reactor, albeit keeping general validity for PWR plants. The following Modelica models have been written to satisfy the IRIS modelling requirements and are presented in this paper: neutronics point kinetic, fuel heat transfer, control rods model, including the innovative internal drive mechanism type, and a once-through type steam generator, thus

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.

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.

System Dynamics Modeling for Emergency Operating System Resilience

Energy Technology Data Exchange (ETDEWEB)

Eng, Ang Wei; Kim, Jong Hyun [KEPCO International Nuclear Graduate School, Ulsan (Korea, Republic of)

2014-10-15

The purpose of this paper is to present a causal model which explain human error cause-effect relationships of emergency operating system (EOS) by using system dynamics (SD) approach. The causal model will further quantified by analyzes nuclear power plant incidents/accidents data in Korea for simulation modeling. Emergency Operating System (EOS) is generally defined as a system which consists personnel, human-machine interface and procedures; and how these components interact and coordinate to respond to an incident or accident. Understanding the behavior of EOS especially personnel behavior and the factors influencing it during accident will contribute in human reliability evaluation. Human Reliability Analysis (HRA) is a method which assesses how human decisions and actions affect to system risk and further used to reduce the human errors probability. There are many HRA method used performance influencing factors (PIFs) to identify the causes of human errors. However, these methods have several limitations. In HRA, PIFs are assumed independent each other and relationship between them are not been study. Through the SD simulation, users able to simulate various situation of nuclear power plant respond to emergency from human and organizational aspects. The simulation also provides users a comprehensive view on how to improve the safety in plants. This paper presents a causal model that explained cause-effect relationships of EOS human. Through SD simulation, users able to identify the main contribution of human error easily. Users can also use SD simulation to predict when and how a human error occurs over time. In future work, the SD model can be expanded more on low level factors. The relationship within low level factors can investigated by using correlation method and further included in the model. This can enables users to study more detailed human error cause-effect relationships and the behavior of EOS. Another improvement can be made is on EOS factors

System Dynamics Modeling for Emergency Operating System Resilience

International Nuclear Information System (INIS)

Eng, Ang Wei; Kim, Jong Hyun

2014-01-01

The purpose of this paper is to present a causal model which explain human error cause-effect relationships of emergency operating system (EOS) by using system dynamics (SD) approach. The causal model will further quantified by analyzes nuclear power plant incidents/accidents data in Korea for simulation modeling. Emergency Operating System (EOS) is generally defined as a system which consists personnel, human-machine interface and procedures; and how these components interact and coordinate to respond to an incident or accident. Understanding the behavior of EOS especially personnel behavior and the factors influencing it during accident will contribute in human reliability evaluation. Human Reliability Analysis (HRA) is a method which assesses how human decisions and actions affect to system risk and further used to reduce the human errors probability. There are many HRA method used performance influencing factors (PIFs) to identify the causes of human errors. However, these methods have several limitations. In HRA, PIFs are assumed independent each other and relationship between them are not been study. Through the SD simulation, users able to simulate various situation of nuclear power plant respond to emergency from human and organizational aspects. The simulation also provides users a comprehensive view on how to improve the safety in plants. This paper presents a causal model that explained cause-effect relationships of EOS human. Through SD simulation, users able to identify the main contribution of human error easily. Users can also use SD simulation to predict when and how a human error occurs over time. In future work, the SD model can be expanded more on low level factors. The relationship within low level factors can investigated by using correlation method and further included in the model. This can enables users to study more detailed human error cause-effect relationships and the behavior of EOS. Another improvement can be made is on EOS factors

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.

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

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....

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.

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.

Estimating spatio-temporal dynamics of stream total phosphate concentration by soft computing techniques.

Science.gov (United States)

Chang, Fi-John; Chen, Pin-An; Chang, Li-Chiu; Tsai, Yu-Hsuan

2016-08-15

This study attempts to model the spatio-temporal dynamics of total phosphate (TP) concentrations along a river for effective hydro-environmental management. We propose a systematical modeling scheme (SMS), which is an ingenious modeling process equipped with a dynamic neural network and three refined statistical methods, for reliably predicting the TP concentrations along a river simultaneously. Two different types of artificial neural network (BPNN-static neural network; NARX network-dynamic neural network) are constructed in modeling the dynamic system. The Dahan River in Taiwan is used as a study case, where ten-year seasonal water quality data collected at seven monitoring stations along the river are used for model training and validation. Results demonstrate that the NARX network can suitably capture the important dynamic features and remarkably outperforms the BPNN model, and the SMS can effectively identify key input factors, suitably overcome data scarcity, significantly increase model reliability, satisfactorily estimate site-specific TP concentration at seven monitoring stations simultaneously, and adequately reconstruct seasonal TP data into a monthly scale. The proposed SMS can reliably model the dynamic spatio-temporal water pollution variation in a river system for missing, hazardous or costly data of interest. Copyright © 2016 Elsevier B.V. All rights reserved.

Dynamic Variables Fail to Predict Fluid Responsiveness in an Animal Model With Pericardial Effusion.

Science.gov (United States)

Broch, Ole; Renner, Jochen; Meybohm, Patrick; Albrecht, Martin; Höcker, Jan; Haneya, Assad; Steinfath, Markus; Bein, Berthold; Gruenewald, Matthias

2016-10-01

The reliability of dynamic and volumetric variables of fluid responsiveness in the presence of pericardial effusion is still elusive. The aim of the present study was to investigate their predictive power in a porcine model with hemodynamic relevant pericardial effusion. A single-center animal investigation. Twelve German domestic pigs. Pigs were studied before and during pericardial effusion. Instrumentation included a pulmonary artery catheter and a transpulmonary thermodilution catheter in the femoral artery. Hemodynamic variables like cardiac output (COPAC) and stroke volume (SVPAC) derived from pulmonary artery catheter, global end-diastolic volume (GEDV), stroke volume variation (SVV), and pulse-pressure variation (PPV) were obtained. At baseline, SVV, PPV, GEDV, COPAC, and SVPAC reliably predicted fluid responsiveness (area under the curve 0.81 [p = 0.02], 0.82 [p = 0.02], 0.74 [p = 0.07], 0.74 [p = 0.07], 0.82 [p = 0.02]). After establishment of pericardial effusion the predictive power of dynamic variables was impaired and only COPAC and SVPAC and GEDV allowed significant prediction of fluid responsiveness (area under the curve 0.77 [p = 0.04], 0.76 [p = 0.05], 0.83 [p = 0.01]) with clinically relevant changes in threshold values. In this porcine model, hemodynamic relevant pericardial effusion abolished the ability of dynamic variables to predict fluid responsiveness. COPAC, SVPAC, and GEDV enabled prediction, but their threshold values were significantly changed. Copyright © 2016 Elsevier Inc. All rights reserved.

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

A model to simulate the dynamic of a PWR pressurizer using the CSMP program

International Nuclear Information System (INIS)

Woiski, E.R.

1981-01-01

A mathematical model has been developed to simulate the dynamic behavior of a PWR pressurizer using the CSMP program. A two-control-volume formulation non-equilibrium model has been used for this purpose. Thermodynamic states are obtained after each integration cycle. The code was tested against experimental results of Shippingport and NPD (Nuclear Power Demonstration Plant) pressurizers. It was also tested against available data from Angra I and Angra II/III safety analysis report. Despite the model simplicity, the lack of important data and the low reliability or the experimental curves, the calculated and experimental results compared well. (Author) [pt

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.

Incorporating human-water dynamics in a hyper-resolution land surface model

Science.gov (United States)

Vergopolan, N.; Chaney, N.; Wanders, N.; Sheffield, J.; Wood, E. F.

2017-12-01

The increasing demand for water, energy, and food is leading to unsustainable groundwater and surface water exploitation. As a result, the human interactions with the environment, through alteration of land and water resources dynamics, need to be reflected in hydrologic and land surface models (LSMs). Advancements in representing human-water dynamics still leave challenges related to the lack of water use data, water allocation algorithms, and modeling scales. This leads to an over-simplistic representation of human water use in large-scale models; this is in turn leads to an inability to capture extreme events signatures and to provide reliable information at stakeholder-level spatial scales. The emergence of hyper-resolution models allows one to address these challenges by simulating the hydrological processes and interactions with the human impacts at field scales. We integrated human-water dynamics into HydroBlocks - a hyper-resolution, field-scale resolving LSM. HydroBlocks explicitly solves the field-scale spatial heterogeneity of land surface processes through interacting hydrologic response units (HRUs); and its HRU-based model parallelization allows computationally efficient long-term simulations as well as ensemble predictions. The implemented human-water dynamics include groundwater and surface water abstraction to meet agricultural, domestic and industrial water demands. Furthermore, a supply-demand water allocation scheme based on relative costs helps to determine sectoral water use requirements and tradeoffs. A set of HydroBlocks simulations over the Midwest United States (daily, at 30-m spatial resolution for 30 years) are used to quantify the irrigation impacts on water availability. The model captures large reductions in total soil moisture and water table levels, as well as spatiotemporal changes in evapotranspiration and runoff peaks, with their intensity related to the adopted water management strategy. By incorporating human-water dynamics in

Age-dependent reliability model considering effects of maintenance and working conditions

International Nuclear Information System (INIS)

Martorell, Sebastian; Sanchez, Ana; Serradell, Vicente

1999-01-01

Nowadays, there is some doubt about building new nuclear power plants (NPPs). Instead, there is a growing interest in analyzing the possibility to extend current NPP operation, where life management programs play an important role. The evolution of the NPP safety depends on the evolution of the reliability of its safety components, which, in turn, is a function of their age along the NPP operational life. In this paper, a new age-dependent reliability model is presented, which includes parameters related to surveillance and maintenance effectiveness and working conditions of the equipment, both environmental and operational. This model may be used to support NPP life management and life extension programs, by improving or optimizing surveillance and maintenance tasks using risk and cost models based on such an age-dependent reliability model. The results of the sensitivity study in the example application show that the selection of the most appropriate maintenance strategy would directly depend on the previous parameters. Then, very important differences are expected to appear under certain circumstances, particularly, in comparison with other models that do not consider maintenance effectiveness and working conditions simultaneously

Dynamics analysis of a boiling water reactor based on multivariable autoregressive modeling

International Nuclear Information System (INIS)

Oguma, Ritsuo; Matsubara, Kunihiko

1980-01-01

The establishment of the highly reliable mathematical model for the dynamic characteristics of a reactor is indispensable for the achievement of safe operation in reactor plants. The authors have tried to model the dynamic characteristics of a reactor based on the identification technique, taking the JPDR (Japan Power Demonstration Reactor) as the object, as one of the technical studies for diagnosing BWR anomaly, and employed the multivariable autoregressive modeling (MAR method) as one of the useful methods for forwarding the analysis. In this paper, the outline of the system analysis by MAR modeling is explained, and the identification experiments and their analysis results performed in the phase 4 of the power increase test of the JPDR are described. The authors evaluated the results of identification based on only reactor noises, making reference to the results of identification in the case of exciting the system by applying artificial irregular disturbance, in order to clarify the extent in which the modeling is possible by reactor noises only. However, some difficulties were encountered. The largest problem is the one concerning the separation and identification of the noise sources exciting the variables from the dynamic characteristics among the variables. If the effective technique can be obtained to this problem, the approach by the identification technique based on the probability model might be a powerful tool in the field of reactor noise analysis and the development of diagnosis technics. (Wakatsuki, Y.)

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)

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…

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

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.

Cost-effective solutions to maintaining smart grid reliability

Science.gov (United States)

Qin, Qiu

As the aging power systems are increasingly working closer to the capacity and thermal limits, maintaining an sufficient reliability has been of great concern to the government agency, utility companies and users. This dissertation focuses on improving the reliability of transmission and distribution systems. Based on the wide area measurements, multiple model algorithms are developed to diagnose transmission line three-phase short to ground faults in the presence of protection misoperations. The multiple model algorithms utilize the electric network dynamics to provide prompt and reliable diagnosis outcomes. Computational complexity of the diagnosis algorithm is reduced by using a two-step heuristic. The multiple model algorithm is incorporated into a hybrid simulation framework, which consist of both continuous state simulation and discrete event simulation, to study the operation of transmission systems. With hybrid simulation, line switching strategy for enhancing the tolerance to protection misoperations is studied based on the concept of security index, which involves the faulted mode probability and stability coverage. Local measurements are used to track the generator state and faulty mode probabilities are calculated in the multiple model algorithms. FACTS devices are considered as controllers for the transmission system. The placement of FACTS devices into power systems is investigated with a criterion of maintaining a prescribed level of control reconfigurability. Control reconfigurability measures the small signal combined controllability and observability of a power system with an additional requirement on fault tolerance. For the distribution systems, a hierarchical framework, including a high level recloser allocation scheme and a low level recloser placement scheme, is presented. The impacts of recloser placement on the reliability indices is analyzed. Evaluation of reliability indices in the placement process is carried out via discrete event

14C and tritium dynamics in wild mammals: a metabolic model

International Nuclear Information System (INIS)

Galeriu, D.; Beresford, N.A.; Melintescu, A.; Crout, N.M.J.; Takeda, H.

2004-01-01

The protection of biota from ionising radiations needs reliable predictions of radionuclide dynamics in wild animals. Data specific for many wild animals radionuclide combinations is lacking and a number of approaches including allometry have been proposed to address this. However, for 14 C and tritium, which are integral components of animals tissues and their diets, a different approach is needed in the absence of experimental data. Here we propose a metabolically based model which can be parameterized predominantly on the basis of published metabolic data. We begin with a metabolic definition of the 14 C and OBT loss rate (assumed to be the same) from the whole body and also specific organs, using available information on field metabolic rate and body composition. The mammalian body is conceptually partitioned into compartments (body water, viscera, adipose, muscle, blood and remainder) and a simple model defined using net maintenance and growth needs of mammals. Intake and excretion, and transfer to body water are modelled using basic metabolic knowledge and published relationships. The model is tested with data from studies using rats and sheep. It provides a reliable prediction for whole body and muscle activity concentrations without the requirement for any calibration specific to 3 H and 14 C. Predictions from the model for representative wild mammals (as selected to be reference organisms within international programmes) are presented. Potential developments of a metabolic model for birds and the application of our work to human food chain modelling are also discussed. (author)

Practical applications of age-dependent reliability models and analysis of operational data

Energy Technology Data Exchange (ETDEWEB)

Lannoy, A.; Nitoi, M.; Backstrom, O.; Burgazzi, L.; Couallier, V.; Nikulin, M.; Derode, A.; Rodionov, A.; Atwood, C.; Fradet, F.; Antonov, A.; Berezhnoy, A.; Choi, S.Y.; Starr, F.; Dawson, J.; Palmen, H.; Clerjaud, L

2005-07-01

The purpose of the workshop was to present the experience of practical application of time-dependent reliability models. The program of the workshop comprises the following sessions: -) aging management and aging PSA (Probabilistic Safety Assessment), -) modeling, -) operation experience, and -) accelerating aging tests. In order to introduce time aging effect of particular component to the PSA model, it has been proposed to use the constant unavailability values on the short period of time (one year for example) calculated on the basis of age-dependent reliability models. As for modeling, it appears that the problem of too detailed statistical models for application is the lack of data for required parameters. As for operating experience, several methods of operating experience analysis have been presented (algorithms for reliability data elaboration and statistical identification of aging trend). As for accelerated aging tests, it is demonstrated that a combination of operating experience analysis with the results of accelerated aging tests of naturally aged equipment could provide a good basis for continuous operation of instrumentation and control systems.

Practical applications of age-dependent reliability models and analysis of operational data

International Nuclear Information System (INIS)

Lannoy, A.; Nitoi, M.; Backstrom, O.; Burgazzi, L.; Couallier, V.; Nikulin, M.; Derode, A.; Rodionov, A.; Atwood, C.; Fradet, F.; Antonov, A.; Berezhnoy, A.; Choi, S.Y.; Starr, F.; Dawson, J.; Palmen, H.; Clerjaud, L.

2005-01-01

The purpose of the workshop was to present the experience of practical application of time-dependent reliability models. The program of the workshop comprises the following sessions: -) aging management and aging PSA (Probabilistic Safety Assessment), -) modeling, -) operation experience, and -) accelerating aging tests. In order to introduce time aging effect of particular component to the PSA model, it has been proposed to use the constant unavailability values on the short period of time (one year for example) calculated on the basis of age-dependent reliability models. As for modeling, it appears that the problem of too detailed statistical models for application is the lack of data for required parameters. As for operating experience, several methods of operating experience analysis have been presented (algorithms for reliability data elaboration and statistical identification of aging trend). As for accelerated aging tests, it is demonstrated that a combination of operating experience analysis with the results of accelerated aging tests of naturally aged equipment could provide a good basis for continuous operation of instrumentation and control systems

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

Model dynamic behaviour analysis with chaotic noise using fuzzy logic based control

International Nuclear Information System (INIS)

Silva, Glauco Antonio Santos da

2002-01-01

This work presents an application of fuzzy control on dynamical system models. It has been observed that fuzzy controllers maybe used as a good alternative to the classical PI controller, once it incorporates human line behavior. Three implication relationships were used for the fussy controllers, namely, Mamdani Min, Larsen and Takagi-Sugeno. Performance comparisons were made aiming at achieving the best performance for each model used. The PI controller was used as a minimum standard, once it has been present in the industry for many years, giving acceptable performances and some degree of reliability . Two kinds of perturbations were introduced in the models to test the controllers: a ramp and chaotic perturbations. The first one is a monotonic, standard increase of an input parameter. The second one presents non-periodicity and irregularity in such a way to be quite rough to the controllers. The chaotic signal, as an analysis tool to dynamical systems, is an interesting contribution of this work. As a general conclusion it can be said the best performance, in this work, was achieved by the Takagi-Sugeno fuzzy controller. (author)

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.)

Dependent systems reliability estimation by structural reliability approach

DEFF Research Database (Denmark)

Kostandyan, Erik; Sørensen, John Dalsgaard

2014-01-01

Estimation of system reliability by classical system reliability methods generally assumes that the components are statistically independent, thus limiting its applicability in many practical situations. A method is proposed for estimation of the system reliability with dependent components, where...... the leading failure mechanism(s) is described by physics of failure model(s). The proposed method is based on structural reliability techniques and accounts for both statistical and failure effect correlations. It is assumed that failure of any component is due to increasing damage (fatigue phenomena...... identification. Application of the proposed method can be found in many real world systems....

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)

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.

Cluster-based upper body marker models for three-dimensional kinematic analysis: Comparison with an anatomical model and reliability analysis.

Science.gov (United States)

Boser, Quinn A; Valevicius, Aïda M; Lavoie, Ewen B; Chapman, Craig S; Pilarski, Patrick M; Hebert, Jacqueline S; Vette, Albert H

2018-04-27

Quantifying angular joint kinematics of the upper body is a useful method for assessing upper limb function. Joint angles are commonly obtained via motion capture, tracking markers placed on anatomical landmarks. This method is associated with limitations including administrative burden, soft tissue artifacts, and intra- and inter-tester variability. An alternative method involves the tracking of rigid marker clusters affixed to body segments, calibrated relative to anatomical landmarks or known joint angles. The accuracy and reliability of applying this cluster method to the upper body has, however, not been comprehensively explored. Our objective was to compare three different upper body cluster models with an anatomical model, with respect to joint angles and reliability. Non-disabled participants performed two standardized functional upper limb tasks with anatomical and cluster markers applied concurrently. Joint angle curves obtained via the marker clusters with three different calibration methods were compared to those from an anatomical model, and between-session reliability was assessed for all models. The cluster models produced joint angle curves which were comparable to and highly correlated with those from the anatomical model, but exhibited notable offsets and differences in sensitivity for some degrees of freedom. Between-session reliability was comparable between all models, and good for most degrees of freedom. Overall, the cluster models produced reliable joint angles that, however, cannot be used interchangeably with anatomical model outputs to calculate kinematic metrics. Cluster models appear to be an adequate, and possibly advantageous alternative to anatomical models when the objective is to assess trends in movement behavior. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

Time domain system identification of longitudinal dynamics of single rotor model helicopter using sidpac

International Nuclear Information System (INIS)

Khaizer, A.N.; Hussain, I.

2015-01-01

This paper presents a time-domain approach for identification of longitudinal dynamics of single rotor model helicopter. A frequency sweep excitation input signal is applied for hover flying mode widely used for space state linearized model. A fully automated programmed flight test method provides high quality flight data for system identification using the computer controlled flight simulator X-plane. The flight test data were recorded, analyzed and reduced using the SIDPAC (System Identification Programs for Air Craft) toolbox for MATLAB, resulting in an aerodynamic model of single rotor helicopter. Finally, the identified model of single rotor helicopter is validated on Raptor 30-class model helicopter at hover showing the reliability of proposed approach. (author)

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.

Systems reliability/structural reliability

International Nuclear Information System (INIS)

Green, A.E.

1980-01-01

The question of reliability technology using quantified techniques is considered for systems and structures. Systems reliability analysis has progressed to a viable and proven methodology whereas this has yet to be fully achieved for large scale structures. Structural loading variants over the half-time of the plant are considered to be more difficult to analyse than for systems, even though a relatively crude model may be a necessary starting point. Various reliability characteristics and environmental conditions are considered which enter this problem. The rare event situation is briefly mentioned together with aspects of proof testing and normal and upset loading conditions. (orig.)

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.

OSS reliability measurement and assessment

CERN Document Server

Yamada, Shigeru

2016-01-01

This book analyses quantitative open source software (OSS) reliability assessment and its applications, focusing on three major topic areas: the Fundamentals of OSS Quality/Reliability Measurement and Assessment; the Practical Applications of OSS Reliability Modelling; and Recent Developments in OSS Reliability Modelling. Offering an ideal reference guide for graduate students and researchers in reliability for open source software (OSS) and modelling, the book introduces several methods of reliability assessment for OSS including component-oriented reliability analysis based on analytic hierarchy process (AHP), analytic network process (ANP), and non-homogeneous Poisson process (NHPP) models, the stochastic differential equation models and hazard rate models. These measurement and management technologies are essential to producing and maintaining quality/reliable systems using OSS.

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.

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.

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

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.

Human reliability

International Nuclear Information System (INIS)

Embrey, D.E.

1987-01-01

Concepts and techniques of human reliability have been developed and are used mostly in probabilistic risk assessment. For this, the major application of human reliability assessment has been to identify the human errors which have a significant effect on the overall safety of the system and to quantify the probability of their occurrence. Some of the major issues within human reliability studies are reviewed and it is shown how these are applied to the assessment of human failures in systems. This is done under the following headings; models of human performance used in human reliability assessment, the nature of human error, classification of errors in man-machine systems, practical aspects, human reliability modelling in complex situations, quantification and examination of human reliability, judgement based approaches, holistic techniques and decision analytic approaches. (UK)

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...

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.

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

A study of operational and testing reliability in software reliability analysis

International Nuclear Information System (INIS)

Yang, B.; Xie, M.

2000-01-01

Software reliability is an important aspect of any complex equipment today. Software reliability is usually estimated based on reliability models such as nonhomogeneous Poisson process (NHPP) models. Software systems are improving in testing phase, while it normally does not change in operational phase. Depending on whether the reliability is to be predicted for testing phase or operation phase, different measure should be used. In this paper, two different reliability concepts, namely, the operational reliability and the testing reliability, are clarified and studied in detail. These concepts have been mixed up or even misused in some existing literature. Using different reliability concept will lead to different reliability values obtained and it will further lead to different reliability-based decisions made. The difference of the estimated reliabilities is studied and the effect on the optimal release time is investigated

Mid-frequency Band Dynamics of Large Space Structures

Science.gov (United States)

Coppolino, Robert N.; Adams, Douglas S.

2004-01-01

High and low intensity dynamic environments experienced by a spacecraft during launch and on-orbit operations, respectively, induce structural loads and motions, which are difficult to reliably predict. Structural dynamics in low- and mid-frequency bands are sensitive to component interface uncertainty and non-linearity as evidenced in laboratory testing and flight operations. Analytical tools for prediction of linear system response are not necessarily adequate for reliable prediction of mid-frequency band dynamics and analysis of measured laboratory and flight data. A new MATLAB toolbox, designed to address the key challenges of mid-frequency band dynamics, is introduced in this paper. Finite-element models of major subassemblies are defined following rational frequency-wavelength guidelines. For computational efficiency, these subassemblies are described as linear, component mode models. The complete structural system model is composed of component mode subassemblies and linear or non-linear joint descriptions. Computation and display of structural dynamic responses are accomplished employing well-established, stable numerical methods, modern signal processing procedures and descriptive graphical tools. Parametric sensitivity and Monte-Carlo based system identification tools are used to reconcile models with experimental data and investigate the effects of uncertainties. Models and dynamic responses are exported for employment in applications, such as detailed structural integrity and mechanical-optical-control performance analyses.

Fault-tolerant embedded system design and optimization considering reliability estimation uncertainty

International Nuclear Information System (INIS)

Wattanapongskorn, Naruemon; Coit, David W.

2007-01-01

In this paper, we model embedded system design and optimization, considering component redundancy and uncertainty in the component reliability estimates. The systems being studied consist of software embedded in associated hardware components. Very often, component reliability values are not known exactly. Therefore, for reliability analysis studies and system optimization, it is meaningful to consider component reliability estimates as random variables with associated estimation uncertainty. In this new research, the system design process is formulated as a multiple-objective optimization problem to maximize an estimate of system reliability, and also, to minimize the variance of the reliability estimate. The two objectives are combined by penalizing the variance for prospective solutions. The two most common fault-tolerant embedded system architectures, N-Version Programming and Recovery Block, are considered as strategies to improve system reliability by providing system redundancy. Four distinct models are presented to demonstrate the proposed optimization techniques with or without redundancy. For many design problems, multiple functionally equivalent software versions have failure correlation even if they have been independently developed. The failure correlation may result from faults in the software specification, faults from a voting algorithm, and/or related faults from any two software versions. Our approach considers this correlation in formulating practical optimization models. Genetic algorithms with a dynamic penalty function are applied in solving this optimization problem, and reasonable and interesting results are obtained and discussed

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

Understanding Dynamic Model Validation of a Wind Turbine Generator and a Wind Power Plant: Preprint

Energy Technology Data Exchange (ETDEWEB)

Muljadi, Eduard; Zhang, Ying Chen; Gevorgian, Vahan; Kosterev, Dmitry

2016-09-01

Regional reliability organizations require power plants to validate the dynamic models that represent them to ensure that power systems studies are performed to the best representation of the components installed. In the process of validating a wind power plant (WPP), one must be cognizant of the parameter settings of the wind turbine generators (WTGs) and the operational settings of the WPP. Validating the dynamic model of a WPP is required to be performed periodically. This is because the control parameters of the WTGs and the other supporting components within a WPP may be modified to comply with new grid codes or upgrades to the WTG controller with new capabilities developed by the turbine manufacturers or requested by the plant owners or operators. The diversity within a WPP affects the way we represent it in a model. Diversity within a WPP may be found in the way the WTGs are controlled, the wind resource, the layout of the WPP (electrical diversity), and the type of WTGs used. Each group of WTGs constitutes a significant portion of the output power of the WPP, and their unique and salient behaviors should be represented individually. The objective of this paper is to illustrate the process of dynamic model validations of WTGs and WPPs, the available data recorded that must be screened before it is used for the dynamic validations, and the assumptions made in the dynamic models of the WTG and WPP that must be understood. Without understanding the correct process, the validations may lead to the wrong representations of the WTG and WPP modeled.

Reconstruction of missing daily streamflow data using dynamic regression models

Science.gov (United States)

Tencaliec, Patricia; Favre, Anne-Catherine; Prieur, Clémentine; Mathevet, Thibault

2015-12-01

River discharge is one of the most important quantities in hydrology. It provides fundamental records for water resources management and climate change monitoring. Even very short data-gaps in this information can cause extremely different analysis outputs. Therefore, reconstructing missing data of incomplete data sets is an important step regarding the performance of the environmental models, engineering, and research applications, thus it presents a great challenge. The objective of this paper is to introduce an effective technique for reconstructing missing daily discharge data when one has access to only daily streamflow data. The proposed procedure uses a combination of regression and autoregressive integrated moving average models (ARIMA) called dynamic regression model. This model uses the linear relationship between neighbor and correlated stations and then adjusts the residual term by fitting an ARIMA structure. Application of the model to eight daily streamflow data for the Durance river watershed showed that the model yields reliable estimates for the missing data in the time series. Simulation studies were also conducted to evaluate the performance of the procedure.

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...

Chaos and reliability in balanced spiking networks with temporal drive.

Science.gov (United States)

Lajoie, Guillaume; Lin, Kevin K; Shea-Brown, Eric

2013-05-01

Biological information processing is often carried out by complex networks of interconnected dynamical units. A basic question about such networks is that of reliability: If the same signal is presented many times with the network in different initial states, will the system entrain to the signal in a repeatable way? Reliability is of particular interest in neuroscience, where large, complex networks of excitatory and inhibitory cells are ubiquitous. These networks are known to autonomously produce strongly chaotic dynamics-an obvious threat to reliability. Here, we show that such chaos persists in the presence of weak and strong stimuli, but that even in the presence of chaos, intermittent periods of highly reliable spiking often coexist with unreliable activity. We elucidate the local dynamical mechanisms involved in this intermittent reliability, and investigate the relationship between this phenomenon and certain time-dependent attractors arising from the dynamics. A conclusion is that chaotic dynamics do not have to be an obstacle to precise spike responses, a fact with implications for signal coding in large networks.

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

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

Physics-based process modeling, reliability prediction, and design guidelines for flip-chip devices

Science.gov (United States)

Michaelides, Stylianos

Flip Chip on Board (FCOB) and Chip-Scale Packages (CSPs) are relatively new technologies that are being increasingly used in the electronic packaging industry. Compared to the more widely used face-up wirebonding and TAB technologies, flip-chips and most CSPs provide the shortest possible leads, lower inductance, higher frequency, better noise control, higher density, greater input/output (I/O), smaller device footprint and lower profile. However, due to the short history and due to the introduction of several new electronic materials, designs, and processing conditions, very limited work has been done to understand the role of material, geometry, and processing parameters on the reliability of flip-chip devices. Also, with the ever-increasing complexity of semiconductor packages and with the continued reduction in time to market, it is too costly to wait until the later stages of design and testing to discover that the reliability is not satisfactory. The objective of the research is to develop integrated process-reliability models that will take into consideration the mechanics of assembly processes to be able to determine the reliability of face-down devices under thermal cycling and long-term temperature dwelling. The models incorporate the time and temperature-dependent constitutive behavior of various materials in the assembly to be able to predict failure modes such as die cracking and solder cracking. In addition, the models account for process-induced defects and macro-micro features of the assembly. Creep-fatigue and continuum-damage mechanics models for the solder interconnects and fracture-mechanics models for the die have been used to determine the reliability of the devices. The results predicted by the models have been successfully validated against experimental data. The validated models have been used to develop qualification and test procedures for implantable medical devices. In addition, the research has helped develop innovative face

Building fast, reliable, and adaptive software for computational science

International Nuclear Information System (INIS)

Rendell, A P; Antony, J; Armstrong, W; Janes, P; Yang, R

2008-01-01

Building fast, reliable, and adaptive software is a constant challenge for computational science, especially given recent developments in computer architecture. This paper outlines some of our efforts to address these three issues in the context of computational chemistry. First, a simple linear performance that can be used to model and predict the performance of Hartree-Fock calculations is discussed. Second, the use of interval arithmetic to assess the numerical reliability of the sort of integrals used in electronic structure methods is presented. Third, use of dynamic code modification as part of a framework to support adaptive software is outlined

A Data-Driven Reliability Estimation Approach for Phased-Mission Systems

Directory of Open Access Journals (Sweden)

Hua-Feng He

2014-01-01

Full Text Available We attempt to address the issues associated with reliability estimation for phased-mission systems (PMS and present a novel data-driven approach to achieve reliability estimation for PMS using the condition monitoring information and degradation data of such system under dynamic operating scenario. In this sense, this paper differs from the existing methods only considering the static scenario without using the real-time information, which aims to estimate the reliability for a population but not for an individual. In the presented approach, to establish a linkage between the historical data and real-time information of the individual PMS, we adopt a stochastic filtering model to model the phase duration and obtain the updated estimation of the mission time by Bayesian law at each phase. At the meanwhile, the lifetime of PMS is estimated from degradation data, which are modeled by an adaptive Brownian motion. As such, the mission reliability can be real time obtained through the estimated distribution of the mission time in conjunction with the estimated lifetime distribution. We demonstrate the usefulness of the developed approach via a numerical example.

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…

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.

Composite reliability evaluation for transmission network planning

Directory of Open Access Journals (Sweden)

Jiashen Teh

2018-01-01

Full Text Available As the penetration of wind power into the power system increases, the ability to assess the reliability impact of such interaction becomes more important. The composite reliability evaluations involving wind energy provide ample opportunities for assessing the benefits of different wind farm connection points. A connection to the weak area of the transmission network will require network reinforcement for absorbing the additional wind energy. Traditionally, the reinforcements are performed by constructing new transmission corridors. However, a new state-of-art technology such as the dynamic thermal rating (DTR system, provides new reinforcement strategy and this requires new reliability assessment method. This paper demonstrates a methodology for assessing the cost and the reliability of network reinforcement strategies by considering the DTR systems when large scale wind farms are connected to the existing power network. Sequential Monte Carlo simulations were performed and all DTRs and wind speed were simulated using the auto-regressive moving average (ARMA model. Various reinforcement strategies were assessed from their cost and reliability aspects. Practical industrial standards are used as guidelines when assessing costs. Due to this, the proposed methodology in this paper is able to determine the optimal reinforcement strategies when both the cost and reliability requirements are considered.

Modeling Misbehavior in Cooperative Diversity: A Dynamic Game Approach

Science.gov (United States)

Dehnie, Sintayehu; Memon, Nasir

2009-12-01

Cooperative diversity protocols are designed with the assumption that terminals always help each other in a socially efficient manner. This assumption may not be valid in commercial wireless networks where terminals may misbehave for selfish or malicious intentions. The presence of misbehaving terminals creates a social-dilemma where terminals exhibit uncertainty about the cooperative behavior of other terminals in the network. Cooperation in social-dilemma is characterized by a suboptimal Nash equilibrium where wireless terminals opt out of cooperation. Hence, without establishing a mechanism to detect and mitigate effects of misbehavior, it is difficult to maintain a socially optimal cooperation. In this paper, we first examine effects of misbehavior assuming static game model and show that cooperation under existing cooperative protocols is characterized by a noncooperative Nash equilibrium. Using evolutionary game dynamics we show that a small number of mutants can successfully invade a population of cooperators, which indicates that misbehavior is an evolutionary stable strategy (ESS). Our main goal is to design a mechanism that would enable wireless terminals to select reliable partners in the presence of uncertainty. To this end, we formulate cooperative diversity as a dynamic game with incomplete information. We show that the proposed dynamic game formulation satisfied the conditions for the existence of perfect Bayesian equilibrium.

Modeling Misbehavior in Cooperative Diversity: A Dynamic Game Approach

Directory of Open Access Journals (Sweden)

Sintayehu Dehnie

2009-01-01

Full Text Available Cooperative diversity protocols are designed with the assumption that terminals always help each other in a socially efficient manner. This assumption may not be valid in commercial wireless networks where terminals may misbehave for selfish or malicious intentions. The presence of misbehaving terminals creates a social-dilemma where terminals exhibit uncertainty about the cooperative behavior of other terminals in the network. Cooperation in social-dilemma is characterized by a suboptimal Nash equilibrium where wireless terminals opt out of cooperation. Hence, without establishing a mechanism to detect and mitigate effects of misbehavior, it is difficult to maintain a socially optimal cooperation. In this paper, we first examine effects of misbehavior assuming static game model and show that cooperation under existing cooperative protocols is characterized by a noncooperative Nash equilibrium. Using evolutionary game dynamics we show that a small number of mutants can successfully invade a population of cooperators, which indicates that misbehavior is an evolutionary stable strategy (ESS. Our main goal is to design a mechanism that would enable wireless terminals to select reliable partners in the presence of uncertainty. To this end, we formulate cooperative diversity as a dynamic game with incomplete information. We show that the proposed dynamic game formulation satisfied the conditions for the existence of perfect Bayesian equilibrium.

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...

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.

Towards an efficient multiphysics model for nuclear reactor dynamics

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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.

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

Reliability analysis framework for computer-assisted medical decision systems

International Nuclear Information System (INIS)

Habas, Piotr A.; Zurada, Jacek M.; Elmaghraby, Adel S.; Tourassi, Georgia D.

2007-01-01

We present a technique that enhances computer-assisted decision (CAD) systems with the ability to assess the reliability of each individual decision they make. Reliability assessment is achieved by measuring the accuracy of a CAD system with known cases similar to the one in question. The proposed technique analyzes the feature space neighborhood of the query case to dynamically select an input-dependent set of known cases relevant to the query. This set is used to assess the local (query-specific) accuracy of the CAD system. The estimated local accuracy is utilized as a reliability measure of the CAD response to the query case. The underlying hypothesis of the study is that CAD decisions with higher reliability are more accurate. The above hypothesis was tested using a mammographic database of 1337 regions of interest (ROIs) with biopsy-proven ground truth (681 with masses, 656 with normal parenchyma). Three types of decision models, (i) a back-propagation neural network (BPNN), (ii) a generalized regression neural network (GRNN), and (iii) a support vector machine (SVM), were developed to detect masses based on eight morphological features automatically extracted from each ROI. The performance of all decision models was evaluated using the Receiver Operating Characteristic (ROC) analysis. The study showed that the proposed reliability measure is a strong predictor of the CAD system's case-specific accuracy. Specifically, the ROC area index for CAD predictions with high reliability was significantly better than for those with low reliability values. This result was consistent across all decision models investigated in the study. The proposed case-specific reliability analysis technique could be used to alert the CAD user when an opinion that is unlikely to be reliable is offered. The technique can be easily deployed in the clinical environment because it is applicable with a wide range of classifiers regardless of their structure and it requires neither additional

Reliability and Maintainability model (RAM) user and maintenance manual. Part 2

Science.gov (United States)

Ebeling, Charles E.

1995-01-01

This report documents the procedures for utilizing and maintaining the Reliability and Maintainability Model (RAM) developed by the University of Dayton for the NASA Langley Research Center (LaRC). The RAM model predicts reliability and maintainability (R&M) parameters for conceptual space vehicles using parametric relationships between vehicle design and performance characteristics and subsystem mean time between maintenance actions (MTBM) and manhours per maintenance action (MH/MA). These parametric relationships were developed using aircraft R&M data from over thirty different military aircraft of all types. This report describes the general methodology used within the model, the execution and computational sequence, the input screens and data, the output displays and reports, and study analyses and procedures. A source listing is provided.

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.

Stochastic reliability and maintenance modeling essays in honor of Professor Shunji Osaki on his 70th birthday

CERN Document Server

Nakagawa, Toshio

2013-01-01

In honor of the work of Professor Shunji Osaki, Stochastic Reliability and Maintenance Modeling provides a comprehensive study of the legacy of and ongoing research in stochastic reliability and maintenance modeling. Including associated application areas such as dependable computing, performance evaluation, software engineering, communication engineering, distinguished researchers review and build on the contributions over the last four decades by Professor Shunji Osaki. Fundamental yet significant research results are presented and discussed clearly alongside new ideas and topics on stochastic reliability and maintenance modeling to inspire future research. Across 15 chapters readers gain the knowledge and understanding to apply reliability and maintenance theory to computer and communication systems. Stochastic Reliability and Maintenance Modeling is ideal for graduate students and researchers in reliability engineering, and workers, managers and engineers engaged in computer, maintenance and management wo...

Reliability Analysis of Core Protection Calculator System by Combining Petri Net and Fault Tree

International Nuclear Information System (INIS)

Kim, Hyejin; Kim, Jonghyun

2013-01-01

This paper proposes an approach to analyzing the reliability of digital systems by combining Petri net (PN) and Fault tree. The Petri net allows modeling event dependencies and interaction, to represent the time sequence, and to model assumptions for dynamic events. The Petri net model can be straightforwardly transformed to fault tree using the gate. Then, the FT can be integrated into the existing PSA. This paper applies the approach to the reliability analysis of Core Protection Calculator System (CPCS). Digital technology is replacing the analog instrumentation and control (I and C) systems in both new and upgraded nuclear power plants. As digital systems are introduced to nuclear power plants, issues related with reliability analyses of these digital systems are being raised. One of these issues is that static fault tree (FT) and event tree (ET) approach cannot properly account for dynamic interactions in the digital systems, such as multiple top events, logic loops and time delay. Many methods have been proposed to solve the problems, but there is no single method that is universally accepted for the application to the current generation probabilistic safety analysis (PSA)

Reliability Analysis of Core Protection Calculator System by Combining Petri Net and Fault Tree

Energy Technology Data Exchange (ETDEWEB)

Kim, Hyejin; Kim, Jonghyun [KEPCO International Nuclear Graduate School, Ulsan (Korea, Republic of)

2013-10-15

This paper proposes an approach to analyzing the reliability of digital systems by combining Petri net (PN) and Fault tree. The Petri net allows modeling event dependencies and interaction, to represent the time sequence, and to model assumptions for dynamic events. The Petri net model can be straightforwardly transformed to fault tree using the gate. Then, the FT can be integrated into the existing PSA. This paper applies the approach to the reliability analysis of Core Protection Calculator System (CPCS). Digital technology is replacing the analog instrumentation and control (I and C) systems in both new and upgraded nuclear power plants. As digital systems are introduced to nuclear power plants, issues related with reliability analyses of these digital systems are being raised. One of these issues is that static fault tree (FT) and event tree (ET) approach cannot properly account for dynamic interactions in the digital systems, such as multiple top events, logic loops and time delay. Many methods have been proposed to solve the problems, but there is no single method that is universally accepted for the application to the current generation probabilistic safety analysis (PSA)

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.

Two-terminal reliability analyses for a mobile ad hoc wireless network

International Nuclear Information System (INIS)

Cook, Jason L.; Ramirez-Marquez, Jose Emmanuel

2007-01-01

Reliability is one of the most important performance measures for emerging technologies. For these systems, shortcomings are often overlooked in early releases as the cutting edge technology overshadows a fragile design. Currently, the proliferation of the mobile ad hoc wireless networks (MAWN) is moving from cutting edge to commodity and thus, reliable performance will be expected. Generally, ad hoc networking is applied for the flexibility and mobility it provides. As a result, military and first responders employ this network scheme and the reliability of the network becomes paramount. To ensure reliability is achieved, one must first be able to analyze and calculate the reliability of the MAWN. This work describes the unique attributes of the MAWN and how the classical analysis of network reliability, where the network configuration is known a priori, can be adjusted to model and analyze this type of network. The methods developed acknowledge the dynamic and scalable nature of the MAWN along with its absence of infrastructure. Thus, the methods rely on a modeling approach that considers the probabilistic formation of different network configurations in a MAWN. Hence, this paper proposes reliability analysis methods that consider the effect of node mobility and the continuous changes in the network's connectivity