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)
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.
Stochastic process corrosion growth models for pipeline reliability
International Nuclear Information System (INIS)
Bazán, Felipe Alexander Vargas; Beck, André Teófilo
2013-01-01
Highlights: •Novel non-linear stochastic process corrosion growth model is proposed. •Corrosion rate modeled as random Poisson pulses. •Time to corrosion initiation and inherent time-variability properly represented. •Continuous corrosion growth histories obtained. •Model is shown to precisely fit actual corrosion data at two time points. -- Abstract: Linear random variable corrosion models are extensively employed in reliability analysis of pipelines. However, linear models grossly neglect well-known characteristics of the corrosion process. Herein, a non-linear model is proposed, where corrosion rate is represented as a Poisson square wave process. The resulting model represents inherent time-variability of corrosion growth, produces continuous growth and leads to mean growth at less-than-one power of time. Different corrosion models are adjusted to the same set of actual corrosion data for two inspections. The proposed non-linear random process corrosion growth model leads to the best fit to the data, while better representing problem physics
Software reliability growth models with normal failure time distributions
International Nuclear Information System (INIS)
Okamura, Hiroyuki; Dohi, Tadashi; Osaki, Shunji
2013-01-01
This paper proposes software reliability growth models (SRGM) where the software failure time follows a normal distribution. The proposed model is mathematically tractable and has sufficient ability of fitting to the software failure data. In particular, we consider the parameter estimation algorithm for the SRGM with normal distribution. The developed algorithm is based on an EM (expectation-maximization) algorithm and is quite simple for implementation as software application. Numerical experiment is devoted to investigating the fitting ability of the SRGMs with normal distribution through 16 types of failure time data collected in real software projects
AMSAA Reliability Growth Guide
National Research Council Canada - National Science Library
Broemm, William
2000-01-01
... has developed reliability growth methodology for all phases of the process, from planning to tracking to projection. The report presents this methodology and associated reliability growth concepts.
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
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
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
Alaa F. Sheta; Amal Abdel-Raouf
2016-01-01
In this age of technology, building quality software is essential to competing in the business market. One of the major principles required for any quality and business software product for value fulfillment is reliability. Estimating software reliability early during the software development life cycle saves time and money as it prevents spending larger sums fixing a defective software product after deployment. The Software Reliability Growth Model (SRGM) can be used to predict the number of...
Assessing the Reliability of Curriculum-Based Measurement: An Application of Latent Growth Modeling
Yeo, Seungsoo; Kim, Dong-Il; Branum-Martin, Lee; Wayman, Miya Miura; Espin, Christine A.
2012-01-01
The purpose of this study was to demonstrate the use of Latent Growth Modeling (LGM) as a method for estimating reliability of Curriculum-Based Measurement (CBM) progress-monitoring data. The LGM approach permits the error associated with each measure to differ at each time point, thus providing an alternative method for examining of the…
Directory of Open Access Journals (Sweden)
Subburaj Ramasamy
2017-01-01
Full Text Available Reliability is one of the quantifiable software quality attributes. Software Reliability Growth Models (SRGMs are used to assess the reliability achieved at different times of testing. Traditional time-based SRGMs may not be accurate enough in all situations where test effort varies with time. To overcome this lacuna, test effort was used instead of time in SRGMs. In the past, finite test effort functions were proposed, which may not be realistic as, at infinite testing time, test effort will be infinite. Hence in this paper, we propose an infinite test effort function in conjunction with a classical Nonhomogeneous Poisson Process (NHPP model. We use Artificial Neural Network (ANN for training the proposed model with software failure data. Here it is possible to get a large set of weights for the same model to describe the past failure data equally well. We use machine learning approach to select the appropriate set of weights for the model which will describe both the past and the future data well. We compare the performance of the proposed model with existing model using practical software failure data sets. The proposed log-power TEF based SRGM describes all types of failure data equally well and also improves the accuracy of parameter estimation more than existing TEF and can be used for software release time determination as well.
Reliability Growth in Space Life Support Systems
Jones, Harry W.
2014-01-01
A hardware system's failure rate often increases over time due to wear and aging, but not always. Some systems instead show reliability growth, a decreasing failure rate with time, due to effective failure analysis and remedial hardware upgrades. Reliability grows when failure causes are removed by improved design. A mathematical reliability growth model allows the reliability growth rate to be computed from the failure data. The space shuttle was extensively maintained, refurbished, and upgraded after each flight and it experienced significant reliability growth during its operational life. In contrast, the International Space Station (ISS) is much more difficult to maintain and upgrade and its failure rate has been constant over time. The ISS Carbon Dioxide Removal Assembly (CDRA) reliability has slightly decreased. Failures on ISS and with the ISS CDRA continue to be a challenge.
International Nuclear Information System (INIS)
Radu, V.
2016-01-01
The problem of thermal fatigue in mixing areas arises in nuclear piping where a turbulent mixing or vortices produce rapid fluid temperature fluctuations with random frequencies. The assessment of fatigue crack growth due to cyclic thermal loads arising from turbulent mixing presents significant challenges, principally due to the difficulty of establishing the actual loading spectrum. To apply the Stochastic approach of thermal fatigue, a frequency temperature response function is proposed. For the elastic thermal stresses distribution solutions, the magnitude of the frequency response function is first derived and checked against the prediction by FEA. The connection between SIF.s power spectral density (PSD) and temperature.s PSD is assured with SIF frequency response function modulus. The frequency of the peaks of each magnitude for KI is supposed to be a stationary narrow-band Gaussian process. The probabilities of failure are estimated by means of the Monte Carlo methods considering a limit state function. (authors)
Proposed reliability cost model
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.
Travel time reliability modeling.
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.,...
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…
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.
Power transformer reliability modelling
Schijndel, van A.
2010-01-01
Problem description Electrical power grids serve to transport and distribute electrical power with high reliability and availability at acceptable costs and risks. These grids play a crucial though preferably invisible role in supplying sufficient power in a convenient form. Today’s society has
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
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 ...
1989-08-01
Random variables for the conditional exponential distribution are generated using the inverse transform method. C1) Generate U - UCO,i) (2) Set s - A ln...e - [(x+s - 7)/ n] 0 + [Cx-T)/n]0 c. Random variables from the conditional weibull distribution are generated using the inverse transform method. C1...using a standard normal transformation and the inverse transform method. B - 3 APPENDIX 3 DISTRIBUTIONS SUPPORTED BY THE MODEL (1) Generate Y - PCX S
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...
Proposed Reliability/Cost Model
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.
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
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
Reliability growth of thin film resistors contact
Directory of Open Access Journals (Sweden)
Lugin A. N.
2010-10-01
Full Text Available Necessity of resistive layer growth under the contact and in the contact zone of resistive element is shown in order to reduce peak values of current flow and power dissipation in the contact of thin film resistor, thereby to increase the resistor stability to parametric and catastrophic failures.
An analytical framework for reliability growth of one-shot systems
International Nuclear Information System (INIS)
Hall, J. Brian; Mosleh, Ali
2008-01-01
In this paper, we introduce a new reliability growth methodology for one-shot systems that is applicable to the case where all corrective actions are implemented at the end of the current test phase. The methodology consists of four model equations for assessing: expected reliability, the expected number of failure modes observed in testing, the expected probability of discovering new failure modes, and the expected portion of system unreliability associated with repeat failure modes. These model equations provide an analytical framework for which reliability practitioners can estimate reliability improvement, address goodness-of-fit concerns, quantify programmatic risk, and assess reliability maturity of one-shot systems. A numerical example is given to illustrate the value and utility of the presented approach. This methodology is useful to program managers and reliability practitioners interested in applying the techniques above in their reliability growth program
Development of reliable pavement models.
2011-05-01
The current report proposes a framework for estimating the reliability of a given pavement structure as analyzed by : the Mechanistic-Empirical Pavement Design Guide (MEPDG). The methodology proposes using a previously fit : response surface, in plac...
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.
Reliability models for Space Station power system
Singh, C.; Patton, A. D.; Kim, Y.; Wagner, H.
1987-01-01
This paper presents a methodology for the reliability evaluation of Space Station power system. The two options considered are the photovoltaic system and the solar dynamic system. Reliability models for both of these options are described along with the methodology for calculating the reliability indices.
Reliability and continuous regeneration model
Directory of Open Access Journals (Sweden)
Anna Pavlisková
2006-06-01
Full Text Available The failure-free function of an object is very important for the service. This leads to the interest in the determination of the object reliability and failure intensity. The reliability of an element is defined by the theory of probability.The element durability T is a continuous random variate with the probability density f. The failure intensity (tλ is a very important reliability characteristics of the element. Often it is an increasing function, which corresponds to the element ageing. We disposed of the data about a belt conveyor failures recorded during the period of 90 months. The given ses behaves according to the normal distribution. By using a mathematical analysis and matematical statistics, we found the failure intensity function (tλ. The function (tλ increases almost linearly.
E. Gregory McPherson; Paula J. Peper
2012-01-01
This paper describes three long-term tree growth studies conducted to evaluate tree performance because repeated measurements of the same trees produce critical data for growth model calibration and validation. Several empirical and process-based approaches to modeling tree growth are reviewed. Modeling is more advanced in the fields of forestry and...
Chen, J D; Sun, H L
1999-04-01
Objective. To assess and predict reliability of an equipment dynamically by making full use of various test informations in the development of products. Method. A new reliability growth assessment method based on army material system analysis activity (AMSAA) model was developed. The method is composed of the AMSAA model and test data conversion technology. Result. The assessment and prediction results of a space-borne equipment conform to its expectations. Conclusion. It is suggested that this method should be further researched and popularized.
Reliability Modeling of Double Beam Bridge Crane
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.
Reliability Modeling of Wind Turbines
DEFF Research Database (Denmark)
Kostandyan, Erik
Cost reductions for offshore wind turbines are a substantial requirement in order to make offshore wind energy more competitive compared to other energy supply methods. During the 20 – 25 years of wind turbines useful life, Operation & Maintenance costs are typically estimated to be a quarter...... and uncertainties are quantified. Further, estimation of annual failure probability for structural components taking into account possible faults in electrical or mechanical systems is considered. For a representative structural failure mode, a probabilistic model is developed that incorporates grid loss failures...
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
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....
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 ontogenetic growth model
West, B. J.; West, D.
2012-02-01
An ontogenetic growth model (OGM) for a thermodynamically closed system is generalized to satisfy both the first and second law of thermodynamics. The hypothesized stochastic ontogenetic growth model (SOGM) is shown to entail the interspecies allometry relation by explicitly averaging the basal metabolic rate and the total body mass over the steady-state probability density for the total body mass (TBM). This is the first derivation of the interspecies metabolic allometric relation from a dynamical model and the asymptotic steady-state distribution of the TBM is fit to data and shown to be inverse power law.
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.
International Nuclear Information System (INIS)
Waterman, T.E.; Takata, A.N.
1983-01-01
The IITRI Urban Fire Spread Model as well as others of similar vintage were constrained by computer size and running costs such that many approximations/generalizations were introduced to reduce program complexity and data storage requirements. Simplifications were introduced both in input data and in fire growth and spread calculations. Modern computational capabilities offer the means to introduce greater detail and to examine its practical significance on urban fire predictions. Selected portions of the model are described as presently configured, and potential modifications are discussed. A single tract model is hypothesized which permits the importance of various model details to be assessed, and, other model applications are identified
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
Stochastic models in reliability and maintenance
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...
Measurement-based reliability/performability models
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.
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
Data Used in Quantified Reliability Models
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.
Economic Growth Models Transition
Directory of Open Access Journals (Sweden)
Coralia Angelescu
2006-03-01
Full Text Available The transitional recession in countries of Eastern Europe has been much longer than expected. The legacy and recent policy mistakes have both contributed to the slow progress. As structural reforms and gradual institution building have taken hold, the post-socialist economics have started to recover, with some leading countries building momentum toward faster growth. There is a possibility that in wider context of globalization several of these emerging market economies will be able to catch up with the more advanced industrial economies in a matter of one or two generations. Over the past few years, most candidate countries have made progress in the transition to a competitive market economy, macroeconomic stabilization and structural reform. However their income levels have remained far below those in the Member States. Measured by per capita income in purchasing power standards, there has been a very limited amount of catching up over the past fourteen years. Prior, the distinctions between Solow-Swan model and endogenous growth model. The interdependence between transition and integration are stated in this study. Finally, some measures of macroeconomic policy for sustainable growth are proposed in correlation with real macroeconomic situation of the Romanian economy. Our study would be considered the real convergence for the Romanian economy and the recommendations for the adequate policies to achieve a fast real convergence and sustainable growth.
Economic Growth Models Transition
Directory of Open Access Journals (Sweden)
Coralia Angelescu
2006-01-01
Full Text Available The transitional recession in countries of Eastern Europe has been much longer than expected. The legacy and recent policy mistakes have both contributed to the slow progress. As structural reforms and gradual institution building have taken hold, the post-socialist economics have started to recover, with some leading countries building momentum toward faster growth. There is a possibility that in wider context of globalization several of these emerging market economies will be able to catch up with the more advanced industrial economies in a matter of one or two generations. Over the past few years, most candidate countries have made progress in the transition to a competitive market economy, macroeconomic stabilization and structural reform. However their income levels have remained far below those in the Member States. Measured by per capita income in purchasing power standards, there has been a very limited amount of catching up over the past fourteen years. Prior, the distinctions between Solow-Swan model and endogenous growth model. The interdependence between transition and integration are stated in this study. Finally, some measures of macroeconomic policy for sustainable growth are proposed in correlation with real macroeconomic situation of the Romanian economy. Our study would be considered the real convergence for the Romanian economy and the recommendations for the adequate policies to achieve a fast real convergence and sustainable growth.
Modeling Reliability Growth in Accelerated Stress Testing
2013-12-01
labels = NA) axis(side = 2, tck = -.015, labels = NA) axis(side = 1, lwd = 0, line = -.6) axis(side = 2, lwd = 0, line = -.6, las = 1) mtext...side = 1, "t", line = 2) mtext(side = 2, "R(t)", line = 2.5) legend("bottomleft", c("Bi-Weibull","Tri-Weibull","NMW", "EMWE"),lty=c(1,1,3,2), lwd =c...1, lwd = 0, line = -.6) axis(side = 2, lwd = 0, line = -.6, las = 1) mtext(side = 1, "t", line = 2) mtext(side = 2, "f(t)", line = 3) legend
Modelling and estimating degradation processes with application in structural reliability
International Nuclear Information System (INIS)
Chiquet, J.
2007-06-01
The characteristic level of degradation of a given structure is modeled through a stochastic process called the degradation process. The random evolution of the degradation process is governed by a differential system with Markovian environment. We put the associated reliability framework by considering the failure of the structure once the degradation process reaches a critical threshold. A closed form solution of the reliability function is obtained thanks to Markov renewal theory. Then, we build an estimation methodology for the parameters of the stochastic processes involved. The estimation methods and the theoretical results, as well as the associated numerical algorithms, are validated on simulated data sets. Our method is applied to the modelling of a real degradation mechanism, known as crack growth, for which an experimental data set is considered. (authors)
A study of software reliability growth from the perspective of learning effects
International Nuclear Information System (INIS)
Chiu, K.-C.; Huang, Y.-S.; Lee, T.-Z.
2008-01-01
For the last three decades, reliability growth has been studied to predict software reliability in the testing/debugging phase. Most of the models developed were based on the non-homogeneous Poisson process (NHPP), and S-shaped type or exponential-shaped type of behavior is usually assumed. Unfortunately, such models may be suitable only for particular software failure data, thus narrowing the scope of applications. Therefore, from the perspective of learning effects that can influence the process of software reliability growth, we considered that efficiency in testing/debugging concerned not only the ability of the testing staff but also the learning effect that comes from inspecting the testing/debugging codes. The proposed approach can reasonably describe the S-shaped and exponential-shaped types of behaviors simultaneously, and the results in the experiment show good fit. A comparative analysis to evaluate the effectiveness for the proposed model and other software failure models was also performed. Finally, an optimal software release policy is suggested
Power Electronic Packaging Design, Assembly Process, Reliability and Modeling
Liu, Yong
2012-01-01
Power Electronic Packaging presents an in-depth overview of power electronic packaging design, assembly,reliability and modeling. Since there is a drastic difference between IC fabrication and power electronic packaging, the book systematically introduces typical power electronic packaging design, assembly, reliability and failure analysis and material selection so readers can clearly understand each task's unique characteristics. Power electronic packaging is one of the fastest growing segments in the power electronic industry, due to the rapid growth of power integrated circuit (IC) fabrication, especially for applications like portable, consumer, home, computing and automotive electronics. This book also covers how advances in both semiconductor content and power advanced package design have helped cause advances in power device capability in recent years. The author extrapolates the most recent trends in the book's areas of focus to highlight where further improvement in materials and techniques can d...
Tracking reliability for space cabin-borne equipment in development by Crow model.
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.
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)
Human reliability data collection and modelling
International Nuclear Information System (INIS)
1991-09-01
The main purpose of this document is to review and outline the current state-of-the-art of the Human Reliability Assessment (HRA) used for quantitative assessment of nuclear power plants safe and economical operation. Another objective is to consider Human Performance Indicators (HPI) which can alert plant manager and regulator to departures from states of normal and acceptable operation. These two objectives are met in the three sections of this report. The first objective has been divided into two areas, based on the location of the human actions being considered. That is, the modelling and data collection associated with control room actions are addressed first in chapter 1 while actions outside the control room (including maintenance) are addressed in chapter 2. Both chapters 1 and 2 present a brief outline of the current status of HRA for these areas, and major outstanding issues. Chapter 3 discusses HPI. Such performance indicators can signal, at various levels, changes in factors which influence human performance. The final section of this report consists of papers presented by the participants of the Technical Committee Meeting. A separate abstract was prepared for each of these papers. Refs, figs and tabs
System reliability time-dependent models
International Nuclear Information System (INIS)
Debernardo, H.D.
1991-06-01
A probabilistic methodology for safety system technical specification evaluation was developed. The method for Surveillance Test Interval (S.T.I.) evaluation basically means an optimization of S.T.I. of most important system's periodically tested components. For Allowed Outage Time (A.O.T.) calculations, the method uses system reliability time-dependent models (A computer code called FRANTIC III). A new approximation, which was called Independent Minimal Cut Sets (A.C.I.), to compute system unavailability was also developed. This approximation is better than Rare Event Approximation (A.E.R.) and the extra computing cost is neglectible. A.C.I. was joined to FRANTIC III to replace A.E.R. on future applications. The case study evaluations verified that this methodology provides a useful probabilistic assessment of surveillance test intervals and allowed outage times for many plant components. The studied system is a typical configuration of nuclear power plant safety systems (two of three logic). Because of the good results, these procedures will be used by the Argentine nuclear regulatory authorities in evaluation of technical specification of Atucha I and Embalse nuclear power plant safety systems. (Author) [es
Condon, David; Revelle, William
2017-01-01
Separating the signal in a test from the irrelevant noise is a challenge for all measurement. Low test reliability limits test validity, attenuates important relationships, and can lead to regression artifacts. Multiple approaches to the assessment and improvement of reliability are discussed. The advantages and disadvantages of several different approaches to reliability are considered. Practical advice on how to assess reliability using open source software is provided.
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
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...
Modeling Exponential Population Growth
McCormick, Bonnie
2009-01-01
The concept of population growth patterns is a key component of understanding evolution by natural selection and population dynamics in ecosystems. The National Science Education Standards (NSES) include standards related to population growth in sections on biological evolution, interdependence of organisms, and science in personal and social…
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)
Reliability Model of Power Transformer with ONAN Cooling
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...
The use of Career Growth Scale in Chinese nurses: Validity and reliability
Jingying Liu; Jipeng Yang; Yanhui Liu; Yang Yang; Hongfu Zhang
2015-01-01
Purpose: To test the validity and reliability of a modified Career Growth Scale (CGS) to assess nurse career growth. Method: A cross-sectional design was used to analyze the use of the CGS to survey 600 full-time registered nurses from Grade A hospitals in Tianjin. Results: A modified scale we called Career Growth of Nurse Scale (CGNS) is acceptable, valid, and reliable for the evaluation of nurse career growth in Chinese hospitals. This scale measured three main factors (career goal, c...
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.
Modeling Population Growth and Extinction
Gordon, Sheldon P.
2009-01-01
The exponential growth model and the logistic model typically introduced in the mathematics curriculum presume that a population grows exclusively. In reality, species can also die out and more sophisticated models that take the possibility of extinction into account are needed. In this article, two extensions of the logistic model are considered,…
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)
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.
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
Stochastic models for tumoral growth
Escudero, Carlos
2006-02-01
Strong experimental evidence has indicated that tumor growth belongs to the molecular beam epitaxy universality class. This type of growth is characterized by the constraint of cell proliferation to the tumor border and the surface diffusion of cells at the growing edge. Tumor growth is thus conceived as a competition for space between the tumor and the host, and cell diffusion at the tumor border is an optimal strategy adopted for minimizing the pressure and helping tumor development. Two stochastic partial differential equations are reported in this paper in order to correctly model the physical properties of tumoral growth in (1+1) and (2+1) dimensions. The advantage of these models is that they reproduce the correct geometry of the tumor and are defined in terms of polar variables. An analysis of these models allows us to quantitatively estimate the response of the tumor to an unfavorable perturbation during growth.
Towards Sustainable Growth Business Models
Energy Technology Data Exchange (ETDEWEB)
Kamp-Roelands, N.; Balkenende, J.P.; Van Ommen, P.
2012-03-15
The Dutch Sustainable Growth Coalition (DSGC) has the following objectives: The DSGC aims to pro-actively drive sustainable growth business models along three lines: (1) Shape. DSGC member companies aim to connect economic profitability with environmental and social progress on the basis of integrated sustainable growth business models; (2) Share. DSGC member companies aim for joint advocacy of sustainable growth business models both internationally and nationally; and (3) Stimulate. DSGC member companies aim to stimulate and influence the policy debate on enabling sustainable growth - with a view to finding solutions to the environmental and social challenges we are facing. This is their first report. The vision, actions and mission of DSGC are documented in the Manifesto in Chapter 2 of this publication. Chapter 3 contains an overview of key features of an integrated sustainable growth business model and the roadmap towards such a model. In Chapter 4, project examples of DSGC members are presented, providing insight into the hands-on reality of implementing the good practices. Chapter 5 offers an overview of how the Netherlands provides an enabling environment for sustainable growth business models. Chapter 6 offers the key conclusions.
Development of a Conservative Model Validation Approach for Reliable Analysis
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
Developing Fast and Reliable Flood Models
DEFF Research Database (Denmark)
Thrysøe, Cecilie; Toke, Jens; Borup, Morten
2016-01-01
. A surrogate model is set up for a case study area in Aarhus, Denmark, to replace a MIKE FLOOD model. The drainage surrogates are able to reproduce the MIKE URBAN results for a set of rain inputs. The coupled drainage-surface surrogate model lacks details in the surface description which reduces its overall...... accuracy. The model shows no instability, hence larger time steps can be applied, which reduces the computational time by more than a factor 1400. In conclusion, surrogate models show great potential for usage in urban water modelling....
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
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
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...
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 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.)
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...
Models for Battery Reliability and Lifetime
Energy Technology Data Exchange (ETDEWEB)
Smith, K.; Wood, E.; Santhanagopalan, S.; Kim, G. H.; Neubauer, J.; Pesaran, A.
2014-03-01
Models describing battery degradation physics are needed to more accurately understand how battery usage and next-generation battery designs can be optimized for performance and lifetime. Such lifetime models may also reduce the cost of battery aging experiments and shorten the time required to validate battery lifetime. Models for chemical degradation and mechanical stress are reviewed. Experimental analysis of aging data from a commercial iron-phosphate lithium-ion (Li-ion) cell elucidates the relative importance of several mechanical stress-induced degradation mechanisms.
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.
MODELING HUMAN RELIABILITY ANALYSIS USING MIDAS
Energy Technology Data Exchange (ETDEWEB)
Ronald L. Boring; Donald D. Dudenhoeffer; Bruce P. Hallbert; Brian F. Gore
2006-05-01
This paper summarizes an emerging collaboration between Idaho National Laboratory and NASA Ames Research Center regarding the utilization of high-fidelity MIDAS simulations for modeling control room crew performance at nuclear power plants. The key envisioned uses for MIDAS-based control room simulations are: (i) the estimation of human error with novel control room equipment and configurations, (ii) the investigative determination of risk significance in recreating past event scenarios involving control room operating crews, and (iii) the certification of novel staffing levels in control rooms. It is proposed that MIDAS serves as a key component for the effective modeling of risk in next generation control rooms.
Model uncertainty in growth empirics
Prüfer, P.
2008-01-01
This thesis applies so-called Bayesian model averaging (BMA) to three different economic questions substantially exposed to model uncertainty. Chapter 2 addresses a major issue of modern development economics: the analysis of the determinants of pro-poor growth (PPG), which seeks to combine high
Perinetti, Giuseppe; Primozic, Jasmina; Sharma, Bhavna; Cioffi, Iacopo; Contardo, Luca
2018-03-28
The capability of the cervical vertebral maturation (CVM) method in the identification of the mandibular growth peak on an individual basis remains undetermined. The diagnostic reliability of the six-stage CVM method in the identification of the mandibular growth peak was thus investigated. From the files of the Oregon and Burlington Growth Studies (data obtained between early 1950s and middle 1970s), 50 subjects (26 females, 24 males) with at least seven annual lateral cephalograms taken from 9 to 16 years were identified. Cervical vertebral maturation was assessed according to the CVM code staging system, and mandibular growth was defined as annual increments in Co-Gn distance. A diagnostic reliability analysis was carried out to establish the capability of the circumpubertal CVM stages 2, 3, and 4 in the identification of the imminent mandibular growth peak. Variable durations of each of the CVM stages 2, 3, and 4 were seen. The overall diagnostic accuracy values for the CVM stages 2, 3, and 4 were 0.70, 0.76, and 0.77, respectively. These low values appeared to be due to false positive cases. Secular trends in conjunction with the use of a discrete staging system. In most of the Burlington Growth Study sample, the lateral head film at age 15 was missing. None of the CVM stages 2, 3, and 4 reached a satisfactorily diagnostic reliability in the identification of imminent mandibular growth peak.
Bressan, Alberto; Lewicka, Marta
2018-03-01
We consider a free boundary problem for a system of PDEs, modeling the growth of a biological tissue. A morphogen, controlling volume growth, is produced by specific cells and then diffused and absorbed throughout the domain. The geometric shape of the growing tissue is determined by the instantaneous minimization of an elastic deformation energy, subject to a constraint on the volumetric growth. For an initial domain with C}^{2,α boundary, our main result establishes the local existence and uniqueness of a classical solution, up to a rigid motion.
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)
Quantitative metal magnetic memory reliability modeling for welded joints
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.
An integrated approach to human reliability analysis -- decision analytic dynamic reliability model
International Nuclear Information System (INIS)
Holmberg, J.; Hukki, K.; Norros, L.; Pulkkinen, U.; Pyy, P.
1999-01-01
The reliability of human operators in process control is sensitive to the context. In many contemporary human reliability analysis (HRA) methods, this is not sufficiently taken into account. The aim of this article is that integration between probabilistic and psychological approaches in human reliability should be attempted. This is achieved first, by adopting such methods that adequately reflect the essential features of the process control activity, and secondly, by carrying out an interactive HRA process. Description of the activity context, probabilistic modeling, and psychological analysis form an iterative interdisciplinary sequence of analysis in which the results of one sub-task maybe input to another. The analysis of the context is carried out first with the help of a common set of conceptual tools. The resulting descriptions of the context promote the probabilistic modeling, through which new results regarding the probabilistic dynamics can be achieved. These can be incorporated in the context descriptions used as reference in the psychological analysis of actual performance. The results also provide new knowledge of the constraints of activity, by providing information of the premises of the operator's actions. Finally, the stochastic marked point process model gives a tool, by which psychological methodology may be interpreted and utilized for reliability analysis
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.
A Survey of Software Reliability Modeling and Estimation
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
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
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.
Maximum Entropy Discrimination Poisson Regression for Software Reliability Modeling.
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.
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
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
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.)
Mudcake growth: Model and implications
Liu, Q.; Santamarina, Carlos
2017-01-01
cementing, and to prevent partial differential sticking. We developed a robust mud cake growth model for water-based mud based on wide stress-range constitutive equations within a Lagrangian reference system to avoid non-natural moving boundary solutions
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
Learning reliable manipulation strategies without initial physical models
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.
A mechanism of extreme growth and reliable signaling in sexually selected ornaments and weapons.
Emlen, Douglas J; Warren, Ian A; Johns, Annika; Dworkin, Ian; Lavine, Laura Corley
2012-08-17
Many male animals wield ornaments or weapons of exaggerated proportions. We propose that increased cellular sensitivity to signaling through the insulin/insulin-like growth factor (IGF) pathway may be responsible for the extreme growth of these structures. We document how rhinoceros beetle horns, a sexually selected weapon, are more sensitive to nutrition and more responsive to perturbation of the insulin/IGF pathway than other body structures. We then illustrate how enhanced sensitivity to insulin/IGF signaling in a growing ornament or weapon would cause heightened condition sensitivity and increased variability in expression among individuals--critical properties of reliable signals of male quality. The possibility that reliable signaling arises as a by-product of the growth mechanism may explain why trait exaggeration has evolved so many different times in the context of sexual selection.
Using LISREL to Evaluate Measurement Models and Scale Reliability.
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…
Travel Time Reliability for Urban Networks : Modelling and Empirics
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
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
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
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
Statistical models and methods for reliability and survival analysis
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
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...
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.
International Nuclear Information System (INIS)
Nakamura, Daisuke; Suzumura, Akitoshi; Shigetoh, Keisuke
2015-01-01
Highly reliable low-cost protective coatings have been sought after for use in crucibles and susceptors for bulk and epitaxial film growth processes involving wide bandgap materials. Here, we propose a production technique for ultra-thick (50–200 μmt) tantalum carbide (TaC) protective coatings on graphite substrates, which consists of TaC slurry application and subsequent sintering processes, i.e., a wet ceramic process. Structural analysis of the sintered TaC layers indicated that they have a dense granular structure containing coarse grain with sizes of 10–50 μm. Furthermore, no cracks or pinholes penetrated through the layers, i.e., the TaC layers are highly reliable protective coatings. The analysis also indicated that no plastic deformation occurred during the production process, and the non-textured crystalline orientation of the TaC layers is the origin of their high reliability and durability. The TaC-coated graphite crucibles were tested in an aluminum nitride (AlN) sublimation growth process, which involves extremely corrosive conditions, and demonstrated their practical reliability and durability in the AlN growth process as a TaC-coated graphite. The application of the TaC-coated graphite materials to crucibles and susceptors for use in bulk AlN single crystal growth, bulk silicon carbide (SiC) single crystal growth, chemical vapor deposition of epitaxial SiC films, and metal-organic vapor phase epitaxy of group-III nitrides will lead to further improvements in crystal quality and reduced processing costs
Energy Technology Data Exchange (ETDEWEB)
Nakamura, Daisuke; Suzumura, Akitoshi; Shigetoh, Keisuke [Toyota Central R and D Labs., Inc., Nagakute, Aichi 480-1192 (Japan)
2015-02-23
Highly reliable low-cost protective coatings have been sought after for use in crucibles and susceptors for bulk and epitaxial film growth processes involving wide bandgap materials. Here, we propose a production technique for ultra-thick (50–200 μmt) tantalum carbide (TaC) protective coatings on graphite substrates, which consists of TaC slurry application and subsequent sintering processes, i.e., a wet ceramic process. Structural analysis of the sintered TaC layers indicated that they have a dense granular structure containing coarse grain with sizes of 10–50 μm. Furthermore, no cracks or pinholes penetrated through the layers, i.e., the TaC layers are highly reliable protective coatings. The analysis also indicated that no plastic deformation occurred during the production process, and the non-textured crystalline orientation of the TaC layers is the origin of their high reliability and durability. The TaC-coated graphite crucibles were tested in an aluminum nitride (AlN) sublimation growth process, which involves extremely corrosive conditions, and demonstrated their practical reliability and durability in the AlN growth process as a TaC-coated graphite. The application of the TaC-coated graphite materials to crucibles and susceptors for use in bulk AlN single crystal growth, bulk silicon carbide (SiC) single crystal growth, chemical vapor deposition of epitaxial SiC films, and metal-organic vapor phase epitaxy of group-III nitrides will lead to further improvements in crystal quality and reduced processing costs.
Average inactivity time model, associated orderings and reliability properties
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.
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
solveME: fast and reliable solution of nonlinear ME models
DEFF Research Database (Denmark)
Yang, Laurence; Ma, Ding; Ebrahim, Ali
2016-01-01
Background: Genome-scale models of metabolism and macromolecular expression (ME) significantly expand the scope and predictive capabilities of constraint-based modeling. ME models present considerable computational challenges: they are much (>30 times) larger than corresponding metabolic reconstr......Background: Genome-scale models of metabolism and macromolecular expression (ME) significantly expand the scope and predictive capabilities of constraint-based modeling. ME models present considerable computational challenges: they are much (>30 times) larger than corresponding metabolic...... reconstructions (M models), are multiscale, and growth maximization is a nonlinear programming (NLP) problem, mainly due to macromolecule dilution constraints. Results: Here, we address these computational challenges. We develop a fast and numerically reliable solution method for growth maximization in ME models...
The reliability of the Adelaide in-shoe foot model.
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.
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...
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.
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
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
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 modeling and analysis of smart power systems
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
A general graphical user interface for automatic reliability modeling
Liceaga, Carlos A.; Siewiorek, Daniel P.
1991-01-01
Reported here is a general Graphical User Interface (GUI) for automatic reliability modeling of Processor Memory Switch (PMS) structures using a Markov model. This GUI is based on a hierarchy of windows. One window has graphical editing capabilities for specifying the system's communication structure, hierarchy, reconfiguration capabilities, and requirements. Other windows have field texts, popup menus, and buttons for specifying parameters and selecting actions. An example application of the GUI is given.
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.
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.
NHPP-Based Software Reliability Models Using Equilibrium Distribution
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.
Viscoelastic model of tungsten 'fuzz' growth
International Nuclear Information System (INIS)
Krasheninnikov, S I
2011-01-01
A viscoelastic model of fuzz growth is presented. The model describes the main features of tungsten fuzz observed in experiments. It gives estimates of fuzz growth rate and temperature range close to experimental ones.
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
Reliability assessment of competing risks with generalized mixed shock models
International Nuclear Information System (INIS)
Rafiee, Koosha; Feng, Qianmei; Coit, David W.
2017-01-01
This paper investigates reliability modeling for systems subject to dependent competing risks considering the impact from a new generalized mixed shock model. Two dependent competing risks are soft failure due to a degradation process, and hard failure due to random shocks. The shock process contains fatal shocks that can cause hard failure instantaneously, and nonfatal shocks that impact the system in three different ways: 1) damaging the unit by immediately increasing the degradation level, 2) speeding up the deterioration by accelerating the degradation rate, and 3) weakening the unit strength by reducing the hard failure threshold. While the first impact from nonfatal shocks comes from each individual shock, the other two impacts are realized when the condition for a new generalized mixed shock model is satisfied. Unlike most existing mixed shock models that consider a combination of two shock patterns, our new generalized mixed shock model includes three classic shock patterns. According to the proposed generalized mixed shock model, the degradation rate and the hard failure threshold can simultaneously shift multiple times, whenever the condition for one of these three shock patterns is satisfied. An example using micro-electro-mechanical systems devices illustrates the effectiveness of the proposed approach with sensitivity analysis. - Highlights: • A rich reliability model for systems subject to dependent failures is proposed. • The degradation rate and the hard failure threshold can shift simultaneously. • The shift is triggered by a new generalized mixed shock model. • The shift can occur multiple times under the generalized mixed shock model.
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
Mudcake growth: Model and implications
Liu, Q.
2017-12-15
Oil and gas account for 60% of the world\\'s energy consumption. Drilling muds that are used to advance oil and gas wells must be engineered to avoid wellbore integrity problems associated with mud cake formation, to favor cake erosion during cementing, and to prevent partial differential sticking. We developed a robust mud cake growth model for water-based mud based on wide stress-range constitutive equations within a Lagrangian reference system to avoid non-natural moving boundary solutions. The comprehensive mud cake growth model readily accommodates environmental factors (e.g., temperature, pH, and ionic concentration) and defines the yield stress distribution for displacement-erosion analyses. Results show that the mud cake thickness is more sensitive to time than to filtration pressure, therefore, time controls the non-uniform distribution of mudcake thickness during drilling. Long filtration time, high permeability, high salinity, high in-situ temperature and low viscosity exacerbate fluid loss and give rise to thick filter cakes. The analysis of residual cake thickness during cement displacement must take into account the effective stress dependent mudcake formation and the time-dependent mud thixotropy. Thixotropy dominates the mud yield stress at high void ratios, e.g. e > 20. The offsetting force that causes differential pressure sticking increases sub-linearly as a power function of the still-time.
Testing the reliability of ice-cream cone model
Pan, Zonghao; Shen, Chenglong; Wang, Chuanbing; Liu, Kai; Xue, Xianghui; Wang, Yuming; Wang, Shui
2015-04-01
Coronal Mass Ejections (CME)'s properties are important to not only the physical scene itself but space-weather prediction. Several models (such as cone model, GCS model, and so on) have been raised to get rid of the projection effects within the properties observed by spacecraft. According to SOHO/ LASCO observations, we obtain the 'real' 3D parameters of all the FFHCMEs (front-side full halo Coronal Mass Ejections) within the 24th solar cycle till July 2012, by the ice-cream cone model. Considering that the method to obtain 3D parameters from the CME observations by multi-satellite and multi-angle has higher accuracy, we use the GCS model to obtain the real propagation parameters of these CMEs in 3D space and compare the results with which by ice-cream cone model. Then we could discuss the reliability of the ice-cream cone model.
Creation and Reliability Analysis of Vehicle Dynamic Weighing Model
Directory of Open Access Journals (Sweden)
Zhi-Ling XU
2014-08-01
Full Text Available In this paper, it is modeled by using ADAMS to portable axle load meter of dynamic weighing system, controlling a single variable simulation weighing process, getting the simulation weighing data under the different speed and weight; simultaneously using portable weighing system with the same parameters to achieve the actual measurement, comparative analysis the simulation results under the same conditions, at 30 km/h or less, the simulation value and the measured value do not differ by more than 5 %, it is not only to verify the reliability of dynamic weighing model, but also to create possible for improving algorithm study efficiency by using dynamic weighing model simulation.
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.
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.
Lazzaroni, Massimo
2012-01-01
This book gives a practical guide for designers and users in Information and Communication Technology context. In particular, in the first Section, the definition of the fundamental terms according to the international standards are given. Then, some theoretical concepts and reliability models are presented in Chapters 2 and 3: the aim is to evaluate performance for components and systems and reliability growth. Chapter 4, by introducing the laboratory tests, puts in evidence the reliability concept from the experimental point of view. In ICT context, the failure rate for a given system can be
Pinhata, Juliana Maira Watanabe; Felippe, Isis Moreira; Gallo, Juliana Failde; Chimara, Erica; Ferrazoli, Lucilaine; de Oliveira, Rosangela Siqueira
2018-04-23
We evaluated the microscopic and macroscopic characteristics of mycobacteria growth indicator tube (MGIT) cultures for the presumptive identification of the Mycobacterium tuberculosis complex (MTBC) and assessed the reliability of this strategy for correctly directing isolates to drug susceptibility testing (DST) or species identification. A total of 1526 isolates of mycobacteria received at the Instituto Adolfo Lutz were prospectively subjected to presumptive identification by the observation of growth characteristics along with cord formation detection via microscopy. The presumptive identification showed a sensitivity, specificity and accuracy of 98.8, 92.5 and 97.9 %, respectively. Macroscopic analysis of MTBC isolates that would have been erroneously classified as non-tuberculous mycobacteria based solely on microscopic morphology enabled us to direct them rapidly to DST, representing a substantial gain to patients. In conclusion, the growth characteristics of mycobacteria in MGIT, when considered along with cord formation, increased the reliability of the presumptive identification, which has a great impact on the laboratory budget and turnaround times.
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
Directory of Open Access Journals (Sweden)
Dejun Yang
Full Text Available ABSTRACT Simulations for root growth, crop growth, and N uptake in agro-hydrological models are of significant concern to researchers. SWMS_2D is one of the most widely used physical hydrologically related models. This model solves equations that govern soil-water movement by the finite element method, and has a public access source code. Incorporating key agricultural components into the SWMS_2D model is of practical importance, especially for modeling some critical cereal crops such as winter wheat. We added root growth, crop growth, and N uptake modules into SWMS_2D. The root growth model had two sub-models, one for root penetration and the other for root length distribution. The crop growth model used was adapted from EU-ROTATE_N, linked to the N uptake model. Soil-water limitation, nitrogen limitation, and temperature effects were all considered in dry-weight modeling. Field experiments for winter wheat in Bouwing, the Netherlands, in 1983-1984 were selected for validation. Good agreements were achieved between simulations and measurements, including soil water content at different depths, normalized root length distribution, dry weight and nitrogen uptake. This indicated that the proposed new modules used in the SWMS_2D model are robust and reliable. In the future, more rigorous validation should be carried out, ideally under 2D situations, and attention should be paid to improve some modules, including the module simulating soil N mineralization.
Reliability modelling - PETROBRAS 2010 integrated gas supply chain
Energy Technology Data Exchange (ETDEWEB)
Faertes, Denise; Heil, Luciana; Saker, Leonardo; Vieira, Flavia; Risi, Francisco; Domingues, Joaquim; Alvarenga, Tobias; Carvalho, Eduardo; Mussel, Patricia
2010-09-15
The purpose of this paper is to present the innovative reliability modeling of Petrobras 2010 integrated gas supply chain. The model represents a challenge in terms of complexity and software robustness. It was jointly developed by PETROBRAS Gas and Power Department and Det Norske Veritas. It was carried out with the objective of evaluating security of supply of 2010 gas network design that was conceived to connect Brazilian Northeast and Southeast regions. To provide best in class analysis, state of the art software was used to quantify the availability and the efficiency of the overall network and its individual components.
Evaluating the reliability of predictions made using environmental transfer models
International Nuclear Information System (INIS)
1989-01-01
The development and application of mathematical models for predicting the consequences of releases of radionuclides into the environment from normal operations in the nuclear fuel cycle and in hypothetical accident conditions has increased dramatically in the last two decades. This Safety Practice publication has been prepared to provide guidance on the available methods for evaluating the reliability of environmental transfer model predictions. It provides a practical introduction of the subject and a particular emphasis has been given to worked examples in the text. It is intended to supplement existing IAEA publications on environmental assessment methodology. 60 refs, 17 figs, 12 tabs
Reliability physics and engineering time-to-failure modeling
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...
Mathematical modeling of microbial growth in milk
Directory of Open Access Journals (Sweden)
Jhony Tiago Teleken
2011-12-01
Full Text Available A mathematical model to predict microbial growth in milk was developed and analyzed. The model consists of a system of two differential equations of first order. The equations are based on physical hypotheses of population growth. The model was applied to five different sets of data of microbial growth in dairy products selected from Combase, which is the most important database in the area with thousands of datasets from around the world, and the results showed a good fit. In addition, the model provides equations for the evaluation of the maximum specific growth rate and the duration of the lag phase which may provide useful information about microbial growth.
Latent Growth and Dynamic Structural Equation Models.
Grimm, Kevin J; Ram, Nilam
2018-05-07
Latent growth models make up a class of methods to study within-person change-how it progresses, how it differs across individuals, what are its determinants, and what are its consequences. Latent growth methods have been applied in many domains to examine average and differential responses to interventions and treatments. In this review, we introduce the growth modeling approach to studying change by presenting different models of change and interpretations of their model parameters. We then apply these methods to examining sex differences in the development of binge drinking behavior through adolescence and into adulthood. Advances in growth modeling methods are then discussed and include inherently nonlinear growth models, derivative specification of growth models, and latent change score models to study stochastic change processes. We conclude with relevant design issues of longitudinal studies and considerations for the analysis of longitudinal data.
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
Do downscaled general circulation models reliably simulate historical climatic conditions?
Bock, Andrew R.; Hay, Lauren E.; McCabe, Gregory J.; Markstrom, Steven L.; Atkinson, R. Dwight
2018-01-01
The accuracy of statistically downscaled (SD) general circulation model (GCM) simulations of monthly surface climate for historical conditions (1950–2005) was assessed for the conterminous United States (CONUS). The SD monthly precipitation (PPT) and temperature (TAVE) from 95 GCMs from phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5) were used as inputs to a monthly water balance model (MWBM). Distributions of MWBM input (PPT and TAVE) and output [runoff (RUN)] variables derived from gridded station data (GSD) and historical SD climate were compared using the Kolmogorov–Smirnov (KS) test For all three variables considered, the KS test results showed that variables simulated using CMIP5 generally are more reliable than those derived from CMIP3, likely due to improvements in PPT simulations. At most locations across the CONUS, the largest differences between GSD and SD PPT and RUN occurred in the lowest part of the distributions (i.e., low-flow RUN and low-magnitude PPT). Results indicate that for the majority of the CONUS, there are downscaled GCMs that can reliably simulate historical climatic conditions. But, in some geographic locations, none of the SD GCMs replicated historical conditions for two of the three variables (PPT and RUN) based on the KS test, with a significance level of 0.05. In these locations, improved GCM simulations of PPT are needed to more reliably estimate components of the hydrologic cycle. Simple metrics and statistical tests, such as those described here, can provide an initial set of criteria to help simplify GCM selection.
DEFF Research Database (Denmark)
Jónsdóttir, Kristjana Ýr; Schmiegel, Jürgen; Jensen, Eva Bjørn Vedel
2008-01-01
In the present paper, we give a condensed review, for the nonspecialist reader, of a new modelling framework for spatio-temporal processes, based on Lévy theory. We show the potential of the approach in stochastic geometry and spatial statistics by studying Lévy-based growth modelling of planar o...... objects. The growth models considered are spatio-temporal stochastic processes on the circle. As a by product, flexible new models for space–time covariance functions on the circle are provided. An application of the Lévy-based growth models to tumour growth is discussed....
Using the Weibull distribution reliability, modeling and inference
McCool, John I
2012-01-01
Understand and utilize the latest developments in Weibull inferential methods While the Weibull distribution is widely used in science and engineering, most engineers do not have the necessary statistical training to implement the methodology effectively. Using the Weibull Distribution: Reliability, Modeling, and Inference fills a gap in the current literature on the topic, introducing a self-contained presentation of the probabilistic basis for the methodology while providing powerful techniques for extracting information from data. The author explains the use of the Weibull distribution
Understanding software faults and their role in software reliability modeling
Munson, John C.
1994-01-01
This study is a direct result of an on-going project to model the reliability of a large real-time control avionics system. In previous modeling efforts with this system, hardware reliability models were applied in modeling the reliability behavior of this system. In an attempt to enhance the performance of the adapted reliability models, certain software attributes were introduced in these models to control for differences between programs and also sequential executions of the same program. As the basic nature of the software attributes that affect software reliability become better understood in the modeling process, this information begins to have important implications on the software development process. A significant problem arises when raw attribute measures are to be used in statistical models as predictors, for example, of measures of software quality. This is because many of the metrics are highly correlated. Consider the two attributes: lines of code, LOC, and number of program statements, Stmts. In this case, it is quite obvious that a program with a high value of LOC probably will also have a relatively high value of Stmts. In the case of low level languages, such as assembly language programs, there might be a one-to-one relationship between the statement count and the lines of code. When there is a complete absence of linear relationship among the metrics, they are said to be orthogonal or uncorrelated. Usually the lack of orthogonality is not serious enough to affect a statistical analysis. However, for the purposes of some statistical analysis such as multiple regression, the software metrics are so strongly interrelated that the regression results may be ambiguous and possibly even misleading. Typically, it is difficult to estimate the unique effects of individual software metrics in the regression equation. The estimated values of the coefficients are very sensitive to slight changes in the data and to the addition or deletion of variables in the
Reliable low precision simulations in land surface models
Dawson, Andrew; Düben, Peter D.; MacLeod, David A.; Palmer, Tim N.
2017-12-01
Weather and climate models must continue to increase in both resolution and complexity in order that forecasts become more accurate and reliable. Moving to lower numerical precision may be an essential tool for coping with the demand for ever increasing model complexity in addition to increasing computing resources. However, there have been some concerns in the weather and climate modelling community over the suitability of lower precision for climate models, particularly for representing processes that change very slowly over long time-scales. These processes are difficult to represent using low precision due to time increments being systematically rounded to zero. Idealised simulations are used to demonstrate that a model of deep soil heat diffusion that fails when run in single precision can be modified to work correctly using low precision, by splitting up the model into a small higher precision part and a low precision part. This strategy retains the computational benefits of reduced precision whilst preserving accuracy. This same technique is also applied to a full complexity land surface model, resulting in rounding errors that are significantly smaller than initial condition and parameter uncertainties. Although lower precision will present some problems for the weather and climate modelling community, many of the problems can likely be overcome using a straightforward and physically motivated application of reduced precision.
Stochastic models for tumoral growth
Escudero, Carlos
2006-01-01
Strong experimental evidence has indicated that tumor growth belongs to the molecular beam epitaxy universality class. This type of growth is characterized by the constraint of cell proliferation to the tumor border, and surface diffusion of cells at the growing edge. Tumor growth is thus conceived as a competition for space between the tumor and the host, and cell diffusion at the tumor border is an optimal strategy adopted for minimizing the pressure and helping tumor development. Two stoch...
Mechanistic model for microbial growth on hydrocarbons
Energy Technology Data Exchange (ETDEWEB)
Mallee, F M; Blanch, H W
1977-12-01
Based on available information describing the transport and consumption of insoluble alkanes, a mechanistic model is proposed for microbial growth on hydrocarbons. The model describes the atypical growth kinetics observed, and has implications in the design of large scale equipment for single cell protein (SCP) manufacture from hydrocarbons. The model presents a framework for comparison of the previously published experimental kinetic data.
Reliable critical sized defect rodent model for cleft palate research.
Mostafa, Nesrine Z; Doschak, Michael R; Major, Paul W; Talwar, Reena
2014-12-01
Suitable animal models are necessary to test the efficacy of new bone grafting therapies in cleft palate surgery. Rodent models of cleft palate are available but have limitations. This study compared and modified mid-palate cleft (MPC) and alveolar cleft (AC) models to determine the most reliable and reproducible model for bone grafting studies. Published MPC model (9 × 5 × 3 mm(3)) lacked sufficient information for tested rats. Our initial studies utilizing AC model (7 × 4 × 3 mm(3)) in 8 and 16 weeks old Sprague Dawley (SD) rats revealed injury to adjacent structures. After comparing anteroposterior and transverse maxillary dimensions in 16 weeks old SD and Wistar rats, virtual planning was performed to modify MPC and AC defects dimensions, taking the adjacent structures into consideration. Modified MPC (7 × 2.5 × 1 mm(3)) and AC (5 × 2.5 × 1 mm(3)) defects were employed in 16 weeks old Wistar rats and healing was monitored by micro-computed tomography and histology. Maxillary dimensions in SD and Wistar rats were not significantly different. Preoperative virtual planning enhanced postoperative surgical outcomes. Bone healing occurred at defect margin leaving central bone void confirming the critical size nature of the modified MPC and AC defects. Presented modifications for MPC and AC models created clinically relevant and reproducible defects. Copyright © 2014 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.
Testing mechanistic models of growth in insects.
Maino, James L; Kearney, Michael R
2015-11-22
Insects are typified by their small size, large numbers, impressive reproductive output and rapid growth. However, insect growth is not simply rapid; rather, insects follow a qualitatively distinct trajectory to many other animals. Here we present a mechanistic growth model for insects and show that increasing specific assimilation during the growth phase can explain the near-exponential growth trajectory of insects. The presented model is tested against growth data on 50 insects, and compared against other mechanistic growth models. Unlike the other mechanistic models, our growth model predicts energy reserves per biomass to increase with age, which implies a higher production efficiency and energy density of biomass in later instars. These predictions are tested against data compiled from the literature whereby it is confirmed that insects increase their production efficiency (by 24 percentage points) and energy density (by 4 J mg(-1)) between hatching and the attainment of full size. The model suggests that insects achieve greater production efficiencies and enhanced growth rates by increasing specific assimilation and increasing energy reserves per biomass, which are less costly to maintain than structural biomass. Our findings illustrate how the explanatory and predictive power of mechanistic growth models comes from their grounding in underlying biological processes. © 2015 The Author(s).
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.).
Reliability model for offshore wind farms; Paalidelighedsmodel for havvindmoelleparker
Energy Technology Data Exchange (ETDEWEB)
Christensen, P.; Lundtang Paulsen, J.; Lybech Toegersen, M.; Krogh, T. [Risoe National Lab., Roskilde (Denmark); Raben, N.; Donovan, M.H.; Joergensen, L. [SEAS (Denmark); Winther-Jensen, M.
2002-05-01
A method for the prediction of the mean availability for an offshore windfarm has been developed. Factors comprised are the reliability of the single turbine, the strategy for preventive maintenance the climate, the number of repair teams, and the type of boats available for transport. The mean availability is defined as the sum of the fractions of time, where each turbine is available for production. The project has been carried out together with SEAS Wind Technique, and their site Roedsand has been chosen as the example of the work. A climate model has been created based on actual site measurements. The prediction of the availability is done with a Monte Carlo-simulation. Software was developed for the preparation of the climate model from weather measurements as well as for the Monte carlo-simulation. Three examples have been simulated, one with guessed parametres, and the other two with parameters more close to the Roedsand case. (au)
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.)
Probabilistic Model for Fatigue Crack Growth in Welded Bridge Details
DEFF Research Database (Denmark)
Toft, Henrik Stensgaard; Sørensen, John Dalsgaard; Yalamas, Thierry
2013-01-01
In the present paper a probabilistic model for fatigue crack growth in welded steel details in road bridges is presented. The probabilistic model takes the influence of bending stresses in the joints into account. The bending stresses can either be introduced by e.g. misalignment or redistribution...... of stresses in the structure. The fatigue stress ranges are estimated from traffic measurements and a generic bridge model. Based on the probabilistic models for the resistance and load the reliability is estimated for a typical welded steel detail. The results show that large misalignments in the joints can...
Scalable Joint Models for Reliable Uncertainty-Aware Event Prediction.
Soleimani, Hossein; Hensman, James; Saria, Suchi
2017-08-21
Missing data and noisy observations pose significant challenges for reliably predicting events from irregularly sampled multivariate time series (longitudinal) data. Imputation methods, which are typically used for completing the data prior to event prediction, lack a principled mechanism to account for the uncertainty due to missingness. Alternatively, state-of-the-art joint modeling techniques can be used for jointly modeling the longitudinal and event data and compute event probabilities conditioned on the longitudinal observations. These approaches, however, make strong parametric assumptions and do not easily scale to multivariate signals with many observations. Our proposed approach consists of several key innovations. First, we develop a flexible and scalable joint model based upon sparse multiple-output Gaussian processes. Unlike state-of-the-art joint models, the proposed model can explain highly challenging structure including non-Gaussian noise while scaling to large data. Second, we derive an optimal policy for predicting events using the distribution of the event occurrence estimated by the joint model. The derived policy trades-off the cost of a delayed detection versus incorrect assessments and abstains from making decisions when the estimated event probability does not satisfy the derived confidence criteria. Experiments on a large dataset show that the proposed framework significantly outperforms state-of-the-art techniques in event prediction.
Trajectories and models of individual growth
Directory of Open Access Journals (Sweden)
Arseniy Karkach
2006-11-01
Full Text Available It has long been recognized that the patterns of growth play an important role in the evolution of age trajectories of fertility and mortality (Williams, 1957. Life history studies would benefit from a better understanding of strategies and mechanisms of growth, but still no comparative research on individual growth strategies has been conducted. Growth patterns and methods have been shaped by evolution and a great variety of them are observed. Two distinct patterns - determinate and indeterminate growth - are of a special interest for these studies since they present qualitatively different outcomes of evolution. We attempt to draw together studies covering growth in plant and animal species across a wide range of phyla focusing primarily on the noted qualitative features. We also review mathematical descriptions of growth, namely empirical growth curves and growth models, and discuss the directions of future research.
Reliability and Validity of a Spanish Version of the Posttraumatic Growth Inventory
Weiss, Tzipi; Berger, Roni
2006-01-01
Objectives. This study was designed to adapt and validate a Spanish translation of the Posttraumatic Growth Inventory (PTGI) for the assessment of positive life changes following the stressful experiences of immigration. Method. A cross-cultural equivalence model was used to pursue semantic, content, conceptual, and technical equivalence.…
Nonconvex Model of Material Growth: Mathematical Theory
Ganghoffer, J. F.; Plotnikov, P. I.; Sokolowski, J.
2018-06-01
The model of volumetric material growth is introduced in the framework of finite elasticity. The new results obtained for the model are presented with complete proofs. The state variables include the deformations, temperature and the growth factor matrix function. The existence of global in time solutions for the quasistatic deformations boundary value problem coupled with the energy balance and the evolution of the growth factor is shown. The mathematical results can be applied to a wide class of growth models in mechanics and biology.
African Journals Online (AJOL)
eobe
Corresponding author, Tel: +234-703. RELIABILITY .... V , , given by the code of practice. However, checks must .... an optimization procedure over the failure domain F corresponding .... of Concrete Members based on Utility Theory,. Technical ...
Reliability assessment using degradation models: bayesian and classical approaches
Directory of Open Access Journals (Sweden)
Marta Afonso Freitas
2010-04-01
Full Text Available Traditionally, reliability assessment of devices has been based on (accelerated life tests. However, for highly reliable products, little information about reliability is provided by life tests in which few or no failures are typically observed. Since most failures arise from a degradation mechanism at work for which there are characteristics that degrade over time, one alternative is monitor the device for a period of time and assess its reliability from the changes in performance (degradation observed during that period. The goal of this article is to illustrate how degradation data can be modeled and analyzed by using "classical" and Bayesian approaches. Four methods of data analysis based on classical inference are presented. Next we show how Bayesian methods can also be used to provide a natural approach to analyzing degradation data. The approaches are applied to a real data set regarding train wheels degradation.Tradicionalmente, o acesso à confiabilidade de dispositivos tem sido baseado em testes de vida (acelerados. Entretanto, para produtos altamente confiáveis, pouca informação a respeito de sua confiabilidade é fornecida por testes de vida no quais poucas ou nenhumas falhas são observadas. Uma vez que boa parte das falhas é induzida por mecanismos de degradação, uma alternativa é monitorar o dispositivo por um período de tempo e acessar sua confiabilidade através das mudanças em desempenho (degradação observadas durante aquele período. O objetivo deste artigo é ilustrar como dados de degradação podem ser modelados e analisados utilizando-se abordagens "clássicas" e Bayesiana. Quatro métodos de análise de dados baseados em inferência clássica são apresentados. A seguir, mostramos como os métodos Bayesianos podem também ser aplicados para proporcionar uma abordagem natural à análise de dados de degradação. As abordagens são aplicadas a um banco de dados real relacionado à degradação de rodas de trens.
Pollution externalities in a Schumpeterian growth model
Koesler, Simon
2010-01-01
This paper extends a standard Schumpeterian growth model to include an environmental dimension. Thereby, it explicitly links the pollution intensity of economic activity to technological progress. In a second step, it investigates the effect of pollution on economic growth under the assumption that pollution intensities are related to technological progress. Several conclusions emerge from the model. In equilibrium, the economy follows a balanced growth path. The effect of pollution on the ec...
A Dialogue about MCQs, Reliability, and Item Response Modelling
Wright, Daniel B.; Skagerberg, Elin M.
2006-01-01
Multiple choice questions (MCQs) are becoming more common in UK psychology departments and the need to assess their reliability is apparent. Having examined the reliability of MCQs in our department we faced many questions from colleagues about why we were examining reliability, what it was that we were doing, and what should be reported when…
Suitability Analysis of Continuous-Use Reliability Growth Projection Models
2015-03-26
47 Appendix B. Storyboard . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51...0 8 17 4 3 2 5 1 7 3 5 1 7 0 8 18 5 2 3 4 1 7 4 4 1 7 0 8 50 Appendix B. Storyboard 51 Bibliography 1. AMSC. Department of Defense Handbook
Numerical Model based Reliability Estimation of Selective Laser Melting Process
DEFF Research Database (Denmark)
Mohanty, Sankhya; Hattel, Jesper Henri
2014-01-01
Selective laser melting is developing into a standard manufacturing technology with applications in various sectors. However, the process is still far from being at par with conventional processes such as welding and casting, the primary reason of which is the unreliability of the process. While...... of the selective laser melting process. A validated 3D finite-volume alternating-direction-implicit numerical technique is used to model the selective laser melting process, and is calibrated against results from single track formation experiments. Correlation coefficients are determined for process input...... parameters such as laser power, speed, beam profile, etc. Subsequently, uncertainties in the processing parameters are utilized to predict a range for the various outputs, using a Monte Carlo method based uncertainty analysis methodology, and the reliability of the process is established....
Rovinelli, Andrea; Guilhem, Yoann; Proudhon, Henry; Lebensohn, Ricardo A.; Ludwig, Wolfgang; Sangid, Michael D.
2017-06-01
Microstructurally small cracks exhibit large variability in their fatigue crack growth rate. It is accepted that the inherent variability in microstructural features is related to the uncertainty in the growth rate. However, due to (i) the lack of cycle-by-cycle experimental data, (ii) the complexity of the short crack growth phenomenon, and (iii) the incomplete physics of constitutive relationships, only empirical damage metrics have been postulated to describe the short crack driving force metric (SCDFM) at the mesoscale level. The identification of the SCDFM of polycrystalline engineering alloys is a critical need, in order to achieve more reliable fatigue life prediction and improve material design. In this work, the first steps in the development of a general probabilistic framework are presented, which uses experimental result as an input, retrieves missing experimental data through crystal plasticity (CP) simulations, and extracts correlations utilizing machine learning and Bayesian networks (BNs). More precisely, experimental results representing cycle-by-cycle data of a short crack growing through a beta-metastable titanium alloy, VST-55531, have been acquired via phase and diffraction contrast tomography. These results serve as an input for FFT-based CP simulations, which provide the micromechanical fields influenced by the presence of the crack, complementing the information available from the experiment. In order to assess the correlation between postulated SCDFM and experimental observations, the data is mined and analyzed utilizing BNs. Results show the ability of the framework to autonomously capture relevant correlations and the equivalence in the prediction capability of different postulated SCDFMs for the high cycle fatigue regime.
Modelling asymmetric growth in crowded plant communities
DEFF Research Database (Denmark)
Damgaard, Christian
2010-01-01
A class of models that may be used to quantify the effect of size-asymmetric competition in crowded plant communities by estimating a community specific degree of size-asymmetric growth for each species in the community is suggested. The model consists of two parts: an individual size......-asymmetric growth part, where growth is assumed to be proportional to a power function of the size of the individual, and a term that reduces the relative growth rate as a decreasing function of the individual plant size and the competitive interactions from other plants in the neighbourhood....
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.
Evaluating North American Electric Grid Reliability Using the Barabasi-Albert Network Model
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...
Growth curve models and statistical diagnostics
Pan, Jian-Xin
2002-01-01
Growth-curve models are generalized multivariate analysis-of-variance models. These models are especially useful for investigating growth problems on short times in economics, biology, medical research, and epidemiology. This book systematically introduces the theory of the GCM with particular emphasis on their multivariate statistical diagnostics, which are based mainly on recent developments made by the authors and their collaborators. The authors provide complete proofs of theorems as well as practical data sets and MATLAB code.
Design Protocols and Analytical Strategies that Incorporate Structural Reliability Models
Duffy, Stephen F.
1997-01-01
Al single crystal turbine blade material; map a simplistic failure strength envelope of the material; develop a statistically based reliability computer algorithm, verify the reliability model and computer algorithm, and model stator vanes for rig tests. Thus establishing design protocols that enable the engineer to analyze and predict the mechanical behavior of ceramic composites and intermetallics would mitigate the prototype (trial and error) approach currently used by the engineering community. The primary objective of the research effort supported by this short term grant is the continued creation of enabling technologies for the macroanalysis of components fabricated from ceramic composites and intermetallic material systems. The creation of enabling technologies aids in shortening the product development cycle of components fabricated from the new high technology materials.
Energy Technology Data Exchange (ETDEWEB)
Michael, Joseph Richard; Grant, Richard P.; Rodriguez, Mark Andrew; Pillars, Jamin; Susan, Donald Francis; McKenzie, Bonnie Beth; Yelton, William Graham
2012-01-01
Tin (Sn) whiskers are conductive Sn filaments that grow from Sn-plated surfaces, such as surface finishes on electronic packages. The phenomenon of Sn whiskering has become a concern in recent years due to requirements for lead (Pb)-free soldering and surface finishes in commercial electronics. Pure Sn finishes are more prone to whisker growth than their Sn-Pb counterparts and high profile failures due to whisker formation (causing short circuits) in space applications have been documented. At Sandia, Sn whiskers are of interest due to increased use of Pb-free commercial off-the-shelf (COTS) parts and possible future requirements for Pb-free solders and surface finishes in high-reliability microelectronics. Lead-free solders and surface finishes are currently being used or considered for several Sandia applications. Despite the long history of Sn whisker research and the recently renewed interest in this topic, a comprehensive understanding of whisker growth remains elusive. This report describes recent research on characterization of Sn whiskers with the aim of understanding the underlying whisker growth mechanism(s). The report is divided into four sections and an Appendix. In Section 1, the Sn plating process is summarized. Specifically, the Sn plating parameters that were successful in producing samples with whiskers will be reviewed. In Section 2, the scanning electron microscopy (SEM) of Sn whiskers and time-lapse SEM studies of whisker growth will be discussed. This discussion includes the characterization of straight as well as kinked whiskers. In Section 3, a detailed discussion is given of SEM/EBSD (electron backscatter diffraction) techniques developed to determine the crystallography of Sn whiskers. In Section 4, these SEM/EBSD methods are employed to determine the crystallography of Sn whiskers, with a statistically significant number of whiskers analyzed. This is the largest study of Sn whisker crystallography ever reported. This section includes a
On a Versatile Stochastic Growth Model
Directory of Open Access Journals (Sweden)
Samiur Arif
2012-06-01
Full Text Available Growth phenomena are ubiquitous and pervasive not only in biology and the medical sciences, but also in economics, marketing and the computer and social sciences. We introduce a three-parameter version of the classic pure-birth process growth model when suitably instantiated, can be used to model growth phenomena in many seemingly unrelated application domains. We point out that the model is computationally attractive since it admits of conceptually simple, closed form solutions for the time-dependent probabilities.
Recent advances in modelling creep crack growth
International Nuclear Information System (INIS)
Riedel, H.
1988-08-01
At the time of the previous International Conference on Fracture, the C* integral had long been recognized as a promising load parameter for correlating crack growth rates in creep-ductile materials. The measured crack growth rates as a function of C* and of the temperature could be understood on the basis of micromechanical models. The distinction between C*-controlled and K I -controlled creep crack growth had been clarified and first attempts had been made to describe creep crack growth in the transient regime between elastic behavior and steady-state creep. This paper describes the progress in describing transient crack growth including the effect of primary creep. The effect of crack-tip geometry changes by blunting and by crack growth on the crack-tip fields and on the validity of C* is analyzed by idealizing the growing-crack geometry by a sharp notch and using recent solutions for the notch-tip fields. A few new three-dimensional calculations of C* are cited and important theoretical points are emphasized regarding the three-dimensional fields at crack tips. Finally, creep crack growth is described by continuum-damage models for which similarity solutions can be obtained. Crack growth under small-scale creep conditions turns out to be difficult to understand. Slightly different models yield very different crack growth rates. (orig.) With 4 figs
Approach for an integral power transformer reliability model
Schijndel, van A.; Wouters, P.A.A.F.; Steennis, E.F.; Wetzer, J.M.
2012-01-01
In electrical power transmission and distribution networks power transformers represent a crucial group of assets both in terms of reliability and investments. In order to safeguard the required quality at acceptable costs, decisions must be based on a reliable forecast of future behaviour. The aim
Wireless Channel Modeling Perspectives for Ultra-Reliable Communications
DEFF Research Database (Denmark)
Eggers, Patrick Claus F.; Popovski, Petar
2018-01-01
Ultra-Reliable Communication (URC) is one of the distinctive features of the upcoming 5G wireless communication. The level of reliability, going down to packet error rates (PER) of $10^{-9}$, should be sufficiently convincing in order to remove cables in an industrial setting or provide remote co...
Kinetic Model of Growth of Arthropoda Populations
Ershov, Yu. A.; Kuznetsov, M. A.
2018-05-01
Kinetic equations were derived for calculating the growth of crustacean populations ( Crustacea) based on the biological growth model suggested earlier using shrimp ( Caridea) populations as an example. The development cycle of successive stages for populations can be represented in the form of quasi-chemical equations. The kinetic equations that describe the development cycle of crustaceans allow quantitative prediction of the development of populations depending on conditions. In contrast to extrapolation-simulation models, in the developed kinetic model of biological growth the kinetic parameters are the experimental characteristics of population growth. Verification and parametric identification of the developed model on the basis of the experimental data showed agreement with experiment within the error of the measurement technique.
Compatible growth models and stand density diagrams
International Nuclear Information System (INIS)
Smith, N.J.; Brand, D.G.
1988-01-01
This paper discusses a stand average growth model based on the self-thinning rule developed and used to generate stand density diagrams. Procedures involved in testing are described and results are included
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.)
Models and data requirements for human reliability analysis
International Nuclear Information System (INIS)
1989-03-01
It has been widely recognised for many years that the safety of the nuclear power generation depends heavily on the human factors related to plant operation. This has been confirmed by the accidents at Three Mile Island and Chernobyl. Both these cases revealed how human actions can defeat engineered safeguards and the need for special operator training to cover the possibility of unexpected plant conditions. The importance of the human factor also stands out in the analysis of abnormal events and insights from probabilistic safety assessments (PSA's), which reveal a large proportion of cases having their origin in faulty operator performance. A consultants' meeting, organized jointly by the International Atomic Energy Agency (IAEA) and the International Institute for Applied Systems Analysis (IIASA) was held at IIASA in Laxenburg, Austria, December 7-11, 1987, with the aim of reviewing existing models used in Probabilistic Safety Assessment (PSA) for Human Reliability Analysis (HRA) and of identifying the data required. The report collects both the contributions offered by the members of the Expert Task Force and the findings of the extensive discussions that took place during the meeting. Refs, figs and tabs
Value function in economic growth model
Bagno, Alexander; Tarasyev, Alexandr A.; Tarasyev, Alexander M.
2017-11-01
Properties of the value function are examined in an infinite horizon optimal control problem with an unlimited integrand index appearing in the quality functional with a discount factor. Optimal control problems of such type describe solutions in models of economic growth. Necessary and sufficient conditions are derived to ensure that the value function satisfies the infinitesimal stability properties. It is proved that value function coincides with the minimax solution of the Hamilton-Jacobi equation. Description of the growth asymptotic behavior for the value function is provided for the logarithmic, power and exponential quality functionals and an example is given to illustrate construction of the value function in economic growth models.
Tax Evasion and Economic Growth in an Endogenous Growth Model
加藤, 秀弥; KATO, Hideya
2004-01-01
This paper presents an endogenous growth model with tax evasion where government expenditures affect production. An individual evades a tax so as to maximize his or her utility, the tax authority controls the detection probability to maximize net tax revenue, and the government chooses the income tax rate to maximize individuals’ utility. The main conclusions are as follows. First, the optical income tax rate with tax evasion is higher than that without tax evasion. Second, the rise in a ...
International Nuclear Information System (INIS)
Arndt, S. A.
2006-01-01
As software-based digital systems are becoming more and more common in all aspects of industrial process control, including the nuclear power industry, it is vital that the current state of the art in quality, reliability, and safety analysis be advanced to support the quantitative review of these systems. Several research groups throughout the world are working on the development and assessment of software-based digital system reliability methods and their applications in the nuclear power, aerospace, transportation, and defense industries. However, these groups are hampered by the fact that software experts and probabilistic safety assessment experts view reliability engineering very differently. This paper discusses the characteristics of a common vocabulary and modeling framework. (authors)
Reliability Analysis of Wireless Sensor Networks Using Markovian Model
Directory of Open Access Journals (Sweden)
Jin Zhu
2012-01-01
Full Text Available This paper investigates reliability analysis of wireless sensor networks whose topology is switching among possible connections which are governed by a Markovian chain. We give the quantized relations between network topology, data acquisition rate, nodes' calculation ability, and network reliability. By applying Lyapunov method, sufficient conditions of network reliability are proposed for such topology switching networks with constant or varying data acquisition rate. With the conditions satisfied, the quantity of data transported over wireless network node will not exceed node capacity such that reliability is ensured. Our theoretical work helps to provide a deeper understanding of real-world wireless sensor networks, which may find its application in the fields of network design and topology control.
Modeling, implementation, and validation of arterial travel time reliability : [summary].
2013-11-01
Travel time reliability (TTR) has been proposed as : a better measure of a facilitys performance than : a statistical measure like peak hour demand. TTR : is based on more information about average traffic : flows and longer time periods, thus inc...
Modeling, implementation, and validation of arterial travel time reliability.
2013-11-01
Previous research funded by Florida Department of Transportation (FDOT) developed a method for estimating : travel time reliability for arterials. This method was not initially implemented or validated using field data. This : project evaluated and r...
Study of redundant Models in reliability prediction of HXMT's HES
International Nuclear Information System (INIS)
Wang Jinming; Liu Congzhan; Zhang Zhi; Ji Jianfeng
2010-01-01
Two redundant equipment structures of HXMT's HES are proposed firstly, the block backup and dual system cold-redundancy. Then prediction of the reliability is made by using parts count method. Research of comparison and analysis is also performed on the two proposals. A conclusion is drawn that a higher reliability and longer service life could be offered by taking a redundant equipment structure of block backup. (authors)
Lu, Yi
2016-01-01
To model students' math growth trajectory, three conventional growth curve models and three growth mixture models are applied to the Early Childhood Longitudinal Study Kindergarten-Fifth grade (ECLS K-5) dataset in this study. The results of conventional growth curve model show gender differences on math IRT scores. When holding socio-economic…
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)
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)
78 FR 45447 - Revisions to Modeling, Data, and Analysis Reliability Standard
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...
Computer Model to Estimate Reliability Engineering for Air Conditioning Systems
International Nuclear Information System (INIS)
Afrah Al-Bossly, A.; El-Berry, A.; El-Berry, A.
2012-01-01
Reliability engineering is used to predict the performance and optimize design and maintenance of air conditioning systems. Air conditioning systems are expose to a number of failures. The failures of an air conditioner such as turn on, loss of air conditioner cooling capacity, reduced air conditioning output temperatures, loss of cool air supply and loss of air flow entirely can be due to a variety of problems with one or more components of an air conditioner or air conditioning system. Forecasting for system failure rates are very important for maintenance. This paper focused on the reliability of the air conditioning systems. Statistical distributions that were commonly applied in reliability settings: the standard (2 parameter) Weibull and Gamma distributions. After distributions parameters had been estimated, reliability estimations and predictions were used for evaluations. To evaluate good operating condition in a building, the reliability of the air conditioning system that supplies conditioned air to the several The company's departments. This air conditioning system is divided into two, namely the main chilled water system and the ten air handling systems that serves the ten departments. In a chilled-water system the air conditioner cools water down to 40-45 degree F (4-7 degree C). The chilled water is distributed throughout the building in a piping system and connected to air condition cooling units wherever needed. Data analysis has been done with support a computer aided reliability software, this is due to the Weibull and Gamma distributions indicated that the reliability for the systems equal to 86.012% and 77.7% respectively. A comparison between the two important families of distribution functions, namely, the Weibull and Gamma families was studied. It was found that Weibull method performed for decision making.
McNeish, Daniel; Dumas, Denis
2017-01-01
Recent methodological work has highlighted the promise of nonlinear growth models for addressing substantive questions in the behavioral sciences. In this article, we outline a second-order nonlinear growth model in order to measure a critical notion in development and education: potential. Here, potential is conceptualized as having three components-ability, capacity, and availability-where ability is the amount of skill a student is estimated to have at a given timepoint, capacity is the maximum amount of ability a student is predicted to be able to develop asymptotically, and availability is the difference between capacity and ability at any particular timepoint. We argue that single timepoint measures are typically insufficient for discerning information about potential, and we therefore describe a general framework that incorporates a growth model into the measurement model to capture these three components. Then, we provide an illustrative example using the public-use Early Childhood Longitudinal Study-Kindergarten data set using a Michaelis-Menten growth function (reparameterized from its common application in biochemistry) to demonstrate our proposed model as applied to measuring potential within an educational context. The advantage of this approach compared to currently utilized methods is discussed as are future directions and limitations.
Forest growth modeling in the Southern Region, National Forest System
International Nuclear Information System (INIS)
Belcher, D.M.
1988-01-01
This paper discusses an attempt to combine individual tree growth models and stand level growth models currently available for the Region into one computer program. Operation of the program is explained and growth models are included
Bayesian methods in reliability
Sander, P.; Badoux, R.
1991-11-01
The present proceedings from a course on Bayesian methods in reliability encompasses Bayesian statistical methods and their computational implementation, models for analyzing censored data from nonrepairable systems, the traits of repairable systems and growth models, the use of expert judgment, and a review of the problem of forecasting software reliability. Specific issues addressed include the use of Bayesian methods to estimate the leak rate of a gas pipeline, approximate analyses under great prior uncertainty, reliability estimation techniques, and a nonhomogeneous Poisson process. Also addressed are the calibration sets and seed variables of expert judgment systems for risk assessment, experimental illustrations of the use of expert judgment for reliability testing, and analyses of the predictive quality of software-reliability growth models such as the Weibull order statistics.
Localisation in a Growth Model with Interaction
Costa, M.; Menshikov, M.; Shcherbakov, V.; Vachkovskaia, M.
2018-05-01
This paper concerns the long term behaviour of a growth model describing a random sequential allocation of particles on a finite cycle graph. The model can be regarded as a reinforced urn model with graph-based interaction. It is motivated by cooperative sequential adsorption, where adsorption rates at a site depend on the configuration of existing particles in the neighbourhood of that site. Our main result is that, with probability one, the growth process will eventually localise either at a single site, or at a pair of neighbouring sites.
Residual Structures in Latent Growth Curve Modeling
Grimm, Kevin J.; Widaman, Keith F.
2010-01-01
Several alternatives are available for specifying the residual structure in latent growth curve modeling. Two specifications involve uncorrelated residuals and represent the most commonly used residual structures. The first, building on repeated measures analysis of variance and common specifications in multilevel models, forces residual variances…
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
Thermal models pertaining to continental growth
International Nuclear Information System (INIS)
Morgan, P.; Ashwal, L.
1988-01-01
Thermal models are important to understanding continental growth as the genesis, stabilization, and possible recycling of continental crust are closely related to the tectonic processes of the earth which are driven primarily by heat. The thermal energy budget of the earth was slowly decreasing since core formation, and thus the energy driving the terrestrial tectonic engine was decreasing. This fundamental observation was used to develop a logic tree defining the options for continental growth throughout earth history
Structural modelling of economic growth: Technological changes
Directory of Open Access Journals (Sweden)
Sukharev Oleg
2016-01-01
Full Text Available Neoclassical and Keynesian theories of economic growth assume the use of Cobb-Douglas modified functions and other aggregate econometric approaches to growth dynamics modelling. In that case explanations of economic growth are based on the logic of the used mathematical ratios often including the ideas about aggregated values change and factors change a priori. The idea of assessment of factor productivity is the fundamental one among modern theories of economic growth. Nevertheless, structural parameters of economic system, institutions and technological changes are practically not considered within known approaches, though the latter is reflected in the changing parameters of production function. At the same time, on the one hand, the ratio of structural elements determines the future value of the total productivity of the factors and, on the other hand, strongly influences the rate of economic growth and its mode of innovative dynamics. To put structural parameters of economic system into growth models with the possibility of assessment of such modes under conditions of interaction of new and old combinations is an essential step in the development of the theory of economic growth/development. It allows forming stimulation policy of economic growth proceeding from the structural ratios and relations recognized for this economic system. It is most convenient in such models to use logistic functions demonstrating the resource change for old and new combination within the economic system. The result of economy development depends on starting conditions, and on institutional parameters of velocity change of resource borrowing in favour of a new combination and creation of its own resource. Model registration of the resource is carried out through the idea of investments into new and old combinations.
Application of a Snow Growth Model to Radar Remote Sensing
Erfani, E.; Mitchell, D. L.
2014-12-01
Microphysical growth processes of diffusion, aggregation and riming are incorporated analytically in a steady-state snow growth model (SGM) to solve the zeroth- and second- moment conservation equations with respect to mass. The SGM is initiated by radar reflectivity (Zw), supersaturation, temperature, and a vertical profile of the liquid water content (LWC), and it uses a gamma size distribution (SD) to predict the vertical evolution of size spectra. Aggregation seems to play an important role in the evolution of snowfall rates and the snowfall rates produced by aggregation, diffusion and riming are considerably greater than those produced by diffusion and riming alone, demonstrating the strong interaction between aggregation and riming. The impact of ice particle shape on particle growth rates and fall speeds is represented in the SGM in terms of ice particle mass-dimension (m-D) power laws (m = αDβ). These growth rates are qualitatively consistent with empirical growth rates, with slower (faster) growth rates predicted for higher (lower) β values. In most models, β is treated constant for a given ice particle habit, but it is well known that β is larger for the smaller crystals. Our recent work quantitatively calculates β and α for cirrus clouds as a function of D where the m-D expression is a second-order polynomial in log-log space. By adapting this method to the SGM, the ice particle growth rates and fall speeds are predicted more accurately. Moreover, the size spectra predicted by the SGM are in good agreement with those from aircraft measurements during Lagrangian spiral descents through frontal clouds, indicating the successful modeling of microphysical processes. Since the lowest Zw over complex topography is often significantly above cloud base, the precipitation is often underestimated by radar quantitative precipitation estimates (QPE). Our SGM is capable of being initialized with Zw at the lowest reliable radar echo and consequently improves
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
In silico modeling for tumor growth visualization.
Jeanquartier, Fleur; Jean-Quartier, Claire; Cemernek, David; Holzinger, Andreas
2016-08-08
Cancer is a complex disease. Fundamental cellular based studies as well as modeling provides insight into cancer biology and strategies to treatment of the disease. In silico models complement in vivo models. Research on tumor growth involves a plethora of models each emphasizing isolated aspects of benign and malignant neoplasms. Biologists and clinical scientists are often overwhelmed by the mathematical background knowledge necessary to grasp and to apply a model to their own research. We aim to provide a comprehensive and expandable simulation tool to visualizing tumor growth. This novel Web-based application offers the advantage of a user-friendly graphical interface with several manipulable input variables to correlate different aspects of tumor growth. By refining model parameters we highlight the significance of heterogeneous intercellular interactions on tumor progression. Within this paper we present the implementation of the Cellular Potts Model graphically presented through Cytoscape.js within a Web application. The tool is available under the MIT license at https://github.com/davcem/cpm-cytoscape and http://styx.cgv.tugraz.at:8080/cpm-cytoscape/ . In-silico methods overcome the lack of wet experimental possibilities and as dry method succeed in terms of reduction, refinement and replacement of animal experimentation, also known as the 3R principles. Our visualization approach to simulation allows for more flexible usage and easy extension to facilitate understanding and gain novel insight. We believe that biomedical research in general and research on tumor growth in particular will benefit from the systems biology perspective.
Energy Technology Data Exchange (ETDEWEB)
Cacuci, D. G. [Commiss Energy Atom, Direct Energy Nucl, Saclay, (France); Cacuci, D. G.; Balan, I. [Univ Karlsruhe, Inst Nucl Technol and Reactor Safetly, Karlsruhe, (Germany); Ionescu-Bujor, M. [Forschungszentrum Karlsruhe, Fus Program, D-76021 Karlsruhe, (Germany)
2008-07-01
In Part II of this work, the adjoint sensitivity analysis procedure developed in Part I is applied to perform sensitivity analysis of several dynamic reliability models of systems of increasing complexity, culminating with the consideration of the International Fusion Materials Irradiation Facility (IFMIF) accelerator system. Section II presents the main steps of a procedure for the automated generation of Markov chains for reliability analysis, including the abstraction of the physical system, construction of the Markov chain, and the generation and solution of the ensuing set of differential equations; all of these steps have been implemented in a stand-alone computer code system called QUEFT/MARKOMAG-S/MCADJSEN. This code system has been applied to sensitivity analysis of dynamic reliability measures for a paradigm '2-out-of-3' system comprising five components and also to a comprehensive dynamic reliability analysis of the IFMIF accelerator system facilities for the average availability and, respectively, the system's availability at the final mission time. The QUEFT/MARKOMAG-S/MCADJSEN has been used to efficiently compute sensitivities to 186 failure and repair rates characterizing components and subsystems of the first-level fault tree of the IFMIF accelerator system. (authors)
International Nuclear Information System (INIS)
Cacuci, D. G.; Cacuci, D. G.; Balan, I.; Ionescu-Bujor, M.
2008-01-01
In Part II of this work, the adjoint sensitivity analysis procedure developed in Part I is applied to perform sensitivity analysis of several dynamic reliability models of systems of increasing complexity, culminating with the consideration of the International Fusion Materials Irradiation Facility (IFMIF) accelerator system. Section II presents the main steps of a procedure for the automated generation of Markov chains for reliability analysis, including the abstraction of the physical system, construction of the Markov chain, and the generation and solution of the ensuing set of differential equations; all of these steps have been implemented in a stand-alone computer code system called QUEFT/MARKOMAG-S/MCADJSEN. This code system has been applied to sensitivity analysis of dynamic reliability measures for a paradigm '2-out-of-3' system comprising five components and also to a comprehensive dynamic reliability analysis of the IFMIF accelerator system facilities for the average availability and, respectively, the system's availability at the final mission time. The QUEFT/MARKOMAG-S/MCADJSEN has been used to efficiently compute sensitivities to 186 failure and repair rates characterizing components and subsystems of the first-level fault tree of the IFMIF accelerator system. (authors)
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
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.
Predicting Madura cattle growth curve using non-linear model
Widyas, N.; Prastowo, S.; Widi, T. S. M.; Baliarti, E.
2018-03-01
Madura cattle is Indonesian native. It is a composite breed that has undergone hundreds of years of selection and domestication to reach nowadays remarkable uniformity. Crossbreeding has reached the isle of Madura and the Madrasin, a cross between Madura cows and Limousine semen emerged. This paper aimed to compare the growth curve between Madrasin and one type of pure Madura cows, the common Madura cattle (Madura) using non-linear models. Madura cattles are kept traditionally thus reliable records are hardly available. Data were collected from small holder farmers in Madura. Cows from different age classes (5years) were observed, and body measurements (chest girth, body length and wither height) were taken. In total 63 Madura and 120 Madrasin records obtained. Linear model was built with cattle sub-populations and age as explanatory variables. Body weights were estimated based on the chest girth. Growth curves were built using logistic regression. Results showed that within the same age, Madrasin has significantly larger body compared to Madura (plogistic models fit better for Madura and Madrasin cattle data; with the estimated MSE for these models were 39.09 and 759.28 with prediction accuracy of 99 and 92% for Madura and Madrasin, respectively. Prediction of growth curve using logistic regression model performed well in both types of Madura cattle. However, attempts to administer accurate data on Madura cattle are necessary to better characterize and study these cattle.
SIERRA - A 3-D device simulator for reliability modeling
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 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)
Modelling the growth of a methanotrophic biofilm
DEFF Research Database (Denmark)
Arcangeli, J.-P.; Arvin, E.
1999-01-01
This article discusses the growth of methanotrophic biofilms. Several independent biofilm growths scenarios involving different inocula were examined. Biofilm growth, substrate removal and product formation were monitored throughout the experiments. Based on the oxygen consumption it was concluded...... that heterotrophs and nitrifiers co-existed with methanotrophs in the biofilm. Heterotrophic biomass grew on soluble polymers formed by the hydrolysis of dead biomass entrapped in the biofilm. Nitrifier populations developed because of the presence of ammonia in the mineral medium. Based on these experimental...... was performed on this model. It indicated that the most influential parameters were those related to the biofilm (i.e. density; solid-volume fraction; thickness). This suggests that in order to improve the model, further research regarding the biofilm structure and composition is needed....
DEFF Research Database (Denmark)
Iwankiewicz, R.; Nielsen, Søren R. K.; Skjærbæk, P. S.
The subject of the paper is the investigation of the sensitivity of structural reliability estimation by a reduced hysteretic model for a reinforced concrete frame under an earthquake excitation.......The subject of the paper is the investigation of the sensitivity of structural reliability estimation by a reduced hysteretic model for a reinforced concrete frame under an earthquake excitation....
Modeling Fish Growth in Low Dissolved Oxygen
Neilan, Rachael Miller
2013-01-01
This article describes a computational project designed for undergraduate students as an introduction to mathematical modeling. Students use an ordinary differential equation to describe fish weight and assume the instantaneous growth rate depends on the concentration of dissolved oxygen. Published laboratory experiments suggest that continuous…
Stochastic Growth Models with No Discounting
Czech Academy of Sciences Publication Activity Database
Sladký, Karel
2007-01-01
Roč. 15, č. 4 (2007), s. 88-98 ISSN 0572-3043 R&D Projects: GA ČR(CZ) GA402/06/0990; GA ČR GA402/05/0115 Institutional research plan: CEZ:AV0Z10750506 Keywords : economic dynamics * stochastic version of the Ramsey growth model * Markov decision processes Subject RIV: AH - Economics
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....
Perinetti, Giuseppe; Contardo, Luca; Castaldo, Attilio; McNamara, James A; Franchi, Lorenzo
2016-07-01
To evaluate the capability of both cervical vertebral maturation (CVM) stages 3 and 4 (CS3-4 interval) and the peak in standing height to identify the mandibular growth spurt throughout diagnostic reliability analysis. A previous longitudinal data set derived from 24 untreated growing subjects (15 females and nine males,) detailed elsewhere were reanalyzed. Mandibular growth was defined as annual increments in Condylion (Co)-Gnathion (Gn) (total mandibular length) and Co-Gonion Intersection (Goi) (ramus height) and their arithmetic mean (mean mandibular growth [mMG]). Subsequently, individual annual increments in standing height, Co-Gn, Co-Goi, and mMG were arranged according to annual age intervals, with the first and last intervals defined as 7-8 years and 15-16 years, respectively. An analysis was performed to establish the diagnostic reliability of the CS3-4 interval or the peak in standing height in the identification of the maximum individual increments of each Co-Gn, Co-Goi, and mMG measurement at each annual age interval. CS3-4 and standing height peak show similar but variable accuracy across annual age intervals, registering values between 0.61 (standing height peak, Co-Gn) and 0.95 (standing height peak and CS3-4, mMG). Generally, satisfactory diagnostic reliability was seen when the mandibular growth spurt was identified on the basis of the Co-Goi and mMG increments. Both CVM interval CS3-4 and peak in standing height may be used in routine clinical practice to enhance efficiency of treatments requiring identification of the mandibular growth spurt.
Using Model Replication to Improve the Reliability of Agent-Based Models
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-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
Dynamic reliability modeling of three-state networks
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...
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
Stochastic modeling for reliability shocks, burn-in and heterogeneous populations
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...
Mathematical foundations of the dendritic growth models.
Villacorta, José A; Castro, Jorge; Negredo, Pilar; Avendaño, Carlos
2007-11-01
At present two growth models describe successfully the distribution of size and topological complexity in populations of dendritic trees with considerable accuracy and simplicity, the BE model (Van Pelt et al. in J. Comp. Neurol. 387:325-340, 1997) and the S model (Van Pelt and Verwer in Bull. Math. Biol. 48:197-211, 1986). This paper discusses the mathematical basis of these models and analyzes quantitatively the relationship between the BE model and the S model assumed in the literature by developing a new explicit equation describing the BES model (a dendritic growth model integrating the features of both preceding models; Van Pelt et al. in J. Comp. Neurol. 387:325-340, 1997). In numerous studies it is implicitly presupposed that the S model is conditionally linked to the BE model (Granato and Van Pelt in Brain Res. Dev. Brain Res. 142:223-227, 2003; Uylings and Van Pelt in Network 13:397-414, 2002; Van Pelt, Dityatev and Uylings in J. Comp. Neurol. 387:325-340, 1997; Van Pelt and Schierwagen in Math. Biosci. 188:147-155, 2004; Van Pelt and Uylings in Network. 13:261-281, 2002; Van Pelt, Van Ooyen and Uylings in Modeling Dendritic Geometry and the Development of Nerve Connections, pp 179, 2000). In this paper we prove the non-exactness of this assumption, quantify involved errors and determine the conditions under which the BE and S models can be separately used instead of the BES model, which is more exact but considerably more difficult to apply. This study leads to a novel expression describing the BE model in an analytical closed form, much more efficient than the traditional iterative equation (Van Pelt et al. in J. Comp. Neurol. 387:325-340, 1997) in many neuronal classes. Finally we propose a new algorithm in order to obtain the values of the parameters of the BE model when this growth model is matched to experimental data, and discuss its advantages and improvements over the more commonly used procedures.
International Nuclear Information System (INIS)
Jiang Jianjun; Zhang Li; Wang Yiqun; Zhang Kun; Peng Yuyuan; Zhou Cheng
2012-01-01
Facing the shortcomings of the traditional cognitive factors and cognitive model, this paper presents a Bayesian networks cognitive reliability model by taking the main control room as a reference background and human factors as the key points. The model mainly analyzes the cognitive reliability affected by the human factors, and for the cognitive node and influence factors corresponding to cognitive node, a series of methods and function formulas to compute the node cognitive reliability is proposed. The model and corresponding methods can be applied to the evaluation of cognitive process for the nuclear power plant operators and have a certain significance for the prevention of safety accidents in nuclear power plants. (authors)
Model case IRS-RWE for the determination of reliability data in practical operation
Energy Technology Data Exchange (ETDEWEB)
Hoemke, P; Krause, H
1975-11-01
Reliability und availability analyses are carried out to assess the safety of nuclear power plants. The paper deals in the first part with the requirement of accuracy for the input data of such analyses and in the second part with the prototype data collection of reliability data 'Model case IRS-RWE'. The objectives and the structure of the data collection are described. The present results show that the estimation of reliability data in power plants is possible and gives reasonable results.
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.
Modeling error distributions of growth curve models through Bayesian methods.
Zhang, Zhiyong
2016-06-01
Growth curve models are widely used in social and behavioral sciences. However, typical growth curve models often assume that the errors are normally distributed although non-normal data may be even more common than normal data. In order to avoid possible statistical inference problems in blindly assuming normality, a general Bayesian framework is proposed to flexibly model normal and non-normal data through the explicit specification of the error distributions. A simulation study shows when the distribution of the error is correctly specified, one can avoid the loss in the efficiency of standard error estimates. A real example on the analysis of mathematical ability growth data from the Early Childhood Longitudinal Study, Kindergarten Class of 1998-99 is used to show the application of the proposed methods. Instructions and code on how to conduct growth curve analysis with both normal and non-normal error distributions using the the MCMC procedure of SAS are provided.
Rademaker, Corné J.; Omedo Bebe, Bockline; Lee, van der Jan; Kilelu, Catherine; Tonui, Charles
2016-01-01
This report provides an overview of how the Kenyan dairy sector performs in three analytical domains: the robustness of the supply chains, the reliability of institutional governance and the resilience of the innovation system. Analysis is by literature review, stakeholder interviews and a
Modeling Conformal Growth in Photonic Crystals and Comparing to Experiment
Brzezinski, Andrew; Chen, Ying-Chieh; Wiltzius, Pierre; Braun, Paul
2008-03-01
Conformal growth, e.g. atomic layer deposition (ALD), of materials such as silicon and TiO2 on three dimensional (3D) templates is important for making photonic crystals. However, reliable calculations of optical properties as a function of the conformal growth, such as the optical band structure, are hampered by difficultly in accurately assessing a deposited material's spatial distribution. A widely used approximation ignores ``pinch off'' of precursor gas and assumes complete template infilling. Another approximation results in non-uniform growth velocity by employing iso-intensity surfaces of the 3D interference pattern used to create the template. We have developed an accurate model of conformal growth in arbitrary 3D periodic structures, allowing for arbitrary surface orientation. Results are compared with the above approximations and with experimentally fabricated photonic crystals. We use an SU8 polymer template created by 4-beam interference lithography, onto which various amounts of TiO2 are grown by ALD. Characterization is performed by analysis of cross-sectional scanning electron micrographs and by solid angle resolved optical spectroscopy.
Integrated Intelligent Modeling, Design and Control of Crystal Growth Processes
National Research Council Canada - National Science Library
Prasad, V
2000-01-01
.... This MURI program took an integrated approach towards modeling, design and control of crystal growth processes and in conjunction with growth and characterization experiments developed much better...
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...
Evaluation of Validity and Reliability for Hierarchical Scales Using Latent Variable Modeling
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…
Reliability Based Optimal Design of Vertical Breakwaters Modelled as a Series System Failure
DEFF Research Database (Denmark)
Christiani, E.; Burcharth, H. F.; Sørensen, John Dalsgaard
1996-01-01
Reliability based design of monolithic vertical breakwaters is considered. Probabilistic models of important failure modes such as sliding and rupture failure in the rubble mound and the subsoil are described. Characterisation of the relevant stochastic parameters are presented, and relevant design...... variables are identified and an optimal system reliability formulation is presented. An illustrative example is given....
DEFF Research Database (Denmark)
Franchin, P.; Ditlevsen, Ove Dalager; Kiureghian, Armen Der
2002-01-01
The model correction factor method (MCFM) is used in conjunction with the first-order reliability method (FORM) to solve structural reliability problems involving integrals of non-Gaussian random fields. The approach replaces the limit-state function with an idealized one, in which the integrals ...
Reliability Models Applied to a System of Power Converters in Particle Accelerators
Siemaszko, D; Speiser, M; Pittet, S
2012-01-01
Several reliability models are studied when applied to a power system containing a large number of power converters. A methodology is proposed and illustrated in the case study of a novel linear particle accelerator designed for reaching high energies. The proposed methods result in the prediction of both reliability and availability of the considered system for optimisation purposes.
Modelling diameter growth, mortality and recruitment of trees in ...
African Journals Online (AJOL)
Modelling diameter growth, mortality and recruitment of trees in miombo woodlands of Tanzania. ... Individual tree diameter growth and mortality models, and area-based recruitment models were developed. ... AJOL African Journals Online.
International Nuclear Information System (INIS)
Harris, D.O.; Lim, E.Y.
1982-01-01
A fracture mechanics model of structural reliability is described. The model assumes that failure occurs due to the subcritical and catastrophic growth of as-fabricated defects. The material properties, stress history, number and dimensions of the initial cracks are treated as random variables. Crack growth is calculated using fracture mechanics principles. The model has been used to estimate the influence of earthquakes on the integrity of circumferential girth butt welds in the large (diameter greater than 30 in.) primary coolant system pipes of a commercial pressurized water reactor. In the absence of earthquakes, the probability of leaks and catastrophic double-ended guillotine breaks is estimated to be 10 -6 and 10 -12 per plant lifetime, respectively. These probabilities were only slightly increased by the occurrence of earthquakes. (author)
International Nuclear Information System (INIS)
EI-Shanshoury, G.I.
2011-01-01
Several statistical distributions are used to model various reliability and maintainability parameters. The applied distribution depends on the' nature of the data being analyzed. The presented paper deals with analysis of some statistical distributions used in reliability to reach the best fit of distribution analysis. The calculations rely on circuit quantity parameters obtained by using Relex 2009 computer program. The statistical analysis of ten different distributions indicated that Weibull distribution gives the best fit distribution for modeling the reliability of the data set of Temperature Alarm Circuit (TAC). However, the Exponential distribution is found to be the best fit distribution for modeling the failure rate
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.
Development of an Environment for Software Reliability Model Selection
1992-09-01
now is directed to other related problems such as tools for model selection, multiversion programming, and software fault tolerance modeling... multiversion programming, 7. Hlardware can be repaired by spare modules, which is not. the case for software, 2-6 N. Preventive maintenance is very important
Fatigue reliability and effective turbulence models in wind farms
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard; Frandsen, Sten Tronæs; Tarp-Johansen, N.J.
2007-01-01
behind wind turbines can imply a significant reduction in the fatigue lifetime of wind turbines placed in wakes. In this paper the design code model in the wind turbine code IEC 61400-1 (2005) is evaluated from a probabilistic point of view, including the importance of modeling the SN-curve by linear...
Powering stochastic reliability models by discrete event simulation
DEFF Research Database (Denmark)
Kozine, Igor; Wang, Xiaoyun
2012-01-01
it difficult to find a solution to the problem. The power of modern computers and recent developments in discrete-event simulation (DES) software enable to diminish some of the drawbacks of stochastic models. In this paper we describe the insights we have gained based on using both Markov and DES models...
Pipeline integrity model-a formative approach towards reliability and life assessment
International Nuclear Information System (INIS)
Sayed, A.M.; Jaffery, M.A.
2005-01-01
Pipe forms an integral part of transmission medium in oil and gas industry. This holds true for both upstream and downstream segments of this global energy business. With the aging of this asset base, emphasis on its operational aspects has been under immense considerations from the operators and regulators sides. Moreover, the milieu of information area and enhancement in global trade has lifted the barriers on means to forge forward towards better utilization of resources. This has resulted in optimized solutions as priority for business and technical manager's world over. There is a paradigm shift from mere development of 'smart materials' to 'low life cycle cost material'. The force inducing this change is a rationale one: the recovery of development costs is no more a problem in a global community; rather it is the pay-off time which matters most to the materials end users. This means that decision makers are not evaluating just the price offered but are keen to judge the entire life cycle cost of a product. The integrity of pipe are affected by factors such as corrosion, fatigue-crack growth, stress-corrosion cracking, and mechanical damage. Extensive research in the area of reliability and life assessment has been carried out. A number of models concerning with the reliability issues of pipes have been developed and are being used by a number of pipeline operators worldwide. Yet, it is emphasised that there are no substitute for sound engineering judgment and allowance for factors of safety. The ability of a laid down pipe network to transport the intended fluid under pre-defined conditions for the entire project envisaged life, is referred to the reliability of system. The reliability is built into the product through extensive benchmarking against industry standard codes. The process of pipes construction for oil and gas service is regulated through American Petroleum Institute's Specification for Line Pipe. Subsequently, specific programs have been
Directory of Open Access Journals (Sweden)
Zongshuai Yan
2015-01-01
Full Text Available The two-terminal reliability calculation for wireless sensor networks (WSNs is a #P-hard problem. The reliability calculation of WSNs on the multicast model provides an even worse combinatorial explosion of node states with respect to the calculation of WSNs on the unicast model; many real WSNs require the multicast model to deliver information. This research first provides a formal definition for the WSN on the multicast model. Next, a symbolic OBDD_Multicast algorithm is proposed to evaluate the reliability of WSNs on the multicast model. Furthermore, our research on OBDD_Multicast construction avoids the problem of invalid expansion, which reduces the number of subnetworks by identifying the redundant paths of two adjacent nodes and s-t unconnected paths. Experiments show that the OBDD_Multicast both reduces the complexity of the WSN reliability analysis and has a lower running time than Xing’s OBDD- (ordered binary decision diagram- based algorithm.
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.
Cognitive modelling: a basic complement of human reliability analysis
International Nuclear Information System (INIS)
Bersini, U.; Cacciabue, P.C.; Mancini, G.
1988-01-01
In this paper the issues identified in modelling humans and machines are discussed in the perspective of the consideration of human errors managing complex plants during incidental as well as normal conditions. The dichotomy between the use of a cognitive versus a behaviouristic model approach is discussed and the complementarity aspects rather than the differences of the two methods are identified. A cognitive model based on a hierarchical goal-oriented approach and driven by fuzzy logic methodology is presented as the counterpart to the 'classical' THERP methodology for studying human errors. Such a cognitive model is discussed at length and its fundamental components, i.e. the High Level Decision Making and the Low Level Decision Making models, are reviewed. Finally, the inadequacy of the 'classical' THERP methodology to deal with cognitive errors is discussed on the basis of a simple test case. For the same case the cognitive model is then applied showing the flexibility and adequacy of the model to dynamic configuration with time-dependent failures of components and with consequent need for changing of strategy during the transient itself. (author)
Growth models and analysis of development
Energy Technology Data Exchange (ETDEWEB)
Mathur, G
1979-10-01
This paper deals with remnants of neoclassical elements in Keynesian and post-Keynesian thought, and attempts to demonstrate that the elimination of these elements from our modes of thinking would not impoverish economic analysis as a means of solving real problems. In the Keynesian analysis the causation from investment to savings is exhibited in terms of income determination. When put in terms of a capital-theory model, the vector of savings is represented in two ways: real savings and counterpart real savings. The former coincides with the investment vector and the latter with the vector of consumption goods foregone for diverting resources towards equipment making. Thus the Keynesian causation in capital theory terms makes the concept of national savings as an independent variable redudant. The Robinsonian causation in a golden age with full employment and its reversal of direction in a steady state with non-employment are then considered. But in each of these, variables like rate of savings and output/capital ratio are found to be dormant variables. They are termed as null variables which, being of no account in both full-employment and unemployment situations, could, without loss, be deleted from the repertory of analytical tools. The Harrod formula of warranted rate of growth, when put in causal form, thus becomes a redundant portion of economics of growth. The real determinants of the growth rate and real wage rate on which the analysis of growth or of development should be based, are also depicted.
Construction of a reliable model pyranometer for irradiance ...
African Journals Online (AJOL)
USER
2010-03-22
Mar 22, 2010 ... hour, latitude and cloud cover are the most widely or commonly used ... models in the Nigerian environment include that of Burari and Sambo .... influence the stability of the assembly (reducing its phase ... earth's surface.
Laar, Matilda E; Marquis, Grace S; Lartey, Anna; Gray-Donald, Katherine
2018-02-17
Length measurements are important in growth, monitoring and promotion (GMP) for the surveillance of a child's weight-for-length and length-for-age. These two indices provide an indication of a child's risk of becoming wasted or stunted, and are more informative about a child's growth than the widely used weight-for-age index (underweight). Although the introduction of length measurements in GMP is recommended by the World Health Organization, concerns about the reliability of length measurements collected in rural outreach settings have been expressed by stakeholders. Our aim was to describe the reliability and challenges associated with community health personnel measuring length for rural outreach GMP activities. Two reliability studies (A and B), using 10 children less than 24 months each, were conducted in the GMP services of a rural district in Ghana. Fifteen nurses and 15 health volunteers (HV) with no prior experience in length measurements were trained. Intra- and inter-observer technical error of measurement (TEM), average bias from expert anthropometrist, and coefficient of reliability (R) of length measurements were assessed and compared across sessions. Observations and interviews were used to understand the ability and experiences of health personnel with measuring length at outreach GMP. Inter-observer TEM was larger than intra-observer TEM for both nurses and HV at both sessions and was unacceptably (compared to error standards) high in both groups at both time points. Average biases from expert's measurements were within acceptable limits, however, both groups tended to underestimate length measurements. The R for lengths collected by nurses (92.3%) was higher at session B compared to that of HV (87.5%). Length measurements taken by nurses and HV, and those taken by an experienced anthropometrist at GMP sessions were of moderate agreement (kappa = 0.53, p reliability of length measurements improved after two refresher trainings for nurses but
Modeling and control of greenhouse crop growth
Rodríguez, Francisco; Guzmán, José Luis; Ramírez-Arias, Armando
2015-01-01
A discussion of challenges related to the modeling and control of greenhouse crop growth, this book presents state-of-the-art answers to those challenges. The authors model the subsystems involved in successful greenhouse control using different techniques and show how the models obtained can be exploited for simulation or control design; they suggest ideas for the development of physical and/or black-box models for this purpose. Strategies for the control of climate- and irrigation-related variables are brought forward. The uses of PID control and feedforward compensators, both widely used in commercial tools, are summarized. The benefits of advanced control techniques—event-based, robust, and predictive control, for example—are used to improve on the performance of those basic methods. A hierarchical control architecture is developed governed by a high-level multiobjective optimization approach rather than traditional constrained optimization and artificial intelligence techniques. Reference trajector...
Reliability Estimation of Aero-engine Based on Mixed Weibull Distribution Model
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.
Transitions in a probabilistic interface growth model
International Nuclear Information System (INIS)
Alves, S G; Moreira, J G
2011-01-01
We study a generalization of the Wolf–Villain (WV) interface growth model based on a probabilistic growth rule. In the WV model, particles are randomly deposited onto a substrate and subsequently move to a position nearby where the binding is strongest. We introduce a growth probability which is proportional to a power of the number n i of bindings of the site i: p i ∝n i ν . Through extensive simulations, in (1 + 1) dimensions, we find three behaviors depending on the ν value: (i) if ν is small, a crossover from the Mullins–Herring to the Edwards–Wilkinson (EW) universality class; (ii) for intermediate values of ν, a crossover from the EW to the Kardar–Parisi–Zhang (KPZ) universality class; and, finally, (iii) for large ν values, the system is always in the KPZ class. In (2 + 1) dimensions, we obtain three different behaviors: (i) a crossover from the Villain–Lai–Das Sarma to the EW universality class for small ν values; (ii) the EW class is always present for intermediate ν values; and (iii) a deviation from the EW class is observed for large ν values
Charge transport models for reliability engineering of semiconductor devices
International Nuclear Information System (INIS)
Bina, M.
2014-01-01
The simulation of semiconductor devices is important for the assessment of device lifetimes before production. In this context, this work investigates the influence of the charge carrier transport model on the accuracy of bias temperature instability and hot-carrier degradation models in MOS devices. For this purpose, a four-state defect model based on a non-radiative multi phonon (NMP) theory is implemented to study the bias temperature instability. However, the doping concentrations typically used in nano-scale devices correspond to only a small number of dopants in the channel, leading to fluctuations of the electrostatic potential. Thus, the granularity of the doping cannot be ignored in these devices. To study the bias temperature instability in the presence of fluctuations of the electrostatic potential, the advanced drift diffusion device simulator Minimos-NT is employed. In a first effort to understand the bias temperature instability in p-channel MOSFETs at elevated temperatures, data from direct-current-current-voltage measurements is successfully reproduced using a four-state defect model. Differences between the four-state defect model and the commonly employed trapping model from Shockley, Read and Hall (SRH) have been investigated showing that the SRH model is incapable of reproducing the measurement data. This is in good agreement with the literature, where it has been extensively shown that a model based on SRH theory cannot reproduce the characteristic time constants found in BTI recovery traces. Upon inspection of recorded recovery traces after bias temperature stress in n-channel MOSFETs it is found that the gate current is strongly correlated with the drain current (recovery trace). Using a random discrete dopant model and non-equilibrium greens functions it is shown that direct tunnelling cannot explain the magnitude of the gate current reduction. Instead it is found that trap-assisted tunnelling, modelled using NMP theory, is the cause of this
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
The open-source, public domain JUPITER (Joint Universal Parameter IdenTification and Evaluation of Reliability) API (Application Programming Interface) provides conventions and Fortran-90 modules to develop applications (computer programs) for analyzing process models. The input ...
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....
Liu, Donhang
2014-01-01
This presentation includes a summary of NEPP-funded deliverables for the Base-Metal Electrodes (BMEs) capacitor task, development of a general reliability model for BME capacitors, and a summary and future work.
Microstructural Modeling of Brittle Materials for Enhanced Performance and Reliability.
Energy Technology Data Exchange (ETDEWEB)
Teague, Melissa Christine [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Teague, Melissa Christine [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Rodgers, Theron [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Rodgers, Theron [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Grutzik, Scott Joseph [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Grutzik, Scott Joseph [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Meserole, Stephen [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Meserole, Stephen [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2017-08-01
Brittle failure is often influenced by difficult to measure and variable microstructure-scale stresses. Recent advances in photoluminescence spectroscopy (PLS), including improved confocal laser measurement and rapid spectroscopic data collection have established the potential to map stresses with microscale spatial resolution (%3C2 microns). Advanced PLS was successfully used to investigate both residual and externally applied stresses in polycrystalline alumina at the microstructure scale. The measured average stresses matched those estimated from beam theory to within one standard deviation, validating the technique. Modeling the residual stresses within the microstructure produced general agreement in comparison with the experimentally measured results. Microstructure scale modeling is primed to take advantage of advanced PLS to enable its refinement and validation, eventually enabling microstructure modeling to become a predictive tool for brittle materials.
Modeling human intention formation for human reliability assessment
International Nuclear Information System (INIS)
Woods, D.D.; Roth, E.M.; Pople, H. Jr.
1988-01-01
This paper describes a dynamic simulation capability for modeling how people form intentions to act in nuclear power plant emergency situations. This modeling tool, Cognitive Environment Simulation or CES, was developed based on techniques from artificial intelligence. It simulates the cognitive processes that determine situation assessment and intention formation. It can be used to investigate analytically what situations and factors lead to intention failures, what actions follow from intention failures (e.g. errors of omission, errors of commission, common mode errors), the ability to recover from errors or additional machine failures, and the effects of changes in the NPP person machine system. One application of the CES modeling environment is to enhance the measurement of the human contribution to risk in probabilistic risk assessment studies. (author)
BIOCHEMICAL HOMEOSTASIS AND BODY GROWTH ARE RELIABLE END POINTS IN CLINICAL NUTRITION TRIALS
Studies of biochemical homeostasis and/or body growth have been included as outcome variables in most nutrition trials in paediatric patients. Moreover, these outcome variables have provided important insights into the nutrient requirements of infants and children, and continue to do so. Examples ...
Modeling of multibranched crosslike crack growth
International Nuclear Information System (INIS)
Canessa, E.; Tanatar, B.
1991-06-01
Multibranched crosslike crack patterns formed in concentrically loaded square plates are studied in terms of fractal geometry, where the associated fractal dimension d f is calculated for their characterization. We apply simplest deterministic and stochastic approaches at a phenomenological level in an attempt to find generic features as guidelines for future experimental and theoretical work. The deterministic model for fracture propagation we apply, which is a variant of the discretized Laplace approach for randomly ramified fractal cracks proposed by Takayasu, reproduces the basic ingredients of observed complex fracture patters. The stochastic model, although is not strictly a model for crack propagation, is based on diffusion-limited aggregation (DLA) for fractal growth and produces slightly more realistic assessment of the crosslike growth of the cracks in asymmetric multibranches. Nevertheless, this simple ad-hoc DLA-version for modeling the present phenomena as well as the deterministic approach for fracture propagation give fractal dimensionality for the fracture pattern in accord with our estimations made from recent experimental data. It is found that there is a crossover of two fractal dimensions, corresponding to the core (higher d f ) and multibranched crosslike (lower D f ) regions, that contains loops, that are interpreted as representing different symmetry regions within the square plates of finite size. (author). 26 refs, 5 figs
Modelling Reliability of Supply and Infrastructural Dependency in Energy Distribution Systems
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...
International Nuclear Information System (INIS)
Kallweit, A.; Schumacher, F.
1977-01-01
A high reliability is called for waste management facilities within the fuel cycle of nuclear power stations which can be fulfilled by providing intermediate storage facilities and reserve capacities. In this report a model based on the theory of Markov processes is described which allows computation of reliability characteristics of waste management facilities containing intermediate storage facilities. The application of the model is demonstrated by an example. (orig.) [de
Nikulin, M; Mesbah, M; Limnios, N
2004-01-01
Parametric and semiparametric models are tools with a wide range of applications to reliability, survival analysis, and quality of life. This self-contained volume examines these tools in survey articles written by experts currently working on the development and evaluation of models and methods. While a number of chapters deal with general theory, several explore more specific connections and recent results in "real-world" reliability theory, survival analysis, and related fields.
Appraisal and Reliability of Variable Engagement Model Prediction ...
African Journals Online (AJOL)
The variable engagement model based on the stress - crack opening displacement relationship and, which describes the behaviour of randomly oriented steel fibres composite subjected to uniaxial tension has been evaluated so as to determine the safety indices associated when the fibres are subjected to pullout and with ...
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)
Reliability Evaluation for the Surface to Air Missile Weapon Based on Cloud Model
Directory of Open Access Journals (Sweden)
Deng Jianjun
2015-01-01
Full Text Available The fuzziness and randomness is integrated by using digital characteristics, such as Expected value, Entropy and Hyper entropy. The cloud model adapted to reliability evaluation is put forward based on the concept of the surface to air missile weapon. The cloud scale of the qualitative evaluation is constructed, and the quantitative variable and the qualitative variable in the system reliability evaluation are corresponded. The practical calculation result shows that it is more effective to analyze the reliability of the surface to air missile weapon by this way. The practical calculation result also reflects the model expressed by cloud theory is more consistent with the human thinking style of uncertainty.
Modeling reliability measurement of interface on information system: Towards the forensic of rules
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.
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
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.
DEFF Research Database (Denmark)
Ambühl, Simon; Kofoed, Jens Peter; Sørensen, John Dalsgaard
2015-01-01
Wave models used for site assessments are subjected to model uncertainties, which need to be quantified when using wave model results for probabilistic reliability assessments. This paper focuses on determination of wave model uncertainties. Four different wave models are considered, and validation...... data are collected from published scientific research. The bias and the root-mean-square error, as well as the scatter index, are considered for the significant wave height as well as the mean zero-crossing wave period. Based on an illustrative generic example, this paper presents how the quantified...... uncertainties can be implemented in probabilistic reliability assessments....
DEFF Research Database (Denmark)
Ambühl, Simon; Kofoed, Jens Peter; Sørensen, John Dalsgaard
2014-01-01
Wave models used for site assessments are subject to model uncertainties, which need to be quantified when using wave model results for probabilistic reliability assessments. This paper focuses on determination of wave model uncertainties. Considered are four different wave models and validation...... data is collected from published scientific research. The bias, the root-mean-square error as well as the scatter index are considered for the significant wave height as well as the mean zero-crossing wave period. Based on an illustrative generic example it is shown how the estimated uncertainties can...... be implemented in probabilistic reliability assessments....
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...
A Structural Reliability Business Process Modelling with System Dynamics Simulation
Lam, C. Y.; Chan, S. L.; Ip, W. H.
2010-01-01
Business activity flow analysis enables organizations to manage structured business processes, and can thus help them to improve performance. The six types of business activities identified here (i.e., SOA, SEA, MEA, SPA, MSA and FIA) are correlated and interact with one another, and the decisions from any business activity form feedback loops with previous and succeeding activities, thus allowing the business process to be modelled and simulated. For instance, for any company that is eager t...
A General Reliability Model for Ni-BaTiO3-Based Multilayer Ceramic Capacitors
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.
Modeling Manufacturing Impacts on Aging and Reliability of Polyurethane Foams
Energy Technology Data Exchange (ETDEWEB)
Rao, Rekha R.; Roberts, Christine Cardinal; Mondy, Lisa Ann; Soehnel, Melissa Marie; Johnson, Kyle; Lorenzo, Henry T.
2016-10-01
Polyurethane is a complex multiphase material that evolves from a viscous liquid to a system of percolating bubbles, which are created via a CO2 generating reaction. The continuous phase polymerizes to a solid during the foaming process generating heat. Foams introduced into a mold increase their volume up to tenfold, and the dynamics of the expansion process may lead to voids and will produce gradients in density and degree of polymerization. These inhomogeneities can lead to structural stability issues upon aging. For instance, structural components in weapon systems have been shown to change shape as they age depending on their molding history, which can threaten critical tolerances. The purpose of this project is to develop a Cradle-to-Grave multiphysics model, which allows us to predict the material properties of foam from its birth through aging in the stockpile, where its dimensional stability is important.
DEFF Research Database (Denmark)
Sin, Gürkan; Meyer, Anne S.; Gernaey, Krist
2010-01-01
The reliability of cellulose hydrolysis models is studied using the NREL model. An identifiability analysis revealed that only 6 out of 26 parameters are identifiable from the available data (typical hydrolysis experiments). Attempting to identify a higher number of parameters (as done in the ori......The reliability of cellulose hydrolysis models is studied using the NREL model. An identifiability analysis revealed that only 6 out of 26 parameters are identifiable from the available data (typical hydrolysis experiments). Attempting to identify a higher number of parameters (as done...
International Nuclear Information System (INIS)
Knee, H.E.; Krois, P.A.; Haas, P.M.; Siegel, A.I.; Ryan, T.G.
1983-01-01
The NRC has developed a structured, quantitative, predictive methodology in the form of a computerized simulation model for assessing maintainer task performance. Objective of the overall program is to develop, validate, and disseminate a practical, useful, and acceptable methodology for the quantitative assessment of NPP maintenance personnel reliability. The program was organized into four phases: (1) scoping study, (2) model development, (3) model evaluation, and (4) model dissemination. The program is currently nearing completion of Phase 2 - Model Development
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
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...
The model case IRS-RWE for the determination of reliability data in practical operation
International Nuclear Information System (INIS)
Hoemke, P.; Krause, H.
1975-11-01
Reliability und availability analyses are carried out to assess the safety of nuclear power plants. This paper deals in the first part with the requirement of accuracy for the input data of such analyses and in the second part with the prototype data collection of reliability data 'Model case IRS-RWE'. The objectives and the structure of the data collection will be described. The present results show that the estimation of reliability data in power plants is possible and gives reasonable results. (orig.) [de
Gilmanshin, I. R.; Kirpichnikov, A. P.
2017-09-01
In the result of study of the algorithm of the functioning of the early detection module of excessive losses, it is proven the ability to model it by using absorbing Markov chains. The particular interest is in the study of probability characteristics of early detection module functioning algorithm of losses in order to identify the relationship of indicators of reliability of individual elements, or the probability of occurrence of certain events and the likelihood of transmission of reliable information. The identified relations during the analysis allow to set thresholds reliability characteristics of the system components.
Maintenance overtime policies in reliability theory models with random working cycles
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...
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
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
On modeling human reliability in space flights - Redundancy and recovery operations
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.
Flower Power: Sunflowers as a Model for Logistic Growth
Fernandez, Eileen; Geist, Kristi A.
2011-01-01
Logistic growth displays an interesting pattern: It starts fast, exhibiting the rapid growth characteristic of exponential models. As time passes, it slows in response to constraints such as limited resources or reallocation of energy. The growth continues to slow until it reaches a limit, called capacity. When the growth describes a population,…
Energy Technology Data Exchange (ETDEWEB)
Dong, Jing [ORNL; Mahmassani, Hani S. [Northwestern University, Evanston
2011-01-01
This paper proposes a methodology to produce random flow breakdown endogenously in a mesoscopic operational model, by capturing breakdown probability and duration. Based on previous research findings that probability of flow breakdown can be represented as a function of flow rate and the duration can be characterized by a hazard model. By generating random flow breakdown at various levels and capturing the traffic characteristics at the onset of the breakdown, the stochastic network simulation model provides a tool for evaluating travel time variability. The proposed model can be used for (1) providing reliability related traveler information; (2) designing ITS (intelligent transportation systems) strategies to improve reliability; and (3) evaluating reliability-related performance measures of the system.
Structural reliability analysis under evidence theory using the active learning kriging model
Yang, Xufeng; Liu, Yongshou; Ma, Panke
2017-11-01
Structural reliability analysis under evidence theory is investigated. It is rigorously proved that a surrogate model providing only correct sign prediction of the performance function can meet the accuracy requirement of evidence-theory-based reliability analysis. Accordingly, a method based on the active learning kriging model which only correctly predicts the sign of the performance function is proposed. Interval Monte Carlo simulation and a modified optimization method based on Karush-Kuhn-Tucker conditions are introduced to make the method more efficient in estimating the bounds of failure probability based on the kriging model. Four examples are investigated to demonstrate the efficiency and accuracy of the proposed method.
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
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.
Brady, Michael P.; Heiser, Lawrence A.; McCormick, Jazarae K.; Forgan, James
2016-01-01
High-stakes standardized student assessments are increasingly used in value-added evaluation models to connect teacher performance to P-12 student learning. These assessments are also being used to evaluate teacher preparation programs, despite validity and reliability threats. A more rational model linking student performance to candidates who…
An adaptive neuro fuzzy model for estimating the reliability of component-based software systems
Directory of Open Access Journals (Sweden)
Kirti Tyagi
2014-01-01
Full Text Available Although many algorithms and techniques have been developed for estimating the reliability of component-based software systems (CBSSs, much more research is needed. Accurate estimation of the reliability of a CBSS is difficult because it depends on two factors: component reliability and glue code reliability. Moreover, reliability is a real-world phenomenon with many associated real-time problems. Soft computing techniques can help to solve problems whose solutions are uncertain or unpredictable. A number of soft computing approaches for estimating CBSS reliability have been proposed. These techniques learn from the past and capture existing patterns in data. The two basic elements of soft computing are neural networks and fuzzy logic. In this paper, we propose a model for estimating CBSS reliability, known as an adaptive neuro fuzzy inference system (ANFIS, that is based on these two basic elements of soft computing, and we compare its performance with that of a plain FIS (fuzzy inference system for different data sets.
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 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.
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.
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.
International Nuclear Information System (INIS)
Hollo, E.
1985-08-01
Present Final Report summarizes results of R/D work done within IAEA-VEIKI (Institute for Electrical Power Research, Budapest, Hungary) Research Contract No. 3210 during 3 years' period of 01.08.1982 - 31.08.1985. Chapter 1 lists main research objectives of the project. Main results obtained are summarized in Chapters 2 and 3. Outcomes from development of failure modelling methodologies and their application for C/I components of WWER-440 units are as follows (Chapter 2): improvement of available ''failure mode and effect analysis'' methods and mini-fault tree structures usable for automatic disturbance (DAS) and reliability (RAS) analysis; general classification and determination of functional failure modes of WWER-440 NPP C/I components; set up of logic models for motor operated control valves and rod control/drive mechanism. Results of development of methods and their application for reliability modelling of NPP components and systems cover (Chapter 3): development of an algorithm (computer code COMPREL) for component-related failure and reliability parameter calculation; reliability analysis of PAKS II NPP diesel system; definition of functional requirements for reliability data bank (RDB) in WWER-440 units. Determination of RDB input/output data structure and data manipulation services. Methods used are a-priori failure mode and effect analysis, combined fault tree/event tree modelling technique, structural computer programming, probability theory application to nuclear field
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.
Reliability Analysis of Sealing Structure of Electromechanical System Based on Kriging Model
Zhang, F.; Wang, Y. M.; Chen, R. W.; Deng, W. W.; Gao, Y.
2018-05-01
The sealing performance of aircraft electromechanical system has a great influence on flight safety, and the reliability of its typical seal structure is analyzed by researcher. In this paper, we regard reciprocating seal structure as a research object to study structural reliability. Having been based on the finite element numerical simulation method, the contact stress between the rubber sealing ring and the cylinder wall is calculated, and the relationship between the contact stress and the pressure of the hydraulic medium is built, and the friction force on different working conditions are compared. Through the co-simulation, the adaptive Kriging model obtained by EFF learning mechanism is used to describe the failure probability of the seal ring, so as to evaluate the reliability of the sealing structure. This article proposes a new idea of numerical evaluation for the reliability analysis of sealing structure, and also provides a theoretical basis for the optimal design of sealing structure.
[Reliability study in the measurement of the cusp inclination angle of a chairside digital model].
Xinggang, Liu; Xiaoxian, Chen
2018-02-01
This study aims to evaluate the reliability of the software Picpick in the measurement of the cusp inclination angle of a digital model. Twenty-one trimmed models were used as experimental objects. The chairside digital impression was then used for the acquisition of 3D digital models, and the software Picpick was employed for the measurement of the cusp inclination of these models. The measurements were repeated three times, and the results were compared with a gold standard, which was a manually measured experimental model cusp angle. The intraclass correlation coefficient (ICC) was calculated. The paired t test value of the two measurement methods was 0.91. The ICCs between the two measurement methods and three repeated measurements were greater than 0.9. The digital model achieved a smaller coefficient of variation (9.9%). The software Picpick is reliable in measuring the cusp inclination of a digital model.
Directory of Open Access Journals (Sweden)
Hea-Jung Kim
2017-06-01
Full Text Available This paper develops Bayesian inference in reliability of a class of scale mixtures of log-normal failure time (SMLNFT models with stochastic (or uncertain constraint in their reliability measures. The class is comprehensive and includes existing failure time (FT models (such as log-normal, log-Cauchy, and log-logistic FT models as well as new models that are robust in terms of heavy-tailed FT observations. Since classical frequency approaches to reliability analysis based on the SMLNFT model with stochastic constraint are intractable, the Bayesian method is pursued utilizing a Markov chain Monte Carlo (MCMC sampling based approach. This paper introduces a two-stage maximum entropy (MaxEnt prior, which elicits a priori uncertain constraint and develops Bayesian hierarchical SMLNFT model by using the prior. The paper also proposes an MCMC method for Bayesian inference in the SMLNFT model reliability and calls attention to properties of the MaxEnt prior that are useful for method development. Finally, two data sets are used to illustrate how the proposed methodology works.
International Nuclear Information System (INIS)
Pan Zhengqiang; Balakrishnan, Narayanaswamy
2011-01-01
Many highly reliable products usually have complex structure, with their reliability being evaluated by two or more performance characteristics. In certain physical situations, the degradation of these performance characteristics would be always positive and strictly increasing. In such a case, the gamma process is usually considered as a degradation process due to its independent and non-negative increments properties. In this paper, we suppose that a product has two dependent performance characteristics and that their degradation can be modeled by gamma processes. For such a bivariate degradation involving two performance characteristics, we propose to use a bivariate Birnbaum-Saunders distribution and its marginal distributions to approximate the reliability function. Inferential method for the corresponding model parameters is then developed. Finally, for an illustration of the proposed model and method, a numerical example about fatigue cracks is discussed and some computational results are presented.
Inter-arch digital model vs. manual cast measurements: Accuracy and reliability.
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.
Directory of Open Access Journals (Sweden)
A. Campanile
2018-01-01
Full Text Available The incidence of collision damage models on oil tanker and bulk carrier reliability is investigated considering the IACS deterministic model against GOALDS/IMO database statistics for collision events, substantiating the probabilistic model. Statistical properties of hull girder residual strength are determined by Monte Carlo simulation, based on random generation of damage dimensions and a modified form of incremental-iterative method, to account for neutral axis rotation and equilibrium of horizontal bending moment, due to cross-section asymmetry after collision events. Reliability analysis is performed, to investigate the incidence of collision penetration depth and height statistical properties on hull girder sagging/hogging failure probabilities. Besides, the incidence of corrosion on hull girder residual strength and reliability is also discussed, focussing on gross, hull girder net and local net scantlings, respectively. The ISSC double hull oil tanker and single side bulk carrier, assumed as test cases in the ISSC 2012 report, are taken as reference ships.
REFERENCE MODELS OF ENDOGENOUS ECONOMIC GROWTH
GEAMĂNU MARINELA
2012-01-01
The new endogenous growth theories are a very important research area for shaping the most effective policies and long term sustainable development strategies. Endogenous growth theory has emerged as a reaction to the imperfections of neoclassical theory, by the fact that the economic growth is the endogenous product of an economical system.
Modeling urban growth in Kigali city Rwanda
Nduwayezu, G.; Sliuzas, R.V.; Kuffer, M.
2017-01-01
The uncontrolled urban growth is the key characteristics in most cities in less developed countries. However, having a good understanding of the key drivers of the city's growth dynamism has proven to be a key instrument to manage urban growth. This paper investigates the main determinants of Kigali
Auconi, Pietro; Scazzocchio, Marco; Defraia, Efisio; McNamara, James A; Franchi, Lorenzo
2014-04-01
To develop a mathematical model that adequately represented the pattern of craniofacial growth in class III subject consistently, with the goal of using this information to make growth predictions that could be amenable to longitudinal verification and clinical use. A combination of computational techniques (i.e. Fuzzy clustering and Network analysis) was applied to cephalometric data derived from 429 untreated growing female patients with class III malocclusion to visualize craniofacial growth dynamics and correlations. Four age groups of subjects were examined individually: from 7 to 9 years of age, from 10 to 12 years, from 13 to 14 years, and from 15 to 17 years. The connections between pathway components of class III craniofacial growth can be visualized from Network profiles. Fuzzy clustering analysis was able to define further growth patterns and coherences of the traditionally reported dentoskeletal characteristics of this structural imbalance. Craniofacial growth can be visualized as a biological, space-constraint-based optimization process; the prediction of individual growth trajectories depends on the rate of membership to a specific 'winner' cluster, i.e. on a specific individual growth strategy. The reliability of the information thus gained was tested to forecast craniofacial growth of 28 untreated female class III subjects followed longitudinally. The combination of Fuzzy clustering and Network algorithms allowed the development of principles for combining multiple auxological cephalometric features into a joint global model and to predict the individual risk of the facial pattern imbalance during growth.
Study of growth kinetic and modeling of ethanol production by ...
African Journals Online (AJOL)
... coefficient (0.96299). Based on Leudking-Piret model, it could be concluded that ethanol batch fermentation is a non-growth associated process. Key words: Kinetic parameters, simulation, cell growth, ethanol, Saccharomyces cerevisiae.
Development of Markov model of emergency diesel generator for dynamic reliability analysis
Energy Technology Data Exchange (ETDEWEB)
Jin, Young Ho; Choi, Sun Yeong; Yang, Joon Eon [Korea Atomic Energy Research Institute, Taejon (Korea)
1999-02-01
The EDG (Emergency Diesal Generator) of nuclear power plant is one of the most important equipments in mitigating accidents. The FT (Fault Tree) method is widely used to assess the reliability of safety systems like an EDG in nuclear power plant. This method, however, has limitations in modeling dynamic features of safety systems exactly. We, hence, have developed a Markov model to represent the stochastic process of dynamic systems whose states change as time moves on. The Markov model enables us to develop a dynamic reliability model of EDG. This model can represent all possible states of EDG comparing to the FRANTIC code developed by U.S. NRC for the reliability analysis of standby systems. to access the regulation policy for test interval, we performed two simulations based on the generic data and plant specific data of YGN 3, respectively by using the developed model. We also estimate the effects of various repair rates and the fractions of starting failures by demand shock to the reliability of EDG. And finally, Aging effect is analyzed. (author). 23 refs., 19 figs., 9 tabs.
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
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.
ARA and ARI imperfect repair models: Estimation, goodness-of-fit and reliability prediction
International Nuclear Information System (INIS)
Toledo, Maria Luíza Guerra de; Freitas, Marta A.; Colosimo, Enrico A.; Gilardoni, Gustavo L.
2015-01-01
An appropriate maintenance policy is essential to reduce expenses and risks related to equipment failures. A fundamental aspect to be considered when specifying such policies is to be able to predict the reliability of the systems under study, based on a well fitted model. In this paper, the classes of models Arithmetic Reduction of Age and Arithmetic Reduction of Intensity are explored. Likelihood functions for such models are derived, and a graphical method is proposed for model selection. A real data set involving failures in trucks used by a Brazilian mining is analyzed considering models with different memories. Parameters, namely, shape and scale for Power Law Process, and the efficiency of repair were estimated for the best fitted model. Estimation of model parameters allowed us to derive reliability estimators to predict the behavior of the failure process. These results are a valuable information for the mining company and can be used to support decision making regarding preventive maintenance policy. - Highlights: • Likelihood functions for imperfect repair models are derived. • A goodness-of-fit technique is proposed as a tool for model selection. • Failures in trucks owned by a Brazilian mining are modeled. • Estimation allowed deriving reliability predictors to forecast the future failure process of the trucks
Reactive burn models and ignition & growth concept
Directory of Open Access Journals (Sweden)
Shaw M.S.
2011-01-01
Full Text Available Plastic-bonded explosives are heterogeneous materials. Experimentally, shock initiation is sensitive to small amounts of porosity, due to the formation of hot spots (small localized regions of high temperature. This leads to the Ignition & Growth concept, introduced by LeeTarver in 1980, as the basis for reactive burn models. A homo- genized burn rate needs to account for three meso-scale physical effects: (i the density of active hot spots or burn centers; (ii the growth of the burn fronts triggered by the burn centers; (iii a geometric factor that accounts for the overlap of deflagration wavelets from adjacent burn centers. These effects can be combined and the burn model defined by specifying the reaction progress variable λ = g(s as a function of a dimensionless reaction length s(t = rbc/ℓbc, rather than by specifying an explicit burn rate. The length scale ℓbc(Ps = [Nbc(Ps]−1/3 is the average distance between burn centers, where Nbc is the number density of burn centers activated by the lead shock. The reaction length rbc(t = ∫t0 D(P(t′dt′ is the distance the burn front propagates from a single burn center, where D(P is the deflagration speed as a function of the local pressure and t is the time since the shock arrival. A key implementation issue is how to determine the lead shock strength in conjunction with a shock capturing scheme. We have developed a robust algorithm for this purpose based on the Hugoniot jump condition for the energy. The algorithm utilizes the time dependence of density, pressure and energy within each cell. The method is independent of the numerical dissipation used for shock capturing. It is local and can be used in one or more space dimensions. The burn model has a small number of parameters which can be calibrated to fit velocity gauge data from shock initiation experiments.
International Nuclear Information System (INIS)
Srividya, A.; Suresh, H.N.; Verma, A.K.; Gopika, V.; Santosh
2006-01-01
Piping systems are part of passive structural elements in power plants. The analysis of the piping systems and their quantification in terms of failure probability is of utmost importance. The piping systems may fail due to various degradation mechanisms like thermal fatigue, erosion-corrosion, stress corrosion cracking and vibration fatigue. On examination of previous results, erosion corrosion was more prevalent and wall thinning is a time dependent phenomenon. The paper is intended to consolidate the work done by various investigators on erosion corrosion in estimating the erosion corrosion rate and reliability predictions. A comparison of various erosion corrosion models is made. The reliability predictions based on remaining strength of corroded pipelines by wall thinning is also attempted. Variables in the limit state functions are modelled using normal distributions and Reliability assessment is carried out using some of the existing failure pressure models. A steady state corrosion rate is assumed to estimate the corrosion defect and First Order Reliability Method (FORM) is used to find the probability of failure associated with corrosion defects over time using the software for Component Reliability evaluation (COMREL). (author)
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.
Stochastic modeling of thermal fatigue crack growth
Radu, Vasile
2015-01-01
The book describes a systematic stochastic modeling approach for assessing thermal-fatigue crack-growth in mixing tees, based on the power spectral density of temperature fluctuation at the inner pipe surface. It shows the development of a frequency-temperature response function in the framework of single-input, single-output (SISO) methodology from random noise/signal theory under sinusoidal input. The frequency response of stress intensity factor (SIF) is obtained by a polynomial fitting procedure of thermal stress profiles at various instants of time. The method, which takes into account the variability of material properties, and has been implemented in a real-world application, estimates the probabilities of failure by considering a limit state function and Monte Carlo analysis, which are based on the proposed stochastic model. Written in a comprehensive and accessible style, this book presents a new and effective method for assessing thermal fatigue crack, and it is intended as a concise and practice-or...
Neo-logistic model for the growth of bacteria
Tashiro, Tohru; Yoshimura, Fujiko
2017-01-01
We propose a neo-logistic model that can describe bacterial growth data precisely. This model is not derived by modifying the logistic model formally, but by incorporating the synthesis of inducible enzymes into the logistic model indirectly. Therefore, the meaning of the parameters of the neo-logistic model becomes physically clear. The neo-logistic model can approximate bacterial growth better than models previously presented, and predict the order of the saturated number of bacteria in the...
Intra-observer reliability and agreement of manual and digital orthodontic model analysis.
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 simulation model for reliability evaluation of Space Station power systems
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.
Testing linear growth rate formulas of non-scale endogenous growth models
Ziesemer, Thomas
2017-01-01
Endogenous growth theory has produced formulas for steady-state growth rates of income per capita which are linear in the growth rate of the population. Depending on the details of the models, slopes and intercepts are positive, zero or negative. Empirical tests have taken over the assumption of
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.
Reliable gain-scheduled control of discrete-time systems and its application to CSTR model
Sakthivel, R.; Selvi, S.; Mathiyalagan, K.; Shi, Y.
2016-10-01
This paper is focused on reliable gain-scheduled controller design for a class of discrete-time systems with randomly occurring nonlinearities and actuator fault. Further, the nonlinearity in the system model is assumed to occur randomly according to a Bernoulli distribution with measurable time-varying probability in real time. The main purpose of this paper is to design a gain-scheduled controller by implementing a probability-dependent Lyapunov function and linear matrix inequality (LMI) approach such that the closed-loop discrete-time system is stochastically stable for all admissible randomly occurring nonlinearities. The existence conditions for the reliable controller is formulated in terms of LMI constraints. Finally, the proposed reliable gain-scheduled control scheme is applied on continuously stirred tank reactor model to demonstrate the effectiveness and applicability of the proposed design technique.
Study on reliability analysis based on multilevel flow models and fault tree method
International Nuclear Information System (INIS)
Chen Qiang; Yang Ming
2014-01-01
Multilevel flow models (MFM) and fault tree method describe the system knowledge in different forms, so the two methods express an equivalent logic of the system reliability under the same boundary conditions and assumptions. Based on this and combined with the characteristics of MFM, a method mapping MFM to fault tree was put forward, thus providing a way to establish fault tree rapidly and realizing qualitative reliability analysis based on MFM. Taking the safety injection system of pressurized water reactor nuclear power plant as an example, its MFM was established and its reliability was analyzed qualitatively. The analysis result shows that the logic of mapping MFM to fault tree is correct. The MFM is easily understood, created and modified. Compared with the traditional fault tree analysis, the workload is greatly reduced and the modeling time is saved. (authors)
Woessner, J.
2012-07-14
Static stress transfer is one physical mechanism to explain triggered seismicity. Coseismic stress-change calculations strongly depend on the parameterization of the causative finite-fault source model. These models are uncertain due to uncertainties in input data, model assumptions, and modeling procedures. However, fault model uncertainties have usually been ignored in stress-triggering studies and have not been propagated to assess the reliability of Coulomb failure stress change (ΔCFS) calculations. We show how these uncertainties can be used to provide confidence intervals for co-seismic ΔCFS-values. We demonstrate this for the MW = 5.9 June 2000 Kleifarvatn earthquake in southwest Iceland and systematically map these uncertainties. A set of 2500 candidate source models from the full posterior fault-parameter distribution was used to compute 2500 ΔCFS maps. We assess the reliability of the ΔCFS-values from the coefficient of variation (CV) and deem ΔCFS-values to be reliable where they are at least twice as large as the standard deviation (CV ≤ 0.5). Unreliable ΔCFS-values are found near the causative fault and between lobes of positive and negative stress change, where a small change in fault strike causes ΔCFS-values to change sign. The most reliable ΔCFS-values are found away from the source fault in the middle of positive and negative ΔCFS-lobes, a likely general pattern. Using the reliability criterion, our results support the static stress-triggering hypothesis. Nevertheless, our analysis also suggests that results from previous stress-triggering studies not considering source model uncertainties may have lead to a biased interpretation of the importance of static stress-triggering.
The application of cognitive models to the evaluation and prediction of human reliability
International Nuclear Information System (INIS)
Embrey, D.E.; Reason, J.T.
1986-01-01
The first section of the paper provides a brief overview of a number of important principles relevant to human reliability modeling that have emerged from cognitive models, and presents a synthesis of these approaches in the form of a Generic Error Modeling System (GEMS). The next section illustrates the application of GEMS to some well known nuclear power plant (NPP) incidents in which human error was a major contributor. The way in which design recommendations can emerge from analyses of this type is illustrated. The third section describes the use of cognitive models in the classification of human errors for prediction and data collection purposes. The final section addresses the predictive modeling of human error as part of human reliability assessment in Probabilistic Risk Assessment
A hybrid reliability algorithm using PSO-optimized Kriging model and adaptive importance sampling
Tong, Cao; Gong, Haili
2018-03-01
This paper aims to reduce the computational cost of reliability analysis. A new hybrid algorithm is proposed based on PSO-optimized Kriging model and adaptive importance sampling method. Firstly, the particle swarm optimization algorithm (PSO) is used to optimize the parameters of Kriging model. A typical function is fitted to validate improvement by comparing results of PSO-optimized Kriging model with those of the original Kriging model. Secondly, a hybrid algorithm for reliability analysis combined optimized Kriging model and adaptive importance sampling is proposed. Two cases from literatures are given to validate the efficiency and correctness. The proposed method is proved to be more efficient due to its application of small number of sample points according to comparison results.
A literature review on growth models and strategies: The missing link in entrepreneurial growth
Directory of Open Access Journals (Sweden)
Syed Fida Hussain Shah
2013-08-01
Full Text Available This study focuses on the importance of growth models, growth strategies, role of knowledge management system in the formulation of effective strategy for the enterprises following growth. Choice of an appropriate growth strategy is at the heart of any successful entrepreneurial venture. Selection of a strategy may be effective for one entrepreneur while it is not for other. Choice of Growth Strategy depends on various different factors, organisational context and environment which may vary from enterprise to enterprise. Resource based view is very important consideration for the entrepreneurs on the path of growth. Evaluation of all kind of resources helps them to grow their enterprises successfully. Selection of an appropriate growth strategy allows the entrepreneurs in overcoming growth challenges and avoiding the growth reversals and setbacks.
Model of load balancing using reliable algorithm with multi-agent system
Afriansyah, M. F.; Somantri, M.; Riyadi, M. A.
2017-04-01
Massive technology development is linear with the growth of internet users which increase network traffic activity. It also increases load of the system. The usage of reliable algorithm and mobile agent in distributed load balancing is a viable solution to handle the load issue on a large-scale system. Mobile agent works to collect resource information and can migrate according to given task. We propose reliable load balancing algorithm using least time first byte (LFB) combined with information from the mobile agent. In system overview, the methodology consisted of defining identification system, specification requirements, network topology and design system infrastructure. The simulation method for simulated system was using 1800 request for 10 s from the user to the server and taking the data for analysis. Software simulation was based on Apache Jmeter by observing response time and reliability of each server and then compared it with existing method. Results of performed simulation show that the LFB method with mobile agent can perform load balancing with efficient systems to all backend server without bottleneck, low risk of server overload, and reliable.
Layered growth model and epitaxial growth structures for SiCAlN alloys
International Nuclear Information System (INIS)
Liu Zhaoqing; Ni Jun; Su Xiaoao; Dai Zhenhong
2009-01-01
Epitaxial growth structures for (SiC) 1-x (AlN) x alloys are studied using a layered growth model. First-principle calculations are used to determine the parameters in the layered growth model. The phase diagrams of epitaxial growth are given. There is a rich variety of the new metastable polytype structures at x=1/6 ,1/5 ,1/4 ,1/3 , and 1/2 in the layered growth phase diagrams. We have also calculated the electronic properties of the short periodical SiCAlN alloys predicted by our layered growth model. The results show that various ordered structures of (SiC) 1-x (AlN) x alloys with the band gaps over a wide range are possible to be synthesized by epitaxial growth.
Development of web-based reliability data analysis algorithm model and its application
International Nuclear Information System (INIS)
Hwang, Seok-Won; Oh, Ji-Yong; Moosung-Jae
2010-01-01
For this study, a database model of plant reliability was developed for the effective acquisition and management of plant-specific data that can be used in various applications of plant programs as well as in Probabilistic Safety Assessment (PSA). Through the development of a web-based reliability data analysis algorithm, this approach systematically gathers specific plant data such as component failure history, maintenance history, and shift diary. First, for the application of the developed algorithm, this study reestablished the raw data types, data deposition procedures and features of the Enterprise Resource Planning (ERP) system process. The component codes and system codes were standardized to make statistical analysis between different types of plants possible. This standardization contributes to the establishment of a flexible database model that allows the customization of reliability data for the various applications depending on component types and systems. In addition, this approach makes it possible for users to perform trend analyses and data comparisons for the significant plant components and systems. The validation of the algorithm is performed through a comparison of the importance measure value (Fussel-Vesely) of the mathematical calculation and that of the algorithm application. The development of a reliability database algorithm is one of the best approaches for providing systemic management of plant-specific reliability data with transparency and continuity. This proposed algorithm reinforces the relationships between raw data and application results so that it can provide a comprehensive database that offers everything from basic plant-related data to final customized data.
A Review of the Progress with Statistical Models of Passive Component Reliability
Directory of Open Access Journals (Sweden)
Bengt O.Y. Lydell
2017-03-01
Full Text Available During the past 25 years, in the context of probabilistic safety assessment, efforts have been directed towards establishment of comprehensive pipe failure event databases as a foundation for exploratory research to better understand how to effectively organize a piping reliability analysis task. The focused pipe failure database development efforts have progressed well with the development of piping reliability analysis frameworks that utilize the full body of service experience data, fracture mechanics analysis insights, expert elicitation results that are rolled into an integrated and risk-informed approach to the estimation of piping reliability parameters with full recognition of the embedded uncertainties. The discussion in this paper builds on a major collection of operating experience data (more than 11,000 pipe failure records and the associated lessons learned from data analysis and data applications spanning three decades. The piping reliability analysis lessons learned have been obtained from the derivation of pipe leak and rupture frequencies for corrosion resistant piping in a raw water environment, loss-of-coolant-accident frequencies given degradation mitigation, high-energy pipe break analysis, moderate-energy pipe break analysis, and numerous plant-specific applications of a statistical piping reliability model framework. Conclusions are presented regarding the feasibility of determining and incorporating aging effects into probabilistic safety assessment models.
A review of the progress with statistical models of passive component reliability
Energy Technology Data Exchange (ETDEWEB)
Lydell, Bengt O. Y. [Sigma-Phase Inc., Vail (United States)
2017-03-15
During the past 25 years, in the context of probabilistic safety assessment, efforts have been directed towards establishment of comprehensive pipe failure event databases as a foundation for exploratory research to better understand how to effectively organize a piping reliability analysis task. The focused pipe failure database development efforts have progressed well with the development of piping reliability analysis frameworks that utilize the full body of service experience data, fracture mechanics analysis insights, expert elicitation results that are rolled into an integrated and risk-informed approach to the estimation of piping reliability parameters with full recognition of the embedded uncertainties. The discussion in this paper builds on a major collection of operating experience data (more than 11,000 pipe failure records) and the associated lessons learned from data analysis and data applications spanning three decades. The piping reliability analysis lessons learned have been obtained from the derivation of pipe leak and rupture frequencies for corrosion resistant piping in a raw water environment, loss-of-coolant-accident frequencies given degradation mitigation, high-energy pipe break analysis, moderate-energy pipe break analysis, and numerous plant-specific applications of a statistical piping reliability model framework. Conclusions are presented regarding the feasibility of determining and incorporating aging effects into probabilistic safety assessment models.
Development of web-based reliability data analysis algorithm model and its application
Energy Technology Data Exchange (ETDEWEB)
Hwang, Seok-Won, E-mail: swhwang@khnp.co.k [Korea Hydro and Nuclear Power Co. Ltd., Jang-Dong 25-1, Yuseong-Gu, 305-343 Daejeon (Korea, Republic of); Oh, Ji-Yong [Korea Hydro and Nuclear Power Co. Ltd., Jang-Dong 25-1, Yuseong-Gu, 305-343 Daejeon (Korea, Republic of); Moosung-Jae [Department of Nuclear Engineering Hanyang University 17 Haengdang, Sungdong, Seoul (Korea, Republic of)
2010-02-15
For this study, a database model of plant reliability was developed for the effective acquisition and management of plant-specific data that can be used in various applications of plant programs as well as in Probabilistic Safety Assessment (PSA). Through the development of a web-based reliability data analysis algorithm, this approach systematically gathers specific plant data such as component failure history, maintenance history, and shift diary. First, for the application of the developed algorithm, this study reestablished the raw data types, data deposition procedures and features of the Enterprise Resource Planning (ERP) system process. The component codes and system codes were standardized to make statistical analysis between different types of plants possible. This standardization contributes to the establishment of a flexible database model that allows the customization of reliability data for the various applications depending on component types and systems. In addition, this approach makes it possible for users to perform trend analyses and data comparisons for the significant plant components and systems. The validation of the algorithm is performed through a comparison of the importance measure value (Fussel-Vesely) of the mathematical calculation and that of the algorithm application. The development of a reliability database algorithm is one of the best approaches for providing systemic management of plant-specific reliability data with transparency and continuity. This proposed algorithm reinforces the relationships between raw data and application results so that it can provide a comprehensive database that offers everything from basic plant-related data to final customized data.
Reliability model for helicopter main gearbox lubrication system using influence diagrams
International Nuclear Information System (INIS)
Rashid, H.S.J.; Place, C.S.; Mba, D.; Keong, R.L.C.; Healey, A.; Kleine-Beek, W.; Romano, M.
2015-01-01
The loss of oil from a helicopter main gearbox (MGB) leads to increased friction between components, a rise in component surface temperatures, and subsequent mechanical failure of gearbox components. A number of significant helicopter accidents have been caused due to such loss of lubrication. This paper presents a model to assess the reliability of helicopter MGB lubricating systems. Safety risk modeling was conducted for MGB oil system related accidents in order to analyse key failure mechanisms and the contributory factors. Thus, the dominant failure modes for lubrication systems and key contributing components were identified. The Influence Diagram (ID) approach was then employed to investigate reliability issues of the MGB lubrication systems at the level of primary causal factors, thus systematically investigating a complex context of events, conditions, and influences that are direct triggers of the helicopter MGB lubrication system failures. The interrelationships between MGB lubrication system failure types were thus identified, and the influence of each of these factors on the overall MGB lubrication system reliability was assessed. This paper highlights parts of the HELMGOP project, sponsored by the European Aviation Safety Agency to improve helicopter main gearbox reliability. - Highlights: • We investigated methods to optimize helicopter MGB oil system run-dry capability. • Used Influence Diagram to assess design and maintenance factors of MGB oil system. • Factors influencing overall MGB lubrication system reliability were identified. • This globally influences current and future helicopter MGB designs
A review of the progress with statistical models of passive component reliability
International Nuclear Information System (INIS)
Lydell, Bengt O. Y.
2017-01-01
During the past 25 years, in the context of probabilistic safety assessment, efforts have been directed towards establishment of comprehensive pipe failure event databases as a foundation for exploratory research to better understand how to effectively organize a piping reliability analysis task. The focused pipe failure database development efforts have progressed well with the development of piping reliability analysis frameworks that utilize the full body of service experience data, fracture mechanics analysis insights, expert elicitation results that are rolled into an integrated and risk-informed approach to the estimation of piping reliability parameters with full recognition of the embedded uncertainties. The discussion in this paper builds on a major collection of operating experience data (more than 11,000 pipe failure records) and the associated lessons learned from data analysis and data applications spanning three decades. The piping reliability analysis lessons learned have been obtained from the derivation of pipe leak and rupture frequencies for corrosion resistant piping in a raw water environment, loss-of-coolant-accident frequencies given degradation mitigation, high-energy pipe break analysis, moderate-energy pipe break analysis, and numerous plant-specific applications of a statistical piping reliability model framework. Conclusions are presented regarding the feasibility of determining and incorporating aging effects into probabilistic safety assessment models
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
Directory of Open Access Journals (Sweden)
Renbin Liu
2014-01-01
some important reliability indices are derived, such as availability, failure frequency, mean vacation period, mean renewal cycle, mean startup period, and replacement frequency. Finally, a production line controlled by two cold-standby computers is modeled to present numerical illustration and its optimal part-time job policy at a maximum profit.
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.
A reliability model for interlayer dielectric cracking during fast thermal cycling
Nguyen, Van Hieu; Salm, Cora; Krabbenborg, B.H.; Krabbenborg, B.H.; Bisschop, J.; Mouthaan, A.J.; Kuper, F.G.; Ray, Gary W.; Smy, Tom; Ohta, Tomohiro; Tsujimura, Manabu
2003-01-01
Interlayer dielectric (ILD) cracking can result in short circuits of multilevel interconnects. This paper presents a reliability model for ILD cracking induced by fast thermal cycling (FTC) stress. FTC tests have been performed under different temperature ranges (∆T) and minimum temperatures (Tmin).
Forest Growth and Yield Models Viewed From a Different Perspective
Jeffery C. Goelz
2002-01-01
Typically, when different forms of growth and yield models are considered, they are grouped into convenient discrete classes. As a heuristic device, I chose to use a contrasting perspective, that all growth and yield models are diameter distribution models that merely differ in regard to which diameter distribution is employed and how the distribution is projected to...
Parameter Estimates in Differential Equation Models for Population Growth
Winkel, Brian J.
2011-01-01
We estimate the parameters present in several differential equation models of population growth, specifically logistic growth models and two-species competition models. We discuss student-evolved strategies and offer "Mathematica" code for a gradient search approach. We use historical (1930s) data from microbial studies of the Russian biologist,…
Reliability analysis of nuclear component cooling water system using semi-Markov process model
International Nuclear Information System (INIS)
Veeramany, Arun; Pandey, Mahesh D.
2011-01-01
Research highlights: → Semi-Markov process (SMP) model is used to evaluate system failure probability of the nuclear component cooling water (NCCW) system. → SMP is used because it can solve reliability block diagram with a mixture of redundant repairable and non-repairable components. → The primary objective is to demonstrate that SMP can consider Weibull failure time distribution for components while a Markov model cannot → Result: the variability in component failure time is directly proportional to the NCCW system failure probability. → The result can be utilized as an initiating event probability in probabilistic safety assessment projects. - Abstract: A reliability analysis of nuclear component cooling water (NCCW) system is carried out. Semi-Markov process model is used in the analysis because it has potential to solve a reliability block diagram with a mixture of repairable and non-repairable components. With Markov models it is only possible to assume an exponential profile for component failure times. An advantage of the proposed model is the ability to assume Weibull distribution for the failure time of components. In an attempt to reduce the number of states in the model, it is shown that usage of poly-Weibull distribution arises. The objective of the paper is to determine system failure probability under these assumptions. Monte Carlo simulation is used to validate the model result. This result can be utilized as an initiating event probability in probabilistic safety assessment projects.
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)
Spiral Growth in Plants: Models and Simulations
Allen, Bradford D.
2004-01-01
The analysis and simulation of spiral growth in plants integrates algebra and trigonometry in a botanical setting. When the ideas presented here are used in a mathematics classroom/computer lab, students can better understand how basic assumptions about plant growth lead to the golden ratio and how the use of circular functions leads to accurate…
Li, Wei Bo; Greiter, Matthias; Oeh, Uwe; Hoeschen, Christoph
2011-12-01
The reliability of biokinetic models is essential in internal dose assessments and radiation risk analysis for the public, occupational workers, and patients exposed to radionuclides. In this paper, a method for assessing the reliability of biokinetic models by means of uncertainty and sensitivity analysis was developed. The paper is divided into two parts. In the first part of the study published here, the uncertainty sources of the model parameters for zirconium (Zr), developed by the International Commission on Radiological Protection (ICRP), were identified and analyzed. Furthermore, the uncertainty of the biokinetic experimental measurement performed at the Helmholtz Zentrum München-German Research Center for Environmental Health (HMGU) for developing a new biokinetic model of Zr was analyzed according to the Guide to the Expression of Uncertainty in Measurement, published by the International Organization for Standardization. The confidence interval and distribution of model parameters of the ICRP and HMGU Zr biokinetic models were evaluated. As a result of computer biokinetic modelings, the mean, standard uncertainty, and confidence interval of model prediction calculated based on the model parameter uncertainty were presented and compared to the plasma clearance and urinary excretion measured after intravenous administration. It was shown that for the most important compartment, the plasma, the uncertainty evaluated for the HMGU model was much smaller than that for the ICRP model; that phenomenon was observed for other organs and tissues as well. The uncertainty of the integral of the radioactivity of Zr up to 50 y calculated by the HMGU model after ingestion by adult members of the public was shown to be smaller by a factor of two than that of the ICRP model. It was also shown that the distribution type of the model parameter strongly influences the model prediction, and the correlation of the model input parameters affects the model prediction to a
DEFF Research Database (Denmark)
Guo, Yifei; Gao, Houlei; Wu, Qiuwei
2017-01-01
and WTGs outage. The wind speed correlation between different WFs is included in the two-dimensional multistate WF model by using an improved k-means clustering method. Then, the entire system with two WFs and a threeterminal VSC-HVDC system is modeled as a multi-state generation unit. The proposed model...... is applied to the Roy Billinton test system (RBTS) for adequacy studies. Both the probability and frequency indices are calculated. The effectiveness and accuracy of the combined model is validated by comparing results with the sequential Monte Carlo simulation (MCS) method. The effects of the outage of VSC-HVDC...... system and wind speed correlation on the system reliability were analyzed. Sensitivity analyses were conducted to investigate the impact of repair time of the offshore VSC-HVDC system on system reliability....
Reliability modelling of repairable systems using Petri nets and fuzzy Lambda-Tau methodology
International Nuclear Information System (INIS)
Knezevic, J.; Odoom, E.R.
2001-01-01
A methodology is developed which uses Petri nets instead of the fault tree methodology and solves for reliability indices utilising fuzzy Lambda-Tau method. Fuzzy set theory is used for representing the failure rate and repair time instead of the classical (crisp) set theory because fuzzy numbers allow expert opinions, linguistic variables, operating conditions, uncertainty and imprecision in reliability information to be incorporated into the system model. Petri nets are used because unlike the fault tree methodology, the use of Petri nets allows efficient simultaneous generation of minimal cut and path sets
International Nuclear Information System (INIS)
Oeren, T.I.; Elzas, M.S.; Sheng, G.; Wageningen Agricultural Univ., Netherlands; McMaster Univ., Hamilton, Ontario)
1985-01-01
As is the case with all scientific simulation studies, computerized simulation of nuclear fuel waste management systems can introduce and hide various types of errors. Frameworks to clarify issues of model reliability and software quality assurance are offered. Potential problems with reference to the main areas of concern for reliability and quality are discussed; e.g., experimental issues, decomposition, scope, fidelity, verification, requirements, testing, correctness, robustness are treated with reference to the experience gained in the past. A list comprising over 80 most common computerization errors is provided. Software tools and techniques used to detect and to correct computerization errors are discussed
Meeting Human Reliability Requirements through Human Factors Design, Testing, and Modeling
Energy Technology Data Exchange (ETDEWEB)
R. L. Boring
2007-06-01
In the design of novel systems, it is important for the human factors engineer to work in parallel with the human reliability analyst to arrive at the safest achievable design that meets design team safety goals and certification or regulatory requirements. This paper introduces the System Development Safety Triptych, a checklist of considerations for the interplay of human factors and human reliability through design, testing, and modeling in product development. This paper also explores three phases of safe system development, corresponding to the conception, design, and implementation of a system.
DEFF Research Database (Denmark)
Jacobsen, Stine Lindahl
The paper will present a phd study concerning reliability and validity of music therapy assessment model “Assessment of Parenting Competences” (APC) in the area of families with emotionally neglected children. This study had a multiple strategy design with a philosophical base of critical realism...... and pragmatism. The fixed design for this study was a between and within groups design in testing the APCs reliability and validity. The two different groups were parents with neglected children and parents with non-neglected children. The flexible design had a multiple case study strategy specifically...
Assessment of Electronic Circuits Reliability Using Boolean Truth Table Modeling Method
International Nuclear Information System (INIS)
EI-Shanshoury, A.I.
2011-01-01
This paper explores the use of Boolean Truth Table modeling Method (BTTM) in the analysis of qualitative data. It is widely used in certain fields especially in the fields of electrical and electronic engineering. Our work focuses on the evaluation of power supply circuit reliability using (BTTM) which involves systematic attempts to falsify and identify hypotheses on the basis of truth tables constructed from qualitative data. Reliability parameters such as the system's failure rates for the power supply case study are estimated. All possible state combinations (operating and failed states) of the major components in the circuit were listed and their effects on overall system were studied
Sullivan, Jennifer L; Rivard, Peter E; Shin, Marlena H; Rosen, Amy K
2016-09-01
The lack of a tool for categorizing and differentiating hospitals according to their high reliability organization (HRO)-related characteristics has hindered progress toward implementing and sustaining evidence-based HRO practices. Hospitals would benefit both from an understanding of the organizational characteristics that support HRO practices and from knowledge about the steps necessary to achieve HRO status to reduce the risk of harm and improve outcomes. The High Reliability Health Care Maturity (HRHCM) model, a model for health care organizations' achievement of high reliability with zero patient harm, incorporates three major domains critical for promoting HROs-Leadership, Safety Culture, and Robust Process Improvement ®. A study was conducted to examine the content validity of the HRHCM model and evaluate whether it can differentiate hospitals' maturity levels for each of the model's components. Staff perceptions of patient safety at six US Department of Veterans Affairs (VA) hospitals were examined to determine whether all 14 HRHCM components were present and to characterize each hospital's level of organizational maturity. Twelve of the 14 components from the HRHCM model were detected; two additional characteristics emerged that are present in the HRO literature but not represented in the model-teamwork culture and system-focused tools for learning and improvement. Each hospital's level of organizational maturity could be characterized for 9 of the 14 components. The findings suggest the HRHCM model has good content validity and that there is differentiation between hospitals on model components. Additional research is needed to understand how these components can be used to build the infrastructure necessary for reaching high reliability.
Discrete Address Beacon System (DABS) Software System Reliability Modeling and Prediction.
1981-06-01
Service ( ATARS ) module because of its interim status. Reliability prediction models for software modules were derived and then verified by matching...System (A’iCR3BS) and thus can be introduced gradually and economically without ma jor olper- ational or procedural change. Since DABS uses monopulse...lineanaly- sis tools or are ured during maintenance or pre-initialization were not modeled because they are not part of the mission software. The ATARS
Growth Kinetics and Modeling of Direct Oxynitride Growth with NO-O2 Gas Mixtures
Energy Technology Data Exchange (ETDEWEB)
Everist, Sarah; Nelson, Jerry; Sharangpani, Rahul; Smith, Paul Martin; Tay, Sing-Pin; Thakur, Randhir
1999-05-03
We have modeled growth kinetics of oxynitrides grown in NO-O_{2} gas mixtures from first principles using modified Deal-Grove equations. Retardation of oxygen diffusion through the nitrided dielectric was assumed to be the dominant growth-limiting step. The model was validated against experimentally obtained curves with good agreement. Excellent uniformity, which exceeded expected walues, was observed.
Detecting Growth Shape Misspecifications in Latent Growth Models: An Evaluation of Fit Indexes
Leite, Walter L.; Stapleton, Laura M.
2011-01-01
In this study, the authors compared the likelihood ratio test and fit indexes for detection of misspecifications of growth shape in latent growth models through a simulation study and a graphical analysis. They found that the likelihood ratio test, MFI, and root mean square error of approximation performed best for detecting model misspecification…
System principles, mathematical models and methods to ensure high reliability of safety systems
Zaslavskyi, V.
2017-04-01
Modern safety and security systems are composed of a large number of various components designed for detection, localization, tracking, collecting, and processing of information from the systems of monitoring, telemetry, control, etc. They are required to be highly reliable in a view to correctly perform data aggregation, processing and analysis for subsequent decision making support. On design and construction phases of the manufacturing of such systems a various types of components (elements, devices, and subsystems) are considered and used to ensure high reliability of signals detection, noise isolation, and erroneous commands reduction. When generating design solutions for highly reliable systems a number of restrictions and conditions such as types of components and various constrains on resources should be considered. Various types of components perform identical functions; however, they are implemented using diverse principles, approaches and have distinct technical and economic indicators such as cost or power consumption. The systematic use of different component types increases the probability of tasks performing and eliminates the common cause failure. We consider type-variety principle as an engineering principle of system analysis, mathematical models based on this principle, and algorithms for solving optimization problems of highly reliable safety and security systems design. Mathematical models are formalized in a class of two-level discrete optimization problems of large dimension. The proposed approach, mathematical models, algorithms can be used for problem solving of optimal redundancy on the basis of a variety of methods and control devices for fault and defects detection in technical systems, telecommunication networks, and energy systems.
Adjoint sensitivity analysis of dynamic reliability models based on Markov chains - I: Theory
International Nuclear Information System (INIS)
Cacuci, D. G.; Cacuci, D. G.; Ionescu-Bujor, M.
2008-01-01
The development of the adjoint sensitivity analysis procedure (ASAP) for generic dynamic reliability models based on Markov chains is presented, together with applications of this procedure to the analysis of several systems of increasing complexity. The general theory is presented in Part I of this work and is accompanied by a paradigm application to the dynamic reliability analysis of a simple binary component, namely a pump functioning on an 'up/down' cycle until it fails irreparably. This paradigm example admits a closed form analytical solution, which permits a clear illustration of the main characteristics of the ASAP for Markov chains. In particular, it is shown that the ASAP for Markov chains presents outstanding computational advantages over other procedures currently in use for sensitivity and uncertainty analysis of the dynamic reliability of large-scale systems. This conclusion is further underscored by the large-scale applications presented in Part II. (authors)
Adjoint sensitivity analysis of dynamic reliability models based on Markov chains - I: Theory
Energy Technology Data Exchange (ETDEWEB)
Cacuci, D. G. [Commiss Energy Atom, Direct Energy Nucl, Saclay, (France); Cacuci, D. G. [Univ Karlsruhe, Inst Nucl Technol and Reactor Safety, D-76021 Karlsruhe, (Germany); Ionescu-Bujor, M. [Forschungszentrum Karlsruhe, Fus Program, D-76021 Karlsruhe, (Germany)
2008-07-01
The development of the adjoint sensitivity analysis procedure (ASAP) for generic dynamic reliability models based on Markov chains is presented, together with applications of this procedure to the analysis of several systems of increasing complexity. The general theory is presented in Part I of this work and is accompanied by a paradigm application to the dynamic reliability analysis of a simple binary component, namely a pump functioning on an 'up/down' cycle until it fails irreparably. This paradigm example admits a closed form analytical solution, which permits a clear illustration of the main characteristics of the ASAP for Markov chains. In particular, it is shown that the ASAP for Markov chains presents outstanding computational advantages over other procedures currently in use for sensitivity and uncertainty analysis of the dynamic reliability of large-scale systems. This conclusion is further underscored by the large-scale applications presented in Part II. (authors)
Data Applicability of Heritage and New Hardware for Launch Vehicle System Reliability Models
Al Hassan Mohammad; Novack, Steven
2015-01-01
Many launch vehicle systems are designed and developed using heritage and new hardware. In most cases, the heritage hardware undergoes modifications to fit new functional system requirements, impacting the failure rates and, ultimately, the reliability data. New hardware, which lacks historical data, is often compared to like systems when estimating failure rates. Some qualification of applicability for the data source to the current system should be made. Accurately characterizing the reliability data applicability and quality under these circumstances is crucial to developing model estimations that support confident decisions on design changes and trade studies. This presentation will demonstrate a data-source classification method that ranks reliability data according to applicability and quality criteria to a new launch vehicle. This method accounts for similarities/dissimilarities in source and applicability, as well as operating environments like vibrations, acoustic regime, and shock. This classification approach will be followed by uncertainty-importance routines to assess the need for additional data to reduce uncertainty.
Directory of Open Access Journals (Sweden)
Jing Li
2015-01-01
Full Text Available Motivated by the need for loosely coupled and asynchronous dissemination of information, message queues are widely used in large-scale application areas. With the advent of virtualization technology, cloud-based message queueing services (CMQSs with distributed computing and storage are widely adopted to improve availability, scalability, and reliability; however, a critical issue is its performance and the quality of service (QoS. While numerous approaches evaluating system performance are available, there is no modeling approach for estimating and analyzing the performance of CMQSs. In this paper, we employ both the analytical and simulation modeling to address the performance of CMQSs with reliability guarantee. We present a visibility-based modeling approach (VMA for simulation model using colored Petri nets (CPN. Our model incorporates the important features of message queueing services in the cloud such as replication, message consistency, resource virtualization, and especially the mechanism named visibility timeout which is adopted in the services to guarantee system reliability. Finally, we evaluate our model through different experiments under varied scenarios to obtain important performance metrics such as total message delivery time, waiting number, and components utilization. Our results reveal considerable insights into resource scheduling and system configuration for service providers to estimate and gain performance optimization.
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
Modeling Urban Spatial Growth in Mountainous Regions of Western China
Directory of Open Access Journals (Sweden)
Guoping Huang
2017-08-01
Full Text Available The scale and speed of urbanization in the mountainous regions of western China have received little attention from researchers. These cities are facing rapid population growth and severe environmental degradation. This study analyzed historical urban growth trends in this mountainous region to better understand the interaction between the spatial growth pattern and the mountainous topography. Three major factors—slope, accessibility, and land use type—were studied in light of their relationships with urban spatial growth. With the analysis of historical data as the basis, a conceptual urban spatial growth model was devised. In this model, slope, accessibility, and land use type together create resistance to urban growth, while accessibility controls the sequence of urban development. The model was tested and evaluated using historical data. It serves as a potential tool for planners to envision and assess future urban growth scenarios and their potential environmental impacts to make informed decisions.
Reliability of Soft Tissue Model Based Implant Surgical Guides; A Methodological Mistake.
Sabour, Siamak; Dastjerdi, Elahe Vahid
2012-08-20
Abstract We were interested to read the paper by Maney P and colleagues published in the July 2012 issue of J Oral Implantol. The authors aimed to assess the reliability of soft tissue model based implant surgical guides reported that the accuracy was evaluated using software. 1 I found the manuscript title of Maney P, et al. incorrect and misleading. Moreover, they reported twenty-two sites (46.81%) were considered accurate (13 of 24 maxillary and 9 of 23 mandibular sites). As the authors point out in their conclusion, Soft tissue models do not always provide sufficient accuracy for implant surgical guide fabrication.Reliability (precision) and validity (accuracy) are two different methodological issues in researches. Sensitivity, specificity, PPV, NPV, likelihood ratio positive (true positive/false negative) and likelihood ratio negative (false positive/ true negative) as well as odds ratio (true results\\false results - preferably more than 50) are among the tests to evaluate the validity (accuracy) of a single test compared to a gold standard.2-4 It is not clear that the reported twenty-two sites (46.81%) which were considered accurate related to which of the above mentioned estimates for validity analysis. Reliability (repeatability or reproducibility) is being assessed by different statistical tests such as Pearson r, least square and paired t.test which all of them are among common mistakes in reliability analysis 5. Briefly, for quantitative variable Intra Class Correlation Coefficient (ICC) and for qualitative variables weighted kappa should be used with caution because kappa has its own limitation too. Regarding reliability or agreement, it is good to know that for computing kappa value, just concordant cells are being considered, whereas discordant cells should also be taking into account in order to reach a correct estimation of agreement (Weighted kappa).2-4 As a take home message, for reliability and validity analysis, appropriate tests should be
A Reliability Model for Ni-BaTiO3-Based (BME) Ceramic Capacitors
Liu, Donhang
2014-01-01
The evaluation of multilayer ceramic capacitors (MLCCs) with base-metal electrodes (BMEs) for potential NASA space project applications requires an in-depth understanding of their reliability. The reliability of an MLCC is defined as the ability of the dielectric material to retain its insulating properties under stated environmental and operational conditions for a specified period of time t. In this presentation, a general mathematic expression of a reliability model for a BME MLCC is developed and discussed. The reliability model consists of three parts: (1) a statistical distribution that describes the individual variation of properties in a test group of samples (Weibull, log normal, normal, etc.), (2) an acceleration function that describes how a capacitors reliability responds to external stresses such as applied voltage and temperature (All units in the test group should follow the same acceleration function if they share the same failure mode, independent of individual units), and (3) the effect and 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 r, and capacitor chip size S. In general, a two-parameter Weibull statistical distribution model is used in the description of a BME capacitors reliability as a function of time. The acceleration function that relates a capacitors reliability to external stresses is dependent on the failure mode. Two failure modes have been identified in BME MLCCs: catastrophic and slow degradation. A catastrophic failure is characterized by a time-accelerating increase in leakage current that is mainly due to existing processing defects (voids, cracks, delamination, etc.), or the extrinsic defects. A slow degradation failure is characterized by a near-linear increase in leakage current against the stress time; this is caused by the electromigration of oxygen vacancies (intrinsic defects). The
Differential model of macroeconomic growth with endogenic cyclicity
Directory of Open Access Journals (Sweden)
Mikhail I. Geraskin
2017-09-01
Full Text Available Objective to elaborate a mathematical model of economic growth taking into account the cyclical nature of macroeconomic dynamics with the model parameters based on the Russian economy statistics. Methods economic and mathematical modeling system analysis regression factor analysis econometric time series analysis. Results the article states that under unstable economic growth in Russia forecasting of strategic prospects of the Russian economy is one of the topical directions of scientific studies. Furthermore construction of predictive models should be based on multiple factors taking into account such basic concepts as the neoKeynesian HarrodDomar model Ramsey ndash Cass ndash Koopmans model S. V. Dubovskiyrsquos concept as well as the neoclassical growth model by R. Solow. They served as the basis for developing a multifactor differential economic growth model which is a modification of the neoclassical growth model by R. Solow taking into account the laborsaving and capitalsaving forms of scientifictechnical progress and the Keynesian concept of investment. The model parameters are determined based on the dynamics of actual GDP employment fixed assets and investments in fixed assets for 19652016 in Russia on the basis of official statistics. The generalized model showed the presence of longwave fluctuations that are not detected during the individual periods modeling. The cyclical nature of macroeconomic dynamics with a period of 54 years was found which corresponds to the parameters of long waves by N. D. Kondratiev. Basing on the model the macroeconomic growth forecast was generated which shows that after 2020 the increase of scientifictechnical progress will be negative. Scientific novelty a model is proposed of the scientifictechnical progress indicator showing the growth rate of the capital productivity ratio to the saving rate a differential model of macroeconomic growth is obtained which endogenously takes cyclicity into account
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
Physics-based process modeling, reliability prediction, and design guidelines for flip-chip devices
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
On New Cautious Structural Reliability Models in the Framework of imprecise Probabilities
DEFF Research Database (Denmark)
Utkin, Lev V.; Kozine, Igor
2010-01-01
models and gen-eralizing conventional ones to imprecise probabili-ties. The theoretical setup employed for this purpose is imprecise statistical reasoning (Walley 1991), whose general framework is provided by upper and lower previsions (expectations). The appeal of this theory is its ability to capture......Uncertainty of parameters in engineering design has been modeled in different frameworks such as inter-val analysis, fuzzy set and possibility theories, ran-dom set theory and imprecise probability theory. The authors of this paper for many years have been de-veloping new imprecise reliability...... both aleatory (stochas-tic) and epistemic uncertainty and the flexibility with which information can be represented. The previous research of the authors related to generalizing structural reliability models to impre-cise statistical measures is summarized in Utkin & Kozine (2002) and Utkin (2004...
Specification and Design of a Fault Recovery Model for the Reliable Multicast Protocol
Montgomery, Todd; Callahan, John R.; Whetten, Brian
1996-01-01
The Reliable Multicast Protocol (RMP) provides a unique, group-based model for distributed programs that need to handle reconfiguration events at the application layer. This model, called membership views, provides an abstraction in which events such as site failures, network partitions, and normal join-leave events are viewed as group reformations. RMP provides access to this model through an application programming interface (API) that notifies an application when a group is reformed as the result of a some event. RMP provides applications with reliable delivery of messages using an underlying IP Multicast media to other group members in a distributed environment even in the case of reformations. A distributed application can use various Quality of Service (QoS) levels provided by RMP to tolerate group reformations. This paper explores the implementation details of the mechanisms in RMP that provide distributed applications with membership view information and fault recovery capabilities.
Reliability and Efficiency of Generalized Rumor Spreading Model on Complex Social Networks
International Nuclear Information System (INIS)
Naimi, Yaghoob; Naimi, Mohammad
2013-01-01
We introduce the generalized rumor spreading model and investigate some properties of this model on different complex social networks. Despite pervious rumor models that both the spreader-spreader (SS) and the spreader-stifler (SR) interactions have the same rate α, we define α (1) and α (2) for SS and SR interactions, respectively. The effect of variation of α (1) and α (2) on the final density of stiflers is investigated. Furthermore, the influence of the topological structure of the network in rumor spreading is studied by analyzing the behavior of several global parameters such as reliability and efficiency. Our results show that while networks with homogeneous connectivity patterns reach a higher reliability, scale-free topologies need a less time to reach a steady state with respect the rumor. (interdisciplinary physics and related areas of science and technology)
Directory of Open Access Journals (Sweden)
Huibing Hao
2015-01-01
Full Text Available Light emitting diode (LED lamp has attracted increasing interest in the field of lighting systems due to its low energy and long lifetime. For different functions (i.e., illumination and color, it may have two or more performance characteristics. When the multiple performance characteristics are dependent, it creates a challenging problem to accurately analyze the system reliability. In this paper, we assume that the system has two performance characteristics, and each performance characteristic is governed by a random effects Gamma process where the random effects can capture the unit to unit differences. The dependency of performance characteristics is described by a Frank copula function. Via the copula function, the reliability assessment model is proposed. Considering the model is so complicated and analytically intractable, the Markov chain Monte Carlo (MCMC method is used to estimate the unknown parameters. A numerical example about actual LED lamps data is given to demonstrate the usefulness and validity of the proposed model and method.
Reliability and Maintainability model (RAM) user and maintenance manual. Part 2
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.
International Nuclear Information System (INIS)
Bouissou, M.; Villatte, N.; Bouhadana, H.; Bannelier, M.
1991-12-01
EDF has been developing for several years an integrated set of knowledge-based and algorithmic tools for automation of reliability assessment of complex (especially sequential) systems. In this environment, the reliability expert has at his disposal all the powerful software tools for qualitative and quantitative processing, besides he gets various means to generate automatically the inputs for these tools, through the acquisition of graphical data. The development of these tools has been based on FIGARO, a specific language, which was built to get an homogeneous system modelling. Various compilers and interpreters get a FIGARO model into conventional models, such as fault-trees, Markov chains, Petri Networks. In this report, we introduce the main basics of FIGARO language, illustrating them with examples
Modeling urban growth in Kigali city Rwanda
African Journals Online (AJOL)
kagoyire
industrialization, land consumption and infrastructural development, have impacted ..... urban growth (reference image) and urban development predicted to the ..... neighboring characteristics (regular water and electricity provision) were not ...
A reliability model of a warm standby configuration with two identical sets of units
International Nuclear Information System (INIS)
Huang, Wei; Loman, James; Song, Thomas
2015-01-01
This article presents a new reliability model and the development of its analytical solution for a warm standby redundant configuration with units that are originally operated in active mode, and then, upon turn-on of originally standby units, are put into warm standby mode. These units can be used later if a standby- turned into active-unit fails. Numerical results of an example configuration are presented and discussed with comparison to other warm standby configurations, and to Monte Carlo simulation results obtained from BlockSim software. Results show that the Monte Carlo simulation model gives virtually identical reliability value when the simulation uses a high number of replications, confirming the developed model. - Highlights: • A new reliability model is developed for a warm standby redundancy with two sets of identical units. • The units subject to state change from active to standby then back to active mode. • A closed form analytical solution is developed with exponential distribution. • To validate the developed model, a Monte Carlo simulation for an exemplary configuration is performed
Reliability modelling and analysis of a multi-state element based on a dynamic Bayesian network
Li, Zhiqiang; Xu, Tingxue; Gu, Junyuan; Dong, Qi; Fu, Linyu
2018-04-01
This paper presents a quantitative reliability modelling and analysis method for multi-state elements based on a combination of the Markov process and a dynamic Bayesian network (DBN), taking perfect repair, imperfect repair and condition-based maintenance (CBM) into consideration. The Markov models of elements without repair and under CBM are established, and an absorbing set is introduced to determine the reliability of the repairable element. According to the state-transition relations between the states determined by the Markov process, a DBN model is built. In addition, its parameters for series and parallel systems, namely, conditional probability tables, can be calculated by referring to the conditional degradation probabilities. Finally, the power of a control unit in a failure model is used as an example. A dynamic fault tree (DFT) is translated into a Bayesian network model, and subsequently extended to a DBN. The results show the state probabilities of an element and the system without repair, with perfect and imperfect repair, and under CBM, with an absorbing set plotted by differential equations and verified. Through referring forward, the reliability value of the control unit is determined in different kinds of modes. Finally, weak nodes are noted in the control unit.
A competing risk model for the reliability of cylinder liners in marine Diesel engines
Energy Technology Data Exchange (ETDEWEB)
Bocchetti, D. [Grimaldi Group, Naples (Italy); Giorgio, M. [Department of Aerospace and Mechanical Engineering, Second University of Naples, Aversa (Italy); Guida, M. [Department of Information Engineering and Electrical Engineering, University of Salerno, Fisciano (Italy); Pulcini, G. [Istituto Motori, National Research Council-CNR, Naples (Italy)], E-mail: g.pulcini@im.cnr.it
2009-08-15
In this paper, a competing risk model is proposed to describe the reliability of the cylinder liners of a marine Diesel engine. Cylinder liners presents two dominant failure modes: wear degradation and thermal cracking. The wear process is described through a stochastic process, whereas the failure time due to the thermal cracking is described by the Weibull distribution. The use of the proposed model allows performing goodness-of-fit test and parameters estimation on the basis of both wear and failure data. Moreover, it enables reliability estimates of the state of the liners to be obtained and the hierarchy of the failure mechanisms to be determined for any given age and wear level of the liner. The model has been applied to a real data set: 33 cylinder liners of Sulzer RTA 58 engines, which equip twin ships of the Grimaldi Group. Estimates of the liner reliability and of other quantities of interest under the competing risk model are obtained, as well as the conditional failure probability and mean residual lifetime, given the survival age and the accumulated wear. Furthermore, the model has been used to estimate the probability that a liner fails due to one of the failure modes when both of these modes act.
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
Growth of cortical neuronal network in vitro: Modeling and analysis
International Nuclear Information System (INIS)
Lai, P.-Y.; Jia, L. C.; Chan, C. K.
2006-01-01
We present a detailed analysis and theoretical growth models to account for recent experimental data on the growth of cortical neuronal networks in vitro [Phys. Rev. Lett. 93, 088101 (2004)]. The experimentally observed synchronized firing frequency of a well-connected neuronal network is shown to be proportional to the mean network connectivity. The growth of the network is consistent with the model of an early enhanced growth of connection, but followed by a retarded growth once the synchronized cluster is formed. Microscopic models with dominant excluded volume interactions are consistent with the observed exponential decay of the mean connection probability as a function of the mean network connectivity. The biological implications of the growth model are also discussed
An Open Modelling Approach for Availability and Reliability of Systems - OpenMARS
Penttinen, Jussi-Pekka; Gutleber, Johannes
2018-01-01
This document introduces and gives specification for OpenMARS, which is an open modelling approach for availability and reliability of systems. It supports the most common risk assessment and operation modelling techniques. Uniquely OpenMARS allows combining and connecting models defined with different techniques. This ensures that a modeller has a high degree of freedom to accurately describe the modelled system without limitations imposed by an individual technique. Here the OpenMARS model definition is specified with a tool independent tabular format, which supports managing models developed in a collaborative fashion. Origin of our research is in Future Circular Collider (FCC) study, where we developed the unique features of our concept to model the availability and luminosity production of particle colliders. We were motivated to describe our approach in detail as we see potential further applications in performance and energy efficiency analyses of large scientific infrastructures or industrial processe...
Modeling the effects of ozone on soybean growth and yield.
Kobayashi, K; Miller, J E; Flagler, R B; Heck, W W
1990-01-01
A simple mechanistic model was developed based on an existing growth model in order to address the mechanisms of the effects of ozone on growth and yield of soybean [Glycine max. (L.) Merr. 'Davis'] and interacting effects of other environmental stresses. The model simulates daily growth of soybean plants using environmental data including shortwave radiation, temperature, precipitation, irrigation and ozone concentration. Leaf growth, dry matter accumulation, water budget, nitrogen input and seed growth linked to senescence and abscission of leaves are described in the model. The effects of ozone are modeled as reduced photosynthate production and accelerated senescence. The model was applied to the open-top chamber experiments in which soybean plants were exposed to ozone under two levels of soil moisture regimes. After calibrating the model to the growth data and seed yield, goodness-of-fit of the model was tested. The model fitted well for top dry weight in the vegetative growth phase and also at maturity. The effect of ozone on seen yield was also described satisfactorily by the model. The simulation showed apparent interaction between the effect of ozone and soil moisture stress on the seed yield. The model revealed that further work is needed concerning the effect of ozone on the senescence process and the consequences of alteration of canopy microclimate by the open-top chambers.
International Nuclear Information System (INIS)
Ramirez-Marquez, Jose Emmanuel; Rocco S, Claudio M.
2009-01-01
This paper introduces an evolutionary optimization approach that can be readily applied to solve stochastic network interdiction problems (SNIP). The network interdiction problem solved considers the minimization of the cost associated with an interdiction strategy such that the maximum flow that can be transmitted between a source node and a sink node for a fixed network design is greater than or equal to a given reliability requirement. Furthermore, the model assumes that the nominal capacity of each network link and the cost associated with their interdiction can change from link to link and that such interdiction has a probability of being successful. This version of the SNIP is for the first time modeled as a capacitated network reliability problem allowing for the implementation of computation and solution techniques previously unavailable. The solution process is based on an evolutionary algorithm that implements: (1) Monte-Carlo simulation, to generate potential network interdiction strategies, (2) capacitated network reliability techniques to analyze strategies' source-sink flow reliability and, (3) an evolutionary optimization technique to define, in probabilistic terms, how likely a link is to appear in the final interdiction strategy. Examples for different sizes of networks are used throughout the paper to illustrate the approach
Modeling the bathtub shape hazard rate function in terms of reliability
International Nuclear Information System (INIS)
Wang, K.S.; Hsu, F.S.; Liu, P.P.
2002-01-01
In this paper, a general form of bathtub shape hazard rate function is proposed in terms of reliability. The degradation of system reliability comes from different failure mechanisms, in particular those related to (1) random failures, (2) cumulative damage, (3) man-machine interference, and (4) adaptation. The first item is referred to the modeling of unpredictable failures in a Poisson process, i.e. it is shown by a constant. Cumulative damage emphasizes the failures owing to strength deterioration and therefore the possibility of system sustaining the normal operation load decreases with time. It depends on the failure probability, 1-R. This representation denotes the memory characteristics of the second failure cause. Man-machine interference may lead to a positive effect in the failure rate due to learning and correction, or negative from the consequence of human inappropriate habit in system operations, etc. It is suggested that this item is correlated to the reliability, R, as well as the failure probability. Adaptation concerns with continuous adjusting between the mating subsystems. When a new system is set on duty, some hidden defects are explored and disappeared eventually. Therefore, the reliability decays combined with decreasing failure rate, which is expressed as a power of reliability. Each of these phenomena brings about the failures independently and is described by an additive term in the hazard rate function h(R), thus the overall failure behavior governed by a number of parameters is found by fitting the evidence data. The proposed model is meaningful in capturing the physical phenomena occurring during the system lifetime and provides for simpler and more effective parameter fitting than the usually adopted 'bathtub' procedures. Five examples of different type of failure mechanisms are taken in the validation of the proposed model. Satisfactory results are found from the comparisons
Directory of Open Access Journals (Sweden)
Ahmad Alferidi
2017-02-01
Full Text Available The contribution of solar power in electric power systems has been increasing rapidly due to its environmentally friendly nature. Photovoltaic (PV systems contain solar cell panels, power electronic converters, high power switching and often transformers. These components collectively play an important role in shaping the reliability of PV systems. Moreover, the power output of PV systems is variable, so it cannot be controlled as easily as conventional generation due to the unpredictable nature of weather conditions. Therefore, solar power has a different influence on generating system reliability compared to conventional power sources. Recently, different PV system designs have been constructed to maximize the output power of PV systems. These different designs are commonly adopted based on the scale of a PV system. Large-scale grid-connected PV systems are generally connected in a centralized or a string structure. Central and string PV schemes are different in terms of connecting the inverter to PV arrays. Micro-inverter systems are recognized as a third PV system topology. It is therefore important to evaluate the reliability contribution of PV systems under these topologies. This work utilizes a probabilistic technique to develop a power output model for a PV generation system. A reliability model is then developed for a PV integrated power system in order to assess the reliability and energy contribution of the solar system to meet overall system demand. The developed model is applied to a small isolated power unit to evaluate system adequacy and capacity level of a PV system considering the three topologies.
Tax Evasion in a Model of Endogenous Growth
Been-Lon Chen
2003-01-01
This paper integrates tax evasion into a standard AK growth model with public capital. In the model, the government optimizes the tax rate, while individuals optimize tax evasion. It studies tax rate, tax evasion and economic growth, and compares them with otherwise identical economies except those without tax evasion. It inquires into the effects of three government policies on tax rate, tax evasion, and economic growth. It finds that an increase in both unit cost of tax evasion and punishme...
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.
Stochastic growth logistic model with aftereffect for batch fermentation process
Rosli, Norhayati; Ayoubi, Tawfiqullah; Bahar, Arifah; Rahman, Haliza Abdul; Salleh, Madihah Md
2014-06-01
In this paper, the stochastic growth logistic model with aftereffect for the cell growth of C. acetobutylicum P262 and Luedeking-Piret equations for solvent production in batch fermentation system is introduced. The parameters values of the mathematical models are estimated via Levenberg-Marquardt optimization method of non-linear least squares. We apply Milstein scheme for solving the stochastic models numerically. The effciency of mathematical models is measured by comparing the simulated result and the experimental data of the microbial growth and solvent production in batch system. Low values of Root Mean-Square Error (RMSE) of stochastic models with aftereffect indicate good fits.
Stochastic growth logistic model with aftereffect for batch fermentation process
International Nuclear Information System (INIS)
Rosli, Norhayati; Ayoubi, Tawfiqullah; Bahar, Arifah; Rahman, Haliza Abdul; Salleh, Madihah Md
2014-01-01
In this paper, the stochastic growth logistic model with aftereffect for the cell growth of C. acetobutylicum P262 and Luedeking-Piret equations for solvent production in batch fermentation system is introduced. The parameters values of the mathematical models are estimated via Levenberg-Marquardt optimization method of non-linear least squares. We apply Milstein scheme for solving the stochastic models numerically. The effciency of mathematical models is measured by comparing the simulated result and the experimental data of the microbial growth and solvent production in batch system. Low values of Root Mean-Square Error (RMSE) of stochastic models with aftereffect indicate good fits
Stochastic growth logistic model with aftereffect for batch fermentation process
Energy Technology Data Exchange (ETDEWEB)
Rosli, Norhayati; Ayoubi, Tawfiqullah [Faculty of Industrial Sciences and Technology, Universiti Malaysia Pahang, Lebuhraya Tun Razak, 26300 Gambang, Pahang (Malaysia); Bahar, Arifah; Rahman, Haliza Abdul [Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor (Malaysia); Salleh, Madihah Md [Department of Biotechnology Industry, Faculty of Biosciences and Bioengineering, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor (Malaysia)
2014-06-19
In this paper, the stochastic growth logistic model with aftereffect for the cell growth of C. acetobutylicum P262 and Luedeking-Piret equations for solvent production in batch fermentation system is introduced. The parameters values of the mathematical models are estimated via Levenberg-Marquardt optimization method of non-linear least squares. We apply Milstein scheme for solving the stochastic models numerically. The effciency of mathematical models is measured by comparing the simulated result and the experimental data of the microbial growth and solvent production in batch system. Low values of Root Mean-Square Error (RMSE) of stochastic models with aftereffect indicate good fits.
Testing R&D-Based Endogenous Growth Models
DEFF Research Database (Denmark)
Kruse-Andersen, Peter Kjær
2017-01-01
R&D-based growth models are tested using US data for the period 1953-2014. A general growth model is developed which nests the model varieties of interest. The model implies a cointegrating relationship between multifactor productivity, research intensity, and employment. This relationship...... is estimated using cointegrated VAR models. The results provide evidence against the widely used fully endogenous variety and in favor of the semi-endogenous variety. Forecasts based on the empirical estimates suggest that the slowdown in US productivity growth will continue. Particularly, the annual long...
International Nuclear Information System (INIS)
Lin, Yanhui
2016-01-01
Components of nuclear safety systems are in general highly reliable, which leads to a difficulty in modeling their degradation and failure behaviors due to the limited amount of data available. Besides, the complexity of such modeling task is increased by the fact that these systems are often subject to multiple competing degradation processes and that these can be dependent under certain circumstances, and influenced by a number of external factors (e.g. temperature, stress, mechanical shocks, etc.). In this complicated problem setting, this PhD work aims to develop a holistic framework of models and computational methods for the reliability-based analysis and maintenance optimization of nuclear safety systems taking into account the available knowledge on the systems, degradation and failure behaviors, their dependencies, the external influencing factors and the associated uncertainties.The original scientific contributions of the work are: (1) For single components, we integrate random shocks into multi-state physics models for component reliability analysis, considering general dependencies between the degradation and two types of random shocks. (2) For multi-component systems (with a limited number of components):(a) a piecewise-deterministic Markov process modeling framework is developed to treat degradation dependency in a system whose degradation processes are modeled by physics-based models and multi-state models; (b) epistemic uncertainty due to incomplete or imprecise knowledge is considered and a finite-volume scheme is extended to assess the (fuzzy) system reliability; (c) the mean absolute deviation importance measures are extended for components with multiple dependent competing degradation processes and subject to maintenance; (d) the optimal maintenance policy considering epistemic uncertainty and degradation dependency is derived by combining finite-volume scheme, differential evolution and non-dominated sorting differential evolution; (e) the
Kinetic models of cell growth, substrate utilization and bio ...
African Journals Online (AJOL)
STORAGESEVER
2008-05-02
May 2, 2008 ... Aspergillus fumigatus. A simple model was proposed using the Logistic Equation for the growth, ... costs and also involved in less sophisticated fermentation ... apply and they are accurately proved that the model can express ...
Kezirian, Michael T.; Phoenix, S. Leigh; Eldridge, Jeffrey I.
2009-01-01
Composite Overwrapped Pressure Vessels (COPVs) are frequently used for storing pressurized gases aboard spacecraft and aircraft when weight saving is desirable compared to all-metal versions. Failure mechanisms in fibrous COPVs and variability in lifetime can be very different from their metallic counterparts; in the former, catastrophic stress-rupture can occur with virtually no warning, whereas in latter, a leak before burst design philosophy can be implemented. Qualification and certification typically requires only one burst test on a production sample (possibly after several pressure cycles) and the vessel need only meet a design burst strength (the maximum operating pressure divided by a knockdown factor). Typically there is no requirement to assess variability in burst strength or lifetime, much less determine production and materials processing parameters important to control of such variability. Characterizing such variability and its source is crucial to models for calculating required reliability over a given lifetime (e.g. R = 0.9999 for 15 years). In this paper we present a case study of how lack of control of certain process parameters in COPV manufacturing can result in variations among vessels and between production runs that can greatly increase uncertainty and reduce reliability. The vessels considered are 40-inch ( NASA Glenn Research center, Cleveland, OH, 44135 29,500 in3 ) spherical COPVs with a 0.74 in. thick Kevlar49/epoxy overwrap and with a titanium liner of which 34 were originally produced. Two burst tests were eventually performed that unexpectedly differed by almost 5%, and were 10% lower than anticipated from burst tests on 26-inch sister vessels similar in every detail. A major observation from measurements made during proof testing (autofrettage) of the 40-inch vessels was that permanent volume growth from liner yielding varied by a factor of more than two (150 in3 to 360 in3 ), which suggests large differences in the residual
Nonlinear Growth Models in M"plus" and SAS
Grimm, Kevin J.; Ram, Nilam
2009-01-01
Nonlinear growth curves or growth curves that follow a specified nonlinear function in time enable researchers to model complex developmental patterns with parameters that are easily interpretable. In this article we describe how a variety of sigmoid curves can be fit using the M"plus" structural modeling program and the nonlinear…
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...
Modeling Energy & Reliability of a CNT based WSN on an HPC Setup
Directory of Open Access Journals (Sweden)
Rohit Pathak
2010-07-01
Full Text Available We have analyzed the effect of innovations in Nanotechnology on Wireless Sensor Networks (WSN and have modeled Carbon Nanotube (CNT based sensor nodes from a device prospective. A WSN model has been programmed in Simulink-MATLAB and a library has been developed. Integration of CNT in WSN for various modules such as sensors, microprocessors, batteries etc has been shown. Also average energy consumption for the system has been formulated and its reliability has been shown holistically. A proposition has been put forward on the changes needed in existing sensor node structure to improve its efficiency and to facilitate as well as enhance the assimilation of CNT based devices in a WSN. Finally we have commented on the challenges that exist in this technology and described the important factors that need to be considered for calculating reliability. This research will help in practical implementation of CNT based devices and analysis of their key effects on the WSN environment. The work has been executed on Simulink and Distributive Computing toolbox of MATLAB. The proposal has been compared to the recent developments and past experimental results reported in this field. This attempt to derieve the energy consumption and reliability implications will help in development of real devices using CNT which is a major hurdle in bringing the success from lab to commercial market. Recent research in CNT has been used to model an energy efficient model which will also lead to the development CAD tools. Library for Reliability and Energy consumption includes analysis of various parts of a WSN system which is being constructed from CNT. Nano routing in a CNT system is also implemented with its dependencies. Finally the computations were executed on a HPC setup and the model showed remarkable speedup.
Growth rate in the dynamical dark energy models
International Nuclear Information System (INIS)
Avsajanishvili, Olga; Arkhipova, Natalia A.; Samushia, Lado; Kahniashvili, Tina
2014-01-01
Dark energy models with a slowly rolling cosmological scalar field provide a popular alternative to the standard, time-independent cosmological constant model. We study the simultaneous evolution of background expansion and growth in the scalar field model with the Ratra-Peebles self-interaction potential. We use recent measurements of the linear growth rate and the baryon acoustic oscillation peak positions to constrain the model parameter α that describes the steepness of the scalar field potential. (orig.)
Growth rate in the dynamical dark energy models.
Avsajanishvili, Olga; Arkhipova, Natalia A; Samushia, Lado; Kahniashvili, Tina
Dark energy models with a slowly rolling cosmological scalar field provide a popular alternative to the standard, time-independent cosmological constant model. We study the simultaneous evolution of background expansion and growth in the scalar field model with the Ratra-Peebles self-interaction potential. We use recent measurements of the linear growth rate and the baryon acoustic oscillation peak positions to constrain the model parameter [Formula: see text] that describes the steepness of the scalar field potential.
Risk evaluations of aging phenomena: the linear aging reliability model and its extensions
International Nuclear Information System (INIS)
Vesely, W.E.
1987-01-01
A model for component failure rates due to aging mechanisms has been developed from basic phenomenological considerations. In the treatment, the occurrences of deterioration are modeled as following a Poisson process. The severity of damage is allowed to have any distribution, however the damage is assumed to accumulate independently. Finally, the failure rate is modeled as being proportional to the accumulated damage. Using this treatment, the linear aging failure rate model is obtained. The applicability of the linear aging model to various mechanisms is discussed. The model can be extended to cover nonlinear and dependent aging phenomena. The implementability of the linear aging model is demonstrated by applying it to the aging data collected in NRC's Nuclear Plant Aging Research (NPAR) Program. The applications show that aging as observed in collected data have significant effects on the component failure probability and component reliability when aging is not effectively detected and controlled by testing and maintenance
Risk evaluations of aging phenomena: The linear aging reliability model and its extensions
International Nuclear Information System (INIS)
Vesely, W.E.
1986-01-01
A model for component failure rates due to aging mechanisms has been developed from basic phenomenological considerations. In the treatment, the occurrences of deterioration are modeled as following a Poisson process. The severity of damage is allowed to have any distribution, however the damage is assumed to accumulate independently. Finally, the failure rate is modeled as being proportional to the accumulated damage. Using this treatment, the linear aging failure rate model is obtained. The applicability of the linear aging model to various mechanisms is discussed. The model can be extended to cover nonlinear and dependent aging phenomena. The implementability of the linear aging model is demonstrated by applying it of the aging data collected in NRC's Nuclear Plant Aging Research (NPAR) Program. The applications show that aging as observed in collected data have significant effects on the component failure probability and component reliability when aging is not effectively detected and controlled by testing and maintenance
Development of thermal hydraulic models for the reliable regulatory auditing code
Energy Technology Data Exchange (ETDEWEB)
Chung, B. D.; Song, C. H.; Lee, Y. J.; Kwon, T. S. [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)
2003-04-15
The objective of this project is to develop thermal hydraulic models for use in improving the reliability of the regulatory auditing codes. The current year fall under the first step of the 3 year project, and the main researches were focused on identifying the candidate thermal hydraulic models for improvement and to develop prototypical model development. During the current year, the verification calculations submitted for the APR 1400 design certification have been reviewed, the experimental data from the MIDAS DVI experiment facility in KAERI have been analyzed and evaluated, candidate thermal hydraulic models for improvement have been identified, prototypical models for the improved thermal hydraulic models have been developed, items for experiment in connection with the model development have been identified, and preliminary design of the experiment has been carried out.
Development of thermal hydraulic models for the reliable regulatory auditing code
International Nuclear Information System (INIS)
Chung, B. D.; Song, C. H.; Lee, Y. J.; Kwon, T. S.
2003-04-01
The objective of this project is to develop thermal hydraulic models for use in improving the reliability of the regulatory auditing codes. The current year fall under the first step of the 3 year project, and the main researches were focused on identifying the candidate thermal hydraulic models for improvement and to develop prototypical model development. During the current year, the verification calculations submitted for the APR 1400 design certification have been reviewed, the experimental data from the MIDAS DVI experiment facility in KAERI have been analyzed and evaluated, candidate thermal hydraulic models for improvement have been identified, prototypical models for the improved thermal hydraulic models have been developed, items for experiment in connection with the model development have been identified, and preliminary design of the experiment has been carried out
Liu, Sheng
2011-01-01
Although there is increasing need for modeling and simulation in the IC package design phase, most assembly processes and various reliability tests are still based on the time consuming ""test and try out"" method to obtain the best solution. Modeling and simulation can easily ensure virtual Design of Experiments (DoE) to achieve the optimal solution. This has greatly reduced the cost and production time, especially for new product development. Using modeling and simulation will become increasingly necessary for future advances in 3D package development. In this book, Liu and Liu allow people
Ebeling, Charles E.
1996-01-01
This report documents the procedures for utilizing and maintaining the Reliability & Maintainability Model (RAM) developed by the University of Dayton for the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC). The purpose of the grant is to provide support to NASA in establishing operational and support parameters and costs of proposed space systems. As part of this research objective, the model described here was developed. This Manual updates and supersedes the 1995 RAM User and Maintenance Manual. Changes and enhancements from the 1995 version of the model are primarily a result of the addition of more recent aircraft and shuttle R&M data.
Bar-El Dadon, Shimrit; Shahar, Ron; Katalan, Vered; Monsonego-Ornan, Efrat; Reifen, Ram
2011-09-01
Skeletal abnormalities are one of the hallmarks of growth delay during gestation. The aim of this study was to determine changes induced by leptin in skeletal growth and development in a rat model of intrauterine growth retardation (IUGR) and to elucidate the possible underlying mechanisms. Intrauterine growth retardation was induced prepartum and the effects of leptin to mothers prenatally or to offspring postnatally were studied. Radii were harvested and tested mechanically and structurally. Tibias were evaluated for growth-plate morphometry. On day 40 postpartum, total bone length and mineral density and tibial growth-plate width and numbers of cells within its zones of offspring treated with leptin were significantly greater than in the control group. Postnatal leptin administration in an IUGR model improves the structural properties and elongation rate of bone. These findings could pave the way to preventing some phenotypic presentations of IUGR. Copyright © 2011 Elsevier Inc. All rights reserved.
Directory of Open Access Journals (Sweden)
Fateme Rezaei
2017-08-01
Full Text Available Probability of structure failure which has been designed by "deterministic methods" can be more than the one which has been designed in similar situation using probabilistic methods and models considering "uncertainties". The main purpose of this research was to evaluate the seismic reliability of steel moment resisting frames rehabilitated with concentric braces by probabilistic models. To do so, three-story and nine-story steel moment resisting frames were designed based on resistant criteria of Iranian code and then they were rehabilitated based on controlling drift limitations by concentric braces. Probability of frames failure was evaluated by probabilistic models of magnitude, location of earthquake, ground shaking intensity in the area of the structure, probabilistic model of building response (based on maximum lateral roof displacement and probabilistic methods. These frames were analyzed under subcrustal source by sampling probabilistic method "Risk Tools" (RT. Comparing the exceedance probability of building response curves (or selected points on it of the three-story and nine-story model frames (before and after rehabilitation, seismic response of rehabilitated frames, was reduced and their reliability was improved. Also the main effective variables in reducing the probability of frames failure were determined using sensitivity analysis by FORM probabilistic method. The most effective variables reducing the probability of frames failure are in the magnitude model, ground shaking intensity model error and magnitude model error
International Nuclear Information System (INIS)
Golovanov, M.N.; Zyuzin, N.N.; Levin, G.L.; Chesnokov, A.N.
1987-01-01
An approach for estimation of reliability factors of complex reserved systems at early stages of development using the method of imitating simulation is considered. Different types of models, their merits and lacks are given. Features of in-core monitoring systems and advosability of graph model and graph theory element application for estimating reliability of such systems are shown. The results of investigation of the reliability factors of the reactor monitoring, control and core local protection subsystem are shown
Markov modeling and reliability analysis of urea synthesis system of a fertilizer plant
Aggarwal, Anil Kr.; Kumar, Sanjeev; Singh, Vikram; Garg, Tarun Kr.
2015-12-01
This paper deals with the Markov modeling and reliability analysis of urea synthesis system of a fertilizer plant. This system was modeled using Markov birth-death process with the assumption that the failure and repair rates of each subsystem follow exponential distribution. The first-order Chapman-Kolmogorov differential equations are developed with the use of mnemonic rule and these equations are solved with Runga-Kutta fourth-order method. The long-run availability, reliability and mean time between failures are computed for various choices of failure and repair rates of subsystems of the system. The findings of the paper are discussed with the plant personnel to adopt and practice suitable maintenance policies/strategies to enhance the performance of the urea synthesis system of the fertilizer plant.
Graphene growth process modeling: a physical-statistical approach
Wu, Jian; Huang, Qiang
2014-09-01
As a zero-band semiconductor, graphene is an attractive material for a wide variety of applications such as optoelectronics. Among various techniques developed for graphene synthesis, chemical vapor deposition on copper foils shows high potential for producing few-layer and large-area graphene. Since fabrication of high-quality graphene sheets requires the understanding of growth mechanisms, and methods of characterization and control of grain size of graphene flakes, analytical modeling of graphene growth process is therefore essential for controlled fabrication. The graphene growth process starts with randomly nucleated islands that gradually develop into complex shapes, grow in size, and eventually connect together to cover the copper foil. To model this complex process, we develop a physical-statistical approach under the assumption of self-similarity during graphene growth. The growth kinetics is uncovered by separating island shapes from area growth rate. We propose to characterize the area growth velocity using a confined exponential model, which not only has clear physical explanation, but also fits the real data well. For the shape modeling, we develop a parametric shape model which can be well explained by the angular-dependent growth rate. This work can provide useful information for the control and optimization of graphene growth process on Cu foil.
International Nuclear Information System (INIS)
Rajpal, P.S.; Shishodia, K.S.; Sekhon, G.S.
2006-01-01
The paper explores the application of artificial neural networks to model the behaviour of a complex, repairable system. A composite measure of reliability, availability and maintainability parameters has been proposed for measuring the system performance. The artificial neural network has been trained using past data of a helicopter transportation facility. It is used to simulate behaviour of the facility under various constraints. The insights obtained from results of simulation are useful in formulating strategies for optimal operation of the system
Basu, Asit P; Basu, Sujit K
1998-01-01
This volume presents recent results in reliability theory by leading experts in the world. It will prove valuable for researchers, and users of reliability theory. It consists of refereed invited papers on a broad spectrum of topics in reliability. The subjects covered include Bayesian reliability, Bayesian reliability modeling, confounding in a series system, DF tests, Edgeworth approximation to reliability, estimation under random censoring, fault tree reduction for reliability, inference about changes in hazard rates, information theory and reliability, mixture experiment, mixture of Weibul
International Nuclear Information System (INIS)
Vasconcelos, Vanderley de; Soares, Wellington Antonio; Marques, Raíssa Oliveira; Silva Júnior, Silvério Ferreira da; Raso, Amanda Laureano
2017-01-01
Non-destructive inspection (NDI) is one of the key elements in ensuring quality of engineering systems and their safe use. NDI is a very complex task, during which the inspectors have to rely on their sensory, perceptual, cognitive, and motor skills. It requires high vigilance once it is often carried out on large components, over a long period of time, and in hostile environments and restriction of workplace. A successful NDI requires careful planning, choice of appropriate NDI methods and inspection procedures, as well as qualified and trained inspection personnel. A failure of NDI to detect critical defects in safety-related components of nuclear power plants, for instance, may lead to catastrophic consequences for workers, public and environment. Therefore, ensuring that NDI methods are reliable and capable of detecting all critical defects is of utmost importance. Despite increased use of automation in NDI, human inspectors, and thus human factors, still play an important role in NDI reliability. Human reliability is the probability of humans conducting specific tasks with satisfactory performance. Many techniques are suitable for modeling and analyzing human reliability in NDI of nuclear power plant components. Among these can be highlighted Failure Modes and Effects Analysis (FMEA) and THERP (Technique for Human Error Rate Prediction). The application of these techniques is illustrated in an example of qualitative and quantitative studies to improve typical NDI of pipe segments of a core cooling system of a nuclear power plant, through acting on human factors issues. (author)
Energy Technology Data Exchange (ETDEWEB)
Vasconcelos, Vanderley de; Soares, Wellington Antonio; Marques, Raíssa Oliveira; Silva Júnior, Silvério Ferreira da; Raso, Amanda Laureano, E-mail: vasconv@cdtn.br, E-mail: soaresw@cdtn.br, E-mail: raissaomarques@gmail.com, E-mail: silvasf@cdtn.br, E-mail: amandaraso@hotmail.com [Centro de Desenvolvimento da Tecnologia Nuclear (CDTN/CNEN-MG), Belo Horizonte, MG (Brazil)
2017-07-01
Non-destructive inspection (NDI) is one of the key elements in ensuring quality of engineering systems and their safe use. NDI is a very complex task, during which the inspectors have to rely on their sensory, perceptual, cognitive, and motor skills. It requires high vigilance once it is often carried out on large components, over a long period of time, and in hostile environments and restriction of workplace. A successful NDI requires careful planning, choice of appropriate NDI methods and inspection procedures, as well as qualified and trained inspection personnel. A failure of NDI to detect critical defects in safety-related components of nuclear power plants, for instance, may lead to catastrophic consequences for workers, public and environment. Therefore, ensuring that NDI methods are reliable and capable of detecting all critical defects is of utmost importance. Despite increased use of automation in NDI, human inspectors, and thus human factors, still play an important role in NDI reliability. Human reliability is the probability of humans conducting specific tasks with satisfactory performance. Many techniques are suitable for modeling and analyzing human reliability in NDI of nuclear power plant components. Among these can be highlighted Failure Modes and Effects Analysis (FMEA) and THERP (Technique for Human Error Rate Prediction). The application of these techniques is illustrated in an example of qualitative and quantitative studies to improve typical NDI of pipe segments of a core cooling system of a nuclear power plant, through acting on human factors issues. (author)
Energy Technology Data Exchange (ETDEWEB)
Duarte, Juliana P.; Leite, Victor C.; Melo, P.F. Frutuoso e, E-mail: julianapduarte@poli.ufrj.br, E-mail: victor.coppo.leite@poli.ufrj.br, E-mail: frutuoso@nuclear.ufrj.br [Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, RJ (Brazil)
2013-07-01
Bayesian networks have become a very handy tool for solving problems in various application areas. This paper discusses the use of Bayesian networks to treat dependent events in reliability engineering typically modeled by Markovian models. Dependent events play an important role as, for example, when treating load-sharing systems, bridge systems, common-cause failures, and switching systems (those for which a standby component is activated after the main one fails by means of a switching mechanism). Repair plays an important role in all these cases (as, for example, the number of repairmen). All Bayesian network calculations are performed by means of the Netica™ software, of Norsys Software Corporation, and Fortran 90 to evaluate them over time. The discussion considers the development of time-dependent reliability figures of merit, which are easily obtained, through Markovian models, but not through Bayesian networks, because these latter need probability figures as input and not failure and repair rates. Bayesian networks produced results in very good agreement with those of Markov models and pivotal decomposition. Static and discrete time (DTBN) Bayesian networks were used in order to check their capabilities of modeling specific situations, like switching failures in cold-standby systems. The DTBN was more flexible to modeling systems where the time of occurrence of an event is important, for example, standby failure and repair. However, the static network model showed as good results as DTBN by a much more simplified approach. (author)
International Nuclear Information System (INIS)
Duarte, Juliana P.; Leite, Victor C.; Melo, P.F. Frutuoso e
2013-01-01
Bayesian networks have become a very handy tool for solving problems in various application areas. This paper discusses the use of Bayesian networks to treat dependent events in reliability engineering typically modeled by Markovian models. Dependent events play an important role as, for example, when treating load-sharing systems, bridge systems, common-cause failures, and switching systems (those for which a standby component is activated after the main one fails by means of a switching mechanism). Repair plays an important role in all these cases (as, for example, the number of repairmen). All Bayesian network calculations are performed by means of the Netica™ software, of Norsys Software Corporation, and Fortran 90 to evaluate them over time. The discussion considers the development of time-dependent reliability figures of merit, which are easily obtained, through Markovian models, but not through Bayesian networks, because these latter need probability figures as input and not failure and repair rates. Bayesian networks produced results in very good agreement with those of Markov models and pivotal decomposition. Static and discrete time (DTBN) Bayesian networks were used in order to check their capabilities of modeling specific situations, like switching failures in cold-standby systems. The DTBN was more flexible to modeling systems where the time of occurrence of an event is important, for example, standby failure and repair. However, the static network model showed as good results as DTBN by a much more simplified approach. (author)
Automatic creation of Markov models for reliability assessment of safety instrumented systems
International Nuclear Information System (INIS)
Guo Haitao; Yang Xianhui
2008-01-01
After the release of new international functional safety standards like IEC 61508, people care more for the safety and availability of safety instrumented systems. Markov analysis is a powerful and flexible technique to assess the reliability measurements of safety instrumented systems, but it is fallible and time-consuming to create Markov models manually. This paper presents a new technique to automatically create Markov models for reliability assessment of safety instrumented systems. Many safety related factors, such as failure modes, self-diagnostic, restorations, common cause and voting, are included in Markov models. A framework is generated first based on voting, failure modes and self-diagnostic. Then, repairs and common-cause failures are incorporated into the framework to build a complete Markov model. Eventual simplification of Markov models can be done by state merging. Examples given in this paper show how explosively the size of Markov model increases as the system becomes a little more complicated as well as the advancement of automatic creation of Markov models
Mechanical model for filament buckling and growth by phase ordering.
Rey, Alejandro D; Abukhdeir, Nasser M
2008-02-05
A mechanical model of open filament shape and growth driven by phase ordering is formulated. For a given phase-ordering driving force, the model output is the filament shape evolution and the filament end-point kinematics. The linearized model for the slope of the filament is the Cahn-Hilliard model of spinodal decomposition, where the buckling corresponds to concentration fluctuations. Two modes are predicted: (i) sequential growth and buckling and (ii) simultaneous buckling and growth. The relation among the maximum buckling rate, filament tension, and matrix viscosity is given. These results contribute to ongoing work in smectic A filament buckling.
Modeling and optimization of algae growth
Thornton, Anthony Richard; Weinhart, Thomas; Bokhove, Onno; Zhang, Bowen; van der Sar, Dick M.; Kumar, Kundan; Pisarenco, Maxim; Rudnaya, Maria; Savcenco, Valeriu; Rademacher, Jens; Zijlstra, Julia; Szabelska, Alicja; Zyprych, Joanna; van der Schans, Martin; Timperio, Vincent; Veerman, Frits
2010-01-01
The wastewater from greenhouses has a high amount of mineral contamination and an environmentally-friendly method of removal is to use algae to clean this runoff water. The algae consume the minerals as part of their growth process. In addition to cleaning the water, the created algal bio-mass has a
International Nuclear Information System (INIS)
Mok, Chin Man; Doughty, Christine; Zhang, Keni; Pruess, Karsten; Kiureghian, Armen; Zhang, Miao; Kaback, Dawn
2010-01-01
A new computer code, CALRELTOUGH, which uses reliability methods to incorporate parameter sensitivity and uncertainty analysis into subsurface flow and transport models, was developed by Geomatrix Consultants, Inc. in collaboration with Lawrence Berkeley National Laboratory and University of California at Berkeley. The CALREL reliability code was developed at the University of California at Berkely for geotechnical applications and the TOUGH family of codes was developed at Lawrence Berkeley National Laboratory for subsurface flow and tranport applications. The integration of the two codes provides provides a new approach to deal with uncertainties in flow and transport modeling of the subsurface, such as those uncertainties associated with hydrogeology parameters, boundary conditions, and initial conditions of subsurface flow and transport using data from site characterization and monitoring for conditioning. The new code enables computation of the reliability of a system and the components that make up the system, instead of calculating the complete probability distributions of model predictions at all locations at all times. The new CALRELTOUGH code has tremendous potential to advance subsurface understanding for a variety of applications including subsurface energy storage, nuclear waste disposal, carbon sequestration, extraction of natural resources, and environmental remediation. The new code was tested on a carbon sequestration problem as part of the Phase I project. Phase iI was not awarded.
Reliability modeling and analysis for a novel design of modular converter system of wind turbines
International Nuclear Information System (INIS)
Zhang, Cai Wen; Zhang, Tieling; Chen, Nan; Jin, Tongdan
2013-01-01
Converters play a vital role in wind turbines. The concept of modularity is gaining in popularity in converter design for modern wind turbines in order to achieve high reliability as well as cost-effectiveness. In this study, we are concerned with a novel topology of modular converter invented by Hjort, Modular converter system with interchangeable converter modules. World Intellectual Property Organization, Pub. No. WO29027520 A2; 5 March 2009, in this architecture, the converter comprises a number of identical and interchangeable basic modules. Each module can operate in either AC/DC or DC/AC mode, depending on whether it functions on the generator or the grid side. Moreover, each module can be reconfigured from one side to the other, depending on the system’s operational requirements. This is a shining example of full-modular design. This paper aims to model and analyze the reliability of such a modular converter. A Markov modeling approach is applied to the system reliability analysis. In particular, six feasible converter system models based on Hjort’s architecture are investigated. Through numerical analyses and comparison, we provide insights and guidance for converter designers in their decision-making.
An Assessment of the VHTR Safety Distance Using the Reliability Physics Model
International Nuclear Information System (INIS)
Lee, Joeun; Kim, Jintae; Jae, Moosung
2015-01-01
In Korea planning the production of hydrogen using high temperature from nuclear power is in progress. To produce hydrogen from nuclear plants, supplying temperature above 800 .deg. C is required. Therefore, Very High Temperature Reactor (VHTR) which is able to provide about 950 .deg. C is suitable. In situation of high temperature and corrosion where hydrogen might be released easily, hydrogen production facility using VHTR has a danger of explosion. Moreover explosion not only has a bad influence upon facility itself but also on VHTR. Those explosions result in unsafe situation that cause serious damage. However, In terms of thermal-hydraulics view, long distance makes low efficiency Thus, in this study, a methodology for the safety assessment of safety distance between the hydrogen production facilities and the VHTR is developed with reliability physics model. Based on the standard safety criteria which is a value of 1 x 10 -6 , the safety distance between the hydrogen production facilities and the VHTR using reliability physics model are calculated to be a value of 60m - 100m. In the future, assessment for characteristic of VHTR, the capacity to resist pressure from outside hydrogen explosion and the overpressure for the large amount of detonation volume in detail is expected to identify more precise safety distance using this reliability physics model
Testing comparison models of DASS-12 and its reliability among adolescents in Malaysia.
Osman, Zubaidah Jamil; Mukhtar, Firdaus; Hashim, Hairul Anuar; Abdul Latiff, Latiffah; Mohd Sidik, Sherina; Awang, Hamidin; Ibrahim, Normala; Abdul Rahman, Hejar; Ismail, Siti Irma Fadhilah; Ibrahim, Faisal; Tajik, Esra; Othman, Norlijah
2014-10-01
The 21-item Depression, Anxiety and Stress Scale (DASS-21) is frequently used in non-clinical research to measure mental health factors among adults. However, previous studies have concluded that the 21 items are not stable for utilization among the adolescent population. Thus, the aims of this study are to examine the structure of the factors and to report on the reliability of the refined version of the DASS that consists of 12 items. A total of 2850 students (aged 13 to 17 years old) from three major ethnic in Malaysia completed the DASS-21. The study was conducted at 10 randomly selected secondary schools in the northern state of Peninsular Malaysia. The study population comprised secondary school students (Forms 1, 2 and 4) from the selected schools. Based on the results of the EFA stage, 12 items were included in a final CFA to test the fit of the model. Using maximum likelihood procedures to estimate the model, the selected fit indices indicated a close model fit (χ(2)=132.94, df=57, p=.000; CFI=.96; RMR=.02; RMSEA=.04). Moreover, significant loadings of all the unstandardized regression weights implied an acceptable convergent validity. Besides the convergent validity of the item, a discriminant validity of the subscales was also evident from the moderate latent factor inter-correlations, which ranged from .62 to .75. The subscale reliability was further estimated using Cronbach's alpha and the adequate reliability of the subscales was obtained (Total=76; Depression=.68; Anxiety=.53; Stress=.52). The new version of the 12-item DASS for adolescents in Malaysia (DASS-12) is reliable and has a stable factor structure, and thus it is a useful instrument for distinguishing between depression, anxiety and stress. Copyright © 2014 Elsevier Inc. All rights reserved.
Stochastic Individual-Based Modeling of Bacterial Growth and Division Using Flow Cytometry
Directory of Open Access Journals (Sweden)
Míriam R. García
2018-01-01
Full Text Available A realistic description of the variability in bacterial growth and division is critical to produce reliable predictions of safety risks along the food chain. Individual-based modeling of bacteria provides the theoretical framework to deal with this variability, but it requires information about the individual behavior of bacteria inside populations. In this work, we overcome this problem by estimating the individual behavior of bacteria from population statistics obtained with flow cytometry. For this objective, a stochastic individual-based modeling framework is defined based on standard assumptions during division and exponential growth. The unknown single-cell parameters required for running the individual-based modeling simulations, such as cell size growth rate, are estimated from the flow cytometry data. Instead of using directly the individual-based model, we make use of a modified Fokker-Plank equation. This only equation simulates the population statistics in function of the unknown single-cell parameters. We test the validity of the approach by modeling the growth and division of Pediococcus acidilactici within the exponential phase. Estimations reveal the statistics of cell growth and division using only data from flow cytometry at a given time. From the relationship between the mother and daughter volumes, we also predict that P. acidilactici divide into two successive parallel planes.
International Nuclear Information System (INIS)
Stern, R.E.; Song, J.; Work, D.B.
2017-01-01
The two-terminal reliability problem in system reliability analysis is known to be computationally intractable for large infrastructure graphs. Monte Carlo techniques can estimate the probability of a disconnection between two points in a network by selecting a representative sample of network component failure realizations and determining the source-terminal connectivity of each realization. To reduce the runtime required for the Monte Carlo approximation, this article proposes an approximate framework in which the connectivity check of each sample is estimated using a machine-learning-based classifier. The framework is implemented using both a support vector machine (SVM) and a logistic regression based surrogate model. Numerical experiments are performed on the California gas distribution network using the epicenter and magnitude of the 1989 Loma Prieta earthquake as well as randomly-generated earthquakes. It is shown that the SVM and logistic regression surrogate models are able to predict network connectivity with accuracies of 99% for both methods, and are 1–2 orders of magnitude faster than using a Monte Carlo method with an exact connectivity check. - Highlights: • Surrogate models of network connectivity are developed by machine-learning algorithms. • Developed surrogate models can reduce the runtime required for Monte Carlo simulations. • Support vector machine and logistic regressions are employed to develop surrogate models. • Numerical example of California gas distribution network demonstrate the proposed approach. • The developed models have accuracies 99%, and are 1–2 orders of magnitude faster than MCS.
Optimal Patent Life in a Variety-Expansion Growth Model
Lin, Hwan C.
2013-01-01
This paper presents more channels through which the optimal patent life is determined in a R&D-based endogenous growth model that permits growth of new varieties of consumer goods over time. Its modeling features include an endogenous hazard rate facing incumbent monopolists, the prevalence of research congestion, and the aggregate welfare importance of product differentiation. As a result, a patent’s effective life is endogenized and less than its legal life. The model is calibrated to a glo...
Modeling of Craniofacial Anatomy, Variation, and Growth
DEFF Research Database (Denmark)
Thorup, Signe Strann
The topic of this thesis is automatic analysis of craniofacial images with respect to changes due to growth and surgery, inter-subject variation and intracranial volume estimation. The methods proposed contribute to the knowledge about specific craniofacial anomalies, as well as provide a tool...... for detailed analyses for clinical and research purposes. Most of the applications in this thesis rely on non-rigid image registration by the means of warping one image into the coordinate system of another image. This warping results in a deformation field that describes the anatomical correspondence between......, thus creating a personalized atlas. The knowledge built into the atlas is e.g. location of anatomical regions and landmarks of importance to surgery planning and evaluation or population studies. With these correspondences, various analyses could be carried out e.g. quantification of growth, inter...
Directory of Open Access Journals (Sweden)
Adriana Studeničová
2012-02-01
Full Text Available As the strains of S. aureus growing during fermentation of raw milk cheeses are exposed to the competitive growth of lactic acid bacteria and their metabolites, in this work, we characterized the growth of the strain S. aureus 2064 isolated from such environment against of water activity values and incubation temperature. Water activity of the tested media was adjusted by NaCl in the range from 0 % to 20.72 % and the experiments were carried out at 37 °C. It was found that the strain under study showed growth until NaCl concentration of 19.95 % in PCA broth. The complete growth cessation of S. aureus 2064 was observed at NaCl concentration higher than 20.72 %. The effect of water activity on the S. aureus 2064 lag-phase duration was described by the modified Davey model with discrepancy of 24.6 %. The growth rate dependence on water activity was described more precisely and reliably by Gibson model that provided the following validation indices: bias factor 0.999 and discrepancy factor 9.6 %. Based on the results we can conclude that secondary models used in this work were suitable to predict growth of S. aureus 2064, originally the ewes´cheese isolate.doi:10.5219/179
Energy Technology Data Exchange (ETDEWEB)
McNiff, B.; Guo, Y.; Keller, J.; Sethuraman, L.
2014-12-01
Bearing failures in the high speed output stage of the gearbox are plaguing the wind turbine industry. Accordingly, the National Renewable Energy Laboratory (NREL) Gearbox Reliability Collaborative (GRC) has performed an experimental and theoretical investigation of loads within these bearings. The purpose of this paper is to describe the instrumentation, calibrations, data post-processing and initial results from this testing and modeling effort. Measured HSS torque, bending, and bearing loads are related to model predictions. Of additional interest is examining if the shaft measurements can be simply related to bearing load measurements, eliminating the need for invasive modifications of the bearing races for such instrumentation.
Final Report: System Reliability Model for Solid-State Lighting (SSL) Luminaires
Energy Technology Data Exchange (ETDEWEB)
Davis, J. Lynn [RTI International, Research Triangle Park, NC (United States)
2017-05-31
The primary objectives of this project was to develop and validate reliability models and accelerated stress testing (AST) methodologies for predicting the lifetime of integrated SSL luminaires. This study examined the likely failure modes for SSL luminaires including abrupt failure, excessive lumen depreciation, unacceptable color shifts, and increased power consumption. Data on the relative distribution of these failure modes were acquired through extensive accelerated stress tests and combined with industry data and other source of information on LED lighting. This data was compiled and utilized to build models of the aging behavior of key luminaire optical and electrical components.
Modelling the Growth of Swine Flu
Thomson, Ian
2010-01-01
The spread of swine flu has been a cause of great concern globally. With no vaccine developed as yet, (at time of writing in July 2009) and given the fact that modern-day humans can travel speedily across the world, there are fears that this disease may spread out of control. The worst-case scenario would be one of unfettered exponential growth.…
Development of thermal hydraulic models for the reliable regulatory auditing code
Energy Technology Data Exchange (ETDEWEB)
Chung, B. D.; Song, C. H.; Lee, Y. J.; Kwon, T. S.; Lee, S. W. [Korea Automic Energy Research Institute, Taejon (Korea, Republic of)
2004-02-15
The objective of this project is to develop thermal hydraulic models for use in improving the reliability of the regulatory auditing codes. The current year fall under the second step of the 3 year project, and the main researches were focused on the development of downcorner boiling model. During the current year, the bubble stream model of downcorner has been developed and installed in he auditing code. The model sensitivity analysis has been performed for APR1400 LBLOCA scenario using the modified code. The preliminary calculation has been performed for the experimental test facility using FLUENT and MARS code. The facility for air bubble experiment has been installed. The thermal hydraulic phenomena for VHTR and super critical reactor have been identified for the future application and model development.
Villacampa, Pilar; Menger, Katja E; Abelleira, Laura; Ribeiro, Joana; Duran, Yanai; Smith, Alexander J; Ali, Robin R; Luhmann, Ulrich F; Bainbridge, James W B
2017-01-01
Retinal ischemia and pathological angiogenesis cause severe impairment of sight. Oxygen-induced retinopathy (OIR) in young mice is widely used as a model to investigate the underlying pathological mechanisms and develop therapeutic interventions. We compared directly the conventional OIR model (exposure to 75% O2 from postnatal day (P) 7 to P12) with an alternative, accelerated version (85% O2 from P8 to P11). We found that accelerated OIR induces similar pre-retinal neovascularization but greater retinal vascular regression that recovers more rapidly. The extent of retinal gliosis is similar but neuroretinal function, as measured by electroretinography, is better maintained in the accelerated model. We found no systemic or maternal morbidity in either model. Accelerated OIR offers a safe, reliable and more rapid alternative model in which pre-retinal neovascularization is similar but retinal vascular regression is greater.
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)
On Latent Growth Models for Composites and Their Constituents.
Hancock, Gregory R; Mao, Xiulin; Kher, Hemant
2013-09-01
Over the last decade and a half, latent growth modeling has become an extremely popular and versatile technique for evaluating longitudinal change and its determinants. Most common among the models applied are those for a single measured variable over time. This model has been extended in a variety of ways, most relevant for the current work being the multidomain and the second-order latent growth models. Whereas the former allows for growth function characteristics to be modeled for multiple outcomes simultaneously, with the degree of growth characteristics' relations assessed within the model (e.g., cross-domain slope factor correlations), the latter models growth in latent outcomes, each of which has effect indicators repeated over time. But what if one has an outcome that is believed to be formative relative to its indicator variables rather than latent? In this case, where the outcome is a composite of multiple constituents, modeling change over time is less straightforward. This article provides analytical and applied details for simultaneously modeling growth in composites and their constituent elements, including a real data example using a general computer self-efficacy questionnaire.
Applied model for the growth of the daytime mixed layer
DEFF Research Database (Denmark)
Batchvarova, E.; Gryning, Sven-Erik
1991-01-01
numerically. When the mixed layer is shallow or the atmosphere nearly neutrally stratified, the growth is controlled mainly by mechanical turbulence. When the layer is deep, its growth is controlled mainly by convective turbulence. The model is applied on a data set of the evolution of the height of the mixed...... layer in the morning hours, when both mechanical and convective turbulence contribute to the growth process. Realistic mixed-layer developments are obtained....
Non-rigid image registration using bone growth model
DEFF Research Database (Denmark)
Bro-Nielsen, Morten; Gramkow, Claus; Kreiborg, Sven
1997-01-01
Non-rigid registration has traditionally used physical models like elasticity and fluids. These models are very seldom valid models of the difference between the registered images. This paper presents a non-rigid registration algorithm, which uses a model of bone growth as a model of the change...... between time sequence images of the human mandible. By being able to register the images, this paper at the same time contributes to the validation of the growth model, which is based on the currently available medical theories and knowledge...
Rating the raters in a mixed model: An approach to deciphering the rater reliability
Shang, Junfeng; Wang, Yougui
2013-05-01
Rating the raters has attracted extensive attention in recent years. Ratings are quite complex in that the subjective assessment and a number of criteria are involved in a rating system. Whenever the human judgment is a part of ratings, the inconsistency of ratings is the source of variance in scores, and it is therefore quite natural for people to verify the trustworthiness of ratings. Accordingly, estimation of the rater reliability will be of great interest and an appealing issue. To facilitate the evaluation of the rater reliability in a rating system, we propose a mixed model where the scores of the ratees offered by a rater are described with the fixed effects determined by the ability of the ratees and the random effects produced by the disagreement of the raters. In such a mixed model, for the rater random effects, we derive its posterior distribution for the prediction of random effects. To quantitatively make a decision in revealing the unreliable raters, the predictive influence function (PIF) serves as a criterion which compares the posterior distributions of random effects between the full data and rater-deleted data sets. The benchmark for this criterion is also discussed. This proposed methodology of deciphering the rater reliability is investigated in the multiple simulated and two real data sets.
The reliability of the Hendrich Fall Risk Model in a geriatric hospital.
Heinze, Cornelia; Halfens, Ruud; Dassen, Theo
2008-12-01
Aims and objectives. The purpose of this study was to test the interrater reliability of the Hendrich Fall Risk Model, an instrument to identify patients in a hospital setting with a high risk of falling. Background. Falls are a serious problem in older patients. Valid and reliable fall risk assessment tools are required to identify high-risk patients and to take adequate preventive measures. Methods. Seventy older patients were independently and simultaneously assessed by six pairs of raters made up of nursing staff members. Consensus estimates were calculated using simple percentage agreement and consistency estimates using Spearman's rho and intra class coefficient. Results. Percentage agreement ranged from 0.70 to 0.92 between the six pairs of raters. Spearman's rho coefficients were between 0.54 and 0.80 and the intra class coefficients were between 0.46 and 0.92. Conclusions. Whereas some pairs of raters obtained considerable interobserver agreement and internal consistency, the others did not. Therefore, it is concluded that the Hendrich Fall Risk Model is not a reliable instrument. The use of more unambiguous operationalized items is preferred. Relevance to clinical practice. In practice, well operationalized fall risk assessment tools are necessary. Observer agreement should always be investigated after introducing a standardized measurement tool. © 2008 The Authors. Journal compilation © 2008 Blackwell Publishing Ltd.
Phase-field model of eutectic growth
International Nuclear Information System (INIS)
Karma, A.
1994-01-01
A phase-field model which describes the solidification of a binary eutectic alloy with a simple symmetric phase diagram is introduced and the sharp-interface limit of this model is explored both analytically and numerically
Skill and reliability of climate model ensembles at the Last Glacial Maximum and mid-Holocene
Directory of Open Access Journals (Sweden)
J. C. Hargreaves
2013-03-01
Full Text Available Paleoclimate simulations provide us with an opportunity to critically confront and evaluate the performance of climate models in simulating the response of the climate system to changes in radiative forcing and other boundary conditions. Hargreaves et al. (2011 analysed the reliability of the Paleoclimate Modelling Intercomparison Project, PMIP2 model ensemble with respect to the MARGO sea surface temperature data synthesis (MARGO Project Members, 2009 for the Last Glacial Maximum (LGM, 21 ka BP. Here we extend that work to include a new comprehensive collection of land surface data (Bartlein et al., 2011, and introduce a novel analysis of the predictive skill of the models. We include output from the PMIP3 experiments, from the two models for which suitable data are currently available. We also perform the same analyses for the PMIP2 mid-Holocene (6 ka BP ensembles and available proxy data sets. Our results are predominantly positive for the LGM, suggesting that as well as the global mean change, the models can reproduce the observed pattern of change on the broadest scales, such as the overall land–sea contrast and polar amplification, although the more detailed sub-continental scale patterns of change remains elusive. In contrast, our results for the mid-Holocene are substantially negative, with the models failing to reproduce the observed changes with any degree of skill. One cause of this problem could be that the globally- and annually-averaged forcing anomaly is very weak at the mid-Holocene, and so the results are dominated by the more localised regional patterns in the parts of globe for which data are available. The root cause of the model-data mismatch at these scales is unclear. If the proxy calibration is itself reliable, then representativity error in the data-model comparison, and missing climate feedbacks in the models are other possible sources of error.
Balanced growth path solutions of a Boltzmann mean field game model for knowledge growth
Burger, Martin
2016-11-18
In this paper we study balanced growth path solutions of a Boltzmann mean field game model proposed by Lucas and Moll [15] to model knowledge growth in an economy. Agents can either increase their knowledge level by exchanging ideas in learning events or by producing goods with the knowledge they already have. The existence of balanced growth path solutions implies exponential growth of the overall production in time. We prove existence of balanced growth path solutions if the initial distribution of individuals with respect to their knowledge level satisfies a Pareto-tail condition. Furthermore we give first insights into the existence of such solutions if in addition to production and knowledge exchange the knowledge level evolves by geometric Brownian motion.
Reliability modeling of a hard real-time system using the path-space approach
International Nuclear Information System (INIS)
Kim, Hagbae
2000-01-01
A hard real-time system, such as a fly-by-wire system, fails catastrophically (e.g. losing stability) if its control inputs are not updated by its digital controller computer within a certain timing constraint called the hard deadline. To assess and validate those systems' reliabilities by using a semi-Markov model that explicitly contains the deadline information, we propose a path-space approach deriving the upper and lower bounds of the probability of system failure. These bounds are derived by using only simple parameters, and they are especially suitable for highly reliable systems which should recover quickly. Analytical bounds are derived for both exponential and Wobble failure distributions encountered commonly, which have proven effective through numerical examples, while considering three repair strategies: repair-as-good-as-new, repair-as-good-as-old, and repair-better-than-old
Modeling Parameters of Reliability of Technological Processes of Hydrocarbon Pipeline Transportation
Directory of Open Access Journals (Sweden)
Shalay Viktor
2016-01-01
Full Text Available On the basis of methods of system analysis and parametric reliability theory, the mathematical modeling of processes of oil and gas equipment operation in reliability monitoring was conducted according to dispatching data. To check the quality of empiric distribution coordination , an algorithm and mathematical methods of analysis are worked out in the on-line mode in a changing operating conditions. An analysis of physical cause-and-effect relations mechanism between the key factors and changing parameters of technical systems of oil and gas facilities is made, the basic types of technical distribution parameters are defined. Evaluation of the adequacy the analyzed parameters of the type of distribution is provided by using a criterion A.Kolmogorov, as the most universal, accurate and adequate to verify the distribution of continuous processes of complex multiple-technical systems. Methods of calculation are provided for supervising by independent bodies for risk assessment and safety facilities.
A smart growth evaluation model based on data envelopment analysis
Zhang, Xiaokun; Guan, Yongyi
2018-04-01
With the rapid spread of urbanization, smart growth (SG) has attracted plenty of attention from all over the world. In this paper, by the establishment of index system for smart growth, data envelopment analysis (DEA) model was suggested to evaluate the SG level of the current growth situation in cities. In order to further improve the information of both radial direction and non-radial detection, we introduced the non-Archimedean infinitesimal to form C2GS2 control model. Finally, we evaluated the SG level in Canberra and identified a series of problems, which can verify the applicability of the model and provide us more improvement information.
Studying historical occupational careers with multilevel growth models
Directory of Open Access Journals (Sweden)
Wiebke Schulz
2010-10-01
Full Text Available In this article we propose to study occupational careers with historical data by using multilevel growth models. Historical career data are often characterized by a lack of information on the timing of occupational changes and by different numbers of observations of occupations per individual. Growth models can handle these specificities, whereas standard methods, such as event history analyses can't. We illustrate the use of growth models by studying career success of men and women, using data from the Historical Sample of the Netherlands. The results show that the method is applicable to male careers, but causes trouble when analyzing female careers.
An auto-focusing heuristic model to increase the reliability of a scientific mission
International Nuclear Information System (INIS)
Gualdesi, Lavinio
2006-01-01
Researchers invest a lot of time and effort on the design and development of components used in a scientific mission. To capitalize on this investment and on the operational experience of the researchers, it is useful to adopt a quantitative data base to monitor the history and usage of the components. This work describes a model to monitor the reliability level of components. The model is very flexible and allows users to compose systems using the same components in different configurations as required by each mission. This tool provides availability and reliability figures for the configuration requested, derived from historical data of the components' previous performance. The system is based on preliminary checklists to establish standard operating procedures (SOP) for all components life phases. When an infringement to the SOP occurs, a quantitative ranking is provided in order to quantify the risk associated with this deviation. The final agreement between field data and expected performance of the component makes the model converge onto a heuristic monitoring system. The model automatically focuses on points of failure at the detailed component element level, calculates risks, provides alerts when a demonstrated risk to safety is encountered, and advises when there is a mismatch between component performance and mission requirements. This model also helps the mission to focus resources on critical tasks where they are most needed
International Nuclear Information System (INIS)
Hall, P.L.; Strutt, J.E.
2003-01-01
In reliability engineering, component failures are generally classified in one of three ways: (1) early life failures; (2) failures having random onset times; and (3) late life or 'wear out' failures. When the time-distribution of failures of a population of components is analysed in terms of a Weibull distribution, these failure types may be associated with shape parameters β having values 1 respectively. Early life failures are frequently attributed to poor design (e.g. poor materials selection) or problems associated with manufacturing or assembly processes. We describe a methodology for the implementation of physics-of-failure models of component lifetimes in the presence of parameter and model uncertainties. This treats uncertain parameters as random variables described by some appropriate statistical distribution, which may be sampled using Monte Carlo methods. The number of simulations required depends upon the desired accuracy of the predicted lifetime. Provided that the number of sampled variables is relatively small, an accuracy of 1-2% can be obtained using typically 1000 simulations. The resulting collection of times-to-failure are then sorted into ascending order and fitted to a Weibull distribution to obtain a shape factor β and a characteristic life-time η. Examples are given of the results obtained using three different models: (1) the Eyring-Peck (EP) model for corrosion of printed circuit boards; (2) a power-law corrosion growth (PCG) model which represents the progressive deterioration of oil and gas pipelines; and (3) a random shock-loading model of mechanical failure. It is shown that for any specific model the values of the Weibull shape parameters obtained may be strongly dependent on the degree of uncertainty of the underlying input parameters. Both the EP and PCG models can yield a wide range of values of β, from β>1, characteristic of wear-out behaviour, to β<1, characteristic of early-life failure, depending on the degree of
Davis, W C; Wyatt, C R; Hamilton, M J; Goff, W L
1992-01-01
Fluorescence flow cytometry was employed to assess the potential of a vital dye, hydroethidine, for use in the detection and monitoring of the viability of hemoparasites in infected erythrocytes, using Babesia bovis as a model parasite. The studies demonstrated that hydroethidine is taken up by B. bovis and metabolically converted to the DNA binding fluorochrome, ethidium. Following uptake of the dye, erythrocytes containing viable parasites were readily distinguished and quantitated. Timed studies with the parasiticidal drug, Ganaseg, showed that it is possible to use the fluorochrome assay to monitor the effects of the drug on the rate of replication and viability of B. bovis in culture. The assay provides a rapid method for evaluation of the in vitro effect of drugs on hemoparasites and for analysis of the effect of various components of the immune response, such as lymphokines, monocyte products, antibodies, and effector cells (T, NK, LAK, ADCC) on the growth and viability of intraerythrocytic parasites.
Directory of Open Access Journals (Sweden)
W. C. Davis
1992-01-01
Full Text Available Fluorescence flow cytometry was employed to assess the potential of a vital dye, hydroethiedine, for use in the detection and monitoring of the viability of hemoparasites in infected erythrocytes, using Babesia bovis as a model parasite. The studies demonstrated that hydroethidine is taken up by B. bovis and metabolically converted to the DNA binding fluorochrone, ethidium. Following uptake of the dye, erythrocytes contamine viable parasites were readily distinguished and quantitated. Timed studies with the parasiticidal drug, Ganaseg, showed that it is possible to use the fluorochrome assay to monitor the effects of the drug on the rate of replication and viability of B. bovis in culture. The assay provides a rapid method for evaluation of the in vitro effect of drugs on hemoparasites and for analysis of the effect of various components of the immune response, such as lymphokines, monocyte products, antibodies, and effector cells (T, NK, LAK, ADCC on the growth and viability of intraerythrocytic parasites.
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
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)
Modeling growth from weaning to maturity in beef cattle breeds
To better understand growth trajectory and maturity differences between beef breeds, three models – Brody, spline, and quadratic – were fit to cow growth data, and resulting parameter estimates were evaluated for 3 breed categories – British, continental, and Brahman-influenced. The data were weight...
Modeling growth of Clostridium perfringens in pea soup during cooling
Jong, de A.E.I.; Beumer, R.R.; Zwietering, M.H.
2005-01-01
Clostridium perfringens is a pathogen that mainly causes food poisoning outbreaks when large quantities of food are prepared. Therefore, a model was developed to predict the effect of different cooling procedures on the growth of this pathogen during cooling of food: Dutch pea soup. First, a growth
Evaluating the Predictive Value of Growth Prediction Models
Murphy, Daniel L.; Gaertner, Matthew N.
2014-01-01
This study evaluates four growth prediction models--projection, student growth percentile, trajectory, and transition table--commonly used to forecast (and give schools credit for) middle school students' future proficiency. Analyses focused on vertically scaled summative mathematics assessments, and two performance standards conditions (high…
Modelling growth curves of Nigerian indigenous normal feather ...
African Journals Online (AJOL)
This study was conducted to predict the growth curve parameters using Bayesian Gompertz and logistic models and also to compare the two growth function in describing the body weight changes across age in Nigerian indigenous normal feather chicken. Each chick was wing-tagged at day old and body weights were ...
A Schumpeterian Model of Entrepreneurship, Innovation, and Regional Economic Growth
Batabyal, A.; Nijkamp, P.
2012-01-01
The authors provide the first theoretical analysis of a one-sector, discrete-time, Schumpeterian model of growth in a regional economy in which consumers are risk neutral, there is no population growth, monopolistic entrepreneurs produce intermediate goods, and a single consumption good is produced
A grain boundary sliding model for cavitation, crack growth and ...
African Journals Online (AJOL)
A model is presented for cavity growth, crack propagation and fracture resulting from grain boundary sliding (GBS) during high temperature creep deformation. The theory of cavity growth by GBS was based on energy balance criteria on the assumption that the matrix is sufficiently plastic to accommodate misfit strains ...
Reliability of a Novel Model for Drug Release from 2D HPMC-Matrices
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Rumiana Blagoeva
2010-04-01
Full Text Available A novel model of drug release from 2D-HPMC matrices is considered. Detailed mathematical description of matrix swelling and the effect of the initial drug loading are introduced. A numerical approach to solution of the posed nonlinear 2D problem is used on the basis of finite element domain approximation and time difference method. The reliability of the model is investigated in two steps: numerical evaluation of the water uptake parameters; evaluation of drug release parameters under available experimental data. The proposed numerical procedure for fitting the model is validated performing different numerical examples of drug release in two cases (with and without taking into account initial drug loading. The goodness of fit evaluated by the coefficient of determination is presented to be very good with few exceptions. The obtained results show better model fitting when accounting the effect of initial drug loading (especially for larger values.
Modeling the reliability and maintenance costs of wind turbines using Weibull analysis
Energy Technology Data Exchange (ETDEWEB)
Vachon, W.A. [W.A. Vachon & Associates, Inc., Manchester, MA (United States)
1996-12-31
A general description is provided of the basic mathematics and use of Weibull statistical models for modeling component failures and maintenance costs as a function of time. The applicability of the model to wind turbine components and subsystems is discussed with illustrative examples of typical component reliabilities drawn from actual field experiences. Example results indicate the dominant role of key subsystems based on a combination of their failure frequency and repair/replacement costs. The value of the model is discussed as a means of defining (1) maintenance practices, (2) areas in which to focus product improvements, (3) spare parts inventory, and (4) long-term trends in maintenance costs as an important element in project cash flow projections used by developers, investors, and lenders. 6 refs., 8 figs., 3 tabs.
Reliable and efficient solution of genome-scale models of Metabolism and macromolecular Expression
DEFF Research Database (Denmark)
Ma, Ding; Yang, Laurence; Fleming, Ronan M. T.
2017-01-01
orders of magnitude. Data values also have greatly varying magnitudes. Standard double-precision solvers may return inaccurate solutions or report that no solution exists. Exact simplex solvers based on rational arithmetic require a near-optimal warm start to be practical on large problems (current ME......Constraint-Based Reconstruction and Analysis (COBRA) is currently the only methodology that permits integrated modeling of Metabolism and macromolecular Expression (ME) at genome-scale. Linear optimization computes steady-state flux solutions to ME models, but flux values are spread over many...... models have 70,000 constraints and variables and will grow larger). We have developed a quadrupleprecision version of our linear and nonlinear optimizer MINOS, and a solution procedure (DQQ) involving Double and Quad MINOS that achieves reliability and efficiency for ME models and other challenging...
Using Evidence Credibility Decay Model for dependence assessment in human reliability analysis
International Nuclear Information System (INIS)
Guo, Xingfeng; Zhou, Yanhui; Qian, Jin; Deng, Yong
2017-01-01
Highlights: • A new computational model is proposed for dependence assessment in HRA. • We combined three factors of “CT”, “TR” and “SP” within Dempster–Shafer theory. • The BBA of “SP” is reconstructed by discounting rate based on the ECDM. • Simulation experiments are illustrated to show the efficiency of the proposed method. - Abstract: Dependence assessment among human errors plays an important role in human reliability analysis. When dependence between two sequent tasks exists in human reliability analysis, if the preceding task fails, the failure probability of the following task is higher than success. Typically, three major factors are considered: “Closeness in Time” (CT), “Task Relatedness” (TR) and “Similarity of Performers” (SP). Assume TR is not changed, both SP and CT influence the degree of dependence level and SP is discounted by the time as the result of combine two factors in this paper. In this paper, a new computational model is proposed based on the Dempster–Shafer Evidence Theory (DSET) and Evidence Credibility Decay Model (ECDM) to assess the dependence between tasks in human reliability analysis. First, the influenced factors among human tasks are identified and the basic belief assignments (BBAs) of each factor are constructed based on expert evaluation. Then, the BBA of SP is discounted as the result of combining two factors and reconstructed by using the ECDM, the factors are integrated into a fused BBA. Finally, the dependence level is calculated based on fused BBA. Experimental results demonstrate that the proposed model not only quantitatively describe the fact that the input factors influence the dependence level, but also exactly show how the dependence level regular changes with different situations of input factors.
A size-structured model of bacterial growth and reproduction.
Ellermeyer, S F; Pilyugin, S S
2012-01-01
We consider a size-structured bacterial population model in which the rate of cell growth is both size- and time-dependent and the average per capita reproduction rate is specified as a model parameter. It is shown that the model admits classical solutions. The population-level and distribution-level behaviours of these solutions are then determined in terms of the model parameters. The distribution-level behaviour is found to be different from that found in similar models of bacterial population dynamics. Rather than convergence to a stable size distribution, we find that size distributions repeat in cycles. This phenomenon is observed in similar models only under special assumptions on the functional form of the size-dependent growth rate factor. Our main results are illustrated with examples, and we also provide an introductory study of the bacterial growth in a chemostat within the framework of our model.
International Nuclear Information System (INIS)
Lee, Chi Woo; Kim, Sun Jin; Lee, Seung Woo; Jeong, Sang Yeong
1993-08-01
This book start what is reliability? such as origin of reliability problems, definition of reliability and reliability and use of reliability. It also deals with probability and calculation of reliability, reliability function and failure rate, probability distribution of reliability, assumption of MTBF, process of probability distribution, down time, maintainability and availability, break down maintenance and preventive maintenance design of reliability, design of reliability for prediction and statistics, reliability test, reliability data and design and management of reliability.
NONLINEAR MODELS FOR DESCRIPTION OF CACAO FRUIT GROWTH WITH ASSUMPTION VIOLATIONS
Directory of Open Access Journals (Sweden)
JOEL AUGUSTO MUNIZ
2017-01-01
Full Text Available Cacao (Theobroma cacao L. is an important fruit in the Brazilian economy, which is mainly cultivated in the southern State of Bahia. The optimal stage for harvesting is a major factor for fruit quality and the knowledge on its growth curves can help, especially in identifying the ideal maturation stage for harvesting. Nonlinear regression models have been widely used for description of growth curves. However, several studies in this subject do not consider the residual analysis, the existence of a possible dependence between longitudinal observations, or the sample variance heterogeneity, compromising the modeling quality. The objective of this work was to compare the fit of nonlinear regression models, considering residual analysis and assumption violations, in the description of the cacao (clone Sial-105 fruit growth. The data evaluated were extracted from Brito and Silva (1983, who conducted the experiment in the Cacao Research Center, Ilheus, State of Bahia. The variables fruit length, diameter and volume as a function of fruit age were studied. The use of weighting and incorporation of residual dependencies was efficient, since the modeling became more consistent, improving the model fit. Considering the first-order autoregressive structure, when needed, leads to significant reduction in the residual standard deviation, making the estimates more reliable. The Logistic model was the most efficient for the description of the cacao fruit growth.
Algorithms for Bayesian network modeling and reliability assessment of infrastructure systems
International Nuclear Information System (INIS)
Tien, Iris; Der Kiureghian, Armen
2016-01-01
Novel algorithms are developed to enable the modeling of large, complex infrastructure systems as Bayesian networks (BNs). These include a compression algorithm that significantly reduces the memory storage required to construct the BN model, and an updating algorithm that performs inference on compressed matrices. These algorithms address one of the major obstacles to widespread use of BNs for system reliability assessment, namely the exponentially increasing amount of information that needs to be stored as the number of components in the system increases. The proposed compression and inference algorithms are described and applied to example systems to investigate their performance compared to that of existing algorithms. Orders of magnitude savings in memory storage requirement are demonstrated using the new algorithms, enabling BN modeling and reliability analysis of larger infrastructure systems. - Highlights: • Novel algorithms developed for Bayesian network modeling of infrastructure systems. • Algorithm presented to compress information in conditional probability tables. • Updating algorithm presented to perform inference on compressed matrices. • Algorithms applied to example systems to investigate their performance. • Orders of magnitude savings in memory storage requirement demonstrated.
Ighravwe, D. E.; Oke, S. A.; Adebiyi, K. A.
2016-06-01
The growing interest in technicians' workloads research is probably associated with the recent surge in competition. This was prompted by unprecedented technological development that triggers changes in customer tastes and preferences for industrial goods. In a quest for business improvement, this worldwide intense competition in industries has stimulated theories and practical frameworks that seek to optimise performance in workplaces. In line with this drive, the present paper proposes an optimisation model which considers technicians' reliability that complements factory information obtained. The information used emerged from technicians' productivity and earned-values using the concept of multi-objective modelling approach. Since technicians are expected to carry out routine and stochastic maintenance work, we consider these workloads as constraints. The influence of training, fatigue and experiential knowledge of technicians on workload management was considered. These workloads were combined with maintenance policy in optimising reliability, productivity and earned-values using the goal programming approach. Practical datasets were utilised in studying the applicability of the proposed model in practice. It was observed that our model was able to generate information that practicing maintenance engineers can apply in making more informed decisions on technicians' management.
The cognitive environment simulation as a tool for modeling human performance and reliability
International Nuclear Information System (INIS)
Woods, D.D.; Pople, H. Jr.; Roth, E.M.
1990-01-01
The US Nuclear Regulatory Commission is sponsoring a research program to develop improved methods to model the cognitive behavior of nuclear power plant (NPP) personnel. Under this program, a tool for simulating how people form intentions to act in NPP emergency situations was developed using artificial intelligence (AI) techniques. This tool is called Cognitive Environment Simulation (CES). The Cognitive Reliability Assessment Technique (or CREATE) was also developed to specify how CBS can be used to enhance the measurement of the human contribution to risk in probabilistic risk assessment (PRA) studies. The next step in the research program was to evaluate the modeling tool and the method for using the tool for Human Reliability Analysis (HRA) in PRAs. Three evaluation activities were conducted. First, a panel of highly distinguished experts in cognitive modeling, AI, PRA and HRA provided a technical review of the simulation development work. Second, based on panel recommendations, CES was exercised on a family of steam generator tube rupture incidents where empirical data on operator performance already existed. Third, a workshop with HRA practitioners was held to analyze a worked example of the CREATE method to evaluate the role of CES/CREATE in HRA. The results of all three evaluations indicate that CES/CREATE represents a promising approach to modeling operator intention formation during emergency operations
Selection, calibration, and validation of models of tumor growth.
Lima, E A B F; Oden, J T; Hormuth, D A; Yankeelov, T E; Almeida, R C
2016-11-01
This paper presents general approaches for addressing some of the most important issues in predictive computational oncology concerned with developing classes of predictive models of tumor growth. First, the process of developing mathematical models of vascular tumors evolving in the complex, heterogeneous, macroenvironment of living tissue; second, the selection of the most plausible models among these classes, given relevant observational data; third, the statistical calibration and validation of models in these classes, and finally, the prediction of key Quantities of Interest (QOIs) relevant to patient survival and the effect of various therapies. The most challenging aspects of this endeavor is that all of these issues often involve confounding uncertainties: in observational data, in model parameters, in model selection, and in the features targeted in the prediction. Our approach can be referred to as "model agnostic" in that no single model is advocated; rather, a general approach that explores powerful mixture-theory representations of tissue behavior while accounting for a range of relevant biological factors is presented, which leads to many potentially predictive models. Then representative classes are identified which provide a starting point for the implementation of OPAL, the Occam Plausibility Algorithm (OPAL) which enables the modeler to select the most plausible models (for given data) and to determine if the model is a valid tool for predicting tumor growth and morphology ( in vivo ). All of these approaches account for uncertainties in the model, the observational data, the model parameters, and the target QOI. We demonstrate these processes by comparing a list of models for tumor growth, including reaction-diffusion models, phase-fields models, and models with and without mechanical deformation effects, for glioma growth measured in murine experiments. Examples are provided that exhibit quite acceptable predictions of tumor growth in laboratory
Gompertzian stochastic model with delay effect to cervical cancer growth
International Nuclear Information System (INIS)
Mazlan, Mazma Syahidatul Ayuni binti; Rosli, Norhayati binti; Bahar, Arifah
2015-01-01
In this paper, a Gompertzian stochastic model with time delay is introduced to describe the cervical cancer growth. The parameters values of the mathematical model are estimated via Levenberg-Marquardt optimization method of non-linear least squares. We apply Milstein scheme for solving the stochastic model numerically. The efficiency of mathematical model is measured by comparing the simulated result and the clinical data of cervical cancer growth. Low values of Mean-Square Error (MSE) of Gompertzian stochastic model with delay effect indicate good fits
Gompertzian stochastic model with delay effect to cervical cancer growth
Energy Technology Data Exchange (ETDEWEB)
Mazlan, Mazma Syahidatul Ayuni binti; Rosli, Norhayati binti [Faculty of Industrial Sciences and Technology, Universiti Malaysia Pahang, Lebuhraya Tun Razak, 26300 Gambang, Pahang (Malaysia); Bahar, Arifah [Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor and UTM Centre for Industrial and Applied Mathematics (UTM-CIAM), Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor (Malaysia)
2015-02-03
In this paper, a Gompertzian stochastic model with time delay is introduced to describe the cervical cancer growth. The parameters values of the mathematical model are estimated via Levenberg-Marquardt optimization method of non-linear least squares. We apply Milstein scheme for solving the stochastic model numerically. The efficiency of mathematical model is measured by comparing the simulated result and the clinical data of cervical cancer growth. Low values of Mean-Square Error (MSE) of Gompertzian stochastic model with delay effect indicate good fits.
Li, Wei Bo; Greiter, Matthias; Oeh, Uwe; Hoeschen, Christoph
2011-12-01
The reliability of biokinetic models is essential for the assessment of internal doses and a radiation risk analysis for the public and occupational workers exposed to radionuclides. In the present study, a method for assessing the reliability of biokinetic models by means of uncertainty and sensitivity analysis was developed. In the first part of the paper, the parameter uncertainty was analyzed for two biokinetic models of zirconium (Zr); one was reported by the International Commission on Radiological Protection (ICRP), and one was developed at the Helmholtz Zentrum München-German Research Center for Environmental Health (HMGU). In the second part of the paper, the parameter uncertainties and distributions of the Zr biokinetic models evaluated in Part I are used as the model inputs for identifying the most influential parameters in the models. Furthermore, the most influential model parameter on the integral of the radioactivity of Zr over 50 y in source organs after ingestion was identified. The results of the systemic HMGU Zr model showed that over the first 10 d, the parameters of transfer rates between blood and other soft tissues have the largest influence on the content of Zr in the blood and the daily urinary excretion; however, after day 1,000, the transfer rate from bone to blood becomes dominant. For the retention in bone, the transfer rate from blood to bone surfaces has the most influence out to the endpoint of the simulation; the transfer rate from blood to the upper larger intestine contributes a lot in the later days; i.e., after day 300. The alimentary tract absorption factor (fA) influences mostly the integral of radioactivity of Zr in most source organs after ingestion.
A new model for simulating growth in fish
Directory of Open Access Journals (Sweden)
Johannes Hamre
2014-01-01
Full Text Available A real dynamic population model calculates change in population sizes independent of time. The Beverton & Holt (B&H model commonly used in fish assessment includes the von Bertalanffy growth function which has age or accumulated time as an independent variable. As a result the B&H model has to assume constant fish growth. However, growth in fish is highly variable depending on food availability and environmental conditions. We propose a new growth model where the length increment of fish living under constant conditions and unlimited food supply, decreases linearly with increasing fish length until it reaches zero at a maximal fish length. The model is independent of time and includes a term which accounts for the environmental variation. In the present study, the model was validated in zebrafish held at constant conditions. There was a good fit of the model to data on observed growth in Norwegian spring spawning herring, capelin from the Barents Sea, North Sea herring and in farmed coastal cod. Growth data from Walleye Pollock from the Eastern Bering Sea and blue whiting from the Norwegian Sea also fitted reasonably well to the model, whereas data from cod from the North Sea showed a good fit to the model only above a length of 70 cm. Cod from the Barents Sea did not grow according to the model. The last results can be explained by environmental factors and variable food availability in the time under study. The model implicates that the efficiency of energy conversion from food decreases as the individual animal approaches its maximal length and is postulated to represent a natural law of fish growth.
Fracture Mechanical Markov Chain Crack Growth Model
DEFF Research Database (Denmark)
Gansted, L.; Brincker, Rune; Hansen, Lars Pilegaard
1991-01-01
propagation process can be described by a discrete space Markov theory. The model is applicable to deterministic as well as to random loading. Once the model parameters for a given material have been determined, the results can be used for any structure as soon as the geometrical function is known....
Mediation Analysis in a Latent Growth Curve Modeling Framework
von Soest, Tilmann; Hagtvet, Knut A.
2011-01-01
This article presents several longitudinal mediation models in the framework of latent growth curve modeling and provides a detailed account of how such models can be constructed. Logical and statistical challenges that might arise when such analyses are conducted are also discussed. Specifically, we discuss how the initial status (intercept) and…
Growth models for Pinus patula in Angola | Delgado-Matas ...
African Journals Online (AJOL)
This study developed growth models for Pinus patula Schiede ex Schltdl. et Cham. for the Central Highlands of Angola for simulating the development of stand characteristics. The model set included dominant height, individual-tree diameter increment, individual-tree height and self-thinning models. The study was based ...
Directory of Open Access Journals (Sweden)
Andrew K. Wills
2016-04-01
Full Text Available Abstract Background Regression models are widely used to link serial measures of anthropometric size or changes in size to a later outcome. Different parameterisations of these models enable one to target different questions about the effect of growth, however, their interpretation can be challenging. Our objective was to formulate and classify several sets of parameterisations by their underlying growth pattern contrast, and to discuss their utility using an expository example. Methods We describe and classify five sets of model parameterisations in accordance with their underlying growth pattern contrast (conditional growth; being bigger v being smaller; becoming bigger and staying bigger; growing faster v being bigger; becoming and staying bigger versus being bigger. The contrasts are estimated by including different sets of repeated measures of size and changes in size in a regression model. We illustrate these models in the setting of linking infant growth (measured on 6 occasions: birth, 6 weeks, 3, 6, 12 and 24 months in weight-for-height-for-age z-scores to later childhood overweight at 8y using complete cases from the Norwegian Childhood Growth study (n = 900. Results In our expository example, conditional growth during all periods, becoming bigger in any interval and staying bigger through infancy, and being bigger from birth were all associated with higher odds of later overweight. The highest odds of later overweight occurred for individuals who experienced high conditional growth or became bigger in the 3 to 6 month period and stayed bigger, and those who were bigger from birth to 24 months. Comparisons between periods and between growth patterns require large sample sizes and need to consider how to scale associations to make comparisons fair; with respect to the latter, we show one approach. Conclusion Studies interested in detrimental growth patterns may gain extra insight from reporting several sets of growth pattern
Quantified Risk Ranking Model for Condition-Based Risk and Reliability Centered Maintenance
Chattopadhyaya, Pradip Kumar; Basu, Sushil Kumar; Majumdar, Manik Chandra
2017-06-01
In the recent past, risk and reliability centered maintenance (RRCM) framework is introduced with a shift in the methodological focus from reliability and probabilities (expected values) to reliability, uncertainty and risk. In this paper authors explain a novel methodology for risk quantification and ranking the critical items for prioritizing the maintenance actions on the basis of condition-based risk and reliability centered maintenance (CBRRCM). The critical items are identified through criticality analysis of RPN values of items of a system and the maintenance significant precipitating factors (MSPF) of items are evaluated. The criticality of risk is assessed using three risk coefficients. The likelihood risk coefficient treats the probability as a fuzzy number. The abstract risk coefficient deduces risk influenced by uncertainty, sensitivity besides other factors. The third risk coefficient is called hazardous risk coefficient, which is due to anticipated hazards which may occur in the future and the risk is deduced from criteria of consequences on safety, environment, maintenance and economic risks with corresponding cost for consequences. The characteristic values of all the three risk coefficients are obtained with a particular test. With few more tests on the system, the values may change significantly within controlling range of each coefficient, hence `random number simulation' is resorted to obtain one distinctive value for each coefficient. The risk coefficients are statistically added to obtain final risk coefficient of each critical item and then the final rankings of critical items are estimated. The prioritization in ranking of critical items using the developed mathematical model for risk assessment shall be useful in optimization of financial losses and timing of maintenance actions.
Models of the Economic Growth and their Relevance
Directory of Open Access Journals (Sweden)
Nicolae MOROIANU
2012-06-01
Full Text Available Until few years ago, the economic growth was something perfect normal, part of an era marked by the transformation speed. Normality itself has been transformed and we currently are influenced by other rules, unknown yet, which should answer the question: “How do we return to the economic growth?” The economic growth and the models aiming to solve this problem concern the economic history even since its beginnings. In this paper we would like to find out what is the relevance that the well-known macroeconomic models still have and which might be their applicability level in a framework created by a black swan event type.
DEFF Research Database (Denmark)
Dimitrov, Nikolay Krasimirov; Friis-Hansen, Peter; Berggreen, Christian
2013-01-01
by the composite failure criteria. Each failure mode has been considered in a separate component reliability analysis, followed by a system analysis which gives the total probability of failure of the structure. The Model Correction Factor method used in connection with FORM (First-Order Reliability Method) proved...
International Nuclear Information System (INIS)
Vichev, S.; Bogdanov, D.
2000-01-01
The purpose of this paper is to introduce the fault tree analysis method as a tool for unit protection reliability estimation. The constant failure rate model applies for making reliability assessment, and especially availability assessment. For that purpose an example for unit primary equipment structure and fault tree example for simplified unit protection system is presented (author)
Modeling truck traffic volume growth congestion.
2009-05-01
Modeling of the statewide transportation system is an important element in understanding issues and programming of funds to thwart potential congestion. As Alabama grows its manufacturing economy, the number of heavy vehicles traversing its highways ...
Another brick in the cell wall: biosynthesis dependent growth model.
Directory of Open Access Journals (Sweden)
Adelin Barbacci
Full Text Available Expansive growth of plant cell is conditioned by the cell wall ability to extend irreversibly. This process is possible if (i a tensile stress is developed in the cell wall due to the coupling effect between turgor pressure and the modulation of its mechanical properties through enzymatic and physicochemical reactions and if (ii new cell wall elements can be synthesized and assembled to the existing wall. In other words, expansive growth is the result of coupling effects between mechanical, thermal and chemical energy. To have a better understanding of this process, models must describe the interplay between physical or mechanical variable with biological events. In this paper we propose a general unified and theoretical framework to model growth in function of energy forms and their coupling. This framework is based on irreversible thermodynamics. It is then applied to model growth of the internodal cell of Chara corallina modulated by changes in pressure and temperature. The results describe accurately cell growth in term of length increment but also in term of cell pectate biosynthesis and incorporation to the expanding wall. Moreover, the classical growth model based on Lockhart's equation such as the one proposed by Ortega, appears as a particular and restrictive case of the more general growth equation developed in this paper.
Bayesian and Classical Estimation of Stress-Strength Reliability for Inverse Weibull Lifetime Models
Directory of Open Access Journals (Sweden)
Qixuan Bi
2017-06-01
Full Text Available In this paper, we consider the problem of estimating stress-strength reliability for inverse Weibull lifetime models having the same shape parameters but different scale parameters. We obtain the maximum likelihood estimator and its asymptotic distribution. Since the classical estimator doesn’t hold explicit forms, we propose an approximate maximum likelihood estimator. The asymptotic confidence interval and two bootstrap intervals are obtained. Using the Gibbs sampling technique, Bayesian estimator and the corresponding credible interval are obtained. The Metropolis-Hastings algorithm is used to generate random variates. Monte Carlo simulations are conducted to compare the proposed methods. Analysis of a real dataset is performed.
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...
A new lifetime estimation model for a quicker LED reliability prediction
Hamon, B. H.; Mendizabal, L.; Feuillet, G.; Gasse, A.; Bataillou, B.
2014-09-01
LED reliability and lifetime prediction is a key point for Solid State Lighting adoption. For this purpose, one hundred and fifty LEDs have been aged for a reliability analysis. LEDs have been grouped following nine current-temperature stress conditions. Stress driving current was fixed between 350mA and 1A and ambient temperature between 85C and 120°C. Using integrating sphere and I(V) measurements, a cross study of the evolution of electrical and optical characteristics has been done. Results show two main failure mechanisms regarding lumen maintenance. The first one is the typically observed lumen depreciation and the second one is a much more quicker depreciation related to an increase of the leakage and non radiative currents. Models of the typical lumen depreciation and leakage resistance depreciation have been made using electrical and optical measurements during the aging tests. The combination of those models allows a new method toward a quicker LED lifetime prediction. These two models have been used for lifetime predictions for LEDs.
Reliability of Current Biokinetic and Dosimetric Models for Radionuclides: A Pilot Study
Energy Technology Data Exchange (ETDEWEB)
Leggett, Richard Wayne [ORNL; Eckerman, Keith F [ORNL; Meck, Robert A. [U.S. Nuclear Regulatory Commission
2008-10-01
This report describes the results of a pilot study of the reliability of the biokinetic and dosimetric models currently used by the U.S. Nuclear Regulatory Commission (NRC) as predictors of dose per unit internal or external exposure to radionuclides. The study examines the feasibility of critically evaluating the accuracy of these models for a comprehensive set of radionuclides of concern to the NRC. Each critical evaluation would include: identification of discrepancies between the models and current databases; characterization of uncertainties in model predictions of dose per unit intake or unit external exposure; characterization of variability in dose per unit intake or unit external exposure; and evaluation of prospects for development of more accurate models. Uncertainty refers here to the level of knowledge of a central value for a population, and variability refers to quantitative differences between different members of a population. This pilot study provides a critical assessment of models for selected radionuclides representing different levels of knowledge of dose per unit exposure. The main conclusions of this study are as follows: (1) To optimize the use of available NRC resources, the full study should focus on radionuclides most frequently encountered in the workplace or environment. A list of 50 radionuclides is proposed. (2) The reliability of a dose coefficient for inhalation or ingestion of a radionuclide (i.e., an estimate of dose per unit intake) may depend strongly on the specific application. Multiple characterizations of the uncertainty in a dose coefficient for inhalation or ingestion of a radionuclide may be needed for different forms of the radionuclide and different levels of information of that form available to the dose analyst. (3) A meaningful characterization of variability in dose per unit intake of a radionuclide requires detailed information on the biokinetics of the radionuclide and hence is not feasible for many infrequently
International Nuclear Information System (INIS)
Knee, H.E.; Haas, P.M.
1985-01-01
A computer model has been developed, sensitivity tested, and evaluated capable of generating reliable estimates of human performance measures in the nuclear power plant (NPP) maintenance context. The model, entitled MAPPS (Maintenance Personnel Performance Simulation), is of the simulation type and is task-oriented. It addresses a number of person-machine, person-environment, and person-person variables and is capable of providing the user with a rich spectrum of important performance measures including mean time for successful task performance by a maintenance team and maintenance team probability of task success. These two measures are particularly important for input to probabilistic risk assessment (PRA) studies which were the primary impetus for the development of MAPPS. The simulation nature of the model along with its generous input parameters and output variables allows its usefulness to extend beyond its input to PRA
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.
Software reliability through fault-avoidance and fault-tolerance
Vouk, Mladen A.; Mcallister, David F.
1992-01-01
Accomplishments in the following research areas are summarized: structure based testing, reliability growth, and design testability with risk evaluation; reliability growth models and software risk management; and evaluation of consensus voting, consensus recovery block, and acceptance voting. Four papers generated during the reporting period are included as appendices.
Cloud-based calculators for fast and reliable access to NOAA's geomagnetic field models
Woods, A.; Nair, M. C.; Boneh, N.; Chulliat, A.
2017-12-01
While the Global Positioning System (GPS) provides accurate point locations, it does not provide pointing directions. Therefore, the absolute directional information provided by the Earth's magnetic field is of primary importance for navigation and for the pointing of technical devices such as aircrafts, satellites and lately, mobile phones. The major magnetic sources that affect compass-based navigation are the Earth's core, its magnetized crust and the electric currents in the ionosphere and magnetosphere. NOAA/CIRES Geomagnetism (ngdc.noaa.gov/geomag/) group develops and distributes models that describe all these important sources to aid navigation. Our geomagnetic models are used in variety of platforms including airplanes, ships, submarines and smartphones. While the magnetic field from Earth's core can be described in relatively fewer parameters and is suitable for offline computation, the magnetic sources from Earth's crust, ionosphere and magnetosphere require either significant computational resources or real-time capabilities and are not suitable for offline calculation. This is especially important for small navigational devices or embedded systems, where computational resources are limited. Recognizing the need for a fast and reliable access to our geomagnetic field models, we developed cloud-based application program interfaces (APIs) for NOAA's ionospheric and magnetospheric magnetic field models. In this paper we will describe the need for reliable magnetic calculators, the challenges faced in running geomagnetic field models in the cloud in real-time and the feedback from our user community. We discuss lessons learned harvesting and validating the data which powers our cloud services, as well as our strategies for maintaining near real-time service, including load-balancing, real-time monitoring, and instance cloning. We will also briefly talk about the progress we achieved on NOAA's Big Earth Data Initiative (BEDI) funded project to develop API
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.)
Quadratic tracer dynamical models tobacco growth
International Nuclear Information System (INIS)
Qiang Jiyi; Hua Cuncai; Wang Shaohua
2011-01-01
In order to study the non-uniformly transferring process of some tracer dosages, we assume that the absorption of some tracer by tobacco is a quadratic function of the tracer quantity of the tracer in the case of fast absorption, whereas the exclusion of the tracer from tobacco is a linear function of the tracer quantity in the case of slow exclusion, after the tracer is introduced into tobacco once at zero time. A single-compartment quadratic dynamical model of Logistic type is established for the leaves of tobacco. Then, a two-compartment quadratic dynamical model is established for leaves and calms of the tobacco. Qualitative analysis of the models shows that the tracer applied to the leaves of the tobacco is excluded finally; however, the tracer stays at the tobacco for finite time. Two methods are also given for computing the parameters in the models. Finally, the results of the models are verified by the 32 P experiment for the absorption of tobacco. (authors)
Modeling and simulation of Si crystal growth from melt
Energy Technology Data Exchange (ETDEWEB)
Liu, Lijun; Liu, Xin; Li, Zaoyang [National Engineering Research Center for Fluid Machinery and Compressors, School of Energy and Power Engineering, Xi' an Jiaotong University, Xi' an, Shaanxi 710049 (China); Miyazawa, Hiroaki; Nakano, Satoshi; Kakimoto, Koichi [Research Institute for Applied Mechanics, Kyushu University, Kasuga 816-8580 (Japan)
2009-07-01
A numerical simulator was developed with a global model of heat transfer for any crystal growth taking place at high temperature. Convective, conductive and radiative heat transfers in the furnace are solved together in a conjugated way by a finite volume method. A three-dimensional (3D) global model was especially developed for simulation of heat transfer in any crystal growth with 3D features. The model enables 3D global simulation be conducted with moderate requirement of computer resources. The application of this numerical simulator to a CZ growth and a directional solidification process for Si crystals, the two major production methods for crystalline Si for solar cells, was introduced. Some typical results were presented, showing the importance and effectiveness of numerical simulation in analyzing and improving these kinds of Si crystal growth processes from melt. (copyright 2009 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)
Growth Curve Models and Applications : Indian Statistical Institute
2017-01-01
Growth curve models in longitudinal studies are widely used to model population size, body height, biomass, fungal growth, and other variables in the biological sciences, but these statistical methods for modeling growth curves and analyzing longitudinal data also extend to general statistics, economics, public health, demographics, epidemiology, SQC, sociology, nano-biotechnology, fluid mechanics, and other applied areas. There is no one-size-fits-all approach to growth measurement. The selected papers in this volume build on presentations from the GCM workshop held at the Indian Statistical Institute, Giridih, on March 28-29, 2016. They represent recent trends in GCM research on different subject areas, both theoretical and applied. This book includes tools and possibilities for further work through new techniques and modification of existing ones. The volume includes original studies, theoretical findings and case studies from a wide range of app lied work, and these contributions have been externally r...
Benchmark data set for wheat growth models
DEFF Research Database (Denmark)
Asseng, S; Ewert, F.; Martre, P
2015-01-01
The data set includes a current representative management treatment from detailed, quality-tested sentinel field experiments with wheat from four contrasting environments including Australia, The Netherlands, India and Argentina. Measurements include local daily climate data (solar radiation, max...... analysis with 26 models and 30 years (1981-2010) for each location, for elevated atmospheric CO2 and temperature changes, a heat stress sensitivity analysis at anthesis, and a sensitivity analysis with soil and crop management variations and a Global Climate Model end-century scenario....
A mathematical model of microalgae growth in cylindrical photobioreactor
Bakeri, Noorhadila Mohd; Jamaian, Siti Suhana
2017-08-01
Microalgae are unicellular organisms, which exist individually or in chains or groups but can be utilized in many applications. Researchers have done various efforts in order to increase the growth rate of microalgae. Microalgae have a potential as an effective tool for wastewater treatment, besides as a replacement for natural fuel such as coal and biodiesel. The growth of microalgae can be estimated by using Geider model, which this model is based on photosynthesis irradiance curve (PI-curve) and focused on flat panel photobioreactor. Therefore, in this study a mathematical model for microalgae growth in cylindrical photobioreactor is proposed based on the Geider model. The light irradiance is the crucial part that affects the growth rate of microalgae. The absorbed photon flux will be determined by calculating the average light irradiance in a cylindrical system illuminated by unidirectional parallel flux and considering the cylinder as a collection of differential parallelepipeds. Results from this study showed that the specific growth rate of microalgae increases until the constant level is achieved. Therefore, the proposed mathematical model can be used to estimate the rate of microalgae growth in cylindrical photobioreactor.