[A reliability growth assessment method and its application in the development of equipment in space cabin].

Science.gov (United States)

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.

Bayesian methods in reliability

Science.gov (United States)

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.

Proposed reliability cost model

Science.gov (United States)

Delionback, L. M.

1973-01-01

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

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.

Modeling Root Growth, Crop Growth and N Uptake of Winter Wheat Based on SWMS_2D: Model and Validation

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.

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)

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

Reliability Engineering

CERN Document Server

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

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)

Cervical vertebral maturation method and mandibular growth peak: a longitudinal study of diagnostic reliability.

Science.gov (United States)

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.

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

OpenAIRE

Hai An; Ling Zhou; Hui Sun

2016-01-01

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

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

Directory of Open Access Journals (Sweden)

Hai An

2016-08-01

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

Software reliability through fault-avoidance and fault-tolerance

Science.gov (United States)

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.

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)

Power Electronic Packaging Design, Assembly Process, Reliability and Modeling

CERN Document Server

Liu, Yong

2012-01-01

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

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...

A mechanism of extreme growth and reliable signaling in sexually selected ornaments and weapons.

Science.gov (United States)

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.

Business Cases for Microgrids: Modeling Interactions of Technology Choice, Reliability, Cost, and Benefit

Science.gov (United States)

Hanna, Ryan

Distributed energy resources (DERs), and increasingly microgrids, are becoming an integral part of modern distribution systems. Interest in microgrids--which are insular and autonomous power networks embedded within the bulk grid--stems largely from the vast array of flexibilities and benefits they can offer stakeholders. Managed well, they can improve grid reliability and resiliency, increase end-use energy efficiency by coupling electric and thermal loads, reduce transmission losses by generating power locally, and may reduce system-wide emissions, among many others. Whether these public benefits are realized, however, depends on whether private firms see a "business case", or private value, in investing. To this end, firms need models that evaluate costs, benefits, risks, and assumptions that underlie decisions to invest. The objectives of this dissertation are to assess the business case for microgrids that provide what industry analysts forecast as two primary drivers of market growth--that of providing energy services (similar to an electric utility) as well as reliability service to customers within. Prototypical first adopters are modeled--using an existing model to analyze energy services and a new model that couples that analysis with one of reliability--to explore interactions between technology choice, reliability, costs, and benefits. The new model has a bi-level hierarchy; it uses heuristic optimization to select and size DERs and analytical optimization to schedule them. It further embeds Monte Carlo simulation to evaluate reliability as well as regression models for customer damage functions to monetize reliability. It provides least-cost microgrid configurations for utility customers who seek to reduce interruption and operating costs. Lastly, the model is used to explore the impact of such adoption on system-wide greenhouse gas emissions in California. Results indicate that there are, at present, co-benefits for emissions reductions when customers

Sintered tantalum carbide coatings on graphite substrates: Highly reliable protective coatings for bulk and epitaxial growth

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.

Sintered tantalum carbide coatings on graphite substrates: Highly reliable protective coatings for bulk and epitaxial growth

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

Reliability models for Space Station power system

Science.gov (United States)

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

1987-01-01

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

Reliability Model of Power Transformer with ONAN Cooling

OpenAIRE

M. Sefidgaran; M. Mirzaie; A. Ebrahimzadeh

2010-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2012-08-15

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

Travel time reliability modeling.

Science.gov (United States)

2011-07-01

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

Proposed Reliability/Cost Model

Science.gov (United States)

Delionback, L. M.

1982-01-01

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

Time domain series system definition and gear set reliability modeling

International Nuclear Information System (INIS)

Xie, Liyang; Wu, Ningxiang; Qian, Wenxue

2016-01-01

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

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

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...

Stochastic models in reliability and maintenance

CERN Document Server

2002-01-01

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

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

A Method of Nuclear Software Reliability Estimation

International Nuclear Information System (INIS)

Park, Gee Yong; Eom, Heung Seop; Cheon, Se Woo; Jang, Seung Cheol

2011-01-01

A method on estimating software reliability for nuclear safety software is proposed. This method is based on the software reliability growth model (SRGM) where the behavior of software failure is assumed to follow the non-homogeneous Poisson process. Several modeling schemes are presented in order to estimate and predict more precisely the number of software defects based on a few of software failure data. The Bayesian statistical inference is employed to estimate the model parameters by incorporating the software test cases into the model. It is identified that this method is capable of accurately estimating the remaining number of software defects which are on-demand type directly affecting safety trip functions. The software reliability can be estimated from a model equation and one method of obtaining the software reliability is proposed

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

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.

Modeling Math Growth Trajectory--An Application of Conventional Growth Curve Model and Growth Mixture Model to ECLS K-5 Data

Science.gov (United States)

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…

Analysis of information security reliability: A tutorial

International Nuclear Information System (INIS)

Kondakci, Suleyman

2015-01-01

This article presents a concise reliability analysis of network security abstracted from stochastic modeling, reliability, and queuing theories. Network security analysis is composed of threats, their impacts, and recovery of the failed systems. A unique framework with a collection of the key reliability models is presented here to guide the determination of the system reliability based on the strength of malicious acts and performance of the recovery processes. A unique model, called Attack-obstacle model, is also proposed here for analyzing systems with immunity growth features. Most computer science curricula do not contain courses in reliability modeling applicable to different areas of computer engineering. Hence, the topic of reliability analysis is often too diffuse to most computer engineers and researchers dealing with network security. This work is thus aimed at shedding some light on this issue, which can be useful in identifying models, their assumptions and practical parameters for estimating the reliability of threatened systems and for assessing the performance of recovery facilities. It can also be useful for the classification of processes and states regarding the reliability of information systems. Systems with stochastic behaviors undergoing queue operations and random state transitions can also benefit from the approaches presented here. - Highlights: • A concise survey and tutorial in model-based reliability analysis applicable to information security. • A framework of key modeling approaches for assessing reliability of networked systems. • The framework facilitates quantitative risk assessment tasks guided by stochastic modeling and queuing theory. • Evaluation of approaches and models for modeling threats, failures, impacts, and recovery analysis of information systems

Growth characteristics of liquid cultures increase the reliability of presumptive identification of Mycobacterium tuberculosis complex.

Science.gov (United States)

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.

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)

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...

Reliability and Model Fit

Science.gov (United States)

Stanley, Leanne M.; Edwards, Michael C.

2016-01-01

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

Reliability modeling of an engineered barrier system

International Nuclear Information System (INIS)

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

1993-01-01

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

Reliability modeling of an engineered barrier system

International Nuclear Information System (INIS)

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

1993-01-01

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

Modeling and Analysis of Component Faults and Reliability

DEFF Research Database (Denmark)

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

2016-01-01

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

Supply chain reliability modelling

Directory of Open Access Journals (Sweden)

Eugen Zaitsev

2012-03-01

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

Conceptual Software Reliability Prediction Models for Nuclear Power Plant Safety Systems

International Nuclear Information System (INIS)

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

2000-01-01

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

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

Stochastic Individual-Based Modeling of Bacterial Growth and Division Using Flow Cytometry

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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.

Plant and control system reliability and risk model

International Nuclear Information System (INIS)

Niemelae, I.M.

1986-01-01

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

Reliability Modeling of Double Beam Bridge Crane

Science.gov (United States)

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

2018-05-01

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

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

Science.gov (United States)

Ha, Taesung

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

Space Vehicle Reliability Modeling in DIORAMA

Energy Technology Data Exchange (ETDEWEB)

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

2016-07-12

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

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

CERN Document Server

Finkelstein, Maxim

2013-01-01

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

Based on Weibull Information Fusion Analysis Semiconductors Quality the Key Technology of Manufacturing Execution Systems Reliability

Science.gov (United States)

Huang, Zhi-Hui; Tang, Ying-Chun; Dai, Kai

2016-05-01

Semiconductor materials and Product qualified rate are directly related to the manufacturing costs and survival of the enterprise. Application a dynamic reliability growth analysis method studies manufacturing execution system reliability growth to improve product quality. Refer to classical Duane model assumptions and tracking growth forecasts the TGP programming model, through the failure data, established the Weibull distribution model. Combining with the median rank of average rank method, through linear regression and least squares estimation method, match respectively weibull information fusion reliability growth curve. This assumption model overcome Duane model a weakness which is MTBF point estimation accuracy is not high, through the analysis of the failure data show that the method is an instance of the test and evaluation modeling process are basically identical. Median rank in the statistics is used to determine the method of random variable distribution function, which is a good way to solve the problem of complex systems such as the limited sample size. Therefore this method has great engineering application value.

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

Maximum Entropy Discrimination Poisson Regression for Software Reliability Modeling.

Science.gov (United States)

Chatzis, Sotirios P; Andreou, Andreas S

2015-11-01

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

NONLINEAR MODELS FOR DESCRIPTION OF CACAO FRUIT GROWTH WITH ASSUMPTION VIOLATIONS

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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.

Wind turbine reliability : a database and analysis approach.

Energy Technology Data Exchange (ETDEWEB)

Linsday, James (ARES Corporation); Briand, Daniel; Hill, Roger Ray; Stinebaugh, Jennifer A.; Benjamin, Allan S. (ARES Corporation)

2008-02-01

The US wind Industry has experienced remarkable growth since the turn of the century. At the same time, the physical size and electrical generation capabilities of wind turbines has also experienced remarkable growth. As the market continues to expand, and as wind generation continues to gain a significant share of the generation portfolio, the reliability of wind turbine technology becomes increasingly important. This report addresses how operations and maintenance costs are related to unreliability - that is the failures experienced by systems and components. Reliability tools are demonstrated, data needed to understand and catalog failure events is described, and practical wind turbine reliability models are illustrated, including preliminary results. This report also presents a continuing process of how to proceed with controlling industry requirements, needs, and expectations related to Reliability, Availability, Maintainability, and Safety. A simply stated goal of this process is to better understand and to improve the operable reliability of wind turbine installations.

Learning reliable manipulation strategies without initial physical models

Science.gov (United States)

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

1990-01-01

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

Transparent reliability model for fault-tolerant safety systems

International Nuclear Information System (INIS)

Bodsberg, Lars; Hokstad, Per

1997-01-01

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

RELIABILITY MODELING BASED ON INCOMPLETE DATA: OIL PUMP APPLICATION

Directory of Open Access Journals (Sweden)

Ahmed HAFAIFA

2014-07-01

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

Estimation of some stochastic models used in reliability engineering

International Nuclear Information System (INIS)

Huovinen, T.

1989-04-01

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

Urban tree growth modeling

Science.gov (United States)

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...

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.

A SOFTWARE RELIABILITY ESTIMATION METHOD TO NUCLEAR SAFETY SOFTWARE

Directory of Open Access Journals (Sweden)

GEE-YONG PARK

2014-02-01

Full Text Available A method for estimating software reliability for nuclear safety software is proposed in this paper. This method is based on the software reliability growth model (SRGM, where the behavior of software failure is assumed to follow a non-homogeneous Poisson process. Two types of modeling schemes based on a particular underlying method are proposed in order to more precisely estimate and predict the number of software defects based on very rare software failure data. The Bayesian statistical inference is employed to estimate the model parameters by incorporating software test cases as a covariate into the model. It was identified that these models are capable of reasonably estimating the remaining number of software defects which directly affects the reactor trip functions. The software reliability might be estimated from these modeling equations, and one approach of obtaining software reliability value is proposed in this paper.

Predicting Madura cattle growth curve using non-linear model

Science.gov (United States)

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.

Quantitative metal magnetic memory reliability modeling for welded joints

Science.gov (United States)

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

2016-03-01

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

Experiment research on cognition reliability model of nuclear power plant

International Nuclear Information System (INIS)

Zhao Bingquan; Fang Xiang

1999-01-01

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

Reliability in the Rasch Model

Czech Academy of Sciences Publication Activity Database

Martinková, Patrícia; Zvára, K.

2007-01-01

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

A reliability-risk modelling of nuclear rad-waste facilities

International Nuclear Information System (INIS)

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

1975-01-01

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

Development of a Conservative Model Validation Approach for Reliable Analysis

Science.gov (United States)

2015-01-01

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

Applications of a fracture mechanics model of structural reliability to the effects of seismic events on reactor piping

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)

Data Used in Quantified Reliability Models

Science.gov (United States)

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

2014-01-01

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

Finite element reliability analysis of fatigue life

International Nuclear Information System (INIS)

Harkness, H.H.; Belytschko, T.; Liu, W.K.

1992-01-01

Fatigue reliability is addressed by the first-order reliability method combined with a finite element method. Two-dimensional finite element models of components with cracks in mode I are considered with crack growth treated by the Paris law. Probability density functions of the variables affecting fatigue are proposed to reflect a setting where nondestructive evaluation is used, and the Rosenblatt transformation is employed to treat non-Gaussian random variables. Comparisons of the first-order reliability results and Monte Carlo simulations suggest that the accuracy of the first-order reliability method is quite good in this setting. Results show that the upper portion of the initial crack length probability density function is crucial to reliability, which suggests that if nondestructive evaluation is used, the probability of detection curve plays a key role in reliability. (orig.)

Reliability modeling of Clinch River breeder reactor electrical shutdown systems

International Nuclear Information System (INIS)

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

1974-01-01

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

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

OpenAIRE

Chassin, David P.; Posse, Christian

2004-01-01

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

Reliability modelling and simulation of switched linear system ...

African Journals Online (AJOL)

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

Models for reliability and management of NDT data

International Nuclear Information System (INIS)

Simola, K.

1997-01-01

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

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

DEFF Research Database (Denmark)

Taskinen, Matti; Mäntysaari, Esa; Lidauer, Martin

2013-01-01

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

A Reliability Based Model for Wind Turbine Selection

Directory of Open Access Journals (Sweden)

A.K. Rajeevan

2013-06-01

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

Integrated reliability condition monitoring and maintenance of equipment

CERN Document Server

Osarenren, John

2015-01-01

Consider a Viable and Cost-Effective Platform for the Industries of the Future (IOF) Benefit from improved safety, performance, and product deliveries to your customers. Achieve a higher rate of equipment availability, performance, product quality, and reliability. Integrated Reliability: Condition Monitoring and Maintenance of Equipment incorporates reliable engineering and mathematical modeling to help you move toward sustainable development in reliability condition monitoring and maintenance. This text introduces a cost-effective integrated reliability growth monitor, integrated reliability degradation monitor, technological inheritance coefficient sensors, and a maintenance tool that supplies real-time information for predicting and preventing potential failures of manufacturing processes and equipment. The author highlights five key elements that are essential to any improvement program: improving overall equipment and part effectiveness, quality, and reliability; improving process performance with maint...

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

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...

Lévy-based growth models

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....

Forecasting craniofacial growth in individuals with class III malocclusion by computational modelling.

Science.gov (United States)

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.

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....

Reliability of EUCLIDIAN: An autonomous robotic system for image-guided prostate brachytherapy

International Nuclear Information System (INIS)

Podder, Tarun K.; Buzurovic, Ivan; Huang Ke; Showalter, Timothy; Dicker, Adam P.; Yu, Yan

2011-01-01

Purpose: Recently, several robotic systems have been developed to perform accurate and consistent image-guided brachytherapy. Before introducing a new device into clinical operations, it is important to assess the reliability and mean time before failure (MTBF) of the system. In this article, the authors present the preclinical evaluation and analysis of the reliability and MTBF of an autonomous robotic system, which is developed for prostate seed implantation. Methods: The authors have considered three steps that are important in reliability growth analysis. These steps are: Identification and isolation of failures, classification of failures, and trend analysis. For any one-of-a-kind product, the reliability enhancement is accomplished through test-fix-test. The authors have used failure mode and effect analysis for collection and analysis of reliability data by identifying and categorizing the failure modes. Failures were classified according to severity. Failures that occurred during the operation of this robotic system were considered as nonhomogenous Poisson process. The failure occurrence trend was analyzed using Laplace test. For analyzing and predicting reliability growth, commonly used and widely accepted models, Duane's model and the Army Material Systems Analysis Activity, i.e., Crow's model, were applied. The MTBF was used as an important measure for assessing the system's reliability. Results: During preclinical testing, 3196 seeds (in 53 test cases) were deposited autonomously by the robot and 14 critical failures were encountered. The majority of the failures occurred during the first few cases. The distribution of failures followed Duane's postulation as well as Crow's postulation of reliability growth. The Laplace test index was -3.82 (<0), indicating a significant trend in failure data, and the failure intervals lengthened gradually. The continuous increase in the failure occurrence interval suggested a trend toward improved reliability. The MTBF

Reliability of EUCLIDIAN: An autonomous robotic system for image-guided prostate brachytherapy

Energy Technology Data Exchange (ETDEWEB)

Podder, Tarun K.; Buzurovic, Ivan; Huang Ke; Showalter, Timothy; Dicker, Adam P.; Yu, Yan [Department of Radiation Oncology, Kimmel Cancer Center (NCI-designated), Thomas Jefferson University, Philadelphia, Pennsylvania 19107 (United States)

2011-01-15

Purpose: Recently, several robotic systems have been developed to perform accurate and consistent image-guided brachytherapy. Before introducing a new device into clinical operations, it is important to assess the reliability and mean time before failure (MTBF) of the system. In this article, the authors present the preclinical evaluation and analysis of the reliability and MTBF of an autonomous robotic system, which is developed for prostate seed implantation. Methods: The authors have considered three steps that are important in reliability growth analysis. These steps are: Identification and isolation of failures, classification of failures, and trend analysis. For any one-of-a-kind product, the reliability enhancement is accomplished through test-fix-test. The authors have used failure mode and effect analysis for collection and analysis of reliability data by identifying and categorizing the failure modes. Failures were classified according to severity. Failures that occurred during the operation of this robotic system were considered as nonhomogenous Poisson process. The failure occurrence trend was analyzed using Laplace test. For analyzing and predicting reliability growth, commonly used and widely accepted models, Duane's model and the Army Material Systems Analysis Activity, i.e., Crow's model, were applied. The MTBF was used as an important measure for assessing the system's reliability. Results: During preclinical testing, 3196 seeds (in 53 test cases) were deposited autonomously by the robot and 14 critical failures were encountered. The majority of the failures occurred during the first few cases. The distribution of failures followed Duane's postulation as well as Crow's postulation of reliability growth. The Laplace test index was -3.82 (<0), indicating a significant trend in failure data, and the failure intervals lengthened gradually. The continuous increase in the failure occurrence interval suggested a trend toward

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....

Modeling Conformal Growth in Photonic Crystals and Comparing to Experiment

Science.gov (United States)

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.

Diagnostic reliability of the cervical vertebral maturation method and standing height in the identification of the mandibular growth spurt.

Science.gov (United States)

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.

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

Science.gov (United States)

Yuan, Zhongda; Deng, Junxiang; Wang, Dawei

2018-02-01

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

NHPP-Based Software Reliability Models Using Equilibrium Distribution

Science.gov (United States)

Xiao, Xiao; Okamura, Hiroyuki; Dohi, Tadashi

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

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

International Nuclear Information System (INIS)

Jordan Cizelj, R.; Vrbanic, I.

2001-01-01

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

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

Science.gov (United States)

Aarset, M.; Wright, J. F.

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

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.

Measurement-based reliability/performability models

Science.gov (United States)

Hsueh, Mei-Chen

1987-01-01

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

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.

Bacterial growth kinetics

International Nuclear Information System (INIS)

Boonkitticharoen, V.; Ehrhardt, J.C.; Kirchner, P.T.

1989-01-01

Quantitative measurement of bacterial growth may be made using a radioassay technique. This method measures, by scintillation counting, the 14 CO 2 derived from the bacterial metabolism of a 14 C-labeled substrate. Mathematical growth models may serve as reliable tools for estimation of the generation rate constant (or slope of the growth curve) and provide a basis for evaluating assay performance. Two models, i.e., exponential and logistic, are proposed. Both models yielded an accurate fit to the data from radioactive measurement of bacterial growth. The exponential model yielded high precision values of the generation rate constant, with an average relative standard deviation of 1.2%. Under most conditions the assay demonstrated no changes in the slopes of growth curves when the number of bacteria per inoculation was changed. However, the radiometric assay by scintillation method had a growth-inhibiting effect on a few strains of bacteria. The source of this problem was thought to be hypersensitivity to trace amounts of toluene remaining on the detector

Nonlinear Growth Models as Measurement Models: A Second-Order Growth Curve Model for Measuring Potential.

Science.gov (United States)

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.

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

Statistical models and methods for reliability and survival analysis

CERN Document Server

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

2013-01-01

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

A Survey of Software Reliability Modeling and Estimation

Science.gov (United States)

1983-09-01

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

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.

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...

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

International Nuclear Information System (INIS)

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

1987-01-01

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

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

Science.gov (United States)

2013-07-29

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

Pocket Handbook on Reliability

Science.gov (United States)

1975-09-01

exponencial distributions Weibull distribution, -xtimating reliability, confidence intervals, relia- bility growth, 0. P- curves, Bayesian analysis. 20 A S...introduction for those not familiar with reliability and a good refresher for those who are currently working in the area. LEWIS NERI, CHIEF...includes one or both of the following objectives: a) prediction of the current system reliability, b) projection on the system reliability for someI future

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.

Emittance growth due to negative-mass instability above transition

International Nuclear Information System (INIS)

Ng, King-Yuen.

1994-08-01

Due to space-charge effect, there is a growth of bunch emittance across transition as a result of negative-mass instability. The models of growth at cutoff frequency and growth from high-frequency Schottky noise are reviewed. The difficulties of performing reliable simulations are discussed. An intuitive self-bunching model for estimating emittance growth is presented

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...

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

Application of a Snow Growth Model to Radar Remote Sensing

Science.gov (United States)

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

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.

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

Model of load balancing using reliable algorithm with multi-agent system

Science.gov (United States)

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.

EFFECT OF DIFFERENT ENVIRONMENTAL FACTORS ON THE GROWTH DYNAMICS OF STAPHYLOCOCCUS AUREUS IN MODEL MEDIUM

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

Damage tolerance reliability analysis of automotive spot-welded joints

International Nuclear Information System (INIS)

Mahadevan, Sankaran; Ni Kan

2003-01-01

This paper develops a damage tolerance reliability analysis methodology for automotive spot-welded joints under multi-axial and variable amplitude loading history. The total fatigue life of a spot weld is divided into two parts, crack initiation and crack propagation. The multi-axial loading history is obtained from transient response finite element analysis of a vehicle model. A three-dimensional finite element model of a simplified joint with four spot welds is developed for static stress/strain analysis. A probabilistic Miner's rule is combined with a randomized strain-life curve family and the stress/strain analysis result to develop a strain-based probabilistic fatigue crack initiation life prediction for spot welds. Afterwards, the fatigue crack inside the base material sheet is modeled as a surface crack. Then a probabilistic crack growth model is combined with the stress analysis result to develop a probabilistic fatigue crack growth life prediction for spot welds. Both methods are implemented with MSC/NASTRAN and MSC/FATIGUE software, and are useful for reliability assessment of automotive spot-welded joints against fatigue and fracture

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

International Nuclear Information System (INIS)

Lee, Seung Woo; Lee, Hwa Ki

2008-01-01

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

Power plant reliability calculation with Markov chain models

International Nuclear Information System (INIS)

Senegacnik, A.; Tuma, M.

1998-01-01

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

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

International Nuclear Information System (INIS)

Lindquist, Tommie

2008-04-01

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

System Reliability Engineering

International Nuclear Information System (INIS)

Lim, Tae Jin

2005-02-01

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

The reliability of the Adelaide in-shoe foot model.

Science.gov (United States)

Bishop, Chris; Hillier, Susan; Thewlis, Dominic

2017-07-01

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

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

International Nuclear Information System (INIS)

Pitigoi, A.; Fernandez, P.

2015-01-01

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

Structural reliability in context of statistical uncertainties and modelling discrepancies

International Nuclear Information System (INIS)

Pendola, Maurice

2000-01-01

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

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

Directory of Open Access Journals (Sweden)

Robert Adam Sobolewski

2015-09-01

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

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 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

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.

System reliability of corroding pipelines

International Nuclear Information System (INIS)

Zhou Wenxing

2010-01-01

A methodology is presented in this paper to evaluate the time-dependent system reliability of a pipeline segment that contains multiple active corrosion defects and is subjected to stochastic internal pressure loading. The pipeline segment is modeled as a series system with three distinctive failure modes due to corrosion, namely small leak, large leak and rupture. The internal pressure is characterized as a simple discrete stochastic process that consists of a sequence of independent and identically distributed random variables each acting over a period of one year. The magnitude of a given sequence follows the annual maximum pressure distribution. The methodology is illustrated through a hypothetical example. Furthermore, the impact of the spatial variability of the pressure loading and pipe resistances associated with different defects on the system reliability is investigated. The analysis results suggest that the spatial variability of pipe properties has a negligible impact on the system reliability. On the other hand, the spatial variability of the internal pressure, initial defect sizes and defect growth rates can have a significant impact on the system reliability.

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

International Nuclear Information System (INIS)

Mitra, S.P.

1979-01-01

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

Modeling reliability of power systems substations by using stochastic automata networks

International Nuclear Information System (INIS)

Šnipas, Mindaugas; Radziukynas, Virginijus; Valakevičius, Eimutis

2017-01-01

In this paper, stochastic automata networks (SANs) formalism to model reliability of power systems substations is applied. The proposed strategy allows reducing the size of state space of Markov chain model and simplifying system specification. Two case studies of standard configurations of substations are considered in detail. SAN models with different assumptions were created. SAN approach is compared with exact reliability calculation by using a minimal path set method. Modeling results showed that total independence of automata can be assumed for relatively small power systems substations with reliable equipment. In this case, the implementation of Markov chain model by a using SAN method is a relatively easy task. - Highlights: • We present the methodology to apply stochastic automata network formalism to create Markov chain models of power systems. • The stochastic automata network approach is combined with minimal path sets and structural functions. • Two models of substation configurations with different model assumptions are presented to illustrate the proposed methodology. • Modeling results of system with independent automata and functional transition rates are similar. • The conditions when total independence of automata can be assumed are addressed.

Reliability modeling and analysis of smart power systems

CERN Document Server

Karki, Rajesh; Verma, Ajit Kumar

2014-01-01

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

Reliability of structures by using probability and fatigue theories

International Nuclear Information System (INIS)

Lee, Ouk Sub; Kim, Dong Hyeok; Park, Yeon Chang

2008-01-01

Methodologies to calculate failure probability and to estimate the reliability of fatigue loaded structures are developed. The applicability of the methodologies is evaluated with the help of the fatigue crack growth models suggested by Paris and Walker. The probability theories such as the FORM (first order reliability method), the SORM (second order reliability method) and the MCS (Monte Carlo simulation) are utilized. It is found that the failure probability decreases with the increase of the design fatigue life and the applied minimum stress, the decrease of the initial edge crack size, the applied maximum stress and the slope of Paris equation. Furthermore, according to the sensitivity analysis of random variables, the slope of Pairs equation affects the failure probability dominantly among other random variables in the Paris and the Walker models

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

International Nuclear Information System (INIS)

Fang Xiang; Zhao Bingquan

2000-01-01

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

Reliability-based assessment of deteriorating ship structures operating in multiple sea loading climates

Energy Technology Data Exchange (ETDEWEB)

Moan, Torgeir [Centre for Ships and Ocean Structures, Norwegian University of Science and Technology, Marine Technology Centre, Tyholt, N 7491 Trondheim (Norway)], E-mail: tormo@marin.ntnu.no; Ayala-Uraga, Efren [Department of Marine Technology, Norwegian University of Science and Technology, Marine Technology Centre, Tyholt, N 7491 Trondheim (Norway)

2008-03-15

A reliability-based model for assessment of deteriorating ships subjected to multiple environmental conditions is established. Deterioration due to combined crack growth and corrosion in structural components of a ship hull is accounted for based on a fracture mechanics formulation. The model enables to take into account the corrosion-induced increased crack growth rate in two ways: (1) the increased stress range produced by the plate thinning (wastage) effect and (2) corrosion fatigue itself. Sensitivity studies are carried out to evaluate the effect of inspection updating on a production ship subjected to two different climate conditions. The hazard rate concept is adopted as a measure of reliability and emphasized throughout the different case studies.

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

Science.gov (United States)

Alonso, Ariel; Laenen, Annouschka

2013-05-01

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

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

International Nuclear Information System (INIS)

Iskandar, Ismed; Gondokaryono, Yudi Satria

2016-01-01

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

Stochastic models for tumoral growth

Science.gov (United States)

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.

Latent Growth and Dynamic Structural Equation Models.

Science.gov (United States)

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.

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.

Testing mechanistic models of growth in insects.

Science.gov (United States)

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).

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

Multiobjective Reliable Cloud Storage with Its Particle Swarm Optimization Algorithm

Directory of Open Access Journals (Sweden)

Xiyang Liu

2016-01-01

Full Text Available Information abounds in all fields of the real life, which is often recorded as digital data in computer systems and treated as a kind of increasingly important resource. Its increasing volume growth causes great difficulties in both storage and analysis. The massive data storage in cloud environments has significant impacts on the quality of service (QoS of the systems, which is becoming an increasingly challenging problem. In this paper, we propose a multiobjective optimization model for the reliable data storage in clouds through considering both cost and reliability of the storage service simultaneously. In the proposed model, the total cost is analyzed to be composed of storage space occupation cost, data migration cost, and communication cost. According to the analysis of the storage process, the transmission reliability, equipment stability, and software reliability are taken into account in the storage reliability evaluation. To solve the proposed multiobjective model, a Constrained Multiobjective Particle Swarm Optimization (CMPSO algorithm is designed. At last, experiments are designed to validate the proposed model and its solution PSO algorithm. In the experiments, the proposed model is tested in cooperation with 3 storage strategies. Experimental results show that the proposed model is positive and effective. The experimental results also demonstrate that the proposed model can perform much better in alliance with proper file splitting methods.

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

Modelling Reliability of Supply and Infrastructural Dependency in Energy Distribution Systems

OpenAIRE

Helseth, Arild

2008-01-01

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

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)

Reliability physics and engineering time-to-failure modeling

CERN Document Server

McPherson, J W

2013-01-01

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

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

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.

Maintenance overtime policies in reliability theory models with random working cycles

CERN Document Server

Nakagawa, Toshio

2015-01-01

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

Stochastic ontogenetic growth model

Science.gov (United States)

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.

Mechanistic model coupling gas exchange dynamics and Listeria monocytogenes growth in modified atmosphere packaging of non respiring food.

Science.gov (United States)

Chaix, E; Broyart, B; Couvert, O; Guillaume, C; Gontard, N; Guillard, V

2015-10-01

A mechanistic model coupling O2 and CO2 mass transfer (namely diffusion and solubilisation in the food itself and permeation through the packaging material) to microbial growth models was developed aiming at predicting the shelf life of modified atmosphere packaging (MAP) systems. It was experimentally validated on a non-respiring food by investigating concomitantly the O2/CO2 partial pressure in packaging headspace and the growth of Listeria monocytogenes (average microbial count) within the food sample. A sensitivity analysis has revealed that the reliability of the prediction by this "super-parametrized" model (no less than 47 parameters were required for running one simulation) was strongly dependent on the accuracy of the microbial input parameters. Once validated, this model was used to decipher the role of O2/CO2 mass transfer on microbial growth and as a MAP design tool: an example of MAP dimensioning was provided in this paper as a proof of concept. Copyright © 2015 Elsevier Ltd. All rights reserved.

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...

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.

Reliability Measure Model for Assistive Care Loop Framework Using Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Venki Balasubramanian

2010-01-01

Full Text Available Body area wireless sensor networks (BAWSNs are time-critical systems that rely on the collective data of a group of sensor nodes. Reliable data received at the sink is based on the collective data provided by all the source sensor nodes and not on individual data. Unlike conventional reliability, the definition of retransmission is inapplicable in a BAWSN and would only lead to an elapsed data arrival that is not acceptable for time-critical application. Time-driven applications require high data reliability to maintain detection and responses. Hence, the transmission reliability for the BAWSN should be based on the critical time. In this paper, we develop a theoretical model to measure a BAWSN's transmission reliability, based on the critical time. The proposed model is evaluated through simulation and then compared with the experimental results conducted in our existing Active Care Loop Framework (ACLF. We further show the effect of the sink buffer in transmission reliability after a detailed study of various other co-existing parameters.

Travel Time Reliability for Urban Networks : Modelling and Empirics

NARCIS (Netherlands)

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

2017-01-01

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

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.

Intra-observer reliability and agreement of manual and digital orthodontic model analysis.

Science.gov (United States)

Koretsi, Vasiliki; Tingelhoff, Linda; Proff, Peter; Kirschneck, Christian

2018-01-23

Digital orthodontic model analysis is gaining acceptance in orthodontics, but its reliability is dependent on the digitalisation hardware and software used. We thus investigated intra-observer reliability and agreement / conformity of a particular digital model analysis work-flow in relation to traditional manual plaster model analysis. Forty-eight plaster casts of the upper/lower dentition were collected. Virtual models were obtained with orthoX®scan (Dentaurum) and analysed with ivoris®analyze3D (Computer konkret). Manual model analyses were done with a dial caliper (0.1 mm). Common parameters were measured on each plaster cast and its virtual counterpart five times each by an experienced observer. We assessed intra-observer reliability within method (ICC), agreement/conformity between methods (Bland-Altman analyses and Lin's concordance correlation), and changing bias (regression analyses). Intra-observer reliability was substantial within each method (ICC ≥ 0.7), except for five manual outcomes (12.8 per cent). Bias between methods was statistically significant, but less than 0.5 mm for 87.2 per cent of the outcomes. In general, larger tooth sizes were measured digitally. Total difference maxilla and mandible had wide limits of agreement (-3.25/6.15 and -2.31/4.57 mm), but bias between methods was mostly smaller than intra-observer variation within each method with substantial conformity of manual and digital measurements in general. No changing bias was detected. Although both work-flows were reliable, the investigated digital work-flow proved to be more reliable and yielded on average larger tooth sizes. Averaged differences between methods were within 0.5 mm for directly measured outcomes but wide ranges are expected for some computed space parameters due to cumulative error. © The Author 2017. Published by Oxford University Press on behalf of the European Orthodontic Society. All rights reserved. For permissions, please email: journals.permissions@oup.com

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

Using LISREL to Evaluate Measurement Models and Scale Reliability.

Science.gov (United States)

Fleishman, John; Benson, Jeri

1987-01-01

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

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.

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

International Nuclear Information System (INIS)

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

2013-01-01

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

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.

Inter-arch digital model vs. manual cast measurements: Accuracy and reliability.

Science.gov (United States)

Kiviahde, Heikki; Bukovac, Lea; Jussila, Päivi; Pesonen, Paula; Sipilä, Kirsi; Raustia, Aune; Pirttiniemi, Pertti

2017-06-28

The purpose of this study was to evaluate the accuracy and reliability of inter-arch measurements using digital dental models and conventional dental casts. Thirty sets of dental casts with permanent dentition were examined. Manual measurements were done with a digital caliper directly on the dental casts, and digital measurements were made on 3D models by two independent examiners. Intra-class correlation coefficients (ICC), a paired sample t-test or Wilcoxon signed-rank test, and Bland-Altman plots were used to evaluate intra- and inter-examiner error and to determine the accuracy and reliability of the measurements. The ICC values were generally good for manual and excellent for digital measurements. The Bland-Altman plots of all the measurements showed good agreement between the manual and digital methods and excellent inter-examiner agreement using the digital method. Inter-arch occlusal measurements on digital models are accurate and reliable and are superior to manual measurements.

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

Reliability of length measurements collected by community nurses and health volunteers in rural growth monitoring and promotion services.

Science.gov (United States)

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

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.

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.)

Dependent systems reliability estimation by structural reliability approach

DEFF Research Database (Denmark)

Kostandyan, Erik; Sørensen, John Dalsgaard

2014-01-01

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

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

International Nuclear Information System (INIS)

Shang Yanlong; Cai Qi; Zhao Xinwen; Chen Ling

2013-01-01

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

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

Science.gov (United States)

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

2018-04-27

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

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

Science.gov (United States)

Zhong, Wei; Kim, Yushim

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

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.

Reliability-based management of buried pipelines considering external corrosion defects

Science.gov (United States)

Miran, Seyedeh Azadeh

-system. Sensitivity analysis is also performed to determine to which incorporated parameter(s) in the growth models reliability of the studied pipeline is most sensitive. The reliability analysis results suggest that newly generated defects should be considered in calculating failure probability, especially for prediction of long-term performance of the pipeline and also, impact of the statistical uncertainty in the model parameters is significant that should be considered in the reliability analysis. Finally, with the evaluated time-dependent failure probabilities, a life cycle-cost analysis is conducted to determine optimal inspection interval of studied pipeline. The expected total life-cycle costs consists construction cost and expected costs of inspections, repair, and failure. The repair is conducted when failure probability from any described failure mode exceeds pre-defined probability threshold after each inspection. Moreover, this study also investigates impact of repair threshold values and unit costs of inspection and failure on the expected total life-cycle cost and optimal inspection interval through a parametric study. The analysis suggests that a smaller inspection interval leads to higher inspection costs, but can lower failure cost and also repair cost is less significant compared to inspection and failure costs.

Systems reliability/structural reliability

International Nuclear Information System (INIS)

Green, A.E.

1980-01-01

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

Reliability modeling of digital RPS with consideration of undetected software faults

Energy Technology Data Exchange (ETDEWEB)

Khalaquzzaman, M.; Lee, Seung Jun; Jung, Won Dea [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Kim, Man Cheol [Chung Ang Univ., Seoul (Korea, Republic of)

2013-10-15

This paper provides overview of different software reliability methodologies and proposes a technic for estimating the reliability of RPS with consideration of undetected software faults. Software reliability analysis of safety critical software has been challenging despite spending a huge effort for developing large number of software reliability models, and no consensus yet to attain on an appropriate modeling methodology. However, it is realized that the combined application of BBN based SDLC fault prediction method and random black-box testing of software would provide better ground for reliability estimation of safety critical software. Digitalizing the reactor protection system of nuclear power plant has been initiated several decades ago and now full digitalization has been adopted in the new generation of NPPs around the world because digital I and C systems have many better technical features like easier configurability and maintainability over analog I and C systems. Digital I and C systems are also drift-free and incorporation of new features is much easier. Rules and regulation for safe operation of NPPs are established and has been being practiced by the operators as well as regulators of NPPs to ensure safety. The failure mechanism of hardware and analog systems well understood and the risk analysis methods for these components and systems are well established. However, digitalization of I and C system in NPP introduces some crisis and uncertainty in reliability analysis methods of the digital systems/components because software failure mechanisms are still unclear.

OSS reliability measurement and assessment

CERN Document Server

Yamada, Shigeru

2016-01-01

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

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

Science.gov (United States)

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

2018-02-01

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

Improved radiograph measurement inter-observer reliability by use of statistical shape models

Energy Technology Data Exchange (ETDEWEB)

Pegg, E.C., E-mail: elise.pegg@ndorms.ox.ac.uk [University of Oxford, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Nuffield Orthopaedic Centre, Windmill Road, Oxford OX3 7LD (United Kingdom); Mellon, S.J., E-mail: stephen.mellon@ndorms.ox.ac.uk [University of Oxford, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Nuffield Orthopaedic Centre, Windmill Road, Oxford OX3 7LD (United Kingdom); Salmon, G. [University of Oxford, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Nuffield Orthopaedic Centre, Windmill Road, Oxford OX3 7LD (United Kingdom); Alvand, A., E-mail: abtin.alvand@ndorms.ox.ac.uk [University of Oxford, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Nuffield Orthopaedic Centre, Windmill Road, Oxford OX3 7LD (United Kingdom); Pandit, H., E-mail: hemant.pandit@ndorms.ox.ac.uk [University of Oxford, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Nuffield Orthopaedic Centre, Windmill Road, Oxford OX3 7LD (United Kingdom); Murray, D.W., E-mail: david.murray@ndorms.ox.ac.uk [University of Oxford, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Nuffield Orthopaedic Centre, Windmill Road, Oxford OX3 7LD (United Kingdom); Gill, H.S., E-mail: richie.gill@ndorms.ox.ac.uk [University of Oxford, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Nuffield Orthopaedic Centre, Windmill Road, Oxford OX3 7LD (United Kingdom)

2012-10-15

Pre- and post-operative radiographs of patients undergoing joint arthroplasty are often examined for a variety of purposes including preoperative planning and patient assessment. This work examines the feasibility of using active shape models (ASM) to semi-automate measurements from post-operative radiographs for the specific case of the Oxford™ Unicompartmental Knee. Measurements of the proximal tibia and the position of the tibial tray were made using the ASM model and manually. Data were obtained by four observers and one observer took four sets of measurements to allow assessment of the inter- and intra-observer reliability, respectively. The parameters measured were the tibial tray angle, the tray overhang, the tray size, the sagittal cut position, the resection level and the tibial width. Results demonstrated improved reliability (average of 27% and 11.2% increase for intra- and inter-reliability, respectively) and equivalent accuracy (p > 0.05 for compared data values) for all of the measurements using the ASM model, with the exception of the tray overhang (p = 0.0001). Less time (15 s) was required to take measurements using the ASM model compared with manual measurements, which was significant. These encouraging results indicate that semi-automated measurement techniques could improve the reliability of radiographic measurements.

Improved radiograph measurement inter-observer reliability by use of statistical shape models

International Nuclear Information System (INIS)

Pegg, E.C.; Mellon, S.J.; Salmon, G.; Alvand, A.; Pandit, H.; Murray, D.W.; Gill, H.S.

2012-01-01

Pre- and post-operative radiographs of patients undergoing joint arthroplasty are often examined for a variety of purposes including preoperative planning and patient assessment. This work examines the feasibility of using active shape models (ASM) to semi-automate measurements from post-operative radiographs for the specific case of the Oxford™ Unicompartmental Knee. Measurements of the proximal tibia and the position of the tibial tray were made using the ASM model and manually. Data were obtained by four observers and one observer took four sets of measurements to allow assessment of the inter- and intra-observer reliability, respectively. The parameters measured were the tibial tray angle, the tray overhang, the tray size, the sagittal cut position, the resection level and the tibial width. Results demonstrated improved reliability (average of 27% and 11.2% increase for intra- and inter-reliability, respectively) and equivalent accuracy (p > 0.05 for compared data values) for all of the measurements using the ASM model, with the exception of the tray overhang (p = 0.0001). Less time (15 s) was required to take measurements using the ASM model compared with manual measurements, which was significant. These encouraging results indicate that semi-automated measurement techniques could improve the reliability of radiographic measurements

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

Science.gov (United States)

Liu, Donhang

2014-01-01

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

Human reliability

International Nuclear Information System (INIS)

Embrey, D.E.

1987-01-01

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

Nonconvex Model of Material Growth: Mathematical Theory

Science.gov (United States)

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.

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...

Reliability-based inspection planning of 20MW offshore wind turbine jacket

DEFF Research Database (Denmark)

Gintautas, Tomas; Sørensen, John Dalsgaard

2018-01-01

This paper presents the application of a risk and reliability based inspection planning framework (RBI) for the InnWind 20MW reference wind turbine jacket sub-structure. A detailed fracture mechanics based fatigue crack growth model is developed and used as basis to derive optimal inspection plans...

A study of operational and testing reliability in software reliability analysis

International Nuclear Information System (INIS)

Yang, B.; Xie, M.

2000-01-01

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

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...

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...

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

Science.gov (United States)

Michaelides, Stylianos

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

The prediction of reliability and residual life of reactor pressure components

International Nuclear Information System (INIS)

Nemec, J.; Antalovsky, S.

1978-01-01

The paper deals with the problem of PWR pressure components reliability and residual life evaluation and prediction. A physical model of damage cumulation which serves as a theoretical basis for all considerations presents two major aspects. The first one describes the dependence of the degree of damage in the crack leading-edge in pressure components on the reactor system load-time history, i.e. on the number of transient loads. Both stages, fatigue crack initiation and growth through the wall until the critical length is reached, are investigated. The crack is supposed to initiate at the flaws in a strength weld joint or in the bimetallic weld of the base ferritic steel and the austenitic stainless overlay cladding. The growth rates of developed cracks are analysed in respect to different load-time histories. Important cyclic properties of some steels are derived from the low-cycle fatigue theory. The second aspect is the load-time history-dependent process of precipitation, deformation and radiation aging, characterized entirely by the critical crack-length value mentioned above. The fracture point, defined by the equation ''crack-length=critical value'' and hence the residual life, can be evaluated using this model and verified by in-service inspection. The physical model described is randomized by considering all the parameters of the model as random. Monte Carlo methods are applied and fatigue crack initiation and growth is simulated. This permits evaluation of the reliability and residual life of the component. The distributions of material and load-time history parameters are needed for such simulation. Both the deterministic and computer-simulated probabilistic predictions of reliability and residual life are verified by prior-to-failure sequential testing of data coming from in-service NDT periodical inspections. (author)

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

Science.gov (United States)

Raykov, Tenko; Marcoulides, George A.

2012-01-01

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

Kinetic Model of Growth of Arthropoda Populations

Science.gov (United States)

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.

Modeling Optimal Scheduling for Pumping System to Minimize Operation Cost and Enhance Operation Reliability

Directory of Open Access Journals (Sweden)

Yin Luo

2012-01-01

Full Text Available Traditional pump scheduling models neglect the operation reliability which directly relates with the unscheduled maintenance cost and the wear cost during the operation. Just for this, based on the assumption that the vibration directly relates with the operation reliability and the degree of wear, it could express the operation reliability as the normalization of the vibration level. The characteristic of the vibration with the operation point was studied, it could be concluded that idealized flow versus vibration plot should be a distinct bathtub shape. There is a narrow sweet spot (80 to 100 percent BEP to obtain low vibration levels in this shape, and the vibration also follows similar law with the square of the rotation speed without resonance phenomena. Then, the operation reliability could be modeled as the function of the capacity and rotation speed of the pump and add this function to the traditional model to form the new. And contrast with the tradition method, the result shown that the new model could fix the result produced by the traditional, make the pump operate in low vibration, then the operation reliability could increase and the maintenance cost could decrease.

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

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

Probabilistic Modeling of the Fatigue Crack Growth Rate for Ni-base Alloy X-750

International Nuclear Information System (INIS)

Yoon, J.Y.; Nam, H.O.; Hwang, I.S.; Lee, T.H.

2012-01-01

Extending the operating life of existing nuclear power plants (NPP's) beyond 60 years. Many aging problems of passive components such as PWSCC, IASCC, FAC and Corrosion Fatigue; Safety analysis: Deterministic analysis + Probabilistic analysis; Many uncertainties of parameters or relationship in general probabilistic analysis such as probabilistic safety assessment (PSA); Bayesian inference: Decreasing uncertainties by updating unknown parameter; Ensuring the reliability of passive components (e.g. pipes) as well as active components (e.g. valve, pump) in NPP's; Developing probabilistic model for failures; Updating the fatigue crack growth rate (FCGR)

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

Science.gov (United States)

Ebeling, Charles E.

1995-01-01

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

Average inactivity time model, associated orderings and reliability properties

Science.gov (United States)

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

2018-02-01

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

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.

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

Energy Technology Data Exchange (ETDEWEB)

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

2008-07-01

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

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

International Nuclear Information System (INIS)

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

2008-01-01

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

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

CERN Document Server

Nakagawa, Toshio

2013-01-01

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

Testing linear growth rate formulas of non-scale endogenous growth models

NARCIS (Netherlands)

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

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

Bayesian Hierarchical Scale Mixtures of Log-Normal Models for Inference in Reliability with Stochastic Constraint

Directory of Open Access Journals (Sweden)

Hea-Jung Kim

2017-06-01

Full Text Available This paper develops Bayesian inference in reliability of a class of scale mixtures of log-normal failure time (SMLNFT models with stochastic (or uncertain constraint in their reliability measures. The class is comprehensive and includes existing failure time (FT models (such as log-normal, log-Cauchy, and log-logistic FT models as well as new models that are robust in terms of heavy-tailed FT observations. Since classical frequency approaches to reliability analysis based on the SMLNFT model with stochastic constraint are intractable, the Bayesian method is pursued utilizing a Markov chain Monte Carlo (MCMC sampling based approach. This paper introduces a two-stage maximum entropy (MaxEnt prior, which elicits a priori uncertain constraint and develops Bayesian hierarchical SMLNFT model by using the prior. The paper also proposes an MCMC method for Bayesian inference in the SMLNFT model reliability and calls attention to properties of the MaxEnt prior that are useful for method development. Finally, two data sets are used to illustrate how the proposed methodology works.

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

Graphene growth process modeling: a physical-statistical approach

Science.gov (United States)

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.

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

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

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

Science.gov (United States)

Yang, Xufeng; Liu, Yongshou; Ma, Panke

2017-11-01

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

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

Directory of Open Access Journals (Sweden)

Zongshuai Yan

2015-01-01

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

A general graphical user interface for automatic reliability modeling

Science.gov (United States)

Liceaga, Carlos A.; Siewiorek, Daniel P.

1991-01-01

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

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.

Product reliability and thin-film photovoltaics

Science.gov (United States)

Gaston, Ryan; Feist, Rebekah; Yeung, Simon; Hus, Mike; Bernius, Mark; Langlois, Marc; Bury, Scott; Granata, Jennifer; Quintana, Michael; Carlson, Carl; Sarakakis, Georgios; Ogden, Douglas; Mettas, Adamantios

2009-08-01

Despite significant growth in photovoltaics (PV) over the last few years, only approximately 1.07 billion kWhr of electricity is estimated to have been generated from PV in the US during 2008, or 0.27% of total electrical generation. PV market penetration is set for a paradigm shift, as fluctuating hydrocarbon prices and an acknowledgement of the environmental impacts associated with their use, combined with breakthrough new PV technologies, such as thin-film and BIPV, are driving the cost of energy generated with PV to parity or cost advantage versus more traditional forms of energy generation. In addition to reaching cost parity with grid supplied power, a key to the long-term success of PV as a viable energy alternative is the reliability of systems in the field. New technologies may or may not have the same failure modes as previous technologies. Reliability testing and product lifetime issues continue to be one of the key bottlenecks in the rapid commercialization of PV technologies today. In this paper, we highlight the critical need for moving away from relying on traditional qualification and safety tests as a measure of reliability and focus instead on designing for reliability and its integration into the product development process. A drive towards quantitative predictive accelerated testing is emphasized and an industrial collaboration model addressing reliability challenges is proposed.

Testing the reliability of ice-cream cone model

Science.gov (United States)

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

2015-04-01

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

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.

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

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

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.

Growth curve models and statistical diagnostics

CERN Document Server

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.

An examination of reliability critical items in liquid metal reactors: An analysis by the Centralized Reliability Data Organization (CREDO)

International Nuclear Information System (INIS)

Humphrys, B.L.; Haire, M.J.; Koger, K.H.; Manneschmidt, J.F.; Setoguchi, K.; Nakai, R.; Okubo, Y.

1987-01-01

The Centralized Reliability Data Organization (CREDO) is the largest repository of liquid metal reactor (LMR) component reliability data in the world. It is jointly sponsored by the US Department of Energy (DOE) and the Power Reactor and Nuclear Fuel Development Corporation (PNC) of Japan. The CREDO data base contains information on a population of more than 21,000 components and approximately 1300 event records. A conservative estimation is that the total component operating hours is approaching 3.5 billion hours. Because data gathering for CREDO concentrates on event (failure) information, the work reported here focuses on the reliability information contained in CREDO and the development of reliability critical items lists. That is, components are ranked in prioritized lists from worst to best performers from a reliability standpoint. For the data contained in the CREDO data base, FFTF and JOYO show reliability growth; EBR-II reveals a slight unreliability growth for those components tracked by CREDO. However, tabulations of events which cause reactor shutdowns decrease with time at each site

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

OpenAIRE

Siemaszko, D; Speiser, M; Pittet, S

2012-01-01

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

Frontiers of reliability

CERN Document Server

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

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.

Reliability of Coulomb stress changes inferred from correlated uncertainties of finite-fault source models

KAUST Repository

Woessner, J.

2012-07-14

Static stress transfer is one physical mechanism to explain triggered seismicity. Coseismic stress-change calculations strongly depend on the parameterization of the causative finite-fault source model. These models are uncertain due to uncertainties in input data, model assumptions, and modeling procedures. However, fault model uncertainties have usually been ignored in stress-triggering studies and have not been propagated to assess the reliability of Coulomb failure stress change (ΔCFS) calculations. We show how these uncertainties can be used to provide confidence intervals for co-seismic ΔCFS-values. We demonstrate this for the MW = 5.9 June 2000 Kleifarvatn earthquake in southwest Iceland and systematically map these uncertainties. A set of 2500 candidate source models from the full posterior fault-parameter distribution was used to compute 2500 ΔCFS maps. We assess the reliability of the ΔCFS-values from the coefficient of variation (CV) and deem ΔCFS-values to be reliable where they are at least twice as large as the standard deviation (CV ≤ 0.5). Unreliable ΔCFS-values are found near the causative fault and between lobes of positive and negative stress change, where a small change in fault strike causes ΔCFS-values to change sign. The most reliable ΔCFS-values are found away from the source fault in the middle of positive and negative ΔCFS-lobes, a likely general pattern. Using the reliability criterion, our results support the static stress-triggering hypothesis. Nevertheless, our analysis also suggests that results from previous stress-triggering studies not considering source model uncertainties may have lead to a biased interpretation of the importance of static stress-triggering.

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.

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....

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.

A hybrid reliability algorithm using PSO-optimized Kriging model and adaptive importance sampling

Science.gov (United States)

Tong, Cao; Gong, Haili

2018-03-01

This paper aims to reduce the computational cost of reliability analysis. A new hybrid algorithm is proposed based on PSO-optimized Kriging model and adaptive importance sampling method. Firstly, the particle swarm optimization algorithm (PSO) is used to optimize the parameters of Kriging model. A typical function is fitted to validate improvement by comparing results of PSO-optimized Kriging model with those of the original Kriging model. Secondly, a hybrid algorithm for reliability analysis combined optimized Kriging model and adaptive importance sampling is proposed. Two cases from literatures are given to validate the efficiency and correctness. The proposed method is proved to be more efficient due to its application of small number of sample points according to comparison results.

Modeling Population Growth and Extinction

Science.gov (United States)

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,…

Modeling of Hybrid Growth Wastewater Bio-reactor

International Nuclear Information System (INIS)

EI Nashaei, S.; Garhyan, P.; Prasad, P.; Abdel Halim, H.S.; Ibrahim, G.

2004-01-01

The attached/suspended growth mixed reactors are considered one of the recently tried approaches to improve the performance of the biological treatment by increasing the volume of the accumulated biomass in terms of attached growth as well as suspended growth. Moreover, the domestic WW can be easily mixed with a high strength non-hazardous industrial wastewater and treated together in these bio-reactors if the need arises. Modeling of Hybrid hybrid growth wastewater reactor addresses the need of understanding the rational of such system in order to achieve better design and operation parameters. This paper aims at developing a heterogeneous mathematical model for hybrid growth system considering the effect of diffusion, external mass transfer, and power input to the system in a rational manner. The model will be based on distinguishing between liquid/solid phase (bio-film and bio-floc). This model would be a step ahead to the fine tuning the design of hybrid systems based on the experimental data of a pilot plant to be implemented in near future

Reliability analysis of the solar array based on Fault Tree Analysis

International Nuclear Information System (INIS)

Wu Jianing; Yan Shaoze

2011-01-01

The solar array is an important device used in the spacecraft, which influences the quality of in-orbit operation of the spacecraft and even the launches. This paper analyzes the reliability of the mechanical system and certifies the most vital subsystem of the solar array. The fault tree analysis (FTA) model is established according to the operating process of the mechanical system based on DFH-3 satellite; the logical expression of the top event is obtained by Boolean algebra and the reliability of the solar array is calculated. The conclusion shows that the hinges are the most vital links between the solar arrays. By analyzing the structure importance(SI) of the hinge's FTA model, some fatal causes, including faults of the seal, insufficient torque of the locking spring, temperature in space, and friction force, can be identified. Damage is the initial stage of the fault, so limiting damage is significant to prevent faults. Furthermore, recommendations for improving reliability associated with damage limitation are discussed, which can be used for the redesigning of the solar array and the reliability growth planning.

Reliability analysis of the solar array based on Fault Tree Analysis

Energy Technology Data Exchange (ETDEWEB)

Wu Jianing; Yan Shaoze, E-mail: yansz@mail.tsinghua.edu.cn [State Key Laboratory of Tribology, Department of Precision Instruments and Mechanology, Tsinghua University,Beijing 100084 (China)

2011-07-19

The solar array is an important device used in the spacecraft, which influences the quality of in-orbit operation of the spacecraft and even the launches. This paper analyzes the reliability of the mechanical system and certifies the most vital subsystem of the solar array. The fault tree analysis (FTA) model is established according to the operating process of the mechanical system based on DFH-3 satellite; the logical expression of the top event is obtained by Boolean algebra and the reliability of the solar array is calculated. The conclusion shows that the hinges are the most vital links between the solar arrays. By analyzing the structure importance(SI) of the hinge's FTA model, some fatal causes, including faults of the seal, insufficient torque of the locking spring, temperature in space, and friction force, can be identified. Damage is the initial stage of the fault, so limiting damage is significant to prevent faults. Furthermore, recommendations for improving reliability associated with damage limitation are discussed, which can be used for the redesigning of the solar array and the reliability growth planning.

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2011-01-01

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

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.

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

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

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

International Nuclear Information System (INIS)

Arndt, S. A.

2006-01-01

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

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)

A comparative study of the probabilistic fracture mechanics and the stochastic Markovian process approaches for structural reliability assessment

Energy Technology Data Exchange (ETDEWEB)

Stavrakakis, G.; Lucia, A.C.; Solomos, G. (Commission of the European Communities, Ispra (Italy). Joint Research Centre)

1990-01-01

The two computer codes COVASTOL and RELIEF, developed for the modeling of cumulative damage processes in the framework of probabilistic structural reliability, are compared. They are based respectively on the randomisation of a differential crack growth law and on the theory of discrete Markov processes. The codes are applied for fatigue crack growth predictions using two sets of data of crack propagation curves from specimens. The results are critically analyzed and an extensive discussion follows on the merits and limitations of each code. Their transferability for the reliability assessment of real structures is investigated. (author).

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

DEFF Research Database (Denmark)

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

2015-01-01

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

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

DEFF Research Database (Denmark)

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

2014-01-01

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

Pollution externalities in a Schumpeterian growth model

OpenAIRE

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...

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.

Circuit design for reliability

CERN Document Server

Cao, Yu; Wirth, Gilson

2015-01-01

This book presents physical understanding, modeling and simulation, on-chip characterization, layout solutions, and design techniques that are effective to enhance the reliability of various circuit units.  The authors provide readers with techniques for state of the art and future technologies, ranging from technology modeling, fault detection and analysis, circuit hardening, and reliability management. Provides comprehensive review on various reliability mechanisms at sub-45nm nodes; Describes practical modeling and characterization techniques for reliability; Includes thorough presentation of robust design techniques for major VLSI design units; Promotes physical understanding with first-principle simulations.

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

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

International Nuclear Information System (INIS)

EI-Shanshoury, G.I.

2011-01-01

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

Value function in economic growth model

Science.gov (United States)

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.

An overview of erosion corrosion models and reliability assessment for corrosion defects in piping system

International Nuclear Information System (INIS)

Srividya, A.; Suresh, H.N.; Verma, A.K.; Gopika, V.; Santosh

2006-01-01

Piping systems are part of passive structural elements in power plants. The analysis of the piping systems and their quantification in terms of failure probability is of utmost importance. The piping systems may fail due to various degradation mechanisms like thermal fatigue, erosion-corrosion, stress corrosion cracking and vibration fatigue. On examination of previous results, erosion corrosion was more prevalent and wall thinning is a time dependent phenomenon. The paper is intended to consolidate the work done by various investigators on erosion corrosion in estimating the erosion corrosion rate and reliability predictions. A comparison of various erosion corrosion models is made. The reliability predictions based on remaining strength of corroded pipelines by wall thinning is also attempted. Variables in the limit state functions are modelled using normal distributions and Reliability assessment is carried out using some of the existing failure pressure models. A steady state corrosion rate is assumed to estimate the corrosion defect and First Order Reliability Method (FORM) is used to find the probability of failure associated with corrosion defects over time using the software for Component Reliability evaluation (COMREL). (author)

A Model of Controlled Growth

Science.gov (United States)

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.

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.

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 models for a nonrepairable system with heterogeneous components having a phase-type time-to-failure distribution

International Nuclear Information System (INIS)

Kim, Heungseob; Kim, Pansoo

2017-01-01

This research paper presents practical stochastic models for designing and analyzing the time-dependent reliability of nonrepairable systems. The models are formulated for nonrepairable systems with heterogeneous components having phase-type time-to-failure distributions by a structured continuous time Markov chain (CTMC). The versatility of the phase-type distributions enhances the flexibility and practicality of the systems. By virtue of these benefits, studies in reliability engineering can be more advanced than the previous studies. This study attempts to solve a redundancy allocation problem (RAP) by using these new models. The implications of mixing components, redundancy levels, and redundancy strategies are simultaneously considered to maximize the reliability of a system. An imperfect switching case in a standby redundant system is also considered. Furthermore, the experimental results for a well-known RAP benchmark problem are presented to demonstrate the approximating error of the previous reliability function for a standby redundant system and the usefulness of the current research. - Highlights: • Phase-type time-to-failure distribution is used for components. • Reliability model for nonrepairable system is developed using Markov chain. • System is composed of heterogeneous components. • Model provides the real value of standby system reliability not an approximation. • Redundancy allocation problem is used to show usefulness of this model.

Modeling error distributions of growth curve models through Bayesian methods.

Science.gov (United States)

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.

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.

Do downscaled general circulation models reliably simulate historical climatic conditions?

Science.gov (United States)

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

2018-01-01

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

On Latent Growth Models for Composites and Their Constituents.

Science.gov (United States)

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.

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.

A simulation model for reliability evaluation of Space Station power systems

Science.gov (United States)

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

1988-01-01

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

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.

Spatiotemporal Simulation of Tourist Town Growth Based on the Cellular Automata Model: The Case of Sanpo Town in Hebei Province

Directory of Open Access Journals (Sweden)

Jun Yang

2013-01-01

Full Text Available Spatiotemporal simulation of tourist town growth is important for research on land use/cover change under the influence of urbanization. Many scholars have shown great interest in the unique pattern of driving urban development with tourism development. Based on the cellular automata (CA model, we simulated and predicted the spatiotemporal growth of Sanpo town in Hebei Province, using the tourism urbanization growth model. Results showed that (1 average annual growth rate of the entire region was 1.5 Ha2 per year from 2005 to 2010, 4 Ha2 per year from 2010 to 2015, and 2.5 Ha2 per year from 2015 to 2020; (2 urban growth rate increased yearly, with regional differences, and had a high degree of correlation with the Euclidean distance of town center, traffic route, attractions, and other factors; (3 Gougezhuang, an important village center in the west of the town, demonstrated traffic advantages and increased growth rate since 2010; (4 Magezhuang village has the largest population in the region, so economic advantages have driven the development of rural urbanization. It showed that CA had high reliability in simulating the spatiotemporal evolution of tourist town, which assists the study of spatiotemporal growth under urbanization and rational protection of tourism resources.

Reliability analysis for wind turbines with incomplete failure data collected from after the date of initial installation

International Nuclear Information System (INIS)

Guo Haitao; Watson, Simon; Tavner, Peter; Xiang Jiangping

2009-01-01

Reliability has an impact on wind energy project costs and benefits. Both life test data and field failure data can be used for reliability analysis. In wind energy industry, wind farm operators have greater interest in recording wind turbine operating data. However, field failure data may be tainted or incomplete, and therefore it needs a more general mathematical model and algorithms to solve the model. The aim of this paper is to provide a solution to this problem. A three-parameter Weibull failure rate function is discussed for wind turbines and the parameters are estimated by maximum likelihood and least squares. Two populations of German and Danish wind turbines are analyzed. The traditional Weibull failure rate function is also employed for comparison. Analysis shows that the three-parameter Weibull function can obtain more accuracy on reliability growth of wind turbines. This work will be helpful in the understanding of the reliability growth of wind energy systems as wind energy technologies evolving. The proposed three-parameter Weibull function is also applicable to the life test of the components that have been used for a period of time, not only in wind energy but also in other industries

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

CERN Document Server

Nikulin, M; Mesbah, M; Limnios, N

2004-01-01

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

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

International Nuclear Information System (INIS)

Kallweit, A.; Schumacher, F.

1977-01-01

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

Reliability methods in nuclear power plant ageing management

International Nuclear Information System (INIS)

Simola, K.

1999-01-01

The aim of nuclear power plant ageing management is to maintain an adequate safety level throughout the lifetime of the plant. In ageing studies, the reliability of components, systems and structures is evaluated taking into account the possible time-dependent degradation. The phases of ageing analyses are generally the identification of critical components, identification and evaluation of ageing effects, and development of mitigation methods. This thesis focuses on the use of reliability methods and analyses of plant- specific operating experience in nuclear power plant ageing studies. The presented applications and method development have been related to nuclear power plants, but many of the approaches can also be applied outside the nuclear industry. The thesis consists of a summary and seven publications. The summary provides an overview of ageing management and discusses the role of reliability methods in ageing analyses. In the publications, practical applications and method development are described in more detail. The application areas at component and system level are motor-operated valves and protection automation systems, for which experience-based ageing analyses have been demonstrated. Furthermore, Bayesian ageing models for repairable components have been developed, and the management of ageing by improving maintenance practices is discussed. Recommendations for improvement of plant information management in order to facilitate ageing analyses are also given. The evaluation and mitigation of ageing effects on structural components is addressed by promoting the use of probabilistic modelling of crack growth, and developing models for evaluation of the reliability of inspection results. (orig.)

Reliability methods in nuclear power plant ageing management

Energy Technology Data Exchange (ETDEWEB)

Simola, K. [VTT Automation, Espoo (Finland). Industrial Automation

1999-07-01

The aim of nuclear power plant ageing management is to maintain an adequate safety level throughout the lifetime of the plant. In ageing studies, the reliability of components, systems and structures is evaluated taking into account the possible time-dependent degradation. The phases of ageing analyses are generally the identification of critical components, identification and evaluation of ageing effects, and development of mitigation methods. This thesis focuses on the use of reliability methods and analyses of plant- specific operating experience in nuclear power plant ageing studies. The presented applications and method development have been related to nuclear power plants, but many of the approaches can also be applied outside the nuclear industry. The thesis consists of a summary and seven publications. The summary provides an overview of ageing management and discusses the role of reliability methods in ageing analyses. In the publications, practical applications and method development are described in more detail. The application areas at component and system level are motor-operated valves and protection automation systems, for which experience-based ageing analyses have been demonstrated. Furthermore, Bayesian ageing models for repairable components have been developed, and the management of ageing by improving maintenance practices is discussed. Recommendations for improvement of plant information management in order to facilitate ageing analyses are also given. The evaluation and mitigation of ageing effects on structural components is addressed by promoting the use of probabilistic modelling of crack growth, and developing models for evaluation of the reliability of inspection results. (orig.)

Power transformer reliability modelling

NARCIS (Netherlands)

Schijndel, van A.

2010-01-01

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

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.

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.

Model uncertainty in growth empirics

NARCIS (Netherlands)

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

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

Assessing reliability of fatigue indicator parameters for small crack growth via a probabilistic framework

Science.gov (United States)

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.

Reliability modeling of degradation of products with multiple performance characteristics based on gamma processes

International Nuclear Information System (INIS)

Pan Zhengqiang; Balakrishnan, Narayanaswamy

2011-01-01

Many highly reliable products usually have complex structure, with their reliability being evaluated by two or more performance characteristics. In certain physical situations, the degradation of these performance characteristics would be always positive and strictly increasing. In such a case, the gamma process is usually considered as a degradation process due to its independent and non-negative increments properties. In this paper, we suppose that a product has two dependent performance characteristics and that their degradation can be modeled by gamma processes. For such a bivariate degradation involving two performance characteristics, we propose to use a bivariate Birnbaum-Saunders distribution and its marginal distributions to approximate the reliability function. Inferential method for the corresponding model parameters is then developed. Finally, for an illustration of the proposed model and method, a numerical example about fatigue cracks is discussed and some computational results are presented.

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

International Nuclear Information System (INIS)

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

2017-01-01

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

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...

Development of Probabilistic Reliability Models of Photovoltaic System Topologies for System Adequacy Evaluation

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.

Calculating system reliability with SRFYDO

Energy Technology Data Exchange (ETDEWEB)

Morzinski, Jerome [Los Alamos National Laboratory; Anderson - Cook, Christine M [Los Alamos National Laboratory; Klamann, Richard M [Los Alamos National Laboratory

2010-01-01

SRFYDO is a process for estimating reliability of complex systems. Using information from all applicable sources, including full-system (flight) data, component test data, and expert (engineering) judgment, SRFYDO produces reliability estimates and predictions. It is appropriate for series systems with possibly several versions of the system which share some common components. It models reliability as a function of age and up to 2 other lifecycle (usage) covariates. Initial output from its Exploratory Data Analysis mode consists of plots and numerical summaries so that the user can check data entry and model assumptions, and help determine a final form for the system model. The System Reliability mode runs a complete reliability calculation using Bayesian methodology. This mode produces results that estimate reliability at the component, sub-system, and system level. The results include estimates of uncertainty, and can predict reliability at some not-too-distant time in the future. This paper presents an overview of the underlying statistical model for the analysis, discusses model assumptions, and demonstrates usage of SRFYDO.

Reliability and Validity of a Spanish Version of the Posttraumatic Growth Inventory

Science.gov (United States)

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.…

Detecting Growth Shape Misspecifications in Latent Growth Models: An Evaluation of Fit Indexes

Science.gov (United States)

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…

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....

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.

QA support for TFTR reliability improvement program in preparation for DT operation

International Nuclear Information System (INIS)

Parsells, R.F.; Howard, H.P.

1987-01-01

As TFTR approaches experiments in the Q=1 regime, machine reliability becomes a major variable in achieving experimental objectives. This paper describes the methods used to quantify current reliability levels, levels required for D-T operations, proposed methods for reliability growth and improvement, and tracking of reliability performance in that growth. Included in this scope are data collection techniques and short comings, bounding current reliability on the upper end, and requirements for D-T operations. Problem characterization through Pareto diagrams provides insight into recurrent failure modes and the use of Duane plots for charting of reliability changes both cumulative and instantaneous, is explained and demonstrated

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

International Nuclear Information System (INIS)

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

2012-01-01

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

Modeling urban fire growth

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

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

DEFF Research Database (Denmark)

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

2002-01-01

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

Neo-logistic model for the growth of bacteria

OpenAIRE

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...

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)

Modelling of nuclear power plant control and instrumentation elements for automatic disturbance and reliability analysis

International Nuclear Information System (INIS)

Hollo, E.

1985-08-01

Present Final Report summarizes results of R/D work done within IAEA-VEIKI (Institute for Electrical Power Research, Budapest, Hungary) Research Contract No. 3210 during 3 years' period of 01.08.1982 - 31.08.1985. Chapter 1 lists main research objectives of the project. Main results obtained are summarized in Chapters 2 and 3. Outcomes from development of failure modelling methodologies and their application for C/I components of WWER-440 units are as follows (Chapter 2): improvement of available ''failure mode and effect analysis'' methods and mini-fault tree structures usable for automatic disturbance (DAS) and reliability (RAS) analysis; general classification and determination of functional failure modes of WWER-440 NPP C/I components; set up of logic models for motor operated control valves and rod control/drive mechanism. Results of development of methods and their application for reliability modelling of NPP components and systems cover (Chapter 3): development of an algorithm (computer code COMPREL) for component-related failure and reliability parameter calculation; reliability analysis of PAKS II NPP diesel system; definition of functional requirements for reliability data bank (RDB) in WWER-440 units. Determination of RDB input/output data structure and data manipulation services. Methods used are a-priori failure mode and effect analysis, combined fault tree/event tree modelling technique, structural computer programming, probability theory application to nuclear field

Using the Weibull distribution reliability, modeling and inference

CERN Document Server

McCool, John I

2012-01-01

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

Power electronics reliability analysis.

Energy Technology Data Exchange (ETDEWEB)

Smith, Mark A.; Atcitty, Stanley

2009-12-01

This report provides the DOE and industry with a general process for analyzing power electronics reliability. The analysis can help with understanding the main causes of failures, downtime, and cost and how to reduce them. One approach is to collect field maintenance data and use it directly to calculate reliability metrics related to each cause. Another approach is to model the functional structure of the equipment using a fault tree to derive system reliability from component reliability. Analysis of a fictitious device demonstrates the latter process. Optimization can use the resulting baseline model to decide how to improve reliability and/or lower costs. It is recommended that both electric utilities and equipment manufacturers make provisions to collect and share data in order to lay the groundwork for improving reliability into the future. Reliability analysis helps guide reliability improvements in hardware and software technology including condition monitoring and prognostics and health management.

Non-linear Growth Models in Mplus and SAS

Science.gov (United States)

Grimm, Kevin J.; Ram, Nilam

2013-01-01

Non-linear growth curves or growth curves that follow a specified non-linear function in time enable researchers to model complex developmental patterns with parameters that are easily interpretable. In this paper we describe how a variety of sigmoid curves can be fit using the Mplus structural modeling program and the non-linear mixed-effects modeling procedure NLMIXED in SAS. Using longitudinal achievement data collected as part of a study examining the effects of preschool instruction on academic gain we illustrate the procedures for fitting growth models of logistic, Gompertz, and Richards functions. Brief notes regarding the practical benefits, limitations, and choices faced in the fitting and estimation of such models are included. PMID:23882134

Reliability of Soft Tissue Model Based Implant Surgical Guides; A Methodological Mistake.

Science.gov (United States)

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

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.

Simulating Urban Growth Using a Random Forest-Cellular Automata (RF-CA Model

Directory of Open Access Journals (Sweden)

Courage Kamusoko

2015-04-01

Full Text Available Sustainable urban planning and management require reliable land change models, which can be used to improve decision making. The objective of this study was to test a random forest-cellular automata (RF-CA model, which combines random forest (RF and cellular automata (CA models. The Kappa simulation (KSimulation, figure of merit, and components of agreement and disagreement statistics were used to validate the RF-CA model. Furthermore, the RF-CA model was compared with support vector machine cellular automata (SVM-CA and logistic regression cellular automata (LR-CA models. Results show that the RF-CA model outperformed the SVM-CA and LR-CA models. The RF-CA model had a Kappa simulation (KSimulation accuracy of 0.51 (with a figure of merit statistic of 47%, while SVM-CA and LR-CA models had a KSimulation accuracy of 0.39 and −0.22 (with figure of merit statistics of 39% and 6%, respectively. Generally, the RF-CA model was relatively accurate at allocating “non-built-up to built-up” changes as reflected by the correct “non-built-up to built-up” components of agreement of 15%. The performance of the RF-CA model was attributed to the relatively accurate RF transition potential maps. Therefore, this study highlights the potential of the RF-CA model for simulating urban growth.

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

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.

United States geological survey's reserve-growth models and their implementation

Science.gov (United States)

Klett, T.R.

2005-01-01

The USGS has developed several mathematical models to forecast reserve growth of fields both in the United States (U.S.) and the world. The models are based on historical reserve growth patterns of fields in the U.S. The patterns of past reserve growth are extrapolated to forecast future reserve growth. Changes of individual field sizes through time are extremely variable, therefore, the reserve growth models take on a statistical approach whereby volumetric changes for populations of fields are used in the models. Field age serves as a measure of the field-development effort that is applied to promote reserve growth. At the time of the USGS World Petroleum Assessment 2000, a reserve growth model for discovered fields of the world was not available. Reserve growth forecasts, therefore, were made based on a model of historical reserve growth of fields of the U.S. To test the feasibility of such an application, reserve growth forecasts were made of 186 giant oil fields of the world (excluding the U.S. and Canada). In addition, forecasts were made for these giant oil fields subdivided into those located in and outside of Organization of Petroleum Exporting Countries (OPEC). The model provided a reserve-growth forecast that closely matched the actual reserve growth that occurred from 1981 through 1996 for the 186 fields as a whole, as well as for both OPEC and non-OPEC subdivisions, despite the differences in reserves definition among the fields of the U.S. and the rest of the world. ?? 2005 International Association for Mathematical Geology.

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.

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 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)

Measuring reliability under epistemic uncertainty: Review on non-probabilistic reliability metrics

Directory of Open Access Journals (Sweden)

Kang Rui

2016-06-01

Full Text Available In this paper, a systematic review of non-probabilistic reliability metrics is conducted to assist the selection of appropriate reliability metrics to model the influence of epistemic uncertainty. Five frequently used non-probabilistic reliability metrics are critically reviewed, i.e., evidence-theory-based reliability metrics, interval-analysis-based reliability metrics, fuzzy-interval-analysis-based reliability metrics, possibility-theory-based reliability metrics (posbist reliability and uncertainty-theory-based reliability metrics (belief reliability. It is pointed out that a qualified reliability metric that is able to consider the effect of epistemic uncertainty needs to (1 compensate the conservatism in the estimations of the component-level reliability metrics caused by epistemic uncertainty, and (2 satisfy the duality axiom, otherwise it might lead to paradoxical and confusing results in engineering applications. The five commonly used non-probabilistic reliability metrics are compared in terms of these two properties, and the comparison can serve as a basis for the selection of the appropriate reliability metrics.

Assessing allometric models to predict vegetative growth of mango (Mangifera indica; Anacardiaceae) at the current-year branch scale.

Science.gov (United States)

Normand, Frédéric; Lauri, Pierre-Éric

2012-03-01

Accurate and reliable predictive models are necessary to estimate nondestructively key variables for plant growth studies such as leaf area and leaf, stem, and total biomass. Predictive models are lacking at the current-year branch scale despite the importance of this scale in plant science. We calibrated allometric models to estimate leaf area and stem and branch (leaves + stem) mass of current-year branches, i.e., branches several months old studied at the end of the vegetative growth season, of four mango cultivars on the basis of their basal cross-sectional area. The effects of year, site, and cultivar were tested. Models were validated with independent data and prediction accuracy was evaluated with the appropriate statistics. Models revealed a positive allometry between dependent and independent variables, whose y-intercept but not the slope, was affected by the cultivar. The effects of year and site were negligible. For each branch characteristic, cultivar-specific models were more accurate than common models built with pooled data from the four cultivars. Prediction quality was satisfactory but with data dispersion around the models, particularly for large values. Leaf area and stem and branch mass of mango current-year branches could be satisfactorily estimated on the basis of branch basal cross-sectional area with cultivar-specific allometric models. The results suggested that, in addition to the heteroscedastic behavior of the variables studied, model accuracy was probably related to the functional plasticity of branches in relation to the light environment and/or to the number of growth units composing the branches.

A dynamic discretization method for reliability inference in Dynamic Bayesian Networks

International Nuclear Information System (INIS)

Zhu, Jiandao; Collette, Matthew

2015-01-01

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

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.

In silico modeling for tumor growth visualization.

Science.gov (United States)

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.

Bridging process-based and empirical approaches to modeling tree growth

Science.gov (United States)

Harry T. Valentine; Annikki Makela; Annikki Makela

2005-01-01

The gulf between process-based and empirical approaches to modeling tree growth may be bridged, in part, by the use of a common model. To this end, we have formulated a process-based model of tree growth that can be fitted and applied in an empirical mode. The growth model is grounded in pipe model theory and an optimal control model of crown development. Together, the...

Regression models for linking patterns of growth to a later outcome: infant growth and childhood overweight

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

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.

A reliability-based maintenance technicians' workloads optimisation model with stochastic consideration

Science.gov (United States)

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.

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

A Reliability Model for Ni-BaTiO3-Based (BME) Ceramic Capacitors

Science.gov (United States)

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

Prediction of safety critical software operational reliability from test reliability using testing environment factors

International Nuclear Information System (INIS)

Jung, Hoan Sung; Seong, Poong Hyun

1999-01-01

It has been a critical issue to predict the safety critical software reliability in nuclear engineering area. For many years, many researches have focused on the quantification of software reliability and there have been many models developed to quantify software reliability. Most software reliability models estimate the reliability with the failure data collected during the test assuming that the test environments well represent the operation profile. User's interest is however on the operational reliability rather than on the test reliability. The experiences show that the operational reliability is higher than the test reliability. With the assumption that the difference in reliability results from the change of environment, from testing to operation, testing environment factors comprising the aging factor and the coverage factor are developed in this paper and used to predict the ultimate operational reliability with the failure data in testing phase. It is by incorporating test environments applied beyond the operational profile into testing environment factors. The application results show that the proposed method can estimate the operational reliability accurately. (Author). 14 refs., 1 tab., 1 fig

Extended object-oriented Petri net model for mission reliability simulation of repairable PMS with common cause failures

International Nuclear Information System (INIS)

Wu, Xin-yang; Wu, Xiao-Yue

2015-01-01

Phased Mission Systems (PMS) have several phases with different success criteria. Generally, traditional analytical methods need to make some assumptions when they are applied for reliability evaluation and analysis of complex PMS, for example, the components are non-repairable or components are not subjected to common cause failures (CCF). However, the evaluation and analysis results may be inapplicable when the assumptions do not agree with practical situation. In this article, we propose an extended object-oriented Petri net (EOOPN) model for mission reliability simulation of repairable PMS with CCFs. Based on object-oriented Petri net (OOPN), EOOPN defines four reusable sub-models to depict PMS at system, phase, or component levels respectively, logic transitions to depict complex components reliability logics in a more readable form, and broadcast place to transmit shared information among components synchronously. After extension, EOOPN could deal with repairable PMS with both external and internal CCFs conveniently. The mission reliability modelling, simulation and analysis using EOOPN are illustrated by a PMS example. The results demonstrate that the proposed EOOPN model is effective. - Highlights: • EOOPN model was effective in reliability simulation for repairable PMS with CCFs. • EOOPN had modular and hierarchical structure. • New elements of EOOPN made the modelling process more convenient and friendlier. • EOOPN had better model reusability and readability than other PNs

Balanced growth path solutions of a Boltzmann mean field game model for knowledge growth

KAUST Repository

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.

Modeling the effects of ozone on soybean growth and yield.

Science.gov (United States)

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.

Plant Growth Modeling Using L-System Approach and Its Visualization

Directory of Open Access Journals (Sweden)

Atris Suyantohadi

2011-05-01

Full Text Available The visualizationof plant growth modeling using computer simulation has rarely been conducted with Lindenmayer System (L-System approach. L-System generally has been used as framework for improving and designing realistic modeling on plant growth. It is one kind of tools for representing plant growth based on grammar sintax and mathematic formulation. This research aimed to design modeling and visualizing plant growth structure generated using L-System. The environment on modeling design used three dimension graphic on standart OpenGL format. The visualization on system design has been developed by some of L-System grammar, and the output graphic on three dimension reflected on plant growth as a virtual plant growth system. Using some of samples on grammar L-System rules for describing of the charaterictics of plant growth, the visualization of structure on plant growth has been resulted and demonstrated.

Knowledge modelling and reliability processing: presentation of the Figaro language and associated tools

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

Reliability Assessment Of Wind Turbines

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard

2014-01-01

Reduction of cost of energy for wind turbines are very important in order to make wind energy competitive compared to other energy sources. Therefore the turbine components should be designed to have sufficient reliability but also not be too costly (and safe). This paper presents models...... for uncertainty modeling and reliability assessment of especially the structural components such as tower, blades, substructure and foundation. But since the function of a wind turbine is highly dependent on many electrical and mechanical components as well as a control system also reliability aspects...... of these components are discussed and it is described how there reliability influences the reliability of the structural components. Two illustrative examples are presented considering uncertainty modeling, reliability assessment and calibration of partial safety factors for structural wind turbine components exposed...

A new lifetime estimation model for a quicker LED reliability prediction

Science.gov (United States)

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.

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...

Reliability Analysis of Sealing Structure of Electromechanical System Based on Kriging Model

Science.gov (United States)

Zhang, F.; Wang, Y. M.; Chen, R. W.; Deng, W. W.; Gao, Y.

2018-05-01

The sealing performance of aircraft electromechanical system has a great influence on flight safety, and the reliability of its typical seal structure is analyzed by researcher. In this paper, we regard reciprocating seal structure as a research object to study structural reliability. Having been based on the finite element numerical simulation method, the contact stress between the rubber sealing ring and the cylinder wall is calculated, and the relationship between the contact stress and the pressure of the hydraulic medium is built, and the friction force on different working conditions are compared. Through the co-simulation, the adaptive Kriging model obtained by EFF learning mechanism is used to describe the failure probability of the seal ring, so as to evaluate the reliability of the sealing structure. This article proposes a new idea of numerical evaluation for the reliability analysis of sealing structure, and also provides a theoretical basis for the optimal design of sealing structure.

The precision and reliability evaluation of 3-dimensional printed damaged bone and prosthesis models by stereo lithography appearance.

Science.gov (United States)

Zou, Yun; Han, Qing; Weng, Xisheng; Zou, Yongwei; Yang, Yingying; Zhang, Kesong; Yang, Kerong; Xu, Xiaolin; Wang, Chenyu; Qin, Yanguo; Wang, Jincheng

2018-02-01

Recently, clinical application of 3D printed model was increasing. However, there was no systemic study for confirming the precision and reliability of 3D printed model. Some senior clinical doctors mistrusted its reliability in clinical application. The purpose of this study was to evaluate the precision and reliability of stereolithography appearance (SLA) 3D printed model.Some related parameters were selected to research the reliability of SLA 3D printed model. The computed tomography (CT) data of bone/prosthesis and model were collected and 3D reconstructed. Some anatomical parameters were measured and statistical analysis was performed; the intraclass correlation coefficient (ICC) was used to was used to evaluate the similarity between the model and real bone/prosthesis. the absolute difference (mm) and relative difference (%) were conducted. For prosthesis model, the 3-dimensional error was measured.There was no significant difference in the anatomical parameters except max height (MH) of long bone. All the ICCs were greater than 0.990. The maximum absolute and relative difference were 0.45 mm and 1.10%; The 3-dimensional error analysis showed that positive/minus distance were 0.273 mm/0.237 mm.The application of SLA 3D printed model in diagnosis and treatment process of complex orthopedic disease was reliable and precise.

Understanding software faults and their role in software reliability modeling

Science.gov (United States)

Munson, John C.

1994-01-01

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

A reliability model for interlayer dielectric cracking during fast thermal cycling

NARCIS (Netherlands)

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).

Reliable gain-scheduled control of discrete-time systems and its application to CSTR model

Science.gov (United States)

Sakthivel, R.; Selvi, S.; Mathiyalagan, K.; Shi, Y.

2016-10-01

This paper is focused on reliable gain-scheduled controller design for a class of discrete-time systems with randomly occurring nonlinearities and actuator fault. Further, the nonlinearity in the system model is assumed to occur randomly according to a Bernoulli distribution with measurable time-varying probability in real time. The main purpose of this paper is to design a gain-scheduled controller by implementing a probability-dependent Lyapunov function and linear matrix inequality (LMI) approach such that the closed-loop discrete-time system is stochastically stable for all admissible randomly occurring nonlinearities. The existence conditions for the reliable controller is formulated in terms of LMI constraints. Finally, the proposed reliable gain-scheduled control scheme is applied on continuously stirred tank reactor model to demonstrate the effectiveness and applicability of the proposed design technique.

A mathematical model of microalgae growth in cylindrical photobioreactor

Science.gov (United States)

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.

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

DEFF Research Database (Denmark)

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

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

Probabilistic modeling of fatigue crack growth in Ti-6Al-4V

International Nuclear Information System (INIS)

Soboyejo, W.O.; Shen, W.; Soboyejo, A.B.O.

2001-01-01

This paper presents the results of a combined experimental and analytical study of the probabilistic nature of fatigue crack growth in Ti-6Al-4V. A simple experimental fracture mechanics framework is presented for the determination of statistical fatigue crack growth parameters from two fatigue tests. The experimental studies show that the variabilities in long fatigue crack growth rate data and the Paris coefficient are well described by the log-normal distributions. The variabilities in the Paris exponent are also shown to be well characterized by a normal distribution. The measured statistical distributions are incorporated into a probabilistic fracture mechanics framework for the estimation of material reliability. The implications of the results are discussed for the probabilistic analysis of fatigue crack growth in engineering components and structures. (orig.)

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

Localisation in a Growth Model with Interaction

Science.gov (United States)

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.

PV Systems Reliability Final Technical Report.

Energy Technology Data Exchange (ETDEWEB)

Lavrova, Olga [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Flicker, Jack David [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Johnson, Jay [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Armijo, Kenneth Miguel [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Gonzalez, Sigifredo [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Schindelholz, Eric John [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Sorensen, Neil R. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Yang, Benjamin Bing-Yeh [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-12-01

The continued exponential growth of photovoltaic technologies paves a path to a solar-powered world, but requires continued progress toward low-cost, high-reliability, high-performance photovoltaic (PV) systems. High reliability is an essential element in achieving low-cost solar electricity by reducing operation and maintenance (O&M) costs and extending system lifetime and availability, but these attributes are difficult to verify at the time of installation. Utilities, financiers, homeowners, and planners are demanding this information in order to evaluate their financial risk as a prerequisite to large investments. Reliability research and development (R&D) is needed to build market confidence by improving product reliability and by improving predictions of system availability, O&M cost, and lifetime. This project is focused on understanding, predicting, and improving the reliability of PV systems. The two areas being pursued include PV arc-fault and ground fault issues, and inverter reliability.

Using the graphs models for evaluating in-core monitoring systems reliability by the method of imiting simulaton

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

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

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

DEFF Research Database (Denmark)

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

2010-01-01

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

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.

Science.gov (United States)

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.

Investigation of Mediational Processes Using Parallel Process Latent Growth Curve Modeling

Science.gov (United States)

Cheong, JeeWon; MacKinnon, David P.; Khoo, Siek Toon

2010-01-01

This study investigated a method to evaluate mediational processes using latent growth curve modeling. The mediator and the outcome measured across multiple time points were viewed as 2 separate parallel processes. The mediational process was defined as the independent variable influencing the growth of the mediator, which, in turn, affected the growth of the outcome. To illustrate modeling procedures, empirical data from a longitudinal drug prevention program, Adolescents Training and Learning to Avoid Steroids, were used. The program effects on the growth of the mediator and the growth of the outcome were examined first in a 2-group structural equation model. The mediational process was then modeled and tested in a parallel process latent growth curve model by relating the prevention program condition, the growth rate factor of the mediator, and the growth rate factor of the outcome. PMID:20157639

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.

Tax Evasion in a Model of Endogenous Growth

OpenAIRE

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...

Cellular Automaton Modeling of Dendritic Growth Using a Multi-grid Method

International Nuclear Information System (INIS)

Natsume, Y; Ohsasa, K

2015-01-01

A two-dimensional cellular automaton model with a multi-grid method was developed to simulate dendritic growth. In the present model, we used a triple-grid system for temperature, solute concentration and solid fraction fields as a new approach of the multi-grid method. In order to evaluate the validity of the present model, we carried out simulations of single dendritic growth, secondary dendrite arm growth, multi-columnar dendritic growth and multi-equiaxed dendritic growth. From the results of the grid dependency from the simulation of single dendritic growth, we confirmed that the larger grid can be used in the simulation and that the computational time can be reduced dramatically. In the simulation of secondary dendrite arm growth, the results from the present model were in good agreement with the experimental data and the simulated results from a phase-field model. Thus, the present model can quantitatively simulate dendritic growth. From the simulated results of multi-columnar and multi-equiaxed dendrites, we confirmed that the present model can perform simulations under practical solidification conditions. (paper)

Nonlinear Growth Models in M"plus" and SAS

Science.gov (United States)

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…

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

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.

Stochastic network interdiction optimization via capacitated network reliability modeling and probabilistic solution discovery

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

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

Science.gov (United States)

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

2018-01-01

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

Reliability assessment of hydraulic cylinders considering service loads and flaw distribution

International Nuclear Information System (INIS)

Altamura, Alessandra; Beretta, Stefano

2012-01-01

Manufacturing process, service conditions and material properties are all necessary requirements to a good design of tubular mechanical components subjected to fatigue. The most common approach to this design is usually deterministic, where a fixed NDT threshold, related to flaw acceptance limit, is set. However many uncertainties are left aside, i.e. the failure probability related to the fatigue strength under applied loads. This paper addresses the reliability evaluation of tubular mechanical components carrying some flaws and subjected to cyclic internal pressure variation. The aim is comparing the probability of failure obtained under several assumptions. A reliability assessment model, based on a random variable approach, has been implemented by using the Monte Carlo method. The analysis of the results, from a case study based on load spectra measurements of hydraulic cylinders of earth moving machines, has consented to evaluate the most important factors influencing the fatigue life prediction of these components. Highlights: ► Reliability evaluation of tubular components subjected to variable internal pressure. ► The dispersion of the threshold controls the stochasticity of crack growth. ► A random variable model has been developed using Monte Carlo. ► Initial crack size and spectrum shape are key factors in reliability evaluation.

Reliability and protection against failure in computer systems

International Nuclear Information System (INIS)

Daniels, B.K.

1979-01-01

Computers are being increasingly integrated into the control and safety systems of large and potentially hazardous industrial processes. This development introduces problems which are particular to computer systems and opens the way to new techniques of solving conventional reliability and availability problems. References to the developing fields of software reliability, human factors and software design are given, and these subjects are related, where possible, to the quantified assessment of reliability. Original material is presented in the areas of reliability growth and computer hardware failure data. The report draws on the experience of the National Centre of Systems Reliability in assessing the capability and reliability of computer systems both within the nuclear industry, and from the work carried out in other industries by the Systems Reliability Service. (author)

Stochastic modelling of avascular tumour growth and therapy

International Nuclear Information System (INIS)

Sahoo, S; Sahoo, A; Shearer, S F C

2011-01-01

In this paper, a generalized stochastic model for the growth of avascular tumours is presented. This model captures the dynamical evolution of avascular tumour cell subpopulations by incorporating Gaussian white noise into the growth rate of the mitotic function. This work generalizes the deterministic model proposed by Sherratt and Chaplain (2001 J. Math. Biol. 43 291) where they formulated a tumour model in an in vivo setting, in terms of continuum densities of proliferating, quiescent and necrotic cells. Detailed simulations of our model show that the inclusion of Gaussian noise in the original model of Sherratt and Chaplain substantially distorts the overall structure of the density profiles in addition to reducing the speed of tumour growth. Within this stochastic carcinogenesis framework the action of therapy is also investigated by replacing Gaussian white noise with a therapy term. We compare a constant therapy protocol with a logarithmic time-dependent protocol. Our results predict that a logarithmic therapy is more effective than the constant therapy protocol.

System principles, mathematical models and methods to ensure high reliability of safety systems

Science.gov (United States)

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.

Surface-bounded growth modeling applied to human mandibles

DEFF Research Database (Denmark)

Andresen, Per Rønsholt

1999-01-01

This thesis presents mathematical and computational techniques for three dimensional growth modeling applied to human mandibles. The longitudinal shape changes make the mandible a complex bone. The teeth erupt and the condylar processes change direction, from pointing predominantly backward...... of the common features. 3.model the process that moves the matched points (growth modeling). A local shape feature called crest line has shown itself to be structurally stable on mandibles. Registration of crest lines (from different mandibles) results in a sparse deformation field, which must be interpolated...... old mandible based on the 3 month old scan. When using successively more recent scans as basis for the model the error drops to 2.0 mm for the 11 years old scan. Thus, it seems reasonable to assume that the mandibular growth is linear....

Discrete Address Beacon System (DABS) Software System Reliability Modeling and Prediction.

Science.gov (United States)

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 Curve Models and Applications : Indian Statistical Institute

CERN Document Server

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...

Selection, calibration, and validation of models of tumor growth.

Science.gov (United States)

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

Development of reliable pavement models.

Science.gov (United States)

2011-05-01

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

A mathematical model of the growth of uterine myomas.

Science.gov (United States)

Chen, C Y; Ward, J P

2014-12-01

Uterine myomas or fibroids are common, benign smooth muscle tumours that can grow to 10  cm or more in diameter and are routinely removed surgically. They are typically slow- growing, well-vascularised, spherical tumours that, on a macro-scale, are a structurally uniform, hard elastic material. We present a multi-phase mathematical model of a fully vascularised myoma growing within a surrounding elastic tissue. Adopting a continuum approach, the model assumes the conservation of mass and momentum of four phases, namely cells/collagen, extracellular fluid, arterial and venous phases. The cell/collagen phase is treated as a poro-elastic material, based on a linear stress-strain relationship, and Darcy's law is applied to describe flow in the extracellular fluid and the two vascular phases. The supply of extracellular fluid is dependent on the capillary flow rate and mean capillary pressure expressed in terms of the arterial and venous pressures. Cell growth and division is limited to the myoma domain and dependent on the local stress in the material. The resulting model consists of a system of nonlinear partial differential equations with two moving boundaries. Numerical solutions of the model successfully reproduce qualitatively the clinically observed three-phase "fast-slow-fast" growth profile that is typical for myomas. The results suggest that this growth profile requires stress-induced resistance to growth by the surrounding tissue and a switch-like cell growth response to stress. Analysis of large-time solutions reveal that while there is a functioning vasculature throughout the myoma, exponential growth results, otherwise power-law growth is predicted. An extensive survey of the effect of parameters on model solutions is also presented, and in particular, the enhanced growth caused by factors such as oestrogen is predicted by the model.

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-O₂ 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.

Parameter Estimates in Differential Equation Models for Population Growth

Science.gov (United States)

Winkel, Brian J.

2011-01-01

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

Reliable low precision simulations in land surface models

Science.gov (United States)

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

2017-12-01

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