Reliability Estimation of Open Source Software based Computational Systems

Software systems are progressively being deployed in many facets of human life. The implication of the failure of such systems, has an assorted impact on its customers. The fundamental aspect that supports a software system, is focus on quality. Reliability describes the ability of the system to function under specified environment for a specified period of time and is used to objectively measure the quality. Evaluation of reliability of a computing system involves computation of hardware and software reliability. Most of the earlier works were given focus on software reliability with no consideration for hardware parts or vice versa. However, a complete estimation of reliability of a computing system requires these two elements to be considered together, and thus demands a combined approach. The present work focuses on this and presents a model for evaluating the reliability of a computing system. The method involves identifying the failure data for hardware components, software components and building a model based on it, to predict the reliability. To develop such a model, focus is given to the systems based on Open Source Software, since there is an increasing trend towards its use and only a few studies were reported on the modeling and measurement of the reliability of such products. The present work includes a thorough study on the role of Free and Open Source Software, evaluation of reliability growth models, and is trying to present an integrated model for the prediction of reliability of a computational system. The developed model has been compared with existing models and its usefulness of is being discussed.

The cross-entropy method for network reliability estimation

Consider a network of unreliable links, modelling for example a communication network. Estimating the reliability of the network-expressed as the probability that certain nodes in the network are connected-is a computationally difficult task. In this paper we study how the Cross-Entropy method can be used to obtain more efficient network reliability estimation procedures. Three techniques of estimation are considered: Crude Monte Carlo and the more sophisticated Permutation Monte Carlo and Merge Process. We show that the Cross-Entropy method yields a speed-up over all three techniques.

Reliability estimation of second life battery system power electronic topologies for grid frequency response applications

This paper is part of a project which aims to research the opportunities for the re-use of batteries after their primary use in low and ultra low carbon vehicles on the electricity grid system. One potential revenue stream is to provide primary/secondary/high frequency response to National Grid through market mechanisms via DNO's or Energy service providers. Some commercial battery energy storage systems (BESS) already exist on the grid system, but these tend to use costly new or high performance batteries. Second life batteries should be available at lower cost than new batteries but reliability becomes an important issue as individual batteries may suffer from degraded performance or failure. Therefore converter topology design could be used to influence the overall system reliability. A detailed reliability calculation of different single phase battery-to-grid converter interfacing schemes is presented. A suitable converter topology for robust and reliable BESS is recommended.

Reliability analysis with suspended items

Reliability analysis has several important engineering applications. Designers and operators of equipment are often interested in the probability of the equipment operating successfully to a given age - this probability is known as the equipment's reliability at that age. Reliability information is also important to those charged with maintaining an item of equipment, as it enables them to model and evaluate alternative maintenance policies for the equipment. In each case, information on failures and survivals of a typical sample of items is used to estimate the required probabilities as a function of the item's age, this process being one of many applications of the statistical techniques known as distribution fitting. In most engineering applications, the estimation procedure must deal with samples containing survivors (suspensions or censorings); this thesis focuses on several graphical estimation methods that are widely used for analysing such samples. Although these methods have been current for many years, they share a common shortcoming: none of them is continuously sensitive to changes in the ages of the suspensions, and we show that the resulting reliability estimates are therefore more pessimistic than necessary. We use a simple example to show that the existing graphical methods take no account of any service recorded by suspensions beyond their respective previous failures, and that this behaviour is inconsistent with one's intuitive expectations. In the course of this thesis, we demonstrate that the existing methods are only justified under restricted conditions. We present several improved methods and demonstrate that each of them overcomes the problem described above, while reducing to one of the existing methods where this is justified. Each of the improved methods thus provides a realistic set of reliability estimates for general (unrestricted) censored samples. Several related variations on these improved methods are also presented and justified. - i

System reliability of randomly vibrating structures: Computational modeling and laboratory testing

The problem of determination of system reliability of randomly vibrating structures arises in many application areas of engineering. We discuss in this paper approaches based on Monte Carlo simulations and laboratory testing to tackle problems of time variant system reliability estimation. The strategy we adopt is based on the application of Girsanov's transformation to the governing stochastic differential equations which enables estimation of probability of failure with significantly reduced number of samples than what is needed in a direct simulation study. Notably, we show that the ideas from Girsanov's transformation based Monte Carlo simulations can be extended to conduct laboratory testing to assess system reliability of engineering structures with reduced number of samples and hence with reduced testing times. Illustrative examples include computational studies on a 10 degree of freedom nonlinear system model and laboratory/computational investigations on road load response of an automotive system tested on a four post Lest rig. (C) 2015 Elsevier Ltd. All rights reserved.

Integrated health prediction of bridge systems using dynamic object oriented Bayesian networks (DOOBNS)

The serviceability and safety of bridges are crucial to people’s daily lives and to the national economy. Every effort should be taken to make sure that bridges function safely and properly as any damage or fault during the service life can lead to transport paralysis, catastrophic loss of property or even casualties. Nonetheless, aggressive environmental conditions, ever-increasing and changing traffic loads and aging can all contribute to bridge deterioration. With often constrained budget, it is of significance to identify bridges and bridge elements that should be given higher priority for maintenance, rehabilitation or replacement, and to select optimal strategy. Bridge health prediction is an essential underpinning science to bridge maintenance optimization, since the effectiveness of optimal maintenance decision is largely dependent on the forecasting accuracy of bridge health performance. The current approaches for bridge health prediction can be categorised into two groups: condition ratings based and structural reliability based. A comprehensive literature review has revealed the following limitations of the current modelling approaches: (1) it is not evident in literature to date that any integrated approaches exist for modelling both serviceability and safety aspects so that both performance criteria can be evaluated coherently; (2) complex system modelling approaches have not been successfully applied to bridge deterioration modelling though a bridge is a complex system composed of many inter-related bridge elements; (3) multiple bridge deterioration factors, such as deterioration dependencies among different bridge elements, observed information, maintenance actions and environmental effects have not been considered jointly; (4) the existing approaches are lacking in Bayesian updating ability to incorporate a variety of event information; (5) the assumption of series and/or parallel relationship for bridge level reliability is always held in all structural reliability estimation of bridge systems. To address the deficiencies listed above, this research proposes three novel models based on the Dynamic Object Oriented Bayesian Networks (DOOBNs) approach. Model I aims to address bridge deterioration in serviceability using condition ratings as the health index. The bridge deterioration is represented in a hierarchical relationship, in accordance with the physical structure, so that the contribution of each bridge element to bridge deterioration can be tracked. A discrete-time Markov process is employed to model deterioration of bridge elements over time. In Model II, bridge deterioration in terms of safety is addressed. The structural reliability of bridge systems is estimated from bridge elements to the entire bridge. By means of conditional probability tables (CPTs), not only series-parallel relationship but also complex probabilistic relationship in bridge systems can be effectively modelled. The structural reliability of each bridge element is evaluated from its limit state functions, considering the probability distributions of resistance and applied load. Both Models I and II are designed in three steps: modelling consideration, DOOBN development and parameters estimation. Model III integrates Models I and II to address bridge health performance in both serviceability and safety aspects jointly. The modelling of bridge ratings is modified so that every basic modelling unit denotes one physical bridge element. According to the specific materials used, the integration of condition ratings and structural reliability is implemented through critical failure modes. Three case studies have been conducted to validate the proposed models, respectively. Carefully selected data and knowledge from bridge experts, the National Bridge Inventory (NBI) and existing literature were utilised for model validation. In addition, event information was generated using simulation to demonstrate the Bayesian updating ability of the proposed models. The prediction results of condition ratings and structural reliability were presented and interpreted for basic bridge elements and the whole bridge system. The results obtained from Model II were compared with the ones obtained from traditional structural reliability methods. Overall, the prediction results demonstrate the feasibility of the proposed modelling approach for bridge health prediction and underpin the assertion that the three models can be used separately or integrated and are more effective than the current bridge deterioration modelling approaches. The primary contribution of this work is to enhance the knowledge in the field of bridge health prediction, where more comprehensive health performance in both serviceability and safety aspects are addressed jointly. The proposed models, characterised by probabilistic representation of bridge deterioration in hierarchical ways, demonstrated the effectiveness and pledge of DOOBNs approach to bridge health management. Additionally, the proposed models have significant potential for bridge maintenance optimization. Working together with advanced monitoring and inspection techniques, and a comprehensive bridge inventory, the proposed models can be used by bridge practitioners to achieve increased serviceability and safety as well as maintenance cost effectiveness.

Effect of constitutive material models on seismic response of two-story reinforced concrete frame

This paper focuses on the finite element (FE) response sensitivity and reliability analyses considering smooth constitutive material models. A reinforced concrete frame is modeled for FE sensitivity analysis followed by direct differentiation method under both static and dynamic load cases. Later, the reliability analysis is performed to predict the seismic behavior of the frame. Displacement sensitivity discontinuities are observed along the pseudo-time axis using non-smooth concrete and reinforcing steel model under quasi-static loading. However, the smooth materials show continuity in response sensitivity at elastic to plastic transition points. The normalized sensitivity results are also used to measure the relative importance of the material parameters on the structural responses. In FE reliability analysis, the influence of smoothness behavior of reinforcing steel is carefully noticed. More efficient and reasonable reliability estimation can be achieved by using smooth material model compare with bilinear material constitutive model.

一种基于可靠性的软件构架描述视图

　提出一种针对软件可靠性估算的描述软件构架的方法构件状态转移概率视图.该方法可以描述出使用基于构架的软件可靠性模型估算构架可靠性所需要的大量信息.在估算构架可靠性的过程中使用该方法可以大大简化工作量,而又可保持原有精度.

Optimal and Robust Designs of Step-stress Accelerated Life Testing Experiments for Proportional Hazards Models

Accelerated life testing (ALT) is widely used to obtain reliability information about a product within a limited time frame. The Cox s proportional hazards (PH) model is often utilized for reliability prediction. My master thesis research focuses on designing accelerated life testing experiments for reliability estimation. We consider multiple step-stress ALT plans with censoring. The optimal stress levels and times of changing the stress levels are investigated. We discuss the optimal designs under three optimality criteria. They are D-, A- and Q-optimal designs. We note that the classical designs are optimal only if the model assumed is correct. Due to the nature of prediction made from ALT experimental data, attained under the stress levels higher than the normal condition, extrapolation is encountered. In such case, the assumed model cannot be tested. Therefore, for possible imprecision in the assumed PH model, the method of construction for robust designs is also explored.

Switch allocation problems in power distribution systems

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Modelo multidimensional de los factores que afectan la interacción entre marketing y ventas en el lanzamiento de nuevos productos en Latino América

Esta tesis se centra en la identificación y análisis de los factores que pueden favorecer o actuar como barreras del éxito de la implementación de la innovación y las relaciones entre sí, desde el enfoque de la interface marketing-ventas. El trabajo empírico se enmarca en el vacío de investigación existente en el campo del proceso de lanzamiento de nuevos productos en los mercados donde operan subsidiarias de empresas multinacionales de consumo masivo (FMCG). Las empresas FMCG son altamente dependientes de la innovación como proceso clave determinante del crecimiento competitivo de mediano y largo plazo. En un contexto de acortamiento del ciclo de vida de los productos, como resultado del desarrollo tecnológico y científico que impactan en el comportamiento de los consumidores, las empresas invierten un mayor nivel de recursos en el desarrollo de nuevos productos, reingeniería y programas de innovación (Mundra, Gulati y Gupta, 2013). Sin embargo, a pesar del aumento en la inversión, las tasas de éxito de la innovación reportadas son inferiores al 25% (Evanschitzky, Eisend, Calantone y Jiang, 2012). Aumentar las tasas de éxito de los proyectos de innovación es reconocida en la literatura como un elemento clave para la supervivencia y competitividad de las empresas, para ser superiores a su competencia y desarrollar nuevos modelos de negocios. A pesar de la existencia de estudios que intentan comprender el proceso de lanzamiento de nuevos productos, no se ha identificado un claro prototipo de gestión de la innovación (Gupta et al, 2007). Profundizando en los factores de éxito, los autores Keupp, Palmié y Gassman (2012) reconocen que la innovación exitosa no depende solamente de la estrategia de selección de los proyectos de innovación, sino también la forma en que los mismos son implementados (Klein and Sorra, 1996; Repenning, 2002; Keupp, Palmié y Gassmann, 2012). Al analizar la implementación de los proyectos de lanzamiento de nuevos productos al mercado, en empresas FMCG, dicho proceso es responsabilidad principalmente de las funciones de marketing y ventas a través de la comunicación con los consumidores y los clientes respectivamente (Ernst, Hoyer y Rubsaamen, 2010). Es decir que el éxito en la implementación de la innovación requiere la gestión efectiva de la relación inter-funcional entre marketing y ventas (Ernst, Hoyer y Rubsaamen, 2010; Hughes, Le Bon y Malshe, 2012). A pesar de la importancia de la integración entre marketing y ventas en la conceptualización e implementación de la innovación, este tema no ha sido estudiado en profundidad (Hughes, Le Bon y Malshe, 2012; Keupp, Palmié y Gassmann, 2012). En las empresas multinacionales, está demostrado que el desempeño de las subsidiarias determinan el éxito competitivo de la empresa a nivel global. El desafío de dichas subsidiarias es conjugar el desarrollo global de innovación y comunicación con las características locales de comportamiento del consumidor y el mercado. Por lo tanto, esta investigación empírica responde a la pregunta académica y de gestión acerca de cómo mejorar las tasas de éxito de lanzamiento de nuevos productos al mercado en subsidiarias de empresas de consumo masivo, desde la perspectiva de la relación entre marketing y ventas. En particular analiza cómo afectan la formalización de los procesos y los mecanismos de comunicación a la confianza interpersonal y a la efectividad de la interface marketing-ventas y dichos factores a su vez sobre la planificación integrada de la implementación de la innovación. La determinación de los factores o ítems que conforman cada uno de los constructos del proceso de ejecución de la innovación, se llevó a cabo a partir de una revisión exhaustiva del estado del arte de la literatura sobre las interfaces funcionales y el proceso de innovación. Posteriormente, los ítems seleccionados (más de 50 en total) fueron validados por referentes de marketing y ventas de Argentina y Uruguay a través de entrevistas en profundidad. A partir de los factores identificados se construyeron dos modelos teóricos: • (1) relativo a la influencia de las dimensiones de confianza interpersonal sobre la efectividad de las uniones inter-funcionales y como los mecanismos organizacionales, tales como la frecuencia y la calidad de la comunicación entre las áreas, afectan la confianza y la relación entre ellas; • (2) relativo a la dimensión planificación integrada de la implementación de la innovación, ya que durante el lanzamiento de nuevos productos al mercado, marketing y ventas utilizan procesos formales que facilitan la comunicación frecuente y efectiva, desarrollando confianza inter-personal que no solamente afecta la efectividad de su relación sino también el desarrollo de planes integrados entre ambas áreas. El estudio fue llevado a cabo en una empresa multinacional de consumo masivo que integra la lista Global 500 (Fortune, 2015), presente en todo el mundo con más de 25 marcas participantes en más de 15 categorías, implementando 150 proyectos de innovación en el último año. El grupo de subsidiarias en estudio fue reconocido a nivel mundial por su desempeño en crecimiento competitivo y su alta contribución al crecimiento total. El modelo analizado en esta tesis fue expandido al resto de América Latina, tratándose entonces de un caso ejemplar que representa una práctica de excelencia en la implementación de la innovación en subsidiarias de una empresa multinacional. La recolección de los datos fue llevado a cabo a través de un cuestionario estructurado y confidencial, enviado a la base de datos de todo el universo de directores y gerentes de marketing y ventas. El nivel de respuesta fue muy elevado (70%), logrando 152 casos válidos. El análisis de datos comprendió el análisis descriptivo de los mismos, estimación de fiabilidad y análisis factorial exploratorio a través del software SPSS v.20. El análisis factorial confirmatorio y el análisis de senderos para examinar las relaciones entre los factores se estudiaron mediante el software R (Package 2.15.1., R Core Team, 2012) (Fox, 2006). Finalmente se llevaron a cabo entrevistas en profundidad a gerentes de marketing y ventas de cada uno de los seis países con el fin de profundizar en los constructos y sus relaciones. Los resultados de los modelos demuestran que la frecuencia de comunicación impacta positivamente en la calidad de la misma, que a su vez afecta directamente la relación entre marketing y ventas. Adicionalmente, la calidad de la comunicación impacta sobre la confianza cognitiva, que a su vez se relaciona no solamente con la confianza afectiva sino también con la relación entre ambas áreas. Esto significa que para mejorar la implementación de la innovación, los gerentes deberían orientarse a reforzar la relación entre marketing y ventas facilitando la construcción de confianza interpersonal primero cognitiva y luego afectiva, incrementando la frecuencia de la comunicación que alimenta la calidad de la comunicación entre ambas áreas. A través del segundo modelo se demuestra que durante el lanzamiento de nuevos productos al mercado, marketing y ventas necesitan emplear procesos formales que faciliten la comunicación frecuente y efectiva. De esta forma se contrarresta el efecto negativo de la formalización sobre la planificación integrada entre ambas áreas. Adicionalmente, los gerentes de ambos departamentos deberían promover la construcción de confianza interpersonal, no solamente para mejorar la efectividad de la relación, sino también para desarrollar planes integrados de implementación de nuevos productos. Finalmente, se valida que la frecuencia de la comunicación, la confianza afectiva y la relación marketing-ventas, se relacionan positivamente con la planificación integrada en la implementación de la innovación. El estudio contribuye a la comprensión de los factores que las empresas pueden emplear para mejorar la relación inter-funcional entre marketing y ventas y la implementación de la innovación en empresas de consumo masivo. El aporte de esta investigación puede ser valorado de dos maneras, los aportes a la gestión y a la academia. Desde el punto de vista empresarial, provee a los líderes al frente de empresas de consumo masivo, del conocimiento sobre los factores que afectan la implementación de la innovación y en definitiva el éxito del negocio a mediano y largo plazo. Desde el punto de vista académico aporta al conocimiento del proceso de implementación de la innovación y en la efectividad de la interface marketing y ventas en un caso de buenas prácticas en el mercado de consumo masivo. A su vez incorpora por primera vez un estudio empírico en geografías emergentes capaces de recuperar el camino de crecimiento posterior a una profunda crisis económica a través de la exitosa implementación de la innovación en sus mercados. ABSTRACT This thesis is focused on the identification, analysis and relationship study of factors which may benefit or hinder the successful deployment of innovation, from a marketing-sales interface perspective. Considering the non-existent investigation dedicated to the study of new products launches into markets in which Fast Moving Consumer Goods (FMCG) companies’ subsidiaries operate, it is that this investigation has been carried out. FMCG companies rely on innovation as their key process for a competitive growth on a medium and long term basis. Nowadays, the life-cycle of products is getting shorter as a result of new technological and scientific development, having impact on consumer behavior, and therefore companies are forced to dedicating more resources to the development of new products, reengineering and innovation programs (Mundra, Gulati and Gupta, 2013). However, in spite of the investment increase, the innovation success rates have been reported to be lower than 25% (Evanschitzky, Eisend, Calantone y Jiang, 2012). Increasing success rates on innovation processes has been considered as a key element on the survival and competitiveness of companies, outperforming competitors and developing new business models. Despite new studies which try to comprehend the process of new products launch, a prototype of innovation management has not yet been identified (Gupta et al, 2007). Emphasizing on success factors, authors Keupp, Palmié and Gassman (2012) recognize that successful innovation does not solely depend on innovation processes’ selection strategy, but it is also based on the way in which these are implemented (Klein and Sorra, 1996; Repenning, 2002; Keupp, Palmié y Gassmann, 2012). While analyzing the implementation of projects for new products releases on massive consumption companies, the two departments in charge of taking this forward are marketing and sales, by focusing on communication strategies with consumers and clients respectively (Ernst, Hoyer y Rubsaamen, 2010). This means that having success on innovation implementation requires an effective management of inter-functional relationship among marketing and sales (Ernst, Hoyer y Rubsaamen, 2010; Hughes, Le Bon y Malshe, 2012). In spite of the importance on the integration between marketing and sales on the conceptualization and implementation of innovation, this subject has not been studied in depth (Hughes, Le Bon y Malshe, 2012; Keupp, Palmié y Gassmann, 2012). In multinational companies, previous research has confirmed that the performance of their subsidiaries determine the competitive success of the company on a global scale. The challenge of said subsidiaries is to conjugate the global innovation development and communication with the local consumer and market behavior. Therefore, this empirical study aims to respond to the academic and management question of how to improve the success rates of new product launches into MNE subsidiary’ markets, from a marketing-sales relationship perspective. Particularly, this investigation analyses how the formalization of products and communication mechanisms affect interpersonal trust and marketing-sales interface effectiveness and also on how these factors affect the overall planning of the implementation of innovation. The determination of which factors build the hypothesis of the innovation execution process was taken forward through an extensive research on the extant literature on functional interfaces and innovation processes. More than 50 items were selected which were in turn validated by marketing and sales referents on Uruguay and Argentina through in depth interviews. Based on the identified factors, two theoretical models were proposed: (1) Relative to the influence that interpersonal trust dimensions have on inter functional linkages effectiveness and how organizational mechanisms such as frequency and quality of communication between departments affect trust and their relationship. (2) Relative to the integrated planning and innovation implementation dimensions. Marketing and sales department use formal process thus allowing inter-personal trust, which affects positively their relationship and also enables the development of integrated planning between them. The study was performed within a massive consumption company which is part of the “Global 500” (Fortune, 2015), with subsidiaries all over the world and more than 25 participant brands in 15 categories, having implemented over 150 innovation projects in the year under study. The analyzed subsidiary group has been awarded worldwide for their performance in competitive growth and their high contribution to the total growth. The model being analyzed in this thesis was implemented throughout Latin America, representing a remarkable case of innovation implementation excellence for subsidiaries of multinational companies. Data recollection was carried out through a structured and confidential questionnaire, sent to the universe of marketing-sales directors and managers’ database available with a high level of responsiveness of 70%, resulting in 152 valid cases. Data exploration involved a descriptive analysis, followed by a reliability estimation and an exploratory factorial analysis carried out through SPSS v.20. Confirmatory factorial analysis and path analysis (to examine relations between the different study factors) were studied using “R” software (Package 2.15.1., R Core Team, 2012) (Fox, 2006). Finally, in depth interviews were carried out to several marketing and sales managers in each of the six countries so as to further confirm the hypothesis and their relations. The models results prove that communication frequency has a positive impact on the quality of the same, which in turn has direct effects on the marketing-sales relations. Additionally, communication quality has an impact on the cognitive trust, which also relates not only to affective trust, but also to the relation between both areas. This means that in order to improve the implementation of innovation, managers should strive to enforce marketing-sales relations, facilitating the interpersonal trust construction (firstly cognitive, followed by affective trust), increasing the communication frequency, and therefore nurturing the communication quality among both areas. Through the second model, the results confirm the importance of creating effective relationships between sales and marketing to facilitate planning integrated new product implementations. While formalized new product development processes provide opportunities for sales and marketing to communicate, this does not directly influence the planning of integrated new product implementations. By using these formal opportunities to communicate to create information quality, it is possible to improve sales and marketing’s ability to integrate information during the planning process. Further, communication quality creates inter-personal trust in the other party’s competences (cognitive-based trust), leading to affect-based trust. Affect-based inter-personal trust, not only to improve the overall effectiveness of the sales and marketing relationship, but also helps in planning integrated new product implementations. This study contributes to the understanding of factors which enterprises can use to improve the inter-functional relations between marketing and sales, and the implementation of innovation in FMCG companies. The contribution of this investigation can be measured in two ways: enrichment of management and contribution to the academic area. From a business perspective, it provides massive consumption businesses leaders with knowledge on which factors affect innovation implementation, which results on mid and long-term success for the company. From an academic point of view, it provides knowledge on a prototype of successful innovation implementation management based on the marketing-sales interface effectiveness through a case study in the FMCG consumption market. Last but not least, it incorporates for the first time an empiric study on emerging geographies capable of recovery post a deep economic crisis through successful innovation implementation on their markets.

Reliability models for existing structures based on dynamic state estimation and data based asymptotic extreme value analysis

The problem of time variant reliability analysis of existing structures subjected to stationary random dynamic excitations is considered. The study assumes that samples of dynamic response of the structure, under the action of external excitations, have been measured at a set of sparse points on the structure. The utilization of these measurements m in updating reliability models, postulated prior to making any measurements, is considered. This is achieved by using dynamic state estimation methods which combine results from Markov process theory and Bayes' theorem. The uncertainties present in measurements as well as in the postulated model for the structural behaviour are accounted for. The samples of external excitations are taken to emanate from known stochastic models and allowance is made for ability (or lack of it) to measure the applied excitations. The future reliability of the structure is modeled using expected structural response conditioned on all the measurements made. This expected response is shown to have a time varying mean and a random component that can be treated as being weakly stationary. For linear systems, an approximate analytical solution for the problem of reliability model updating is obtained by combining theories of discrete Kalman filter and level crossing statistics. For the case of nonlinear systems, the problem is tackled by combining particle filtering strategies with data based extreme value analysis. In all these studies, the governing stochastic differential equations are discretized using the strong forms of Ito-Taylor's discretization schemes. The possibility of using conditional simulation strategies, when applied external actions are measured, is also considered. The proposed procedures are exemplifiedmby considering the reliability analysis of a few low-dimensional dynamical systems based on synthetically generated measurement data. The performance of the procedures developed is also assessed based on a limited amount of pertinent Monte Carlo simulations. (C) 2010 Elsevier Ltd. All rights reserved.

Estimation of time variant reliability of randomly parametered non-linear vibrating systems

The problem of time variant reliability analysis of randomly parametered and randomly driven nonlinear vibrating systems is considered. The study combines two Monte Carlo variance reduction strategies into a single framework to tackle the problem. The first of these strategies is based on the application of the Girsanov transformation to account for the randomness in dynamic excitations, and the second approach is fashioned after the subset simulation method to deal with randomness in system parameters. Illustrative examples include study of single/multi degree of freedom linear/non-linear inelastic randomly parametered building frame models driven by stationary/non-stationary, white/filtered white noise support acceleration. The estimated reliability measures are demonstrated to compare well with results from direct Monte Carlo simulations. (C) 2014 Elsevier Ltd. All rights reserved.

Markov chain splitting methods in structural reliability integral estimation

Monte Carlo simulation methods involving splitting of Markov chains have been used in evaluation of multi-fold integrals in different application areas. We examine in this paper the performance of these methods in the context of evaluation of reliability integrals from the point of view of characterizing the sampling fluctuations. The methods discussed include the Au-Beck subset simulation, Holmes-Diaconis-Ross method, and generalized splitting algorithm. A few improvisations based on first order reliability method are suggested to select algorithmic parameters of the latter two methods. The bias and sampling variance of the alternative estimators are discussed. Also, an approximation to the sampling distribution of some of these estimators is obtained. Illustrative examples involving component and series system reliability analyses are presented with a view to bring out the relative merits of alternative methods. (C) 2015 Elsevier Ltd. All rights reserved.