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1
Saini, Gagandeep Singh. "Reliability-based design with system reliability and design improvement." Diss., Rolla, Mo. : Missouri University of Science and Technology, 2009. http://scholarsmine.mst.edu/thesis/pdf/Saini_09007dcc8070d586.pdf.
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Thesis (M.S.)--Missouri University of Science and Technology, 2009.Vita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed November 23, 2009) Includes bibliographical references (p. 66-68).
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Akkas, Izzet Saygin. "Reliability Based Water Distribution Network Design." Master's thesis, METU, 2006. http://etd.lib.metu.edu.tr/upload/12607830/index.pdf.
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The need of water and the limited sources, force the researchers to find the most economical and feasible solution in the design of a water distribution network. In this study, reliability and optimization of a water distribution network are taken into account together in the design stage of the network. The relationship between reliability of a water distribution network and its cost is examined during the design of a water distribution network. A methodology for deciding the reliability level of the selected design is proposed by examining the reliability-cost relationship. The design alternatives for the case study area are obtained by the aid of a commercially available software WADISO employing partial enumeration optimization technique. The reliability value for each of the design alternative is calculated according to Misirdali (2003)&rsquos adaptation based on the methodology proposed by Bao and Mays (1990) by the aid of a hydraulic network solver program HapMam prepared by Nohutç
u (2002). For purposes of illustration, the skeletonized form of Ankara Water Distribution Network subpressure zone (N8-1) is taken as the case study area. The methodology in this study, covering the relation between the reliability and the cost of a water distribution network and the proposed reliability level can be used in the design of new systems.
3
Cortes, Romero Juan Jose. "Reliability based design of marine risers." Thesis, University of Newcastle Upon Tyne, 1999. http://hdl.handle.net/10443/774.
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The harsh environment in which offshore structures must operate, their intended service life and the uncertainties inherent to the load processes, have been the impulse for investigation of their reliability. The method most extensively applied for this purpose during the last two decades was the Structural Systems Reliability, which can not be coupled with the finite element method. Therefore the objectives of the present work are to investigate the applicability of a technique which allows the utilization of the reliability analysis methods with a marine riser modelled by the finite element method, FEM, and revision of the reliability levels associated with this riser, including the fatigue life. For these purposes the response surface methodology was selected, among a number of methods. A response surface approach which requires a low number of experiments with the FEM model was elected, calculations for construction of the response surface are further simplified by the assumption of statistical independence among the basic variables. It is demonstrated in the present study that the response surface is capable of producing an equivalent and explicit limit state function which is used at a second stage with the First Order Reliability Method and the Adaptive Importance Sampling simulation technique. However, it was found that the assumption of independence is not always valid. In this case, a method is proposed in which the correlated variables are implicitly considered at the level of the mechanical model. The reliability of the marine riser was reviewed with the proposed algorithms, finding that the validity of the reliability levels depend on the number of basic variables considered and their statistical properties. The significant reduction in required computing time achieved with the response surface methodology allowed parametric studies to be carried out, in order to investigate the impact of different statistical properties of the basic variables. The fatigue reliability case was also investigated with the S-N approach. The introduction of uncertainty in the fatigue life estimation proved that acceptable levels of deterministic fatigue life may render unacceptablelevels of reliability. The uncertainty associated with the stress range is the most significant variable, though the present fatigue reliability formats consider it in a very simplified manner, therefore an approach is suggested with which the stress uncertainty can be considered in a more detailed fashion. However, the algorithm used here for construction of the response surface was unable to produce the required surface. Therefore it is concluded that though the response surface is capable of handling a large number of structural reliability cases, there are instances in which more research efforts are needed.
4
Moon, Min-Yeong. "Confidence-based model validation for reliability assessment and its integration with reliability-based design optimization." Diss., University of Iowa, 2017. https://ir.uiowa.edu/etd/5816.
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Conventional reliability analysis methods assume that a simulation model is able to represent the real physics accurately. However, this assumption may not always hold as the simulation model could be biased due to simplifications and idealizations. Simulation models are approximate mathematical representations of real-world systems and thus cannot exactly imitate the real-world systems. The accuracy of a simulation model is especially critical when it is used for the reliability calculation. Therefore, a simulation model should be validated using prototype testing results for reliability analysis. However, in practical engineering situation, experimental output data for the purpose of model validation is limited due to the significant cost of a large number of physical testing. Thus, the model validation needs to be carried out to account for the uncertainty induced by insufficient experimental output data as well as the inherent variability existing in the physical system and hence in the experimental test results. Therefore, in this study, a confidence-based model validation method that captures the variability and the uncertainty, and that corrects model bias at a user-specified target confidence level, has been developed. Reliability assessment using the confidence-based model validation can provide conservative estimation of the reliability of a system with confidence when only insufficient experimental output data are available.
Without confidence-based model validation, the designed product obtained using the conventional reliability-based design optimization (RBDO) optimum could either not satisfy the target reliability or be overly conservative. Therefore, simulation model validation is necessary to obtain a reliable optimum product using the RBDO process. In this study, the developed confidence-based model validation is integrated in the RBDO process to provide truly confident RBDO optimum design. The developed confidence-based model validation will provide a conservative RBDO optimum design at the target confidence level. However, it is challenging to obtain steady convergence in the RBDO process with confidence-based model validation because the feasible domain changes as the design moves (i.e., a moving-target problem). To resolve this issue, a practical optimization procedure, which terminates the RBDO process once the target reliability is satisfied, is proposed. In addition, the efficiency is achieved by carrying out deterministic design optimization (DDO) and RBDO without model validation, followed by RBDO with the confidence-based model validation. Numerical examples are presented to demonstrate that the proposed RBDO approach obtains a conservative and practical optimum design that satisfies the target reliability of designed product given a limited number of experimental output data.
Thus far, while the simulation model might be biased, it is assumed that we have correct distribution models for input variables and parameters. However, in real practical applications, only limited numbers of test data are available (parameter uncertainty) for modeling input distributions of material properties, manufacturing tolerances, operational loads, etc. Also, as before, only a limited number of output test data is used. Therefore, a reliability needs to be estimated by considering parameter uncertainty as well as biased simulation model. Computational methods and a process are developed to obtain confidence-based reliability assessment. The insufficient input and output test data induce uncertainties in input distribution models and output distributions, respectively. These uncertainties, which arise from lack of knowledge – the insufficient test data, are different from the inherent input distributions and corresponding output variabilities, which are natural randomness of the physical system.
5
Dersjö, Tomas. "Reliability based design optimization for structural components /." Stockholm : Skolan för teknikvetenskap, Kungliga Tekniska högskolan, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-11824.
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Dersjö, Tomas. "Reliability based design optimization for structural components." Licentiate thesis, KTH, Solid Mechanics (Div.), 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-11824.
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Dinegdae, Yared Hailegiorgis. "Reliability-based Design Procedure for Flexible Pavements." Licentiate thesis, KTH, Byggvetenskap, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-165280.
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Load induced top-down fatigue cracking has been recognized recently as a major distress phenomenon in asphalt pavements. This failure mode has been observed in many parts of the world, and in some regions, it was found to be more prevalent and a primary cause of pavements failure. The main factors which are identified as potential causes of top down fatigue cracking are primarily linked to age hardening, mixtures fracture resistance and unbound layers stiffness. Mechanistic Empirical analytical models, which are based on hot mix asphalt fracture mechanics (HMA-FM) and that could predict crack initiation time and propagation rate, have been developed and shown their capacity in delivering acceptable predictions. However, in these methods, the effect of age hardening and healing is not properly accounted and moreover, these models do not consider the effect of mixture morphology influence on long term pavement performance. Another drawback of these models is, as analysis tools they are not suitable to be used for pavement design purpose. The main objective of this study is to develop a reliability calibrated design framework in load resistance factor design (LRFD) format which could be implemented to design pavement sections against top down fatigue cracking. For this purpose, asphalt mixture morphology based sub-models were developed and incorporated to HMA-FM to characterize the effect of aging and degradation on fracture resistance and healing potential. These sub-models were developed empirically exploiting the observed relation that exist between mixture morphology and fracture resistance. The developed crack initiation prediction model was calibrated and validated using pavement sections that have high quality laboratory data and observed field performance history. As traffic volume was identified in having a dominant influence on predicted performance, two separate model calibration and validation studies were undertaken based on expected traffic volume. The predictions result for both model calibration and validation was found to be in an excellent agreement with the observed performance in the field. A LRFD based design framework was suggested that could be implemented to optimize pavement sections against top-down fatigue cracking. To achieve this objective, pavement sections with various design target reliabilities and functional requirements were analyzed and studied. A simplified but efficient limit state equation was generated using a central composite design (CCD) based response surface methodology, and FORM based reliability analysis was implemented to compute reliabilities and formulate associated partial safety factors. A design example using the new partial safety factors have clearly illustrated the potential of the new method, which could be used to supplement existing design procedures.QC 20150427
8
Stineburg, Jeffrey. "Software reliability prediction based on design metrics." Virtual Press, 1999. http://liblink.bsu.edu/uhtbin/catkey/1154775.
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This study has presented a new model for predicting software reliability based on design metrics. An introduction to the problem of software reliability is followed by a brief overview of software reliability models. A description of the models is given, including a discussion of some of the issues associated with them. The intractability of validating life-critical software is presented. Such validation is shown to require extended periods of test time that are impractical in real world situations. This problem is also inherent in fault tolerant software systems of the type currently being implemented in critical applications today. The design metrics developed at Ball State University is proposed as the basis of a new model for predicting software reliability from information available during the design phase of development. The thesis investigates the proposition that a relationship exists between the design metric D(G) and the errors that are found in the field. A study, performed on a subset of a large defense software system, discovered evidence to support the proposition.Department of Computer Science
9
Kim, John Sang. "Reliability-based design of a retaining wall." Diss., Virginia Tech, 1995. http://hdl.handle.net/10919/40214.
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A retaining wall is subject to various limit states such as sliding, overturning and bearing capacity, and it can fail by anyone of them. Since a great deal of uncertainty is involved in the analysis of the limit states, the use of detenninistic conventional safety factors may produce a misleading result.
The main objective of this study is to develop a procedure for the optimum design of a retaining wall by using the reliability theory. Typical gravity retaining walls with four different heights were selected in this study. The walls were designed first to satisfy the conventional design criteria, and later the safety indices inherent in the walls were computed by using Advanced First Order Second Moment method. With the safety indices the probabilities of failure for the three limit states were calculated and the probabilistically optimized design could be achieved by using the probability of failure. The influence of the coefficient of variation on the probability of failure was investigated. The ratios of base width to wall height which lead to the optimum design were obtained through a parametric study.Ph. D.
10
LEE, SEUNG JOO. "RELIABILITY-BASED OPTIMAL STRUCTURAL AND MECHANICAL DESIGN." Diss., The University of Arizona, 1987. http://hdl.handle.net/10150/184136.
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Structural reliability technology provides analytical tools for management of uncertainty in all relevant design factors in structural and mechanical systems. Generally, the goal of analysis is to compute probabilities of failure in structural components or system having single or multiple failure mode. Alternately, modern optimization methods provide efficient numerical algorithms for locating optima, particularly in large-scale systems having prescribed deterministic constraints. Optimization procedure can accommodate random variables either directly in its objective function or as one of the primary constraints. The combination of elementary optimization and probabilistic design techniques is the subject of this study. Presented herein is a general strategy for optimization when the design factors are random variables and some or all of the constraints are probability statements. A literature review has indicated that optimization technology in a reliability context has not been fully explored for the general case of nonlinear performance functions and nonnormal variates associated multiple failure modes. This research focuses upon development of the theory to address this general problem. Because analysis algorithms are complicated, a computer code, program RELOPT, is constructed to automate the analysis. The objective function to be minimized is arbitrary, but would generally be the total expected lifetime costs including all initial costs as well as all costs associated with failure. Uncertainty is assumed to be possible in all design factors (including the factors to be determined), and they are modeled as random variables. In general, all of the constraints can be probability statements. The generalized reduce gradient (GRG) method was used for optimization calculations. Options for point probability calculations are first order reliability analysis using the Rackwitz-Fiessler (R-F) or advanced reliability analysis using Wu/FPI. For system reliability analysis either the first order Cornell's bounds or the second order Ditlevsen's bounds can be specified. Several examples are presented to illustrate the full range of capabilities of RELOPT. The program is validated by checking with independent and exact solutions. An example is provided which demonstrates that the cost of running RELOPT can be substantial as the size of the problem increases.
11
Basova, Habib Gurkan. "Reliability-based design optimization using buffered failure probability." Thesis, Monterey, California : Naval Postgraduate School, 2010. http://edocs.nps.edu/npspubs/scholarly/theses/2010/Jun/10Jun%5FBasova.pdf.
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Thesis (M.S. in Operations Research)--Naval Postgraduate School, June 2010.Thesis Advisor(s): Royset, Johannes O. ; Second Reader: Wood, R. Kevin. "June 2010." Description based on title screen as viewed on July 14, 2010. Author(s) subject terms: Reliability-based Design Optimization, Failure Probability, Buffered Failure Probability, Structural Reliability. Includes bibliographical references (p. 37-41). Also available in print.
12
Dersjö, Tomas. "Methods for reliability based design optimization of structural components." Doctoral thesis, KTH, Hållfasthetslära (Avd.), 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-90753.
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Cost and quality are key properties of a product, possibly even the two most important. Onedefinition of quality is fitness for purpose. Load-bearing products, i.e. structural components,loose their fitness for purpose if they fail. Thus, the ability to withstand failure is a fundamentalmeasure of quality for structural components. Reliability based design optimization(RBDO) is an approach for development of structural components which aims to minimizethe cost while constraining the probability of failure. However, the computational effort ofan RBDO applied to large-scale engineering problems has prohibited it from employment inindustrial applications. This thesis presents methods for computationally efficient RBDO.A review of the work presented on RBDO algorithms reveals that three constituentsof an RBDO algorithm has rendered significant attention; i ) the solution strategy for andnumerical treatment of the probabilistic constraints, ii ) the surrogate model, and iii) theexperiment design. A surrogate model is ”a model of a model”, i.e. a computationally cheapapproximation of a physics-based but computationally expensive computer model. It is fittedto responses from the physics-motivated model obtained via a thought-through combinationof experiments called an experiment design.In Paper A, the general algorithm for RBDO employed in this work, including the sequentialapproximation procedure used to treat the probabilistic constraints, is laid out. A singleconstraint approximation point (CAP) is used to save computational effort with acceptablelosses in accuracy. The approach is used to optimize a truck component and incorporatesthe effect that production related design variables like machining and shot peening have onfatigue life.The focus in Paper B is on experiment design. An algorithm employed to construct anovel experiment design for problems with multiple constraints is presented. It is based onan initial screening and uses the specific problem structure to combine one-factor-at-a-timeexperiments to a several-factors-at-a-time experiment design which reduces computationaleffort.In Paper C, a surrogate model tailored for RBDO is introduced. It is motivated by appliedsolid mechanics considerations and the use of the first order reliability method to evaluate theprobabilistic constraint. An optimal CAP is furthermore deduced from the surrogate model.In Paper D, the paradigm to use sets of experiments rather than one experiment at atime is challenged. A new procedure called experiments on demand (EoD) is presented. TheEoD procedure utilizes the core of RBDO to quantify the demand for new experiments andaugments it by a D-optimality criterion for added robustness and numerical stability.QC 20120229
13
Ludeña, Alexis Joseph. "Reliability-based analysis and design of 2D trusses." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/90025.
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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2014.Thesis: S.B., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2014.
Cataloged from PDF version of thesis.
Includes bibliographical references (page 61).
Current safety factors used in structural design do not accurately account for uncertainties in material properties and required loads. These factors usually lead to overly designed structures but can also lead to under-designed structures because they are poor estimates of uncertainty. To correctly quantify the uncertainty in a structure we use reliability-based methods to analyze a 2D truss. This study first explores various types of methods used to calculate the reliability of an element to develop an automated analysis program. After finding the best methods needed for an accurate calculation of reliability, we define a set of random variables which affect the reliability of a structure. By developing a computationally automated framework to calculate the reliability of a 2D truss and its bar elements, we can gauge the efficiency and effectiveness of current design factors used. Additionally, we can also quantify the sensitivity of our analysis to its parameters to better understand the impact a single random variable can have in the overall calculation of reliability. Lastly, this reliability analysis framework can be used to conduct the reliability-based design of a steel bar member and a 2D truss system to optimize their probability of failure for various failure criteria.
by Alexis Joseph Ludena.
M. Eng.
S.B.
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Li, Zhongwei. "Reliability-Based Design Optimization of Nonlinear Beam-Columns." Diss., Virginia Tech, 2018. http://hdl.handle.net/10919/82958.
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This dissertation addresses the ultimate strength analysis of nonlinear beam-columns under axial compression, the sensitivity of the ultimate strength, structural optimization and reliability analysis using ultimate strength analysis, and Reliability-Based Design Optimization (RBDO) of the nonlinear beam-columns. The ultimate strength analysis is based on nonlinear beam theory with material and geometric nonlinearities. Nonlinear constitutive law is developed for elastic-perfectly-plastic beam cross-section consisting of base plate and T-bar stiffener. The analysis method is validated using commercial nonlinear finite element analysis. A new direct solving method is developed, which combines the original governing equations with their derivatives with respect to deformation matric and solves for the ultimate strength directly. Structural optimization and reliability analysis use a gradient-based algorithm and need accurate sensitivities of the ultimate strength to design variables. Semi-analytic sensitivity of the ultimate strength is calculated from a linear set of analytical sensitivity equations which use the Jacobian matrix of the direct solving method. The derivatives of the structural residual equations in the sensitivity equation set are calculated using complex step method. The semi-analytic sensitivity is more robust and efficient as compared to finite difference sensitivity. The design variables are the cross-sectional geometric parameters. Random variables include material properties, geometric parameters, initial deflection and nondeterministic load. Failure probabilities calculated by ultimate strength reliability analysis are validated by Monte Carlo Simulation. Double-loop RBDO minimizes structural weight with reliability index constraint. The sensitivity of reliability index with respect to design variables is calculated from the gradient of limit state function at the solution of reliability analysis. By using the ultimate strength direct solving method, semi-analytic sensitivity and gradient-based optimization algorithm, the RBDO method is found to be robust and efficient for nonlinear beam-columns. The ultimate strength direct solving method, semi-analytic sensitivity, structural optimization, reliability analysis, and RBDO method can be applied to more complicated engineering structures including stiffened panels and aerospace/ocean structures.Ph. D.
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Loferski, Joseph R. "A reliability based design procedure for wood pallets." Diss., Virginia Polytechnic Institute and State University, 1985. http://hdl.handle.net/10919/52303.
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Pallets are widely used to efficiently store and handle goods and are often subjected to bending and impact loads. The consequences of structural failure of a loaded pallet can include loss of goods, increased labor and equipment costs, and possible severe or fatal injury to humans. - The pallet industry, which annually consumes nearly 20% of all lumber manufactured in the United States, recognized a need for a rational design methodology, based upon engineering principles, to ensure consistent safety and economy in pallets of any geometry. To satisfy this need a cooperative research project between Virginia Tech, the U. S. Forest Service, and the National Wooden Pallet and Container Association was established. The objective of the project was to develop methods to design pallets for strength, stiffness, and durability. A primary expected benefit of the design methodology is to allow comparison of different pallet designs on a performance basis, without the need for extensive physical testing. This dissertation presents the results of this cooperative research project.
The developed methodology was computerized (Pallet Design System (PDS)) and is intended to allow pallet manufactures to obtain estimates of the maximum safe load capacity or the member dimensions required to resist known loads. Additionally, the program produces estimates of the durability and cost-per-use for pallets in specific service environments. PDS is limited in scope to pallets with up to four stringers and a maximum of 15 deckboards. Five different load types and four support modes can be analyzed. These include uniformly distributed and concentrated loads, and racked, stacked, and sling support modes. The techniques for estimating the strength and stiffness are based on matrix structural analysis and classical beam theory. The deckboard-stringer joints are modeled as spring elements, the stiffness of which are based upon characteristics of the fastener. Most fasteners commonly used in pallet construction (i.e. threaded nails or staples) can be analyzed. A probabilistic design technique based on mean value methods was applied in PDS to ensure safety in the resulting designs. The safety index was calibrated to pallet designs associated with warehouse load data. The physical properties of the material are estimated using either a modified clear-wood property approach (ASTM D-245 method), or in·graded testing of pallet lumber. The durability estimates are based upon studies of field data and economic analysis.Ph. D.
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Bjureland, William. "On reliability-based design of rock tunnel support." Licentiate thesis, KTH, Jord- och bergmekanik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-204919.
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Tunneling involves large uncertainties. Since 2009, design of rock tunnels in European countries should be performed in accordance with the Eurocodes. The main principle in the Eurocodes is that it must be shown in all design situations that no relevant limit state is exceeded. This can be achieved with a number of different methods, where the most common one is design by calculation. To account for uncertainties in design, the Eurocode states that design by calculation should primarily be performed using limit state design methods, i.e. the partial factor method or reliability-based methods. The basic principle of the former is that it shall be assured that a structure’s resisting capacity is larger than the load acting on the structure, with high enough probability. Even if this might seem straightforward, the practical application of limit state design to rock tunnel support has only been studied to a limited extent. The aim of this licentiate thesis is to provide a review of the practical applicability of using reliability-based methods and the partial factor method in design of rock tunnel support. The review and the following discussion are based on findings from the cases studied in the appended papers. The discussion focuses on the challenges of applying fixed partial factors, as suggested by Eurocode, in design of rock tunnel support and some of the practical difficulties the engineer is faced with when applying reliability-based methods to design rock tunnel support. The main conclusions are that the partial factor method (as defined in Eurocode) is not suitable to use in design of rock tunnel support, but that reliability-based methods have the potential to account for uncertainties present in design, especially when used within the framework of the observational method. However, gathering of data for statistical quantification of input variables along with clarification of the necessary reliability levels and definition of “failure” are needed.QC 20170407
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Mahadevan, Sankaran. "Stochastic finite element-based structural reliability analysis and optimization." Diss., Georgia Institute of Technology, 1988. http://hdl.handle.net/1853/19517.
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Wang, Jia. "Reliability analysis and reliability-based optimal design of linear structures subjected to stochastic excitations /." View abstract or full-text, 2010. http://library.ust.hk/cgi/db/thesis.pl?CIVL%202010%20WANG.
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Gavrilovic, Stevan. "Reliability-based design optimization using DDM enabled finite elements." Thesis, University of British Columbia, 2015. http://hdl.handle.net/2429/54167.
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Rts is a risk-based structural optimization, multi-platform computer program that incorporates uncertainty into structural analysis with the utilization of random variable parameters. The major contribution to this thesis is that Rts now has the capability to perform reliability-based design optimization using Finite Element Method (FEM) analytical sensitivities. Analytical gradients are exact, more efficient, and convergence is achieved more rapidly in gradient- based optimization methods when compared to finite difference sensitivity methods. For this thesis, I have derived and implemented both nodal and material analytical gradients throughout the Rts framework starting at the finite element level up through to the optimization level. The Reliability-Based Design Optimization (RBDO) model stream includes an FEM model, a COST model, a RISK model with built-in First-Order Reliability Model (FORM), and the orchestrating RBDO model. A program wide Direct Differentiation Method (DDM) framework was additionally established that provides efficient analytical gradient calculations throughout the model stream. The FEM elements implemented consist of the Bilinear-Mindlin four node and nine node plate elements. An academic COST model was created to showcase the multi-model capabilities of Rts and the ability to calculate DDM dependencies of downstream models. Additionally, a RISK model was implemented that incorporated a built-in FORM model with gradient-history capabilities and in-model DDM dependency calculations; the RISK measure used is the mean cost. The RBDO model was also built upon to include DDM capabilities and downstream model integration. Finally, two reliability-based design optimization examples were implemented using both nodal and material sensitivities. The thickness and width of a timber cantilever beam was optimized with respect to mean cost taking into account deflection damage and construction cost.Applied Science, Faculty of
Civil Engineering, Department of
Graduate
20
ALMEIDA, ALEX FABIANO DE. "RELIABILITY-BASED DESIGN OPTIMIZATION OF REINFORCED CONCRETE PLANE FRAMES." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2008. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=11577@1.
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CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOEste trabalho compara o projeto ótimo determinístico (DDO) com o projeto ótimo baseado em confiabilidade (RBDO) de pórticos planos de concreto armado. A estrutura é modelada por uma malha de elementos finitos usando elementos de barras e considerando a não-linearidade geométrica e dos materiais. Na formulação do problema de otimização proposto as variáveis de projeto são definidas para cada elemento finito da malha. Elas são as armaduras superior e inferior das seções transversais de extremidade do elemento, a altura da seção do elemento, as áreas de armadura transversal e o parâmetro D usado para descrever os estados limites últimos de acordo com a norma brasileira NBR 6118 (ABNT, 2004). Os algoritmos de otimização utilizados são os de programação quadrática seqüencial (PQS), programação linear seqüencial (PLS) e o método das direções viáveis (MDV). As variáveis randômicas do problema de RBDO são a resistência à compressão do concreto, as resistências à tração e à compressão do aço, assim como as cargas aplicadas. As funções de comportamento são de dois tipos, a primeira é relativa à carga crítica da estrutura e a segunda ao controle de deslocamento para o estado limite de utilização. Para o cálculo da probabilidade de falha de uma função de comportamento, em cada iteração do problema de RBDO, o método FORM (PMA) utilizará o algoritmo HMV para obtenção do ponto de projeto. Análise de sensibilidade é feita pelo método analítico.
This work compares the Deterministic Design Optimization (DDO) with the Reliability-Based Design Optimization (RBDO) of reinforced concrete plane frames. The structure is modeled by a finite element mesh using bar elements and considering both geometric and material nonlinearities. In the formulation of the proposed optimization problem the design variables are defined for each element of the finite element mesh. They are the areas of tensile and compressive reinforcement at the element ends, the depth of the element rectangular cross-section, the areas of shear reinforcement, and the parameter D used to describe the deformation limit sates for the element cross-sections defined according to the Brazilian code for the design of concrete structures NBR 6118 (ABNT, 2004). The optimization algorithms used are the Sequential Linear Programming (SLP), the Sequential Quadratic Programming (SQP) and the Method of Feasible Direction (MFD). The random variables of the RBDO problem are the concrete compressive strength, the steel compressive and tensile strength, as well as some applied loads. The performance functions are of two types, the first relates to the critical load of the structure and the second to the control of displacements in the serviceability state. For performing the calculation of the probability of failure for the associated performing function in each iteration of the RBDO problem, the method FORM (PMA) will be used in connection with the HMV algorithm for obtaining the project point. The sensitivity analyses are carried out by the analytical method.
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NARVAEZ, NATHALY SARASTY. "RELIABILITY-BASED DESIGN OF RC BEAMS STRENGTHENED WITH CFC." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2012. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=21011@1.
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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIROCOORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO
PROGRAMA DE EXCELENCIA ACADEMICA
No Brasil, o dimensionamento de estruturas de concreto armado segue as recomendações da norma brasileira NBR 6118-2003. A norma brasileira, usa a metodologia de dimensionamento semi-probabilístico que não quantifica a probabilidade de falha de um elemento estrutural. A análise de confiabilidade de estruturas é uma ferramenta que possibilita o cálculo da probabilidade de falha associada a um estado limite e também um dimensionamento para uma determinada probabilidade de falha denominada probabilidade de falha alvo. Este trabalho tem como objetivo desenvolver uma metodologia que possibilite o dimensionamento baseado em confiabilidade de seções de vigas de concreto armado sem e com reforço com compósitos de fibras de carbono. Na análise de confiabilidade desenvolvida foram consideradas como variáveis aleatórias o carregamento, as resistências do aço e do concreto, e a resistência à tração dos compósitos de fibras de carbono com propriedades estatísticas determinadas com base nos resultados dos ensaios realizados no laboratório de Estruturas e Materiais do Departamento de Engenharia Civil da PUC-Rio (LEM-DEC). Exemplos de dimensionamento de seções de vigas de concreto armado submetidas à força cortante e à flexão foram realizados inicialmente por métodos semi-probabilísticos e depois utilizando a metodologia proposta baseada em confiabilidade. A análise dos resultados mostra a viabilidade de um projeto baseado em confiabilidade usando um índice de probabilidade de falha determinado para cada tipo de projeto aliando economia e segurança.
In Brazil, the design of reinforced concrete structures follows the recommendations of Brazilian standard NBR 6118-2003. The Brazilian standard uses the methodology of semi-probabilistic design that does not quantify the probability of failure of a structural element. The reliability analysis of structures is a tool that allows the calculation of probability of failure associated with a limit state and also the design for a given probability of failure. This work aims to develop a methodology that enables the Reliability-based-design of concrete beams sections with and without strengthening with carbon fiber composites. In the reliability analysis were considered as random variables the loads, the compression concrete strenght, yield strenght, and tensile strength of carbon fiber composites with certain statistical properties based on the results of tests performed in the Structures and Materials laboratory at PUC-Rio (LEM-DEC). Examples of reinforced concrete beams strengthened with CFC were performed initially by semi-probabilistic methods and then using the proposed methodology based on reliability. The analysis shows the feasibility of a Reliability-baseddesign using a reliability index of failure probability determined for each type of project combining economy and safety.
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Yang, Luo. "RELIABILITY-BASED DESIGN AND QUALITY CONTROL OF DRIVEN PILES." University of Akron / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=akron1153755606.
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Chang, Ching-Chiao. "Optimal reliability-based design of bulk water supply systems." Master's thesis, University of Cape Town, 2011. http://hdl.handle.net/11427/14593.
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Includes bibliographical references.Bulk water supply systems are usually designed according to deterministic design guidelines. In South Africa, design guidelines specify that a bulk storage reservoir should have a storage capacity of 48 hours of annual average daily demand (AADD), and the feeder pipe a capacity of 1.5 times AADD (CSIR, 2000). Nel & Haarhoff (1996) proposed a stochastic analysis method that allowed the reliability of a reservoir to be estimated based on a Monte Carlo analysis of consumer demand, fire water demand and pipe failures. Van Zyl et al. (2008) developed this method further and proposed a design criterion of one failure in ten years under seasonal peak conditions. In this study, a method for the optimal design of bulk water supply systems is proposed with the design variables being the configuration of the feeder pipe system, the feeder pipe diameters (i.e. capacity), and the size of the bulk storage reservoir. The stochastic analysis method is applied to determine a trade-off curve between system cost and reliability, from which the designer can select a suitable solution. Optimisation of the bulk system was performed using the multi-objective genetic algorithm, NSGA-II. As Monte Carlo sampling can be computationally expensive, especially when large numbers of simulations are required in an optimisation exercise, a compression heuristic was implemented and refined to reduce the computational effort required of the stochastic simulation. Use of the compression heuristic instead of full Monte Carlo simulation in the reliability analysis achieved computational time savings of around 75% for the optimisation of a typical system. Application of the optimisation model showed that it was able to successfully produce a set of Pareto-optimal solutions ranging from low reliability, low cost solutions to high reliability, high cost solutions. The proposed method was first applied to a typical system, resulting in an optimal reservoir size of approximately 22 h AADD and feeder pipe capacity of 2 times AADD. This solution achieved 9% savings in total system cost compared to the South African design guidelines. In addition, the optimal solution proved to have better reliability that one designed according to South African guidelines. A sensitivity analysis demonstrated the effects of changing various system and stochastic parameters from typical to low and high values. The sensitivity results revealed that the length of the feeder pipe system has the greatest impact on both the cost and reliability of the bulk system. It was also found that a single feeder pipe is optimal in most cases, and that parallel feeder pipes are only optimal for short feeder pipe lengths. The optimisation model is capable of narrowing down the search region to a handful of possible design solutions, and can thus be used by the engineer as a tool to assist with the design of the final system.
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Scarth, Carl. "Robust and reliability-based aeroelastic design of composite wings." Thesis, University of Bristol, 2016. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.707752.
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Ezzati, Ghasem. "Reliability-based design optimisation methods in large scale systems." Thesis, Federation University Australia, 2015. http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/99881.
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Doctor of PhilosophyStructural optimisation is an important field of applied mathematics, which has proved useful in engineering projects. Reliability-based design optimisation (RBDO) can be considered a branch of structural optimisation. Different RBDO approaches have been applied in real world problems (e.g. vehicle side impact model, short column design, etc.). Double-loop, single-loop, and decoupled approaches are three categories in RBDO. This research focuses on double-loop approaches, which consider reliability analysis problems in their inner loops and design optimisation calculations in their outer loops. In recent decades, double-loop approaches have been studied and modified in order to improve their stability and efficiency, but many shortcomings still remain, particularly regarding reliability analysis methods. This thesis will concentrate on development of new reliability analysis methods that can be applied to solve RBDO problems. As a local optimisation algorithm, the conjugate gradient method will be adopted. Furthermore, a new method will be introduced to solve a reliability analysis problem in the polar space. The reliability analysis problem must be transformed into an unconstrained optimisation problem before solving in the polar space. Two methods will be introduced here and their stability and efficiency will be compared with the existing methods via numerical experiments. Next, we consider applications of RBDO models to electricity networks. Most of the current optimisation models of these networks are categorised as deterministic design optimisation models. A probabilistic constraint is introduced in this thesis for electricity networks. For this purpose, a performance function must be defined for a network in order to define safety and failure conditions. Then, new non-deterministic design optimisation models will be formulated for electricity networks by using the mentioned probabilistic constraint. These models are designed to keep failure probability of the network below a predetermined and accepted safety level.
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Ehnbom, Victor, and Filip Kumlin. "Reliability Based Design of Lime-Cement Columns based on Total Settlement Criterion." Thesis, KTH, Jord- och bergmekanik, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-41768.
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The geotechnical community has since decades been acquainted with the use of statistical approach for design optimizations. This has been approved as an operational method by many practitioners in the field but is yet to see a major full-scale breakthrough and acceptance in practice. The advantage of quantifying the many different sources of uncertainties in a design is already a fairly acknowledged method and is in this report expanded for the use in the case of road embankments founded on soft soil improved by lime-cement columns. Statistical approach was adopted with practice of reliability base design (RBD ) to consider the importance of ingoing variables’ variability with the target of streamlining the result by decreasing uncertainties (by means of increased measurements, careful installation, etc.). By constructing a working model that gives the corresponding area ratio between columns and soil needed to fulfill the different criterion set as input values, weight is put on investigating the effects of different coefficients of variation (COV ). The analyses show that the property variabilities have a significant influence on the requisite area ratio that an active use of RBD is a useful tool for optimizing designs in geotechnical engineering. The methodology favors the contractors own development of the mixing process since higher design values can be utilized when
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Ramakrishna, Gnyaneshwar. "Physics-based modeling methodology for reliability of microvias." Thesis, Georgia Institute of Technology, 2002. http://hdl.handle.net/1853/18843.
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Vadamodala, Lavanya. "Reliability Based Multi-Objective Design Optimization for Switched Reluctance Machines." University of Akron / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=akron162033146640203.
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Reynolds, James Bernard. "Advanced analysis and reliability-based design of steel scaffolding systems." Thesis, The University of Sydney, 2014. http://hdl.handle.net/2123/11626.
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This thesis presents a comprehensive investigation of the advanced analysis, reliability-based design and optimisation of steel support scaffolding systems. Support scaffolding systems are used to provide temporary support to timber formwork systems, reinforcement, concrete, workmen and equipment, during the construction of permanent structures such as buildings and bridges. Stick-type steel scaffolds with cuplok joints are the focus of the thesis. This thesis includes the collection and statistical analysis of shore load effects occurring as a result of construction dead and live loads. A comprehensive series of U-head joint subassembly tests, allowed the top rotational stiffness to be rationally quantified for advanced finite element modelling. Advanced finite element models are calibrated using data compiled in a previous investigation involving eighteen full-scale tests. This calibration exercise also provides statistical data for modelling error. Monte Carlo simulations using advanced analysis are performed to determine the statistical distributions of system strength for a range of geometric configurations of support scaffold systems. The research showed that system strength was governed mainly by jack extension at the top and bottom of the scaffolding system. By incorporating the load statistics and system strength statistics, the thesis determined the reliability of various steel scaffolding systems designed by the fundamental Load-Resistance-Factor-Design (LRFD) equation. The study further proposed a more efficient LRFD equation for steel scaffolding, based on an acceptable target reliability index.
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Arikan, Gokce. "Reliability-based Design Model For Rubble-mound Coastal Defense Structures." Phd thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/3/12611602/index.pdf.
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In this thesis, a new computer model (tool) for the reliability-based design of
rubble-mound coastal defense structures is developed in which design is
carried out in a user frienly way giving outputs on time variant reliability for
the predetermined lifetimes and damage levels. The model aims to perform the
following steps:
1. Determine the sources of uncertainties in design parameters
2. Evaluate the damage risk of coastal structures which are at design stage
and are recently constructed.
3. Study the sensitivity of limit state functions to the design parameters.
Different from other reliability studies on coastal projects, a new design
computer program is developed that can be easily used by everyone working in
coastal engineering field.
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Villanueva, Diane. "Reliability Based Design Including Future Tests and Multi-Agent Approaches." Phd thesis, Saint-Etienne, EMSE, 2013. http://tel.archives-ouvertes.fr/tel-00862355.
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The initial stages of reliability-based design optimization involve the formulation of objective functions and constraints, and building a model to estimate the reliability of the design with quantified uncertainties. However, even experienced hands often overlook important objective functions and constraints that affect the design. In addition, uncertainty reduction measures, such as tests and redesign, are often not considered in reliability calculations during the initial stages. This research considers two areas that concern the design of engineering systems: 1) the trade-off of the effect of a test and post-test redesign on reliability and cost and 2) the search for multiple candidate designs as insurance against unforeseen faults in some designs. In this research, a methodology was developed to estimate the effect of a single future test and post-test redesign on reliability and cost. The methodology uses assumed distributions of computational and experimental errors with re-design rules to simulate alternative future test and redesign outcomes to form a probabilistic estimate of the reliability and cost for a given design. Further, it was explored how modeling a future test and redesign provides a company an opportunity to balance development costs versus performance by simultaneously designing the design and the post-test redesign rules during the initial design stage.The second area of this research considers the use of dynamic local surrogates, or surrogate-based agents, to locate multiple candidate designs. Surrogate-based global optimization algorithms often require search in multiple candidate regions of design space, expending most of the computation needed to define multiple alternate designs. Thus, focusing on solely locating the best design may be wasteful. We extended adaptive sampling surrogate techniques to locate multiple optima by building local surrogates in sub-regions of the design space to identify optima. The efficiency of this method was studied, and the method was compared to other surrogate-based optimization methods that aim to locate the global optimum using two two-dimensional test functions, a six-dimensional test function, and a five-dimensional engineering example.
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Mancini, Luigi Vincenzo. "Reliability issues in the design of distributed object-based architectures." Thesis, University of Newcastle Upon Tyne, 1989. http://hdl.handle.net/10443/2057.
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This thesis is aimed at enhancing the existing set of techniques for building distributed systems, specifically from the point of view of fault-tolerant com- puting. Reliability is of fundamental importance in the design and operation of dis- tributed systems, as an increasing number of computers are employed in the automation of various essential services. In the past decade, much research effort has been concerned with the object-based methodology for the design and implementation of reliable distributed systems. This thesis describes three contributions to this effort. First, it is shown that object-based programming features can in fact be introduced into pro- cedural languages provided that these languages are endowed with certain facilities. Then, work is discussed which illustrates the relationship between distributed object-based architectures and an apparently different form of distributed architectures based on processes. This work puts the notion of object-based architectures into a new perspective, which shows that the object-based philosophy and the process-based philosophy are the dual of each other. Finally, an important aspect of the design of an object-based distributed architecture is investigated, that of automatic garbage collection. A distri- buted garbage collection scheme is described that handles fault tolerance by an extension of the technique commonly employed to detect unwanted com- putations in distributed architectures. The scheme proposed can also be seen as yet a further illustration of the link between object-based and process-based architectures.
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Ndashimye, Maurice. "Accounting for proof test data in Reliability Based Design Optimization." Thesis, Stellenbosch : Stellenbosch University, 2015. http://hdl.handle.net/10019.1/97108.
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Thesis (MSc)--Stellenbosch University, 2015.ENGLISH ABSTRACT: Recent studies have shown that considering proof test data in a Reliability Based Design Optimization (RBDO) environment can result in design improvement. Proof testing involves the physical testing of each and every component before it enters into service. Considering the proof test data as part of the RBDO process allows for improvement of the original design, such as weight savings, while preserving high reliability levels. Composite Over-Wrapped Pressure Vessels (COPV) is used as an example application of achieving weight savings while maintaining high reliability levels. COPVs are light structures used to store pressurized fluids in space shuttles, the international space station and other applications where they are maintained at high pressure for extended periods of time. Given that each and every COPV used in spacecraft is proof tested before entering service and any weight savings on a spacecraft results in significant cost savings, this thesis put forward an application of RBDO that accounts for proof test data in the design of a COPV. The method developed in this thesis shows that, while maintaining high levels of reliability, significant weight savings can be achieved by including proof test data in the design process. Also, the method enables a designer to have control over the magnitude of the proof test, making it possible to also design the proof test itself depending on the desired level of reliability for passing the proof test. The implementation of the method is discussed in detail. The evaluation of the reliability was based on the First Order Reliability Method (FORM) supported by Monte Carlo Simulation. Also, the method is implemented in a versatile way that allows the use of analytical as well as numerical (in the form of finite element) models. Results show that additional weight savings can be achieved by the inclusion of proof test data in the design process.
AFRIKAANSE OPSOMMING: Onlangse studies het getoon dat die gebruik van ontwerp spesifieke proeftoets data in betroubaarheids gebaseerde optimering (BGO) kan lei tot 'n verbeterde ontwerp. BGO behels vele aspekte in die ontwerpsgebied. Die toevoeging van proeftoets data in ontwerpsoptimering bring te weë; die toetsing van 'n ontwerp en onderdele voor gebruik, die aangepaste en verbeterde ontwerp en gewig-besparing met handhawing van hoë betroubaarsheidsvlakke. 'n Praktiese toepassing van die BGO tegniek behels die ontwerp van drukvatte met saamgestelde materiaal bewapening. Die drukvatontwerp is 'n ligte struktuur wat gebruik word in die berging van hoë druk vloeistowwe in bv. in ruimtetuie, in die internasionale ruimtestasie en in ander toepassings waar hoë druk oor 'n tydperk verlang word. Elke drukvat met saamgestelde materiaal bewapening wat in ruimtevaartstelsels gebruik word, word geproeftoets voor gebruik. In ruimte stelselontwerp lei massa besparing tot 'n toename in loonvrag. Die tesis beskryf 'n optimeringsmetode soos ontwikkel en gebaseer op 'n BGO tegniek. Die metode word toegepas in die ontwerp van drukvatte met saamgestelde materiaal bewapening. Die resultate toon dat die gebruik van proeftoets data in massa besparing optimering onderhewig soos aan hoë betroubaarheidsvlakke moontlik is. Verdermeer, die metode laat ook ontwerpers toe om die proeftoetsvlak aan te pas om sodoende by ander betroubaarheidsvlakke te toets. In die tesis word die ontwikkeling en gebruik van die optimeringsmetode uiteengelê. Die evaluering van betroubaarheidsvlakke is gebaseer op 'n eerste orde betroubaarheids-tegniek wat geverifieer word met talle Monte Carlo simulasie resultate. Die metode is ook so geskep dat beide analitiese sowel as eindige element modelle gebruik kan word. Ten slotte, word 'n toepassing getoon waar resultate wys dat die gebruik van die optimeringsmetode met die insluiting van proeftoets data wel massa besparing kan oplewer.
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Luo, Liheng. "Design and reliability-based optimization of the piezoelectric flex transducer." Thesis, Lancaster University, 2018. http://eprints.lancs.ac.uk/127992/.
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In recent years, the rapid development of low power consuming devices has resulted in a high demand for mobile energy harvesters. The main contribution of this thesis is to optimize the novel piezoelectric energy harvesting device called the piezoelectric flex transducer, which was developed by other researchers for the purpose of harvesting biokinetic energy from human gait. The optimization uses both conventional and reliability-based optimization approaches in order to improve the electrical power generation from the device. First, the piezoelectric flex transducer is modeled by using the finite element method with the finite element analysis software ANSYS APDL. Seven geometric parameters of the piezoelectric energy harvester are considered as design variables. A set of designs with different design variables are generated by the Design of Experiment technique, the generated designs are analyzed by the finite element model and the surrogate models that representing the behavior of the FEM are built by these inputs and the results of the FEA. Conventional optimization, taking into consideration different safety factors, is driven by the von mises stress of the device and is then searched by a mathematical algorithm with the assistance of surrogate models. To improve the efficiency of the surrogate modeling, a multi-level surrogate modeling approach for fast convergence will be introduced and the method will be demonstrated by optimizing the PFT device. As the optimal design is subject to a low stress safety factor, which may be unreliable with the uncertainties of the real-world, the reliability and sensitivity of the optimal design are analyzed. A Monte Carlo simulation is employed to analyse how the electrical power output has been affected by the input parameters with parametric uncertainties. The design parameters of a set of designs are perturbed around the optimal design parameters in order to imitate the optimal design under parametric uncertainties. The effects of parametric uncertainties are then evaluated by the constructed surrogate models. The method for improving the product reliability will be demonstrated.
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Cho, Hyunkyoo. "Efficient variable screening method and confidence-based method for reliability-based design optimization." Diss., University of Iowa, 2014. https://ir.uiowa.edu/etd/4594.
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The objectives of this study are (1) to develop an efficient variable screening method for reliability-based design optimization (RBDO) and (2) to develop a new RBDO method incorporated with the confidence level for limited input data problems. The current research effort involves: (1) development of a partial output variance concept for variable screening; (2) development of an effective variable screening sequence; (3) development of estimation method for a confidence level of a reliability output; and (4) development of a design sensitivity method for the confidence level.
In the RBDO process, surrogate models are frequently used to reduce the number of simulations because analysis of a simulation model takes a great deal of computational time. On the other hand, to obtain accurate surrogate models, we have to limit the dimension of the RBDO problem and thus mitigate the curse of dimensionality. Therefore, it is desirable to develop an efficient and effective variable screening method for reduction of the dimension of the RBDO problem. In this study, it is found that output variance is critical for identifying important variables in the RBDO process. A partial output variance, which is an efficient approximation method based on the univariate dimension reduction method (DRM), is proposed to calculate output variance efficiently. For variable screening, the variables that has larger partial output variances are selected as important variables. To determine important variables, hypothesis testing is used so that possible errors are contained at a user-specified error level. Also, an appropriate number of samples is proposed for calculating the partial output variance. Moreover, a quadratic interpolation method is studied in detail to calculate output variance efficiently. Using numerical examples, performance of the proposed variable screening method is verified. It is shown that the proposed method finds important variables efficiently and effectively.
The reliability analysis and the RBDO require an exact input probabilistic model to obtain accurate reliability output and RBDO optimum design. However, often only limited input data are available to generate the input probabilistic model in practical engineering problems. The insufficient input data induces uncertainty in the input probabilistic model, and this uncertainty forces the RBDO optimum to lose its confidence level. Therefore, it is necessary to consider the reliability output, which is defined as the probability of failure, to follow a probability distribution. The probability of the reliability output is obtained with consecutive conditional probabilities of input distribution type and parameters using the Bayesian approach. The approximate conditional probabilities are obtained under reasonable assumptions, and Monte Carlo simulation is applied to practically calculate the probability of the reliability output. A confidence-based RBDO (C-RBDO) problem is formulated using the derived probability of the reliability output. In the C-RBDO formulation, the probabilistic constraint is modified to include both the target reliability output and the target confidence level. Finally, the design sensitivity of the confidence level, which is the new probabilistic constraint, is derived to support an efficient optimization process. Using numerical examples, the accuracy of the developed design sensitivity is verified and it is confirmed that C-RBDO optimum designs incorporate appropriate conservativeness according to the given input data.
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Letcher, Todd M. "Structural reliability through robust design optimization and energy-based fatigue analysis." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1343742266.
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Noh, Yoojeong Choi Kyung K. "Input model uncertainty and reliability-based design optimization with associated confidence level." [Iowa City, Iowa] : University of Iowa, 2009. http://ir.uiowa.edu/etd/412.
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Ren, Zhong. "An Efficient Method for Reliability-based Design Optimization when the Design Variables are Random." University of Toledo / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1373021397.
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Jiang, Yu, and 姜宇. "Reliability-based transit assignment : formulations, solution methods, and network design applications." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2014. http://hdl.handle.net/10722/207991.
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Dithinde, Mahongo. "Characterisation of model uncertainty for reliability-based design of pile foundations." Thesis, Stellenbosch : Stellenbosch University, 2007. http://hdl.handle.net/10019.1/21612.
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Dissertation (PhD)--University of Stellenbosch, 2007.ENGLISH ABSTRACT: To keep pace with international trends, the introduction of geotechnical limit state design in South Africa is inevitable. To pave the way for implementation of limit state pile design in the country, the study quantifies model uncertainty in the classic static pile design formula under the Southern African geologic environment. The generated model uncertainty statistics are used to calibrate partial resistance factors in a reliability-based design framework. A series of pile performance predictions by the static formula are compared with measured performances. To capture the distinct soil types for the geologic region of Southern Africa as well as the local pile design and construction experience base, pile load tests and associated geotechnical data from the Southern African geologic environment are used. The methodology of collecting, compiling, and analyzing the pile load tests to derive the measured ultimate pile capacities is described. To facilitate the computation of the theoretical capacities, the site specific geotechnical data in the database are transformed to the desired engineering soil properties through well established empirical correlations. For a given pile test case, model uncertainty is presented in terms of a model factor computed as the ratio of the measured to the theoretical capacity, leading to n realisations of the model factor. To facilitate further interpretation and generalisation of the model factor realisation data, statistical analysis is carried out. The statistical analysis comprises of graphical representation by histograms, outliers detection and correction of erroneous values, and using the corrected data to compute the sample moments (mean, standard deviations, skewness and kurtosis) needed in reliability analysis. The analyses demonstrate that driven piles depict higher variability compared to bored piles irrespective of materials type. Furthermore, for a given pile installation method (driven or bored) the variability in non-cohesive materials is higher than that in cohesive materials. In addition to the above statistics, reliability analysis requires the theoretical probability distribution for the random variable under consideration. Accordingly it is demonstrated that the lognormal distribution is the most appropriate theoretical model for the model factor. Another key basis for reliability theory is the notion of randomness of the basic variables. To verify that the variation in the model factor is not explainable by deterministic variations in the database, an investigation of correlation of the model factor with underlying pile design parameters is carried out. It is shown that such correlation is generally weak. Correlation can have a significant impact on the calculated reliability index if not accounted for. Accordingly, the effects of the exhibited correlation is investigated through an approach based on regression theory in which systematic effects of design parameters are taken into account (generalised model factor). The model factor statistics from the conventional approach and those from the generalised model factor approach are used to determine reliability indexes implied by the current design practice. It is demonstrated that no significant improvement in values of the reliability indexes is gained by taking into account the effects of the weak correlation. The model factor statistics derived on the basis of the standard model factor approach are used to calibrate resistance factors. Four first order reliability methods are employed for the calibration of resistance factors. These include; the Mean Value First-Order Second Moment approach, an Approximate Mean Value First-Order Second Moment approach, the Advanced First-Order Second Moment approach using Excel spreadsheet, and the Advanced First-Order Second Moment approach (design point method). The resistance factors from the various calibration methods are presented for the target reliability index values of 2.0, 2.5, and 3.0. The analyses of the results demonstrate that for a given target reliability index, the resistance factors from the different methods are comparable. Furthermore, it is shown that for a given material type, the resistance factors are quite close irrespective of the pile installation method, suggesting differentiation of partial factors in terms of materials types only. Finally, resistance factors for use in probabilistic limit state pile design in South Africa are recommended.
AFRIKAANSE OPSOMMING: Ten einde in pas te bly met internasionale neigings, is dit onafwendbaar dat geotegniese limietstaat-ontwerp in Suid Afrika ingevoer word. Ter voorbereiding vir die plaaslike toepassing van limietstaatontwerp op heipale, kwantifiseer hierdie ondersoek onsekerheid rondom die model vir klassieke statiese heipaalontwerpformules in die Suid Afrikaanse geologiese omgewing. Die statistiek van modelonsekerheid wat gegenereer is, word gebruik om parsiële weerstandsfaktore in ’n betoubaarheid-gebasseerde ontwerpraamwerk te kalibreer. ’n Reeks voorspellings van die gedrag van heipale volgens die statiese formules word vergelyk met die gemete gedrag. Om die kenmerkende grond-tipes in die geologiese gebied van Suidelike Afrika sowel as die plaaslike ondervinding met heipaalontwerp en - konstruksie vas te lê, word heipaaltoetse en die gassosieerde geotegniese data vanuit hierdie geologiese omgewing gebruik. Die metodiek vir die versameling, saamstelling en analise van heipaaltoetse om uiterste kapasiteite daarvan te bepaal, word beskryf. Terreinspesifieke geotegniese data in die databasis word getransformeer na die vereisde ingenieurseienskappe volgens gevestigde empiriese korrelasies. Vir ’n gegewe heipaaltoets word modelonsekerheid weergegee in terme van ’n modelfaktor wat bereken word as die verhouding van die gemete tot die teoretiese kapasiteit waaruit n uitkomstes van die modelfaktor dus gegenereer word. Om verdere interpretasie en veralgemening van die modelfaktordata te vergemaklik, word ’n statistiese analise daarop uitgevoer. Die statistiese analise bestaan uit grafiese voorstellings deur middel van histogramme, uitkenning van uitskieters en verbetering van foutiewe waardes, waarna die statistiese momente (gemiddeld, standaardafwyking, skeefheid en kurtose) vir gebruik in betroubaarheidsanalise bereken word. Volgens die analises toon ingedrewe heipale ’n groter veranderlikheid as geboorde pale, ongeag die grondtipe. Verder is die veranderlikheid van heipale in kohesielose materiale hoër as in kohesiewe materiale, ongeag die installasiemetode (ingedrewe of geboor). Bykomend tot bogemelde statistiek, vereis betroubaarheidsanalise die teoretiese waarskynlikheidsdistribusie van die ewekansige veranderlike onder beskouing. Ooreenkomstig word illustreer dat die log-normale verspreiding die mees toepaslike verspreiding vir die modelfaktor is. ’n Verdere sleutelvereiste vir betroubaarheidsteorie is die mate van ewekansigheid van die basiese veranderlikes. Om te bepaal of die variasie in die modelfaktor nie deur deterministiese veranderlikes in die databasis verduidelik kan word nie, word ’n ondersoek na die korrelasie van die modelfaktor met onderliggende heipaalontwerpfaktore uitgevoer. Sodanige korrelasie is in die algemeen as laag bevind. Korrelasie kan ’n belangrike invloed op die berekende betroubaarheidsindeks hê indien dit nie in ag geneem word nie. Dienooreenkomstig word die effek van die getoonde korrelasie ondersoek met behulp van die metode van regressie-analise waarin sistematiese effekte van ontwerpparameters in berekening gebring word (veralgemeende modelfaktor). Die modelfaktorstatistiek wat volg uit die konvensionele benadering en dié van die veralgemeende benadering word gebruik om betroubaarheidsindekse te bepaal wat deur die bestaande ontwerppraktyk geïmpliseer word. Die bevinding is dat daar nie ’n noemenswaardige verbetering in die waardes van die betroubaarheidsindekse is wanneer die effek van die swak korrelasie in berekening gebring word nie. Die statistiek van die modelfaktor wat afgelei is volgens die standaardbenadering word gebruik om die weerstandsfaktore te kalibreer. Vier eerste-orde betroubaarheidsmetodes word gebruik om die weerstandsfaktore te kalibreer, naamlik die Gemiddelde Waarde Eerste-Orde Tweede Moment benadering, die Benaderde Gemiddelde Waarde Eerste-Orde Tweede Moment benadering, die Gevorderde Eerste-Orde Tweede Moment benadering waarin ’n Excel sigblad gebruik word en die Gevorderde Eerste-Orde Tweede Moment benadering (die ontwerppuntmetode). Die weerstandsfaktore vanaf die verskillende kalibrasiemetodes word weergegee vir waardes van 2.0, 2.5 en 3.0 van die teikenbetroubaarheidsindeks. ’n Ontleding van die resultate toon dat vir ’n gegewe teiken betroubaarheidsindeks die weerstandsfaktore vanaf die verskillende metodes vergelykbaar is. Verder word getoon dat vir ’n gegewe grondsoort, die weerstandsfaktore vir verskillende metodes van installasie van die heipaal nie veel verskil nie. Dit wil dus voorkom asof parsiële faktore in terme van die grondsoort uitgedruk kan word. Ten slotte word weerstandsfaktore vir gebruik in plastiese limietstaatontwerp van heipale in Suid Afrika aanbeveel.
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King, Jason Maxwell. "Risk Quantification and Reliability Based Design Optimization in Reusable Launch Vehicles." Wright State University / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=wright1291160215.
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Li, Lin. "Reliability Based Design for Slope Stabilization Using Drilled Shafts and Anchors." University of Akron / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=akron1415117410.
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Sun, Zhouming. "Reliability-based method for stability of mine entry design and evaluation." Morgantown, W. Va. : [West Virginia University Libraries], 2000. http://etd.wvu.edu/templates/showETD.cfm?recnum=1575.
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Thesis (Ph. D.)--West Virginia University, 2000.Title from document title page. Document formatted into pages; contains xi, 162 p. : ill. (some col.). Vita. Includes abstract. Includes bibliographical references (p. 156-161).
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Shayan, Shabnam. "System reliability-based design of 2D steel frames by advanced analysis." Thesis, The University of Sydney, 2013. http://hdl.handle.net/2123/10196.
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The design of steel frames by geometric and material nonlinear analysis also referred to as -inelastic‖ or -advanced‖ analysis, is permitted by most specifications such as AISC360-10 and AS4100. In these specifications, the strength of a structural frame can be determined by system analysis in lieu of checking member resistances to the specific provisions of the Specification, provided a comparable or higher level of structural reliability. In designing by advanced analysis, the system resistance factor is applied to the frame strength determined by analysis. Provided that the design strength exceeds the required strength, the design is deemed adequate, requiring no further check of individual member resistance. The system-based design of steel structures by advanced analysis leads to a more efficient structural design process and achieves a more uniform level of structural reliability. The main impediment to adopting the procedure in practical applications is the apparent difficulty in assigning an appropriate resistance factor to the structural system. This thesis illustrates the novel framework of the system design-by-analysis approach and how to determine suitable system resistance factors accounting for inherent uncertainties in the ultimate strength of a frame. All key parameters influencing the frame strength are modelled as random and Monte-Carlo type simulations are conducted. New approaches for modelling initial geometric imperfections and residual stresses are introduced. The simulation results for a series of 2D low-to-mid-rise steel frames, which represent typical steel building inventory as well as frames from the literature, are presented obtained according to the proposed methodology. Braced and moment resisting frames are analysed under various load combinations and the system resistance factors are derived for different reliability levels.
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Michaelides, Stylianos. "Physics-based process modeling, reliability prediction, and design guidelines for flip-chip devices." Diss., Georgia Institute of Technology, 1999. http://hdl.handle.net/1853/16028.
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Gaul, Nicholas John. "Modified Bayesian Kriging for noisy response problems and Bayesian confidence-based reliability-based design optimization." Diss., University of Iowa, 2014. https://ir.uiowa.edu/etd/1322.
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The objective of this study is to develop a new modified Bayesian Kriging (MBKG) surrogate modeling method that can be used to carry out confidence-based reliability-based design optimization (RBDO) for problems in which simulation analyses are inherently noisy and standard Kriging approaches fail. The formulation of the MBKG surrogate modeling method is presented, and the full conditional distributions of the unknown MBKG parameters are derived and coded into a Gibbs sampling algorithm. Using the coded Gibbs sampling algorithm, Markov chain Monte Carlo is used to fit the MBKG surrogate model.
A sequential sampling method that uses the posterior credible sets for inserting new design of experiment (DoE) sample points is proposed. The sequential sampling method is developed in such a way that the new DoE sample points added will provide the maximum amount of information possible to the MBKG surrogate model, making it an efficient and effective way to reduce the number of DoE sample points needed. Therefore, it improves the posterior distribution of the probability of failure efficiently.
Finally, a confidence-based RBDO method using the posterior distribution of the probability of failure is developed. The confidence-based RBDO method is developed so that the uncertainty of the MBKG surrogate model is included in the optimization process.
A 2-D mathematical example was used to demonstrate fitting the MBKG surrogate model and the developed sequential sampling method that uses the posterior credible sets for inserting new DoE. A detailed study on how the posterior distribution of the probability of failure changes as new DoE are added using the developed sequential sampling method is presented. Confidence-based RBDO is carried out using the same 2-D mathematical example. Three different noise levels are used for the example to compare how the MBKG surrogate modeling method, the sequential sampling method, and the confidence-based RBDO method behave for different amounts of noise in the response. A comparison of the optimization results for the three different noise levels for the same 2-D mathematical example is presented.
A 3-D multibody dynamics (MBD) engineering block-car example is presented. The example is used to demonstrate using the developed methods to carry out confidence-based RBDO for an engineering problem that contains noise in the response. The MBD simulations for this example were done using the commercially available MBD software package RecurDyn. Deterministic design optimization (DDO) was first done using the MBKG surrogate model to obtain the mean response values, which then were used with standard Kriging methods to obtain the sensitivity of the responses. Confidence-based RBDO was then carried out using the DDO solution as the initial design point.
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Ba-abbad, Mazen. "Reliability-based Design Optimization of a Nonlinear Elastic Plastic Thin-Walled T-Section Beam." Diss., Virginia Tech, 2004. http://hdl.handle.net/10919/27895.
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A two part study is performed to investigate the application of reliability-based design
optimization (RBDO) approach to design elastic-plastic stiffener beams with Tsection.
The objectives of this study are to evaluate the benefits of reliability-based
optimization over deterministic optimization, and to illustrate through a practical
design example some of the difficulties that a design engineer may encounter while
performing reliability-based optimization. Other objectives are to search for a
computationally economic RBDO method and to utilize that method to perform
RBDO to design an elastic-plastic T-stiffener under combined loads and with
flexural-torsional buckling and local buckling failure modes. First, a nonlinear
elastic-plastic T-beam was modeled using a simple 6 degree-of-freedom non-linear
beam element. To address the problems of RBDO, such as the high non-linearity and
derivative discontinuity of the reliability function, and to illustrate a situation where
RBDO fails to produce a significant improvement over the deterministic
optimization, a graphical method was developed. The method started by obtaining a
deterministic optimum design that has the lowest possible weight for a prescribed
safety factor (SF), and based on that design, the method obtains an improved
optimum design that has either a higher reliability or a lower weight or cost for the
same level of reliability as the deterministic design. Three failure modes were
considered for an elastic-plastic beam of T cross-section under combined axial and
bending loads. The failure modes are based on the total plastic failure in a beam
section, buckling, and maximum allowable deflection. The results of the first part
show that it is possible to get improved optimum designs (more reliable or lighter
weight) using reliability-based optimization as compared to the design given by
deterministic optimization. Also, the results show that the reliability function can be
highly non-linear with respect to the design variables and with discontinuous
derivatives. Subsequently, a more elaborate 14-degrees-of-freedom beam element
was developed and used to model the global failure modes, which include the
flexural-torsional and the out-of-plane buckling modes, in addition to local buckling
modes. For this subsequent study, four failure modes were specified for an elasticplastic
beam of T-cross-section under combined axial, bending, torsional and shear
loads. These failure modes were based on the maximum allowable in-plane, out-ofplane
and axial rotational deflections, in addition, to the web-tripping local buckling.
Finally, the beam was optimized using the sequential optimization with reliabilitybased
factors of safety (SORFS) RBDO technique, which was computationally very
economic as compared to the widely used nested optimization loop techniques. At
the same time, the SOPSF was successful in obtaining superior designs than the
deterministic optimum designs (either up to12% weight savings for the same level of
safety, or up to six digits improvement in the reliability for the same weight for a
design with Safety Factor 2.50).Ph. D.
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Al-Remal, Ahmad Mejbas. "Risk-based design of structures for fire." Thesis, University of Edinburgh, 2013. http://hdl.handle.net/1842/8924.
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Techniques of performance-based design in fire safety have developed notably in the past two decades. One of the reasons for departing from the prescriptive methods is the ability of performance-based methods to form a scientific basis for the cost-risk-benefit analysis of different fire safety alternatives. Apart from few exceptions, observation of past fires has shown that the structure’s contribution to the overall fire resistance was considerably underestimated. The purpose of this research is to outline a risk-based design approach for structures in fire. Probabilistic methods are employed to ascertain uniform reliability indices in line with the classical trend in code development. Modern design codes for complex phenomena such as fire have been structured to facilitate design computations. Prescriptive design methods specify fire protection methods for structural systems based on laboratory controlled and highly restrictive testing regimes. Those methods inherently assume that the tested elements behave similarly in real structures irrespective of their loading, location or boundary conditions. This approach is contested by many researchers, and analyses following fire incidents indicated alarming discrepancy between anticipated and actual structural behaviour during real fires. In formulating design and construction codes, code writers deal with the inherent uncertainties by setting a ceiling to the potential risk of failure. The latter process is implemented by specifying safety parameters, that are derived via probabilistic techniques aimed at harmonising the risks ensuing different load scenarios. The code structure addresses the probability of failure with adequate detail and accuracy. The other component of the risk metric, namely the consequence of failure, is a subjective field that assumes a multitude of variables depending on the context of the problem. In codified structural design, the severity of failure is implicitly embodied in the different magnitudes of safety indices applied to different modes of structural response. This project introduces a risk-based method for the design of structures in fire. It provides a coherent approach to a quantified treatment of risk elements that meets the demands of performance-based fire safety methods. A number of proposals are made for rational acceptable risk and reliability parameters in addition to a damage index with applications in structural fire safety design. Although the example application of the proposed damage index is a structure subjected to fire effects, the same rationale can be easily applied to the assessment of structural damage due to other effects.
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Liu, Wenyu. "System Reliability-Based Design of Three-Dimensional Steel Structures by Advanced Analysis." Thesis, The University of Sydney, 2016. http://hdl.handle.net/2123/16126.
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The system-based design of steel structure using advanced analysis leads to a more efficient structural design process and achieves a more uniform level of structural system reliability over the conventional member based design method because of the capability in capturing the limit state strength of a real structure and accounting system effects explicitly such as the load redistribution subsequent to first yielding. Current specifications such as AISC360-10 and AS4100 permitted the use of advanced analysis obviating the check of member resistances, thus provide a comparable or higher structural reliability. The main impediment to adopting this method in practical applications is the apparent difficulty in assigning an appropriate resistance factor to structural system especially in three-dimensional frames. This thesis illustrates the novel framework of the Direct Design Method (DDM) for designing structures by analysis without recourse to a structural design standard and proposed a methodology for development of suitable system resistance factors for accounting inherent uncertainties in ultimate strength of three-dimensional steel frames. New approaches for modelling initial geometric imperfections are introduced. The reliability assessment and system resistance factors for a series of three-dimensional low-to-mid-rise steel frames, which represent the current steel building inventory in Australia are obtained taking into account inherent uncertainty in material and geometry by Monte Carlo simulation. Braced and unbraced (sway) frames with regular and irregular configurations as well as various cross-section types and materials are analysed under various load combinations including gravity and gravity plus wind, and the system resistance factors are derived for different reliability levels to incorporate the effect of uncertainties on frame performance. Member cross-sections are selected to provide different system failure modes such as beam flexural-torsional buckling, beam/column yielding and spatial sway instability with torsion involve. Recommendations are made for the appropriate target reliabilities and associated system resistance factors for use in designing three-dimensional steel frames with both cold-formed Hollow Steel Section (HSS) and hot-rolled I-section at system level by advanced analysis.
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Mansour, Rami. "Reliability Assessment and Probabilistic Optimization in Structural Design." Doctoral thesis, KTH, Hållfasthetslära (Avd.), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-183572.
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Research in the field of reliability based design is mainly focused on two sub-areas: The computation of the probability of failure and its integration in the reliability based design optimization (RBDO) loop. Four papers are presented in this work, representing a contribution to both sub-areas. In the first paper, a new Second Order Reliability Method (SORM) is presented. As opposed to the most commonly used SORMs, the presented approach is not limited to hyper-parabolic approximation of the performance function at the Most Probable Point (MPP) of failure. Instead, a full quadratic fit is used leading to a better approximation of the real performance function and therefore more accurate values of the probability of failure. The second paper focuses on the integration of the expression for the probability of failure for general quadratic function, presented in the first paper, in RBDO. One important feature of the proposed approach is that it does not involve locating the MPP. In the third paper, the expressions for the probability of failure based on general quadratic limit-state functions presented in the first paper are applied for the special case of a hyper-parabola. The expression is reformulated and simplified so that the probability of failure is only a function of three statistical measures: the Cornell reliability index, the skewness and the kurtosis of the hyper-parabola. These statistical measures are functions of the First-Order Reliability Index and the curvatures at the MPP. In the last paper, an approximate and efficient reliability method is proposed. Focus is on computational efficiency as well as intuitiveness for practicing engineers, especially regarding probabilistic fatigue problems where volume methods are used. The number of function evaluations to compute the probability of failure of the design under different types of uncertainties is a priori known to be 3n+2 in the proposed method, where n is the number of stochastic design variables.QC 20160317