• Structural Engineering and Mechanics
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• v.71 no.4
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• pp.329-339
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• 2019

Assessment of failure probability, especially for a complex structure, requires a considerable number of calls to the numerical model. Reliability methods have been developed to decrease the computational time. In this approach, the original numerical model is replaced by a surrogate model which is usually explicit and much faster to evaluate. The current paper proposed an efficient reliability method based on Monte Carlo simulation (MCS) and multi-gene genetic programming (MGGP) as a robust variant of genetic programming (GP). GP has been applied in different fields; however, its application to structural reliability has not been tested. The current study investigated the performance of MGGP as a surrogate model in structural reliability problems and compares it with other surrogate models. An adaptive Metropolis algorithm is utilized to obtain the training data with which to build the MGGP model. The failure probability is estimated by combining MCS and MGGP. The efficiency and accuracy of the proposed method were investigated with the help of five numerical examples.

• Structural Engineering and Mechanics
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• v.23 no.5
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• pp.455-468
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• 2006

Smart structural systems are defined as ones that demonstrate the ability to modify their characteristics and/or properties in order to respond favorably to unexpected severe loading conditions. The performance of such a task requires a set of additional components to be integrated within such systems. These components belong to three major categories, sensors, processors and actuators. It is wellknown that all structural systems entail some level of uncertainty, because of their extremely complex nature, lack of complete information, simplifications and modeling. Similarly, sensors, processors and actuators are expected to reflect a similar uncertain behavior. As it is imperative to be able to evaluate the impact of such components on the behavior of the system, it is as important to ensure, or at least evaluate, the reliability of such components. In this paper, a system model for reliability assessment of smart structural systems is outlined. The presented model is considered a necessary first step in the development of a reliability assessment algorithm for smart structural systems. The system model outlines the basic components of the system, in addition to, performance functions and inter-relations among individual components. A fault tree model is developed in order to aggregate the individual underlying component reliabilities into an overall system reliability measure. Identification of appropriate limit states for all underlying components are beyond the scope of this paper. However, it is the objective of this paper to set up the necessary framework for identifying such limit states. A sample model for a three-story single bay smart rigid frame, is developed in order to demonstrate the proposed framework.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1997.10a
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• pp.145-154
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• 1997

The results of optimum design by the deterministic approach adopted in the current design codes depend upon the safety levels of the applied code. But, it is now generally recognized that structural problems are nondeterministic and, consequently, that engineering optimum design must cope with uncertainties. Therefore, it is not an overstatement to affirm that the combination of reliability-based design procedures and optimization techniques is the only means of providing a powerful tool to obtain a practical optimum design solution. In the paper, reliability based optimum design procedure as a rational approach to optimum structural design is presented. The design constraints are formulated based on the ASD, LRFD and reliability theories. The reliability analysis is based on an advanced first-order second moment approach. Uncertainties in the structural strength and loading due to inherent variability as well as modeling and prediction errors are included in failure due to combined bending and shear. For the realistic reliability-based optimization of continuous steel box girder bridges, interactive non-linear limit state model is formulated based on the von Mises's combined stress yield criterion. Comparative results are presented when the ASD criteria are used for the optimum design of a structure under reliability constraints. In addition, this study comparatively shows the results of the optimum design for various criteria of design codes.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.884-891
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• 2020

The collapse of bridges can cause massive casualties and economic losses. Therefore, it is thus essential to evaluate the structural safety of bridges. For this task, structural reliability analysis, considering various bridge-related uncertainty factors, is often used. This paper proposes a new computational platform to perform structural reliability analysis for bridges and evaluate their structural safety under various loading conditions. For this purpose, a software package of reliability analysis, Finite Element Reliability Using MATLAB (FERUM), was integrated with MIDAS/CIVIL, which is a widely-used commercial software package specialized for bridges. Furthermore, a graphical user interface (GUI) control module has been added to FERUM to overcome the limitations of software operation. In this study, the proposed platform was applied to a simple frame structure, and the analysis results of the FORM (First-Order Reliability Method) and MCS (Monte Carlo simulation), which are representative reliability analysis methods, were compared. The proposed platform was verified by confirming that the calculated failure probability difference was less than 5%. In addition, the structural safety of a pre-stressed concrete (PSC) bridge was evaluated considering the KL-510 vehicle model. The proposed new structural reliability analysis platform is expected to enable an effective reliability-based safety evaluation of bridges.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1998.10a
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• pp.61-68
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• 1998

It has become important to evaluate the qualitive reliability and condition assessment of existing structural systems in order to establish a rational program for repair and maintenance. Since most of if existing structural system may suffer from defect corrosion and damage, it is necessary to account for their effects in fuzzy reliability analysis, In this paper, an attempt is made to develope a reliability analysis for damaged structural systems using failure possibility theory. Damage state is specified in terms of linguistic valiables using natural language information and numerical information, which are defined by fuzzy sets. Using a subjective condition index of failure possibility and information of the damage state is introduced into the calculation of failure probability. The subjective condition index of quantitative and qualitative analysis method is newly proposed based on the fuzzy set operations, namely logical product, drastic product, logical sum and drastic sum

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2001.04a
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• pp.102-109
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• 2001

In order to take account of the statistical properties of probability variables used in the structural analysis, the conventional approach using the safety factor based on past experience usually estimated the safety of a structure. The real structures could only be analyzed with the error in estimation of loads, material characters and the dimensions of the members. But the errors should be considered systematically in the structural analysis. Structural safety could not precisely be appraised by the traditional structural design concept. Recently, new approach based on the probability concept has been applied to the assessment of structural safety using the reliability concept. Thus, the computer program by the Probabilistic FEM is developed by incorporating the probabilistic concept into the conventional FEM method. This paper estimated for the reliability of a plane stress structure by Advanced First-Order Second Moment method using von Mises, Tresca and Mohr-Coulomb failure criterions. The reliability index and failure probability of attained by the Monte Carlo Simulation method with the von Mises criterion were same as PFEM, but the Monte Carlo Simulation were very time-consuming. The variance of member thickness and load could influence the reliability and failure probability most sensitively among the design variables from the results of the parameter analysis. And proper failure criterion must be used to design safely.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1991.04a
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• pp.34-42
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• 1991

This study is directed for the development of an efficient system-level Importance Sampling Technique for system reliability analysis of bridge structures Many methods have been proposed for structural reliability assessment purposes, such as the First-order Second-Moment Method, the Advanced Second-Moment Method, Computer Simulation, etc. The Importance Sampling Technique can be employed to obtain accurate estimates of the required probability with reasonable computation effort. Based on the observation and the results of application, it nay be concluded that Importance Sampling Method is a very effective tool for the system reliability analysis.

• Structural Engineering and Mechanics
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• v.65 no.6
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• pp.751-760
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• 2018

Damages in concrete structures due to aging and other factors could be a serious and immense matter. Making the best selection of the most viable and practical repairing and strengthening techniques are relatively difficult tasks using traditional methods of structural analyses. This is due to the fact that the traditional methods used for assessing aging structure are not fully capable when considering the randomness in strength, loads and cost. This paper presents a reliability-based methodology for assessing reinforced concrete members. The methodology of this study is based on probabilistic analysis, using statistics of the random variables in the performance function equations. Principles of reliability updating are used in the assessment process, as new information is taken into account and combined with prior probabilistic models. The methodology can result in a reliability index ${\beta}$ that can be used to assess the structural component by comparing its value with a standard value. In addition, these methods result in partial safety factor values that can be used for the purpose of strengthening the R/C elements of the existing structure. Calculations and computations of the reliability indices and the partial safety factors values are conducted using the First-order Reliability Method and Monte Carlo simulation.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2001.10a
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• pp.425-431
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• 2001

In order to take account of the statistical properties of probability variables used in the structural analysis, the conventional approach using the safety factor based on past experience usually estimated the safety of a structure. The real structures could only be analyzed with the error in estimation of loads, material characters and the dimensions of the members. But the errors should be considered systematically in the structural analysis. Structural safety could not precisely be appraised by the traditional structural design concept. Recently, new approach based on the probability concept has been applied to the assessment of structural safety using the reliability concept. In this study, safety of structures will estimated by the reliability analysis with commercial structural software that has the tools of nonlinear elastic-plastic 3-D analysis. Experimental test result is compared to results from this research and Coan/sup 1)/ In this paper, AFOSM(Advanced First-Order Second Moment method) is applied with von Mises, Tresca and Mohr-Coulomb failure criterions. The reliability index β and probability of failure P/sub f/ can be obtained by following this practical procedure as judgement a safety of structures and necessity of reinforcing.

• Journal of the Korea institute for structural maintenance and inspection
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• v.7 no.4
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• pp.217-224
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• 2003

The objective of this paper is to suggest the technique of program to perform structural optimization design after reliability analysis to consider the uncertainties of structural reponses. AFOSM method is used for reliability analysis then, structural optimization design is developed for 10-bar truss and 3 span 10 stories planar frame model is subject to reliability indices and probability of failure by reliability analysis. SQP method is used for optimization design method, this method has many attractions. As a result of analyzing with having and not having constraints and uncertainty, the minimum weight of truss and planar frame increased respectively 20.92% and average 8.08%.