Automatic generation of stochastically dominant failure modes of frame structures

Murotsu, Yoshisada; Okada, Hiroo; Taguchi, Katashi; Grimmelt, M.; Yonezawa, Masaaki

doi:10.1016/0167-4730(84)90004-3

Cited by 68 publications

(17 citation statements)

References 6 publications

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“…The test case used is a simple test case with truss bar structures based on one in [15] and [16], solving it with discrete cross-section types variables (as in [9]). The computational domain, loading and boundary conditions are shown in Fig.…”

Section: Test Casementioning

confidence: 99%

Comparing the Fully Stressed Design and the Minimum Constrained Weight Solutions in Truss Structures

Greiner

Emperador

Galván

et al. 2015

Computational Methods in Applied Sciences

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The optimization structural design problems of Fully Stressed Design (FSD) and Minimum Constrained Weight (MCW) are compared in this work in a simple truss test case with discrete cross-section type bar sizing, where both optimum designs are coincident. An analysis of the whole search space is included, and the optimization behaviour of evolutionary algorithms are compared with multiple population sizing and mutation rates in both problems. Results of average, best and standard deviation metrics indicate the success and the robustness of the methodology, as well as the fastest and easiest behaviour when considering the FSD case.

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Section: Test Casementioning

confidence: 99%

Comparing the Fully Stressed Design and the Minimum Constrained Weight Solutions in Truss Structures

Greiner

Emperador

Galván

et al. 2015

Computational Methods in Applied Sciences

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“…This was a six-bar truss structure shown in Fig. 2 and taken from an example in Murotsu et al (1984). The ultimate limit state of the truss based on resistance (stresses) was taken into account.…”

Section: Introductionmentioning

confidence: 99%

Truss topology optimization for mass and reliability considerations—co-evolutionary multiobjective formulations

Greiner

Hajela

2011

Struct Multidisc Optim

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The paper presents an approach for simultaneous optimization of structural mass and reliability in discrete truss structures. In addition to member sizing, the selection of an optimal topology from a pre-specified ground structure is a feature of the proposed methodology. To allow for a global search, optimization is performed using a multiobjective evolutionary algorithm. System reliability is based on a recently developed computational approach that is efficient and could be integrated within the framework of an evolutionary optimization process. The presence of multiple allowable topologies in the optimization process was handled through co-evolution in competing subpopulations. A unique feature of the algorithm is an automatic reunification of these populations using hypervolume measure-based indicator as reunification criterion to attain greater search efficiency. Numerical experiments demonstrate the computational advantages of the proposed method. These advantages become more pronounced for large-scale optimization problems, where the standard evolutionary approach fails to produce the desired results.

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“…Shao et al, 1999, proposed an improved simulation-based selective searching technique which genetic algorithm (GA) is used to find as small number of dominant failure modes. Kim et al, 2013, proposed a similar searching method to the one by (Murotsu et al, 1984), in that a GA scheme is used for search, but different in terms of two distinct GA search strategies such as searching direction and elitism. Therefore, dominant failure modes are obtained by a simulation-based selective searching technique employing a genetic algorithm the probabilities of the failure are computed by a matrix based system reliability (MSR) method.…”

Section: Selective Searching Technique For Dominant Fail-ure Modesmentioning

confidence: 99%

“…Therefore, it is infeasible in most cases to enumerate all the possible failure modes for system reliability analysis (Kim et al, 2013). In order to overcome this difficulty, many studies have focused on the possibility of using only dominant failure modes with significant likelihood, instead of using all possible failure modes (Moses et al, 1979;Murotsu et al, 1984). Shao et al, 1999, proposed an improved simulation-based selective searching technique which genetic algorithm (GA) is used to find as small number of dominant failure modes.…”

Section: Selective Searching Technique For Dominant Fail-ure Modesmentioning

confidence: 99%

“…Therefore, dominant failure modes are obtained by a simulation-based selective searching technique employing a genetic algorithm the probabilities of the failure are computed by a matrix based system reliability (MSR) method. In Murotsu et al, 1984, is documented many methods developed to identify dominant failure modes.…”

Section: Selective Searching Technique For Dominant Fail-ure Modesmentioning

confidence: 99%

See 1 more Smart Citation

Multi-Scale System Reliability Analysis

Esposito

Gomes

2015

Procedings of the XXXVI Iberian Latin American Congress on Computational Methods in Engineering

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Abstract. The development of methods that allow to numerically reproduce the actual behavior of real structural systems has challenged scientists and researchers and urged them to address issues that extend beyond the integrity of a system. Therefore, a series of new parameters must be taken into account to evaluate the failure of a real structural system, especially in redundant systems. In the present paper, an accurate technique is developed to satisfy the probabilistic analysis. The proposed method estimates the reliability of the system with techniques that enable detecting multiple failure modes and, using the chi-squared distribution, a one direction exact integration is performed to calculate the failure probability of each mode in a more precise way than conventional approximation and simulation methods. This technique is based on the conventional (HDM) Hyperspace Division Method procedures which approximate the limit state surface by a series of spherical segments for provide accurate estimates of failure probabilities of components or systems. Besides, in this work, nonlinearity is considered by adopting an elastic plasticity model with linear hardening. Numerical applications showed the accuracy and efficiency of the methodology in the evaluation of the failure probability of problems represented by high nonlinear limit state functions with multiple failure regions.

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Automatic generation of stochastically dominant failure modes of frame structures

Cited by 68 publications

References 6 publications

Comparing the Fully Stressed Design and the Minimum Constrained Weight Solutions in Truss Structures

Comparing the Fully Stressed Design and the Minimum Constrained Weight Solutions in Truss Structures

Truss topology optimization for mass and reliability considerations—co-evolutionary multiobjective formulations

Multi-Scale System Reliability Analysis

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