Advanced probabilistic structural analysis method for implicit performance functions

Wu, Y.-T.; Millwater, Harry; Cruse, T. A.

doi:10.2514/3.25266

Cited by 394 publications

(82 citation statements)

References 7 publications

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“…The AMV method provides a bridge between a crude mean value (MV) based analysis and an accurate Monte Carlo method based analysis of the cumulative probability distribution function [11]. It is, in general, a substantially more accurate method than the MV method, with a minor increase in the number of calculations required.…”

Section: Advanced Mean Value Methodsmentioning

confidence: 99%

Probabilistic finite element analysis of residual stress formation in shrink-fit ceramic/steel gun barrels

Grujičić

DeLong

Derossett

2002

Proceedings of the Institution of Mechanical Engineers, Part L:

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The development of residual stresses in a hybrid a-SiC lining/CrMoV steel jacket gun barrel during shrink tting of the jacket over the lining is studied using a probabilistic nite element analysis. Particular attention is given to understanding the development of the axial compressive stress in the ceramic lining, since this stress (if suf ciently high) can prevent lining failure caused by formation and growth of circumferential cracks near the barrel ends. To quantify the effect of variability in various design, material and process parameters on the magnitude and the distribution of the axial residual stress, a probabilistic structural analysis approach, known as the advanced mean value (AMV) method, is used, enabling determination of the cumulative distribution function for failure of the lining. The results obtained are validated using the adaptive importance sampling (AIS) method, an ef cient direct statistical sampling technique. Lastly, the corresponding sensitivity factors which quantify the effect of variability in each parameter on the magnitude of axial residual stresses in the ceramic lining are computed. The results indicate that the loss of the compressive axial stress in the lining near the barrel ends is affected to the greatest extent by the magnitude of the friction coef cient at the lining/barrel interface.

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Section: Advanced Mean Value Methodsmentioning

confidence: 99%

Probabilistic finite element analysis of residual stress formation in shrink-fit ceramic/steel gun barrels

Grujičić

DeLong

Derossett

2002

Proceedings of the Institution of Mechanical Engineers, Part L:

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“…We also point out that problem can be solved by efficient schemes already developed in the literature. This problem is here solved by using the advanced mean value algorithm, originally proposed in the work of Wu et al Besides, in this work, the interest points of the structure (the points where we find the Worst Case Scenarios) are taken as Gauss nodes inside the finite elements.…”

Section: Proposed Approachmentioning

confidence: 99%

Reliability‐based topology optimization of structures under stress constraints

Santos

Torii

Novotny

2018

Numerical Meth Engineering

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Summary In this paper, we propose an approach for reliability‐based design optimization where a structure of minimum weight subject to reliability constraints on the effective stresses is sought. The reliability‐based topology optimization problem is formulated by using the performance measure approach, and the sequential optimization and reliability assessment method is employed. This strategy allows for decoupling the reliability‐based topology optimization problem into 2 steps, namely, deterministic topology optimization and reliability analysis. In particular, the deterministic structural optimization problem subject to stress constraints is addressed with an efficient methodology based on the topological derivative concept together with a level‐set domain representation method. The resulting algorithm is applied to some benchmark problems, showing the effectiveness of the proposed approach.

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“…The advanced mean value (AMV) method [4,5] combines the information from the mean value first-order (MVFO) step and one additional deterministic analysis to obtain a substantially improved reliability estimate. Several more sophisticated reliability-analysis techniques have been developed to overcome the difficulty of FORM.…”

confidence: 99%

“….15 is used to calculate the motor torque T. For this particular example, the advanced mean value method (AMV) [4,5] estimated the system reliability accurately and efficiently. Figure 38.6 shows the calculated cumulative distribution If the estimated reliability is not satisfactory, a reliability-based design optimization (RBDO) [43][44][45][46] algorithm can be used to change the mean values of the six random variables so that the reliability requirement is met.…”

Section: Glass Guidance Design Reliabilitymentioning

confidence: 99%

Probabilistic Analysis and Design in Automotive Industry

Mourelatos¹,

Tu²,

Ding³

2004

Engineering Design Reliability Handbook

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Delivering reliable, high-quality products at low cost has become the key to survival in today's global economy. The presence of uncertainty in the analysis and design of engineering systems has always been recognized. Traditional deterministic analysis accounts for these uncertainties through the use of empirical safety factors. These safety factors are derived from past experience and do not provide quantifiable measures of the frequency at which failure will occur.Engineering design usually involves a trade-off between maximizing reliability at the component or system level while achieving cost targets. In contrast to the traditional deterministic design, probabilistic analysis provides the required information for optimum design and accomplishes both goals simultaneously. In the automotive industry, quality products are vehicles whose specifications, as manufactured, meet customer requirements. Given the uncertainties in loads, materials, and manufacturing, modern methods of reliability analysis should be used to ensure automotive quality in terms of reliability measures.In large-scale systems, often encountered in the automotive and aerospace industries among others, reliability predictions based on expensive full-scale tests are not economically feasible. Efficient computational methods represent a far better alternative. The first requirement of a computational reliability analysis is to develop a quantitative model of the behavior of interest. Subsequently, the statistical behavior is defined for all random variables involved in the limit-state function that separates the failure and the Zissimos P. Mourelatos

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Advanced probabilistic structural analysis method for implicit performance functions

Cited by 394 publications

References 7 publications

Probabilistic finite element analysis of residual stress formation in shrink-fit ceramic/steel gun barrels

Probabilistic finite element analysis of residual stress formation in shrink-fit ceramic/steel gun barrels

Reliability‐based topology optimization of structures under stress constraints

Probabilistic Analysis and Design in Automotive Industry

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