An efficient strategy for reliability-based multidisciplinary design optimization using BLISS

Ahn, JoongHo; Kwon, Jin Hyuk

doi:10.1007/s00158-005-0565-6

Cited by 59 publications

(21 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These algorithms were proved to be more robust than HLRF-based algorithms in solving forward reliability problems [14]. In addition, they were also found to be more efficient in solving large scale constraintbased reliability problems [23,24]. Although this method has been used in solving forward reliability problems, this study is the first attempt to extend the applications of the BFGS formula to inverse reliability analysis.…”

Section: Mathematical Problems In Engineeringmentioning

confidence: 94%

HLRF‐BFGS‐Based Algorithm for Inverse Reliability Analysis

Ramesh

Mirza

Kang

2017

Mathematical Problems in Engineering

View full text Add to dashboard Cite

This study proposes an algorithm to solve inverse reliability problems with a single unknown parameter. The proposed algorithm is based on an existing algorithm, the inverse first-order reliability method (inverse-FORM), which uses the Hasofer Lind Rackwitz Fiessler (HLRF) algorithm. The initial algorithm analyzed in this study was developed by modifying the HLRF algorithm in inverse-FORM using the Broyden-Fletcher-Goldarb-Shanno (BFGS) update formula completely. Based on numerical experiments, this modification was found to be more efficient than inverse-FORM when applied to most of the limit state functions considered in this study, as it requires comparatively a smaller number of iterations to arrive at the solution. However, to achieve this higher computational efficiency, this modified algorithm sometimes compromised the accuracy of the final solution. To overcome this drawback, a hybrid method by using both the algorithms, original HLRF algorithm and the modified algorithm with BFGS update formula, is proposed. This hybrid algorithm achieves better computational efficiency, compared to inverse-FORM, without compromising the accuracy of the final solution. Comparative numerical examples are provided to demonstrate the improved performance of this hybrid algorithm over that of inverse-FORM in terms of accuracy and efficiency.

show abstract

Section: Mathematical Problems In Engineeringmentioning

confidence: 94%

HLRF‐BFGS‐Based Algorithm for Inverse Reliability Analysis

Ramesh

Mirza

Kang

2017

Mathematical Problems in Engineering

View full text Add to dashboard Cite

show abstract

“…An early paper on RBDO using SQP is presented by Ahn and Kwon (2006). Karadeniz et al (2009) optimized offshore towers using SQP and FORM.…”

Section: Pr[h(y ) < 0] ≈ (−β Hl )mentioning

confidence: 99%

Reliability-based design optimization using SORM and SQP

Strömberg

2017

Struct Multidisc Optim

View full text Add to dashboard Cite

In this work a second order approach for reliabilitybased design optimization (RBDO) with mixtures of uncorrelated non-Gaussian variables is derived by applying second order reliability methods (SORM) and sequential quadratic programming (SQP). The derivation is performed by introducing intermediate variables defined by the incremental iso-probabilistic transformation at the most probable point (MPP). By using these variables in the Taylor expansions of the constraints, a corresponding general first order reliability method (FORM) based quadratic programming (QP) problem is formulated and solved in the standard normal space. The MPP is found in the physical space in the metric of Hasofer-Lind by using a Newton algorithm, where the efficiency of the Newton method is obtained by introducing an inexact Jacobian and a line-search of Armijo type. The FORM-based SQP approach is then corrected by applying four SORM approaches: Breitung, Hohenbichler, Tvedt and a recent suggested formula. The proposed SORMbased SQP approach for RBDO is accurate, efficient and robust. This is demonstrated by solving several established benchmarks, with values on the target of reliability that are considerable higher than what is commonly used, for mixtures of five different distributions (normal, lognormal, Gumbel, gamma and Weibull). Established benchmarks are also generalized in order to study problems with large number of variables and several constraints. shown that the proposed approach efficiently solves a problem with 300 variables and 240 constraints within less than 20 CPU minutes on a laptop. Finally, a most well-know deterministic benchmark of a welded beam is treated as a RBDO problem using the proposed SORM-based SQP approach.

show abstract

“…Many research of reliability based MDO methods and various RBDO techniques was studied [34][35][36][37][38][39][40]. In this research, the CO method was implemented and combined with RBDO and PBDO methods [41].…”

Section: Rbdo/pbdo With Mdomentioning

confidence: 99%

Aircraft derivative design optimization considering global sensitivity and uncertainty of analysis models

Park¹,

Chung²,

Lee³

2016

International Journal of Aeronautical and Space Sciences

View full text Add to dashboard Cite

Aircraft manufacturing companies have to consider multiple derivatives to satisfy various market requirements. They modify or extend an existing aircraft to meet new market demands while keeping the development time and cost to a minimum. Many researchers have studied the derivative design process, but these research efforts consider baseline and derivative designs together, while using the whole set of design variables. Therefore, an efficient process that can reduce cost and time for aircraft derivative design is needed. In this research, a more efficient design process is proposed which obtains global changes from local changes in aircraft design in order to develop aircraft derivatives efficiently. Sensitivity analysis was introduced to remove unnecessary design variables that have a low impact on the objective function. This prevented wasting computational effort and time on low priority variables for design requirements and objectives. Additionally, uncertainty from the fidelity of analysis tools was considered in design optimization to increase the probability of optimization results. The Reliability Based Design Optimization (RBDO) and Possibility Based Design Optimization (PBDO) methods were proposed to handle the uncertainty in aircraft conceptual design optimization. In this paper, Collaborative Optimization (CO) based framework with RBDO and PBDO was implemented to consider uncertainty. The proposed method was applied for civil jet aircraft derivative design that increases cruise range and the number of passengers. The proposed process provided deterministic design optimization, RBDO, and PBDO results for given requirements.

show abstract

An efficient strategy for reliability-based multidisciplinary design optimization using BLISS

Cited by 59 publications

References 20 publications

HLRF‐BFGS‐Based Algorithm for Inverse Reliability Analysis

HLRF‐BFGS‐Based Algorithm for Inverse Reliability Analysis

Reliability-based design optimization using SORM and SQP

Aircraft derivative design optimization considering global sensitivity and uncertainty of analysis models

Contact Info

Product

Resources

About