Advanced Response Surface Method for Structural Reliability

2011 ◽  
Author(s):  
D.L. Allaix ◽  
V.I. Carbone ◽  
G. Mancini
Keyword(s):  
Response Surface ◽  
Response Surface Method ◽  
Structural Reliability ◽  
Surface Method

An Efficient Response Surface Method Using Givens Transformation for Structural Reliability Analysis

2012 ◽  
Vol 532-533 ◽  
pp. 408-411
Author(s):  
Wei Tao Zhao ◽  
Yi Yang ◽  
Tian Jun Yu
Keyword(s):  
Response Surface ◽  
Response Surface Method ◽  
Structural Reliability ◽  
Limit State ◽  
State Function ◽  
Limit State Function ◽  
Surface Method ◽  
Mathematical Techniques ◽  
Input Variables ◽  
Improved Accuracy

The response surface method was proposed as a collection of statistical and mathematical techniques that are useful for modeling and analyzing a system which is influenced by several input variables. This method gives an explicit approximation of the implicit limit state function of the structure through a number of deterministic structural analyses. However, the position of the experimental points is very important to improve the accuracy of the evaluation of failure probability. In the paper, the experimental points are obtained by using Givens transformation in such way these experimental points nearly close to limit state function. A Numerical example is presented to demonstrate the improved accuracy and computational efficiency of the proposed method compared to the classical response surface method. As seen from the result of the example, the proposed method leads to a better approximation of the limit state function over a large region of the design space, and the number of experimental points using the proposed method is less than that of classical response surface method.

Response surface method strategies coupled with NLFEA for structural reliability analysis of prestressed bridges

2021 ◽  
Author(s):  
Silvia J. Sarmiento Nova ◽  
Jaime Gonzalez-Libreros ◽  
Gabriel Sas ◽  
Rafael A. Sanabria Díaz ◽  
Maria C. A. Texeira da Silva ◽  
...  
Keyword(s):  
Reliability Analysis ◽  
Response Surface ◽  
Response Surface Method ◽  
Structural Reliability ◽  
Limit State ◽  
Material Behavior ◽  
Nonlinear Material ◽  
State Function ◽  
Surface Method ◽  
Highly Nonlinear

<p>The Response Surface Method (RSM) has become an essential tool to solve structural reliability problems due to its accuracy, efficacy, and facility for coupling with Nonlinear Finite Element Analysis (NLFEA). In this paper, some strategies to improve the RSM efficacy without compromising its accuracy are tested. Initially, each strategy is implemented to assess the safety level of a highly nonlinear explicit limit state function. The strategy with the best results is then identified and used to carry out a reliability analysis of a prestressed concrete bridge, considering the nonlinear material behavior through NLFEA simulation. The calculated value of &#120573; is compared with the target value established in Eurocode for ULS. The results showed how RSM can be a practical methodology and how the improvements presented can reduce the computational cost of a traditional RSM giving a good alternative to simulation methods such as Monte Carlo.</p>

Application of a new local effective constrained response surface method in structural reliability optimization design

2019 ◽  
Vol 36 (3) ◽  
pp. 1055-1078 ◽  
Author(s):  
Hailiang Su ◽  
Fengchong Lan ◽  
Yuyan He ◽  
Jiqing Chen
Keyword(s):  
Response Surface ◽  
Response Surface Method ◽  
Optimization Design ◽  
Structural Reliability ◽  
Reliability Optimization ◽  
Content Type ◽  
Meta Model ◽  
Proxy Model ◽  
Surface Method ◽  
Sampling Points

Purpose Meta-model method has been widely used in structural reliability optimization design. The main limitation of this method is that it is difficult to quantify the error caused by the meta-model approximation, which leads to the inaccuracy of the optimization results of the reliability evaluation. Taking the local high efficiency of the proxy model, this paper aims to propose a local effective constrained response surface method (LEC-RSM) based on a meta-model. Design/methodology/approach The operating mechanisms of LEC-RSM is to calculate the index of the local relative importance based on numerical theory and capture the most effective area in the entire design space, as well as selecting important analysis domains for sample changes. To improve the efficiency of the algorithm, the constrained efficient set algorithm (ESA) is introduced, in which the sample point validity is identified based on the reliability information obtained in the previous cycle and then the boundary sampling points that violate the constraint conditions are ignored or eliminated. Findings The computational power of the proposed method is demonstrated by solving two mathematical problems and the actual engineering optimization problem of a car collision. LEC-RSM makes it easier to achieve the optimal performance, less feature evaluation and fewer algorithm iterations. Originality/value This paper proposes a new RSM technology based on proxy model to complete the reliability design. The originality of this paper is to increase the sampling points by identifying the local importance of the analysis domain and introduce the constrained ESA to improve the efficiency of the algorithm.

RELIABILITY DESIGN EVALUATION AND OPTIMIZATION OF A NITROGEN GAS BOTTLE USING RESPONSE SURFACE METHOD

2010 ◽  
Vol 17 (02) ◽  
pp. 119-132 ◽  
Author(s):  
P. BHATTACHARJEE ◽  
K. RAMESH KUMAR ◽  
T. A. JANARDHAN REDDY
Keyword(s):  
Design Optimization ◽  
Response Surface ◽  
Response Surface Method ◽  
Structural Reliability ◽  
Operating Conditions ◽  
Optimization Under Uncertainty ◽  
Reliability Based Design Optimization ◽  
Nitrogen Gas ◽  
Reliability Based Design ◽  
Surface Method

Optimization of any aerospace product results in increasing payload capacity of space vehicles. Essentially weight, volume and cost are the main constraints. Design optimization studies for aerospace system are increasingly gaining importance. The problem of optimum design under uncertainty has been formulated as reliability-based design optimization. The reliability based optimization, which includes robustness requirements leads to multi-objective optimization under uncertainty. In this paper Reliability, based design optimization study is carried out under linear constraint optimization to minimize the weight of a nitrogen gas bottle with specified target reliability. Response surface method considering full factorial experiment is used to establish multiple regression equation for induced hoop stress and maximum strain. Necessary data pertaining to design, manufacturing and operating conditions are collected systematically for variability study. Structural reliability is evaluated using Advanced First-Order Second-Moment Method (AFOSM). Finally, optimization formulation established and it has been discussed in this paper.

Structural Reliability Analysis Using Fourier Orthogonal Neural Network Method

2013 ◽  
Vol 838-841 ◽  
pp. 360-363 ◽  
Author(s):  
Li Rong Sha ◽  
Yue Yang
Keyword(s):  
Neural Network ◽  
Reliability Analysis ◽  
Response Surface ◽  
Response Surface Method ◽  
Failure Probability ◽  
Structural Reliability ◽  
Random Variables ◽  
Structural Reliability Analysis ◽  
Surface Method ◽  
Structural Responses

In order to predict the failure probability of a complicated structure, the structural responses usually need to be predicted by a numerical procedure, such as FEM method. The response surface method could be used to reduce the computational effort required for reliability analysis. However the conventional response surface method is still time consuming when the number of random variables is large. In this paper, a Fourier orthogonal neural network (FONN)-based response surface method is proposed. In this method, the relationship between the random variables and structural responses is established using FONN models. Then the FONN model is connected to the first order and second moment method (FORM) to predict the failure probability. Numerical example result shows that the proposed approach is efficient and accurate, and is applicable to structural reliability analysis.

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