... optimisation radial basis function networks regression analysis sampling methods splines (mathematics) vehicle dynamics Vehicle crashworthiness is of great importance today to the automotive industry. A good rating in crashworthiness gives an automaker a strong argument for sales. Therefore...

... that can represent and propagate both aleatory and epistemic uncertainties, no matter what uncertainty propagation method is used. However, we note here that analytical approximation methods (e.g., FORM and SORM) and efficient sampling methods (e.g., importance sampling) can also be used within...

... directly at reducing the number of evaluations for both objective function and constraints. The proposed method builds on existing mode pursuing sampling method and incorporates two intriguing strategies: (1) generating more sample points in the neighborhood of the promising regions, and (2) biasing...

... Sampling Method for Probability of Failure Calculation ,” Struct. Safety 0167-4730 , 3 ( 2 ), pp. 109 – 115 . 10.1016/0167-4730(86)90012-3 Karamchandani , A. , Bjerager , P. , and Cornell , C. , 1989 , “ Adaptive Importance Sampling ,” Proceedings of the Fifth International...

... methods. Several examples are used to demonstrate the proposed methodology. 11 08 2009 11 03 2010 20 05 2010 20 05 2010 design engineering gradient methods Monte Carlo methods optimisation probability random processes reliability theory sampling methods...

... sampling methods variable fidelity optimization sequential sampling surrogate model Bayesian approach model fusion design confidence Variable-fidelity methods have been developed to solve optimization problems that involve simulations with extreme computational expenses ( 1 2 3...

... traditional reliability methods. 21 08 2006 13 08 2007 19 05 2008 failure analysis least squares approximations Monte Carlo methods reliability response surface methodology sampling methods structural engineering Monte Carlo simulation indicator function response surface...

...Rahul Rai; Matthew Campbell Sequential sampling refers to a set of experimental design methods where the next sample point is determined by information from previous experiments. This paper introduces a new sequential sampling method where optimization and user knowledge are used to guide...

... engineering optimisation sampling methods search problems discrete variable optimization metamodeling MPS black-box functions Assume that f ( x ) is positive on S [ f ] . In general, if f ( x ) is negative for some X ∊ S [ f...

... analysis sampling methods design engineering failure surface frontier reliability assessment discriminative sampling reliability analysis Conventionally, variation and uncertainties in materials, manufacturing, assembly, field usage, and so on are taken into consideration through safety...

..., and Adaptive and Interactive Modeling System. A real-world frontal impact design problem is used as an example, which is a complex, highly nonlinear, transient, dynamic, large deformation finite element model. To study the accuracy of the metamodel, the optimal Latin Hypercube Sampling method is used...

... problems. 13 02 2004 26 11 2004 Pareto optimisation design sampling methods Modern design problems often involve multiple objectives and are thus treated as multiobjective optimization (MOO) problems. Excluding methods dealing with uncertainties, in general MOO methods can...

..., and the results are shown to compare closely to those from a Latin hypercube sampling method. The SAMS technique is also demonstrated to yield computational savings of up to 90% relative to the sampling-based method. 04 11 2003 28 06 2004 process design stochastic processes sampling methods...

... circumstances. Under the framework of probabilistic optimization, we propose to use a most probable point (MPP) based importance sampling method, a method rooted in the field of reliability analysis, for evaluating the feasibility robustness. The advantages of this approach are discussed. Though our discussions...