due to the probabilistic nature and uncertainties of structural parameters, reliability-based optimization will enable engineers to account for the safety of the structures and allow for its decision making applicability. thus, reliability-based design will substitute deterministic rules of codes of practice. space structures are of those types that have an exceedingly high range of applicabili...

This paper built the 100% frontal crash model of minibus, 8 thickness components which have obvious effect on vehicle performance were selected as design variables, and choose appropriate evaluation index responses. Use DOE experimental method to get 70 set training data Kriging approximate based data. The is optimized by PSO algorithm, in scheme, amax m has decreased 7.6% 0.87%, D1, D2 D3 7.7%...

Design of blast resistant structures is an important subject in structural engineering, attracting the attention of governments, researchers, and engineers. Thus, given the benefits of optimization in engineering, development and assessment of optimization methods for optimum design of structures against blast is of great importance. In this research, multi-objective optimization of steel momen...

Due to the favorable performance of structural topology optimization to create a proper understanding in the early stages of design, this issue is taken into consideration from the standpoint of research or industrial application in recent decades. Over the last three decades, several methods have been proposed for topology optimization. One of the methods that has been effectively used in stru...

One primary problem in shape optimization of structures is making a robust link between design model (geometric description) and analysis model. This paper investigates the potential of Isogeometric Analysis (IGA) for solving this problem. The generic framework of shape optimization of structures is presented based on Isogeometric analysis. By discretization of domain via NURBS functions, the a...

Constrained optimization problems have a wide range of applications in science, economics, and engineering. In this paper, a neural network model is proposed to solve a class of nonsmooth constrained optimization problems with a nonsmooth convex objective function subject to nonlinear inequality and affine equality constraints. It is a one-layer non-penalty recurrent neural network based on the...