Structural and Multidisciplinary Optimization

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Stochastic optimization of acoustic response – a numerical and experimental comparison
Structural and Multidisciplinary Optimization - Tập 23 - Trang 405-411 - 2002
M. Tinnsten, P. Carlsson, M. Jonsson
The objective of the work presented is to compare results from numerical optimization with experimental data and to highlight and discuss the differences between two fundamentally different optimization methods. The problem domain is minimization of acoustic emission and the structure used in the work is a closed cylinder with forced vibration of one end. The optimization method used in this paper...... hiện toàn bộ
Exact optimal structural layouts for non-self-adjoint problems
Structural and Multidisciplinary Optimization - Tập 5 - Trang 204-206 - 1993
G. I. N. Rozvany, O. Sigmund, T. Lewiński, D. Gerdes, T. Birker
Using optimality criteria for trusses with displacement constraints, a truss layout is optimized for a point load and a given displacement in different directions, with a view to demonstrating some unexpected features of non-self-adjoint problems.
An alternative interpolation scheme for minimum compliance topology optimization
Structural and Multidisciplinary Optimization - Tập 22 - Trang 116-124 - 2014
M. Stolpe, K. Svanberg
We consider the discretized zero-one continuum topology optimization problem of finding the optimal distribution of two linearly elastic materials such that compliance is minimized. The geometric complexity of the design is limited using a constraint on the perimeter of the design. A common approach to solve these problems is to relax the zero-one constraints and model the material properties by a...... hiện toàn bộ
Two alternative ways for solving the coordination problem in multilevel optimization
Structural and Multidisciplinary Optimization - - 1993
Jaroslaw Sobieszczanski‐Sobieski
First-order sequential convex programming using approximate diagonal QP subproblems
Structural and Multidisciplinary Optimization - Tập 45 - Trang 479-488 - 2011
L. F. P. Etman, Albert A. Groenwold, J. E. Rooda
Optimization algorithms based on convex separable approximations for optimal structural design often use reciprocal-like approximations in a dual setting; CONLIN and the method of moving asymptotes (MMA) are well-known examples of such sequential convex programming (SCP) algorithms. We have previously demonstrated that replacement of these nonlinear (reciprocal) approximations by their own second ...... hiện toàn bộ
A deep reinforcement learning optimization framework for supercritical airfoil aerodynamic shape design
Structural and Multidisciplinary Optimization - - 2024
Ziyang Liu, Miao Zhang, Di Sun, Li Li, Gang Chen
In the context of traditional aerodynamic shape optimization design methods, the necessity to re-execute the complete optimization process when the initial shape changes poses significant challenges in engineering applications. These challenges encompass problems like data wastage and restricted ability for experience learning. We propose a policy learning-based optimization method that can automa...... hiện toàn bộ
Preliminary announcement
Structural and Multidisciplinary Optimization - Tập 7 - Trang 90-90 - 1994
Forthcoming papers
Structural and Multidisciplinary Optimization - - 1997
Selective dimension reduction method (DRM) to enhance accuracy and efficiency of most probable point (MPP)–based DRM
Structural and Multidisciplinary Optimization - Tập 61 Số 3 - Trang 999-1010 - 2020
Jeong Woo Park, Hyunkyoo Cho, Ikjin Lee
Multiparameter structural optimization using FEM and multipoint explicit approximations
Structural and Multidisciplinary Optimization - Tập 6 - Trang 7-14 - 1993
V. V. Toropov, A. A. Filatov, A. A. Polynkin
A unified approach to various problems of structural optimization, based on approximation concepts, is presented. The approach is concerned with the development of the iterative technique, which uses in each iteration the information gained at several previous design points (multipoint approximations) in order to better fit constraints and/or objective functions and to reduce the total number of F...... hiện toàn bộ
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