Multi-resolution multi-scale topology optimization -- a new paradigm
From MaRDI portal
Publication:1579964
DOI10.1016/S0020-7683(99)00251-6zbMath0981.74044OpenAlexW2042368310MaRDI QIDQ1579964
Publication date: 21 March 2002
Published in: International Journal of Solids and Structures (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/s0020-7683(99)00251-6
convergencedesign optimizationintermediate variablesdensity variablesmulti-resolution multi-scale topology optimizationwavelet-based variable space
Related Items
Design space optimization using a numerical design continuation method, A parallel and multiscale strategy for the parametric study of transient dynamic problems with friction, Topology optimization of elastic continua using restriction., An adaptive method for high-resolution topology design, Topology design optimization of geometrically nonlinear structures using meshfree method, A new interpolation technique to deal with fluid-porous media interfaces for topology optimization of heat transfer, Machine learning for topology optimization: physics-based learning through an independent training strategy, A study of multiscale wavelet-based elements for adaptive finite element analysis, An explicit length scale control approach in SIMP-based topology optimization, Volume preserving nonlinear density filter based on Heaviside functions, A computational paradigm for multiresolution topology optimization (MTOP), Enhanced analysis of design sensitivities in topology optimization, Improving multiresolution topology optimization via multiple discretizations, Topology optimization in wavelet space, A parallel strategy for the multiparametric analysis of structures with large contact and friction surfaces, Topology optimization method with nonlinear diffusion, An alternative truly-mixed formulation to solve pressure load problems in topology optimization, Explicit feature control in structural topology optimization via level set method, Topology optimization in B-spline space, Universal machine learning for topology optimization, Minimum length scale control in structural topology optimization based on the moving morphable components (MMC) approach, Filters in topology optimization based on Helmholtz-type differential equations
