scholarly journals Density gradient‐based adaptive refinement of analysis mesh for efficient multiresolution topology optimization

2021 ◽  
Author(s):  
Francesco Mezzadri ◽  
Xiaoping Qian
Keyword(s):  
Topology Optimization ◽  
Density Gradient ◽  
Adaptive Refinement ◽  
Gradient Based ◽  
Multiresolution Topology Optimization

A Density Gradient Approach to Topology Optimization Under Design-Dependent Boundary Loading

2018 ◽  
Author(s):  
Cunfu Wang ◽  
Xiaoping Qian
Keyword(s):  
Topology Optimization ◽  
Density Gradient ◽  
Optimization Method ◽  
Spatial Gradient ◽  
Computationally Efficient ◽  
Physical Density ◽  
Gradient Based ◽  
Design Dependent Loads ◽  
Previous Iteration ◽  
Gradient Approach

The paper proposes a density gradient based approach to topology optimization under design-dependent boundary loading. In the density-based topology optimization method, we impose the design dependent loads through spatial gradient of the density. We transform design-dependent boundary loads into a volume form through volume integral of density gradient. In many applications where loadings only need to be exerted on partial boundary, we introduce an auxiliary loading density to keep track of the loading boundary. During the optimization, the loading density is updated by tracking the changes of the physical density in the vicinity of the loading boundary at previous iteration. The proposed approach is easy to implement and computationally efficient. In addition, by adding more auxiliary density fields, the proposed approach is applicable to multiple design-dependent loads. To prevent the intersection of different loading boundaries, a Heaviside projection based integral constraint is developed. Both heat conduction problems under convection loading and elastic problems under hydrostatic pressure loading are presented to illustrate the effectiveness and efficiency of the method.

scholarly journals Density gradient based regularization of topology optimization problems

PAMM ◽  
2005 ◽  
Vol 5 (1) ◽  
pp. 423-424 ◽  
Author(s):  
Gregor Kotucha ◽  
Klaus Hackl
Keyword(s):  
Topology Optimization ◽  
Density Gradient ◽  
Optimization Problems ◽  
Gradient Based

An Adaptive EFG-FE Computational Model for Thermal Elasto-Plastic Frictional Contact Problems

2008 ◽  
Vol 33-37 ◽  
pp. 821-826
Author(s):  
Zheng Zhang ◽  
Geng Liu ◽  
Tian Xiang Liu
Keyword(s):  
Frictional Heating ◽  
Contact Problems ◽  
Coupling Model ◽  
Adaptive Refinement ◽  
Frictional Heat ◽  
Plastic Behavior ◽  
Initial Stiffness ◽  
Gradient Based ◽  
Local Adaptive Refinement ◽  
The Cost

An adaptive meshless element-free Galerkin-finite element (EFG-FE) coupling model for thermal elasto-plastic contact problems is developed to investigate the influences of the steady-state frictional heating on the contact performance of two contacting bodies. The thermal elasto-plastic contact problems using the initial stiffness method is presented. The local adaptive refinement strategy and the strain energy gradient-based error estimation for EFG-FE coupling method are combined. The adaptive meshless model takes into account the temperature variation, micro plastic flow, and the coupled thermo-elasto-plastic behavior of the materials, considering the strain-hardening property of the materials and temperature-dependent yield strength. The adaptive model is verified through the contact analysis of a cylinder with an elasto-plastic plane. The thermal effects on the contact pressure, stresses distributions with certain frictional heat inputs are studied. The results show that the accuracy of the solutions from the adaptive refinement model is satisfactory but the cost of the CPU time is much less than that for the uniform refinement calculation.

Finding Better Local Optima in Topology Optimization via Tunneling

2018 ◽  
Author(s):  
Shanglong Zhang ◽  
Julián A. Norato
Keyword(s):  
Topology Optimization ◽  
Optimization Problems ◽  
Structural Response ◽  
Free Form ◽  
Local Optima ◽  
Design Representation ◽  
Tunneling Method ◽  
Optimization Parameters ◽  
Gradient Based ◽  
Geometric Primitives

Topology optimization problems are typically non-convex, and as such, multiple local minima exist. Depending on the initial design, the type of optimization algorithm and the optimization parameters, gradient-based optimizers converge to one of those minima. Unfortunately, these minima can be highly suboptimal, particularly when the structural response is very non-linear or when multiple constraints are present. This issue is more pronounced in the topology optimization of geometric primitives, because the design representation is more compact and restricted than in free-form topology optimization. In this paper, we investigate the use of tunneling in topology optimization to move from a poor local minimum to a better one. The tunneling method used in this work is a gradient-based deterministic method that finds a better minimum than the previous one in a sequential manner. We demonstrate this approach via numerical examples and show that the coupling of the tunneling method with topology optimization leads to better designs.

scholarly journals QR-patterns: artefacts in multiresolution topology optimization

2018 ◽  
Vol 58 (4) ◽  
pp. 1335-1350 ◽  
Author(s):  
Deepak K. Gupta ◽  
Matthijs Langelaar ◽  
Fred van Keulen
Keyword(s):  
Topology Optimization ◽  
Multiresolution Topology Optimization

scholarly journals Data-Driven Additive Manufacturing Constraints for Topology Optimization

2018 ◽  
Author(s):  
Benjamin M. Weiss ◽  
Joshua M. Hamel ◽  
Mark A. Ganter ◽  
Duane W. Storti
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
Optimal Designs ◽  
Data Driven ◽  
Constraint Function ◽  
Manufacturing Constraint ◽  
Gradient Based ◽  
Fixed Radius ◽  
Different Shapes ◽  
Moving Morphable Components

The topology optimization (TO) of structures to be produced using additive manufacturing (AM) is explored using a data-driven constraint function that predicts the minimum producible size of small features in different shapes and orientations. This shape- and orientation-dependent manufacturing constraint, derived from experimental data, is implemented within a TO framework using a modified version of the Moving Morphable Components (MMC) approach. Because the analytic constraint function is fully differentiable, gradient-based optimization can be used. The MMC approach is extended in this work to include a “bootstrapping” step, which provides initial component layouts to the MMC algorithm based on intermediate Solid Isotropic Material with Penalization (SIMP) topology optimization results. This “bootstrapping” approach improves convergence compared to reference MMC implementations. Results from two compliance design optimization example problems demonstrate the successful integration of the manufacturability constraint in the MMC approach, and the optimal designs produced show minor changes in topology and shape compared to designs produced using fixed-radius filters in the traditional SIMP approach. The use of this data-driven manufacturability constraint makes it possible to take better advantage of the achievable complexity in additive manufacturing processes, while resulting in typical penalties to the design objective function of around only 2% when compared to the unconstrained case.

Multi-Component Topology Optimization for Powder Bed Additive Manufacturing (MTO-A)

2018 ◽  
Author(s):  
Yuqing Zhou ◽  
Tsuyoshi Nomura ◽  
Kazuhiro Saitou
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
Simultaneous Optimization ◽  
Previous Attempt ◽  
Numerical Instability ◽  
Feature Size ◽  
Powder Bed ◽  
Nonlinear Projection ◽  
Gradient Based ◽  
Length Width

This paper presents a gradient-based multi-component topology optimization (MTO) method for structures assembled from components made by powder bed additive manufacturing. It is built upon our previous work on the continuously-relaxed MTO framework utilizing the concept of fractional component membership. The previous attempt on the integration of the relaxed MTO framework with additive manufacturing constraints, however, suffered from numerical instability for larger size problems, limiting its application to 2D low-resolution examples. To overcome this difficulty, this paper proposes an improved MTO formulation based on a design field regularization and a nonlinear projection of component membership variables, with a focus on powder bed additive manufacturing. For each component, constraints on the maximum allowable build volume (i.e., length, width, and height), the elimination of enclosed voids, and the minimum printable feature size are imposed during the simultaneous optimization of the overall base topology and component partitioning. The scalability of the new MTO formulation is demonstrated by a few 2D examples with much higher resolution than previously reported, and the first reported 3D example of MTO.

Note on spatial gradient operators and gradient-based minimum length constraints in SIMP topology optimization

2019 ◽  
Vol 60 (1) ◽  
pp. 393-400 ◽  
Author(s):  
Kaike Yang ◽  
Eduardo Fernandez ◽  
Cao Niu ◽  
Pierre Duysinx ◽  
Jihong Zhu ◽  
...  
Keyword(s):  
Topology Optimization ◽  
Minimum Length ◽  
Spatial Gradient ◽  
Gradient Based
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