scholarly journals Multiscale, thermomechanical topology optimization of self-supporting cellular structures for porous injection molds

2019 ◽  
Vol 25 (9) ◽  
pp. 1482-1492
Author(s):  
Tong Wu ◽  
Andres Tovar
Keyword(s):  
Topology Optimization ◽  
Mechanical Performance ◽  
Mechanical Load ◽  
Design Method ◽  
Three Dimensional ◽  
Optimization Method ◽  
Cellular Structures ◽  
Injection Mold ◽  
Computationally Efficient ◽  
Content Type

Purpose This paper aims to establish a multiscale topology optimization method for the optimal design of non-periodic, self-supporting cellular structures subjected to thermo-mechanical loads. The result is a hierarchically complex design that is thermally efficient, mechanically stable and suitable for additive manufacturing (AM). Design/methodology/approach The proposed method seeks to maximize thermo-mechanical performance at the macroscale in a conceptual design while obtaining maximum shear modulus for each unit cell at the mesoscale. Then, the macroscale performance is re-estimated, and the mesoscale design is updated until the macroscale performance is satisfied. Findings A two-dimensional Messerschmitt Bolkow Bolhm (MBB) beam withstanding thermo-mechanical load is presented to illustrate the proposed design method. Furthermore, the method is implemented to optimize a three-dimensional injection mold, which is successfully prototyped using 420 stainless steel infiltrated with bronze. Originality/value By developing a computationally efficient and manufacturing friendly inverse homogenization approach, the novel multiscale design could generate porous molds which can save up to 30 per cent material compared to their solid counterpart without decreasing thermo-mechanical performance. Practical implications This study is a useful tool for the designer in molding industries to reduce the cost of the injection mold and take full advantage of AM.

Application of topology optimization method for the gothic greenhouse design

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jalal Javadi Moghaddam ◽  
Davood Momeni ◽  
Ghasem Zarei
Keyword(s):  
Topology Optimization ◽  
Safety Factor ◽  
Structural Design ◽  
Volume Fraction ◽  
Design Method ◽  
Optimization Method ◽  
Content Type ◽  
Final Design ◽  
Structure Strength ◽  
Structural Compliance

Purpose This research presents a design method for designing greenhouse structures based on topology optimization. Moreover, the structural design of a gothic greenhouse is proposed in which its structural strength has been improved by using this proposed method. In this method, the design of the structure is done mathematically; therefore, in the design process, more attention can be focused on the constraint space and boundary conditions. It was also shown how the static reliability and fatigue coefficients will change as a result of the design of the greenhouse structure with this method. Another purpose of this study is to find the weakest part of the greenhouse structure against lateral winds and other general loads on the greenhouse structure. Design/methodology/approach In the proposed method, the outer surface and the allowable volume as a constraint domain were considered. The desired loads can be located on the constraint domain. The topology optimization was used to minimize the mass and structural compliance as the objective function. The obtained volume was modified for simplifying the construction. The changes in the shape of the greenhouse structure were investigated by choosing three different penalty numbers for the topology optimization algorithm. The final design of the proposed structure was performed based on the total simultaneous critical loads on the structure. The results of the proposed method were compared in the order of different volume fractions. This showed that the volume fraction approach can significantly reduce the weight of the structure while maintaining its strength and stability. Findings Topology optimization results showed different strut and chords composition because of the changes in maximum mass limit and volume fraction. The results showed that the fatigue was more hazardous, and it decreased the strength of structure nearly three times more than a static analysis. Further, it was noticed that how the penalty numbers can affect topology optimization results. An optimal design based on topology optimization results was presented to improve the proposed greenhouse design against destruction and demolition. Furthermore, this study shows the most sensitive part of the greenhouse against the standard loads of wind, snow, and crop. Originality/value The obtained designs were compared with a conventional arch greenhouse, and then the structural performances were shown based on standard loads. The results showed that in designing the proposed structure, the optimized changes increased the structure strength against the standard loads compared to a simple arch greenhouse. Moreover, the stress safety factor and fatigue safety factor because of different designs of this structure were also compared with each other.

Design and optimization of nonuniform cellular structures

2017 ◽  
Vol 232 (7) ◽  
pp. 1280-1293 ◽  
Author(s):  
Xin Jin ◽  
Guo-Xi Li ◽  
Meng Zhang
Keyword(s):  
Topology Optimization ◽  
Cellular Structure ◽  
Mechanical Performance ◽  
Design Method ◽  
Lightweight Design ◽  
Structure Design ◽  
Cellular Structures ◽  
Manufacturing Constraints ◽  
Element Analysis ◽  
Design And Optimization

Topology optimization and cellular structure infilling are two important approaches to achieve a lightweight design while meeting the relevant mechanical property requirements. In this work, we present a density-variable cellular structure design method combined with topology optimization while ensuring the manufacturability. The effective mechanical properties are reported as functions of the relative density to combine cellular structures with the topology optimization model. The manufacturing constraints are analyzed and expressed in topology optimization. In addition, density-variable cellular structures are rapidly modeled by mapping the topology optimization results to the relative densities of cells and via the use of user-defined features. It is shown by means of finite element analysis that the proposed design approach can improve the mechanical performance compared to the uniform cellular structure under the same weight reduction. And the choice of cell size for higher stiffness of the designed structure varies with different values of manufacturing constraints.

Structural topology optimization of bridge girders in cable supported bridges

2018 ◽  
Author(s):  
Mads Baandrup ◽  
Ole Sigmund ◽  
Niels Aage
Keyword(s):  
Topology Optimization ◽  
Large Scale ◽  
Design Method ◽  
Optimization Method ◽  
Bridge Girders ◽  
Structural Topology ◽  
Box Girders ◽  
Box Girder ◽  
Fine Mesh ◽  
Further Development

<p>This work applies a ultra large scale topology optimization method to study the optimal structure of bridge girders in cable supported bridges.</p><p>The current classic orthotropic box girder designs are limited in further development and optimiza­ tion, and suffer from substantial fatigue issues. A great disadvantage of the orthotropic girder is the loads being carried one direction at a time, thus creating stress hot spots and fatigue problems. Hence, a new design concept has the potential to solve many of the limitations in the current state­ of-the-art.</p><p>We present a design method based on ultra large scale topology optimization. The highly detailed structures and fine mesh-discretization permitted by ultra large scale topology optimization reveal new design features and previously unseen eff ects. The results demonstrate the potential of gener­ ating completely different design solutions for bridge girders in cable supported bridges, which dif­ fer significantly from the classic orthotropic box girders.</p><p>The overall goal of the presented work is to identify new and innovative, but at the same time con­ structible and economically reasonable, solutions tobe implemented into the design of future cable supported bridges.</p>

A new jig-shape optimization method for the high aspect ratio wing

2018 ◽  
Vol 91 (1) ◽  
pp. 124-133
Author(s):  
Zhe Yuan ◽  
Shihui Huo ◽  
Jianting Ren
Keyword(s):  
Aspect Ratio ◽  
Shape Optimization ◽  
High Aspect Ratio ◽  
Optimization Design ◽  
Design Method ◽  
Aircraft Design ◽  
Optimization Method ◽  
Attack Angle ◽  
Structural Deformation ◽  
Content Type

Purpose Computational efficiency is always the major concern in aircraft design. The purpose of this research is to investigate an efficient jig-shape optimization design method. A new jig-shape optimization method is presented in the current study and its application on the high aspect ratio wing is discussed. Design/methodology/approach First, the effects of bending and torsion on aerodynamic distribution were discussed. The effect of bending deformation was equivalent to the change of attack angle through a new equivalent method. The equivalent attack angle showed a linear dependence on the quadratic function of bending. Then, a new jig-shape optimization method taking integrated structural deformation into account was proposed. The method was realized by four substeps: object decomposition, optimization design, inversion and evaluation. Findings After the new jig-shape optimization design, both aerodynamic distribution and structural configuration have satisfactory results. Meanwhile, the method takes both bending and torsion deformation into account. Practical implications The new jig-shape optimization method can be well used for the high aspect ratio wing. Originality/value The new method is an innovation based on the traditional single parameter design method. It is suitable for engineering application.

Large-scale three-dimensional anisotropic topology optimization of variable-axial lightweight composite structures

2021 ◽  
pp. 1-15
Author(s):  
Yuqing Zhou ◽  
Tsuyoshi Nomura ◽  
Enpei Zhao ◽  
Kazuhiro Saitou
Keyword(s):  
Topology Optimization ◽  
Composite Structures ◽  
Large Scale ◽  
Volume Fraction ◽  
Three Dimensional ◽  
Optimization Method ◽  
Optimized Design ◽  
Adaptive Meshing ◽  
Design Synthesis ◽  
Fiber Placement

Abstract Variable-axial fiber-reinforced composites allow for local customization of fiber orientation and thicknesses. Despite their significant potential for performance improvement over the conventional multiaxial composites and metals, they pose challenges in design optimization due to the vastly increased design freedom in material orientations. This paper presents an anisotropic topology optimization method for designing large-scale, 3D variable-axial lightweight composite structures subject to multiple load cases. The computational challenges associated with large-scale 3D anisotropic topology optimization with extremely low volume fraction are addressed by a tensor-based representation of 3D orientation that would avoid the 2π periodicity of angular representations such as Euler angles, and an adaptive meshing scheme, which, in conjunction with PDE regularization of the density variables, refines the mesh where structural members appear and coarsens where there is void. The proposed method is applied to designing a heavy-duty drone frame subject to complex multi-loading conditions. Finally, the manufacturability gaps between the optimized design and the fabrication-ready design for Tailored Fiber Placement (TFP) is discussed, which motivates future work toward a fully-automated design synthesis.

scholarly journals Microstructural Topology Optimization of Constrained Layer Damping on Plates for Maximum Modal Loss Factor of Macrostructures

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Zhanpeng Fang ◽  
Lei Yao ◽  
Shuxia Tian ◽  
Junjian Hou
Keyword(s):  
Topology Optimization ◽  
Loss Factor ◽  
Strain Energy ◽  
Design Method ◽  
Optimization Method ◽  
Constrained Layer Damping ◽  
Viscoelastic Materials ◽  
Modal Strain Energy ◽  
Design Variables ◽  
Microstructural Topology Optimization

This paper presents microstructural topology optimization of viscoelastic materials for the plates with constrained layer damping (CLD) treatments. The design objective is to maximize modal loss factor of macrostructures, which is obtained by using the Modal Strain Energy (MSE) method. The microstructure of the viscoelastic damping layer is composed of 3D periodic unit cells. The effective elastic properties of the unit cell are obtained through the strain energy-based method. The density-based topology optimization is adopted to find optimal microstructures of viscoelastic materials. The design sensitivities of modal loss factor with respect to the design variables are analyzed and the design variables are updated by Method of Moving Asymptotes (MMA). Numerical examples are given to demonstrate the validity of the proposed optimization method. The effectiveness of the optimal design method is illustrated by comparing a solid and an optimized cellular viscoelastic material as applied to the plates with CLD treatments.

scholarly journals Spatial Baseline Optimization for Spaceborne Multistatic SAR Tomography Systems

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 2106 ◽  
Author(s):  
Jiuchao Zhao ◽  
Anxi Yu ◽  
Yongsheng Zhang ◽  
Xiaoxiang Zhu ◽  
Zhen Dong
Keyword(s):  
Surface Deformation ◽  
Design Method ◽  
Geometric Model ◽  
Three Dimensional ◽  
Optimization Method ◽  
Deformation Measurement ◽  
Experimental Simulation ◽  
Baseline Design ◽  
Imaging Performance ◽  
The Impact

Spaceborne multistatic synthetic aperture radar (SAR) tomography (SMS-TomoSAR) systems take full advantage of the flexible configuration of multistatic SAR in the space, time, phase, and frequency dimensions, and simultaneously achieve high-precision height resolution and low-deformation measurement of three-dimensional ground scenes. SMS-TomoSAR currently poses a series of key issues to solve, such as baseline optimization, spatial transmission error estimation and compensation, and the choice of imaging algorithm, which directly affects the performance of height-dimensional imaging and surface deformation measurement. This paper explores the impact of baseline distribution on height-dimensional imaging performance for the baseline optimization issue, and proposes a feasible baseline optimization method. Firstly, the multi-base multi-pass baselines of an SMS-TomoSAR system are considered equivalent to a group of multi-pass baselines from monostatic SAR. Secondly, we establish the equivalent baselines as a symmetric-geometric model to characterize the non-uniform characteristic of baseline distribution. Through experimental simulation and model analysis, an approximately uniform baseline distribution is shown to have better SMS-TomoSAR imaging performance in the height direction. Further, a baseline design method under uniform-perturbation sampling with Gaussian distribution error is proposed. Finally, the imaging performance of different levels of perturbation is compared, and the maximum baseline perturbation allowed by the system is given.

scholarly journals A Modified Shuffled Frog Leaping Algorithm for the Topology Optimization of Electromagnet Devices

2020 ◽  
Vol 10 (18) ◽  
pp. 6186
Author(s):  
Wenjia Yang ◽  
Siu Lau Ho ◽  
Weinong Fu
Keyword(s):  
Topology Optimization ◽  
Local Search ◽  
Three Dimensional ◽  
Optimization Method ◽  
Memetic Algorithms ◽  
Local Optimum ◽  
Shuffled Frog Leaping Algorithm ◽  
Electromagnetic Problems ◽  
Electromagnetic Devices ◽  
Shuffled Frog Leaping

The memetic algorithms which employ population information spreading mechanism have shown great potentials in solving complex three-dimensional black-box problems. In this paper, a newly developed memetic meta-heuristic optimization method, known as shuffled frog leaping algorithm (SFLA), is modified and applied to topology optimization of electromagnetic problems. Compared to the conventional SFLA, the proposed algorithm has an extra local search step, which allows it to escape from the local optimum, and hence avoid the problem of premature convergence to continue its search for more accurate results. To validate the performance of the proposed method, it was applied to solving the topology optimization of an interior permanent magnet motor. Two other EAs, namely the conventional SFLA and local-search genetic algorithm, were applied to study the same problem and their performances were compared with that of the proposed algorithm. The results indicate that the proposed algorithm has the best trade-off between the results of objective values and optimization time, and hence is more efficient in topology optimization of electromagnetic devices.

An experience-independent inverse design optimization method of compressor cascade airfoil

2019 ◽  
Vol 233 (4) ◽  
pp. 431-442 ◽  
Author(s):  
Yujie Zhu ◽  
Yaping Ju ◽  
Chuhua Zhang
Keyword(s):  
Design Optimization ◽  
Design Method ◽  
Three Dimensional ◽  
Optimal Solution ◽  
Leading Edge ◽  
Optimization Method ◽  
Inverse Design ◽  
Compressor Cascade ◽  
Suction Surface ◽  
Inverse Design Method

Most of the inverse design methods of turbomachinery experience the shortcoming where the target aerodynamic parameters need to be manually specified depending on the designers’ experience and insight, making the design result aleatory and even deviated from the real optimal solution. To tackle this problem, an experience-independent inverse design optimization method is proposed and applied to the redesign of a compressor cascade airfoil in this study. The experience-independent inverse design optimization method can automatically obtain the target pressure distribution along the cascade airfoil through the genetic algorithm, rather than through the manual specification approach. The shape of cascade airfoil is then solved by the adjoint method. The effectiveness of the experience-independent inverse design optimization method is demonstrated by two inverse design cases of the compressor cascade airfoil, i.e. the inverse design of only the suction surface and the inverse design of both the suction and pressure surfaces. The results show that the proposed inverse design method is capable of significantly improving the aerodynamic performance of the compressor cascade. At the examined flow condition, a thin airfoil profile is beneficial to flow accelerations near the leading edge and flow separation avoidance near the trailing edge. The proposed inverse design method is quite generic and can be extended to the three-dimensional inverse design of advanced compressor blades.

Robust topology optimization for continuum structures with random loads

2018 ◽  
Vol 35 (2) ◽  
pp. 710-732 ◽  
Author(s):  
Jie Liu ◽  
Guilin Wen ◽  
Qixiang Qing ◽  
Fangyi Li ◽  
Yi Min Xie
Keyword(s):  
Topology Optimization ◽  
Optimization Method ◽  
Computational Time ◽  
Optimization Approach ◽  
Random Load ◽  
Content Type ◽  
Continuum Structures ◽  
Robust Topology Optimization ◽  
Random Loads ◽  
Expansion Technique

Purpose This paper aims to tackle the challenge topic of continuum structural layout in the presence of random loads and to develop an efficient robust method. Design/methodology/approach An innovative robust topology optimization approach for continuum structures with random applied loads is reported. Simultaneous minimization of the expectation and the variance of the structural compliance is performed. Uncertain load vectors are dealt with by using additional uncertain pseudo random load vectors. The sensitivity information of the robust objective function is obtained approximately by using the Taylor expansion technique. The design problem is solved using bi-directional evolutionary structural optimization method with the derived sensitivity numbers. Findings The numerical examples show the significant topological changes of the robust solutions compared with the equivalent deterministic solutions. Originality/value A simple yet efficient robust topology optimization approach for continuum structures with random applied loads is developed. The computational time scales linearly with the number of applied loads with uncertainty, which is very efficient when compared with Monte Carlo-based optimization method.

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