Topology Optimization of Micromachined Structures With Surface Micromachining Manufacturing Constraints

2006 ◽  
Author(s):  
Aravind Alwan ◽  
G. K. Ananthasuresh
Keyword(s):  
Topology Optimization ◽  
Optimization Methods ◽  
Manufacturing Cost ◽  
Manufacturing Constraints ◽  
Surface Micromachining ◽  
Out Of Plane ◽  
Gradient Based ◽  
Plane Direction ◽  
New Formulation ◽  
Design Parameterization

Topology optimization methods have been shown to have extensive application in the design of microsystems. However, their utility in practical situations is restricted to predominantly planar configurations due to the limitations of most microfabrication techniques in realizing structures with arbitrary topologies in the direction perpendicular to the substrate. This study addresses the problem of synthesizing optimal topologies in the out-of-plane direction while obeying the constraints imposed by surface micromachining. A new formulation that achieves this by defining a design space that implicitly obeys the manufacturing constraints with a continuous design parameterization is presented in this paper. This is in contrast to including manufacturing cost in the objective function or constraints. The resulting solutions of the new formulation obtained with gradient-based optimization directly provide the photolithographic mask layouts. Two examples that illustrate the approach for the case of stiff structures are included.

Non-Probabilistic Based Topology Optimization Under External Load Uncertainty With Eigenvalue-Superposition of Convex Models

2013 ◽  
Author(s):  
Xike Zhao ◽  
Hae Chang Gea ◽  
Wei Song
Keyword(s):  
Topology Optimization ◽  
External Load ◽  
Optimization Problems ◽  
Optimization Methods ◽  
Optimization Method ◽  
Convex Model ◽  
Structure Response ◽  
Gradient Based ◽  
Bounded Convex ◽  
Topology Optimization Method

In this paper the Eigenvalue-Superposition of Convex Models (ESCM) based topology optimization method for solving topology optimization problems under external load uncertainties is presented. The load uncertainties are formulated using the non-probabilistic based unknown-but-bounded convex model. The sensitivities are derived and the problem is solved using gradient based algorithm. The proposed ESCM based method yields the material distribution which would optimize the worst structure response under the uncertain loads. Comparing to the deterministic based topology optimization formulation the ESCM based method provided more reasonable solutions when load uncertainties were involved. The simplicity, efficiency and versatility of the proposed ESCM based topology optimization method can be considered as a supplement to the sophisticated reliability based topology optimization methods.

Coupled Multi-Material and Joint Topology Optimization: A Proof of Concept

2018 ◽  
Author(s):  
Vlad Florea ◽  
Vishrut Shah ◽  
Stephen Roper ◽  
Garrett Vierhout ◽  
Il Yong Kim
Keyword(s):  
Topology Optimization ◽  
Cost Effective ◽  
Material Design ◽  
Optimization Methods ◽  
Manufacturing Constraints ◽  
Proof Of Concept ◽  
Efficient Design ◽  
Engineering Costs ◽  
Increasing Demand ◽  
Material Layout

Over the past decade there has been an increasing demand for light-weight components for the automotive and aerospace industries. This has led to significant advancement in Topology Optimization methods, especially in developing new algorithms which can consider multi-material design. While Multi-Material Topology Optimization (MMTO) can be used to determine the optimum material layout and choice for a given engineering design problem, it fails to consider practical manufacturing constraints. One such constraint is the practical joining of multi-component designs. In this paper, a new method will be proposed for simultaneously performing MMTO and Joint Topology Optimization (JTO). This algorithm will use a serial approach to loop through the MMTO and JTO phases to obtain a truly optimum design which considers both aspects. A case study is performed on an automotive ladder frame chassis component as a proof of concept for the proposed approach. Two loops of the proposed process resulted in a reduction of components and in the number of joints used between them. This translates into a tangible improvement in the manufacturability of the MMTO design. Ultimately, being able to consider additional manufacturing constraints in the Topology Optimization process can greatly benefit research and development efforts. A better design is reached with fewer iterations, thus driving down engineering costs. Topology Optimization can help in determining a cost effective and efficient design which address existing structural design challenges.

Incorporating Manufacturing Constraints in Topology Optimization Methods: A Survey

2017 ◽  
Author(s):  
Alok Sutradhar ◽  
Jaejong Park ◽  
Payam Haghighi ◽  
Jacob Kresslein ◽  
Duane Detwiler ◽  
...  
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
Optimization Methods ◽  
Manufacturing Processes ◽  
Complex Geometries ◽  
Manufacturing Constraints ◽  
Post Processing ◽  
Optimization Framework ◽  
Manufacturing Methods ◽  
Traditional Manufacturing

Topology optimization provides optimized solutions with complex geometries which are often not suitable for direct manufacturing without further steps or post-processing by the designer. There has been a recent progression towards linking topology optimization with additive manufacturing, which is less restrictive than traditional manufacturing methods, but the technology is still in its infancy being costly, time-consuming, and energy inefficient. For applications in automotive or aerospace industries, the traditional manufacturing processes are still preferred and utilized to a far greater extent. Adding manufacturing constraints within the topology optimization framework eliminates the additional design steps of interpreting the topology optimization result and converting it to viable manufacturable parts. Furthermore, unintended but inevitable deviations that occur during manual conversion from the topology optimized result can be avoided. In this paper, we review recent advances to integrate (traditional) manufacturing constraints in the topology optimization process. The focus is on the methods that can create manufacturable and well-defined geometries. The survey will discuss the advantages, limitations, and related challenges of manufacturability in topology optimization.

Gradient-Based Multi-Component Topology Optimization for Additive Manufacturing (MTO-A)

2017 ◽  
Author(s):  
Yuqing Zhou ◽  
Kazuhiro Saitou
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
Simultaneous Optimization ◽  
Minimum Length ◽  
Manufacturing Constraints ◽  
Component Level ◽  
Component Size ◽  
Design Variables ◽  
Gradient Based ◽  
Minimum Length Scale

Topology optimization for additive manufacturing has been limited to the component-level designs with the component size smaller than the printer’s build volume. To enable the design of structures larger than the printer’s build volume, this paper presents a gradient-based multi-component topology optimization framework for structures assembled from components built by additive manufacturing. Constraints on component geometry for additive manufacturing are incorporated in the density-based topology optimization, with additional design variables specifying fractional component membership. For each component, constraints on build size, enclosed voids, overhangs, and the minimum length scale are imposed during the simultaneous optimization of overall base topology and component partitioning. The preliminary result on a minimum compliance structure shows promising advantages over the conventional monolithic topology optimization. Manufacturing constraints previously applied to monolithic topology optimization gain new interpretations when applied to multi-component assemblies, which can unlock richer design space for topology exploration.

Numerical Methods for the Design of Meso-Structures: A Comparative Review

2015 ◽  
Author(s):  
Marcus Yoder ◽  
Zachary Satterfield ◽  
Mohammad Fazelpour ◽  
Joshua D. Summers ◽  
Georges Fadel
Keyword(s):  
Topology Optimization ◽  
Shape Optimization ◽  
Material Properties ◽  
Optimization Methods ◽  
Optimization Techniques ◽  
Future Research ◽  
Structured Materials ◽  
3 Dimensional ◽  
Comparative Review ◽  
Gradient Based

Over the past decade, there has been an increase in the intentional design of meso-structured materials that are optimized to target desired material properties. This paper reviews and critically compares common numerical methodologies and optimization techniques used to design these meso-structures by analyzing the methods themselves and published applications and results. Most of the reviewed research targets mechanical material properties, including effective stiffness and crushing energy absorption. The numerical methodologies reviewed include topology and size/shape optimization methods such as homogenization, Solid Isotropic Material with Penalization, and level sets. The optimization techniques reviewed include genetic algorithms (GAs), particle swarm optimization (PSO), gradient based, and exhaustive search methods. The research reviewed shows notable patterns. The literature reveals a push to apply topology optimization in an ever-growing number of 3-dimensional applications. Additionally, researchers are beginning to apply topology optimization and size/shape optimization to multiphysics problems. The research also shows notable gaps. Although PSOs are comparable evolutionary algorithms to GAs, the use of GAs dominates over PSOs. These patterns and gaps, along with others, are discussed in terms of possible future research in the design of meso-structured materials.

Synthesis of Gear-Linkage Mechanisms by Topology Optimization

2018 ◽  
Author(s):  
Neung Hwan Yim ◽  
Seok Won Kang ◽  
Yoon Young Kim
Keyword(s):  
Topology Optimization ◽  
Design Space ◽  
Synthesis Method ◽  
Variable Stiffness ◽  
Optimization Methods ◽  
Optimization Method ◽  
Planar Mechanisms ◽  
Gear Design ◽  
Linkage Design ◽  
Gradient Based

This work is concerned with a new mechanism synthesis method for the simultaneous determination of the type, number and dimension of mechanisms by topology optimization. Earlier topology optimization methods can synthesize linkage mechanisms that consist only of links and joints. The proposed synthesis method is a gradient-based topology optimization method useful for the synthesis of planar mechanisms consisting of linkages and gears. To formulate the topology optimization based method, we propose two superposed design spaces as a ground structure: the linkage and gear design spaces. The gear design space is discretized by newly proposed gear blocks while the linkage design space by rigid blocks. The zero-length springs with variable stiffness are used to control the connectivity of blocks, which in turns determines the configuration of the synthesized mechanism. After the proposed topology-optimization-based synthesis formulation is presented, its effectiveness and validity are checked with various synthesis examples.

scholarly journals An efficient approach to reliability-based topology optimization for the structural lightweight design of planar continuum structures

2021 ◽  
Vol 37 ◽  
pp. 270-281
Author(s):  
Fangfang Yin ◽  
Kaifang Dang ◽  
Weimin Yang ◽  
Yumei Ding ◽  
Pengcheng Xie
Keyword(s):  
Topology Optimization ◽  
Lightweight Design ◽  
Integrated Design ◽  
Optimization Methods ◽  
Filter Function ◽  
Continuum Structures ◽  
Performance Indexes ◽  
Reliability Method ◽  
Economic Indexes ◽  
The Impact

Abstract In order to solve the application restrictions of deterministic-based topology optimization methods arising from the omission of uncertainty factors in practice, and to realize the calculation cost control of reliability-based topology optimization. In consideration of the current reliability-based topology optimization methods of continuum structures mainly based on performance indexes model with a power filter function. An efficient probabilistic reliability-based topology optimization model that regards mass and displacement as an objective function and constraint is established based on the first-order reliability method and a modified economic indexes model with a composite exponential filter function in this study. The topology optimization results obtained by different models are discussed in relation to optimal structure and convergence efficiency. Through numerical examples, it can be seen that the optimal layouts obtained by reliability-based models have an increased amount of material and more support structures, which reveals the necessity of considering uncertainty in lightweight design. In addition, the reliability-based modified model not only can obtain lighter optimal structures compared with traditional economic indexes models in most circumstances, but also has a significant advantage in convergence efficiency, with an average increase of 44.59% and 64.76% compared with the other two reliability-based models. Furthermore, the impact of the reliability index on the results is explored, which verifies the validity of the established model. This study provides a theoretical reference for lightweight or innovative feature-integrated design in engineering applications.

scholarly journals A Comprehensive Review of Isogeometric Topology Optimization: Methods, Applications and Prospects

2020 ◽  
Vol 33 (1) ◽  
Author(s):  
Jie Gao ◽  
Mi Xiao ◽  
Yan Zhang ◽  
Liang Gao
Keyword(s):  
Topology Optimization ◽  
Computer Aided Design ◽  
Numerical Technique ◽  
Optimization Methods ◽  
Negative Influence ◽  
Comprehensive Overview ◽  
Promising Alternative ◽  
Computer Aided ◽  
Optimal Material ◽  
Material Layout

AbstractTopology Optimization (TO) is a powerful numerical technique to determine the optimal material layout in a design domain, which has accepted considerable developments in recent years. The classic Finite Element Method (FEM) is applied to compute the unknown structural responses in TO. However, several numerical deficiencies of the FEM significantly influence the effectiveness and efficiency of TO. In order to eliminate the negative influence of the FEM on TO, IsoGeometric Analysis (IGA) has become a promising alternative due to its unique feature that the Computer-Aided Design (CAD) model and Computer-Aided Engineering (CAE) model can be unified into a same mathematical model. In the paper, the main intention is to provide a comprehensive overview for the developments of Isogeometric Topology Optimization (ITO) in methods and applications. Finally, some prospects for the developments of ITO in the future are also presented.

Mechanism of the Transition From In-Plane Buckling to Helical Buckling for a Stiff Nanowire on an Elastomeric Substrate

2016 ◽  
Vol 83 (4) ◽  
Author(s):  
Youlong Chen ◽  
Yong Zhu ◽  
Xi Chen ◽  
Yilun Liu
Keyword(s):  
High Performance ◽  
Three Dimensional ◽  
Stretchable Electronics ◽  
Buckling Mode ◽  
Design And Optimization ◽  
Out Of Plane ◽  
Plane Direction ◽  
Plane Displacement ◽  
Helical Buckling ◽  
Selection Of

In this work, the compressive buckling of a nanowire partially bonded to an elastomeric substrate is studied via finite-element method (FEM) simulations and experiments. The buckling profile of the nanowire can be divided into three regimes, i.e., the in-plane buckling, the disordered buckling in the out-of-plane direction, and the helical buckling, depending on the constraint density between the nanowire and the substrate. The selection of the buckling mode depends on the ratio d/h, where d is the distance between adjacent constraint points and h is the helical buckling spacing of a perfectly bonded nanowire. For d/h > 0.5, buckling is in-plane with wavelength λ = 2d. For 0.27 < d/h < 0.5, buckling is disordered with irregular out-of-plane displacement. While, for d/h < 0.27, buckling is helical and the buckling spacing gradually approaches to the theoretical value of a perfectly bonded nanowire. Generally, the in-plane buckling induces smaller strain in the nanowire, but consumes the largest space. Whereas the helical mode induces moderate strain in the nanowire, but takes the smallest space. The study may shed useful insights on the design and optimization of high-performance stretchable electronics and three-dimensional complex nanostructures.

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.

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