Stress-Constrained Thermo-Elastic Topology Optimization: A Topological Sensitivity Approach

Author(s):  
Shiguang Deng ◽  
Krishnan Suresh ◽  
James Joo

The focus of this paper is on thermo-elastic topology optimization where the structure is subject to both mechanical and thermal loads. Such problems are of significant importance, for example, in the aircraft industry where structures subject to aerodynamic forces and thermal-gradients must be optimized. A popular strategy for solving such problems is Solid Isotropic Material with Penalization (SIMP) where pseudo-densities serve as optimization parameters. Yet another strategy is the Rational Approximation of Material Properties (RAMP) that overcomes some of the deficiencies of SIMP. Both methods fundamentally rely on parameterization of the material properties as a function of the pseudo-densities. Here we consider an alternate level-set approach that relies on the concept of topological sensitivity. The advantages of the proposed method over SIMP and RAMP are: (1) ad hoc material parameterization is not required (2) the stresses are well-defined at all points within the evolving topology and (3) the underlying stiffness matrices are always well-conditioned. The proposed method is illustrated through numerical experiments.

Author(s):  
Shiguang Deng ◽  
Krishnan Suresh

This paper focuses on topology optimization of structures subject to a compressive load in a thermal environment. Such problems are important, for example, in aerospace, where structures are prone to thermally induced buckling. Popular strategies for thermo-elastic topology optimization include Solid Isotropic Material with Penalization (SIMP) and Rational Approximation of Material Properties (RAMP). However, since both methods fundamentally rely on material parameterization, they are often challenged by: (1) pseudo buckling modes in low-density regions, and (2) ill-conditioned stiffness matrices. To overcome these, we consider here an alternate level-set approach that relies discrete topological sensitivity. Buckling sensitivity analysis is carried out via direct and adjoint formulations. Augmented Lagrangian method is then used to solve a buckling constrained compliance minimization problem. Finally, 3D numerical experiments illustrate the efficiency of the proposed method.


Author(s):  
Shanglong Zhang ◽  
Julián A. Norato

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.


Author(s):  
Shiguang Deng ◽  
Krishnan Suresh

Topology optimization is a systematic method of generating designs that maximize specific objectives. While it offers significant benefits over traditional shape optimization, topology optimization can be computationally demanding and laborious. Even a simple 3D compliance optimization can take several hours. Further, the optimized topology must typically be manually interpreted and translated into a CAD-friendly and manufacturing friendly design. This poses a predicament: given an initial design, should one optimize its topology? In this paper, we propose a simple metric for predicting the benefits of topology optimization. The metric is derived by exploiting the concept of topological sensitivity, and is computed via a finite element swapping method. The efficacy of the metric is illustrated through numerical examples.


Author(s):  
Ji-Hong Zhu ◽  
Wei-Hong Zhang

The purpose of this paper is to give an overall introduction of the structural optimization research works in ESAC group in 2011. Four main topics are involved, i.e. 1) topology optimization with multiphase materials, 2) integrated layout and topology optimization, 3) prediction of effective material properties and 4) composite design. More detailed techniques and some numerical results are also presented and discussed here.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Meisam Takalloozadeh ◽  
Gil Ho Yoon

Purpose Body forces are always applied to structures in the form of the weight of materials. In some cases, they can be neglected in comparison with other applied forces. Nevertheless, there is a wide range of structures in civil and mechanical engineering in which weight or other types of body forces are the main portions of the applied loads. The optimal topology of these structures is investigated in this study. Design/methodology/approach Topology optimization plays an increasingly important role in structural design. In this study, the topological derivative under body forces is used in a level-set-based topology optimization method. Instability during the optimization process is addressed, and a heuristic solution is proposed to overcome the challenge. Moreover, body forces in combination with thermal loading are investigated in this study. Findings Body forces are design-dependent loads that usually add complexity to the optimization process. Some problems have already been addressed in density-based topology optimization methods. In the present study, the body forces in a topological level-set approach are investigated. This paper finds that the used topological derivative is a flat field that causes some instabilities in the optimization process. The main novelty of this study is a technique used to overcome this challenge by using a weighted combination. Originality/value There is a lack of studies on level-set approaches that account for design-dependent body forces and the proposed method helps to understand the challenges posed in such methods. A powerful level-set-based approach is used for this purpose. Several examples are provided to illustrate the efficiency of this method. Moreover, the results show the effect of body forces and thermal loading on the optimal layout of the structures.


2016 ◽  
Vol 83 (7) ◽  
Author(s):  
Grace X. Gu ◽  
Leon Dimas ◽  
Zhao Qin ◽  
Markus J. Buehler

A paradigm in nature is to architect composites with excellent material properties compared to its constituents, which themselves often have contrasting mechanical behavior. Most engineering materials sacrifice strength for toughness, whereas natural materials do not face this tradeoff. However, biology's designs, adapted for organism survival, may have features not needed for some engineering applications. Here, we postulate that mimicking nature's elegant use of multimaterial phases can lead to better optimization of engineered materials. We employ an optimization algorithm to explore and design composites using soft and stiff building blocks to study the underlying mechanisms of nature's tough materials. For different applications, optimization parameters may vary. Validation of the algorithm is carried out using a test suite of cases without cracks to optimize for stiffness and compliance individually. A test case with a crack is also performed to optimize for toughness. The validation shows excellent agreement between geometries obtained from the optimization algorithm and the brute force method. This study uses different objective functions to optimize toughness, stiffness and toughness, and compliance and toughness. The algorithm presented here can provide researchers a way to tune material properties for a vast number of engineering problems by adjusting the distribution of soft and stiff materials.


Author(s):  
Krishnan Suresh

In multi-objective topology optimization, a design is defined to be “pareto-optimal” if no other design exists that is better with respect to one objective, and as good with respect to others. This unfortunately suggests that unless other ‘better’ designs are found, one cannot declare a particular topology to be pareto-optimal. In this paper, we first show that a topology can be guaranteed to be (locally) pareto-optimal if certain inherent properties associated with the topological sensitivity field are satisfied, i.e., no further comparison is necessary. This, in turn, leads to a deterministic, i.e., non-stochastic, method for directly tracing pareto-optimal frontiers using the classic fixed-point iteration scheme. The proposed method can generate the full set of pareto-optimal topologies in a single-run, and is therefore both efficient and predictable, as illustrated through numerical examples.


Author(s):  
Trung Pham ◽  
Christopher Hoyle ◽  
Yue Zhang ◽  
Tam Nguyen

Topology optimization (TO) aims to find a material distribution within a reference domain, which optimizes objective function(s) and satisfies certain constraints. Topology optimization has various potential applications in early phases of structural design, e.g., reducing structural weight or maximizing structural stiffness. However, most research on TO has focused on linear elastic materials, which has severely restricted applications of TO to hyperelastic structures made of, e.g., rubber or elastomer. While there is some work in literature on TO of nonlinear continua, to the best knowledge of the authors there is no work which investigates the different models of hyperelastic material. Furthermore, topology optimized designs often possess complex geometries and intermediate densities making it difficult to manufacture such designs using conventional methods. Additive Manufacturing (AM) is capable of handling such complexities. Continuing advances in AM will allow for usage of rubber-like materials, which are modeled by hyperelastic constitutive laws, in producing complex structures designed by TO. The contribution of this paper is an investigation of different models of hyperelastic materials taking account of both geometrical and material nonlinearities, and their influences on the resulting topologies. Topology optimization of nonlinear continua is the main topic of few papers. This paper considers different isotropic hyperelastic models including the Ogden, Arruda–Boyce and Yeoh model under finite deformations, which have not yet been implemented in the context of topology optimization of continua. This paper proposes to start with a reference domain having known boundary and loading conditions. Material parameters of different models that fill the domain are also known. Maximizing the stiffness of the structure subject to a volume constraint is used as the design objective. The domain is then meshed into a large number of finite elements, and each element is assigned a density between 0 and 1, which becomes design variable of the optimization problem. These densities are further penalized to make intermediate densities (i.e., not 0 or 1) less favorable. Optimized material distribution will be constructed from optimized values of design variables. Because of the penalization factors that make the problem nonlinear, the Method of Moving Asymptotes (MMA) is utilized to update it iteratively. At each iteration the nonlinear finite element problem is solved using the Finite Element Analysis Program (FEAP), which has been modified to accept penalized densities on element stiffness matrices and internal nodal forces, and a filtering scheme is applied on the sensitivities of objective function to guarantee the existence of solution. The proposed method is tested on several numerical examples. The first two examples are common benchmark models, which are a simply supported beam , and a beam fixed at two ends. Both models are subjected to a concentrated force at midpoints of their edges. The effects of linear and nonlinear material behaviors are compared with regards to resulting designs. The third example is a foremost attempt to reflect on TO in design of airless tire through a simple model, which demonstrates capability of the method in solving real-world design problems.


2013 ◽  
Vol 49 (5) ◽  
pp. 2073-2076 ◽  
Author(s):  
Takayuki Yamada ◽  
Hayato Watanabe ◽  
Garuda Fujii ◽  
Toshiro Matsumoto

Sign in / Sign up

Export Citation Format

Share Document