Structural topology optimization with strength and heat conduction constraints

Takezawa, Akihiro; Yoon, Gil Ho; Jeong, Soo‐Hwan; Kobashi, Makoto; Kitamura, Mitsuru

doi:10.1016/j.cma.2014.04.003

Cited by 86 publications

(23 citation statements)

References 46 publications

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“…Gao (Gao and Zhang, 2010), Deaton (Deaton and Grandhi,2013) Xia (Xia and Wang, 2008) Takezawa (Takezawa et al, 2014(Takezawa et al, ) ( , 2015 Eiji KATAMINE (Kruijf et al, 2007) (Chen et al, 2010) Lagrange 2.…”

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confidence: 99%

Multi-objective shape optimization for maximizing stiffness in thermo-elastic fields

Katamine

Arai

2017

Transactions of the JSME (In Japanese)

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This paper presents a numerical solution to multi-objective shape optimization in order to achieve stiffness maximization in thermoelastic fields. Compliance evaluated by thermal deformation based on temperature distribution and by mechanical deformation based on surface force or body force is used as an objective functional by using weighting method.Shape gradient of the multi-objective shape problem is derived theoretically using the Lagrange multiplier method, adjoint variable method, and the formulae of the material derivative. Reshaping is carried out by the traction method proposed as an approach to solving shape optimization problems. Numerical analyses program for the shape optimization is developed based on FreeFem++, and the validity of proposed method is confirmed by results of 2D numerical analyses.

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confidence: 99%

Multi-objective shape optimization for maximizing stiffness in thermo-elastic fields

Katamine

Arai

2017

Transactions of the JSME (In Japanese)

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“…From the thermal point of view (Figure 14(c)), Anderson et al 26 provides the constant internal temperature of the fluid inside the pipes h ¼ 413K and a total absorbed heat Q tot ¼ 590W. As for the mechanical field, the inlet heat applied on the portion of cross section is split by four and considered per unit of length as in equation 15Q ¼ Q tot 4L ¼ 0:48W=mm (15) Given the aforementioned boundary conditions, three different optimization problems have been set up and the final topologies are shown in Figure 15. plane quad elements, eight nodes each one, are employed for the analysis.…”

Section: Thermomechanical Topology Optimization: Validation On a Realmentioning

confidence: 99%

A new methodology for thermostructural topology optimization: Analytical definition and validation

Caivano

Tridello

Codegone

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part L:

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In the last few years, the rapid diffusion of components produced through additive manufacturing processes has boosted the research on design methodologies based on topology optimization algorithms. Structural topology optimization is largely employed since it permits to minimize the component weight and maximize its stiffness and, accordingly, optimize its resistance under structural loads. On the other hand, thermal topology optimization has been less investigated, even if in many applications, such as turbine blades, engines, heat exchangers, thermal loads have a crucial impact. Currently, structural and thermal optimizations are mainly considered separately, despite the fact that they are both present and coupled in components in service condition. In the present paper, a novel methodology capable of defining the optimized structure under simultaneous thermomechanical constraints is proposed. The mathematical formulation behind the optimization algorithm is reported. The proposed methodology is finally validated on literature benchmarks and on a real component, confirming that it permits to define the topology, which presents the maximized thermal and mechanical performance.

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“…Since the pioneer paper by Bendsøe and Kikuchi [1], topology optimization has been used widely in designing mechanical components and other engineering applications e.g., thermoelasticity [2], fluid flow [3,4], acoustics [5], wave propagation [6], aerospace design [7], multi-functional material design [8][9][10][11], multi-physics systems [12,13], etc. New innovative materials and smart structures can also be designed, e.g., functionally graded piezo-composites have been developed using topology optimization and homogenization technique [14].…”

Section: Introductionmentioning

confidence: 99%