Some considerations on multi-material topology optimization using ordered SIMP

Silveira, Otavio Augusto Alves da; Palma, Lucas Farias

doi:10.1007/s00158-022-03379-7

Cited by 19 publications

(13 citation statements)

References 22 publications

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“…This work applies an ordered multi-material strategy [6] for optimizing the topology of porous structures with a focus on addressing thermal conduction challenges of the classic volume-to-point problem [9]. Both TO and MMTO methods are presented and then results are compared and discussed.…”

Section: Methodsmentioning

confidence: 99%

“…The ordered SIMP interpolation [6] aims to enhance the degrees of freedom of previous approaches while overcoming convergence issues, e.g., ineffective penalization of intermediate densities and shadowy topology post-processing. Moreover, the key aspect of multi-material topology optimization with ordered SIMP interpolation is to correctly assign material properties.…”

Section: Multi-materials Topology Optimizationmentioning

confidence: 99%

“…The values of thermal conductivity, taken from [12] for the metal foams, are listed in Table 1, which also shows how to pass from the actual thermal conductivity to the normalized one (kN) -obtained with respect to the maximum one, i.e., 47 W/(m K) -depending on the porosity. Starting from these values, since the thermal conductivity of the Mn+1 material exceeds that of a material Mn, the equation for the interpolated normalized modulus of thermal conductivity (kN = k/kmax), valid for γN ∈ [γm, γm+1], is written as follows [6]:…”

Section: Multi-materials Topology Optimizationmentioning

confidence: 99%

“…One of the key methodologies introduced in the research is the ordered SIMP interpolation [5], which is designed to handle multi-material topology optimization effectively. This approach -born in the field of structural engineering -involves sorting candidate materials in ascending order of their normalized mass densities and interpolating material properties, such as the modulus of elasticity and cost, based on these densities [6]. In the field of thermal engineering -to the authors' knowledge -few attempts of application of this methodology have been proposed [7], [8], especially for benchmark cases as the volume-to-point problem.…”

Section: Introductionmentioning

confidence: 99%

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Enhancing the degrees of freedom of topology optimization via variable-porosity metal foams: Design of heat conduction paths in a volume-to-point problem

Bianco,

Fragnito,

Iasiello

et al. 2024

J. Phys.: Conf. Ser.

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Multi-material topology optimization determines the optimal distribution of different materials within a design domain in order to achieve specific performance goals. This work takes advantage of such technique to enhance the thermal performance of a benchmark heat conduction problem. The aim is to investigate the impact of enhancing the degrees of freedom introducing different materials, i.e., variable-porosity metal foams in addition to the high-conductivity solid, in the design of heat conduction paths under a constant weight constraint. The study leverages a well-established case study – volume-to-point problem – in the field of thermal management, ensuring a consistent basis for comparison. It consists of a square domain with a uniform heat source and a Dirichlet condition at a point on the boundary. Interpolation functions – ordered solid isotropic material with penalization (SIMP) type – allow the properties – in this case thermal conductivity – of materials to be correctly assigned. The distinction between materials is made by means of different thresholds on the projection function. By varying the foam porosity, we investigate the trade-offs between weight and heat dissipation efficiency. The objective is to find the ideal combination of materials that maximizes heat transfer – minimizing the average domain temperature – while conforming to weight constraints. Findings reveal that multi-material topology optimization – when applied to heat conduction problems – can outperform other design approaches, such as the growth-based algorithm, the evolved constructal tree, and the classical topology optimization (with one solid material), thereby paving the ground to innovative heat sink designs in weight-constrained environments.

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Section: Methodsmentioning

confidence: 99%

Section: Multi-materials Topology Optimizationmentioning

confidence: 99%

Section: Multi-materials Topology Optimizationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Enhancing the degrees of freedom of topology optimization via variable-porosity metal foams: Design of heat conduction paths in a volume-to-point problem

Bianco,

Fragnito,

Iasiello

et al. 2024

J. Phys.: Conf. Ser.

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“…Topology optimization methods are mainly divided into Solid Isotropic Material with Penalization (SIMP) and Bi-directional Evolutionary Structural Optimization (BESO). The SIMP algorithm is representative of some considerations on SIMP topology optimization proposed by da Silveira et al [1] and an efficient topology method written by Munk et al [2], while the representative BESO algorithm is like the further BESO method for topology optimization proposed by Gao et al [3] and Ghabreie [4]. Based on the BESO, Gaganelis et al [5] and Xie and Li [6] proposed a method for distinguishing tension and compression stress algorithms, and Clausen et al [7] proposed exploiting additive infill in topology optimization.…”

Section: Introductionmentioning

confidence: 99%

Topology Optimization of Dual-Material Structures with Porous Materials

Zhou

2023

J. Phys.: Conf. Ser.

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To improve the buckling resistance of the structure and the effective utilization of materials, a topology optimization algorithm using dual materials is designed in this paper. Among them, the two materials are solid and porous, respectively. The single-material structure topology optimization algorithm in two-dimensional structures has been relatively perfect. However, the two-dimensional algorithm is limited to the topology optimization of a single material, and it cannot improve the buckling resistance of the actual compression structure. At the same time, the optimization algorithm for the three-dimensional structure still needs to be improved. The dual-material topology optimization algorithm using porous materials constructed in this paper assigns porous materials with good compressive capacity to the compression parts and solid materials with good tensile properties to the tension parts. Therefore, the structure of the compression part of the structure is strengthened, and the unnecessary structure of the tension part is simplified. In conclusion, the algorithm in this paper greatly improves the buckling resistance of the structure and maximizes the utilization of each design unit.

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