A spatial kernel approach for topology optimization

Roux, Willem; Yi, Guilian; Gandikota, Imtiaz

doi:10.1016/j.cma.2019.112794

Cited by 8 publications

(3 citation statements)

References 28 publications

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“…[ 49 ] The addition of spatial variables can solve complex design problems, for example, highly nonlinear mechanical events. [ 50 ]…”

Section: Design Concepts For Fgmammentioning

confidence: 99%

“…[49] The addition of spatial variables can solve complex design problems, for example, highly nonlinear mechanical events. [50] TO technique exploits the far-reaching capabilities of AM technologies to fabricate sophisticated FGSs like selective laser melting (SLM). [51,52] However, material extrusion-based AM technologies such as fused deposition modeling (FDM) tend to produce material gradients over the material compositions.…”

Section: Topology Optimizationmentioning

confidence: 99%

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A Review on Functionally Graded Materials and Structures via Additive Manufacturing: From Multi‐Scale Design to Versatile Functional Properties

Yan

Feng

Liu

et al. 2020

Adv Materials Technologies

330

116

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Functionally graded materials (FGMs) and functionally graded structures (FGSs) are special types of advanced composites with peculiar features and advantages. This article reviews the design criteria of functionally graded additive manufacturing (FGAM), which is capable of fabricating gradient components with versatile functional properties. Conventional geometrical‐based design concepts have limited potential for FGAM and multi‐scale design concepts (from geometrical patterning to microstructural design) are needed to develop gradient components with specific graded properties at different locations. FGMs and FGSs are of great interest to a larger range of industrial sectors and applications including aerospace, automotive, biomedical implants, optoelectronic devices, energy absorbing structures, geological models, and heat exchangers. This review presents an overview of various fabrication ideas and suggestions for future research in terms of design and creation of FGMs and FGSs, benefiting a wide variety of scientific fields.

show abstract

“…[ 49 ] The addition of spatial variables can solve complex design problems, for example, highly nonlinear mechanical events. [ 50 ]…”

Section: Design Concepts For Fgmammentioning

confidence: 99%

Section: Topology Optimizationmentioning

confidence: 99%

A Review on Functionally Graded Materials and Structures via Additive Manufacturing: From Multi‐Scale Design to Versatile Functional Properties

Yan

Feng

Liu

et al. 2020

Adv Materials Technologies

330

116

View full text Add to dashboard Cite

show abstract

“…In computational design, extensive research has been conducted regarding deep learning in fields such as design optimization (e.g., size/shape/topology optimization), computer-aided design (CAD), computer-aided manufacturing (CAM), computer-aided engineering (CAE), and meta-modeling, among others (Yoo et al, 2020). In particular, topology optimization is a research field that actively applies machine learning and deep learning (Lin & Lin, 2005;Sosnovik & Oseledets, 2017;Keshavarzzadeh et al, 2020;Roux et al, 2020). By definition, topology optimization is a methodology to determine the optimal distribution of material in a design space, given a set of load and boundary conditions.…”

Section: Introductionmentioning

confidence: 99%