Data‐Driven Design for Metamaterials and Multiscale Systems: A Review
Metamaterials are artificial materials designed to exhibit effective material parameters that
go beyond those found in nature. Composed of unit cells with rich designability that are …
go beyond those found in nature. Composed of unit cells with rich designability that are …
Physics-guided, physics-informed, and physics-encoded neural networks in scientific computing
Recent breakthroughs in computing power have made it feasible to use machine learning
and deep learning to advance scientific computing in many fields, including fluid mechanics …
and deep learning to advance scientific computing in many fields, including fluid mechanics …
[HTML][HTML] Data-driven topology optimization of spinodoid metamaterials with seamlessly tunable anisotropy
We present a two-scale topology optimization framework for the design of macroscopic
bodies with an optimized elastic response, which is achieved by means of a spatially-variant …
bodies with an optimized elastic response, which is achieved by means of a spatially-variant …
Investigation of concurrent multiscale topology optimization for designing lightweight macrostructure with high thermal conductivity
Lightweight and high heat conductive solid structures are playing important role in various
fields of engineering. To maximize the design performance for such structures, we …
fields of engineering. To maximize the design performance for such structures, we …
Rational designs of mechanical metamaterials: Formulations, architectures, tessellations and prospects
Abstract Mechanical Metamaterials (MMs) are artificially designed structures with
extraordinary properties that are dependent on micro architectures and spatial tessellations …
extraordinary properties that are dependent on micro architectures and spatial tessellations …
Design of graded lattice sandwich structures by multiscale topology optimization
Graded lattice sandwich structures (GLSSs) enable superior structural performances due to
the continuously-varying configurations and properties of lattices in space. This paper …
the continuously-varying configurations and properties of lattices in space. This paper …
A comprehensive review of isogeometric topology optimization: methods, applications and prospects
Topology Optimization (TO) is a powerful numerical technique to determine the optimal
material layout in a design domain, which has accepted considerable developments in …
material layout in a design domain, which has accepted considerable developments in …
Non-parametric optimization for lightweight and high heat conductive structures under convection using metaheuristic structure binary-distribution method
In this paper, we propose a novel Metaheuristic Structure Binary-Distribution (MSB) method
for attaining lightweight and high thermal conductive structure. MSB combines metaheuristic …
for attaining lightweight and high thermal conductive structure. MSB combines metaheuristic …
Physics-guided, physics-informed, and physics-encoded neural networks and operators in scientific computing: Fluid and solid mechanics
SA Faroughi, NM Pawar… - Journal of …, 2024 - asmedigitalcollection.asme.org
Advancements in computing power have recently made it possible to utilize machine
learning and deep learning to push scientific computing forward in a range of disciplines …
learning and deep learning to push scientific computing forward in a range of disciplines …
Multiscale topology optimization for minimizing frequency responses of cellular composites with connectable graded microstructures
This paper develops an efficient multiscale topology optimization method for minimizing the
frequency response of cellular composites over a given frequency interval, which consist of …
frequency response of cellular composites over a given frequency interval, which consist of …