83 citations · 331 across the 17 of their papers we have counts for
17 papers
VoroTO: Multiscale Topology Optimization of Voronoi Structures using Surrogate Neural Networks
Rahul Kumar Padhy, Krishnan Suresh, Aaditya Chandrasekhar
Cellular structures found in nature exhibit remarkable properties such as high strength, high energy absorption, excellent thermal/acoustic insulation, and fluid transfusion. Many…
TOMAS: Topology Optimization of Multiscale Fluid Devices using Variational Autoencoders and Super-Shapes
Rahul Kumar Padhy, Krishnan Suresh, Aaditya Chandrasekhar
In this paper, we present a framework for multiscale topology optimization of fluid-flow devices. The objective is to minimize dissipated power, subject to a desired contact-area.…
Isoparametric Tangled Finite Element Method for Nonlinear Elasticity
Bhagyashree Prabhune, Krishnan Suresh
An important requirement in the standard finite element method (FEM) is that all elements in the underlying mesh must be tangle-free i.e., the Jacobian must be positive throughout…
FluTO: Graded Multiscale Fluid Topology Optimization using Neural Networks
Rahul Kumar Padhy, Aaditya Chandrasekhar, Krishnan Suresh
Fluid-flow devices with low dissipation, but high contact area, are of importance in many applications. A well-known strategy to design such devices is multi-scale topology optimiz…
A Generalized Framework for Microstructural Optimization using Neural Networks
Saketh Sridhara, Aaditya Chandrasekhar, Krishnan Suresh
Microstructures, i.e., architected materials, are designed today, typically, by maximizing an objective, such as bulk modulus, subject to a volume constraint. However, in many appl…
Towards tangled finite element analysis over partially inverted hexahedral elements
Bhagyashree Prabhune, Krishnan Suresh
If a finite element mesh contains concave elements, it is said to tangled. Tangled meshes can occur during mesh generation, mesh optimization, and large deformation simulations, an…
FRC-TOuNN: Topology Optimization of Continuous Fiber Reinforced Composites using Neural Network
Aaditya Chandrasekhar, Amir Mirzendehdel, Morad Behandish +1
In this paper, we present a topology optimization (TO) framework to simultaneously optimize the matrix topology and fiber distribution of functionally graded continuous fiber-reinf…
GM-TOuNN: Graded Multiscale Topology Optimization using Neural Networks
Aaditya Chandrasekhar, Saketh Sridhara, Krishnan Suresh
Multiscale topology optimization (M-TO) entails generating an optimal global topology, and an optimal set of microstructures at a smaller scale, for a physics-constrained problem.…
Stress constrained thermo-elastic topology optimization with varying temperature fields via augmented topological sensitivity based level-set
Shiguang Deng, Krishnan Suresh
Engineering structures must often be designed to resist thermally induced stresses. Significant progress has been made on the design of such structures through thermo-elastic topol…
Multi-constrained 3D topology optimization via augmented topological level-set
Shiguang Deng, Suresh Krishnan
The objective of this paper is to introduce and demonstrate a robust methodology for solving multi-constrained 3D topology optimization problems. The proposed methodology is a comb…
Multi-constrained topology optimization via the topological sensitivity
Shiguang Deng, Krishnan Suresh
The objective of this paper is to introduce and demonstrate a robust method for multi-constrained topology optimization. The method is derived by combining the topological sensitiv…
Topology optimization under thermo-elastic buckling
Shiguang Deng, Suresh Krishnan
The focus of this paper is on topology optimization of continuum structures subject to thermally induced buckling. Popular strategies for solving such problems include Solid Isotro…
Integrating Material Selection with Design Optimization via Neural Networks
Aaditya Chandrasekhar, Saketh Sridhara, Krishnan Suresh
The engineering design process often entails optimizing the underlying geometry while simultaneously selecting a suitable material. For a certain class of simple problems, the two…
Length Scale Control in Topology Optimization using Fourier Enhanced Neural Networks
Aaditya Chandrasekhar, Krishnan Suresh
Length scale control is imposed in topology optimization (TO) to make designs amenable to manufacturing and other functional requirements. Broadly, there are two types of length-sc…
Estimation of elastic behaviors of metal components containing process induced porosity
Shiguang Deng, Carl Soderhjelm, Diran Apelian +1
Significant progress has been made for assessing the influence of porosity on the performance metrics for cast components through various modeling techniques. However, a computatio…
Second-Order Defeaturing Estimator of Manufacturing-Induced Porosity on Structural Elasticity
Shiguang Deng, Carl Soderhjelm, Diran Apelian +1
Manufactured metallic components often contain non-uniformly distributed pores of complex morphologies. Since such porosity defects have significant influence on material behaviors…
AuTO: A Framework for Automatic differentiation in Topology Optimization
Aaditya Chandrasekhar, Saketh Sridhara, Krishnan Suresh
A critical step in topology optimization (TO) is finding sensitivities. Manual derivation and implementation of the sensitivities can be quite laborious and error-prone, especially…