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H. Alicia Kim

Publications and source records attributed to H. Alicia Kim.

6 recordsLinked to original sources

Sparse Narrow-Band Topology Optimization for Large-Scale Thermal-Fluid Applications

We propose a fluid-based topology optimization methodology for convective heat-transfer problems that can manage an extensive number of design variables, enabling the fine geometric features required for the next generation of heat-exchangers design. Building on the classical Borrvall-Petersson formulation for the Stokes flow, we introduce an optimization algorithm that focuses computational effort on the fluid-solid interface, where it is most needed. To address the high cost of repeated forward and adjoint analyses and to avoid leakage through nominally solid regions, we exclude fictitious solid voxels from the analysis by imposing the no-slip boundary conditions in the vicinity of the fluid-solid interface. In contrast to the prior approaches, the fictitious solids are also excluded from the global optimization problem via reducing it to a sequence of local narrow-band subproblems with a variable design space. The contribution of our method is that large-scale optimization can be solved efficiently by continuous simplex method while reliably obtaining binary designs without additional filtering or projection. We demonstrate efficiency of the method on multiple examples, including the optimization of a two-fluid heat exchanger at $Pe=10^4$ on a $370^3$ grid comprising $5\times10^7$ design variables using only a single desktop workstation.

physics.flu-dyn↗

Tailoring high precision polynomial architected material constitutive responses via inverse design

The design of specified nonlinear mechanical responses into a structure or material is a highly sought after capability, which would have a significant impact in areas such as wave tailoring in metamaterials, impact mitigation, soft robotics, and biomedicine. Here, we present a topology optimization approach to design structures for desired polynomial nonlinear behavior, wherein we formulate the problem in such a way as to decouple the nonlinear response from the stiffness. We show results across qualitatively different polynomial behaviors while achieving a high degree of precision, creating a path toward analytically tractable nonlinear dynamical systems. The approach enables access to previously difficult to design for, or hitherto unachieved, nonlinear behavior via optimized structures, which can furthermore be incorporated as unit cells of designer materials with tailored nonlinear properties.

cond-mat.mtrl-sci↗

Thermo-mechanical level-set topology optimization of a load carrying battery pack for electric aircraft

A persistent challenge with the development of electric vertical take-off and landing vehicles (eVTOL) to meet flight power and energy demands is the mass of the load and thermal management systems for batteries. One possible strategy to overcome this problem is to employ optimization techniques to obtain a lightweight battery pack while satisfying structural and thermal requirements. In this work, a structural battery pack with high-energy-density cylindrical cells is optimized using the level-set topology optimization method. The heat generated by the batteries is predicted using a high-fidelity electrochemical model for a given eVTOL flight profile. The worst-case scenario for the battery's heat generation is then considered as a source term in the weakly coupled steady-state thermomechanical finite element model used for optimization. The objective of the optimization problem is to minimize the weighted sum of thermal compliance and structural compliance subjected to a volume constraint. The methodology is demonstrated with numerical examples for different sets of weights. The optimized results due to different weights are compared, discussed, and evaluated with thermal and structural performance indicators. The optimized pack topologies are subjected to a transient thermal finite element analysis to assess the battery pack's thermal response.

math.OC↗

Robust topology optimization of structures under uncertain propagation of imprecise stochastic-based uncertain field

This study introduces a novel computational framework for Robust Topology Optimization (RTO) considering imprecise random field parameters. Unlike the worst-case approach, the present method provides upper and lower bounds for the mean and standard deviation of compliance as well as the optimized topological layouts of a structure for various scenarios. In the proposed approach, the imprecise random field variables are determined utilizing parameterized p-boxes with different confidence intervals. The Karhunen-Loève (K-L) expansion is extended to provide a spectral description of the imprecise random field. The linear superposition method in conjunction with a linear combination of orthogonal functions is employed to obtain explicit mathematical expressions for the first and second order statistical moments of the structural compliance. Then, an interval sensitivity analysis is carried out, applying the Orthogonal Similarity Transformation (OST) method with the boundaries of each of the intermediate variable searched efficiently at every iteration using a Combinatorial Approach (CA). Finally, the validity, accuracy, and applicability of the work are rigorously checked by comparing the outputs of the proposed approach with those obtained using the particle swarm optimization (PSO) and Quasi-Monte-Carlo Simulation (QMCS) methods. Three different numerical examples with imprecise random field loads are presented to show the effectiveness and feasibility of the study.

cs.CE↗

Level-set topology optimization considering nonlinear thermoelasticity

At elevated temperature environments, elastic structures experience a change of the stress-free state of the body that can strongly influence the optimal topology of the structure. This work presents level-set based topology optimization of structures undergoing large deformations due to thermal and mechanical loads. The nonlinear analysis model is constructed by multiplicatively decomposing thermal and mechanical effects and introducing an intermediate stress-free state between the undeformed and deformed coordinates. By incorporating the thermoelastic nonlinearity into the level-set topology optimization scheme, wider design spaces can be explored with the consideration of both mechanical and thermal loads. Four numerical examples are presented that demonstrate how temperature changes affect the optimal design of large-deforming structures. In particular, we show how optimization can manipulate the material layout in order to create a counteracting effect between thermal and mechanical loads, even up to a degree that buckling and snap-through are suppressed. Hence the consideration of large deformations in conjunction with thermoelasticity opens many new possibilities for controlling and manipulating the thermo-mechanical response via topology optimization.

cs.CE↗

Stochastic level-set method for shape optimisation

We present a new method for stochastic shape optimisation of engineering structures. The method generalises an existing deterministic scheme, in which the structure is represented and evolved by a level-set method coupled with mathematical programming. The stochastic element of the algorithm is built on the methods of statistical mechanics and is designed so that the system explores a Boltzmann-Gibbs distribution of structures. In non-convex optimisation problems, the deterministic algorithm can get trapped in local optima: the stochastic generalisation enables sampling of multiple local optima, which aids the search for the globally-optimal structure. The method is demonstrated for several simple geometrical problems, and a proof-of-principle calculation is shown for a simple engineering structure.

cond-mat.stat-mech↗