Comparative Evaluation of Algorithms for Achieving Ultrapacked Thermal Greases: Microstructural Models and Effective Behavior
| Autor: | Huanyu Liao, Sukshitha Achar P. L., Ganesh Subbarayan |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
010302 applied physics
Mathematical optimization Materials science Optimization algorithm Computer science business.industry Computer programming 02 engineering and technology Particulates 021001 nanoscience & nanotechnology 01 natural sciences Computer Science Applications Electronic Optical and Magnetic Materials Comparative evaluation Nonlinear programming Mechanics of Materials 0103 physical sciences Thermal Electrical and Electronic Engineering 0210 nano-technology Process engineering business Network model |
| Zdroj: | ASME 2019 International Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Microsystems. |
| DOI: | 10.1115/ipack2019-6501 |
| Popis: | As device power density increases, there is a need to dissipate generated heat by increasing particle volume loading in thermal interface materials. In this work, we develop and evaluate algorithms for generating ultrapacked microstructures of particles. Simulated microstructures reported in the literature rarely contain particle volume fractions greater than 60%. However, commercially available thermal greases claim to achieve volume fractions in the range of 60–80%. Therefore, to analyze effectiveness of commercially available particle-filled thermal interface materials, there is a need to develop algorithms capable of generating ultrapacked microstructures. The particle packing problem is initially posed as a nonlinear programming problem (NLP), and formal optimization algorithms are applied to generate microstructures that are maximally packed. Since accuracy of the simulated behavior is dependent on the number of particles in the simulation cell, efficiently simulating large number of particles is imperative. However, the packing simulation is computationally expensive. Therefore, various optimization algorithms are systematically evaluated to assess the computational efficiency as measured by the time to generate the microstructures for a system containing a large number of particles. The evaluated algorithms include the penalty function methods, best-in-class sequential programming method, matrix-less conjugate gradient method as well as the augmented Lagrangian method. In addition, heuristic algorithms are also evaluated to achieve computationally efficient packing. The evaluated heuristic algorithms are mainly based on the Drop-Fall-Shake method, but modified to more effectively simulate the mixing process in commercial planetary mixers. With the developed procedures, Representative Volume Elements (RVE) with volume fraction as high as 74% are demonstrated. The simulated microstructures are analyzed using our previously developed random network model to estimate the effective thermal and mechanical behavior given a particle arrangement. |
| Databáze: | OpenAIRE |
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