Characteristic of the Dynamics of Disorder in Crystalline and Amorphous Materials

This work provides the evidence to apply simulation methods that are applicable to systems with structural randomness to simulate crystalline materials at high temperatures. My work not only open the avenue to expand the simulation capability of materials but also provides insight to the physics of vibrations of atoms under different temperature and for different types of materials. I have also evaluated the reliability of Molecular Dynamics simulations at the frequency level and found that theses types of simulations, despite the previous belief, are reliable at low temperatures but up to a measurable frequency. In addition, the result of my work explains the reason for high thermal conductivity of amorphous silicon by showing computational evidence for the presence of high wavelength modes in this material and this work is the first computational work reaching reported low-frequency modes

Open Source Software Problems in Heat Transfer to Explore Assumptions and Models

Energy2D software can be downloaded here: http://energy.concord.org/energy2d/ After opening the application, choose File -\u3e Open and select one of the .e2d files available for download here under additional files. Click the Run button to get started. The main download has a document that provides a detailed description of the adaptation of a freely available software program, Energy2D, for problems focused on the exploration and limitations of assumptions made in models commonly used in an undergraduate heat transfer course. The motivation for creating homework problems that use Energy2D is to explore the accuracy and limitations of the models used in heat transfer. The models are commonly utilized because they are easy to use and accurate even when not entirely valid, so these problems will provide students with a better understanding of their accuracy and of when they break down. Examples of models that are used here include 1D steady conduction with no generation, assuming a uniform base surface temperature or uniform convection coefficient for extended surfaces, using shape factors for 2D steady conduction, and the lumped capacitance method for transient conduction. Additional problems were in the process of being developed and will be continually developed during the Spring 2021 semester. The remainder of the document will be organized by problem in order of their coverage in MAE 3440 Heat Transfer at Utah State University

An Interpretable Boosting-based Predictive Model for Transformation Temperatures of Shape Memory Alloys

In this study, we demonstrate how the incorporation of appropriate feature engineering together with the selection of a Machine Learning (ML) algorithm that best suits the available dataset, leads to the development of a predictive model for transformation temperatures that can be applied to a wide range of shape memory alloys. We develop a gradient boosting ML surrogate model capable of predicting Martensite Start, Martensite Finish, Austenite Start, and Austenite Finish transformation temperatures with an average accuracy of more than 95% by explicitly taking care of potential distribution changes when modeling different alloy systems. We included heat treatment, rolling, extrusion processing parameters, and alloy system categorical features in the model input features to achieve more accurate and realistic results. In addition, using Shapley values, which are calculated based on the average marginal contribution of features to all possible coalitions, this study was able to gain insights into the governing features and their effect on predicted transformation temperatures, providing a unique opportunity to examine the critical parameters and features in martensite transformation temperatures

Thermal management of electrical circuits

Technology development over the past decade made the logical components more efficient, but the efficiency was not priceless. The increase in efficiency occurred in parallel with increase in energy consumption. More energy consumption led to a more overheating problem that is one of the main technology limitation reasons. Since the importance of the thermal management in logical components has been considered, several approaches were offered to the industry. The preliminary solution was provided by increasing the heat dissipation by convection. Heat fins are the industrial products that are designed based on this approach. But further developments in electrical engineering led to heat generations close to 100 that are not dissipated with the mentioned solution. Newest trends to solve the problem led to new technologies as, Thermal Ground Planes, Heat pipes and other Nano and Micro solution based technologies. The battery thermal management project has targeted the macro solutions. We are taking advantage of heat simulation programs like Star ccm+ to generate models of the systems to evaluate the problem more accurate, the simulations also help the project through evaluating offered solution without the need to create real models. Regarding the given explanations, macro solution has been simulated and tested and more approaches are being considered. We hope to step into Nano and Micro mechanical world to obtain more efficient solutions