2020fall ME PhD申请 第一版SOP, 虚心求教

第一版SOP, 第一段主要讲动机，穿插一点研究兴趣，第二段将兴趣，第三段讲研究经历，第四段总结，另外，需要将已经发表的论文在SOP中提及吗？虚心求教。
Personal Statement
I am a graduate student, applying for a Ph.D. in mechanical engineering to explore how best to implement machining full process simulation efficiently and how best to pass on what I learn to others. As precision machine elements require lower trial cost and higher machining accuracy, new integrated machining simulation procedure and new simulation method have begun to emerge. Engineers conduct simulations spanning from much prominent software, such as Virfac, Advantedge, Abaqus, or Nastran, and each software may only solve part of the simulation job and may cost lots of time. I am fascinated with the challenges inherent in developing a new simulation method and want to contribute to meeting these challenges. My ultimate goal is to share what I learn with others, as a professor. Research and education are of the same significance at a time when mechanical engineering is with great coverage in Industry 4.0 and is advancing a great deal. I want to contribute to this ongoing revolution by investigating full process machining simulation while giving back to the current and next-generation as an educator.
How to determine the best machining processing plan among all plans which contain a large number of machining operations? As the deformation of one machine element is influenced by multiple factors such as cutting forces, heat, or residual stresses, simulation considering all these factors would be time-consuming. The accumulated error between simulations for different machining operations is also thorny. I want to learn how to find an efficient modeling method to evaluate the deformation for selecting a better machining processing plan. Furthermore, machining steps under one operation need optimizations sometimes. I would like to study how to optimize the machining allowance and machining sequence of these machining steps utilizing less-computing simulations. Moreover, the selecting of the cutting condition, such as the cutting path, is significant for each machining step. I believe that integrating and developing simulations of processing plans, machining operations, and machining steps are beneficial for the industry to improve manufacturing abilities. To implement the integration and development of the simulation modeling, one must consider the entire manufacturing process of machine elements and have a full understanding of machining simulation details.
During my postgraduate career at XX University and my undergraduate career at XX university, research experience has given me the background to explore these problems in more depth as a doctoral student. This year, I have been working with Professor XX and Professor XX to research machining-induced residual stresses and distortion control of thin-walled parts. The overall purpose of the research is to provide a new method with less computation and experiments for optimizing the machining operations of thin-walled aero-parts. We have developed a new semi-empirical method to predict residual stress profiles introduced by machining Inconel 718 alloy. Residual stress investigations are of great importance because the residual stress has an enormous impact on distortions. Distortions are indicators to whether machining operations are reasonable or not. Thus, given that we aim to optimize machining operations efficiently, our residual stress prediction method could achieve speedup in the optimization by taking advantage of both the empirical method and the finite element method. We innovatively utilize the bimodal Gaussian curve and the Random Forest algorithm to develop the prediction model. Besides, another exciting work of ours is about the sensitivity analysis of Johnson-Cook material constants influence on finite element simulation of turning Inconel 718. The Johnson-Cook constitutive equation, which represents the relation between stress and strain under different temperature, plays a crucial role in cutting simulation. However, the Johnson-Cook material constants are acquired from Hopkinson bar experiments every time, consuming much time and money. Therefore, we have made a comprehensive sensitivity analysis of these constants on simulated residual stresses, cutting forces, and cutting chip to guide constant selecting. At present, most of our research focuses on machining-induced residual stresses because distortions of thin-walled parts, especially whose thickness is under two millimeters, are influenced by machining-induced residual stresses most. Also, I participated in the project of “XXXX” with Professor XX and Professor XX last year. This project is the basement of our current research. These two projects are the enlightenment for me and made me decide to devote myself to scientific research.
To sum up, my goals as a Ph.D. student are to research how to efficiently implementing full process machining simulation and how to develop a new simulation modeling method that requires less computation and experiments. Challenges continue to be emphasizing the computing efficiency of simulations and accumulated errors among simulations. I would be excited to have the opportunity to contribute to addressing these challenges for real industrial applications under the background of Industry 4.0. Finally, I want to learn how best to communicate these challenges and proposed solutions to others as a future educator.