Characterizing Residual Stress on Pipework Weld Repairs Using Machine Learning.

当我在地板的绿色区域内保持我的步伐绕过弯道时，我震惊地看到一个巨大的炽热的钢锭从一个建筑物大小的熔炉中出来后，被铁轨降到一个平台上。当我们继续在韩国昌原的斗山重工核反应堆生产部门参观工厂时，我接近了代表团，试图不被周围的焊接活动分散注意力。我在加纳核能研究所担任技术专家时，参加了为期两周的原子能机构-KHNP关于成功启动新国家核能方案的强化培训方案，这促使我对自己的目的进行了一段时间的强烈自我反思，直到那时我才努力确定这一点。与来自世界各地的志同道合的工程师和研究人员接触，他们本着合作的精神分享知识，以促进核能的发展，我很快意识到这是一个我更适合的领域，我将满足于致力于做出重大贡献。因此，尽管拥有生物医学工程学士学位，我还是决定攻读核工程硕士学位。在我的本科和研究生学习期间进行了研究，并花了两年时间在核研究机构分析数据并完成了Udemy的认证课程，我获得了数据科学，Pytorch机器学习，分子动力学，Monte Carlo模拟和科学写作等方面的技能。所有这些都告诉我解决问题的方法，并允许我构建研究项目，进行实验和模拟，并从输出数据中获得有意义的见解-所有这些都是研究的关键。例如，我的硕士论文要求我使用Python脚本开发自定义数据模块，以自动化从模拟日志文件中阅读特定数值并处理、计算和绘制结果的过程。因此，通过减少重复的工作流程，我有更多的时间专注于结果解释。

As I rounded the curve while maintaining my pace within the green area of the floor, I was shocked to see a massive red-hot ingot being lowered by rails onto a platform after emerging from a building-sized furnace. I closed in on the delegation as we continued our factory tour at Doosan Heavy Industries' nuclear reactor production division in Changwon, South Korea, attempting not to be distracted by the surrounding welding activities. Participating in that two-week intensive IAEA-KHNP training programme on the successful launch of nuclear power programmes for newcomer countries while I was employed as a technologist at the Ghana nuclear power institute prompted a period of intense self-reflection regarding my purpose, something I had struggled to determine up until that point. Engaging with like-minded engineers and researchers from around the world as they shared knowledge in the spirit of cooperation to advance nuclear energy, I quickly realized that this was a field to which I was more suited and to which I would be content devoting myself to making significant contributions. Consequently, despite having a bachelor's degree in biomedical engineering, I decided to pursue master's studies in nuclear engineering. Having conducted research during both my undergraduate and graduate studies, as well as spending two years analyzing data in a nuclear research institution and completing certification courses on Udemy, I have acquired skills in data science, machine learning with Pytorch, molecular dynamics, Monte Carlo simulation, and scientific writing, among others. All of these inform my approach to problem-solving and allow me to construct research projects, conduct experiments and simulations, and derive meaningful insights from output data-all of which are crucial to research. For example, my master's thesis required me to develop custom data modules with Python scripts to automate the process of reading specific numerical values from simulation logfiles and processing, computing, and graphing the results. Consequently, by reducing repetitive workflows, I had more time to focus on result interpretation.