Characterizing Residual Stress on Pipework Weld Repairs Using Machine Learning.

使用机器学习表征管道焊缝修复的残余应力。

• 批准号: 2883610
• 金额: --
• 依托单位: The Open University
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2883610
• 关键词: Characterizing; Residual; Stress; Pipework; Weld

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.

当我在地板的绿色区域内保持步调的同时绕过弯道时，我震惊地看到一块巨大的烧红的锭从建筑物大小的熔炉中出来后被铁轨降到平台上。当我们继续参观斗山重工位于韩国昌原的核反应堆生产部门的工厂时，我靠近了代表团，试图不被周围的焊接活动分散注意力。当我在加纳核电研究所担任技术专家时，参加了为期两周的 IAEA-KHNP 强化培训计划，内容是为新来者国家成功启动核电计划，这促使我对自己的目的进行了一段时间的强烈自我反思，这是我的目标。直到那时为止，我们一直在努力确定。与来自世界各地志同道合的工程师和研究人员接触，本着合作精神分享知识以推进核能发展，我很快意识到这是一个我更适合并且愿意投身其中的领域做出重大贡献。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。我在本科和研究生期间进行了研究，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，因此我掌握了数据科学、Pytorch 机器学习、分子动力学、蒙特卡罗模拟等方面的技能，以及科学写作等等。所有这些都告诉我解决问题的方法，使我能够构建研究项目、进行实验和模拟，并从输出数据中获得有意义的见解——所有这些对研究都至关重要。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，以自动执行从模拟日志文件中读取特定数值以及处理、计算和绘制结果的过程。因此，通过减少重复的工作流程，我有更多时间专注于结果解释。