Re4Rail: AI and digital twin-based automated technology to real-time repair, reuse, recycle and repurpose railway granular media

Re4Rail：基于人工智能和数字孪生的自动化技术，可实时修复、再利用、回收和重新利用铁路颗粒介质

• 批准号: EP/Y015401/1
• 负责人: Yunlong Guo
• 金额: $ 23.84万
• 依托单位: University of Birmingham
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FY015401%2F1
• 关键词: Re4Rail; AI; digital; twin; based

Re4Rail project aims to build new technological enablers for sustainable asset management throughout the life cycle of railway granular media (RGM). The technological enablers include a health monitoring system (during service for repair) and circularity management (through end-of-life reuse, recycle and repurpose) aiming for zero carbon emissions of RGM, of which railway ballast and sub-ballast provide crucial support to track systems. Re4Rail will be achieved by establishing an innovative AI & digital twin-based automated technology for real-time RGM defect diagnosis and prognosis (Re4Tech). The applicant will conduct Re4Rail under the supervision of world-renown scientists at University of Birmingham (UoB), and secondment supervisors across sectors at Loram Finland Oy (non-academic) and at University of Illinois Urbana-Champaign (academic). Not only will Re4Rail revolutionise the smart maintenance and circular economy for RGM, but it will also enact the applicant's new competency in artificial intelligence, digital transformation, and geophysics, and endorse my employability skills in both academia and industry within UK and Europe. It also opens a new door of using novel data science tools (AI and digital twin) in solving challenging engineering issues (RGM digitalisation and sustainability) towards accomplishing global common goal (zero carbon emissions). Re4Tech will reduce RGM-related costs by 55% (expected) through the following improvements: (i) Re4Tech will classify and guide materials circularity optimisation, which will reduce the inspection and maintenance frequencies by 80% (expected); (ii) increase RGM operational life by 50% (expected); and (iii) reduce usage of raw granular materials by 40% (expected). Re4Rail will reduce carbon emissions by 70% (expected) throughout its life cycle, plus reducing inspection and maintenance frequencies. Re4Rail will empower Europe to certainly become a world leader in digital maintenance of railway towards net zero by 2030.

Re 4 Rail项目旨在为铁路颗粒介质（RGM）的整个生命周期中的可持续资产管理构建新的技术推动因素。技术推动因素包括健康监测系统（在维修服务期间）和循环管理（通过报废再利用，回收和再利用），旨在实现RGM的零碳排放，其中铁路道碴和次道碴为轨道系统提供关键支持。Re 4 Rail将通过建立一种创新的基于AI和数字孪生的自动化技术来实现实时RGM缺陷诊断和预后（Re 4 Tech）。申请人将在伯明翰大学（UoB）世界知名科学家的监督下进行Re 4 Rail，并在Loram Finland Oy（非学术）和伊利诺伊大学厄巴纳-香槟分校（学术）的跨部门借调监督员。Re 4 Rail不仅将彻底改变RGM的智能维护和循环经济，还将使申请人在人工智能，数字化转型和物理学方面具备新的能力，并认可我在英国和欧洲学术界和工业界的就业技能。它还打开了一扇新的大门，使用新的数据科学工具（人工智能和数字孪生）来解决具有挑战性的工程问题（RGM数字化和可持续性），以实现全球共同目标（零碳排放）。Re 4 Tech将通过以下改进将RGM相关成本降低55%（预期）：（i）Re 4 Tech将分类并指导材料循环优化，这将减少80%的检查和维护频率（预期）;（ii）将RGM使用寿命延长50%（预期）;以及（iii）将原颗粒材料的使用量减少40%（预期）。Re 4 Rail将在其整个生命周期内减少70%的碳排放量，并减少检查和维护频率。Re 4 Rail将使欧洲在2030年前成为铁路数字化维护的世界领导者。