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

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:
依托单位国家:
英国
项目类别:
Fellowship
财政年份:
2024
资助国家:
英国
项目状态:
未结题
起止时间:
2024 至 --

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中文摘要
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英文摘要
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.
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