Unlocking the Potential of Recycled Fibre Reinforcements in Construction: Automating Quality Assessment through Machine Learning (ML)

释放再生纤维增强材料在建筑中的潜力：通过机器学习 (ML) 自动进行质量评估

• 批准号: 10080040
• 金额: $ 6.37万
• 依托单位: ZERO WASTE WORKS LIMITED
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=10080040
• 关键词: Unlocking; Potential; Recycled; Fibre; Reinforcements

The UK has pledged to end its contribution to climate change by 2050 and recently declared a climate emergency. The construction industry, which is responsible for a significant portion of carbon emissions, needs to adopt more recycled materials. The shift towards a circular economy is crucial, and the construction sector must take bold action to meet carbon reduction targets. The use of low carbon solutions like recycled fibres recovered from End-of-Life tyres is essential for achieving carbon-neutral construction. However, assessing the quality of these fibres is challenging due to their varying geometries and this impedes their market acceptance. To address this, the project aims to automate the quality assessment using machine learning techniques. By improving efficiency and providing evidence of quality, this collaboration seeks to promote the adoption of recycled fibres in reinforced concrete applications, reducing waste and CO2 emissions in sustainable construction.

英国已承诺到2050年停止对气候变化的贡献，并于最近宣布进入气候紧急状态。占碳排放量很大一部分的建筑行业需要采用更多的可回收材料。向循环经济转型至关重要，建筑行业必须采取大胆行动，实现碳减排目标。使用低碳解决方案，如从报废轮胎中回收的回收纤维，对于实现碳中和结构至关重要。然而，由于其不同的几何形状，评估这些纤维的质量具有挑战性，这阻碍了它们的市场接受度。为了解决这个问题，该项目旨在使用机器学习技术自动化质量评估。通过提高效率和提供质量证据，该合作旨在促进在钢筋混凝土应用中采用再生纤维，减少可持续建筑中的废物和二氧化碳排放。