Reimagined Environmentally-friendly Design (RE-Design) of Reinforced Concrete Infrastructure

分布式传感的使用使人们能够了解钢筋混凝土(RC)基础设施(如桥梁和建筑物)的结构行为，这是以前从未可能实现的。这些来自大量传感器的数据，当与复杂的分析方法相结合时，将通过导致RC设计的突破性进展来影响结构工程。与此同时，到2050年，城市人口将增加25亿，这将创造对基础设施的巨大需求，并增加二氧化碳排放。对钢筋混凝土受弯构件形状优化的研究表明，可以减少20-44%的实际二氧化碳。此外，使用功能级配混凝土(FGC)可以进一步减少材料的使用，这种混凝土的水泥用量根据结构需求而不同。但广泛的实施也带来了一个挑战，即让设计师、建筑商和业主了解这些选择如何影响复杂的结构性能和对他们行为的信心。重新设想的环境友好设计(RE-Design)计划将通过1)开发创新的RC实验，提供独特的数据集以更好地了解复杂的行为，以及2)开发将高质量的分布式传感器测量与用于参数研究的稳健数值模型(传感器分析融合)相结合的技术，使RC基础设施的设计和使用显著减少二氧化碳含量，从而导致重新设想的设计方法来减少二氧化碳含量。研究计划分为三个主题：1.结构优化增强；2.FGC发展；3.传感器-分析融合。主题1将涉及具有优化横截面的梁和具有不同轴向约束水平的板的测试。主题2将涉及细长FGC梁和深FGC梁的测试，这些梁使用正常水泥和减量水泥(约40%的减量)混凝土的组合。这些测试，再加上分布的传感数据，将使人们能够了解这些低浓度二氧化碳样本的行为。主题3将开发将实验结果与数字模型(传感器-分析融合)相结合的技术，以模拟主题1和主题2的实验，并进行参数研究以开发设计方法。该项目的预期成果包括：i)通过减少材料使用，以更低的经济和环境成本为社会提供民用基础设施；ii)通过使用创新技术和设计，潜在地将全球二氧化碳排放量减少5%；iii)新的设计技术，可以适用于使用碳中性材料(如木材)的结构，并保持现有的RC基础设施资产的使用。这项研究将培训14名HQP，并使加拿大在HQP培训和研究专业知识方面处于该领域的领先地位，使加拿大顾问能够在国际上提供领先的服务。

The use of distributed sensing enables an understanding of structural behaviour of reinforced concrete (RC) infrastructure, such as bridges and buildings, that has never before been possible. This data from a large number of sensors, when coupled with sophisticated approaches to analysis, will impact structural engineering by leading to groundbreaking advances in RC design. At the same time, 2.5 billion more people will live in urban areas by the year 2050, creating significant demand for infrastructure and increasing CO2 production. Research into shape optimization of RC flexural members has shown the possibility of reducing embodied CO2 by 20-44%. In addition, the use of functionally graded concrete (FGC), where the amount of cement varies based on the structural demand, could further reduce material use. But widespread implementation comes with the challenge of providing designers, builders, and owners with understanding of how these choices affect complex structural performance and confidence in their behaviour. The Reimagined Environmentally-friendly Design (RE-Design) program will enable the design and use of RC infrastructure with significantly reduced embodied CO2 through 1) the development of innovative RC experiments that provide unique data sets to better understand complex behaviour, and 2) the development of techniques for merging high-quality distributed sensor measurements with robust numerical models (sensor-analysis fusion) for parametric studies that will lead to reimagined design approaches to reduce CO2 content. The research program is divided into three themes: 1. Structural optimization enhancement, 2. FGC development, and 3. Sensor-analysis fusion. Theme 1 will involve the testing of beams with optimized cross-sections and slabs with varying levels of axial restraint. Theme 2 will involve tests of both slender and deep FGC beams with combinations of normal and reduced cement (~40% less) concrete. These tests, coupled with distributed sensing data, will enable the behaviour of these low embodied CO2 specimens to be understood. Theme 3 will develop techniques for merging the results of experiments with numerical models (sensor-analysis fusion) to model the experiments from Themes 1 and 2 and to undertake parametric studies to develop design approaches. The anticipated outcomes of this project include i) providing civil infrastructure at a lower cost to society, both economic and environmental, by reducing material use, ii) potential reductions in global CO2 emissions of up to 5% through the use of innovative technologies and design, and iii) new design techniques that can be adapted for structures using carbon neutral materials, such as timber, and to keep existing RC infrastructure assets in service. The research will result in the training of 14 HQP and position Canada as a leader in this area in terms of HQP training and research expertise, enabling Canadian consultants to offer leading edge services internationally.