IUCRC Planning Grant University of Houston: Center for Visual Structural Expertise for Resilience (C-ViSER)

将机器学习创新整合到结构工程实践中，为提高美国建筑环境的安全性、弹性和环境可持续性，并支持美国经济增长提供了机会。工程和建筑服务业对美国至关重要，占美国GDP的2.8%，并对全球约37%的碳排放量承担重大责任。结构设计和评估是该领域的关键，是建筑愿景与施工或维护项目实现之间的桥梁。设计、评估和分析的早期阶段对项目的结果和运营生命周期有着至关重要的影响。尽管如此重要，但深入探索替代方法或解决方案通常时间和成本高昂，限制了优化项目弹性，安全性，可持续性和功能性的潜力。通过人工智能的进步来提高结构工程师的生产力、能力和协作，可以解决这些限制。设想中的弹性视觉结构专业知识中心（C-ViSER）将专注于开发基础机器学习创新，以增强建筑环境中的设计和管理实践。为了在实践中实现和实施这些创新，该中心将培养一支精通结构工程和人工智能的多元化劳动力队伍。这一方法不仅促进了科学进步，还促进了结构工程领域的包容性发展，并将为建筑环境、经济增长和社会福祉带来广泛的利益。该赠款支持规划一个新的IUCRC（C-ViSER），该中心由两个研究基地组成-普渡大学（PU）和休斯顿大学（UH）-具有互补的研究优势。UH为该中心带来了结构工程生成人工智能，数字双胞胎计算机视觉，合成数据集生产，机器人和传感器系统，开源工具开发，损伤和断裂建模以及高级地理传感方面的专业知识。这些站点将协同工作，计划创建适应性强、可扩展和准确的端到端ML驱动的应用程序，使结构工程师能够从自己的数字和视觉数据中可靠、有效地提取有意义的信息，这些数据可以在云、商用笔记本电脑和便携式设备上运行。该中心的研究将满足行业对结构工程基础人工智能系统的需求，旨在改变传统的工程实践，以实现最大的影响。该中心的活动将直接关系到全国各地的众多公司提供有关结构工程，建筑，设计，分析，取证，维护，管理和施工服务。该中心更广泛的影响是通过开发创新来服务社会，这些创新将导致更安全的结构，更有信心在其使用寿命内继续发挥功能，更少的费用和对维护和维修的适当关注。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估而被认为值得支持。

The integration of machine learning innovations into the practice of structural engineering offers opportunities to enhance the safety, resilience, and environmental sustainability of the United States' built environment and support growth of the U.S. economy. The engineering and architecture services sector is critical to the nation, accounting for 2.8% of the U.S. GDP, and bears substantial responsibility for approximately 37% of the global carbon emissions. Structural design and evaluation, pivotal in this sector, serve as the bridge between architectural vision and the realization of construction or maintenance projects. The early stages of design, assessment, and analysis crucially impact a project’s outcome and operational life cycle. Despite this importance, the in-depth exploration of alternative approaches or solutions is typically time and cost-prohibitive, limiting the potential for optimizing project resilience, safety, sustainability, and functionality. Enhancing the productivity, capabilities, and collaborations of structural engineers through artificial intelligence advancements can address these limitations. The envisioned Center for Visual Structural Expertise for Resilience (C-ViSER) will focus on developing foundational machine learning innovations to enhance design and management practices in the built environment. To realize and implement these innovations in practice, the Center will cultivate a diverse workforce skilled in both structural engineering and artificial intelligence. This approach not only fosters scientific advancement but also promotes inclusive development within the structural engineering field and will catalyze wide-reaching benefits for the built environment, economic growth, and societal well-being.This grant supports planning of a new IUCRC (C-ViSER) comprised of two sites – Purdue University (PU), and University of Houston (UH) - that have complementary research strengths. UH brings to the Center expertise in generative AI for structural engineering, computer vision for digital twins, synthetic dataset production, robotics and sensor systems, open-source tool development, damage and fracture modeling, and advanced geosensing. The sites will work collaboratively to plan the creation of adaptable, scalable, and accurate end-to-end ML-powered applications to enable structural engineers in their efforts to reliably and efficiently extract meaningful information from their own digital and visual data that can run on the cloud, commercial laptops, and portable devices. The Center’s research will address the industry need for foundational AI systems for structural engineering designed to transform traditional engineering practices for maximum impact. The Center’s activities will be directly relevant to the numerous companies across the nation providing services related to structural engineering, architecture, design, analysis, forensics, maintenance, management, and construction. The broader impacts of the center are to serve society by developing innovations that will result in safer structures, greater confidence in their continued functionality over their lifetime, with less expense and just the right amount of attention dedicated to maintenance and repair.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.