CAREER: Multi-Physics Modeling for Probabilistic Design and Engineering of Sustainable Infrastructure

这项教师早期职业发展（Career）计划将创建新的、以科学为基础的计算机模型，以准确预测钢筋混凝土基础设施的恶化。物质基础设施是我们生活质量的基础，也是国家发展和进步的基础。然而，桥梁、水坝和其他结构的设计是安全、高效、持久的，同时也是社会、环境和经济可持续的，并不是直截了当的。我们日益恶化的基础设施继续需要更多的维护预算，同时消耗大量的物质资源和能源。通过这项研究创建的新模型将导致基础设施系统的设计，在其长达数十年的生命周期中降低经济成本、环境排放和负面社会影响。这些模型的一个重要创新是它们考虑不确定性的能力。不确定的未来事件可能包括基础设施使用模式的演变、气候变化或新的、更可持续的建筑技术的引入。通过重新思考我们国家基础设施的设计和管理，这项研究的结果将有利于美国的经济、环境和社会。研究涉及土木工程、材料科学、电化学、工业生态学等多个学科。这种多学科的方法将被用来增加未被充分代表的群体在本科生、研究生和实践专业水平的研究和教育中的参与。未来的钢筋混凝土设计标准应该将基于物理的材料和结构模型与基于概率可靠度的方法结合起来，以设计安全高效的结构。为了推进可持续基础设施设计领域，本研究致力于开发(i)暴露于恶劣环境下的钢筋混凝土结构退化的多物理场、多尺度数值模型，（ii）捕获钢筋混凝土材料全生命周期影响的概率生命周期评估模型，以及（iii）基于可靠性的基础设施系统设计方法，满足经济、环境、社会可持续性限制了国家。劣化模型将通过计算将较小尺度下的离子传输、钢筋腐蚀起始和腐蚀扩展的物理化学过程与较大尺度下钢筋混凝土结构劣化的有限元模型联系起来。当与概率生命周期影响措施正交整合时，可以计算钢筋混凝土基础设施未来经济、社会和环境影响的演变，以及其满足长期、以可持续发展为重点、减少影响目标的可能性。最终，本研究为将以可持续为中心的设计目标融入现代结构工程设计方法提供了一条途径。

This Faculty Early Career Development (CAREER) Program grant will create new, science-based, computer models to accurately predict the deterioration of reinforced concrete infrastructure. Physical infrastructure forms a foundation for our quality of life and enables national development and progress. However, the design of bridges, dams, and other structures that are safe, efficient, and long lasting, while also socially, environmentally, and economically sustainable, has not proven to be straightforward. Our deteriorating infrastructure continues to require larger maintenance budgets, while consuming vast material resources and energy. The new models created through this research will result in the design of infrastructure systems that reduce economic cost, environmental emissions, and negative societal impacts over their decades-long life cycles. An important innovation of these models is their ability to consider uncertainty. Uncertain future events may include evolving use patterns of infrastructure, a changing climate, or the introduction of new, more sustainable, construction technologies. By rethinking the design and management of our national infrastructure, results from this research will benefit the United States economy, environment, and society. The research involves a number of disciplines including civil engineering, material science, electrochemistry, and industrial ecology. This multi-disciplinary approach will be leveraged to increase participation of underrepresented groups in research and education at the undergraduate, graduate, and practicing professional levels.Future reinforced concrete design standards should couple physics-based models of materials and structures with probabilistic reliability-based methods in order to design safe and efficient structures. To advance the field of sustainable infrastructure design, this research engages in development of (i) multi-physics, multi-scale numerical models for deterioration of reinforced concrete structures exposed to harsh environments, (ii) probabilistic life cycle assessment models that capture the full life cycle impacts of reinforced concrete materials, and (iii) reliability-based design approaches for infrastructure systems that meet economic, environmental, and social sustainability limit states. Deterioration models will computationally link physiochemical processes of ion transport, reinforcement corrosion initiation, and corrosion propagation at smaller scales with finite element models of degraded reinforced concrete structures at larger scales. When orthogonally integrated with probabilistic life cycle impact measures, the evolution of future economic, social, and environmental impacts of reinforced concrete infrastructure can be computed, along with its likelihood of meeting long-term, sustainability-focused, impact reduction targets. Ultimately, this research provides a pathway for integrating sustainability-focused design goals into modern structural engineering design methods.