RSB/Collaborative Research: A Sequential Decision Framework to Support Trade Space Exploration of Multi-Hazard Resilient and Sustainable Building Designs

由于决策过程中必须考虑到各种经济、环境、社会和技术因素，多灾害弹性和可持续建筑（RSB）的设计必然是复杂的。这些广泛的考虑导致在众多设计目标（例如，最小化生命周期成本、可能的损失和环境影响）。谈判这些权衡需要新的决策框架和工具，使多危害RSB设计的高效和有效的探索。行为经济学、心理学、营销和认知工程领域的文献支持这样的前提：决策是一个同时构建和满足个人偏好的过程。本研究的目的是形式化的创新顺序决策过程中，量身定制的同时偏好建设和满意度，多危险RSB的设计。模型模拟将在一系列增加保真度的同时进行，决策者（DM）认识到设计空间和固有的权衡（贸易空间），形成偏好，然后满足这些偏好，挑选一组考虑的设计，以达到最终的选择。框架发展的关键如下：（1）创建一个复杂性指数，该指数将使建筑物与其社会、技术、经济、政策和环境背景相关，并评估该背景对建筑物可持续性的影响，以及相反地，建筑物对其更大的区域背景的影响，（2）迭代地探索创新的多灾害RSB设计，（3）建立一组可行的设计目标和设计指标阈值，以及（4）开发贸易空间的数字可视化，以促进和证明设计选择的合理性。序贯决策框架将通过提供DM、设计团队和利益相关者之间的学习、可视化和信息共享机制，对综合设计过程产生积极影响，从而产生对环境、社会和财务负责的建筑设计。 该研究项目的成果将是一个严格的，顺序的，决策框架的基础上，渐进的基于模型的仿真和可视化算法，以支持贸易空间探索多危险RSB设计。进化算法将在每个级别的模型保真度，以产生土壤基础结构围护结构建筑系统的设计方案，考虑一系列的材料，结构形式和建筑部件。通过整合现有的基于性能的概率评估模型、生命周期评估模型和新的概率建筑恢复模型，将为每个建筑设计备选方案和危险情景生成广泛的设计指标。建筑物恢复模型将采用系统可靠性方法开发，并将产生事后功能和恢复时间指标。建筑物恢复模式将明确说明内部功能和外部因素，如公用事业以及组织和技术系统的能力，从而使人们能够在社区复原力的更广泛背景下理解特定的建筑物设计。将开发新的交互式视觉分析技术和可视化算法，以促进多维贸易空间探索，使DM能够协商并深入了解相互冲突的设计指标之间的复杂关系，以确定具有弹性和可持续性的设计。正式的框架将被应用到深入的案例研究中的中高层住宅，商业和混合用途的RSBs的设计受到地震和/或飓风在城市环境中。

The design of multi-hazard resilient and sustainable buildings (RSB) is necessarily complex due to the various economic, environmental, social, and technical considerations that must be factored into the decision-making process. These broad considerations result in tradeoffs among the numerous design objectives (e.g., minimizing life cycle cost, probable losses, and environmental impact). Negotiating these tradeoffs necessitates new decision-making frameworks and tools to enable efficient and effective exploration of multi-hazard RSB designs. Literature in the fields of behavioral economics, psychology, marketing, and cognitive engineering support the premise that decision-making is a simultaneous process of both constructing and satisfying one's preferences. The objective of this research is to formalize an innovative sequential decision process, tailored to simultaneous preference construction and satisfaction, for the design of multi-hazard RSB. Model simulations will be performed in a sequence of increasing fidelity while simultaneously decision-makers (DMs) become cognizant of the design space and inherent tradeoffs (trade space), form preferences, and then satisfy these preferences, culling the set of considered designs throughout to arrive at a final choice. Key to the framework's development are the following: (1) creating a complexity index that will situate the building in relation to its social, technical, economic, policy, and environmental context, and assessing the impact of this context on the sustainability of the building, and conversely, the impact of the building on its larger, regional context, (2) iteratively exploring for innovative multi-hazard RSB designs, (3) establishing sets of feasible design objectives and threshold values of design metrics, and (4) developing digital visualizations of the trade space to facilitate and justify design choices. The sequential decision framework will have a positive impact on the integrative design process by providing mechanisms for learning, visualizing, and sharing of information among the DMs, design team, and stakeholders so that the outcome is an environmentally, socially, financially responsible building design. The outcome of this research project will be a rigorous, sequential, decision framework based on progressive model-based simulation and visualization algorithms to support trade space exploration for multi-hazard RSB designs. Evolutionary algorithms will be employed at each level of model fidelity to generate soil-foundation-structural-envelope building system design alternatives, which consider an array of materials, structural forms, and building components. A broad array of design metrics will be generated for each building design alternative and hazard scenario(s) by integrating existing probabilistic performance-based assessment models, life cycle assessment models, and new probabilistic building recovery models. The building recovery models will be developed using a systems reliability approach and will generate the post-event functionality and recovery time metrics. The building recovery models will explicitly account for internal functions and externalities, such as utilities and the capacity of both organizational and technical systems, thereby allowing a particular building design to be understood in the broader context of a community's resilience. Novel interactive visual analytic techniques and visualization algorithms will be developed to facilitate multi-dimensional trade space exploration, allowing DMs to negotiate and gain insight into the intricate relationships among the conflicting design metrics to identify designs that are both resilient and sustainable. The formalized framework will be applied to in-depth case studies for the design of mid- and high-rise residential, commercial, and mixed-use RSBs threatened by earthquakes and/or hurricanes in urban environments.