SAI-R: Reducing Natural Hazards Risks by Incorporating Community Impacts and Equity
SAI-R: Reducing Natural Hazards Risks by Incorporating Community Impacts and Equity
批准号:
2228559
负责人:
David Johnson
金额:
$74.24万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-09-15 至 2025-08-31
中文摘要
加强美国基础设施(SAI)是NSF的一项计划,旨在促进以人为本的基础和潜在的变革性研究,以加强美国的基础设施。有效的基础设施为社会经济活力和广泛改善生活质量奠定了坚实的基础。强大、可靠和有效的基础设施刺激私营部门创新,促进经济增长,创造就业机会,提高公共部门服务提供的效率,加强社区建设,促进机会平等,保护自然环境,增强国家安全,并推动美国的领导地位。为了实现这些目标,需要来自科学和工程学科的专业知识。SAI重点关注人类推理和决策、治理以及社会和文化过程的知识如何能够建设和维护有效的基础设施,从而改善生活和社会,并建立在技术和工程进步的基础上。在现代建筑规范实施之前设计的混凝土建筑物在20世纪70年代中期可能非常容易倒塌。在像加州这样的地震活跃地区,成千上万的这种建筑物仍然在使用。这包括住宅楼、学校和医院等关键设施。虽然这些漏洞是已知的,但要求改造的地方法令在降低风险方面基本上没有成功。有关抗震改造的建筑规范几乎完全侧重于结构脆弱性和防止地震期间的生命损失。他们往往忽视人们对建筑物功能的重视,以及在极端事件发生后尽快重新使用建筑物的能力。本SAI研究项目确定了不同利益相关者支付各种类型建筑物抗震改造费用的意愿。它还调查了成功激励行动所必需的优先事项和激励措施。本研究的长期目标是确定有效的政策制定策略,以激励社区在未来地震灾害袭击之前减轻地震风险。本项目使用多种方法更好地捕捉人类与建筑环境和基础设施脆弱性之间的互动反馈。一种方法使用定性和定量方法相结合的方法来获取建筑功能和使用的测量结果,这些测量结果可用于预测社区成员如何根据成本、受影响的建筑物以及在发生大地震时的性能来优先考虑不同的改造方案。另一种方法使用物理实验和地震模拟原型建筑特征,以更好地表征这种类型的混凝土建筑的脆弱性和不同改造方案的有效性。这些社会和物理实验所产生的数据相结合,产生一个决策支持系统,决策者可以使用它来设计改造和资金战略,是密切配合社区的偏好。将利益相关者的偏好纳入风险缓解工作将改善和加强对未来地震灾害的恢复能力。该奖项由社会、行为和经济(SBE)科学理事会和工程理事会支持。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,被认为值得支持。
英文摘要
Strengthening American Infrastructure (SAI) is an NSF Program seeking to stimulate human-centered fundamental and potentially transformative research that strengthens America’s infrastructure. Effective infrastructure provides a strong foundation for socioeconomic vitality and broad quality of life improvement. Strong, reliable, and effective infrastructure spurs private-sector innovation, grows the economy, creates jobs, makes public-sector service provision more efficient, strengthens communities, promotes equal opportunity, protects the natural environment, enhances national security, and fuels American leadership. To achieve these goals requires expertise from across the science and engineering disciplines. SAI focuses on how knowledge of human reasoning and decision-making, governance, and social and cultural processes enables the building and maintenance of effective infrastructure that improves lives and society and builds on advances in technology and engineering.Concrete buildings designed prior to the implementation of modern building codes in the mid-1970s may be highly vulnerable to collapse. Many thousands of these structures in seismically active areas like California are still in service. This includes residential buildings, schools, and critical facilities like hospitals. Although these vulnerabilities are known, local ordinances mandating retrofits have been largely unsuccessful in achieving risk reductions. Building codes governing seismic retrofits focus almost exclusively on structural vulnerability and preventing loss of life during an earthquake. They tend to ignore the value that people place on the functionality of buildings and the ability to reoccupy them as quickly as possible after an extreme event. This SAI research project identifies different stakeholders’ willingness to pay for seismic retrofits on various types of buildings. It also investigates the priorities and incentives that are necessary to successfully motivate action. The long-term aim of this research is to identify effective policy-making strategies to motivate communities to mitigate seismic risks before a future earthquake disaster strikes.This project uses several approaches to better capture the feedback between human interaction with the built environment and infrastructure vulnerability. One approach uses a mix of qualitative and quantitative methods to elicit measures of building functionality and usage that can be used to predict how community members prioritize different retrofit options based on their cost, the buildings affected, and resulting performance in the event of a major earthquake. Another approach uses physical experiments and simulation of earthquakes on archetypal building features to better characterize the vulnerability of this type of concrete building and the effectiveness of different retrofit options. The data generated by these social and physical experiments are combined to produce a decision support system that policy makers can use to design retrofit and funding strategies that are closely aligned with the revealed preferences of the community. Incorporating stakeholder preferences into risk mitigation efforts will improve and strengthen resilience to future earthquake disasters.This award is supported by the Directorate for Social, Behavioral, and Economic (SBE) Sciences and the Directorate for Engineering.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.
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