NEESR-II: Toward Rapid Return to Occupancy in Unbraced Steel Frames

该奖项是NSF 08-519项目招标乔治·e·布朗地震工程模拟（NEES）研究网络（NEESR）竞赛的结果，包括波特兰州立大学（牵头机构）、华盛顿大学（次级奖项）和加州州立大学洛杉矶分校（次级奖项）。该项目将利用内华达大学里诺分校的多个振动台NEES设备。钢框架建筑的基本抗震设计理念一直是依靠重力荷载系统，以防止生命损失。然而，建筑业主和社会的期望不再满足于仅仅提供生命安全，因此需要新的结构系统来实现更高的性能水平，以限制损害。其中一个设计目标需要包括快速恢复入住，特别是在地震低于最大预期的情况下。该项目的总体目标是开发一种抗横向荷载系统，即链接柱框架系统，用于能够达到特定目标性能水平的无支撑钢框架。提出的结构系统包括新型和传统结构部件的配置，它们共同导致可预测和快速恢复的损伤。NEES设备站点提供了一种独特的能力，可以通过实验评估动态载荷下的系统级响应，这需要研究结构部件的相互作用，并评估拟议建筑框架的潜在优势。该NEES个人研究项目将通过开发独特的抗震荷载抵抗系统来改变中地震和高地震活动性地区的抗震设计方法，从而为该项目的智力价值做出贡献。该研究将使用先进的实验和计算研究方法来发展对系统和组件行为的必要理解。将生成来自大规模动态实验的数据集，以确保能够捕获组件和系统行为的分析模型得到开发。通过这样的实验和分析研究项目获得的深入理解将使稳健设计方法的发展成为可能。本研究的结果不仅会影响抗震设计，还会产生其他更广泛的影响。利用这种新的结构系统将减少震后停机时间和建筑维修成本，因此将对减少地震损失和生命周期成本产生重大影响。此外，该研究将发展对一种新型复合结构的理解，这种结构可以适应其他结构部件。该项目还将影响工程教育和多样性，通过与来自少数族裔和主要本科院校的教师和本科生的积极合作。建议的活动与综合教育组成部分相结合，旨在强调能力和性能设计在本科工程教育中的重要性。这些教育方面将通过使用现有的NEES网络远程呈现工具的研究参与得到加强。该项目的数据将通过NEES数据存储库（http://www.nees.org）提供。

This award is an outcome of the NSF 08-519 program solicitation George E. Brown, Jr. Network for Earthquake Engineering Simulation (NEES) Research (NEESR) competition and includes Portland State University (lead institution), University of Washington (subaward), and California State University, Los Angeles (subaward). The project will utilize the multiple shake table NEES equipment site at the University of Nevada, Reno. The basic seismic design philosophy for steel frame buildings has been to rely on the gravity load system in order to prevent loss of life. However, the expectations of building owners and society are no longer satisfied with merely providing life safety, so new structural systems are needed for achieving improved performance levels that limit damage. One of the design targets needs to include rapid return to occupancy, especially for earthquakes that are less severe than the maximum expected. The overall objective of this project is to develop a lateral load resisting system, the linked column frame system, for unbraced steel frames capable of achieving specific target performance levels. The proposed structural system includes configurations of novel and conventional structural components that together result in predictable and rapidly recoverable damage. NEES equipment sites offer a unique capability to experimentally evaluate system level response under dynamic loads, which is required to study the interaction of the structural components and evaluate the potential advantages of the proposed building frames. This NEES individual investigator project will transform seismic design approach in regions of moderate and high seismicity by developing a unique seismic load resisting system, thereby contributing to the intellectual merit of the project. The research will use advanced experimental and computational research methods to develop the necessary understanding of system and component behaviors. Data sets from large-scale dynamic experiments will be generated to ensure that analytical models capable of capturing both component and system behavior are developed. The depth of understanding achieved through such an experimental and analytical research program will enable the development of robust design methodologies. The outcomes of this research will not only impact seismic design, but also result in other broader impacts. Utilization of such new structural systems will reduce post-event downtime and building repair costs, and thus will have a significant impact on reducing earthquake losses and life-cycle costs. Further, the research will develop understanding of a novel composite construction that could be adapted to other structural components. This project will also impact engineering education and diversity through active collaboration with faculty and undergraduate students from a minority serving and predominantly undergraduate institution. The proposed activities are combined with an integrated educational component designed to emphasize the importance of capacity and performance design in undergraduate engineering education. These educational aspects will be reinforced through research participation using existing NEES web based telepresence tools. Data from this project will be made available through the NEES data repository (http://www.nees.org).