SGER: NEESR Payload - Large-Scale Validation of Innovative SMA Recentering Devices for Multi-Span Bridges

本探索性研究小额资助(SGER)项目是根据计划征集NSF 05-527，NEES Research(NEESR)提交的NEESR有效载荷项目。该项目将使用美国国家科学基金会NEESR奖CMS-0420347的实验测试装置，题为“NEESR-SG：采用常规和创新材料的桥梁系统的抗震性能”。这一有效载荷项目的结果将存档在NEES Consortium，Inc.(www.nees.org)维护的NEES数据库中。智能优点：形状记忆合金是一类独特的合金，它能够经历大的位移，并通过马氏体相变恢复到原始的未变形构型。首席调查员之前的工作重点是优化合金的性能，使其能够用于地震应用。这导致了线材和大棒材的理想性能的发展，以及组件阻尼器和重新定心装置的开发和测试。这些研究首次显示了大棒和钢丝的理想旗形超弹性特性。该NEESR有效载荷项目将使用内华达大学雷诺分校的多跨桥梁测试装置，根据NSF NEESR奖CMS-0420347，在NEES设备现场设计、开发和测试桥梁结构上的创新形状记忆合金设备，以验证先前组件测试和分析研究的结果。将测试三套设备：捆绑的SMA钢丝、优化的SMA棒和SMA基复合材料。试验测试将与使用OpenSees的分析研究相结合，以确定装置的最佳性能，以限制上部结构的位移和对柱的要求以及桥台的相对位移。其他分析研究将包括为中小型企业开发详细的模型。将开发几种类型的SMA元素，并在OpenSees元素库中提供。桥梁分析模型的结果将被用来绘制桥梁易损性曲线，以说明这些创新的改造措施在概率框架内的可行性，并允许将带有SMA重新定位装置的桥梁系统的脆弱性降低与其他传统改造措施进行比较。使用佐治亚理工学院的教学振动台，将首先开发一个测试设置的小规模模型，以评估随后将应用于UNR桥梁结构的概念。小型SMA钢丝(直径0.08英寸)将用于小规模实验。广泛的影响：该项目将利用佐治亚理工学院现有AGEP计划的资源，瞄准并资助代表人数不足的本科生参与研究计划的所有方面，包括小规模研究、大规模研究和分析。这项研究的更广泛影响是，前景看好的新形状记忆合金技术的使用将得到验证，这将显著改善桥梁在地震中的性能，从而潜在地减少地震造成的人员伤亡和经济损失。此外，本项目所获得的知识将为智能材料在其他结构系统中的应用奠定基础。

0526889AbstractThis Small Grant for Exploratory Research (SGER) project is a NEESR payload project submitted in accordance with program solicitation NSF 05-527, NEES Research (NEESR). This project will use the experimental test set-up of NSF NEESR award CMS-0420347 entitled "NEESR-SG: Seismic Performance of Bridge Systems with Conventional and Innovative Materials." Results from this payload project will be archived in the NEES data repository maintained by NEES Consortium, Inc. (www.nees.org). Intellectual merit: Shape memory alloys are a class of unique alloys that have the ability to undergo large displacements and revert back to their original undeformed configuration via a martensitic transformation. Previous work by the Principal Investigator has focused on the optimization of the properties of the alloys such that they can be used in seismic applications. This has led to the development of ideal properties for both wire and large bars and the development and testing of component dampers and recentering devices. These studies were the first to show idealized flag-shaped superelastic properties in both large bars and wire. This NEESR payload project will use the multi-span bridge test set-up at the University of Nevada, Reno (UNR), NEES equipment site under NSF NEESR award CMS-0420347 to design, develop, and test innovative SMA devices on the bridge structure to validate the results of previous component testing and analytical studies. Three sets of devices will be tested: bundled SMA wire, optimized SMA bars, and SMA-based composites. The experimental tests will be coupled with analytical studies using OpenSees to determine the optimal properties of the devices to limit superstructure displacement and demands on columns and relative displacement at the abutment. Additional analytical studies will include the development of detailed models for SMAs. Several types of SMA elements will be developed and provided in the OpenSees element library. The results of the analytical models of the bridge will be used to develop bridge fragility curves to illustrate the viability of these innovative retrofit measures in a probabilistic framework and allow for comparison of the reduction in vulnerability of the bridge system with SMA recentering devices with other traditional retrofit measures. Using an instructional shake table located at Georgia Tech, a small-scale model of the test set-up will first be developed to evaluate concepts that will then be applied on the UNR bridge structure. Small SMA wires (0.08" diameter) will be used for the small-scale experiment.Broader Impacts: The project will leverage resources from an existing AGEP program at Georgia Tech to target and fund underrepresented undergraduate students to participate in all aspects of the research program, including the small-scale study, large-scale study, and analysis. The broader impact of the research is that the use of the promising, new SMA technology will be validated, which would significantly improve the performance of bridges during earthquakes, resulting in the potential reduction in casualties and economic losses from earthquakes. Furthermore, the knowledge gained by this project will provide the foundation for the use of smart materials in other structural systems.