Lateral Load Behavior and Modeling of Shear-Dominant RC Walls for Performance-Based Design

该研究的目标是开发和验证新的建模方法，适用于利用固体钢筋混凝土墙的建筑物的重力和地震荷载的组合。特别是，该项目将研究低层、中层和高层建筑中常用的钢筋混凝土墙的结构性能，以开发新的计算机/数值模型和建筑规范设计指南。为了实现这些目标，将在加州大学洛杉矶分校的结构/地震工程研究实验室进行模拟地震荷载下测试大约10个典型墙体配置的大型模型。墙壁将装有高分辨率传感器，以测量载荷、应力、应变及其变形。测试观察和收集的传感器数据将用于了解损坏如何累积并最终导致崩溃。 该项目将提供方法，以预测损害下中度至强烈的地面震动。将提议对具有这些墙的新建和现有建筑物的基于性能的设计的建筑规范进行修改。研究结果将使工程师能够设计更安全和更经济的新建筑物，并评估现有建筑物的性能，以确定哪些建筑物在预期伤亡和经济损失方面对社区构成重大危险。新的数据，沿着现有的数据从以前的测试，将被编译成一个全面的数据库，并存档到一个社区数据库，使未来的研究和发展。经验证的计算机模型将在开放源码环境中开发，以促进进一步的研究和设计研究。结果将通过一个互动网站和其他鼓励积极参与的网络协作工具传播。该研究将为研究生和本科生提供高级培训，包括高中实习生的积极参与，并包括行业的积极参与。将利用已建立的机构伙伴关系，在项目中招募代表性不足的群体

The goals of the research are to develop and validate new modeling approaches appropriate for combined gravity and earthquake loads for buildings that utilize solid reinforced concrete walls. In particular, the project will study the structural performance of reinforced concrete walls, which are commonly used in the low-, medium-, and high-rise building construction, to develop new computer/numerical models and building code design guidelines. To accomplish these goals, approximately ten large-scale models of typical wall configurations will be tested under simulated earthquake loading in the Structural/Earthquake Engineering Research Laboratory at UCLA. The walls will be instrumented with high-resolution sensors to measure loads, stresses, strains, and their deformations. Test observations and the collected sensor data will be used to understand how damage accumulates and ultimately leads to collapse. Project will provide methodology to predict damage under moderate to intense ground shaking. The changes to building codes for the performance-based design for both new and existing buildings with these walls will be proposed. The research results will enable engineers to design safer and more economical new buildings and to evaluate the performance of existing buildings to identify those posing significant hazard to the community in terms of expected casualties and economic losses. The new data, along with existing data from prior tests, will be compiled into a comprehensive database and archived into a community data repository to enable future research and development. The validated computer models will be developed in an open-source environment to facilitate further research and design studies. The results will be disseminated via an interactive web site and other web-based collaboration tools that encourage active participation. The research will provide advanced training to graduate and undergraduate students, incorporate active participation by high school interns, and include active participation from industry. Underrepresented groups will be recruited in the project using well established institutional partnerships