SGER: Implosion of a Building and Progressive Collapse Analysis of Structures
SGER:建筑物的内爆和结构的渐进式倒塌分析
基本信息
- 批准号:0601258
- 负责人:
- 金额:$ 3.49万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2005
- 资助国家:美国
- 起止时间:2005-12-15 至 2006-11-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Abstract-0601258Preventing progressive collapse is a gravely important problem for society, particularly after the attacks on the Murrah Federal building in 1995 and the terrorist attacks on September 11, 2001. Such prevention requires knowledge of system-level behavior, but there is very little actual data because system-level tests are prohibitively expensive. Progressive collapse is by nature a system-level problem where the spread of an initial local failure from element to element eventually results in the collapse of an entire structure or a disproportionately large part of it (ASCE 7, 2002). Our understanding of collapse mechanisms and structural capacities under such conditions is limited because relevant experimental results on the behavior of elements and whole structures are scarce.This proposal describes an exploratory research plan that obtains realistic and reliable data from a full-scale reinforced concrete (RC) structure scheduled to be imploded, in order to determine its capacity and potential progressive collapse mechanism after imposing preplanned damage scenarios. The data obtained form the building are realistic and reliable, because there is no need to impose any structural damage to RC beams and columns prior to the implosion other than making some small holes in exploding columns to place explosives. The nonstructural elements in the imploding stories will be removed for the ease of collapse. The removal of nonstructural elements will not considerably affect the collapse mechanism, yet makes it easier to examine the deformation capacity of structural elements without the complication introduced by nonstructural elements. The research program will serve as a first step to demonstrate the possibility of collection of such data, and the value of the data in developing reliable capacity models as well as procedures for reliable progressive collapseanalysis. GSA (2003) and DOD (2004) use scenarios with the removal of one column as the initial local failure to examine progressive collapse of structures. Prior to the main implosion of a building, some of the columns are exploded to evaluate the response of the building and proper implosion strategy. Based on an existing collaboration with the Controlled Demolition Inc, these columns will be chosen jointly with CDI experts. The building will be instrumented at two stages; one during the explosion tests and one during the main implosion. The first stage will provide invaluable information about the post-failure system response of the building, which will significantly help improve modeling techniques and estimation of demands following the removal of load bearing elements. The data collected from the second stage will be utilized to develop capacity models for collapse of RC structural elements due to the imposed large displacements and forces. The main objectives of the experiment are to: understand mechanisms of progressive collapse and failure modes; evaluate procedures for progressive collapse analysis currently used by engineers; determine effects of reinforcement details, joints and floor diaphragms on progressive collapse; identify deformation capacities of critical elements; and calibrate and verify advanced material and geometric nonlinear dynamic analysis of the structure.Intellectual Merit: In this exploratory and innovative research, a full-scale system-levelexperimental program will be carried out to collect reliable responses from a RC structure with preplanned damage. Utilizing the data, the effects of reinforcement detailing on progressive collapse will be studied. The recorded data will be used to develop capacity models, which in turn can be used to more reliably estimate potential progressive collapse of structures. Furthermore, the data will be used to calibrate and verify advanced nonlinear dynamic analysis of progressive collapse.Broader Impact: Development of reliable progressive collapse analysis leads to identifyingstructures that are potentially hazardous, which in turn results in better allocation of limited resources in rehabilitation of structures and development of cost-effective retrofit plans for existing structures. The outcomes of this project will also help quantify the effectiveness of structural integrity requirements in current codes for new structures. Furthermore, the outcomes can be used in examining collapse prevention performance of existing structures and their rehabilitation.
摘要-0601258防止连续倒塌是一个严重的社会问题,特别是在1995年对默拉联邦大楼的袭击和2001年9月11日的恐怖袭击之后。这种预防需要系统级行为的知识,但实际数据很少,因为系统级测试非常昂贵。渐进式倒塌本质上是一个系统级问题,其中初始局部失效从元件到元件的传播最终导致整个结构或其不成比例的大部分倒塌(ASCE 7,2002)。由于缺乏有关构件和整体结构性能的试验结果,我们对这种条件下的倒塌机理和结构承载力的理解是有限的。本提案描述了一个探索性的研究计划,从一个计划内爆的全尺寸钢筋混凝土(RC)结构中获得现实和可靠的数据,以确定其能力和潜在的渐进式倒塌机制后,实施预先计划的损害情况。从该建筑物获得的数据是真实可靠的,因为没有必要施加任何结构损伤的RC梁和柱之前,爆柱的一些小孔放置炸药。内爆楼层中的非结构性构件将被移除,以便于倒塌。非结构元素的删除不会对倒塌机制产生很大影响,但可以更容易地检查结构元素的变形能力,而不会引入非结构元素的复杂性。该研究计划将作为第一步,展示收集此类数据的可能性,以及数据在开发可靠容量模型以及可靠渐进倒塌分析程序方面的价值。GSA(2003)和DOD(2004)使用移除一根柱作为初始局部失效的场景来检查结构的连续倒塌。在建筑物主内爆发生前,先对部分立柱进行爆破,以评估建筑物的反应和合理的内爆策略。根据与控制拆除公司的现有合作,这些柱子将与CDI专家共同选择。该建筑将在两个阶段安装仪器;一个在爆炸试验期间,一个在主内爆期间。第一阶段将提供有关建筑物故障后系统响应的宝贵信息,这将大大有助于改进建模技术和拆除承重构件后的需求估计。从第二阶段收集的数据将被用来开发能力模型的RC结构元件的崩溃,由于施加大的位移和力。试验的主要目的是:了解连续倒塌的机理和破坏模式;评估工程师目前使用的连续倒塌分析程序;确定钢筋详图、接头和楼板隔板对连续倒塌的影响;确定关键构件的变形能力;校准和验证结构的先进材料和几何非线性动力分析。在这项探索性和创新性的研究中,将进行一个完整的系统级实验计划,以收集可靠的反应,从钢筋混凝土结构与预先计划的损伤。利用这些数据,将研究钢筋构造对连续倒塌的影响。记录的数据将用于开发容量模型,进而可用于更可靠地估计结构的潜在连续倒塌。更广泛的影响:可靠的连续倒塌分析的发展导致识别潜在危险的结构,这反过来又导致更好地分配有限的资源,在结构的修复和发展具有成本效益的改造计划,为现有结构。该项目的成果还将有助于量化新结构现行规范中结构完整性要求的有效性。此外,研究结果可用于现有建筑物的防倒塌性能检查及其修复。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Mehrdad Sasani其他文献
Convolutional variational autoencoder for Northeast US coastal wind and flood hazard data augmentation
- DOI:
10.1007/s00521-025-11085-w - 发表时间:
2025-03-05 - 期刊:
- 影响因子:4.500
- 作者:
Yiming Jia;Mehrdad Sasani - 通讯作者:
Mehrdad Sasani
Convolutional autoencoder-based ground motion clustering and selection
基于卷积自动编码器的地震动聚类与选取
- DOI:
10.1016/j.soildyn.2025.109240 - 发表时间:
2025-04-01 - 期刊:
- 影响因子:4.600
- 作者:
Yiming Jia;Mehrdad Sasani - 通讯作者:
Mehrdad Sasani
Mehrdad Sasani的其他文献
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{{ truncateString('Mehrdad Sasani', 18)}}的其他基金
Scalable Assessment of Urban Earthquake Resilience: A Novel Model-informed Deep Learning Paradigm
城市抗震能力的可扩展评估:一种新的基于模型的深度学习范式
- 批准号:
2053741 - 财政年份:2021
- 资助金额:
$ 3.49万 - 项目类别:
Standard Grant
RSB: A Decision and Design Framework for Multi-Hazard Resilient and Sustainable Buildings
RSB:针对多种灾害的弹性和可持续建筑的决策和设计框架
- 批准号:
1455450 - 财政年份:2015
- 资助金额:
$ 3.49万 - 项目类别:
Standard Grant
NEESR: Near Collapse Performance of Existing Reinforced Concrete Frame Buildings
NEESR:现有钢筋混凝土框架建筑的近倒塌性能
- 批准号:
1135005 - 财政年份:2012
- 资助金额:
$ 3.49万 - 项目类别:
Standard Grant
CAREER: Multihazard Progressive Collapse Analysis of Structures
职业:结构的多灾害渐进倒塌分析
- 批准号:
0547503 - 财政年份:2006
- 资助金额:
$ 3.49万 - 项目类别:
Standard Grant
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