CAREER: Computational Platform for Recursive Adaptive Multi-level Analysis of Structures under Extreme Events

职业:极端​​事件下结构递归自适应多级分析的计算平台

基本信息

  • 批准号:
    0547670
  • 负责人:
  • 金额:
    $ 49.99万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2006
  • 资助国家:
    美国
  • 起止时间:
    2006-02-15 至 2012-01-31
  • 项目状态:
    已结题

项目摘要

Abstract : In this project, development of a computational platform is proposed for analyses and whole-system simulations of structural response during extreme events, such as blasts, explosions and high-velocity impact. The platform will be constructed with novel methods developed through research, and with best available technologies for extreme event simulations. The structural response will be obtained at multiple spatial and temporal scales simultaneously, in order to achieve high fidelity and computational efficiency. Three different scales will be considered: (Fine Scale) In the immediate vicinity of the extreme event, response will be simulated using a novel Mesh-free method. Within this zone, the consideration of extremely fine spatial and temporal scales is needed to capture fracture, fragmentation and phase changes of materials under high-strain rates. (Medium Scale) For the structural members adjacent to the fine scale zone, novel Finite Element methods will be utilized to capture failure through cracking, large deformations, and inelastic material behavior. (Coarse Scale) For the rest of the structure, robust and accurate structural (beam, plate) finite elements will be used to obtain the global response. These three types of zones will be interfaced with novel methods that will enable the use of non-matching temporal and spatial discretizations (i.e., different time-step sizes, finite elements and mesh-free nodes) within each zone. Through this methodology, it will be possible to obtain local (member and material failure) and global (structural collapse) responses with a high accuracy and computational efficiency. The proposed platform will also be capable of performing recursive and adaptive computations to enhance computational efficiency. The proposed computational platform will be capable of considering the global and local response of structures during extreme events. This approach is necessary to determine the failure of members that are directly exposed to the extreme events and the progressive collapse mechanisms of the structure as a whole. Currently there is no such simulation tool in existence. As such, the proposed platform will aid forensic engineers in vulnerability assessment studies, and in the development of blast/impact-resistant design and retrofitting techniques. The research outcomes will have a broad impact on related fields. The element formulations, analysis methods and algorithms generated throughout the project will be applicable to earthquake engineering, material response modeling, fracture mechanics, and structural dynamics fields in general. Through the outreach activities, the project will generate a viable synergy between researchers in academia, in national research laboratories, and forensic engineers. The graduate students will be trained through research, internships, and participation in outreach.
摘要:本项目拟开发一个计算平台,用于爆炸、爆炸和高速撞击等极端事件下结构响应的分析和全系统模拟。该平台将采用通过研究开发的新方法,以及可用于极端事件模拟的最佳技术来构建。同时在多个空间和时间尺度上获得结构响应,以达到高保真度和计算效率。将考虑三种不同的尺度:(细尺度)在极端事件附近,将使用一种新颖的无网格方法模拟响应。在该区域内,需要考虑极其精细的时空尺度来捕捉材料在高应变速率下的断裂、破碎和相变。(中尺度)对于靠近细尺度区域的结构构件,将采用新颖的有限元方法来捕获裂纹、大变形和非弹性材料行为的破坏。对于结构的其余部分,将使用鲁棒和精确的结构(梁,板)有限元来获得整体响应。这三种类型的区域将通过新颖的方法进行接口,这些方法将能够在每个区域内使用非匹配的时间和空间离散化(即不同的时间步长,有限元和无网格节点)。通过这种方法,将有可能以高精度和计算效率获得局部(构件和材料失效)和全局(结构倒塌)响应。该平台还将能够执行递归和自适应计算,以提高计算效率。所提出的计算平台将能够考虑结构在极端事件中的全局和局部响应。这种方法对于确定直接暴露在极端事件中的构件的破坏和整个结构的渐进破坏机制是必要的。目前还没有这样的模拟工具存在。因此,拟议的平台将帮助法医工程师进行脆弱性评估研究,以及开发抗爆炸/抗冲击设计和改造技术。研究成果将对相关领域产生广泛影响。在整个项目中产生的元素公式、分析方法和算法将适用于地震工程、材料响应建模、断裂力学和结构动力学等领域。通过外联活动,该项目将在学术界、国家研究实验室的研究人员和法医工程师之间产生可行的协同作用。研究生将通过研究、实习和参与外展活动来接受培训。

项目成果

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Ertugrul Taciroglu其他文献

Experimental study on bond performance of staggered lap rebars in ultra-high performance concrete (UHPC)
  • DOI:
    10.1016/j.conbuildmat.2024.136756
  • 发表时间:
    2024-06-28
  • 期刊:
  • 影响因子:
  • 作者:
    Yupeng Xie;Ergang Xiong;Zhongwen Gong;Junce Zhang;Yuan Gao;Ertugrul Taciroglu
  • 通讯作者:
    Ertugrul Taciroglu
A scaling-based generalizable integrated ML-mechanics model for lateral response of self-centering walls
基于缩放的可推广集成机器学习-力学模型用于自复位墙体的侧向响应
  • DOI:
    10.1016/j.engstruct.2025.120326
  • 发表时间:
    2025-08-01
  • 期刊:
  • 影响因子:
    6.400
  • 作者:
    Amir Ali Shahmansouri;Abouzar Jafari;Habib Akbarzadeh Bengar;Ying Zhou;Ertugrul Taciroglu
  • 通讯作者:
    Ertugrul Taciroglu
A hybrid stacked ensemble model for rapid seismic damage assessment with imbalanced training data: A case study on the 2023 Kahramanmaraş earthquakes
用于不平衡训练数据的快速地震损伤评估的混合堆叠集成模型:以 2023 年卡赫拉曼马拉什地震为例
  • DOI:
    10.1016/j.engstruct.2025.120754
  • 发表时间:
    2025-10-01
  • 期刊:
  • 影响因子:
    6.400
  • 作者:
    Sara Mostofi;Zafer Yilmaz;Hasan Basri Başağa;Fatih Yesevi Okur;Ahmet Can Altunişik;Ertugrul Taciroglu
  • 通讯作者:
    Ertugrul Taciroglu
A method to truncate elastic half-plane for soil–structure interaction analysis under moving loads and its implementation to ABAQUS
  • DOI:
    10.1016/j.soildyn.2024.109015
  • 发表时间:
    2025-01-01
  • 期刊:
  • 影响因子:
  • 作者:
    Yufeng Dong;Wenyang Zhang;Anoosh Shamsabadi;Ahmad Dehghanpoor;Li Shi;Ertugrul Taciroglu
  • 通讯作者:
    Ertugrul Taciroglu
Wildfire Fuels Mapping through Artificial Intelligence-based Methods: A Review
基于人工智能方法的野火燃料制图:综述
  • DOI:
    10.1016/j.earscirev.2025.105064
  • 发表时间:
    2025-03-01
  • 期刊:
  • 影响因子:
    10.000
  • 作者:
    Riyaaz Uddien Shaik;Mohamad Alipour;Kasra Shamsaei;Eric Rowell;Bharathan Balaji;Adam Watts;Branko Kosovic;Hamed Ebrahimian;Ertugrul Taciroglu
  • 通讯作者:
    Ertugrul Taciroglu

Ertugrul Taciroglu的其他文献

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{{ truncateString('Ertugrul Taciroglu', 18)}}的其他基金

Planning Grant: Engineering Research Center for Wildfire Hazard Resilience and Risk Engineering (WiRE)
规划资助:野火灾害抵御力和风险工程工程研究中心(WiRE)
  • 批准号:
    2124455
  • 财政年份:
    2021
  • 资助金额:
    $ 49.99万
  • 项目类别:
    Standard Grant
RAPID: Wind, Thermal, and Earthquake Monitoring of the Watts Towers
RAPID:瓦茨塔的风、热和地震监测
  • 批准号:
    1331299
  • 财政年份:
    2013
  • 资助金额:
    $ 49.99万
  • 项目类别:
    Standard Grant
Collaborative Research: Validated Multiscale Simulation Framework for Large-strain Thermo-mechanical Response of Open-Cell Aluminum Foams
合作研究:经过验证的开孔泡沫铝大应变热机械响应的多尺度模拟框架
  • 批准号:
    1031181
  • 财政年份:
    2010
  • 资助金额:
    $ 49.99万
  • 项目类别:
    Continuing Grant
SGER: Field Testing of a Non-ductile Reinforced Concrete Building in Turkey
SGER:土耳其非延性钢筋混凝土建筑的现场测试
  • 批准号:
    0755333
  • 财政年份:
    2007
  • 资助金额:
    $ 49.99万
  • 项目类别:
    Standard Grant

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Computational Methods for Analyzing Toponome Data
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