Multiscale Constitutive Model Development for Deteriorating Concrete

劣化混凝土的多尺度本构模型开发

• 批准号: RGPIN-2022-04668
• 负责人: Erkmen, Emre
• 金额: $ 2.26万
• 依托单位: Concordia University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=746382
• 关键词: Multiscale; Constitutive; Model; Development; Deteriorating

Majority of civil infrastructure is constructed using concrete material. For concrete, deterioration of mechanical properties is an important problem that effects the public safety and economy. Understanding the current state of deteriorated concrete is essential to evaluate the residual capacity. On the other and, understanding the residual capacity of an existing structure is essential when it comes to making decisions about retrofitting, demolishing or continuing with operations. Aging deterioration and/or failure of concrete material under excessive loads manifests itself by crack development. In Canada, freeze-thaw cycles and Alkali-Silica Reaction (ASR) in humid environment are major reasons of crack development in concrete. On the other hand, excessive loading may also occur due to earthquakes or explosions. During the service life of a concrete structures, it is possible to conduct non-destructive testing and/or analysis based on computer modelling for condition assessments purposes. Non-destructive testing such as image processing, ultra-sonic-devices and/or elastic wave propagation can help identify the crack configurations. There is currently a significant need in the industry for residual capacity evaluation tools for aging concrete structures. The currently available tools offer limited modelling capabilities when it comes to evaluating the residual capacity of an existing deteriorated structure because safety factors and simplifications proposed by the guidelines during the design stage of new structures cannot be adopted to cover up modelling errors. It is crucial to predict the structural behaviour based on its existing condition to identify realistic failure scenarios. The proposed research aims to develop a constitutive model for concrete material considering the existing crack configuration that can be adopted in structural analysis up to failure. For this purpose, the proposed research aims to develop a computational framework that incorporates the heterogenous nature of the concrete material such that crack development at the meso-scale and uncertainties in the distributions of the aggregate and cracks can be considered. The proposed computational framework can be used for residual capacity analysis of structures, and as such it will provide engineers a thorough and practical basis on which to decide whether to resume continual operation, retrofit or demolish an existing concrete structure. By developing capabilities to assess the residual capacity of deteriorated concrete structures, the proposed research addresses a timely need that is complementary to advancements in non-destructive testing capabilities that identify existing cracks. Accurate evaluation of the residual capacity will support a well-informed decision-making process between public safety and economy, when questions are raised regarding the health and safety of existing concrete structures.

大多数民用基础设施都是使用混凝土材料构建的。对于混凝土，机械性能的恶化是影响公共安全和经济的重要问题。了解当前混凝土恶化的状态对于评估剩余能力至关重要。另一方面，了解现有结构的剩余能力对于做出改造，拆除或继续操作的决策至关重要。在过多的负载下，混凝土材料的老化恶化和/或失败通过裂纹发育表现出来。在加拿大，在潮湿环境中，冻融周期和碱性二氧化硅反应（ASR）是混凝土裂纹发育的主要原因。另一方面，由于地震或爆炸，也可能发生过多的负载。在混凝土结构的使用寿命中，有可能基于计算机建模来进行无损的测试和/或分析，以进行状态评估。非毁灭性测试，例如图像处理，超声波设备和/或弹性波传播可以帮助识别裂纹配置。目前，该行业需要对衰老混凝土结构的剩余能力评估工具的重要需求。当前可用的工具在评估现有结构恶化的剩余功能时提供了有限的建模能力，因为在新结构的设计阶段提出的安全因素和简化不能采用新结构的设计阶段来掩盖建模错误。至关重要的是根据其现有条件预测结构行为，以识别现实的故障情况。拟议的研究旨在开发一个构成模型，以考虑到在失败之前可以在结构分析中采用的现有裂纹配置的具体材料。为此，拟议的研究旨在开发一个计算框架，该计算框架结合了混凝土材料的异质性质，以便可以考虑使用骨料和裂纹的分布中的中尺度和不确定性的裂纹发育。所提出的计算框架可用于对结构的剩余能力分析，因此，它将为工程师提供一个彻底而实用的基础，以决定是否恢复持续的操作，改造或拆除现有的混凝土结构。通过开发评估混凝土结构恶化的剩余能力的能力，拟议的研究解决了及时的需求，该需求与识别现有裂缝的非破坏性测试能力的进步相辅相成。当对现有混凝土结构的健康和安全提出问题时，对剩余能力的准确评估将支持公共安全与经济之间的明智的决策过程。