课题基金 / 基金详情

ERI: Correlating Cyclical and Coupled Exposure to Concrete Performance and Service Life

ERI: Correlating Cyclical and Coupled Exposure to Concrete Performance and Service Life
ERI:将周期性和耦合暴露与混凝土性能和使用寿命相关联
批准号:
2347037
负责人:
Richard Deschenes
金额:
$19.99万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2024
资助国家:
美国
项目状态:
未结题
起止时间:
2024-04-01 至 2026-03-31

项目摘要

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中文摘要
翻译
该工程研究启动(ERI)奖支持旨在评估暴露在恶劣环境中的混凝土性能的研究,这些环境在温暖潮湿和寒冷季节之间循环,由于气候变化的严重程度不断增加。混凝土是最广泛使用的建筑材料,它的生产释放了8%的人为二氧化碳。限制这种环境负担需要改进预测混凝土性能和延长新旧混凝土基础设施使用寿命的方法。混凝土的微观结构是多孔的,并且由于季节或长期气候变化而随着时间的推移而演变。基于稳定环境的现有测试方法和模型可能无法检测到这种相互作用,从而导致具体的基础设施在恶劣的周期性环境中恶化。使用一种新的加速测试方法,混凝土将暴露在模拟极端环境的条件下,然后研究这些环境之间的相互作用。实验结果将为模型的发展提供数据,以预测在周期性和变化的环境中的混凝土性能。该研究将试图为工程师和材料科学家提供对混凝土微观结构演变与其在恶劣环境下各自使用寿命之间关系的基本理解。本研究将整合教育和课程开发,以增加本科生和研究生对先进材料科学、数据科学和整体模型开发的参与。本研究的目的是量化周期性、动态和耦合环境赋予的微观结构和输运性质的变化,并了解这些变化导致的相互作用机制。已经确定,当暴露在另一种环境中时,侵略性环境会改变混凝土的微观结构,导致性能下降,这是由于季节或气候变化造成的。本研究的目标是(a)模拟由周期性、动态和耦合环境引起的劣化,(b)测量模拟期间微观结构和输运特性的变化,以及(c)将微观结构变化与性能联系起来。以下基本问题将被解决:(1)当暴露于周期性或动态环境时,混凝土的哪些微观结构特征会发生改变?(2)一种环境赋予混凝土的物理化学变化与另一种环境中混凝土的耐久性之间是否存在相互作用?(3)暴露于周期性、动态或耦合环境中,混凝土的性能是如何降低的?这项研究的长期目标是通过模型开发将微观结构和传输特性与性能和使用寿命联系起来。这项研究将为PI团队提供材料科学、数据科学和整体模型开发方面的基础知识。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
This Engineering Research Initiation (ERI) award supports research that aims to assess the performance of concrete exposed to harsh environments that cycle between warm-humid and cold seasons that are increasing in severity due to climate change. Concrete is the most widely used construction material and its production releases 8% of human-caused carbon dioxide. Limiting this environmental burden requires improved methods for predicting concrete performance and extending the useful life of new and existing concrete infrastructure. The microstructure of concrete is porous and evolves over time due to seasonal or long-term climate changes. Existing test methodologies and models based on stable environments may not detect this interaction, leading to concrete infrastructure that deteriorates in harsh, cyclical environments. Using a novel accelerated test method, concrete will be exposed to conditions that simulate extreme environments and then the interaction between these environments will be studied. The experimental results will supply data for the development of models to predict concrete performance in cyclical and changing environments. The research will attempt to supply engineers and material scientists with a fundamental understanding of the relationships between the evolving microstructure of concrete and its respective service life in harsh environments. This research will integrate education and curriculum development to increase involvement of undergraduate and graduate students in advanced materials science, data science, and holistic model development.The goal of this research is to quantify changes in microstructural and transport properties imparted by cyclical, dynamic, and coupled environments and to understand the mechanism of interaction resulting from those changes. It has been established that aggressive environments alter concrete microstructure resulting in degraded performance when exposed to another environment, as occurs due to seasonal or climate change. The objectives of this research are to (a) simulate the deterioration caused by cyclical, dynamic, and coupled environments, (b) measure the resulting changes in microstructural and transport properties over the duration of the simulation, and (c) correlate microstructural changes to performance. The following fundamental questions will be addressed: (1) what microstructural characteristics of concrete are altered when exposed to cyclical or dynamic environments? (2) does an interaction occur between the physicochemical changes imparted by one environment and the durability of concrete in another environment? (3) how is the performance of concrete diminished by exposure to cyclical, dynamic, or coupled environments? The long-term aim of this research initiation is to correlate microstructural and transport properties to performance and service life through model development. This research will provide the PI’s team with foundational knowledge in materials science, data science, and holistic model development.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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