Digital Mix Design for Performance Optimization of Asphalt Concrete

沥青混凝土性能优化的数字配合比设计

• 批准号: 1000172
• 负责人: Linbing Wang
• 金额: $ 28.95万
• 依托单位: Virginia Polytechnic Institute and State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-05-01 至 2015-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1000172&HistoricalAwards=false
• 关键词: Digital; Mix; Design; Performance; Optimization

The objective of this project is to use modeling and simulation methods to understand the fundamental deformation and failure mechanisms of asphalt concrete, which will lead to designing better performing mixes of balanced capability against rutting, fatigue and thermal cracking; and integration of mix design into pavement structure design. It will be achieved though making use of advanced x-ray computed tomography to no-destructively characterize the three-dimensional representations of aggregate particles (Digital Particle), high performance computing to select an optimum gradation through packing a set of digital particles based on maximizing the particle contacts and loading transfer uniformity, and the digital specimen and digital test techniques developed through a previous project supported by the National Science Foundation to evaluate asphalt concrete?s resistance against permanent deformation, fatigue and thermal cracking. These innovations have great potential impact on designing long-lasting mixes, and more accurate predictions of the behavior of these mixes under real road conditions, leading to extended pavement life and reduced life cycle cost.Asphalt paving industries directly and indirectly employ about 900,000 people. Designing and constructing long-lasting asphalt concrete pavements have significant impacts on saving limited natural and economic resources. The project will also integrate fundamental mechanism identification, simulation and visualization into both practical use and teaching of next generation engineers. In addition, the project will tie into an existing Virginia Tech Transportation Institute?s K-12 program to allow these participants have hands-on experience on performing both traditional mix design and digital mix design during their visit. A mini Research Experience for Undergraduate (REU) program will be managed during the last year of the project to expose the undergraduate students, especially those of minority and underrepresented to the advanced technology and attract them to graduate study in science and engineering.

该项目的目的是利用建模和仿真方法来了解沥青混凝土的基本变形和破坏机制，这将导致设计性能更好的混合料，平衡车辙，疲劳和热裂的能力；将混合料设计融入到路面结构设计中。它将通过使用先进的x射线计算机断层扫描来非破坏性地表征聚集粒子的三维表示（数字粒子），高性能计算来选择最佳级配，通过填充一组基于最大化粒子接触和载荷传递均匀性的数字粒子，以及之前由国家科学基金会支持的评估沥青混凝土的项目开发的数字样本和数字测试技术？抗永久变形、抗疲劳、抗热裂。这些创新对设计持久的混合料具有巨大的潜在影响，可以更准确地预测混合料在实际道路条件下的性能，从而延长路面寿命，降低生命周期成本。沥青铺装行业直接和间接雇用了约90万人。设计和施工长效沥青混凝土路面对节约有限的自然资源和经济资源具有重要意义。该项目还将把基本机制识别、仿真和可视化整合到下一代工程师的实际应用和教学中。此外，该项目将与现有的弗吉尼亚理工大学交通学院（Virginia Tech Transportation Institute）合并。我们的K-12课程，让这些参与者在参观期间有实践传统混音设计和数字混音设计的经验。在项目的最后一年，将管理一个小型的本科生研究经验（REU）计划，让本科生，特别是少数民族和代表性不足的本科生接触到先进的技术，并吸引他们进入理工科研究生学习。