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.

本项目的目标是使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，这将导致设计出更好的混合料，平衡抗车辙，疲劳和热开裂的能力;并将混合料设计集成到路面结构设计中。它将通过利用先进的x射线计算机断层扫描技术来实现非破坏性地表征聚集体颗粒的三维表示（数字颗粒），高性能计算，通过基于最大化颗粒接触和负载转移均匀性的包装一组数字颗粒来选择最佳级配，和数字试样和数字测试技术，通过以前的项目由国家科学基金会支持，以评估沥青混凝土？抗永久变形、疲劳和热裂纹。这些创新对设计耐久混合料具有巨大的潜在影响，并能更准确地预测这些混合料在真实的道路条件下的性能，从而延长路面使用寿命并降低生命周期成本。沥青铺路行业直接和间接雇用约90万人。设计和建造耐久性沥青混凝土路面对于节省有限的自然和经济资源具有重大影响。该项目还将把基本机制识别、仿真和可视化集成到下一代工程师的实际使用和教学中。此外，该项目将配合现有的弗吉尼亚理工大学交通研究所？的K-12计划，让这些参与者在访问期间有执行传统混合设计和数字混合设计的实践经验。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，以使本科生，特别是少数民族和代表性不足的学生接触先进技术，并吸引他们进入科学和工程研究生课程。