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
基本信息
- 批准号:1000172
- 负责人:
- 金额:$ 28.95万
- 依托单位:
- 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:
- 关键词:
项目摘要
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。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Linbing Wang其他文献
Analysis of mineral composition and microstructure of gravel aggregate based on XRD and SEM
基于X射线衍射和扫描电镜的碎石骨料矿物成分和微观结构分析
- DOI:
10.1080/14680629.2017.1329869 - 发表时间:
2017-06 - 期刊:
- 影响因子:3.7
- 作者:
Jiangfeng Wu;Linbing Wang;Linjian Meng - 通讯作者:
Linjian Meng
Tensile strength and paste–aggregate bonding characteristics of self-consolidating concrete
自密实混凝土的拉伸强度及浆体-骨料粘结特性
- DOI:
- 发表时间:
2014 - 期刊:
- 影响因子:0
- 作者:
C. Druta;Linbing Wang;D. Lane - 通讯作者:
D. Lane
Mechanical properties of rock materials with related to mineralogical characteristics and grain size through experimental investigation: a comprehensive review
- DOI:
10.1007/s11709-017-0387-9 - 发表时间:
2017-06-10 - 期刊:
- 影响因子:3.100
- 作者:
Wenjuan Sun;Linbing Wang;Yaqiong Wang - 通讯作者:
Yaqiong Wang
Implementation of ensemble Artificial Neural Network and MEMS wireless sensors for In-Situ asphalt mixture dynamic modulus prediction
- DOI:
10.1016/j.conbuildmat.2023.131118 - 发表时间:
2023-05-09 - 期刊:
- 影响因子:
- 作者:
Cheng Zhang;Dylan G. Ildefonzo;Shihui Shen;Linbing Wang;Hai Huang - 通讯作者:
Hai Huang
Automated, economical, and environmentally-friendly asphalt mix design based on machine learning and multi-objective grey wolf optimization
基于机器学习和多目标灰狼优化的自动化、经济、环保沥青混合料设计
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Jian Liu;Fangyu Liu;Linbing Wang - 通讯作者:
Linbing Wang
Linbing Wang的其他文献
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{{ truncateString('Linbing Wang', 18)}}的其他基金
Collaborative Research: MEMONET: Understanding memory in neuronal networks through a brain-inspired spin-based artificial intelligence
合作研究:MEMONET:通过受大脑启发的基于自旋的人工智能了解神经元网络中的记忆
- 批准号:
2308924 - 财政年份:2022
- 资助金额:
$ 28.95万 - 项目类别:
Continuing Grant
Collaborative Research: MEMONET: Understanding memory in neuronal networks through a brain-inspired spin-based artificial intelligence
合作研究:MEMONET:通过受大脑启发的基于自旋的人工智能了解神经元网络中的记忆
- 批准号:
1939987 - 财政年份:2019
- 资助金额:
$ 28.95万 - 项目类别:
Continuing Grant
An International Workshop on the Genome of Stone-based Civil Infrastructure Materials, Beijing, China, 2016
国际石基土木基础设施材料基因组研讨会,中国北京,2016
- 批准号:
1545757 - 财政年份:2015
- 资助金额:
$ 28.95万 - 项目类别:
Standard Grant
An International Workshop on Smart and Resilient Transportation Infrastructure
智能和弹性交通基础设施国际研讨会
- 批准号:
1066168 - 财政年份:2011
- 资助金额:
$ 28.95万 - 项目类别:
Standard Grant
Support for US Participants to 2nd International Workshop on Microstructure and Micromechanics of Stone-based Infrastructure Materials; Beijing, China; Fall 2008
支持美国参与者参加第二届石基基础设施材料微观结构和微观力学国际研讨会;
- 批准号:
0829376 - 财政年份:2008
- 资助金额:
$ 28.95万 - 项目类别:
Standard Grant
Development and Implementation of Digital Specimen and Digital Tester Technique for Infrastructure Materials
基础设施材料数字化试样和数字化测试仪技术的开发与实施
- 批准号:
0619969 - 财政年份:2006
- 资助金额:
$ 28.95万 - 项目类别:
Continuing Grant
INTERNATIONAL WORKSHOP: MICRSOSTRUCTURE AND MICROMECHANICS OF STONE BASED INFRASTRUCTURE MATERIALS
国际研讨会:石基基础设施材料的微观结构和微观力学
- 批准号:
0612689 - 财政年份:2006
- 资助金额:
$ 28.95万 - 项目类别:
Standard Grant
Unified Approach for Multiscale Characterization, Modeling, and Simulation for Stone-based Infrastructure Materials
石基基础设施材料多尺度表征、建模和仿真的统一方法
- 批准号:
0625927 - 财政年份:2006
- 资助金额:
$ 28.95万 - 项目类别:
Standard Grant
Development and Implementation of Digital Specimen and Digital Tester Technique for Infrastructure Materials
基础设施材料数字化试样和数字化测试仪技术的开发与实施
- 批准号:
0438480 - 财政年份:2004
- 资助金额:
$ 28.95万 - 项目类别:
Continuing Grant
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