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Calibration and validation of mechanistic-empirical performance models for pavement design and remaining service life analysis

Calibration and validation of mechanistic-empirical performance models for pavement design and remaining service life analysis
用于路面设计和剩余使用寿命分析的机械经验性能模型的校准和验证
批准号:
RGPIN-2018-05010
负责人:
Shalaby, Ahmed
金额:
$2.62万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2018
资助国家:
加拿大
项目状态:
已结题
起止时间:
2018-01-01 至 2019-12-31

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中文摘要
翻译
基础设施性能的长期可靠性是实现加拿大政府通过筹集私人和公共资本为公路建设和更新提供资金的战略的关键因素。因此,提高地面交通基础设施的复原力和可持续性是加拿大经济的战略优先事项,也是对所有加拿大人的安全和保障的关键要求。在过去的十年里,力学-经验路面设计指南及其实现软件路面ME越来越多地被应用于基于基本材料特性、力学结构响应和验证的现场性能的设计和生命周期分析。这些工具已经开始取代基于经验方法的传统设计方法。*向机械-经验路面设计过渡需要大量的工作来建立材料、交通和遇险数据库,并为各种部件开发适当的性能和损坏模型。几家加拿大运输机构推迟了实施机械经验设计的计划,直到建立了适当的必要数据库和模型。包括马尼托巴省在内的一些机构正在探索新的机械设计工具,只使用可能不完全适应当地条件的默认输入值。*发现号研究的目的是加速材料数据库的本地校准,并生成高质量的性能模型,以提出可在马尼托巴省实施并也适用于其他地区的优化和验证的设计工具。这项工作将检查预测的痛苦对个别设计输入的敏感性,以评估程序的可靠性,并证明将资源分配给额外的数据收集或实验室测试是合理的。这项研究将以申请人和他的研究团队为马尼托巴省基础设施部、温尼伯市和育空地区公共工程部的最新发现为基础,这些部门为沥青混凝土和散粒材料生产当地校准的材料投入。*发现者研究将产生基础知识,并开发设计工具,以更准确地对当地材料和破损的性能进行基准测试和建模。这些工具对于支持重型建筑行业是至关重要的,这是加拿大经济的一个主要部门,在加拿大和国际上竞争激烈的基于知识的环境中运营。*这项研究将促进HQP的特殊研究生培训,并将向本科生介绍研究密集型环境。学员将做出原创性的研究贡献,并获得非常理想的分析和实用工程技能。
英文摘要
The long-term reliability of infrastructure performance is a critical element in fulfilling the Government of Canada strategy to finance highway construction and renewal through raising private and public capital. Therefore, improving the resilience and sustainability of surface transportation infrastructure is a strategic priority for the Canadian economy, and a critical requirement for the safety and security of all Canadians. Over the past decade, the mechanistic-empirical pavement design guide and its implementation software Pavement ME, are being increasingly applied for design and life cycle analysis that are based on fundamental material properties, mechanistic structural responses and verified field performance. These tools have started to replace traditional design methods that are based on an empirical approach.******The transition to mechanistic-empirical pavement design requires a substantial level of effort to establish material, traffic and distress databases, and to develop appropriate performance and damage models for the various components. Several Canadian transportation agencies have deferred plans to implement mechanistic-empirical designs until the appropriate requisite databases and models are established. Some agencies, including Manitoba, are exploring the new mechanistic design tools using only default input values that may not be fully responsive to local conditions.******The purpose of this Discovery research is to accelerate the local calibration of material databases and to generate high-quality performance models to present an optimized and validated design tool that can be implemented in Manitoba and also adapted to other regions. The work will examine the sensitivity of predicted distresses to individual design inputs in order to assess the reliability of the procedure, and to justify the allocation of resources to additional data collection or laboratory testing. The research will build on the recent findings by the applicant and his research team, for the Manitoba Department of Infrastructure, the City of Winnipeg, and the Yukon Department of Public Works, which produced locally-calibrated material inputs for asphalt concrete and unbound granular materials.******The Discovery research will generate fundamental knowledge, and develop design tools to benchmark and model the performance of local materials and distresses more accurately. These tools are critically-needed to support the heavy construction industry, a major sector of the Canadian economy that operates in a highly competitive knowledge-based environment both in Canada and internationally.******The research will facilitate exceptional graduate training of HQPs, and will introduce undergraduate students to a research-intensive environment. The trainees will make original research contributions, and acquire highly-desirable analytical and practical engineering skills.
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Calibration and validation of mechanistic-empirical performance models for pavement design and remaining service life analysis
  • 批准号:
    RGPIN-2018-05010
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $5.25万
  • 财政年份:
    2022
  • 负责人:
    Shalaby, Ahmed
  • 依托单位:
Calibration and validation of mechanistic-empirical performance models for pavement design and remaining service life analysis
  • 批准号:
    RGPIN-2018-05010
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.62万
  • 财政年份:
    2021
  • 负责人:
    Shalaby, Ahmed
  • 依托单位:
Enhanced characterization of asphalt mix performance to support balanced mix design and climate-resilient sustainable pavement structures
  • 批准号:
    556533-2020
  • 项目类别:
    Alliance Grants
  • 资助金额:
    $8.13万
  • 财政年份:
    2021
  • 负责人:
    Shalaby, Ahmed
  • 依托单位:
Enhanced characterization of asphalt mix performance to support balanced mix design and climate-resilient sustainable pavement structures
  • 批准号:
    556533-2020
  • 项目类别:
    Alliance Grants
  • 资助金额:
    $2.16万
  • 财政年份:
    2020
  • 负责人:
    Shalaby, Ahmed
  • 依托单位:
海外基金