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Developing Slope Asset Management Tools Considering Geotechnical and Remote Sensing Data for Transportation Infrastructure

Developing Slope Asset Management Tools Considering Geotechnical and Remote Sensing Data for Transportation Infrastructure
考虑交通基础设施的岩土工程和遥感数据开发斜坡资产管理工具
批准号:
RGPIN-2019-05668
负责人:
Hutchinson, DJean
金额:
$3.13万
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:
2020
资助国家:
加拿大
项目状态:
已结题
起止时间:
2020-01-01 至 2021-12-31

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中文摘要
翻译
交通基础设施是加拿大政府定义的重要战略资产。在拟议的计划中,我们专注于管理暴露于岩石边坡潜在危害的铁路和公路走廊-称为岩土工程资产(GA)。 随着沥青、桥梁和涵洞评估的发展,岩土工程资产管理(GAM)越来越多地被运输走廊的管理者采用。建立了测试这些资产状况的设计技术和方法,例如,路面状况指数表明,如果在关键时刻不进行维护,质量会迅速下降。将这些概念应用于遗传算法是该领域的新兴研究课题。岩土工程资产,特别是斜坡,由于材料的固有可变性,在很大程度上隐藏在斜坡内,并且缺乏对触发故障的重复事件的影响的具体和可靠的理解,导致材料强度和斜坡状况的逐步恶化,因此不太清楚。GAM需要了解现状和风险,优先考虑维护并改善生命周期。 路堑边坡破坏的可能性通常使用定性评级系统进行估计:在确定破坏概率较高的边坡时,进行详细的工作,以更详细地评估危险并制定缓解战略,其中可能包括监测,警告,保护或支持。未能检测到即将发生的故障或实施有效的解决方案的后果是意外和破坏性的滑坡事件对运输走廊的影响。这可能导致在进行紧急维修时基础设施能力的损失、基础设施以外的破坏、财务损失、受伤,在极端情况下甚至死亡。 在本项目中,我们将定义岩石边坡“类型”,代表随时间推移的行为和条件的预期变化。定义的条件曲线将指导GA斜率的评估和缓解,以减少意外故障,优化支出并指导基于风险的决策。使用我们使用激光雷达和摄影测量开发的远程监测技术,将使我们能够评估各种地质和边坡管理环境中的基础设施边坡行为,考虑到我们在加拿大岩石边坡上正在进行的工作以及从全球边坡收集的监测数据。从这个分析中,我们还将确定影响岩石边坡状况曲线的因素,包括工程缓解工程。使用基于游戏引擎物理的模拟工具,在岩石斜坡上校准,我们将评估条件曲线代表未来斜坡行为的程度。这应导致政策的改变,鼓励各机构采取前瞻性的资产管理办法。 该计划将培养1 PDF,3 PhD,5 MASc和4UG学生。
英文摘要
Transportation infrastructure is a critical strategic asset as defined by the Government of Canada. In the proposed program, we are focused on the management of railway and highway corridors exposed to potential hazards originating from rock slopes - termed Geotechnical Assets (GA). Geotechnical Asset Management (GAM) is increasingly being adopted by managers of transportation corridors, with development in the evaluation of asphalt, bridges and culverts. Design techniques and methods for testing the condition of these assets are established, for example the Pavement Condition Index demonstrates a rapid decline in quality if maintenance is not done at a critical time. Applying these concepts to GAs is the emerging research topic in this field. Geotechnical Assets, in particular slopes, are less well understood due to the inherent variability in the materials which are largely hidden from view within the slope, and the lack of specific and reliable understanding of the influence of repeated events that trigger failures, leading to progressive deterioration in the material strength and slope condition. GAM is required to understand present condition and risk, prioritize maintenance and improve the life cycle. The potential for cut slope failure is often estimated using qualitative rating systems: where higher failure probability slopes are identified, detailed work is done to assess the hazard in more detail and to devise mitigation strategies, which may include monitoring, warning, protection or support. The consequence of failing to detect impending failure or implement effective solutions, is the impact of unexpected and damaging landslide events on the transportation corridor. This may lead to loss of infrastructure capacity while emergency repairs are made, damage that extends beyond the infrastructure, financial loss, injury and in extreme cases, fatalities. In this project, we will define rock slope "types", representative of expected change in behaviour and condition over time. The condition curves defined will guide evaluation and mitigation of the GA slopes, in order to reduce unexpected failures, optimise expenditures and guide risk based decision making. Using the remote monitoring techniques we have developed using LiDAR and photogrammetry will permit us to evaluate infrastructure slope behaviour in a variety of geological and slope management settings, considering our ongoing work on rock slopes in Canada and monitoring data collected from slopes worldwide. From this analysis, we will also define the factors that influence rock slope condition curves, including engineering mitigation works. Using game engine physics based simulation tools, calibrated on rock slopes, we will assess how well the condition curves represent future slope behaviour. This should lead to a change in policy that encourages agencies to take a forward looking approach to asset management. The proposed program will train 1PDF, 3PhD, 5MASc and 4UG students.
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Developing Slope Asset Management Tools Considering Geotechnical and Remote Sensing Data for Transportation Infrastructure
  • 批准号:
    RGPIN-2019-05668
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $3.13万
  • 财政年份:
    2022
  • 负责人:
    Hutchinson, DJean
  • 依托单位:
Developing Slope Asset Management Tools Considering Geotechnical and Remote Sensing Data for Transportation Infrastructure
  • 批准号:
    RGPIN-2019-05668
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $3.13万
  • 财政年份:
    2021
  • 负责人:
    Hutchinson, DJean
  • 依托单位:
Developing Slope Asset Management Tools Considering Geotechnical and Remote Sensing Data for Transportation Infrastructure
  • 批准号:
    RGPIN-2019-05668
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $3.13万
  • 财政年份:
    2019
  • 负责人:
    Hutchinson, DJean
  • 依托单位:
Multi-purpose high speed, high accuracy LiDAR scanner for surface and underground geomechanics assessment in harsh environments
  • 批准号:
    RTI-2016-00448
  • 项目类别:
    Research Tools and Instruments
  • 资助金额:
    $10.91万
  • 财政年份:
    2015
  • 负责人:
    Hutchinson, DJean
  • 依托单位:
海外基金