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Three-Dimensional Mixed-Mode Fracture Mechanics Methodologies for Structural Integrity Assessments of Welded Structures

Three-Dimensional Mixed-Mode Fracture Mechanics Methodologies for Structural Integrity Assessments of Welded Structures
用于焊接结构结构完整性评估的三维混合模式断裂力学方法
批准号:
RGPIN-2020-06550
负责人:
Wang, Xin
金额:
$1.97万
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:
2021
资助国家:
加拿大
项目状态:
已结题
起止时间:
2021-01-01 至 2022-12-31

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中文摘要
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英文摘要
Safe operation of high-performance welded engineering structures, such as those in nuclear pressure vessel and piping, gas/oil pipelines, aerospace and offshore industries, is of significant practical importance. During the service life span, flaws can occur in the welds and are in the form of surface, corner and embedded cracks. Therefore, to ensure safety operation and to facilitate the life extensions of these structures, it is critically important to have advanced engineering tools to quantify the behaviors of such weldment flaws and to provide reliable estimates of the safety margins against fatigue and fracture failures. In current engineering practice, fracture mechanics based methodologies have been widely used for the safety assessment of defective welded structures. Within the fracture mechanics framework, special techniques for treating the material inhomogeneity, mismatch and crack front constraint, and for accounting for the effects of welding residual stresses, have now been well developed. However, most developments thus far are for flaws under mode I (opening mode) loading. The service conditions of engineering welded structures are complex, generally involving tension, bending, torsion and shear loading. As a result, the local loading conditions around 3D crack fronts consist of all three modes, i.e., mode I (opening), mode II (in-plane shear) and mode III (out-of-plane shear). To properly carry out the safety assessment for these cases, mixed-mode effects must be considered. Presently, specific tools are not available to properly carry out assessment of 3D flaws in weldments under mixed-mode loading. The objective of the proposed research is to fill this knowledge gap by developing and validating advanced engineering tools for the reliable assessment of structural integrity of welded structures with various 3D defects under complex mixed-mode service loading conditions. The proposed work includes advances in the following four areas: 1). characterization of crack front fields in weldments under mixed-mode conditions incorporating the effects of different features including material inhomogeneity, strength mismatch and residual stress; 2). study of failure processes of cracks in weldment using micromechanics-based models under mixed mode loadings to establish corresponding fracture failure criteria; 3). experimental testing of mixed-mode fracture and fatigue specimens with different weldment features to calibrate and validate the failure criteria; and 4). failure assessment and fatigue crack growth prediction of 3D defects in welded structural components by applying the newly developed fracture failure criteria. The outcome of the proposed research will provide comprehensive understanding of mixed-mode loading on ductile fracture and fatigue propagation behavior of weldments, and be of significant engineering importance to the design, safe operation of high-performance welded engineering structures.
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Personalized Location Recommendation on Location-Based Social Networks by Efficiently Utilizing Spatio-Temporal Information
  • 批准号:
    RGPIN-2018-03916
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $6.27万
  • 财政年份:
    2022
  • 负责人:
    Wang, Xin
  • 依托单位:
Three-Dimensional Mixed-Mode Fracture Mechanics Methodologies for Structural Integrity Assessments of Welded Structures
  • 批准号:
    RGPIN-2020-06550
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.97万
  • 财政年份:
    2022
  • 负责人:
    Wang, Xin
  • 依托单位:
Personalized Location Recommendation on Location-Based Social Networks by Efficiently Utilizing Spatio-Temporal Information
  • 批准号:
    RGPIN-2018-03916
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $3.13万
  • 财政年份:
    2021
  • 负责人:
    Wang, Xin
  • 依托单位:
Personalized Location Recommendation on Location-Based Social Networks by Efficiently Utilizing Spatio-Temporal Information
  • 批准号:
    RGPIN-2018-03916
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $3.13万
  • 财政年份:
    2020
  • 负责人:
    Wang, Xin
  • 依托单位:
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Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis