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Modeling of Concrete Anchors Supporting Non-Structural Components Subjected to Strong Wind and Adverse Environmental Conditions

Aragao Almeida, Salvio, Jr
http://orcid.org/0000-0002-9501-2703
http://rave.ohiolink.edu/etdc/view?acc_num=toledo1564764404011142

Abstract Details

2019, Master of Science, University of Toledo, Civil Engineering.
Hurricanes are responsible for approximately $28bn of damage every year in the United States, which is expected to increase to $151bn/year by the year 2075 due to climate change propelling more destructive hurricanes. Reconnaissance investigations estimate that 35% of this damage comes from anchorage failure of non-structural components (NSC). The design of NSC anchorage is traditionally done based on experimental results from quasi-static single-anchor tests, which neglect the dynamic effects of strong wind loading. During strong winds, the anchorage of NSCs can be damaged due to bending of the NSC-supporting beams, which has not yet been quantified. In addition, the adverse environmental conditions of elevated temperatures and concrete cracking to which these anchors are exposed prior to hurricane incidence contribute to the alarming anchor failure rates observed today. This study aims to investigate and quantify the damaging influence of the bending of the NSC-supporting beams and adverse environmental conditions on NSC anchorage to advance the current knowledge and propose new design recommendations to mitigate hurricane damage. To achieve this goal, 3D high-fidelity nonlinear finite element models ranging from single-anchors to holistic structures are created to quantify the studied influences in the local- and system-level scales. The analyses indicate that the studied adverse environmental conditions reduce the anchor load capacity by up to 70%, while the bending of the NSC-supporting beams leads to a premature anchor failure up to 62% below its expected capacity. To avoid these premature failures, a safe-design region based on the geometry of the system is proposed. In addition, this study also aims to provide simpler and faster analysis alternatives to enable the usage of the proposed modeling technique by practitioner engineers. To achieve this goal: 1) a 2D modeling approach named “equivalent cone” is proposed and verified with the 3D numerical results; and 2) an artificial neural network is created, trained, and tested with experimental data from a worldwide database to rapidly predict the load capacity of anchors damaged by concrete cracking. These simpler alternatives significantly reduce the complexities involved in the anchor analysis while preserving the accuracy of the advanced 3D numerical models
Serhan Guner (Committee Chair)
Douglas Nims (Committee Member)
Luis Mata (Committee Member)
105 p.
Civil Engineering
Anchors; finite element; artificial neural network; adverse environmental conditions; wind loading

Recommended Citations

Citations

  • Aragao Almeida, Jr, S. (2019). Modeling of Concrete Anchors Supporting Non-Structural Components Subjected to Strong Wind and Adverse Environmental Conditions [Master's thesis, University of Toledo]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1564764404011142

    APA Style (7th edition)

  • Aragao Almeida, Jr, Salvio. Modeling of Concrete Anchors Supporting Non-Structural Components Subjected to Strong Wind and Adverse Environmental Conditions. 2019. University of Toledo, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=toledo1564764404011142.

    MLA Style (8th edition)

  • Aragao Almeida, Jr, Salvio. "Modeling of Concrete Anchors Supporting Non-Structural Components Subjected to Strong Wind and Adverse Environmental Conditions." Master's thesis, University of Toledo, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1564764404011142

    Chicago Manual of Style (17th edition)

toledo1564764404011142
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This open access ETD is published by University of Toledo and OhioLINK.