Phase 2: Computationally Informed Methodologies for Capturing the Effect of Intervening Structures during Truck Impact Events
项目名称: Phase 2: Computationally Informed Methodologies for Capturing the Effect of Intervening Structures during Truck Impact Events
摘要: The continued, multi-step approach involving detailed computational modeling and the development of simplified design approaches for estimating the effect of vehicle-column will be extended. In the second phase, the yield line theoretical analysis will be extended to various angles of truck attack crashing into the barrier, as this was established in the current phase for perpendicular loading to the barrier only, supported by numerical simulations using Abaqus. This way, design graphs or tables will be produced to help Kansas Department of Transportation (KDOT) engineers account for various scenarios to select cases that are safe, relatively conservative and accurate. An expanded set of vehicle velocities, vehicle orientations, barrier types, and pier configurations will be explored with detailed computational simulations. Preliminary development of a “Riera Function” for the studied truck will conducted. Since the hypothetically impacting vehicle must first pass through a vehicle barrier, it can be assumed that the vehicle barrier is failed. Yield line theory describes the behavior of under reinforced concrete elements where energy is dissipated primarily by plastic deformation in the reinforcement. Yield line analysis of the vehicle barrier will likely also help to estimate the energy dissipated and reduce the demand on the column. The singular objective of the proposed research is the further development of a design methodology for the accidental bridge pier impact by trucks that have departed the roadway.
状态: Active
资金: 59664
资助组织: Kansas Department of Transportation
项目负责人: Ruby, Jeff
执行机构: Kansas State University Transportation Center
开始时间: 20200815
预计完成日期: 20210901
主题领域: Bridges and other structures;Design;Highways;Planning and Forecasting;Safety and Human Factors
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