Concrete masonry unit walls subjected to blast pressure were analyzed with the finite element method, with the goal of developing a computationally-efficient and accurate model. Wall behavior can be grouped into three modes of failure, which correspond to three ranges of blast pressures. Computational results were compared to high-speed video images and debris velocities obtained from experimental data. A parametric analysis was conducted to determine the sensitivity of computed results to critical modeling values. It was found that the model has the ability to replicate experimental results with good agreement. However, it was also found that, without knowledge of actual material properties of the specific wall to be modeled, computational results are not reliable predictors of wall behavior.
A life cycle cost analysis (LCCA) was conducted on prestressed concrete bridges using carbon fiber reinforced polymer (CFRP) bars and strands. Traditional reinforcement materials of uncoated steel with cathodic protection and epoxy-coated steel were also considered for comparison. A series of deterministic LCCAs were first conducted to identify a range of expected cost outcomes for different bridge spans and traffic volumes. Then, a probabilistic LCCA was conducted on selected structures that included activity timing and cost random variables. It was found that although more expensive initially, the use of CFRP reinforcement has the potential to achieve significant reductions in life cycle cost, having a 95% probability to be the least expensive alternative beginning at year 23-77 after initial construction, depending on the bridge case considered. In terms of life cycle cost, the most effective use of CFRP reinforcement was found to be for an AASHTO beam bridge in a high traffic volume area.
A procedure for conducting reliability analysis of reinforced concrete beams subjected to a fire load is presented. This involves identifying relevant load combinations, specifying critical load and resistance random variables, and establishing a high-temperature performance model for beam capacity. Based on the procedure, an initial reliability analysis is conducted using currently available data. Significant load random variables are taken to be dead load, sustained live load, and fire temperature. Resistance is in terms of moment capacity, with random variables taken as steel yield strength, concrete compressive strength, placement of reinforcement, beam width, and thermal diffusivity. A semi-empirical model is used to estimate beam moment capacity as a function of fire exposure time, which is calibrated to experimental data available in the literature.The effect of various beam parameters were considered, including cover, beam width, aggregate type, compressive strength, dead to live load ratio, reinforcement ratio, support conditions, mean fire temperature, and other parameters. Using the suggested procedure, reliability was estimated from zero to four hours of fire exposure using Monte Carlo simulation. It was found that reliability decreased nonlinearly as a function of time, while the most significant parameters were concrete cover; span/depth ratio when axial restraints are present, mean fire temperature; and support conditions.
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