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The use of recycled coarse aggregate in concrete structures promotes environmental sustainability; however, performance of these structures might be negatively impacted when it is used as a replacement to traditional aggregate. This paper aims to simulate recycled concrete beams strengthened with carbon fiber-reinforced polymer (CFRP), to advance the modeling and use of recycled concrete structures.

To investigate the performance of beams with recycled coarse aggregate concrete (RCAC), finite element models (FEMs) were developed to simulate 12 preloaded RCAC beams, strengthened with two CFRP strengthening schemes. Details of the modeling are provided including the material models, boundary conditions, applied loads, analysis solver, mesh analysis and computational efficiency.

Using FEM, a parametric study was carried out to assess the influence of CFRP thickness on the strengthening efficiency. The FEM provided results in good agreement with those from the experiments with differences and standard deviation not exceeding 11.1% and 3.1%, respectively. It was found that increasing the CFRP laminate thickness improved the load-carrying capacity of the strengthened beams.

The developed models simulate the preloading and loading up to failure with/without CFRP strengthening for the investigated beams. Moreover, the models were validated against the experimental results of 12 beams in terms of crack pattern as well as load, deflection and strain.

Punching can trigger catastrophic failures in flat slabs because of its sudden nature resulting from exceeding the shear capacity of slabs. Effect of using recycled aggregate, as an environmental-friendly alternative to traditional RC structures, on punching behavior of these slabs was not sufficiently investigated in the literature. Hence, this paper aims to experimentally study the effect of using recycled coarse aggregate (RCA) on the punching shear capacity (PSC) of RC flat slabs. The RCA is produced by crushing of waste of concrete standard cubes obtained from compression tests.

A total of 12 slab-column connection specimens with different slab thicknesses (140, 160 and 200 mm) and different RCA percentages (0%, 30% and 70%) were prepared and tested under a central point load, to test its effect on the behavior of flat slabs. The punching failure loads of the tested specimens were compared with those obtained according to the provisions of different international building codes.

Compared with natural aggregate concrete, mixes with 30% and 70% RCA experienced reductions in the compressive that did not exceed 4% and 21%, while reductions of 4% and 13% were observed for the tensile strength, respectively. The increase in the amount of RCA reduced the PSC by 0%–7%, 0%–4% and 4%–10% for slabs with a thickness of 140, 160 and 200 mm, respectively. For slabs with punching shear reinforcement (PSR), ACI 318 provided the closest estimation for the PSC by 9%, whereas EURO 2 overestimated the PSC by 25% and ECP 203 underestimated the PSC by 41%.

The provided conclusions are obtained from the conducted experimental work where a constant W/C ratio, aggregate type and a maximum aggregate size of 19 mm for the RCA were adopted.

Enhancement in the behavior of flat slabs with various thicknesses and amounts of RCA because of introducing PSR is experimentally evaluated. The failure loads of the tested slabs with recycled and normal coarse aggregates were compared against different code provisions.

Purpose – This chapter provides details of research that attempts to relate traffic operational conditions on uninterrupted flow facilities (e.g., freeways and expressways) with real-time crash likelihood. Unlike incident detection, the purpose of this line of work is to proactively assess crash likelihood and potentially reduce the likelihood through proactive traffic management techniques, including variable speed limit and ramp metering among others.

Methodology – The chapter distinguishes between the traditional aggregate crash frequency-based approach to safety evaluation and the approach needed for real-time crash risk estimation. Key references from the literature are summarised in terms of the reported effect of different traffic characteristics that can be derived in near real-time, including average speed, temporal variation in speed, volume and lane-occupancy, on crash occurrence.

Findings – Traffic and weather parameters are among the real-time crash-contributing factors. Among the most significant traffic parameters is speed particularly in the form of coefficient of variation of speed.

Research implications – In the traffic safety field, traditional data sources are infrastructure-based traffic detection systems. In the future, if automatic traffic detection systems could provide reliable data at the vehicle level, new variables such as headway could be introduced. Transferability of real-time crash prediction models is also of interest. Also, the potential effects of different management strategies to reduce real-time crash risk could be evaluated in a simulation environment.

Practical implications – This line of research has been at the forefront of bringing data mining and other machine-learning techniques into the traffic management arena. We expect these analysis techniques to play a more important role in real-time traffic management, not just for safety evaluation but also for congestion pricing and alternate routing.