With the recent development of 3D printing technology, concrete materials are sometimes used in 3D printing. Concrete structures based on 3D printing have been characterized to have the form of multiple layer build-up. Unlike general concrete structures, therefore, the 3D-printed concrete can be regarded as an orthotropic material. The material property of the 3D-printed concrete’s interface between layers is expected to be far different from that of general concrete bodies since there are no aggregate interlocks and weak chemical bonding. Such a difference finally affects the structural performance of concrete structures even though the interfaces are formed before initial setting of the concrete. The current study mainly reviewed the changes in fracture energy (toughness) with respect to various environmental conditions of such interface. Changes in fracture energies of interfaces between concrete layers were measured using low-speed Crack Mouth Opening Displacement (CMOD) closed loop concrete fracture test. The experimental results indicated reduction in fracture energy as well as tensile strengths. To improve the tensile strength of interfaces, the use of bridging materials is suggested. Since it was assumed that reduction in fracture energy could be a cause of shear strength, to evaluate the reduced structural performance of concrete structure constructed with multiple interfaces by 3D printing technology, the shear strength of RC beam by 3D printing technology was predicted and compared with that of plain RC beam. Based on the fracture energy measured in this study, Modified Compression Field Theory (MCFT) theory-applied Vector 2 program was employed to predict the degree of reduction in shear strength without considering stirrups. Reduction factors were presented based on the obtained results to predict the reduction in shear strength due to interfaces before initial setting of the concrete.

Recently, there was a collision accident involving vehicle–concrete median barrier in South Korea, and unfortunately, passengers on the opposite direction road were killed by the flying broken pieces of concrete generated by the collision. Primarily after this accident, we felt the need for developing an improved concrete median barrier up to level of SB6 impact severity in order to minimize the amount of broken pieces of concrete and any possibility of traffic accident casualty under the impact loading of truck. Accordingly, in this study, several designs of concrete median barriers have been examined, and a preliminary study has been conducted for developing and verifying appropriate collision model. First, type of vehicle was selected based on impact analysis on rigid wall. Then, the effects of element size and other key parameters on the capacity of the concrete median barrier under impact were studied. It was found that the key parameters for controlling behaviors of the median barrier under impact loading were contact option, threshold value, and mesh and boundary conditions. Furthermore, as a parametric study, effect of geometry and amount of wire-mesh or steel rebar in concrete median barrier on impact resistances of median barrier for reducing the collision debris were investigated. The amount of volume loss after the collision of truck was compared for various reinforcement ratios.

In this study, risk analysis was conducted to evaluate the vulnerability of bridge columns to vehicle impact. A three‐step risk analysis procedure was used. The first step involved a Preliminary Risk Analysis (PRA), which was an initial screening step to determine whether a bridge column requires second‐step analysis or not. The second step was a Simplified Risk Analysis (SRA), which involved determining the level of risk (low, moderate, or high) for a bridge column. The third step comprised a Detailed Risk Analysis (DRA). Computer simulation was based on the results of SRA. In this study, the risk level of 8,267 bridges in South Korea was evaluated, and a resulting total of 58 bridge columns in the Risk Level High (RLH) category were selected as a result of SRA. These bridge columns were classified into five types based on their slenderness ratio. Using these five types of bridge column, DRA was conducted. As expected, larger deformations of the bridge column were observed if the vehicle velocity and slenderness ratio were both increased. Using the bridge columns in the categories of response high and response moderate under vehicle impact, fragility curves were proposed using statistical data of material strength and the few results of the numerical analysis.

In South Korea, the number of vehicles is gradually increasing. The number of heavy vehicles in 2010 increased up to 19% in less than five years. Therefore, the chances of heavy vehicle-concrete median barrier (CMB) collision also became higher than in the past; therefore, a need to study a stricter design level for improving the current CMB (CMB-15) under harsher environments arose. Accordingly, in the present study, a new concrete median barrier was designed under a stricter impact severity, SB6(420 kJ), compared to the current design impact severity, SB5-B (270 kJ). In particular, shock absorbing devices to absorb impact energy were applied to the CMB. An empty space allows the dowel bars to deform and absorb collision energy. Therefore, deformable CMB was designed and tested. The key parameters selected in our study were dowel bar and wire-mesh. A series of numerical analyses were conducted to evaluate the proposed new deformable CMB designs with shock absorbers. Finally, the optimal design, CMB-17S, was proposed after several evaluations of the proposed designs and a full-scale field test. It was found that, although the developed model did not accurately predict the impact sequence due to certain differences between the actual truck and the truck model, the permanent deformation after collision could be well predicted. Based on the observations from a full-scale impact test, it was recommended that the top part of the CMB should be strengthened since major volume loss occurred due to local impact, which appeared to be due to punching shear failure.

In the present study, the amount of fragments generated and their travel distances due to vehicle collision with concrete median barrier (CMB) was analyzed and predicted. In this regard, machine learning was applied to the results of numerical analysis, which were developed by comparing with field test. The numerical model was developed using smoothed particle hydrodynamics (SPH). SPH is a mesh-free method that can be used to predict the amount of fragments and their travel distances from concrete structures under impact loading. In addition, deep neural network (DNN) and gradient boosting machine (GBM) were also employed as machine learning methods. In this study, the results of DNN, GBM, and numerical analysis were then compared with the conducted field test. Such comparisons revealed that numerical analysis generated lower error than both DNN and GBM. When prediction results of both the amount of fragments and their travel distances were considered, the result of DNN showed smaller errors than that of GBM. Therefore, in studies where machine learning is used to predict the amount of fragments and their travel distances, careful selection of an appropriate method from the various available machine learning methods such as DNN, GBM, and random forest is absolutely important.