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This paper experimentally investigates the blast-resistant characteristics of hybrid fiber-reinforced concrete (HFRC) panels by contact detonation tests. The control specimen of plain concrete, polypropylene (PP), polyvinyl alcohol (PVA) and steel fiber-reinforced concrete were prepared and tested for characterization in contrast with PP-Steel HFRC and PVA-Steel HFRC. The sequent contact detonation tests were conducted with panel damage recorded and measured. Damaged HFRC panels were further comparatively analyzed whereby the blast-resistance performance was quantitively assessed via damage coefficient and blast-resistant coefficient. For both PP-Steel and PVA-Steel HFRC, the best blast-resistant performance was achieved at around 1.5% steel + 0.5% PP-fiber hybrid. Finally, the fiber-hybrid effect index was introduced to evaluate the hybrid effect on the explosion-resistance performance of HFRC panels. It revealed that neither PP-fiber or PVA-fiber provide positive hybrid effect on blast-resistant improvement of HFRC panels.

The finite element model of projectile penetrating multi-layered reinforced concrete target was established via LS-DYNA solver. The penetration model was validated with the test data in terms of residual velocity and deflection angle.  Parametric analyses were carried out through the verified penetration model. Seven influential factors for penetration conditions, including the initial velocity of projectile, initial angle of attack of projectile, initial dip angle of projectile, the first layer thickness of concrete target, the residual layer thickness of concrete target, target distance and the layer number of concrete target, were put emphasis on further analysis. Furthermore, the influence of foregoing factors on residual velocity and deflection angle of projectile were numerically obtained and discussed. Based on genetic algorithm, the BP neural network model was trained by 263 sets of data obtained from the parametric analyses, whereby the prediction models of residual velocity and attitude angle of projectile under different penetration conditions were achieved. The error between the prediction data obtained by this model and the reserved 13 sets of test data is found to be negligible.