The precise prediction, evaluation, and improvement of tunnel blasting effects represent the core topic of safe and efficient construction in underground engineering. With the deep integration of numerical simulation technology, intelligent algorithms, and new material technologies, the prediction of tunnel blasting effects has been significantly developing toward refinement and intelligence. Important improvements have been achieved in the prediction accuracy of key indicators, such as blasting fragment size distribution, peak vibration control, and surrounding rock damage range assessment.Precise prediction, evaluation, and improvement are of fundamental significance for optimizing blasting design, improving construction quality, ensuring project safety, and controlling costs. The study focused on core evaluation indicators, including blasthole residual hole rate, overbreak and underbreak control, profile flatness, and blasting advance. It systematically reviewed the latest research progress on prediction, evaluation, and improvement technologies for tunnel blasting effects at home and abroad. The scientific guiding value of numerical simulation methods and artificial intelligence prediction technologies in blasting parameter optimization was deeply analyzed. By comparing the performance characteristics and applicable conditions of different prediction models and combining with typical engineering cases, the internal mapping rules between blasting parameter adjustment and effect improvement were clarified. The significant effect of key parameter optimization on the improvement of blasting quality was verified. On this basis, the key technical development directions for intelligent blasting were put forward, providing path guidance for improving the blasting control level under complex geological and construction environments.
REN et al. (Wed,) studied this question.