In the heart of China’s bustling construction and energy sectors, a groundbreaking study has emerged, promising to revolutionize the way we predict and manage vibrations from single-hole bench blasting. Led by Dr. Li Hongchao from the School of Public Safety and Emergency Management at Kunming University of Science and Technology, this research introduces a novel vibration prediction model that could significantly enhance safety and efficiency in mining and infrastructure projects.
The study, published in *Yantu gongcheng xuebao* (translated to *Rock and Soil Mechanics*), addresses a critical challenge in the energy and construction industries: accurately predicting the vibrations caused by blasting. These vibrations, if not properly managed, can impact nearby structures, infrastructure, and even public safety. The research team, which includes experts from various prestigious institutions, has developed a model that describes the randomness and non-stationarity of blast waveforms with unprecedented accuracy.
Dr. Li Hongchao explains, “Our model uses a frequency function determined through modulating white noise and a gamma function as the intensity function. This approach allows us to capture the complex and dynamic nature of blasting vibrations more effectively than previous methods.”
The team’s innovative approach involves comparing the model’s output with field-measured waveforms, using residual similarity as an evaluation index. Through a meticulous process of trial and error, they narrowed down the parameter intervals that best match real-world data. Further refinement was achieved using orthogonal design and range analysis, ensuring the model’s parameters are optimized for accuracy.
The results are impressive. The model’s output waveform curve aligns closely with the peak time, peak vibration velocity, duration, and main frequency of field-measured waveforms. This alignment proves the model’s correctness and the effectiveness of the parameter determination method. When compared to the widely used Sadovsky formula, the new model demonstrated a smaller calculation error, highlighting its superiority.
Dr. Li Shenglin from China University of Mining and Technology (Beijing) added, “This model not only enhances our predictive capabilities but also offers a more reliable tool for ensuring safety and minimizing disruptions in blasting operations. The energy sector, in particular, stands to benefit greatly from this advancement.”
The implications of this research are far-reaching. Accurate vibration prediction can lead to better planning and execution of blasting operations, reducing the risk of structural damage and improving overall project efficiency. For the energy sector, this means more precise and safer extraction processes, which can translate to cost savings and enhanced operational safety.
As the construction and energy industries continue to evolve, the need for advanced predictive models becomes increasingly critical. This research by Dr. Li Hongchao and his team represents a significant step forward, offering a robust tool that can shape future developments in the field. With the model’s proven accuracy and reliability, it is poised to become a standard in vibration prediction, benefiting not only the energy sector but also infrastructure development and public safety.
In the words of Dr. Li Hongchao, “This is just the beginning. We are excited about the potential applications of our model and look forward to seeing how it will be utilized to enhance safety and efficiency in various industries.”