*Important notice: This news reports on an unedited version of an accepted paper and is awaiting final editing. Therefore, the paper should not be regarded as conclusive or treated as established information.
Researchers have developed a wave component characterization method based on three-dimensional polarization states to decompose and separate vibration waves from the blasting demolition of tall buildings, analyzing their component characteristics to improve hazard assessment and control.
Study: Decomposition and separation of vibration waves from blasting demolition of tall buildings and their component characteristics. Image Credit: WijnandG/Shutterstock.com
Urban Demolition Vibration Need
Blasting demolition is a widely adopted technique for removing large structures in urban environments, preferred for its efficiency and economy over conventional mechanical methods. However, the process generates significant ground vibrations that can threaten nearby buildings and underground infrastructure.
Unlike vibrations from underground blasting, those from structural demolition are complex, arising from two distinct sources: explosive detonation (blast vibration) and structural impact during collapse (collapse vibration).
Traditional assessment methods, which rely primarily on peak particle velocity (PPV) and dominant frequency, struggle to fully separate these contributions or identify the specific roles of compressional (P), shear (S), and Rayleigh (R) waves.
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Wave Component Deconstruction System
This study introduces a novel wave component deconstruction system to separate and analyze the distinct vibration waves generated during tall-building blasting demolition. The technical approach combines field observations, advanced signal processing, and a newly proposed quantitative measure.
Initially, the research uses multi-source field data, including three-component vibration velocity histories recorded at monitoring points surrounding the demolition site, complemented by unmanned aerial vehicle (UAV) footage and high-speed photography to capture the entire collapse process.
The method extracts detailed information about particle motion. We derive three-dimensional particle motion trajectories by denoising and integrating the recorded velocity signals into displacement histories.
From these trajectories, a polarization ellipsoid is constructed, and its characteristic parameters, such as eigenvalues, eigenvectors, principal axis lengths, main polarization direction, and phase differences between directional components, are calculated. These parameters are fundamental to seismological polarization analysis, enabling precise identification and separation of P, S, and R waves.
The original vibration signal is divided into stages using the known initiation delays of the explosive circuits and the observed collapse of motion in the visual records. Within these stages, P, S, and R waves are distinguished by their unique particle-motion trajectories, two-dimensional projection shapes, polarization directions, and inter-component phase relations. To quantify the evolving dominance of these wave types during propagation, we propose a normalized dominance factor function.
Dominant Wave Evolution Patterns
The study's findings reveal a clear distinction in the component structures and propagation behaviors of blast and collapse vibration waves, offering crucial insights into their respective impacts on nearby structures. Blast vibration waves, generated by explosive detonation, demonstrated a dynamic evolution in dominant wave types.
Initially, the P-wave component, characterized by slender, near-linear particle motion trajectories, dominated the early stages, especially in blasting sequence 1. As demolition progressed through subsequent blasting sequences (2 to 4), the S-wave increased its contribution and often became the largest-amplitude component, while the R-wave also developed.
This P-to-S dominant transition was strongly direction-dependent: in the vertical direction, it occurred at a scaled blast distance of approximately 2.004 to 2.005, whereas in the transverse direction, it was delayed to about 2.277, indicating a larger controlling region for the compressional wave in the transverse response.
In contrast, collapse vibration waves, primarily induced by the final ground impact of the collapsing structure, were predominantly controlled by S and R waves, with the P-wave component being negligible for ground-surface monitoring points.
The R-wave typically formed large, closed elliptical trajectories, dominating the outer contour of the particle motion, while the S-wave influenced the internal trajectory patterns. The dominance of collapse waves also exhibited directional asymmetry. In the vertical direction, the near field (up to about 103.017 m) was primarily governed by the R-wave, transitioning to S-wave dominance further out.
However, in the transverse direction, the S-wave maintained dominance throughout the entire measured range (40 m to 380 m), with the R-wave acting as a secondary component. This persistent S-wave dominance in the transverse direction suggests significant, sustained shear motion affecting nearby structures, with implications for their stability.
Wave-Component Control Paradigm
This research developed and implemented a wave-component deconstruction system, providing a robust method for separating and characterizing vibration waves generated during the blasting demolition of tall buildings.
This detailed understanding of how different wave types develop and propagate from demolition events is invaluable for predicting their specific impact on nearby structures.
The findings suggest moving beyond traditional, generalized assessment criteria to a more refined, wave-component-centric control paradigm, enabling safer demolition practices and better protection of existing buildings and infrastructure in densely populated areas.
Journal Reference
Yao Y., Kang Y., et al. (2026). Decomposition and separation of vibration waves from blasting demolition of tall buildings and their component characteristics. Nature Communications. DOI: 10.1038/s41467-026-76458-8, https://www.nature.com/articles/s41467-026-76458-8