Experimental Study on Dynamic Response Characteristics of Rural Residential Buildings Subjected to Blast-Induced Vibrations

Abstract

Numerous rural residential buildings exhibit inadequate seismic performance when subjected to blast-induced vibrations, which poses potential threats to their overall stability and structural integrity when in proximity to blasting project sites. The investigation conducted in conjunction with the Qianshi Mountain blasting operations along the Wenzhou segment of the Hangzhou–Wenzhou High-Speed Railway integrates household field surveys and empirical measurements to perform modal analysis of rural residential buildings through finite element simulation. Adhering to the principle of stratified arrangement and composite measurement point configuration, an effective and reasonable experimental observation framework was established. In this investigation, the seven-story rural residential building in adjacent villages was selected as the research object. Strong-motion seismographs were strategically positioned adjacent to frame columns on critical stories (ground, fourth, seventh, and top floors) within the observational system to acquire test data. Methodical signal processing techniques, including effective signal extraction, baseline correction, and schedule conversion, were employed to derive temporal dynamic characteristics for each story. Combined with the Fourier transform, the frequency–domain distribution patterns of different floors are subsequently obtained. Leveraging the structural dynamic theory, time–domain records were mathematically converted to establish the structure’s maximum response spectra under blast-induced loading conditions. Through the analysis of characteristic curves, including floor acceleration response spectra, dynamic amplification coefficients, and spectral ratios, the dynamic response patterns of rural residential buildings subjected to blast-induced vibrations have been elucidated. Following the normalization of peak acceleration and velocity parameters, the mechanisms underlying differential floor-specific dynamic responses were examined, and the layout principles of measurement points were subsequently formulated and summarized. These findings offer valuable insights for enhancing the seismic resilience and structural safety of rural residential buildings exposed to blast-induced vibrations, with implications for both theoretical advancements and practical engineering applications.

1. Introduction

As a critical tool in construction projects, engineering blasting technology finds extensive application across tunnel operations, mining activities, and the development of hydro-power infrastructure. Its advantages lie in rapid execution, cost efficiency, and operational adaptability. However, the adverse effects of blasting operations on adjacent structures are equally concerning, particularly through destructive phenomena such as building damage or catastrophic collapse, tunnel deformation, fractures in civil and industrial structures, and slope instability in open excavations [1]. Observations from numerous blasting projects reveal that rural residential buildings are frequently widespread in the adjacent areas. Predominantly constructed in the absence of stringent regulatory frameworks and failing to align with contemporary seismic design codes, these residential structures inherently demonstrate structural deficiencies stemming from an emphasis on architectural aesthetics at the expense of engineering robustness, compounded by construction methodologies adapted to localized contextual constraints. Consequently, the dynamic behavior of such vulnerable dwellings under blast-induced excitations necessitates meticulous scientific investigation to establish empirically grounded assessment protocols for vibration mitigation and structural reinforcement strategies [2,3,4,5,6,7].

In the existing research, considerable attention has been directed toward investigating the characteristics of blast-induced vibrations. Scholars have systematically analyzed the propagation patterns, spectral signatures, and contributing factors. Empirical evidence demonstrates that blast-induced vibrations may induce a spectrum of adverse effects on adjacent rural residential buildings, manifesting from superficial hairline cracks to catastrophic structural failures [8]. The severity of impacts arises from the synergistic interaction of multiple variables, encompassing blasting operational parameters (such as explosive charge weight, detonation sequencing) [9,10,11], geophysical transmission media (including subsurface geology and soil typology) [12], and inherent architectural attributes (such as material resilience and construction methodology) [13]. Notably, peak particle velocity (PPV) emerges as the primary metric for assessing blast-induced vibrations severity; frequency is also an important parameter because rural residential buildings respond differently to vibrations of different frequencies [14,15]. The frequency sensitivity stems from the structural particularities of rural residential buildings, which often lack modern seismic fortification measures. Further research indicates that the foundational typology, the distance of blast sources, and the structural conditions significantly affect the seismic performance of rural residential buildings [16,17]. For instance, shallow foundations common in rural residential buildings demonstrate heightened susceptibility to resonant amplification effects at specific frequency ranges, while age-related material degradation exacerbates susceptibility to cumulative damage mechanisms. Concurrently, architectural variables such as irregular mass distribution, non-engineered construction joints, and substandard reinforcement detailing, prevalent in vernacular building practices, contribute to stress concentration under dynamic loading regimes such as blast-induced vibrations.

In impact analysis, the elevation amplification effect is one of the key factors to be considered when assessing the threats. Blast-induced vibrations exhibit a height-directional amplification phenomenon within building structures, whereby taller constructions demonstrate progressively greater vibrational intensity at upper levels [18,19,20]. Through an actual engineering blasting test, three-directional peak vibration velocities in high-rise buildings show marked amplification trends at elevated positions, with intensity increasing proportionally to height [21]. Similarly, the analysis of the blast-induced vibration monitoring data of a 33-story high-rise building by Faramarzi et al. indicates that both the vertical vibration velocity and the main vibration frequency have elevation amplification effects, which are more obvious in the middle and top of the building [18]. Notably, these dynamic responses demonstrate greater magnitude in mid-story and upper-story locations, suggesting complex interaction mechanisms between incident wave-field and structural resonance frequencies at increased elevations.

The phenomenon arises from multiple contributing factors, including wave reflection patterns at structural discontinuities, height-dependent modal participation during vibration cycles, and potential superposition effects from reflected wave components. Research indicates that buildings exceeding three stories in height begin to exhibit measurable elevation amplification, with effects becoming pronounced above six stories under typical blasting excitation frequencies [15]. This vertical response gradient necessitates site-specific monitoring strategies that incorporate elevation-distributed sensor arrays, rather than relying solely on ground-level instrumentation. Furthermore, the interaction between incident vibration frequencies and structural natural frequencies becomes particularly critical at elevated levels [21], where even moderate ground motion inputs may induce disproportionate dynamic responses due to reduced damping ratios and altered mass participation factors. For the dynamic response of high-rise buildings subjected to blast-induced vibrations, it shows that the vertical vibration velocity is usually greater than that in the horizontal directions [22]. As a complex dynamic system, buildings have different responses to vibrations of different frequencies on different floors, which may cause certain frequencies of vibration to resonate or be amplified on specific floors. Research has found that the amplification effect of structures on energy components of different frequencies is selective, which means that vibration energy of certain frequencies is more easily absorbed and amplified by buildings, thereby leading to a greater structural response [23]. These findings underscore the importance of three-dimensional dynamic analysis in vulnerability assessments for multi-story buildings subjected to blast-induced vibrations.

Reviewing the current research status of blast-induced vibrations and structural dynamic response, there are relatively few studies on specific rural residential buildings, and there is also a lack of systematic experimental data. Therefore, based on the blasting project site of Qianshi Mountain in the Wenzhou section of Hangzhou–Wenzhou High-Speed Railway, and taking the typical rural residential buildings located in the adjacent area of the blasting site as the research object, this research conducts the dynamic response of the rural residential building subjected to blast-induced vibrations. This research provides an important reference basis for evaluating the impact of blast-induced vibrations on rural residential buildings and provides an important safety reference basis for related blasting projects.

2. Generalization of Experimental Site

2.1. Geological Conditions of Experimental Site

In order to meet the requirements of railway engineering construction and associated ancillary projects, comprehensive blasting and excavation works were undertaken on Qianshi Mountain within the Wenzhou section of the Hangzhou–Wenzhou Railway. The blasting zone extends 460 m from east to west, with a maximum north-to-south span of 260 m. The mountain reaches a peak elevation of 90 m, and the total excavation is approximately 3.8 million cubic meters. The aerial comparison before and after the blasting clearly presents the proximity relationship between the blasting source and the village building complex, as shown in Figure 1. The blast-induced vibrations have a particularly significant dynamic impact on the adjacent rural residential buildings. In this test, the blasting construction operation adopts the method of small steps, weak loosening, deep holes combined with shallow blasting, mainly controlled blasting, and mechanical-assisted excavation operation is combined with the construction. The unique spatial relative position characteristics of the test site provide test element guarantees for this research.

The test site is situated within a river terrace-valley system and exhibits pronounced geological stratigraphic characteristics. The surface water network, comprising seasonal streams and irrigation ditches, is densely distributed across adjacent agricultural land. The groundwater level fluctuates at depths of 0–1.0 m below ground level, demonstrating marked seasonal variations. The upper geological section is a heterogeneous sedimentary sequence, including clay, silt, silty clay, silty clay interspersed with crushed stones, silty sand, coarse gravel soil, and the quaternary residual slope accumulation of gravel-bearing silty clay layers, which were formed through complex sedimentary processes (marine, alluvial, and fluvial). The underlying bedrock is the fused tuff of the Zhuji Formation of the Late Jurassic. However, due to the thick overburden, the surface soil with low bearing capacity may amplify the ground vibration caused by blasting. In accordance with the requirements of the engineering safety oversight authority, this trial increased the quantity of blast holes, reduced the charge volume per hole, and employed delayed detonation techniques to distribute energy more rationally. These measures aim to mitigate risks associated with rock projection caused by concentrated energy release, while minimizing the impact of blast-induced vibrations on adjacent structures.

2.2. Relative Positional Relationship

During single blast trials, limitations on the quantity and resources allocated to monitoring instrumentation preclude comprehensive testing of all rural residential structures adjacent to the test site. Consequently, this study selected typical representative rural residential buildings as its primary research. Field inspections and surveys revealed that the majority of local rural residential buildings comprise reinforced concrete frame structures constructed or renovated between 1990 and 2010. A seven-story reinforced concrete frame structure, exhibiting the greatest architectural prominence and characteristic features of the region, was chosen as the principal investigation target. Situated approximately 580 m from the blasting origin, its relative spatial configuration is illustrated in Figure 2.

2.3. Structural Dimension Measurement

Following site inspections and occupant surveys, the selected rural residential observation structure was constructed circa 2005. It is arranged in an east–west orientation and adopts a seven-story and seven-bay reinforced concrete frame structure. With the exception of terraces on the eastern and western extremities of the uppermost floor, the structural layout remains consistent across all levels. The overall elevation of the building reaches 24 m (including roof structures), establishing it as the tallest rural residence within the near field. To ascertain geometric dimensions and structural particulars, methodologies encompassing occupant interviews and direct measurements were employed, utilizing standard instrumentation such as infrared laser rangefinders, floor thickness gauges, and steel tape measures. The on-site household investigation is shown in Figure 3.

In terms of specific geometric dimensions, the floor height is 2.8 m, the floor slab thickness is 0.12 m, the thickness of both the interior and exterior walls is 0.3 m, the overall width of the room is 24.5 m, the depth is 14.9 m, and the width of each room is 3.5 m. Additionally, an elevator shaft and a staircase are set on the east side, with a width of 3.5 m and a depth of 2.9 m. The size of the frame columns is 400 mm × 500 mm. The frame beam size is 300 mm × 480 mm. The ground floor partially adopts filled partition walls, and there are no partition walls on the second to seventh floors. The facade layout of the rural residence building is shown in Figure 4, and its floor plan layout is shown in Figure 5.

3. Experimental Design

For the constraints on instrumentation quantity and resource allocation, it is imperative to identify strategically critical locations for instrument deployment to ensure the relevance and reliability of measured data. Therefore, during the experimental design, by establishing a finite element model and combining it with the method of calculating modal analysis, we can fully grasp the structural modes of rural residential buildings, thereby determining the key parts of rural residential buildings, designing the observation system, and reasonably placing the instrument positions.

3.1. FEM Modeling

Considering the substantial computational demands of nonlinear analysis for reinforced concrete frame structures, optimization of modeling complexity and calculation duration is achievable while preserving a reasonably accurate representation of the inherent dynamic characteristics of the rural residential building. During the modeling process, non-structural elements such as partition walls, doors, and windows were intentionally simplified, as these components do not contribute to load-bearing capacity. Consequently, the finite element model exclusively incorporates primary structural elements, including beams, columns, and slabs, which constitute the load-bearing framework of the reinforced concrete structure.

In terms of material arrangement, the primary reinforcement configuration for the reinforced concrete frame structure employs HRB400 grade for longitudinal bars and HPB300 grade for stirrups. Cross-sectional reinforcement detailing has been streamlined for computational efficiency. Regarding steel reinforcement properties, fundamental parameters including Density, Young’s modulus, and Poisson’s ratio were established at 7850 kg/m³, 206 GPa, and 0.3, respectively. Considering the mechanical behaviors of reinforcing bars and concrete, both fall within the scope of nonlinear analysis. The characteristics of reinforcement after yield can be described by the elastic stage (with the slope being the Young’s modulus E) and the plastic stage (with a slope of 0.01E after yield) when the double-line model is adopted for reinforcing bars. A bilinear kinematic hardening model was adopted to characterize reinforcing bars’ behavior, effectively capturing post-yield strengthening effects while maintaining reasonable simulation accuracy. Its constitutive relationship is shown in Figure 6a. The concrete composition was specified as C30 grade, with Density, Young’s modulus, and Poisson’s ratio parameters set at 2500 kg/m³, 300 GPa, and 0.2, respectively. To model the cumulative damage evolution in concrete elements, an elastoplastic damage-coupled constitutive framework capable of representing irreversible plastic deformation was selected (The Concrete Damaged Plasticity model) as outlined in referenced studies [24,25]. Detailed material parameters are tabulated in

Table 1. The required CDP model parameters.

Dilation Angle	Eccentricity	Stress Ratio	Shape Coefficient	Viscosity Parameter
30°	0.1	1.16	0.66667	0.0005

. At present, many building industry research institutes have established standardized concrete constitutive relations through extensive experimental statistics and theoretical analysis. By adjusting the segmented equations (such as the ascending and descending segments) and damage parameters, it can cover concrete of different strength grades. In the elastic stage, the stress–strain relationship is defined by the elastic modulus and Poisson’s ratio of the concrete. In the inelastic stage, the stress–strain numerical correspondence directly given by the design requirements is adopted. The specific relationship is shown in Figure 6b. The contact mode between the steel bars and the concrete is set as embedded, which means the steel bars are embedded into the concrete.

In terms of grid division, there exists a critical balance between computational efficiency and accuracy: excessively coarse meshes compromise the fidelity of numerical results, while overly refined grids impose disproportionate computational burdens. For the rural residential building, mesh resolution must be judiciously calibrated to ensure adequate geometric representation while adhering to the element size guidelines recommended by Kuhlemeyer et al. [26] and Lysmer et al. [27]. This approach optimizes both analytical precision and computational feasibility.

In terms of boundary conditions and constraint settings, through the part of this field regarding the vibration of buildings caused by boundary events [28], the rural residential buildings have reached a state of geotechnical equilibrium following over three decades of consolidation. Consequently, the foundation boundary may be idealized as a fully fixed constraint to reflect the absence of further differential settlement. Regarding structural connectivity, the frame beams and columns, constructed as monolithic cast-in-place elements, were computationally unified through Boolean merging operations during finite element assembly, thereby eliminating interfacial discontinuities. While the floor slabs also comprise cast-in-place concrete, their sequential installation post-dating the primary frame necessitates distinct boundary treatment. Specifically, the interface between slabs and the pre-existing frame components was defined using tie constraint formulations to accommodate coordinated deformation behavior while preserving the methodological distinction between primary and secondary structural elements.

To facilitate a comprehensive comparison of natural vibration characteristics across different stories within the rural residential building and inform the instrumentation deployment strategy, distinct finite element models were formulated to analyze the global structural dynamic behavior. Two primary modeling paradigms were adopted. The first simplifies the structural system by focusing on primary load-bearing components, represented by a beam–column framework model (denoted as Model A). This configuration incorporates only the essential gravitational and lateral force-resisting elements. The second paradigm extends this framework by integrating floor diaphragms, thereby constituting a complete three-dimensional frame model (denoted as Model B). Both finite element representations were independently developed to evaluate the influence of slab-frame interaction on modal response parameters. The specific structural components included in each computational model are detailed in

Table 2. The structural composition of the calculation model.

Model Number	Model Name	Structural Composition
Model A	Beam–column frame model	Column + Beam
Model B	Complete three-dimensional frame model	Column + Beam + Slab

, and the finite element modeling is shown in Figure 7.

3.2. Modal Analysis of Rural Residential Buildings

Modal parameters of the rural residential building encapsulate their intrinsic dynamic attributes and serve as the foundational prerequisite for comprehending the global dynamic response characteristics of structures. The theoretical underpinnings of modal analysis are firmly rooted in structural dynamics and vibration theory, with the fundamental objective revolving around the extraction of modal parameters through the resolution of the structural eigenvalue problem [29,30]. Modern finite element analyses typically employ advanced eigenvalue solution algorithms to extract modal parameters from the system. Notable methodologies include the subspace iteration method, the Lanczos algorithm, and the Automatic Multi-Level Substructuring (AMS). Among these, the Lanczos algorithm is the most commonly adopted method.

3.2.1. Modal Analysis of Beam–Column Frame Model (Model A)

The rural residential building exhibits planar symmetry, with uniform facade configurations observed across all stories except for the seventh-floor terrace. This architectural regularity not only streamlines construction procedures but also reduces the complexity of finite element discretization, thereby enhancing computational efficiency. The natural frequency spectrum for the initial 20 modes of the beam–column framework model (Model A) is presented in

Table 3. The natural frequency spectrum for the initial 20 modes of beam–column framework model (Model A).

Mode	Frequency (Hz)	Mode	Frequency (Hz)	Mode	Frequency (Hz)
1	1.7028	8	2.2771	15	3.0022
2	1.7601	9	2.3442	16	3.0890
3	1.8004	10	2.5649	17	3.1582
4	1.8612	11	2.7861	18	3.2262
5	1.9579	12	2.9200	19	3.2606
6	1.9794	13	2.9432	20	3.3808
7	2.1325	14	2.9498

, while the corresponding deformation patterns for the first six vibration modes are illustrated in Figure 8. The modal characteristics provide critical insights into the dynamic coupling behavior of the structural system, enabling targeted instrumentation placement for experimental modal analysis.

Through analysis, the frequencies of the first six vibration modes are 1.7028 Hz, 1.7601 Hz, 1.8004 Hz, 1.8612 Hz, 1.9579 Hz, and 1.9794 Hz, respectively. The characteristics of Mode 1 are overall bending in the binning direction and longitudinal beam bending, and the reaction of the top frame beam is the most obvious. The characteristics of Mode 2 are overall torsional deformation, longitudinal beam bending, and frame column bending. Among them, the corner columns of the frame columns and the top frame beams have the most obvious reactions. The characteristics of Mode 3 are the overall bending in the depth direction, the bending of the crossbeam, and the bending of the frame column. Among them, the reactions of the frame column and frame beam at the middle part between the sixth and seventh floors are the most obvious. The characteristics of Mode 4 are overall torsional deformation, bending of frame beams, and bending of frame columns. Among them, the reactions of frame columns and frame beams at both ends of the sixth and seventh floors are the most obvious. The characteristics of Mode 5 are overall torsional deformation, frame column bending, and beam bending. Among them, the reaction of the frame beam in the middle part of the depth direction of each floor is the most obvious. The characteristics of Mode 6 are the overall bending and torsion in the depth direction, as well as the bending of frame columns and beams. Among them, the reactions of frame columns and beams at the middle and end parts of the sixth and seventh floors of rural residential buildings are the most obvious.

3.2.2. Modal Analysis of Complete Three-Dimensional Frame Model (Model B)

The natural frequency spectrum for the initial 20 modes of the complete three-dimensional frame model (Model B) is shown in

Table 4. The natural frequency spectrum for the initial 20 modes of complete three-dimensional frame model (Model B).

Mode	Frequency (Hz)	Mode	Frequency (Hz)	Mode	Frequency (Hz)
1	1.8634	8	6.5160	15	6.5669
2	2.1281	9	6.5168	16	6.5678
3	2.2054	10	6.5177	17	6.5687
4	5.5448	11	6.5185	18	6.5691
5	6.4524	12	6.5190	19	6.5698
6	6.4564	13	6.5463	20	6.6544
7	6.5156	14	6.5621

, and its vibration patterns in the first six orders are shown in Figure 9.

Through analysis, the frequencies of the first six vibration modes are 1.8634 Hz, 2.1281 Hz, 2.2054 Hz, 5.5448 Hz, 6.4524 Hz, and 6.4564 Hz, respectively. Among them, the characteristics of the first three vibration modes are consistent with the part of the above-mentioned beam–column structure Model (Model A), due to the addition of floor slab components, the vibration mode characteristics of each order have undergone certain changes. Specifically, the characteristics of the first-order vibration mode are the overall bending in the bay direction and the bending of the frame columns. The floor slabs of each floor respond uniformly, and the response becomes more obvious as the height of the floor increases. The characteristics of the second-order vibration mode are the overall bending in the depth direction and the bending of the frame columns. Its characteristics are similar to those of the first-order vibration mode, also manifested as the uniform response of the floor slabs on each floor. As the height of the floor increases, the response becomes more obvious. The third-order vibration mode feature is the overall torsional deformation of rural residential buildings. Similarly, the floor slabs of each floor twist along the center position of the floor slabs, and the corner edges of the floor slabs and the corner columns of the frame columns react most obviously. The characteristics of the fourth-order vibration mode are the overall bending in the barium direction of rural residential buildings and the bending of frame columns. With the increase of floor height, the reaction characteristics also show a trend of strengthening, weakening, and strengthening. The floor of the sixth floor hardly reacts, while the floor of the third and fourth floors reacts more obviously with the roof of the seventh floor. The characteristics of the fifth-order vibration mode are the overall bending and torsion of rural residential buildings along the depth direction, the bending of frame columns, and the deformation of floor slabs. With the increase of floor height, the reaction characteristics also show a trend of strengthening, weakening, and strengthening. The floor slab of the sixth floor hardly reacts, while the floor slab of the fourth floor reacts more obviously with the roof slab of the seventh floor. The characteristic of the sixth vibration mode is the deformation of the roof slab of the seventh floor, and the reaction is most obvious at the center of the floor slab.

3.3. Natural Vibration Characteristics of Rural Residential Buildings

A comparative analysis of the beam–column framework model (Model A) and the complete three-dimensional frame model (Model B) of rural residential buildings reveals the following structured insights:

(1)

By comparing the frequency differences of the first 20 vibration modes, it is found that the overall vibration of the observed objects in the test mainly occurs in the low-frequency band. Among them, the vibration mode frequencies of the rural residential building are all within 7 Hz, and the superposition effect of high-order vibration modes is prominent. Such vibration mode frequency values are caused by the stiffness, overall height, and structural characteristics of the rural residential building, which are also related to the overall planar layout of the structure.

(2)

By comparing the differences in modes and vibration forms of each order, it is found that the overall vibration mode characteristics of the first few orders of the structure are all manifested as binning and depth direction bending, frame column bending, frame beam bending, overall torsional deformation, floor slab deformation, especially the reactions of the top layer of the structure are relatively obvious. The main reason for the differences is also related to its structural and construction characteristics. Therefore, it is necessary to focus on the layout of instruments in the frame beams, frame columns, and the top layer of the structure.

(3)

Compared with Model A, Model B takes the floor slab into account on this basis. The floor slab forms a whole, and the vibration mode frequency of the rural residence building increases as a whole. Many floor slab responses also occur in the first 20 modes. Moreover, in the characteristics of the fourth and fifth modal vibration modes, it is observed that as the height of the floor increases, the reaction characteristics also show a trend of strengthening, weakening, and strengthening. The floor of the sixth floor hardly reacts, while the floor of the third and fourth floors reacts more obviously with the roof of the seventh floor. Therefore, it is not only necessary to install the instruments on the top floor, but also to pay special attention to the placement of instruments on the middle floors such as the third and fourth floors, as well as between adjacent floors.

3.4. Design of Experimental Observation System

In this test, the ETNA-2 digital strong-motion accelerograph produced by Kinemetrics Co., Ltd. (Pasadena, CA, USA) was employed to acquire blast-induced vibration data. This instrument is renowned for its exceptional performance and incorporates triaxial EpiSensor accelerometers, enabling simultaneous recording of ground acceleration components in the east–west (EW), north–south (NS), and vertical (UD) directions. Key attributes include its compact form factor, lightweight construction, broad dynamic range (±2 g~±10 g), robust stability, and user-friendly operation, facilitating straightforward deployment in field conditions. The technical specifications of the ETNA-2, as outlined in

Table 5. The technical specifications of the ETNA-2 digital strong-motion accelerograph.

ETNA-2 digital strong seismograph	Sensor
	Type:	Triaxial EpiSensor force balance accelerometers, orthogonally oriented
	Full scale range:	User selectable at ±1 g, ±2 g or ±4 g
	Bandwidth:	DC to 200 Hz
	Dynamic range:	155 dB+
	Digitizer
	Channels:	3 24-bit sensor channels for the internal sensors bandwidth-optimized 32-bit data path
	Sample rates and Acquisition modes:	100sps/continuous (ring buffer)

. The instrument’s seismic-grade design and compatibility with standard installation protocols render it suitable for rugged field applications, while its triaxial configuration permits comprehensive characterization of blast-induced vibrations.

To ensure the relevance and efficacy of the observation, the principle of ‘layered arrangement and composite measurement point layout’ along the vertical axis is adopted. Priority is assigned to monitoring the bottom and top layers to capture the primary global vibration modes and localized dynamic responses. Simultaneously, practical considerations such as instrument accessibility, structural compatibility, and measurement repeatability inform the selection of deployment locations, ensuring the identification of reasonable, effective, and operationally viable key positions for sensor placement. To facilitate the later data comparison and analysis, the various deployment positions of the instruments are named by floor numbers. The corresponding floors from bottom to top are respectively named the ground, fourth, seventh, and roof levels, as shown in Figure 10. Concurrently, the instrumentation grid must be systematically aligned with the orthogonal coordinate framework relative to the building’s geometric axes, wherein the X-axis corresponds to the transverse width dimension, the Y-axis to the longitudinal depth dimension, and the Z-axis to the vertical elevation axis.

4. Data Processing and Analysis

In accordance with the designed experimental observation system, the original data signals observed still need to adopt a series of methods and measures for data processing. Combined with the technical regulations for strong vibration observation, this section systematically elaborates the data processing methods:

(a)

Time–Domain Analysis: Evaluation of temporal waveforms to quantify peak particle velocities, acceleration amplitudes, and duration parameters.

(b)

Frequency–Domain Analysis: Spectral decomposition via fast Fourier transform (FFT) to identify modal frequencies and energy distribution across the vibration spectrum.

(c)

Structural Dynamic Characterization: Assessment of dynamic amplification factors (DAFs) and damping ratios to quantify the vibration transmission characteristics of the rural residential building.

These analyses facilitate the correlation of field measurements with theoretical predictions of structural response, thereby enabling critical evaluations of building performance under transient loading conditions.

4.1. Data Processing

4.1.1. Data Pre-Processing

Based on systematic characterization of the test site, the typical duration of the explosion ranges from 0.5 to 3 s. To optimize computational efficiency and mitigate superfluous background noise processing, a 10 s temporal window is systematically captured for each event, encompassing 2 s of pre-trigger baseline data and 8 s of post-trigger transient response. This protocol ensures comprehensive acquisition of the blast-induced vibration envelope while minimizing extraneous signal components. After the baseline correction is completed, it provides a certain reference basis for the later comparative analysis of the acceleration time history of each measurement point.

4.1.2. Schedule Conversion

Time–history transformation constitutes a critical process in blast-induced vibration signal analysis, enabling the conversion of acceleration time–domain records into equivalent velocity and displacement histories. The underlying mathematical principle involves the numerical integration of discrete time-series data through quadrature algorithms [31]. However, the theoretical continuum integration must be approximated via discrete summation techniques, for blast-induced vibration signals are inherently non-stationary and discretely sampled. The discretization process transforms the analytical integral into a tractable algebraic operation, where the Riemann sum approximation of the area under the acceleration–time curve yields the corresponding velocity history, and subsequent iterative integration generates the displacement profile. Despite the numerical implementation, the procedure remains mathematically close to the definite integral operation, thereby preserving the physical fidelity of the dynamic response reconstruction. The numerical integration of acceleration time histories to derive velocity and displacement profiles is typically accomplished through quadrature algorithms such as the Trapezoidal Rule or Simpson’s Rule [32,33,34]. The Trapezoidal Rule, as a fundamental method, approximates the integral as a piecewise linear function, with its discrete formulation expressed as:

$$v_k=v_{k-1}+{\displaystyle \frac{a_{k-1}+a_k}{2}}\mathrm{\Delta }t,$$

(1)

$$d_k=d_{k-1}+{\displaystyle \frac{v_{k-1}+v_k}{2}}\mathrm{\Delta }t,$$

(2)

The approach effectively computes the area under the acceleration–time curve by summing trapezoidal segments between consecutive data points. While computationally efficient, the Trapezoidal Rule introduces cumulative phase errors proportional to the square of the sampling frequency, necessitating careful consideration of time-step discretization and high-frequency noise filtering to mitigate aliasing effects. By contrast, Simpson’s Rule employs quadratic interpolation between data points, while offering improved accuracy for smooth acceleration histories at the expense of increased computational complexity. Therefore, when calculating the velocity time history, using the Trapezoidal Rule can take into account both efficiency and high-frequency noise to meet the requirements of the calculation results.

4.2. Analysis of Experimental Characteristics of Rural Residential Buildings

4.2.1. Time–Domain Analysis

After systematic pre-processing of raw observational data, including coherent signal extraction and baseline drift compensation, a corrected acceleration time–history curve is obtained. Figure 11 illustrates the X, Y, and Z directions’ acceleration time histories recorded at the ground, fourth, seventh, and top floors of the rural residential building. Key observations include:

(1)

The acceleration amplitude variation on the top floor is notably greater than on the ground floor, while the time–history curve exhibits tail oscillations. This phenomenon likely arises from the top floor’s reduced mass and stiffness, such as lightweight roofing materials or ancillary attic structures. As blast-induced seismic waves propagate upward, inertial effects intensify seismic amplification, yielding heightened acceleration responses accompanied by persistent oscillations.

(2)

The variation of the acceleration amplitude in the vertical direction (Z-direction) is significantly greater than that in the horizontal direction (X and Y directions). The reason for this phenomenon should be the stiffness of the multi-story reinforced concrete frame structure in the vertical direction is greater than that in the horizontal directions. Therefore, the natural frequency of the rural residential building in the vertical direction is relatively closer to the main shock frequency of blast-induced seismic waves, which is prone to cause the structure to generate an acceleration response higher than that in the horizontal directions.

(3)

From the ground floor to the top floor of the rural residential building, the overall change of peak acceleration in three directions is not consistent. It does not gradually increase according to the height of the building. There is a process of decreasing peak acceleration in the middle part of the floors.

Presently, the prevailing norms and standards across numerous nations predominantly adhere to the joint criterion system for blast-induced vibration safety, which integrates peak particle velocity (PPV) and dominant vibration frequency parameters [35,36,37,38]. Within this safety framework, it is stipulated that when the blast-induced dominant frequency range falls within 10 Hz < f ≤ 50 Hz, the corresponding permissible particle vibration velocity threshold ranges between 2.0 and 2.5 cm/s. To facilitate analysis of velocity variation patterns across different floors in the vertical space, this study examines the time–history velocity profiles in the X, Y, and Z directions for the rural residential building in Figure 12. It can be found:

(1)

The variation in velocity amplitude on the top floor is markedly more pronounced than on other floors. A comparative analysis of peak velocities between the ground floor and the top floor reveals that the peak velocity increases from 1.57 × 10⁻³ cm/s to 1.99 × 10⁻³ cm/s in the X-direction. In the Y-direction, it rises from 1.51 × 10⁻³ cm/s to 3.07 × 10⁻³ cm/s, while in the Z-direction, it escalates from 5.63 × 10⁻³ cm/s to 9.24 × 10⁻³ cm/s. Consequently, the peak velocity increments in the X, Y, and Z directions on the top floor exhibit a consistent upward trend, attributable to the inherent structural rigidity of rural residential buildings.

(2)

Analogous to the acceleration time–history patterns, the blast-induced vertical velocity amplitude (Z-direction) demonstrates a considerably greater magnitude than horizontal components (X and Y directions). Notably, the maximum peak velocity is recorded in the Z-direction at the uppermost story, reaching 9.24 × 10⁻³ cm/s. While this velocity remains substantially below the threshold prescribed by safety regulations, the dynamic amplification effect on the upper levels of the rural residential building is particularly pronounced, indicating significant vibration amplification at the uppermost floor despite the low absolute velocities.

4.2.2. Frequency–Domain Analysis

Although the amplitude and duration of the time–domain signal can be intuitively understood, the frequency–domain characteristics cannot be observed for the blast-induced seismic signal, which belongs to a mixture of interference waves containing various frequency components. The Fourier transform constitutes a cornerstone of digital signal processing, with the discrete Fourier transform (DFT) serving as the optimal tool for frequency–domain analysis [39]. Application of DFT to discretely sampled blast-induced seismic signal enables derivation of the Fourier amplitude spectrum for acceleration time-histories at each observation point. The Nyquist frequency resolvable from the 100 Hz sampling rate [40,41,42] corresponds to a maximum decomposable frequency component of 50 Hz. The fast Fourier transform (FFT) algorithm integrated within MATLAB is typically employed in engineering applications, which offers substantially enhanced computational efficiency relative to the discrete Fourier transform (DFT). To facilitate comparative analysis of frequency distribution patterns across vertical floors of the rural residential building, the Fourier amplitude spectra for each directional component were independently analyzed in Figure 13.

(1)

A comparative analysis of the Fourier amplitude spectra in the X, Y, and Z directions for the ground floor reveals that the dominant frequency of the rural residential building subjected to blast-induced vibrations approximates 33 Hz, and there are also many dominant frequencies.

(2)

By comparing the Fourier amplitude spectrum curves for the X, Y, and Z directions on the seventh and top floors of the rural residential building, it was observed that multiple distinct dominant frequencies emerged between 10 and 30 Hz in the Y and Z directions. The 33 Hz dominant frequency also exhibited more pronounced amplitudes across all directions. This indicates that both the seventh floor and the top floor demonstrate comparable amplification effects on specific frequency components under blast-induced vibrations.

(3)

Through comparative analysis of the Fourier amplitude spectra in the X, Y, and Z directions for the rural residential building, it is evident that the frequency–domain components of the signals on both the seventh floor and the top floor exhibit greater complexity. The dynamic amplification effect in rural residential structures manifests not only through high-frequency oscillations during velocity time histories but also via broadened frequency bandwidths with the floor height increases. Specifically, the number of dominant frequencies within the low-frequency range progressively increases at higher stories, accompanied by the emergence of additional dominant frequencies with enhanced spectral responses. This phenomenon collectively demonstrates a multi-frequency band selective amplification effect across vertical stories.

(4)

Combining Figure 12 and Figure 13, compared with natural seismic vibrations, blasting-induced vibrations have the characteristics of higher frequency, faster attenuation of vibration intensity, shorter duration, and smaller source energy. The spectral characteristics of the measured blasting-induced signals are affected by the explosives (blast source), the site (propagation path), and the inherent characteristics of the structures.

4.3. Analysis of Dynamic Amplification Characteristics of Rural Residential Buildings

4.3.1. Characteristics of Acceleration Response Spectrum

The response spectrum analysis theory establishes a dynamic relationship between the structural dynamic characteristics and the properties of the ground motion [43,44]. Based on the motion equation of a single-degree-of-freedom system under ground motion and combined with the Duhamel integral [45] for solution, the response spectrum of the structural system can be obtained. If the relative displacement response spectrum, relative velocity response spectrum, and absolute acceleration response spectrum of the system are represented by $S_d$, $S_v$ and $S_a$ respectively, when the damping ratio $\xi$ of the system is constant, the absolute acceleration response spectrum can be expressed as:

$$S_a={\left|\ddot{U}(t)+{\ddot{U}}_g(t)\right|}_{\max }={\omega }_0{\left|{\displaystyle \underset{0}{\overset{t}{\int }}{\ddot{U}}_g(\tau )}{e}^{-\xi {\omega }_0(t-\tau )}\sin {\omega }_0(t-\tau )d\tau \right|}_{\max },$$

(3)

The acceleration response spectra for the rural residential building systems, computed with a 5% damping ratio, were derived for various floor levels using a logarithmic coordinate system to emphasize high-frequency characteristics. The horizontal axis (period, T) spans 0.02–1.28 s on a base-2 logarithmic scale, while the vertical axis (spectral acceleration, Sa) ranges from 0.0001–0.1 on a base-10 logarithmic scale. Floor-specific spectra are presented in Figure 14 with the following key observations:

(1)

The overall contour profiles of acceleration response spectrum curves for the rural residential building exhibit notable similarities across floor levels. In the X and Y directions, spectral accelerations demonstrate an initial rise followed by gradual attenuation with increasing characteristic periods, accompanied by multiple secondary peaks indicative of complex modal interactions. In the Z-direction, a comparable trend is observed, marked by a pronounced single peak followed by a gradual decline, reflecting limited higher-mode participation compared to horizontal responses. These directional disparities arise from differences in structural dynamics: horizontal responses are influenced by lateral torsional and flexural modes, while vertical behavior is governed by axial and short-period flexural modes.

(2)

Comparison of acceleration response spectra for the ground, fourth, seventh, and top floors in X, Y, and Z directions reveals that the abscissa of the primary peak consistently occurs at 0.03 s across all elevations. This corresponds to the previously established fundamental frequency of approximately 33 Hz for the site under blast-induced vibrations, with numerous spectral components aligning with dominant frequencies observed in corresponding Fourier amplitude spectra. The consistency of peak locations across floor levels underscores the site-specific vibration response characteristics governed by blast-related frequency content.

(3)

Comparison of acceleration response spectra in X and Y directions across the ground, fourth, seventh, and top floors reveals consistent amplitude rankings and shape similarities. Spectral magnitudes follow a uniform progression from largest to smallest: the top floor, the seventh floor, the fourth floor, and the ground floor. No residual peaks are observed in the Z-direction spectra. Amplitudes increase progressively with floor elevation, attributable to the structural symmetry of the rural residential building and central axis instrumentation deployment, which minimizes torsional effects and emphasizes vertical accumulation of dynamic responses.

4.3.2. Characteristics of Dynamic Amplification Coefficient

The standard response spectrum, defined as the relationship between the ratio of a structural system’s maximum dynamic response (acceleration, velocity, or displacement) to the peak ground motion and the system’s inherent properties (natural vibration period, damping ratio), encapsulates the frequency-selective amplification of blast-induced seismic wave components by the structure. This spectrum quantifies the dynamic response characteristics of the system under blast loading conditions and is synonymously termed the dynamic amplification coefficient, categorized into acceleration, velocity, and displacement variants [46]. The acceleration dynamic amplification coefficient derived from this experimental analysis is expressed mathematically in Equation (4).

$${\beta }_a={\displaystyle \frac{S_a}{{\left|a\right|}_{\max }}},$$

(4)

The acceleration dynamic amplification coefficients in the X, Y, and Z directions of each floor of the rural residential building were calculated, respectively, and the comparison curves are shown in Figure 15. The characteristics are summarized as follows:

(1)

The contour profiles of amplification coefficient curves exhibit directional consistency. The acceleration dynamic amplification coefficients demonstrate an initial rise followed by gradual attenuation as the period increases, which is a trend mirroring the acceleration response spectrum. Notably, directional anisotropy is evident: the X-direction exhibits a unimodal profile, the Y-direction a trimodal configuration, and the Z-direction a bimodal pattern. These variations reflect differential modal participation across orthogonal axes, likely stemming from structural asymmetries, non-uniform stiffness distribution, or anisotropic foundation interactions. Despite these directional discrepancies, the overall variation pattern aligns with the acceleration response spectrum, underscoring the frequency-dependent amplification mechanism governed by the structure’s dynamic properties and site-specific excitation characteristics.

(2)

The comparison of acceleration dynamic amplification coefficient curves in the X-direction across the fourth, seventh, and top floors reveals consistent spectral peaks at a characteristic period of 0.03 s, corresponding to the site’s dominant blast-induced frequency of 33 Hz. The pronounced amplification effect on the top floor is attributed to vertical variability in dynamic response, where upper floors exhibit reduced damping and increased participation in higher-order vibration modes. This trend mirrors the acceleration response spectrum findings, where spectral magnitudes diminish with decreasing floor elevation due to cumulative energy dissipation and foundation proximity effects.

(3)

The dynamic amplification effect is most pronounced on the top floor across all directions. This phenomenon reveals selective amplification characteristics at elevated levels: The directional anisotropy is evident, with distinct response patterns in orthogonal axes, alongside spectral selectivity tied to specific characteristic periods. The top floor’s dominance arises from cumulative modal participation and reduced damping, as intermediate floors may exhibit comparable or lesser amplification depending on resonance with site-specific excitation frequencies and structural natural vibration modes.

4.3.3. Characteristics of Spectral Ratio Curve

The acceleration dynamic amplification coefficients in the X, Y, and Z directions of each floor of the rural residential building were calculated, respectively, and the comparison curves are shown in Figure 16. The characteristics are summarized as follows:

To elucidate the vertical dynamic characteristics of the rural residential building under blasting-induced vibrations, the instrument positions at the ground floor level serve as reference points for the transfer function spectral ratios. Leveraging the acceleration response spectrum data, spectral ratio curves were derived for each floor relative to the ground floor reference in the X, Y, and Z directions. By definition, the spectral ratio at the ground floor ground position equates to a horizontal line at unity (1.0) on the vertical axis, as depicted in Figure 15. This reference line facilitates comparison across floor levels, highlighting variations in dynamic amplification with elevation. The spectral ratio characteristics of each floor are summarized as follows:

(1)

The spectral ratio curves for the X-direction acceleration response spectra of the rural residential building’s ground, fourth, seventh, and top floors reveal distinct peaks at a characteristic period of 0.40 s, corresponding to a frequency of 2.5 Hz. Notably, under the characteristic period of 0.12 s, peaks emerge on the top and fourth floors, whereas the seventh floor exhibits a comparatively smaller spectral ratio value.

(2)

The spectral ratio curves for the Y-direction acceleration response spectra of the rural residential building’s first, fourth, seventh, and top floors similarly exhibit prominent peaks at a characteristic period of 0.40 s, corresponding to a dominant frequency of 2.5 Hz. Additionally, the top floor’s curves display distinct peaks under the characteristic periods of 0.06 s and 0.10 s, though the fourth and seventh floors do not exhibit concurrent peaks at these periods.

(3)

The spectral ratio curves for the Z-direction acceleration response spectra of the rural residential building’s ground, fourth, seventh, and top floors exhibit notable peaks at a characteristic period of 0.07 s, corresponding to a dominant frequency of 14.3 Hz. This observation aligns with the signal spectrum analysis findings, indicating heightened sensitivity to short-period, high-frequency vertical excitations.

5. Discussion

5.1. The Difference of Dynamic Response

Since acceleration effectively captures the transient structural response to blasting actions, while velocity reflects energy input and dissipation characteristics, the peak acceleration and peak velocity values at the ground floor reference points exhibit variability across different rural residential buildings and operational conditions. Consequently, the peak acceleration and peak velocity data were normalized relative to the ground floor references, yielding the peak acceleration ratio (PPAR, Equation (5)) and peak velocity ratio (PPVR, Equation (6)). The inter-floor comparisons derived from these ratios are illustrated in Figure 17.

$$PPAR={\displaystyle \frac{PP{A}_{\mathrm{target}}}{PP{A}_{\mathrm{reference}}}},$$

(5)

$$PPVR={\displaystyle \frac{PP{V}_{\mathrm{target}}}{PP{V}_{\mathrm{reference}}}}$$

(6)

The longitudinal and transverse stiffness differentials within the structure result in non-uniform amplification of peak acceleration and velocity at the uppermost story across the X, Y, and Z axes. Notably, peak acceleration amplifications attain 12%, 56%, and 37% in the respective directions, while peak velocity amplifications reach 27%, 103%, and 64% across the same axes. This phenomenon primarily arises from the structural idiosyncrasies of rural residential construction, wherein the absence of load-bearing elements such as shear walls between framework columns engenders comparatively greater horizontal stiffness (in X-Y planes), contrasted with reduced vertical stiffness (along the Z-axis), thereby modulating vibration response patterns. Furthermore, the progression of peak acceleration across story heights does not adhere to a linear trend, instead being influenced by interactions between horizontal and vertical vibration modes. Horizontal vibration signatures exhibit heightened sensitivity to structural stiffness variations and mass distribution, whereas vertical oscillations are constrained by rigid connections between floor slabs and framework components. This latter effect induces pronounced stiffness degradation at the uppermost structural level, consequently influencing acceleration response dynamics.

In the actual investigation, it was found that the fourth floor (the middle floor) is used as a storage warehouse. Around the placement of the instruments, some goods and materials (mainly small keychains, metal hangers, and other small hardware handicrafts) may have formed “additional mass dampers” [47,48,49,50,51]. The loading situation of the goods is shown in Figure 18. These items absorbed horizontal medium-to-high-frequency vibrations, thereby dissipating corresponding energy at the fourth floor level and reducing peak acceleration values. Concurrently, cargo loading altered the local mass distribution of the structure, suppressing modal participation rates in intermediate zones. This phenomenon underscores the considerable influence of structural characteristics and internal load distribution within rural residential buildings on their vibration responses. The incorporation of measures such as ‘additional mass dampers’ offers a viable means of enhancing structural vibration performance, thereby reducing damage to rural residential buildings.

5.2. Optimize Monitoring Point Layout Criteria

At present, the selection and placement of monitoring points for most rural residential buildings frequently rely on historical practices rather than evidence-based criteria, with industry standards lacking explicit guidelines regarding critical vibration velocity monitoring zones in conventional civil structures. Through dynamic response analysis of rural residential buildings, this study reveals that peak particle velocity (PPV) exhibits marked nonlinear vertical amplification, with structural summit measurements contributing disproportionately to damage assessments of rural dwellings. The following optimization suggestions are proposed for rural construction blast-induced vibration monitoring point criteria:

(1)

Primary Monitoring Points: Set at ground-bearing wall-column junctions in typical rural structures to capture basal vibration data inputs.

(2)

Supplementary Monitoring Points: Positioned at the four corners and ridge line midpoints of rooftops in conventional rural buildings to detect PPV amplification arising from the whip effect.

(3)

Selective Monitoring Points: Targeted at weak structural zones based on building significance, natural frequencies, and foundation conditions. These may include mid-floor stiffness transition areas, fenestration openings, or other vulnerable zones. Where feasible, wireless sensor networks are recommended for multi-story synchronous monitoring.

The horizontal amplification effect at the summit of the rural residential building manifests as pronounced low-frequency enhancement, indicative of the structural selectivity toward long-period, low-frequency components within blast-induced vibration signals. Concurrently, to counter velocity amplification at elevated positions, tuned liquid dampers (TLDs) are advocated for rooftop installations, such as attic spaces, to enhance low-frequency energy dissipation [52,53,54,55,56]. Based on the findings of this experiment, it can be surmised that variations in the layout characteristics, floor heights, and structural stiffness of rural residential buildings significantly influence the dynamic amplification effect under vibration conditions at blasting sites. The influence of the building structure’s slabs also deserves further in-depth analysis. Furthermore, these factors are closely linked to the conditions of the blasting site and the surrounding environment. The influencing factors in this domain necessitate further exploration and validation.

6. Conclusions

Based on the dynamic response test of the Mountain Qianshi blasting project in the Wenzhou segment of the Hangzhou–Wenzhou High-Speed Railway, the dynamic response characteristics of rural residential buildings subjected to blast-induced vibrations were analyzed. Through a combination of modal analysis, strong-motion instrumentation, and advanced signal processing techniques, the study systematically examined vibrational characteristics and dynamic amplification patterns across different story levels, offering technical insights into structural performance. The main conclusions are as follows:

(1)

Time–domain dynamic characteristic analysis revealed that the acceleration amplitude variation at the top floor of the structure was markedly greater than that on the ground floor, with vertical acceleration and velocity amplitudes exhibiting significantly greater variability compared to the horizontal direction. This phenomenon arises because the vertical stiffness of the multi-story reinforced concrete frame structure exceeds the horizontal stiffness, contributing to the observed disparities in dynamic response.

(2)

Frequency–domain distribution analysis indicated that rural residential buildings exhibit a site-specific optimal frequency of approximately 33 Hz under blasting loads, with multiple advantageous frequencies observed. Notably, the frequency–domain components of signals recorded on the seventh and the top floor levels demonstrated greater complexity. As floor elevation increased, predominant frequencies exhibited a tendency to shift toward lower frequency bands. Blast-induced vibration energy manifested low-frequency concentration and high-frequency attenuation, resulting in a multi-band, multi-directional selective amplification effect across the structural height.

(3)

Analysis of characteristic curves, including floor acceleration response spectra, dynamic amplification coefficients, and spectral ratios, indicated that the dynamic amplification effect is most pronounced on the top floor of the structure. However, this amplification did not exhibit a direct proportionality with story elevation. Certain intermediate floors, such as the fourth story in the Y-direction, also demonstrated significant amplification under specific periodic conditions. The amplification phenomenon observed at elevated stories exhibited directional selectivity and period-dependent variability, suggesting a complex interaction between structural resonance characteristics and blast-induced excitation frequencies.

(4)

Analysis of the dynamic response revealed that the “additional mass damper” effect induced by accidental loading facilitated the dissipation of medium and high-frequency vibrational energy. This energy attenuation manifested as reduced local acceleration and velocity amplitudes, demonstrating pronounced nonlinear variation across story heights. Such behavior elucidated the regulatory mechanism through which irregular construction loading patterns in rural residences influence the redistribution of blast-induced vibration energy, particularly by leveraging inadvertent mass-damping effects to modulate structural response characteristics.

(5)

In light of the experimental findings, the analysis of the disparities in floor dynamic responses was conducted. Subsequently, optimization criteria for the layout of monitoring points were proposed, offering valuable insights for further research and engineering applications. Additionally, practical guidance was provided to enhance the seismic resilience and safety of rural residential buildings exposed to blast-induced vibrations.