Estimating Site Characteristic Parameters of the Gobi Desert Region Using Seismic Noise

Li, Ya; Chen, Shengyang; Lei, Jie

doi:https://doi.org/10.1155/2023/3188065

Shock and Vibration

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Abstract Introduction Discussion Conclusions Data Availability Conflicts of Interest Acknowledgments References Copyright Related Articles

Research Article | Open Access

Volume 2023 | Article ID 3188065 | https://doi.org/10.1155/2023/3188065

Estimating Site Characteristic Parameters of the Gobi Desert Region Using Seismic Noise

Ya Li,¹Shengyang Chen,²and Jie Lei²

Academic Editor: Denise-Penelope Kontoni

Received01 Mar 2023

Revised28 Jun 2023

Accepted03 Jul 2023

Published13 Jul 2023

Abstract

In the Gobi desert region, the predominant frequency of the horizontal-to-vertical spectral ratio (HVSR) curve of seismic noise () is typically above 3 Hz. However, most of the existing formulas for estimating cover thickness (H) based on are only applicable for values below 5 Hz. Therefore, new formulas that can accurately calculate H in this region are crucially needed. To this end, a case study was conducted where noise measurements were carried out in the Gobi region in China, as well as in the east and northeast regions of China. The HVSR curves and were calculated, and a formula that correlates with H was derived. In addition, formulas that correlate with V_s20 (average shear-wave velocities to depth 20 m) and V_s30 (average shear-wave velocities to depth 30 m) were fitted. The relationship between the site fundamental period () and () was also investigated. Finally, by using all of the noise measurements and applying the derived relationships, a method for rapidly measuring the site type was proposed. The results showed that the equation for calculating H in this paper is highly reliable, with relative errors less than 30% compared to other researchers. The correlation between and V_s30 was higher than that between and V_s20. The accuracy rate of the proposed method for fast identification of ground types was greater than 80%.

1. Introduction

It is widely accepted amongst the earthquake engineering community that ground geology has a significant effect on ground motion [1–4], and the seismic design codes determine the design response spectrum according to the ground types for seismic fortification. In recent years, two critical parameters for identifying ground types are H (thickness of sediment) and V_sz (average shear-wave velocities to depth z) [5–7]. For example, the Chinese code for seismic design of building uses H and V_s20 (average shear-wave velocities to depth 20 m) to piecewise site types [8], while Eurocode 8 [9] employs V_s30 (average shear-wave velocities to depth 30 m) as the only parameter for ground type identification. Hence, estimating H, V_s20, and V_s30 is a matter of great importance in civil engineering.

Boreholes, excavations, and other geotechnical investigations are primary methods for measuring H and V_sz [4]. However, these methods are often prohibitively expensive. Though leveraging geophysics may reduce costs, most techniques are challenging to deploy in urban areas. To overcome those limitations, several researchers have employed the microtremor horizontal-to-vertical spectral ratio (HVSR) technique to measure H and V_sz (e.g., [4, 10–17]).

The microtremor HVSR technique, also known as the Nakamura technique [18, 19], is widely used to analyze the ground dynamic characteristics due to its high cost-effectiveness in the survey and negligible interference with the environment [20, 21]. The microtremor HVSR has been utilized in various studies, such as in the Grenoble basin [22], Thessaloniki basin [23], and Trabzon-Arsin basin [24], to investigate the seismic response of sites in the frequency domain and evaluate the resonance frequency of sediments.

Due to the close relationship between the resonance frequency of the sediments and the subsurface structure and geotechnical parameters (e.g., H and V_sz), Ibs-von Seht and Wohlenberg [12] used the microtremor HVSR to calculate H for the first time and found that the main peak frequency of the microtremor HVSR curve () correlates well with H and then established a quantitative relationship between H and for Lower Rhine Embayment (Germany). Since then, Delgado et al. [25] and Parolai et al. [4] fitted new relationships to calculate H and V_sz for the region in Spain and Cologne Area, respectively. However, in those studies, the relationships between H and are valid for soils from a few tens of meters to more than 1000 m thick. Also, Lin and Wang [26] investigated that the for Gobi desert in China ranged from 3 Hz to 14.2 Hz. Moreover, more than 90% of the sediment thickness in boreholes in the Gobi desert is less than 20 m, with half being less than 5 m. Therefore, the relationships between and that have been fitted previously are inadequate for Gobi desert in China.

H, V_s20, and V_s30 have been widely used as site class delineators; nonetheless, many studies have shown that those parameters are not adequate to distinguish the ground classification [7, 27]. Thus, efforts have been made in the search for alternative site proxies to H, V_s20, and V_s30. Zhao et al. [28] proposed using T₀ (fundamental period of site) and horizontal-to-vertical (H/V) response spectral ratios over a wide period range to classify K-NET stations in Japan and developed a GMM using the period-based classification scheme. Hassani and Atkinson [29] have concluded that T₀ was superior to V_s30 in identifying site effects in central and eastern North America. Meanwhile, in California, Hassani and Atkinson [30] was able to achieve an additional 5% reduction in the standard deviation of residuals by incorporating T₀ into the model after accounting for site effects related to V_s30 and Z_1.0 (depth to V_S = 1.0 km/s).

Based on the abovementioned literature review, the following points are the main conclusions:(a)The microtremor HVSR method is widely applied in calculating H and V_se in urban areas due to its cost-effectiveness and noninvasive nature to the environment.(b)The existing microtremor HVSR method for calculating H and V_se is suitable for sites with the predominant frequency of HVSR below 5 Hz. However, it is not applicable to Gobi desert and similar areas, where the predominant frequency of HVSR ranges from 3 Hz to 14 Hz.(c)H and V_se are the most widely used site class delineators; nonetheless, those parameters are not adequate to distinguish the site effects at one site from those at another site period.

In order to derive a new formula for accurately calculating H and V_se for the Gobi desert and expand the applicable range of the formula variables, as well as to enable fast identification of ground types based on microtremor HVSR, noise measurements were carried out in China. Then, the HVSR curves were calculated and analyzed. On this basis, a study was conducted to investigate the relationship between site characteristic parameters (H, V_s20, V_s30, and T_s) and the dominant frequency of the HVSR curve. By using all of the noise measurements and applying the derived relationships, a method for fast identification of ground types based on the microtremor HVSR was proposed. Moreover, the discussion section compares the research findings of this study with the research results of other scholars.

2. Methodology

A total of 85 boreholes are collected and plotted in Figure 1(a), which are divided into three groups based on location: west sites (including 45 boreholes, located in Gobi desert), northeast sites (including 36 boreholes), and east sites (including 4 boreholes). The corresponding H and V_s30 (calculated using equation (1)) for all 85 boreholes are illustrated in Figures 1(b) and 1(c), respectively. As shown in the figures, the minimum and maximum H values for the west sites were 5 m and 100 m, respectively. Furthermore, 76% of these sites had a cover thickness of less than 20 m, with only one site exceeding 90 m. The V_s30 values for the west sites are evenly distributed between 300 m/s and 700 m/s. Conversely, the east sites exhibited H values greater than 100 m and V_s30 values less than 200 m/s. As for the northeast sites, the H values ranged from 20 m to 100 m and the V_s30 values ranged from 100 m/s to 250 m/s. Overall, the H values for the west sites are smaller than those of the northeast and east sites, while the V_s30 values are greater, indicating that the west sites are harder than the other two locations. The western sites are located around the Junggar basin, which is characterized by a substantial amount of sedimentary deposits. These deposits primarily include sandstone, conglomerate, mudstone, and coal seams. The northeast sites and west sites are located in plain areas, primarily composed of clay and silty clay, respectively. The soil in these sites is composed of three layers in general, with 0–7 m of the top layer filled.

(a)

(b)

(c)

Seismic noise measurements are conducted in close proximity to the drilling sites using the TAG-33M accelerometer (Figure 2). The TAG-33M accelerometer, which integrates a sensor and a data collector, is used for measuring microtremors in three directions. This accelerometer is ideal for field measurements and other applications. It features an antioxidation aluminum casing, waterproof connectors, and stainless steel leveling and fixing screws, which allow it to function under challenging field conditions. The compact device is simple to install and troubleshoot. In addition, the accelerometer has a sampling frequency range of 0.001 Hz–200 Hz and is capable of operating at temperatures ranging from −40°C to 60°C, making it suitable for the low-temperature conditions of the winter sites.

(a)

(b)

The installation procedure for recording ground seismic noise using the TAG-33M accelerometer is as follows [31]:(a)After selecting the appropriate installation location, we use a compass to mark the true north and east directions on the surface and then drill a D8 mm × 45 mm hole at the installation location using an impact drill (Figure 3(a))(b)We insert an M6 × 60 expansion screw into the hole (Figure 3(b))(c)We loosen the nut and place the accelerometer in the center position and then tighten the nut to secure it onto the accelerometer’s clip(d)We adjust the orientation of the accelerometer and then adjust the leveling screws until the bubble is centered (Figure 3(c))

(a)

(b)

(c)

To ensure reliable microtremor recordings, two instruments were placed on the same borehole. Each recording lasted 25 minutes, with a sampling rate of 100 Hz. The resulting signals from all three directions (up-down, north-south, and east-west) are displayed in Figure 4.

d0 is the smaller value between the thickness of the cover layer and 20 m, di is the thickness of the ith layer, and is the shear wave velocity of the ith layer.

3. Calculation and Analysis of the HVSR Curve

A Hanning window with a 28% bandwidth was chosen because it provided sufficiently good smoothing without suppressing significant features in the spectrum. Following the Site Effects Assessment using AMbient Excitations (SESAME) criteria [32], the signal relative to each window was detrended, baseline corrected, tapered, and band-pass filtered between 0.1 and 25 Hz. The fast Fourier transform of the three signal components for each analysis window was then performed, and the HVSR curves were determined using equation (3). The main peak frequency of the HVSR curve for the 85 sites is listed in Table 1. It is worth noting that although the sampling frequency was 100 samples, the spectral range shown was limited to 0.1–20 Hz, which is typically considered appropriate for studies of seismic microzoning and earthquake engineering.

As presented in Table 1, the main peak frequency of the HVSR curve exhibited a range of 0.58 Hz–12.5 Hz across the 85 sites investigated. For the west sites, described in Figure 1(a) and labeled 1 to 45, the predominant frequency range of the HVSR curve was between 1.1 Hz and 12.5 Hz. As for the northeast sites (labeled 46 to 81), the predominant frequency range of the HVSR curve was between 1.0 Hz and 4.9 Hz, while for the eastern sites (labeled 82 to 85), it was between 0.5 Hz and 1 Hz. Furthermore, based on the Chinese seismic code, the 85 sites were categorized into three groups (II, III, and IV) and their corresponding HVSR curves are presented in Figure 5.in which H_EW(i) and H_NS(i) indicate the NS and EW direction spectrum curves relative to the ith window, V(i) indicates the up-down direction spectrum curves relative to the ith window, and n indicates the window number.

(a)

(b)

(c)

As depicted in Figure 5, the shape of the HVSR curve varies considerably based on the ground type. For class IV sites, the HVSR curves exhibit a single peak and the predominant frequency is less than 1 Hz. In contrast, for harder sites such as class II and III, the HVSR curves have multiple peaks and the predominant frequency is greater than 1 Hz. Furthermore, the peak of the HVSR curve is more pronounced at higher frequencies for class II sites.

4. Uncertainties in Microtremor Data Analysis

The random nature of ambient noise (both in time and space) is a critical issue in microtremor data analysis [33, 34], particularly in densely populated areas such as the northeast and east sites due to industrialization and heavy traffic activities. To minimize such random ambient noise, microtremor data are preferably collected during early morning hours to achieve results closer to reality and ensure stability. However, in the Karamay area, since the measurement points are all located in uninhabited areas, the measurements are not limited to the morning. All measurement points are simultaneously measured using two instruments.

After the aforementioned steps, the HVSR curve is calculated and the peak is evaluated according to the SESAME project criteria. For HVSR curves with unclear peaks, we analyze them using methods described in Sections 3.2.1 and 3.2.2 of SESAME, as well as a clustering analysis method developed by our research group. The schematic diagram of the clustering analysis method is shown in Figure 6, and the specific steps are as follows:

(a)Microtremor HVSR curves are inputted, and K-means is used to cluster them into two main clusters 20 times(b)For each cluster, the cost function (J) is calculated and the clustering output with the smallest J value is selected as the final result(c)AHVSR_NS (average HVSR for NS direction) and AHVSR_EW (average HVSR for EW direction) curves for both clusters are then calculated(d)The correlation distance between AHVSR_NS and AHVSR_EW for each cluster is calculated and compared(e)The cluster HVSR curves with the smaller correlation distance are considered the SHVSR (HVSR for the site) curves

5. Site Characteristic Parameters

5.1. Relationship

Ibs-von Seht and Wohlenberg [12] demonstrated that the resonance frequency of the soil layer (f_r, which can be estimated from the peak in the HVSR curve) was closely linked to H using the following relationship:

Using the (listed in Table 1) and H obtained from the borehole data, a nonlinear regression fit of equation (4) was performed and obtained for the investigated area using the following equation:

Values and standard errors of the correlation coefficients a and b are given in Table 2. Figure 7 shows the relationship between and H, where the distribution range of is 0.58 Hz∼12.5 Hz, and the adjusted R-square value is 0.94 which is significantly greater than critical values of correlation coefficient r(85−2)_0.001 = 0.36259. These results indicate a strong correlation between and H in the frequency range of 0.58 Hz–12.5 Hz.

5.2. and Relationships

V_s20 (calculated using equation (2)) and V_s30 (calculated using equation (1)) are two important parameters to classify the site; therefore, a fast method to estimate those parameters is a matter of great importance. Delgado et al. [25] showed that the average shear wave velocity of the soft sedimentary column, V_s, can be related to H through a relationship of the following form:

The relationship between H and was fitted by equation (4). By substituting equation (4) into equations (6) and (7), another equation was obtained. Thus, a nonlinear regression fit of equation (7) was performed using , V_s20, and V_s30, resulting in the following equation for the investigated area:

Values and standard errors of the correlation coefficients a and b for the two equations are also listed in Table 2. Figure 8 shows the vs. V_s20 and vs. V_s30. The adjusted R² values are 0.70 and 0.87, respectively, both of which are greater than r(85−2)_0.001 = 0.36259. This suggests a strong correlation between and V_s20 or V_s30 in the frequency range of 0.58 Hz–12.5 Hz. Moreover, the higher R² value for the regression with V_s30 indicates a stronger correlation between and V_s30 than between and V_s20. In addition, while there is a strong correlation among V_s20, V_s30, and within the range of 0.58 Hz–12.5 Hz, the correlation among V_s20, V_s30, and is not significant within the range of 0.58 Hz–12.5 Hz.

(a)

(b)

5.3. Relationship

Several kinds of research studies have shown that the Nakamura method was fully established as an assessment method for the site fundamental period (T_s, calculate using equation (10), in which V_sb is the equivalent shear wave velocity, calculated using equation (11)); for accuracy-eliminated T_s using the HVSR method, the relationship between was studied.in which H is the depth of the bedrock, d_i is the thickness of the ith layer, and is the shear wave velocity of the ith layer.

Using the () and , a nonlinear regression fit of equation (4) was performed and obtained for the investigated areas using the following equation:

Figure 9 shows the regression curve of the and , and the adjusted R² value is 0.91 which is greater than r(85–2)_0.001 = 0.36259. It indicated that there is a strong correlation between and in the range of 0.08 s–1.72 s. Besides, it can be seen from Figure 6 that when is less than 0.13 s, the points are evenly distributed near the red () line. However, when is greater than 0.13 s, the points are not distributed near the red line and trend towards the -axis.

6. Identification of Ground Types

In China, the classification of ground types is based on Table 3 which uses two parameters, H and V_s20, to determine the site type. For example, a site is classified as type II when H and V_s20 range from 3 m to 50 m and 150 m/s to 250 m/s, respectively. Using Table 3 and equations (5) (the red line in the figure) and (8) (the black line in the figure), Figure 10 is plotted. The boundaries of H (calculated using equation (5)) described in Table 3 are represented by L1, L3, and L5, while the boundaries of V_s20 (calculated using equation (8)) are represented by L2, L4, and L6.

It can be seen from Figure 10 that when , H (calculate using equation (5)) is greater than 80 m; meanwhile, V_s (calculate using equation (8)) is less than 126 m/s; therefore, the ground type is IV (identify using Table 3). By the same token, the corresponding for the I, II, and III-type sites is in the range >15.35 Hz, 1.77 Hz–15.35 Hz, and 1.13 Hz–1.77 Hz, respectively. The method for fast identification of ground types based on microtremor HVSR is listed in equation (13).

7. Discussion

Table 4 presents two different relationships between H and f_H/V derived by Ibs-Von and Craig, respectively. Figure 11 shows a comparison between equation (5) and those relationships. It should be noted that equation (5) was derived from data for , while the equations derived by Ibs-Von and Craig were based on data for and .

(a)

(b)

In the frequency range of 0.14–4.5 Hz, the relative error between equation (5) and Ibs-Von’s equation is below 40% and the relative error is below 20% in the frequency range of 0.58–2.5 Hz. However, at higher frequencies (1–4.5 Hz), equation (5) gives deeper depths of the bedrock than those calculated by Ibs-Von’s equation and the relative error increases as the frequency increases. In the frequency range of 2.06–12.39 Hz, the relative error is below 30% between equation (5) and Craig’s equation. Figure 12 provides a detailed comparison between equation (5) and Ibs-Von’s equation. It can be observed that, for Ibs-Von’s equation, there is only one site that , which could lead to inaccurate calculation of the formula at higher frequencies. All these comparisons indicated that equation (5) is valid for the calculated H.

A total of 178 boreholes were gathered from the literature sources Qi [35] and Chen [36], which included the borehole database and f_H/V data. These boreholes were classified based on Table 3 into 102 II-type sites, 70 III-type sites, and 6 IV-type sites. The statistics of H and V_s20 for these boreholes are shown in Figures 13(a) and 13(b). The H values of the 178 boreholes are evenly distributed from 5 m to 120 m, with a minimum of 7.5 m and a maximum of less than 120 m. The V_s20 values range from 100 m/s to 400 m/s.

(a)

(b)

Two methods were used to classify the 178 sites based on their ground types: the method described in Section 6 and the TSSM [37]. The results are shown in Figure 14, where the black and red lines represent the demarcation lines based on the two methods, respectively. The accuracy rate (R, calculated using equation (14)) for equation (13) in identifying the site types (II, III, and IV) was 81%, 98%, and 83%, respectively, all of which were above 80%. In contrast, the accuracy rate (R) of the TSSM method in identifying site types was 100%, 0%, and 47%, respectively, unable to accurately identify III-type sites.in which N is the right site number and T is the total site number.

8. Conclusions

This work aims to investigate the relationships of , , and for the Gobi region and expand the applicable range of the relationships variables. Applying the derived relationships, a method to quickly determine the site type was proposed. The following points are the main conclusions drawn from this work:(a)The shape of HVSR varies significantly depending on the ground type. For class IV sites, the HVSR curves exhibit a single peak, with the predominant frequency being less than 1 Hz. However, for harder sites such as class II and III sites, the HVSR curves show multiple peaks and the predominant frequency is greater than 1 Hz.(b)In the frequency range of 0.58 Hz–12.5 Hz, there is a strong correlation between and H. The equation to calculate H in this paper exhibited high reliability with relative errors less than 30% compared to other researchers.(c)In the frequency range of 0.58 Hz–12.5 Hz, there is a strong correlation between and V_s20 as well as V_s30, with a stronger correlation observed between and V_s30 than between and V_s20.(d)There is a strong correlation between and within the range of 0.08 s–1.72 s.(e)The method for fast identification of ground types based on microtremor HVSR achieved an accuracy rate exceeding 80% for 178 sites. Specifically, the accuracy rates for the three types of sites (II, III, and IV) were 81%, 98%, and 83%, respectively.

Symbols

:	Predominant frequency of the HVSR curve
H:	Cover thickness
:	Average shear-wave velocities to depth 20 m
:	Average shear-wave velocities to depth 30 m
:	Fundamental period of the site
:	Fundamental period of the HVSR curve
:	Average shear-wave velocities to depth z
:	Predominant frequency of site
:	Average shear wave velocity of the soft sedimentary
:	The thickness of the ith layer
:	The shear wave velocity of the ith layer.

Data Availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

Acknowledgments

This work was supported by the Theoretical Study on Flexural Behavior of Precast Concrete Sandwich Panel (grant no. 52208181).

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Copyright © 2023 Ya Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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