Method for acquiring data for seismic liquefaction potential assessment and method for seismic liquefaction assessment

Abstract

The present application belongs to the technical field of earthquake sandy soil liquefaction evaluation, and in particular relates to an evaluation data acquisition method for earthquake liquefaction potential evaluation and an earthquake liquefaction evaluation method, wherein the evaluation data acquisition method comprises the following steps: S1, acquiring a seismic displacement waveform or a strain waveform of a target site during an earthquake; S2, detecting a wave peak and a wave trough of each period of each component seismic displacement waveform or strain waveform, calculating a difference value between the wave peak and the wave trough, and comparing the difference value with a preset statistical significance threshold; and S3, obtaining a dynamic cyclic vibration number representing the driving strength of earthquake liquefaction based on period counting. The present application solves the technical defect that the prior art cannot accurately reflect the actual dynamic loading level of soil during an earthquake, and provides a measurement method for directly acquiring key physical parameters that can truly reflect the driving strength of earthquake liquefaction from displacement waveforms or strain waveforms and a liquefaction potential evaluation method.

Description

Technical Field

[0001] This invention relates to the field of earthquake sand liquefaction assessment technology, and more specifically, to a method for acquiring earthquake liquefaction potential assessment data and an earthquake liquefaction assessment method. Background Technology

[0002] Liquefaction is a physical phenomenon in sandy soils, especially saturated cohesive soils. Under static or cyclic stress, the soil strength decreases and loses shear strength due to the cumulative increase in pore water pressure, and a phase transition occurs, changing from a solid to a liquid state. Liquefaction triggered by earthquakes can cause severe catastrophic damage and foundation failure, including damage to land, houses and buildings, pipelines, roads and highways, tunnels, river structures such as bridges, port facilities and utilities, and other civil engineering infrastructure. Liquefaction can also have catastrophic consequences for marine structures.

[0003] Although liquefaction is a direct physical consequence of pore water pressure buildup, the mechanisms of liquefaction have been understood through three fundamental approaches: (i) laboratory testing, (ii) field investigations, and (iii) theoretical and numerical simulation methods. Among these, laboratory testing, using various testing equipment such as single shear tests, torsional shear tests, shaking table tests, and triaxial tests, provides valuable insights, revealing the complex relationships and connections between liquefaction initiation, soil properties, pore water pressure buildup, deformation and strain, confining pressure, shear modulus, load intensity, and duration, thus playing a fundamental role in understanding liquefaction mechanisms. However, because liquefaction is influenced by multiple complex factors, laboratory test results may not be directly applicable to field conditions. The second approach is field investigation, which directly obtains data on the liquefaction resistance of the target area by conducting Standard Penetration Tests (SPT), Cone Penetration Tests (CPT), and / or Becker Penetration Tests. Since SPT errors can be significant, for critical projects that could cause catastrophic damage and severe engineering consequences, the more accurate (but more expensive) CPT should be used.

[0004] Based on a large number of laboratory test results, field investigations and theoretical simulations, a variety of methods and procedures for assessing liquefaction potential have been developed, which can be mainly classified into five categories: (i) stress method; (ii) strain / displacement method; (iii) shear wave velocity method; (iv) energy method; and (v) multi-index empirical method.

[0005] Among these methods and procedures, the most well-known and widely used is the assessment method based on the simplified empirical stress method. The key input physical parameters of the simplified empirical stress method are the horizontal peak ground acceleration (PGA) and the equivalent stress cycle number of the target site, used to assess liquefaction potential based on the cycle stress ratio and cycle resistance ratio. Since strain increments can be converted into changes in pore water pressure, liquefaction potential can be assessed by setting a certain strain threshold; this is the second type of method. The third type of method is based on shear wave velocity. The main advantage of shear wave velocity-based methods is that shear wave velocity directly reflects the combined changes in soil shear modulus and density, and can be measured through geophysical or laboratory testing methods; it can also be approximately correlated with the blow count of the Standard Penetration Test (SPT), which is very suitable for sites where SPT or CPT tests cannot be performed. However, this type of method is based on the assumption of small displacements, while liquefaction is known to be a medium-to-large displacement and strain phenomenon. The fourth type of energy-based methods can be further divided into two categories: methods based on seismic and stress / strain energy, and methods based on calculating energy using acceleration maps. The former can be used to calculate the accumulation of pore water pressure, while the latter simply compares the energy values ​​calculated from surface and deep acceleration maps to assess liquefaction potential. Since measurements also contain random errors, and physical liquefaction models are difficult to make completely accurate, probabilistic methods are also applied to liquefaction potential assessment; their effectiveness depends on the correctness of the physical model within a certain range of uncertainty. Recent advances in artificial intelligence (AI) and machine learning may see wider application in future liquefaction potential assessments, but this still depends on the availability and accuracy of laboratory and field data. However, given the destructive impact of liquefaction on geotechnical engineering and its dependence on many complex factors, costly measures are recommended to improve in-situ soil and foundation stability to prevent liquefaction, particularly for critical structures and / or facilities such as nuclear power plants.

[0006] The assessment of liquefaction potential has traditionally relied primarily on raw, strong vibration records. By acquiring acceleration records, the peak (horizontal) acceleration corresponding to the cyclic stress ratio can be calculated, along with shear strain, shear wave velocity, and energy values ​​derived from the acceleration waveform records. However, recent research on computational accelerometers clearly demonstrates that, despite being designed and manufactured for over a century based on a forward calculation framework, their mathematical essence is essentially an ill-conditioned inversion problem [Xu Peiliang, Chinese Invention Patent No. ZL2021 1 0045157.6, US Invention Patent No. US 12 188 959 B2; Xu PL (2024) Concept of computerized accelerometers. Sensors and Actuators A: Physical, 378, 115787, https: / / doi.org / 10.1016 / j.sna.2024.115787]. This implies that the raw output data of traditional accelerometers is more like noise, with peak acceleration potentially exhibiting errors of hundreds or even thousands of times.

[0007] Based on numerous laboratory tests and reports, the driving mechanism of earthquake-induced liquefaction is clearly attributed to cyclic loading. Although the most crucial parameter for liquefaction assessment, namely the number of dynamic loading cycles, can be accurately counted in laboratory tests, surprisingly, this parameter is completely absent in earthquake-induced liquefaction sites. Current methods for obtaining this parameter either roughly estimate it from earthquake magnitude or approximate it using Standard Penetration Test (SPT) results. For example, the number of dynamic loading cycles might be 10, 20, and 30 for earthquakes of magnitudes M7, M7.5, and M8, respectively, but even for the same magnitude, different literature sources may give different numbers of cycles. For an M7.5 earthquake, the equivalent number of dynamic loading cycles could range from a few to over 30. Strong-motion acceleration waveforms, after removing high-frequency noise, are used to calculate the number of dynamic loading cycles. However, since the spatial gradient of acceleration is related to the curvature of the dynamic stress load over time, the period of a strong-motion record is not necessarily related to the period of the dynamic stress load, not to mention the fundamental problem of numerical inaccuracies inherent in traditional accelerometers.

[0008] To date, the physical parameters obtained from laboratory tests for all liquefaction assessment methods may not be suitable for liquefaction sites. In field experiments, cone penetration tests (CPT), standard penetration tests (SPT), or shear wave velocities are not only costly but also have limited coverage and cannot obtain the key liquefaction physical parameter of dynamic loading cycles during earthquakes. In fact, there is currently no method that can provide effective information on the key physical parameter of loading cycles during earthquakes for liquefaction assessment. On the other hand, there are also significant numerical errors in horizontal peak ground acceleration and acceleration records or strong ground motion records [Xu PL, Du F, Shu Y, Zhang HP, Shi Y (2021) Regularized reconstruction of peak groundvelocity and acceleration from very high-rate GNSS precise point positioningwith applications to the 2013 Lushan Mw6.6 earthquake. Journal of Geodesy, 95, 17, https: / / doi.org / 10.1007 / s00190-020-01449-6].

[0009] This invention aims to directly determine the most critical physical parameters in the earthquake-induced liquefaction mechanism using a Global Navigation Satellite System (GNSS) or strain gauge, namely the number of dynamic loading cycles, duration, frequency and power spectrum during the earthquake, so as to achieve liquefaction potential assessment and identification.

[0010] In summary, existing earthquake liquefaction assessment methods suffer from the following three fundamental technical deficiencies: (i) The complete absence of the most critical dynamic loading cycle physical parameters at the earthquake-induced liquefaction site It is well known that the driving mechanism of earthquake-induced liquefaction is the number of dynamic loading cycles. However, the number of dynamic loading cycles, which is the most important parameter for liquefaction assessment, can only be obtained in laboratory experiments. In earthquake-induced liquefaction sites, this parameter is completely missing.

[0011] (II) Data Source Distortion – Measurement Problems of Traditional Accelerometers The mathematical essence of traditional accelerometers is an ill-conditioned inversion problem. Their raw output data is numerically incorrect and physically meaningless, resembling amplified noise rather than a true acceleration signal. The resulting peak acceleration (PGA) exhibits orders-of-magnitude errors—hundreds or even thousands of times greater than the true physical value. This fundamental measurement flaw causes all liquefaction assessment methods that use PGA as a core input parameter (such as empirical stress methods and energy methods) to lose their physical authenticity from the very beginning.

[0012] (III) Failure of the assessment framework – loss of physical authenticity of stress assessment methods The complete absence of crucial dynamic loading cycle parameters at the liquefaction site, coupled with the distorted PGA data mentioned above, means that existing stress assessment methods (such as the simplified empirical stress method) cannot accurately characterize the actual dynamic load level borne by soil elements during earthquakes. Furthermore, field measurement methods (such as SPT and CPT) can only obtain static physical parameters of the soil before or after the earthquake, and cannot directly determine key liquefaction-driving parameters such as the number of dynamic loading cycles during the earthquake. Therefore, the existing technical system suffers from insurmountable physical gaps at both the data input and assessment framework levels, which will significantly impact the liquefaction potential assessment results. Summary of the Invention

[0013] To address the shortcomings of existing earthquake liquefaction assessment methods, such as the complete absence of the dynamic loading cycle count (the most important parameter for liquefaction assessment) at the earthquake-induced liquefaction site, and the fact that traditional accelerometers are not designed based on ill-conditioned inversion problems, resulting in raw peak ground acceleration (PGA) data that is essentially noise, with numerical errors of hundreds or even thousands of times depending on the magnitude of the original measurement error, potentially leading to a loss of physical authenticity in liquefaction potential assessment methods based on this distorted PGA, and an inability to accurately reflect the actual dynamic loading level experienced by the soil during an earthquake, this invention provides a method for acquiring earthquake liquefaction potential assessment data and an earthquake liquefaction potential assessment method that directly obtains key physical parameters that truly reflect the driving intensity of earthquake liquefaction from measured displacement or strain waveforms.

[0014] The technical solution of this invention: A method for acquiring data for assessing seismic liquefaction potential includes the following steps: S1. Obtain the seismic displacement waveform or strain waveform of the target site during the earthquake. S2. Detect the peaks and troughs of each cycle of the seismic displacement or strain waveform for each component, calculate the difference between the peak and trough values, and compare this difference with a statistical significance threshold: If the difference between the peak and trough values ​​is less than the statistical significance threshold, then the peak and trough are determined not to constitute a valid cyclic vibration event and are not included in the period count of valid cyclic vibration events. If the difference between the peak and trough values ​​is greater than or equal to the statistical significance threshold, then the pair of peaks and troughs is determined to constitute a valid cyclic vibration event and is included in the period count of valid cyclic vibration events. S3. Based on the period count of effective cyclic vibration events, obtain the number of dynamic cyclic vibrations that characterize the intensity of seismic liquefaction driving.

[0015] Furthermore, in step S1: The seismic displacement waveform was generated by solving GNSS observation data; The strain waveform is calculated from the GNSS displacement waveforms of at least three stations, or acquired by a strain gauge.

[0016] Furthermore, the statistical significance threshold is determined based on the nominal accuracy of the waveform acquisition device or the accuracy estimated from the acquired waveform data, and then according to... The mean square error is determined by multiples.

[0017] Furthermore, based on the identified effective cyclic vibration events, the time when the vibration begins or the time when the first effective cyclic vibration event occurs and the time when the last effective cyclic vibration event ends are determined, and the time span between the two is calculated to obtain the duration of cyclic vibration in the seismic liquefaction-driven process.

[0018] Furthermore, spectral analysis is performed on the earthquake displacement waveform or strain waveform to extract waveform frequency and power spectrum parameters.

[0019] Furthermore, based on the number of dynamic cyclic vibrations, the duration of the cyclic vibrations, and the waveform frequency and power spectrum parameters, a liquefaction assessment of the target site is conducted.

[0020] A method for assessing seismic liquefaction potential includes the following steps: S1. Obtain the seismic displacement waveform or strain waveform of each component of the target site during the earthquake. S2. Detect the peaks and troughs of each cycle of the seismic displacement or strain waveform for each component, calculate the difference between the peak and trough values, and compare this difference with a preset statistical significance threshold: If the difference between the peak and trough values ​​is less than the statistical significance threshold, then the peak and trough are determined not to constitute a valid cyclic vibration event and are not included in the period count of valid cyclic vibration events. If the difference between the peak and trough values ​​is greater than or equal to the statistical significance threshold, then the pair of peaks and troughs is determined to constitute a valid cyclic vibration event and is included in the period count of valid cyclic vibration events. S3, Obtain parameters: Based on period counting, the number of dynamic cyclic vibrations characterizing the intensity of seismic liquefaction driving is obtained; S4. Utilize the number of dynamic cyclic vibrations to assess the liquefaction potential and output the liquefaction potential assessment results of the target site.

[0021] Furthermore, it also includes determining the start time of vibration or the occurrence time of the first effective cyclic vibration event and the end time of the last effective cyclic vibration event by identifying effective cyclic vibration events, calculating the time span between the two, and obtaining the duration of cyclic vibration in the seismic liquefaction-driven process. The liquefaction potential assessment results were confirmed by the duration of cyclic vibration.

[0022] Furthermore, it also includes performing spectral analysis on the earthquake displacement waveform or strain waveform to extract the waveform frequency and its power spectrum parameters; The liquefaction potential assessment results were confirmed using waveform frequency and its power spectrum parameters.

[0023] A system for acquiring data on seismic liquefaction potential assessment includes: The waveform acquisition module acquires the seismic displacement waveform or strain waveform of the target site during the earthquake. The effective event identification module detects the peaks and troughs of each cycle of the seismic displacement or strain waveform, calculates the difference between the peak and trough values, and compares this difference with a preset statistical significance threshold. If the difference between the peak and trough values ​​is less than the statistical significance threshold, then the peak and trough are determined not to constitute a valid cyclic vibration event and are not included in the period count of valid cyclic vibration events. If the difference between the peak and trough values ​​is greater than or equal to the statistical significance threshold, then the pair of peaks and troughs is determined to constitute a valid cyclic vibration event and is included in the period count of valid cyclic vibration events. The cycle count module obtains the dynamic cycle vibration count, which characterizes the intensity of seismic liquefaction, based on cycle counting.

[0024] The beneficial effects of this invention are: To date, liquefaction assessment methods primarily rely on laboratory-based physical parameter acquisition, which may not be suitable for field liquefaction scenarios. In field experiments, cone penetration tests (CPT), standard penetration tests (SPT), or shear wave velocity measurements are not only costly but also fail to obtain the physical parameters of liquefaction during earthquakes. In fact, there is currently no method to provide effective information on the crucial physical parameter of the number of dynamic loading cycles during an earthquake for liquefaction assessment. Furthermore, peak ground acceleration (PGA) and acceleration records or strong ground motion records also contain significant numerical errors.

[0025] This invention takes a completely different approach than previous methods. First, it proposes to directly measure the seismic displacement waveform using the Global Navigation Satellite System (GNSS), or to calculate the displacement waveform obtained from GNSS, or to acquire the strain waveform of the target site during the earthquake using a strain gauge. The difference between the peaks and troughs of each cycle of the displacement or strain waveform is detected and compared with a statistical significance threshold. The most critical physical parameters of the liquefaction mechanism are calculated using the seismic displacement or strain waveform, namely the number of dynamic loading cycles, duration, frequency and power spectrum during the earthquake. Then, the magnitude of the number of dynamic loading cycles is used to segment the liquefaction potential, and combined with the duration and spectral characteristics, a graded assessment of low, medium, high and extremely high liquefaction potential is given. Attached Figure Description

[0026] Figure 1 This is a flowchart of the method for acquiring earthquake liquefaction potential assessment data according to the present invention; Figure 2 This is a system diagram of the data acquisition process for seismic liquefaction potential assessment in this invention; Figure 3 This is a waveform of seismic displacement from a GNSS observation station closest to the epicenter in the Tohoku region during the 2011 Great East Japan Earthquake (Magnitude 9). Figure 4 This is a spectrum of the seismic displacement waveform before and after the peak value at a GNSS observation station closest to the epicenter in the Tohoku region during the 2011 Great East Japan Earthquake (Magnitude 9). Figure 5 This is a waveform of seismic displacement from a GNSS observation station in the Tohoku region, the fifth closest to the epicenter, during the 2011 Great East Japan Earthquake (Magnitude 9). Figure 6 This is a spectrum of the seismic displacement waveform before and after the peak value of a GNSS observation station in the Tohoku region, which is the fifth closest to the epicenter, during the 2011 Great East Japan Earthquake (Magnitude 9). Figure 7 This is a waveform of seismic displacement from a GNSS observation station in the Tokyo Bay area during the 2011 Great East Japan Earthquake (magnitude 9). Figure 8This is a spectrum of the displacement waveform before and after the peak value of a GNSS observation station in the Tokyo Bay area during the 2011 Great East Japan Earthquake (Magnitude 9). Detailed Implementation One or more embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0027] It should be understood that the steps described in the method embodiments of this disclosure may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of this disclosure is not limited in this respect.

[0028] To date, no method has been able to provide effective information on the key physical parameter of the number of dynamic loading cycles during an earthquake for liquefaction assessment. Therefore, all liquefaction assessment methods do not consider this crucial liquefaction physical parameter, which is the measured number of dynamic loading cycles during an earthquake, and instead rely solely on PGA or strong-motion records. However, the waveform of the strong-motion records output by traditional accelerometers is numerically incorrect and physically meaningless, resembling amplified noise rather than a true acceleration signal. Consequently, the peak acceleration (PGA) obtained from this method exhibits numerical deviations on the order of magnitude—the error can reach hundreds or even thousands of times compared to the true physical value.

[0029] This invention first proposes to directly measure seismic displacement waves using the Global Navigation Satellite System (GNSS), set a statistical significance threshold for the displacement difference between wave crests and troughs, and use the seismic displacement waveform to calculate the most critical physical parameters of the liquefaction mechanism, namely the number of dynamic loading cycles, duration, frequency and power spectrum during the earthquake. Then, by segmenting the number of dynamic loading cycles and combining the duration and spectral characteristics, a graded assessment of low, medium, high and extremely high liquefaction potential is given.

[0030] The specific implementation method is as follows: Please refer to Figure 1 and Figure 2 The process of dynamically loading the loop count includes the following steps: S1. Obtain the seismic displacement waveform or strain waveform of the target site during the earthquake. S2. Detect the peaks and troughs of each cycle of the seismic displacement or strain waveform for each component, calculate the difference between the peak and trough values, and compare this difference with a preset statistical significance threshold: If the difference between the peak and trough values ​​is less than the statistical significance threshold, it will not be identified as a valid cyclic vibration event and will not be included in the cycle count. If the difference between the peak and trough values ​​is greater than or equal to the statistical significance threshold, then the pair of peaks and troughs is determined to constitute a valid cyclic vibration event and is included in the period count of valid cyclic vibration events. Due to the nonlinearity of seismic displacement and strain waveforms, sometimes even very strong nonlinearity, coupled with the error of measuring instruments, for periodic waveforms that are extremely difficult to judge, the number of cyclic vibration periods measured by different people may have small errors.

[0031] S3. Based on period counting, obtain the number of dynamic cyclic vibrations that characterize the intensity of seismic liquefaction driving.

[0032] It should be noted that the seismic displacement waveform or strain waveform described in this invention is not limited to data collected during the most recent earthquake at the target site, nor is it limited to data obtained through real-time transmission or online monitoring. Any historical seismic displacement waveform record that can reflect the dynamic displacement characteristics of the target site during an earthquake, as long as its data quality meets the resolution requirements for subsequent effective cyclic vibration event identification, can be used as data input for the method of this invention.

[0033] In practical applications, the seismic displacement waveform or strain waveform can be derived from: observation data recorded by GNSS receivers or strain gauges deployed at the target site during an earthquake; historical seismic displacement waveform data covering the target site stored in regional seismic observation networks or engineering strong motion monitoring databases; or pre-processed seismic displacement waveform data products of the target site provided by third-party data service providers.

[0034] In other words, as long as the complete or partial displacement waveform or strain waveform generated at the target site during the earthquake can be obtained, the method of this invention can be used to extract physical parameters for liquefaction assessment, such as the number of cyclic dynamic vibrations. There is no specific time correlation requirement between the earthquake occurrence time and the execution time of the method of this invention—it can be a retrospective analysis and liquefaction potential assessment using historical earthquake events, or a near real-time rapid assessment of the current earthquake.

[0035] In addition to obtaining the number of times the dynamic loading loop is obtained, the duration of the loop vibration can also be obtained.

[0036] Based on the identified effective cyclic vibration events, the occurrence time of the seismic vibration event and the end time of the last effective cyclic vibration event of the site to be evaluated are determined, and the time span between the two is calculated to obtain the duration of cyclic vibration of the seismic liquefaction-driven process.

[0037] The seismic waveform can also be subjected to spectral analysis to extract its frequency and power spectrum parameters.

[0038] The liquefaction potential of the target site is assessed using the number of dynamic cyclic vibrations, and the assessment result is output. Further, the duration of the cyclic vibrations is used to confirm the liquefaction potential assessment result. Alternatively, the waveform frequency and its power spectral parameters can be used to confirm the liquefaction potential assessment result. This allows for a graded assessment of low, medium, high, and extremely high liquefaction potential.

[0039] It should be noted that, due to the lack of effective means in existing technologies to directly measure the number of cyclic dynamic vibrations during an earthquake, the industry has not yet established a quantitative standard for liquefaction discrimination based on the number of cyclic dynamic vibrations. The method of this invention is the first to achieve direct on-site measurement of the number of cyclic dynamic vibrations during an earthquake, providing a technical basis for establishing such a standard.

[0040] To facilitate understanding of the physical meaning of the cyclic dynamic vibration count output by the method of this invention and its reference value in liquefaction potential assessment, the following provides a set of exemplary correspondences based on an embodiment based on seismic displacement waveforms. In the limited embodiments accumulated by the inventors, when the statistical significance threshold is set to 4 cm, the following approximate correspondence trend between the liquefaction risk level and the cyclic dynamic vibration count is observed: when the cyclic dynamic vibration count is between 0 and 14, the site liquefaction risk is relatively low; when the cyclic dynamic vibration count is between 15 and 24, the liquefaction risk is moderate; when the cyclic dynamic vibration count is between 25 and 34, the liquefaction risk is high; and when the cyclic dynamic vibration count exceeds 35, the liquefaction risk is extremely high.

[0041] It should be emphasized that the above correspondence is only an exemplary description based on the current limited sample and does not constitute any limitation on the scope of protection of the present invention. As the method of the present invention is promoted and applied in actual engineering and a large amount of earthquake liquefaction case data is accumulated, the above numerical range may be dynamically adjusted according to the following factors: (1) the difference in GNSS observation accuracy of different target sites and the different settings of statistical significance thresholds; (2) the influence of different earthquake magnitudes, source mechanisms and site soil types on the relationship between cyclic load and liquefaction response; (3) the differentiated requirements of regional or specific engineering type liquefaction protection standards.

[0042] Therefore, when applying the method of the present invention, those skilled in the art can independently set the correspondence between the number of cyclic dynamic vibrations and liquefaction potential in combination with specific engineering requirements and site conditions, or use the number of cyclic dynamic vibrations as a key evaluation parameter in conjunction with other liquefaction evaluation physical parameters (such as the duration of cyclic vibration, spectral characteristic parameters, etc.) to obtain liquefaction potential evaluation results suitable for specific target sites.

[0043] Example 1 The following uses measured data from a GNSS observation station during the 2011 Great East Japan Earthquake (Magnitude 9). This example fully illustrates the implementation process of the method of this invention. This embodiment covers the entire process from acquiring GNSS displacement waveforms, setting statistical significance thresholds, identifying effective cyclic vibration events, counting the number of cyclic dynamic vibrations, calculating the duration of cyclic vibrations, to extracting spectral feature parameters. Those skilled in the art should understand that the specific values ​​given in this embodiment (such as a 4 cm threshold, 7 cycles, and a duration of 223 seconds) are only used to exemplify the feasibility and effectiveness of the method of this invention and do not constitute a limitation on the scope of protection of this invention.

[0044] like Figure 3 The figure shows the displacement waveform of the observation station during the earthquake. The coseismic displacement of this station produced permanent displacements of 503.5 cm eastward, 150.9 cm southward, and 116.2 cm downward in the east-west, north-south, and vertical directions, respectively.

[0045] Considering the measurement error characteristics of high-frequency GNSS, this model uses the physical significance of the displacement difference between the peaks and troughs in the displacement waveform as the criterion for statistical significance thresholding. Specifically, although conventional measurement data processing typically uses three times the standard error as the statistical significance threshold, the threshold set here is to ensure that the physical meaning of the identified displacement difference between the peaks and troughs is almost entirely unaffected by measurement errors, thus truly reflecting the seismic cyclic loading effect. Because the accuracy of the east-west and north-south directions estimated from GNSS data from different observation stations may vary, for convenience, including in this embodiment, we set the statistical significance threshold for the displacement difference between the peaks and troughs in the east-west and north-south directions to 4 cm. This threshold corresponds to a standard error multiple α of approximately 9.9 times in the east-west direction and 8.8 times in the north-south direction, which is much higher than the conventional three times standard error standard, thereby minimizing the interference of measurement errors on the identification of cyclic vibration events. Based on the above statistical significance threshold, peak and trough detection is performed on the displacement waveforms in the east-west and north-south directions, respectively. For each pair of adjacent peaks and troughs, calculate the amplitude of the peak and trough, referred to as peak-trough amplitude, and compare the peak-trough amplitude with the corresponding statistical significance threshold (4 cm): If the peak-to-valley amplitude is less than 4 cm, the fluctuation is deemed insignificant and is not included in the period count of the effective cyclic vibration event. If the peak-to-valley amplitude is greater than or equal to 4 cm, then the pair of peaks and troughs is determined to constitute an effective half-cycle and is included in the cycle count of the effective cyclic vibration event.

[0046] Two consecutive effective half-cycles with opposite displacement directions are combined and counted into a complete effective cyclic vibration cycle.

[0047] The effective cyclic vibration periods of the displacement waveforms in the east-west and north-south directions were counted separately. The maximum number of effective cyclic vibration periods in the two horizontal directions was defined as the horizontal dynamic loading cycle number of the target site. In this embodiment, the horizontal dynamic loading cycle number of the station was 7.

[0048] The key parameter output in this embodiment is the number of horizontal dynamic loading cycles, N. This parameter can be directly used as the input for seismic liquefaction potential assessment, and the output will show the liquefaction potential assessment results for the target site.

[0049] Based on the above statistics of the number of horizontal dynamic loading cycles, the duration of horizontal cyclic vibration at the target site is further determined. The specific steps are as follows: First, for the high-frequency GNSS displacement waveform of the observation station, the initial vibration time in the east-west and north-south directions, or the start time of the first identification as a valid cyclic vibration event, is determined as the initial vibration time of the observation station, denoted as t. 01 and t 02 .

[0050] Secondly, determine the final loading time in each horizontal direction. Record the end time of the last (i.e., the final) effective cyclic vibration event in the displacement waveforms of the east-west and north-south directions, denoted as t. h1 and t h2 ; Then, determine the duration of the horizontal cyclic vibration. Calculate the duration of the cyclic vibration in the east-west and north-south directions respectively (t). h1 - t 01 ) and (t h2 - t 02 The larger of the two values ​​is taken as the duration of the horizontal cyclic vibration at the observation station, denoted as . t.

[0051] It should be noted that the larger of the duration of the east-west and north-south cyclic vibrations is used as the duration of the horizontal cyclic vibrations to ensure that the duration of the horizontal cyclic vibrations can fully cover the time period during which effective cyclic loading is still occurring in either of the two horizontal directions, thus conservatively reflecting the duration of the seismic cyclic load on the site soil.

[0052] In this embodiment, the duration of the horizontal cyclic vibration of the GNSS observation station calculated using the above method is 223 seconds, that is... t = 223 seconds.

[0053] Furthermore, the horizontal displacement waveform of the GNSS observation station is subjected to spectral transformation processing to obtain the corresponding displacement waveform spectrum.

[0054] like Figure 4The displacement waveform spectrum of this embodiment is provided. Spectral characteristic parameters related to liquefaction assessment can be extracted from the spectrum, including but not limited to: frequency components and their power spectra. These spectral characteristic parameters can serve as auxiliary discriminant indicators for liquefaction potential assessment.

[0055] Because the GNSS observation station only has 7 horizontal dynamic loading cycles, the duration of the horizontal cyclic vibration is short, and its displacement waveform spectrum is... Figure 4 The frequency components are simple, therefore, the liquefaction potential of this station is low. The number of cyclic dynamic vibrations (N=7), the duration of horizontal cyclic vibrations, and the spectral characteristic parameters can also serve as objective physical inputs for further quantitative assessment of the liquefaction potential of this target site.

[0056] Example 2 The following uses measured data from the fifth closest GNSS observation station to the epicenter in the Tohoku region during the 2011 Great East Japan Earthquake (magnitude 9). This example fully illustrates the implementation process of the method of this invention. This embodiment covers the entire process from acquiring GNSS displacement waveforms, setting statistical significance thresholds, identifying effective cyclic vibration events, counting the number of cyclic dynamic vibrations, calculating the duration of cyclic vibrations, to extracting spectral feature parameters. Those skilled in the art should understand that the specific values ​​given in this embodiment (such as a 4 cm threshold, 29 cycles, and a duration of 209 seconds) are only used to exemplify the feasibility and effectiveness of the method of this invention and do not constitute a limitation on the scope of protection of this invention.

[0057] like Figure 5 The displacement waveforms of the 5th closest GNSS station to the epicenter in the Tohoku region during the 2011 Great East Japan Earthquake (Magnitude 9). During the earthquake, the coseismic displacement at this station shifted eastward by 378.8 cm and southward by 114.7 cm in the east-west and north-south directions, respectively, with a subsidence of 48.4 cm. Similar to Example 1, a statistical significance threshold of 4 cm was set for the displacement difference between the peak and trough in the east-west and north-south directions, equivalent to the selected error multiple for the east-west and north-south directions. The magnitudes were 8.9 and 6.8 times respectively, resulting in 29 horizontal cyclic dynamic vibrations. The duration of the horizontal cyclic vibration at this GNSS observation station was 209 seconds. (Auxiliary displacement waveform spectrum diagram) Figure 6 The station exhibits rich frequency components and power spectrum characteristics, indicating high liquefaction potential.

[0058] Example 3 The following example uses measured data from a GNSS observation station in the Tokyo Bay area during the 2011 Great East Japan Earthquake (Magnitude 9). This fully illustrates the implementation process of the method of the present invention. This embodiment covers the entire process from acquiring GNSS displacement waveforms, setting statistical significance thresholds, identifying effective cyclic vibration events, counting the number of cyclic dynamic vibrations, calculating the duration of cyclic vibrations, to extracting spectral feature parameters. Those skilled in the art should understand that the specific values ​​given in this embodiment (such as a 4 cm threshold, 72 cycles, and a duration of 935 seconds) are only used to exemplify the feasibility and effectiveness of the method of the present invention and do not constitute a limitation on the scope of protection of the present invention.

[0059] Figure 7 The displacement waveforms of a GNSS station in the Tokyo Bay area during the 2011 Great East Japan Earthquake (Magnitude 9). During the earthquake, the station's coseismic displacement shifted eastward by 10.6 cm and northward by 1.9 cm in the east-west and north-south directions, respectively, with a subsidence of 6.3 cm. Similar to Example 1, a statistical significance threshold of 4 cm was set for the displacement difference between the peak and trough in the east-west and north-south directions, equivalent to the selected error multiple for the east-west and north-south directions. The values ​​reached 9.7 and 8.1 times respectively, resulting in a horizontal cyclic dynamic vibration number of 72 and a cyclic dynamic vibration duration of 935 seconds. The displacement waveform spectrum diagram ( Figure 8 The station exhibits very rich frequency components and power spectrum characteristics, indicating that it has extremely high liquefaction potential.

[0060] Example 4 The following examples illustrate the subsequent processing of the obtained strain waveform. After obtaining the strain waveform of the target site during the earthquake (whether calculated from the displacement waveforms of at least three GNSS stations or directly acquired by the strain gauge), the subsequent steps, such as effective cyclic vibration event identification, cyclic dynamic vibration cycle count, cyclic vibration duration calculation, and spectral feature parameter extraction, are consistent with the methods described in the above examples based on earthquake displacement waveforms.

[0061] The above description is merely a preferred embodiment of the present invention and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features disclosed in this disclosure that have similar functions.

[0062] Furthermore, while the operations are described in a specific order, this should not be construed as requiring these operations to be performed in the specific order shown or in a sequential order. In certain environments, multitasking and parallel processing may be advantageous. Similarly, while several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of this disclosure. Certain features described in the context of individual embodiments may also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented individually or in any suitable sub-combination in multiple embodiments.

[0063] Although the subject matter has been described using language specific to structural features and / or methodological logic, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. Rather, the specific features and actions described above are merely illustrative examples of implementing the claims.

Claims

1. A method for acquiring data for assessing seismic liquefaction potential, characterized in that, Includes the following steps: S1. Obtain the seismic displacement waveform or strain waveform of the target site during the earthquake. S2. Detect the peaks and troughs of each cycle of the seismic displacement or strain waveform for each component, calculate the difference between the peak and trough values, and compare this difference with a statistical significance threshold: If the difference between the peak and trough values ​​is less than the statistical significance threshold, then the peak and trough are determined not to constitute a valid cyclic vibration event and are not included in the period count of valid cyclic vibration events. If the difference between the peak and trough values ​​is greater than or equal to the statistical significance threshold, then the pair of peaks and troughs is determined to constitute a valid cyclic vibration event and is included in the period count of valid cyclic vibration events. S3. Based on the period count of effective cyclic vibration events, obtain the number of dynamic cyclic vibrations that characterize the intensity of seismic liquefaction driving.

2. The method for acquiring data for assessing seismic liquefaction potential according to claim 1, characterized in that, In step S1: The seismic displacement waveform was generated by solving GNSS observation data; The strain waveform is calculated from the GNSS displacement waveforms of at least three stations, or acquired by a strain gauge.

3. The method for acquiring data for assessing seismic liquefaction potential according to claim 2, characterized in that, The statistical significance threshold is determined based on the nominal accuracy of the waveform acquisition device or an estimated accuracy from the acquired waveform data, and then according to... The mean square error is determined by multiples.

4. The method for acquiring data for assessing seismic liquefaction potential according to claim 3, characterized in that, Based on the identified effective cyclic vibration events, the time when the vibration begins or the time when the first effective cyclic vibration event occurs and the time when the last effective cyclic vibration event ends are determined. The time span between the two is calculated to obtain the duration of cyclic vibration in the seismic liquefaction-driven process.

5. The method for acquiring data for assessing seismic liquefaction potential according to claim 4, characterized in that, Spectral analysis is performed on the earthquake displacement waveform or strain waveform to extract waveform frequency and power spectrum parameters.

6. The method for acquiring data for assessing seismic liquefaction potential according to claim 5, characterized in that, Also includes: Based on the number of dynamic cyclic vibrations, the duration of the cyclic vibrations, and the waveform frequency and power spectrum parameters, a liquefaction assessment of the target site is conducted.

7. A method for assessing seismic liquefaction potential based on any one of claims 1 to 6, characterized in that, Includes the following steps: S1. Obtain the seismic displacement waveform or strain waveform of each component of the target site during the earthquake. S2. Detect the peaks and troughs of each cycle of the seismic displacement or strain waveform for each component, calculate the difference between the peak and trough values, and compare this difference with a preset statistical significance threshold: If the difference between the peak and trough values ​​is less than the statistical significance threshold, then the peak and trough are determined not to constitute a valid cyclic vibration event and are not included in the period count of valid cyclic vibration events. If the difference between the peak and trough values ​​is greater than or equal to the statistical significance threshold, then the pair of peaks and troughs is determined to constitute a valid cyclic vibration event and is included in the period count of valid cyclic vibration events. S3, Obtain parameters: Based on period counting, the number of dynamic cyclic vibrations characterizing the intensity of seismic liquefaction driving is obtained; S4. Utilize the number of dynamic cyclic vibrations to assess the liquefaction potential and output the liquefaction potential assessment results of the target site.

8. The method for assessing seismic liquefaction potential according to claim 7, characterized in that: It also includes determining the start time of vibration or the occurrence time of the first effective cyclic vibration event and the end time of the last effective cyclic vibration event by identifying effective cyclic vibration events, calculating the time span between the two, and obtaining the duration of cyclic vibration in the seismic liquefaction-driven process. The duration of cyclic vibration was used to confirm the liquefaction potential assessment results.

9. The method for assessing seismic liquefaction potential according to claim 8, characterized in that: It also includes performing spectral analysis on the earthquake displacement waveform or strain waveform to extract the waveform frequency and its power spectrum parameters; The liquefaction potential assessment results were confirmed using waveform frequency and its power spectrum parameters.

10. A system for acquiring data on seismic liquefaction potential assessment, characterized in that, include: The waveform acquisition module acquires the seismic displacement waveform or strain waveform of the target site during the earthquake. The effective event identification module detects the peaks and troughs of each cycle of the seismic displacement or strain waveform, calculates the difference between the peak and trough values, and compares this difference with a preset statistical significance threshold. If the difference between the peak and trough values ​​is less than the statistical significance threshold, then the peak and trough are determined not to constitute a valid cyclic vibration event and are not included in the period count of valid cyclic vibration events. If the difference between the peak and trough values ​​is greater than or equal to the statistical significance threshold, then the pair of peaks and troughs is determined to constitute a valid cyclic vibration event and is included in the period count of valid cyclic vibration events. The cycle count module obtains the dynamic cycle vibration count, which characterizes the intensity of seismic liquefaction driving, based on cycle counting.

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