Pub Date : 2024-09-10DOI: 10.1016/j.soildyn.2024.108961
Tunnels embedded in liquefiable soil are frequently subjected to uplift and sustain serious damage during major earthquakes. Mitigation methods to prevent the flotation of these tunnels must be developed and implemented in the natural environment. For this purpose, this study proposes a new method that uses stone columns to enhance soil drainage and mitigate soil liquefaction around tunnels. A circular tunnel in liquefied soil is simulated using a 2D finite element model, PLAXIS 2D, and subjected to a sinusoidal input motion. The tunnel's pre-construction and post-construction scenarios are examined. Parametric studies are carried out to investigate the effect of changing several parameters, such as the distance between stone columns and tunnel springing, the diameter of stone columns, the spacing between stone columns, the number of stone column rows, and the stone column arrangement patterns on the effectiveness of liquefaction mitigation. The study reveals that liquefaction mitigation is enhanced by using stone columns closer to tunnel springing, with larger diameters, less spacing, and more rows of stone columns that are arranged in a square pattern. It also emphasizes the importance of timely implementation of stone columns for maximum benefit.
{"title":"Stone column strategies for mitigating liquefaction-induced uplift of tunnels","authors":"","doi":"10.1016/j.soildyn.2024.108961","DOIUrl":"10.1016/j.soildyn.2024.108961","url":null,"abstract":"<div><p>Tunnels embedded in liquefiable soil are frequently subjected to uplift and sustain serious damage during major earthquakes. Mitigation methods to prevent the flotation of these tunnels must be developed and implemented in the natural environment. For this purpose, this study proposes a new method that uses stone columns to enhance soil drainage and mitigate soil liquefaction around tunnels. A circular tunnel in liquefied soil is simulated using a 2D finite element model, PLAXIS 2D, and subjected to a sinusoidal input motion. The tunnel's pre-construction and post-construction scenarios are examined. Parametric studies are carried out to investigate the effect of changing several parameters, such as the distance between stone columns and tunnel springing, the diameter of stone columns, the spacing between stone columns, the number of stone column rows, and the stone column arrangement patterns on the effectiveness of liquefaction mitigation. The study reveals that liquefaction mitigation is enhanced by using stone columns closer to tunnel springing, with larger diameters, less spacing, and more rows of stone columns that are arranged in a square pattern. It also emphasizes the importance of timely implementation of stone columns for maximum benefit.</p></div>","PeriodicalId":49502,"journal":{"name":"Soil Dynamics and Earthquake Engineering","volume":null,"pages":null},"PeriodicalIF":4.2,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142162128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-08DOI: 10.1016/j.soildyn.2024.108950
The noise horizontal-to-vertical spectral ratio (NHV) has been applied for inverting subsurface velocity structures, but the non-uniqueness issue in the inversion remains prominent. Parameter sensitivity analysis is crucial for understanding the extent to which parameters influence inversion results, providing reasonable value ranges for each parameter, and offering rational constraints to mitigate the non-uniqueness of solutions. This study takes 636 sites from the KiK-net network as benchmark sites and employs the Monte Carlo method based on Toro's statistical model to generate 200 random samples for each site's shear wave velocity (VS), compressional wave velocity (VP), layer thickness (h), and density (ρ) parameters. These random samples are then combined into six scenarios, serving as the stochastic site models for uncertainty analysis. Finally, based on the diffuse field assumption (DFA) for NHV forward modeling, the NHVs and their standard deviations are calculated for each scenario. The standard deviations of NHV are further utilized to conduct a sensitivity analysis of soil layer parameter uncertainties' impact on NHV. The results indicate: 1) The NHV peak frequency (fpeak) is most sensitive to the VS and h combination, followed by the VS and ρ combination. Among single-parameter scenarios, fpeak is most sensitive to VS, followed by h, and relatively insensitive to VP and ρ. 2) The NHV peak amplitude (Apeak) is most sensitive to the VS and ρ combination, followed by the VS and h combination. Among single-parameter scenarios, Apeak is most sensitive to VS, approaching the sensitivity level of the VS and h combination, followed by ρ, and relatively insensitive to h and VP. 3) Within the 0.1–50 Hz frequency band, the NHV curve is most sensitive to the VS and h combination, followed by the VS and ρ combination, and the single-parameter VS scenario. Among single-parameter scenarios, the NHV curve is secondly sensitive to h, while its sensitivity to VP and ρ is relatively low. The sensitivity patterns of NHV to soil parameters revealed in this study are widely applicable, providing effective constraints for NHV inversion, assisting in optimizing parameter combinations, assessing the feasibility of inversion schemes and the credibility of results, and offering beneficial insights for improving the efficiency of the inversion process.
噪声水平垂直谱比(NHV)已被用于反演地下速度结构,但反演中的非唯一性问题依然突出。参数敏感性分析对于了解参数对反演结果的影响程度、为每个参数提供合理的取值范围以及提供合理的约束条件以减轻解的非唯一性至关重要。本研究以 KiK 网络中的 636 个站点为基准站点,采用基于 Toro 统计模型的 Monte Carlo 方法,为每个站点的剪切波速度(VS)、压缩波速度(VP)、层厚度(h)和密度(ρ)参数生成 200 个随机样本。然后将这些随机样本组合成六个方案,作为随机站点模型进行不确定性分析。最后,根据用于 NHV 正向建模的扩散场假设 (DFA),计算出每个方案的 NHV 及其标准偏差。进一步利用 NHV 的标准偏差,对土层参数不确定性对 NHV 的影响进行敏感性分析。结果表明1) NHV 峰值频率(fpeak)对 VS 和 h 组合最敏感,其次是 VS 和 ρ 组合。2) NHV 峰值振幅(Apeak)对 VS 和 ρ 组合最敏感,其次是 VS 和 h 组合。在单参数方案中,Apeak 对 VS 最敏感,接近 VS 和 h 组合的敏感度,其次是 ρ,而对 h 和 VP 相对不敏感。3) 在 0.1-50 Hz 频段内,NHV 曲线对 VS 和 h 组合最敏感,其次是 VS 和 ρ 组合,以及单参数 VS 方案。在单参数方案中,NHV 曲线对 h 的敏感度次之,而对 VP 和 ρ 的敏感度相对较低。本研究揭示的 NHV 对土壤参数的敏感性规律具有广泛的适用性,可为 NHV 反演提供有效的约束条件,有助于优化参数组合、评估反演方案的可行性和结果的可信度,并为提高反演过程的效率提供有益的启示。
{"title":"Influence of soil parameter uncertainties on site ambient noise horizontal to vertical spectral ratio modeling","authors":"","doi":"10.1016/j.soildyn.2024.108950","DOIUrl":"10.1016/j.soildyn.2024.108950","url":null,"abstract":"<div><p>The noise horizontal-to-vertical spectral ratio (NHV) has been applied for inverting subsurface velocity structures, but the non-uniqueness issue in the inversion remains prominent. Parameter sensitivity analysis is crucial for understanding the extent to which parameters influence inversion results, providing reasonable value ranges for each parameter, and offering rational constraints to mitigate the non-uniqueness of solutions. This study takes 636 sites from the KiK-net network as benchmark sites and employs the Monte Carlo method based on Toro's statistical model to generate 200 random samples for each site's shear wave velocity (<em>V</em><sub>S</sub>), compressional wave velocity (<em>V</em><sub>P</sub>), layer thickness (<em>h</em>), and density (<em>ρ</em>) parameters. These random samples are then combined into six scenarios, serving as the stochastic site models for uncertainty analysis. Finally, based on the diffuse field assumption (DFA) for NHV forward modeling, the NHVs and their standard deviations are calculated for each scenario. The standard deviations of NHV are further utilized to conduct a sensitivity analysis of soil layer parameter uncertainties' impact on NHV. The results indicate: 1) The NHV peak frequency (<em>f</em><sub>peak</sub>) is most sensitive to the <em>V</em><sub>S</sub> and <em>h</em> combination, followed by the <em>V</em><sub>S</sub> and <em>ρ</em> combination. Among single-parameter scenarios, <em>f</em><sub>peak</sub> is most sensitive to <em>V</em><sub>S</sub>, followed by <em>h</em>, and relatively insensitive to <em>V</em><sub>P</sub> and <em>ρ</em>. 2) The NHV peak amplitude (<em>A</em><sub>peak</sub>) is most sensitive to the <em>V</em><sub>S</sub> and <em>ρ</em> combination, followed by the <em>V</em><sub>S</sub> and <em>h</em> combination. Among single-parameter scenarios, <em>A</em><sub>peak</sub> is most sensitive to <em>V</em><sub>S</sub>, approaching the sensitivity level of the <em>V</em><sub>S</sub> and <em>h</em> combination, followed by <em>ρ</em>, and relatively insensitive to <em>h</em> and <em>V</em><sub>P</sub>. 3) Within the 0.1–50 Hz frequency band, the NHV curve is most sensitive to the <em>V</em><sub>S</sub> and <em>h</em> combination, followed by the <em>V</em><sub>S</sub> and <em>ρ</em> combination, and the single-parameter <em>V</em><sub>S</sub> scenario. Among single-parameter scenarios, the NHV curve is secondly sensitive to <em>h</em>, while its sensitivity to <em>V</em><sub>P</sub> and <em>ρ</em> is relatively low. The sensitivity patterns of NHV to soil parameters revealed in this study are widely applicable, providing effective constraints for NHV inversion, assisting in optimizing parameter combinations, assessing the feasibility of inversion schemes and the credibility of results, and offering beneficial insights for improving the efficiency of the inversion process.</p></div>","PeriodicalId":49502,"journal":{"name":"Soil Dynamics and Earthquake Engineering","volume":null,"pages":null},"PeriodicalIF":4.2,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142158017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-07DOI: 10.1016/j.soildyn.2024.108960
This paper presents a novel analytical model based on a fictitious saturated soil pile (FSSP) model, Biot's theory, and the Novak plane strain model for analyzing the horizontal vibration of a floating pile in saturated soil. First, the horizontal displacement of the saturated soil and horizontal resistance to the pile were determined using the separation variable method and potential functions. Next, the horizontal vibration response of the pile was obtained by deriving differential equations specific to the FSSP, considering its complete contact with the solid pile. The analytical model was then validated by reducing the proposed solution and comparing it with solutions presented in the literature. Finally, the effects of various soil parameters, such as the FSSP length, damping ratio, elastic modulus, and porosity, on the horizontal vibration response of the floating pile were analyzed.
{"title":"A new analytical solution for horizontal vibration of floating pile in saturated soil based on FSSP method","authors":"","doi":"10.1016/j.soildyn.2024.108960","DOIUrl":"10.1016/j.soildyn.2024.108960","url":null,"abstract":"<div><p>This paper presents a novel analytical model based on a fictitious saturated soil pile (FSSP) model, Biot's theory, and the Novak plane strain model for analyzing the horizontal vibration of a floating pile in saturated soil. First, the horizontal displacement of the saturated soil and horizontal resistance to the pile were determined using the separation variable method and potential functions. Next, the horizontal vibration response of the pile was obtained by deriving differential equations specific to the FSSP, considering its complete contact with the solid pile. The analytical model was then validated by reducing the proposed solution and comparing it with solutions presented in the literature. Finally, the effects of various soil parameters, such as the FSSP length, damping ratio, elastic modulus, and porosity, on the horizontal vibration response of the floating pile were analyzed.</p></div>","PeriodicalId":49502,"journal":{"name":"Soil Dynamics and Earthquake Engineering","volume":null,"pages":null},"PeriodicalIF":4.2,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142151453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-07DOI: 10.1016/j.soildyn.2024.108959
The environmental vibration problems caused by underground trains have recently received widespread attention. An accurate prediction method is essential for vibration assessment around metro lines and for implementing necessary vibration isolation measures. Previous studies have indicated that a hybrid method that combines numerical modelling and experimental measurements can effectively reduce prediction uncertainty with wide adaptability. However, few studies have reported hybrid methods for predicting environmental vibrations caused by underground trains. However, these methods are limited owing to inconvenient excitation experiments in tunnels. Therefore, this study proposes a convenient hybrid prediction method. Subsequently, an experimental study was performed to validate the applicability of the Betti–Rayleigh dynamic reciprocal theorem to the proposed method. A case study was conducted using numerical simulations to verify the feasibility and accuracy of the proposed hybrid method. Finally, a numerical study was conducted to investigate the influence of adjacent hammer spacing and line-source length on the prediction results. The study results demonstrated that the Betti–Rayleigh dynamic reciprocal theorem is applicable to the proposed hybrid prediction method. Hybrid prediction method has been proven to exhibit high accuracy. The adjacent hammer spacing and line-source length can affect the prediction accuracy. Accordingly, the adjacent hammer spacing should be smaller than 19.2 m, and the line-source length should be larger than 80 m in underground train-induced vibration prediction projects under similar conditions.
{"title":"Hybrid method combining numerical modelling and experimental measurements for predicting ground-borne vibrations induced by underground trains","authors":"","doi":"10.1016/j.soildyn.2024.108959","DOIUrl":"10.1016/j.soildyn.2024.108959","url":null,"abstract":"<div><p>The environmental vibration problems caused by underground trains have recently received widespread attention. An accurate prediction method is essential for vibration assessment around metro lines and for implementing necessary vibration isolation measures. Previous studies have indicated that a hybrid method that combines numerical modelling and experimental measurements can effectively reduce prediction uncertainty with wide adaptability. However, few studies have reported hybrid methods for predicting environmental vibrations caused by underground trains. However, these methods are limited owing to inconvenient excitation experiments in tunnels. Therefore, this study proposes a convenient hybrid prediction method. Subsequently, an experimental study was performed to validate the applicability of the Betti–Rayleigh dynamic reciprocal theorem to the proposed method. A case study was conducted using numerical simulations to verify the feasibility and accuracy of the proposed hybrid method. Finally, a numerical study was conducted to investigate the influence of adjacent hammer spacing and line-source length on the prediction results. The study results demonstrated that the Betti–Rayleigh dynamic reciprocal theorem is applicable to the proposed hybrid prediction method. Hybrid prediction method has been proven to exhibit high accuracy. The adjacent hammer spacing and line-source length can affect the prediction accuracy. Accordingly, the adjacent hammer spacing should be smaller than 19.2 m, and the line-source length should be larger than 80 m in underground train-induced vibration prediction projects under similar conditions.</p></div>","PeriodicalId":49502,"journal":{"name":"Soil Dynamics and Earthquake Engineering","volume":null,"pages":null},"PeriodicalIF":4.2,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142151455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-07DOI: 10.1016/j.soildyn.2024.108947
Data driven models are useful in various classification and regression problems in bridge engineering. Although machine learning applications in identifying the performance and characteristics of bridges has been increasing, repair cost modeling using real earthquake damage data is only sparsely reported in the literature. This study assesses various machine learning models for repair cost estimation of reinforced concrete (RC) bridges damaged by the 2015 Gorkha earthquake in Nepal. Ensemble learning interpretation is used to hierarchize bridge attributes based on their relative importance in repair cost prediction. The impact of individual features is also assessed using various combinations of bridge features. The results indicate that two categorical features, discrete damage state and foundation type, are the most important in predicting repair cost. Of the various models tested, extra trees (ET) ensemble outperformed any other ensemble as well as base learner methods. The findings indicate that, for the case-study data used here, repair cost is better estimated by a classification model for damage state in series with a regression model than just a regression model.
{"title":"Nonlinear tree based regression ensemble modeling for repair cost prediction in earthquake damaged RC bridges","authors":"","doi":"10.1016/j.soildyn.2024.108947","DOIUrl":"10.1016/j.soildyn.2024.108947","url":null,"abstract":"<div><p>Data driven models are useful in various classification and regression problems in bridge engineering. Although machine learning applications in identifying the performance and characteristics of bridges has been increasing, repair cost modeling using real earthquake damage data is only sparsely reported in the literature. This study assesses various machine learning models for repair cost estimation of reinforced concrete (RC) bridges damaged by the 2015 Gorkha earthquake in Nepal. Ensemble learning interpretation is used to hierarchize bridge attributes based on their relative importance in repair cost prediction. The impact of individual features is also assessed using various combinations of bridge features. The results indicate that two categorical features, discrete damage state and foundation type, are the most important in predicting repair cost. Of the various models tested, extra trees (ET) ensemble outperformed any other ensemble as well as base learner methods. The findings indicate that, for the case-study data used here, repair cost is better estimated by a classification model for damage state in series with a regression model than just a regression model.</p></div>","PeriodicalId":49502,"journal":{"name":"Soil Dynamics and Earthquake Engineering","volume":null,"pages":null},"PeriodicalIF":4.2,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142151454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-07DOI: 10.1016/j.soildyn.2024.108946
As structural safety emerges as a paramount concern and with the advancement in vibration control technology, a notable gap persists in accurately simulating structural state nonlinearity, especially within the field of inerter-based seismic control technology. Dealing with the need to upgrade the seismic performance of practical nonlinear structures, this study proposes a structural state nonlinearity-based design method for inerter-incorporated civil structures by incorporating the target seismic performance, structural nonlinearity level, and ground motion effects. By establishing mechanical models of inerter-based systems with straightforward parameters and a prototypical bilinear model for the primary structure, governing equations for inerter-incorporated structures were derived. Later, structural state nonlinearity-based design method for inerter-based systems, including optimization criteria and parameter distribution pattern, is elaborated. Simultaneously, this study also provides structural state nonlinearity-based design curves and modification formulae related to structural state nonlinearity and peak ground acceleration of earthquake. Validated using a 10-story multiple-degree-of-freedom (MDOF) structure subjected to earthquakes, the results highlight the effectiveness of the method, emphasizing its potential in controlling seismic responses of structures within the predetermined performance target. In addition, the absolute acceleration mitigation effect of inerter-based systems is investigated. The efficiency and robustness of the proposed method are also verified under near-fault and far-fault earthquakes. In essence, this research pioneers an approach in inerter-based design, bridging structural state nonlinearity, and potentially reshaping seismic control strategies to align with diverse structural states.
{"title":"Structural state nonlinearity-based design and modification formulae of inerter-based systems","authors":"","doi":"10.1016/j.soildyn.2024.108946","DOIUrl":"10.1016/j.soildyn.2024.108946","url":null,"abstract":"<div><p>As structural safety emerges as a paramount concern and with the advancement in vibration control technology, a notable gap persists in accurately simulating structural state nonlinearity, especially within the field of inerter-based seismic control technology. Dealing with the need to upgrade the seismic performance of practical nonlinear structures, this study proposes a structural state nonlinearity-based design method for inerter-incorporated civil structures by incorporating the target seismic performance, structural nonlinearity level, and ground motion effects. By establishing mechanical models of inerter-based systems with straightforward parameters and a prototypical bilinear model for the primary structure, governing equations for inerter-incorporated structures were derived. Later, structural state nonlinearity-based design method for inerter-based systems, including optimization criteria and parameter distribution pattern, is elaborated. Simultaneously, this study also provides structural state nonlinearity-based design curves and modification formulae related to structural state nonlinearity and peak ground acceleration of earthquake. Validated using a 10-story multiple-degree-of-freedom (MDOF) structure subjected to earthquakes, the results highlight the effectiveness of the method, emphasizing its potential in controlling seismic responses of structures within the predetermined performance target. In addition, the absolute acceleration mitigation effect of inerter-based systems is investigated. The efficiency and robustness of the proposed method are also verified under near-fault and far-fault earthquakes. In essence, this research pioneers an approach in inerter-based design, bridging structural state nonlinearity, and potentially reshaping seismic control strategies to align with diverse structural states.</p></div>","PeriodicalId":49502,"journal":{"name":"Soil Dynamics and Earthquake Engineering","volume":null,"pages":null},"PeriodicalIF":4.2,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142151452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-06DOI: 10.1016/j.soildyn.2024.108956
Many grain silos in earthquake intensity areas are at significant risk of post-seismic damage, which compromise their functionality and pose an enormous challenge to post-disaster rescue and social stability. However, the current specifications based on fixed-base foundations are not fit for the seismic design of silos in soft soil areas. Therefore, it is of great practical significance to study the seismic disaster prevention of siloes considering soil-structure interaction (SSI) for food security and post-disaster supply. In this research, a column-bearing silo in a soft soil area is taken as the research object. The relative displacement response, elastic-plastic development and storage lateral pressure of the structure under different ground motions are studied in detail when the state of filling storage material is empty, half-filled and fully filled. Compared with the fixed-base model, the mechanism of the ground motion response and the influence of the SSI effects on the dynamic characteristics of the column-bearing silo structure under different storage conditions are revealed. In addition, structural vulnerability analysis is carried out with the incremental dynamic analysis (IDA) method. Finally, the structural damage probability with and without SSI effects under different storage conditions is further discussed. The results demonstrate that the SSI effects have a certain damping effect on the column-bearing silo. The amount of storage material changes the failure probability of the structure. Moreover, full-silo is the most dangerous condition, indicating that the filling state of storage material affects the stiffness degradation. This study provides theoretical insight to the influence of the SSI effect on the seismic resilience of structures.
{"title":"Seismic responses and vulnerability assessment of column-bearing silos with soil-structure interaction","authors":"","doi":"10.1016/j.soildyn.2024.108956","DOIUrl":"10.1016/j.soildyn.2024.108956","url":null,"abstract":"<div><p>Many grain silos in earthquake intensity areas are at significant risk of post-seismic damage, which compromise their functionality and pose an enormous challenge to post-disaster rescue and social stability. However, the current specifications based on fixed-base foundations are not fit for the seismic design of silos in soft soil areas. Therefore, it is of great practical significance to study the seismic disaster prevention of siloes considering soil-structure interaction (SSI) for food security and post-disaster supply. In this research, a column-bearing silo in a soft soil area is taken as the research object. The relative displacement response, elastic-plastic development and storage lateral pressure of the structure under different ground motions are studied in detail when the state of filling storage material is empty, half-filled and fully filled. Compared with the fixed-base model, the mechanism of the ground motion response and the influence of the SSI effects on the dynamic characteristics of the column-bearing silo structure under different storage conditions are revealed. In addition, structural vulnerability analysis is carried out with the incremental dynamic analysis (IDA) method. Finally, the structural damage probability with and without SSI effects under different storage conditions is further discussed. The results demonstrate that the SSI effects have a certain damping effect on the column-bearing silo. The amount of storage material changes the failure probability of the structure. Moreover, full-silo is the most dangerous condition, indicating that the filling state of storage material affects the stiffness degradation. This study provides theoretical insight to the influence of the SSI effect on the seismic resilience of structures.</p></div>","PeriodicalId":49502,"journal":{"name":"Soil Dynamics and Earthquake Engineering","volume":null,"pages":null},"PeriodicalIF":4.2,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142151451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-05DOI: 10.1016/j.soildyn.2024.108957
In recent years, there has been a growing recognition of the importance of vertical ground motions in the seismic design of engineering structures. A comprehensive understanding of the small-strain constrained modulus M0, which is a key input soil parameter, is essential for conducting a reliable analysis of vertical site response. Natural soils in engineering scenarios are often subjected to various anisotropic stress states, and the role of such loading on M0 is a critical concern that remains incompletely understood. This paper presents a systematic experimental program aimed at addressing this issue. Using a triaxial apparatus, sand specimens initially isotropically consolidated were subjected to various anisotropic stress states, including triaxial compression and triaxial extension. The evolutions of M0 at different stress states were captured by exciting elastic compression waves through embedded bender-extender elements. The specimens were tested under a wide range of states in terms of void ratio, axial stress, and radial stress. The study demonstrates that the impact of stress anisotropy is complex, depending on the magnitude of the stress ratio, the loading mode, and the initial state of the specimen. A practical model is suggested for the improved characterization of M0 under the anisotropic stress states. This model considers two primary mechanisms that are associated with the effects of stress anisotropy.
{"title":"Small strain constrained modulus of dry sands: The impact of anisotropic loading","authors":"","doi":"10.1016/j.soildyn.2024.108957","DOIUrl":"10.1016/j.soildyn.2024.108957","url":null,"abstract":"<div><p>In recent years, there has been a growing recognition of the importance of vertical ground motions in the seismic design of engineering structures. A comprehensive understanding of the small-strain constrained modulus <em>M</em><sub><em>0</em></sub>, which is a key input soil parameter, is essential for conducting a reliable analysis of vertical site response. Natural soils in engineering scenarios are often subjected to various anisotropic stress states, and the role of such loading on <em>M</em><sub><em>0</em></sub> is a critical concern that remains incompletely understood. This paper presents a systematic experimental program aimed at addressing this issue. Using a triaxial apparatus, sand specimens initially isotropically consolidated were subjected to various anisotropic stress states, including triaxial compression and triaxial extension. The evolutions of <em>M</em><sub><em>0</em></sub> at different stress states were captured by exciting elastic compression waves through embedded bender-extender elements. The specimens were tested under a wide range of states in terms of void ratio, axial stress, and radial stress. The study demonstrates that the impact of stress anisotropy is complex, depending on the magnitude of the stress ratio, the loading mode, and the initial state of the specimen. A practical model is suggested for the improved characterization of <em>M</em><sub><em>0</em></sub> under the anisotropic stress states. This model considers two primary mechanisms that are associated with the effects of stress anisotropy.</p></div>","PeriodicalId":49502,"journal":{"name":"Soil Dynamics and Earthquake Engineering","volume":null,"pages":null},"PeriodicalIF":4.2,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142137022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-05DOI: 10.1016/j.soildyn.2024.108898
This paper proposes a re-centring and self-balanced inerter (RSBI). The rhombic linkage achieves self-balanced of the torque on the screw, which releases the constraints demanded at the end of the screw and reduces the working wastage and cost of the screw. The flywheel's re-centring feature is guaranteed by introducing a self-resetting spring and enhances the stability of the system. More specifically, firstly, the resonance analysis method provides the optimized mounting angle of the RSBI's rhombic linkage. Then, the user-friendly optimal design strategy of the four-parameter inerter system, are derived by applying the fixed-point theory, and the validity of the optimized parameters is verified by parameter and time history analysis. Finally, nonlinear model of the RSBI is performed to account for the nonlinearity due to the variation of the rhombic linkage angle at large working strokes. The nonlinear amplitude frequency response function of the system is obtained using the harmonic balance method and the working stroke of the inerter is classified by comparing it with the linear frequency response function. The device proposed in this paper provides a good control effect on the displacement and acceleration control of the main structure under multiple seismic waves. The nonlinearity of the device is appropriately exploited to almost double the working stroke of the inerter, which can effectively reduce the size of the device.
{"title":"Seismic performance analysis and optimization of a re-centring and self-balanced inerter driven by a rhombic linkage","authors":"","doi":"10.1016/j.soildyn.2024.108898","DOIUrl":"10.1016/j.soildyn.2024.108898","url":null,"abstract":"<div><p>This paper proposes a re-centring and self-balanced inerter (RSBI). The rhombic linkage achieves self-balanced of the torque on the screw, which releases the constraints demanded at the end of the screw and reduces the working wastage and cost of the screw. The flywheel's re-centring feature is guaranteed by introducing a self-resetting spring and enhances the stability of the system. More specifically, firstly, the resonance analysis method provides the optimized mounting angle of the RSBI's rhombic linkage. Then, the user-friendly optimal design strategy of the four-parameter inerter system, are derived by applying the fixed-point theory, and the validity of the optimized parameters is verified by parameter and time history analysis. Finally, nonlinear model of the RSBI is performed to account for the nonlinearity due to the variation of the rhombic linkage angle at large working strokes. The nonlinear amplitude frequency response function of the system is obtained using the harmonic balance method and the working stroke of the inerter is classified by comparing it with the linear frequency response function. The device proposed in this paper provides a good control effect on the displacement and acceleration control of the main structure under multiple seismic waves. The nonlinearity of the device is appropriately exploited to almost double the working stroke of the inerter, which can effectively reduce the size of the device.</p></div>","PeriodicalId":49502,"journal":{"name":"Soil Dynamics and Earthquake Engineering","volume":null,"pages":null},"PeriodicalIF":4.2,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142151450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-05DOI: 10.1016/j.soildyn.2024.108943
Due to the limited features and poor accuracy of current methods for predicting the dynamic response of subgrades, this paper proposes an innovative approach that combines subgrade dynamic response field tests and machine learning (ML) technology. This method uses Bayesian optimization XGBoost (BO-XGBoost), Bayesian optimization LightGBM (BO-LightGBM), and Bayesian optimization CatBoost (BO-CatBoost) models to analyze the effects of physical properties and stress conditions on the dynamic stress, dynamic acceleration, and dynamic displacement of the subgrade. The optimal ML model was selected on the basis of the residuals, coefficient of determination (R2), mean squared error (MSE), and mean absolute error of the prediction results. Using SHapley additive exPlanations (SHAP), the global importance, feature importance, and feature interaction behaviours of the optimal ML model input features were explained, and the main controlling features affecting the dynamic stress, dynamic acceleration, and dynamic displacement of the subgrade were obtained. The research results indicate that the prediction results of the BO-XGBoost, BO-LightGBM, and BO-CatBoost models for dynamic stress, dynamic acceleration, and dynamic displacement are mostly within the 10 % error range, and the R2 values of these three models are greater than 0.98. On the basis of the comparison results of the hyperparameter combinations, the objective of MSE (MSEobj), and the error evaluation metrics, the BO-CatBoost model yields the highest prediction accuracy, making it the optimal ML prediction model. This prediction method can quickly and intelligently obtain the main controlling features of dynamic stress, dynamic acceleration, and dynamic displacement, including depth (H), axle load (P), frequency (f), and moisture content (w). The boundary conditions for these four features are as follows: H > −1.3 m, P > 10 ton, f > 3.7 Hz, and w >18.1 %. The research results contribute to enhancing the service performance and lifespan of expressways.
{"title":"Prediction method for the dynamic response of expressway lateritic soil subgrades on the basis of Bayesian optimization CatBoost","authors":"","doi":"10.1016/j.soildyn.2024.108943","DOIUrl":"10.1016/j.soildyn.2024.108943","url":null,"abstract":"<div><p>Due to the limited features and poor accuracy of current methods for predicting the dynamic response of subgrades, this paper proposes an innovative approach that combines subgrade dynamic response field tests and machine learning (ML) technology. This method uses Bayesian optimization XGBoost (BO-XGBoost), Bayesian optimization LightGBM (BO-LightGBM), and Bayesian optimization CatBoost (BO-CatBoost) models to analyze the effects of physical properties and stress conditions on the dynamic stress, dynamic acceleration, and dynamic displacement of the subgrade. The optimal ML model was selected on the basis of the residuals, coefficient of determination (<em>R</em><sup>2</sup>), mean squared error (MSE), and mean absolute error of the prediction results. Using SHapley additive exPlanations (SHAP), the global importance, feature importance, and feature interaction behaviours of the optimal ML model input features were explained, and the main controlling features affecting the dynamic stress, dynamic acceleration, and dynamic displacement of the subgrade were obtained. The research results indicate that the prediction results of the BO-XGBoost, BO-LightGBM, and BO-CatBoost models for dynamic stress, dynamic acceleration, and dynamic displacement are mostly within the 10 % error range, and the <em>R</em><sup>2</sup> values of these three models are greater than 0.98. On the basis of the comparison results of the hyperparameter combinations, the objective of MSE (MSE<sub>obj</sub>), and the error evaluation metrics, the BO-CatBoost model yields the highest prediction accuracy, making it the optimal ML prediction model. This prediction method can quickly and intelligently obtain the main controlling features of dynamic stress, dynamic acceleration, and dynamic displacement, including depth (<em>H</em>), axle load (<em>P</em>), frequency (<em>f</em>), and moisture content (<em>w</em>). The boundary conditions for these four features are as follows: <em>H</em> > −1.3 m, <em>P</em> > 10 ton, <em>f</em> > 3.7 Hz, and <em>w</em> >18.1 %. The research results contribute to enhancing the service performance and lifespan of expressways.</p></div>","PeriodicalId":49502,"journal":{"name":"Soil Dynamics and Earthquake Engineering","volume":null,"pages":null},"PeriodicalIF":4.2,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142149071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}