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1.
Determination of liquefaction susceptibility of soil: a least square support vector machine approach
This article adopts least square support vector machine (LSSVM) for determination of liquefactions susceptibility of soil based on standard penetration test data. Two models (Models I and II) have been developed. For Model I, input variables are cyclic stress ratio and standard penetration test value (N). Model II employs peak ground acceleration and N as input variables. The developed LSSVM models (Models I and II) give equations for determination of liquefaction susceptibility of soil. The performances of Models I and II are the same. The developed LSSVM gives probabilistic output. The results of LSSVM have been compared with the artificial neural network model. This article shows that N and the peak ground acceleration are sufficient input parameters for determination of liquefaction susceptibility of soil. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
2.
Kumar Deepak Samui Pijush Kim Dookie Singh Anshuman 《Geotechnical and Geological Engineering》2021,39(2):1049-1058
In this research, deep learning (DL) model is proposed to classify the soil reliability for liquefaction. The applicability of the DL model is tested in comparison with emotional backpropagation neural network (EmBP). The database encompassing cone penetration test of Chi–Chi earthquake. This study uses cone resistance (qc) and peck ground acceleration as inputs for prediction of liquefaction susceptibility of soil. The performance of developed models has been assessed by using various parameters (receiver operating characteristic, sensitivity, specificity, Phi correlation coefficient, Precision–Recall F measure). The performance of DL is excellent. Consistent results obtained from the proposed deep learning model, compared to the EmBP, indicate the robustness of the methodology used in this study. In addition, both the developed model was also tested on global earthquake data. During validation on global data, both the models shows good results based on fitness parameters. The developed classification models a simple, but also efficient decision-making tool in engineering design to quantitatively assess the liquefaction potential. The finding of this paper can be further used to capture the relationship between soil and earthquake parameters.
相似文献3.
Least square support vector machine and relevance vector machine for evaluating seismic liquefaction potential using SPT 总被引：4，自引：1，他引：3
Pijush Samui 《Natural Hazards》2011,59(2):811-822
The determination of liquefaction potential of soil is an imperative task in earthquake geotechnical engineering. The current
research aims at proposing least square support vector machine (LSSVM) and relevance vector machine (RVM) as novel classification
techniques for the determination of liquefaction potential of soil from actual standard penetration test (SPT) data. The LSSVM
is a statistical learning method that has a self-contained basis of statistical learning theory and excellent learning performance.
RVM is based on a Bayesian formulation. It can generalize well and provide inferences at low computational cost. Both models
give probabilistic output. A comparative study has been also done between developed two models and artificial neural network
model. The study shows that RVM is the best model for the prediction of liquefaction potential of soil is based on SPT data. 相似文献
4.
The seismic performance of a tailings impoundment can be adversely affected by the behavior of the retained tailings. However, there remains considerable uncertainty in tailings liquefaction analysis. Twenty cyclic simple shear tests conducted on tailings from a gold mine in Quebec, Canada, were simulated numerically. The simulations indicated that the dynamic behavior of tailings could be modelled reasonably well, except that the weighted cyclic resistance curve of the tailings differed from that of clean sand which was used to develop the constitutive model (UBCSAND). An (N1)60-CS value of 10 blows/30 cm was estimated for the tailings based on calibration at a CSR of 0.10 for 15 cycles of loading. Numerical simulation of the behavior of a 20-m-high deposit of tailings during an earthquake (Mw = 5.9) indicated liquefaction of the upper 8 m of tailings. Liquefaction analysis using the Simplified method with published magnitude scaling factors (MSF) did not predict the occurrence of liquefaction. The use of MSF values calculated from the laboratory testing predicted liquefaction in the upper 8 m of tailings, corresponding quite well with the numerical simulation. The results indicate that both analytical and numerical methods can be used to evaluate the potential for tailings liquefaction under seismic loads. 相似文献
5.
The liquefaction potential of saturated cohesionless deposits in Guwahati city, Assam, was evaluated. The critical cyclic stress ratio required to cause liquefaction and the cyclic stress ratio induced by an earthquake were obtained using the simplified empirical method developed by Seed and Idriss (J soil Mech Found Eng ASCE 97(SM9):1249–1273, 1971, Ground motions and soil liquefaction during earthquakes. Earthquake Engineering Research Institute, Berkeley, CA, 1982) and Seed et al. (J Geotech Eng ASCE 109(3):458–483, 1983, J Geotech Eng ASCE 111(12):1425–1445, 1985) and the Idriss and Boulanger (2004) method. Critical cyclic stress ratio was based on the empirical relationship between standard penetration resistance and cyclic stress ratio. The liquefaction potential was evaluated by determining factor of safety against liquefaction with depth for areas in the city. A soil database from 200 boreholes covering an area of 262 km2 was used for the purpose. A design peak ground acceleration of 0.36 g was used since Guwahati falls in zone V according to the seismic zoning map of India. The results show that 48 sites in Guwahati are vulnerable to liquefaction according to the Seed and Idriss method and 49 sites are vulnerable to liquefaction according to the Idriss and Boulanger method. Results are presented as maps showing zones of levels of risk of liquefaction. 相似文献
6.
Application of the adaptive neuro-fuzzy inference system for prediction of soil liquefaction 总被引：1，自引：1，他引：0
The determination of liquefaction potential of soils induced by earthquake is a major concern and an essential criterion in the design process of the civil engineering structures. A purely empirical interpretation of the filed case histories relating to liquefaction potential is often not well constrained due to the complication associated with this problem. In this study, an integrated fuzzy neural network model, called Adaptive Neuro-Fuzzy Inference System (ANFIS), is developed for the assessment of liquefaction potential. The model is trained with large databases of liquefaction case histories. Nine parameters such as earthquake magnitude, the water table, the total vertical stress, the effective vertical stress, the depth, the peak acceleration at the ground surface, the cyclic stress ratio, the mean grain size, and the measured cone penetration test tip resistance were used as input parameters. The results revealed that the ANFIS model is a fairly promising approach for the prediction of the soil liquefaction potential and capable of representing the complex relationship between seismic properties of soils and their liquefaction potential. 相似文献
7.
Liquefaction potential (LP) assessment plays a significant role in damages due to earthquake. The spirit underlying the present work is the evaluation of LP by correlating most significant parameters reflecting the dynamic response of soil with actual field behavior wherein an attempt of integrating the effect of dynamic soil properties and ground motion parameters simulating the actual site conditions is being made. Accordingly, a dynamic response–based Elementary Empirical Liquefaction Model (EELM) is proposed by processing a total of 314 reported case records covering a wide range of parameters demarcating “yes” and “no” zones of liquefaction. The method to develop the EELM essentially consists of evaluation of liquefaction potential, defining functional form of EELM representing dynamic response of soil to earthquake shaking, collection of data, computation of model parameters and formulation followed by validation of the model. The proposed empirical model though in fundamental form is found to perform fairly well resulting into an overall success rate of 86 % for both liquefaction and non-liquefaction points with significantly high success rate of 98 % for liquefied cases. Comparison of predictive performance of the proposed EELM with other approaches shows higher efficiency and thus signifies the theme of employing integrated approach. 相似文献
8.
以剪切波速与地表峰值加速度为依据的地震液化确定性及概率判别法 总被引：2，自引：0，他引：2
剪切波速作为土性的基本参数,为评价土体抵抗地震液化的能力提供了一种方法。回顾了以剪切波速和地表峰值加速度为依据的场地地震液化判别方法的演化历史,依据他人收集的现场液化资料,合计49次地震、618例液化/不液化场地数据,提出了确定液化临界曲线的基本原则,给出了基于修正剪切波速与地表峰值加速度的液化临界曲线,验证了液化临界曲线的位置对细粒含量、有效上覆压力、震级等因素取值变化的合理性,分析了估计土层循环应力比CSR的剪应力折减系数、震级标定系数、有效上覆压力修正系数等因素的不确定性对液化临界曲线的敏感性。结果表明：液化临界曲线对各种影响因素具有很好的适用性。利用Monte Carlo模拟、加权最大似然法和加权经验概率法,给出了建议的液化临界曲线的名义抗液化安全系数与液化概率的经验关系式及概率等值线,并对核电厂Ⅰ类、Ⅱ类和Ⅲ类抗震物项地基,分别建议了相应的液化临界曲线。该方法以丰富的现场液化数据为依据,具有广泛的应用前景。 相似文献
9.
Probabilistic and spatial liquefaction analysis using CPT data: a case study for Alameda County site
Soil liquefaction is one of the major concerns causing damage to the structures in saturated sand deposits during earthquakes. Simplified methods for the assessment of liquefaction potential rely on the limit states that are generally established with built-in conservatism and a great deal of subjectivity. Well-known SPT- and CPT-based methods are widely used in the design practice for this purpose due to their simplicity and reasonable predictive capability. However, these methods do not account for various sources of uncertainties explicitly. Moreover, evaluations are made only at the locations of test results and are generalized for the whole region, which may not give accurate results where spatial variation of soil properties is significant. The present study focuses on the probabilistic evaluation of liquefaction potential of Alameda County site, California, considering spatial variation of soil indices related to CPT soundings. A stochastic soil model is adopted for this purpose using random field theory and principles of geostatistics by developing 2D exponential correlation functions. It has been observed that the probability of liquefaction is significantly underestimated as much as 34 %, if the spatial dependence of soil indices is not considered. Further, the effect of spatial variation is more prominent in low-level earthquakes compared to the high-level earthquakes, showing a 41.5 % deviation for magnitude 8.1 and a 60.5 % deviation for magnitude 5.0 earthquake at a depth of 10 m. 相似文献
10.
以标贯试验为依据的砂土液化确定性及概率判别法 总被引：1，自引：0，他引：1
核电厂址非基岩场地的地基液化问题是核电厂选址的关键问题,亟需建立核电厂址地基液化判别方法。回顾了以标贯试验和地表峰值加速度为依据的砂土液化判别方法的演化历史,依据Idriss-Boulanger确定液化临界曲线的基本方法,提出了确定液化临界曲线的基本原则,分别依据美国液化数据库、中国抗震规范液化判别式所用的液化数据及综合两者的液化数据资料,给出了相应的液化临界曲线,验证了液化临界曲线的位置对不同的细粒含量、有效上覆压力、现场试验方法的液化数据的合理性,分析了测量或估计土层循环应力比和修正标贯击数各种因素的不确定性对液化临界曲线的敏感性,结果表明：所提的液化临界曲线不易受各种因素的影响。利用Monte Carlo模拟、加权最大似然法和加权经验概率法,给出了液化临界曲线的名义抗液化安全系数与液化概率的经验关系式及概率等值线,并对核电厂Ⅰ类、Ⅱ类和Ⅲ类抗震物项地基,给出了相应的液化临界曲线。 相似文献
11.
Jiban K. Sarker Mehedi Ahmed Ansary Md. S. Rahman A. M. M. Safiullah 《Environmental Earth Sciences》2010,60(3):643-653
Mymensingh municipality lies in one of the most earthquake-prone areas of Bangladesh. The town was completely destroyed during
the Great Indian Earthquake of 12 June 1897, for which the surface-wave magnitude was 8.1. In this study the 1897 Great Indian
Earthquake was used as a scenario event for developing seismic microzonation maps for Mymensingh. For microzonation purposes
SPT data from 87 boreholes were collected from different relevant organizations. To verify those data ten boreholes of depth
up to 30 m were drilled. Intensity values obtained for different events were calibrated against attenuation laws to check
applicability to the study area. Vibration characteristics at diverse points of the study area were estimated by employing
the one-dimensional wave-propagation software SHAKE. SHAKE discretizes the soil profile into several layers and uses an iterative
technique to represent the non-linear behavior of the soil by adjusting the material properties at each iteration step. The
required input information includes depth, shear wave velocity, damping factor, and unit weight of each soil layer. The liquefaction
resistance factor and the resulting liquefaction potential were estimated to quantify the severity of liquefaction. Quantification
of secondary site effects and the weighting scheme for combining the various seismic hazards were heuristic, based on judgment
and expert opinion. 相似文献
12.
In this paper a new approach is presented, based on evolutionary polynomial regression (EPR), for determination of liquefaction potential of sands. EPR models are developed and validated using a database of 170 liquefaction and non-liquefaction field case histories for sandy soils based on CPT results. Three models are presented to relate liquefaction potential to soil geometric and geotechnical parameters as well as earthquake characteristics. It is shown that the EPR model is able to learn, with a very high accuracy, the complex relationship between liquefaction and its contributing factors in the form of a function. The attained function can then be used to generalize the learning to predict liquefaction potential for new cases not used in the construction of the model. The results of the developed EPR models are compared with a conventional model as well as a number of neural network-based models. It is shown that the proposed EPR model provides more accurate results than the conventional model and the accuracy of the EPR results is better than or at least comparable to that of the neural network-based models proposed in the literature. The advantages of the proposed EPR model over the conventional and neural network-based models are highlighted. 相似文献
13.
饱和砂土地震液化判别的可拓聚类预测方法 总被引：4，自引：0，他引：4
基于可拓学的物元模型和聚类分析原理,提出了饱和砂土地震液化判别的可拓聚类方法。选取地震烈度、震中距、砂层埋置深度、地下水位、标贯击数、平均粒径、不均匀系数和动剪应力比等8个影响因素,作为饱和砂土地震液化的评价因子,构建了经典域物元和节域物元。应用物元理论和可拓集合中的关联函数,建立预测模型,通过聚类分析得到饱和砂土地震液化的判别结果。实例研究表明,该模型能客观地反映砂土的液化规律,可拓聚类预测方法应用于饱和砂土地震液化判别是有效可行的。 相似文献
14.
为研究地震作用下饱和砂土液化判别及地震放大效应的影响因素,采用边界面塑性模型框架内开发的砂土本构模型,基于开源有限元平台OpenSees建立了一维剪切梁土柱模型。以循环应力比CSR和循环抗力比CRR为控制指标,对比了不同液化判别方法的差异,分析了地震荷载类型和砂土相对密度对液化判别和放大效应的影响。研究表明:与数值模拟结果相比,Seed简化法计算的CSR更大,判断饱和砂土场地发生液化的可能性更高;冲击型地震波较振动型地震波更容易使饱和砂土场地发生液化,砂土相对密度越小场地越容易发生液化;放大系数随埋深的减小而增大,振动型地震波引起的放大效应整体大于冲击型,埋深较大时放大系数随砂土相对密度的增大而减小。 相似文献
15.
This paper proposes a systematic framework for real-time assessment of spatial liquefaction hazard of port areas considering local seismic response characteristics based on a geographic information system (GIS) platform. The framework is integrated and embedded with sequential, interrelated subprocedures and a database for liquefaction-induced damage evaluation that standardizes and both individually and collectively quantifies analytical results. To integrate the current in situ condition of a selected port area, the framework functions as a spatial database system for geotechnical and structural data and as a recipient of automatic transmission of seismic monitoring data. The geotechnical profile correlated with liquefaction potential is compiled into a geotechnical spatial grid built by geostatistical methods. Linked with the geotechnical spatial grid, the processing of site-specific responses is automatically interpreted from previously derived correlations between rock acceleration and maximum acceleration of each soil layer. As a result, the liquefaction severity is determined based on a combined geotechnical spatial grid with seismic load correlation in real-time according to a simplified procedure, allowing calculation of the liquefaction potential index (LPI). To demonstrate practical applications of the framework in estimating the liquefaction hazard in real-time, liquefaction-hazard maps were visualized for two earthquake scenarios, verifying the applicability of the proposed framework. 相似文献
16.
Liquefaction of loose, saturated granular soils during earthquakes poses a major hazard in many regions of the world. The determination of liquefaction potential of soils induced by earthquake is a major concern and an essential criterion in the design process of the civil engineering structures. A large number of factors that affect the occurrence of liquefaction during earthquake exist a form of uncertainty of non-statistical nature. Fuzzy systems are used to handle uncertainty from the data that cannot be handled by classical methods. It uses the fuzzy set to represent a suitable mathematical tool for modeling of imprecision and vagueness. The pattern classification of fuzzy classifiers provides a means to extract fuzzy rules for information mining that leads to comprehensible method for knowledge extraction from various information sources. Therefore, it is necessary to handle the soil liquefaction problem in a rational framework of fuzzy set theory. This study investigates the feasibility of using fuzzy comprehensive evaluation model for predicting soil liquefaction during earthquake. In the fuzzy comprehensive evaluation model of soil liquefaction, the following factors, such as earthquake intensity, standard penetration number, mean diameter and groundwater table, are selected as the evaluating indices. The results show that the method is a useful tool to assess the potential of soil liquefaction. 相似文献
17.
India is prone to earthquake hazard; almost 65 % area falls in high to very high seismic zones, as per the seismic zoning map of the country. The Himalaya and the Indo-Gangetic plains are particularly vulnerable to high seismic hazard. Any major earthquake in Himalaya can cause severe destruction and multiple fatalities in urban centers located in the vicinity. Seismically induced ground motion amplification and soil liquefaction are the two main factors responsible for severe damage to the structures, especially, built on soft sedimentary environment. These are essentially governed by the size of earthquake, epicentral distance and geology of the area. Besides, lithology of the strata, i.e., sediment type, grain size and their distribution, thickness, lateral discontinuity and ground water depth, play an important role in determining the nature and degree of destruction. There has been significant advancement in our understanding and assessment of these two phenomena. However, data from past earthquakes provide valuable information which help in better estimation of ground motion amplification and soil liquefaction for evaluation of seismic risk in future and planning the mitigation strategies. In this paper, we present the case studies of past three large Indian earthquakes, i.e., 1803 Uttaranchal earthquake (Mw 7.5); 1934 Bihar–Nepal earthquake (Mw 8.1) and 2001 Bhuj earthquake (Mw 7.7) and discuss the role of soft sediments particularly, alluvial deposits in relation to the damage pattern due to amplified ground motions and soil liquefaction induced by the events. The results presented in the paper are mainly focused around the sites located on the river banks and experienced major destruction during these events. It is observed that the soft sedimentary sites located even far from earthquake epicenter, with low water saturation, experienced high ground motion amplification; while the sites with high saturation level have undergone soil liquefaction. We also discuss the need of intensifying studies related to ground motion amplification and soil liquefaction in India as these are the important inputs for detailed seismic hazard estimation. 相似文献
18.
Filippo Santucci de Magistris Giovanni Lanzano Giovanni Forte Giovanni Fabbrocino 《Natural Hazards》2014,74(2):1069-1094
National and international seismic codes and recommendations provide criteria for liquefaction exclusion based on a peak ground acceleration (PGA) threshold value. In this paper, after a brief review of the procedures and the values suggested in those documents, a database of liquefaction case histories was created, exploiting the background data used in the most relevant verification charts, currently employed in research and professional practice. This dataset was used to identify, on the basis of simple statistical analyses, a PGA threshold on the free ground surface below which liquefaction is unlikely to occur, regardless of the geological site conditions. The calculated value, which is on the order of 0.07–0.1 g, based on the model employed to fit the data, was analyzed in light of information collected during the 2012 Emilia seismic sequence in Italy, which produced many liquefaction events triggered by low acceleration values. The case history of the Emilia earthquake advises setting a PGA threshold for code and recommendations at the lower probability level of occurrence, in the order of 1 %. 相似文献
19.
20.
This article examines the capability of Minimax Probability Machine (MPM) for the determination of stability of slope. MPM is constructed within a probabilistic framework. This study uses MPM as classification and regression tools. Unit weight (γ), cohesion (c), angle of internal friction (φ), slope angle (β), height (H) and pore water pressure coefficient (ru) have been used as inputs of the MPM model. The outputs of MPM are stability status of slope and factor of safety (F). The results of MPM have been compared with the artificial neural network models. The experimental results demonstrate that the developed MPM is a promising tool for the determination of stability of slope. 相似文献