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Application of machine learning algorithms for the evaluation of seismic soil liquefaction potential

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Frontiers of Structural and Civil Engineering 2021年第2期15卷 490-505页

作者： Mahmood AHMAD Xiao-Wei TANG Jiang-Nan QIU Feezan AHMA Wen-Jing GU State Key Laboratory of Coastal and Offshore Engineering Dalian University of TechnologyDalian 116024China Department of Civil Engineering University of Engineering and Technology Peshawar(Bannu Campus)Bannu 28100Pakistan School of Economics&Management Dalian University of TechnologyDalian 116024China Department of Civil Engineering Abasyn UniversityPeshawar 25000Pakistan

This study investigates the performance of four machine learning(ML)algorithms to evaluate the earthquake-induced liquefaction potential of soil based on the cone penetration test field case history records using the Bayesian belief network(BBN)learning software *** BBN structures that were developed by ML algorithms-K2,hill climbing(HC),tree augmented naive(TAN)Bayes,and Tabu search were adopted to perform parameter learning in Netica,thereby fixing the BBN *** performance measure indexes,namely,overall accuracy(OA),precision,recall,F-measure,and area under the receiver operating characteristic curve,were used to evaluate the training and testing BBN models’performance and highlight the capability of the K2 and TAN Bayes models over the Tabu search and HC *** sensitivity analysis results showed that the cone tip resistance and vertical effective stress are the most sensitive factors,whereas the mean grain size is the least sensitive factor in the prediction of seismic soil liquefaction *** results of this study can provide theoretical support for researchers in selecting appropriate ML algorithms and improving the predictive performance of seismic soil liquefaction potential models.

关键词： seismic soil liquefaction Bayesian belief network cone penetration test parameter learning structural learning

A step forward towards a comprehensive framework for assessing liquefaction land damage vulnerability:Exploration from historical data

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Frontiers of Structural and Civil Engineering 2020年第6期14卷 1476-1491页

作者： Mahmood AHMAD Xiao-Wei TANG Jiang-Nan QIU Feezan AHMAD Wen-Jing GU State Key Laboratory of Coastal and Ofishore Engineering Dalian University of TechnologyDalian 116024China Department of Civil Engineering University of Engineering and Technology Peshawar(Bannu Campus)Bannu 28100Pakistan School of Economics&Management Dalian University of TechnologyDalian 116024China Deparment of Civil Enginering Abasyn UniversitPeshawar 25000Pakistan

The unprecedented liquefaction-related land damage during earthquakes has highlighted the need to develop a model that better interprets the liquefaction land damage vulnerability(LLDV)when determining whether liquefaction is likely to cause damage at the ground's *** paper presents the development of a novel comprehensive framework based on select case history records of cone penetration tests using a Bayesian belief network(BBN)methodology to assess seismic soil liquefaction and liquefaction land damage potentials in one *** BBN-based LLDV model is developed by integrating multi-related factors of seismic soil liquefaction and its induced hazards using a machine learming(ML)algorithm-K2 and domain knowledge(DK)data fusion *** with the C4.5 decision tree-J48 model,naive Bayesian(NB)classifier,and BBN-K2 ML prediction methods in terms of overall accuracy and the Cohen's kappa coefficient,the proposed BBN K2 and DK model has a better performance and provides a substitutive novel LLDV framework for characterizing the vulnerability of land to liquefaction-induced *** proposed model not only predicts quantitatively the seismic soil liquefaction potential and its ground damage potential probability but can also identify the main reasons and fault-finding state combinations,and the results are likely to assist in decisions on seismic risk mitigation measures for sustainable *** proposed model is simple to perform in practice and provides a step toward a more sophisticated liquefaction risk assessment *** study also interprets the BBN model sensitivity analysis and most probable explanation of seismic soil liquefed sites based on an engineering point of view.

关键词： Bayesian belief network liquefaction-induced damage potential cone penetration test soil liquefaction structural leaming and domain knowledge

Seismic liquefaction potential assessment by using relevance vector machine

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Earthquake Engineering and Engineering Vibration 2007年第4期6卷 331-336页

作者： Pijush Samui Department of Civil Engineering Indian Institute of Science Bangalore 560012 India

Determining the liquefaction potential of soil is important in earthquake engineering. This study proposes the use of the Relevance Vector Machine （RVM） to determine the liquefaction potential of soil by using actual cone penetration test （CPT） data. RVM is based on a Bayesian formulation of a linear model with an appropriate prior that results in a sparse representation. The results are compared with a widely used artificial neural network （ANN） model. Overall, the RVM shows good performance and is proven to be more accurate than the ANN model. It also provides probabilistic output. The model provides a viable tool for earthquake engineers to assess seismic conditions for sites that are susceptible to liquefaction.

关键词： liquefaction cone penetration test relevance vector machine artificial neural network

Assessment of rapid impact compaction in ground improvement from in-situ testing

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Journal of Central South University 2013年第3期20卷 786-790页

作者： M.M.Mohammed H.Roslan S.Firas Department of Civil Engineering Faculty of EngineeringUniversity of MalayaKuala Lumpur 50603Malaysia

Ground improvement has been used on many construction sites to densify granular materials, in other word, to improve soil properties and reduce potential settlement. This work presents a case study of ground improvement using rapid impact compaction （RIC）. The research site comprises the construction of workshop and depots as part of railway development project at Batu Gajah-Ipoh, Malaysia. In-situ testing results show that the subsurface soil comprises mainly of sand and silty sand through the investigated depth extended to 10 m. Groundwater is approximately 0.5 m below the ground surface. Evaluation of improvement was based on the results of pre- and post-improvement cone penetration test （CPT）. Interpretation software has been used to infer soil properties. Load test was conducted to estimate soil settlement. It is found that the technique succeeds in improving soil properties namely the relative density increases from 45% to 70%, the friction angle of soil is increased by an average of 3°, and the soil settlement is reduced by 50%： The technique succeeds in improving soil properties to approximately 5.0 m in depth depending on soil uniformity with depth.

关键词： cone penetration test granular soil compaction rapid impact compaction relative density settlement improvement depth in-situ testing

Assessment of clay stiffness and strength parameters using index properties

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Journal of Rock Mechanics and Geotechnical Engineering 2018年第3期10卷 579-593页

作者： Sayed M.Ahmed Structural Engineering Department Ain Shams University

A new approach is developed to determine the shear wave velocity in saturated soft to firm clays using measurements of the liquid limit, plastic limit, and natural water content with depth. The shear wave velocity is assessed using the site-specific variation of the natural water content with the effective mean stress. Subsequently, an iterative process is envisaged to obtain the clay stiffness and strength *** at-rest earth pressure coefficient, as well as bearing capacity factor and rigidity index related to the cone penetration test, is also acquired from the analyses. Comparisons are presented between the measured clay parameters and the results of corresponding analyses in five different case studies. It is demonstrated that the presented approach can provide acceptable estimates of saturated clay stiffness and strength parameters. One of the main privileges of the presented methodology is the site-specific procedure developed based on the relationships between clay strength and stiffness parameters, rather than adopting direct correlations. Despite of the utilized iterative processes, the presented approach can be easily implemented using a simple spreadsheet, benefiting both geotechnical researchers and practitioners.

关键词： Soft to firm clays Atterberg limits Shear wave velocity Small-strain shear modulus Constrained modulus Undrained shear strength Effective friction angle cone penetration test

Liquefaction prediction using support vector machine model based on cone penetration data

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Frontiers of Structural and Civil Engineering 2013年第1期7卷 72-82页

作者： Pijush SAMUI Centre for Disaster Mitigation and Management VIT UniversityVellore-632014India

A support vector machine(SVM)model has been developed for the prediction of liquefaction susceptibility as a classification problem,which is an imperative task in earthquake *** paper examines the potential of SVM model in prediction of liquefaction using actual field cone penetration test(CPT)data from the 1999 Chi-Chi,Taiwan *** SVM,a novel learning machine based on statistical theory,uses structural risk minimization(SRM)induction principle to minimize the *** cone resistance(q_(c))and cyclic stress ratio(CSR),model has been developed for prediction of liquefaction using *** an attempt has been made to simplify the model,requiring only two parameters(q_(c)and maximum horizontal acceleration a_(max)),for prediction of ***,developed SVM model has been applied to different case histories available globally and the results obtained confirm the capability of SVM *** Chi-Chi earthquake,the model predicts with accuracy of 100%,and in the case of global data,SVM model predicts with accuracy of 89%.The effect of capacity factor(C)on number of support vector and model accuracy has also been *** study shows that SVM can be used as a practical tool for prediction of liquefaction potential,based on field CPT data.

关键词： earthquake cone penetration test liquefaction support vector machine(SVM) prediction

Prediction of the shear wave velocity Vs from CPT and DMT at research sites

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Frontiers of Structural and Civil Engineering 2014年第1期8卷 83-92页

作者： Amoroso SARA Department of Seismology and Tectonophysics Istituto Nazionale di Geofisica e Vulcanologia L'Aquila 67100 Italy

The paper examines the correlations to obtain rough estimates of the shear wave velocity Vs from non- seismic dilatometer tests （DMT） and cone penetration tests （CPT）. While the direct measurement of Vs is obviously preferable, these correlations may turn out useful in various circumstances. The experimental results at six international research sites suggest that the DMT predictions of Vs from the parameters ID （material index）, KD （horizontal stress index）, MDMT （constrained modulus） are more reliable and consistent than the CPT predictions from qc （cone resistance）, presumably because of the availability, by DMT, of the stress history index KD.

关键词： horizontal stress index shear wave velocity flat dilatometer test cone penetration test

A hybrid approach for evaluating CPT-based seismic soil liquefaction potential using Bayesian belief networks

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Journal of Central South University 2020年第2期27卷 500-516页

作者： MAHMOOD Ahmad TANG Xiao-wei QIU Jiang-nan GU Wen-jing FEEZAN Ahmad State Key Laboratory of Coastal and Offshore Engineering Dalian University of TechnologyDalian 116024China Department of Civil Engineering University of Engineering and Technology Peshawar(Bannu Campus)Bannu 28100Pakistan Faculty of Management and Economics Dalian University of TechnologyDalian 116024China Department of Civil Engineering Abasyn UniversityPeshawar 25000Pakistan

Discernment of seismic soil liquefaction is a complex and non-linear procedure that is affected by diversified factors of uncertainties and *** Bayesian belief network(BBN)is an effective tool to present a suitable framework to handle insights into such uncertainties and cause–effect *** intention of this study is to use a hybrid approach methodology for the development of BBN model based on cone penetration test(CPT)case history records to evaluate seismic soil liquefaction *** this hybrid approach,naive model is developed initially only by an interpretive structural modeling(ISM)technique using domain knowledge(DK).Subsequently,some useful information about the naive model are embedded as DK in the K2 algorithm to develop a BBN-K2 and DK *** results of the BBN models are compared and validated with the available artificial neural network(ANN)and C4.5 decision tree(DT)models and found that the BBN model developed by hybrid approach showed compatible and promising results for liquefaction potential *** BBN model developed by hybrid approach provides a viable tool for geotechnical engineers to assess sites conditions susceptible to seismic soil *** study also presents sensitivity analysis of the BBN model based on hybrid approach and the most probable explanation of liquefied sites,owing to know the most likely scenario of the liquefaction phenomenon.

关键词： Bayesian belief network cone penetration test seismic soil liquefaction interpretive structural modeling structural learning

In Situ tests--Predicted vs. Observed Settlements： A Comparative Case Study

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Journal of Civil Engineering and Architecture 2014年第7期8卷 824-832页

作者： Neritan Shkodrani Ergys Anamali Luisa Dhimitri Shpresa Gashi Department of Civil Engineering Faculty of Civil Engineering Polytechnic University of Tirana Tirane 1001 Albania Unit of Geotechnical Engineering T.T. Soil & Earthquake Consulting Tirane 1001 Albania

This paper aims to deal with the comparison of the estimated settlements derived by in situ tests with the observed settlements in site, in order to evaluate the accuracy of settlement prediction by in situ tests, in comparison not only with site observation by topographic means, but also with the values of settlements derived by numerical analysis by means of PLAXIS 2D and 3 D. The site where are carried out the tests and periodically are observed the settlements since the beginning of construction process, is located in the Oil Product Terminal, at the industrial park of Porto Romano, Durres, Albania. The main purpose of this project was the ground improvement by using preloading method in order to prevent liquefaction process and settlements. The data used to conduct this study are taken by the site investigation done after inserting into the soil vertical drains made of columns of free--draining gravel （gravel pile drains） until 14 m depth and center-to-center spacing of 2 m, and wick drains （premanufactured） until 25 m depth and center-to-center spacing of 1.8 m. The observed settlements are periodically measured by topographic equipments. This paper will present the conclusions derived by settlement analyzes from in situ tests and site observations.

关键词： Settlements cone penetration test dilatometer test constrained modulus.