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A constrained neural network model for soil liquefaction assessment with global applicability

Yifan ZHANG, Rui WANG, Jian-Min ZHANG, Jianhong ZHANG

《结构与土木工程前沿（英文）》 2020年 第14卷 第5期   页码 1066-1082 doi: 10.1007/s11709-020-0651-2

摘要： A constrained back propagation neural network (C-BPNN) model for standard penetration test based soil liquefaction assessment with global applicability is developed, incorporating existing knowledge for liquefaction triggering mechanism and empirical relationships. For its development and validation, a comprehensive liquefaction data set is compiled, covering more than 600 liquefaction sites from 36 earthquakes in 10 countries over 50 years with 13 complete information entries. The C-BPNN model design procedure for liquefaction assessment is established by considering appropriate constraints, input data selection, and computation and calibration procedures. Existing empirical relationships for overburden correction and fines content adjustment are shown to be able to improve the prediction success rate of the neural network model, and are thus adopted as constraints for the C-BPNN model. The effectiveness of the C-BPNN method is validated using the liquefaction data set and compared with that of several liquefaction assessment methods currently adopted in engineering practice. The C-BPNN liquefaction model is shown to have improved prediction accuracy and high global adaptability.

关键词： soil liquefaction assessment     case history dataset     constrained neural network model     existing knowledge    

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In situ-based assessment of soil liquefaction potential–Case study of an earth dam in Tunisia

Ikram GUETTAYA,Mohamed Ridha EL OUNI

《结构与土木工程前沿（英文）》 2014年 第8卷 第4期   页码 456-461 doi: 10.1007/s11709-014-0259-5

摘要： The present paper examines the evaluation of liquefaction potential of an earth dam foundation in Tunisia. The assessment of soil liquefaction was made using deterministic and probabilistic simplified procedures developed from several case histories. The data collected from the field investigation performed before and after the vibrocompaction are analyzed and the results are reported. The obtained results show that after vibrocompaction, a significant improvement of the soil resistance reduces the liquefaction potential of the sandy foundation. Indeed, in the untreated layers, the factor of safety drops below 1 which means that the soil is susceptible for liquefaction. However, in the compacted horizons, the values of exceed the unit which justifies the absence of liquefaction hazard of the foundation.

关键词： liquefaction     cone penetration test (CPT)     standard penetration test (SPT)     vibrcompaction     sand    

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Liquefaction assessment using microtremor measurement, conventional method and artificial neural network

Sadegh REZAEI,Asskar Janalizadeh CHOOBBASTI

《结构与土木工程前沿（英文）》 2014年 第8卷 第3期   页码 292-307 doi: 10.1007/s11709-014-0256-8

摘要： Recent researchers have discovered microtremor applications for evaluating the liquefaction potential. Microtremor measurement is a fast, applicable and cost-effective method with extensive applications. In the present research the liquefaction potential has been reviewed by utilization of microtremor measurement results in Babol city. For this purpose microtremor measurements were performed at 60 measurement stations and the data were analyzed by suing Nakmaura’s method. By using the fundamental frequency and amplification factor, the value of vulnerability index ( ) was calculated and the liquefaction potential has been evaluated. To control the accuracy of this method, its output has been compared with the results of Seed and Idriss [ ] method in 30 excavated boreholes within the study area. Also, the results obtained by the artificial neural network (ANN) were compared with microtremor measurement. Regarding the results of these three methods, it was concluded that the threshold value of liquefaction potential is . On the basis of the analysis performed in this research it is concluded that microtremors have the capability of assessing the liquefaction potential with desirable accuracy.

关键词： liquefaction     microtremor     vulnerability index     artificial neural networks (ANN)     microzonation    

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

Mahmood AHMAD, Xiao-Wei TANG, Jiang-Nan QIU, Feezan AHMAD, Wen-Jing GU

《结构与土木工程前沿（英文）》 2021年 第15卷 第2期   页码 490-505 doi: 10.1007/s11709-020-0669-5

摘要： 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 Netica. The 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 models. The performance measure indexes, namely, overall accuracy ( ), precision, recall, , 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 models. The 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 potential. The 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    

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A step forward towards a comprehensive framework for assessing liquefaction land damage vulnerability

Mahmood AHMAD, Xiao-Wei TANG, Jiang-Nan QIU, Feezan AHMAD, Wen-Jing GU

《结构与土木工程前沿（英文）》 2020年 第14卷 第6期   页码 1476-1491 doi: 10.1007/s11709-020-0670-z

摘要： 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 surface. This 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 model. The BBN-based LLDV model is developed by integrating multi-related factors of seismic soil liquefaction and its induced hazards using a machine learning (ML) algorithm-K2 and domain knowledge (DK) data fusion methodology. Compared 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 damage. The 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 development. The proposed model is simple to perform in practice and provides a step toward a more sophisticated liquefaction risk assessment modeling. This study also interprets the BBN model sensitivity analysis and most probable explanation of seismic soil liquefied sites based on an engineering point of view.

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

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Evaluation of liquefaction-induced lateral displacement using Bayesian belief networks

Mahmood AHMAD, Xiao-Wei TANG, Jiang-Nan QIU, Feezan AHMAD

《结构与土木工程前沿（英文）》 2021年 第15卷 第1期   页码 80-98 doi: 10.1007/s11709-021-0682-3

摘要： Liquefaction-induced lateral displacement is responsible for considerable damage to engineered structures during major earthquakes. Therefore, an accurate estimation of lateral displacement in liquefaction-prone regions is an essential task for geotechnical experts for sustainable development. This paper presents a novel probabilistic framework for evaluating liquefaction-induced lateral displacement using the Bayesian belief network (BBN) approach based on an interpretive structural modeling technique. The BBN models are trained and tested using a wide-range case-history records database. The two BBN models are proposed to predict lateral displacements for free-face and sloping ground conditions. The predictive performance results of the proposed BBN models are compared with those of frequently used multiple linear regression and genetic programming models. The results reveal that the BBN models are able to learn complex relationships between lateral displacement and its influencing factors as cause–effect relationships, with reasonable precision. This study also presents a sensitivity analysis to evaluate the impacts of input factors on the lateral displacement.

关键词： Bayesian belief network     seismically induced soil liquefaction     interpretive structural modeling     lateral displacement    

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A review of soil nematodes as biological indicators for the assessment of soil health

Qiaofang LU, Tongtong LIU, Nanqi WANG, Zhechao DOU, Kunguang WANG, Yuanmei ZUO

《农业科学与工程前沿（英文）》 2020年 第7卷 第3期   页码 275-281 doi: 10.15302/J-FASE-2020327

摘要：

Healthy soils are essential for sustainable agricultural development and soil health requires careful assessment with increasing societal concern over environmentally friendly agricultural development. Soil health is the capacity of soil to function within ecological boundaries to sustain productivity, maintain environmental quality, and promote plant and animal health. Physical, chemical and biological indicators are used to evaluate soil health; the biological indicators include microbes, protozoa and metazoa. Nematodes are the most abundant metazoa and they vary in their sensitivity to pollutants and environmental disturbance. Soil nematode communities are useful biological indicators of soil health, with community characteristics such as abundance, diversity, community structure and metabolic footprint all closely correlated with the soil environment. The community size, complexity and structure reflect the condition of the soil. Both free-living and plant-parasitic nematodes are effective ecological indicators, contributing to nutrient cycling and having important roles as primary, secondary and tertiary consumers in food webs. Tillage inversion, cropping patterns and nutrient management may have strong effects on soil nematodes, with changes in soil nematode communities reflecting soil disturbance. Some free-living nematodes serve as biological models to test soil condition in the laboratory and because of these advantages soil nematodes are increasingly being used as biological indicators of soil health.

关键词： biological indicators     community characteristics     soil health     soil nematodes    

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Ecotoxicity assessment of soil irrigated with domestic wastewater using different extractions

Wenyan LIANG,Lili SUI,Yuan ZHAO,Feizhen LI,Lijun LIU,Di XIE

《环境科学与工程前沿（英文）》 2015年 第9卷 第4期   页码 685-693 doi: 10.1007/s11783-014-0752-z

摘要： The toxicity of soil irrigated with treated domestic wastewater (site A) and untreated gray wastewater (site B) were investigated. Soil extracts were prepared using distilled water, acid solvent (0.1 mol·L HCl), and organic solvent (acetone:petroleum ether:cyclohexane= 1:1:1) to understand the type of pollutants responsible for the ecotoxicity associated with wastewater irrigation. The soil toxicity was assessed using a luminescence inhibition assay with for acute toxicity, a micronucleus assay with root tips and a single cell gel electrophoresis assay of mice lymphocytes for genotoxicity. The physicochemical properties and the heavy metal (HM) contents of the irrigated soil were also analyzed. The results indicated that the wastewater irrigation at site A had no effects on the soil properties. With the exception of Pb, Zn, Fe, and Mn, the accumulation of HMs (Cu, Ni, and Cr) occurred. However, the irrigation at site A did not result in obvious acute toxicity or genotoxicity in the soil. The soil properties changed greatly, and HMs (Cu, Ni, and Cr) accumulated in site B. There were significant increases in the acute toxic and genotoxic effects in the soils from site B. The ecotoxicity in site B came primarily from organic-extractable pollutants.

关键词： ecotoxicology     domestic wastewater     soil irrigation     risk assessment     organic extraction    

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Assessment of glass fiber-reinforced polyester pipe powder in soil improvement

《结构与土木工程前沿（英文）》 2021年 第15卷 第3期   页码 742-753 doi: 10.1007/s11709-021-0732-x

摘要： This study investigates the use of glass fiber-reinforced polyester (GRP) pipe powder (PP) for improving the bearing capacity of sandy soils. After a series of direct share tests, the optimum PP addition for improving the bearing capacity of soils was found to be 12%. Then, using the optimum PP addition, the bearing capacity of the soil was estimated through a series of loading tests on a shallow foundation model placed in a test box. The bearing capacity of sandy soil was improved by up to 30.7%. The ratio of the depth of the PP-reinforced soil to the diameter of the foundation model (H/D) of 1.25 could sufficiently strengthen sandy soil when the optimum PP ratio was used. Microstructural analyses showed that the increase in the bearing capacity can be attributed to the chopped fibers in the PP and their multiaxial distribution in the soil. Besides improving the engineering properties of soils, using PP as an additive in soils would reduce the accumulation of the industrial waste, thus providing a twofold benefit.

关键词： shallow foundation     sandy soil     bearing capacity     soil improvement     pipe powder    

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Machine learning-based seismic assessment of framed structures with soil-structure interaction

《结构与土木工程前沿（英文）》 2023年 第17卷 第2期   页码 205-223 doi: 10.1007/s11709-022-0909-y

摘要： The objective of the current study is to propose an expert system framework based on a supervised machine learning technique (MLT) to predict the seismic performance of low- to mid-rise frame structures considering soil-structure interaction (SSI). The methodology of the framework is based on examining different MLTs to obtain the highest possible accuracy for prediction. Within the MLT, a sensitivity analysis was conducted on the main SSI parameters to select the most effective input parameters. Multiple limit state criteria were used for the seismic evaluation within the process. A new global seismic assessment ratio was introduced that considers both serviceability and strength aspects by utilizing three different engineering demand parameters (EDPs). The proposed framework is novel because it enables the designer to seismically assess the structure, while simultaneously considering different EDPs and multiple limit states. Moreover, the framework provides recommendations for building component design based on the newly introduced global seismic assessment ratio, which considers different levels of seismic hazards. The proposed framework was validated through comparison using non-linear time history (NLTH) analysis. The results show that the proposed framework provides more accurate results than conventional methods. Finally, the generalization potential of the proposed framework was tested by investigating two different types of structural irregularities, namely, stiffness and mass irregularities. The results from the framework were in good agreement with the NLTH analysis results for the selected case studies, and peak ground acceleration (PGA) was found to be the most influential input parameter in the assessment process for the case study models investigated. The proposed framework shows high generalization potential for low- to mid-rise structures.

关键词： seismic hazard     artificial neural network     soil-structure interaction     seismic analysis    

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REGIONAL ASSESSMENT OF SOIL NITROGEN MINERALIZATION IN DIVERSE CROPLAND OF A REPRESENTATIVE INTENSIVE

《农业科学与工程前沿（英文）》 2023年 第10卷 第4期   页码 530-540 doi: 10.15302/J-FASE-2023515

摘要：

Soil nitrogen mineralization (Nmin) is a key process that converts organic N into mineral N that controls soil N availability to plants. However, regional assessments of soil Nmin in cropland and its affecting factors are lacking, especially in relation to variation in elevation. In this study, a 4-week incubation experiment was implemented to measure net soil Nmin rate, gross nitrification (Nit) rate and corresponding soil abiotic properties in five field soils (A–C, maize; D, flue-cured tobacco; and E, vegetables; with elevation decreasing from A to E) from different altitudes in a typical intensive agricultural area in Dali City, Yunnan Province, China. The results showed that soil Nmin rate ranged from 0.10 to 0.17 mg·kg−1·d−1 N, with the highest value observed in field E, followed by fields D, C, B, and A, which indicated that soil Nmin and Nit rates varied between fields, decreasing with elevation. The soil Nit rate ranged from 434.2 to 827.1 µg·kg−1·h−1 N, with the highest value determined in field D, followed by those in fields E, C, B, and A. The rates of soil Nmin and Nit were positively correlated with several key soil parameters, including total soil N, dissolved organic carbon and dissolved inorganic N across all fields, which indicated that soil variables regulated soil Nmin and Nit in cropland fields. In addition, a strong positive relationship was observed between soil Nmin and Nit. These findings provide a greater understanding of the response of soil Nmin among cropland fields related to spatial variation. It is suggested that the soil Nmin from cropland should be considered in the evaluation of the N transformations at the regional scale.

关键词： cropland     gross nitrification rate     regulatory factors     soil nitrogen mineralization     spatial variation    

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Experimental study of two saturated natural soils and their saturated remoulded soils under three consolidated undrained stress paths

Mingjing JIANG, Haijun HU, Jianbing PENG, Serge LEROUEIL

《结构与土木工程前沿（英文）》 2011年 第5卷 第2期   页码 225-238 doi: 10.1007/s11709-011-0108-8

摘要： In this paper, an experimental investigation is conducted to study the mechanical behavior of saturated natural loess, saturated natural filling in ground fissure and their corresponding saturated remoulded soils under three consolidated undrained triaxial stress tests, namely, conventional triaxial compression test (CTC), triaxial compression test (TC) and reduced triaxial compression test (RTC). The test results show that stress-strain relation, i.e. strain-softening or strain-hardening, is remarkably influenced by the structure, void ratio, stress path and confining pressure. Natural structure, high void ratio, TC stress path, RTC stress path and low confining pressures are favorable factors leading to strain-softening. Excess pore pressure during shearing is significantly affected by stress path. The tested soils are different from loose sand on character of strain-softening and are different from common clay on excess pore water pressure behavior. The critical states in ′– space in CTC, TC and RTC tests almost lie on one line, which indicates that the critical state is independent of the above stress paths. As for remoulded loess or remoulded filling, the critical state line (CSL) and isotropic consolidation line (ICL) in -log ′ space are almost straight, while for natural loess or natural filling, in -log ′ space there is a turning point on the CSL, which is similar to the ICL.

关键词： stress paths     static liquefaction     natural soil     remoulded soil     loess     structure     total strength indices     excess pore pressure    

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

Pijush SAMUI

《结构与土木工程前沿（英文）》 2013年 第7卷 第1期   页码 72-82 doi: 10.1007/s11709-013-0185-y

摘要： 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 engineering. This 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 earthquake. The SVM, a novel learning machine based on statistical theory, uses structural risk minimization (SRM) induction principle to minimize the error. Using cone resistance ( ) and cyclic stress ratio ( ), model has been developed for prediction of liquefaction using SVM. Further an attempt has been made to simplify the model, requiring only two parameters ( and maximum horizontal acceleration ), for prediction of liquefaction. Further, developed SVM model has been applied to different case histories available globally and the results obtained confirm the capability of SVM model. For 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 ( ) on number of support vector and model accuracy has also been investigated. The 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    

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Probability distributions of arsenic in soil from brownfield sites in Beijing (China): statistical characterizationof the background populations and implications for site assessment studies

Marina ACCORNERO,Lin JIANG,Eugenio NAPOLI,Marco CREMONINI,Giovanni FERRO,Federica BELLORO,Maosheng ZHONG

《环境科学与工程前沿（英文）》 2015年 第9卷 第3期   页码 465-474 doi: 10.1007/s11783-014-0678-5

摘要： A probabilistic analysis was performed on soil arsenic concentration data from 4 brownfield sites at Beijing (Chaoyang and Haidian Districts), involved in environmental assessment studies. The available data sets were processed to provide a statistical characterization of the background populations and differentiate “anomalous data” from the natural range of variation of arsenic concentrations in soil. The site-specific background distributions and the existing wide-scale background values defined for the Beijing area were compared, discussing related implications for the definition of metal contamination soil screening levels (SSLs) in site assessment studies. The statistical analysis of As data sets discriminated site-specific background populations, encompassing 88% to 94% of the sample data, from outliers values, associated with either subsoil natural enrichments or possible anthropogenic releases. Upper Baseline Concentration ( ) limits (+ 2 level), including most of the site-specific metal background variability, were derived based on the statistical characterization of the background populations. Sites in the Chaoyang South District area had values in the range 10.4–12.6 mg·kg . These ranges provide meaningful SSL values to be adopted for As in local site assessment studies. Using the wide-scale background value for the Beijing area would have erroneously classified most of the areas in the subject sites as potentially contaminated.

关键词： upper baseline concentration     site assessment     arsenic     probability plot    

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Nitrogen distribution in the products from the hydrothermal liquefaction of sp. and sp.

《化学科学与工程前沿（英文）》 2022年 第16卷 第6期   页码 985-995 doi: 10.1007/s11705-021-2126-y

摘要： The high contents of nitrogen-containing organic compounds in biocrude obtained from hydrothermal liquefaction of microalgae are one of the most concerned issues on the applications and environment. In the project, Chlorella sp. and Spirulina sp. were selected as raw materials to investigate the influence of different reaction conditions (i.e., reaction temperature, residence time, solid loading rate) on the distribution of nitrogen in the oil phase and aqueous phase. Three main forms of nitrogen-containing organic compounds including nitrogen-heterocyclic compounds, amide, and amine were detected in biocrudes. The contents of nitrogen-heterocyclic compounds decreased with temperature while amide kept increasing. The effect of residence time on the components of nitrogen-containing organic compounds was similar with that of temperature. However, the influence of solid loading rate was insignificant. Moreover, it was also found that the differences of amino acids in the protein components in the two microalgae might affect the nitrogen distribution in products. For example, nitrogen in basic amino acids of Spirulina sp. preferred to go into the aqueous phase comparing with the nitrogen in neutral amino acids of Chlorella sp. In summary, a brief reaction map was proposed to describe the nitrogen pathway during microalgae hydrothermal liquefaction.

关键词： microalgae     hydrothermal liquefaction     biocrude     nitrogen distribution    

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标题 作者 时间 类型 操作

A constrained neural network model for soil liquefaction assessment with global applicability

Yifan ZHANG, Rui WANG, Jian-Min ZHANG, Jianhong ZHANG

期刊论文

In situ-based assessment of soil liquefaction potential–Case study of an earth dam in Tunisia

Ikram GUETTAYA,Mohamed Ridha EL OUNI

期刊论文

Liquefaction assessment using microtremor measurement, conventional method and artificial neural network

Sadegh REZAEI,Asskar Janalizadeh CHOOBBASTI

期刊论文

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

Mahmood AHMAD, Xiao-Wei TANG, Jiang-Nan QIU, Feezan AHMAD, Wen-Jing GU

期刊论文

A step forward towards a comprehensive framework for assessing liquefaction land damage vulnerability

Mahmood AHMAD, Xiao-Wei TANG, Jiang-Nan QIU, Feezan AHMAD, Wen-Jing GU

期刊论文

Evaluation of liquefaction-induced lateral displacement using Bayesian belief networks

Mahmood AHMAD, Xiao-Wei TANG, Jiang-Nan QIU, Feezan AHMAD

期刊论文

A review of soil nematodes as biological indicators for the assessment of soil health

Qiaofang LU, Tongtong LIU, Nanqi WANG, Zhechao DOU, Kunguang WANG, Yuanmei ZUO

期刊论文

Ecotoxicity assessment of soil irrigated with domestic wastewater using different extractions

Wenyan LIANG,Lili SUI,Yuan ZHAO,Feizhen LI,Lijun LIU,Di XIE

期刊论文

Assessment of glass fiber-reinforced polyester pipe powder in soil improvement

期刊论文

Machine learning-based seismic assessment of framed structures with soil-structure interaction

期刊论文

REGIONAL ASSESSMENT OF SOIL NITROGEN MINERALIZATION IN DIVERSE CROPLAND OF A REPRESENTATIVE INTENSIVE

期刊论文

Experimental study of two saturated natural soils and their saturated remoulded soils under three consolidated undrained stress paths

Mingjing JIANG, Haijun HU, Jianbing PENG, Serge LEROUEIL

期刊论文

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

Pijush SAMUI

期刊论文

Probability distributions of arsenic in soil from brownfield sites in Beijing (China): statistical characterizationof the background populations and implications for site assessment studies

Marina ACCORNERO,Lin JIANG,Eugenio NAPOLI,Marco CREMONINI,Giovanni FERRO,Federica BELLORO,Maosheng ZHONG

期刊论文

Nitrogen distribution in the products from the hydrothermal liquefaction of sp. and sp.

期刊论文