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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

Improved Prediction of Slope Stability under Static and Dynamic Conditions Using Tree-BasedModels

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Computer Modeling in Engineering & Sciences 2023年第10期137卷 455-487页

作者： Feezan ahmad Xiaowei Tang Jilei Hu mahmood ahmad Behrouz Gordan State Key Laboratory of Coastal and Offshore Engineering Dalian University of TechnologyDalian116024China Key Laboratory of Geological Hazards on Three Gorges Reservoir Area Ministry of EducationChina Three Gorges UniversityYichang443002China Department of Civil Engineering Faculty of EngineeringInternational Islamic University MalaysiaJalan GombakSelangor50728Malaysia Department of Civil Engineering University of Engineering and Technology Peshawar(Bannu Campus)Bannu28100Pakistan Faculty of Civil Engineering Islamic Azad UniversityVaramin Pishva BranchTehran15914Iran

Slope stability prediction plays a significant role in landslide disaster prevention and *** paper’s reduced error pruning(REP)tree and random tree(RT)models are developed for slope stability evaluation and meeting the high precision and rapidity requirements in slope *** data set of this study includes five parameters,namely slope height,slope angle,cohesion,internal friction angle,and peak ground *** available data is split into two categories:training(75%)and test(25%)*** output of the RT and REP tree models is evaluated using performance measures including accuracy(Acc),Matthews correlation coefficient(Mcc),precision(Prec),recall(Rec),and *** applications of the aforementionedmethods for predicting slope stability are compared to one another and recently established soft computing models in the *** analysis of the Acc together with Mcc,and F-score for the slope stability in the test set demonstrates that the RT achieved a better prediction performance with(Acc=97.1429%,Mcc=0.935,F-score for stable class=0.979 and for unstable case F-score=0.935)succeeded by the REP tree model with(Acc=95.4286%,Mcc=0.896,F-score stable class=0.967 and for unstable class F-score=0.923)for the slope stability dataset The analysis of performance measures for the slope stability dataset reveals that the RT model attains comparatively better and reliable results and thus should be encouraged in further research.

关键词： Slope stability seismic excitation static condition random tree reduced error pruning tree

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

Comparison of bioavailability and pharmacokinetics of diclofenac sodium and diclofenac potassium in normal and dehydrated rabbits

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药学学报 2009年第1期44卷 80-84页

作者： mahmood ahmad Muhammad IQBAL Ghulam MURTAZA Department of Pharmacy Faculty of Pharmacy and Alternative Medicines the lslamia University of Bahawalpur Bahawalpur 63100 Pakistan

Two different salts of diclofenac,diclofenac sodium and diclofenac potassium,in tablet dosage form were tested for their bioavailability and disposition kinetics in a group of eighteen rabbits in normal and experimentally induced dehydrated conditions with a wash out period of 7 days between both stages of *** and physiological parameters were also measured in both normal and dehydrated *** levels in plasma were determined using a validated reversed phase HPLC *** kinetic parameters ***0-∞,Cmax,Tmax and other disposition kinetics were obtained with non-compartmental *** parameters *** cell volume,plasma glucose and total lipid concentration in dehydrated rabbits increased *** concentration of diclofenac sodium and diclofenac potassium decreased significantly in water deprived *** comparison,diclofenac potassium in normal and dehydrated state of the same group of rabbits showed a significantly increased plasma concentration when compared with diclofenac sodium.

关键词：生物药效率药物动力学药物化学生物化学

Pharmacokinetic modelling of microencapsulated metronidazole

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药学学报 2009年第6期44卷 674-679页

作者： mahmood ahmad Khalid PERVAIZ Ghulam MURTAZA Munaza RAMZAN Department of Pharmacy Faculty of Pharmacy and Alternative Medicines Department of Mathematics The Islamia University of Bahawalpur

The aim of present study is to develop a pharmacokinetic model for microencapsulated metroni- dazole to predict drug absorption pattern in healthy human and validate this model internally. Metronidazole was microencapsulated into ethylcellulose shells followed by the conversion of these microcapsules into tablets. Dissolution study of tablets was conducted in 450 mL double distilled water, 0.1 mol·L-1 HCl and phosphate buffer (pH 6.8) maintained at (37 ± 0.5) ℃ using USP apparatus II at 50, 100 and 150 r·min-1. Three metronidazole tablets (T1: fast release, T2: moderate release, T3: slow release and reference) were administered to twenty four healthy human volunteers and serial blood samples were collected for 12 hours followed by their analysis using RP-HPLC. Drug release data were analyzed by various model dependent and independent approaches. Drug absorbed (%) was determined by Wagner-Nelson method from plasma concentration profile. Internal predictability was checked from Cmax and AUC. Optimum dissolution profile was observed in double distilled water and 50 r·min-1. A good level A correlation was observed between drug dissolution and absorption profiles (correlation coefficient, R2 = 0.900 9, 0.942 6, 0.901 5 and 0.932 for T1, T2, T3 and reference, respectively). Internal predictability was found less than 10%. Good correlation coefficients and low prediction errors elaborate the validity of this mathematical in-vitro in-vivo correlation model as a predictive tool for the determination of pharmacokinetics from dissolution data.

关键词：药物分析药物化学药物吸收磷酸盐缓冲液

Seismic Liquefaction Resistance Based on Strain Energy Concept Considering Fine Content Value Effect and Performance Parametric Sensitivity Analysis

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Computer Modeling in Engineering & Sciences 2023年第4期135卷 733-754页

作者： Nima Pirhadi Xusheng Wan Jianguo Lu Jilei Hu mahmood ahmad Farzaneh Tahmoorian School of Civil Engineering and Geomatics Southwest Petroleum UniversityChengdu610500China Key Laboratory of Geological Hazards on ThreeGorges ReservoirArea Ministry of EducationChina Three Gorges UniversityYichang443002China College of Civil Engineering&Architecture China Three Gorges UniversityYichang443002China Department of Civil Engineering Faculty of EngineeringInternational Islamic University MalaysiaJalan GombakSelangor50728Malaysia Department of Civil Engineering University of Engineering and Technology Peshawar(Bannu Campus)Bannu28100Pakistan Central Queensland University Queensland4740Australia

Liquefaction is one of the most destructive phenomena caused by earthquakes,which has been studied in the issues of potential,triggering and hazard *** strain energy approach is a common method to investigate liquefaction *** this study,two Artificial Neural Network(ANN)models were developed to estimate the liquefaction resistance of sandy soil based on the capacity strain energy concept(W)by using laboratory test data.A large database was collected from the *** group of the dataset was utilized for validating the process in order to prevent overtraining the presented *** investigate the complex influence of fine content(FC)on liquefaction resistance,according to previous studies,the second database was arranged by samples with FC of less than 28%and was used to train the second ANN ***,two presented ANN models in this study,in addition to four extra available models,were applied to an additional 20 new samples for comparing their results to show the capability and accuracy of the presented models ***,a parametric sensitivity analysis was performed through Monte Carlo Simulation(MCS)to evaluate the effects of parameters and their uncertainties on the liquefaction resistance of *** to the results,the developed models provide a higher accuracy prediction performance than the previously *** sensitivity analysis illustrated that the uncertainties of grading parameters significantly affect the liquefaction resistance of soils.

关键词： Liquefaction resistance capacity strain energy artificial neural network sensitivity analysis Monte Carlo Simulation

An assessment of k-εturbulence models for gas distribution analysis

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Nuclear Science and Techniques 2017年第10期28卷 87-94页

作者： Muhammad Saeed Ji-Yang Yu Aniseh Ahmed Atef AbdaUa Xian-Ping Zhong mahmood ahmad Ghazanfar Department of Engineering Physics Tsinghua UniversityBeijing 100084China

This paper presents the gas distribution analysis by injecting air fountain into the containment and simulations with the HYDRAGON code. Turbulence models of standard k-ε(SKE), re-normalization group k-ε(RNG) and a realizable k-ε(RLZ) are used to assess the effects on the gas distribution analysis during a severe accident in a nuclear power plant. By comparing with experimental data,the simulation results of the RNG and SKE turbulence models agree well with the experimental data on the prediction of dimensionless density distributions. The results illustrate that the turbulence model choice had a small effect on the simulation results, particularly the region near to the air fountain source.

关键词：湍流模型气体分布实验数据严重事故重整化群分布检测 RNG 空气源

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

A numerical study of fracture initiation under different loads during hydraulic fracturing

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Journal of Central South University 2020年第12期27卷 3875-3887页

作者： TANG Shi-bin DONG Zhuo WANG Jia-xu mahmood 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

The fracture initiation behavior for hydraulic fracturing treatments highlighted the necessity of proposing fracture criteria that precisely predict the fracture initiation type and location during the hydraulic fracturing *** the present study,a Mohr-Coulomb criterion with a tensile cut-off is incorporated into the finite element code to determine the fracture initiation type and location during the hydraulic fracturing *** fracture criterion considers the effect of fracture inclination angle,the internal friction angle and the loading conditions on the distribution of stress field around the fracture *** results indicate that the internal friction angle resists the shear fracture ***,as the internal friction angle increases,greater external loads are required to maintain the hydraulic fracture *** to the increased pressure of the injected water,the tensile fracture ultimately determines the fracture initiation ***,the shear fracture preferentially occurs as the stress anisotropy coefficient *** the maximum tensile stress and equivalent maximum shear stress decrease as the stress anisotropy coefficient increases,which indicates that the greater the stress anisotropy coefficient,the higher the external loading required to propagate a new *** numerical results obtained in this paper provide theoretical supports for establishing basis on investigating of the hydraulic fracturing characteristics under different conditions.

关键词： hydraulic fracturing internal friction angle stress anisotropy coefficient finite element method