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采石场粉尘和海砂混合物力学性能试验和数值研究

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岩土力学 2024年第9期45卷 2728-2740页

作者： tiep pham duc TU Nguyen Van PHONG pham duc CHINH Mai Viet PHONG Nguyen Viet 越南勒奎东技术大学特殊工程技术研究所河内越南

越南等发展中国家的道路基础设施建设需要大量天然砂。河砂日益紧缺,其供应量将持续下降。因此,建筑行业必须实施可持续发展战略,将废弃材料与各种可利用资源相结合,以有效应对这一严峻形势。本研究的目的是测试采石场粉尘和海砂混合物... 详细信息

越南等发展中国家的道路基础设施建设需要大量天然砂。河砂日益紧缺,其供应量将持续下降。因此,建筑行业必须实施可持续发展战略,将废弃材料与各种可利用资源相结合,以有效应对这一严峻形势。本研究的目的是测试采石场粉尘和海砂混合物的力学性能,并评估其在高速公路路基层中的潜在应用。进行了一系列试验,包括材料的含水率、相对密度、休止角测试和三轴试验,以研究不同配比下混合物的组成。结合Plaxis土工试验中的校准进行了广泛的参数研究,得出了割线模量E_(50)和围压曲线。根据加州承载比CBR对公路路基层所用材料的评估结果,证明海砂和采石场粉尘混合物具有适当性能,可用于公路路基的建设。

关键词：采石场粉尘海砂土工试验模块固结试验三轴试验路基层公路加州承载比

循环三轴试验加载频率和压实度对重塑砂土液化行为的影响

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岩土力学 2024年第6期45卷 1813-1823页

作者： THUY Do Van tiep pham duc HIEU Nguyen Van THANG pham Cao 勒奎东技术大学特殊工程技术研究所越南河内越南航空科技协会越南河内

通过对各向同性固结不排水试样进行循环三轴试验,研究了饱和重塑砂土的液化行为。试验采用恒幅正弦载荷,通过测量剪切模量、阻尼比、轴向应变和超孔隙水压力比的变化,评估了加载频率(分别为0.1、0.5、1.0 Hz)和压实度(分别为0.95、0.90... 详细信息

通过对各向同性固结不排水试样进行循环三轴试验,研究了饱和重塑砂土的液化行为。试验采用恒幅正弦载荷,通过测量剪切模量、阻尼比、轴向应变和超孔隙水压力比的变化,评估了加载频率(分别为0.1、0.5、1.0 Hz)和压实度(分别为0.95、0.90和0.80)对砂土液化行为的影响。试验结果表明,对于压实度为0.95的砂样,在5000次加载循环中,0.1 Hz的加载频率对液化过程影响甚微;而对于压实度为0.90和0.80的砂样,此频率的影响显著。对于压实度为0.80的砂样,当频率增加到0.5 Hz时几乎一加载就直接发生液化。这表明增加加载频率会加快液化速度,而增加压实度则会减慢液化速度。因此,通过一系列的试验可以模拟现场砂土在不同频率下的动荷载条件。试验结果表明,饱和砂土的液化行为由以下因素决定:(1)试样的压实度越低,液化越容易发生;(2)加载频率越高,液化越容易发生;(3)循环轴向应变越大,发生液化所需的循环次数越少;(4)超孔隙水压力随加载循环次数增加,直至试样完全液化。

关键词：液化行为加载频率循环三轴试验饱和固结不排水条件重塑砂土压实度

Landslide Susceptibility Mapping Using RBFN-Based Ensemble Machine Learning Models

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 467-500页

作者： Landslide Susceptibility Mapping Using RBFN-Based Ensemble Machine Learning Models duc-Dam Nguyen Nguyen Viet tiep Quynh-Anh Thi Bui Hiep Van Le Indra Prakash Romulus Costache Manish Pandey Binh Thai pham Faculty of Civil Engineering University of Transport TechnologyThanh XuanHa Noi100000Vietnam Faculty of Hydraulic Engineering Hanoi University of Civil EngineeringHa Noi100000Vietnam DDG(R)Geological Survey of India Gandhinagar382010India Research Institute of the University of Bucharest Bucharest050663Romania National Institute of Hydrology and Water Management Bucharest013686Romania Department of Civil Engineering Transilvania University of BrasovBrasov500152Romania Danube Delta National Institute for Research and Development Tulcea820112Romania Marwadi University Research Center(MURC) Marwadi UniversityRajkotGujaratBharat360003India Department of Civil Engineering Faculty of Engineering&TechnologyMarwadi UniversityRajkotGujaratBharat360003India

This study was aimed to prepare landslide susceptibility maps for the Pithoragarh district in Uttarakhand,India,using advanced ensemble models that combined Radial Basis Function Networks(RBFN)with three ensemble learning techniques:DAGGING(DG),MULTIBOOST(MB),and ADABOOST(AB).This combination resulted in three distinct ensemble models:DG-RBFN,MB-RBFN,and ***,a traditional weighted method,Information Value(IV),and a benchmark machine learning(ML)model,Multilayer Perceptron Neural Network(MLP),were employed for comparison and *** models were developed using ten landslide conditioning factors,which included slope,aspect,elevation,curvature,land cover,geomorphology,overburden depth,lithology,distance to rivers and distance to *** factors were instrumental in predicting the output variable,which was the probability of landslide *** analysis of the models’performance indicated that the DG-RBFN model,with an Area Under ROC Curve(AUC)of 0.931,outperformed the other *** AB-RBFN model achieved an AUC of 0.929,the MB-RBFN model had an AUC of 0.913,and the MLP model recorded an AUC of *** results suggest that the advanced ensemble ML model DG-RBFN was more accurate than traditional statistical model,single MLP model,and other ensemble models in preparing trustworthy landslide susceptibility maps,thereby enhancing land use planning and decision-making.

关键词： Landslide susceptibility map spatial analysis ensemble modelling information values(IV)

Prediction of Shear Bond Strength of Asphalt Concrete Pavement Using Machine Learning Models and Grid Search Optimization Technique

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 691-712页

作者： Quynh-Anh Thi Bui Dam duc Nguyen Hiep Van Le Indra Prakash Binh Thai pham Civil Engineering Department University of Transport Technology54 Trieu KhucThanh XuanHanoi100000Vietnam DDG(R)Geological Survey of India Gandhinagar382010India

Determination of Shear Bond strength(SBS)at interlayer of double-layer asphalt concrete is crucial in flexible pavement *** study used three Machine Learning(ML)models,including K-Nearest Neighbors(KNN),Extra Trees(ET),and Light Gradient Boosting Machine(LGBM),to predict SBS based on easily determinable input ***,the Grid Search technique was employed for hyper-parameter tuning of the ML models,and cross-validation and learning curve analysis were used for training the *** models were built on a database of 240 experimental results and three input variables:temperature,normal pressure,and tack coat *** validation was performed using three statistical criteria:the coefficient of determination(R2),the Root Mean Square Error(RMSE),and the mean absolute error(MAE).Additionally,SHAP analysis was also used to validate the importance of the input variables in the prediction of the *** show that these models accurately predict SBS,with LGBM providing outstanding ***(Shapley Additive explanation)analysis for LGBM indicates that temperature is the most influential factor on ***,the proposed ML models can quickly and accurately predict SBS between two layers of asphalt concrete,serving practical applications in flexible pavement structure design.

关键词： Shear bond asphalt pavement grid search optimization machine learning

Bio-Inspired Binary Bees Algorithm for a Two-Level Distribution Optimisation Problem

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Journal of Bionic Engineering 2010年第2期7卷 161-167页

作者： duc Troung pham Manufacturing Engineering Centre Cardiff University

Two uncoupleable distributions, assigning missions to robots and allocating robots to home stations, accompany the use ofmobile service robots in *** the given problem, two workload-related objectives and five groups of constraints areproposed.A bio-mimicked Binary Bees Algorithm (BBA) is introduced to solve this multiobjective multiconstraint combinatorialoptimisation problem, in which constraint handling technique (Multiobjective Transformation, MOT), multiobjectiveevaluation method (nondominance selection), global search strategy (stochastic search in the variable space), local searchstrategy (Hamming neighbourhood exploitation), and post-processing means (feasibility selection) are the main *** is then demonstrated with a case study, presenting the execution process of the algorithm, and also explaining the change ofelite number in evolutionary *** optimisation result provides a group of feasible nondominated two-level distributionschemes.

关键词： Binary Bees Algorithm bioinspiration two-level distribution combinatorial optimisation multiobjectives multi-constraints

Rapid design of top-performing metal-organic frameworks with qualitative representations of building blocks

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npj Computational Materials 2023年第1期9卷 585-598页

作者： Yigitcan Comlek Thang duc pham Randall Q.Snurr Wei Chen Department of Mechanical Engineering Northwestern UniversityEvanstonILUSA Department of Chemical and Biological Engineering Northwestern UniversityEvanstonILUSA

Data-driven materials design often encounters challenges where systems possess qualitative(categorical)***,representing Metal-organic frameworks(MOFs)through different building blocks poses a challenge for designers to incorporate qualitative information into design optimization,and leads to a combinatorial challenge,with large number of MOFs that could be *** this work,we integrated Latent Variable Gaussian Process(LVGP)and Multi-Objective Batch-Bayesian Optimization(MOBBO)to identify top-performing MOFs adaptively,autonomously,and *** showcased that our method(i)requires no specific physical descriptors and only uses building blocks that construct the MOFs for global optimization through qualitative representations,(ii)is application and property independent,and(iii)provides an interpretable model of building blocks with physical *** searching only~1%of the design space,LVGP-MOBBO identified all MOFs on the Pareto front and 97%of the 50 top-performing designs for the CO_(2) working capacity and CO_(2)/N2 selectivity properties.

关键词： properties qualitative autonomous

Graphical method based on modified maximum force criterion to indicate forming limit curves of 22MnB5 boron steel sheets at elevated temperatures

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Journal of Iron and Steel Research International 2021年第8期28卷 1009-1018页

作者： Thanh Luyen Quoc-Tuan pham Thi-Bich Mac Tien-Long Banh duc-Toan Nguyen Faculty of Mechanical Engineering Hungyen University of Technology and EducationHungyen 160000Vietnam Division of Computational Mathematics and Engineering Institute for Computational ScienceTon Duc Thang UniversityHo Chi Minh City 70000Vietnam Faculty of Civil Engineering Ton Duc Thang UniversityHo Chi Minh City 70000Vietnam School of Mechanical Engineering Hanoi University of Science and TechnologyHanoi City 100000Vietnam

A new approach for predicting forming limit curves(FLCs)at elevated temperatures was proposed *** are often used to predict failure and determine the optimal forming parameters of automotive ***,a graphical method based on a modified maximum force criterion was applied to estimate the FLCs of 22MnB5 boron steel sheets at room temperature using various hardening ***,the predicted FLC data at room temperature were compared with corresponding data obtained from Nakazima's tests to obtain the best *** estimate the FLC at elevated temperatures,tensile tests were conducted at various temperatures to determine the ratios of equivalent fracture strains between the corresponding elevated temperatures and room *** at elevated temperatures could be established based on obtained ***,the predicted FLCs at elevated temperatures did not agree well with the corresponding FLC experimental data of Zhou et al.A new method was proposed herein to improve the prediction of FLCs at elevated *** FLC calculated at room tem-perature was utilized to predict the failure of Nakazima's samples via finite element *** on the simulation results at room temperature,the mathematical relationships between the equivalent ductile fracture strain versus stress triaxiality and strain ratio were established and then combined with ratios between elevated and room temperatures to calculate the FLCs at different *** predicted FLCs at elevated temperatures agree well with the corresponding experimental FLC data.

关键词： Forming limit curve Modified maximum force criterion Graphical method Hardening law Finite element method Boron steel sheet Elevated temperature

Occurrence of microcystins in water,sediment,and aquatic animals in Dau Tieng Reservoir,Vietnam

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Journal of Oceanology and Limnology 2024年第6期42卷 1751-1763页

作者： Thanh Luu pham Manh Ha BUI Tan duc NGUYEN Thanh Son DAO Faculty of Environment and Labour Safety Ton Duc Thang UniversityHo Chi Minh City 700000Vietnam Faculty of Environment Saigon UniversityHo Chi Minh City 700000Vietnam Guangdong Provincial Key Laboratory of Marine Disaster Prediction and Prevention and Guangdong Provincial Key Laboratory of Marine BiotechnologyShantou UniversityShantou 515063China Faculty of Environment and Natural Resources Ho Chi Minh City University of Technology(HCMUT)Ho Chi Minh City 700000Vietnam Asian Center for Water Research(Centre Asiatique de Recherchesur l’Eau CARE)Ho Chi Minh City University of Technology(HCMUT)Vietnam National UniversityHo Chi Minh City 700000Vietnam

This study investigates the variations of microcystins(MCs)in water,cyanobacterial blooms,sediment,and aquatic organisms collected from the Dau Tieng Reservoir(DTR).*** liquid chromatography(HPLC)was employed to measure MC concentrations in various target *** indicate that Microcystis *** as the primary MC producer in the *** average concentrations of analyzed MCs in surface water ranged from 1.10 to 5.54μg/L,temporally and *** sediment,average concentrations varied from 0.15 to 1.13μg/g wet weight(WW)temporally and from 0.41 to 0.72μg/g WW *** were detected in different organs of fish species(Oreochromis *** Labiobarbus sp.)and in the entire soft tissues of bivalve(Corbicula sp.)and gastropod(Assiminea sp.).The highest observed MC concentration in July was 0.83±0.22μg/g WW in the intestines of fish Oreochromis *** presence of MCs in grass shrimp Palaemonetes *** observed solely in June,reaching a concentration of 0.28±0.19μg/g *** is the first report of MC accumulation in the grass shrimp Palaemonetes *** field *** the bivalve Corbicula sp.,the presence of analyzed MCs was consistent throughout the study period,except for March and September,with the highest concentrations in July at 0.77±0.1μg/g *** correlation analysis revealed significant positive correlations between MCs in water and sediment with MC concentrations in aquatic animals,indicating the potential transfer of MCs across different trophic *** estimated daily intake values for analyzed MCs indicate that fish collected from the DTR are considered safe for consumption,as long as only the edible organs,such as the muscle,are ***,bivalves or gastropods collected from the DTR are not safe for human *** study underscored the importance of monitoring MC accumulation in aquatic animals used as food to mitigate adverse effects on human health.

关键词： aquatic animal bioaccumulation cyanotoxin health risk toxic cyanobacteria

Spatial prediction of rainfall-induced shallow landslides using hybrid integration approach of Least-Squares Support Vector Machines and differential evolution optimization:a case study in Central Vietnam

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International Journal of Digital Earth 2016年第11期9卷 1077-1097页

作者： Dieu Tien Bui Binh Thai pham Quoc Phi Nguyen Nhat-duc Hoang Geographic Information System Group Department of Business Administration and Computer ScienceUniversity College of Southeast NorwayBøi TelemarkNorway Faculty of Geomatics and Land Administration Hanoi University of Mining and GeologyHanoiVietnam Department of Civil Engineering Gujarat Technological UniversityAhmedabadGujaratIndia Department of Geotechnical Engineering University of Transport TechnologyHa NoiVietNam Department of Environmental Sciences Hanoi University of Mining and GeologyHanoiVietnam Faculty of Civil Engineering Institute of Research and DevelopmentDuy Tan UniversityDanangVietnam

This study represents a hybrid intelligence approach based on the differential evolution optimization and Least-Squares Support Vector Machines for shallow landslide prediction,named as *** LSSVM is used to establish a landslide prediction model whereas the DE is adopted to search the optimal tuning parameters of the LSSVM *** this research,a GIS database with 129 historical landslide records in the Quy Hop area(Central Vietnam)has been collected to establish the hybrid *** receiver operating characteristic(ROC)curve and area under the curve(AUC)were used to assess the performance of the newly constructed *** results show that the proposed model has high performances with approximately 82%of AUCs on both training and validating *** model’s results were compared with those obtained from other methods,Support Vector Machines,Multilayer Perceptron Neural Networks,and J48 Decision *** result comparison demonstrates that the DE-LSSVMSLP deems best suited for the dataset at hand;therefore,the proposed model can be a promising tool for spatial prediction of rainfall-induced shallow landslides for the study area.

关键词： Shallow landslide Least-Squares Support Vector Machines differential evolution GIS Vietnam