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A novel finite element formulation for static bending analysis of functionally graded porous sandwich plates

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Frontiers of Structural and Civil Engineering 2022年第12期16卷 1599-1620页

作者： Van Chinh NGUYEN Trung Thanh tran Trung NGUYEN-THOI quoc-Hoa PHAM Faculty of Mechanical Engineering Le Quy Don Technical UniversityHanoiVietnam Laboratory for Applied and Industrial Mathematics Institute for Computational Science and Artificial IntelligenceVan Lang UniversityHo Chi Minh CityVietnam Faculty of Mechanical-Electrical and Computer Engineering Van Lang UniversityHo Chi Minh CityVietnam Faculty of Engineering and Technology Nguyen Tat Thanh UniversityHo Chi Minh CityVietnam

This article aims to propose a finite element formulation based on quasi-3D theory for the static bending analysis of functionally graded porous(FGP)sandwich *** FGP sandwich plates consist of three layers including the bottom skin of homogeneous metal,the top skin of fully ceramic and the FGP core layer with uneven porosity distribution.A quadrilateral(q4)element with nine degrees of freedom(DOFs)per node is derived and employed in analyzing the static bending response of the plate under uniform and/or sinusoidally distributed *** accuracy of the present finite element formulation is verified by comparing the obtained numerical results with the published results in the ***,some numerical examples are performed to examine the effects of the parameters including power-law index k and porosity coefficient on the static bending response of rectangular FGP sandwich *** addition,a problem with a complicated L-shape model is conducted to illustrate the superiority of the proposed finite element method.

关键词： sandwich plates functionally graded porous static bending quasi-3D theory q4 element

Assessment of different machine learning techniques in predicting the compressive strength of self-compacting concrete

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Frontiers of Structural and Civil Engineering 2022年第7期16卷 928-945页

作者： Van quan tran Hai-Van Thi MAI Thuy-Anh NGUYEN Hai-Bang LY Faculty of Civil Engineering University of Transport TechnologyHanoi 100000Vietnam

The compressive strength of self-compacting concrete(SCC)needs to be determined during the construction design *** paper shows that the compressive strength of SCC(CS of SCC)can be successfully predicted from mix design and curing age by a machine learning(ML)technique named the Extreme Gradient Boosting(XGB)algorithm,including non-hybrid and hybrid *** ML techniques,such as Linear regression(LR),K-Nearest Neighbors(KNN),Support Vector Machine(SVM),Decision Trees(DTR),Random Forest(RF),Gradient Boosting(GB),and Artificial Neural Network using two training algorithms LBFGS and SGD(denoted as ann_LBFGS and ann_SGD),are also compared with the XGB ***,the hybrid models of eight ML techniques and Particle Swarm Optimization(PSO)are constructed to highlight the reliability and accuracy of SCC compressive strength prediction by the XGB_PSO hybrid *** highest number of SCC samples available in the literature is collected for building the ML *** with previously published works’performance,the proposed XGB method,both hybrid and non-hybrid models,is the most reliable and robust of the examined techniques,and is more accurate than existing ML methods(R2=0.9644,RMSE=4.7801,and MAE=3.4832).Therefore,the XGB model can be used as a practical tool for engineers in predicting the CS of SCC.

关键词： compressive strength self-compacting concrete machine learning techniques particle swarm optimization extreme gradient boosting

Exponential Continuous Non-Parametric Neural Identifier With Predefined Convergence Velocity

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IEEE/CAA Journal of Automatica Sinica 2022年第6期9卷 1049-1060页

作者： Mariana Ballesteros Rita q.Fuentes-Aguilar Isaac Chairez Instituto Politécnico Nacional Centro de Innovación y Desarrollo Tecnológico en Cómputo Unidad Profesional Interdisciplinaria de Biotecnología 07340Mexico CityMexico Tecnológico de Monterrey School of Engineering and SciencesZapopanJalisco 45138Mexico Department of Bioprocesses UPIBIInstituto Politécnico Nacional07340Mexico City

This paper addresses the design of an exponential function-based learning law for artificial neural networks(anns)with continuous *** ann structure is used to obtain a non-parametric model of systems with uncertainties,which are described by a set of nonlinear ordinary differential *** novel adaptive algorithms with predefined exponential convergence rate adjust the weights of the *** first algorithm includes an adaptive gain depending on the identification error which accelerated the convergence of the weights and promotes a faster convergence between the states of the uncertain system and the trajectories of the neural *** second approach uses a time-dependent sigmoidal gain that forces the convergence of the identification error to an invariant set characterized by an *** generalized volume of this ellipsoid depends on the upper bounds of uncertainties,perturbations and modeling *** application of the invariant ellipsoid method yields to obtain an algorithm to reduce the volume of the convergence region for the identification *** adaptive algorithms are derived from the application of a non-standard exponential dependent function and an associated controlled Lyapunov *** examples demonstrate the improvements enforced by the algorithms introduced in this study by comparing the convergence settings concerning classical schemes with non-exponential continuous learning *** proposed identifiers overcome the results of the classical identifier achieving a faster convergence to an invariant set of smaller dimensions.

关键词： Exponential Lyapunov functions learning laws non-parametric identifier predefined convergence rate

Improved knowledge-based neural network(KBNN)model for predicting spring-back angles in metal sheet bending

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International Journal of Modeling, Simulation, and Scientific Computing 2014年第2期5卷 65-91页

作者： Tinh quoc Bui Anh Viet tran Abid Ali Shah Department of Civil Engineering University of Siegen Paul-Bontz-Str.9-1157076 SiegenGermany School of Mechanical and Automotive Engineering University of Ulsan San 29Mugeo 2-dong NamguP.O.Box 18UlsanSouth Korea

We develop an efficiently improved knowledge-based neural network(KBNN)associated with optimization algorithms and finite element analysis(FEA)to accurately predict spring-back angles in metal sheet *** well-known V and U prevalent processes of bending are *** KBNN predictive results are based on the empirical model and artificial neural network(ann)*** empirical model is constructed from the FEA results using response surface method,while the multilayer perceptron is employed to create the *** trained KBNN can accurately model the relation-ship between the spring-back angles and process *** obtained results are validated against other existing methods showing a high accuracy.

关键词： Metal sheet bending spring-back angles knowledge-based neural network genetic algorithm optimization algorithm

Application of machine learning technique for predicting and evaluating chloride ingress in concrete

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Frontiers of Structural and Civil Engineering 2022年第9期16卷 1153-1169页

作者： Van quan tran Van Loi GIAP Dinh Phien VU Riya Catherine GEORGE Lanh Si HO Department of Civil Engineering University of Transport TechnologyHanoi 100000Vietnam Civil and Environmental Engineering Program Graduate School of Advanced Science and EngineeringHiroshima UniversityHiroshima 739-8527Japan

The degradation of concrete structure in the marine environment is often related to chloride-induced corrosion of reinforcement ***,the chloride concentration in concrete is a vital parameter for estimating the corrosion level of reinforcement *** research aims at predicting the chloride content in concrete using three hybrid models of gradient boosting(GB),artificial neural network(ann),and random forest(RF)in combination with particle swarm optimization(PSO).The input variables for modeling include exposure condition,water/binder ratio(W/B),cement content,silica fume,time exposure,and depth of *** results indicate that three models performed well with high accuracy of prediction(R2⩾0.90).Among three hybrid models,the model using GB_PSO achieved the highest prediction accuracy(R2=0.9551,RMSE=0.0327,and MAE=0.0181).Based on the results of sensitivity analysis using SHapley Additive exPlanation(SHAP)and partial dependence plots 1D(PDP-1D),it was found that the exposure condition and depth of measurement were the two most vital variables affecting the prediction of chloride *** the number of different exposure conditions is larger than two,the exposure significantly impacted the chloride content of concrete because the chloride ion ingress is affected by both chemical and physical *** study provides an insight into the evaluation and prediction of the chloride content of concrete in the marine environment.

关键词： gradient boosting random forest chloride content concrete sensitivity analysis

Forest characteristics and population structure of Glyptostrobus pensilis, a globally endangered relict species of southeastern China

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Plant Diversity 2019年第4期41卷 237-249页

作者： Cindy q. Tang Yongchuan Yang Arata Momohara Huan-Chong Wang Hong Truong Luu Shuaifeng Li Kun Song Shenhua qian Ben LePage Yi-Fei Dong Peng-Bin Han Masahiko Ohsawa Buu Thach Le Huu Dang tran Minh Tri Dang Ming-Chun Peng Chong-Yun Wang Institute of Ecology and Geobotany School of Ecology and Environmental ScienceYunnan UniversityDongwaihuan South RoadUniversity TownChenggong New DistrictKunmingYunnan 650504China The Nature Conservancy Society of Japan Mitoyo Bldg.2F1-16-10 ShinkawaChuo-kuTokyo 104-0033Japan Key Laboratory of Three Gorges Reservoir Region's Eco-Environment Ministry of EducationChongqing UniversityChongqing 400045China Graduate School of Horticulture Chiba University648 MatsudoChiba 271-8510Japan Institute of Botany Yunnan UniversityKunmingYunnan 650091China Southern Institute of Ecology Vietnam Academy o f Science and TechnologyHo Chi Minh CityViet Nam Research Institute of Resource Insects Chinese Academy of ForestryKunmingYunnan 650224China School o f Ecological and Environmental Sciences East China Normal UniversityShanghai 200241China Pacific Gas and Electric Company 3401 Crow Canyon RoadSan RamonCA 94583USA The Academy of Natural Science 1900 Benjamin Franklin ParkwayPhiladelphiaPA 19W3USA

The Chinese water pine Glyptostrobus pensilis is the sole surviving species of the genus Glyptostrobus. It is endemic to southern China, central Vietnam, and eastern Laos, and today it is nearly extinct in the wild. Forest community characteristics and population structure of G. pensilis in China have remained un-known up to now. We investigated six swamp forest stands and analyzed their forest community characteristics (i.e. vertical stratification, species composition, and diversity) and population structure, including the frequency distribution of DBH (diameter at breast height) and age-classes as found in Fujian Province, southeastern China. The vertical stratifications of all the forest stands were rather simple. The remaining wild specimens ranged from roughly 15 to some 357 years for an average of ca. 85 years, with only a few individuals less than 20 years old. Compared with the stands and populations of G. pensilis in Vietnam, the taxonomic compositions of the stands in the two regions were different, except for the dominant species-G. pensilis. The Shannon-Wiener index showed the overstory of each stand had much lower diversity (0.26 on average) in Fujian Province than that (1.97 on average) in Vietnam, whereas the diversity indices were about the same (around 2.41) for the understories in the two regions. Furthermore, we discovered 18 G. pensilis seedlings at the study sites in Fujian Province. This discovery demonstrates that G. pensilis regeneration is extremely poor and its populations are declining, although these populations are rela-tively healthier than those in Vietnam.

关键词： Age-class Fujian Province Glyptostrobus Regeneration Relict plant Vietnam

Characteristics and outcomes of hepatocellular carcinoma patients with macrovascular invasion following surgical resection: a meta-analysis of 40 studies and 8,218 patients

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Hepatobiliary Surgery and Nutrition 2022年第6期11卷 848-860,I0001-I0015页

作者： Daniel q.Huang Andrew tran Eunice XTan Sanjna N.Nerurkar Readon Teh Margaret L.P.Teng Ee Jin Yeo Biyao Zou Connie Wong Carlos O.Esquivel CAndrew Bonham Mindie H.Nguyen Division of Gastroenterology and Hepatology Department of MedicineNational University HospitalSingaporeSingapore Department of Medicine Yong Loo Lin School of MedicineNational University of SingaporeSingaporeSingapore Duke University DurhamNCUSA Adelaide Medical School The University of AdelaideAdelaideAustralia Division of Gastroenterology and Hepatology Department of MedicineStanford University Medical CenterPalo AltoCAUSA Department of Epidemiology and Population Health Stanford University School of MedicineStanfordCAUSA Lane Medical Library Stanford University School of MedicineStanfordCAUSA Division of Abdominal transplantation Department of SurgeryStanford University School of MedicineStanfordCAUSA

Background:Guidelines recommend that hepatocellular carcinoma(HCC)patients with portal vein tumor thrombosis(PVTT)and/or hepatic vein tumor thrombosis(HVTT)should undergo systemic ***,recent data suggest that surgical resection may be beneficial in selected cases,but outcomes are *** aimed to estimate pooled overall survival(OS),recurrence free survival(RFS)and complication rates in HCC patients with macrovascular invasion(MVI)following surgical ***:In this systematic review and meta-analysis,two investigators independently searched PubMed,Embase,and Cochrane databases from inception to Nov 10,2020,without language restrictions,for studies reporting outcomes of adult HCC patients with MVI who underwent liver resection with curative ***:We screened 8,598 articles and included 40 studies involving 8,218 *** all patients with MVI,the pooled median OS was 14.39 months[95%confidence interval(CI):10.99-18.84],1-year OS was 54.47%(95%CI:46.12-62.58%)and 3-year OS was 23.20%(95%CI:16.61-31.42%).Overall,1-and 3-year RFS were 27.70%(95%CI:21.00-35.57%)and 10.06%(95%CI:6.62-15.01%),*** patients with PVTT,median OS was 20.41 months in those with segmental/2nd order involvement compared to 12.91 months if 1st order branch was involved and 6.41 months if the main trunk was *** pooled rate of major complications was 6.17%(95%CI:3.53-10.56%).Conclusions:Overall median survival was 14.39 months for HCC patients with MVI following *** survival was higher in PVTT with segmental/2nd order involvement at 20.41 versus 6.41 months if the main trunk was involved.

关键词： Hepatocellular carcinoma(HCC) resection portal vein macrovascular invasion(MVI) recurrence

Theoretical Investigations on Mapping Mean Distributions of Particulate Matter,Inert,Reactive,and Secondary Pollutants from Wildfires by Unmanned Air Vehicles(UAVs)

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Open Journal of Air Pollution 2015年第3期4卷 149-174页

作者： Nicole Molders Mary K.Butwin James M.Madden Huy N.q.tran Kenneth Sassen Gerhard Kramm Geophysical Institute University of Alaska FairbanksFairbanksUSA Department of Atmospheric Sciences College of Natural Science and MathematicsUniversity of Alaska FairbanksFairbanksUSA Bingham Entrepreneurship&Energy Research Center Utah State UniversityVernalUSA 4Department of Atmospheric ScienceUniversity of UtahSalt Lake CityUSA 5Engineering Meteorology ConsultingFairbanksUSA

Evaluated Weather Research and Forecasting model inline with chemistry (WRF/Chem) simulations of the 2009 Crazy Mountain Complex wildfire in Interior Alaska served as a testbed for typical Alaska wildfire-smoke conditions. A virtual unmanned air vehicle (UAV) sampled temperatures, dewpoint temperatures, primary inert and reactive gases and particular matter of different sizes as well as secondary pollutants from the WRF/Chem results using different sampling patterns, altitudes and speeds to investigate the impact of the sampling design on obtained mean distributions. In this experimental design, the WRF/Chem data served as the “grand truth” to assess the mean distributions from sampling. During frontal passage, the obtained mean distributions were sensitive to the flight patterns, speeds and heights. For inert constituents mean distributions from sampling agreed with the “grand truth” within a factor of two at 1000 m. Mean distributions of gases involved in photochemistry differed among flight patterns except for ozone. The diurnal cycle of these gases’ concentrations led to overestimation (underestimation) of 20 h means in areas of high (low) concentrations as compared to the “grand truth.” The mean ozone distribution was sensitive to the speed of the virtual UAV. Particulate matter showed the strongest sensitivity to the flight patterns, especially during precipitation.

关键词： WRF/Chem Wildfire Smoke Unmanned Aircraft Vehicles Theoretical Flight Design CALIPSO

First Record of Sphenomorphus incognitus (Thompson, 1912) (Squamata: Scincidae) from Vietnam with Some Notes on Natural History

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Asian Herpetological Research 2012年第2期3卷 147-150页

作者： Truong quang NGUYEN Tung Thanh tran Tao Thien NGUYEN Wolfgang BHME Thomas ZIEGLER Institute of Ecology and Biological Resources Vietnam Academy of Science and Technology Present address: Department of Terrestrial Ecology Cologne Biocenter University of Cologne Vinh Phuc College of Education 4. Vietnam National Museum of Nature Vietnam Academy of Science and Technology 5. Zoologisches Forschungsmuseum Alexander Koenig 6. AG Zoologischer Garten Kln

Sphenomorphus incognitus is recorded for the first time outside of China. The new locality record is from the Tay Yen Tu Nature Reserve in Bac Giang Province, northeastern Vietnam at elevations between 200–450 m. Based on the newly collected specimens, we present an expanded description and provide data on the natural history of this species in northern Vietnam.

关键词： new record Sphenomorphus incognitus Tay Yen Tu Nature Reserve Bac Giang Province Vietnam