检索结果-南通市图书馆

A novel ensemble model for predicting the performance of a novel vertical slot fishway

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Frontiers of Structural and Civil Engineering 2020年第6期14卷 1418-1444页

作者： aydin shishegaran Mohammad SHOKROLLAHI Ali MIRNOROLLAHI Arshia shishegaran Mohammadreza MOHAMMAD KHANI Deparlment of Water and Environmental Engineering School of Civil EngineeringIran University of Science and TechnologyTehran ***Iran Department of Water and Environmental Engineering School of Civil EngineeringSemnan UniversitySemnan 35131-19111Iran Department of Water and Enironmental Engineering School of Civil EngineeringIslamic Azad University Central Tehran BranchTehran ***Iran School of Progress Engineering Iran University of Science and TechnologyTehran ***Iran

We investigate the performance of a novel vertical slot fishway by employing finite volume and surrogate models.Multiple linear regression,multiple log equation regression,gene expression programming,and combinations of these models are employed to predict the maximum turbulence,maximum velocity,resting area,and water depth of the middle pool in the fishway.The statistical parameters and error terms,including the coefficient of determination,root mean square error,normalized square error,maximum positive and negative errors,and mean absolute percentage error were employed to evaluate and compare the accuracy of the models.We also conducted a parametric study.The independent variables include the opening between bafles(OBB),the ratio of the length of the large and small baffles,the volume flow rate,and the angle of the large baffle.The results show that the key parameters of the maximum turbulence and velocity are the volume flow rate and OBB.

关键词： novel vertical slot fishway parametric study finite volume method ensemble model gene expression programming

Performance of a novel bent-up bars system not interacting with concrete

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Frontiers of Structural and Civil Engineering 2019年第6期13卷 1301-1315页

作者： aydin shishegaran Mohammad Reza GHASEMI Hesam VARAEE School of Civil Engineering Iran University of Science and TechnologyTehran 13114-16846Iran Structural Engineering Department of Civil EngineeringUniversity of Sistan and BaluchestanZahedan 98167-45845Iran Structural Engineering Ale Taha Institute of Higher EducationTehran 14888-36164Iran

Increasing the bending and shear capacities of reinforced concrete members is an interesting issue in structural engineering.In recent years,many studies have been carried out to improve capacities of reinforced concrete members such as using post and pre-tensioning,Fiber Reinforced Polymer and other techniques.This paper proposes a novel and significant technique to increase the flexural capacity of simply supported reinforced concrete beams.The proposed method uses a new reinforcement bar system having bent-up bars,covered with rubber tubes.This technique will avoid interaction of bent-up bars with concrete.They are located in the zone where compressive and tensile forces act against one anothe匚The compressive force in the upper point of the bent-up bars is exerted to the end point of these bars located under neutral axis.Moreover,the tensile stress is decreased in reinforcements located under the neutral axis.This will cause the Reinforced Concrete(RC)beam to endure extra loading before reaching yield stress.These factors may well be considered as reasons to increase bending capacity in the new system.The laboratory work together with finite element method analysis were carried out in this investigation.Furthermore,bending capacity,ductility,strength,and cracking zone were assessed for the new proposed system and compared with the conventional model.Both the FEM simulation and the experimental test results revealed that the proposed system has significant impact in increasing the load bearing capacity and the stiffness of the RC beams.In the present study,an equation is formulated to calculate bending capacity of a new reinforcement bar system beam.

关键词： bending capacity rubber tube stress transfer bent-up bars ductility cracking

Evaluation of a novel Asymmetric Genetic Algorithm to optimize the structural design of 3D regular and irregular steel frames

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Frontiers of Structural and Civil Engineering 2020年第5期14卷 1110-1130页

作者： Mohammad Sadegh ES-HAGHI aydin shishegaran Timon RABCZUK School of Civil Engineering Khajeh Nasir Toosi University of TechnologyTehran 19697-64499Iran School of Civil Engineering Iran University of Science and TechnologyTehran 13114-16846Iran Division of Computational Mechanics Ton Duc Thang UniversityHo Chi Minh CityVietnam Faculty of Civil Engineering Ton Duc Thang UniversityHo Chi Minh CityVietnam

We propose a new algorithm,named Asymmetric Genetic Algorithm(AGA),for solving optimization problems of steel frames.The AGA consists of a developed penalty function,which helps to find the best generation of the population.The objective function is to minimize the weight of the whole steel structure under the constraint of ultimate loads defined for structural steel buildings by the American Institute of Steel Construction(AISC).Design variables are the cross-sectional areas of elements(beams and columns)that are selected from the sets of side-flange shape steel sections provided by the AISC.The finite element method(FEM)is utilized for analyzing the behavior of steel frames.A 15-storey three-bay steel planar frame is optimized by AGA in this study,which was previously optimized by algorithms such as Particle Swarm Optimization(PSO),Particle Swarm Optimizer with Passive Congregation(PSOPC),Particle Swarm Ant Colony Optimization(HPSACO),Imperialist Competitive Algorithm(ICA),and Charged System Search(CSS).The results of AGA such as total weight of the structure and number of analyses are compared with the results of these algorithms.AGA performs better in comparison to these algorithms with respect to total weight and number of analyses.In addition,five numerical examples are optimized by AGA,Genetic Algorithm(GA),and optimization modules of SAP2000,and the results of them are compared.The results show that AGA can decrease the time of analyses,the number of analyses,and the total weight of the structure.AGA decreases the total weight of regular and irregular steel frame about 11.1%and 26.4%in comparing with the optimized results of SAP2000,respectively.

关键词： optimization steel frame Asymmetric Genetic Algorithm constraints of ultimate load constraints of serviceability limits penalty function

Surrogate models for the prediction of damage in reinforced concrete tunnels under internal water pressure

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2021年第8期22卷 632-656页

作者： Alireza BIGDELI aydin shishegaran Mohammad Ali NAGHSH Behnam KARAMI Arshia shishegaran Gholamreza ALIZADEH School of Civil Engineering Iran University of Science and TechnologyTehran 16846-13114Iran Institute of Structural Mechanics Bauhaus-University WeimarWeimar D-99423Germany School of Civil Engineering Isfahan University of TechnologyIsfahan ***Iran International Institute of Earthquake Engineering and Seismology Tehran 19537-14453Iran School of Civil Engineering Islamic Azad UniversityTehran 158474331Iran

In the present study,the performance of reinforced concrete tunnel(RCT)under internal water pressure is evaluated by using nonlinear finite element analysis and surrogate models.Several parameters,including the compressive and tensile strength of concrete,the size of the longitudinal reinforcement bar,the transverse bar diameter,and the internal water pre ssure,are considered as the input variables.Based on the levels of variables,36 mix designs are selected by the Taguchi method,and 12 mix designs are proposed in this study.Carbon fiber reinforced concrete(CFRC)or glass fiber reinforced concrete(GFRC)is considered for simulating these 12 samples.Principal component regression(PCR),Multi Ln equation regression(MLnER),and gene expression programming(GEP)are employed for predicting the percentage of damaged surfaces(PDS)of the RCT,the effective tensile plastic strain(ETPS),the maximum deflection of the RCT,and the deflection of crown of RCT.The error terms and statistical parameters,including the maximum positive and negative errors,mean absolute percentage error(MAPE),root mean square error(RMSE),coefficient of determination,and normalized square error(NMSE),are utili zed to evaluate the accuracy of the models.Based on the results,GEP performs better than other models in predicting the outputs.The results sh ow that the internal water pressure and the mechanical properties of concrete have the most effect on the damag e and deflection of the RCT.

关键词： Gene expression programming(GEP) Taguchi method Finite element(FE)analysis Effective tensile plastic strain(ETPS) Deflection Damage

Prediction of the load-carrying capacity of reinforced concrete connections under post-earthquake fire

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2021年第6期22卷 441-466页

作者： aydin shishegaran Mehdi MORADI Mohammad Ali NAGHSH Behnam KARAMI Arshia shishegaran School of Civil Engineering Iran University of Science and TechnologyTehranIran Institute of Structural Mechanics Bauhaus-Universitat WeimarWeimar 99423Germany School of Civil Engineering Isfahan UniversityIsfahanIran School of Civil Engineering Isfahan University of TechnologyIsfahanIran International Institute of Earthquake Engineering and Seismology TehranIran 不详

Finding out the most effective parameters relating to the resistance of reinforced concrete connections(RCCs)is an important topic in structural engineering.In this study,first,a finite element(FE)model is developed for simulating the performance of RCCs under post-earthquake fire(PEF).Then surrogate models,including multiple linear regression(MLR),multiple natural logarithm(Ln)equation regression(MLn ER),gene expression programming(GEP),and an ensemble model,are used to predict the remaining load-carrying capacity of an RCC under PEF.The statistical parameters,error terms,and a novel statistical table are used to evaluate and compare the accuracy of each surrogate model.According to the results,the ratio of the longitudinal reinforcement bars of the column(RLC)has a significant effect on the resistance of an RCC under PEF.Increasing the value of this parameter from 1%to 8%can increase the residual load-carrying capacity of an RCC under PEF by 492.2%when the RCC is exposed to fire at a temperature of 1000°C.Moreover,based on the results,the ensemble model can predict the residual load-carrying capacity with suitable accuracy.A safety factor of 1.55 should be applied to the results obtained from the ensemble model.

关键词： Reinforced concrete connection(RCC) Post-earthquake fire(PEF) Surrogate models Load-carrying capacity Gene expression programming(GEP) Ensemble model

An innovative model for predicting the displacement and rotation of column-tree moment connection under fire

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Frontiers of Structural and Civil Engineering 2021年第1期15卷 194-212页

作者： Mohammad Ali NAGHSH aydin shishegaran Behnam KARAMI Timon RABCZUK Arshia shishegaran Hamed TAGHAVIZADEH Mehdi MORADI Department of Civil Engineering Isfahan University of TechnologyIsfahan 84156-83111Iran School of Civil Engineering School of Civil EngineeringIran University of Science and TechnologyTehran 13114-16846Iran Department of Civil Engineering International Institute of Earthquake Engineering and SeismologyTehran 19539-14453Iran Division of Computational Mechanics Ton Duc Thang UniversityHo Chi Minh CityVietnam Faculty of Civil Engineering Ton Duc Thang UniversityHo Chi Minh CityVietnam Department of Civil Engineering Islamic Azad UniversityTehran 16511-53311Iran Department of Civil Engineering Isfahan UniversityIsfahan 81746-73441Iran

In this study,we carried out nonlinear finite element simulations to predict the performance of a columntree moment connection(CTMC)under fire and static loads.We also conducted a detailed parameter study based on five input variables,including the applied temperature,number of flange bolts,number of web bolts,length of the beam,and applied static loads.The first variable is changed among seven levels,whereas the other variables are changed among three levels.Employing the Taguchi method for variables 2-5 and their levels,9 samples were designed for the parameter study,where each sample was exposed to 7 different temperatures yielding 63 outputs.The related variables for each output are imported for the training and testing of different surrogate models.These surrogate models include a multiple linear regression(MLR),multiple Ln equation regression(MLnER),an adaptive network-based fuzzy inference system(ANFIS),and gene expression programming(GEP).44 samples were used for training randomly while the remaining samples were employed for testing.We show that GEP outperforms MLR,MLnER,and ANFIS.The results indicate that the rotation and deflection of the CTMC depend on the temperature.In addition,the fire resistance increases with a decrease in the beam length;thus,a shorter beam can increase the fire resistance of the building.The numbers of flanges and web bolts slightly affect the rotation and displacement of the CTMCs at temperatures of above 400℃.

关键词： column-tree moment connection Finite element model parametric study fire regression models gene expression programming

Performance of fixed beam without interacting bars

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Frontiers of Structural and Civil Engineering 2020年第5期14卷 1180-1195页

作者： aydin shishegaran Behnam KARAMI Timon RABCZUK Arshia shishegaran Mohammad Ali NAGHSH Mohammreza MOHAMMAD KHANI School of Civil Engineering Iran University of Science and TechnologyTehran 13114-16846Iran International Institute of Earthquake Engineering and Seismology Tehran 19537-14453Iran Division of Computational Mechanics Ton Duc Thang UniversityHo Chi Minh CityVietnam Faculty of Civil Engineering Ton Duc Thang UniversityHo Chi Minh CityVietnam School of Civil engineering Islamic Azad UniversityTehran ***Iran School of Civil Engineering Isfahan University of TechnologyIsfahan ***Iran

Increasing the bending capacity of reinforced concrete(RC)elements is one of important topics in structure engineering.The goal of this study is to develop a transferred stress system(TSS)on longitudinal reinforcement bars for increasing the bending capacity of RC frames.The study is divided into two parts,i.e.,experimental tests and nonlinear FE analysis.The experiments were carried out to determine the load-deflection curves and crack patterns of the ordinary and TSS fixed frame.The FE models were developed for simulating the fixed frames.The obtained load-deflection results and the observed cracks from the FE analysis and experimental tests are compared to evaluate the validation of the FE nonlinear models.Based on the validated FE models,the stress distribution on the ordinary and TSS bars were evaluated.We found the load carrying capacity and ductility of TSS fixed beam are 29.39%and 23.69%higher compared to those of the ordinary fixed beams.The crack expansion occurs on the ordinary fixed beam,although there are several crack openings at mid-span of the TSS fixed beam.The crack distribution was changed in the TSS fixed frame.The TSS fixed beam is proposed to employ in RC frame instead of ordinary RC beam for improving the performance of RC frame.

关键词： transferred stress system bending capacity crack opening crack propagation FE nonlinear model stress distribution

Combination of sensitivity and uncertainty analyses for sediment transport modeling in sewer pipes

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

International Journal of Sediment Research 2020年第2期35卷 157-170页

作者： Isa Ebtehaj Hossein Bonakdari Mir Jafar Sadegh Safari Bahram Gharabaghi Amir Hossein Zaji Hossien Riahi Madavar Zohreh Sheikh Khozani Mohammad Sadegh Es-haghi aydin shishegaran Ali Danandeh Mehr Department of Civil Engineering Razi University Environmental Research Center Razi University Department of Civil Engineering Yasar University 4. School of EngineeringUniversity of Guelph 5. Department of Water EngineeringVali-e-Asr University of Rafsanjan 6. Smart and Sustainable Township Research CenterFaculty of Engineering&Built EnvironmentUniversiti Kebangsaan Malaysia 7. School of Civil EngineeringK.N.Toosi University of Technology 8. Department of Waterand EnvironmentalIran University of Science and Technology 9. Department of Civil EngineeringAntalya Bilim University

Mitigation of sediment deposition in lined open channels is an essential issue in hydraulic engineering practice.Hence,the limiting velocity should be determined to keep the channel bottom clean from sediment deposits.Recently,sediment transport modeling using various artificial intelligence(AI) techniques has attracted the interest of many researchers.The current integrated study highlights unique insight for modeling of sediment transport in sewer and urban drainage systems.A novel methodology based on the combination of sensitivity and uncertainty analyses with a machine learning technique is proposed as a tool for selection of the best input combination for modeling process at non-deposition conditions of sediment transport.Utilizing one to seven dimensionless parameters,127 models are developed in the current study.In order to evaluate the different parameter co mbinations and select the training and te sting data,four strategies are considered.Considering the densimetric Froude number(Fr) as the dependent parameter,a model with independent parameters of volumetric sediment concentration(CV) and relative particle size(d/R) gave the best results with a mean absolute relative error(MARE) of 0.1 and a root means square error(RMSE) of 0.67.Uncertainty analysis is applied with a machine learning technique to investigate the credibility of the proposed methods.The percentage of the observed sample data bracketed by95% predicted uncertainty bound(95 PPU) is computed to assess the uncertainty of the best models.

关键词： Non-deposition Sediment transport Sensitivity analysis Sewer Uncertainty analysis Urban drainage