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An Effective Hybrid Model of ELM and Enhanced GWO for Estimating compressive strength of Metakaolin-Contained Cemented Materials

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1521-1555页

作者： Abidhan Bardhan Raushan Kumar Singh Mohammed Alatiyyah Sulaiman Abdullah Alateyah Department of Civil Engineering National Institute of Technology PatnaPatnaIndia Department of Computer Engineering and Applications GLA UniversityMathuraIndia Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam Bin Abdulaziz UniversityAl-KharjSaudi Arabia Department of Computer Science College of Science and ArtsQassim UniversityUnaizahSaudi Arabia

This research proposes a highly effective soft computing paradigm for estimating the compressive strength(CS)of metakaolin-contained cemented *** proposed approach is a combination of an enhanced grey wolf optimizer(EGWO)and an extreme learning machine(ELM).EGWO is an augmented form of the classic grey wolf optimizer(GWO).Compared to standard GWO,EGWO has a better hunting mechanism and produces an optimal *** EGWO was used to optimize the ELM structure and a hybrid model,ELM-EGWO,was *** train and validate the proposed ELM-EGWO model,a sum of 361 experimental results featuring five influencing factors was *** on sensitivity analysis,three distinct cases of influencing parameters were considered to investigate the effect of influencing factors on predictive *** consequences show that the constructed ELM-EGWO achieved the most accurate precision in both training(RMSE=0.0959)and testing(RMSE=0.0912)*** outcomes of the ELM-EGWO are significantly superior to those of deep neural networks(DNN),k-nearest neighbors(KNN),long short-term memory(LSTM),and other hybrid ELMs constructed with GWO,particle swarm optimization(PSO),harris hawks optimization(HHO),salp swarm algorithm(SSA),marine predators algorithm(MPA),and colony predation algorithm(CPA).The overall results demonstrate that the newly suggested ELM-EGWO has the potential to estimate the CS of metakaolin-contained cemented materials with a high degree of precision and robustness.

关键词： Metakaolin-contained cemented materials compressive strength extreme learning machine grey wolf optimizer swarm intelligence uncertainty analysis artificial intelligence

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Assessment of compressive strength of jet grouting by machine learning

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第1期16卷 102-111页

作者： Esteban Diaz Edgar Leonardo Salamanca-Medina Roberto Tomas Departamento de Ingeniería Civil Escuela Politécnica SuperiorUniversidad de AlicanteP.O.Box 99E-03080AlicanteSpain

Jet grouting is one of the most popular soil improvement techniques,but its design usually involves great uncertainties that can lead to economic cost overruns in construction *** high dispersion in the properties of the improved material leads to designers assuming a conservative,arbitrary and unjustified strength,which is even sometimes subjected to the results of the test *** present paper presents an approach for prediction of the uniaxial compressive strength(UCS)of jet grouting columns based on the analysis of several machine learning algorithms on a database of 854 results mainly collected from different research *** selected machine learning model(extremely randomized trees)relates the soil type and various parameters of the technique to the value of the compressive *** the complex mechanism that surrounds the jet grouting process,evidenced by the high dispersion and low correlation of the variables studied,the trained model allows to optimally predict the values of compressive strength with a significant improvement with respect to the existing ***,this work proposes for the first time a reliable and easily applicable approach for estimation of the compressive strength of jet grouting columns.

关键词： Jet grouting Ground improvement compressive strength Machine learning

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Prediction of Geopolymer Concrete compressive strength Using Convolutional Neural Networks

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1455-1486页

作者： Kolli Ramujee Pooja Sadula Golla Madhu Sandeep Kautish Abdulaziz S.Almazyad Guojiang Xiong Ali Wagdy Mohamed Department of Civil Engineering VNR Vignana Jyothi Institute of Engineering and TechnologyHyderabadTelangana500090India Department of Information Technology VNR Vignana Jyothi Institute of Engineering and TechnologyHyderabadTelangana500090India Department of Computer Science LBEF Campus(Asia Pacific University of Technology&InnovationMalaysia)Kathmandu44600Nepal Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Guizhou Key Laboratory of Intelligent Technology in Power System College of Electrical EngineeringGuizhou UniversityGuiyang550025China Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmmanJordan

Geopolymer concrete emerges as a promising avenue for sustainable development and offers an effective solution to environmental *** attributes as a non-toxic,low-carbon,and economical substitute for conventional cement concrete,coupled with its elevated compressive strength and reduced shrinkage properties,position it as a pivotal material for diverse applications spanning from architectural structures to transportation *** this context,this study sets out the task of using machine learning(ML)algorithms to increase the accuracy and interpretability of predicting the compressive strength of geopolymer concrete in the civil engineering *** achieve this goal,a new approach using convolutional neural networks(CNNs)has been *** study focuses on creating a comprehensive dataset consisting of compositional and strength parameters of 162 geopolymer concrete mixes,all containing Class F fly *** selection of optimal input parameters is guided by two distinct *** first criterion leverages insights garnered from previous research on the influence of individual features on compressive *** second criterion scrutinizes the impact of these features within the model’s predictive *** to enhancing the CNN model’s performance is the meticulous determination of the optimal *** a systematic trial-and-error process,the study ascertains the ideal number of epochs for data division and the optimal value of k for k-fold cross-validation—a technique vital to the model’s *** model’s predictive prowess is rigorously assessed via a suite of performance metrics and comprehensive score ***,the model’s adaptability is gauged by integrating a secondary dataset into its predictive framework,facilitating a comparative evaluation against conventional prediction *** unravel the intricacies of the CNN model’s learning trajectory,a loss plot is deployed to elucidate its learning rat

关键词： Class F fly ash compressive strength geopolymer concrete prediction deep learning convolutional neural network

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Fluid Dynamics & Materials Processing 2024年第9期20卷 2077-2090页

作者： Jin Yang Senye Liu Xingyang He Ying Su Jingyi Zeng Bohumír Strnadel School of Civil Engineering Architecture and EnvironmentHubei University of TechnologyWuhan430068China Building Waterproof Engineering and Technology Research Center of Hubei Province Hubei University of TechnologyWuhan430068China Center of Advanced Innovation Technologies VŠB-Technical University of Ostrava70833 Ostrava-PorubaCzech Republic

Phosphate tailings are usually used as backfill material in order to recycle tailings *** study considers the effect of the mix proportions of clinker-free binders on the fluidity,compressive strength and other key performances of cementitious backfill materials based on phosphate *** particular,three solid wastes,phosphogypsum(PG),semi-aqueous phosphogypsum(HPG)and calcium carbide slag(CS),were selected to activate wet ground granulated blast furnace slag(WGGBS)and three different phosphate tailings backfill materials were ***,rheology,settling ratio,compressive strength,water resistance and ion leaching behavior of backfill materials were *** to the results,when either PG or HPG is used as the sole activator,the fluidity properties of the materials are *** tailings backfill material activated with PG present the largest fluidity and the lowest yield ***,the backfill material’s compressive strength is considerably increased to 2.9 MPa at 28 days after WGGBS activation using a mix of HPG and CS,all with a settling ratio of only 1.15 ***,all the three ratios of binder have obvious solidification effects on heavy metal ions Cu and Zn,and P in phosphate tailings.

关键词： Fluidity rheology compressive strength phosphate tailing backfill material

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An Investigation into the compressive strength,Permeability and Microstructure of Quartzite-Rock-Sand Mortar

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Fluid Dynamics & Materials Processing 2024年第4期20卷 859-872页

作者： Wei Chen Wuwen Liu Yue Liang School of Civil Engineering Architecture and EnvironmentHubei University of TechnologyWuhan430068China

River sand is an essential component used as a fine aggregate in mortar and *** to unrestrained exploitation,river sand resources are gradually being *** requires alternative *** study deals with the properties of cement mortar containing different levels of manufactured sand(MS)based on quartzite,used to replace river *** river sand was replaced at 20%,40%,60%and 80%with MS(by weight or volume).The mechanical properties,transfer properties,and microstructure were examined and compared to a control group to study the impact of the replacement *** results indicate that the compressive strength can be improved by increasing such a *** strength was improved by 35.1%and 45.5%over that of the control mortar at replacement levels of 60%and 80%,*** there was a weak link between porosity and gas permeability in the mortars with manufactured sand,the gas permeability decreased with growing the replacement *** microstructure of the MS mortar was denser,and the cement paste had fewer microcracks with increasing the replacement level.

关键词： Manufactured sand quartzite compressive strength gas permeability microstructure

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compressive strength and abrasion resistance of concrete containing SiO_2 and CuO nanoparticles in different curing media

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Science China(Technological Sciences) 2011年第9期54卷 2349-2357页

作者： Shadi RIAHI Ali NAZARI Department of Materials Science and Engineering Saveh BranchIslamic Azad University

In the present study,abrasion resistance and compressive strength of concrete specimens containing SiO2 and CuO nanoparticles in different curing media have been *** cement was partially replaced by up to 2.0 wt%of SiO2 and CuO nanoparticles and the mechanical properties of the produced specimens were *** the nanoparticles content was found to increase the abrasion resistance of the specimens cured in water and saturated limewater,while this condition was not observed for compressive strength in the both curing *** enhancement of abrasion resistance was higher for the specimens containing SiO2 nanoparticles in both curing *** abrasion resistance and compressive strength of the specimens followed a similar regime as the nanoparticles increased for the specimens cured in saturated limewater,some experimental relationships has been presented to correlate these two properties of concrete for this curing *** the whole,it has been concluded that the abrasion resistance of concrete does not only depend on the corresponding compressive strength.

关键词： nanopartlcles abrasion resistance compressive strength curing medium thermogravimetric analysis XRD SEM

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compressive strength Development and Microstructure of Cement-asphalt Mortar

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Journal of Wuhan University of Technology(Materials Science) 2011年第5期26卷 998-1003页

作者：王强阎培渝 Department of Civil Engineering Tsinghua University

The compressive strength developing process and the microstructure of cement-asphalt mortar （CA mortar） were *** fluidity of CA mortar has a great influence on its *** optimum value of spread diameter of slump flow test is in the range of 300 to 400 *** compressive strength of CA mortar keeps a relatively high growth rate in 56 days and grows slowly *** residual water of hydration in CA mortar freezes under minus environmental temperature which can lead to a significant reduction of the strength of CA *** A/C retards asphalt emulsion splitting and thus prolongs the setting process of CA *** hydration products of cement form the major structural framework of hardened CA mortar and asphalt is a weak phase in the framework but improves the viscoelastic behavior of CA ***,asphalt emulsion should be used as much as possible on the condition that essential performance criterions of CA mortar are satisfied.

关键词： asphalt emulsion compressive strength CA mortar microstructure

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compressive strength of Polymer Grouting Material at Different Temperatures

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Journal of Wuhan University of Technology(Materials Science) 2010年第6期25卷 962-965页

作者：石明生 Faculty of Infrastructure Engineering Dalian University of Technology School of Water Conservancy and Environment Zhengzhou University

In order to study the influence of temperature on compressive strength of polymer grouting material,the compression specimen injection mold is self-made,and the uniaxial compressive test was carried out in the temperature control box under different *** change regularity of compressive strength of polymer grouting material under different temperatures and the law of volume changes of polymer samples were *** experimental results show that：the compressive strength of polymer material increases with the increase of density;the temperature change has a certain influence on the compressive strength of polymer grouting material;the compressive strength decreases with temperature increases under the same density,but the compressive strength is not significantly affected by temperature when the density is less than 0.4 g/cm3;the volume change of the samples accords with the law of thermal expansion and contraction when temperature changes,and the increase of the volume is obvious when it is under high *** achievements will provide an important basis to the application of the polymer grouting material.

关键词： polymer grouting material compressive strength density temperature volume

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compressive strength Estimation for the Fiber-Reinforced Polymer (FRP)-Confined Concrete Columns with Different Shapes Using Artificial Neural Networks

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Journal of Donghua University(English Edition) 2015年第3期32卷 395-400页

作者：曹玉贵李小青胡隽 College of Civil Engineering and Mechanics Huazhong University of Science and Technology

An evaluation of existing strength of concrete columns confined with fiber-reinforced polymer( FRP) was presented with extensive collection of experimental data. According to the evaluation results, artificial neural networks( ANNs) model to predict the ultimate strength of FRP confined column with different shapes was proposed. The models had seven inputs including the column length,the tensile strength of the FRP in the hoop direction,the total thickness of FRP,the diameter of the concrete specimen,the elastic modulus of FRP,the corner radius and the concrete compressive strength. The compressive strength of the confined concrete was the output data. The results reveal that the proposed models have good prediction and generalization capacity with acceptable errors.

关键词： compressive strength concrete column artificial neural networks(ANN) fiber-reinforced polymer(FRP)

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compressive strength of Hydrostatic-Stress-Sensitive Materials at High Strain-Rates

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Transactions of Tianjin University 2008年第5期14卷 324-328页

作者： LI QM LU YB School of Mechanical Aerospace and Civil Engineering The University of Manchester PO Box 88 Manchester M60 1QD UK

Many engineering materials demonstrate dynamic enhancement of their compressive strength with the increase of strain-rate, which have been included in material models to improve the reliability of numerical simulations of the material and structural responses under impact and blast loads. The strain-rate effects on the dynamic compressive strength of a range of engineering materials which behave in hydrostatic-stress-sensitive manner were investigated. It is concluded that the dynamic enhancement of the compressive strength of a hydrostatic-stress-sensitive material may include inertia-induced lateral confinement effects, which, as a non-strain-rate factor, may greatly enhance the compressive strength of these materials. Some empirical formulae based on the dynamic stress-strain measurements over-predict the strain-rate effects on the compressive strength of these hydrostatic-stress-sensitive materials, and thus may over-estimate the structural resistance to impact and blast loads, leading to non-conservative design of protective structures.

关键词： hydrostatic-stress-sensitive materials split Hopkinson pressure bar dynamic increase factor compressive strength numerical simulation

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