One issue with layer application of roller compacted concrete(RCC)is the development of cold joints,which can cause damage to RCC *** this study,fly ash was used in place of 0%,20%,40%,and 60%of the cement or aggregat...
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One issue with layer application of roller compacted concrete(RCC)is the development of cold joints,which can cause damage to RCC *** this study,fly ash was used in place of 0%,20%,40%,and 60%of the cement or aggregate to examine the impact of interlayer cold joint formation on RCC *** promote cold joint formation,the second layer was placed and compacted with a delay of 0,60,120,or 180 min after the first *** methods were tried for preventing cold joints from forming:one was to apply a bedding mortar to the interlayer,another was to add a set retarder admixture,and the third was to spray an adhesion-enhancing chemical additive on the surface of the first *** on the 28 d specimens’compressive and splitting-tensile strengths as well as the depth of water penetration under pressure,the most effective method was found to be applying interlayer bedding *** 180 min delayed layer castings,the splitting-tensile and compressive strengths of the control samples decreased by 31%and 17%,respectively,while the strengths of mixtures applying interlayer bedding mortar decreased by 9%and 10%.In addition,bedding mortar treatment decreased the water permeability by 59%compared to the *** cold joint decreased all mixtures’moduli of elasticity,regardless of the age of the *** the interlayer delay was 60 min,the modulus of elasticity decreased by 1%–4%.It was between 2%and 14%,and between 10%and 24%at 120 and 180 min for the interlayer *** longer the delay in placing the second RCC layer,the more detrimental the effect of the cold *** effect was most noticeable on mechanical and permeability properties tested with applied load or water pressure parallel to the cold joint,such as flexural and splitting tensile strengths and water penetration depth under pressure.
The road construction industry aims to contribute to the protection of already compromised *** mix asphalt(CMA)is a measure initiated by the road industry to protect the environment and preserve *** having additional ...
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The road construction industry aims to contribute to the protection of already compromised *** mix asphalt(CMA)is a measure initiated by the road industry to protect the environment and preserve *** having additional benefits,CMA has attracted little attention due to its inferior ***'s performance is enhanced using a sustainable binder bio-modifier,natural cup lump rubber(CLR)is one of *** study evaluated the tensile properties,rutting,moisture susceptibility,and adhesion properties of CLR-modified CMA(CMA-CR).The tensile property was enhanced by 26%due to CLR ***-CR had excellent rutting resistance of less than 2 mm rut depth at 10,000 load cycles,showing 70%improvement compared with conventional *** susceptibility evaluation indicated that CMA-CR had tensile strength ratio(TSR)value of 104%,satisfying the minimum 80%requirement of AASHTO *** also retained more than 96%bitumen *** moisture damage resistance was improved by 12%and 10%in terms of TSR and stripping,*** durability results revealed that the CMA-CR mixture prevented higher mass loss,representing 14%improvement compared with conventional CMA.
Alkali-activated materials/geopolymer(AAMs),due to their low carbon emission content,have been the focus of recent studies on ecological *** terms of performance,fly ash and slag are preferredmaterials for precursors ...
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Alkali-activated materials/geopolymer(AAMs),due to their low carbon emission content,have been the focus of recent studies on ecological *** terms of performance,fly ash and slag are preferredmaterials for precursors for developing a one-part ***,determining the optimum content of the input parameters to obtain adequate performance is quite challenging and scarcely ***,in this study,machine learning methods such as artificial neural networks(ANN)and gene expression programming(GEP)models were developed usingMATLAB and GeneXprotools,respectively,for the prediction of compressive strength under variable input materials and content for fly ash and slag-based one-part *** database for this study contains 171 points extracted from literature with input parameters:fly ash concentration,slag content,calcium hydroxide content,sodium oxide dose,water binder ratio,and curing *** performance of the two models was evaluated under various statistical indices,namely correlation coefficient(R),mean absolute error(MAE),and rootmean square error(RMSE).In terms of the strength prediction efficacy of a one-part geopolymer,ANN outperformed *** and parametric analysis were also performed to identify the significant contributor to *** to a sensitivity analysis,the activator and slag contents had the most effects on the compressive strength at 28 *** water binder ratio was shown to be directly connected to activator percentage,slag percentage,and calcium hydroxide percentage and inversely related to compressive strength at 28 days and curing temperature.
The interactions between reinforced concrete(RC)frames and infill walls play an important role in the seismic response of frames,particularly for low-rise *** walls can increase the overall lateral strength and stiffn...
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The interactions between reinforced concrete(RC)frames and infill walls play an important role in the seismic response of frames,particularly for low-rise *** walls can increase the overall lateral strength and stiffness of the frame owing to their high strength and ***,local wall-frame interactions can also lead to increased shear demand in the columns owing to the compressive diagonal strut force from the infill wall,which can result in failure or in serious situations,*** this study,the effectiveness of a design strategy to consider the complex infill wall interaction was *** approach was used to design example RC frames with infill walls in locations with different seismicity levels in *** performance of these frames was assessed using nonlinear static,and dynamic *** performance of the frames and the failure modes were compared with those of frames designed without considering the infill wall or the local *** was found that even though the overall responses of the buildings designed with and without consideration of the local interaction of the infill walls were similar in terms the overall lateral strength,the failure modes were *** proposed method can eliminate the column shear failure from the ***,the merits and limitations of this approach are discussed and summarized.
Surface wave inversion is a key step in the application of surface waves to soil velocity ***,a common practice for the process of inversion is that the number of soil layers is assumed to be known before using heuris...
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Surface wave inversion is a key step in the application of surface waves to soil velocity ***,a common practice for the process of inversion is that the number of soil layers is assumed to be known before using heuristic search algorithms to compute the shear wave velocity profile or the number of soil layers is considered as an optimization ***,an improper selection of the number of layers may lead to an incorrect shear wave velocity *** this study,a deep learning and genetic algorithm hybrid learning procedure is proposed to perform the surface wave inversion without the need to assume the number of soil ***,a deep neural network is adapted to learn from a large number of synthetic dispersion curves for inferring the layer ***,the shear-wave velocity profile is determined by a genetic algorithm with the known layer *** applying this procedure to both simulated and real-world cases,the results indicate that the proposed method is reliable and efficient for surface wave inversion.
The accurate prediction of bearing capacity is crucial in ensuring the structural integrity and safety of pile *** research compares the Deep Neural Networks(DNN),Convolutional Neural Networks(CNN),Recurrent Neural Ne...
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The accurate prediction of bearing capacity is crucial in ensuring the structural integrity and safety of pile *** research compares the Deep Neural Networks(DNN),Convolutional Neural Networks(CNN),Recurrent Neural Networks(RNN),Long Short-Term Memory(LSTM),and Bidirectional LSTM(BiLSTM)algorithms utilizing a data set of 257 dynamic pile load tests for the first ***,this research illustrates the multicollinearity effect on DNN,CNN,RNN,LSTM,and BiLSTM models’performance and accuracy for the first time.A comprehensive comparative analysis is conducted,employing various statistical performance parameters,rank analysis,and error matrix to evaluate the performance of these *** performance is further validated using external validation,and visual interpretation is provided using the regression error characteristics(REC)curve and Taylor *** from the comparative analysis reveal that the DNN(Coefficient of determination(R^(2))_(training(TR))=0.97,root mean squared error(RMSE)_(TR)=0.0413;R^(2)_(testing(TS))=0.9,RMSE_(TS)=0.08)followed by BiLSTM(R^(2)_(TR)=0.91,RMSE_(TR)=0.782;R^(2)_(TS)=0.89,RMSE_(TS)=0.0862)model demonstrates the highest performance *** is noted that the BiLSTM model is better than LSTM because the BiLSTM model,which increases the amount of information for the network,is a sequence processing model made up of two LSTMs,one of which takes the input in a forward manner,and the other in a backward *** prediction of pile-bearing capacity is strongly influenced by ram weight(having a considerable multicollinearity level),and the effect of the considerable multicollinearity level has been determined for the model based on the recurrent neural network *** this study,the recurrent neural network model has the least performance and accuracy in predicting the pile-bearing capacity.
This study aims to investigate the influence of various vegetation patches with varying porosities on the hydraulic properties of a vegetated open channel under subcritical flow *** research work investigated three ty...
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This study aims to investigate the influence of various vegetation patches with varying porosities on the hydraulic properties of a vegetated open channel under subcritical flow *** research work investigated three types of vegetation patches:Rigid,flexible,and a combination of the *** total five vegetation patches with three different porosities for each patch were *** of these vegetation patches on various hydraulic parameters such as backwater rise,energy reduction,water surface slope in the vegetation patch,hydraulic jump formation on the downstream side of the vegetation patch,reduction in fluid force index(RFI),moment index(RMI),overflow volume(ΔQ)were *** findings revealed that the backwater rise increased in the case of rigid patch as the initial Froude number increased,whereas it decreased in the case of flexible and combined vegetation *** was observed that as the porosity increased from low(P_(r)=0.90)to high(P_(r)=0.99),the backwater rise decreased for all vegetation *** relative energy reduction rate increased for the rigid patch and showed a reverse trend for the flexible and combined vegetation patches with increasing initial Froude *** the combined vegetation arrangement,the energy reduction values were highest for the alternate rigid and flexible(ARF)vegetation patches and lowest for the longitudinal rigid and flexible(LRF)vegetation *** study identified the presence of a hydraulic jump downstream of the vegetation patch,as indicated by the Froude number in the range of 1.0–*** study also found that RFI,RMI,ΔQ had the highest values of 19.05%,19.05%,80.20%.The results of this study provide insight into the impact of vegetation patches with varying porosities on open-channel flow characteristics and can help develop sustainable vegetation management strategies.
In this study,the instability and bifurcation diagrams of a functionally graded(FG)porous sandwich beam on an elastic,viscous foundation which is influenced by an axial load,are investigated with an analytical *** do ...
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In this study,the instability and bifurcation diagrams of a functionally graded(FG)porous sandwich beam on an elastic,viscous foundation which is influenced by an axial load,are investigated with an analytical *** do so,the Timoshenko beam theory is utilized to take the shear deformations into account,and the nonlinear Von-Karman approach is adopted to acquire the equations of ***,to turn the partial differential equations(PDEs)into ordinary differential equations(ODEs)in the case of equations of motion,the method of Galerkin is employed,followed by the multiple time scale method to solve the resulting *** impact of parameters affecting the response of the beam,including the porosity distribution,porosity coefficient,temperature increments,slenderness,thickness,and damping ratios,are explicitly *** is found that the parameters mentioned above affect the bifurcation points and instability of the sandwich porous beams,some of which,including the effect of temperature and porosity distribution,are less noticeable.
The study aims to develop machine learning-based mechanisms that can accurately predict the axial capacity of high-strength concrete-filled steel tube(CFST)*** predicting the axial capacity of a CFST column is always ...
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The study aims to develop machine learning-based mechanisms that can accurately predict the axial capacity of high-strength concrete-filled steel tube(CFST)*** predicting the axial capacity of a CFST column is always challenging for *** artificial neural networks(ANNs),random forest(RF),and extreme gradient boosting(XG-Boost),a total of 165 experimental data sets were *** selected input parameters included the steel tensile strength,concrete compressive strength,tube diameter,tube thickness,and column *** results indicated that the ANN and RF demonstrated a coefficient of determination(R2)value of 0.965 and 0.952 during the training and 0.923 and 0.793 during the testing *** most effective technique was the XG-Boost due to its high efficiency,optimizing the gradient boosting,capturing complex patterns,and incorporating regularization to prevent *** outstanding R2 values of 0.991 and 0.946 during the training and testing were *** to flexibility in model hyperparameter tuning and customization options,the XG-Boost model demonstrated the lowest values of root mean square error and mean absolute error compared to the other *** to the findings,the diameter of CFST columns has the greatest impact on the output,while the column length has the least influence on the ultimate bearing capacity.
The performance of concrete-filled steel tubular (CFST) composite joints needs to be investigated under different loading types. Thus, the influential parameters should be evaluated with an aim to enhance the load-bea...
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