Plain concrete is strong in compression but brittle in tension,having a low tensile strain capacity that can significantly degrade the long-term performance of concrete structures,even when steel reinforcing is presen...Plain concrete is strong in compression but brittle in tension,having a low tensile strain capacity that can significantly degrade the long-term performance of concrete structures,even when steel reinforcing is present.In order to address these challenges,short polymer fibers are randomly dispersed in a cement-based matrix to forma highly ductile engineered cementitious composite(ECC).Thismaterial exhibits high ductility under tensile forces,with its tensile strain being several hundred times greater than conventional concrete.Since concrete is inherently weak in tension,the tensile strain capacity(TSC)has become one of the most extensively researched properties.As a result,developing a model to predict the TSC of the ECC and to optimize the mixture proportions becomes challenging.Meanwhile,the effort required for laboratory trial batches to determine the TSC is reduced.To achieve the research objectives,five distinct models,artificial neural network(ANN),nonlinear model(NLR),linear relationship model(LR),multi-logistic model(MLR),and M5P-tree model(M5P),are investigated and employed to predict the TSCof ECCmixtures containing fly ash.Data from115 mixtures are gathered and analyzed to develop a new model.The input variables include mixture proportions,fiber length and diameter,and the time required for curing the various mixtures.The model’s effectiveness is evaluated and verified based on statistical parameters such as R2,mean absolute error(MAE),scatter index(SI),root mean squared error(RMSE),and objective function(OBJ)value.Consequently,the ANN model outperforms the others in predicting the TSC of the ECC,with RMSE,MAE,OBJ,SI,and R2 values of 0.42%,0.3%,0.33%,0.135%,and 0.98,respectively.展开更多
This study investigates the efficacy of sodium alginate(SA),xanthan gum(XG),guar gum(GG)and chitosan(CS)d each applied at five different solid biopolymer-to-water mass ratios(or dosages)and cured for 7 d and 28 d d on...This study investigates the efficacy of sodium alginate(SA),xanthan gum(XG),guar gum(GG)and chitosan(CS)d each applied at five different solid biopolymer-to-water mass ratios(or dosages)and cured for 7 d and 28 d d on the unconfined compressive strength(UCS)performance of a high plasticity clayey soil.Moreover,on identifying the optimum biopolymer-treatment scenarios,their performance was compared against conventional stabilization using hydrated lime.For a given curing time,the UCS for all biopolymers followed a riseefall trend with increasing biopolymer dosage,peaking at an optimum dosage and then subsequently decreasing,such that all biopolymer-stabilized samples mobilized higher UCS values compared to the unamended soil.The optimum dosage was found to be 1.5%for SA,XG and CS,while a notably lower dosage of 0.5%was deemed optimum for GG.Similarly,for a given biopolymer type and dosage,increasing the curing time from 7 d to 28 d further enhanced the UCS,with the achieved improvements being generally more pronounced for XG-and CS-treated cases.None of the investigated biopolymers was able to produce UCS improvements equivalent to those obtained by the 28-d soilelime samples;however,the optimum XG,GG and CS dosages,particularly after 28 d of curing,were easily able to replicate 7-d lime stabilization outcomes achieved with as high as twice the soil’s lime demand.Finally,the fundamental principles of clay chemistry,in conjunction with the soil mechanics framework,were employed to identify and discuss the clayebiopolymer stabilization mechanisms.展开更多
文摘Plain concrete is strong in compression but brittle in tension,having a low tensile strain capacity that can significantly degrade the long-term performance of concrete structures,even when steel reinforcing is present.In order to address these challenges,short polymer fibers are randomly dispersed in a cement-based matrix to forma highly ductile engineered cementitious composite(ECC).Thismaterial exhibits high ductility under tensile forces,with its tensile strain being several hundred times greater than conventional concrete.Since concrete is inherently weak in tension,the tensile strain capacity(TSC)has become one of the most extensively researched properties.As a result,developing a model to predict the TSC of the ECC and to optimize the mixture proportions becomes challenging.Meanwhile,the effort required for laboratory trial batches to determine the TSC is reduced.To achieve the research objectives,five distinct models,artificial neural network(ANN),nonlinear model(NLR),linear relationship model(LR),multi-logistic model(MLR),and M5P-tree model(M5P),are investigated and employed to predict the TSCof ECCmixtures containing fly ash.Data from115 mixtures are gathered and analyzed to develop a new model.The input variables include mixture proportions,fiber length and diameter,and the time required for curing the various mixtures.The model’s effectiveness is evaluated and verified based on statistical parameters such as R2,mean absolute error(MAE),scatter index(SI),root mean squared error(RMSE),and objective function(OBJ)value.Consequently,the ANN model outperforms the others in predicting the TSC of the ECC,with RMSE,MAE,OBJ,SI,and R2 values of 0.42%,0.3%,0.33%,0.135%,and 0.98,respectively.
基金supported by an Australian Government Research Training Program(RTP)scholarship.
文摘This study investigates the efficacy of sodium alginate(SA),xanthan gum(XG),guar gum(GG)and chitosan(CS)d each applied at five different solid biopolymer-to-water mass ratios(or dosages)and cured for 7 d and 28 d d on the unconfined compressive strength(UCS)performance of a high plasticity clayey soil.Moreover,on identifying the optimum biopolymer-treatment scenarios,their performance was compared against conventional stabilization using hydrated lime.For a given curing time,the UCS for all biopolymers followed a riseefall trend with increasing biopolymer dosage,peaking at an optimum dosage and then subsequently decreasing,such that all biopolymer-stabilized samples mobilized higher UCS values compared to the unamended soil.The optimum dosage was found to be 1.5%for SA,XG and CS,while a notably lower dosage of 0.5%was deemed optimum for GG.Similarly,for a given biopolymer type and dosage,increasing the curing time from 7 d to 28 d further enhanced the UCS,with the achieved improvements being generally more pronounced for XG-and CS-treated cases.None of the investigated biopolymers was able to produce UCS improvements equivalent to those obtained by the 28-d soilelime samples;however,the optimum XG,GG and CS dosages,particularly after 28 d of curing,were easily able to replicate 7-d lime stabilization outcomes achieved with as high as twice the soil’s lime demand.Finally,the fundamental principles of clay chemistry,in conjunction with the soil mechanics framework,were employed to identify and discuss the clayebiopolymer stabilization mechanisms.
