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
The split Hopkinson pressure bar （SHPB） testing with diameter 40 mm was used to investigate the dynamic mechanical properties of engineered cementitious composites （ECCs） with different fly ash content. The basic ...The split Hopkinson pressure bar （SHPB） testing with diameter 40 mm was used to investigate the dynamic mechanical properties of engineered cementitious composites （ECCs） with different fly ash content. The basic properties including deformation, energy absorption capacity, strain-stress relationship and failure patterns were discussed. The ECCs showed strain-rate dependency and kept better plastic flow during impact process compared with reactive powder concrete （RPC） and concrete, but the critical compressive strength was lower than that of RPC and concrete. The bridging effect of PVA fiber and addition of fly ash can significantly improve the deformation and energy absorption capacities of ECCs. With the increase of fly ash content in ECCs, the static and dynamic compressive strength lowered and the dynamic increase factor enhanced. Therefore, to meet different engineering needs, the content of fly ash can be an important index to control the static and dynamic mechanical properties of ECCs.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.
文摘The split Hopkinson pressure bar （SHPB） testing with diameter 40 mm was used to investigate the dynamic mechanical properties of engineered cementitious composites （ECCs） with different fly ash content. The basic properties including deformation, energy absorption capacity, strain-stress relationship and failure patterns were discussed. The ECCs showed strain-rate dependency and kept better plastic flow during impact process compared with reactive powder concrete （RPC） and concrete, but the critical compressive strength was lower than that of RPC and concrete. The bridging effect of PVA fiber and addition of fly ash can significantly improve the deformation and energy absorption capacities of ECCs. With the increase of fly ash content in ECCs, the static and dynamic compressive strength lowered and the dynamic increase factor enhanced. Therefore, to meet different engineering needs, the content of fly ash can be an important index to control the static and dynamic mechanical properties of ECCs.
