In the text of Wolf Totem, there are many spots of indeterminacy left purposely or involuntarily by the author in the depiction of characters, scenes, events and in the use of culture-related expressions, which are to...In the text of Wolf Totem, there are many spots of indeterminacy left purposely or involuntarily by the author in the depiction of characters, scenes, events and in the use of culture-related expressions, which are to be filled in by individual＇s interpretation through active reading of the work. Howard Goldblatt, as the translator of this work, adopts ＂creative rewriting＂ in the translation of Wolf Totem to actualize the indeterminacy and the factors guiding his concretization.展开更多
The application and promotion of waste glass powder concrete(WGPC)cansignificantly alleviate the pressure of concrete material scarcity and environmental pollution.Compressive strength(CS)is a critical parameter for e...The application and promotion of waste glass powder concrete(WGPC)cansignificantly alleviate the pressure of concrete material scarcity and environmental pollution.Compressive strength(CS)is a critical parameter for evaluating the efficacy of WGPC.Unlike conventional testing methods,machine learning techniques offer precise and reliable predictions of concrete’s compressive strength,especially in its long-term mechanical properties.In this work,four models,namely Multiple Linear Regression(MLR),Back Propagation Neural Network(BPNN),Support Vector Regression(SVR),and Random Forest Regression(RFR)were employed.Furthermore,particle swarm optimization(PSO)algorithm and cross-validation techniques were applied to fine-tune the model parameters,striving for peak prediction performance.The results indicated that optimized models generally exhibit enhanced predictive accuracy compared to their basic counterparts.Notably,the PSO-RFR model excels among all evaluated models,showcasing superior performance on the testing dataset.It achieves a coefficient of determination(R^(2))of 0.9231,a mean absolute error(MAE)of 2.1073,and a root mean square error(RMSE)of 3.6903.When compared to experimental results,the PSO-RFR and PSO-BPNN models demonstrate exceptional predictive accuracy.Notably,the PSO-BPNN model exhibits the closest R^(2)values between its training and test sets.This close alignment of R^(2)values between the training and testing sets reflects the PSO-BPNN model’s superior generalization ability for unseen data.The findings present an efficient method for predicting concrete’s compressive strength,contributing to the sustainable development of concrete materials,and providing theoretical support for their research and application.展开更多
This study investigates the impact of Type D additive,Plastiment 83 AM,on the compressive strength and microstructure of Portland Composite Cement(PCC)concrete with a target compressive strength of 18.7 MPa,utilizing ...This study investigates the impact of Type D additive,Plastiment 83 AM,on the compressive strength and microstructure of Portland Composite Cement(PCC)concrete with a target compressive strength of 18.7 MPa,utilizing a mixing,stirring,and treatment model that simulates batching plant conditions.The study investigated additive dosages of 0%,0.15%,0.25%,0.35%,and 0.40%,with stirring durations of 15 min,2,4,6,and 6.5 h.Compressive strength tests were conducted at the ages of 7,14,28,56,and 90 days on cylindrical specimens,and at 24 h for setting time tests.Microstructural analysis using Energy Dispersive X-ray Spectroscopy(EDX)was performed at 56 days of age.The results showed that the optimal dosage was 0.15%,combined with the addition of Plastiment 83 AM 0.10%at 2 h of stirring,which achieved the highest compressive strength of 20.5 MPa at 90 days.A reduction in compressive strength of the setting time samples from the initial value to 24 h was observed in mixtures stirred for 6 and 6.5 h.A decrease in compressive strength was also observed in both mixtures between 56 and 90 days.EDX analysis revealed different chemical compositions in each mix.At a stirring duration of 6 and 6.5 h,Plastiment 83 AM dosages of 0.35%and 0.40%showed the presence of Magnesium(Mg)and Aluminium(Al)(at 6 h)and Al and phosphorus(at 6.5 h).The presence of inhibited the hydration process,resulting in a very small increase in compressive strength from 14 to 28 days.Magnesium reduced the compressive strength to 75%,and phosphorus to 63%of the target compressive strength.展开更多
This study introduces superabsorbent polymers(SAP)into recycled concrete and,through freeze-thaw cycle tests,unconfined compressive strength tests,and nuclear magnetic resonance(NMR)analysis,evaluates the freeze-thaw ...This study introduces superabsorbent polymers(SAP)into recycled concrete and,through freeze-thaw cycle tests,unconfined compressive strength tests,and nuclear magnetic resonance(NMR)analysis,evaluates the freeze-thaw resistance and durability of recycled concrete samples under varying freeze-thaw cycles.The results indicate that an appropriate addition of SAP significantly enhances the freeze-thaw resistance of recycled concrete.After 200 freeze-thaw cycles,the RS0.6 sample retained good surface integrity,demonstrating the best performance.Compared to NAC,its mass loss decreased by 1.16%,the relative dynamic modulus improved by 7.01%,and the compressive strength loss rate decreased by 5.41%.Additionally,T2 spectrum analysis revealed that adding SAP optimized the pore structure of recycled concrete and mitigated pore development during freeze-thaw cycles.As the number of freeze-thaw cycles increased,the RS0.3 and RS0.6 samples demonstrated superior frost resistance compared to NAC.However,an excessive amount of SAP increased pore expansion during subsequent freeze-thaw cycles,ultimately weakening frost resistance.展开更多
In strong aggressive areas,Indonesian standards specify a maximum penetration of 30 mm.Concrete utilizes sulfate-resistant Portland Pozzolan Cement(PPC)for a target strength of 30 MPa,with and without silica fume and ...In strong aggressive areas,Indonesian standards specify a maximum penetration of 30 mm.Concrete utilizes sulfate-resistant Portland Pozzolan Cement(PPC)for a target strength of 30 MPa,with and without silica fume and plastic fiber(SR-SFF-sea and SR-N-SFF).Some samples of SR-N-SFF are immersed in the sea(SR-N-SFF-sea),while others are protected(SR-N-SFF-protected).Additionally,concrete using non-sulfate-resistant cement(NSR-sea)with a strength of 20.75 MPa was also evaluated.All samples were subjected to penetration depth testing according to the DIN EN 12390-8 standard,demonstrating that they met the penetration requirements for intense aggression.The study employed cylindrical samples measuring 15 cm in diameter and 30 cm in height to assess compressive strength and natural penetration fromthe split tensile test.Samples were placed into the sea at the fishing boat dock in Lampung,Indonesia,at 9 days of age following 7 days of immersion curing.The results indicated that sulfate-resistant Portland Composite Cement(PCC)is unsuitable for protected areas,as its strength is inferior to that of concrete submerged in seawater.Concrete featuring sulfate-resistant PCC,silica fume,and plastic fiber(SR-SFF-sea)exhibited lower strength compared to SR-N-SFF-protected samples.Conversely,SR-N-SFF-sea achieved the highest strength of 46 MPa at 56 days,with a notable increase in strength occurring from 21 to 56 days,while no increase in penetration depth was observed during this period.The standard penetration depth of SR-N-SFF-sea is 17.8mm,which can serve as a guideline for creating durable concrete in marine environments.展开更多
Received:06 December 2025;Accepted:25 February 2026;Published:30 March 2026 ABSTRACT:In the last decade,the importance of sustainable construction and artificial intelligence(AI)in civil engineering has been underline...Received:06 December 2025;Accepted:25 February 2026;Published:30 March 2026 ABSTRACT:In the last decade,the importance of sustainable construction and artificial intelligence(AI)in civil engineering has been underlined in many studies.Numerous studies highlighted the superiority of AI techniques over simple and mathematical regression analyses,which suffer from relatively poor generalization and an inability to capture highly non-linear relationships among inputs and output(s)parameters.In this study,to evaluate the compressive strength of concrete with glass powder(GP)and recycled aggregates,600 concrete samples were tested in the laboratory,and their results were evaluated.For intelligent assessment of concrete compressive strength(CCS),the study utilized an improved artificial neural network(ANN)with particle swarm optimization(PSO)algorithm and imperialist competitive algorithm(ICA).For training the models,the experimentally obtained data were used.The concrete ingredients formed the inputs of the AI-based predictive models of CCS.The experimental findings reveal that the implementation of recycled coarse aggregates in concrete from a sustainable construction point of view is advantageous and can enhance the CCS by 11.43%.Apart from that,findings indicate that utilization of 10%GP can lead to a nearly 20%increase in CCS(from 44.6 to 54.1 MPa).Additionally,the experimental observations show almost 40%improvement of CCS when 5%micro silica was used in the concrete mixture.Based on the findings,the study suggests the utilization of waste glass powder to partially replace cement in concrete,which can reduce the amount of cement production.This reduction from economic,energy-saving,and environmental(reduction in greenhouse gas emissions)points of view is of interest.On the other hand,the AI results show that the PSO-based ANN model outperforms the ICA-based ANN for the utilized dataset.According to the findings,the PSO-based ANN predictive model(with a coefficient of determination value of 0.939 and root mean square value of 0.113 for testing data)is a capable tool in predicting the CCS.Hence,this study recommends the implementation of AI-based models in CCS assessment.展开更多
This study aimed to investigate the influence of recycled sand(RS)content and water-binder ratio on the long term performance of recycled sand concrete(RSC).A 220 days drying shrinkage and creep test of RSC was conduc...This study aimed to investigate the influence of recycled sand(RS)content and water-binder ratio on the long term performance of recycled sand concrete(RSC).A 220 days drying shrinkage and creep test of RSC was conducted,and the microhardness of ITZ were analyzed to explain the differences in performance.The experimental results indicate that,when RS content is 50%,the drying shrinkage and creep strain of RSC is the smallest.This is attributed to the highest microhardness in the ITZ when the RS content is 50%.When the RS content is 100%,the shrinkage and creep strains increase due to the high water absorption of RS,which leads to the evaporation of additional water and the deterioration of the ITZ.As the water-binder ratio increases,the drying shrinkage and creep strain of RSC with different RS content increases.According to the EC2 specification and the CEB-FIP specification,the drying shrinkage and creep prediction models for RSC have been established.展开更多
We investigated the effects of fly ash(FA)content on the mechanical properties of recycled aggregate concrete(RAC)and its regeneration potential under freeze and thaw(F-T)cycles.The physical properties of second-gener...We investigated the effects of fly ash(FA)content on the mechanical properties of recycled aggregate concrete(RAC)and its regeneration potential under freeze and thaw(F-T)cycles.The physical properties of second-generation recycled concrete aggregates(RCA)were used to analyze the regeneration potential of RAC after F-T cycles.Scanning electron microscopy was used to study the interfacial transition zone microstructure of RAC after F-T cycles.Results showed that adding 20%FA to RAC significantly enhanced its mechanical properties and frost resistance.Before the F-T cycles,the compressive strength of RAC with 20%FA reached 48.3 MPa,exceeding research strength target of 40 MPa.A majority of second-generation RCA with FA had been verified to attain class Ⅲ,which enabled their practical application in non-structural projects such as backfill trenches and road pavement.However,the second-generation RCA with 20%FA can achieve class Ⅱ,making it ideal for 40 MPa structural concrete.展开更多
The engineering application of low-alkali sulphoaluminate cement(L-SAC)is hindered due to the difficulty in adjusting the setting and hardening time.In this paper,lithium hydroxide and borax are mixed into L-SAC to re...The engineering application of low-alkali sulphoaluminate cement(L-SAC)is hindered due to the difficulty in adjusting the setting and hardening time.In this paper,lithium hydroxide and borax are mixed into L-SAC to regulate its setting and hardening process,so as to prepare a sulphoaluminate concrete material with high early strength and high fluidity.The effects of the ratio of lithium hydroxide to borax on the properties of L-SAC concrete were studied by hydration heat,XRD,TG-DTG,SEM and MIP.The experimental results show that the slump increases with the increase of borax content,and the early(3 h)strength increases with the increase of lithium hydroxide content.When 0.05% lithium hydroxide and 0.4% borax are added,the 0.5 h slump reaches 195 mm,and the 3 h compressive strength reaches 15.9 MPa.The increase of lithium hydroxide will promote the formation of early hydration products AFt and AH3 gel and accelerate the hydration process,while borax will inhibit the dissolution and hydration of cement and delay the setting and hardening process of concrete.The combination of the two ensures that the concrete has the characteristics of high early strength and high fluidity,and the early workability and mechanical properties can be controlled by the mix ratio.For long-term mechanical properties,the special concrete does not produce AFm,which can ensure the continuous development of strength.展开更多
Based on the split hopkinson pressure bar(SHPB)tests results,the cubic specimens have been numerically modeled in this paper to investigate the impact of key factors,such as the rise time,duration,and incident pulse s...Based on the split hopkinson pressure bar(SHPB)tests results,the cubic specimens have been numerically modeled in this paper to investigate the impact of key factors,such as the rise time,duration,and incident pulse shape,on achieving stress uniformity.After analysis,the paper provides actionable methods aimed at optimizing the conditions for stress uniformity within the cubic specimen.Finally,the lateral inertia effect of cubic specimen has been scrutinized to address the existing gap in this academic area.展开更多
A comprehensive full-sieve-hole grading correction method was used to adjust aggregate gradings.The fatigue properties of recycled concrete aggregate(RCA)asphalt mixtures were investigated using an improved indirect t...A comprehensive full-sieve-hole grading correction method was used to adjust aggregate gradings.The fatigue properties of recycled concrete aggregate(RCA)asphalt mixtures were investigated using an improved indirect tensile fatigue test under temperature-humidity coupling based on 20-year meteorological data of Beijing,and the degeneration mechanism was further explored by scanning electron microscopy and energy-dispersive spectroscopy.The experimental results indicate that replacing 5-20 mm coarse limestone aggregate(LA)with RCA at a 50% substitution volume can mitigate the impact of RCA variations on the asphalt mixture proportioning design.All RCA asphalt mixtures have lower initial fatigue properties than the LA asphalt mixture.However,under temperature-humidity coupling,the long-term fatigue property of an RCA asphalt mixture with a low proportion of recycled brick exceeds that of the LA asphalt mixture,and the fatigue life decline rate of the RCA asphalt mixture during 10-year service decreases by approximately 25%.This is due to the penetration of the asphalt mortar into the RCA through the pores and cracks on the RCA surface.It forms an interfacial transition zone composed of asphalt mortar and cement mortar and further reduces the mixture damage caused by the water and freeze-thaw conditions.展开更多
Nonlinear static procedures are widely adopted in structural engineering practice for seismic performance assessment due to their simplicity and computational efficiency.However,their reliability depends heavily on ho...Nonlinear static procedures are widely adopted in structural engineering practice for seismic performance assessment due to their simplicity and computational efficiency.However,their reliability depends heavily on how the nonlinear behaviour of structural components is represented.The recent earthquakes in Albania(2019)and Türkiye(2023)have underscored the need for accurate assessment techniques,particularly for older reinforced concrete buildings with poor detailing.This study quantifies the discrepancies between default and user-defined component modelling in pushover analysis of pre-modern reinforced concrete structures,analysing two representative low-and mid-rise reinforced concrete frame buildings.The lumped plasticity approach incorporates moment-rotation relationships derived from actual member properties and reinforcement configurations,while the distributed plasticity approach uses software-generated default properties based on modern codes.Results show that the distributed plasticity models systematically overestimate both the strength and the deformation capacity by up to 35%compared to lumped plasticity models,especially in buildings with poor detailing and low concrete strength.These findings demonstrate that default software procedures,widely used in practice but not validated for pre-modern structures,produce dangerously unconservative seismic performance estimates.The study provides quantitative evidence of the critical need for tailored modelling strategies that reflect the actual conditions of the existing building stock.展开更多
Accurate prediction of concrete compressive strength is fundamental for optimizing mix designs,improving material utilization,and ensuring structural safety in modern construction.Traditional empirical methods often f...Accurate prediction of concrete compressive strength is fundamental for optimizing mix designs,improving material utilization,and ensuring structural safety in modern construction.Traditional empirical methods often fail to capture the non-linear relationships among concrete constituents,especially with the growing use of supple-mentary cementitious materials and recycled aggregates.This study presents an integrated machine learning framework for concrete strength prediction,combining advanced regression models—namely CatBoost—with metaheuristic optimization algorithms,with a particular focus on the Somersaulting Spider Optimizer(SSO).A comprehensive dataset encompassing diverse mix proportions and material types was used to evaluate baseline machine learning models,including CatBoost,XGBoost,ExtraTrees,and RandomForest.Among these,CatBoost demonstrated superior accuracy across multiple performance metrics.To further enhance predictive capability,several bio-inspired optimizers were employed for hyperparameter tuning.The SSO-CatBoost hybrid achieved the lowest mean squared error and highest correlation coefficients,outperforming other metaheuristic approaches such as Genetic Algorithm,Particle Swarm Optimization,and Grey Wolf Optimizer.Statistical significance was established through Analysis of Variance and Wilcoxon signed-rank testing,confirming the robustness of the optimized models.The proposed methodology not only delivers improved predictive performance but also offers a transparent framework for mix design optimization,supporting data-driven decision making in sustainable and resilient infrastructure development.展开更多
We employed machine learning approaches and visualization interpretation methods to explore the influencing factors of the compressive strength of sea sand concrete to attain a better understanding of the inherent law...We employed machine learning approaches and visualization interpretation methods to explore the influencing factors of the compressive strength of sea sand concrete to attain a better understanding of the inherent laws of concrete mix design.Four models,including random forest,Cat Boost,XGBoost,and deep neural network,were trained.The experimental results demonstrate that the XGBoost model performs the best in predicting the strength of sea sand concrete.Its R^(2)value reached 0.9999,and evaluation indexes such as MAPE,RMSE,MAE,and MSE are superior to those of other models.The principal component analysis(PCA)was conducted to visually analyze the structure and distribution of the original feature data,and Pearson correlation coefficient analysis and Shapley additive explanation(SHAP)were utilized to explore the impact of input characteristics on the strength of sea sand concrete.SHAP analysis is more conducive to revealing the nonlinear effects of various characteristics on the model prediction results,especially that particle size of stone has significant impacts on the strength of sea sand concrete.In addition,experimental verification was carried out to confirm the accuracy of the optimized training model.These findings offer some insights for the future design and application of sea sand in high-performance marine and coastal infrastructure.展开更多
Severe failures of nonstructural components have occurred during previous earthquakes.Claddings are one of the most widely used nonstructural component and are installed in many modern buildings;therefore,an evaluatio...Severe failures of nonstructural components have occurred during previous earthquakes.Claddings are one of the most widely used nonstructural component and are installed in many modern buildings;therefore,an evaluation of their seismic performance is important and cannot be ignored.To investigate the seismic performance of large-sized high performance concrete cladding(HPCC),a series of full-scale experimental tests were conducted using a unidirectional shaking table.A steel supporting frame was used to install the HPCCs and reproduce the effects of the building under earthquake.The tests were divided into two parts:in-plane(IP)testing and out-plane(OP)testing.Three recorded accelerograms,one artificial accelerogram,and one sinusoidal accelerogram were used to conduct the shaking table tests.The results show that the maximum recorded IP responses of acceleration and interstory drift ratio were 1.04 g and 1/97,while the OP responses were 1.02 g and 1/51.The HPCCs functioned well throughout the entire experimental protocol.The fundamental frequency of the HPCCs systems rarely changed after the tests.展开更多
Utilization of ceramic wastes to fabricate concrete can not only effectively dispose the wastes,but also reduce the energy and source consumptions.Therefore,we fabricated a green ultra high performance concrete using ...Utilization of ceramic wastes to fabricate concrete can not only effectively dispose the wastes,but also reduce the energy and source consumptions.Therefore,we fabricated a green ultra high performance concrete using ceramic waste powder(CWP)to replace 55%of cement,and ceramic waste aggregate(CWA)to replace 100%natural quartz sand.However,high content of ceramic wastes will harm the concrete performance including workability and mechanical properties.Therefore,a low-cost and low carbon nano-calcium carbonate(NC)was introduced to compensate for the defects caused by large amounts of CWP and CWA to workability and mechanical behavior.The experimental results show that the workability of ultra high performance concrete with large amounts of CWP and CWA(UHPCLCC)increases by 28.57%with NC content of 5%.Moreover,the flexural strengths,fracture energy,compressive strengths,and compressive toughness of UHPCLCC increase up to 29.6%,56.5%,20.4%,and 37.6%,respectively,which is caused by the nano-core effect of NC.展开更多
Crushing waste coral concrete into recycled aggregates to create recycled coral aggregate concrete(RCAC)contributes to sustainable construction development on offshore islands and reefs.To investigate the impact of re...Crushing waste coral concrete into recycled aggregates to create recycled coral aggregate concrete(RCAC)contributes to sustainable construction development on offshore islands and reefs.To investigate the impact of recycled coral aggregate on concrete properties,this study performed a comprehensive analysis of the physical properties of recycled coral aggregate and the basic mechanical properties and microstructure of RCAC.The test results indicate that,compared to coral debris,the crushing index of recycled coral aggregate was reduced by 9.4%,while porosity decreased by 33.5%.Furthermore,RCAC retained the early strength characteristics of coral concrete,with compressive strength and flexural strength exhibiting a notable increase as the water-cement ratio decreased.Under identical conditions,the compressive strength and flexural strength of RCAC were 12.7% and 2.5% higher than coral concrete's,respectively,with porosity correspondingly reduced from 3.13% to 5.11%.This enhancement could be attributed to the new mortar filling the recycled coral aggregate.Scanning electron microscopy(SEM)analysis revealed three distinct interface transition zones within RCAC,with the‘new mortar-old mortar’interface identified as the weakest.The above findings provided a reference for the sustainable use of coral concrete in constructing offshore islands.展开更多
This study investigates the influence of loading frequency on the fatigue behavior of ballastless track concrete for high-speed railways,aiming to support the development of concrete capable of withstanding higher ope...This study investigates the influence of loading frequency on the fatigue behavior of ballastless track concrete for high-speed railways,aiming to support the development of concrete capable of withstanding higher operational speeds.Fatigue tests were conducted at loading frequencies ranging from 5 to 40 Hz,with a focus on fatigue life,damage evolution,energy dissipation,and residual fatigue strain in the concrete.The results indicate that between 5 and 15 Hz,the fatigue life and energy dissipation remain relatively stable,with minimal damage evolution and small residual strains.As the frequency increases to 15-20 Hz,the fatigue life and energy dissipation gradually decrease,while damage accumulation and residual strain increase.Beyond 20 Hz,both fatigue life and energy dissipation decrease rapidly,damage accumulation becomes more pronounced,and residual strain continues to rise.These phenomena are primarily attributed to the increased strain rate and load change rate at higher frequencies,which affect the microstructure evolution and lead to reduced fatigue performance.展开更多
Rapid quantification of seismic-induced damage immediately following an earthquake is critical for determining whether a structure is safe for continued occupation or requires evacuation.This study proposes a novel da...Rapid quantification of seismic-induced damage immediately following an earthquake is critical for determining whether a structure is safe for continued occupation or requires evacuation.This study proposes a novel damage identification method that utilizes limited strain data points,significantly reducing installation,maintenance,and data analysis costs compared to traditional distributed sensor networks.The approach integrates finite element(FE)modeling to generate capacity curves through pushover analysis,incorporates noise-augmented datasets for Artificial Neural Network(ANN)training,and classifies structural conditions into four damage levels:Operational(OP),Immediate Occupancy(IO),Life Safety(LS),and Collapse Prevention(CP).To evaluate the method’s accuracy and efficiency,it was applied to two reinforced concrete(RC)frames;a single-story frame tested experimentally under cyclic loading and a three-story frame analyzed under various lateral load patterns.Strain data from selected beam and column ends were used as ANN inputs,while the corresponding damage classes served as outputs.Confusion matrix results demonstrated high true positive rates(>85%for the single-story and>90%for the three-story frame),even with a reduced number of sensors.The model also exhibited strong robustness to White Gaussian Noise(SNR=2.5-5 dB)and generalized effectively to nonlinear time-history analyses under scaled ground motions(PGA=0.1-1.0 g).Feature selection using the MRMR and ANOVA algorithms further enhanced computational efficiency.Overall,the proposed ANN-based framework has strong potential for real-time structural health monitoring applications.展开更多
Conventional low-carbon concrete design approaches have often overlooked carbonation durability and the progressive loss of cover caused by surface scaling,both of which can increase the long-term risk of reinforcemen...Conventional low-carbon concrete design approaches have often overlooked carbonation durability and the progressive loss of cover caused by surface scaling,both of which can increase the long-term risk of reinforcement corrosion.To address these limitations,this study proposes an improved design framework for low-carbon slag concrete that simultaneously incorporates carbonation durability and cover scaling effects into the mix proportioning process.Based on experimental data,a linear predictive model was developed to estimate the 28-day compressive strength of slag concrete,achieving a correlation coefficient of R=0.87711 and a root mean square error(RMSE)of 7.55 MPa.The mechanism-based equation exhibits strong physical interpretability,as each parameter corresponds to a clear physical process,satisfying the requirements of design codes for physical significance.By integrating the strength and carbon-emission models,the carbon-emission efficiency was further analyzed.Across all water–binder ratios(0.3,0.4,0.5),CO_(2) emissions per unit strength decreased steadily with increasing slag content,indicating that carbon efficiency is primarily governed by slag replacement rather than the water/binder ratio.Four design cases,all with a design strength of 30 MPa,were then evaluated to illustrate the combined effects of carbonation and scaling.In Case 1,without considering carbonation durability,the carbonation depth after 50 years exceeded the 25 mm cover,leading to potential corrosion.In Case 2,when carbonation durability was considered,the required actual strength increased to 31.28 MPa.When mild cover scaling of 3 mm was introduced(Case 3),the required strength rose to 34.59 MPa,and under severe scaling of 10 mm(Case 4),it increased to 45.73 MPa.These results indicate that intensified scaling demands higher strength and lower water/binder ratios to maintain durability.Overall,the proposed framework quantitatively balances strength,durability,and embodied carbon,supporting sustainable low-carbon concrete design.展开更多
文摘In the text of Wolf Totem, there are many spots of indeterminacy left purposely or involuntarily by the author in the depiction of characters, scenes, events and in the use of culture-related expressions, which are to be filled in by individual＇s interpretation through active reading of the work. Howard Goldblatt, as the translator of this work, adopts ＂creative rewriting＂ in the translation of Wolf Totem to actualize the indeterminacy and the factors guiding his concretization.
文摘The application and promotion of waste glass powder concrete(WGPC)cansignificantly alleviate the pressure of concrete material scarcity and environmental pollution.Compressive strength(CS)is a critical parameter for evaluating the efficacy of WGPC.Unlike conventional testing methods,machine learning techniques offer precise and reliable predictions of concrete’s compressive strength,especially in its long-term mechanical properties.In this work,four models,namely Multiple Linear Regression(MLR),Back Propagation Neural Network(BPNN),Support Vector Regression(SVR),and Random Forest Regression(RFR)were employed.Furthermore,particle swarm optimization(PSO)algorithm and cross-validation techniques were applied to fine-tune the model parameters,striving for peak prediction performance.The results indicated that optimized models generally exhibit enhanced predictive accuracy compared to their basic counterparts.Notably,the PSO-RFR model excels among all evaluated models,showcasing superior performance on the testing dataset.It achieves a coefficient of determination(R^(2))of 0.9231,a mean absolute error(MAE)of 2.1073,and a root mean square error(RMSE)of 3.6903.When compared to experimental results,the PSO-RFR and PSO-BPNN models demonstrate exceptional predictive accuracy.Notably,the PSO-BPNN model exhibits the closest R^(2)values between its training and test sets.This close alignment of R^(2)values between the training and testing sets reflects the PSO-BPNN model’s superior generalization ability for unseen data.The findings present an efficient method for predicting concrete’s compressive strength,contributing to the sustainable development of concrete materials,and providing theoretical support for their research and application.
文摘This study investigates the impact of Type D additive,Plastiment 83 AM,on the compressive strength and microstructure of Portland Composite Cement(PCC)concrete with a target compressive strength of 18.7 MPa,utilizing a mixing,stirring,and treatment model that simulates batching plant conditions.The study investigated additive dosages of 0%,0.15%,0.25%,0.35%,and 0.40%,with stirring durations of 15 min,2,4,6,and 6.5 h.Compressive strength tests were conducted at the ages of 7,14,28,56,and 90 days on cylindrical specimens,and at 24 h for setting time tests.Microstructural analysis using Energy Dispersive X-ray Spectroscopy(EDX)was performed at 56 days of age.The results showed that the optimal dosage was 0.15%,combined with the addition of Plastiment 83 AM 0.10%at 2 h of stirring,which achieved the highest compressive strength of 20.5 MPa at 90 days.A reduction in compressive strength of the setting time samples from the initial value to 24 h was observed in mixtures stirred for 6 and 6.5 h.A decrease in compressive strength was also observed in both mixtures between 56 and 90 days.EDX analysis revealed different chemical compositions in each mix.At a stirring duration of 6 and 6.5 h,Plastiment 83 AM dosages of 0.35%and 0.40%showed the presence of Magnesium(Mg)and Aluminium(Al)(at 6 h)and Al and phosphorus(at 6.5 h).The presence of inhibited the hydration process,resulting in a very small increase in compressive strength from 14 to 28 days.Magnesium reduced the compressive strength to 75%,and phosphorus to 63%of the target compressive strength.
基金Funded by the Science and Technology Program of Gansu Province(Nos.25JRRA497,23ZDFA017)the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDB0950000)High-level Talent Funding of Kashi。
文摘This study introduces superabsorbent polymers(SAP)into recycled concrete and,through freeze-thaw cycle tests,unconfined compressive strength tests,and nuclear magnetic resonance(NMR)analysis,evaluates the freeze-thaw resistance and durability of recycled concrete samples under varying freeze-thaw cycles.The results indicate that an appropriate addition of SAP significantly enhances the freeze-thaw resistance of recycled concrete.After 200 freeze-thaw cycles,the RS0.6 sample retained good surface integrity,demonstrating the best performance.Compared to NAC,its mass loss decreased by 1.16%,the relative dynamic modulus improved by 7.01%,and the compressive strength loss rate decreased by 5.41%.Additionally,T2 spectrum analysis revealed that adding SAP optimized the pore structure of recycled concrete and mitigated pore development during freeze-thaw cycles.As the number of freeze-thaw cycles increased,the RS0.3 and RS0.6 samples demonstrated superior frost resistance compared to NAC.However,an excessive amount of SAP increased pore expansion during subsequent freeze-thaw cycles,ultimately weakening frost resistance.
文摘In strong aggressive areas,Indonesian standards specify a maximum penetration of 30 mm.Concrete utilizes sulfate-resistant Portland Pozzolan Cement(PPC)for a target strength of 30 MPa,with and without silica fume and plastic fiber(SR-SFF-sea and SR-N-SFF).Some samples of SR-N-SFF are immersed in the sea(SR-N-SFF-sea),while others are protected(SR-N-SFF-protected).Additionally,concrete using non-sulfate-resistant cement(NSR-sea)with a strength of 20.75 MPa was also evaluated.All samples were subjected to penetration depth testing according to the DIN EN 12390-8 standard,demonstrating that they met the penetration requirements for intense aggression.The study employed cylindrical samples measuring 15 cm in diameter and 30 cm in height to assess compressive strength and natural penetration fromthe split tensile test.Samples were placed into the sea at the fishing boat dock in Lampung,Indonesia,at 9 days of age following 7 days of immersion curing.The results indicated that sulfate-resistant Portland Composite Cement(PCC)is unsuitable for protected areas,as its strength is inferior to that of concrete submerged in seawater.Concrete featuring sulfate-resistant PCC,silica fume,and plastic fiber(SR-SFF-sea)exhibited lower strength compared to SR-N-SFF-protected samples.Conversely,SR-N-SFF-sea achieved the highest strength of 46 MPa at 56 days,with a notable increase in strength occurring from 21 to 56 days,while no increase in penetration depth was observed during this period.The standard penetration depth of SR-N-SFF-sea is 17.8mm,which can serve as a guideline for creating durable concrete in marine environments.
文摘Received:06 December 2025;Accepted:25 February 2026;Published:30 March 2026 ABSTRACT:In the last decade,the importance of sustainable construction and artificial intelligence(AI)in civil engineering has been underlined in many studies.Numerous studies highlighted the superiority of AI techniques over simple and mathematical regression analyses,which suffer from relatively poor generalization and an inability to capture highly non-linear relationships among inputs and output(s)parameters.In this study,to evaluate the compressive strength of concrete with glass powder(GP)and recycled aggregates,600 concrete samples were tested in the laboratory,and their results were evaluated.For intelligent assessment of concrete compressive strength(CCS),the study utilized an improved artificial neural network(ANN)with particle swarm optimization(PSO)algorithm and imperialist competitive algorithm(ICA).For training the models,the experimentally obtained data were used.The concrete ingredients formed the inputs of the AI-based predictive models of CCS.The experimental findings reveal that the implementation of recycled coarse aggregates in concrete from a sustainable construction point of view is advantageous and can enhance the CCS by 11.43%.Apart from that,findings indicate that utilization of 10%GP can lead to a nearly 20%increase in CCS(from 44.6 to 54.1 MPa).Additionally,the experimental observations show almost 40%improvement of CCS when 5%micro silica was used in the concrete mixture.Based on the findings,the study suggests the utilization of waste glass powder to partially replace cement in concrete,which can reduce the amount of cement production.This reduction from economic,energy-saving,and environmental(reduction in greenhouse gas emissions)points of view is of interest.On the other hand,the AI results show that the PSO-based ANN model outperforms the ICA-based ANN for the utilized dataset.According to the findings,the PSO-based ANN predictive model(with a coefficient of determination value of 0.939 and root mean square value of 0.113 for testing data)is a capable tool in predicting the CCS.Hence,this study recommends the implementation of AI-based models in CCS assessment.
基金Funded by the National Key Research and Development Program of China(No.2020YFC1909905)the Science and Technology Research and Development Plan of China National Railway Group Co.,Ltd.(No.L2022G009)the New Cornerstone Science Foundation through the XPLORER PRIZE。
文摘This study aimed to investigate the influence of recycled sand(RS)content and water-binder ratio on the long term performance of recycled sand concrete(RSC).A 220 days drying shrinkage and creep test of RSC was conducted,and the microhardness of ITZ were analyzed to explain the differences in performance.The experimental results indicate that,when RS content is 50%,the drying shrinkage and creep strain of RSC is the smallest.This is attributed to the highest microhardness in the ITZ when the RS content is 50%.When the RS content is 100%,the shrinkage and creep strains increase due to the high water absorption of RS,which leads to the evaporation of additional water and the deterioration of the ITZ.As the water-binder ratio increases,the drying shrinkage and creep strain of RSC with different RS content increases.According to the EC2 specification and the CEB-FIP specification,the drying shrinkage and creep prediction models for RSC have been established.
基金Funded by the Natural Science Foundation of Jiangsu Province(No.BK20220626)the National Natural Science Foundation of China(No.52078068)+2 种基金Science and Technology Innovation Foundation of NIT(No.KCTD006)Jiangsu Marine Structure Service Performance Improvement Engineering Research CenterKey Laboratory of Jiangsu"Marine Floating Wind Power Technology and Equipment"。
文摘We investigated the effects of fly ash(FA)content on the mechanical properties of recycled aggregate concrete(RAC)and its regeneration potential under freeze and thaw(F-T)cycles.The physical properties of second-generation recycled concrete aggregates(RCA)were used to analyze the regeneration potential of RAC after F-T cycles.Scanning electron microscopy was used to study the interfacial transition zone microstructure of RAC after F-T cycles.Results showed that adding 20%FA to RAC significantly enhanced its mechanical properties and frost resistance.Before the F-T cycles,the compressive strength of RAC with 20%FA reached 48.3 MPa,exceeding research strength target of 40 MPa.A majority of second-generation RCA with FA had been verified to attain class Ⅲ,which enabled their practical application in non-structural projects such as backfill trenches and road pavement.However,the second-generation RCA with 20%FA can achieve class Ⅱ,making it ideal for 40 MPa structural concrete.
基金Funded by the National Natural Science Foundation of China(No.52568032)Guangxi Key Research and Development Program(GKNos.AB24010020,AB23026071,and AD24010062)。
文摘The engineering application of low-alkali sulphoaluminate cement(L-SAC)is hindered due to the difficulty in adjusting the setting and hardening time.In this paper,lithium hydroxide and borax are mixed into L-SAC to regulate its setting and hardening process,so as to prepare a sulphoaluminate concrete material with high early strength and high fluidity.The effects of the ratio of lithium hydroxide to borax on the properties of L-SAC concrete were studied by hydration heat,XRD,TG-DTG,SEM and MIP.The experimental results show that the slump increases with the increase of borax content,and the early(3 h)strength increases with the increase of lithium hydroxide content.When 0.05% lithium hydroxide and 0.4% borax are added,the 0.5 h slump reaches 195 mm,and the 3 h compressive strength reaches 15.9 MPa.The increase of lithium hydroxide will promote the formation of early hydration products AFt and AH3 gel and accelerate the hydration process,while borax will inhibit the dissolution and hydration of cement and delay the setting and hardening process of concrete.The combination of the two ensures that the concrete has the characteristics of high early strength and high fluidity,and the early workability and mechanical properties can be controlled by the mix ratio.For long-term mechanical properties,the special concrete does not produce AFm,which can ensure the continuous development of strength.
基金Funded by the National Natural Science Foundation of China(Nos.52278518 and 51938011)the Natural Science Foundation of the Jiangsu Higher Education Institutions of China(No.24KJB560021)。
文摘Based on the split hopkinson pressure bar(SHPB)tests results,the cubic specimens have been numerically modeled in this paper to investigate the impact of key factors,such as the rise time,duration,and incident pulse shape,on achieving stress uniformity.After analysis,the paper provides actionable methods aimed at optimizing the conditions for stress uniformity within the cubic specimen.Finally,the lateral inertia effect of cubic specimen has been scrutinized to address the existing gap in this academic area.
基金Funded by"Green Construction and Maintenance of Road Engineering"the Belt and Road Joint Laboratory,International(Hong Kong,Macao and Taiwan)Science and Technology Cooperation Project(No.Z251100007125040)the National Key R&D Program of China(No.2022YFC3803403)+3 种基金the Project of Construction and Support for High-level Innovative Teams of Beijing Municipal Institutions(No.BPHR20220109)the Cultivation Project Funds for Beijing University of Civil Engineering and Architecture(No.X24013)the BUCEA Doctor Graduate Scientific Research Ability Improvement Project(No.DG2024016)the China Scholarship Council(No.202408110091)。
文摘A comprehensive full-sieve-hole grading correction method was used to adjust aggregate gradings.The fatigue properties of recycled concrete aggregate(RCA)asphalt mixtures were investigated using an improved indirect tensile fatigue test under temperature-humidity coupling based on 20-year meteorological data of Beijing,and the degeneration mechanism was further explored by scanning electron microscopy and energy-dispersive spectroscopy.The experimental results indicate that replacing 5-20 mm coarse limestone aggregate(LA)with RCA at a 50% substitution volume can mitigate the impact of RCA variations on the asphalt mixture proportioning design.All RCA asphalt mixtures have lower initial fatigue properties than the LA asphalt mixture.However,under temperature-humidity coupling,the long-term fatigue property of an RCA asphalt mixture with a low proportion of recycled brick exceeds that of the LA asphalt mixture,and the fatigue life decline rate of the RCA asphalt mixture during 10-year service decreases by approximately 25%.This is due to the penetration of the asphalt mortar into the RCA through the pores and cracks on the RCA surface.It forms an interfacial transition zone composed of asphalt mortar and cement mortar and further reduces the mixture damage caused by the water and freeze-thaw conditions.
文摘Nonlinear static procedures are widely adopted in structural engineering practice for seismic performance assessment due to their simplicity and computational efficiency.However,their reliability depends heavily on how the nonlinear behaviour of structural components is represented.The recent earthquakes in Albania(2019)and Türkiye(2023)have underscored the need for accurate assessment techniques,particularly for older reinforced concrete buildings with poor detailing.This study quantifies the discrepancies between default and user-defined component modelling in pushover analysis of pre-modern reinforced concrete structures,analysing two representative low-and mid-rise reinforced concrete frame buildings.The lumped plasticity approach incorporates moment-rotation relationships derived from actual member properties and reinforcement configurations,while the distributed plasticity approach uses software-generated default properties based on modern codes.Results show that the distributed plasticity models systematically overestimate both the strength and the deformation capacity by up to 35%compared to lumped plasticity models,especially in buildings with poor detailing and low concrete strength.These findings demonstrate that default software procedures,widely used in practice but not validated for pre-modern structures,produce dangerously unconservative seismic performance estimates.The study provides quantitative evidence of the critical need for tailored modelling strategies that reflect the actual conditions of the existing building stock.
文摘Accurate prediction of concrete compressive strength is fundamental for optimizing mix designs,improving material utilization,and ensuring structural safety in modern construction.Traditional empirical methods often fail to capture the non-linear relationships among concrete constituents,especially with the growing use of supple-mentary cementitious materials and recycled aggregates.This study presents an integrated machine learning framework for concrete strength prediction,combining advanced regression models—namely CatBoost—with metaheuristic optimization algorithms,with a particular focus on the Somersaulting Spider Optimizer(SSO).A comprehensive dataset encompassing diverse mix proportions and material types was used to evaluate baseline machine learning models,including CatBoost,XGBoost,ExtraTrees,and RandomForest.Among these,CatBoost demonstrated superior accuracy across multiple performance metrics.To further enhance predictive capability,several bio-inspired optimizers were employed for hyperparameter tuning.The SSO-CatBoost hybrid achieved the lowest mean squared error and highest correlation coefficients,outperforming other metaheuristic approaches such as Genetic Algorithm,Particle Swarm Optimization,and Grey Wolf Optimizer.Statistical significance was established through Analysis of Variance and Wilcoxon signed-rank testing,confirming the robustness of the optimized models.The proposed methodology not only delivers improved predictive performance but also offers a transparent framework for mix design optimization,supporting data-driven decision making in sustainable and resilient infrastructure development.
基金Funded by the Chongqing Natural Science Foundation Project(No.cstc202ljcyj-msxmX0725)。
文摘We employed machine learning approaches and visualization interpretation methods to explore the influencing factors of the compressive strength of sea sand concrete to attain a better understanding of the inherent laws of concrete mix design.Four models,including random forest,Cat Boost,XGBoost,and deep neural network,were trained.The experimental results demonstrate that the XGBoost model performs the best in predicting the strength of sea sand concrete.Its R^(2)value reached 0.9999,and evaluation indexes such as MAPE,RMSE,MAE,and MSE are superior to those of other models.The principal component analysis(PCA)was conducted to visually analyze the structure and distribution of the original feature data,and Pearson correlation coefficient analysis and Shapley additive explanation(SHAP)were utilized to explore the impact of input characteristics on the strength of sea sand concrete.SHAP analysis is more conducive to revealing the nonlinear effects of various characteristics on the model prediction results,especially that particle size of stone has significant impacts on the strength of sea sand concrete.In addition,experimental verification was carried out to confirm the accuracy of the optimized training model.These findings offer some insights for the future design and application of sea sand in high-performance marine and coastal infrastructure.
基金National Key R&D Program of China under Grant No.2024YFD1600404。
文摘Severe failures of nonstructural components have occurred during previous earthquakes.Claddings are one of the most widely used nonstructural component and are installed in many modern buildings;therefore,an evaluation of their seismic performance is important and cannot be ignored.To investigate the seismic performance of large-sized high performance concrete cladding(HPCC),a series of full-scale experimental tests were conducted using a unidirectional shaking table.A steel supporting frame was used to install the HPCCs and reproduce the effects of the building under earthquake.The tests were divided into two parts:in-plane(IP)testing and out-plane(OP)testing.Three recorded accelerograms,one artificial accelerogram,and one sinusoidal accelerogram were used to conduct the shaking table tests.The results show that the maximum recorded IP responses of acceleration and interstory drift ratio were 1.04 g and 1/97,while the OP responses were 1.02 g and 1/51.The HPCCs functioned well throughout the entire experimental protocol.The fundamental frequency of the HPCCs systems rarely changed after the tests.
基金Funded by the National Science Foundation of China(No.52368031)the China Postdoctoral Science Foundation(No.2022M713497)+1 种基金the Jiangxi Provincial Natural Science Foundation(No.20252BAC250115)the Jiangxi Provincial Department of Transportation Science and Technology Project(No.2022H0017)。
文摘Utilization of ceramic wastes to fabricate concrete can not only effectively dispose the wastes,but also reduce the energy and source consumptions.Therefore,we fabricated a green ultra high performance concrete using ceramic waste powder(CWP)to replace 55%of cement,and ceramic waste aggregate(CWA)to replace 100%natural quartz sand.However,high content of ceramic wastes will harm the concrete performance including workability and mechanical properties.Therefore,a low-cost and low carbon nano-calcium carbonate(NC)was introduced to compensate for the defects caused by large amounts of CWP and CWA to workability and mechanical behavior.The experimental results show that the workability of ultra high performance concrete with large amounts of CWP and CWA(UHPCLCC)increases by 28.57%with NC content of 5%.Moreover,the flexural strengths,fracture energy,compressive strengths,and compressive toughness of UHPCLCC increase up to 29.6%,56.5%,20.4%,and 37.6%,respectively,which is caused by the nano-core effect of NC.
基金Funded by Natural Science Foundation of Guangxi(No.2025GXNSFBA069565)Guangxi Science and Technology Program(No.AD25069101)Guangxi Bagui Scholars Fund。
文摘Crushing waste coral concrete into recycled aggregates to create recycled coral aggregate concrete(RCAC)contributes to sustainable construction development on offshore islands and reefs.To investigate the impact of recycled coral aggregate on concrete properties,this study performed a comprehensive analysis of the physical properties of recycled coral aggregate and the basic mechanical properties and microstructure of RCAC.The test results indicate that,compared to coral debris,the crushing index of recycled coral aggregate was reduced by 9.4%,while porosity decreased by 33.5%.Furthermore,RCAC retained the early strength characteristics of coral concrete,with compressive strength and flexural strength exhibiting a notable increase as the water-cement ratio decreased.Under identical conditions,the compressive strength and flexural strength of RCAC were 12.7% and 2.5% higher than coral concrete's,respectively,with porosity correspondingly reduced from 3.13% to 5.11%.This enhancement could be attributed to the new mortar filling the recycled coral aggregate.Scanning electron microscopy(SEM)analysis revealed three distinct interface transition zones within RCAC,with the‘new mortar-old mortar’interface identified as the weakest.The above findings provided a reference for the sustainable use of coral concrete in constructing offshore islands.
基金sponsored by the National Natural Science Foundation of China(Grant No.52438002)the New Cornerstone Science Foundation through the XPLORER PRIZE.
文摘This study investigates the influence of loading frequency on the fatigue behavior of ballastless track concrete for high-speed railways,aiming to support the development of concrete capable of withstanding higher operational speeds.Fatigue tests were conducted at loading frequencies ranging from 5 to 40 Hz,with a focus on fatigue life,damage evolution,energy dissipation,and residual fatigue strain in the concrete.The results indicate that between 5 and 15 Hz,the fatigue life and energy dissipation remain relatively stable,with minimal damage evolution and small residual strains.As the frequency increases to 15-20 Hz,the fatigue life and energy dissipation gradually decrease,while damage accumulation and residual strain increase.Beyond 20 Hz,both fatigue life and energy dissipation decrease rapidly,damage accumulation becomes more pronounced,and residual strain continues to rise.These phenomena are primarily attributed to the increased strain rate and load change rate at higher frequencies,which affect the microstructure evolution and lead to reduced fatigue performance.
基金funded by UTM Fundamental Research Grant(PY/2024/01221,Cost centre no.:Q.J130000.3822.23H73)HiCoE Grant Scheme(Cost centre no.:R.J130000.7822.4J738)。
文摘Rapid quantification of seismic-induced damage immediately following an earthquake is critical for determining whether a structure is safe for continued occupation or requires evacuation.This study proposes a novel damage identification method that utilizes limited strain data points,significantly reducing installation,maintenance,and data analysis costs compared to traditional distributed sensor networks.The approach integrates finite element(FE)modeling to generate capacity curves through pushover analysis,incorporates noise-augmented datasets for Artificial Neural Network(ANN)training,and classifies structural conditions into four damage levels:Operational(OP),Immediate Occupancy(IO),Life Safety(LS),and Collapse Prevention(CP).To evaluate the method’s accuracy and efficiency,it was applied to two reinforced concrete(RC)frames;a single-story frame tested experimentally under cyclic loading and a three-story frame analyzed under various lateral load patterns.Strain data from selected beam and column ends were used as ANN inputs,while the corresponding damage classes served as outputs.Confusion matrix results demonstrated high true positive rates(>85%for the single-story and>90%for the three-story frame),even with a reduced number of sensors.The model also exhibited strong robustness to White Gaussian Noise(SNR=2.5-5 dB)and generalized effectively to nonlinear time-history analyses under scaled ground motions(PGA=0.1-1.0 g).Feature selection using the MRMR and ANOVA algorithms further enhanced computational efficiency.Overall,the proposed ANN-based framework has strong potential for real-time structural health monitoring applications.
基金supported by the National Natural Science Foundation of China(No.52463034)supported by the Korea Institute of Energy Technology Evaluation and Planning funded by the Ministry of Trade,Industry and Energy(No.2025-02314098)of the Republic of Koreasupported by the Regional Innovation System&Education(RISE)program through the Gangwon RISE Center,funded by the Ministry of Education(MOE)and the Gangwon State(G.S.),Republic of Korea(2025-RISE-10-002).
文摘Conventional low-carbon concrete design approaches have often overlooked carbonation durability and the progressive loss of cover caused by surface scaling,both of which can increase the long-term risk of reinforcement corrosion.To address these limitations,this study proposes an improved design framework for low-carbon slag concrete that simultaneously incorporates carbonation durability and cover scaling effects into the mix proportioning process.Based on experimental data,a linear predictive model was developed to estimate the 28-day compressive strength of slag concrete,achieving a correlation coefficient of R=0.87711 and a root mean square error(RMSE)of 7.55 MPa.The mechanism-based equation exhibits strong physical interpretability,as each parameter corresponds to a clear physical process,satisfying the requirements of design codes for physical significance.By integrating the strength and carbon-emission models,the carbon-emission efficiency was further analyzed.Across all water–binder ratios(0.3,0.4,0.5),CO_(2) emissions per unit strength decreased steadily with increasing slag content,indicating that carbon efficiency is primarily governed by slag replacement rather than the water/binder ratio.Four design cases,all with a design strength of 30 MPa,were then evaluated to illustrate the combined effects of carbonation and scaling.In Case 1,without considering carbonation durability,the carbonation depth after 50 years exceeded the 25 mm cover,leading to potential corrosion.In Case 2,when carbonation durability was considered,the required actual strength increased to 31.28 MPa.When mild cover scaling of 3 mm was introduced(Case 3),the required strength rose to 34.59 MPa,and under severe scaling of 10 mm(Case 4),it increased to 45.73 MPa.These results indicate that intensified scaling demands higher strength and lower water/binder ratios to maintain durability.Overall,the proposed framework quantitatively balances strength,durability,and embodied carbon,supporting sustainable low-carbon concrete design.
