[5] [5] HAN T, WANG X, LI D, et al. Damage and degradation mechanism for single intermittent cracked mortar specimens under a combination of chemical solutions and dry-wet cycles［J］. Constr Build Mater, 2019, 213: 567-581.

[10] [10] LIANG N, MAO J, YAN R, et al. Corrosion resistance of multiscale polypropylene fiber-reinforced concrete under sulfate attack［J］. Case Studies in Constr Mater, 2022, 16: e01065.

[19] [19] DILLARD R J, MURRAY C D, DESCHENES R A. Belitic calcium sulfoaluminate cement subjected to sulfate attack and sulfuric acid［J］. Constr Build Mater, 2022, 343: 128089.

[20] [20] WALLY G B, MAGALHES F C, PINTO DA SILVA FILHO L C. From prescriptive to performance-based: An overview of international trends in specifying durable concretes［J］. J Build Eng, 2022, 52: 104359.

[21] [21] SHAH V, BISHNOI S. Carbonation resistance of cements containing supplementary cementitious materials and its relation to various parameters of concrete［J］. Constr Build Mater, 2018, 178: 219-232.

[22] [22] WALLY G B, MAGALHES F C, JUNIOR F K S, et al. Estimating service life of reinforced concrete structures with binders containing silica fume and metakaolin under chloride environment: durability indicators and probabilistic assessment［J］. Mater Struct, 2021, 54(2): 1-16.

[24] [24] NIU D, ZHANG L, FU Q, et al. Critical conditions and life prediction of reinforcement corrosion in coral aggregate concrete［J］. Constr Build Mater, 2020, 238: 117685.

[25] [25] SHAO W, WANG Y, SHI D. Corrosion-fatigue life prediction of reinforced concrete square piles in marine environments［J］. Eng Failure Anal, 2022, 138: 106324.

[28] [28] WU J, XU J, DIAO B, et al. Fatigue life prediction for the reinforced concrete (RC) beams under the actions of chloride attack and fatigue［J］. Eng Struct, 2021, 242: 112543.

[29] [29] ASTERIS P G, SKENTOU A D, BARDHAN A, et al. Predicting concrete compressive strength using hybrid ensembling of surrogate machine learning models［J］. Cem Concr Res, 2021, 145: 106449.

[32] [32] JI T, LIN T, LIN X. A concrete mix proportion design algorithm based on artificial neural networks［J］. Cem Concr Res, 2006, 36(7): 1399-1408.

[34] [34] TAM V W Y, BUTERA A, LE K N, et al. A prediction model for compressive strength of CO2 concrete using regression analysis and artificial neural networks［J］. Constr Build Mater, 2022, 324: 126689.

[35] [35] AMIRI M, HATAMI F. Prediction of mechanical and durability characteristics of concrete including slag and recycled aggregate concrete with artificial neural networks (ANNs)［J］. Constr Build Mater, 2022, 325: 126839.

[37] [37] HUANG L, CHEN J, TAN X. BP-ANN based bond strength prediction for FRP reinforced concrete at high temperature［J］. Eng Struct, 2022, 257: 114026.

[38] [38] BI Y, CHEN C, HUANG X, et al. Discrimination method of biomass slagging tendency based on particle swarm optimization deep neural network (DNN)［J］. Energy, 2022: 125368.

[39] [39] ANJALI R, VENKATESAN G. Optimization of mechanical properties and composition of M-sand and pet particle added concrete using hybrid deep neural network-horse herd optimization algorithm［J］. Constr Build Mater, 2022, 347: 128334.

[40] [40] WEN Z, ZHOU R, SU H. MR and stacked GRUs neural network combined model and its application for deformation prediction of concrete dam［J］. Expert Systems Appl, 2022, 201: 117272.

[44] [44] LIU P, CHEN Y, YU Z, et al. Effect of sulfate solution concentration on the deterioration mechanism and physical properties of concrete［J］. Constr Build Mater, 2019, 227: 116641.

[45] [45] YANG S, HAN M, CHEN X, et al. Influence of sulfate crystallization on bond-slip behavior between deformed rebar and concrete subjected to combined actions of dry-wet cycle and freeze-thaw cycle［J］. Constr Build Mater, 2022, 345: 128368.

[47] [47] WEI Y, CHAI J, QIN Y, et al. Effect of fly ash on mechanical properties and microstructure of cellulose fiber-reinforced concrete under sulfate dry-wet cycle attack［J］. Constr Build Mater, 2021, 302: 124207.

[48] [48] ZOU D, QIN S, LIU T, et al. Experimental and numerical study of the effects of solution concentration and temperature on concrete under external sulfate attack［J］. Cem Concr Res, 2021, 139: 106284.

[50] [50] IDIART A E, LóPEZ C M, CAROL I. Modeling of drying shrinkage of concrete specimens at the meso-level［J］. Mater Struct, 2011, 44(2): 415-435.

[52] [52] HAY R, OSTERTAG C P. New insights into therole of fly ash in mitigating alkali-silica reaction (ASR) in concrete［J］. Cem Concr Res, 2021, 144: 106440.