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Effect of Molarity of Sodium Hydroxide on the Strength Behavior of Fiber-Reinforced Geopolymer Concrete Exposed to Elevated Temperature | ||
| Journal of Rehabilitation in Civil Engineering | ||
| مقاله 9، دوره 12، شماره 2 - شماره پیاپی 34، مرداد 2024، صفحه 111-128 اصل مقاله (1.44 M) | ||
| نوع مقاله: Regular Paper | ||
| شناسه دیجیتال (DOI): 10.22075/jrce.2023.30282.1831 | ||
| نویسندگان | ||
| Abbasali Saffar1؛ Mohammad Ehsanifar* 2؛ Seyed Mohammad Mirhoseini3؛ Mohammad Javad Taheri Amiri4 | ||
| 1Ph.D. Student, Department of Civil Engineering, Arak Branch, Islamic Azad University, Arak, Iran | ||
| 2Associate Professor, Department of Industrial Engineering, Arak Branch, Islamic Azad University, Arak, Iran | ||
| 3Assistant Professor, Department of Civil Engineering, Arak Branch, Islamic Azad University, Arak, Iran | ||
| 4Assistant Professor, Department of Civil Engineering, higher education institute of Pardisan, Freidonkenar, Iran | ||
| تاریخ دریافت: 09 فروردین 1402، تاریخ بازنگری: 01 تیر 1402، تاریخ پذیرش: 14 تیر 1402 | ||
| چکیده | ||
| Ordinary concrete production is highly energy intensive and caused to greenhouse gas emission responsible for global warming. Geopolymer mixtures are the eco-friendly alternative for to protect the CO2 emission in concrete industry. In this study, the post-fire behavior of fiber reinforced geopolymer concrete (FRGPC) was investigated based on molarity changing approach. To do so, supplementary cementitious materials such as fly ash, metakaolin and zeolite are used to provide binary and ternary FRGPC mixtures. For this aim, FRGPC exposed to elevated temperature at the 200, 500, 800 °C. In addition, three molarity (12, 14, 16) of solution is studied for better strength performance. The result of this study presented that the ratio of the post-fire residual strength of the sample of Z10MK20 increased by 8.1% at 200 °C, 14.1% at 500 °C, and decreased by 5.2% at 800 °C. The 28-day sample resistance, with 20% replacement of metakaolin, was measured at 45.8 MPa after adding fibers (2% constant volume of 1-3% polypropylene fibers). Also, with increasing the molarity of FRGPC mixtures from 12 to 16, the heat resistance behavior in FRGPC had an increase about 6%. Increasing the volume of polypropylene (PP) fibers up to 3% by volume did not have much effect on the heat resistance behavior of FRGPC. Beside, post-fire strength of FRGPC was predicted using artificial neural network (ANN) and support vector machines (SVM) with the integration of water cycle algorithm (WCA). Based on the coefficient of determination obtained in the training and testing stages, ANN-WCA model had an acceptable performance in predicting the post-fire residual strength of FRGPC. Additionally, the sensitivity analysis manifested that the molarity of the FRGPC mixtures and the exposed temperature had the greatest effect and PP fibers had the least effect on post-fire residual strength of FRGPC. | ||
تازه های تحقیق | ||
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| کلیدواژهها | ||
| Strength behavior؛ Ternary blended GPC؛ Molarity؛ Elevated temperature؛ Artificial intelligence | ||
| مراجع | ||
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[1] Amran M, Huang SS, Debbarma S, Rashid RSM. Fire resistance of geopolymer concrete: A critical review. Constr Build Mater 2022;324:126722. https://doi.org/10.1016/J.CONBUILDMAT.2022.126722.
[2] Phoo-Ngernkham T, Sata V, Hanjitsuwan S, Ridtirud C, Hatanaka S, Chindaprasirt P. High calcium fly ash geopolymer mortar containing Portland cement for use as repair material. Constr Build Mater 2015;98:482–8. https://doi.org/10.1016/J.CONBUILDMAT.2015.08.139.
[3] Jumaa NH, Ali IM, Nasr MS, Falah MW. Strength and microstructural properties of binary and ternary blends in fly ash-based geopolymer concrete. Case Stud Constr Mater 2022;17:e01317. https://doi.org/10.1016/J.CSCM.2022.E01317.
[4] Prasad Burle V, Kiran T, Anand N, Andrushia D, Al-Jabri K. Post-fire investigation on the mechanical properties and physical characteristics of fibre-reinforced geopolymer concrete. J Struct Fire Eng 2023;ahead-of-print. https://doi.org/10.1108/JSFE-01-2023-0016/FULL/XML.
[5] Sasi Rekha M, Sumathy SR. Engineering properties of Self-cured Geopolymer concrete binded with supplementary cementitious materials. Mater Today Proc 2022;69:879–87. https://doi.org/10.1016/J.MATPR.2022.07.357.
[6] Huang Y, Han M, Yi R. Microstructure and properties of fly ash-based geopolymeric material with 5A zeolite as a filler. Constr Build Mater 2012;33:84–9. https://doi.org/10.1016/J.CONBUILDMAT.2012.01.014.
[7] Albidah A, Alqarni AS, Abbas H, Almusallam T, Al-Salloum Y. Behavior of Metakaolin-Based geopolymer concrete at ambient and elevated temperatures. Constr Build Mater 2022;317:125910. https://doi.org/10.1016/J.CONBUILDMAT.2021.125910.
[8] Moradikhou AB, Esparham A, Jamshidi Avanaki M. Physical & mechanical properties of fiber reinforced metakaolin-based geopolymer concrete. Constr Build Mater 2020;251:118965. https://doi.org/10.1016/J.CONBUILDMAT.2020.118965.
[9] Kaya M, Koksal F, Gencel O, Munir MJ, Kazmi SMS. Influence of micro Fe2O3 and MgO on the physical and mechanical properties of the zeolite and kaolin based geopolymer mortar. J Build Eng 2022;52:104443. https://doi.org/10.1016/J.JOBE.2022.104443.
[10] Gülşan ME, Alzeebaree R, Rasheed AA, Niş A, Kurtoğlu AE. Development of fly ash/slag based self-compacting geopolymer concrete using nano-silica and steel fiber. Constr Build Mater 2019;211:271–83. https://doi.org/10.1016/J.CONBUILDMAT.2019.03.228.
[11] Deb PS, Nath P, Sarker PK. The effects of ground granulated blast-furnace slag blending with fly ash and activator content on the workability and strength properties of geopolymer concrete cured at ambient temperature. Mater Des 2014;62:32–9. https://doi.org/10.1016/J.MATDES.2014.05.001.
[12] Okoye FN, Durgaprasad J, Singh NB. Effect of silica fume on the mechanical properties of fly ash based-geopolymer concrete. Ceram Int 2016;42:3000–6. https://doi.org/10.1016/J.CERAMINT.2015.10.084.
[13] Luhar S, Chaudhary S, Luhar I. Development of rubberized geopolymer concrete: Strength and durability studies. Constr Build Mater 2019;204:740–53. https://doi.org/10.1016/J.CONBUILDMAT.2019.01.185.
[14] Park Y, Abolmaali A, Kim YH, Ghahremannejad M. Compressive strength of fly ash-based geopolymer concrete with crumb rubber partially replacing sand. Constr Build Mater 2016;118:43–51. https://doi.org/10.1016/J.CONBUILDMAT.2016.05.001.
[15] Aly AM, El-Feky MS, Kohail M, Nasr ESAR. Performance of geopolymer concrete containing recycled rubber. Constr Build Mater 2019;207:136–44. https://doi.org/10.1016/J.CONBUILDMAT.2019.02.121.
[16] Albitar M, Mohamed Ali MS, Visintin P, Drechsler M. Effect of granulated lead smelter slag on strength of fly ash-based geopolymer concrete. Constr Build Mater 2015;83:128–35. https://doi.org/10.1016/J.CONBUILDMAT.2015.03.009.
[17] Muttashar HL, Ariffin MAM, Hussein MN, Hussin MW, Ishaq S Bin. Self-compacting geopolymer concrete with spend garnet as sand replacement. J Build Eng 2018;15:85–94. https://doi.org/10.1016/J.JOBE.2017.10.007.
[18] Albidah A, Alghannam M, Abbas H, Almusallam T, Al-Salloum Y. Characteristics of metakaolin-based geopolymer concrete for different mix design parameters. J Mater Res Technol 2021;10:84–98. https://doi.org/10.1016/J.JMRT.2020.11.104.
[19] Pothisiri T, Panedpojaman P. Modeling of bonding between steel rebar and concrete at elevated temperatures. Constr Build Mater 2012;27:130–40. https://doi.org/10.1016/J.CONBUILDMAT.2011.08.014.
[20] Yu R, Spiesz P, Brouwers HJH. Development of an eco-friendly Ultra-High Performance Concrete (UHPC) with efficient cement and mineral admixtures uses. Cem Concr Compos 2015;55:383–94. https://doi.org/10.1016/J.CEMCONCOMP.2014.09.024.
[21] Zanotti C, Borges PHR, Bhutta A, Banthia N. Bond strength between concrete substrate and metakaolin geopolymer repair mortar: Effect of curing regime and PVA fiber reinforcement. Cem Concr Compos 2017;80:307–16. https://doi.org/10.1016/J.CEMCONCOMP.2016.12.014.
[22] Dutta S, Mandal JN. Model Studies on Geocell-Reinforced Fly Ash Bed Overlying Soft Clay. J Mater Civ Eng 2015;28:04015091. https://doi.org/10.1061/(ASCE)MT.1943-5533.0001356.
[23] Tanyildizi H, Yonar Y. Mechanical properties of geopolymer concrete containing polyvinyl alcohol fiber exposed to high temperature. Constr Build Mater 2016;126:381–7. https://doi.org/10.1016/J.CONBUILDMAT.2016.09.001.
[24] Ganesh AC, Muthukannan M. Development of high performance sustainable optimized fiber reinforced geopolymer concrete and prediction of compressive strength. J Clean Prod 2021;282:124543. https://doi.org/10.1016/J.JCLEPRO.2020.124543.
[25] Vaidya S, Allouche EN. Strain sensing of carbon fiber reinforced geopolymer concrete. Mater Struct Constr 2011;44:1467–75. https://doi.org/10.1617/S11527-011-9711-3/METRICS.
[26] Albidah A, Abadel A, Alrshoudi F, Altheeb A, Abbas H, Al-Salloum Y. Bond strength between concrete substrate and metakaolin geopolymer repair mortars at ambient and elevated temperatures. J Mater Res Technol 2020;9:10732–45. https://doi.org/10.1016/J.JMRT.2020.07.092.
[27] TAHERI AMIRI MJ, Ashrafian A, Haghighi FR, Javaheri Barforooshi M. Prediction of the Compressive Strength of Self-compacting Concrete containing Rice Husk Ash using Data Driven Models. Modares Civ Eng J 2019;19:209–21.
[28] Razeghi HR, Ghadir P, Javadi AA. Mechanical Strength of Saline Sandy Soils Stabilized with Alkali-Activated Cements. Sustain 2022, Vol 14, Page 13669 2022;14:13669. https://doi.org/10.3390/SU142013669.
[29] Ghadir P, Razeghi HR. Effects of sodium chloride on the mechanical strength of alkali activated volcanic ash and slag pastes under room and elevated temperatures. Constr Build Mater 2022;344:128113. https://doi.org/10.1016/J.CONBUILDMAT.2022.128113.
[30] Ashrafian A, Panahi E, Salehi S, Karoglou M, Asteris PG. Mapping the strength of agro-ecological lightweight concrete containing oil palm by-product using artificial intelligence techniques. Structures 2023;48:1209–29. https://doi.org/10.1016/J.ISTRUC.2022.12.108.
[31] Ashrafian A, Shahmansouri AA, Akbarzadeh Bengar H, Behnood A. Post-fire behavior evaluation of concrete mixtures containing natural zeolite using a novel metaheuristic-based machine learning method. Arch Civ Mech Eng 2022;22:101. https://doi.org/10.1007/s43452-022-00415-7.
[32] C618 Standard Specification for Coal Fly Ash and Raw or - Google Scholar n.d.
[33] ASTM C39 / C39M Standard Test Method for Compressive - Google Scholar n.d.
[34] Belalia Douma O, Boukhatem B, Ghrici M, Tagnit-Hamou A. Prediction of properties of self-compacting concrete containing fly ash using artificial neural network. Neural Comput Appl 2017;28:707–18. https://doi.org/10.1007/S00521-016-2368-7/METRICS.
[35] Ashrafian A, Taheri Amiri MJ, haghighi farshidreza. Modeling the Slump Flow of Self-Compacting Concrete Incorporating Metakaolin Using Soft Computing Techniques. J Struct Constr Eng 2019;6:5–20. https://doi.org/10.22065/jsce.2018.90214.1243.
[36] An D, Kim NH, Choi JH. Practical options for selecting data-driven or physics-based prognostics algorithms with reviews. Reliab Eng Syst Saf 2015;133:223–36. https://doi.org/10.1016/J.RESS.2014.09.014.
[37] Rajaee T, Shahabi A. Evaluation of wavelet-GEP and wavelet-ANN hybrid models for prediction of total nitrogen concentration in coastal marine waters. Arab J Geosci 2016;9:1–15. https://doi.org/10.1007/S12517-015-2220-X/METRICS.
[38] Komasi M, Goudarzi H, Behniya A. Studying the process of space-time ground water level by support vector machine and Kriging Method in GIS (case study: silakhor plain). J Water Soil Conserv 2017;24:195–209. https://doi.org/10.22069/JWSC.2017.11640.2611.
[39] Barman M, Choudhury NBD, Sutradhar S. A regional hybrid GOA-SVM model based on similar day approach for short-term load forecasting in Assam, India. Energy 2018;145:710–20.
[40] Meng E, Huang S, Huang Q, Fang W, Wu L, Wang L. A robust method for non-stationary streamflow prediction based on improved EMD-SVM model. J Hydrol 2019;568:462–78. https://doi.org/10.1016/J.JHYDROL.2018.11.015.
[41] Cortes C, Vapnik V. Support-Vector Networks. Mach Learn 1995;20:273–97. https://doi.org/10.1023/A:1022627411411.
[42] Ashrafian A, Shokri F, Taheri Amiri MJ, Yaseen ZM, Rezaie-Balf M. Compressive strength of Foamed Cellular Lightweight Concrete simulation: New development of hybrid artificial intelligence model. Constr Build Mater 2020;230:117048. https://doi.org/10.1016/J.CONBUILDMAT.2019.117048.
[43] Eskandar H, Sadollah A, Bahreininejad A, Hamdi M. Water cycle algorithm – A novel metaheuristic optimization method for solving constrained engineering optimization problems. Comput Struct 2012;110–111:151–66. https://doi.org/10.1016/J.COMPSTRUC.2012.07.010.
[44] Noparast M, Hematian M, Ashrafian A, Javad M, Amiri T, Azarijafari H. Development of a non-dominated sorting genetic algorithm for implementing circular economy strategies in the concrete industry. Sustain Prod Consum 2021;27:933–46. https://doi.org/10.1016/j.spc.2021.02.009.
[45] Zhang W, Lee D, Lee J, Lee C. Residual strength of concrete subjected to fatigue based on machine learning technique. Struct Concr 2022;23:2274–87. https://doi.org/10.1002/SUCO.202100082.
[46] Asteris PG, Lourenço PB, Hajihassani M, Adami CEN, Lemonis ME, Skentou AD, et al. Soft computing-based models for the prediction of masonry compressive strength. Eng Struct 2021;248:113276. https://doi.org/10.1016/J.ENGSTRUCT.2021.113276. | ||
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