بررسی خواص مهندسی بتن خود تراکم فوق توانمند الیافی و پیش‌بینی خواص رئولوژی آن با شبکه عصبی هیبریدی و RBF

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه مهندسی عمران، واحد نجف آباد، دانشگاه آزاد اسلامی، نجف آباد، ایران

2 گروه مهندسی عمران، دانشگاه قم، قم، ایران

چکیده

امروزه استفاده از بتن­های نوین در حال گسترش است، یکی از انواع این نوع بتن، بتن خود تراکم فوق توانمند الیافی است که شناخت خواص رئولوژی و مکانیکی آن از اهمیت بالایی برخوردار است. ساخت بتن و انجام آزمایش‌های مربوط به آن هزینه‌های مختص به خود را داراست، یکی از راه کارهای کاهش این هزینه‌ها استفاده از روش‌هایی است که بتواند خواص بتن را پیش‌بینی کند. در این تحقیق در قسمت اول از سنگدانه‌های گارنت و بازالت، میکرو سیلیس، خاکستر بادی، نانو سیلیس و الیاف فولادی جهت ساخت بتن خود تراکم فوق توانمند الیافی (UHPSCC) استفاده شده و خواص رئولوژی، مقاومت فشاری، کششی و ریزساختار آن بررسی شده است. جهت صرفه‌جویی در هزینه‌های ساخت و در قسمت دوم این تحقیق، پیش‌بینی و تخمین دو شبکه عصبی مصنوعی ANN-GA (ترکیب شبکه عصبی مصنوعی و الگوریتم ژنتیک) و RBF-NN (شبکه عصبی توابع بنیادی شعاعی) از خواص رئولوژی بتن خود تراکم فوق توانمند الیافی و مقایسه آن با نتایج آزمایشگاهی بررسی شده است. خواص رئولوژی بتن خود تراکم فوق توانمند الیافی که در این تحقیق مورد بررسی قرار گرفته شامل قطر جریان اسلامپ (D)، زمان جریان اسلامپ (T50)، آزمایش قیفV و آزمایش جعبه L است. نتایج آزمایشگاهی نشان‌دهنده مقاومت فشاری و کششی بالا و قرارگرفتن خواص رئولوژی در محدوده مورد پذیرش EFNARC است. تخمین و پیش‌بینی دو شبکه عصبی مورد بررسی از خواص رئولوژی این نوع بتن، نشان‌دهنده دقت قابل‌قبول پیش‌بینی هر دو شبکه عصبی دارد. در میان این دو شبکه عصبی مصنوعی، دقت پیش‌بینی ANN-GA بیشتر است.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Investigating the engineering properties of fiber-reinforced ultra-high performance self-compacting concrete and predicting its rheological properties using a hybrid neural network and RBF

نویسندگان [English]

  • Alireza Rashno 1
  • Mohamadreza Adlparvar 1 2
  • Mohsen Izadinia 1
1 Department of Civil Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran
2 Department of Civil Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran
چکیده [English]

This study investigates the rheological and mechanical properties of ultra-high performance fiber reinforced self-compacting concrete (UHPSCC) using garnet and basalt aggregates, microsilica, fly ash, nanosilica, and steel fibers. To reduce construction costs, two artificial neural networks (ANN-GA and RBF-NN) are used to predict UHPSCC properties and compared with laboratory results. The studied rheological properties include slump flow diameter, slump flow time, V-funnel test, and L-box test. The laboratory results show high compressive and tensile strength, and acceptable rheological properties within EFNARC acceptance range. Both neural networks demonstrate acceptable accuracy in predicting rheological properties, with ANN-GA having higher prediction accuracy. Understanding UHPSCC properties is essential for the construction industry, and the use of ANN-GA can save on costs while maintaining accuracy in predicting its properties.

کلیدواژه‌ها [English]

  • Fiber-reinforced ultra-high performance self-compacting concrete
  • Rheology properties
  • Prediction
  • ANN-GA
  • RBF-NN

مراجع

[1] H. Song, K. Byun, S. Kim, D. Choi, Early-age creep and shrinkage in self-compacting concrete incorporating GGBFS, in:  Proceedings of the 2nd international RILEM symposium on self-compacting concrete. Tokyo: COMS Engineering Corporation, 2001, pp. 413-422.
[2] T.R. Naik, R. Kumar, B.W. Ramme, F. Canpolat, Development of high-strength, economical self-consolidating concrete, Construction and Building Materials, 30 (2012) 463-469.
[3] O.H. Wallevik, J.E. Wallevik, Rheology as a tool in concrete science: The use of rheographs and workability boxes, Cement and concrete research, 41(12) (2011) 1279-1288.
[4]M. Cyr, C. Legrand, M. Mouret, Study of the shear thickening effect of superplasticizers on the rheological behaviour of cement pastes containing or not mineral additives, Cement and concrete research, 30 (2000) 1477-1483.
[5]T. Lecompte, A. Perrot, Non-linear modeling of yield stress increase due to SCC structural build-up at rest, Cement and Concrete Research, 92 (2017) 92-97.
[6]M. Alkaysi, S. El-Tawil, Z. Liu, W. Hansen, Effects of silica powder and cement type on durability of ultra high performance concrete (UHPC), Cement and Concrete Composites, 66 (2016) 47-56.
[7]W.H. Kwan, M. Ramli, C.B. Cheah, Flexural strength and impact resistance study of fibre reinforced concrete in simulated aggressive environment, Construction and Building Materials, 63 (2014) 62-71.
[8]M. Nili, A. Ghorbankhani, A. AlaviNia, M. Zolfaghari, Assessing the impact strength of steel fibre-reinforced concrete under quasi-static and high velocity dynamic impacts, Construction and Building Materials, 107 (2016) 264-271.
[9]D.-Y. Yoo, N. Banthia, Mechanical properties of ultra-high-performance fiber-reinforced concrete: A review, Cement and Concrete Composites, 73 (2016) 267-280.
[10]A. Arora, M. Aguayo, H. Hansen, C. Castro, E. Federspiel, B. Mobasher, N. Neithalath, Microstructural packing-and rheology-based binder selection and characterization for Ultra-high Performance Concrete (UHPC), Cement and Concrete Research, 103 (2018) 179-190.
[11]S. Abbas, M. Nehdi, M. Saleem, Ultra-high performance concrete: Mechanical performance, durability, sustainability and implementation challenges, International Journal of Concrete Structures and Materials, 10 (2016) 271-295.
[12]V. Afroughsabet, L. Biolzi, T. Ozbakkaloglu, High-performance fiber-reinforced concrete: a review, Journal of materials science, 51 (2016) 6517-6551.
[13]V. Afroughsabet, T. Ozbakkaloglu, Mechanical and durability properties of high-strength concrete containing steel and polypropylene fibers, Construction and building materials, 94 (2015) 73-82.
[14]N. Van Tuan, G. Ye, K. Van Breugel, A.L. Fraaij, D. Dai Bui, The study of using rice husk ash to produce ultra high performance concrete, Construction and Building Materials, 25(4) (2011) 2030-2035.
[15]Q. Song, R. Yu, X. Wang, S. Rao, Z. Shui, A novel self-compacting ultra-high performance fibre reinforced concrete (SCUHPFRC) derived from compounded high-active powders, Construction and Building Materials, 158 (2018) 883-893.
[16]E. Fehling, M. Schmidt, S. Stürwald, Ultra High Performance Concrete:(UHPC); Proceedings of the Second International Symposium on Ultra High Performance Concrete, Kassel, Germany, March 05-07, 2008, kassel university press GmbH, 2008.
[17]E. Brühwiler, E. Denarié, Rehabilitation and strengthening of concrete structures using ultra-high performance fibre reinforced concrete, Structural Engineering International, 23(4) (2013) 450-457.
[18] H.L. Muttashar, M.A. Mohd Ariffin, M.W. Hussin, S.B. Ishaq, Realisation of enhanced self-compacting geopolymer concrete using spent garnet as sand replacement, Magazine of Concrete Research, 70 (2018) 558-569.
[19]P. Li, Q. Yu, H. Brouwers, Effect of coarse basalt aggregates on the properties of Ultra-high Performance Concrete (UHPC), Construction and Building Materials, 170 (2018) 649-659.
[20]K.H. Mo, S.P. Yap, U.J. Alengaram, M.Z. Jumaat, C.H. Bu, Impact resistance of hybrid fibre-reinforced oil palm shell concrete, Construction and Building Materials, 50 (2014) 499-507.
[21]B. Balakrishnan, A. Awal, Mechanical properties and thermal resistance of high volume fly ash concrete for energy efficiency in building construction, in:  Key Engineering Materials, Trans Tech Publ, pp. , (2016) 99-108.
[22]A. Muller, K. Scrivener, J. Skibsted, A. Gajewicz, P. McDonald, Influence of silica fume on the microstructure of cement pastes: New insights from 1H NMR relaxometry, Cement and Concrete Research,74 (2015) 116-125.
[23]Y. Cai, P. Hou, X. Cheng, P. Du, Z. Ye, The effects of nanoSiO2 on the properties of fresh and hardened cement-based materials through its dispersion with silica fume, Construction and Building Materials, 148 (2017) 770-780.
[24]F. Shaikh, S. Supit, P. Sarker, A study on the effect of nano silica on compressive strength of high volume fly ash mortars and concretes, Materials & Design, 60 (2014) 433-442.
[25]A.J. Paulson, R.A. Prabhavathy, S. Rekh, E. Brindha, Application of neural network for prediction of compressive strength of silica fume concrete, Int. J. Civ. Eng. Technol, 10(2) (2019) 1859-1867.
[26]F.X. Li, Q.J. Yu, J.X. Wei, J.X. Li, Predicting the workability of self-compacting concrete using artificial neural network, in:  Advanced Materials Research, Trans Tech Publ, 2011, pp. 1730-1734.
[27]M.A. Getahun, S.M. Shitote, Z.C.A. Gariy, Artificial neural network based modelling approach for strength prediction of concrete incorporating agricultural and construction wastes, Construction and Building Materials, 190 (2018) 517-525.
[28]Z. Keshavarz, H. Torkian, Application of ANN and ANFIS models in determining compressive strength of concrete, Journal of Soft Computing in Civil Engineering, 2(1) (2018) 62-70.
[29]M. Mazloom, S.F. Tajar, F. Mahboubi, Long-term quality control of self-compacting semi-lightweight concrete using short-term compressive strength and combinatorial artificial neural networks, Computers and Concrete, An International Journal, 25(5) (2020) 401-409.
[30]H. Eskandari-Naddaf, R. Kazemi, ANN prediction of cement mortar compressive strength, influence of cement strength class, Construction and Building Materials, 138 (2017) 1-11.
[31]E.M. Golafshani, A. Ashour, Prediction of self-compacting concrete elastic modulus using two symbolic regression techniques, Automation in Construction, 64 (2016) 7-19.
[32]M.I. Al-Khatib, S. Al-Martini, Predicting the rheology of self-consolidating concrete under hot weather, Proceedings of the Institution of Civil Engineers-Construction Materials, 172(5) (2019) 235-245.
[33]M.R. Kaloop, P. Samui, M. Shafeek, J.W. Hu, Estimating slump flow and compressive strength of self-compacting concrete using emotional neural networks, Applied Sciences, 10(23) (2020) 8543.
[34]F. Zahiri, H. Eskandari-Naddaf, Optimizing the compressive strength of concrete containing micro-silica, nano-silica, and polypropylene fibers using extreme vertices mixture design, Frontiers of Structural and Civil Engineering, 13 (2019) 821-830.
[35]A. Rashno, A. Saghaeifar, Durability of ultra-high-performance self-compacting concrete with hybrid fibers, Emerging Materials Research, 9(2) (2020) 331-341.
[36]R. Parichatprecha, P. Nimityongskul, Analysis of durability of high performance concrete using artificial neural networks, Construction and Building Materials, 23(2) (2009) 910-917.
[37]R. Venkatakrishnaiah, G. Sakthivel, Bulk utilization of flyash in self compacting concrete. KSCE J, Civil Eng,  (2017).
[38]K. Janković, S. Stanković, D. Bojović, M. Stojanović, L. Antić, The influence of nano-silica and barite aggregate on properties of ultra high performance concrete, Construction and Building Materials, 126 (2016) 147-156.
[39]S. EFNARC, Guidelines for self-compacting concrete, London, UK: Association House, 32 (2002) 34.
[40]C. Bibm, E. Ermco, EFNARC: The European guidelines for self compacting concrete, Specification, Production and Use, 63 (2005).
[41]BS EN 12390-3, Testing Hardened Concrete. Part 3: Compressive Strength of Test Specimens, BSI British Standards Institution, (2019).
[42] ACI 318M-08, A. Standard, Building Code Requirements for Structural Concrete and Commentary, Reported by ACI Committee, 318 (2008).
[43]M.U. Rashid, Experimental investigation on durability characteristics of steel and polypropylene fiber reinforced concrete exposed to natural weathering action, Construction and Building Materials, 250 (2020) 118910.
[44] ASTM C496. Testing, M.C.C.-o. Concrete, C. Aggregates, Standard test method for splitting tensile strength of cylindrical concrete specimens, ASTM International, (2011).
نشریه مهندسی عمران امیرکبیر
دوره 55، شماره 5
مرداد 1402
صفحه 1103-1120

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