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تعیین درصد بهینه سنگدانههای درشت بتن بازیافتی مورد استفاده در محیط‌های خورنده براساس مدل کریجینگ | ||
| نشریه مهندسی عمران امیرکبیر | ||
| مقاله 5، دوره 53، شماره 3، خرداد 1400، صفحه 863-878 اصل مقاله (1.91 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22060/ceej.2019.16560.6299 | ||
| نویسندگان | ||
| عبد القیوم دهواری1؛ محمود میری* 2؛ محمد رضا سهرابی1 | ||
| 1گروه عمران ، دانشگاه سیستان و بلوچستان | ||
| 2دانشگاه سیستان و بلوچستان | ||
| چکیده | ||
| در این مقاله، سنگدانههای درشت بتن پسماند پس از بازیافت بصورت سنگدانههای بازیافتی در مخلوط بتن برای بررسی تأثیر استفاده از آنها روی خصوصیات دوام و مکانیکی بتن در یک محیط خورنده استفاده شده‌اند. به این منظور پارامترهایی مانند جذب آب، تخلخل، مقاومت الکتریکی و مقاومت فشاری برای نمونه‌های ساخته شده در آزمایشگاه، اندازه‌گیری شده‌اند. در این تحقیق مدل‌های تخمین پارامترهای دوام و مکانیکی بتن با استفاده از روش مدل‌سازی کریجینگ بدست آمده‌اند و سپس این مدل‌ها با استفاده از الگوریتم بهینه سازی حرکت مولکول‌های گاز ایده‌آل به عنوان قیود مسأله بهینه سازی مورد ارزیابی قرار گرفته‌اند، و مقادیر بهینه تابع هدف یعنی میزان حداکثر استفاده از سنگدانههای درشت بازیافتی و حداقل میزان سیمان مصرفی برای دست‌یابی به یک بتن دوست‌دار محیط‌زیست بدست آمده‌اند. نتایج بهینه سازی نشان داده است در یک محیط با رطوبت 70 درصد، غلظت یون کلرید 3 درصد و دمای 23 و در دامنه سطح خورندگی بالا با بهینه سازی تک هدفه نقطه بهینه دارای 33/20 درصد سنگدانه درشت بازیافتی در نسبت آب به سیمان 40/0 است. همچنین در فرآیند بهینه سازی چند هدفه و در دامنه سطح خورندگی بالا برای یک محیط با رطوبت 70 درصد، غلظت یون کلرید 5 درصد و دما 23 نقطه طراحی با 34/18 درصد سنگدانه درشت بازیافتی در نسبت آب به سیمان 40/0 بدست آمده، که نتایج مشابه آن در بهینه سازی تک هدفه مشاهده نشده است. | ||
| کلیدواژه‌ها | ||
| سنگدانه درشت بازیافتی؛ بهینهسازی؛ مقاومت الکتریکی؛ مدل کریجینگ؛ الگوریتم حرکت مولکول‌های گاز ایده‌آل | ||
| موضوعات | ||
| تکنولوژی بتن؛ زباله جامد شهری؛ مصالح مختلف ساختمانی | ||
| عنوان مقاله [English] | ||
| Determining Optimum Percent of Recycled Coarse Aggregates used in Corrosive Environment Based on Kriging Model | ||
| نویسندگان [English] | ||
| aAbdol ghaium dehvari1؛ Mahmoud Miri2؛ Mohamad Reza Sohrabi1 | ||
| 1Dept. of Civil Eng. University of Sistan and Baluchestan | ||
| 2University of Sistan and Baluchestan | ||
| چکیده [English] | ||
| In this research, have been used of Kriging surrogate methods to obtain the mechanical and durability parameters’ estimation models and a very recent meta-heuristic optimization algorithm to obtain the optimum amount of recycled coarse aggregates and cement in the concrete mix to reach an environmentally friendly concrete. Results have shown that the optimum design point in a 70% humidity environment, 3% chloride ion concentration, and a temperature of 23 at high corrosion risk level has been reached at 20.33% and 0.40 of recycled coarse aggregate and water-cement ratio, respectively, in single-objective optimization. In addition to this, multi-objective optimization results have shown that in an environment with a 70% humidity environment, 5% chloride ion concentration, and a temperature of 23 the optimum design point has been obtained at 18.34%, 0.40 of recycled coarse aggregate, and water-cement ratio, respectively, that the same results hadn’t been observed in the single-objective optimization procedure. | ||
| کلیدواژه‌ها [English] | ||
| Recycled coarse aggregate, Optimization, Electrical resistance, Kriging model, Ideal gas molecular movement algorithm | ||
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[1] N. Kisku, H. Joshi, M. Ansari, S.K. Panda, Sanket Nayak, Sekhar Chandra Dutta. A critical review and assessment for usage of recycled aggregate as sustainable construction material, Construction and Building Materials, (2016). [2] Upal Mohammad Towfiqul Quadir, Kamrul Islam, A.H.M. Muntasir Billah, M. Shahria Alam. Mechanical and durability properties of concrete using recycled granulated steel, Construction and Building Materials, 123(2016)174–183. [3] Sumaiya Binte Huda, M. Shahria Alam. Mechanical behavior of three generations of 100% repeated recycled coarse aggregate concrete, Construction and Building Materials, 65 (2014) 574–582. [4] Wil V. Srubar III. Stochastic service-life modeling of chloride-induced corrosion in recycled-aggregate concrete, Cement & Concrete Composites, 55 (2015) 103–111. [5] Marco Pepe, Romildo Dias Toledo Filho, Eduardus A.B. Koenders, Enzo Martinelli. A novel mix design methodology for Recycled Aggregate Concrete, Construction and Building Materials, 122(2016) 362–372. [6] S. Boudali, D.E. Kerdal, K. Ayed, B. Abdulsalam, A.M. Soliman. Performance of self-compacting concrete incorporating recycled concrete fines and aggregate exposed to sulphate attack, Construction and Building Materials, 124(2016)705–713. [7] Yimmy Fernando Silva, Rafael Andres Robayo, Pedro Enrique Mattey, Silvio Delvasto. Properties of self-compacting concrete on fresh and hardened with residue of masonry and recycled concrete, Construction and Building Materials,124 (2016) 639–644. [8] Bo Yu, LuFeng Yang, Ming Wu, Bing Li. Practical model for predicting corrosion rate of steel reinforcement in concrete structures, Construction and Building Materials, 54 (2014) 385–401. [9] Bo Yu, Jianbo Liu, Zheng Chen. Probabilistic evaluation method for corrosion risk of steel reinforcement based on concrete resistivity, Construction and Building Materials, 138 (2017) 101–113. [10] Michelle R. Nokken and R. Doug Hooton. Electrical Conductivity Testing, American Concrete International, (2006). [11] Hamed Layssi, Pouria Ghods, Aali R. Alizadeh, and Mustafa Salehi. Electrical Resistivity of Concrete, (2015). [12] Jafar Vahedi, Mohammad Reza Ghasemi, Mahmoud Miri, An adaptive divergence-based method for structural reliability analysis via multiple Kriging models. Applied Mathematical Modelling, (2018). [13] Buyu Jia, XiaoLin Yu, QuanSheng Yan. A new sampling strategy for Kriging based response surface method and its application in structural reliability, Advances in Structural Engineering, (2016) 1–18. [14] Neela Deshpande, Shreenivas Londhe, Sushma Kulkarni. Modeling compressive strength of recycled aggregate concrete by Artificial Neural Network, Model Tree and Non-linear Regression, International Journal of Sustainable Built Environment, 3(2014) 187–198. [15] S.N. Lophaven, J. Søndergaard, H.B. Nielsen, DACE A Matlab Kriging Toolbox, IMM Informatiocs Math.Model. (2002). [16] S. Castric, L. Denis-Vidal, Z. Cherfi, G. Joly Blanchard, N. Boudaoud. Modeling Pollutant Emissions of Diesel Engine based on Kriging Models: a Comparison between Geostatistic and Gaussian Process Approach, Proceedings of the 14th IFAC Symposium on Information Control Problems in Manufacturing Bucharest, Romania, (2012)23-25. [17] Alexander I. J. Forrester, András Sóbester and Andy J. Keane. Engineering Design via Surrogate Modelling: A Practical Guide, University of Southampton, UK, John Wiley & Sons Ltd, (2008). [18] Singiresu S. Rao. Engineering Optimization Theory and Practice, Fourth Edition, Published by John Wiley & Sons, Inc., Hoboken, New Jersey, (2009). [19] Hesam Varaee, Mohammad Reza Ghasemi. Engineering optimization based on ideal gas molecular movement algorithm, Engineering with Computers, (2016). [20] Yaser Moodi, Seyed Roohollah Mousavi, Alireza Ghavidel, Mohammad Reza Sohrabi, Mohsen Rashki. Using Response Surface Methodology and providing a modified model using whale algorithm for estimating the compressive strength of columns confined with FRP sheets, Construction and Building Materials, 183 (2018) 163–170. [21] Nikola Tosic, Snezana Marinkovic, Tina Dasic, Milos Stani. Multicriteria optimization of natural and recycled aggregate concrete for structural use, Journal of Cleaner Production, 87 (2015) 766–776. [22] Mohammad Reza Ghasemi, Hesam Varaee. A fast multi‑objective optimization using an efficient ideal gas molecular movement algorithm, Engineering with Computers, (2016). [23] ASTM C 29/C 29M-97. Standard Test Method for Bulk Density (“Unit Weight”) and Voids in Aggregate. [24] ASTM C 127-04. Standard Test Method for Density, Relative Density (Specific Gravity), and Absorption of Coarse Aggregate. [25] ASTM C 128-04a. Standard Test Method for Density, Relative Density (Specific Gravity), and Absorption of Fine Aggregate. [26] ASTM C 33- 01. Standard Specification for Concrete Aggregates. [27] ASTM C 642/C 642M-06. Standard Test Method for Density, Absorption, and Voids in Hardened Concrete. [28] ASTM C 39/C 39M-05. Standard Test Method for Compressive Strength of Cylindrical Concrete Specimens. [29] ASTM C 1760-12. Standard Test Method for Bulk Electrical Conductivity of Hardened Concrete. [30] Ma Kang and Li Weibin, Effect of the Aggregate Size on Strength Properties of Recycled Aggregate Concrete, Advances in Materials Science and Engineering, (2018) https://doi.org/10.1155/2018/2428576 [31] C.S. Poon, Z.H. Shui, L. Lam, Effect of microstructure of ITZ on compressive strength of concrete prepared with recycled aggregates, Construction and Building Materials, 18 (2004) 461–468. [32] Gongbing Yue, Peng Zhang , Qiuyi Li , and Qianqian Li, Performance Analysis of a Recycled Concrete Interfacial Transition Zone in a Rapid Carbonization Environment, Advances in Materials Science and Engineering, (2018) https://doi.org/10.1155/2018/1962457 [33] Rob B. Polder. Test methods for onsite measurement of resistivity of Concrete a RILEM TC-154 technical recommendation, Construction and Building Materials, 15 (2001) 125-131. [34] Thomas, R. J., Properties and Performance of Alkali-Activated Concrete, PhD Thesis, Clarkson University, Department of Civil Engineering, Potsdam NY, 2016.
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