International Journal of Optimization in Civil Engineering
عنوان نشریه
IJOCE
Engineering & Technology
http://ijoce.iust.ac.ir
18
agent2
2228-7558
doi
en
jalali
1396
10
1
gregorian
2018
1
1
8
1
online
1
fulltext
en
NUMERICAL TECHNIQUES FOR DIFFERENT THERMAL INSULATION MATERIALS
Applications
Applications
پژوهشي
Research
<p>The objective of this work is to predict the temperature of the different types of walls which are Ferro cement wall, reinforced cement concrete (RCC) wall and two types of cavity walls (combined RCC with Ferrocement and combined two Ferro cement walls) with the help of mathematical modeling. The property of low thermal transmission of small air gap between the constituents of combine materials has been utilized to obtain energy efficient wall section. Ferro cement is a highly versatile form of reinforced concrete made up of wire mesh, sand, water, and cement, which possesses unique qualities of strength and serviceability. The significant intention of the proposed technique is to frame a mathematical modeling with the aid of optimization techniques. Mathematical modeling is done by minimizing the cost and time consumed in the case of extension of the existing work. Mathematical modeling is utilized to predict the temperature of the different wall such as RCC wall, Ferro cement, combined RCC with Ferro cement and combined Ferro cement wall. The different optimization algorithms such as Social Spider Optimization (SSO), Genetic Algorithm (GA) and Group Search Optimization (GSO) are utilized to find the optimal weights α and β of the mathematical modeling. All optimum results demonstrate that the attained error values between the output of the experimental values and the predicted values are closely equal to zero with the SSO model. The results of the proposed work are compared with the existing methods and the minimum errors with SSO algorithm for the case of two combined RCC wall was found to be less than 2%.</p>
ferro cement wall, reinforced cement concrete (RCC), wall temperature, social spider optimization (SSO), genetic algorithm (GA), group search optimization (GSO), air gap, energy efficient wall section.
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http://ijoce.iust.ac.ir/browse.php?a_code=A-10-66-165&slc_lang=en&sid=1
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M. K.
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180031947532846001242
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Panda
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