Advances in concrete construction

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On the optimization of building energy, material, and economic management using soft computing

  • Wei, Zhao (School of Management, Wuhan Polytechnic University) ;
  • Zandi, Yousef (Department of Civil Engineering, Tabriz Branch, Islamic Azad University) ;
  • Gholizadeh, Morteza (Department of Civil Engineering, Tabriz Branch, Islamic Azad University) ;
  • Selmi, Abdellatif (Department of Civil Engineering, College of Engineering, Prince Sattam bin Abdulaziz University) ;
  • Roco-Videla, Angel (Programa Magister en Ciencias Quimico-biologicas, Facultad de Ciencias de la Salud, Universidad Bernardo O'Higgins) ;
  • Konbr, Usama (Department of Architecture, Faculty of Engineering, Tanta University)
  • Received : 2020.11.25
  • Accepted : 2021.04.21
  • Published : 2021.06.25
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Abstract

This paper provides energy and economic analysis relevant to the cooling season in building enclosures. For a whole year, an Energy Plus thermal transfer model has been created and simulated. Simulations were made from the cities in five different areas of climate in China using weather data files. Energy savings were done from natural cold (e.g., outdoor air), and electricity reductions were performed from air-conditioning electricity devices. This research has investigated the relationship between the cost and building energy while finding a strong and positive correlation. This study has used the Artificial Intelligence (AI) model as Extreme Learning Machine (ELM) and Teaching Learning Based Optimization (TLBO) to calculate the accurate measurement. Three regression models as Pearson correlation coefficient (r), root mean square (RMSE), and coefficient of determination (R2) was used to calculate the results. Following the results of (R2) and RMSE, ELM has shown its higher performance in predicting the strength, energy, and cost of building materials. Based on the simulation results, for office buildings situated in cold areas, the energy savings resulting from phase change materials (PCM) are more prevalent. The test findings demonstrate that the energy savings from PCM applications for the cool area and hot summers and cold winter office buildings were increased. Simple payback time indicated that PCMBs in inhabited buildings could be used cost-effectively in a mild temperature environment.

Keywords

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  89. Shariati, M. (2008), "Assessment of building using nonedestructive test techniques (ultra Sonic Pulse Velocity and Schmidt Rebound Hammer)", Universiti Putra Malaysia.
  90. Shariati, M. (2013), "Behaviour of C-shaped shear connectors in stell concrete composite beams", Jabatan Kejuruteraan Awam, Fakulti Kejuruteraan, Universiti Malaya.
  91. Shariati, M. (2020), "Evaluation of seismic performance factors for tension-only braced frames", Steel Compos. Struct., 35(4), 599-609. https://doi.org/10.12989/scs.2020.35.4.599.
  92. Shariati, M., Armaghani, D.J., Khandelwal, M., Zhou, J., Eyvaziyan, A. and Khorami, M. (2021), "Assessment of longstanding effects of fly ash and silica fume on the compressive strength of concrete using extreme learning machine and artificial neural network", J. Adv. Eng. Comput., 5(1), 50-75. http://dx.doi.org/10.25073/jaec.202151.308.
  93. Shariati, M., Azar, S.M., Arjomand, M.A., Tehrani, H.S., Daei, M. and Safa, M. (2019a), "Comparison of dynamic behavior of shallow foundations based on pile and geosynthetic materials in fine-grained clayey soils", Geomech. Eng., 19(6), 473. https://doi.org/10.12989/gae.2019.19.6.473.
  94. Shariati, M., Azar, S.M., Arjomand, M.A., Tehrani, H.S., Daei, M. and Safa, M. (2020a), "Evaluating the impacts of using piles and geosynthetics in reducing the settlement of fine-grained soils under static load", Geomech. Eng., 20(2), 87-101. https://doi.org/10.12989/gae.2020.20.2.087.
  95. Shariati, M., Faegh, S.S., Mehrabi, P., Bahavarnia, S., Zandi, Y., Masoom, D.R., Toghroli, A., Trung, N.T. and Salih, M.N. (2019b), "Numerical study on the structural performance of corrugated low yield point steel plate shear walls with circular openings", Steel Compos. Struct., 33(4), 569-581. https://doi.org/10.12989/scs.2019.33.4.569.
  96. Shariati, M., Ghorbani, M., Naghipour, M., Alinejad, N. and Toghroli, A. (2020b), "The effect of RBS connection on energy absorption in tall buildings with braced tube frame system", Steel Compos. Struct., 34(3), 393. https://doi.org/10.12989/scs.2020.34.3.393.
  97. Shariati, M., Grayeli, M., Shariati, A. and Naghipour, M. (2020c), "Performance of composite frame consisting of steel beams and concrete filled tubes under fire loading", Steel Compos. Struct., 36(5), 587-602. https://doi.org/10.12989/scs.2020.36.5.587.
  98. Shariati, M., Heyrati, A., Zandi, Y., Laka, H., Toghroli, A., Kianmehr, P., Safa, M., Salih, M.N. and Poi-Ngian, S. (2019c), "Application of waste tire rubber aggregate in porous concrete", Smart Struct. Syst., 24(4), 553-566. https://doi.org/10.12989/sss.2019.24.4.553.
  99. Shariati, M., Mafipour, M.S., Ghahremani, B., Azarhomayun, F., Ahmadi, M., Trung, N.T. and Shariati, A. (2020d), "A novel hybrid extreme learning machine-grey wolf optimizer (ELMGWO) model to predict compressive strength of concrete with partial replacements for cement", Eng. Comput., 1-23. https://doi.org/10.1007/s00366-020-01081-0.
  100. Shariati, M., Mafipour, M.S., Haido, J.H., Yousif, S.T., Toghroli, A., Trung, N.T. and Shariati, A. (2020e), "Identification of the most influencing parameters on the properties of corroded concrete beams using an Adaptive Neuro-Fuzzy Inference System (ANFIS)", Steel Compos. Struct., 34(1), 155. http://dx.doi.org/10.12989/scs.2020.34.1.155.
  101. Shariati, M., Mafipour, M.S., Mehrabi, P., Ahmadi, M., Wakil, K., Trung, N.T. and Toghroli, A. (2020f), "Prediction of concrete strength in presence of furnace slag and fly ash using Hybrid ANN-GA (Artificial Neural Network-Genetic Algorithm)", Smart Struct. Syst., 25(2), 183. https://doi.org/10.12989/sss.2020.25.2.183.
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