IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i21p11957-d667677.html
   My bibliography  Save this article

Thermal Behavior and Energy Efficiency of Modified Concretes in the Tropical Climate: A Systemic Review

Author

Listed:
  • Yeong Huei Lee

    (Department of Civil and Construction Engineering, Faculty of Engineering and Science, Curtin University, CDT 250, Miri 98009, Sarawak, Malaysia)

  • Mugahed Amran

    (Department of Civil Engineering, College of Engineering, Prince Sattam Bin Abdulaziz University, Alkharj 11942, Saudi Arabia
    Department of Civil Engineering, Faculty of Engineering and IT, Amran University, Amran 9677, Yemen)

  • Yee Yong Lee

    (Department of Civil Engineering, Faculty of Engineering, Universiti Malaysia Sarawak, Kota Samarahan 94300, Sarawak, Malaysia)

  • Ahmad Beng Hong Kueh

    (Department of Civil Engineering, Faculty of Engineering, Universiti Malaysia Sarawak, Kota Samarahan 94300, Sarawak, Malaysia)

  • Siaw Fui Kiew

    (Curtin Malaysia Research Institute, Sarawak Biovalley Pilot Plant, Curtin University, Sarawak Malaysia, CDT 250, Miri 98009, Sarawak, Malaysia)

  • Roman Fediuk

    (Polytechnic Institute, Far Eastern Federal University, 690922 Vladivostok, Russia)

  • Nikolai Vatin

    (Peter the Great St. Petersburg Polytechnic University, 195251 St. Petersburg, Russia)

  • Yuriy Vasilev

    (Peter the Great St. Petersburg Polytechnic University, 195251 St. Petersburg, Russia)

Abstract

Concrete remains the most utilised construction material for building envelopes, which regulate the indoor temperature to achieve human thermal comfort. Often, the energy consumption for building performance appraisal is related to the thermal behaviour of building materials as heating, ventilation, and air conditioning systems all variously contribute to human comfort. Following the development of concrete technology, many types of concrete have been invented to serve several purposes in the construction industry. To clearly understand the concrete type tailored for the specifics of a construction project, the local climate, concrete mechanical properties, and concrete thermal behaviours should be primarily identified to achieve energy efficiency, which also suits the sustainability of global materials. This paper, therefore, reviews the modified concrete thermal behaviours in the tropical climate for more systematic city planning in order to achieve better energy efficiency. Urban heat islands in the tropics and contributing factors, as well as heat transfer mechanisms, are first highlighted. The requirements of concrete thermal behaviour for building envelopes are then discussed through specific heat capacity, thermal conductivity, thermal diffusivity, time lag, and decrement factor in the context of applications and energy consumption in the tropical regions. With a case study, it is found that concrete thermal behaviours directly affect the energy consumption attributed mainly to the use of cooling systems in the tropics. The study can be a reference to mitigating the urban heat island phenomenon in the planning of urban development.

Suggested Citation

  • Yeong Huei Lee & Mugahed Amran & Yee Yong Lee & Ahmad Beng Hong Kueh & Siaw Fui Kiew & Roman Fediuk & Nikolai Vatin & Yuriy Vasilev, 2021. "Thermal Behavior and Energy Efficiency of Modified Concretes in the Tropical Climate: A Systemic Review," Sustainability, MDPI, vol. 13(21), pages 1-24, October.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:21:p:11957-:d:667677
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/21/11957/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/13/21/11957/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Saidur Rahaman & Selim Jahangir & Md Senaul Haque & Ruishan Chen & Pankaj Kumar, 2021. "Spatio-temporal changes of green spaces and their impact on urban environment of Mumbai, India," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(4), pages 6481-6501, April.
    2. Sanusi Saheed & Farah N. A. Abd. Aziz & Mugahed Amran & Nikolai Vatin & Roman Fediuk & Togay Ozbakkaloglu & Gunasekaran Murali & Mohammad Ali Mosaberpanah, 2020. "Structural Performance of Shear Loaded Precast EPS-Foam Concrete Half-Shaped Slabs," Sustainability, MDPI, vol. 12(22), pages 1-17, November.
    3. Capozzoli, Alfonso & Gorrino, Alice & Corrado, Vincenzo, 2013. "A building thermal bridges sensitivity analysis," Applied Energy, Elsevier, vol. 107(C), pages 229-243.
    4. Nusrat Jannat & Aseel Hussien & Badr Abdullah & Alison Cotgrave, 2020. "A Comparative Simulation Study of the Thermal Performances of the Building Envelope Wall Materials in the Tropics," Sustainability, MDPI, vol. 12(12), pages 1-26, June.
    5. Zingre, Kishor T. & Wan, Man Pun & Tong, Shanshan & Li, Hua & Chang, Victor W.-C. & Wong, Swee Khian & Thian Toh, Winston Boo & Leng Lee, Irene Yen, 2015. "Modeling of cool roof heat transfer in tropical climate," Renewable Energy, Elsevier, vol. 75(C), pages 210-223.
    6. Maytham S. Ahmed & Azah Mohamed & Raad Z. Homod & Hussain Shareef, 2016. "Hybrid LSA-ANN Based Home Energy Management Scheduling Controller for Residential Demand Response Strategy," Energies, MDPI, vol. 9(9), pages 1-20, September.
    7. Weinan Gan & Yunzhong Cao & Wen Jiang & Liangqiang Li & Xiaolin Li, 2019. "Energy-Saving Design of Building Envelope Based on Multiparameter Optimization," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-11, December.
    8. Jain, Rishee K. & Smith, Kevin M. & Culligan, Patricia J. & Taylor, John E., 2014. "Forecasting energy consumption of multi-family residential buildings using support vector regression: Investigating the impact of temporal and spatial monitoring granularity on performance accuracy," Applied Energy, Elsevier, vol. 123(C), pages 168-178.
    9. Li, Ran & Wang, Zhimin & Gu, Chenghong & Li, Furong & Wu, Hao, 2016. "A novel time-of-use tariff design based on Gaussian Mixture Model," Applied Energy, Elsevier, vol. 162(C), pages 1530-1536.
    10. Chua, K.J. & Chou, S.K., 2010. "Energy performance of residential buildings in Singapore," Energy, Elsevier, vol. 35(2), pages 667-678.
    11. Drissi, Sarra & Ling, Tung-Chai & Mo, Kim Hung, 2020. "Thermal performance of a solar energy storage concrete panel incorporating phase change material aggregates developed for thermal regulation in buildings," Renewable Energy, Elsevier, vol. 160(C), pages 817-829.
    12. Fathipour, Reza & Hadidi, Amin, 2017. "Analytical solution for the study of time lag and decrement factor for building walls in climate of Iran," Energy, Elsevier, vol. 134(C), pages 167-180.
    13. Noura Ghabra & Lucelia Rodrigues & Philip Oldfield, 2017. "The impact of the building envelope on the energy efficiency of residential tall buildings in Saudi Arabia," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 12(4), pages 411-419.
    14. Naji, Sareh & Keivani, Afram & Shamshirband, Shahaboddin & Alengaram, U. Johnson & Jumaat, Mohd Zamin & Mansor, Zulkefli & Lee, Malrey, 2016. "Estimating building energy consumption using extreme learning machine method," Energy, Elsevier, vol. 97(C), pages 506-516.
    15. Kontoleon, K.J. & Eumorfopoulou, E.A., 2008. "The influence of wall orientation and exterior surface solar absorptivity on time lag and decrement factor in the Greek region," Renewable Energy, Elsevier, vol. 33(7), pages 1652-1664.
    16. Fateh Nassim Melzi & Allou Same & Mohamed Haykel Zayani & Latifa Oukhellou, 2017. "A Dedicated Mixture Model for Clustering Smart Meter Data: Identification and Analysis of Electricity Consumption Behaviors," Energies, MDPI, vol. 10(10), pages 1-21, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Leandro S. Silva & Mohammad K. Najjar & Carina M. Stolz & Assed N. Haddad & Mayara Amario & Dieter Thomas Boer, 2024. "Multiple Dimensions of Energy Efficiency of Recycled Concrete: A Systematic Review," Energies, MDPI, vol. 17(15), pages 1-33, August.
    2. Yi Xuan Tang & Yeong Huei Lee & Mugahed Amran & Roman Fediuk & Nikolai Vatin & Ahmad Beng Hong Kueh & Yee Yong Lee, 2022. "Artificial Neural Network-Forecasted Compression Strength of Alkaline-Activated Slag Concretes," Sustainability, MDPI, vol. 14(9), pages 1-20, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zingre, Kishor T. & Wan, Man Pun & Wong, Swee Khian & Toh, Winston Boo Thian & Lee, Irene Yen Leng, 2015. "Modelling of cool roof performance for double-skin roofs in tropical climate," Energy, Elsevier, vol. 82(C), pages 813-826.
    2. Liu, Che & Sun, Bo & Zhang, Chenghui & Li, Fan, 2020. "A hybrid prediction model for residential electricity consumption using holt-winters and extreme learning machine," Applied Energy, Elsevier, vol. 275(C).
    3. Amasyali, Kadir & El-Gohary, Nora M., 2018. "A review of data-driven building energy consumption prediction studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1192-1205.
    4. Kwonsik Song & Kyle Anderson & SangHyun Lee & Kaitlin T. Raimi & P. Sol Hart, 2020. "Non-Invasive Behavioral Reference Group Categorization Considering Temporal Granularity and Aggregation Level of Energy Use Data," Energies, MDPI, vol. 13(14), pages 1-21, July.
    5. Juan D. Velásquez & Lorena Cadavid & Carlos J. Franco, 2023. "Intelligence Techniques in Sustainable Energy: Analysis of a Decade of Advances," Energies, MDPI, vol. 16(19), pages 1-45, October.
    6. Venkatraj, V. & Dixit, M.K., 2022. "Challenges in implementing data-driven approaches for building life cycle energy assessment: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    7. Zhong, Hai & Wang, Jiajun & Jia, Hongjie & Mu, Yunfei & Lv, Shilei, 2019. "Vector field-based support vector regression for building energy consumption prediction," Applied Energy, Elsevier, vol. 242(C), pages 403-414.
    8. Li, Xinyi & Yao, Runming, 2020. "A machine-learning-based approach to predict residential annual space heating and cooling loads considering occupant behaviour," Energy, Elsevier, vol. 212(C).
    9. Ramya Kuppusamy & Srete Nikolovski & Yuvaraja Teekaraman, 2023. "Review of Machine Learning Techniques for Power Quality Performance Evaluation in Grid-Connected Systems," Sustainability, MDPI, vol. 15(20), pages 1-29, October.
    10. Kamel, Ehsan & Sheikh, Shaya & Huang, Xueqing, 2020. "Data-driven predictive models for residential building energy use based on the segregation of heating and cooling days," Energy, Elsevier, vol. 206(C).
    11. Mirrahimi, Seyedehzahra & Mohamed, Mohd Farid & Haw, Lim Chin & Ibrahim, Nik Lukman Nik & Yusoff, Wardah Fatimah Mohammad & Aflaki, Ardalan, 2016. "The effect of building envelope on the thermal comfort and energy saving for high-rise buildings in hot–humid climate," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 1508-1519.
    12. Zingre, Kishor T. & Wan, Man Pun & Yang, Xingguo, 2015. "A new RTTV (roof thermal transfer value) calculation method for cool roofs," Energy, Elsevier, vol. 81(C), pages 222-232.
    13. Li, Wenqiang & Gong, Guangcai & Fan, Houhua & Peng, Pei & Chun, Liang, 2020. "Meta-learning strategy based on user preferences and a machine recommendation system for real-time cooling load and COP forecasting," Applied Energy, Elsevier, vol. 270(C).
    14. Zingre, Kishor T. & Wan, Man Pun & Tong, Shanshan & Li, Hua & Chang, Victor W.-C. & Wong, Swee Khian & Thian Toh, Winston Boo & Leng Lee, Irene Yen, 2015. "Modeling of cool roof heat transfer in tropical climate," Renewable Energy, Elsevier, vol. 75(C), pages 210-223.
    15. Lusis, Peter & Khalilpour, Kaveh Rajab & Andrew, Lachlan & Liebman, Ariel, 2017. "Short-term residential load forecasting: Impact of calendar effects and forecast granularity," Applied Energy, Elsevier, vol. 205(C), pages 654-669.
    16. Gupta, V. & Deb, C., 2023. "Envelope design for low-energy buildings in the tropics: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 186(C).
    17. Homod, Raad Z., 2018. "Analysis and optimization of HVAC control systems based on energy and performance considerations for smart buildings," Renewable Energy, Elsevier, vol. 126(C), pages 49-64.
    18. Amal A. Al-Shargabi & Abdulbasit Almhafdy & Dina M. Ibrahim & Manal Alghieth & Francisco Chiclana, 2021. "Tuning Deep Neural Networks for Predicting Energy Consumption in Arid Climate Based on Buildings Characteristics," Sustainability, MDPI, vol. 13(22), pages 1-20, November.
    19. Xiao, Liye & Shao, Wei & Liang, Tulu & Wang, Chen, 2016. "A combined model based on multiple seasonal patterns and modified firefly algorithm for electrical load forecasting," Applied Energy, Elsevier, vol. 167(C), pages 135-153.
    20. Yaoyao Zhu & Gabriel Hoh Teck Ling, 2022. "A Systematic Review of Morphological Transformation of Urban Open Spaces: Drivers, Trends, and Methods," Sustainability, MDPI, vol. 14(17), pages 1-22, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:13:y:2021:i:21:p:11957-:d:667677. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.