IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i18p10164-d633174.html
   My bibliography  Save this article

Using Multivariate Regression and ANN Models to Predict Properties of Concrete Cured under Hot Weather

Author

Listed:
  • Ahsen Maqsoom

    (Department of Civil Engineering, COMSATS University Islamabad, Wah Cantt 47040, Pakistan)

  • Bilal Aslam

    (Department of Earth Sciences, Quaid-i-Azam University, Islamabad 45320, Pakistan)

  • Muhammad Ehtisham Gul

    (Department of Civil Engineering, COMSATS University Islamabad, Wah Cantt 47040, Pakistan)

  • Fahim Ullah

    (School of Civil Engineering and Surveying, University of Southern Queensland, Springfield Central, QLD 4300, Australia)

  • Abbas Z. Kouzani

    (School of Engineering, Deakin University, Geelong, VIC 3216, Australia)

  • M. A. Parvez Mahmud

    (School of Engineering, Deakin University, Geelong, VIC 3216, Australia)

  • Adnan Nawaz

    (Department of Civil Engineering, COMSATS University Islamabad, Wah Cantt 47040, Pakistan)

Abstract

Concrete is an important construction material. Its characteristics depend on the environmental conditions, construction methods, and mix factors. Working with concrete is particularly tricky in a hot climate. This study predicts the properties of concrete in hot conditions using the case study of Rawalpindi, Pakistan. In this research, variable casting temperatures, design factors, and curing conditions are investigated for their effects on concrete characteristics. For this purpose, water–cement ratio ( w / c ), in-situ concrete temperature ( T ), and curing methods of the concrete are varied, and their effects on pulse velocity ( PV ), compressive strength ( fc ), depth of water penetration ( WP ), and split tensile strength ( ft ) were studied for up to 180 days. Quadratic regression and artificial neural network (ANN) models have been formulated to forecast the properties of concrete in the current study. The results show that T , curing period, and moist curing strongly influence fc , ft , and PV , while WP is adversely affected by T and moist curing. The ANN model shows better results compared to the quadratic regression model. Furthermore, a combined ANN model of fc , ft , and PV was also developed that displayed higher accuracy than the individual ANN models. These models can help construction site engineers select the appropriate concrete parameters when concreting under hot climates to produce durable and long-lasting concrete.

Suggested Citation

  • Ahsen Maqsoom & Bilal Aslam & Muhammad Ehtisham Gul & Fahim Ullah & Abbas Z. Kouzani & M. A. Parvez Mahmud & Adnan Nawaz, 2021. "Using Multivariate Regression and ANN Models to Predict Properties of Concrete Cured under Hot Weather," Sustainability, MDPI, vol. 13(18), pages 1-28, September.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:18:p:10164-:d:633174
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/18/10164/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/18/10164/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Binder, Jj, 1985. "On The Use Of The Multivariate Regression-Model In Event Studies," Journal of Accounting Research, Wiley Blackwell, vol. 23(1), pages 370-383.
    2. Ahmad Hasan & Khaled A. Al-Sallal & Hamza Alnoman & Yasir Rashid & Shaimaa Abdelbaqi, 2016. "Effect of Phase Change Materials (PCMs) Integrated into a Concrete Block on Heat Gain Prevention in a Hot Climate," Sustainability, MDPI, vol. 8(10), pages 1-14, October.
    3. Tanzila Akmal & Faisal Jamil, 2021. "Assessing Health Damages from Improper Disposal of Solid Waste in Metropolitan Islamabad–Rawalpindi, Pakistan," Sustainability, MDPI, vol. 13(5), pages 1-18, March.
    4. Ullah, Fahim & Qayyum, Siddra & Thaheem, Muhammad Jamaluddin & Al-Turjman, Fadi & Sepasgozar, Samad M.E., 2021. "Risk management in sustainable smart cities governance: A TOE framework," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    5. Qadeer Ali & Muhammad Jamaluddin Thaheem & Fahim Ullah & Samad M. E. Sepasgozar, 2020. "The Performance Gap in Energy-Efficient Office Buildings: How the Occupants Can Help?," Energies, MDPI, vol. 13(6), pages 1-27, March.
    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. Kamran Iqbal & Hafiz Suliman Munawar & Hina Inam & Siddra Qayyum, 2021. "Promoting Customer Loyalty and Satisfaction in Financial Institutions through Technology Integration: The Roles of Service Quality, Awareness, and Perceptions," Sustainability, MDPI, vol. 13(23), pages 1-20, November.
    2. Sergiu-Mihai Alexa-Stratulat & Daniel Covatariu & Ana-Maria Toma & Ancuta Rotaru & Gabriela Covatariu & Ionut-Ovidiu Toma, 2022. "Influence of a Novel Carbon-Based Nano-Material on the Thermal Conductivity of Mortar," Sustainability, MDPI, vol. 14(13), pages 1-14, July.

    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. Kamran Iqbal & Hafiz Suliman Munawar & Hina Inam & Siddra Qayyum, 2021. "Promoting Customer Loyalty and Satisfaction in Financial Institutions through Technology Integration: The Roles of Service Quality, Awareness, and Perceptions," Sustainability, MDPI, vol. 13(23), pages 1-20, November.
    2. Ahsen Maqsoom & Bilal Aslam & Sharjeel Ismail & Muhammad Jamaluddin Thaheem & Fahim Ullah & Hafiz Zahoor & Muhammad Ali Musarat & Nikolai Ivanovich Vatin, 2021. "Assessing Rainwater Harvesting Potential in Urban Areas: A Building Information Modelling (BIM) Approach," Sustainability, MDPI, vol. 13(22), pages 1-21, November.
    3. Bernard, Jean-Thomas & Idoudi, Nadhem & Khalaf, Lynda & Yelou, Clement, 2007. "Finite sample multivariate structural change tests with application to energy demand models," Journal of Econometrics, Elsevier, vol. 141(2), pages 1219-1244, December.
    4. Baruch, Shmuel & Panayides, Marios & Venkataraman, Kumar, 2017. "Informed trading and price discovery before corporate events," Journal of Financial Economics, Elsevier, vol. 125(3), pages 561-588.
    5. repec:vuw:vuwscr:18973 is not listed on IDEAS
    6. Andr� Betzer & Markus Doumet & Ulf Rinne, 2013. "How policy changes affect shareholder wealth: the case of the Fukushima Dai-ichi nuclear disaster," Applied Economics Letters, Taylor & Francis Journals, vol. 20(8), pages 799-803, May.
    7. Jan Bartholdy & Glenn Boyle & Roger Stover, 2004. "Deposit insurance and the stock market: evidence from Denmark," The European Journal of Finance, Taylor & Francis Journals, vol. 10(6), pages 567-578.
    8. Jared F. Egginton & James I. Hilliard & Andre P. Liebenberg & Ivonne A. Liebenberg, 2010. "What Effect Did AIG's Bailout, and the Preceding Events, Have on Its Competitors?," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 13(2), pages 225-249, September.
    9. Choy, Siu Kai & Lai, Tat-Kei & Ng, Travis, 2017. "Do tax havens create firm value?," Journal of Corporate Finance, Elsevier, vol. 42(C), pages 198-220.
    10. Brown, Jeffrey R. & Cummins, J. David & Lewis, Christopher M. & Wei, Ran, 2004. "An empirical analysis of the economic impact of federal terrorism reinsurance," Journal of Monetary Economics, Elsevier, vol. 51(5), pages 861-898, July.
    11. Shuying Wang & Yifei Gao & Hongchang Zhou, 2022. "Research on Green Total Factor Productivity Enhancement Path from the Configurational Perspective—Based on the TOE Theoretical Framework," Sustainability, MDPI, vol. 14(21), pages 1-20, October.
    12. Komulainen, Ruey & Nätti, Satu, 2023. "Barriers to blockchain adoption: Empirical observations from securities services value network," Journal of Business Research, Elsevier, vol. 159(C).
    13. Ning Chen & Yu Chen, 2022. "Anomalous Vehicle Recognition in Smart Urban Traffic Monitoring as an Edge Service," Future Internet, MDPI, vol. 14(2), pages 1-22, February.
    14. Chong, Beng-Soon & Liu, Ming-Hua & Altunbas, Yener, 1996. "The impact of universal banking on the risks and returns of Japanese financial institutions," Pacific-Basin Finance Journal, Elsevier, vol. 4(2-3), pages 181-195, July.
    15. Sen, Suphi & von Schickfus, Marie-Theres, 2020. "Climate policy, stranded assets, and investors’ expectations," Journal of Environmental Economics and Management, Elsevier, vol. 100(C).
    16. Cummins, J. David & Lewis, Christopher M. & Wei, Ran, 2006. "The market value impact of operational loss events for US banks and insurers," Journal of Banking & Finance, Elsevier, vol. 30(10), pages 2605-2634, October.
    17. Robert Feinberg & Richard Harper, 1999. "Regime Effects of EU Market Integration Policies on the UK Financial Sector," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 15(4), pages 357-365, December.
    18. Sascha Kolaric, 2024. "The impact of climate litigation and activism on stock prices: the case of oil and gas majors," Review of Managerial Science, Springer, vol. 18(11), pages 3141-3172, November.
    19. Kenneth S. Bartunek & Jeff Madura, 1996. "Wealth effects of reserve requirement reductions in the 1990s on depository institutions," Review of Financial Economics, John Wiley & Sons, vol. 5(2), pages 191-204.
    20. Marcus T. Allen & Jeff Madura & Kenneth J. Wiant, 1995. "Commercial Bank Exposure and Sensitivity to the Real Estate Market," Journal of Real Estate Research, American Real Estate Society, vol. 10(2), pages 129-140.
    21. Antonio De Nicola & Maria Luisa Villani, 2021. "Smart City Ontologies and Their Applications: A Systematic Literature Review," Sustainability, MDPI, vol. 13(10), pages 1-40, May.

    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:18:p:10164-:d:633174. 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.