Predictive Modelling of Indoor Thermal Comfort in Selected Mixed-Mode Buildings in Caleb University, Lagos, Nigeria

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@article{1718751,
      author = {Omojuwa Opemipo, Lawal Sophia, Awosika Ayomide, Adeniran Omobolanle, Asaju Opeyemi},
      title = {Predictive Modelling of Indoor Thermal Comfort in Selected Mixed-Mode Buildings in Caleb University, Lagos, Nigeria},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {9},
      number = {12},
      pages = {3036-3043},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1718751.pdf},
      abstract = {This study investigated indoor thermal comfort in selected mixed‑mode buildings at Caleb University, Lagos, Nigeria, and developed evidence‑based recommendations for improving occupant comfort and building performance. Field measurements of air temperature, relative humidity, and air velocity were collected alongside 200 occupant questionnaires assessing thermal sensation, preference, and satisfaction in teaching and administrative spaces. Descriptive analysis and comparison of measured conditions with occupant responses showed that most occupants reported warm thermal sensations and a strong preference for cooler conditions; thermal satisfaction was generally moderate to low. Higher temperatures and humidity correlated with warmer sensations and reduced satisfaction, while spaces with improved airflow recorded more favourable responses, indicating that temperature, humidity, and air movement jointly shape comfort in these mixed‑mode buildings. Occupant suggestions emphasized better functioning mechanical cooling, increased fans, modified window designs for cross‑ventilation, shading, and landscaping to reduce solar gain. Based on these findings, the study recommends prioritized maintenance and augmentation of cooling systems, enhanced natural ventilation through window and façade modifications, localized airflow improvements, and routine monitoring using sensors, together with occupant engagement and phased predictive‑modelling–guided retrofits. The results highlight the need to integrate passive and active measures tailored to tropical, university environments to achieve reliable, energy‑efficient thermal comfort.},
      keywords = {Caleb University, Energy Efficiency, Indoor Thermal Comfort, Mixed-Mode Buildings, Predictive Modelling.},
      month = {June},
      doi = {https://doi.org/10.64388/IREV9I12-1718751}
  }