Mr. Arash Pourghorban
Mr. Arash Pourghorban
Research Interests
Indoor Environmental Quality (IEQ), Building Physics, Occupant Behaviour, Energy Efficiency in Buildings, Building/Energy Simulation, Sustainable Buildings, Green Architecture.
. Pourghorban, A., V.W.C. Chang, and J. Zhou, Delving beneath the surface: A systematic review of human experience of indoor thermal environments through electroencephalogram (EEG). Building and Environment, 2024. 257: p. 111533.
https://doi.org/10.1016/j.buildenv.2024.111533
. Pourghorban, Arash, and H. Asoodeh, The impacts of advanced glazing units on annual performance of the Trombe wall systems in cold climates, Sustainable Energy Technologies and Assessments, 2022, 51.
https://doi.org/10.1016/j.seta.2022.101983
. Pourghorban, Arash, B.M. Kari, and H. Asoodeh, Holistic survey of reflective insulation systems (RISs) in vertical applications in building envelopes under various climatic conditions, Energy, 2022, 242.
https://doi.org/10.1016/j.energy.2021.122959
. Pourghorban, Arash, B.M. Kari, and E. Solgi, Assessment of reflective insulation systems in wall application in hot-arid climates, Sustainable Cities and Society, 2020, 52.
https://doi.org/10.1016/j.scs.2019.101734
. Pourghorban, Arash and B.M. Kari, Evaluation of reflective insulation systems in wall application by guarded hot box apparatus, and comparative investigation with ASHRAE and ISO 15099. Construction and Building Materials, 2019. 207: p. 84-97.
https://doi.org/10.1016/j.conbuildmat.2019.02.097
. Pourghorban, Arash, Data-driven numerical models for the prediction of the thermal resistance value of the Enclosed Airspaces (EAs) in building envelopes. Journal of Building Performance Simulation, 2023. 16: p.57:71.
https://doi.org/10.1080/19401493.2022.2110287
. G Pazouki, A Pourghorban, Using a hybrid artificial intelligence method for estimating the compressive strength of recycled aggregate self-compacting concrete. European Journal of Environmental and Civil Engineering, 2021, 1-25.
https://doi.org/10.1080/19648189.2021.1908915
. G Pazouki, A Pourghorban, Anticipation of the compressive strength of steel fiber‐reinforced concrete by different types of artificial intelligence methods. Structural Concrete, 2022.
https://doi.org/10.1002/suco.202100776
Teaching Commitments
- CLV2263 - Water systems
- ENE3031 - Building sustainability
- ENE2021 - Energy and the environment
- CLV4288 - Water treatment