A Super Performance Dew Point Cooler for Data Centres

Hourly performance forecast of a dew point cooler using explainable Artificial Intelligence and evolutionary optimisations by 2050 (2020)
Journal Article
Golizadeh Akhlaghi, Y., Aslansefat, K., Zhao, X., Sadati, S., Badiei, A., Xiao, X., Shittu, S., Fan, Y., & Ma, X. (2021). Hourly performance forecast of a dew point cooler using explainable Artificial Intelligence and evolutionary optimisations by 2050. Applied energy, 281, Article 116062. https://doi.org/10.1016/j.apenergy.2020.116062

The empirical success of the Artificial Intelligence (AI), has enhanced importance of the transparency in black box Machine Learning (ML) models. This study pioneers in developing an explainable and interpretable Deep Neural Network (DNN) model for a... Read More about Hourly performance forecast of a dew point cooler using explainable Artificial Intelligence and evolutionary optimisations by 2050.

Can whole building energy models outperform numerical models, when forecasting performance of indirect evaporative cooling systems? (2020)
Journal Article
Badiei, A., Akhlaghi, Y. G., Zhao, X., Li, J., Yi, F., & Wang, Z. (2020). Can whole building energy models outperform numerical models, when forecasting performance of indirect evaporative cooling systems?. Energy Conversion and Management, 213, Article 112886. https://doi.org/10.1016/j.enconman.2020.112886

This paper presents a whole building energy modelling work incorporating a state-of-the-art indirect evaporative cooling system. The model is calibrated and validated with real-life empirical data, and is capable of representing actual performance of... Read More about Can whole building energy models outperform numerical models, when forecasting performance of indirect evaporative cooling systems?.