Mr Amirali Shateri

NameMr Amirali Shateri
Research instituteCollege of Science and Engineering
ORCIDhttps://orcid.org/0000-0002-6399-0211

Research outputs

Data-driven optimization of turbulent kinetic energy and tumble-y in combustion engines: A comparative study of machine learning models

Shateri, A., Yang, Z., Liu, Y. and Xie, J. 2025. Data-driven optimization of turbulent kinetic energy and tumble-y in combustion engines: A comparative study of machine learning models. Fuel. 389, pp. 1-22. https://doi.org/10.1016/j.fuel.2025.134590

Machine Learning-Based Molecular Dynamics Studies on Predicting Thermophysical Properties of Ethanol–Octane Blends

Shateri, A., Yang, Z. and Xie, J. 2025. Machine Learning-Based Molecular Dynamics Studies on Predicting Thermophysical Properties of Ethanol–Octane Blends. Energy and Fuels. 39 (2). https://doi.org/10.1021/acs.energyfuels.4c05653

New insights into impact-induced removal of the deposited droplet

Xie, F., Xin, H., Liu, Q., Yang, Z., Shateri, A., Hong, W. and Liao, M. 2024. New insights into impact-induced removal of the deposited droplet. Physics of Fluids. 36 (11), pp. 1-33. https://doi.org/10.1063/5.0240101

Phase diagram for nanodroplet impact on solid spheres：From hydrophilic to superhydrophobic surfaces

Liao, M, Liu, Q, Yang, Z., Shateri, A., Hong, W and Xie, F 2024. Phase diagram for nanodroplet impact on solid spheres：From hydrophilic to superhydrophobic surfaces. Physics of Fluids. 36 (9), pp. 1-45. https://doi.org/10.1063/5.0228131

Use of magnetic fluids in process system for pipe isolations

Emmerson, J. O., Amirali Shateri and Jianfei Xie 2024. Use of magnetic fluids in process system for pipe isolations. Heliyon. 10 (15), pp. 1-14. https://doi.org/10.1016/j.heliyon.2024.e35221

Utilizing Artificial intelligence to identify an Optimal Machine learning model for predicting fuel consumption in Diesel engines

Shateri, A., Yang, Z. and Xie, J. 2024. Utilizing Artificial intelligence to identify an Optimal Machine learning model for predicting fuel consumption in Diesel engines. Energy and AI. 16, pp. 1-17. https://doi.org/10.1016/j.egyai.2024.100360

Utilizing Artificial intelligence to identify an Optimal Machine learning model for predicting fuel consumption in Diesel engines

Amirali Shateri, Zhiyin Yang and Jianfei Xie 2024. Utilizing Artificial intelligence to identify an Optimal Machine learning model for predicting fuel consumption in Diesel engines. Energy and AI. 16, pp. 1-17. https://doi.org/10.1016/j.egyai.2024.100360
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