Jianfei Xie
| Name | Jianfei Xie |
|---|---|
| Job title | Senior Lecturer in Mechanical and Manufacturing Engineering |
| Research institute | College of Science and Engineering |
| ORCID | https://orcid.org/0000-0002-2217-3506 |
Research outputs
Performance optimization and entropy-TOPSIS evaluation of a thermochemical solar thermal power generation system based on packed bed reactor exothermic characteristics
Chen, J., Yang, X., Cui, J., Huo, Y. and Xie, J. 2025. Performance optimization and entropy-TOPSIS evaluation of a thermochemical solar thermal power generation system based on packed bed reactor exothermic characteristics. Energy Conversion and Management. 336. https://doi.org/10.1016/j.enconman.2025.119891Data-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.2025.134590Machine 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.4c05653Use 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.e35221Chaos synchronization of two coupled map lattice systems using safe reinforcement learning
Ding, J., Lei, Y., Jianfei Xie and Small, M. 2024. Chaos synchronization of two coupled map lattice systems using safe reinforcement learning. Chaos, Solitons & Fractals. 186, pp. 1-13. https://doi.org/10.1016/j.chaos.2024.115241Multi-perspective analysis of adiabatic compressed air energy storage system with cascaded packed bed latent heat storage under variable conditions
Cui, J., Yang, X., Chen, J., Su, H. and Jianfei Xie 2024. Multi-perspective analysis of adiabatic compressed air energy storage system with cascaded packed bed latent heat storage under variable conditions. Energy. 305, pp. 1-15. https://doi.org/10.1016/j.energy.2024.132373Enhanced heat transfer and thermal storage performance of molten K2CO3 by ZnO nanoparticles: A molecular dynamics study
Ji, C., Yang, X., Ma, Y., Guo, Z. and Jianfei Xie 2024. Enhanced heat transfer and thermal storage performance of molten K2CO3 by ZnO nanoparticles: A molecular dynamics study. Journal of Molecular Liquids. 407, pp. 1-9. https://doi.org/10.1016/j.molliq.2024.125203Numerical Simulation of the Interaction between a Planar Shock Wave and a Cylindrical Bubble
Onwuegbu, S., Yang, Z. and Xie, J. 2024. Numerical Simulation of the Interaction between a Planar Shock Wave and a Cylindrical Bubble. Modelling. 5 (2), pp. 483-501. https://doi.org/10.3390/modelling5020026Molecular dynamics study on interfacial diffusion characterization of nanoparticle TiO2 and metal Fe in high-temperature molten salt thermal energy storage system
Xueming Yang, Zhijin Guo, Chang Ji, Yongfu Ma and Jianfei Xie 2024. Molecular dynamics study on interfacial diffusion characterization of nanoparticle TiO2 and metal Fe in high-temperature molten salt thermal energy storage system. Solar Energy Materials and Solar Cells. 271, pp. 1-12. https://doi.org/10.1016/j.solmat.2024.112854Utilizing 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.2024.100360Utilizing 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.2024.100360Performance comparison of CSP system with different heat transfer and storage fluids at multi-time scales by means of system advisor model
Xueming Yang, Hu Zhao, Ming Zhang, Chang Ji and Jianfei Xie 2024. Performance comparison of CSP system with different heat transfer and storage fluids at multi-time scales by means of system advisor model. Solar Energy Materials and Solar Cells. 269, pp. 1-12. https://doi.org/10.1016/j.solmat.2024.112765Multi-factor analysis and optimization design of a cascaded packed-bed thermal storage system coupled with adiabatic compressed air energy storage
Xueming Yang, Jie Cui, Yi Li, He Chi and Jianfei Xie 2023. Multi-factor analysis and optimization design of a cascaded packed-bed thermal storage system coupled with adiabatic compressed air energy storage. Energy Conversion and Management. 300, pp. 1-13. https://doi.org/10.1016/j.enconman.2023.117961Approaches for describing processes of fuel droplet heating and evaporation in combustion engines
Jianfei Xie 2023. Approaches for describing processes of fuel droplet heating and evaporation in combustion engines. Fuel. 360, pp. 1-14. https://doi.org/10.1016/j.fuel.2023.130465High thermal conductivity of porous graphite/paraffin composite phase change material with 3D porous graphite foam
Xueming Yang, Chunbo Li, YongFu Ma, He Chi, Zongjie Hu and Jianfei Xie 2023. High thermal conductivity of porous graphite/paraffin composite phase change material with 3D porous graphite foam. Chemical Engineering Journal. 473, pp. 1-9. https://doi.org/10.1016/j.cej.2023.145364AI-Guided Computing Insights into a Thermostat Monitoring Neonatal Intensive Care Unit (NICU)
Zhang, N., Wood, O., Yang, Z. and Xie, J. 2023. AI-Guided Computing Insights into a Thermostat Monitoring Neonatal Intensive Care Unit (NICU). Sensors. 23 (9), pp. 1-16. https://doi.org/10.3390/s23094492Molecular dynamics study on the kinematic viscosity, density and structure of fuel blends containing n-decane and biofuel compound of ethyl decanoate or ethyl dodecanoate
Xueming Yang, Qiang Liu, Yongfu Ma, Jianfei Xie and Bingyang Cao 2023. Molecular dynamics study on the kinematic viscosity, density and structure of fuel blends containing n-decane and biofuel compound of ethyl decanoate or ethyl dodecanoate. Journal of Molecular Liquids. 379, pp. 1-13. https://doi.org/10.1016/j.molliq.2023.121680A mean free path approach to the micro/nanochannel gas flows
Xie, Jianfei 2020. A mean free path approach to the micro/nanochannel gas flows. Advances in Aerodynamics. https://doi.org/10.1186/s42774-020-00035-wVariation of molecular mean free path in confined geometries
Xie, Jianfei 2019. Variation of molecular mean free path in confined geometries. AIP Publishing. https://doi.org/10.1063/1.5119594.Effective mean free path and viscosity of confined gases
Xie, Jianfei 2019. Effective mean free path and viscosity of confined gases. Physics of Fluids. 31 (7), p. 072002. https://doi.org/10.1063/1.5108627Lattce Boltzmann mdoelling of natural convection of power-law fluids under wall vibrations
Xie, Jianfei and Cao, Bing-Yang 2018. Lattce Boltzmann mdoelling of natural convection of power-law fluids under wall vibrations. https://doi.org/10.1615/ihtc16.cov.020599A test of the effectiveness of pore scale fluid flow simulations and constitutive equations for modelling the effects of mineral dissolution on rock permeability
Lamy-Chappuis, Benoit, Yardley, Bruce W.D., He, Shuisheng, Zu, Yingqing and Xie, Jianfei 2018. A test of the effectiveness of pore scale fluid flow simulations and constitutive equations for modelling the effects of mineral dissolution on rock permeability. 483, pp. 501-510. https://doi.org/10.1016/j.chemgeo.2018.03.020Influence of travelling surface waves on nanofluidic viscosity
Xie, Jianfei and Cao, Bing-Yang 2018. Influence of travelling surface waves on nanofluidic viscosity. 160, pp. 42-50. https://doi.org/10.1016/j.compfluid.2017.10.022Natural convection of power-law fluids under wall vibrations: A lattice Boltzmann study
Xie, Jianfei 2017. Natural convection of power-law fluids under wall vibrations: A lattice Boltzmann study. 72 (8), pp. 600-627. https://doi.org/10.1080/10407782.2017.1394134Relative permeabilities of supercritical CO2 and brine in carbon sequestration by a two-phase lattice Boltzmann method
Xie, Jianfei, He, S., Zu, Y. Q., Lamy-Chappuis, B. and Yardley, B. W. D. 2017. Relative permeabilities of supercritical CO2 and brine in carbon sequestration by a two-phase lattice Boltzmann method. 53 (8), pp. 2637-2649. https://doi.org/10.1007/s00231-017-2007-6Effect of various surface conditions on nanochannel flows past permeable walls
Xie, Jianfei and Cao, Bing-Yang 2016. Effect of various surface conditions on nanochannel flows past permeable walls. 43 (1), pp. 65-75. https://doi.org/10.1080/08927022.2016.1233547Nanochannel flow past permeable walls via molecular dynamics
Xie, Jianfei and Cao, Bing-Yang 2016. Nanochannel flow past permeable walls via molecular dynamics. 6 (7), p. 075307. https://doi.org/10.1063/1.4959022Molecular Dynamics Study on Fluid Flow in Nanochannels With Permeable Walls
Xie, Jianfei and Cao, Bing-Yang 2016. Molecular Dynamics Study on Fluid Flow in Nanochannels With Permeable Walls. https://doi.org/10.1115/mnhmt2016-6421Two approaches to modelling the heating of evaporating droplet
Xie, Jianfei 2014. Two approaches to modelling the heating of evaporating droplet. https://doi.org/10.1016/j.icheatmasstransfer.2014.08.0041395
total views of outputs168
total downloads of outputs59
views of outputs this month5
downloads of outputs this month