| RANS turbulence model development using CFD-driven machine learning Y Zhao, HD Akolekar, J Weatheritt, V Michelassi, RD Sandberg Journal of Computational Physics 411, 109413, 2020 | 199 | 2020 |
| Development and Use of Machine-Learnt Algebraic Reynolds Stress Models for Enhanced Prediction of Wake Mixing in Low-Pressure Turbines HD Akolekar, J Weatheritt, N Hutchins, RD Sandberg, G Laskowski, ... Journal of Turbomachinery 141 (4), 2019 | 67* | 2019 |
| Machine-Learnt Turbulence Closures for Low-Pressure Turbines With Unsteady Inflow Conditions HD Akolekar, RD Sandberg, N Hutchins, V Michelassi, G Laskowski Journal of Turbomachinery 141 (10), 2019 | 28* | 2019 |
| Transition Modeling for Low Pressure Turbines Using Computational Fluid Dynamics Driven Machine Learning HD Akolekar, F Waschkowski, Y Zhao, R Pacciani, RD Sandberg Energies 14 (15), 4680, 2021 | 26 | 2021 |
| Integration of Machine Learning and Computational Fluid Dynamics to Develop Turbulence Models for Improved Low-Pressure Turbine Wake Mixing Prediction HD Akolekar, Y Zhao, R Sandberg, R Pacciani Journal of Turbomachinery 143 (12), 1-12, 2021 | 26* | 2021 |
| Assessment of machine-learned turbulence models trained for improved wake-mixing in low-pressure turbine flows R Pacciani, M Marconcini, F Bertini, S Rosa Taddei, E Spano, Y Zhao, ... Energies 14 (24), 8327, 2021 | 8 | 2021 |
| ChatGPT--a Blessing or a Curse for Undergraduate Computer Science Students and Instructors? I Joshi, R Budhiraja, H Dev, J Kadia, MO Ataullah, S Mitra, D Kumar, ... SIGCSE 2024: Proceedings of the 55th ACM Technical Symposium on Computer …, 2024 | 7* | 2024 |
| Turbulence Model Development for Low & High Pressure Turbines Using a Machine Learning Approach HD Akolekar, Y Zhao, RD Sandberg, N Hutchins, V Michelassi International Society of Air Breathing Engines, 2019 | 7 | 2019 |
| Turbulence Model Development and Implementation for Low Pressure Turbines Using a Machine Learning Approach HD Akolekar University of Melbourne, 2019 | 6 | 2019 |
| " With Great Power Comes Great Responsibility!": Student and Instructor Perspectives on the influence of LLMs on Undergraduate Engineering Education I Joshi, R Budhiraja, PD Tanna, L Jain, M Deshpande, A Srivastava, ... arXiv e-prints, arXiv: 2309.10694, 2023 | 5* | 2023 |
| Development of a Simulation Program to Optimise Process Parameters of Steam Power Cycles HD Akolekar, P Srinivasan, JS Challa International Journal of Thermal & Environmental Engineering 8 (1), 55-61, 2014 | 5 | 2014 |
| It's not like Jarvis, but it's pretty close!” - Examining ChatGPT's Usage among Undergraduate Students in Computer Science R Budhiraja, I Joshi, JS Challa, HD Akolekar, D Kumar Proceedings of the 26th Australasian Computing Education Conference, 124-133, 2024 | 3 | 2024 |
| Multi-Objective Development of Machine-Learnt Closures for Fully Integrated Transition and Wake Mixing Predictions in Low Pressure Turbines HD Akolekar, F Waschkowski, R Pacciani, Y Zhao, RD Sandberg Turbo Expo: Power for Land, Sea, and Air 86113, V10CT32A013, 2022 | 2 | 2022 |
| Machine-learning based optimization of a biomimiced herringbone microstructure for superior aerodynamic performance RS Patel, HD Akolekar Engineering Research Express 5 (4), 045065, 2023 | 1 | 2023 |
| CFD-Based Boundary Layer Prediction of Axisymmetric Bodies of Revolution H Akolekar, D Pook, D Ranmuthugala Australasian Fluid Mechanics Conference, 2020 | 1 | 2020 |
| A Data Driven Approach for Generalizing the Laminar Kinetic Energy Model for Separation and Bypass Transition in Low and High Pressure Turbines Y Fang, Y Zhao, H Akolekar, A Ooi, R Sandberg, R Pacciani, ... Journal of Turbomachinery 146 (9), 2024 | | 2024 |
| A Data-Driven Approach for Generalizing the Laminar Kinetic Energy Model for Separation and Bypass Transition in Low-and High-Pressure Turbines Y Fang, Y Zhao, HD Akolekar, ASH Ooi, RD Sandberg, R Pacciani, ... Turbo Expo: Power for Land, Sea, and Air 87103, V13CT32A025, 2023 | | 2023 |
| CFD-ready Turbulence Models from Gene Expression Programming: Concepts Y Zhao, HD Akolekar, RD Sandberg APS Division of Fluid Dynamics Meeting Abstracts, G17. 003, 2019 | | 2019 |
| Understanding loss mechanisms in turbomachinery to increase efficiency HD Akolekar University of Melbourne, 2016 | | 2016 |
Richard D SandbergUniversity of Melbourne在 unimelb.edu.au 的电子邮件经过验证
