Publications by Fluids and Energy

Are you looking for publications by Section of Fluids and Energy? On this page you can find all the publications made by the Section of Fluids and Energy - Department of Mechanical and Production Engineerin, Aarhus University.

Below you can find a list of all the publications, their publishing date, their author(s), and title. The list can be sorted by date, author, and title:

List of Publications

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Hansen, C., I. A. Yang, X. & Abkar, M. (2023). Data-Driven Dynamical System Models of Roughness-Induced Secondary Flows in Thermally Stratified Turbulent Boundary Layers. Journal of Fluids Engineering, Transactions of the ASME, 145(6), Artikel FE-22-1510. https://doi.org/10.1115/1.4057016

Hansen, C., I. A. Yang, X. & Abkar, M. (2022). Data-Driven Dynamical System Models of Roughness-Induced Secondary Flows in Thermally Stratified Boundary Layers. I Proceedings of the ASME 2022 Fluids Engineering Division Summer Meeting : Volume 2: Multiphase Flow (MFTC); Computational Fluid Dynamics (CFDTC); Micro and Nano Fluid Dynamics (MNFDTC) Artikel FEDSM2022-87630, V002T05A023 American Society of Mechanical Engineers (ASME). https://doi.org/10.1115/FEDSM2022-87630

Zinck Thellufsen, J., Lund, H., Vad Mathiesen, B., Østergaard, P. A., Sorknæs, P., Nielsen, S., Thøis Madsen, P. & Bruun Andresen, G. (2024). Cost and systems effects of nuclear power in carbon-neutral energy systems. Applied Energy, 371, Artikel 123705. https://doi.org/10.1016/j.apenergy.2024.123705

Gøtske, E. K., Bruun Andresen, G. & Victoria, M. (2023). Cost and Efficiency Requirements for Successful Electricity Storage in a Highly Renewable European Energy System. PRX Energy, 2(2), Artikel 023006. https://doi.org/10.1103/PRXEnergy.2.023006

Farah, S., Bokde, N. & Andresen, G. B. (2024). Cost and CO₂ emissions co-optimisation of green hydrogen production in a grid-connected renewable energy system. International Journal of Hydrogen Energy, 84, 164-176. https://doi.org/10.1016/j.ijhydene.2024.08.062

Legaard, C. M., Schranz, T., Schweiger, G., Drgona, J., Falay, B., Gomes, C., Iosifidis, A., Abkar, M. & Larsen, P. G. (2023). Constructing Neural Network Based Models for Simulating Dynamical Systems. ACM Computing Surveys, 55(11), 1-34. Artikel 236. https://doi.org/10.1145/3567591

Yang, X. I. A., Zhang, W., Abkar, M. & Anderson, W. (2024). Computational fluid dynamics: Its carbon footprint and role in carbon reduction. Journal of Renewable and Sustainable Energy, 16(5), Artikel 055906. https://doi.org/10.1063/5.0217320

Niazi, K. A. K. & Victoria, M. (2023). Comparative analysis of photovoltaic configurations for agrivoltaic systems in Europe. Progress in Photovoltaics, 31(11), 1101-1113. https://doi.org/10.1002/pip.3727

Yang, J., Stroh, A., Bagheri, S., Frohnapfel, B. & Forooghi, P. (2025). Characterization of hydrodynamic and thermal properties of anisotropic irregular roughness. International Journal of Heat and Fluid Flow, 116, Artikel 109888. https://doi.org/10.1016/j.ijheatfluidflow.2025.109888

Rincón, M. J., Reclari, M., Yang, X. & Abkar, M. (2023). CFD-aided morphing and design optimisation of ultrasonic flow meters. I The 14th International ERCOFTAC Symposium on Engineering Turbulence Modelling and Measurements (s. 109-114) https://www.ercoftac.org/etmm/program/conference-program/

Moon, J., Jang, C., Mahravan, E. & Kim, D. (2025). Cavitation bubble-induced hydrodynamic loading and interfacial deformation in an air pocket. Journal of Fluid Mechanics, 1016, Artikel A39. https://doi.org/10.1017/jfm.2025.10398

Ambrose, H. W., Engelbrecht, N., Alamia, A. & Kofoed, M. V. W. (2025). Biomethanation With Renewable Energy: Harnessing the Carbon-Water-Energy Nexus. Abstract fra 33rd European Biomass Conference & Exhibition , Valencia, Spanien.

Morree, A. D. & Tabula Sapiens Consortium (2025). Benchmarking cell type and gene set annotation by large language models with AnnDictionary. Nature Communications, 16(1), Artikel 9511. https://doi.org/10.1038/s41467-025-64511-x

Jensen, R. M. & Forooghi, P. (2025). A study of turbulent flow over patchy roughness. Journal of Fluid Mechanics, 1006, Artikel A28. https://doi.org/10.1017/jfm.2024.1095

Yang, J., Stroh, A., Lee, S., Bagheri, S., Frohnapfel, B. & Forooghi, P. (2024). Assessment of Roughness Characterization Methods for Data-Driven Predictions. Flow, Turbulence and Combustion, 113(2), 275-292. https://doi.org/10.1007/s10494-024-00549-z

Colombo, M., Meng, Y., Poirier-Quinot, M., Rollet, A. L., Geeverding, A., Delcea, M., deMello, A. J. & Abou-Hassan, A. (2024). Assessing the Effect of Magnetite Nanoflowers on Platelets in a Multiscale Approach in the Context of Thromboembolic Diseases. ACS Applied Nano Materials, 7(17), 20085-20093. https://doi.org/10.1021/acsanm.4c02715

Zehtabiyan-Rezaie, N. & Abkar, M. (2023). A short note on turbulence characteristics in wind-turbine wakes. Journal of Wind Engineering and Industrial Aerodynamics, 240, Artikel 105504. https://doi.org/10.1016/j.jweia.2023.105504

Amarloo, A., Zehtabiyan-Rezaie, N. & Abkar, M. (2024). A progressive data-augmented RANS model for enhanced wind-farm simulations. Energy, 313, Artikel 133762. https://doi.org/10.1016/j.energy.2024.133762

Giauque, A., Giguet, C., Vadrot, A. & Corre, C. (2024). A priori test of Large-Eddy Simulation models for the Sub-Grid Scale turbulent stress tensor in perfect and transcritical compressible real gas Homogeneous Isotropic Turbulence. Computers and Fluids, 268, Artikel 106091. https://doi.org/10.1016/j.compfluid.2023.106091

E. S. Chen, P., Bin, Y., I. A. Yang, X., Shi, Y., Abkar, M. & I. Park, G. (2023). A priori screening of data-enabled turbulence models. Physical Review Fluids, 8(12), Artikel 124606. https://doi.org/10.1103/PhysRevFluids.8.124606

Cleve, J., Schmiegel, J. & Greiner, M. (2008). Apparent scale correlations in a random multifractal process. European Physical Journal B. Condensed Matter and Complex Systems, 63(1), 109-116. https://doi.org/10.1140/epjb/e2008-00218-6

Hansen, C., I.A. Yang, X. & Abkar, M. (2023). A POD-mode-augmented wall model and its applications to flows at non-equilibrium conditions. Journal of Fluid Mechanics, 975, Artikel A24. https://doi.org/10.1017/jfm.2023.857

Baungaard, M., Abkar, M., van der Laan, M. P. & Kelly, M. (2022). A numerical investigation of a wind turbine wake in non-neutral atmospheric conditions. Journal of Physics: Conference Series, 2265(2), Artikel 022015. https://doi.org/10.1088/1742-6596/2265/2/022015

Zehtabiyan-Rezaie, N. & Abkar, M. (2023). An extended k- ε model for wind-farm simulation. I 14th International ERCOFTAC Symposium on Engineering Turbulence Modelling and Measurements: Proceedings (s. 373-378)

Zehtabiyan-Rezaie, N. & Abkar, M. (2024). An extended K-ɛ model for wake-flow simulation of wind farms. Renewable Energy, 222, Artikel 119904. https://doi.org/10.1016/j.renene.2023.119904

Sanz-Cuadrado, C., Rahdan, P., Zhang, Z., Victoria, M. & Belén Cristóbal, A. (2026). A New Approach to Assess Individual Contributions to Energy Transition Goals. Energy Policy, 210, Artikel 115055. https://doi.org/10.1016/j.enpol.2025.115055

Nozarian, S., Abkar, M. & Forooghi, P. (2024). An analysis of drag reduction using spanwise forcing on rough walls. International Journal of Heat and Fluid Flow, 106, Artikel 109306. https://doi.org/10.1016/j.ijheatfluidflow.2024.109306

Chedevergne, F., Yang, J., Stroh, A. & Forooghi, P. (2025). Analysis of Separation in the Roughness Sublayer Using DNS Data and DANS/DEM Modelling of Roughness Effects. Flow, Turbulence and Combustion, 114(3), 713-735. Artikel 021202. https://doi.org/10.1007/s10494-024-00585-9

Rincón, M. J., Reclari, M., Yang, X. I. A. & Abkar, M. (2025). A generalisable data-augmented turbulence model with progressive and interpretable corrections for incompressible wall-bounded flows. International Journal of Heat and Fluid Flow, 116, Artikel 109970. https://doi.org/10.1016/j.ijheatfluidflow.2025.109970

Migliorini, M., Doll, U., Lawson, N. J., Melnikov, S. M., Steinbock, J., Dues, M., Zachos, P. K., Röhle, I. & MacManus, D. G. (2025). Advancements on the use of Filtered Rayleigh Scattering (FRS) with Machine learning methods for flow distortion in Aero-Engine intakes. Experimental Thermal and Fluid Science, 160, 111325. Artikel 111325. https://doi.org/10.1016/j.expthermflusci.2024.111325

Yang, J., Velandia, J., Bansmer, S., Stroh, A. & Forooghi, P. (2023). A comparison of hydrodynamic and thermal properties of artificially generated against realistic rough surfaces. International Journal of Heat and Fluid Flow, 99, Artikel 109093. https://doi.org/10.1016/j.ijheatfluidflow.2022.109093

Sanz Cuadrado, C., Cristóbal, A. B., Zhang, Z., Rahdan, P. & Victoria, M. (2022). Achieving a New European Energy Awareness (AURORA): Deliverable 1.1 – Near-Zero Emissions Citizens Label. https://www.aurora-h2020.eu/wp-content/uploads/2022/09/D1.1-Near-Zero-Emission-Citizens-Label-PU.pdf

Dues, M., Dues, F., Steinbock, J., Melnikov, S., Doll, U., Röhle, I., Migliorini, M. & K. Zachos, P. (2024). 2D3C Measurement Of Velocity, Pressure And Temperature Fields In A Intake Flow Of An Air Turbine By Filtered Rayleigh Sattering (FRS) And Validation With LDV And PIV. I 21th International Symposium on the Application of Laser and Imaging Techniques to Fluid Mechanics https://doi.org/10.55037/lxlaser.21st.21

Lund, H., Zinck Thellufsen, J., Vad Mathiesen, B., Thøis Madsen, P., Østergaard, P. A., Nielsen, S., Sorknæs, P., Wenzel, H., Sørensen, P. B., Bruun Andresen, G. & Victoria, M. (2022). 16 energiforskere fra fem universiteter: Lad os få mere fakta i atomkraftdebatten: Der er ikke behov for atomkraft for at sikre stabilitet i elforsyningen. Det vil kun gøre den dyrere og samtidig forsinke den grønne omstilling, skriver en række forskere i et svar til kernefysikere, som har efterlyst mere helstøbt og åben vurdering af atomkraft i Danmark. . Altinget. https://www.altinget.dk/forsyning/artikel/16-energiforskere-fra-fem-universiteter-lad-os-faa-mere-fakta-i-atomkraftdebatten

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Revideret 13.11.2025

AU Engineering