Publications

Below you can find a complete list of the publications that are written by employees at the Publications at Department of Mechanical and Production Engineering for example journal articles, books, reports etc.

Publication list

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Balling, O. & SIRANGELO, D. (2022). Drawbar pull testing for machine-soil interaction characterization. 35-36. Abstract from Advances and Innovations in Agricultural Engineering., Herning, Denmark.

Nozarian, S. (2025). Drag Prediction and Modification in Smooth- and Rough-Wall-Bounded Turbulent Flows. [PhD thesis, Aarhus University].

Srinivasan, V., Song, B., Luo, J., Karupppasamy, S., Elara Mohan, R., Blessing, L. & Wood, K. (2023). Do Analogies and Analogical Distance Influence Ideation Outcomes in Engineering Design? In S. Mukherjee, V. Dutt & N. Srinivasan (Eds.), Applied Cognitive Science and Technology: Implications of Interactions Between Human Cognition and Technology (pp. 211–230). Springer. https://doi.org/10.1007/978-981-99-3966-4_13

Rahdan, P., Zeyen, E., Gallego-Castillo, C. & Victoria, M. (2024). Distributed photovoltaics provides key benefits for a highly renewable European energy system. Applied Energy, 360, Article 122721. https://doi.org/10.1016/j.apenergy.2024.122721

Fulco, S., Budzik, M. K., Xiao, H., Durian, D. J. & Turner, K. T. (2025). Disorder enhances the fracture toughness of 2D mechanical metamaterials. PNAS Nexus, 4(2), Article pgaf023. https://doi.org/10.1093/pnasnexus/pgaf023

Manti, S. & Lucantonio, A. (2024). Discovering interpretable physical models using symbolic regression and discrete exterior calculus. Machine Learning: Science and Technology, 5(1), Article 015005. https://doi.org/10.1088/2632-2153/ad1af2

Dideriksen, A. K., Andersen, M. F., Priest, J., Eriksen, N. F., Frandsen, M. T., Melvad, C., Rasmussen, T. F., Nielsen, N. H. K., Strømsnes, C. T., Ahlebæk, M. J., Samsing, S., Larsen, T. B., Don, J., Pedersen, L. A. N., Jacobsen, R. H., Rysgaard, S., Kim, J. M., Bayer, R., Christensen, C. ... Karoff, C. (2024). DISCO-2 – an ambitious earth observing student CubeSat for arctic climate research. Frontiers in Remote Sensing, 5, Article 1474560. https://doi.org/10.3389/frsen.2024.1474560

Yang, J., Stroh, A., Chung, D. & Forooghi, P. (2022). Direct numerical simulation-based characterization of pseudo-random roughness in minimal channels. Journal of Fluid Mechanics, 941, Article A47. https://doi.org/10.1017/jfm.2022.331

Xie, Z. & Andresen, G. B. (2024). Direct and Indirect Hydrogen Storage: Dynamics and Interactions in the Transition to a Renewable Energy Based System for Europe.

Zhou, Z., Yang, X., Wang, H. & Zhang, X. (2022). Digital Twin with Integrated Robot-Human/Environment Interaction Dynamics for an Industrial Mobile Manipulator. Proceedings - IEEE International Conference on Robotics and Automation (ICRA), 5041-5047. https://doi.org/10.1109/ICRA46639.2022.9812004

Ma, G., da Silva, E. R. & Møller, C. (2024). Digital Twin-based Demand-Driven Production Planning and Scheduling System: A New Conceptual Framework. Procedia CIRP, 130, 705-710. https://doi.org/10.1016/j.procir.2024.10.152

Jensen, A. M. D., Schoerghofer-Queiroz, A., Ulriksen, M. D., Tcherniak, D., Damkilde, L., Talasila, P., Larsen, P. G. & Abbiati, G. (2024). Digital twin as a service for damage prognosis of offshore wind turbine foundations. In W. Desmet, B. Pluymers, D. Moens & J. del Fresno Zarza (Eds.), Proceedings of ISMA 2024 - International Conference on Noise and Vibration Engineering and USD 2024 - International Conference on Uncertainty in Structural Dynamics (pp. 4127-4141). KU Leuven, Departement Werktuigkunde.

Addo-Tenkorang, R., Møller, C. & Chen, K.-L. (2023). Digital Transformation Roadmap for Danish SME Smart Factories: Benefits and Future Research. In International Conference on Smart Business Technologies (pp. 41-60)

Glisic, M., Møller, C., Veluri, B. & Ramanujan, D. (2024). Digital Process Passport: A Conceptual Model for Information Collection and Sharing In Sustainable Manufacturing. Procedia CIRP, 130(27), 1077-1083. https://doi.org/10.1016/j.procir.2024.10.209

Suhr, M., Orlowitz, E., Hansen, J. F. & Brandt, A. (2022). Digital image correlation and operational modal analysis: A study of influential factors for non-contact measurements. 2778-2784. Paper presented at ISMA 2022: Leuven Conference on Noise and Vibration Engineering, Leuven , Belgium.

Velu, R., Karupppasamy, S. & Kumar Subramaniyan, A. K. (Eds.) (2024). Digital Design and Manufacturing of Medical Devices and Systems. (1 ed.) Springer. https://doi.org/10.1007/978-981-99-7100-8

Farhadiyadkuri, F. (2023). Development of Robotic Brace for AIS Treatment. [PhD thesis, Aarhus University]. Aarhus Universitet.

Feng, H., Gomes, C., Sandberg, M., Thule, C., Lausdahl, K. & Larsen, P. G. (2021). Developing a Physical and Digital Twin: An Example Process Model. In Companion Proceedings - 24th International Conference on Model-Driven Engineering Languages and Systems, MODELS-C 2021 (pp. 286-295). IEEE. https://doi.org/10.1109/MODELS-C53483.2021.00050

Bruun Andresen, G. (2024, Apr). det lykkelige Nordsøen - genåbning af Danmarks største gas-felt, Tyra-feltet. Instagram.com. https://www.instagram.com/p/C50BZMOMwXU/?igsh=dXQ5anoweTc1NHFk&img_index=1

D. Huang, X. L. ., Jain, N., Abkar, M., Kunz, R. F. & Yang, X. I. A. (2021). Determining a priori a RANS model’s applicable range via global epistemic uncertainty quantification. Computers & Fluids, 230, Article 105113. https://doi.org/10.1016/j.compfluid.2021.105113

Djeffal, S., Ghoul, A., Saadi, A., Izri, Z., Morakchi, M. R. & Wang, H. (2025). Design optimization and simulation of a 3D printed cable-driven continuum robot using IKM-ANN and nTop software. Proceedings of the Institution of Mechanical Engineers. Part I: Journal of Systems and Control Engineering, 239(2), 200-218. https://doi.org/10.1177/09596518241276233

Budzik, M. K., Dias, M. A. & Hoffmann, U. S. (2023). Design of failure loads and crack growth by width varying interfaces. 142. Abstract from International Conference on Adhesive Bonding 2023, Porto, Portugal.

He, L., Wang, C., Zhang, M., Li, J., Chen, T. & Zhou, X. (2025). Design of BCC/FCC dual-solid solution refractory high-entropy alloys through CALPHAD, machine learning and experimental methods. npj Computational Materials, 11(1), Article 105. https://doi.org/10.1038/s41524-025-01597-3

Gøtske, E. K., Andresen, G. B., Neumann, F. & Victoria, M. (2024). Designing a sector-coupled European energy system robust to 60 years of historical weather data. Nature Communications, 15(1), Article 10680. https://doi.org/10.1038/s41467-024-54853-3

Formentini, G. & Ramanujan, D. (2023). Design for circular disassembly: Evaluating the impacts of product end-of-life status on circularity through the parent-action-child model. Journal of Cleaner Production, 405, Article 137009. https://doi.org/10.1016/j.jclepro.2023.137009

Si, G., Sun, L., Zhang, Z. & Zhang, X. (2021). Design, Fabrication, and Testing of a Novel 3D 3-Fingered Electrothermal Microgripper with Multiple Degrees of Freedom. Micromachines, 12(4), Article 444. https://doi.org/10.3390/mi12040444

Si, G., Zhao, Z., Zhang, Z. & Zhang, X. (2024). Design and Experimental Investigation of a Force Sensor for a 3-D Electrothermal Microgripper. IEEE Sensors Journal, 24(3), 2934-2944. https://doi.org/10.1109/JSEN.2023.3336214

Cristóbal, A. B., Sanz-Cuadrado, C., Zhang, Z., Victoria, M., Fialho, L., Cavaco, A., Bokalič, M. & Narvarte, L. (2025). Delving into the modeling and operation of energy communities as epicenters for systemic transformations. Universal Access in the Information Society, 24(3), 2007-2023. https://doi.org/10.1007/s10209-023-01056-0

Jensen, H. M., Sørensen, K. D. & Clausen, J. (2008). Delamination of Compressed Thin Layers at Corners. https://pure.au.dk/admin/files/15365084/CornerDelaminationICTAM08.pdf

Sørensen, K. D., Jensen, H. M. & Clausen, J. (2008). Delamination of Compressed Thin Layers at Corners. International Journal of Solids and Structures, 45(22-23), 5867-5878. https://doi.org/10.1016/j.ijsolstr.2008.07.004

Zhou, Z., Li, L. & Zhang, X. (2021). Deep Learning on 3D Object Detection for Automatic Plug-in Charging Using a Mobile Manipulator. In 2021 IEEE International Conference on Robotics and Automation (ICRA) (pp. 4148-4154). IEEE. https://doi.org/10.1109/ICRA48506.2021.9561106

Hudert, M. M., Elvebakken, M. F., Meagher, M., Mangliar, L., Zhang, X. & Esterle, L. (2022). Deep learning enhanced robotic fabrication of timber-to-timber connections with densified hardwood nails. In Proceedings of the IASS 2022 Symposium affiliated with APCS 2022 conference: Innovation - Sustainability - Legacy (pp. 1740-1748)

Strässle, R. M., Faldella, F. & Doll, U. (2024). Deep learning-based image segmentation for instantaneous flame front extraction. Experiments in Fluids, 65(6), Article 94. https://doi.org/10.1007/s00348-024-03814-z

Fulco , S., Budzik, M. K., D. Bain , E. & T. Turner , K. (2022). Decoupling toughness and strength through architected plasticity. Extreme Mechanics Letters, 57, Article 101912. https://doi.org/10.1016/j.eml.2022.101912

Hu, P., Li, S. & Budzik, M. K. (2025). Decoupling fracture energy from crack area via surface patterning. Surfaces and Interfaces, 62, Article 106066. https://doi.org/10.1016/j.surfin.2025.106066

Pedersen, T. T. (2023). Decision support for renewable energy integration through exploration of near-optimal solutions. [PhD thesis, Aarhus University]. Aarhus Universitet.

Schwenk-Nebbe, L. J., Victoria, M. & Bruun Andresen, G. (2021). Dataset: A proxy for historical CO2 emissions related to centralised electricity generation in Europe. Data in Brief, 36, Article 107016. https://doi.org/10.1016/j.dib.2021.107016

Li, X., Cheng, Y., Møller, C. & Lee, J. (2025). Data issues in industrial AI systems: A meta-review and research strategy. Computers in Industry, 173, Article 104361. https://doi.org/10.1016/j.compind.2025.104361

Amarloo, A., Cinnella, P., Iosifidis, A., Forooghi, P. & Abkar, M. (2023). Data-driven Reynolds stress models based on the frozen treatment of Reynolds stress tensor and Reynolds force vector. Physics of Fluids, 35(7), Article 075154. https://doi.org/10.1063/5.0160977

Amarloo, A. (2024). Data-Driven RANS Modelling and Prediction of Turbulent Flows. [PhD thesis, Aarhus University]. Aarhus University.

Eidi, A., Zehtabiyan-Rezaie, N., Chiassi, R., Yang, X. I. A. & Abkar, M. (2022). Data-driven quantification of model-form uncertainty in Reynolds-averaged simulations of wind farms. Physics of Fluids, 34(8), Article 085135. https://doi.org/10.1063/5.0100076

Truong, T. T., Airao, J., Hojati, F., Ilvig, C. F., Azarhoushang, B., Karras, P. & Aghababaei, R. (2024). Data-driven prediction of tool wear using Bayesian regularized artificial neural networks. Measurement: Journal of the International Measurement Confederation, 238, Article 115303. https://doi.org/10.1016/j.measurement.2024.115303

Böttjer, T., Ørnskov Rønsch, G., Gonçalves Gomes, C. Â., Ramanujan, D., Iosifidis, A. & Larsen, P. G. (2021). Data-Driven Identification of Remaining Useful Life for Plastic Injection Moulds. In A.-L. Andersen, R. Andersen, D. Brunoe, M. Stoettrup Schioenning Larsen, K. Nielsen, A. Napoleone & S. Kjeldgaard (Eds.), Towards Sustainable Customization: Bridging Smart Products and Manufacturing Systems: Proceedings of the Changeable, Agile, Reconﬁgurable and Virtual Production Conference and the World Mass Customization & Personalization Conference (pp. 431-439). Springer. https://www.springerprofessional.de/en/data-driven-identification-of-remaining-useful-life-for-plastic-/19816878

Böttjer, T., Ørnskov Rønsch, G., Gomes, C., Ramanujan, D., Iosifidis, A. & Larsen, P. G. (2022). Data-Driven Identification of Remaining Useful Life for Plastic Injection Moulds. In A.-L. Andersen, R. Andersen, T. D. Brunoe, M. Stoettrup Schioenning Larsen, K. Nielsen, A. Napoleone & S. Kjeldgaard (Eds.), Towards Sustainable Customization: Bridging Smart Products and Manufacturing Systems - Proceedings of the 8th Changeable, Agile, Reconfigurable and Virtual Production Conference CARV 2021 and 10th World Mass Customization and Personalization Conference MCPC 2021 (pp. 431-439). Springer. https://doi.org/10.1007/978-3-030-90700-6_49

Zehtabiyan-Rezaie, N., Iosifidis, A. & Abkar, M. (2022). Data-driven fluid mechanics of wind farms: A review. Journal of Renewable and Sustainable Energy, 14(3), Article 032703. https://doi.org/10.1063/5.0091980

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), Article 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. In 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) Article FEDSM2022-87630, V002T05A023 American Society of Mechanical Engineers (ASME). https://doi.org/10.1115/FEDSM2022-87630

Dias, M. A., E.F. Athanasiadis, A., N. Fernando, D. & Budzik, M. K. (2024). Damage propagation in Architected-Interfaces. 1. Abstract from American Physical Society March Meeting 2024, Minneapolis , Minnesota, United States. https://meetings.aps.org/Meeting/MAR24/Session/Q35.10

Malekan, M., Bloch-Jensen, C. D., Zolbin, M. A., Ørskov, K. B., Jensen, H. M. & Aghababaei, R. (2021). Cutting edge wear in high-speed stainless steel end milling. International Journal of Advanced Manufacturing Technology, 114(9-10), 2911-2928. https://doi.org/10.1007/s00170-021-07006-5

Aghababaei, R., Malekan, M. & Budzik, M. (2021). Cutting Depth Dictates the Transition from Continuous to Segmented Chip Formation. Physical Review Letters, 127(23), Article A202. https://doi.org/10.1103/PhysRevLett.127.235502

Displaying results 351 to 400 out of 524

Revised 22.02.2024

AU Engineering