Profil

LENGIEWICZ Jakub

Main Referenced Co-authors
BORDAS, Stéphane  (13)
DESHPANDE, Saurabh  (9)
BEEX, Lars  (3)
Hołobut, Paweł (3)
LAVIGNE, Thomas  (3)
Main Referenced Keywords
Contact (2); Deep Learning (2); Mechanics of Materials (2); Agricultural robots (1); artery (1);
Main Referenced Unit & Research Centers
Institute of Computational Engineering (2)
ULHPC - University of Luxembourg: High Performance Computing (2)
Main Referenced Disciplines
Engineering, computing & technology: Multidisciplinary, general & others (12)
Computer science (9)
Mechanical engineering (7)
Civil engineering (5)
Materials science & engineering (4)

Publications (total 19)

The most downloaded
276 downloads
Deshpande, S., Lengiewicz, J., & Bordas, S. (01 August 2022). Probabilistic Deep Learning for Real-Time Large Deformation Simulations. Computer Methods in Applied Mechanics and Engineering, 398 (0045-7825), 115307. doi:10.1016/j.cma.2022.115307 https://hdl.handle.net/10993/51869

The most cited

32 citations (Scopus®)

Lengiewicz, J., de Souza, M., Lahmar, M. A., Courbon, C., Dalmas, D., Stupkiewicz, S., & Scheibert, J. (October 2020). Finite deformations govern the anisotropic shear-induced area reduction of soft elastic contacts. Journal of the Mechanics and Physics of Solids, 143, 104056. doi:10.1016/j.jmps.2020.104056 https://hdl.handle.net/10993/43469

Deshpande, S., Sosa, R. I., Bordas, S., & Lengiewicz, J. (August 2023). Novel deep learning approaches for learning scientific simulations [Paper presentation]. The 14th International Conference of Computational Methods (ICCM2023), Ho Chi Minh, Vietnam.
Peer reviewed

Deshpande, S., Lengiewicz, J., & Bordas, S. (27 June 2023). Novel Geometric Deep Learning Surrogate Framework for Non-Linear Finite Element Simulations [Poster presentation]. The Platform for Advanced Scientific Computing (PASC) Conference 2023.
Peer reviewed

Deshpande, S., Bordas, S., & Lengiewicz, J. (2023). MAgNET: A Graph U-Net Architecture for Mesh-Based Simulations. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/54969.

Deshpande, S., Sosa, R. I., Bordas, S., & Lengiewicz, J. (2023). Convolution, aggregation and attention based deep neural networks for accelerating simulations in mechanics. Frontiers in Materials. doi:10.3389/fmats.2023.1128954
Peer Reviewed verified by ORBi

LAVIGNE, T., BORDAS, S., & LENGIEWICZ, J. (March 2023). Identification of material parameters and traction field for soft bodies in contact. Computer Methods in Applied Mechanics and Engineering, 406, 115889. doi:10.1016/j.cma.2023.115889
Peer Reviewed verified by ORBi

LAVIGNE, T., MAZIER, A., Perney, A., BORDAS, S., Hild, F., & LENGIEWICZ, J. (December 2022). Digital Volume Correlation for large deformations of soft tissues: Pipeline and proof of concept for the application to breast ex vivo deformations. Journal of the Mechanical Behavior of Biomedical Materials, 136, 105490. doi:10.1016/j.jmbbm.2022.105490
Peer Reviewed verified by ORBi

Deshpande, S., Lengiewicz, J., & Bordas, S. (2022). Real Time Hyper-elastic Simulations with Probabilistic Deep Learning. In 15th World Congress on Computational Mechanics (WCCM-XV).
Peer reviewed

Deshpande, S., Lengiewicz, J., & Bordas, S. (01 August 2022). Probabilistic Deep Learning for Real-Time Large Deformation Simulations. Computer Methods in Applied Mechanics and Engineering, 398 (0045-7825), 115307. doi:10.1016/j.cma.2022.115307
Peer Reviewed verified by ORBi

Mazier, A., Lavigne, T., Lengiewicz, J., Deshpande, S., Urcun, S., & Bordas, S. (July 2022). Towards real-time patient-specific breast simulations: from full-field information to surrogate model [Paper presentation]. 9th World Congress of Biomechanics.

Deshpande, S., Lengiewicz, J., & Bordas, S. (28 June 2022). Real-Time Large Deformation Simulations Using Probabilistic Deep Learning Framework [Poster presentation]. The Platform for Advanced Scientific Computing (PASC) Conference.

Deshpande, S., Lengiewicz, J., & Bordas, S. (2022). Real-time large deformations: A probabilistic deep learning approach. In The 8th European Congress on Computational Methods in Applied Sciences and Engineering.
Peer reviewed

Magliulo, M., Lengiewicz, J., Zilian, A., & Beex, L. (15 April 2021). Frictional interactions for non-localised beam-to-beam and beam-inside-beam contact. International Journal for Numerical Methods in Engineering, 122 (7), 1706-1731. doi:10.1002/nme.6596
Peer Reviewed verified by ORBi

Lengiewicz, J., & Hołobut, P. (2021). Artificial life of shape-shifters.

Lengiewicz, J., & Hołobut, P. (2021). Sztuczne życie zmiennokształtnych.

Piranda, B., Chodkiewicz, P., Holobut, P., Bordas, S., Bourgeois, J., & Lengiewicz, J. (2021). Distributed Prediction of Unsafe Reconfiguration Scenarios of Modular Robotic Programmable Matter. IEEE Transactions on Robotics, 37 (6), 2226-2233. doi:10.1109/TRO.2021.3074085
Peer Reviewed verified by ORBi

Magliulo, M., Lengiewicz, J., Zilian, A., & Beex, L. (November 2020). Beam-inside-beam contact: Mechanical simulations of slender medical instruments inside the human body. Computer Methods and Programs in Biomedicine, 196, 105527. doi:10.1016/j.cmpb.2020.105527
Peer reviewed

Lengiewicz, J., de Souza, M., Lahmar, M. A., Courbon, C., Dalmas, D., Stupkiewicz, S., & Scheibert, J. (October 2020). Finite deformations govern the anisotropic shear-induced area reduction of soft elastic contacts. Journal of the Mechanics and Physics of Solids, 143, 104056. doi:10.1016/j.jmps.2020.104056
Peer Reviewed verified by ORBi

Magliulo, M., Lengiewicz, J., Zilian, A., & Beex, L. (2020). Non-localised contact between beams with circular and elliptical cross-sections. Computational Mechanics, 65, 1247-1266. doi:10.1007/s00466-020-01817-1
Peer Reviewed verified by ORBi

Hołobut, P., Lengiewicz, J., & Bordas, S. (2020). Autonomous model-based assessment of mechanical failures of reconfigurable modular robots with a Conjugate Gradient solver. In 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 11696-11702). IEEE. doi:10.1109/iros45743.2020.9341232
Peer reviewed

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