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Welcome to my webpage

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My interests lie in the mechanics of nonlinear systems and structures on multiple lengths and time scales, statistical and probabilistic mechanical phenomena, and the development of new methods for their efficient treatment.

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I am a group leader at the Institute of General Mechanics at RWTH Aachen University. I hold a PhD degree in Mechanics and Structural dynamics as well as a Master's degree in Civil Engineering from the Technical University of Vienna, both of which I finished with distinction.

 

I received the interdisciplinary Open Seed Fund twice and the Theodore von Kármán Fellowship within the excellence initiatives of the federal ministry of education and research and the German research fund.

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Journal articles (peer-reviewed)

2022

[44] T. Focks, F. Bamer, B. Markert, Z. Wu, B. Stamm, Displacement field splitting of defective hexagonal lattices, Physical Review B 106 (2022) 014105, https://link.aps.org/doi/10.1103/PhysRevB.106.014105.

[43] T. Arjoune, B. Markert, F. Bamer, Non-incremental response evaluation in geometrically nonlinear structural dynamics using a space-time stiffness operator, Computational Mechanics (2022) Online First, https://doi.org/10.1007/s00466-022-02169-8.

[42] X. Cao, A. Oueslati, N. Shirafkan, F. Bamer, B. Markert, G. deSaxcé, Closed form solutions for the dynamics of a pressurized elastoplastic thin-walled tube, Thin-Walled Structures 174 (2022) 109080, https://doi.org/10.1016/j.tws.2022.109080.

[41] Y. Heider, F. Bamer, F. Ebrahem, B. Markert, Self-organized criticality in fracture models at different scales, Examples and Counterexamples 2 (2022) 100054, https://doi.org/10.1016/j.exco.2022.100054.

[40] A. Koeppe, F. Bamer, M. Selzer, B. Nestler, B. Markert, Explainable Artificial Intelligence for Mechanics: Physics-Explaining Neural Networks for Constitutive Models, Frontiers in Materials 8 (2022) 824958, https://doi.org/10.3389/fmats.2021.824958.

[39] S. Mostafavi, F. Bamer, B. Markert, Molecular dynamics simulation of interface atomic diffusion in ultrasonic metal welding: Effect of crystal orientation and sliding velocity, The International Journal of Advanced Manufacturing Technology 118 (2022) 2339-2353, https://doi.org/10.1007/s00170-021-07987-3.

[38] D. Thaler, L. Elezaj, F. Bamer, B. Markert, Training Data Selection for Machine Learning-Enhanced Monte Carlo Simulations in Structural Dynamics, Applied Sciences 12 (2022) 581, https://doi.org/10.3390/ app12020581.

2021

[37] F. Bamer, S.S. Alshabab, A. Paul, F. Ebrahem, B. Markert, B. Stamm, Data-driven classification of elementary rearrangement events in silica glass, Scripta Materialia 205 (2021) 114179, https://doi.org/10.1016/j.scriptamat.2021.114179.

[36] X. Cao, A. Oueslati, N. Shirafkan, F. Bamer, B. Markert, G. Saxcé, A non-incremental numerical method for dynamic elastoplastic problems by the symplectic Brezis–Ekeland–Nayroles principle, Computer Methods in Appied Mechanics and Engineering 384 (2021) 113908, https://doi.org/10.1016/j.cma.2021.113908.

[35] D. Thaler, M. Stoffel, B. Markert, F. Bamer, Machine‐learning‐enhanced tail end prediction of structural response statistics in earthquake engineering, Earthquake Engineering & Structural Dynamics 50 (2021) 2098-2114, https://doi.org/10.1002/eqe.3432.

[34] F. Bamer, N. Shirafkan, X. Cao, A. Oueslati, M. Stoffel, G. Saxcé, B. Markert, A Newmark space-time formulation in structural dynamics, Computational Mechanics 67 (2021) 1331-1348, https://doi.org/10.1007/s00466-021-01989-4.

[33] F. Bamer, D. Thaler, M. Stoffel, B. Markert, A Monte Carlo Simulation Approach in Non-linear Structural Dynamics Using Convolutional Neural Networks, Frontiers in Built Environment 53 (2021) https://www.frontiersin.org/articles/10.3389/fbuil.2021.679488.

2020

[32] M Mundt, A Koeppe, S David, F Bamer, W Potthast, B Markert, Prediction of ground reaction force and joint moments based on optical motion capture data during gait, Medical Engineering & Physics 86 (2020) 29-34, https://doi.org/10.1016/j.medengphy.2020.10.001.

[31] F. Ebrahem, F. Bamer, B. Markert, Origin of reversible and irreversible atomic-scale rearrangements in a model two-dimensional network glass, Physical Review E 102 (2020) 033006, https://link.aps.org/doi/10.1103/PhysRevE.102.033006.

[30] M. Stoffel, F. Bamer, B. Markert, Deep convolutional neural networks in structural dynamics under consideration of viscoplastic material behaviour, Mechanics Research Communications 108 (2020) 103565, https://doi.org/10.1016/j.mechrescom.2020.103565.

[29] M. Mundt, A. Koeppe, F. Bamer, S. David, B. Markert, Artificial neural networks in motion analysis—applications of unsupervised and heuristic feature selection techniques, Sensors 20 (2020) 4581, https://doi.org/10.3390/s20164581.

[28] A. Koeppe, F. Bamer, B. Markert, An intelligent nonlinear meta element for elastoplastic continua: deep learning using a new Time-distributed Residual U-Net architecture, Computer Methods in Applied Mechanics and Engineering 366 (2020) 113088, https://doi.org/10.1016/j.cma.2020.113088.

[27] F. Ebrahem, J. Stratmann, M. Stoffel, B. Markert, F. Bamer, Continuous Zachariasen carbon monolayers under tensile deformation: Insights from molecular dynamics simulations, Extreme Mechanics Letters 38 (2020) 100744, https://doi.org/10.1016/j.eml.2020.100744.

[26] M. Stoffel, R. Gulakala, F. Bamer, B. Markert, Artificial neural networks in structural dynamics: A new modular radial basis function approach vs. convolutional and feedforward topologies, Computer Methods in Applied Mechanics and Engineering 364 (2020) 112989, https://doi.org/10.1016/j.cma.2020.112989.

[25] F. Ebrahem, F. Bamer, B. Markert, Vitreous 2D silica under tension: From brittle to ductile behaviour, Materials Science and Engineering: A 780 (2020) 139189, https://doi.org/10.1016/j.msea.2020.139189.

[24] N. Shirafkan, F. Bamer, M. Stoffel, B. Markert, Quasistatic analysis of elastoplastic structures by the proper generalized decomposition in a space-time approach, Mechanics Research Communications 104 (2020) 103500, https://doi.org/10.1016/j.mechrescom.2020.103500.

[23] F. Bamer, F. Ebrahem, B. Markert, Elementary plastic events in a Zachariasen glass under shear and pressure, Materialia 9 (2020) 100556, https://doi.org/10.1016/j.mtla.2019.100556.

[22] F. Ebrahem, F. Bamer, B. Markert, Stone–Wales defect interaction in quasistatically deformed 2D silica, Journal of Materials Science 55 (2020) 3470-3483, https://doi.org/10.1007/s10853-019-04274-1.

[21] M. Mundt, A. Koeppe, S. David, T. Witter, F. Bamer, W. Potthast, B. Markert, Estimation of gait mechanics based on simulated and measured IMU data using an artificial neural network, Frontiers in bioengineering and biotechnology 8  (2020) 41, https://doi.org/10.3389/fbioe.2020.00041.

[20] M. Mundt, W. Thomsen, T. Witter, A. Koeppe, S. David, F. Bamer, W. Potthast, Prediction of lower limb joint angles and moments during gait using artificial neural networks, Medical & biological engineering & computing 58 (2020), 211-225, https://doi.org/10.1007/s11517-019-02061-3.

2019

[19] F. Bamer, N. Strubel, J. Shi, B. Markert, A visco-elastoplastic pounding damage formulation,

Engineering Structures 197 (2019) 109373, https://doi.org/10.1016/j.engstruct.2019.109373.

[18] A. Koeppe, F. Bamer, B. Markert, An efficient Monte Carlo strategy for elasto-plastic structures based on recurrent neural networks, Acta Mechanica 230 (2019) 3279-3293, https://doi.org/10.1007/s00707-019-02436-5.

[17] M. Mundt, S. David, A. Koeppe, F. Bamer, B. Markert, W. Potthast, Intelligent prediction of kinetic parameters during cutting manoeuvres, Medical & Biological Engineering & Computing 57 (2019), 1833-1841, https://doi.org/10.1007/s11517-019-02000-2.

[16] F. Bamer, F. Ebrahem, B. Markert, Athermal mechanical analysis of Stone-Wales defects in two-dimensional silica, Computational Materials Science 163 (2019) 301-307, https://doi.org/10.1016/j.commatsci.2019.03.050.

[15] M. Stoffel, F. Bamer, B. Markert, Stability of feed forward artificial neural networks versus nonlinear structural models in high speed deformations: A critical comparison, Archives of Mechanics 71 (2019) 95-111, http://doi.org/10.24423/aom.3091.

[14] M. Mundt, W. Thomsen, S. David, T. Dupré, F. Bamer, W. Potthast, B. Markert, Assessment of the measurement accuracy of inertial sensors during different tasks of daily living, Journal of Biomechanics 84 (2019) 81-86, https://doi.org/10.1016/j.jbiomech.2018.12.023.

[13] F. Bamer, F. Ebrahem, B. Markert, Plasticity in vitreous silica induced by cyclic tension considering rate-dependence: Role of the network topology, Journal of Non-Crystalline Solids 503 (2019) 176-181, https://doi.org/10.1016/j.jnoncrysol.2018.09.043.

[12] J. Shi, F. Bamer, B. Markert, A substructure formulation for the earthquake-induced nonlinear structural pounding problem,

Earthquakes and Structures 17 (2019) 101-113, https://doi.org/10.12989/eas.2019.17.1.101.

[11] M. Stoffel, F. Bamer, B. Markert, Neural network based constitutive modeling of nonlinear viscoplastic structural response,

Mechanics Research Communications 95 (2019) 85-88, https://doi.org/10.1016/j.mechrescom.2019.01.004.

2018

[10] F. Bamer, A Hertz-pounding formulation with a nonlinear damping and a dry friction element, Acta Mechanica 229 (2019) 4485-4494,

[9] F. Bamer, B. Markert, A nonlinear visco‐elastoplastic model for structural pounding, Earthquake Engineering & Structural Dynamics 47 (2018) 2490-2495,

[8] M. Stoffel, F. Bamer, B. Markert, Artificial neural networks and intelligent finite elements in non-linear structural mechanics, Thin-Walled Structures 131 (2018) 102-106,

[7] F. Bamer, J. Shi, B. Markert, Efficient solution of the multiple seismic pounding problem using hierarchical substructure techniques, Computational Mechanics 62 (2018) 761-782,

[6] F. Ebrahem, F. Bamer, B. Markert, The influence of the network topology on the deformation and fracture behaviour of silica glass: A molecular dynamics study, Computational Materials Science 149 (2018) 162-169,

[5] J. Shi, F. Bamer, B. Markert, A structural pounding formulation using systematic modal truncation,

Shock and Vibration 2018 (2018) Article ID 6378085, https://doi.org/10.1155/2018/6378085.

2017 and before

[4] F. Bamer, B. Markert, An efficient response identification strategy for nonlinear structures subject to nonstationary generated seismic excitations, Mechanics Based Design of Structures and Machines 45 (2017), 313-330,

[3] F. Bamer, A.K. Amiri, C. Bucher, A new model order reduction strategy adapted to nonlinear problems in earthquake engineering, Earthquake engineering & structural dynamics 46 (2017), 537-559,

[2] F. Bamer, C. Bucher, A Model Reduction Method adapted for non-linear Problems in Earthquake Engineering

BAUINGENIEUR 92 (2017) 2-6.

[1] F. Bamer, C. Bucher, Application of the proper orthogonal decomposition for linear and nonlinear structures under transient excitations, Acta Mechanica 223 (2012) 2549-2563,

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