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RAPPEL Hussein

Main Referenced Co-authors
BEEX, Lars  (19)
BORDAS, Stéphane  (17)
HALE, Jack  (11)
Noels, Ludovic (4)
Akbari, Ahmad (2)
Main Referenced Keywords
Bayesian inference (17); parameter identification (9); Bayes’ theorem (7); Bayes' theorem (6); elastoplasticity (6);
Main Referenced Unit & Research Centers
University of Luxembourg: Institute of Computational Engineering (1)
Main Referenced Disciplines
Mechanical engineering (23)
Engineering, computing & technology: Multidisciplinary, general & others (15)
Materials science & engineering (13)
Civil engineering (10)
Aerospace & aeronautics engineering (9)

Publications (total 26)

The most downloaded
1325 downloads
RAPPEL, H., BEEX, L., HALE, J., & BORDAS, S. (n.d.). Bayesian inference for the stochastic identification of elastoplastic material parameters: Introduction, misconceptions and insights. (v4). ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/28631. https://hdl.handle.net/10993/28631

The most cited

119 citations (OpenAlex)

RAPPEL, H., BEEX, L., HALE, J., Noels, L., & BORDAS, S. (2019). A Tutorial on Bayesian Inference to Identify Material Parameters in Solid Mechanics. Archives of Computational Methods in Engineering, 1-25. doi:10.1007/s11831-018-09311-x https://hdl.handle.net/10993/37698

RAPPEL, H., Wu, L., Noels, L., & BEEX, L. (2021). A Bayesian framework to identify random parameter fields based on the copula theorem and Gaussian fields: Application to polycrystalline materials. Journal of Applied Mechanics. doi:10.1115/1.4044894
Peer Reviewed verified by ORBi

Mahamedou, M., Zulueta Uriondo, K., Chung, C. N., RAPPEL, H., BEEX, L., Adam, L., Arriaga, A., Major, Z., Wu, L., & Noels, L. (15 July 2019). Bayesian Identification of Mean-Field Homogenization model parameters and uncertain matrix behavior in non-aligned short fiber composites. Composite Structures, 220, 64-80. doi:10.1016/j.compstruct.2019.03.066
Peer Reviewed verified by ORBi

RAPPEL, H., & BEEX, L. (June 2019). Estimating fibres' material parameter distributions from limited data with the help of Bayesian inference. European Journal of Mechanics. A, Solids, 75, 169-196. doi:10.1016/j.euromechsol.2019.01.001
Peer Reviewed verified by ORBi

RAPPEL, H. (12 February 2019). Probabilistic modeling natural way to treat data [Paper presentation]. 1st Diriven workshop.

Barbosa, J., BORDAS, S., Carvalho, A., DING, C., LIAN, H., Loja, M. A., Mathew, T., Natarajan, S., RAPPEL, H., Rodrigues, J., & SUAREZ AFANADOR, C. A. (2019). Geometrical and material uncertainties for the mechanics of composites [Paper presentation]. IGA 2019.

RAPPEL, H., BEEX, L., Noels, L., & BORDAS, S. (January 2019). Identifying elastoplastic parameters with Bayes' theorem considering double error sources and model uncertainty. Probabilistic Engineering Mechanics, 55, 28-41. doi:10.1016/j.probengmech.2018.08.004
Peer Reviewed verified by ORBi

RAPPEL, H., BEEX, L., HALE, J., Noels, L., & BORDAS, S. (2019). A Tutorial on Bayesian Inference to Identify Material Parameters in Solid Mechanics. Archives of Computational Methods in Engineering, 1-25. doi:10.1007/s11831-018-09311-x
Peer reviewed

RAPPEL, H. (2018). Model and parameter identification through Bayesian inference in solid mechanics [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/36672

RAPPEL, H., BEEX, L., & BORDAS, S. (23 July 2018). Identifying fibre material parameter distributions with little experimental efforts [Paper presentation]. 13th World Congress in Computational Mechanics.

RAPPEL, H., BEEX, L., & BORDAS, S. (22 July 2018). Identifying material parameter distributions of fibers with extremely limited experimental efforts [Paper presentation]. 13th World Congress in Computational Mechanics.

RAPPEL, H., BEEX, L., & BORDAS, S. (2017). Bayesian inference to identify parameters in viscoelasticity. Mechanics of Time-Dependent Materials. doi:10.1007/s11043-017-9361-0
Peer reviewed

RAPPEL, H., BEEX, L., HALE, J., & BORDAS, S. (12 December 2016). Bayesian inference for parameter identification in computational mechanics [Poster presentation]. Computational Sciences for Medicine Workshop, Luxembourg, Luxembourg.

RAPPEL, H., BEEX, L., HALE, J., & BORDAS, S. (07 September 2016). Bayesian inference for material parameter identification in elastoplasticity [Paper presentation]. European Mechanics of Materials Conference (EMMC15), Brussels, Belgium.

RAPPEL, H., BEEX, L., HALE, J., & BORDAS, S. (09 June 2016). A Bayesian approach for parameter identification in elastoplasticity [Paper presentation]. ECCOMAS Congress 2016, Crete Island, Greece.

RAPPEL, H., BEEX, L., HALE, J., & BORDAS, S. (June 2016). A Bayesian approach for parameter identification in elastoplasticity [Paper presentation]. ECCOMAS Congress 2016, Crete Island, Greece.

RAPPEL, H., BEEX, L., HALE, J., & BORDAS, S. (2016). Bayesian inference for material parameter identification. Luxembourg, Luxembourg: University of Luxembourg. https://orbilu.uni.lu/handle/10993/27346

RAPPEL, H., BEEX, L., HALE, J., & BORDAS, S. (04 February 2016). An introduction to Bayesian inference for material parameter identification [Paper presentation]. Kick off meeting for STOMMMAC project, Mont-Saint-Guibert, Belgium.

BORDAS, S., HALE, J., BEEX, L., RAPPEL, H., Kerfriden, P., Goury, O., & Akbari, A. (2015). Multi-scale methods for fracture: model learning across scales, digital twinning and factors of safety
: primer on Bayesian Inference [Paper presentation]. EMPA High-performance Multiscale-Scale Day, Dübendorf, Switzerland.

BORDAS, S., BEEX, L., Kerfriden, P., Paladim, D.-A., Olivier, G., Akbari, A., & RAPPEL, H. (18 November 2015). Multi-scale methods for fracture: model learning across scales, digital twinning and factors of safety [Paper presentation]. Empa's topical day on “Multiscale high-performance computational modelling”, Zürich, Switzerland.

BEEX, L., BORDAS, S., RAPPEL, H., & HALE, J. (14 October 2014). Discrete Multiscale Modelling and Future Research Plans concerning Metals (presentation) [Paper presentation]. ArcelorMittal Steel Forming Network Seminar 'Numerical Methods', Metz, France.

BEEX, L., BORDAS, S., RAPPEL, H., & HALE, J. (14 October 2014). Discrete Multiscale Modelling and Future Research Plans concerning Metals [Paper presentation]. ArcelorMittal Steel Forming Network Seminar 'Numerical Methods', Metz, France.

RAPPEL, H., Yousefi-Koma, A., Jalil, J., & Ako, B. (10 July 2014). Numerical Time-Domain Modeling of Lamb Wave Propagation Using Elastodynamic Finite Integration Technique. Shock and Vibration, 2014, 6. doi:10.1155/2014/434187
Peer Reviewed verified by ORBi

RAPPEL, H., Yousefi-Koma, A., & Baseri, H. (18 February 2014). Shape control of Bio-inspired tail by shape memory alloy actuator: an experimental study [Paper presentation]. The Bi-Annual International Conference on Experimental Solid Mechanics-X-Mech.

RAPPEL, H., & Yousefi-Koma, A. (07 May 2013). Fundamental asymmetric lamb wave ( a0 ) interaction with rectangular notch using elastodynamic finite integration technique (EFIT) [Paper presentation]. 21st Annual International Conference on Mechanical Engineering-ISME 2013.

RAPPEL, H., & Haeri Yazdi, M. R. (23 February 2012). Design of a model predictive controller for welding robot under impact loading [Poster presentation]. 3rd National Manufacturing Engineering Conference (NMEC).

RAPPEL, H., BEEX, L., HALE, J., & BORDAS, S. (n.d.). Bayesian inference for the stochastic identification of elastoplastic material parameters: Introduction, misconceptions and insights. (v4). ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/28631.

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