Publications and communications of Maarten Arnst

Tomasetti, R., & Arnst, M. (16 June 2025). Graph Abstraction for Efficient Scheduling of Asynchronous Workloads on GPU [Poster presentation]. PASC25, Windisch, Switzerland.

Gregov, T., Pattyn, F., & Arnst, M. (01 May 2025). Sensitivity of grounding-line migration to ice-shelf pinning [Poster presentation]. EGU General Assembly 2025, Vienna, Austria. doi:10.5194/egusphere-egu25-11628

Arnst, M., & Tomasetti, R. (07 March 2024). Design Patterns and Performance Analysis of Polymorphism in Multiphysics FE Assembly on GPU [Paper presentation]. SIAM Conference on Parallel Processing for Scientific Computing (PP24), Baltimore, United States.

Tomasetti, R., & Arnst, M. (07 March 2024). Efficiently implementing FE boundary conditions using stream-orchestrated execution on GPU [Paper presentation]. SIAM Conference on Parallel Computing for Scientific Computing (PP24), Baltimore, United States.

Gregov, T., Pattyn, F., & Arnst, M. (10 November 2023). Grounding-line flux conditions for marine ice-sheet systems under effective-pressure-dependent and hybrid friction laws. Journal of Fluid Mechanics, 975. doi:10.1017/jfm.2023.760

Delhez, C., Rivière, N., Erpicum, S., Pirotton, M., Archambeau, P., Arnst, M., Bierens, J., & Dewals, B. (2023). Drift of a drowning victim in rivers: conceptualization and global sensitivity analysis under idealized flow conditions. Water Resources Research. doi:10.1029/2022WR034358

Schmitz, V., Arnst, M., El kadi Abderrezzak, K., Pirotton, M., Erpicum, S., Archambeau, P., & Dewals, B. (2023). Global sensitivity analysis of a dam breaching model: To which extent is parameter sensitivity case-dependent? Water Resources Research. doi:10.1029/2022WR033894

Gregov, T., Pattyn, F., & Arnst, M. (24 April 2023). Investigation of numerical continuation methods for marine ice-sheet systems formulated as contact problems [Poster presentation]. EGU General Assembly 2023, Vienne, Austria. doi:10.5194/egusphere-egu23-8932

Coheur, J., Magin, T., Chatelain, P., & Arnst, M. (2023). Bayesian identification of pyrolysis model parameters for thermal protection materials using an adaptive gradient-informed sampling algorithm with application to a Mars atmospheric entry. International Journal for Uncertainty Quantification, 13 (2), 53-80. doi:10.1615/int.j.uncertaintyquantification.2022042928

Gregov, T., Pattyn, F., & Arnst, M. (01 September 2022). Numerical continuation methods for marine ice-sheet systems with various friction laws [Paper presentation]. ACOMEN 2022, Liège, Belgium.

Budo, A., Bartholet Jules, Hillewaert, K., Arnst, M., & Terrapon, V. (02 August 2022). Geometrical variability in a through-flow model: manufacturing tolerance effects on compressor blades [Paper presentation]. ACOMEN 2022.

Gregov, T., Pattyn, F., & Arnst, M. (09 June 2022). A primal-dual formulation for numerical simulations of marine ice sheets with various friction laws [Paper presentation]. ECCOMAS Congress 2022, Oslo, Norway.

Gregov, T., Pattyn, F., & Arnst, M. (24 May 2022). Extension of marine ice-sheet flux conditions to effective-pressure-dependent and hybrid friction laws [Paper presentation]. EGU General Assembly 2022, Vienne, Austria. doi:10.5194/egusphere-egu22-10208

Denoël, V.* , Bruyère, O.* , Louppe, G., Bureau, F., D'ORIO, V., Fontaine, S., Gillet, L., Guillaume, M., Haubruge, E., Lange, A.-C., Michel, F., Hulle, R. V., Arnst, M., Donneau, A.-F.* , & Saegerman, C.*. (04 March 2022). Decision-based interactive model to determine re-opening conditions of a large university campus in Belgium during the first COVID-19 wave. Archives of Public Health, 80 (1). doi:10.1186/s13690-022-00801-w

Schmitz, V., Arnst, M., El Kadi Abderrezzak, K., Pirotton, M., Erpicum, S., Archambeau, P., & Dewals, B. (2022). Uncertainty analysis of a lumped physically based numerical model of dam breaching. In Proceedings of the 39th IAHR World Congress. International Association for Hydro-Environment Engineering and Research (IAHR). doi:10.3850/IAHR-39WC2521716X2022466

Budo, A., Mouriaux Sophie, Bartholet Jules, Arnst, M., & Terrapon, V. (14 October 2021). Geometric uncertainties in through-flow model [Paper presentation]. Journées des doctorants Safran (JDD HAIDA).

Coheur, J., Torres-Herrador, F., Chatelain, P., Mansour, N., Magin, T., & Arnst, M. (2021). Analytical solution for multi-component pyrolysis simulations of thermal protection materials. Journal of Materials Science. doi:10.1007/s10853-020-05727-8

Torres-Herrador, F.* , Coheur, J.* , Panerai, F., Magin, T., Arnst, M., Mansour, N., & Blondeau, J. (2020). Competitive kinetic model for the pyrolysis of the Phenolic Impregnated Carbon Ablator. Aerospace Science and Technology. doi:10.1016/j.ast.2020.105784

Arnst, M. (2020). Elements of stochastic processes 2019-2020: course material.

Bulthuis, K., Pattyn, F., & Arnst, M. (25 June 2019). Estimation of confidence regions for random excursion sets with application to large-scale ice-sheet simulations [Paper presentation]. UNCECOMP 2019: 3rd International Conference on Uncertainty Quantification in Computational Sciences and Engineering, Hersonissos, Greece.

Liegeois, K., Boman, R., Phipps, E., Mertens, P., Krasikov, Y., & Arnst, M. (25 June 2019). Ensemble propagation for efficient uncertainty quantification: Application to the thermomechanical modeling of a first mirror for the ITER core CXRS diagnostics [Paper presentation]. UNCECOMP 2019 / 3rd International Conference on Uncertainty Quantification in Computational Sciences and Engineering.

Liegeois, K., Boman, R., Phipps, E., & Arnst, M. (25 April 2019). Efficient parametric computations using ensemble propagation for high dimensional finite element models [Paper presentation]. CÉCI Scientific Meeting.

Bulthuis, K., Arnst, M., Sun, S., & Pattyn, F. (24 April 2019). Uncertainty quantification of the multi-centennial response of the Antarctic Ice Sheet to climate change. The Cryosphere, 13, 1349-1380. doi:10.5194/tc-13-1349-2019

Bulthuis, K., Arnst, M., Sainan, S., & Pattyn, F. (11 March 2019). Uncertainty Quantification of the Multi-centennial Response of the Antarctic Ice Sheet to climate change [Paper presentation]. SIAM Conference on Mathematical & Computational Issues in the Geosciences (GS19), Houston, United States.

Liegeois, K., Boman, R., Phipps, E., & Arnst, M. (28 February 2019). Ensemble Propagation for Efficient Uncertainty Quantification of Mechanical Contact Problems [Paper presentation]. SIAM Conference on Computational Science and Engineering.

Liegeois, K., Boman, R., Phipps, E., Wiesner, T., & Arnst, M. (17 April 2018). On the Ensemble Propagation for Efficient Uncertainty Quantification of Mechanical Contact Problems [Paper presentation]. SIAM Conference on Uncertainty Quanti cation 2018.

Bulthuis, K., Arnst, M., Pattyn, F., & Favier, L. (16 April 2018). Stochastic Modeling of Uncertainties in Fast Essential Antarctic Ice Sheet Models [Paper presentation]. SIAM Conference on Uncertainty Quantification 2018, Garden Grove (Los Angeles), United States - California.

Coheur, J., Magin, T., Chatelain, P., & Arnst, M. (April 2018). Bayesian Inference on Uncertain Kinetic Parameters for the Pyrolysis of Composite Ablators [Paper presentation]. SIAM Conference on Uncertainty Quantification (UQ18), Los Angeles, United States.

Hoang Truong, V., Wu, L., Golinval, J.-C., Arnst, M., & Noels, L. (April 2018). Stochastic multiscale model of MEMS stiction accounting for high order statistical moments of non-Gaussian contacting surfaces. Journal of Microelectromechanical Systems, 27 (2), 137-155. doi:10.1109/JMEMS.2018.2797133

Bulthuis, K., Arnst, M., & Pattyn, F. (2017). Modelling ice flow for large-scale ice-sheet simulations.

Arnst, M. (August 2017). Guiding model improvement in dynamic substructuring: sensitivity analysis and nonparametric probabilistic modeling approach [Paper presentation]. ICOSSAR 2017 International Conference on Structural Safety & Reliability.

Liegeois, K., Boman, R., Mertens, P., Panin, A., Phipps, E., & Arnst, M. (19 July 2017). Ensemble propagation for efficient uncertainty quantification on emerging architectures: Application to thermomechanical contact [Poster presentation]. Quantification of Uncertainty: Improving Efficiency and Technology, Trieste, Italy.

Hoang Truong, V., Wu, L., Paquay, S., Golinval, J.-C., Arnst, M., & Noels, L. (June 2017). A computational stochastic multiscale methodology for MEMS structures involving adhesive contact. Tribology International, 110, 401-425. doi:10.1016/j.triboint.2016.10.007

Bulthuis, K., Arnst, M., Pattyn, F., & Favier, L. (April 2017). Uncertainty quantification of Antarctic contribution to sea-level rise using the fast Elementary Thermomechanical Ice Sheet (f.ETISh) model [Paper presentation]. European Geosciences Union General Assembly 2017, Vienna, Austria.

Coheur, J., Arnst, M., Chatelain, P., & Magin, T. (01 March 2017). Uncertainty Quantification of Aerothermal Flow Simulation Through Low-Density Ablative Thermal Protection Materials [Poster presentation]. 8th VKI PhD Symposium, Rhode-Saint-Genèse, Belgium.

Bulthuis, K., Arnst, M., Pattyn, F., & Favier, L. (05 September 2016). Instability and abrupt changes in marine ice sheet behaviour [Paper presentation]. 1st CRITICS Workshop and Summer School on Critical Transitions in Complex Systems, Kulhuse, Denmark.

Arnst, M. (09 June 2016). Sensitivity analysis of parametric uncertainties and modeling errors in generalized probabilistic modeling [Paper presentation]. ECCOMAS European Congress on Computational Methods in Applied Sciences and Engineering.

Arnst, M., Liegeois, K., Boman, R., & Ponthot, J.-P. (18 May 2016). Comparison of interval and stochastic methods for uncertainty quantification in metal forming [Paper presentation]. ICOMP International Conference on COmputational methods in Manufacturing Processes.

Arnst, M., Abello Álvarez, B., Boman, R., & Ponthot, J.-P. (26 May 2015). Parametric uncertainty quantification in the presence of modeling errors: Bayesian approach and application to metal [Paper presentation]. UNCECOMP International Conference on Uncertainty Quantification in Computational Sciences and Engineering, Crète, Greece.

Arnst, M. (May 2015). Nonintrusive probabilistic quantification of uncertainties with application to the management of manufacturing tolerances [Paper presentation]. IE-net Managing, handling, and modeling uncertainty in mechanical design.

Lucas, V., Wu, L., Arnst, M., Golinval, J.-C., Paquay, S., & Noels, L. (27 August 2014). Prediction of meso-scale mechanical properties of poly-silicon materials [Paper presentation]. EMMC14 - European Mechanics of Materials Conference 2014, Gothenburg, Sweden.

Hoang Truong, V., Wu, L., Arnst, M., Golinval, J.-C., Muller, R., Voicu, R., & Noels, L. (26 June 2014). A probabilistic model of the adhesive contact forces between rough surfaces in the MEMS stiction context [Paper presentation]. 6th International Conference on Advanced Computational Methods in Engineering, ACOMEN 2014, Ghent, Belgium.

Lucas, V., Wu, L., Arnst, M., Golinval, J.-C., Paquay, S., Nguyen, V. D., & Noels, L. (2014). Prediction of macroscopic mechanical properties of a polycrystalline microbeam subjected to material uncertainties. In Á. Cunha, E. Caetano, P. Ribeiro, ... G. Muller (Eds.), Proceedings of the 9th International Conference on Structural Dynamics, EURODYN 2014 (pp. 2691-2698).

Arnst, M. (31 March 2014). UQ Benchmark Problems for Multiphysics Modeling [Paper presentation]. SIAM Conference on Uncertainty Quantification, Savannah, Georgia, United States.

Arnst, M., & Ponthot, J.-P. (2014). An overview of nonintrusive characterization, propagation, and sensitivity analysis of uncertainties in computational mechanics. International Journal for Uncertainty Quantification, 4, 387-421. doi:10.1615/Int.J.UncertaintyQuantification.2014006990

Lucas, V., Wu, L., Arnst, M., Golinval, J.-C., Paquay, S., & Noels, L. (December 2013). Probabilistic model for MEMS micro-beam resonance frequency made of polycrystalline linear anisotropic material [Paper presentation]. 5th Asia Pacific Congress on Computational Mechanics & 4th International Synposium on Computational Mechanics APCOM & ISCM 2013, Singapore, Singapore.

Arnst, M. (2007). Inversion of probabilistic models of structures using measured transfer functions [Doctoral thesis, Ecole Centrale Paris]. ORBi-University of Liège. https://orbi.uliege.be/handle/2268/103160