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prof. dr. D.T. (Daan) Crommelin

Faculty of Science
Korteweg-de Vries Instituut
Photographer: Dirk Gillissen

Visiting address
  • Science Park 107
  • Room number: C3.134
Postal address
  • Postbus 94248
    1090 GE Amsterdam
  • Publications

    2019

    2018

    • Bhaumik, D., Crommelin, D., & Zwart, B. (2018). Mitigation of large power spills by an energy storage device in a stand alone energy system. Journal of Energy Storage, 16, 76-83. https://doi.org/10.1016/j.est.2017.12.012 [details]
    • Bisewski, K., Crommelin, D., & Mandjes, M. (2018). Controlling the time discretization bias for the supremum of brownian motion. ACM Transactions on Modeling and Computer Simulation, 28(3), [24]. https://doi.org/10.1145/3177775 [details]
    • Bisewski, K., Crommelin, D., & Mandjes, M. (2018). Simulation-based assessment of the stationary tail distribution of a stochastic differential equation. In M. Rabe, A. A. Juan, N. Mustafee, A. Skoogh, S. Jain, & B. Johansson (Eds.), WSC'18: proceedings of the 2018 Winter Simulation Conference, December 9-12, 2018, Gothenburg, Sweden : Simulation for a noble cause (pp. 1742-1753). (Proceedings of the Winter Simulation Conference; Vol. 2018). Piscataway, NJ: IEEE. https://doi.org/10.1109/WSC.2018.8632197 [details]
    • Crommelin, D. (2018). Cellular Automata for Clouds and Convection. In P-Y. Louis, & F. R. Nardi (Eds.), Probabilistic Cellular Automata: Theory, Applications and Future Perspectives (pp. 327-339). (Emergence, Complexity and Computation; Vol. 27). Cham: Springer. https://doi.org/10.1007/978-3-319-65558-1_20 [details]
    • Eggels, A. W., & Crommelin, D. T. (2018). Uncertainty Quantification with dependent inputs: wind and waves. In R. Owen, R. de Borst, J. Reese, & C. Pearce (Eds.), Proceedings of the 6th. European Conference on Computational Mechanics (Solids, Structures and Coupled Problems ECCM 6, 7th. European Conference on Computational Fluid Dynamics ECFD 7, Glasgow, Scotland, UK, June 11-15, 2018 (pp. 4099-4110). Barcelona: International Center for Numerical Methods in Engineering. [details]
    • Eggels, A. W., Crommelin, D. T., & Witteveen, J. A. S. (2018). Clustering-based collocation for uncertainty propagation with multivariate dependent inputs. International Journal for Uncertainty Quantification, 8(1), 43-59. https://doi.org/10.1615/Int.J.UncertaintyQuantification.2018020215 [details]

    2017

    • Berner, J., Achatz, U., Batté, L., Bengtsson, L., de la Cámara, A., Christensen, H. M., ... Yano, J-I. (2017). Stochastic Parameterization: Toward a New View of Weather and Climate Models. Bulletin of the American Meteorological Society, 98(3), 565-587. https://doi.org/10.1175/BAMS-D-15-00268.1 [details]
    • Gottwald, G. A., Crommelin, D. T., & Franzke, C. L. E. (2017). Stochastic climate theory. In C. L. E. Franzke, & T. J. O'Kane (Eds.), Nonlinear and Stochastic Climate Dynamics (pp. 209-240). Cambridge: Cambridge University Press. [details]
    • Verheul, N., Viebahn, J., & Crommelin, D. (2017). Covariate-based stochastic parameterization of baroclinic ocean eddies. Mathematics of Climate and Weather Forecasting, 3(1), 90-117. https://doi.org/10.1515/mcwf-2017-0005 [details]

    2016

    • Bhaumik, D., Crommelin, D., & Zwart, B. (2016). A computational method for optimizing storage placement to maximize power network reliability. In T. M. K. Roeder, P. I. Frazier, R. Szechtman, E. Zhou, T. Huschka, & S. E. Chick (Eds.), WSC'16 : Winter Simulation Conference: simulating complex service systems : Crystal Gateway Marriott, Arlington, VA, December 11-14, 2016 (pp. 883-894). Piscataway, NJ: IEEE. https://doi.org/10.1109/WSC.2016.7822150 [details]
    • Dorrestijn, J., Crommelin, D. T., Siebesma, A. P., Jonker, H. J. J., & Selten, F. (2016). Stochastic Convection Parameterization with Markov Chains in an Intermediate-Complexity GCM. Journal of the Atmospheric Sciences, 73(3), 1367-1382. https://doi.org/10.1175/JAS-D-15-0244.1 [details]
    • Verheul, N., & Crommelin, D. (2016). Data-driven stochastic representations of unresolved features in multiscale models. Communications in Mathematical Sciences, 14(5), 1213 – 1236. https://doi.org/10.4310/CMS.2016.v14.n5.a2

    2015

    • Crommelin, D., & Khouider, B. (2015). Stochastic and Statistical Methods in Climate, Atmosphere, and Ocean Science. In B. Engquist (Ed.), Encyclopedia of Applied and Computational Mathematics (pp. 1377-1386). Heidelberg: Springer Reference. https://doi.org/10.1007/978-3-540-70529-1_565 [details]

    2014

    • Thompson, W. F., Monahan, A. H., & Crommelin, D. (2014). Parametric Estimation of the Stochastic Dynamics of Sea Surface Winds. Journal of the Atmospheric Sciences, 71(9), 3465-3483. https://doi.org/10.1175/JAS-D-13-0260.1 [details]
    • Wadman, W., Crommelin, D., & Frank, J. (2014). A separated splitting technique for disconnected rare event sets. In A. Tolk, S. Y. Diallo, I. O. Ryzhov, L. Yilmaz, S. Buckley, & J. A. Miller (Eds.), Proceedings of the 2014 Winter Simulation Conference: exploring big data through simulation: December 7-10, 2014, Westin Savannah Harbor Resort, Savannah, GA (pp. 522-532). Piscataway, NJ: IEEE. https://doi.org/10.1109/WSC.2014.7019917 [details]

    2013

    • Wadman, W., Bloemhof, G., Crommelin, D., & Frank, J. (2013). Probablistic Power Flow Simulations Allowing Temporary Current Overloading. In A. Ozdemir (Ed.), Proceedings of the 12th International Conference on Probabilistic Methods Applied to Power Systems (PMAPS 2012), 10-14th June 2012, Istanbul, Turkey (pp. 494-499). Istanbul: PAMPS. [details]

    Journal editor

    • Crommelin, D. T. (editor) (2014-2018). Multiscale Modeling & Simulation (Journal).
    This list of publications is extracted from the UvA-Current Research Information System. Questions? Ask the library or the Pure staff of your faculty / institute. Log in to Pure to edit your publications. Log in to Personal Page Publication Selection tool to manage the visibility of your publications on this list.
  • Ancillary activities
    • Centrum voor Wiskunde & Informatica
      Medewerker CWI