Full list


2023

  • H. Turbé,   M. Bjelogrlic,   C. Lovis,   G. Mengaldo ,   Evaluation of post-hoc interpretability methods in time-series classification,   Nature Machine Intelligence.

  • A. Gualandi,   D. Faranda,   C. Marone,   M. Cocco,   G. Mengaldo ,   Deterministic and stochastic chaos characterize laboratory earthquakes,   Earth and Planetary Science Letters.


  • 2022

  • A. Lario,   R. Maulik,   O. T. Schmidt,   G. Rozza,   G. Mengaldo ,   Neural-network learning of SPOD latent dynamics,   Journal of Computational Physics.

  • R. Maulik,   V. Rao,   J. Wang,   G. Mengaldo ,   E. Constantinescu,   B. Lusch,   P. Balaprakash,   I. Foster,   R. Kotamarthi,   Efficient high-dimensional variational data assimilation with machine-learned reduced-order models,   Geoscientific Model Development.

  • M. W. Hess,   A. Lario,   G. Mengaldo ,   G. Rozza,   Reduced order modeling for spectral element methods: current developments in Nektar++ and further perspectives,   arXiv preprint arXiv:2201.05404.

  • G. Mengaldo ,   F. Renda,   S. L. Brunton,   M. Bächer,   M. Calisti,   C. Duriez,   G. S. Chirikjian,   C. Laschi,   A concise guide to modelling the physics of embodied intelligence in soft robotics,   Nature Reviews Physics.

  • R. C. Moura,   A. F. C. Silva,   G. Mengaldo ,   S. J. Sherwin,   Spectral/hp element methods' linear mechanism of (apparent) energy transfer in Fourier space: Insights into dispersion analysis for implicit LES,   Journal of Computational Physics.


  • 2021

  • G. Mengaldo ,   R. Maulik,   Pyspod: A python package for spectral proper orthogonal decomposition (spod),   Journal of Open Source Software.

  • R. Maulik,   G. Mengaldo ,   PyParSVD: A streaming, distributed and randomized singular-value-decomposition library,   2021 7th International Workshop on Data Analysis and Reduction for Big Scientific Data (DRBSD-7).

  • N. Tonicello,   R. C. Moura,   G. Lodato,   G. Mengaldo ,   Fully-discrete spatial eigenanalysis of discontinuous spectral element methods: insights into well-resolved and under-resolved vortical flows,   arXiv preprint arXiv:2111.13891.

  • G. Mengaldo ,   D. Moxey,   M. Turner,   R. C. Moura,   A. Jassim,   M. Taylor,   J. Peiró,   and S. J. Sherwin,   Industry-Relevant Implicit Large-Eddy Simulation of a High-Performance Road Car via Spectral/hp Element Methods,   SIAM Review.


  • 2020

  • D. Moxey,   C. D. Cantwell,   Y. Bao,   A. Cassinelli,   G. Castiglioni,   S. Chun,   E. Juda,   E. Kazemi,   K. Lackhove,   J. Marcon,   G. Mengaldo ,   D. Serson,   M. Turner,   H. Xu,   J. Peiró,   R. M. Kirby,   S. J. Sherwin;,   Nektar++: Enhancing the capability and application of high-fidelity spectral/hp element methods,   Computer Physics Communications.

  • B. Dorschner,   K. Yu,   G. Mengaldo ,   T. Colonius,   A fast multi-resolution lattice Green's function method for elliptic difference equations,   Journal of Computational Physics.

  • R. C. Moura,   P. Fernandez,   G. Mengaldo ,   S. J. Sherwin,   Viscous diffusion effects in the eigenanalysis of (hybridisable) DG methods,   Spectral and High Order Methods for Partial Differential Equations ICOSAHOM 2018.


  • 2019

  • P. Fernandez,   R. C. Moura,   G. Mengaldo ,   J. Peraire,   Non-modal analysis of spectral element methods: Towards accurate and robust large-eddy simulations,   Computer Methods in Applied Mechanics and Engineering.

  • O. T. Schmidt,   G. Mengaldo ,   G. Balsamo,   N. P. Wedi,   Spectral empirical orthogonal function analysis of weather and climate data,   Monthly Weather Review.

  • G. Mengaldo ,   Batch 1: definition of several weather & climate dwarfs,   arXiv preprint arXiv:1908.06089.

  • A. Müller,   W. Deconinck,   C. Kühnlein,   G. Mengaldo ,   M. Lange,   N. P. Wedi,   P. Bauer,   P. K. Smolarkiewicz,   M. Diamantakis,   S.-J. Lock,   The ESCAPE project: energy-efficient scalable algorithms for weather prediction at exascale,   Geoscientific Model Development.


  • 2018

  • G. Mengaldo ,   R.C. Moura,   B. Giralda,   J. Peiró,   S. J. Sherwin,   Spatial eigensolution analysis of discontinuous Galerkin schemes with practical insights for under-resolved computations and implicit LES,   Computers & Fluids.

  • A. R. Winters,   R. C. Moura,   G. Mengaldo ,   G. J. Gassner,   S. Walch,   J. Peiro,   S. J. Sherwin,   A comparative study on polynomial dealiasing and split form discontinuous Galerkin schemes for under-resolved turbulence computations,   Journal of Computational Physics.

  • G. Mengaldo ,   A. A. Wyszogrodzki,   M. Diamantakis,   S.-J. Lock,   F. X. Giraldo,   N. P. Wedi,   Current and emerging time-integration strategies in global numerical weather and climate prediction,   Archives of Computational Methods in Engineering.

  • G. Mengaldo ,   D. De Grazia,   R. C. Moura,   S. J. Sherwin,   Spatial eigensolution analysis of energy-stable flux reconstruction schemes and influence of the numerical flux on accuracy and robustness,   Journal of Computational Physics.


  • 2017

  • R. C. Moura,   G. Mengaldo ,   J. Peiró,   S. J. Sherwin,   On the eddy-resolving capability of high-order discontinuous Galerkin approaches to implicit LES/under-resolved DNS of Euler turbulence,   Journal of Computational Physics.

  • R. C. Moura,   G. Mengaldo ,   J. Peiró,   S. J. Sherwin,   An LES setting for DG-based implicit LES with insights on dissipation and robustness,   Spectral and High Order Methods for Partial Differential Equations ICOSAHOM 2016.

  • G. Mengaldo ,   S. Liska,   K. Yu,   T. Colonius,   T. Jardin,   Immersed boundary lattice Green function methods for external aerodynamics,   23rd AIAA Computational Fluid Dynamics Conference.

  • W. Deconinck,   P. Bauer,   M. Diamantakis,   M. Hamrud,   C. Kühnlein,   P. Maciel,   G. Mengaldo ,   T. Quintino,   B. Raoult,   P. K. Smolarkiewicz,   Atlas: A library for numerical weather prediction and climate modelling,   Computer Physics Communications.

  • D. Moxey,   C. D. Cantwell,   G. Mengaldo ,   D. Serson,   D. Ekelschot,   J. Peiró,   S. J. Sherwin,   R. M. Kirby,   Towards p-adaptive spectral/hp element methods for modelling industrial flows,   Spectral and High Order Methods for Partial Differential Equations ICOSAHOM 2016.


  • 2016

  • G. Mengaldo ,   D. De Grazia,   P. E. Vincent,   S. J. Sherwin,   On the connections between discontinuous Galerkin and flux reconstruction schemes: extension to curvilinear meshes,   Journal of Scientific Computing.


  • 2015

  • C. D. Cantwell,   D. Moxey,   A. Comerford,   A. Bolis,   G. Rocco,   G. Mengaldo ,   D. De Grazia,   S. Yakovlev,   J.-E. Lombard,   D. Ekelschot,   B. Jordi,   H. Xu,   Y. Mohamied,   C. Eskilsson,   B. Nelson,   P. Vos,   C. Biotto,   R. M. Kirby,   S. J. Sherwin;,   Nektar++: An open-source spectral/hp element framework,   Computer Physics Communications.

  • G. Mengaldo ,   M. Kravtsova,   A. I. Ruban,   S. J. Sherwin,   Triple-deck and direct numerical simulation analyses of high-speed subsonic flows past a roughness element,   Journal of Fluid Mechanics.

  • G. Mengaldo ,   D. De Grazia,   D. Moxey,   P. E. Vincent,   S. J. Sherwin,   Dealiasing techniques for high-order spectral element methods on regular and irregular grids,   Journal of Computational Physics.


  • 2014

  • D. De Grazia,   G. Mengaldo ,   D. Moxey,   P. E. Vincent,   S. J. Sherwin,   Connections between the discontinuous Galerkin method and high‐order flux reconstruction schemes,   International Journal for Numerical Methods in Fluids.

  • G. Mengaldo ,   D. De Grazia,   J. Peiro,   A. Farrington,   F. Witherden,   P. E. Vincent,   S. J. Sherwin,   A Guide to the Implementation of Boundary Conditions in Compact High-Order Methods for Compressible Aerodynamics,   AIAA Aviation 2014.




  • PhD Thesis


    2015

  • G. Mengaldo,   Discontinuous spectral/hp element methods: development, analysis and applications to compressible flows.