Peter J. Schmid

According to our database, Peter J. Schmid authored at least 20 papers between 1993 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

An adaptive learning strategy for surrogate modeling of high-dimensional functions - Application to unsteady hypersonic flows in chemical nonequilibrium.

Clément Scherding, Georgios Rigas, Denis Sipp, Peter J. Schmid, Taraneh Sayadi

Comput. Phys. Commun., 2025

Sliding plane formalism for aeroacoustic and adjoint-based sensitivity calculations.

Anton Glazkov, Miguel Fosas de Pando, Peter J. Schmid, Li He

Comput. Phys. Commun., 2025

2024

A robust computational framework for variational data assimilation of mean flows with sparse measurements corrupted by strong outliers.

Souvik Ghosh, Vincent Mons, Denis Sipp, Peter J. Schmid

J. Comput. Phys., 2024

2023

RONAALP: Reduced-Order Nonlinear Approximation with Active Learning Procedure.

Clément Scherding, Georgios Rigas, Denis Sipp, Peter J. Schmid, Taraneh Sayadi

CoRR, 2023

Mori-Zwanzig latent space Koopman closure for nonlinear autoencoder.

Priyam Gupta, Peter J. Schmid, Denis Sipp, Taraneh Sayadi, Georgios Rigas

CoRR, 2023

2022

Parallel-in-time adjoint-based optimization - application to unsteady incompressible flows.

S. Costanzo, Taraneh Sayadi, Miguel Fosas de Pando, Peter J. Schmid, P. Frey

J. Comput. Phys., 2022

Data-driven framework for input/output lookup tables reduction - with application to hypersonic flows in chemical non-equilibrium.

Clément Scherding, Georgios Rigas, Denis Sipp, Peter J. Schmid, Taraneh Sayadi

CoRR, 2022

2021

A parallel-in-time approach for accelerating direct-adjoint studies.

Calum S. Skene, Maximilian F. Eggl, Peter J. Schmid

J. Comput. Phys., 2021

Symmetry-Aware Autoencoders: s-PCA and s-nlPCA.

Simon Kneer, Taraneh Sayadi, Denis Sipp, Peter J. Schmid, Georgios Rigas

CoRR, 2021

2020

Nonlinear model reduction: a comparison between POD-Galerkin and POD-DEIM methods.

Denis Sipp, Miguel Fosas de Pando, Peter J. Schmid

CoRR, 2020

2018

A gradient-based framework for maximizing mixing in binary fluids.

Maximilian F. Eggl, Peter J. Schmid

J. Comput. Phys., 2018

2016

Nonlinear model-order reduction for compressible flow solvers using the Discrete Empirical Interpolation Method.

Miguel Fosas de Pando, Peter J. Schmid, Denis Sipp

J. Comput. Phys., 2016

2013

Erratum: Hybrid Reduced-Order Integration with Proper Orthogonal Decomposition and Dynamic Mode Decomposition.

Matthew O. Williams, Peter J. Schmid, J. Nathan Kutz

Multiscale Model. Simul., 2013

Hybrid Reduced-Order Integration with Proper Orthogonal Decomposition and Dynamic Mode Decomposition.

Matthew O. Williams, Peter J. Schmid, J. Nathan Kutz

Multiscale Model. Simul., 2013

2012

Efficient evaluation of the direct and adjoint linearized dynamics from compressible flow solvers.

Miguel Fosas de Pando, Denis Sipp, Peter J. Schmid

J. Comput. Phys., 2012

A relaxation method for large eigenvalue problems, with an application to flow stability analysis.

Xavier Garnaud, Lutz Lesshafft, Peter J. Schmid, J.-M. Chomaz

J. Comput. Phys., 2012

Adjoint algorithms for the Navier-Stokes equations in the low Mach number limit.

Gary J. Chandler, Matthew P. Juniper, Joseph W. Nichols, Peter J. Schmid

J. Comput. Phys., 2012

2011

Iterative optimization based on an objective functional in frequency-space with application to jet-noise cancellation.

Jan Schulze, Peter J. Schmid, Jörn Sesterhenn

J. Comput. Phys., 2011

2010

A preconditioned Krylov technique for global hydrodynamic stability analysis of large-scale compressible flows.

Christoph J. Mack, Peter J. Schmid

J. Comput. Phys., 2010

1993

Pseudospectra of the Orr-Sommerfeld Operator.

Satish C. Reddy, Peter J. Schmid, Dan S. Henningson

SIAM J. Appl. Math., 1993