World's Best Scientists 2026 revealed!

D-Index & Metrics

Mechanical and Aerospace Engineering

D-Index
51
Citations
9333
World Ranking
1118
National Ranking
452

Overview

Matthias Ihme is affiliated with Stanford University in the United States and contributes extensively to research in engineering, particularly within computational mechanics and related disciplines. Their work focuses strongly on areas involving combustion processes, fluid dynamics, and thermodynamics.

Their main fields of study include:

  • Engineering

Within this broad area, their subfields of study encompass:

  • Computational Mechanics
  • Biomedical Engineering
  • Fluid Flow and Transfer Processes
  • Aerospace Engineering
  • Global and Planetary Change

The core topics in Matthias Ihme's research cover:

  • Combustion and flame dynamics
  • Advanced Combustion Engine Technologies
  • Phase Equilibria and Thermodynamics
  • Computational Fluid Dynamics and Aerodynamics
  • Combustion and Detonation Processes
  • Fire effects on ecosystems
  • Gas Dynamics and Kinetic Theory

The scientist has published numerous papers in frequent collaboration with colleagues including Wai Tong Chung, Davy Brouzet, Guillaume Vignat, Émeric Boigné, and Nguyen Ly.

They have contributed to a variety of publications, often appearing in venues such as:

  • Proceedings of the Combustion Institute
  • Combustion and Flame
  • arXiv (Cornell University)
  • SSRN Electronic Journal
  • Journal of Computational Physics

Selected recent papers authored or co-authored by Matthias Ihme include:

  • Combustion machine learning: Principles, progress and prospects (2022), published in Progress in Energy and Combustion Science
  • A Review of Physics-Informed Machine Learning in Fluid Mechanics (2023), published in Energies
  • Next Day Wildfire Spread: A Machine Learning Dataset to Predict Wildfire Spreading From Remote-Sensing Data (2022), published in IEEE Transactions on Geoscience and Remote Sensing
  • Chemical and Reactive Transport Processes Associated with Hydraulic Fracturing of Unconventional Oil/Gas Shales (2022), published in Chemical Reviews
  • Between supercritical liquids and gases - Reconciling dynamic and thermodynamic state transitions (2020), published in The Journal of Supercritical Fluids

Best Publications

  • Modeling of radiation and nitric oxide formation in turbulent nonpremixed flames using a flamelet/progress variable formulation

    Matthias Ihme;Heinz Pitsch

  • Prediction of local extinction and re-ignition effects in non-premixed turbulent combustion using a flamelet/progress variable approach

    Matthias Ihme;Chong M. Cha;Heinz Pitsch

  • Prediction of extinction and reignition in nonpremixed turbulent flames using a flamelet/progress variable model. 2. Application in LES of Sandia flames D and E

    Matthias Ihme;Heinz Pitsch

  • Combustion machine learning: Principles, progress and prospects

    Unknown

  • Prediction of autoignition in a lifted methane/air flame using an unsteady flamelet/progress variable model

    Matthias Ihme;Yee Chee See

  • Prediction of extinction and reignition in nonpremixed turbulent flames using a flamelet/progress variable model: 1. A priori study and presumed PDF closure

    Matthias Ihme;Heinz Pitsch

  • LES flamelet modeling of a three-stream MILD combustor: Analysis of flame sensitivity to scalar inflow conditions

    Matthias Ihme;Yee Chee See

  • Short Note: Regularization of reaction progress variable for application to flamelet-based combustion models

    Matthias Ihme;Lee Shunn;Jian Zhang

  • An entropy-stable hybrid scheme for simulations of transcritical real-fluid flows

    Peter C. Ma;Yu Lv;Matthias Ihme

  • Optimal artificial neural networks and tabulation methods for chemistry representation in LES of a bluff-body swirl-stabilized flame

    Matthias Ihme;Christoph Schmitt;Heinz Pitsch

  • Fuel effects on lean blow-out in a realistic gas turbine combustor

    Lucas Esclapez;Peter C. Ma;Eric Mayhew;Rui Xu

  • A Review of Physics-Informed Machine Learning in Fluid Mechanics

    Unknown

  • Combustion and Engine-Core Noise

    Matthias Ihme

  • Large-Eddy Simulation of a Jet-in-Hot-Coflow Burner Operating in the Oxygen-Diluted Combustion Regime

    Matthias Ihme;Jian Zhang;Jian Zhang;Guowei He;Bassam Dally

  • Chemical and Reactive Transport Processes Associated with Hydraulic Fracturing of Unconventional Oil/Gas Shales.

    Unknown

  • Discontinuous Galerkin method for multicomponent chemically reacting flows and combustion

    Yu Lv;Matthias Ihme

  • Ignition regimes in rapid compression machines

    Kevin P. Grogan;S. Scott Goldsborough;Matthias Ihme

  • An Unsteady/Flamelet Progress Variable Method for LES of Nonpremixed Turbulent Combustion

    Heinz Pitsch;Matthias Ihme

  • Compositional inhomogeneities as a source of indirect combustion noise

    Luca Magri;Jeff O’Brien;Matthias Ihme

  • Widom Lines in Binary Mixtures of Supercritical Fluids

    Muralikrishna Raju;Daniel T. Banuti;Peter C. Ma;Matthias Ihme

  • Reduced-order modeling of turbulent reacting flows with application to ramjets and scramjets

    Sean M. Torrez;James F. Driscoll;Matthias Ihme;Matthew L. Fotia

  • Analysis of segregation and bifurcation in turbulent spray flames: A 3D counterflow configuration

    Aymeric Vié;Benedetta Franzelli;Yang Gao;Tianfeng Lu

  • Weak and strong ignition of hydrogen/oxygen mixtures in shock-tube systems

    Kevin P. Grogan;Matthias Ihme

Frequent Co-Authors

Heinz Pitsch
Heinz Pitsch RWTH Aachen University
James F. Driscoll
James F. Driscoll University of Michigan–Ann Arbor
Jacqueline H. Chen
Jacqueline H. Chen Sandia National Laboratories
Ralf Deiterding
Ralf Deiterding University of Southampton
Matthew P. Juniper
Matthew P. Juniper University of Cambridge
Christian Hasse
Christian Hasse Technical University of Darmstadt
Hai Wang
Hai Wang Stanford University
Rebecca Fahrig
Rebecca Fahrig Siemens Healthcare (United States)
Jonathan H. Frank
Jonathan H. Frank Sandia National Laboratories
Parviz Moin
Parviz Moin Stanford University

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