About

Aaron Towne is an Associate Professor of Mechanical Engineering at the University of Michigan. His research interests include fluid mechanics, reduced-complexity modeling, data-driven modeling, flow control, and aeroacoustics. He has made significant contributions to the understanding and modeling of turbulent flows, employing resolvent-based estimation techniques for control of turbulent aerodynamic flows. Towne's work has been recognized through several awards, including the NSF CAREER Award for his proposal on scale-dependent reduced-order models for turbulent flows, and the Young Investigator Program award from the Air Force Office of Scientific Research for his research in this area. He has also been involved in projects related to hypersonic boundary layers and the formation of hydrogen gas clumps in supernova remnants. As a faculty member, he joined the University of Michigan in 2018 and is based at the G.G. Brown Laboratory in Ann Arbor, MI.

Research topics

• Computer Science
• Physics
• Mechanics
• Database

Selected publications

• Data-Driven Reduced-Complexity Modeling of Fluid Flows: A Community Challenge

  arXiv (Cornell University) · 2026-01-07

  preprintOpen access

  We introduce a community challenge designed to facilitate direct comparisons between data-driven methods for compression, forecasting, and sensing of complex aerospace flows. The challenge is organized into three tracks that target these complementary capabilities: compression (compact representations for large datasets), forecasting (predicting future flow states from a finite history), and sensing (inferring unmeasured flow states from limited measurements). Across these tracks, multiple challenges span diverse flow datasets and use cases, each emphasizing different model requirements. The challenge is open to anyone, and we invite broad participation to build a comprehensive and balanced picture of what works and where current methods fall short. To support fair comparisons, we provide standardized success metrics, evaluation tools, and baseline implementations, with one classical and one machine-learning baseline per challenge. Final assessments use blind tests on withheld data. We explicitly encourage negative results and careful analyses of limitations. Outcomes will be disseminated through an AIAA Journal Virtual Collection and invited presentations at AIAA conferences.

  PublisherDOI

• Statistical Modeling of Energy Amplification of Inflow Perturbations in Boundary Layer Flows

  2026-01-08

  articleSenior author

  Linear growth of disturbances plays a crucial role in the laminar-to-turbulent transition in boundary layers as well as other wall-bounded flows. Though the linearized Navier-Stokes operator may be stable in such flows, the non-normality of the operator can lead to significant transient growth of disturbances, which can ultimately lead to transition. The importance of this transition mechanism is usually quantified by the maximum energy growth undergone by any disturbance to the boundary layer. Clearly, this is an upper bound for the (linear) transient growth experienced by real disturbances, and a statistical framework that studies the average, rather than extreme, disturbance behavior has recently been proposed. The framework is based on the assumption that disturbances evolve linearly, and it gives an exact relation between the two-point correlation tensor of the incipient disturbances and the turbulent intensity of downstream ones. The primary aims of this work are to implement this framework for a transitional Blasius boundary layer and to conduct a direct numerical simulation (DNS) of the same flow in order to test the predictions of the statistical framework. Applying the framework to spatial transient growth requires the use of a spatial marching method, and we use the one-way Navier-Stokes equations (OWNS). We also develop a reduced-basis technique to approximate formulae in the statistical framework that would otherwise be intractable for this flow. To model the statistics of the free-stream turbulence, the inflow disturbances are prescribed using the von K\'arm\'an energy spectrum. Finally, we present a comparison of the kinetic energy growth obtained from the DNS with that predicted by the statistical framework.

  PublisherDOI

• Data-Driven Reduced-Complexity Modeling of Fluid Flows: A Community Challenge

  ArXiv.org · 2026-01-07

  articleOpen access

  We introduce a community challenge designed to facilitate direct comparisons between data-driven methods for compression, forecasting, and sensing of complex aerospace flows. The challenge is organized into three tracks that target these complementary capabilities: compression (compact representations for large datasets), forecasting (predicting future flow states from a finite history), and sensing (inferring unmeasured flow states from limited measurements). Across these tracks, multiple challenges span diverse flow datasets and use cases, each emphasizing different model requirements. The challenge is open to anyone, and we invite broad participation to build a comprehensive and balanced picture of what works and where current methods fall short. To support fair comparisons, we provide standardized success metrics, evaluation tools, and baseline implementations, with one classical and one machine-learning baseline per challenge. Final assessments use blind tests on withheld data. We explicitly encourage negative results and careful analyses of limitations. Outcomes will be disseminated through an AIAA Journal Virtual Collection and invited presentations at AIAA conferences.

  PublisherOA PDF

• Wave interactions in a screeching jet

  Open MIND · 2026-03-05

  preprintSenior author

  We use a series of global models to investigate the linear and nonlinear interactions between shock cells, Kelvin-Helmholtz waves, guided jet modes, and other fluctuations in a screeching jet. First, we identify a set of lightly damped global eigenmodes of the Navier-Stokes operator linearized about the mean flow and show that they result from interactions with different shock-cell wavenumbers. Second, we use resolvent analysis to study the linear input-output behavior of the jet and obtain a time-periodic representation of the screech mode, which compares favorably with experimental data. Third, we use harmonic resolvent analysis to study triadic interactions, including inter-frequency energy transfer, between the screech mode determined from resolvent analysis and other fluctuations in the jet. The components of the optimal harmonic resolvent mode at harmonics of the screech frequency match experimental observations that have not been previously predicted by global models. Fourth, we leverage a novel bilinear formulation of harmonic resolvent analysis to study the impact of the screech mode's nonlinear self-interaction on other fluctuations in the jet. We show that the forcing provided by this nonlinear self-interaction of the screech mode, along with its triadic interactions with other frequencies embedded within the harmonic resolvent operator, is sufficient to explain the redistribution of energy to other frequencies and the associated experimental observations. In aggregate, these findings underscore the critical role of triadic and nonlinear interactions in shaping screech dynamics and offer a promising workflow for studying similar interactions in other flows dominated by periodic motions.

  DOI

• Resolvent-based estimation of a turbulent wake

  Journal of Fluid Mechanics · 2026-04-16

  articleOpen accessSenior author

  We present a resolvent-based framework for estimating turbulent velocity fluctuations in the wake of a spanwise-periodic NACA0012 airfoil at Mach 0.3, Reynolds number 23 000, and an angle of attack of $6^{\circ }$ . Building on the methodology of Jung et al. (2025, J. Fluid Mech. 1016, A41), we extend the approach to the more complex regime of a turbulent wake, which involves three primary challenges: (i) globally unstable modes in the linearised Navier–Stokes operator, (ii) multi-scale turbulent structures and (iii) high-dimensional datasets. To address these challenges, we employ a data-driven approach that constructs causal resolvent-based estimation kernels from cross-spectral densities obtained via large-eddy simulations. These kernels are derived using the Wiener–Hopf method, which optimally enforces causality, thereby enhancing real-time estimation accuracy. The framework captures the spectral signatures of coherent structures and, through the empirically determined cross-spectral densities, implicitly accounts for the coloured statistics of the nonlinear forcing acting on the linear system. To handle the computational demands of the high-dimensional estimation problem, we utilise parallel algorithms developed within the same framework. We further investigate sensor placement by analysing single-sensor estimation error and coherence with target flow quantities. Results demonstrate accurate causal estimation of streamwise velocity for the spanwise-averaged, spanwise-Fourier-transformed and mid-span flow using limited shear-stress measurements on the surface of the airfoil. This study underscores the potential of the resolvent-based framework for efficient estimation in compressible, turbulent environments.

  PublisherOA PDFDOI

• Toward Resolvent-Based Estimation and Control of Wavepackets in Supersonic Turbulent Jets

  2026-01-08

  article

  High-speed-jet turbulent mixing noise remains a challenging problem, and here we aim to reduce it using a wavepacket-cancellation strategy. This approach is enabled by the recently developed resolvent-based estimation and control framework, which uses near-nozzle sensors to detect noise-generating wavepackets and suppress them via actuation. This paper presents three main results toward this larger goal: (i) data-driven estimation for a Mach 1.5 supersonic jet using large-eddy simulations to identify coherent structures and inform sensor-target placement; (ii) resolvent-based estimation for the linearized jet, which achieves reasonable accuracy in reconstructing relevant flow features from limited sensor data; and (iii) preliminary resolvent-based control for the linearized jet, demonstrating a 34% reduction in the root mean square of streamwise-momentum fluctuations using only one sensor and one actuator. These findings demonstrate the potential of the resolvent-based framework for mitigating noise-generating wavepacket structures in supersonic jets and provide an important foundation for future computational and experimental investigations.

  PublisherDOI

• Statistical Characterization of Transient Energy Growth in Rayleigh-Taylor Instability under Multimodal Perturbations

  2026-01-08

  articleSenior author

  A novel statistical framework developed by Frame and Towne (2024) is employed and extended to examine how initial conditions influence the linear evolution of the Rayleigh-Taylor instability. The analysis focuses on the evolution of the mean energy for two representative classes of initial perturbations. The first class, based on a Gaussian spatial correlation, reveals a time delay in the onset of instability growth and a non-monotonic dependence of this delay on the perturbation correlation length. This behavior suggests a low-pass-filter-like selection of modes governing the evolution of the mean energy. The second class consists of perturbations formed as linear combinations of Fourier modes with random phase shifts and amplitudes drawn from a prescribed spectrum. For this case, an analytical expression for the mean energy growth is derived, linking the spectral content of the initial perturbations to the temporal evolution of the energy through the initial spectral amplitudes. This formulation enables direct comparison with ensembles of three-dimensional direct numerical simulations, demonstrating both the framework's predictive capability and the limitations imposed by the problem's non-autonomous nature. Finally, the effects of viscosity and density stratification are analyzed, showing how these factors modify the time-delay mechanism and influence the early-stage evolution of the instability.

  PublisherDOI

• Wave interactions in a screeching jet

  arXiv (Cornell University) · 2026-03-05

  articleOpen accessSenior author

  We use a series of global models to investigate the linear and nonlinear interactions between shock cells, Kelvin-Helmholtz waves, guided jet modes, and other fluctuations in a screeching jet. First, we identify a set of lightly damped global eigenmodes of the Navier-Stokes operator linearized about the mean flow and show that they result from interactions with different shock-cell wavenumbers. Second, we use resolvent analysis to study the linear input-output behavior of the jet and obtain a time-periodic representation of the screech mode, which compares favorably with experimental data. Third, we use harmonic resolvent analysis to study triadic interactions, including inter-frequency energy transfer, between the screech mode determined from resolvent analysis and other fluctuations in the jet. The components of the optimal harmonic resolvent mode at harmonics of the screech frequency match experimental observations that have not been previously predicted by global models. Fourth, we leverage a novel bilinear formulation of harmonic resolvent analysis to study the impact of the screech mode's nonlinear self-interaction on other fluctuations in the jet. We show that the forcing provided by this nonlinear self-interaction of the screech mode, along with its triadic interactions with other frequencies embedded within the harmonic resolvent operator, is sufficient to explain the redistribution of energy to other frequencies and the associated experimental observations. In aggregate, these findings underscore the critical role of triadic and nonlinear interactions in shaping screech dynamics and offer a promising workflow for studying similar interactions in other flows dominated by periodic motions.

  PublisherOA PDF

• Modal decomposition

  Elsevier eBooks · 2025-01-01 · 1 citations

  book-chapterSenior author
  PublisherDOI

• Contributors

  Elsevier eBooks · 2025-01-01

  book-chapterOpen access
  PublisherDOI

Recent grants

• CAREER: Scale-dependent reduced-order models for turbulent flows

  NSF · $532k · 2022–2027

Frequent coauthors

• Peter Jordan

  Institut Pprime

  163 shared

• Vincent Jaunet

  Université de Poitiers

  97 shared

• Tim Colonius

  57 shared

• Daniel Edgington-Mitchell

  Monash University

  51 shared

• Eduardo Martini

  Université de Poitiers

  48 shared

• André V. G. Cavalieri

  42 shared

• Guillaume A. Brès

  Centre National de la Recherche Scientifique

  41 shared

• Damon Honnery

  Monash University

  37 shared

Education

• Ph.D. Mechanical Engineering , Mechanical and Civil Engineering

  California Institute of Technology

  2015

• M.S. Mechanical Engineering, Mechanical and Civil Engineering

  California Institute of Technology

  2010

• B.S. Engineering Mechanics, Engineering Physics

  University of Wisconsin Madison

  2009

Awards & honors

• Young Investigator Program award (2023)
• DURIP award (2023)
• NSF CAREER Award for work modeling turbulent flows (2023)
• Young Investigator Program Award (2019)