Miles Chan

I am an aerospace engineer (PhD, Caltech 2025) with expertise in modeling, simulation, and analysis of linear and nonlinear dynamical systems incorporating fluid dynamics, thermal effects, structural elements, and aerospace vehicles using equation- and data-driven methods. I am also experienced in mechanical design, stress analysis, machining, and rapid prototyping. I am self-driven and independent, but also a capable collaborator and communicator.

>> My PhD thesis, Reduced Order Modeling of Near-wall and Roughness Sublayer Turbulence, documents models I developed to provide inexpensive predictions of structures, statistics, and engineering quantities-of-interest (e.g. drag) in the turbulent flow response to smooth and textured surfaces.

🔬 research highlights

Turbulent fluid flow is a highly multi-scale, nonlinear physical system. Simulating turbulent flows requires memory- and CPU-intensive computations, and the resulting high-dimensional data is challenging to interpret. In my research, I develop methods for reduced-order modeling of near-wall and roughness sublayer turbulence. Day-to-day, my work includes running computational fluid dynamics simulations on high-performance computing clusters, developing meaningful data analyses and flow visualizations, and constructing reduced-order representations which capture key flow features using spectral and modal analysis techniques. I also use theory- and equation-driven methods, in particular resolvent analysis of the Navier-Stokes equations, to construct predictive low-order models.

Resolvent Analysis for Predicting Roughness Sublayer Turbulence

Miles Chan, Ugo Piomelli, Beverley McKeon

I conducted the theoretical development and software implementation of a generalizable, equation-based reduced order model for the turbulent flow response to surface roughness, using resolvent analysis with a surface-dependent forcing term. This method predicts flow features, statistics, and drag observed in rough wall channel flow with a large reduction in computational expense as measured in degrees of freedom, memory usage, and wall time. The results are compared with direct numerical simulations of rough wall channel at engineering-relevant friction Reynolds numbers. The work is documented in my thesis and an upcoming publication. Skills used include MATLAB, MPI, C++, data visualization and analysis, pre- and post-processing of simulation inputs/results.

Data-driven Modeling of Near-wall Turbulence for WMLES

Zvi Hantsis, Miles Chan, Ugo Piomelli, Beverley McKeon

I developed methods for modeling turbulent fluctuations in the near-wall layer of wall-modeled LES at high Reynolds numbers, using data and Reynolds-number scaling approaches from resolvent analysis. The work is documented in my thesis and a submitted publication. Skills used include MATLAB, C++, MPI, data visualization and analysis, pre- and post-processing of simulation inputs/results.

🎻 music

I have been playing the violin since I was 5. At Stanford, I take private lessons and regularly perform in solo, chamber, and orchestral roles.

Saint-Saëns Introduction and Rondo Capriccioso with Caltech Orchestra (2023)

Schumann Piano Quartet (2023)

Schubert Death and the Maiden (2023)

🏃 sports

I enjoy both the training and social aspects of running and cycling with friends from Stanford Cycling, Caltech Alpine Club runners, and Caltech Triathlon.

17:32 in the Santa Run 5k (2023)

4:51:02 at Santa Cruz 70.3 (2022)

2:57:33 at Los Angeles Marathon (2022)

1:24:02 at Rose Bowl Half (2022)

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