arXiv subjects

Joseph C. Oefelein

Publications and source records attributed to Joseph C. Oefelein.

8 recordsLinked to original sources

arXiv2026

Planar Lagrangian transport and scalar-gradient organization in a turbulent reacting shear layer

We analyze planar Lagrangian transport and scalar-gradient organization in a supersonic, reacting hydrogen-air temporal mixing layer using time-resolved mid-plane data from a three-dimensional direct numerical simulation. The analysis combines forward/backward finite-time Lyapunov exponent (FTLE) fields, operational FTLE-ridge skeletons, Cauchy-Green deformation measures, shear-LCS metrics, and planar hyperbolic geodesic-LCS extraction to examine how finite-time stretching structures the reacting shear layer. The time-resolved FTLE ridges identify repelling and attracting finite-time transport skeletons in the constrained two-dimensional slice, from which ridge geometry, intersection occupancy, persistence, and scalar-conditioned transport are quantified. Hyperbolic geodesic LCS are extracted from Cauchy-Green tensors reconstructed from planar flow maps as strainlines seeded at high-$λ_{\max}$ normal maxima, providing a variational counterpart to the operational FTLE-ridge skeleton. We then relate the transport skeleton to temperature, mixture fraction, and a reaction intermediate. The results show localized forward/backward ridge overlap, strong scalar-gradient enrichment, finite-time geodesic LCS that occupy the same high-strain transport skeleton, residual direction-dependent separation from a time- and cross-stream-stratified null model, and scalar-response lags that remain compact relative to decorrelation and FTLE-integration scales. Together, these results provide a transport-oriented characterization of coherent structures and their role in mid-plane mixing within a compressible reacting shear flow.

physics.flu-dyn↗

arXiv2026

Receptivity and Biorthogonal Decomposition in a Reacting Temporal Mixing Layer

We examine receptivity and biorthogonal decomposition in a reacting temporal mixing layer using direct and adjoint eigenmodes of a finite-thickness compressible linearized operator built from the mean reacting base state. The analysis focuses on the Kelvin--Helmholtz branch and asks how the reacting base state modifies the selected temporal instability, where localized forcing most efficiently excites it, and how strongly the associated modal family is represented in time-resolved planar simulation data. Receptivity maps are constructed for mass, momentum, thermal, and mixture-fraction forcing channels using an energy-weighted adjoint projection, with biorthogonality enforced by the corresponding direct--adjoint inner product. A complementary biorthogonal decomposition provides modal amplitudes and cumulative few-mode reconstructions at the fundamental streamwise wavenumber. The finite-thickness branch is interpreted against a compressible vortex-sheet reference built from the outer-stream states. The reacting layer supports an unstable finite-thickness Kelvin--Helmholtz family over low-to-moderate wavenumbers even though the discontinuous reference is essentially neutral. Mass forcing leads the raw localized receptivity maps, mixture-fraction forcing follows through composition-pressure coupling, and chemistry-weighted thermal forcing identifies the strongest thermochemical support of the same family. The results show how distributed reacting thermodynamics reorganize compressible shear-layer instability and how that reorganized branch remains embedded in the nonlinear flow.

physics.flu-dyn↗

arXiv2026

Near-Field Combustion-Noise Source Dynamics in a Reacting Supersonic Temporal Mixing Layer

Compressibility and chemical reactions in reacting flows provide source mechanisms for pressure fluctuations whose signatures depend on the flow, source distribution, and acoustic environment. Bounded flows can sustain strong feedback and narrowband tones, whereas boundary-free flows more often exhibit broadband source activity distributed across frequency. Near-field combustion-noise source dynamics are examined in a supersonic reacting hydrogen-air temporal mixing layer using high-fidelity time-resolved direct numerical simulation data. Pressure, heat-release, and dilatation fields are used to identify how localized reacting structures, compressive disturbances, broadband spectral content, and burst-driven temporal organization interact. The results show weak pressure--heat-release coherence concentrated within selected low-frequency bands, with no collapse onto a single dominant mode. Combustion intermittency modulates the near-field pressure response within these bands and is accompanied by burst-driven amplitude modulation and transient trajectory sensitivity, while the overall dynamics remain broadband and bounded. A planar source-radiation-potential projection further shows moderate low-frequency angular bias associated with the heat-release source distribution. Information-theoretic measures indicate that pressure fluctuations share more statistical structure with heat release than with dilatation. The analysis characterizes source-side organization and near-field pressure response in the sampled DNS of a reacting shear layer, providing a basis for subsequent observer-based or acoustic-analogy radiation calculations.

physics.flu-dyn↗

arXiv2026

Event-level compression--chemistry coupling in a supersonic reacting temporal mixing layer

Compression and heat release interact intermittently in high-speed reacting shear layers, and whole-field averages can obscure their coupling. We examine this coupling in a supersonic reacting hydrogen--air temporal mixing layer using time-resolved mid-plane slices from a three-dimensional direct numerical simulation. A fixed dilatation threshold identifies connected compression events, and exothermic heat release and mixture-fraction-gradient activity are then conditioned on the evolving event population. The record separates into startup ($t^*<5$), transition ($5\le t^*<20$), and developed ($t^*\ge 20$) regimes, with the developed regime carrying the persistent compression--chemistry interaction. In this regime, compression appears as a population of intermittent events with no single structure dominating the field. Stronger exothermic response is associated with larger maximum-event area, larger event count, greater compression--heat-release overlap, and smaller distance from compression to the most exothermic regions. Scalar-gradient amplification peaks near zero lag relative to compression-area excursions, whereas the strongest exothermic response precedes peak compression coverage by $Δt^*\approx -0.85$. These results show that compression organizes chemistry most clearly through event population, overlap, proximity, and lag, providing an event-level description of compression--chemistry coupling in an open supersonic reacting shear layer.

physics.flu-dyn↗

arXiv2026

Filtering effects on entropy transport and entropy-production structure in a supersonic reacting shear layer

Spatial filtering is examined in time-resolved mid-plane DNS fields of a supersonic reacting shear layer using a sequence of box filters. The analysis tracks a nondimensional entropy-like scalar $s^\ast$, its in-plane material derivative $D s^\ast / D t^\ast$, a residual $Π_s^\ast$, and viscous and conductive entropy-production diagnostics, $σ_μ^\ast$ and $σ_k^\ast$. Filtering changes $s^\ast$ only weakly, attenuates $D s^\ast / D t^\ast$ and the strongest tails of $σ_μ^\ast$ and $σ_k^\ast$, but broadens the residual distribution and increases the residual RMS with filter width. The residual remains concentrated in the layer core that carries the largest mechanical and thermal activity. Conditional statistics show that $|Π_s^\ast|$ rises with both entropy-production intensity and entropy-gradient strength. Spectral and structural diagnostics show that increasing filter width removes high-wavenumber content and simplifies the geometry of the high-$|Π_s^\ast|$ sets. Coarser filtering therefore increasingly distorts entropy transport preferentially through the most dynamically and thermally active structures, rather than uniformly across the plane.

physics.flu-dyn↗

arXiv2018

Compressive sensing adaptation for polynomial chaos expansions

Basis adaptation in Homogeneous Chaos spaces rely on a suitable rotation of the underlying Gaussian germ. Several rotations have been proposed in the literature resulting in adaptations with different convergence properties. In this paper we present a new adaptation mechanism that builds on compressive sensing algorithms, resulting in a reduced polynomial chaos approximation with optimal sparsity. The developed adaptation algorithm consists of a two-step optimization procedure that computes the optimal coefficients and the input projection matrix of a low dimensional chaos expansion with respect to an optimally rotated basis. We demonstrate the attractive features of our algorithm through several numerical examples including the application on Large-Eddy Simulation (LES) calculations of turbulent combustion in a HIFiRE scramjet engine.

stat.ML↗

arXiv2018

Compressive Sensing with Cross-Validation and Stop-Sampling for Sparse Polynomial Chaos Expansions

Compressive sensing is a powerful technique for recovering sparse solutions of underdetermined linear systems, which is often encountered in uncertainty quantification analysis of expensive and high-dimensional physical models. We perform numerical investigations employing several compressive sensing solvers that target the unconstrained LASSO formulation, with a focus on linear systems that arise in the construction of polynomial chaos expansions. With core solvers of l1_ls, SpaRSA, CGIST, FPC_AS, and ADMM, we develop techniques to mitigate overfitting through an automated selection of regularization constant based on cross-validation, and a heuristic strategy to guide the stop-sampling decision. Practical recommendations on parameter settings for these techniques are provided and discussed. The overall method is applied to a series of numerical examples of increasing complexity, including large eddy simulations of supersonic turbulent jet-in-crossflow involving a 24-dimensional input. Through empirical phase-transition diagrams and convergence plots, we illustrate sparse recovery performance under structures induced by polynomial chaos, accuracy and computational tradeoffs between polynomial bases of different degrees, and practicability of conducting compressive sensing for a realistic, high-dimensional physical application. Across test cases studied in this paper, we find ADMM to have demonstrated empirical advantages through consistent lower errors and faster computational times.

stat.CO↗

arXiv2018

Global Sensitivity Analysis and Estimation of Model Error, Toward Uncertainty Quantification in Scramjet Computations

The development of scramjet engines is an important research area for advancing hypersonic and orbital flights. Progress toward optimal engine designs requires accurate flow simulations together with uncertainty quantification. However, performing uncertainty quantification for scramjet simulations is challenging due to the large number of uncertain parameters involved and the high computational cost of flow simulations. These difficulties are addressed in this paper by developing practical uncertainty quantification algorithms and computational methods, and deploying them in the current study to large-eddy simulations of a jet in crossflow inside a simplified HIFiRE Direct Connect Rig scramjet combustor. First, global sensitivity analysis is conducted to identify influential uncertain input parameters, which can help reduce the systems stochastic dimension. Second, because models of different fidelity are used in the overall uncertainty quantification assessment, a framework for quantifying and propagating the uncertainty due to model error is presented. These methods are demonstrated on a nonreacting jet-in-crossflow test problem in a simplified scramjet geometry, with parameter space up to 24 dimensions, using static and dynamic treatments of the turbulence subgrid model, and with two-dimensional and three-dimensional geometries.

physics.data-an↗