arXiv subjects

Jeremy Redding

Publications and source records attributed to Jeremy Redding.

3 recordsLinked to original sources

arXiv2026

Pareto-Optimal Hypersonic Vehicle Design with Canonical-Coordinate Neural Operator Surrogates Under Ablation-Driven Shape Change and Incidence Variation

High-fidelity CFD is essential for coupled hypersonic aerodynamic and aerothermal phenomena, but its cost precludes multi-objective design optimization. We develop three DeepONet surrogates for two hypersonic configurations, unified by one device: the trunk receives coordinates in which the varying feature is held fixed. The first is a prescribed family of 37 spherically blunted tangent ogives, varied through ogive radius of curvature to span nose-tip ablation forebody change; no ablation is computed. A body-fitted canonical transformation maps every domain onto a common (s, eta) space, retaining physical coordinates for forces and heat transfer. A branch network predicts reduced coefficients and a Transolver trunk with Physics-Attention learns the spatial basis; a two-step strategy optimizes both jointly, orthonormalizes the basis by QR factorization, and trains a second-stage branch for unseen geometries. Surrogates cover density, pressure, velocity, temperatures, conductivities and species mass fractions. In leave-one-out tests, drag, mean and peak wall heat flux are recovered to 1.16%, 1.62% and 5.29%; a sweep of 1001 geometries gives a 200-design Pareto front trading 6.68% in drag for 4.42% in peak heating (a diagnostic, not an objective). The second is the 3D AEDC waverider at 29 angles of attack: static mesh, moving leading-edge shock. For surface quantities, the same construction predicts integrated heat load within 0.22% and force coefficients to errors below 2.6x10^-5; Pareto fronts identify angles of attack trading drag, lift and heating. For the volume field, a Cartesian trunk smears the shock; a frozen ShockNet supplies a shock-aligned coordinate and a hotspot-aware mixture of experts corrects the residual, recovering density to 12.28% relative L2 error at a held-out incidence (5.08x10^7 nodes). The 1001-design sweep takes about three minutes on a single CPU.

math-ph↗

arXiv2024

High fidelity simulations of unstart phenomena in a scramjet inlet due to angle of attack

This work investigates the unsteady behavior of unstart phenomena within a scramjet inlet using advanced computational techniques. Scramjets and ramjets, with their reliance on inlet compression, offer promising airbreathing propulsion for hypersonic regimes. This research focuses on understanding and modeling the onset of unstart phenomena in supersonic inlets, a critical step towards developing mitigation strategies. These strategies have the potential to improve engine efficiency, range, and maneuverability of hypersonic vehicles. To achieve this, the state-of-the-art compressible flow solver, Eilmer, is used to simulate shockwave behavior within the inlet/isolator of a planar scramjet characterized experimentally at North Carolina State University (NCSU). Baseline comparisons are presented with the wind tunnel experiments via the shock structures present within the isolator section conducted at Mach 3.9 on a 3D scramjet inlet model. Simulations are then carried out at varying angles of attack (0 to 10 deg) and multiple pitch rates (10 deg/sec and 100 deg/sec) to demonstrate the shock train inertial response and to characterize unstart onset. In both cases the timing of inlet unstart is observed to correlate well with the rapid surge in exit pressure as well as shock detachment at the lower leading edge region. Lastly, exit pressures are significantly higher in the 10 deg/s case than in that of the 100 deg/s case at the same angle of attack. These observations suggest that unstart is not only dependent on angle of attack but also on AoA pitch rate. The findings provide valuable insights into the unsteady flow behavior during hypersonic inlet unstart, with potential applications for unstart detection at high angles of attack.

physics.flu-dyn↗

arXiv2024

Analysis of thermochemical non-equilibrium hypersonic flow over a waverider with uncertainty quantification

The objective of this work is to assess the impact of parameter uncertainty on hypersonic aerothermal surface heating predictions in Reynolds-Averaged Navier-Stokes (RANS) simulations using non-intrusive uncertainty quantification (UQ) techniques. RANS-based models are considered indispensable tools in computational fluid dynamics (CFD) analysis for the iterative and cost-effective exploration of innovative design concepts. However, these RANS models heavily rely on empirical constants that often require tuning due to the lack of physical knowledge and complexity of the problem, introducing significant uncertainties that hinder their predictive capabilities. Therefore, this research investigates the influence of the turbulent Prandtl number uncertainty, that governs the level of shear stress and heat flux present in the turbulent flow, on key output quantities of interest (QoIs). The US3D hypersonics solver is employed to simulate aeroheating over a hypersonic waverider configuration using the classical Menter Shear Stress Transport (SST) turbulence model. A polynomial chaos expansion (PEC) framework is presented that enables a global sensitivity analysis and forward propagation of uncertainty for a range of turbulent prandtl number, generating statistics including skewness and kurtosis of the QoIs. In addition, Sobol indices are calculated to quantify the relative contribution of the turbulent prandtl number to the overall uncertainty in the heat flux and surface pressure outputs. The results provide valuable insights into the underlying aeroheating behavior in RANS simulations under hypersonic non-equilibrium flow conditions over a waverider previously studied at the Arnold Engineering Development Center (AEDC) facility. These findings will inform future design processes and improve the reliability of RANS-based predictions in hypersonic applications.

physics.flu-dyn↗