A methodology for leveraging a combination of linear (through convolution integrals) and nonlinear (through Volterra series) reduced-order modeling (ROM) development was demonstrated on both a two- and three-degree-of-freedom (2-DOF and 3-DOF, respectively) aeroelastic system. The linear/nonlinear ROM approach was demonstrated against previous work in the field for a 2-DOF system and subsequently extended to a 3-DOF (flapped airfoil) system. Excellent agreement was demonstrated at limit cycle oscillation (LCO) onset (flutter) prediction between computational fluid dynamics, linear ROMs, and nonlinear ROMs. Although linear ROMs were sufficient to predict LCO onset, the nonlinear Volterra correction was required to estimate the amplitude of post-LCOs. Corrections that accounted for more coupling between degrees of freedom predicted the amplitudes more accurately. A study was undertaken to determine the minimal training set required to produce reasonable LCO amplitude estimates of the 3-DOF airfoil. A controller was also implemented in an effort to mitigate LCO onset and flutter divergence and to demonstrate the usefulness and power of leveraging the ROM for control design. A full-state feedback controller, tuned via a linear quadratic regulator (LQR), was shown to be effective in controlling the system below LCO onset. However, beyond LCO onset, this specific linear controller structure was observed to be ineffective in controlling the system. Future work will evaluate nonlinear control methods in which the ROM can be deployed as a part of the control system to update the LQR gains in a fully coupled approach.

We present in this paper a model of the transport of human respiratory particles on a Charlotte Area Transit System (CATS) bus to examine the efficacy of interventions to limit exposure to SARS-CoV-2, the virus that causes COVID-19. The methods discussed here utilize a commercial Navier–Stokes flow solver, RavenCFD, using a massively parallel supercomputer to model the flow of air through the bus under varying conditions, such as windows being open or the HVAC flow settings. Lagrangian particles are injected into the RavenCFD predicted flow fields to simulate the respiratory droplets from speaking, coughing, or sneezing. These particles are then traced over time and space until they interact with a surface or are removed via the HVAC system. Finally, a volumetric Viral Mean Exposure Time (VMET) is computed to quantify the risk of exposure to the SARS-CoV-2 under various environmental and occupancy scenarios. Comparing the VMET under varying conditions should help identify viable methods to reduce the risk of viral exposure of CATS bus passengers during the COVID-19 pandemic.

Heat transfer on a swept cylinder leading edge subject to shock-shock interactions is investigated with Corvid Technologies' RavenCFD solver. A previously published experimental campaign at the NASA Langley 20-Inch Mach 6 Air Tunnel is modeled with RavenCFD, US3D, and FUN3D codes. The shock-shock interaction is between the bow shock of a 6.35-mm radius swept cylinder and an impinging planar oblique shock, generated from a flat plate leading edge. Gridding practices are investigated with multiple levels of conformal mesh refinement and an overset grid. Using an overset gridding strategy, a more accurate heat transfer distribution is obtained using only 22% of the cells of the finest conformal grid. The RavenCFD, US3D, and FUN3D results are compared to each other and to the published experimental data to establish best practices for RavenCFD use and provide a measure of code-to-code variation.

Interpolation in the overset domain connectivity information for a cell-centered CFD flow solver will typically use a least square procedure to determine the interpolation weights. The weights produced using the least square procedure are not bounded between zero and one. Thus the interpolation can be non-monotonic and introduce new extrema in the solution, which can cause difficulties with the CFD solution. Interpolation using a dual grid, which connects primal cell centers to form dual grid cells, can be used with tri-linear interpolation to produce weights bounded between zero and one. Forming the dual grid for a structured grid is trivial since the connectivity between cell centers is implicit. For an unstructured grid the dual grid connectivity must be generated. This paper investigates the use of tetrahedral meshing technology to form a tetrahedral unstructured dual grid. The first approach uses a global dual grid where a single grid connects all cell centers, which can be expensive to store. The second approach investigated uses a set of local dual grids where each primal grid element has an associated local dual grid that is independent of neighboring local duals. The local dual grid can reduce memory requirements by loading only the set of local dual grids required for interpolation. Compressible CFD solutions using the least square interpolation weights are compared with solutions using the global dual grid interpolation weights. These results show that the non-monotonic interpolation using the least square interpolation weights can cause solution instabilities. Clipping the interpolated values obtained by using the least square weights will force the interpolation to be monotonic and solution stability is preserved. The CFD solution is stable when using the dual grid interpolation weights as expected. For the configurations and conditions considered in this investigation the solution results using the dual grid interpolation and the clipped least square interpolation show only minor differences.