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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 163 records · Page 9

Surface-Normal Active Flow Control for Lift Enhancement and Separation Mitigation for High-Lift Common Research Model

This study explores the feasibility of using small surface-normal jets near the flap trailing edge as active aerodynamic load control on the high-lift Common Research Model wing/-body configuration. Chimera Grid Tools are utilized to generate structured curvilinear overset grids, and the Reynolds-averaged Navier-Stokes solver OVERFLOW is employed to solve for the flow-field around the geometry. The so-called microjet is initially employed across both the inboard and the outboard flaps on the pressure-side near the trailing edge. It is shown that implementing the microjet on the inboard flap is more effective compared to implementing it on the outboard flap. This is because, prior to microjet implementation, the flow on the outboard flap exhibits extensive separation, while the flow on the inboard flap exhibits moderate separation. For microjet implementation across the inboard flap only, the relationship between momentum coefficient of the microjet and lift-enhancement is found to be∆CL'1.66√Cμfor the rangeCμ= 0.00−0.012. We show that implementing a microjet with a jet velocity ratio of one, which corresponds toCμ= 0.003, can shift the linear region of the lift curve by ∆CL= 0.08. The linear shift in the lift curve is significant for enhancing airplane performance such as increasing its payload. Microjet implementation effects on the drag coefficient are also investigated through a drag decomposition analysis. Further, we employ an induced drag analysis based on the spanwise load distribution and show that the microjet-related increase in pressure drag coefficient is dominated by the increase in the induced drag while microjet implementation reduces the form drag. These preliminary results show that favorable changes in aerodynamic performance can be achieved by using the surface-normal jets presented in this study.

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Transonic Lift and Drag Predictions using Wall Modelled Large Eddy Simulations

Wall-modelled Large Eddy Simulations (WMLES) of the NASA Common Research Model (CRM) at transonic conditions and various angles of attacks leading up to and including shock-induced flow separation are performed using the LAVA computational framework. The simulations are shown to accurately predict the lift curve slope and the onset of separation characterized by the break in the pitching moment. Furthermore, careful assessment of skin-friction drag at cruise condition and its subsequent decrease with increasing angles of attack are shown to be in agreement with viscous sublayer resolving Reynolds Averaged Navier Stokes(RANS) simulations. The small differences between WMLES and RANS appear to be of the same order as differences seen between two RANS models at the cruise-point. Some sensitivity is observed to the coefficient used in the subgrid scale model, although this can be reconciled by noting the low chord- and shock-incidence Reynolds numbers (Rex≈106) seen in the outboard regions of the wing, along with the uncertainties associated with tripping and the numerical transition that occurs near the leading edge. Among the primary drawbacks seen in the WMLES predictions is the subdued increase in wave-drag with increasing angle-of-attack and the shock intensity when compared with experimental data. Preliminary assessment suggests that additional span- and stream-wise grid resolution is likely needed in mid- and out-board portions of the wing to better resolve the shock-induced separated flow and to further investigate prediction accuracy of unsteady temporal characteristics of the problem.

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Cartesian Mesh Simulations for the Third AIAA Sonic Boom Prediction Workshop

Simulation results are presented for all cases from the Third AIAA Sonic Boom Prediction Workshop. An inviscid, embedded-boundary Cartesian-mesh flow solver is used in conjunction with adjoint-based mesh adaptation to compute nearfield pressure signatures. Specialized techniques are applied to maximize accuracy and minimize cost on Cartesian meshes. The Richardson-based error estimate highlights regions of the signatures most sensitive to mesh refinement. Timing results and coarse, medium, and fine mesh sizes for nearfield cases demonstrate that the parallel decomposition approach is efficient in both computational time and wall-clock. Pressure signals are propagated to the ground using an augmented Burgers’ equation solver to predict boom carpets. Ground signatures and loudness metrics are presented for a standard atmosphere as well as more realistic atmospheric profiles, which affect overall noise levels and can significantly widen the boom carpet. Mesh convergence studies show that high sampling frequencies, around 500 kHz, are required for propagation, and the sampling frequency increases at large off-track angles with longer acoustic ray paths and propagation times. The numerical methods yield accurate results for predicting low sonic boom signatures while being among the least computationally expensive of the workshop.

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Evaluation of CFD Predictions of CobraMRV Control Surface Effectiveness at the NASA Langley Unitary Plan Wind Tunnel

The ability of CFD simulations to serve as a surrogate for wind tunnel testing at high supersonic speeds has been evaluated for a sub-scale model of the Co-Optimization Blunt-body Re-entry Analysis-Mid-lift-to-drag Rigid Vehicle (CobraMRV) human Mars entry vehicle concept. The vehicle was tested at the Unitary Plan Wind Tunnel (UPWT) at the NASA Langley Research Center under flow conditions and surface control configurations relevant to the entry stage of a flight mission. The CFD simulations were performed prior to gaining access to test results in order to assess how blind predictions obtained using best practices compare to experiments. Solutions of empty tunnel simulations were used as inflow boundary condition for the CobraMRV simulations in a truncated portion of the test section. Different solvers and turbulence models were used by separate teams to assess sensitivity to numerical methods, physics, and users. After release of the test results, the pre-test computations were compared to the experimental results, and additional analyses have been conducted to explain observed discrepancies. The amount of time and resources dedicated to each phase of the computational work was logged for comparison to that required for wind tunnel tests, and to inform planning of future CFD data base development projects.

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Uncertainty Estimates for Sonic-Boom Pressure Signatures and Loudness Carpets

A non-intrusive uncertainty quantification method is applied to computational analysis of supersonic, low-boom aircraft. The mean and standard deviation statistics of the pressure waveforms and loudness metrics are evaluated through use of numerical quadrature. The probability density function (p.d.f.) of these outputs is evaluated via kernel density estimation. The simulations use an inviscid, embedded-boundary Cartesian-mesh flow solver in the nearfield combined with an augmented Burgers’ equation solver for propagation in the farfield. The results show that the p.d.f. of the waveform is bimodal at shocks, which makes the mean and standard deviation statistics inappropriate. Despite this limitation, we show that the moment statistics can provide effective assessment of discrepancies when comparing with experimental data. This is demonstrated by presenting uncertainty analysis of a wind-tunnel test and showing that we significantly improve the predictions when we include the test uncertainties in the simulation. Normal distributions are obtained for the ground signature and loudness metrics, which is primarily due to the careful shaping of the low-boom waveform. Separation of variables and error control are used to reduce computational cost. We demonstrate that this is an efficient approach in the sense of balancing numerical errors in the statistics quadrature with discretization errors in the solvers.

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Adjoint-Based Minimization of X-59 Sonic Boom Noise Via Control Surfaces

A multidisciplinary design optimization methodology to directly minimize the ground-level noise generated by a supersonic aircraft's sonic boom is presented. A gradient-based optimizer is coupled with a Cartesian Euler flow solver and an atmospheric propagation tool to forge a unique design capability. Adjoint formulations for both the flow solver and propagation tool are also coupled to provide sensitivities in an efficient manner. The design method is demonstrated on the X-59 Low-Boom Flight Demonstrator by optimizing control surface deflections to improve ground-level noise while maintaining trimmed cruise flight. Two noise minimization examples and a noise maximization are presented. All optimized designs result in measurable improvement in the ground-level noise objective. Extensive surveys of the design space confirm that the optimization method is effective in finding a local optimum. Moreover, repeated application of the method with varying initial design points also demonstrates the robustness of the method.

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