A computational framework to support the quantification of system uncertainties and sensitivities for rotorcraft applications is presented using the NASA Design and Analysis of Rotorcraft (NDARC) conceptual sizing tool. A 90 passenger conceptual tiltrotor configuration was used for case demonstration in the modeling of uncertainties in NDARCs emission module. A non-intrusive forward propagation uncertainty quantification approach was applied to ensemble simulations using a Monte Carlo methodology with stratified Latin hypercube sampling. An off-the-shelf software, DAKOTA, which supports trade studies and design space exploration, including optimization, surrogate modeling and uncertainty analysis, was used to address the research goals. Further, a toolsuite was developed incorporating DAKOTA with automated design processes and methods using function wrappers to execute program routines including support for data post-processing. Uncertainties in rotorcraft emissions modeling using the Average Temperature Response metric for a set mission profile were studied. NDARC under-estimates the effects of emissions when using the baseline modeling parameters for the Average Temperature Response compared with mean results from Monte Carlo simulations. A global sensitivity analysis was further undertaken to quantify the contribution of the various emission species on output sensitivity. The work demonstrates that the developed toolsuite is robust and could support the quantification of system uncertainties and sensitivities in future rotorcraft design efforts.
Convective weather is currently the largest contributor to air traffic delays in the United States. In order to make effective traffic flow management decisions to mitigate these delays, weather forecasts must be made as early and as accurately as possible. A forecast product that could be used to mitigate convective weather impacts is the Consolidated Storm Prediction for Aviation. This product provides forecasts of cloud water content and convective top heights at 0-to 8-hour look-ahead times. The objective of this study was to examine a method of predicting the impact of convective weather on air traffic sector capacities using these forecasts. Polygons representing forecast convective weather were overlaid at multiple flight levels on a sector map to calculate the fraction of each sector covered by weather. The fractional volume coverage was used as the primary metric to determine convection's impact on sectors. Results reveal that the forecasts can be used to predict the probability and magnitude of weather impacts on sector capacity up to eight hours in advance.
The Multirotor Test Bed (MTB) is a new capability for testing a wide array of advanced vertical take-off and landing (VTOL) rotor configurations, with a primary focus on testing in the U.S. Army 7- by 10-Foot Wind Tunnel at NASA Ames Research Center. The MTB was designed to allow adjustment of the vertical, lateral, and longitudinal placement of each rotor, as well as allow tilt adjustment of each rotor and pitch adjustment of the whole assembly. Each rotor can tilt forward 90 deg and backwards 5 deg. In addition, the entire MTB can tilt forward 20 deg and backwards 10 deg. This flexibility allows the system to be tested in many different configurations. There is a six-axis load cell under each rotor assembly, to measure both the steady and dynamic loads produced by each rotor. The wind tunnel scales can measure loads on the full assembly. The overall goal of the MTB project is to help gain a better understanding of the performance, control, interactional aerodynamics, and acoustics of multirotor systems. A hybrid CFD tool called RotCFD (Rotorcraft Computational Fluid Dynamics) was used to simulate the MTB in several testing configurations. This paper explains the method of running the RotCFD simulations and explores the results from the simulations. The objective of this paper is to compare the RotCFD simulation results with the MTB wind tunnel test data, seeking to further validate RotCFD for multirotor systems and assess the influence of aerodynamic interactions on individual rotor performance.
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