Rotorcraft Optimization Tools: Incorporating Rotorcraft Design Codes into Multi-Disciplinary Design, Analysis, and Optimization

One of the goals of NASA's Revolutionary Vertical Lift Technology Project (RVLT) is to provide validated tools for multidisciplinary design, analysis and optimization (MDAO) of vertical lift vehicles. As part of this effort, the software package, RotorCraft Optimization Tools (RCOTOOLS), is being developed to facilitate incorporating key rotorcraft conceptual design codes into optimizations using the OpenMDAO multi-disciplinary optimization framework written in Python. RCOTOOLS, also written in Python, currently supports the incorporation of the NASA Design and Analysis of RotorCraft (NDARC) vehicle sizing tool and the Comprehensive Analytical Model of Rotorcraft Aerodynamics and Dynamics II (CAMRAD II) analysis tool into OpenMDAO-driven optimizations. Both of these tools use detailed, file-based inputs and outputs, so RCOTOOLS provides software wrappers to update input files with new design variable values, execute these codes and then extract specific response variable values from the file outputs. These wrappers are designed to be flexible and easy to use. RCOTOOLS also provides several utilities to aid in optimization model development, including Graphical User Interface (GUI) tools for browsing input and output files in order to identify text strings that are used to identify specific variables as optimization input and response variables. This paper provides an overview of RCOTOOLS and its us

A new design concept for indraft wind-tunnel inlets with application to the national full-scale aerodynamic complex

The present inlet design concept for an indraft wind tunnel, which is especially suited to applications for which a specific test section flow quality is required with minimum inlet size, employs a cascade or vaneset to control flow at the inlet plane, so that test section total pressure variation is minimized. Potential flow panel methods, together with empirical pressure loss predictions, are used to predict inlet cascade performance. This concept has been used to develop an alternative inlet design for the 80 x 120-ft wind tunnel at NASA Ames Research Center. Experimental results show that a short length/diameter ratio wind tunnel inlet furnishing atmospheric wind isolation and uniform test section flow can be designed

Blade Motion Correlation for the Full-Scale UH-60A Airloads Rotor

Testing was successfully completed in May 2010 on a full-scale UH-60A rotor system in the USAF's National Full-Scale Aerodynamics Complex (NFAC) 40- by 80-Foot Wind Tunnel.[1] The primary objective of this NASA Army sponsored test program was to acquire a comprehensive set of validation-quality measurements ona full-scale pressure-instrumented rotor system at conditions that challenge the most sophisticated modeling andsimulation tools. The test hardware included the same rotor blades used during the UH-60A Airloads flight test.[2] Key measurements included rotor performance, blade loads, blade pressures, blade displacements, and rotorwake measurements using large-field Particle Image Velocimetry (PIV) and Retro-reflective Background Oriented Schlieren (RBOS)

Comparison of full-scale, small-scale, and CFD results for F/A-18 forebody slot blowing

It has been shown experimentally that forebody flow control devices provide a significant increase in yaw control for fighter aircraft at high angle-of-attack. This study presents comparisons of the various experimental and computational results for tangential slot blowing on the F/A-18 configuration. Experimental results are from the full-scale and 6 percent-scale model test and computational solutions are from both isolated forebody and and full aircraft configurations. The emphasis is on identifying trends in the variation of yawing moment with blowing-slot exit conditions. None of the traditional parameters (mass flow ratio, blowing momentum coefficient, velocity ratio) succeeded in collapsing all of the results into a common curve. Several factors may effect the agreement between the 6 percent- and full-scale results including Reynolds number effects, sensitivity of boundary layer transition from laminar to turbulent flow, and poor geometric fidelity, particularly of the blowing slot. The disagreement between the full-scale and computed yawing moments may be due to a mismatch in the slot exit conditions for the same mass flow ratio or aircraft configuration modeling. The general behavior of slot blowing on the 6 percent-scale and computational models is correct, but neither matches the full-scale results

Convective Weather Forecast Quality Metrics for Air Traffic Management Decision-Making

Since numerical weather prediction models are unable to accurately forecast the severity and the location of the storm cells several hours into the future when compared with observation data, there has been a growing interest in probabilistic description of convective weather. The classical approach for generating uncertainty bounds consists of integrating the state equations and covariance propagation equations forward in time. This step is readily recognized as the process update step of the Kalman Filter algorithm. The second well known method, known as the Monte Carlo method, consists of generating output samples by driving the forecast algorithm with input samples selected from distributions. The statistical properties of the distributions of the output samples are then used for defining the uncertainty bounds of the output variables. This method is computationally expensive for a complex model compared to the covariance propagation method. The main advantage of the Monte Carlo method is that a complex non-linear model can be easily handled. Recently, a few different methods for probabilistic forecasting have appeared in the literature. A method for computing probability of convection in a region using forecast data is described in Ref. 5. Probability at a grid location is computed as the fraction of grid points, within a box of specified dimensions around the grid location, with forecast convection precipitation exceeding a specified threshold. The main limitation of this method is that the results are dependent on the chosen dimensions of the box. The examples presented Ref. 5 show that this process is equivalent to low-pass filtering of the forecast data with a finite support spatial filter. References 6 and 7 describe the technique for computing percentage coverage within a 92 x 92 square-kilometer box and assigning the value to the center 4 x 4 square-kilometer box. This technique is same as that described in Ref. 5. Characterizing the forecast, following the process described in Refs. 5 through 7, in terms of percentage coverage or confidence level is notionally sound compared to characterizing in terms of probabilities because the probability of the forecast being correct can only be determined using actual observations. References 5 through 7 only use the forecast data and not the observations. The method for computing the probability of detection, false alarm ratio and several forecast quality metrics (Skill Scores) using both the forecast and observation data are given in Ref. 2. This paper extends the statistical verification method in Ref. 2 to determine co-occurrence probabilities. The method consists of computing the probability that a severe weather cell (grid location) is detected in the observation data in the neighborhood of the severe weather cell in the forecast data. Probabilities of occurrence at the grid location and in its neighborhood with higher severity, and with lower severity in the observation data compared to that in the forecast data are examined. The method proposed in Refs. 5 through 7 is used for computing the probability that a certain number of cells in the neighborhood of severe weather cells in the forecast data are seen as severe weather cells in the observation data. Finally, the probability of existence of gaps in the observation data in the neighborhood of severe weather cells in forecast data is computed. Gaps are defined as openings between severe weather cells through which an aircraft can safely fly to its intended destination. The rest of the paper is organized as follows. Section II summarizes the statistical verification method described in Ref. 2. The extension of this method for computing the co-occurrence probabilities in discussed in Section HI. Numerical examples using NCWF forecast data and NCWD observation data are presented in Section III to elucidate the characteristics of the co-occurrence probabilities. This section also discusses the procedure for computing throbabilities that the severity of convection in the observation data will be higher or lower in the neighborhood of grid locations compared to that indicated at the grid locations in the forecast data. The probability of coverage of neighborhood grid cells is also described via examples in this section. Section IV discusses the gap detection algorithm and presents a numerical example to illustrate the method. The locations of the detected gaps in the observation data are used along with the locations of convective weather cells in the forecast data to determine the probability of existence of gaps in the neighborhood of these cells. Finally, the paper is concluded in Section V

Summary of Full-Scale Blade Displacement Measurements of the UH- 60A Airloads Rotor

Blade displacement measurements using multi-camera photogrammetry techniques were acquired for a full-scale UH-60A rotor, tested in the National Full-Scale Aerodynamic Complex 40-Foot by 80-Foot Wind Tunnel. The measurements, acquired over the full rotor azimuth, encompass a range of test conditions that include advance ratios from 0.15 to 1.0, thrust coefficient to rotor solidity ratios from 0.01 to 0.13, and rotor shaft angles from -10.0 to 8.0 degrees. The objective was to measure the blade displacements and deformations of the four rotor blades and provide a benchmark blade displacement database to be utilized in the development and validation of rotorcraft prediction techniques. An overview of the blade displacement measurement methodology, system development, and data analysis techniques are presented. Sample results based on the final set of camera calibrations, data reduction procedures and estimated corrections that account for registration errors due to blade elasticity are shown. Differences in blade root pitch, flap and lag between the previously reported results and the current results are small. However, even small changes in estimated root flap and pitch can lead to significant differences in the blade elasticity values

Wind Tunnel Results of Pneumatic Forebody Vortex Control Using Rectangular Slots a Chined Forebody

A subsonic wind tunnel investigation of pneumatic vortex flow control on a chined forebody using slots was accomplished at a dynamic pressure of 50 psf resulting in a R(n)/ft of 1.3 x 10(exp 6). Data were acquired from angles of attack ranging from -4deg to +34deg at side slips of +0.4deg and +10.4deg. The test article used in this study was the 10% scale Fighter Lift and Control (FLAC) advanced diamond winged, vee-tailed fighter configuration. Three different slot blowing concepts were evaluated; outward, downward, and tangential with ail blowing accomplished asymmetrically. The results of three different mass flows (0.067, 0.13, and 0.26 lbm/s; C(sub mu)'s of less than or equal to 0.006, 0.011. and 0.022 respectively) were analyzed and reported. Test data are presented on the effects of mass flows, slot lengths and positions and blowing concepts on yawing moment and side force generation. Results from this study indicate that the outward and downward blowing slots developed yawing moment and side force increments in the direction opposite of the blowing side while the tangential blowing slots generated yawing moment and side force increments in the direction towards the blowing side. The outward and downward blowing slots typically produced positive pitching moment increments while the tangential blowing slots typically generated negative pitching moment increments. The slot blowing nearest the forebody apex was most effective at generating the largest increments and as the slot was moved aft or increased in length, its effectiveness at generating forces and moments diminished

Full-Scale Wind Tunnel Studies of F/A-18 Tail Buffet

Tail buffet studies were conducted on a full-scale, production, F/A-18, fighter aircraft in the 80- by 120-Foot Wind Tunnel of the National Full-Scale Aerodynamic Complex at NASA Ames Research Center in Moffett Field, California. The F/A-18 was tested over an angle-of-attack range of 18deg to 50deg, a side-slip range of -15deg to 15deg, and at wind speeds of up to 100 knots. The maximum speed corresponds to a Reynolds number of 12.3 x 10(exp 6) based on mean aerodynamic chord and a Mach number of 0.15. The port, vertical tail fin was instrumented with thirty-two surface pressure transducers, arranged in four by four arrays on both sides on the fin. The aircraft was also equipped with a removable Leading Edge eXtension (LEX) fence that is used on F/A-18 aircraft to reduce tail buffet loads. Time-averaged, power-spectral analysis results are presented for the tail fin bending moment derived from the integrated pressure field. The results are only for the zero side-slip condition, both with and without the LEX fence. The LEX fence significantly reduces the magnitude of the root-mean-square pressures and bending moments. Scaling issues are addressed by comparing full-scale results for pressures at the 60%-span and 45%-chord location with published results of small-scale, F/A-18 tail-buffet tests. The comparison shows that the tail buffet frequency scales very well with length and velocity. Root-mean-square pressures and power spectra do not scale as well. The LEX fence is shown to reduce tail buffet loads at all model scales

A Fast-Time Simulation Tool for Analysis of Airport Arrival Traffic

The basic objective of arrival sequencing in air traffic control automation is to match traffic demand and airport capacity while minimizing delays. The performance of an automated arrival scheduling system, such as the Traffic Management Advisor developed by NASA for the FAA, can be studied by a fast-time simulation that does not involve running expensive and time-consuming real-time simulations. The fast-time simulation models runway configurations, the characteristics of arrival traffic, deviations from predicted arrival times, as well as the arrival sequencing and scheduling algorithm. This report reviews the development of the fast-time simulation method used originally by NASA in the design of the sequencing and scheduling algorithm for the Traffic Management Advisor. The utility of this method of simulation is demonstrated by examining the effect on delays of altering arrival schedules at a hub airport