Porous wind tunnel corrections for counterrotation propeller testing

A procedure is described for the correction of wind-tunnel wall interference effects on the experimental measurement of aerodynamic coefficients. The correction is given by the difference between the values obtained in two different numerical simulations: In the first one the flow over the model in free-air conditions is simulated, whereas in the second one, the measured pressure values over the wind tunnel walls are used as boundary conditions. A necessary preliminarly step is the choice of the number, location, and accuracy of the pressure measurements. A strategy is proposed to determine these parameters, based on the same correction procedure in which the experimental part is replaced by numerical simulation. This strategy is applied to the subsonic flow around a complete aircraft configuration by means of a potential flow solver. The sensitivity to the number and location of sensors, as well as to the transducer accuracy, is investigated. Given the desired correction accuracy, the proposed strategy permits identification of suitable configurations with reduced time and computational costs

A wall interference assessment and correction method for two-dimensional subsonic wind-tunnel testing is presented. Pressure coefficient and angle-of-attack correction are calculated using velocity measurements on interfaces inside the wind tunnel. A mathematical representation of the test article and tunnel wall boundary conditions is not required. Available experimental data of an NACA 0012 airfoil tested at a Mach number of 0.70 and at two different angle of attack in a solid wall wind tunnel are applied to the method. Blockage corrections are computed and corrected surface pressure coefficients compare favorably to free-air flowfield data if the tunnel flowfield is subsonic. The present wall interference correction method can determine blockage corrections in transonic wind-tunnel flowflelds with restrictions. The computed angle-of-attack correction is negligible for the given experimental data. Nomenclature c = chord length c* = critical pressure coefficient cp.(x, 0) = pressure coefficient correction Acp = error of pressure coefficient correction CPT(X, 0) = pressure coefficient on the centerline of the wind tunnel CPT(X, h^ = pressure coefficient on first interface cpy(x, 0) = pressure coefficient in unconfined flow h = tunnel semiheight

Panel method code ANTARES was developed to solve subsonic wall interference problems in a threedimensional wind tunnel with non-rectangular crosssection. The code uses a singularity representation of the test article. Volume and viscous separation wake blockage effects of the test article are represented by chains of point doublets. Lifting effects are represented by line doublets. The closed wall, open jet, perforated wall, or slotted wall boundary condition may be assigned to each individual wall panel centroid. The code also allows the user to solve wall interference problems with a mixed set of wall boundary conditions. ANTARES may be applied to a fullspan or semispan model test. A typical panel model of the test section consists of up to 8000 panels. A LU decomposition algorithm is used to solve the corresponding large linear system of equations. Therefore, it is critical to compile the code using DOUBLE PRECISION data type in order to obtain sufficiently accurate numerical solutions of the linear system. Available classical solutions of three different wall interference correction problems show excellent agreement with numerical results obtained by using ANTARES. Nomenclature dij — matrix coefficient bi = component of right hand side vector ci» • • • , c4 = boundary condition coefficients F = upwash factor (see Ref. [8], p.29) i = wall panel index j = wall panel index I = slot parameter (see Ref. [3]) M = Mach number n = total number of unknowns N = total number of panels R = restriction parameter * Senior Aerodynamicist; Sverdrup Technology, Inc. This material is declared a work of the U.S. Government and is not subject to copyright protection in the United States. u = unit round-off error or relative machine precision for floating point operations uw = axial interference velocity UQQ = reference velocity vw = interference velocity, ^-direction ww = interference velocity, ^-direction x = x-coordinate y = t/-coordinate z — z-coordinate Aa = ww/u00; angle of attack correction e = UW/UQQ', blockage factor fj,j = source strength slope p = bound associated with Gaussian elimination 4> = velocity potential of wind tunnel flow field (j)m = velocity potential of test article (f)w = wall interference velocity potential of the wind tunnel flow field in combination with a set of constants ci, • • • , c4. Then, in incompressible flow, we get: n ,^ = 0 (1) where x is the streamwise coordinate, n is the outward normal vector on the test section boundary, and ci,C2,cs,C4 are coefficients that describe the wall boundary conditions. Table 2 lists values of these coefficients for six different types of boundary conditions. The total perturbation velocity potential (/> may be written as the sum of the potential c/>m caused by the test article and the potential (j)w caused by the wind tunnel walls, i.e. the wall interference potential. We get : (/> = 4>m + w (2) Combining Eqs. (1) and (2), we get : + 02 d dx / • N = ci(t)

A high speed advanced counterrotation propeller, was tested in the NASA-Lewis 9 x 15 foot Anechoic Wind Tunnel at simulated takeoff/approach conditions of 0.2 Mach number. Acoustic measurements were taken with fixed floor microphones, an axially translating microphone probe, and with a polar microphone probe which was fixed to the propeller nacelle and could take both sideline and circumferential acoustic surveys. Aerodynamic measurements were also made to establish the propeller operating conditions. The propeller was run over a range of blade setting angles from 36.4/36.5 to 41.1/39.4 deg, tip speeds from 165 to 259 m/sec, rotor spacings from 1.56 to 3.63 based on forward rotor tip chord to aerodynamic separation, and angles of attack to + or - 16 deg. First order rotor alone tones showed highest directivity levels near the propeller plane, while interaction tone showed high levels throughout sideline directivity, especially toward the propeller rotation axis. Interaction tone levels were sensitive to propeller row spacing while rotor alone tones showed little spacing effect. There is a decreased noise level associated with higher propeller blade numbers for the same overall propeller thrust.

The use of a monorail ro (; kE::t sled system is detailed and recomme nded as a method of obtaining aerodyna mic data in a regime of high Mach and Reynolds numbers .The aerodyna mic and mechanical design of the Sandia rocket sleds is described , and the data c ollection system discussed in detail.The system has been successfu lly used by Sandia Laborato ry t o a cquire pressure data on conecylinders .These data are compared with data from free-fligh t r ockP.ts, wind-tunn el tests, anrl computer calcula tions.A principal advantage of the sled testing method is the high degree of accuracy possible in determini ng actual test condition s, which include Mach number, static pressure , and static temperat ure .Explorato ry tests indicate that sleds may be used to collect other types of experiment al data such as heat-tran sfer and boundary -layer transition .The high-spee d sled testing technique appears to be the most promis ing method of simulatin g flight condition s at low altitudes at Mach numbers up to M = 8.To date, excellent data have been obtained at a velocity of 7430 ft/sec (M = 6.53) which to our knowledg e is the highest velocity ever attained by a ro cket sled.At this speed, and the Holloman Air Force Base track altitude, the Reynolds number was 42 x 106 per ft, and the -dynamic pressure, 55,000 lbs/ft2. I. Introduct ionDuring wind tunnel and f:;:-ee-fiigh t rocket tests of slightly blunted, slender ( 5 to 2 5 degree half-angle ) cone-cyli nder bodies, it was noted that at Mach numbers greater than 4, the surface pressure ratio, Pm/P cn (measure d surface pressure divided by free-stre am static pressure) , in the region just aft of the cone-cyli nder junction was a strong function of free-stre am Reynolds number.Attempts to gather wind tunnel data at Reynolds numbers over 107 per ft and Mach numbers over M = 4. 5 were thwarted by inadequat e high-pressure facilities and/ or inadequat e pressure measurin g capabiliti es to meet the accuracy requirem e nt of 2 percent of the pressure ratio .

This paper analyzes the effect of wind tunnel wall interference on the airfoil aerodynamic performance, based on the results of experiment and CFD numerical simulation. The experimental measurement was made in IET using the low-speed and closed wind tunnel. The airfoil was DU91-W2-250. The numerical simulation with tunnel wall (wall), without tunnel wall (no wall) and without side tunnel wall (no side wall) were performed. Through the comparison the results between Exp and CFD, it is feasible to use CFD numerical simulation in this paper. And we get the following conclusions: the upper and lower tunnel walls make the flowing area decrease and the velocity increase due to the thickness of boundary layer on the walls, and they also casuse that C l and C d increase. The side tunnel walls cause span-wise flowing and delay the flow separation on the surface of airfoil, meanwhile, they cause that the velocity decreases, C l decreases and C d increases. At small angles of attack, the effect of side tunnel walls on the flowing of airfoil surface can be neglected. However, this effect is very significant at large angles of attack. The classical method can not work well at large angle of attacks for the correction of wall interference in wind tunnel because it doesn’t consider the effect of tunnel wall boundary layer. The C l should be increased through the correction, meanwhile, it is found that the flowing is not two-dimensional flow at large angles of attack in the free-air condition, so we suggest that the pressure measurement with more cross sections or using balance method should be used to obtain the aerodynamic performance of airfoil.

In the paper we present a correction model for wall interference on rotors of wind turbines or propellers in wind tunnels. The model, which is based on a one-dimensional momentum approach, is validated against results from Navier–Stokes computations using a generalized actuator disc principle. In the model the exchange of axial momentumbetweenthetunnelandtheambientroomisrepresentedbyasimpleformula,derivedfromactuatordisc computations. The correction model is validated against Navier–Stokes computations of the flow about a wind turbine rotor. Generally, the corrections from the model are in very good agreement with the computations, demonstrating that one-dimensional momentum theory is a reliable way of predicting corrections for wall interference in wind tunnels with closed as well as open cross sections.

Accurate understanding of aerodynamic characteristics is critical for air vehicle design. This study applies the impulse-momentum theorem to estimate internal drag of an asymmetric air vehicle. Both computational fluid dynamics (CFD) and wind tunnel tests were employed. Numerical analysis using STAR-CCM + was conducted across various Mach numbers, while wind tunnel tests were conducted under only specific Mach number conditions. The measured data from wind tunnel tests, which is considered representative, were compared with CFD plane-averaged values, indicating fairly good agreement. However, discrepancies arose when comparing CFD cell-averaged values with the plane-averaged values. To address this, a correction function was developed to describe the differences. It was observed that the ratio of internal drag coefficient from the cell-averaged values to that of the plane-averaged values followed an exponential function of Mach number. This approach allows wind tunnel data to be transformed into a form akin to cell-averaged values, enhancing internal drag estimation accuracy. Future research will explore additional methodologies to further refine and validate the proposed approach.

In order to obtain an understanding of the effects of forward velocity on exhaust noise suppression, flight and wind-tunnel noise tests were conducted using a J85 turbojet engine. Nozzle configurations of primary interest were a 104-tube suppressor with and without an acoustically treated shroud. Engine installation was as nearly idential as possible for both flight and wind tunnel tests. Some differences necessarily existed, however; e.g., for the flight tests the engine was in motion with respect to the microphones, and for the wind-tunnel tests it was not. Exact simultaneous matching of engine speed, exhaust velocity, and exhaust temperature was not possible, and the wind-tunnel maximum Mach number was ∼0.27, while the flight Mach number was ∼0.37. The nominal jet velocity range was 450–640 m/sec. For both experiments, background noise limited the jet velocity range for which significant data could be obtained. The observed forward velocity effects for the suppressor indicate that jet noise has been suppressed to a level where the in-flight directivity is similar to that expected for internally generated noise.

It is often imperative to test and validate the development of active flutter suppression technology in wind tunnels or flight near and beyond the flutter speed. This is done not only to fine-tune mathematical models but also to examine the active control laws that were synthesized from such models. However, in-flight flutter tests are often dangerous, costly, and sometimes infeasible. Wind tunnel tests are usually more affordable and less risky leading to higher productivity in evaluating alternative configurations and control law strategies. The University of Washington’s MARGE-I aeroservoelastic wind tunnel model is a flexible half-wing-body-tail model with active ailerons and elevator. The work here studies SISO mixed-sensitivity H∞ control for active flutter suppression, which is designed subject to requirements and hardware constraints. Such controller is validated by wind tunnel tests, where the closed-loop margins in both simulation and experiments are quantified and compared. A previously published safe wind tunnel and flight test technique is used to generate flutter mechanisms. The set of control surfaces is partitioned into destabilizing and stabilizing ones, where a destabilizing controller reshapes the aeroservoelastic system to yield the desired unstable dynamic characteristics, and the stabilizing controller is used to study active flutter control strategies.

This paper presents results of wind tunnel and acoustic tests to investigate buffet loads on Shuttle Thermal Protection System (TPS) tiles. It also describes the application of these results to the prediction of tile buffet loads for the first Shuttle flight into orbit (STS-1). The tests were conducted in wind tunnels at transonic and supersonic Mach numbers and in a progressive wave tube. The wind tunnel tests included single tiles of various thicknesses and arrays of tiles mounted on both rigid and elastic substructures. The corresponding acoustic tests were of the single tiles only. In most cases the “test” tiles were of Orbiter qualified material and they were bonded to the panels and proof-loaded in accordance with flight-vehicle specifications. The fixtures for the panel installations in the wind tunnels were designed to simulate flow regions on the Orbiter where shock waves and related high pressure gradients and high dynamic loads would occur. The results of the wind tunnel tests indicate that significant tile buffet loads occurred due to separated flows and oscillating shocks. Separated flow excitation caused higher buffet loads than oscillating shocks for a given level of excitation, however, the highest combined steady and dynamic loads occurred when shock waves with ΔP > 1.5 psi were on tiles.

A new improved NI based pressure sensor calibration module is developed at CSIR-NAL 1.2m Wind Tunnel for calibrating and health monitoring of the pressure transducers. The Mach number and non-dimensional coefficients are computed using the pressure sensor data along with the balance data measured during the wind tunnel testing. The pressure transducers used for wind tunnel tests include static pressure transducers, total pressure transducers and base pressure transducers. These transducers are calibrated every six months to adhere to the ISO standards followed by NAL. The introduction of user friendly features and technology upgradation into the new system has enhanced the efficiency of calibration. This paper presents the approach for the new calibration scheme, software architecture, hardware features and typical results. The developed system has been tested and is currently used extensively at 1.2m wind tunnel.

Despite a steady decrease in the overall usage of wind tunnels due to the increasing reliability and speed of computational fluid dynamics (CFD), ground testing remains a fundamental part of the development of an air vehicle. In this context, one of the new trends is represented by data assimilation (DA), whereby experimental and numerical measurements are combined together in an attempt to extract more complete and accurate information from the available data. This work presents an assessment of a variational data assimilation framework for the problem of wind tunnel wall interference corrections. The methodology minimizes the discrepancy between experimental measurements and the corresponding values from a Reynolds-averaged Navier-Stokes (RANS) simulation by optimally tuning the free-stream angle of attack and Mach number, as well as a corrective field for the turbulence model. The framework is first validated on synthetic data, and then tested on two cases at high Mach number and low angle of attack using pressure coefficients on the model’s surface as the reference measurements. The assimilated pressure coefficients match the reference ones better than those obtained from a linear correction technique. Furthermore, assimilating also a corrective term in the turbulence model improves the quality of the results with respect to assimilating only the angle of attack and Mach number.

Obtaining accurate predictions of aircraft aerodynamic coefficients from wind tunnel tests is a difficult task Wind tunnel users have struggled with the effects of wall interference, model support interference, subscale Reynolds number, etc for almost the entire history of powered flight Since wall interference is one of the principal problems this paper emphasizes the need to minimize it, especially in the near sonic test regime Practical ways of minimizing wall interference are identified This is best accomplished for near sonic testing by locally variable porosity with inclined hole perforations A number of porosity setting schemes are identified some of which are quite simple

In order to evaluate the accuracy of computational fluid dynamics (CFD) for flow over a ship geometry, a comparison with an existing wind tunnel test of a simplified LHA hull with wind straight down the bow is made. One of the U.S. Navy's main interests in ship airwakes is the effect they have on aircraft operating nearby. In the interest of providing a more uniform flowfield in the vicinity of the ship, the wind tunnel test also investigates the effect of adding a downward -deflected flap to the bow, meant to mimic the rounded deck edge at the bow of later LHD -class ships, in contr ast to the sharp 90 -degree corner found on LHA - and earlier LHD -class ships. The CFD portion of this test also evaluates the effectiveness of the bow flap to show if CFD can match the trends of such geometry modifications. Furthermore, the CFD test investi gates the sensitivity of the solution to the grid resolution at the bow, where a large separation bubble affects a large portion of the flight deck, and will also determine if filtering the CFD data to mimic the performance of the wind tunnel equipment alt ers the results. This study seeks to validate CFD against wind tunnel data for this geometry and reinforce the wind tunnel assessment of the bow flap’s effectiveness. I. Introduction All branches of the U.S. military share an interest in the operation of air craft in the vicinity of ships. The airwake shed as wind flows over a ship can greatly influence the safety and ease of such operation. Features such as antennae, masts, radomes, deck equipment, and superstructures generate a complex flowfield that varies substantially with wind speed and direction. Due to the expense of repeating flight tests over different combinations of wind speed and direction, and with different aircraft types, CFD becomes an important tool in reducing such a test matrix by screening test conditions to those most crucial, and by evaluating ship geometries to predict problems and establish best design practices early in a ship's planning stage. To date, wind tunnels have borne much of the load for ship airwake testing, but they suffer f rom several drawbacks. Obviously, wind tunnels must use very small scale factors for ships, but they cannot achieve the airspeed required to match full -scale Reynolds numbers (Re). The small scale also decreases the period and size of pertinent flow featur es, making them difficult to detect. In addition, wind tunnel tests often require lengthy surveys or prior knowledge of the flowfield to find and adequately resolve off -body flow phenomena. In contrast, CFD can run any arbitrary physical scale, output resu lts at a user -determined frequency, and provide results over the entire solution space as a matter of course. However, wind tunnels certainly still provide an invaluable service in validating CFD and in testing conditions for which CFD is currently not sui table.