American Institute of Aeronautics and Astronautics
DESIGN DEVELOPMENT STRATEGIES AND TECHNOLGY INTEGRATION FOR SUPERSONIC AIRCRAFT OF LOW PERCEIVED SONIC BOOM
Peter M. Hartwich,* Billy A. Burroughs,† James S. Herzberg,‡ and Curtiss D. Wiler§
The Boeing Company – Phantom WorksMail Code H013-B308
Huntington Beach, CA 92647-2099
Abstract
This paper describes Boeing’s response to the challenges set forth by the Defense Advanced Research Project Agency (DARPA) in their Quiet Supersonic Platform (QSP) program. The objective of the QSP program was to foster the development, maturation, and integration of technologies that are expected to enable efficient and unrestricted supersonic flight over land. The express intention of the DARPA QSP program management was to drive the development of future supersonic cruise air vehicles off current trend lines. In response to this challenge, Boeing developed an unconventional multi-cycle plan to establish a potentially new design space for deriving low-boom air vehicles. Having put in place low-boom design guidelines in that manner, the next task at hand was to achieve the flight efficiencies as demanded by the DARPA QSP program through technology integration. Four key technology areas were identified. These areas are: (1) nonlinear configuration shaping tools and processes for aiding the design of efficient low-boom configurations, (2) laminar flow control for low lift-independent drag, (3) advanced high-recovery inlet technology, and (4) advanced materials and structural design concepts for low operating weight empty (OWE). The integration of these technologies with several of the Boeing QSP concepts is described along with their potential impact on the integrated air vehicle performance.
Introduction
Today, supersonic flight over land is restricted to remote areas. The sonic boom produced by current supersonic production aircraft is considered too loud to be acceptable to the general public. Sonic boom was one of the key issues that worked against the development of an environmentally acceptable and economically viable (e.g., sufficient market size) High Speed Civil Transport. Similarly, several market analyses seem to suggest that availability of a low-boom aircraft would help to make a business case for launching a Supersonic Business Jet (SSBJ), as unrestricted supersonic flight over land is projected to double the market size for an SSBJ.
A Congressional study was initiated to determine the position of the U.S. Air Force on addressing sonic boom in future air vehicle programs. Besides general good-neighbor policies, the issue of mission planning was to be addressed. For instance, there is concern that rapid forward deployment will be inhibited by restriction on supersonic sorties over friendly nations.
These are only two examples of recent developments that prompted DARPA to launch the QSP program1. The purpose of the QSP program is to foster the development and integration of technology that will permit unrestricted supersonic flight over land for vehicles that could be missionized for either civilian (i.e., SSBJ) or military purposes (e.g., strike or reconnaissance).
The sole requirement of the QSP program was to produce a sonic boom ground signature with an initial pressure rise of less than 0.3 psf. Figure 1 illustrates the significance of this requirement. This figure shows the variation of the initial overpressure of sonic boom ground signatures with takeoff gross weight (TOGW) for existing and planned supersonic cruise aircraft. The QSP low-boom requirement clearly breaks away from the trend line. This indicates the need for the development of unconventional supersonic aircraft concepts to meet the QSP low-boom requirement. As a caveat let it be mentioned that, while deemed difficult to match, the QSP low-boom requirement is still considered as too lenient by many.
The challenge of meeting this low-boom requirement was exacerbated by a host of demanding performance goals established by the QSP program. As envisioned by DARPA, a QSP-compliant air vehicle is a 100-klbs TOGW aircraft, designed for cruise at Mach 2.4, with a range of 6,000 nm, capable of carrying 20klbs payload, being aerodynamically highly efficient [lift-to-drag (L/D) > 11], satisfying Stage-3 noise regulations, and using highly efficient propulsion systems with thrust-specific fuel consumption (TSFC) of less than 1.05 lb/(lb*hr).
This paper recounts the salient features of Boeing’s response to the technical challenges of the QSP program. As a first step, Boeing employed a requirements allocation process to identify key technologies required to meet the challenges of the
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QSP program. This requirements flowdown process spawned a multi-cycle air vehicle development plan to establish an initial design space for low-boom aircraft. Having put in place low-boom design guidelines in that manner, the next task at hand was to achieve the flight efficiencies as demanded by the DARPA QSP program through technology integration. Four key technology areas were identified. These areas are: (1) nonlinear configuration shaping tools and processes for aiding the design of efficient low-boom configurations, (2) laminar flow control for low lift-independent drag, (3) advanced high-recovery inlet technology, and (4) advanced materials and structural design concepts for a low OWE. The integration of these technologies with several of the Boeing QSP concept air vehicles is described along with their potential impact on the integrated air vehicle performance.
Technical Approach
Requirements Allocation Process
Boeing initiated their QSP development program with a requirements flowdown process. This approach has been found useful in identifying vehicle characteristics along with their enabling or enhancing technologies that are relevant to the development of a QSP compliant air vehicle. As applied in the Boeing QSP program, this process consisted of two steps. These two steps are captured pictorially in Figures 2 and 3.
The Requirements Allocation Matrix (RAM) in Figure 2 is used to correlate salient features of candidate QSP air vehicles with the QSP low-boom requirement and QSP performance goals. The QSP performance goals are considered to be prioritized in a manner consistent with DARPA’s vision for the QSP Phase-I program. The take-off gross weight (TOGW) is fixed at 100 klbs, the cruise Mach number at 2.4, and the payload at 20 klbs. The goal is to drive the performance of the QSP baseline air vehicle as close as possible to the QSP range goal. The cruise lift-to-drag ratio is considered to be a fallout. The QSP goals for TSFC and engine thrust-to-weight ratio are considered to be primarily worked by the engine companies. The Stage-3 noise goal is deferred to a later detail design phase.
The RAM in Figure 2 can be interpreted in two ways. Reading it columnwise, the RAM indicates the vehicle characteristics that impact the low-boom requirement or any of the QSP performance goals. The multiple hits in each column suggest the need for integrated QSP airframe/propulsion system solutions. Reading the RAM by rows, it shows the relevance of any particular vehicle characteristic to the QSP low-boom requirement and on the QSP performance goals.
With one exception, the RAM demonstrates that several vehicle features are associated with the QSP low-boom requirement or any of the QSP performance goals. The sole exception is the need for high-temperature structures which is primarily driven by the prioritization of the QSP goal for cruise Mach number and by military requirements. If cruise Mach numbers below 2 were to be considered, conventional aluminum structures could be used which pose little technology risk.
Figure 3 depicts a lower-level flowdown of the requirements that identifies technologies that will either enable or enhance a certain air vehicle feature. All technologies that are of benefit to the engine and nozzle concepts are omitted here as they were pursued by QSP program participants whose focus is on propulsion technology and integration.
The QSP technologies are ranked using an aggregate score that includes their relevance to the overall vehicle concept (i.e., multiple hits across all air vehicle characteristics), their impact on sonic-boom overpressure or a performance measure, their compatibility with Boeing’s QSP baseline air vehicle, and the Technical Readiness Level (TRL) of a certaintechnology.2 The three top-ranked technology areas are all related to configuration shaping. The two lowest-ranked technologies are external synthetic vision and a thermal keel technology for sonic boom mitigation. The external vision technology is considered to have minor impact on either sonic boom characteristics or air vehicle performance. The thermal keel technology has potentially huge impact on mitigating sonic boom.3 Yet, this technology is considered as having very low maturity (= low TRL), and all of its integrations so far with Boeing’s QSP concepts have had an unacceptable adverse impact on the integrated air vehicle performance.
Material trades and advanced structural design concepts have a high impact on payload fraction and range, and are ranked forth. Mid-ranked are three aerodynamics technologies that address the reduction of lift-independent drag. This emphasis on reducing lift-independent drag is founded on experiences in the NASA/Industry High Speed Research (HSR) program as illustrated in Figure 4.
Figure 4 shows a top-down estimate of a feasible design space for Mach-2.4 configurations with an aspect ratio of 2, which is representative of the QSP-type concept air vehicles. These top-down performance estimates were developed in the NASA/Industry High Speed Research (HSR) program.4 The figure of merit is maximum lift-to-drag ratio (L/D) as a function of two shape parameters of a drag polar: CD,0 which is a measure of the
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minimum lift-independent drag, and KE which is the shape parameter of the drag-due-to-lift parabola.
In the HSR program, nonlinear aerodynamic shape optimization was extensively exercised, and the drag-due-to-lift was driven toward the limits of the feasible design space, primarily through twist and camber optimization. By introducing technologies such as novel hybrid laminar flow control and innovative inlet concepts, the QSP program attempted to go beyond the level of aerodynamic performance in the HSR program by reducing the lift-independent drag component as well.
Design Process
The performance and sonic boom characteristics of eight air vehicles were established. Among the eight entries were four “Best-in-Class” air vehicles provided by Boeing advanced projects in the areas of airlifters, strike aircraft, recce airplanes, and supersonic business jets. The other four QSP candidates were based on so-called shape-derived air vehicle configurations. Three of the latter four aircraft configurations exploited shock cancellation5 and slenderness6 principles to design low-boom air vehicles. The remaining shape-derived QSP candidate air vehicle reflects an attempt to derive a low-boom version of an aircraft concept that initially was aimed at drag reduction through exploiting natural laminar flow concepts for supersonic air vehicles with unswept wings.7
Based on their sensitivity to technology insertion, the most efficient air vehicles with the lowest sonic boom ground signatures were subjected to subsequent design iterations. As a fallback position, far-out technologies, presently in their infancy, were identified for reducing the sonic boom ground signatures to QSP-compatible levels in case that configuration design and integration of performance-enhancing and boom-mitigating technologies proved insufficient. These more exotic technologies all involved energy disposition concepts such as plasma discharge.8
Performance Trade Studies
Sonic Boom Assessment
The sonic boom ground signatures for the eight configurations in Figure 5, and of any subsequent variants of these designs, were predicted with the Boeing-proprietary MDBOOM12 wave propagation code, using linear and nonlinear aerodynamic input. Owing to a multipole F-function approximation, the MDBOOM code allows for efficient and accurate sonic boom analysis using aerodynamic input as computed from Computational Fluid Dynamics (CFD) codes. This multipole F-function is the discriminator between the MDBOOM code and other wave
propagation methods that are based on modified linear theory.13 To explain this feature, recall that linear modified theory is valid only in the acoustic farfield. There, the aerodynamic and the acoustic solutions are coupled by
r
FM
p
pp
βτγ
2
),(2 Θ=−∞
∞∞ (1)
with
( )12 −−= ∞Mrxτ (2)
The left-hand side of Eq. (1) links a CFD-based aerodynamic nearfield solution to the acoustic farfield represented by the F-function on the right-hand-side of that equation.12 This equation is only valid if the CFD-computed pressures in that equation represent a so-called farfield radiating solution. This implies that the principle of separation of variables [i.e, p~1/r0.5and F=f(θ,τ)] applies. An obvious approach to using CFD would be to run the CFD solution out to distances where this condition is satisfied. For complex configurations such as low-boom supersonic transports, however, this condition may not be met even at CFD farfield boundary conditions placed at a distance of several fuselage lengths; besides, that would lead to very inefficient CFD solutions.
George14 solved the small-disturbance approximation to the full potential equation using multipoles. Page and Plotkin exploited George’s multipoles to match CFD solutions.12 Their approach works as follows. First, a CFD-computed pressure distribution is sampled on a cylinder of radius R that cuts through the integration domain. Then, multipoles are fit to that CFD solution, using George’s full radius-dependent formulation. In a final step, these multipole fits are then used in their farfield-limit to compute the Fourier components of a farfield F-function.
The accuracy of such CFD-based MDBOOM sonic boom analysis has been demonstrated in flight experiments during the NASA HSR program. There, flight test data were taken at NASA Dryden by having a F-16 chase airplane tracking a SR-71 at supersonic speeds.15 Figure 6 shows comparisons between computed and measured midfield pressure signatures. The two data plots compare the experimental pressure distributions with two sets of CFD-based MDBOOM analyses. The two comparisons show correlations between computed and measured pressures for two different flight conditions and for two different under-track stations. In either plot, the CFD-based MDBOOM results match the experimental data quite well for the nose and canopy shocks. Any
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discrepancies between analyses and experiment are attributed to the fact that the CFD-based MDBOOM analysis omitted modeling of the vertical tails, and it was conducted for flow-through rather than powered nacelles, thus missing spillage and plume effects.
Because of cost and schedule considerations, the CFD-based sonic boom analyses were judiciously used to calibrate the more rapid sonic boom analyses using linear aerodynamics input, and to analyze certain configurations with highly nonlinear fluid dynamics. The latter is exemplified in Figure 7 for one of Boeing’s shock cancellation QSP concepts. This figure compares under-track and off-track sonic boom ground signatures computed for a shape-derived QSP concept air vehicle as computed using linear and nonlinear aerodynamics input. The idea behind this shape-derived QSP concept air vehicle is to exploit shock cancellation for sonic boom reduction. Specifically, this QSP design is intended to contain most of compression wave inside the box wing such that they cannot affect the exterior flowfield. Linear theory fails to capture the complex three-dimensional shock structures in the interior of the box wing; linear theory treats this as a superposition of external shock structures. As a result, the aerodynamic solution from linear theory overpredicts the nearfield pressure signature of this shock-cancellation concept, which leads to much higher overpressures in the ground signature, under track and off track, than predicted by the CFD-based sonic boom analysis process.
CFD-Based Optmization for Low-Boom Configuration Shaping
Boeing believed that high-fidelity tools and processes were required to satisfy the aggressive QSP low-boom requirement. Given the schedule of the fast-paced QSP program, Boeing decided to modify an existing nonlinear CFD-based aerodynamic shape optimization tool, AeroShop (=Aerodynamic Shape Optimization Program) to quickly establish a CFD-based shape optimization capability to aid the design of low-boom QSP concepts. Boeing felt that this plug-&-play approach was the only way to have such a high-fidelity low-boom design capability in hand in time to support the development of Boeing’s QSP concept air vehicle.
The AeroShop design tool and process was developed under the HSR program.16 It is essentially a script-based framework that controls the interaction between the various elements of an aerodynamic shape optimization process. The modularity of AeroShop lent itself to a rather simple extension to include an aerodynamic shape optimization capability for reducing the sonic boom ground signature of a subject configuration. The block diagram in Figure 8
illustrates this comparatively straightforward extension of AeroShop to a combined MDBOOM/AeroShop design software.
Key in this process is the identification of a suite of effective design variables. In the analysis/sensitivity section, each design variable is perturbed, and the aerodynamic response is captured in an Euler analysis. The change in the aerodynamic solution is propagated to the ground using the MDBOOM software. Currently, the changes in overpressure are recorded as sensitivities to changes in the design variables; other sensitivity measures have since been implemented such as perceived loudness measures or RMS deviations from a prescribed shaped boom ground signature. The optimizer determines a feasible multi-dimensional gradient from the complete sensitivity information and drives the overall solutions to a configuration down that path in a process termed “1-D search” or “line search.” Once an extremum in this “1-D search” has been encountered, the next design iteration is begun by perturbing the end-product of the just completed design cycle in the just described manner. Once repetition of this design loop has reached a point of diminishing returns, the optimization process is terminated.
Results
The Boeing QSP program set out by evaluating the sonic boom qualities of the eight initial QSP configurations as defined in Figure 4. The primary intent was to map out a parameter space for subsequent low-boom design studies. A secondary purpose was to determine the effect of configuration shape on the sensitivity of these point-of-departure designs to technology insertion for boom reduction. Here, the latter means to use technology to reduce the cruise weight of the initial QSP configurations. Direct weight reductions were assumed to be achieved through materials trades and advanced design concepts. Examples of indirect weight-reducing technologies are laminar flow control for reduced fuel burn, and waverider inlet technology for lighter and smaller inlets. The key results of this study are captured in Figure 9 by plotting initial pressure rise against aircraft weight.
The primary result of these assessments is that the sonic boom of performance derived aircraft (i.e., Strike) can be reduced by insertion of technology to levels that otherwise can only be attained by shape-derived air vehicles. For the latter, advanced technologies are key to flying these low-boom designs efficiently.
The initial sonic boom assessment as summarized in Figure 9 identified several geometric and/or aerodynamic characteristics as primary sonic boom
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effectors. First off, it appears to be crucial to have an initial perturbation either due to a lifting device (e.g., a canard) or a geometric feature (e.g., canopy). Secondly, the strength of these initial perturbations needs to be comparable to any subsequent pressure perturbations (e.g., the lifting wing shocks). A third shaped-boom effector is the spreading of the major perturbations along the aircraft longitudinal axis so as to delay coalescence of the attendant pressure waves into a single shock. Following these guidelines, nonstandard (instead of the customary N -shaped) sonic boom ground signatures were consistently produced by the reduced boom concept air vehicles.
The two aircraft concepts with the lowest overpressure in the sonic boom ground signature, as shown in Figure 9, were taken forward into additional design cycles. The GCASES tool was used to optimize the performance trades for these two candidate QSP concept air vehicles. These trades identified three key technologies that for either aircraft had the biggest impact on improving systems. These results are illustrated in Figure 10 for variants of the shape-derived QSP concept air vehicle. The upper detail in Figure 10 gives the range of the baseline QSP concept vehicle identified as 403E, and of the 403E vehicle with technology insertions. The technologies are: (1) advanced materials trades and probabilistic structural design, (2) hybrid laminar flow control, and (3) novel inlet technology. These technologies combined increased the range of the 403E version from less than 2,500 nm to more than 4,200 nm. If one assumes that the QSP propulsion goal of a TSFC of 1.05 lb/(lb*hr) will be achieved as well, then the 403E is estimated to flay a distance of close to 5,000 nm. To appreciate these performance data, recall that the 403E is a 100 klbs TOGW aircraft, designed to carry 20 klbs payload at a cruise Mach number of 2.4.
The lower detail illustrates the effectiveness of the MDBOOM/AeroShop optimization technology in reducing the initial pressure rise in the sonic boom ground signatures for yet two other design iterations on Boeing’s shape-derived QSP concept air vehicle. The application of MDBOOM/AeroShop to an earlier variant of the shaped-derived QSP concept aircraft, identified as 402, reduced the overpressure by more than 20 percent. The other MDBOOM/AeroShop application to a later design iteration on the shape-derived QSP air vehicle, taken from the 403x design series, reduced the overpressure by more than 30 percent. These results demonstrate that the MDBOOM/AeroShop tool and process were indeed developed in time to support Boeing’s QSP design development of the QSP-compliant air vehicle. They also attest to the fact that the MDBOOM/AeroShop method was an integral part of the QSP design development process rather than just some showcase demonstration.
Figure 11 illustrates the first-ever application of the MDBOOM/AeroShop process to one of Boeing’s earlier design iterations on a QSP concept aircraft. In just six design iterations, the overpressure of the 402 sonic boom ground signature was reduced from 0.78 psf to 0.62 psf, or by more than 20 percent. This was primarily achieved by reducing the overall strength of the nose/canard shock system as illustrated by the two Mach-contour plots.
In this initial application of the MDBOOM/ AeroShop nonlinear low-boom design tool to the 402 configuration, 22 design variables were used to change the configuration geometry. These 22 design variables included twist and camber variations for the canard and the wing, camber variables for the fuselage, nose droop and angle of attack. As also shown in the composite Figure 11, the optimization of these design variables produced a realistic and buildable design.
The MDBOOM/AeroShop method produced its optimization results in a rather short turnaround time. Using 32 processors of an SGI Origin-2000 computer, a design iteration was completed in 12 wall-clock hours. This rapid turnaround enabled the MDBOOM/AeroShop method to produce timely optimization results for the design development of the QSP baseline air vehicle configuration.
Future extensions of the MDBOOM/AeroShop tool will include the implementation of fuselage shaping variables. Looking further down the road, planform design variables will be included as part of an effort to expand MDBOOM/AeroShop into a multidisciplinary optimization (MDO) toolkit.
In returning to the discussion of key QSP technology areas, first consider advanced materials trade studies and probabilistic design strategies. To begin the discussion of Figure 12, note that one direct benefit of structural weight reduction is its effect on range for one of Boeing’s shape-derived SP concept air vehicles. With a fixed TOGW of 100,000 lbs, replacing 10,000 lbs of structural weight yields approximately 1,800nm increase in range. The Boeing structures trade study has achieved considerable weight reductions through an optimized mix of advanced composite materials, and through application of Boeing’s probabilistic analysis & design system (PADS). Cost aspects were brought into this trade study by assessments of alternate fabrication & assembly methods.
As shown in Figure 12, a composite design (skin-stringer fuselage, honeycomb wing box) utilizing BMI 5250-4 was chosen for its heat resistance and relative ease of manufacture compared to, for instance, the HSR-heritage PETI-5 resins. The development of an ability to use a vacuum assisted resin transfer method (VARTM) for high temperature composites will lower
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production costs. Additional weight savings are realized by considering advanced subsystem technologies such as titanium metal matrix composite designs for the landing gear and all-electric aircraft controls.
The proposed probabilistic analysis procedure aims at quantifying and predicting inherent uncertainties in loads, material, and manufacturing processes. These analyses form the basis for the design of structures that are optimized for the environment in which they are to perform. In a traditional deterministic design approach, safety factors are applied which provide a sense of security but without specific structural failure and reliability values. In this approach, the actual level of protection is unknown. It may be conservative resulting in a weight increase, or it may also be excessive with the resultant increase in risk.
Figure 13 summarizes the integration of a hybrid laminar flow control (HLFC) concept with one of Boeing’s shape-derived QSP concepts. It is assumed that the supersonic natural laminar flow (SSNLF) technology for unswept wings maintains laminar flow up to the 70-percent local chord station of the canard or up to the rudder hinge line of the vertical tail. Suction is applied in the neighborhood of the wing leading-edge highlight. Suction is required to maintain laminar flow in the attachment line boundary layer along a blunt leading edge. Boeing’s design trade studies identified wings with a blunt leading edge as a preferred solution. Blunt subsonic leading edges promote aerodynamic efficiency (i.e., leading-edge thrust) and low-boom characteristics (i.e., suppression of leading-edge shocks). Beyond the leading edge region, the surface roughness concept for maintaining laminar flow on swept wings, developed by Saric and Reed,17 is assumed to maintain extend laminar flow up to the flap hinge lines. Alternatively, a pressure distribution tailoring scheme could also be used to suppress further crossflow generation and extend the laminar flow. The effects of turbulent wedges from wing, canard, and tail tips, from intersections of the canard, the wing, and the vertical tail with the fuselage, and from the engine diverters have been accounted for.
Leading-edge suction on the wing is also used for boundary layer control to maintain attached flow under low speed, high lift conditions, in order to achieve a high L/D for reduced community noise. The effectiveness of suction boundary-layer control for suppression of leading edge separation at high angles of attack was demonstrated in the early 1990s during a wind tunnel test on a modified SCAT-15 model in the NASA LaRC 14x22 tunnel.18 Thus, leading-edge suction holds the promise of obviating the need for high-lift leading-edge devices such as flaps or slats.
This would help to avoid boundary-layer transition due to surface discontinuities as they are typically introduced by conventional leading-edge devices such as flaps.
This application of HLFC technology to this variant of Boeing’s QSP concept air vehicle yielded a reduction of skin-friction drag by about 24 percent. This translates into a total drag reduction of about 8 percent. This estimate includes the impact of a weight penalty due to the need for plumbing and pumps to facilitate the leading-edge suction, and the power requirements for operating the suction pumps.
Figure 14 gives an overview of the inlet technologies considered in Boeing’s QSP program. Boeing has assessed two innovative inlet concepts in the QSP program, a mixed-compression-type inlet with SMART (Smart Mesoflaps for Recirculatory Aeroelastic Transpiration) technology,19,20 and a so-called waverider inlet concept that relies on isentropic external compression. Compared to the mixed-compression-type inlets developed in the NASA/Industry HSR program, these novel inlet concepts hold the promise of lower weight, less drag, and reduced mechanical complexity.
Being yet lighter and smaller than mixed-compression SMART inlets, the waverider-type inlets with SMART technology have been selected for the Boeing QSP baseline air vehicles. In these design studies the question arose as to the mechanical scalability of the SMART concept.
The SMART technology has been pioneered by University of Illinois at Urbanna-Champaign (UIUC) and has so far been demonstrated in small-scale proof-of-concept studies and on sub-scale inlet models. Boeing has planned to demonstrate the SMART technology in bigger wind-tunnel facilities, using SMART passive venting panels sized to the bleed requirements of a real-life supersonic inlet. Other paths to SMART technology maturation are currently still being pursued.
Concluding Remarks
A design development process has been presented for the development of a QSP concept air vehicle. Salient features of the tools and processes as in use at Boeing in the QSP design trade studies have been discussed. Key technology areas were identified for enabling the development of economically viable and environmentally acceptable commercial supersonic cruise aircraft, and of new parameter spaces for cost/range trading in the military strike mission arena. The impact of these technologies was illustrated for several aircraft taken from a multi-cycle trade design study conducted under the auspices of the DARPA QSP program.
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Acknowledgments
This work was funded by DARPA Quiet Supersonic Platform (QSP) Agreement MDA972-02-9-0003 and by Boeing under Internal Research and Development. The Boeing QSP leadership team would like to acknowledge the contributions by the members of the Boeing QSP team: Dave Bruns, Peter Camacho, Luis Carus, James Hager, Eliko Ikeda, Suk Kim, Derek MacWilkinson, Todd Magee, Rick Marsh, Fred McQuilkin, Alan Okazaki, Rich Ouellette, Pradip Parikh, Fred Roos, Markus Schneider, Kamal Shweyk, Tom Tsotsis, and Eric Unger.
References1 Wlezien, R., and Veitch, L.,” The DARPA Quiet Supersonic Platform Program,” AIAA Paper 2002-0143, Jan. 2002.2 Mankins, J., “Technology Readiness Levels,” www.hq.nasa.gov/office/codeq/trl/trl.pdf, Apr. 1995.3 Orr, M., Mozingo, J., Bowersox, R., Marconi, F., and Schetz, J., “Sonic Boom Alleviation by Thermal Keel Configurations, “ AIAA Paper 2002-0149, Jan. 2002.4 Kulfan, R.M., “Configuration Aerodynamics Metrics Update,” 1997 NASA High-Speed Research Program –Aerodynamic Performance Workshop, Vol. I – Executive Summaries, NASA CDCP-1005, Apr. 1997, pp. 103-157.5 Kulfan, R.M., “Application of Hypersonic Favorable Aerodynamic Interference Concepts to Supersonic Aircraft,” AIAA Paper 78-1458, Aug. 1978.6 Seebass, R., and George, A.R., “Sonic Boom Minimization,” The Journal of the Acoustical Society of America, Vol. 51, No. 2 (part 3), 1972, pp. 686-694.7 Tracy, R., Chase, J., and Kroo, I., “Natural Laminar Flow for Efficient Supersonic Aircraft,” AIAA Paper 2002-0146, Jan. 2002.8 Miles, R., Martinelli, L., and Macheret, S., “Suppression of Sonic Boom by Dynamic Off-Body Energy Addition and Shape Optimization,” AIAA Paper 2002-0150, Jan. 2002.9 Guo, C.S.”CASES Aerodynamic Performance Methods,” McDonnell-Douglas Technical Report, MDC 91K1098, Jul. 1992.10 Guo, C.S., “CASES Aerodynamic Design and Analysis Methods,” McDonnell-Douglas Technical Report, MDC-K4847, Aug. 1990.11 Guo, C.S., “CASES Mass Property Estimation System (MAPES),” McDonnell-Douglas Technical Report, MDC-K4351, Mar. 1989.12 Page, J.A., and Plotkin, K.J., “An Efficient Method for Incorporating Computational Fluid Dynamics Into Sonic Boom Prediction,” AIAA Paper 91-3275, Sep. 1991.13 Thomas, C.L.,”Extrapolation of Sonic Boom Signatures by the Waveform Parameter Method,” NASA TN D-6832, Jun. 1972.14 George, A.R., “Reduction of Sonic Boom by Azimuthal Redistribution of Overpressure,” AIAA Paper 68-158, Jan. 1968.
15 Haering, E.A., Ehrenberger, L.J., and Whitmore, S.A., “Preliminary Airborne Measurements for the SR-71 Sonic Boom Propagation Experiment,” NASA TM 104307, Jun. 1995.16 Agrawal, S., Narducci, R.P., Kuruvila, G., Sundaram, P., and Hager, J.O., “CFD-Based Aerodynamic Shape Optimization,” European Congress on Computational Methods in Applied Sciences & Engineering (ECCOMAS 2000), Barcelona (Spain), September 2000.17 Saric, W.S., and Reed, H.L., “Supersonic Laminar Flow Control onSwept Wings Using Distributed Roughness,” AIAA Paper 2002-0148, Jan. 2002.18 Campbell, B.A., Applin, Z.T., Kemmerly, G.T., Coe, P.L., Jr. , Owens, D.B., Gile, B.E., Parikh, P.G., and Smith, D., “Subsonic Investigation of a Leading-Edge Boundary Layer Control Suction System on a High-Speed Civil Transport Configuration,” NASA NASA/TM-1999-209700, Dec. 1999.19 Hafenrichter, E.S., Lee, Y., McIlwain, S.T., Dutton, J.C., and Loth, E., “Experiments on Normal Shock/Boundary Layer Interaction Control Using Aeroelastic Microflaps,” AIAA Paper 2001-0156, Jan. 2001.20 McIlwain, S.T., Kim, J.Y., Loth, E., Geubelle, P.H., and Torterelli, D., “Simulations of an Aeroelastic Control System for Shock/Boundary-Layer Interactions,” AIAA Paper 2001-0269, Jan. 2001.
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Fig. 1 The QSP low-boom requirement breaks away from the trend established by recording the initial over pressures of the sonic boom ground signatures for existing and planned supersonic aircraft.
Fig. 2 Correlations of air vehicle characteristics with QSP performance goals and the QSP Phase I low boom requirement indicate the need for an integrated platform systems solution.
Fig. 3 Correlations of air vehicle characteristics with candidate technologies indicate the need for technology suites rather than “silver bullet” solutions.
American Institute of Aeronautics and Astronautics
6
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8
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11
0
50
DCKEDragLift
××××====
.)( max
KE too high
KE too low
CD0KE
M∞∞∞∞=2.4AR=2
0.0060
0.0064
0.0072
0.00800.0076
0.40
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0.56Laminar Flow Technologies
SMART/WaveriderInlet Technology
CD0too low
Lift
CD0
KExCL2
Drag
CD0• Skin Friction• Volume
• Interference &Excresence
KExCL2
• Induced
• Wave DragDue to Lift
• Lift• Trim
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CD0too high(L
ift/
Dra
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ax
Fig. 4 Aerodynamic performance projections for a supersonic cruise aircraft using estimates of maximum lift-to-drag ratio as a function of lift-dependent and lift-independent drag.
Fig. 5 Illustration of Boeing’s multi-cycle QSP concept air vehicle development program
Fig. 6 Comparisons with flight test data indicate that CFD-based MDBOOM sonic boom analysis is accurate and robust.
Recce
SSBJ
•Laminar Flow•Structures & Materials•SMART
Mili
tary
Co
mm
(100klbs class)
Airlifter
StrikeBalanced Solution
Low Sonic-Boom
Configuration
Sonic Boom Breakthrough Technologies
• Off-Body Energy Deposition
Sonic Boom Technology Enhancements
Shape-DerivedMission-Derived
X (feet)
Ove
rpre
ssu
re,∆
P(lb
s/ft
2)
-50 0 50 100 150 200-10
-8
-6
-4
-2
0
2
4
6
8
10
SR-71 Flight Da taCFL3D / MDBOOM, cylinder a t R/L=0.333CFL3D / MDBOOM, cylinder a t R/L=0.274
H/L=7.88
, ,
M∞∞∞∞=1.25AOA=3.16 deg.CL=0.085CFL3D (Euler)
Track Signatures at ~8 fuselage lengths off the SR-71
SR-71 Flight Test Data
CFD/MDBOOM - R/L=0.333CFD/MDBOOM - R/L=0.274
X (feet)
Ove
rpre
ssu
re,∆
P(lb
s/ft
2)
-50 0 50 100 150 200-10
-8
-6
-4
-2
0
2
4
6
8
10
SR-71 Flight Da taCFL3D / MDBOOM, cylinder a t R/L=0.333CFL3D / MDBOOM, cylinder a t R/L=0.274
H/L=7.88
, ,
M∞∞∞∞=1.25AOA=3.16 deg.CL=0.085CFL3D (Euler)
Track Signatures at ~8 fuselage lengths off the SR-71
SR-71 Flight Test Data
CFD/MDBOOM - R/L=0.333CFD/MDBOOM - R/L=0.274
SR-71 Flight Test Data
CFD/MDBOOM - R/L=0.333CFD/MDBOOM - R/L=0.274
X (feet)
Ove
rpre
ssur
e,∆P
(lbs/
ft2)
-50 0 50 100 150 200 250-4
-3
-2
-1
0
1
2
3
4
SR-71 Flight DataCFL3D / MDBOOM, cylinder a t R/L=0.333CFL3D / MDBOOM, cylinder a t R/L=0.274
H/L=17.1
M∞∞∞∞=1.47AOA=4.06 deg.CL=0.122CFL3D (Euler)
Track Signatures at ~17 fuselage lengths off the SR-71
SR-71 Flight Test DataCFD/MDBOOM - R/L=0.333
CFD/MDBOOM - R/L=0.274
X (feet)
Ove
rpre
ssur
e,∆P
(lbs/
ft2)
-50 0 50 100 150 200 250-4
-3
-2
-1
0
1
2
3
4
SR-71 Flight DataCFL3D / MDBOOM, cylinder a t R/L=0.333CFL3D / MDBOOM, cylinder a t R/L=0.274
H/L=17.1
M∞∞∞∞=1.47AOA=4.06 deg.CL=0.122CFL3D (Euler)
Track Signatures at ~17 fuselage lengths off the SR-71
SR-71 Flight Test DataCFD/MDBOOM - R/L=0.333
CFD/MDBOOM - R/L=0.274
SR-71 Flight Test DataCFD/MDBOOM - R/L=0.333
CFD/MDBOOM - R/L=0.274
Predicted and measured nose andcanopy shocks correlate wellPredictions insensitive to placementof nearfield/farfield interfaceCFD-based MDBOOM analysis stillneeds to include effects of
inlet spillageexhaust plumesvertical tails
Pressures at 0.3 body lengths (R/L=0.3)
SR-71 flight tests were conducted under the sonic boom element of the NASA/Industry High Speed Research (HSR) Program [Haering & Ehrenberger, 1996]
10
American Institute of Aeronautics and Astronautics
Fig. 7 CFD-based MDBOOM results capture nonlinear flow interactions for accurate predictions of sonic boom signatures of complex configurations
Fig. 8 Flow diagram of a modular nonlinear shape optimization methodology for supporting low-boom design development.
Fig. 9 Sensitivity of initial overpressure in sonic boom ground signatures to configuration shaping and to aircraft weight.
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