Multidisciplinary Optimization of Aircraft Aerodynamics for Distributed Propulsion Configurations
Abstract
:1. Introduction
2. Development and Tendency of Aero-Propulsion
3. Performance and Coupling Effects of Aero-Propulsion
3.1. Configuration Design of Distributed Propulsion
3.2. Layout Features of Distributed Propulsion
3.3. Aero-Propulsive Coupling Effects
4. Multidisciplinary Analysis and Optimization in Aero-Propulsive Design
4.1. Interaction of Aero-Propulsion
4.2. Wake Ingestion and Propulsion Technologies
- (i)
- Propulsion layout: In terms of the wingspan samples, distances between propulsors are all arranged in an even manner. Their thrust distributions are not arranged by considering the drag on each domain of an aircraft. This arrangement would cause a high drag domain (the central axis of an aircraft) to propel with low thrust and a low drag domain (the domain farther from the center axis) to propel with high thrust. If propulsor location is not considered according to the magnitude of the drag, the thrust might be dispersed and inadequate. It would cause the trailing edge to fail to reach the state of thrust balance, further causing the wake to dissipate. Ultimately, more propulsors would be requested, leading to higher energy consumption;
- (ii)
- Dilemmas in aero-propulsive integration: From the individual BLI local optimization to the aero-propulsive overall optimization, the difficulty of simulating and optimizing the performance of an overall aircraft is still sustained. The first reason is that local optimization results would mismatch the local optimization results of the overall optimization results. The second is that the computational methods and tools used to execute the overall aircraft optimization are more complex than the process for local optimization. In addition, the performance analysis of multidisciplinary objects is inherently flawed, such as the flight range, maximum take-off mass (MTOM), and fuel usage. The designer could adjust these at their discretion. Raising one factor’s performance to be advantaged and lowering the other two, or maximizing two of them and lowering one, can generate an illusion for readers that performance has been improved. Most proposal data are adjusted by optimization, in which the essential problem has not been solved, unless three of those performances are significantly better than others. Otherwise, advanced algorithms or MDAO must be performed on the displayed data.
4.3. Propulsion Controlled Aircraft
4.4. Frameworks of Multidisciplinary Optimization
5. Research Challenges and Future Trends
5.1. Scheme of Aero-Propulsive Configuration
5.2. Flow Distortion Optimization
5.3. Application of Energy Methods
Ref. | Energy Sources | Consumables | Configuration | Gravimetric Energy (MJ/kg) | Composition Product | Emission Product |
---|---|---|---|---|---|---|
[97] | Mechanical | Gasoline | Jet fuel, power | , | + | |
[98] | turbine, fan. | |||||
. | ||||||
[99] | Pneumatic | Liquefied Natural | Gas Generator, jet | |||
[100] | Gas (Methane) | fuel, power turbine, | ||||
Liquid hydrogen | gearbox, fan. | 142 | ||||
[101] | Electrical | Lithium-ion | Battery, DC/AC | |||
(All electric) | inverter, electric | |||||
motor, gearbox, fan | ||||||
[102] | Hybrid-electric | Liquefied Natural | Gas Generator, jet | , | , | |
[103] | (Serial hybrid | Gas, lithium-ion | fuel, power turbine, | |||
[104] | electric propulsion) | electric generator, | ||||
AC/DC rectifier, | ||||||
Battery, DC/AC | ||||||
inverter, Electric | ||||||
motor, fan. | ||||||
[105] | Electroaerodynamic | Lithium-ion | Polymer cells | , | ||
[106] | polymer cells |
5.4. Algorithm of Multidisciplinary Optimization
6. Conclusions
- Propulsion-airframe: The choice of configuration coupling objects lead to a huge performance difference in the aero-propulsive layout. An incorrect pairing potentially loses the layout benefits from an original configuration. When DP is mounted on the TWB wing, a regional propulsor has to be embedded simultaneously in the aft to rectify the problem of wake losses in the aft. Meanwhile, the larger and more concentrated thrust at the aft either fills or even penetrates the wake. These circumstances cause the DP layout to become invalid and redundant on TWB. Contrarily, the coupling relation between DP and BWB can maintain the original thrust characteristics of DP. It can add some extra benefits to aircraft configuration, such as omitting the area and weight of the rudder, improving the flight performance in the L/D ratio, shortening takeoff distance under specific conditions, etc. However, studies in boundary layer ingestion (BLI) in regional propulsion have shown that TWB has a propulsion efficiency advantage over BWB. The reason is that the current distributed method of BLI is unable to fill the wake loss in BWB completely. Since the drag of BWB is not concentrated on the central axis but is diffused, it makes the uniform thrust of DP unable to achieve the effect of thrust–drag balance after being integrated with BWB. To achieve complete distributed advancement, the distribution of thrust should not depend on the number of propulsors, but should take into account the drag on the aircraft;
- Scheme and design: The layouts and frameworks of 59 aero-propulsive cases from different research units are analyzed. Most layout ideas are constructed and based on the parametric model of the predecessors. The propulsor positions are mostly those predicted to be likely to have high propulsion efficiency. Then, various commercial MDO software is used to optimize the target performance, such as flight range, load, fuel quantity, etc. In fact, scheme selection, evaluation, and analysis of aero-propulsion should be conducted before constructing the parametric model, because conducting the MDO with the existing conventional propulsors and DP layout will not obtain a fresh and effective scheme. From an essential viewpoint of DP, DP does not refer to the distribution of propulsors but the distribution of thrust. These physical limitations lead to the neglect of elongated cross-flow fans that can fully cover the trailing edge of the BWB. Additionally, energy or more advanced propulsion systems that could assist the elongated cross-flow fan are also ignored. Thus, a thrust–drag analysis and calculation model framework for the aircraft’s trailing edge is urgently established such that thrust corresponding to the drag can be distributed and coordinated in each trailing part of the aircraft. This configuration could improve layout efficiency and effectiveness to promptly accomplish momentum balance and reduce the energy consumption of flight;
- MDO framework: In terms of multidisciplinary optimization, it can be found that the current goal of disciplinary integration is growing larger. The integrated disciplines include aerodynamics, propulsion, structure, weight, stability, control, and additional duct systems. In the wake of functional coordination and coupling, the problem of mutual interference also happened. In general, splitting or local computing methods are unable to solve these problems. Since there are too many interdisciplinary subjects, large-scale multi-level nesting multidisciplinary optimization modeling and efficient parallel algorithms that possess coupled performance analysis have to deal with these problems. Among them, the path design of system level and attribute classification can be used to improve scale precision and enhance the reliability of parallel algorithms. On the other hand, the current commercial MDO framework allows users to use optimization algorithms easily. However, they are mostly optimization programs with extremely slow convergence speeds. In addition, the codes of these algorithms cannot be modified in order to compare their efficiency. An optimization system that allows users to explore the coupling system and develop, improve, and update personally could accelerate the development of optimization methods. It has become one of the current trends of MDO development.
Funding
Conflicts of Interest
Appendix A
Ref. | Year | Selected BWB | Engines Location | Thrust Split | Number of Engines (Fans) | Mach Number | Wing Area (m2) | MTOM (kg) | Payload (kg) | Fuel (kg) | Pax | L/D (Cru) | Range (km) | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
[8] | 2011 | BWB-450-1 | PA | No | 4 | (4) | 0.85 | 1245 | 390,920 | 47,700 | 142,578 | 480 | 23.90 | 14,353 |
[8] | 2011 | BWB-450-2 | PA | No | 8 | (8) | 0.85 | 1258 | 420,929 | 47,700 | 166,007 | 480 | 24.23 | 14,353 |
[8] | 2011 | BWB-450-3 | BLI | No | 8 | (8) | 0.85 | 1248 | 410,432 | 47,700 | 159,442 | 480 | 24.90 | 14,353 |
[8] | 2011 | BWB-450-4 | BLI | No | 8 | (8) | 0.85 | 1248 | 409,602 | 47,700 | 158,628 | 480 | 24.92 | 14,353 |
[8] | 2011 | BWB-450-5 | BLI | No | 8 | (8) | 0.85 | 1249 | 399,603 | 47,700 | 156,947 | 480 | 24.54 | 14,353 |
[8] | 2011 | BWB-450-6 | BLI | No | 8 | (8) | 0.85 | 1258 | 414,230 | 47,700 | 162,579 | 480 | 24.39 | 14,353 |
[8] | 2011 | BWB-450-7 | BLI | No | 8 | (8) | 0.85 | 1260 | 420,712 | 47,700 | 167,787 | 480 | 24.52 | 14,353 |
[8] | 2011 | BWB-450-8 | BLI | No | 8 | (8) | 0.85 | 1243 | 390,699 | 47,700 | 144,412 | 480 | 24.28 | 14,353 |
[117] | 2007 | CESTOL-3000 nmi | BLI | No | 12 | (12) | 0.80 | 444 | 85,793 | 18,144 | 20,003 | 170 | - | 5556 |
[117] | 2007 | CESTOL-500 nmi | BLI | No | 12 | (12) | 0.80 | 444 | 71,610 | 18,144 | 5821 | 170 | - | 926 |
[117] | 2007 | CESTOL-150 nmi | BLI | No | 12 | (12) | 0.80 | 444 | 69,325 | 18,144 | 3988 | 170 | - | 278 |
[82] | 2014 | FW-UWE | UW | No | 2 | (2) | 0.85 | - | 181,437 | 18,144 | 84,000 | 256 | 20.00 | 16,000 |
[118] | 2011 | BWB-350 | BLI | No | 18 | (18) | 0.85 | - | 232,000 | - | - | 350 | - | 11,112 |
[22] | 2016 | BW-11 mission | BLI | No | 2 | (2) | 0.85 | 1391 | 481,148 | 65,115 | 193,821 | 555 | - | 14,173 |
[83] | 2001 | Hybrid layout-IWB | PA | No | 4 | (4) | 0.85 | 1588 | 518,910 | 103,419 | 280,000 | 975 | 24.5 | 14,168 |
[83] | 2001 | Lifting-body | UW | No | 4 | (4) | 0.80 | 1670 | 583,774 | 121,294 | - | 940 | - | 10,000 |
[35] | 2006 | SAX-12 | BLI | No | 4 | (4) | 0.80 | 754 | 154,290 | - | 74,224 | 215 | 21.9 | 14,816 |
[36] | 2007 | SAX-40 | BLI | Yes | 3 | (9) | 0.80 | 836 | 150,847 | 23,405 | 33,253 | 215 | 20.1 | 9260 |
[119] | 2014 | BWB | PA | No | 2 | (2) | 0.85 | 748 | 186,970 | 22,680 | - | 224 | - | 14,816 |
[120] | 2015 | BWB100-02 | PA | No | 2 | (2) | 0.78 | 254 | 54,295 | 12,882 | 9752 | 105 | 22.5 | 926 |
[120] | 2015 | BWB100-03 | PA | No | 2 | (2) | 0.78 | 261 | 54,295 | 12,882 | 9752 | 105 | 23.3 | 926 |
[120] | 2015 | BWB100-10 | PA | No | 2 | (2) | 0.78 | 236 | 52,345 | 12,882 | 9979 | 105 | 21.4 | 926 |
[120] | 2015 | BWB100-12 | PA | No | 2 | (2) | 0.78 | 248 | 52,345 | 12,882 | 9979 | 105 | 24.3 | 926 |
[120] | 2015 | BWB300-00 | PA | No | 2 | (2) | 0.84 | 797 | 348,586 | 63,957 | 125,781 | 310 | 25.8 | 11,112 |
[120] | 2015 | BWB300-02 | PA | No | 2 | (2) | 0.84 | 892 | 348,586 | 63,957 | 125,781 | 310 | 29.3 | 11,112 |
[121] | 2014 | BWB100-1 | PA | No | 2 | (2) | 0.78 | 261 | 54,975 | 15,014 | 13,608 | 100 | 23.00 | 926 |
[121] | 2014 | BWB160-1 | PA | No | 2 | (2) | 0.79 | 371 | 98,566 | 26,762 | 21,092 | 160 | 26.60 | 1852 |
[121] | 2014 | BWB220-1 | PA | No | 2 | (2) | 0.80 | 594 | 196,224 | 60,872 | 73,028 | 220 | 28.90 | 5556 |
[121] | 2014 | BWB300-1 | PA | No | 2 | (2) | 0.84 | 880 | 375,030 | 317,742 | 138,346 | 300 | 30.00 | 11,112 |
[121] | 2014 | LFC100-1 | PA | No | 2 | (2) | 0.78 | 290 | 53,841 | 14,969 | 13,608 | 100 | 24.00 | 926 |
[121] | 2014 | LFC160-1 | PA | No | 2 | (2) | 0.79 | 460 | 59,073 | 26,308 | 21,092 | 160 | 27.90 | 1852 |
[121] | 2014 | LFC220-1 | PA | No | 2 | (2) | 0.80 | 709 | 201,577 | 61,643 | 73,028 | 220 | 30.30 | 5556 |
[68] | 2018 | BWB | PA | No | 3 | (3) | 0.85 | 900 | 435,617 | 59,000 | 142,622 | 450 | - | 15,742 |
[122] | 2016 | VELA 3 | UW | No | 4 | (4) | - | - | 635,029 | 124,284 | 312,072 | 750 | 22.10 | - |
[123] | 2013 | OREIO | PA | No | 3 | (3) | 0.80 | 744 | 475,800 | 45,359 | 57,611 | - | 23.30 | 12,038 |
[124] | 2011 | N2A | PA | No | 2 | (2) | 0.79 | 859 | 209,333 | 46,720 | 63,458 | - | 21.61 | 11,112 |
[124] | 2011 | N2B | BLI | Yes | 3 | (9) | 0.80 | 846 | 216,545 | 46,720 | 66,587 | - | 21.55 | 11,112 |
[124] | 2011 | N2A-EXTE | PA | No | 2 | (2) | 0.81 | 925 | 213,914 | 46,720 | 65,493 | - | 21.42 | 11,112 |
[125] | 2017 | ACFA | PA | No | 2 | (2) | 0.85 | - | 363,781 | 45,359 | - | 450 | - | 13,334 |
[126] | 2012 | BWB | PA | No | 4 | (4) | 0.82 | 1051 | 405,900 | 122,100 | 151,000 | - | 25.40 | 15,403 |
[127] | 2011 | ERA-224 | PA | No | 3 | (3) | 0.85 | 772 | 202,756 | 45,545 | 56,246 | 223 | 23.53 | - |
[128] | 2012 | HWB98 | PA | No | 2 | (2) | 0.78 | - | 45,813 | 9800 | 5906 | 98 | 20.70 | 4445 |
[128] | 2012 | HWB160 | PA | No | 2 | (2) | 0.78 | - | 75,342 | 17,128 | 10,369 | 160 | 23.10 | 5325 |
[128] | 2012 | HWB216 | PA | No | 2 | (2) | 0.80 | - | 130,136 | 20,185 | 35,349 | 216 | 22.30 | 12,223 |
[128] | 2012 | HWB301 | PA | No | 2 | (2) | 0.84 | - | 246,119 | 53,569 | 66,506 | 301 | 23.50 | 13,890 |
[128] | 2012 | HWB400 | PA | No | 3 | (3) | 0.85 | - | 314,612 | 67,059 | 67,064 | 400 | 23.70 | 10,742 |
[129] | 2018 | Ascent 1000 | BLI | No | 2 | (2) | 0.80 | - | 46,802 | 17,091 | 7983 | 112 | 21.60 | 5926 |
[84] | 2014 | Aft-mounted | BLI | No | 4 | (4) | 0.82 | 1091 | 406,000 | 66,400 | 149,000 | 400 | 27.20 | 14,400 |
[84] | 2014 | Wing-mounted | UW | No | 4 | (4) | 0.82 | 1043 | 406,000 | 66,400 | 157,000 | 400 | 23.70 | 13,600 |
[84] | 2014 | Forward-swept | UW | No | 4 | (4) | 0.82 | 1074 | 406,000 | 66,400 | 183,000 | 400 | 22.50 | 16,500 |
[4] | 2016 | Baseline BWB | UW | No | 2 | (2) | 0.85 | 937 | 203,675 | 33,309 | 64,814 | 350 | - | 14,816 |
[124] | 2008 | BWB | UW | No | 4 | (4) | 0.85 | - | 670,000 | 100,110 | 132,920 | 700 | - | 14,200 |
[130] | 2010 | H1 | BLI | No | 4 | (4) | 0.83 | 540 | 171,287 | 18,371 | 25,368 | 180 | 22.10 | 5556 |
[130] | 2010 | H2 | BLI | No | 4 | (4) | 0.83 | 778 | 279,950 | 44,707 | 11,126 | 256 | 24.40 | 15,372 |
[130] | 2010 | H3 | BLI | No | 4 | (4) | 0.83 | 941 | 470,566 | 60,977 | 126,159 | 354 | 24.10 | 14,075 |
[131] | 2018 | BWB150 | PA | No | 2 | (2) | 0.78 | 308 | 72,000 | 20,500 | 13,320 | 156 | 18.00 | 3917 |
[131] | 2018 | BWB250 | PA | No | 2 | (2) | 0.80 | 575 | 170,000 | 43,800 | 46,580 | 248 | 19.40 | 7264 |
[131] | 2018 | BWB400 | PA | No | 2 | (2) | 0.84 | 818 | 262,000 | 64,000 | 66,555 | 368 | 19.10 | 6700 |
[132] | 2015 | baseline HWB | BLI | No | 2 | (2) | 0.84 | - | 243,253 | 29,030 | - | 300 | 21.60 | 4066 |
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Selected Aircraft | Engine Location | Number of Engines (Fans) | Mach Number | Wing Area (m2) | MTOM (kg) | Payload (kg) | Max. Seat | L/D (Cruise) | Range (km) | Cumulative Noise (EPNdB) | Mission Fuel (kg) |
---|---|---|---|---|---|---|---|---|---|---|---|
SAX-12 | BLI (IPS) | 4 (4) | 0.80 | - | 154,290 | - | 215 | 21.90 | 14,816 | - | - |
SAX-40 | BLI (MPS) | 3 (9) | 0.80 | 836 | 150,847 | 23,405 | 215 | 20.10 | 9260 | 185.0 | 33,253 |
N2A-EXTE | PA (IPS) | 2 (2) | 0.81 | 925 | 213,914 | 46,720 | - | 21.42 | 11,112 | 251.0 | 65,453 |
N2B | BLI (MPS) | 3 (9) | 0.80 | 846 | 216,545 | 46,720 | - | 21.55 | 11,112 | 274.4 | 66,587 |
N3-X | BLI (MPS) | 2 (15∼21) | 0.84 | - | - | 107,048 | 300 | - | 13,890 | - | - |
Ref. | Section | Specific Condition | Benefits | Defects |
---|---|---|---|---|
[48] [49] | Fuselage/ body | TWB | ★ Flight performance is easier to discriminate by accumulated long-term experiences. | ★ The fuselage has to be elongated to embed a circle aft propulsion system, resulting in higher costs with low benefits. |
★ No maneuverability and integration problems; the division of operation for each unit is clear. | ★ The non-integrated “body" is difficult to deploy DP systems. | |||
[50] | BWB | ★ The load distribution is more uniform and significant in load advantages. ★ Easier to implant DP in an integrated platform. | ★ Maneuverability problems have to be addressed for aircraft without rudder and flaps. ★ The interaction between wing, control surfaces, and DP adds complexity to the design. | |
[51] [52] | Wing | Jet wing | ★ Reduces lift-induced drag. ★ The pitching moment of blades could change the direction and magnitude of the thrust vector. It could replace flaps and slats to improve flight performance in stability, controllability, and safety. | ★ In the case of replacing a rudder with wing jets, when the energy transmission process cannot be started on time, there is a dilemma that the control wheel cannot be driven. |
Jet flap | ★ It provides an active circulation control of the airfoil through the suction-side blowing. ★ Ejects high-velocity air from a downward slot so flaps can obtain a high lift. | ★ It has a thinner exhaust port with lower exhaust flow volume, the effect is not as significant as other methods. | ||
[53] [54] | Split wing | ★ Ingesting low-momentum air from the boundary layer can significantly reduce the required kinetic energy, while maintaining the required thrust velocity and thus increasing propulsion efficiency. ★ The truss structure of the split-wing provides adequate load-bearing capacity. It could significantly reduce the wing weight and bending moment. ★ It could garner a high lift coefficient via powered- lift. | ★ The inherent complexity of inboard structures in DP systems must be considered. | |
[55] [56] | Under wing | ★ Can improve the aerodynamic efficiency of the L/D ratio. | ★ The under-wing duct is susceptible to foreign object damage, and its noise is relatively large. | |
[57] | ★ Provide additional bending relief to the main wing structure. | |||
[58] [59] | BLI | ★ Reduced the ram drag at the engine inlet and improved propulsive efficiency (energy-saving). ★ Produce wake filling to reduce the required thrust and energy, further reducing emissions. ★ Effectively balances the CG and offsets part of the load. ★ A noise-shielded configuration. | ★ Anergy comes with energy. It is almost impossible to achieve complete wake filling. ★ The straight duct does not achieve an actual function of BLI, while flow distortion occurs on the embedded S-duct. | |
[60] | Pylon | ★ Provides an appropriate external surface to allow the intake and exhaust integration, access for inspection, removal, and maintenance requirements. | ★ Wetted area and load are increased, and the nose is downward at the thrust moment. ★ A drastic reduction in CG range happens via displaced thrust axis. ★ Have a high static instability. | |
[61] [62] | Trailing edge | Parallel | ★ A parallel trailing edge with nearly 0° of wing sweep makes it easier to arrange the DP to attain momentum balance and reduce wake losses. | ★ Low L/D ratio. |
[63] | Angular | ★ The trailing edge with an angular back sweep Wing has a higher L/D ratio. | ★ The angular trailing edge makes it difficult to shape DP in alignment. It becomes more complex to allocate the thrust speed to meet the momentum balance. | |
Circumfere- ntial | ★ Removing a significant share of fuselage drag could substantially increase the L/D ratio. ★ Provides BLI to serve the wake filling (energy- saving.) | ★ To account for the axisymmetric contraction of the aft towards the fan inlet, fuselage length has to increase by 2.0 m. ★ The horizontal tail needs to be increased to balance the pitching moment of an aircraft; it leads the fuselage to a bending moment, and the weight is increased greatly. | ||
[48] [49] | Propulsor | Regional | ★ The Mach number is generally ≈ 0.85, and the number of engines is less than 4. The thrust force is concentrated and easier to estimate. | ★ Wake losses occur in places without thrust, resulting in high energy consumption. |
[50] [64] | Distributed | ★ A system with more engines has redundancy for increased safety and reliability. ★ Noise can be significantly reduced due to the low bypass ratio of the engine. ★ Smaller and lightly changeable propulsors could improve affordability and reduce the life-cycle cost by up to 50%. | ★ Have to ensure that the wake filling is filled precisely and not excessively. ★ Mach number is between 0.75 and 0.8, and more than 4 engines. The more dispersed the engines, the more the propulsion effect is significantly reduced. |
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Luo, S.; Eng, T.Z.; Tang, Z.; Ma, Q.; Su, J.; Bugeda, G. Multidisciplinary Optimization of Aircraft Aerodynamics for Distributed Propulsion Configurations. Appl. Sci. 2024, 14, 7781. https://doi.org/10.3390/app14177781
Luo S, Eng TZ, Tang Z, Ma Q, Su J, Bugeda G. Multidisciplinary Optimization of Aircraft Aerodynamics for Distributed Propulsion Configurations. Applied Sciences. 2024; 14(17):7781. https://doi.org/10.3390/app14177781
Chicago/Turabian StyleLuo, Shaojun, Tian Zi Eng, Zhili Tang, Qianrong Ma, Jinyou Su, and Gabriel Bugeda. 2024. "Multidisciplinary Optimization of Aircraft Aerodynamics for Distributed Propulsion Configurations" Applied Sciences 14, no. 17: 7781. https://doi.org/10.3390/app14177781