Applications

Aerospace

Lift-plus-cruise aircraft

Vehicle design

We apply large-scale multidisciplinary design optimization (MDO) to lift-plus-cruise air taxis. Dedicated lifting rotors and a cruise propulsor connect vehicle sizing to very different flight regimes, making system completeness and reliable optimization across mission and failure conditions central questions.

Optimizing the coupled aircraft

An integrated physics-based model accounts for nominal flight, engine-out cases, structural sizing, noise, and electrical limits in one design problem. The optimized NASA reference configuration reduces gross weight by 6.5% relative to its baseline, demonstrating a tractable system-level workflow across the conditions detailed below.

Paper: Ruh et al. [1]

Replacing blanket margins with modeled uncertainty

A separate study uses sensitivity-guided uncertainty propagation to compare nominal, safety-factor, and uncertainty-aware designs. For its assumed uncertainties and formulation, the uncertainty-aware design reduces empty weight by 10.4% relative to the safety-factor design, showing the cost of conservatism in that comparison.

Paper: Wang et al. [2]

Animation of the 15 modeled design conditions, including nominal flight, motor-failure, static structural-sizing, and quasi-steady transition cases. Source paper
Mission diagram showing hover, transition, climb, cruise, descent, motor-failure, and static structural-sizing conditions for a lift-plus-cruise aircraft.
The 15 modeled design conditions: nominal mission, motor-failure, and static structural-sizing cases. Source paper
Diagram connecting a central lift-plus-cruise aircraft geometry model to stability, trim, structures, aerodynamics, acoustics, propulsion, motor, weight, and battery analyses.
A geometry-centric computational model couples the aircraft disciplines used in the full-system optimization. Source paper
Top-view comparisons of initial, baseline, and optimized lift-plus-cruise aircraft configurations.
Planform geometry comparison between the initial, baseline, and optimized designs. Source paper
Plots of optimized aircraft gross weight versus battery energy density and final battery state of charge, with the baseline design marked.
Sensitivity of the full-scale MDO solution to battery energy density and final state of charge; the star marks the baseline design. Source paper

Optimization problem

Optimization formulation
Formulation element Full-scale MDOWing structural sizing — aggregatedWing structural sizing — nonaggregated
CaseNASA lift-plus-cruise vehicle: full-system design
ObjectiveMinimize aircraft mass.Minimize wing structural mass.Minimize wing structural mass.
Design variables
Aspect ratio (wing/tail) 2——
Planform area (wing/tail) 2——
Fuselage length 1——
Rotor radius 5——
Blade chord (5 × 4) 20——
Blade twist (5 × 4) 20——
Battery mass 1——
Motor length 5——
Lift-rotor speed — hover 4——
Lift-rotor speed — transition (5 × 4) 20——
Lift-rotor speed — OEI (4 × 7) 28——
Pusher-rotor speed — transition (×5) 5——
Pusher-rotor speed — climb/cruise/descent 3——
Aircraft pitch — climb/cruise/descent/+3g/−1g 5——
Elevator deflection — transition 5——
Elevator deflection — climb/cruise/descent 3——
Front spar thickness 888
Rear spar thickness 888
Top skin thickness 888
Bottom skin thickness 888
Aircraft pitch angle —22
Total design variables1613434
Constraints
Hover total noise 1——
Hover aircraft trim (Fz, Mx, My) 3——
Climb aircraft trim (Fx, Fz, My) 3——
Cruise aircraft trim (Fx, Fz, My) 3——
Descent aircraft trim (Fx, Fz, My) 3——
Transition aircraft trim (v̇, ṗ, q̇, ṙ) (5 × 4) 20——
OEI aircraft trim (Fy, Fz, Mx, My, Mz) (4 × 5) 20——
+3g and −1g vertical force 2——
Static margin 1——
Transition acceleration (u̇, ẇ) (5 × 2) 10——
Skin-plate buckling 14——
Final battery state of charge 1——
Rotor-radius intersection 2——
Motor torque safety margin 9——
Hover rotor tip speed 4——
Aggregated buckling constraints —2—
Aggregated stress constraints —2—
Aggregated z-displacement constraints —2—
z-force equilibrium —22
Buckling constraints ——14
Stress constraints ——80
z-displacement constraints ——18
Total constraints968114
Models and conditions15 conditions covering nominal flight segments, four one-engine-inoperative cases, and +3g/−1g static cases; coupled aerodynamic, propulsion, structural, acoustic, electrical, and stability models.
Representative sourceSystem-Level, Large-Scale Multidisciplinary Design Optimization of an Air Taxi Concept
Source locatorTable 6, page 15; problem size summarized on page 19.

References

  1. Marius L. Ruh, Michael A. P. Warner, Luca Scotzniovsky, Andrew H. Fletcher, Mark Z. Sperry, John T. Hwang. System-Level, Large-Scale Multidisciplinary Design Optimization of an Air Taxi Concept. Journal of Aircraft, 2026.
    DOIPDF
  2. Bingran Wang, Marius L. Ruh, Aoran Tian, Luca Scotzniovsky, John T. Hwang. Large-scale MDO under uncertainty of an eVTOL aircraft using dimension reduction via global sensitivity analysis. AIAA AVIATION FORUM AND ASCEND 2025, 2025.
    DOIPDF
  3. Sebastiaan P. van Schie, Marius L. Ruh, Andrew H. Fletcher, Michael Warner, Mark Sperry, Luca Scotzniovsky, Nicholas C. Orndorff, Ru Xiang, Jiayao Yan, Han Zhao, Joshua Krokowski, Jiun-Shyan Chen, Darshan Sarojini, Hyunjune Gill, Seongkyu Lee, Andrew C. Tagg, Ryan Anderson, Eric Green, Cibin Joseph, Andrew Ning, Zeyu Cheng, Zhi Cao, Chunting Mi, Alexandre T. Guibert, Ashley Cronk, Alicia A. Kim, Shirley Meng, Christopher Silva, John T. Hwang. Large-Scale Distributed Multidisciplinary Design Optimization of the NASA Lift-Plus-Cruise Air Taxi Concept. AIAA SCITECH 2025 Forum, 2025.
    DOIPDF

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