Hydrogen-powered aircraft offer a promising pathway to reduce the aviation sector’s climate impact, with fuel cells providing high-efficiency power conversion at around 50 ^∘ C. Since this heat is generated inside the aircraft, implementing an active thermal management system to dissipate it becomes a critical design consideration. In this paper, a holistic design methodology for the TMS to calculate its mass, power demand, and drag is presented. Exceeding previous work, the assessment includes the impact of this integration on the design of other on-board systems and the aircraft’s performance in terms of mission energy. Thereby explicitly covering "snowball effects" at the system level. Applied to the 70-passenger ESBEF-CP1 concept aircraft, the analysis shows that the TMS itself adds around 3850 kg system mass distributed over ten pods, 7 kN drag, and 700 kW peak fan power, resulting in a 29
Flight through the lower part of the Earth’s atmosphere with active convection is characterized by high turbulence intensities. This has important consequences for the design of smaller aircraft, UAVs, and wind turbines. Dedicated free-flight measurements with a high performance sailplane revealed an increase in friction drag for inflow conditions with high turbulence intensities. The present study aims to investigate the reasons for this drag increase. Next to the exaggeration of small scale modes in the transitional boundary layer, such as Tollmien-Schlichting waves, high inflow turbulence causes unsteady inflow conditions on scales affecting the overall airfoil pressure distribution. Employing an experimental setup in the Laminar Wind Tunnel, the influence of such large scale fluctuations is investigated. For this study, these experiments are limited to periodic, two-dimensional inflow oscillations with low reduced frequency to enable high-resolution phase-averaged results. A gust generator is used upstream of a natural laminar flow airfoil to generate the specific inflow oscillations. Lift and drag coefficients are measured with pressure sensors installed in the wind tunnel model and in a wake rake. A low response time is realized to capture the unsteady airfoil behavior. In parallel hot-film sensors are used to measure boundary layer quantities, allowing for a spectral investigation. The results presented in this publication show an increase in drag coefficient at the lower corner of the laminar bucket, consistent with observations from the free-flight measurement campaigns. Hot-film sensor data and spatiotemporally resolved wake rake measurements clearly demonstrate the temporal upstream shift of the transition front on the pressure side, as well as the resulting increase in drag. A spectral evaluation of the hot-film sensor data underlines this finding. For the suction side of the investigated airfoil, no similar behavior could be observed, obviously due to the significant differences in the base pressure distribution.
This paper presents the powertrain integration as well as the structural wing design of an unmanned demonstrator. Different powertrain integration and structural concepts were qualitatively evaluated and compared to identify the most suitable approach. More precisely, different concepts for the placement of the batteries and the inverters were compared. Additionally, various structural concepts for the wing design were analyzed. Load-bearing connections between the powertrain components and the necessary wing structure to withstand the expected loads during flight testing were designed. All structural elements were iteratively designed to reduce weight while ensuring strength and stability. The structural integrity was verified with suitable finite element simulations. Furthermore, the resulting wing design for the eight-engine distributed electric propulsion concept was compared to a reference design. For this comparison, a second wing, with the same wing area, but only two electric engines with the same propulsive power was developed. Although, the wing structure of the distributed electric propulsion version is 9
This article presents a simulation and optimization framework designed to identify the optimal external geometry of candidate launchers for space during conceptual design phase. The framework employs statistical analysis on an archive generated through the optimization process to identify and rank the most influential control variables. This is accomplished by storing and post-processing the chromosomes produced by the genetic algorithm, using quantitative methods such as eta-squared and correlation techniques, to reveal the relationships and effects of each control variable on aerodynamic efficiency. The resulting rankings are compared with a rapid sensitivity analysis to assess the practicality and effectiveness of these methods. This approach improves the understanding of how design variables influence overall performance, offering valuable insights for refining and optimizing aerospace conceptual designs. A semi-analytical method is used for aerodynamic prediction, enabling the calculation of aerodynamic coefficients, which supports trajectory simulation through the integration of equations of motion.
The climate impact of aviation resulting from both CO_2 emissions and non-CO_2 effects is gaining attention from aviation stakeholders seeking to identify potential mitigation options. There is a need to consolidate the use of assessment methods and climate metrics, which are required to convert aviation non-CO_2 effects into CO_2 -equivalent emissions. We provide an overview of the operational, technological and scenario-based climate impact assessment methods that have been applied in literature as well as considerations and requirements for the choice of climate metric. We propose a four-layer technology climate impact assessment methodology, which includes: (1) the technology parameters, such as entry into service and temporal and spatial network use; (2) the calculation of three-dimensional aircraft trajectories and emission inventories; (3) the calculation of radiative forcing and induced temperature change time series; and (4) the overall climate impact, measured using a climate metric. We recommend two climate metrics that best fulfill the requirements, the Average Temperature Response (ATR100) and the Efficacy-weighted Global Warming Potential (EGWP100), both over 100 years. Additionally, we discuss further steps, such as the understanding of the most sensitive parameters in this approach, how uncertainties can be included to provide robust estimates, aspects of verification and update possibilities for new findings in research.
The optimisation of aircraft performance is a crucial aspect of improving fuel efficiency and thus reducing the environmental impact of air transport. A potential improvement for the early design process of an aircraft in terms of time efficiency and accuracy, is the involvement of more accurate, computationally based data instead of statistically based handbook methods. To overcome huge calculation times for higher fidelity data acquisition, surrogate models, which are mostly regression-based models fed with results from higher order models, are a promising solution. In this paper, a process for the automated generation of surrogate models for aeroelastic structural sizing optimizations, using an open-source Python-library is investigated. After methodology development and implementation work, different surrogate algorithms are applied to a test case. The tested surrogate models for aeroelastic structural sizing executes within seconds, compared to hours for the original calculation method. This enormous performance gain enables the calculation of derivatives for an optimization-algorithm and thereby further increases the performance of a surrogate-based shape optimization.
Future high-speed propulsion concepts hold great potential for routine space access and sustainable high-speed flight. However, their development still requires extensive research, particularly in understanding the complex base flow aerodynamics during transonic flight, thus requiring detailed experimental testing. Transonic testing and numerical simulations of tunnel-installed, powered-on models still present many challenges and limitations. In this work, a combined experimental and numerical study is carried out, in an attempt to address some of these challenges. The aim is to identify effective approaches based on Reynolds-averaged Navier–Stokes simulations and to assess their accuracy in predicting the mean base flow for a high-speed, powered-on model installed in a transonic tunnel under large blockage conditions. The motivation stems from the high blockage ratios typically encountered in small-scale transonic facilities when testing powered-on models. This environment is challenging to model computationally. Important details related to computational domain, boundary conditions and proper matching of the experimental flow state are discussed. The impact of the blockage and model support on the base flow inside the tunnel, as well as its similarity relative to free-air conditions, are also highlighted. The results show that the proposed modelling approach can capture the flow field with a maximum error in the base pressure which is below 1.6
A piloted simulation experiment was conducted in the NASA Ames Vertical Motion Simulator to quantify differences in pilot workload and mission effectiveness between different levels of flight control augmentation (ranging from enduring fleet representative to advanced fly-by-wire) during two scout-representative mission vignettes. The study used a combination of experimental test pilots and operational pilots, and data collection included classic (rating scales) and emerging (physiological monitoring) techniques. Four aircraft configurations were included in the study, consisting of two configurations with full-authority fly-by-wire flight control systems representative of current state-of-the-art designs, and two configurations with partial-authority flight control systems representative of those found on enduring fleet aircraft. Overall, the full-authority fly-by-wire configurations showed improvement over partial-authority legacy flight control system configurations in all metrics examined, including improved ability to fly lower and maintain airspeed, reduction in workload, and increase in mission effectiveness.
This paper describes the first ever flight demonstration of a stability augmentation system using electromechanical inline actuators in a rotorcraft without hydraulic force amplification. A coaxial ultralight helicopter equipped with the stability augmentation system is used as a flight demonstrator. The paper covers the synthesis of requirements for the system, the design process and architecture of the system, technical challenges, the algorithms including the control laws, safety features, flight testing, and flight test results. The flight test campaign includes scaled down versions of well established mission task elements for handling qualities evaluation adapted from literature. Measurement data and pilot feedback indicate that the stabilization is effective and workload is reduced. The flight demonstration proves that the proposed system can be integrated safely into small rotorcraft despite the space and weight limits and the actuation force requirements. To emphasize the scientific contribution of the flight demonstration, the paper also includes a brief discussion of the dynamics of reversible control trains, a qualitative explanation of the expected actuator feedback forces, and a description of the associated challenges and open questions.
Future aircraft with increasingly flexible high aspect ratio wings are more vulnerable to gust and turbulence encounters. Active control technologies are therefore required to mitigate the effects of atmospheric disturbances and reduce structural sizing loads. However, the achievable load alleviation performance is constrained by system limitations such as time delays, parasitic dynamics, actuator limits, and sensor noise. In this context, model predictive control systems offer strong potential, as they can address these limitations. This paper presents the design and evaluation of such a model predictive gust load alleviation controller for a flexible test wing. The aeroelastic simulation model is based on a modal description of the structural dynamics and aerodynamic strip theory, with its parameters identified from ground vibration and wind tunnel tests. A Kalman filter is designed to estimate structural loads and non-measurable quantities including generalized structural coordinates and wind disturbances from highly noisy wind tunnel measurements. Preview information of upcoming gusts is provided to the controller, enabling feedforward control to compensate for time delays. The formulation can account for actuator limits and maximum allowable loads, ensuring effective operation within the system boundaries. To reduce the computational effort of the controller, Laguerre functions and an efficient soft output constraint formulation are employed. The resulting control system is evaluated in virtual wind tunnel tests based on the identified model with gust encounters of varying frequency. Further, the effects of degraded actuator limits and failure cases are investigated. Particular emphasis is placed on encounters with short and load-critical gusts, where the controller achieves good load alleviation performance despite restrictive system limitations.
Low visibility conditions due to the presence of fog can lead to delays or cancellations of arriving and departing flights to avoid possible incidents or accidents at airports. Therefore, accurate visibility forecasts are required to keep airport capacity as high as possible. Recently, some studies explored the use of machine learning algorithms and routine surface meteorological observations to produce fog forecasts. This study explores the potential of machine learning (ML) models trained solely on surface observations for short-term fog nowcasting at Ezeiza International Airport in Argentina, within 6 h from initialization time. Three simple ML methods—a logistic regression, a decision tree, and a random forest—were evaluated using 20 years of data. Results show that nonlinear methods (decision tree and random forest) required fewer, simpler predictors to match or exceed the forecasting skill of the logistic regression, which relied more heavily on complex variable transformations. All methods significantly outperformed climatological and persistence-conditional reference models. In all three methods, forecast skill was strongly influenced by the fog condition at initialization time, highlighting the importance of persistence in short-range fog prediction. The results also suggest that future improvements may depend more on incorporating additional atmospheric information than on increasing model complexity alone. The models trained in this study represent a promising operational tool for aviation forecasting and could also complement operational numerical models, whose ability to resolve fog-scale processes remains limited.
The process of transferring fuel from a tanker aircraft to a receiving aircraft is called air-to-air refueling (AAR). This study examines the probe-and-drogue method of AAR, in which a tanker aircraft flies ahead of a receiving aircraft and extends a flexible hose with an attached drogue midflight, allowing the receiver to manually couple its refueling probe with the drogue. In previous research the German Aerospace Center developed two visual, mixed-reality assistance systems to support receiver pilots during contact approach and contact hold by visualizing important, previously unavailable information. One system visualizes the relative speed difference between the probe and the drogue, while the other highlights the drogue’s rim and displays fuel offload information. The second assistance system was only tested in a preliminary state focusing on drogue highlighting without fuel offload and status information. This study examines these assistance systems, though the primary aim is not to evaluate pilot usability and experience, but to assess the effectiveness of the methodology used for evaluating Human Factors (HF) aspects in visual, mixed-reality assistance systems during simulated AAR contact approaches. Conducted in a fighter aircraft simulator, the study involved six experienced fighter aircraft squadron pilots performing multiple refueling contact approaches with and without visual assistance. Alongside simulator flight data, HF aspects such as workload, situation awareness, performance, usability and user experience were recorded and analyzed. The applied methodology proved to be effective for evaluating HF aspects of visual mixed-reality assistance systems for pilots. However, the employed methods did not yield robust statistical findings, as expected given the small sample size. Nevertheless, the findings suggest that visual mixed-reality assistance systems may influence pilot behavior and may facilitate pilot support during manual AAR.
Designing supersonic wings requires substantial resources, and the rapid generation of accurate data sets is crucial for the iterative design process. This research focuses on improving the current vortex lattice method (VLM) to enhance its capabilities for supersonic wing design. Four principal improvements are introduced: (i) advanced unsteady analysis modelling via the Unsteady VLM (UVLM) for better dynamic analysis, (ii) enhanced drag prediction through refined shockwave modelling using the Taylor-Maccoll hypervelocity approach (TMHM), which modifies the aerodynamic influence coefficient (AIC) matrix to account for shockcone interactions at each panel, (iii) improved compressibility correction by incorporating the multiphase lattice Boltzmann method (LBM) using a double distribution function on a D2Q9 lattice with a 6-moment equation for greater accuracy in supersonic flow, and (iv) integration of these improvements within the Tornado VLM framework. Verification and validation against Reynolds-averaged navier–stokes (RANS) and Unsteady RANS (URANS) simulations are performed for two supersonic configurations: the SCALOS canard aircraft and the Concorde delta wing. The improved VLM demonstrates reductions in drag coefficient prediction error of up to 21
A variable cycle engine provides the capability to operate the same engine at high thrust requirements with high specific thrust and at low thrust requirements at low specific fuel consumption. The variation of bypass ratio and thereby mass flow rate can also be utilized to reduce the spillage and aftbody drag of the aircraft. This characteristic of the variable cycle engine potentially increases the mission endurance and makes it a candidate for sixth generation fighter aircraft. The disadvantages of a variable cycle engine are the more complex mechanical layout and control structure as well as higher engine mass. Thus, the engine selection for a future fighter aircraft requires carefully executed studies. For the multi-disciplinary study presented here, extensive data on spillage drag and especially aftbody drag was generated. So, the drag values as well as the fuel consumption during the mission of a generic fighter aircraft can be calculated. The major boundary condition of this study is to leave the airframe unchanged in order to focus on the comparison of the engines and have no further influence from the airframe. The results show that the bypass ratio of the variable cycle engine can be scheduled to reduce both the spillage and aftbody drag compared to the conventional engine. When the engine mass remains the same, this leads to a small benefit in mission endurance. With an investigated engine mass penalty of 200 kg on the other hand, the mission endurance of the aircraft with variable cycle engines is lower than the one of the conventionally powered aircraft.
Urban Air Mobility (UAM) is emerging as a disruptive solution to traffic congestion, environmental degradation, and limited transport infrastructure in densely populated cities. At the core of UAM systems are autonomous electric Vertical Take-Off and Landing (eVTOL) aircraft, designed to operate within complex urban airspaces. This review examines how Artificial Intelligence (AI) serves as a foundational enabler in the development, operation, and integration of eVTOL platforms. It explores AI’s critical role in flight control, real-time navigation, path optimization, fault detection, and predictive maintenance. Enabling technologies such as digital twins, edge AI, and distributed learning frameworks are also reviewed, with emphasis on their role in enhancing decision-making, scalability, and operational resilience. In addition, this paper identifies pressing challenges that must be addressed before large-scale deployment becomes feasible, including limitations in battery technology, fragmented AI integration, regulatory uncertainties, and ethical concerns surrounding autonomy and human oversight. A phased strategic roadmap is proposed, outlining the transition from supervised trials to fully autonomous, AI-managed aerial mobility networks. The paper also highlights the need for standardized testbeds, real-world validation environments, and ethical co-design practices to ensure trust, compliance, and social acceptance. Ultimately, the review underscores the necessity of multidisciplinary collaboration across AI, aerospace engineering, urban policy, and ethics to realize a sustainable and intelligent UAM future.
This paper presents a sizing and design methodology for the conceptual phase of blended wing body (BWB) aircraft aerodynamics. The proposed design framework provides a sized and trimmed lifting body with predefined longitudinal stability. Starting from a specified sizing point and cabin geometry, a four-segment lifting body planform is constructed. The fuselage segment is defined by encasing the cabin, while the remaining lifting surface area is allocated to the wing and sized according to the required wing loading. The methodology incorporates distinct longitudinal stabilization and trimming processes. The aerodynamic center is primarily determined by the lifting body planform, allowing an independent definition of the aerodynamic behavior based on airfoil selection. To achieve desired stability margins, the wing is relocated in relation to the fuselage in an iterative process. To minimize vortex lattice method executions, a Gaussian Process Regression serves as a surrogate model in determining the aerodynamic center location. Tailored fuselage airfoils provide both positive pitching moments and lift through variations in camberline and thickness distribution. The iterative trimming process ensures that the aerodynamic behavior meets the design requirements while fitting the cabin within the fuselage airfoils at all times. Ultimately, this methodology yields a sized and trimmed BWB lifting body with well-defined longitudinal stability characteristics, enabling effective exploration of the BWB design space. The paper is limited in scope as it does include simplified mass models, no structural boundary conditions or consideration of flight dynamic lateral motions.
Rotorcraft gearboxes are quite unique in the industry as they generally deal with high power, high overall gear ratio, low available space and a strong push towards weight reduction. The first reduction stage typically deals with very high input speeds. The main functional components (gears and bearings) typically require pressurized lubrication; when for any reason oil is not effectively drained away it can lead to overheating, especially on high-speed gears. Even if literature provides many examples both in academic and industrial environments, the specificity of each case makes it impossible to draw general conclusion. For the same reason, the current work is based on experimental testing on two cases shown here to exemplify the issue and its solution. The first example represents a Main Gearbox (MGB) where one of the Input Modules (first reduction stage) had a mild overheating issue. Upon investigation it was found that it got entirely flooded with oil; then, after further investigation, the issue was understood and easily solved. The second example shows a Nose Gearbox where an unexpected windage phenomenon prevented oil drainage to the scavenge pump, thus leading to extreme and almost instantaneous overheating of the module. The key result is that identifying the causes of the issues allowed to provide a quick and easy solution.
Enhancing propulsive efficiency at micro aerial vehicle (MAV) scale remains challenging because low Reynolds number aerodynamics, structural flexibility, and severe power constraints limit the effectiveness of conventional rotor design strategies. This paper investigates a new hybrid flapping-rotary propulsion concept, termed the Hybrid Flapping Wing Rotor (Hybrid FWR), which superposes controlled flapping on a rotating blade to exploit stroke-wise asymmetry while retaining a compact rotorcraft architecture. A unified analytical framework is developed, comprising (i) a kinematic model that captures mechanically constrained flapping and inertia-driven passive pitching with experimentally informed transition coefficients, (ii) a blade-element-based aerodynamic model to estimate stroke-resolved forces, and (iii) an experimentally fitted motor–power model to enforce constant input power while varying the hybridisation ratio. The resulting lift-coefficient evaluation accounts explicitly for unequal upstroke and downstroke durations. Model predictions indicate a consistent optimum hybridisation ratio near 0.7–0.8, where aerodynamic loading in the upstroke is minimised, and lift production is concentrated in the downstroke, maximising the cycle-averaged lift coefficient for a given power. More than 200 bench-top trials using a two-motor prototype corroborate the existence of an optimum near a hybrid ratio of 0.7, demonstrating up to a 2.148-fold improvement in power efficiency relative to pure rotation under comparable lift conditions. The findings clarify the physical mechanism governing the optimum and provide a practical basis for efficiency-oriented design and further high-fidelity refinement.
Aerodynamic interactions between propellers and wings can be utilized to increase the energy efficiency of aircraft in cruise flight. Aircraft concepts dedicated to exploit the interactions are wingtip mounted propellers (WTP) and distributed propulsion (DP). The simulation results for three wings corresponding to different aircraft types differing in cruise Mach number and PAX are compared. Thereby, it is determined whether the previously examined findings with the wing of a 19 PAX Beechcraft 1900D type aircraft are only valid for this specific design or replicable. For this purpose, the wings of a Cessna 208 Caravan type aircraft as an example for a 9 PAX and an ATR 42 as a 50 PAX are now considered in addition. In the first part, CFD simulations for the three wings with different propeller-wing arrangements (WTP, partial DP, full DP) in cruise flight are evaluated with respect to the required power and compared with each other. In addition, the influence of the spanwise propeller position and the inclination angle is compared for the 19 and the 50 PAX wings and in the second part, the transferability of the wing-propeller simulations to the aircraft level as well as the energy and emission saving potential of propeller-driven configurations with partial DP are discussed. The second order finite volume flow solver TAU is used for the numerical simulations, employing Reynolds-Averaged Navier–Stokes equations. The influence of the propeller on the wing is modeled with a steady state Actuator Disc method. The study shows that the interactions are qualitatively and quantitatively similar for different aircraft sizes. With partial DP configurations, a saving in required power of approximately 4-5% can be expected relative to conventional propeller driven aircraft purely by utilizing the aerodynamic interactions.
