Aircraft Systems Research Articles

Design methodology and simulation analysis of hybrid fuel cell and battery systems for powering unmanned aircraft systems

Hybrid fuel cell and battery systems are currently among the most promising options for increasing the flight autonomy of unmanned aircraft systems. The ratio between the size of the battery and the fuel cell is a delicate issue in power system design. Both devices are necessary; the battery, with a quick response, to respond to demand peaks, and the fuel cell, with a slow dynamic response, but greater energy density, to increase its autonomy. One of the most important tasks in designing the hybrid system is selecting the appropriate size of each component so that it can respond to peak demands, extend its autonomy as far as possible and reduce its weight.The purpose of this research was to establish a design procedure for hybrid power systems for unmanned aerial systems, which means selecting the best size for each component. The hybrid system's modeling and the dynamic simulation of its response to demand curves are the foundation of this procedure. The simulation results include the consumption of the fuel cell as a function of time, the battery’s charge status and an estimate of its autonomy for each demand curve. The analysis of the simulation results guides the choice of component size, adapting each one to achieve minimum fuel consumption for the characteristic demand curves for which the unmanned aircraft system is designed. After modeling the components of the hybrid system and describing the simulation procedure, this contribution proposes an example of a design for an unmanned aircraft system with a maximum takeoff weight of 20 kg. In this case, the most appropriate size for the fuel cell was 2000 W and a 3000 mAh 10S Lithium-Polymer battery. Fitted with a 12-liter hydrogen tank, stored at a maximum pressure of 300 bar, an estimated autonomy of 1.5 h can be expected.

Assessment of current methane emission quantification techniques for natural gas midstream applications

Abstract. Methane emissions from natural gas systems are increasingly scrutinized, and accurate reporting requires quantification of site- and source-level measurement. We evaluate the performance of 10 available state-of-the-art CH4 emission quantification approaches against a blind controlled-release experiment at an inerted natural gas compressor station in 2021. The experiment consisted of 17 blind 2 h releases at a single exhaust point or multiple simultaneous ones. The controlled releases covered a range of methane flow rates from 0.01 to 50 kg h−1. Measurement platforms included aircraft, drones, trucks, vans, ground-based stations, and handheld systems. Herewith, we compare their respective strengths, weaknesses, and potential complementarity depending on the emission rates and atmospheric conditions. Most systems were able to quantify the releases within an order of magnitude. The level of errors from the different systems was not significantly influenced by release rates larger than 0.1 kg h−1, with much poorer results for the 0.01 kg h−1 release. It was found that handheld optical gas imaging (OGI) cameras underestimated the emissions. In contrast, the “site-level” systems, relying on atmospheric dispersion, tended to overestimate the emission rates. We assess the dependence of emission quantification performance on key parameters such as wind speed, deployment constraints, and measurement duration. At the low wind speeds encountered (below 2 m s−1), the experiments did not reveal a significant dependence on wind speed. The ability to quantify individual sources degraded during multiple-source releases. Compliance with the Oil and Gas Methane Partnership's (OGMP 2.0) highest level of reporting may require a combination of the specific advantages of each measurement technique and will depend on reconciliation approaches. Self-reported uncertainties were either not available or were based on the standard deviation in a series of independent realizations or fixed values from expert judgment or theoretical considerations. For most systems, the overall relative errors estimated in this study are higher than self-reported uncertainties.

Balancing predictability and flexibility through operation volume-constrained visual flight rule operations in low altitude airspaces

The advancement in uncrewed aircraft systems such as small drones and advanced air mobility vehicles such as Electric Vertical Take Off and Landing aircraft (eVTOL) has called for airspace integration at low altitudes of both traditional aircraft, such as helicopters and new entrants, such as drones and eVTOL. Currently, the trajectories and necessary buffers around them of flights operating under visual flight rules are not possible to predict. This research proposes the use of flight mission characteristics to model the trajectory and evaluates temporal, lateral and vertical deviations to define the safety buffers which can be used to generate operation volumes, geo-fencing such low-altitude flights and separating them from other traffic in a safe and efficient manner. Real flight test data obtained for the purposes of this study and pilots’ interviews assure high fidelity and practicability of the proposal.

Degradation of the 2014–2015 Holuhraun vent-proximal edifice in Iceland

AbstractThe earliest stages of volcanic vent degradation are rarely measured, leaving a gap in the knowledge that informs landform degradation models of cinder cones and other monogenetic vent structures. We documented the initial degradation of a 500-m-long spatter rampart at the primary vent of the 2014–2015 Holuhraun eruption in northern Iceland with high-resolution topographic change maps derived from terrestrial laser scanning (TLS) and photogrammetric surveys using an unoccupied aircraft system (UAS). Topographic differencing shows a total negative volume change of 42,637 m3, and a total positive volume change (basal deposition) of 10,304 m3 (primarily as deposition at the base of steeply sloping surfaces). Two distinct styles of volume changes were observed on the interior and exterior of the spatter rampart. Material on the interior of the vent was removed from oversteepened slopes by discrete rockfalls, while diffusive processes were qualitatively evident on the exterior slopes. We propose a novel conceptual landform evolution model for spatter ramparts that combines rockfall processes on the interior walls, diffusive gravitational sliding on the exterior slopes, and incorporates cooling contraction and compaction over the entire edifice to describe the observed modes of topographic change during the onset of degradation. Potential hazards at fresh spatter ramparts are rockfalls at high slope areas of the vent interior walls where contacts between spatter clasts are prone to weakening by fumarolic activity, weathering, and settling. To capture such hazards, our data suggest a cadence for monitoring changes yearly for the first few years post-eruption, and at longer intervals thereafter.

Enhancing sustainable urban air transportation: Low-noise UAS flight planning using noise assessment simulator

Low-altitude flights of unmanned aircraft systems (UASs), such as drones, can cause substantial noise pollution in urban areas. This study aims to tackle the crucial issue of noise in UAS flight planning and analyze the feasibility of implementing low-noise urban flights at a micro level. We employ a virtual flight simulator to accurately model the UAS noise impact in realistic flights and optimize the flight path via a heuristic algorithm accordingly. The flight noise assessment incorporates a sound source modeling technique for practical UAS models and an efficient Gaussian beam tracing method for outdoor noise propagation in realistic environments. Case studies for flight simulations are conducted in a representative resident community and metropolitan area to evaluate the noise impact resulting from different flight paths. By comparing our approach with benchmark shortest-distance paths, we validate its effectiveness in significantly reducing en-route noise exposure, encompassing both instantaneous and continuous noise levels. This method holds great potential for contributing to the planning and management of urban air transport systems. It effectively mitigates noise impact, promoting quieter and more environmentally friendly UAS operations and sustainable urban transportation.

Live Location Sharing System (L2S2): Empowering Management of Unmanned Aircraft Systems (UAS) Operations

Transparency and confidence-building measures in Unmanned Aircraft Systems (UAS) operations continue to be important topics of discussion in various contexts. Transparency helps build trust and alleviate concerns about the use of UAS, especially in sensitive areas or situations where privacy and security are paramount. Meanwhile, confidence-building measures aim to establish trust and mitigate potential risks associated with UAS operations, particularly in complex UAS operations involving multiple teams. These measures include implementing systems that enable the identification and tracking of UAS operations activities that can be achieved through technologies such as global positioning system (GPS)-based tracking systems. Although there are several UAS operations GPS-based management systems available in the market, it requires a certain initial investment cost that creates a barrier for some parties, particularly smaller organisations or those with limited budgets. Therefore, in this study, we have developed a web-based application called as Live Location Sharing System (L2S2) by leveraging the capabilities of Traccar, a free and open-source GPS tracking system. Through this system, the movement activities of the Malaysian Space Agency (MYSA) UAS operation teams can be monitored in real-time by the mission commander, which has finally empowered the management of UAS operations as a whole.

Unmanned Aircraft Systems in Road Assessment: A Novel Approach to the Pavement Condition Index and VIZIR Methodologies

This paper presents an innovative approach to road assessment, focusing on enhancing the Pavement Condition Index (PCI) and Visión Inspection de Zones et Itinéraires Á Risque (VIZIR) methodologies by integrating Unmanned Aircraft System (UAS) technology. The research was conducted in an urban setting, utilizing a UAS to capture high-resolution imagery, which was subsequently processed to generate detailed orthomosaics of road surfaces. This study critically analyzed the discrepancies between traditional field measurements and UAS-derived data in pavement condition assessment. The study findings demonstrate that photogrammetry-derived data from UAS offer at least similar or, in some cases, improved information on the collection of a comprehensive state of roadways, particularly in local and collector roads. Furthermore, this study proposed key modifications to the existing methodologies, including dividing the road network into segments for more precise and relevant data collection. These enhancements aim to address the limitations of current practices in capturing the diverse and dynamic conditions of urban infrastructure. Integrating UAS technology improves the measurement of pavement condition assessments and offers a more efficient, cost-effective, and scalable approach to urban infrastructure management. The implications of this study are significant for urban planners and policymakers, providing a robust framework for future infrastructure assessment and maintenance strategies.

Critically Leveraging Theory for Optimal Control of Quadrotor Unmanned Aircraft Systems

In the dynamic realm of Unmanned Aerial Vehicles (UAVs), and, more specifically, Quadrotor drones, this study heralds a ground-breaking integrated optimal control methodology that synergizes a distributed framework, predictive control, H-infinity control techniques, and the incorporation of a Kalman filter for enhanced noise reduction. This cutting-edge strategy is ingeniously formulated to bolster the precision of Quadrotor trajectory tracking and provide a robust countermeasure to disturbances. Our comprehensive engineering of the optimal control system places a premium on the accuracy of orbital navigation while steadfastly ensuring UAV stability and diminishing error margins. The integration of the Kalman filter is pivotal in refining the noise filtration process, thereby significantly enhancing the UAV’s performance under uncertain conditions. A meticulous examination has disclosed that, within miniature Quadrotors, intrinsic forces are trivial when set against the formidable influence of control signals, thus allowing for a streamlined system dynamic by judiciously minimizing non-holonomic behaviors without degrading system performance. The proposed control schema, accentuated by the Kalman filter’s presence, excels in dynamic efficiency and is ingeniously crafted to rectify any in-flight model discrepancies. Through exhaustive Matlab/Simulink simulations, our findings validate the exceptional efficiency and dependability of the advanced controller. This study advances Quadrotor UAV technology by leaps and bounds, signaling a pivotal evolution for applications that demand high-precision orbital tracking and enhanced noise mitigation through sophisticated nonlinear control mechanisms.

Data-driven integrated study on operational performance degradation detection and recovery control of VFDR

The Variable Flow Ducted Rocket (VFDR) serves as the preferred propulsion system for hypersonic aircraft. However, it is prone to health degradation issues due to component failures, aging, and changes in operational conditions, which significantly challenge flight safety. This study introduces a data-driven integrated control approach for modeling, diagnosing, and remedying performance deterioration. Initially, a method for open-set modeling of performance degradation is developed using the Linear Parameter-Varying (LPV) modeling technique and gap metric theory, tackling the hurdles of data collection, overlapping fault classes, and modeling of unidentified faults in the VFDR system; thus, providing vital data support for detecting performance degradation. Moreover, employing the LPV model for performance degradation, a hybrid deep neural network combining multi-scale CNN and LSTM is trained to diagnose system performance issues online using multi-dimensional time-domain sequential data. Subsequently, a smooth transition control method utilizing sliding mode compensation is applied to regain control of system performance based on diagnostic outcomes and a pre-established VFDR performance recuperation controller. Simulations of three types of performance deterioration scenarios caused by changes in actuators, sensors, and the system's operational environment are conducted to demonstrate the efficiency of the proposed approach. The simulation outcomes affirm that the proposed approach is capable of effectively modeling system performance deterioration, diagnosing faults, and controlling recovery, offering promising technical support for the secure operation of intricate closed-loop control systems with stringent precision and reliability requirements.

Brandt's vole hole detection and counting method based on deep learning and unmanned aircraft system.

Rodents are essential to the balance of the grassland ecosystem, but their population outbreak can cause major economic and ecological damage. Rodent monitoring is crucial for its scientific management, but traditional methods heavily depend on manual labor and are difficult to be carried out on a large scale. In this study, we used UAS to collect high-resolution RGB images of steppes in Inner Mongolia, China in the spring, and used various object detection algorithms to identify the holes of Brandt's vole (Lasiopodomys brandtii). Optimizing the model by adjusting evaluation metrics, specifically, replacing classification strategy metrics such as precision, recall, and F1 score with regression strategy-related metrics FPPI, MR, and MAPE to determine the optimal threshold parameters for IOU and confidence. Then, we mapped the distribution of vole holes in the study area using position data derived from the optimized model. Results showed that the best resolution of UAS acquisition was 0.4cm pixel-1, and the improved labeling method improved the detection accuracy of the model. The FCOS model had the highest comprehensive evaluation, and an R2 of 0.9106, RMSE of 5.5909, and MAPE of 8.27%. The final accuracy of vole hole counting in the stitched orthophoto was 90.20%. Our work has demonstrated that UAS was able to accurately estimate the population of grassland rodents at an appropriate resolution. Given that the population distribution we focus on is important for a wide variety of species, our work illustrates a general remote sensing approach for mapping and monitoring rodent damage across broad landscapes for studies of grassland ecological balance, vegetation conservation, and land management.

Discrete space-time processing in multifunctional radar systems

In radar systems, all basic tasks, from signal detection to their recognition, are solved under conditions of a priori uncertainty arising, among other things, due to natural or organized interference. The task of maintaining a balance between the speed of the information-measuring and control system and the detail of the assessment of the phase coordinates of targets is of particular relevance in modern on-board multifunctional radar systems of fighter aircraft. In such systems, all basic tasks are solved with strict restrictions on space-time resources. The purpose of the work is to analyze the options for reviewing the airspace that provide the solution of basic tasks in multifunctional radar systems with restrictions on the permissible time of observation of targets and taking into account electronic countermeasures. Based on the analysis performed using performance indicators that ensure the noise immunity of multifunctional radar systems, rational variants of a discrete space-time survey for active phased antenna arrays are proposed. In modern antennas with electromechanical scanning, two space viewing modes are used – continuous direction-finding mode and on-pass tracking. In the continuous direction-finding mode, the detail of the phase coordinate estimates is realized only for a single target, but the secrecy of the actions of the multifunctional radar system is not ensured. In the pass-through tracking mode, a high level of detail is provided for assessing the phase coordinates of targets and the noise immunity of multifunctional radar systems. Therefore, in this mode, it is advisable to evaluate only the noise immunity of multifunctional radar systems against the background of natural interference. The greatest detail of estimates of the phase coordinates of targets and noise immunity are achieved in multifunctional radar systems with active phased antenna arrays, the element base of which allows for a fast discrete space-time overview when all parameters of the electromagnetic wave change, including its polarization, according to pseudo-random laws. The use of modern onboard time standards with stability up to 〖10〗^(-18) in combination with high-speed electromechanical switches will significantly increase the detail of the evaluation of the phase coordinates of targets and noise immunity, including during group actions of aircraft. The proposed review options relate to a new priority scientific and technical direction  correction of techniques (principles, methods and algorithms) for the construction of avionics using technological advances in the development of the element base of active phased antenna arrays.

Derivation of Ambient Enhancement Factors of Impregnated Twisted Pairs for Partial Discharge Risk Evaluation

Partial discharge (PD) is the main issue challenging the electrical machine (EM) insulation system for more electric aircraft (MEA) applications. Indeed, the trend of adopting higher DC link voltage and fast switching device further boost the risk of PD. Partial discharge inception voltage (PDIV) is mostly dominated by ambient conditions (i.e., temperature, pressure, and humidity), and their influence is accounted for through experimentally determined ambient enhancement factors. For non-impregnated windings, ambient enhancement factors are suggested by both IEC 60034-18-41 and recent literature. However, in many applications, EMs’ windings are often impregnated with resin to improve thermal performance, mechanical resistance, and electrical insulation. In this case, no indications of the enhancement factors for PD risk assessment are given. The ambient enhancement factors are experimentally determined in this paper to enable the PD risk evaluation for impregnated windings. These factors are obtained relying on an extensive PD investigation, where PDIV and partial discharge extinction voltage are measured under variable temperature, pressure, and humidity conditions. Finally, the tests are performed on different wire types and motorette samples to validate the applicability of the derived factors.

An Advanced Propulsion Motor With Enhanced Winding Cooling System for a Solar-Powered Aircraft

Solar-powered aircraft are being upsized and required to carry more payloads, which poses great challenges for propulsion motors, especially for their cooling considering extreme lightweight. Due to remarkable thermal performance, heat pipes (HPs) become one of the most promising solutions for aircraft propulsion motors. However, this may also lead to extra losses, which requires a more intensive study to maximize HP thermal benefits and minimize motor losses. In this paper, a propulsion motor with an HP-based winding cooling system is developed, and the effects of HP insertion on motor performance are investigated. Firstly, a motor topology is proposed, and five HPs of different sizes are selected from the market as candidates, with their thermal properties experimentally measured. Then, an appropriate HP size is determined based on a comprehensive evaluation of the thermal performance and losses of the motors with candidate HPs. Finally, the above results are verified by motor prototyping and testing. Both simulation and test results indicate a significant improvement in cooling capacity, as well as extended motor performance boundaries.

Investigation on gas–liquid–solid three-phase flow characteristics in aircraft wastewater pipes

The aircraft wastewater system is an important system for civil aircraft. The wastewater is transported through the pipeline under the pressure difference between the cabin and the vacuum wastewater tank, and its flow time and characteristics are crucial for the system design. In this paper, the gas–liquid–solid flow of aircraft wastewater is investigated using the Euler–Euler–Euler multiphase flow numerical simulation method. The influencing factors of wastewater flow are analyzed. Afterward, the impact of different factors on the flow time and characteristics is analyzed, such as pressure differences between the cabin and the tank, pipeline length, pipeline inner diameter, and the disturbance for a straight long pipeline. The results show that the wastewater flow time is reduced from 6.4 to 2.6 s with the increase in the pressure difference from 20 to 60 kPa and increased from 3.4 to 10.2 s with the increase in the pipeline length from 30 to 70 m. The results obtained provide a modern theoretical basis for the design of such systems of vacuum wastewater and have a wide range of applications not only in aviation but also in other modern kinds of transport (rail, shipping), contributing to reducing their negative impact on the environment.

Sensitivity Analysis and Optimization of a Liquid Cooling Thermal Management System for Hybrid Fuel Cell Aircraft

The objective of this work is to perform a comprehensive system analysis of a liquid-cooling thermal management system for a hybrid-electric aircraft using fuel cells for general aviation by sizing and optimizing the system with respect to a given objective. A sensitivity analysis on the different design parameters and model assumptions is also performed and their impact on the aircraft and its performances will be assessed. Firstly, the case study is defined and an optimization is run with some initial assumptions leading to a feasibility study for the implementation of this system. The sensitivity analysis is then undergone for the chosen coolant type and fuel cell stack temperature selected after the first optimization. Incorporating the findings of this analysis, a second optimization is run on the thermal management system with improved inputs in order to demonstrate a scenario with reduced penalty on the aircraft. Preliminary results show that implementing this hybrid propulsion system along with its thermal management is feasible with a reduction in payload and range. In addition, it can be concluded that initial assumptions and design choices are shown to have a significant impact on the system’s sizing and should be considered in aircraft sizing design loops.

Morning Glory Flower Detection in Aerial Images Using Semi-Supervised Segmentation with Gaussian Mixture Models

The invasive morning glory, Ipomoea purpurea (Convolvulaceae), poses a mounting challenge in vineyards by hindering grape harvest and as a secondary host of disease pathogens, necessitating advanced detection and control strategies. This study introduces a novel automated image analysis framework using aerial images obtained from a small fixed-wing unmanned aircraft system (UAS) and an RGB camera for the large-scale detection of I. purpurea flowers. This study aimed to assess the sampling fidelity of aerial detection in comparison with the actual infestation measured by ground validation surveys. The UAS was systematically operated over 16 vineyard plots infested with I. purpurea and another 16 plots without I. purpurea infestation. We used a semi-supervised segmentation model incorporating a Gaussian Mixture Model (GMM) with the Expectation-Maximization algorithm to detect and count I. purpurea flowers. The flower detectability of the GMM was compared with that of conventional K-means methods. The results of this study showed that the GMM detected the presence of I. purpurea flowers in all 16 infested plots with 0% for both type I and type II errors, while the K-means method had 0% and 6.3% for type I and type II errors, respectively. The GMM and K-means methods detected 76% and 65% of the flowers, respectively. These results underscore the effectiveness of the GMM-based segmentation model in accurately detecting and quantifying I. purpurea flowers compared with a conventional approach. This study demonstrated the efficiency of a fixed-wing UAS coupled with automated image analysis for I. purpurea flower detection in vineyards, achieving success without relying on data-driven deep-learning models.

Current approaches in UAV Operational Risk Assessment and Practical Considerations

The expansion of Unmanned Aircraft Systems (UAS) is creating new markets, particularly in Urban Air Mobility (UAM), which presents unique challenges. Beyond the risk of mid-air collisions, UAM services in urban areas introduce ground risks to buildings, traffic routes, and pedestrians. This research explores trends in Ground Risk models for different operation planning stages: strategic, pre-tactical, and tactical. It offers a logical pipeline for UAS operators, emphasizing detailed analysis and data source considerations, along with the importance of model interoperability. Using a Naples case study, the research provides practical steps for national authorities to streamline the UAS authorization process.

Rapid, iterative design approach for preliminary configuration of a High Altitude, Long Endurance aircraft

This paper presents a rapid iterative design approach, used to develop a preliminary configuration of an Unmanned Aerial Vehicle (UAV), which is to perform a High-Altitude, Long Endurance (HALE) mission. First, based on a set of requirements, an initial aircraft concept is developed.The rapid iterative design approach revolves around an energy-based flight profile simulation, which is updated with an improved aerodynamic model of the aircraft during every iteration. An aircraft configuration is defined by a set of constant parameters. A corresponding flight profile consists of an altitude and velocity profile, as a function of time. The behaviour of the aircraft is simulated based on the specified flight profile.For sizing the aircraft components exposed to the airstream, the aerodynamic design phase aims to create an airframe which achieves the performance outlined in the flight performance simulation, utilizing the obtained aircraft parameters. Using the geometric data, a 3D-model of the aircraft is created, which is essential for the aircraft’s weight and balance calculations and for determining the airframe shape exposed to the airflow. A Computational Fluid Dynamics (CFD) simulation is conducted to obtain the actual aerodynamic characteristics of the airframe. If the performance requirement of the flight performance simulation is not met, another iteration of the aerodynamic design phase is required.The design framework stands out due to its rapid iteration capability, accessibility, and straightforward application, making it particularly advantageous for educational settings in which students engage with aircraft design. The approach aims to offer satisfactory results for an initial aircraft conceptualization.This design framework emerged from the DLR Design Challenge 2023, an annual competition hosted by the German Center for Aerospace Research, where student teams develop preliminary aircraft designs. This years challenge tasked the teams with designing an aircraft system to restore internet coverage over a disaster-affected region. The described approach was used to develop the Sentinel System of the DHBW Ravensburg team. However, the simulation and development process is not limited to applications within this challenge.

Experimental Propeller Performance Analysis of Distributed, Single and Isolated configurations

Distributed propulsion (DP) configurations are a promising concept for future aircraft systems. The main objective of the presented experiment is to investigate aerodynamic interactions of such configurations in detail and compare DP results to a single propeller configuration. The experimental setup at the Propulsion Test Facility, TU Braunschweig, features three co-rotating propellers. These are not attached directly to the wing, but are mounted on a separate carrier. This decoupling allows the forces and moments acting on wing and propeller to be considered separately. Additionally, different relative propeller positions are set up easily. In order to eliminate side wall effects, only the centre propeller and the centre wing element are subject of investigation for the distributed configuration. The periodically repeating outboard propellers reduce the wind tunnel interference while providing a true DP setup for the instrumented centre. Additionally to the DP setup, tests for conventional propeller wing configurations (only centre propeller installed) as well as isolated propeller and clean wing tests were performed. Thus, the DP effects on wing and propeller and the effect of the downstream wing on the propeller are clearly identified. The comparison between single propeller and distributed propulsion configurations shows that with distributed propulsion the drag increase is reduced from 326% to 216% compared to a clean wing. This effect is intensified by a greater thrust level and higher angles of attack. In order to identify the distributed propulsion effects, the forces acting on the propeller as well as the resulting efficiency of the propeller are compared between the distributed and single propeller configuration for two different relative propeller positions. The efficiency of the centre propeller is increased due to the outer propellers by approx. 2% to 3%.

Sustainable Urban Drone Operations: FF2020 view

Experts worldwide agree that development of operations of Unmanned Aircraft Systems (UAS, commonly known as drones) above populated areas, to remain socially acceptable, must satisfy a set of crucial criteria: safety, security, environmental sustainability (including noise and pollution reduction) and compliance with legal requirements (encompassing liability, privacy and alignment with urban land use regulations). However, for both commercial organisations and entities carrying flights in the public interest, these operations need to also be economically sustainable. This article considers two illustrative scenarios: (1) the urgent transport of medical equipment (e.g., defibrillators) on an ad-hoc basis, precisely when and where required, rather than on a routine schedule; (2) security or plant safety applications, where a drone remains on standby, recharging its batteries in a designated ‘nest,’ ready to take-off for capturing imagery or sensory data when triggered by security personnel or by automatic alerts (e.g., a camera detecting an individual penetrating a perimeter). Deploying one remote pilot for each ‘sleeping’ drone 24/7 would lead to enormous service costs, difficult to be sustained by any organisation. The drone hence needs to be completely autonomous, meaning that a remote pilot would no longer be necessary. The concept, often referred to as ‘Drones in the Box,’ is technically feasible and currently exists. Organisation of the operations, however, goes beyond technical feasibility. According to the Automation Concept by the Joint Authorities for Rulemaking on Unmanned Systems (JARUS), this falls under level 5 of automation. In this highest level, there is neither involvement of a remote pilot in aircraft flight functions, both on the ground and in the air, nor any human awareness of dynamic operational parameters. In essence, to ensure economic sustainability, the 24/7 operations must entirely eliminate the need for remote pilots. Nonetheless, a UAS operator would still exist as the legal entity responsible for organising and overseeing operations, securing necessary approvals and being accountable for the process. Therefore, a professional job profile would still be necessary, to possibly trigger the flight, receive the collected information and act upon or activate the Emergency Response Plan (ERP) when required. This professional would neither need to be trained nor licenced as Remote Pilot but the position should be 24/7. In scenarios such as the two mentioned examples, security personnel may already be on duty 24/7 to safeguard certain facilities (e.g., hospitals) or provide emergency medical services (e.g., 118 in Italy). These operations could thus become economically viable if these personnel were trained by the operator for this on-demand duty. The Flying Forward 2020 (FF2020) project has coined this role as the ‘Fleet Manager’ and intends to standardise it through ISO (International Organisation for Standardisation), for global harmonisation.