Aircraft Systems Research Articles

Aerial Wildlife Image Repository for animal monitoring with drones in the age of artificial intelligence.

Drones (unoccupied aircraft systems) have become effective tools for wildlife monitoring and conservation. Automated animal detection and classification using artificial intelligence (AI) can substantially reduce logistical and financial costs and improve drone surveys. However, the lack of annotated animal imagery for training AI is a critical bottleneck in achieving accurate performance of AI algorithms compared to other fields. To bridge this gap for drone imagery and help advance and standardize automated animal classification, we have created the Aerial Wildlife Image Repository (AWIR), which is a dynamic, interactive database with annotated images captured from drone platforms using visible and thermal cameras. The AWIR provides the first open-access repository for users to upload, annotate, and curate images of animals acquired from drones. The AWIR also provides annotated imagery and benchmark datasets that users can download to train AI algorithms to automatically detect and classify animals, and compare algorithm performance. The AWIR contains 6587 animal objects in 1325 visible and thermal drone images of predominantly large birds and mammals of 13 species in open areas of North America. As contributors increase the taxonomic and geographic diversity of available images, the AWIR will open future avenues for AI research to improve animal surveys using drones for conservation applications. Database URL: https://projectportal.gri.msstate.edu/awir/.

Integrated Power and Thermal Management System for a Hybrid-Electric Aircraft: Integrated Modelling and Passive Cooling Analysis

Abstract Aircraft electrification introduces challenges in power and thermal management. In a hybrid-electric aircraft (HEA), the additional heat loads generated by the high-power electrical components in the propulsion system can negate the benefits of the HEA. Consequently, an integrated energy management system is required for the HEA to reject the additional heat loads while minimizing energy consumption. This paper presents the integrated modelling method for an integrated power and thermal management system (IPTMS) for HEA. With this method, a platform can be developed to assess the varying efficiencies of the components in the electrical propulsion system (EPS), and the performance of the thermal management system (TMS), such as passive cooling, during a flight mission. This makes it applicable to modular designs and optimizations of the IPTMS. A small/medium range (SMR) aircraft similar to ATR72 is studied. In this study, the EPS operates only during take-off and climb. Therefore, the platform assesses the heat and power loads of the IPTMS for a typical flight mission (take-off and climb) in this study. The performance of passive cooling is also analysed across this typical flight mission and under normal, hot-day, and cold-day conditions. It was found that passive cooling is sufficient under these three conditions, and the active temperature control is requried to ensure the components' temperatures are above the minimum temperatures. These findings imply the potential to minimize TMS weight and energy consumption, providing an insight for further research on IPTMS.

Optimization of 3D Printing While Traveling En Route to Extend Range of Unmanned Aircraft Systems for Multilocation Mission Scenarios

Abstract The nexus of two relatively recent technologies, additive manufacturing and unmanned aircraft systems (UAS), has enabled new and unique capabilities that have only started to be realized in integrated systems. This article explores and quantifies the impact of 3D printing parts for UAS, or entire UAS systems, on an agent platform, while this agent travels to multiple locations as part of a mission objective. The fully printed or enhanced UAS can then be released at launch points farther away from the goal locations. This, in turn, can accelerate mission completion times and reduce travel costs depending upon the ratio between vehicle speed and 3D printing rate. Thousands of scenarios are optimized across the design space to minimize the travel path length for the agent platform as a result of 3D printing en route to the locations of interest. Results indicate that based on the print capability and agent travel speed, an exponential decay in the amount of travel distance of the agent platform occurs. For unity ratios of print speed and agent speed in the considered design space, a decrease of 55% in the total required distance of our agent is observed. This reduction in total travel distance can reduce time, fuel, cost, and other aspects including other environmental and social impacts. A generalized optimization formulation is also presented at the end to enable similar analyses with other en route range-extending technology such as battery charging.

Advanced Manufacturing Techniques in Aerospace Engineering

A significant change in the design, production, and integration of aircraft systems and components has been brought about by advanced manufacturing techniques in aerospace engineering. These methods, which include a variety of cutting-edge procedures and technological advancements, are revolutionizing the aerospace sector by improving the effectiveness, dependability, and performance of airplanes and spacecraft. This article provides a thorough review of the influence of advanced manufacturing methods on the high-stakes area of aerospace engineering by delving into the fundamental definitions, evolution, importance, research gaps, and present significance of these techniques.

In-situ observations of charged Saharan dust from an uncrewed aircraft system

<i>In-situ</i> observations of charged Saharan dust from an uncrewed aircraft system

Privacy’s Sky-High Battle: The Use of Unmanned Aircraft Systems for Law Enforcement in the European Union

Benefiting from the rapid advancements in Unmanned Aircraft Systems (UAS) technology with enhanced tracking and data collection capabilities, law enforcement authorities re-discovered air as a dimension where state power can be exercised in a more affordable, accessible, and compact way. On the other hand, during law enforcement operations, UAS can collect various types of data that can be personal or sensitive, threatening the right to privacy and data protection of the data subjects. Risks include challenges related to data security, bulk data collection, the diminished transparency and fairness resulting from the inconspicuous nature of UAS, as well as ethical concerns intertwined with privacy and data protection. Upon examination of the legal framework including the General Data Protection Regulation the Law Enforcement Directive, various Aviation rules, and the new proposal for the Artificial Intelligence Act, it becomes apparent that the EU legal framework’s adequacy in safeguarding privacy and data protection against law enforcement use of UAS is context-dependent, varying across use cases. The current framework lacks clarity, leading to arbitrary application and limited protection for data subjects. Enforcement of safeguards is insufficient, and the Aviation Regulations, applicable to law enforcement UAS, require member states' opt-in, which has not occurred as of the authors’ knowledge. The Artificial Intelligence Act addresses UAS operations but focuses on market risks rather than obligations imposed on law enforcement authorities. Consequently, the existing framework is rendered inadequate for medium to high-risk law enforcement operations, leaving individuals vulnerable and insufficiently protected against intrusive UAS surveillance. Rectifying this involves addressing the enforcement gap and making the necessary amendments to relevant regulatory aspects. Additionally, the implementation of specific technical measures and steps to foster effective cooperation among stakeholders in UAS deployment for law enforcement is imperative.

Adaptive Flying Assistance Controller Design to Suppress Nonlinear Pilot-Induced Oscillations

Nonlinear pilot-induced oscillations (PIOs) pose a threat to the safety of piloted aircraft in flight. This study aimed to address this safety concern. A novel method for designing an assistance controller based on incremental model predictive control is proposed to aid pilots in suppressing categories 2 and 3 PIOs. In the assistance controller design, the characteristics of the full pilot–aircraft system are considered through a predictive model that integrates the dynamics of the pilot, actuator, and aircraft. This ensures that the assistance controller coordinates with both the pilot and aircraft. Additionally, an adaptive logic for the pilot–controller authority assignment is proposed to automatically adjust the role of the assistance controller. This adaptive logic adopts a model predictive technique to determine whether the pilot’s independent control will cause actuator saturation over the receding prediction horizon. By doing so, the assistance controller is restricted to work only when the actuator saturation constraints are activated. The pilot model-based simulations and the human-in-the-loop experiments demonstrated that the proposed assistance controller can effectively assist pilots in dealing with factors causing nonlinear PIOs while maintaining a harmonious cooperative relationship with the pilot.

UAS‐based multispectral imaging for detecting iron chlorosis in grain sorghum

AbstractThis study uses a small unmanned aircraft system equipped with a multispectral sensor to assess various vegetation indices (VIs) for their potential to monitor iron deficiency chlorosis (IDC) in a grain sorghum (Sorghum bicolor L.) crop. IDC is a nutritional disorder that stunts a plants’ growth and causes its leaves to yellow due to an iron deficit. The objective of this project is to find the best VI to detect and monitor IDC. A series of flights were completed over the course of the growing season and processed using Structure‐from‐Motion photogrammetry to create orthorectified, multispectral reflectance maps in the red, green, red‐edge, and near‐infrared wavelengths. Ground data collection methods were used to analyze stress, chlorophyll levels, and grain yield, correlating them to the multispectral imagery for ground control and precise crop examination. The reflectance maps and soil‐removed reflectance maps were used to calculate 25 VIs whose separability was then calculated using a two‐class distance measure, determining which contained the largest separation between the pixels representing IDC and healthy vegetation. The field‐acquired data were used to conclude which VIs achieved the best results for the dataset as a whole and at each level of IDC (low, moderate, and severe). It was concluded that the MERIS terrestrial chlorophyll index, normalized difference red‐edge, and normalized green (NG) indices achieved the highest amount of separation between plants with IDC and healthy vegetation, with the NG reaching the highest levels of separability for both soil‐included and soil‐removed VIs.

China’s New Pattern of Rule of Law on UAS

China as the world’s prominent market for Unmanned Aircraft Systems (UAS) has just passed a new regulation on UAS. The new regulation is expected to form a new pattern of rule of law on UAS in China. With the need for harmonisation of laws internationally, this article highlights the three aspects out of China’s new UAS legislation against an international setting.

Drone imagery and deep learning for mapping the density of wild Pacific oysters to manage their expansion into protected areas

The recent expansion of wild Pacific oysters already had negative repercussions on sites in Europe and has raised further concerns over their potential harmful impact on the balance of biomes within protected areas. Monitoring their colonisation, especially at early stages, has become an urgent ecological issue. Current efforts to monitor wild Pacific oysters rely on “walk-over” surveys that are highly laborious and often limited to specific areas of easy access. Remotely Piloted Aircraft Systems (RPAS), commonly known as drones, can provide an effective tool for surveying complex terrains and detect Pacific oysters. This study provides a novel workflow for automated detection, counting and mapping of individual Pacific oysters to estimate their density per square meter by using Convolutional Neural Networks (CNNs) applied to drone imagery. Drone photos were collected at low tides and altitudes of approximately 10 m across a variety of cases of rocky shore and mudflats scenarios. Using object detection, we compared how different Convolutional Neural Networks (CNNs) architectures including YOLOv5s, YOLOv5m, TPH-YOLOv5 and FR-CNN performed in the detection of Pacific oysters over the surveyed areas. We report the precision of our model at 88% with a difference in performance of 1% across the two sites. The workflow presented in this work proposes the use of grid maps to visualize the density of Pacific oysters per square meter towards ecological management and the creation of time series to identify trends.

SIMULATION MODEL FOR UNMANNED AERIAL COMPLEXES AT LAUNCHING POSITIONS SURVIVABILITY ASSESSEMENT

The relevance of issues related to the justification of the rational approaches to the combat operations planning using unmanned aircraft systems, which are now assigned the main role in attacking the enemy by fire, necessitates the development of methods for evaluating such actions. The issue of increasing the survivability of unmanned aircraft systems under combat conditions is of important applied importance. The subject of the study is the unmanned aircraft systems application under the conditions of enemy action planning process. The article uses operations research methods. The purpose of the work is to develop a simulation model in the form of an algorithm, that allows conducting process research based on quantitative estimates and substantiating decisions aimed at increasing the survivability of unmanned aircraft systems under conditions of enemy action. By varying the parameters of the simulation model, it becomes possible to develop the most rational solutions for the unmanned aircraft systems use, ensuring the maximum level of their survivability under the specific conditions of combat operations. A simulation model is proposed, with the help of which it is possible to quantitatively evaluate decisions regarding the tactics of using UAV and finding ways to increase the level of their survivability under the conditions of enemy fire. During the implementation of the proposed model, statistics of the results of the simulated fire impact are accumulated, that allows to calculate estimates of the probability of UAV, deployed at the launching positions, to get various degrees of damage. By varying the specified parameters, it becomes possible to develop the most rational solutions aimed at increasing the survivability of UAV under the specific conditions of combat activities performing. The proposed simulation model for the survivability of unmanned aircraft systems assessment may be used in the decision support system for the appropriate level commander.

Aerial Remote Sensing Archaeology—A Short Review and Applications

Aerial and remote sensing archaeology are tools for identifying marks on images of archaeological remains covered by soil. In other words, they are archaeological prospection tools that fall into the category of non-destructive research methods. In this paper, a short review of these valuable research tools is carried out, presenting the way marks appear, and also the categories of aerial and remote sensing archaeology, depending on the medium of storage of images and the type of platform of transfer of sensors. The timing of the emergence of each category is determined and examples of relevant surveys are presented. Focusing on the use of an Unmanned Aircraft System (UAS) with a multispectral sensor (aerial remote sensing archaeology), their partial utilization is revealed for collecting images in areas outside of the visible spectrum, aiming at the identification of covered archaeological remains. To this end, examples of the use of UAS with different sensors are presented and indexes that have been used so far in respective applications are gathered. Aerial remote sensing archaeology took place in two areas of particular interest in Northern Greece. UAS WingtraOne GEN II was used to collect multispectral images. In both study areas, soil and vegetation or crop marks were detected, possibly covered archaeological remains, initially in RGB orthophotomosaics and then more clearly in the index maps, such as the normalized difference vegetation index, simple ratio, brightness index, second brightness index, and anthocyanin reflectance index 2b.

КРАТКИЙ ОБЗОР ВОЗМОЖНОСТЕЙ СОВРЕМЕННЫХ БЕСПИЛОТНЫХ ЛЕТАТЕЛЬНЫХ АППАРАТОВ ПРИ РЕШЕНИИ ЗАДАЧ ПО ОБЕСПЕЧЕНИЮ БЕЗОПАСНОСТИ

A brief analysis and generalization of the possibilities of using modern unmanned aerial vehicles in solving security problems in various fields of human activity is given. The advantages and disadvantages of modern unmanned aircraft systems are noted. Particular emphasis in the description is placed on the promising development of the capabilities of unmanned aerial vehicles. It was noted that until 2030 in the Russian Federation it is planned to invest 560 billion rubles in the development of unmanned aerial systems.

Toward on-demand measurements of greenhouse gas emissions using an uncrewed aircraft AirCore system

Abstract. This paper evaluates the performance of a multirotor uncrewed aircraft and AirCore system (UAAS) for measuring vertical profiles of wind velocity (speed and direction) and the mole fractions of methane (CH4) and carbon dioxide (CO2), and it presents a use case that combines UAAS measurements and dispersion modeling to quantify CH4 emissions from a dairy farm. To evaluate the atmospheric sensing performance of the UAAS, four field deployments were performed at three locations in the San Joaquin Valley of California where CH4 hotspots were observed downwind of dairy farms. A comparison of the observations collected on board the UAAS and an 11 m meteorological tower show that the UAAS can measure wind velocity trends with a root mean squared error varying between 0.4 and 1.1 m s−1 when the wind magnitude is less than 3.5 m s−1. Findings from UAAS flight deployments and a calibration experiment also show that the UAAS can reliably resolve temporal variations in the mole fractions of CH4 and CO2 occurring over periods of 10 s or longer. Results from the UAAS and dispersion modeling use case further demonstrate that UAASs have great potential as low-cost tools for detecting and quantifying CH4 emissions in near real time.

Monitoring and Reconstruction of Actuator and Sensor Attacks for Lipschitz Nonlinear Dynamic Systems Using Two Types of Augmented Descriptor Observers

Fault data injection attacks may lead to a decrease in system performance and even a malfunction in system operation for an automatic feedback control system, which has motive to develop an effective method for rapidly detecting such attacks so that appropriate measures can be taken correspondingly. In this study, a secure descriptor estimation technique is proposed for continuous-time Lipschitz nonlinear cyber physical systems affected by actuator attacks, sensor attacks, and unknown process uncertainties. Specifically, by forming a new state vector composed of original system states and sensor faults, an equivalent descriptor dynamic system is built. A proportional and derivate sliding-mode observer is presented so that the system states, sensor attack, and actuator attack can be reconstructed successfully. The observer gains are obtained by using linear matrix inequality to secure robustly stable estimation error dynamics. Moreover, a robust descriptor fast adaptive observer estimator is presented as a complement. Finally, the efficacy levels of the proposed design approaches are validated using a vertical take-off and landing aircraft system. Comparison studies are also carried out to assess the tracking performances of the proposed algorithms.

MIGRATING TO ARP4754A: TAILORING OF ARCHITECTURE AND SYSTEMS REQUIREMENTS DEFINITION PROCESSES IN THE ROTORCRAFT INDUSTRY

AbstractRotorcrafts are very complex systems that require a huge systems engineering effort to design, implement and integrate. A successful aircraft design is a matter of good integration between engineering disciplines and suppliers just as much as it is about finding a good technical solution to the customers' expectations. This issue is well understood within the industry and competent authorities. Companies now face the challenge of transitioning from integrating complex systems to make an aircraft (as per ARP4754) to engineering and collating a complex aircraft system as per ARP4754A: in other words, the focus shifted to a more holistic view to the aircraft development, a game changer in all respects. Leonardo Helicopters is tailoring its internal processes to reflect this change and challenge. While the ideal process can be defined today, the transition takes time and a significant change in culture and organization needs to take place. To support the transition, the authors have developed a hybrid approach to the aircraft architecture and system requirements definition process. This new approach leverages existing expertise at a system level to facilitate the integration between systems and the subsequent migration to bridge the gap with the aircraft engineering activities required by the ARP4754A.

Usage and structural health monitoring systems in military tactical transport aircraft

The variability of use in the military tactical transport aircraft is not always well captured in the intended use declared by the operators. On the other hand, the computers installed in the aircraft are already collecting huge amount of data that can be downloaded on ground with no additional burden. With the properly data analysis and management on ground, and by using the existing flight physics models of the aircraft or by training neuronal networks it is possible to use the data to obtain relevant information. Such as usage figures, detect potential overloads, obtain loads and stresses several times by second. Those loads and stress time histories can then use to re-calculate the fatigue and crack propagation is the same way as per certification in a cycle-by-cycle basis, then re-evaluate the maintenance to optimized it according to real use of the aircraft. Produce operational recommendations and perform prognosis analysis considering the past and intended use in the future. On the other hand, for local areas prone to accidental damage, direct sensor measurements can be used for damage monitoring.

Validation of an Abaqus impact wave propagation model

Structural Health Monitoring (SHM) is an important topic in aircraft industry to reduce the maintenance costs and increase the availability of an aircraft fleet through automating the determination of the health of the aircraft structure and systems using on-site sensors, like piezoelectric (PZT) and optic fibre Bragg grating (FBG) sensors that are often applied in SHM sensor networks. A finite element model for wave propagation due to an impact is very desirable to enable the design of optimal sensor network configurations for SHM applications, to obtain a better understanding of wave propagation (especially in composite structures) and also to generate simulated (virtual) test data for SHM algorithm development. Therefore, an Abaqus explicit finite element (FE) model was developed for wave propagation due to impacts. To validate such a model, a series of impact tests were performed with a drop tower on an aluminium clamped square panel, at different impact energy levels and different impact locations. On the panel, eight FBG and six PZT sensors were installed. These experimental results were used to validate the FE model, in which the impacts were simulated and the computed PZT and FBG sensor responses were compared against the experimental results. The paper will present the impact test setup, the finite element model and the validation results. The main focus of the paper will be the sensitivity analysis, identifying the model parameters that significantly affect the impact sensor responses and their optimal settings. A very good correlation between the numerical and experimental results was obtained. In near future work, the model will be extended to a (thermoplastic) composite panel, for which experimental results on a flat composite panel already have been collected, and a stiffened composite panel representative of an actual horizontal tail plane are planned.

Health Management of Aircraft Fuel Systems: A Practical Prognostic Perspective

Aircraft health management, specifically pertaining to fuel systems, is a comprehensive process that is undertaken to ensure the continuous airworthiness of the aircraft over its entire lifespan. The integration of health management into aircraft systems requires a methodical strategy to quantitatively evaluate the possible advantages provided by each specific application. Gaining a thorough comprehension of the advantages linked to integrated health management systems provides useful insights for enhancing the design of these systems and formulating efficient prognostic techniques. The role of prognosis in the field of prognostics and health management (PHM) is essential for improving the dependability of systems. Prognosis involves accurately predicting the remaining useful life (RUL) within the domain of integrated health management. This study improves the precision of prediction results, optimises the derived prerequisites for health management in the specialised field of RUL prediction for aircraft fuel systems, provides a thorough understanding, and advances the grasp of the previously described requirements in a more effective way. Additionally, it presents the most suitable solutions in order to address these demands by utilising prognostic techniques. Furthermore, this study presents an analysis of the proposed hybrid prognostic approach in the setting of controlled laboratory conditions. The applications encompassed in this work consist of three main areas. Firstly, the evaluation of inspection interval modifications is conducted by taking into account load and environmental monitoring data. Secondly, design considerations for damage prognostics are incorporated into the analysis. Lastly, a design modification is presented as an example of how condition-based maintenance (CBM) can be facilitated. A methodology that enables the efficient and well-founded construction of a health management system, specifically designed for aircraft fuel systems, is presented. This methodology, together with its associated outcomes, presents a compelling advantage in terms of lowering life cycle expenses while simultaneously enhancing availability, dependability, and performance.

Validation of Doppler Wind Lidar Measurements with an Uncrewed Aircraft System (UAS) in the Daytime Atmospheric Boundary Layer

Abstract One of the most widely used systems for wind speed and direction observations at meteorological sites is based on Doppler wind lidar (DWL) technology. The wind vector derivation strategies of these instruments rely on the assumption of stationary and homogeneous horizontal wind, which is often not the case over heterogeneous terrain. This study focuses on the validation of two DWL systems, operated by the German Weather Service [Deutscher Wetterdienst (DWD)] and installed at the boundary layer field site Falkenberg (Lindenberg, Germany), with respect to measurements from a small, fixed-wing uncrewed aircraft system (UAS) of the type Multi-Purpose Airborne Sensor Carrier (MASC-3). A wind vector intercomparison at an altitude range from 100 to 500 m between DWL and UAS is performed, after a quality control of the aircraft’s data accuracy against a cup anemometer and wind vane mounted on a meteorological mast also operating at the location. Both DWL systems exhibit an overall root-mean-square difference in the wind vector retrieval of less than 22% for wind speed and lower than 18° for wind direction. The enhancement or deterioration of these statistics is analyzed with respect to scanning height and atmospheric stability. The limitations of this type of validation approach are highlighted and accounted for in the analysis.