Aircraft Systems Research Articles

An analytical view on Unmanned Aircraft Systems

<p>Unmanned Aircraft Systems (UAS) is a booming technology with a future perspective and does have a huge potential to transfigure warfare and enable up-to-date civilian applications. It furthermore matures in a technological way as to be impinged into the civil society. In 2010, the importance of scientific applications in the respective field was demonstrated by DOD in the contemporary years. In recent years, UAS has played an integral role in a number of missions that are public, like law enforcement, which is local, board surveillance, weather monitoring, wildlife surveys, and military training. UAS do force some challenges that are numbered as lacking a pilot who is on-board in order to see and hence avoid supplemental aircraft, and furthermore, the extensive discrepancy in the missions related to UAS, and in order to implement the operations in the NextGen time frame impinged in NAS, the capabilities of the respective topic must be communicated. The applications of UAS are numbered as Ariel Mapping and Meteorology, intelligence, remote sensing, surveillance and reconnaissance, environmental monitoring and agriculture, border security, security applications and law enforcement, counter insurgency, electronic attacks, attack strikes, communication relays, target identification, and designation. Via this survey paper, it can be concluded that UAS is emerging as a valuable and helpful technology having tremendous potential for revolting warfare and enabling new applications w.r.t the UAS field.<strong></strong></p>

Walruses from space: walrus counts in simultaneous remotely piloted aircraft system versus very high‐resolution satellite imagery

AbstractRegular counts of walruses (Odobenus rosmarus) across their pan‐Arctic range are necessary to determine accurate population trends and in turn understand how current rapid changes in their habitat, such as sea ice loss, are impacting them. However, surveying a region as vast and remote as the Arctic with vessels or aircraft is a formidable logistical challenge, limiting the frequency and spatial coverage of field surveys. An alternative methodology involving very high‐resolution (VHR) satellite imagery has proven to be a useful tool to detect walruses, but the feasibility of accurately counting individuals has not been addressed. Here, we compare walrus counts obtained from a VHR WorldView‐3 satellite image, with a simultaneous ground count obtained using a remotely piloted aircraft system (RPAS). We estimated the accuracy of the walrus counts depending on (1) the spatial resolution of the VHR satellite imagery, providing the same WorldView‐3 image to assessors at three different spatial resolutions (i.e., 50, 30 and 15 cm per pixel) and (2) the level of expertise of the assessors (experts vs. a mixed level of experience – representative of citizen scientists). This latter aspect of the study is important to the efficiency and outcomes of the global assessment programme because there are citizen science campaigns inviting the public to count walruses in VHR satellite imagery. There were 73 walruses in our RPAS ‘control’ image. Our results show that walruses were under‐counted in VHR satellite imagery at all spatial resolutions and across all levels of assessor expertise. Counts from the VHR satellite imagery with 30 cm spatial resolution were the most accurate and least variable across levels of expertise. This was a successful first attempt at validating VHR counts with near‐simultaneous, in situ, data but further assessments are required for walrus aggregations with different densities and configurations, on different substrates.

The Challenges of Blood Sample Delivery via Drones in Urban Environment: A Feasibility Study through Specific Operation Risk Assessment Methodology

In recent years, Unmanned Aircraft System (UAS) usage in the medical sector as an alternative to traditional means of goods transport has grown significantly. Even though the reduced response time achieved with UASs can be lifesaving in critical situations, their usage must comply with technological constraints such as range, speed and capacity, while minimizing potential risks. In this paper, the feasibility of a drone operation dedicated to the transport of blood samples in an urban area is studied through a safety risk analysis. The assessment utilizes the Specific Operation Risk Assessment (SORA) framework, in line with current European regulations, and extends it to define flight trajectories with minimal risk. A case study in the Helsinki urban area is used as a reference, with an exemplary case of commercial drone transportation of blood samples between the Töölö and Malmi Hospitals. By leveraging the drone performance capabilities and minimizing the risk for people on the ground, this approach demonstrates that medical delivery using drones in densely populated urban environments remains challenging. Nonetheless, it argues that the proposed method can enhance risk awareness and support the planning of feasible operations.

Sensor Fault Reconstruction Using Robustly Adaptive Unknown-Input Observers.

Sensors are a key component in industrial automation systems. A fault or malfunction in sensors may degrade control system performance. An engineering system model is usually disturbed by input uncertainties, which brings a challenge for monitoring, diagnosis, and control. In this study, a novel estimation technique, called adaptive unknown-input observer, is proposed to simultaneously reconstruct sensor faults as well as system states. Specifically, the unknown input observer is used to decouple partial disturbances, the un-decoupled disturbances are attenuated by the optimization using linear matrix inequalities, and the adaptive technique is explored to track sensor faults. As a result, a robust reconstruction of the sensor fault as well as system states is then achieved. Furthermore, the proposed robustly adaptive fault reconstruction technique is extended to Lipschitz nonlinear systems subjected to sensor faults and unknown input uncertainties. Finally, the effectiveness of the algorithms is demonstrated using an aircraft system model and robotic arm and comparison studies.

Development of an Uneven Terrain Decision-Aid Landing System for Fixed-Wing Aircraft Based on Computer Vision

This paper presents a computer vision-based standalone decision-aid landing system for light fixed-wing aircraft, aiming to enhance safety during emergency landings. Current landing assistance systems in airports, such as Instrument Landing Systems (ILSs) and Precision Approach Path Indicators (PAPIs), often rely on costly and location-specific ground equipment, limiting their utility for low-payload light aircraft. Especially in emergency conditions, the pilot may be forced to land on an arbitrary runway where the road flatness and glide angle cannot be ensured. To address these issues, a stereo vision-based auxiliary landing system is proposed, which is capable of estimating an appropriate glide slope based on the terrain, to assist pilots in safe landing decision-making. Moreover, in real-world scenarios, challenges with visual-based methods arise when attempting emergency landings on complex terrains with diverse objects, such as roads and buildings. This study solves this problem by employing the Gaussian Mixture Model (GMM) to segment the color image and extract ground points, while the iterative weighted plane fitting (IWPF) algorithm is introduced to mitigate the interference of outlier feature points, reaching a highly robust plane normal estimation. With the aid of the proposed system, the pilot is able to evaluate the landing glide angle/speed with respect to the uneven terrain. Simulation results demonstrate that the proposed system can successfully achieve landing guidance in unknown environments by providing glide angle estimations with an average error of less than 1 degree.

Probabilistic Higher-Order Velocity Obstacle for Dynamic Collision Avoidance in Uncertain Environments

Autonomous systems like unmanned aircraft systems are touted as front-runners in terms of efficiency and agility in challenging operations like emergency response. The ability of autonomous agents in such systems to avoid collisions with dynamic obstacles while navigating through an obstacle-cluttered environment is critical for success in any mission. In addition to that, further challenges are posed by environments with uncertainties in obstacles’ motion, sensing, and occluded regions. To this end, a higher-order velocity obstacle–based novel motion planner is presented in this paper in a probabilistic setup for smooth, collision-free navigation of the agent with acceleration constraints in uncertain, unstructured environments with an element of anticipation for the future environment. The effectiveness of the developed algorithm for safe, collision-free, and smooth navigation of the agent is investigated in simulation studies in two different kinds of environments, one with known trajectories of obstacles and the other with unknown maneuvering trajectories of obstacles. Extensive simulation studies are performed in the presence of dynamic obstacles to elucidate the performance of the proposed algorithm on four crucial parameters—mission time, computational time, minimum obstacle distance, and an overall control effort under varied obstacle densities. With satisfactory performance in all these aspects, the developed algorithm possesses strong potential for real-time implementation.

Observing low-altitude features in ozone concentrations in a shoreline environment via uncrewed aerial systems

Abstract. Ozone is a pollutant formed in the atmosphere by photochemical processes involving nitrogen oxides (NOx) and volatile organic compounds (VOCs) when exposed to sunlight. Tropospheric boundary layer ozone is regularly measured at ground stations and sampled infrequently through balloon, lidar, and crewed aircraft platforms, which have demonstrated characteristic patterns with altitude. Here, to better resolve vertical profiles of ozone within the atmospheric boundary layer, we developed and evaluated an uncrewed aircraft system (UAS) platform for measuring ozone and meteorological parameters of temperature, pressure, and humidity. To evaluate this approach, a UAS was flown with a portable ozone monitor and a meteorological temperature and humidity sensor to compare to tall tower measurements in northern Wisconsin. In June 2020, as a part of the WiscoDISCO20 campaign, a DJI M600 hexacopter UAS was flown with the same sensors to measure Lake Michigan shoreline ozone concentrations. This latter UAS experiment revealed a low-altitude structure in ozone concentrations in a shoreline environment showing the highest ozone at altitudes from 20–100 m a.g.l. These first such measurements of low-altitude ozone via a UAS in the Great Lakes region revealed a very shallow layer of ozone-rich air lying above the surface.

Method for measuring non-stationary motion attitude based on MEMS-IMU array data fusion and adaptive filtering

The error characteristics of a typical commercial MEMS-IMU were analyzed. Using 15 ICM-42688 sensors, a 3*5 MEMS-IMU array was designed, and a weighted data fusion method based on Allan variance for the MEMS-IMU array was proposed. This effectively reduces the random measurement errors of the MEMS-IMU, providing a data foundation for the precise measurement of motion and attitude of robots, vehicles, aircraft, and other systems under low-cost conditions. The text describes a measurement method for non-stationary motion attitudes of sports vehicles based on adaptive Kalman-Mahony. Specifically, it first uses adaptive Kalman filter on array sensor data to calculate the measurement noise in real-time and adaptively adjust the filtering gain. Then, it determines the compensation coefficient of the accelerometer to the gyroscope angular velocity based on the motion state of the vehicle, and solves the attitude through complementary filtering to obtain the motion attitude quaternion. Finally, it converts it into the roll angle, pitch angle, and yaw angle of the sports vehicle. Experimental results show that the proposed MEMS-IMU array weighted data fusion method based on Allan variance has significant advantages over traditional single MEMS-IUM methods and traditional average weighting methods in reducing sensor angle random walk and zero drift instability. The proposed adaptive Kalman-Mahony attitude measurement method also shows a significant improvement in the accuracy of non-stationary motion attitude measurement compared to traditional methods.

THE IMPACT OF STRESS-ASSOCIATED DISEASES OF THE DIGESTIVE ORGANS ON THE PSYCHOPHYSIOLOGICAL STATE OF OPERATORS OF UNMANNED AIRCRAFT SYSTEMS

Introduction. In the conditions of martial law, an important role belongs to modern military equipment, which includes unmanned aircraft systems (UAS). Оperators of UAS in the course of combat missions are significantly affected by the stress factor. It provokes the occurrence of stress-associated diseases in them, therefore, studying the specifics of the impact of stress-associated diseases on the psychophysiological state of operators determines the relevance of this study. The purpose of the study. To establish the patterns of influence of stress-associated diseases of the digestive organs on the psychophysiological state of the operators of unmanned aircraft systems. Materials and methods. In the course of the research, 94 operators of UAS under the age of 40 were examined, who were then divided into groups based on their health status. The examination was carried out using modern modified methods implemented on the basis of the software and hardware complex for psychophysiological research «PFI-2». The results. It has been proven that stress-associated diseases of the digestive organs significantly worsen (p<0,05) the psychophysiological state of operators of UAS in a sufficiently large number of professionally important psychophysiological qualities. The reliable influence of the «state of health» factor on the indicators of simple and complex visual-motor reaction of operators of UAS is shown. The analysis of correlation constellations according to cognitive parameters showed that 6 of them are observed in healthy operators, 2 in mildly ill patients, and 1 in severely ill patients, that is, the system of connections between cognitive functions breaks down quite strongly with the development of stress-associated diseases of the digestive organs. There is a natural decrease in the number of connections in the series «healthy (13) – mildly ill (10) – severely ill (5)». It is shown that the stress that causes the disease fundamentally destroys the system of ensuring professional activity. Conclusions. It was established that stress-associated diseases of the digestive organs negatively affect the psychophysiological state of operators. The degree of degradation of the structure of correlation relations (р=0,0491) as a result of the influence of the stress factor on the operators was revealed. A hypothesis regarding the destruction of the system of connections between cognitive psychophysiological parameters depending on the «severity of the disease» is proposed. The need to develop a set of measures to prevent the development of stress-related diseases among operators of UAS has been established.

Optimum image alignment setting selection for structure-from-motion photogrammetry using Remotely Piloted Aircraft Systems (RPAS) to support coral habitat classification

Coral reefs provide a range of ecological services and support highly diverse coastal ecosystem. However, the extent of living corals has been reduced by half globally as a result of anthropogenic natural stressors. Continuous monitoring by deploying accessible remote sensing (RS) methods to map coral habitats is necessary for effective conservation and management strategies. Recently, there has been an increased use of Remotely Piloted Aircraft Systems (RPAS) for coral reef RS. Image misalignment is considered a key problem in the Structure from Motion (SfM) workflow. Combinations of image alignment settings (IAS) and key point limit (KPL) optimizations aim to improve quality of the sparse cloud while lowering SfM reconstruction uncertainty, increasing projection accuracy, and ultimately improving coral habitat classification accuracy. In this study, the orthoimages were produced from a total of 25 IAS (lowest, low, medium, high and highest) and KPM (5k, 10k, 20k, 40k, and 60k) combinations using Agisoft™ Metashape software. Measurements of geometric distortion, efficiency, and completeness were used to evaluate these orthoimages with three visible bands. Results that satisfied the requirements for both geometric quality, spectral accuracy, processing efficiency identified the optimum alignment methods needed for routinely monitoring and mapping of coral reefs of Pulau Bidong. The SfM-image alignment techniques chosen for this study could produce the coral mapping extent, a higher number of tie points and matches, better image alignment success and coral habitat classification accuracy, less processing time and memory usage and no geometric distortions. The development of the methodology for the optimum parametrization of RPAS multispectral imagery would be beneficial to researchers studying coral reefs, marine sciences, and RS data analysts. It would provide them reliable methods for evaluating the quality of orthoimages and faster processing methods to achieve coastal RS objectives.

Nachhaltige Antriebssysteme für künftige Flugzeugsysteme

ZusammenfassungDie steigende Erderwärmung und die erforderlichen Maßnahmen, um diese einzudämmen, sind Themen, für die möglichst bald von den Naturwissenschaftler:innen und Ingenieur:innen Lösungen gefunden werden müssen. Die Diskussion um die Art der künftigen Mobilität hat mittlerweile alle Bereiche erfasst, von Autos, Lastkraftwagen und Schiffen bis hin zu Flugzeugen. Leider ist das Thema sehr komplex, systemübergreifend, politisch und ideologisch besetzt. Vieles ist nur mithilfe gemeinsamer internationaler Anstrengungen zu lösen.

Experimental validation of a UAS at engine ingestion conditions: Part 2 Model validation

With uncrewed aircraft systems (UASs) becoming more popular in recent years there is an increasing risk of a midair collision with aircraft for which there are currently no regulations in place. Bird impacts have been thoroughly studied for years and are considered soft body impacts. The bird impact research cannot be directly applied to UAS ingestions since they are hard body impacts. Some recent research has looked into understanding the differences between soft and hard body impacts on aircraft engines. However, this research used primarily unvalidated models for the harsh conditions of an ingestion event, which creates uncertainty in the results. This work intends to fill in this gap in understanding by developing a validated computational model of a UAS for engine ingestion simulations. Part I of this work presented the experimental test plan and experimental results of UAS critical components and full UAS being launched at test articles with representative features of a fan blade. This work discusses the computational modeling completed in LS-DYNA to simulate the physical tests and to update and validate the UAS models.

Experimental validation of a UAS at engine ingestion conditions: Part I Experiments

In recent years, uncrewed aircraft systems (UASs) have greatly increased in popularity and accessibility to the public. This dramatic increase has led to a substantial risk of a midair collision between a UAS and a commercial aircraft, and these collisions need to be analyzed to understand the dangers associated with them. Soft body (i.e., birds or ice) impacts have been happening since the early days of flight and have been studied thoroughly. In contrast, there has been significantly less research on hard body impacts, with most of the currently published research not using experimentally validated models at the conditions expected to be seen in an engine ingestion. The purpose of this work is to discuss the design and execution of experiments to improve and validate a UAS model for high speed impacts for future engine ingestion studies. The overall effort consisted of first conducting physical tests that represent specific high speed ingestion scenarios. Then simulating these tests using a high fidelity finite element tool. Then finally updating the model as necessary. The design of the experiments, experimental test setup, instrumentation and experimental results are highlighted in Part I of this work. The computational model update and validation of the UAS at conditions seen in an engine ingestion are done in Part II of this work.

Structure Design and Heat Transfer Performance Analysis of a Novel Composite Phase Change Active Cooling Channel Wall for Hypersonic Aircraft.

Efficient and stable heat dissipation structure is crucial for improving the convective heat transfer performance of thermal protection systems (TPSs) for hypersonic aircraft. However, the heat dissipation wall of the current TPS is limited by a single material and structure, inefficiently dissipating the large amount of accumulated heat generated during the high-speed maneuvering flight of hypersonic aircraft. Here, a convection cooling channel structure of TPS is proposed, which is an innovative multi-level structure inspired by the natural honeycomb. An active cooling channel (PCM-HC) is designed by using a variable-density topology optimization method and filled with phase change material (PCM). Numerical simulations are used to investigate the thermal performance of the PCM-HC wall, focusing on the influence of PCM properties, structural geometric parameters, and PCM types on heat transfer characteristics. The results demonstrate that the honeycomb-like convection cooling channel wall, combined with PCM latent heat of phase change, exhibits superior heat dissipation capability. With a heat flux input of 50 kW/m2, the maximum temperature on the inner wall of PCM-HC is reduced by 12 K to 20 K. Different PCMs have opposing effects on heat transfer performance due to their distinct thermophysical properties. This work can provide a theoretical basis for the design of high-efficiency cooling channel, improving the heat dissipation performance in the TPS of hypersonic aircraft.

Identification of unique electromagnetic signatures from GLRaV-3 infected grapevine leaves in different stages of virus development.

Grapevine leafroll associated virus 3 (GLRaV-3) is one of the most common viruses that adversely affect grape production quality around the world. Grapevine virus is usually detected by polymerase chain reaction (PCR) tests, but the main diagnostic challenges with the PCR are uneven distribution of symptoms, low virus titers in early stage, and the tests are time consuming and expensive. In the absence of effective control and treatment for grapevine virus, the recommendation is to remove infected vines before they become a source of transmission and a rapid and early detection method for viruses is urgently needed. This study investigated how GLRaV-3 infection affects spectral behavior of grapevine leaves and the use of remote sensing tools to identify changes caused by the biotic stress. A Real-Time RT-qPCR test was performed to select representative vines with healthy and GLRaV-3 infection, and changes in electromagnetic (EM) spectrum of leaves were observed with a portable hyperspectral spectrometer and a multispectral sensor on a remotely piloted aircraft system (RPAS). The results of this study suggest that foliar EM reflectance may differ depending on the presence or absence of visible symptoms of infected leaves and different stages of virus infection progress could be indicated by changes in the relative rate of reflectance around 700 nm. This research also confirmed that the development of a narrow-band hyperspectral index for the detection of grapevine virus is feasible, further research is recommended in a much more comprehensive investigation including a combination of hyperspectral sensor and chlorophyll fluorescence sensors, interpolation of suspect wavebands into ratios or indices, larger sample sizes and a more controlled study environment.

Numerical investigation of jet impingement on flat/concave cooling of CO2 with different phase states under high heat flux

The thermal load and high temperature brought by the increase in power of electronic devices or the increase in speed of supersonic aircraft limit the respective development. In this paper, a numerical model of CO2 jet impingement cooling of a constant heat flux plate/concave surface in different phase states was established. Secondly, the non-equilibrium phase transition and the real-thermophysical properties of CO2 was considered. The effects of different wall heat flux (0.7 MW/m2 ∼ 6.5 MW/m2) and initial phase states on the impact cooling performance of CO2 jet were studied.It is found that for SCO2 jet impingement, when the inlet temperature is lower than the pseudo-critical temperature, the heat transfer coefficient increases with the increase of inlet pressure, and the maximum increase is 24.7 %. For near-critical liquid CO2 (LCO2) jet impingement, low latent heat prevents temperature overshoot in the heat flux range studied. With the increase of the proportion of dry ice in the inlet, the heat transfer coefficient also increases. When q > 3 MW/m2, the heat transfer coefficient of dry ice jet impact is 2.5 ∼ 3 times and 1 ∼ 1.4 times of that of SCO2 and near-critical LCO2 jet impingement for the flat plate model, respectively. For concave surface with high heat flux, near-critical LCO2 jet impingement cooling effect is relatively good. In addition, concave surface will aggravate the uneven cooling surface temperature.The results can provide more references for the CO2 jet impingement technology in the design of stagnation cooling system of supersonic aircraft and thermal management of high-power electronic devices.

Experimental evaluation of alternative ceiling-based ventilation systems for long-range passenger aircraft

AbstractAlternative ventilation technology bricks, such as ceiling-based, sidewall-based or floor-based ventilation, are of high interest in terms of manufacturing and customization benefits for passenger aircraft. Two novel ventilation systems and state-of-the-art Mixing Ventilation (MV) were experimentally investigated under static conditions in a ground-based research facility. In case of Micro-Jet Ventilation, a perforated ceiling brings the air into the cabin as localized micro-jets with high momentum. Further, Low-Momentum Ceiling Ventilation characterized by a low-momentum air supply through planar and large-surface inlets is investigated. The measurement techniques and the test matrix were designed in order to quantify and evaluate thermal comfort, local air quality and energy efficiency of the ventilation concept. The results proved that there is not one single ventilation concept which optimizes all challenges: air quality, thermal comfort and energy efficiency. Both advantages and disadvantages were found for each ventilation system. In terms of technology bricks, the following main results were found: The average local age-of-air was between 5 and 14%, depending on the boundary conditions. It was lower for the ceiling-based concepts compared to state-of-the-art MV. At the same time the average CO2 concentration decreased by 7–14% for the ceiling-based concepts compared to MV. The local velocities in the vicinity of the passengers were similar for cruise conditions, whereas they decreased by up to 38% in case of hot-day-on-ground conditions for ceiling-based ventilation compared to MV. On the other hand, the heat removal efficiency was low for all concepts and the temperature stratification increased in case of ceiling-based ventilation.

Precision pest control using purpose-built uncrewed aerial system (UAS) technology and a novel bait pod system

Controlling invasive species is critical due to their impact on disease transmission, endangerment of native species, and biodiversity loss. While crewed aircraft can effectively distribute bait over large areas to target pests, their use becomes impractical and costly in small, isolated regions with rugged terrain. Though feasible in smaller sites, ground control operations pose challenges such as high expenses, safety risks, and potential worker injuries in hazardous terrain. An innovative approach employing unmanned aerial systems (UASs) for precise bait deployment has been developed to address these issues. Our team engineered a purpose-built system designed specifically for deploying bait within innovative bait pods. Field trials in New Zealand validated its efficacy, with significant improvements observed in subsequent trials due to enhancements in bait pod design. The median deployment accuracy achieved was 1.91 meters from the target, with no statistically significant difference between open and forested areas. This advanced system enables precise bait placement, facilitating pest control in complex landscapes, challenging terrain, and dense vegetation. Its smart functionality and adaptability allow maximum accuracy and efficiency across various aircraft and autopilot systems. This innovative tool holds promise in managing invasive species, complementing existing strategies to expedite ecosystem restoration and safeguard biodiversity.

Research on Step-Down Aviation Three-Phase Power Factor Correction based on Machine Learning and Optimization Algorithm

Objectives: The study looks at power quality issues, such as phase imbalance, voltage sags, and power factor issues, in aircraft systems. It highlights how immediate power factor correction steps are required to avoid equipment longevity problems and boost system efficiency, which will ultimately improve the performance of the entire aviation system. Methodology: Using a variety of data sources, real-time data gathering, and machine learning approaches, this study focuses on data collecting and real-time monitoring in aviation systems. Predictive modeling, testing methods for data preparation and analysis, and optimization algorithms for capacitor bank size and placement are all included. Considerations for privacy and security are covered. Result: Salp Swarm Optimization and the Dragonfly Algorithm are used in the study to assess the ideal capacitor sizes and positions, which results in better voltage profiles and lower active power losses. Aviation systems benefit from improved power factor correction through the application of integrated machine learning and optimization, which promotes sustainability and energy efficiency. Conclusion: The study demonstrated the significance of power factor correction in aviation by successfully addressing power quality issues in aircraft electrical systems through the use of optimization algorithms for capacitor sizing and location.

Liquid hydrogen storage and transfer-control system for integrated zero emission aviation (IZEA)

The growth in the aviation sector has highlighted the need to decrease carbon emissions, a significant factor in climate change. Hydrogen is a potential alternative clean fuel due to its high energy density. As a collaborative effort in developing integrated zero emission aviation (IZEA, a NASA ULI), we present the design concept for a liquid hydrogen storage system for short-range aircraft with a gravimetric index greater than 0.6. Our design leverages the cryogenic cooling power of liquid hydrogen to support the temperature and heat loads of various power system components, such as the high-temperature superconducting (HTS) generator, HTS motor, DC power distribution cable network, and power electronic converters. By controlling the pressure in the storage tank, we demonstrate that it is feasible to deliver the desired mass flow rate of hydrogen while effectively cooling the power system components using practical heat exchangers. Also, since heat exchangers are an integral part of our hydrogen storage and flow system, their design also impacts the overall system storage density. The entire system is designed considering the space and weight factors of an aircraft. This work represents a significant advancement towards developing the complete IZEA thermal management system for a given airplane and flight profile.