Mission Operations Research Articles

An Examination of UAS Incidents: Characteristics and Safety Considerations

This paper examines the characteristics and implications of reported Unmanned Aircraft Systems (UAS) incidents in the National Aeronautics and Space Administration (NASA) Aviation Safety Reporting System (ASRS) database for UAS incidents operated by remote pilots licensed under Part 107. Characteristics examined include seasonal patterns of incidents, operational mission, and number of contributing factors, as well as crew configuration, timing of incident detection, and airspace class. Results are compared with previous research and with incident data for recreational users. The narratives for each incident are assessed to provide a greater context for the incidents and to determine how the incidents vary in different classes of airspace. Findings reveal that UAS incidents often involve multiple contributing factors, including environmental, human, equipment, and policy issues; there is an increasing prevalence of human-related issues over equipment problems compared to previous research; this reflects historic safety trends in crewed aviation. Near-miss incidents with crewed aircraft are a very real concern, particularly in Class D airspace, which often includes general aviation (GA) and helicopter operations. This research underscores the need for timely communication during urgent nighttime UAS operations as well as enhanced safety culture at both operator and organizational levels.

Extreme Space Weather Events of the Past 30 Years: Preparation for Data From Mission Vigil

AbstractExtreme Space Weather events can negatively affect ground‐based infrastructure and satellite communications. European Space Agency plans to launch a new operational mission, Vigil, to monitor space weather activity and provide timely warnings about immediate danger. In this work, we have identified 24 instruments that have already acquired data on 8 space missions and are similar to instruments planned for mission Vigil. We then selected the 39 most extreme space weather events that affected the Earth in the past 30 years and gathered Vigil‐like data for them. The objective of this work and our main motivation was to address the following question: “How would Vigil have observed extreme space weather events if it had been operational during those events?” For this reason, we prepared a pipeline for the community to obtain images and in‐situ measurements for these specific periods, allowing straightforward applications for the follow‐up data‐driven studies. This effort could maximize Vigil's potential. Additionally, we studied the sources of extreme space weather events and the time it took for solar plasma to reach Earth's magnetosphere. This analysis demonstrates the utilization of the gathered data set and provides interesting insights into the most hazardous space events that influenced society in recent decades.

Comparison of lunar rover wheel performance in soils with different cohesive properties

Wheeled mobile robots, rovers, are highly effective in lunar exploration. However, the lunar regolith can cause wheel slippage, resulting in an inability to travel for the rover. A single-wheel testbed is usually used to analyze a rover wheel’s driving performance. Our experiment can control the rotation and translation of the wheels separately, realizing experiments in any slippage condition. Moreover, this testbed can conduct experiments using regolith simulant with a cohesive property, in addition to Toyoura sand, which is non-cohesive sand collected from the earth.This paper presents the results of a driving test on two types of loose soil: Toyoura sand and regolith simulant (FJS-1). The wheel used in the experiment is the preliminary version of the actual flight model of a 10 kg class lunar exploration microrover. The results reveal that the traction performance on both sands improves as the slip ratio increases. The performance did not depend on velocity but on vertical load. It should be noted that the cohesive simulant shows a higher difference in traction performance than Toyoura sand. These findings, measured in detail from the low-slip to the high-slip range, contribute to the actual driving operation of the rover missions.

Preliminary Trajectory Analysis of CubeSats with Electric Thrusters in Nodal Flyby Missions for Asteroid Exploration

This paper studies the performance of an interplanetary CubeSat equipped with a continuous-thrust primary propulsion system in a heliocentric mission scenario, which models a nodal flyby with a potential near-Earth asteroid. In particular, the mathematical model discussed in this work considers a small array of (commercial) miniaturized electric thrusters installed onboard a typical CubeSat, whose power-generation system is based on the use of classic solar panels. The paper also discusses the impact of the size of thrusters’ array on the nominal performance of the transfer mission by analyzing the trajectory of the CubeSat from an optimization point of view. In this context, the propulsive characteristics of a commercial electric thruster which corresponds to a iodine-fueled gridded ion-propulsion system are considered in this study, while the proposed procedure can be easily extended to a generic continuous-thrust propulsion system whose variation in thrust magnitude and specific impulse as a function of the input electric power is a known analytic function. Using an indirect approach, the paper illustrates the optimal guidance law, which allows the interplanetary CubeSat to reach a given solar distance, with the minimum flight time, by starting from a circular (ecliptic) parking orbit of assigned radius. The mission scenario is purely two-dimensional and models a rapid nodal flyby with a near-Earth asteroid whose nodal distance coincides with the solar distance to be reached.

Application of multi architecture modelling method in intelligent electric–vehicle design

With the improvement of automobile intelligence, the research and development of the system is becoming increasingly complex and the development of the overall life cycle of the automobile system is facing increasing challenges. In this study, we propose a model-based systems engineering (MBSE) method through the development of multiarchitecture modelling language in order to support complex product development process modelling starting from the mission. Meanwhile, index verification and hybrid automaton simulations are employed to realise the static cost analysis of an architecture scheme and the rationality analysis of behaviour properties during the development process. Finally, a case of intelligent electric vehicle in a dual-vehicle system is established. In addition, the development process of mission–operation–feature/function–logic–physical (MOFLP) architecture is modelled and verified using multiarchitecture modelling language. Our results demonstrate that the multiarchitecture modelling language can support the multistage architecture description of the life cycle of complex products and perform static and dynamic analysis during the architecture description process.

Reliability evaluation of the grabbing, positioning, and release mechanism for gravitational wave detection

Predicting reliability is an essential part of the design phase for ensuring mission success. In the realm of gravitational wave detection, the integrity and dependability of the Grabbing, Positioning, and Release Mechanism (GPRM) are paramount for its effective space-based deployment. However, predicting reliability of a complex mechanical system like the GPRM during the design phase poses significant challenges due to the harsh and variable conditions of the space environment. This paper addresses these challenges by proposing a reliability evaluation method that combines the stochastic and degradation characteristics of the GPRM, according to which both randomness of the stud position and the degradation of the piezoelectric coefficient are considered. Failure criteria are established based on mission performance indicators, and the Kaplan-Meier estimator is used to analyze the mechanism reliability of the GPRM over time. The result predicts that the reliability of the GPRM is around 0.8 after 107 operating cycles. This finding demonstrates that our proposed method is an effective approach for evaluating reliability, offering valuable insights for ensuring the long-term performance and successful operation of precision mechanisms.

Innovative Power Strategies for CubeSats: Enhancing Solar Energy Capture and Efficient Storage Solutions

CubeSats, a revolutionary class of small satellites, have significantly democratized access to space by offering compact, cost-effective, and highly versatile platforms for scientific, commercial, and educational applications. These miniaturized spacecrafts have become indispensable tools for conducting Earth observation, atmospheric studies, deep-space exploration, and technology demonstrations. However, the efficient management of power systems remains a critical challenge due to the constraints imposed by their small size, limited surface area for solar energy harvesting, and the harsh conditions of space. This paper explores innovative approaches to optimizing the energy systems of CubeSats, focusing on advancements in solar energy harvesting, energy storage technologies, and power management strategies. It highlights the potential of high- efficiency photovoltaic materials, such as multi-junction and perovskite solar cells, to enhance energy capture by utilizing broader portions of the solar spectrum. The study also examines energy storage technologies, including lithium-ion, lithium-polymer, and emerging solid-state batteries, comparing their performance, reliability, and applicability in space missions. Furthermore, hybrid energy storage systems, which combine different storage technologies like batteries and supercapacitors, are analyzed for their ability to dynamically balance energy supply and demand, ensuring stability and efficiency under variable conditions. The research delves into advanced optimization techniques, such as Maximum Power Point Tracking (MPPT) algorithms, which adaptively maximize energy extraction from solar panels, and thermal management strategies that mitigate efficiency losses due to overheating. Load scheduling, depth-of-discharge control, and real-time diagnostics are discussed as critical strategies to extend battery lifespan and ensure continuous operation. Mathematical models and experimental data are integrated to validate these techniques and provide actionable insights for the design and operation of CubeSat energy systems. By addressing the unique challenges of CubeSat power management, this study contributes to the development of robust, sustainable, and high-performance energy solutions. These advancements not only enhance CubeSat mission capabilities and longevity but also pave the way for more ambitious applications, including interplanetary exploration and multi- satellite constellations. The findings of this research are intended to benefit academia, space agencies, and industries, fostering innovation in small satellite technology and expanding the possibilities for cost-effective and impactful space exploration.

Simulation Evaluation and Case Study Verification of Equipment System of Systems Support Effectiveness

As the scale of missions continues to expand, equipment support has emerged as a critical component of military combat effectiveness. Consequently, the supportability of a system of systems (SOS) for equipment has become as essential quality requirement alongside its performance metrics. This study systematically assessed the effectiveness of equipment SOS support through a task-driven methodology. Initially, a model for generating equipment support tasks was developed to translate the operational requirements into a sequence of support tasks. Subsequently, a simulation model was constructed to evaluate the equipment SOS support system, and solutions were derived for the corresponding SOS-level support effectiveness indexes. Finally, the feasibility and characteristics of the proposed models and simulation methodology were validated through a case study involving an emergency operational mission for an air combat group formation. The results indicate that the increased reliability of the equipment system correlates with a reduced failure rate and lower resource consumption for maintenance and support per device, thereby improving support efficiency. The methodology presented in this article provides a framework for evaluating the effectiveness of equipment SOS support while facilitating informed decision-making in information warfare conditions.

DenseNet-Enabled Intelligent Ship Energy Consumption Prediction Method with Navigation Information and Environmental Factors

As a crucial procedure, ship energy consumption prediction is of great significance for the implementation of navigation planning, energy efficiency improvement, and emission reduction strategies. Currently, various studies have been conducted, primarily focusing on container ships, cargo ships, bulk carriers or tankers, with relatively fewer studies dedicated to research vessels. Regarding the limitations of low accuracy and poor effectiveness in ship energy consumption prediction, caused by the diverse voyages and specialized operational missions of research vessels, this paper proposes a DenseNet-enabled energy consumption prediction model considering the complex navigation information and diverse environmental factors. By leveraging the high parameter efficiency of DenseNet, effective feature extraction and strong generalization capabilities can be achieved, which provide more reliable and accurate predictions. Firstly, due to the fact that the real-time fuel consumption is influenced by a variety of internal and external factors, multi-source monitoring data are obtained and analyzed. After data analysis and feature extraction, the processed data and features are utilized to establish the prediction model. Through validations on the actual voyage data, it is demonstrated that the DenseNet-based prediction model outperforms the ResNet, DBCNN, and FCNN models in terms of both accuracy and predictive reliability. Therefore, the proposed method is capable of accurately predicting ship energy consumption under diverse shipping conditions and provides valuable guidance for the development of intelligent shipping.

Testing Performance of Modeling and Simulation Code of Liquid Propellant Supply System Using Method of Characteristics

The primary objective of a liquid propellant supply system is to supply propellant to the engine, enabling stable mission performance. Therefore, the system design must aim at minimizing factors that may contribute to instability while satisfying the specified requirements. Modeling and simulation (M&S) techniques are typically used to achieve efficient design, offering advantages such as the ability to simulate various conditions without constraints, thereby reducing initial development costs and time. Consequently, the performance and accuracy of the M&S program can significantly impact the overall development process. In this study, the method of characteristics (MOC) is used to effectively calculate internal flow in pipes, thereby developing an M&S code with excellent accuracy and performance. The efficiency of the developed in-house code is evaluated by comparing the simulation results with those of a commercial program. Additionally, a water supply experiment is conducted, and the experimental results are compared with the two simulation outcomes for validation. The comparative analysis highlights the superior performance and accuracy of the in-house code over the commercial program, with the in-house code demonstrating an average accuracy improvement of approximately 2% to 3% and with computational performance being approximately 1.7 times faster.

Time Is a Tool: Evaluation of a Prolonged Casualty Care Curriculum With a Focus on Temporal Fidelity.

In current and anticipated future conflicts, including large-scale combat operations, medical teams are tasked to provide prolonged casualty care (PCC) or extended patient care that occurs when delays in evacuation exceed the team's capabilities. Although the principles of PCC are often taught to military medical providers using simulation, educators rarely dedicate the time to training required to simulate the prolonged nature of these encounters. Therefore, a lack of knowledge exists regarding which aspects of extended care may be lost in an accelerated training scenario. To close this knowledge gap within military medical education and training, we modified an existing PCC curriculum at the USU, Operation Gunpowder, to focus on temporal fidelity, extending the length of the simulated encounter to 21 hours. We used a qualitative phenomenological design to explore the students' experiences and perceptions by closely analyzing their assigned reflection papers. We identified four themes from the students' reflection papers: (1) Recognized effects of fatigue, (2) navigated resource limitations, (3) realized the value of teamwork, and (4) noted the importance of communication and documentation. These themes revealed benefits of incorporating temporal fidelity into PCC training, including self-awareness of personal limits and possible strategies to mitigate fatigue when medical or operational mission requirements dictate sleep deprivation. Future studies are needed to determine other training scenarios that would benefit from adherence to temporal fidelity. Wars and disasters require medical providers trained in PCC. Future educational activities aimed at teaching PCC should continue to incorporate temporal fidelity to help teach these valuable lessons.

Analysis of Radio Science Data from the KaT Instrument of the 3GM Experiment During JUICE’s Early Cruise Phase

The JUpiter Icy Moon Explorer (JUICE) mission, launched on 14 April 2023, aims to explore Jupiter and its Galilean moons, with arrival in the Jovian system planned for mid-2031. One of the scientific investigations is the Geodesy and Geophysics of Jupiter and the Galilean Moons (3GM) radio science experiment, designed to study the interior structures of Europa, Callisto, and Ganymede and the atmospheres of Jupiter and the Galilean moons. The 3GM experiment employs a Ka-band Transponder (KaT) to enable two-way coherent range and Doppler measurements used for the gravity experiment and an Ultra Stable Oscillator (USO) for one-way downlink occultation experiments. This paper analyzes KaT data collected at the ESA/ESTRACK ground station in Malargüe, Argentina, during the Near-Earth Commissioning Phase (NECP) in May 2023 and the first in-cruise payload checkout (PC01) in January 2024. The radiometric data were fitted using both NASA’s Mission Analysis, Operations, and Navigation Toolkit Environment (MONTE) and ESA’s General Orbit Determination and Optimization Toolkit (GODOT) software. The comparison of the orbital solutions showed an excellent agreement. In addition, the Doppler and range residuals allowed a preliminary assessment of the quality of the radiometric measurements. During the NECP pass, the radio link data showed a range-rate noise of 0.012 mm/s at 1000 s integration time, while the root mean square of the range residuals sampled at 1 s was 8.4 mm. During the first payload checkout, the signal power at the KaT input closely matched the value expected at Jupiter, due to a specific ground station setup. This provided early indications of the 3GM’s performance during the Jovian phase. In this test, the accuracy of range data at an integration time of 1s, particularly sensitive to the link signal-to-noise ratio, degraded to 13.6 cm, whilst the range-rate accuracy turned out to be better than 0.003 mm/s at 1000 s, thanks to the accurate tropospheric delay calibration system (TDCS) available at the Malargue station (inactive during NECP).

Dust removal on solar panels of exploration rovers using Chladni patterns

The buildup of dust on solar panels has significantly reduced the operational lifespan and mission performance of exploration rovers, and traditional dust removal techniques have proven inadequate for the Martian environment. The present study proposes a novel method for removing dust from the solar panels of Mars exploration rovers using Chladni patterns, addressing the persistent issue of efficiency loss due to Martian dust accumulation. To overcome these challenges, the proposed method leveraged Chladni patterns, generated by specific frequencies, to effectively clear dust from the panels. We conducted experiments that identified optimal frequencies, frequency sequences, and plate shapes for dust removal, demonstrating the method’s effectiveness. In conclusion, our approach not only enhances the efficiency of solar panels but also has the potential to improve the overall performance and longevity of Mars exploration missions.

Ducted Fan Design for VTOL Aircraft Flight Mission Based on Bayesian Optimization

Vertical takeoff and landing (VTOL) aircraft have great potential in both military and civil applications. Due to the high power and energy requirements of VTOL and its potential widespread use in the future, it is important to improve the overall efficiency of VTOL aircraft, where one promising way is using the ducted fan concept because of the potentially higher aerodynamic performance and noise shielding effects. The goal of this paper is to adopt an approach that can efficiently include both continuous and discrete ducted fan design variables and further to design and to optimize the ducted fan for conceptual VTOL aircraft design study. Firstly, the open-source Ducted Fan Design Code (DFDC) tool is employed for fast and efficient ducted fan analysis. Then, we formulate the ducted fan design and optimization problem as mixed integer nonlinear programming to include both class-shape-transformation-based parameters and intuitive ducted fan parameters. The performance of the ducted fan was optimized for hovering, cruising, and the overall flight mission based on the Bayesian optimization approach. The results showed that optimization considering only hovering or cruising can enhance the performance of the ducted fan at the corresponding phase, but the overall aircraft performance might not be improved. As such, the whole aircraft flight mission performance was set as the design objective while carrying out the ducted fan optimization, which in the end led to the reduction of fuel consumption from the original 828.41 kg to 713.46 kg, i.e., about 15.9% fuel saving for the selected flight mission.

Preliminary Design of Expendable and Reusable Mixed-Staged Launch Vehicles

One of the very first tasks in launch vehicle design is the preliminary sizing. It is necessary for further design choices, but it should deliver a precise estimate of the launch vehicle’s mass and geometry as possible. Orbital launch vehicles can be either expendable or partially/fully reusable and can assume various stage configurations. Finding an optimal solution under practical constraints is a challenging task, which gives a wide design space for potential future launch vehicles. Hence, a generalized mathematical model of a launch vehicle design has been developed and implemented as a versatile and easily modifiable programming tool for fast and parametric system characterization and optimization. The model uses several basic parameters useful in describing launch vehicles and introduces some new parameters to account for reusability. Analytical and semi-empirical correlations are used to determine the overall system and mission performance of a launch vehicle for a given reference mission, including mass and geometry, and calculate the optimal launcher staging. The implementation of the model also allows coupling with other tools, which forms a design chain with respect to aerodynamics and trajectory simulation. With this design chain, several launch vehicles have been modeled and validated, proving the applicability of the method.

The RADARSAT Constellation Mission for Soil Moisture Retrieval of Bare Soil by Compact Polarimetry and Random Forest Regression

The RADARSAT Constellation Mission (RCM) performance evaluation is currently in progress for core Synthetic Aperture Radar (SAR) applications. This study aims to investigate the retrieval of Soil Moisture Content (SMC) in bare soil with RCM compact polarimetry and Random Forest Regression (RFR). The focus is on RH (right circular transmit and linear horizontal receive signal) and RV (right circular transmit and linear vertical receive signal) backscattering, which are the primary RCM Compact Polarimetric (CP) products. SMC retrieval is pursued over a wide range of radar incidence angles. Then, an attempt is made to retrieve SMC at higher radar incidence angles only. Furthermore, soil moisture maps are produced and used for analyzing the captured soil moisture variability. CP SAR images acquired with the RCM SC30MCP mode over three Canadian experimental sites are considered in our study. The sites are equipped with calibrated Real-Time In-Situ Soil Monitoring for Agriculture (RISMA) stations. A RFR retrieval algorithm was able to predict SMC with a correlation of 0.75 when compared to in-situ soil moisture measurements. A Root Mean Square Error (RMSE) = 5.9%, a bias = −1.5%, and an unbiased RMSE (ubRMSE) = 5.7% are achieved. A degradation in performance is reported for SMC retrieval under higher radar incidence angles. Results of our study indicate promising performance for capturing near-surface soil moisture variability under bare soil conditions.

SYNERGISTIC CONFLICT-FREE UAV SWARM MOVEMENT MODELING USING METAHEURISTIC APPROACHES

The paper considers a new synergistic conflict-free movement model for unmanned aerial vehicle (UAV) swarm on the battlefield, based on the metaheuristic approach of particle swarm optimization (PSO). The paper presents an improved algorithm that ensures effective swarm coordination, traffic safety and efficient communication between UAVs. The model is designed to be used in various combat conditions and demonstrates the ability of the swarm to adapt to dynamic changes on the battlefield and perform tasks with high efficiency. Improvements to the PSO algorithm include the addition of collision avoidance force vectors, which allows each UAV take into account the position of its neighbors and avoid conflict situations. This ensures a more stable and smoother UAV swarm movement, reducing the risk of collisions and increasing the overall effectiveness of combat missions. The model also provides for the ability to adapt to changing conditions on the battlefield, which allows the UAV swarm to respond effectively to new threats and challenges.The simulation results show that the proposed metaheuristic approach based on the improved PSO algorithm is capable of calculating suboptimal trajectories for UAV swarm, minimizing the risk of collisions and improving the overall performance of combat missions. A comparative analysis with the classical PSO algorithm has revealed the advantages of the proposed model in the context of the efficiency of coordination and safety of UAV swarm movement. These results confirm the prospects of using the developed approach to control UAV swarms in combat conditions.The proposed algorithm allows each UAV in the swarm to take into account the other UAV position and speed, which allows maintaining the optimal distance between them, reducing collision probability. This is achieved by introducing an avoidance force vector that is directed away from other UAVs. This approach allows a swarm of UAVs to act as a single organized structure, which significantly increases the efficiency of performing tasks in complex and dynamic combat conditions. In addition, the model takes into account various combat scenarios, including obstacle avoidance, target acquisition, and retreat to a safe distance. This makes the algorithm a versatile tool for managing UAV swarms in real-world combat conditions, where the speed of reaction and accuracy of task execution are crucial.

Simulation for SEAD Mission with MUM-T

In the air power, UAVs have played a large and diversified role in performing missions from simple to high-level complex ones. In particular, the suppression of enemy air defenses(SEAD) is very dangerous for a pilot so it is expected that the manned-unmanned teaming(MUM-T) system with tailless stealthy unmanned aerial vehicle(UAV) will greatly enhance effectiveness of the mission while ensuring the pilot safe. This paper describes simulation studies of remote airborne control(RAC) environment for performing the SEAD mission by MUM-T, by which the air force pilot remotely controls tailless UAVs individually or small UAVs in swarm. Through this simulation, air force pilot can derive the concept of MUM-T mission operation with various UAVs in the future, and it can be used to upgrade the MUM-T system by verifying the effectiveness of the mission.

Mission performance of different landing gear types in medium-sized twin engine helicopters

Mission performance of different landing gear types in medium-sized twin engine helicopters

Defining and Measuring Crewmember Operational State for Spaceflight Operations.

A suite of human health and performance metrics can be used to provide a holistic cognitive, physical, and emotional view of an individual and assess how well they are integrated with the overall system during spaceflight missions. The combination of such individual metrics as defined here is notionally termed "crewmember operational state." This work identifies and defines the contributing components that comprise the proposed crewmember operational state. Considerations of how to measure the components in a spaceflight environment are summarized and the steps required to analyze and integrate these measurements into an operational framework are outlined. Use of the measurements and integration steps are then extended into several applications relevant to human spaceflight mission design and operations. For the framework and applications defined here to become operationally feasible, several limitations and gaps that remain to be addressed are presented with recommended future research and enabling technology advancement needs. Zero M, Klaus D, Arquilla K, Fanchiang C. Defining and measuring crewmember operational state for spaceflight operations. Aerosp Med Hum Perform. 2024; 95(12):919-929.