Mission Time Research Articles

A Balanced Mission Planning for Multiple Unmanned Underwater Vehicles in Complex Marine Environments

The collaboration of a multiple unmanned underwater vehicles (multi-UUVs) system has attracted widespread attention in recent years, as it can overcome the limitations of a single UUV and enhance mission completion efficiency. Oriented towards patrol and exploration missions with multiple waypoints, this paper proposes a balanced mission planning strategy, aiming to improve mission quality while reducing mission time for multi-UUVs. Firstly, due to the uneven performance of the two optimization objectives, a quick initialization screening method is employed specifically for mission quality to reduce the mission space. Secondly, to ensure mission load distribution and collaboration among multi-UUVs, and ease the difficulty in solving the issues of mission allocation and route planning, a balanced bi-level mission planning method based on regional segmentation is proposed. Finally, applicable weight evaluation criteria are utilized to evaluate the feasible solution set and determine the optimal solution. The efficacy of the balanced mission planning strategy is substantiated through comprehensive numerical simulations in a complex 2D marine environment.

Uncrewed Aerial Vehicle Routing Problem for Integrated Crewed and Uncrewed Aircraft Operations

Last-mile delivery systems are one of the numerous industrial applications of uncrewed aircraft systems (UAS). This study analyzes UAS-based package delivery systems in the context of the integrated operations of crewed and uncrewed aircraft. It introduces a multi-trip, time-dependent vehicle routing problem aimed at optimizing UAS delivery routes within integrated operations. By conducting numerical simulations of helicopters (crewed aircraft) and UAS missions sharing the same airspace, the optimal UAS routes for resolving potential conflicts in the shared airspace can be effectively determined without any adverse impact on helicopter operations. Knowing the helicopter mission times in advance enables the efficient planning of UAS missions. The results of this study provide valuable insights regarding the implementation of integrated crewed and uncrewed aircraft operations.

A Time and Energy Efficient Multi-UAV Coverage Planning for the Search and Rescue Mission under Wind fields

This paper discusses how to quickly and efficiently search for victims when a disaster occurs. Since the search area is large, the search time of a single UAV will be too long to satisfy the golden window of the search and rescue mission. Therefore, it is necessary to dispatch multiple UAVs to conduct a cooperative search by proposing a multi-UAV area coverage planning under wind fields (MUCPW) algorithm and its variant MUCPW-A to achieve the shortest mission time. It first averagely divides the search area into several regions, formulates equations to calculate the minimum mission time and corresponding energy consumption among all possible area partition methods. As compared to related work, simulation results show that MUCPW and MUCPW-A achieve the shortest mission time and the least energy consumption to search all victims in the search and rescue mission. Further, MUCPW-A achieves the smallest standard deviation in energy consumption.

Adaptive robust fault-tolerant control of spinning tether system for space debris removal

The Spinning Tether System (STS) is currently recognized as one of the most effective and ideal platforms for removing space debris. It offers several advantages, including a non-contact mechanism, rapid deorbit capabilities, stable spinning, and a short preparation time for subsequent missions. The system primarily depends on the thrusters of the main spacecraft and the capture device for its spin-up process. Although modern technology and quality management methods strive to minimize thruster failures, the capture of debris significantly affects the STS. This impact can induce tether oscillations and cause actuator failures, thereby destabilizing the spin-up process. Given these challenges, this paper explores the design of fault-tolerant control strategies to enhance system reliability during the post-capture spin-up phase. Initially, a dynamic model using quaternions as generalized coordinates was established based on the constrained Lagrange equation. This model facilitated a detailed analysis of potential thruster failure modes. Subsequently, the optimal trajectory for the spin-up process was planned using the pseudo-spectral method, ensuring efficiency and safety in control execution. To address the identified vulnerabilities, the study introduces an adaptive robust fault-tolerant controller. This controller, based on a BLF and integrated with a nonlinear neural network disturbance observer, is designed to operate effectively under fault conditions. Numerical simulations were conducted to validate the performance of the controller, demonstrating its capability to maintain stable control of the system, both after detecting a fault signal and following an actuator failure.

A Novel MPC Formulation for Dynamic Target Tracking with Increased Area Coverage for Search-and-Rescue Robots

Robots are increasingly deployed for search-and-rescue (SaR), in order to speed up rescuing the victims in the aftermath of disasters. These robots require effective mission planning approaches to determine time and space-efficient trajectories that steer them faster towards (moving) victims, while dealing with uncertainties. Model predictive control (MPC) is an effective optimization-based control approach that has been used to steer robots along reference trajectories determined by higher level controllers. Determining the trajectory of the robots directly via MPC has the advantage of optimizing multiple SaR criteria while handling the constraints. We, thus, introduce a path planning approach based on MPC for indoor SaR robots that allows the robot to systematically chase the moving victims, when no reference trajectory is provided. The proposed approach combines target-oriented and coverage-oriented search, and allows for systematic handling of environmental uncertainties, by deploying a robust tube-based version of the introduced MPC formulation. In addition, we model the movements of the victims for MPC, by adopting an existing evacuation model. We present a case study, using Gazebo, MATLAB, and ROS, where the performance of the proposed MPC controller is evaluated compared to four state-of-the-art methods (two target-oriented methods based on MPC and A* and two heuristic algorithms for area coverage). The results show that, while robust to uncertainties, our approach overall outperforms the other methods, with regards to victim detection, area coverage, and mission time.

Enhancing Mission Wellness: Iterative Optimization and Stakeholder Engagement to Promote Sexual and Reproductive Health in the United States Military.

Sexual and reproductive health is critical for the readiness of the warfighter, as costs of sexually transmitted infections and unintended pregnancy result in added health care costs, lost mission time, and impact on morale. The Multiphase Optimization Strategy (MOST) is an engineering-inspired framework used to optimize biobehavioral interventions. The Military Active-Duty Reproductive and Sexual Health (MARSH) research team applied the MOST framework to develop "Mission Wellness"-an electronic health intervention to promote sexual and reproductive health within the U.S. Military. From 2017 to 2022, the MARSH team implemented the first and second phases of MOST to develop and optimize "Mission Wellness." All phases received institutional review board approval. The first phase consisted of expert and literature review, qualitative interviews, and beta testing to identify intervention components and the optimization objective and to inform study design. The second phase consisted of a factorial trial. Figures1-4 outline the research program approach, demographics of the sample, and format of the app. Service members who used the application found it to be acceptable and, overall, reported that it would be easier to talk to a sexual partner about risk behaviors and history at the post-intervention assessment compared to baseline. This iterative optimization approach using both local and strategic engagement enhanced program development and set the stage for dissemination and implementation efforts. In line with the iterative nature of MOST, the lessons learned during the optimization trial led the MARSH team to return "Mission Wellness" to the preparation phase. The utilization of mixed (i.e., qualitative and quantitative) research methods and engagement with stakeholders at multiple levels of the military enterprise provided the information necessary to further optimize "Mission Wellness." This programmatic approach also provides a blueprint for the development of research design and testing in military health care balancing rigor and agility.

Structural control on the landscape evolution and avulsive behavior of rivers at mountain exits: The example of the Kosi River in eastern Nepal Himalaya

The Kosi River flows from the eastern Nepal Himalaya into the state of Bihar (India) and has experienced frequent avulsions, causing extensive flood-related damage. Because of this avulsive behavior, the Kosi is called the “Sorrow of Bihar.” The avulsion of 2008 was the most catastrophic avulsion event recorded for the Kosi and has been attributed primarily to hydrological and sedimentological processes that formed a super-elevated river channel and caused avulsion. Detailed topographic analysis of the region near the Kosi exit from the Himalaya, using mean-corrected and resampled 1-arc, Shuttle Radar Topography Mission (SRTM) and Real Time Kinematic Global Positioning System (RTK-GPS) datasets, reveals that the Kosi channel is super-elevated only relative to its eastern floodplain. The western floodplain elevation is similar to or higher than the Kosi channel in the region between the Kosi River exit from the main eastern Nepal Himalaya and the Kosi barrage at the Indo-Nepal border. Structurally, the Kosi exits the Himalaya in the transition zone between the closed Trijuga dun to the west and the Dharan salient to the east. The Trijuga dun is closed by the Main Frontal thrust (MFT)-related frontal topography or the Outer Churia Hills. The eastern slopes of these hills induce west-to-east topographic slope in the channel, such that topographic avulsion indices are highest only in the Outer Churia Hills affected parts of the Kosi Channel and the 2008 avulsion region. Therefore, our preferred model for the primary control on the channel's asymmetric, metastable, super-elevation is the influence of the tectonically controlled MFT-related Outer Churia Hills on the Kosi River channel. Geomorphological processes have operated in the Kosi channel in this backdrop. This study emphasizes that detailed structural and topographic analysis of river exits from mountain belts like the Himalaya can provide better insights into river channel metastability and avulsion worldwide.

Design and analysis of a novel thermal management system for serving next-generation aircraft with megawatt-level heat loads

Due to the development of electronics and high-energy pulse devices, in conjunction with the increasing flight speeds, the instantaneous heat load of next-generation aircraft will reach the megawatt level, which poses severe challenges for thermal management. To improve the heat dissipation capability, this paper presents a novel thermal management system (TMS) employing liquefied natural gas (LNG). This TMS design incorporates four merits: LNG and fuel share the heat load of electronics which dramatically enhances the mission time; the air circulation subsystem selects different combinations of heat sinks depending on the engine's operational state; LNG spray cooling efficiently handles the heat load of directed energy weapons; the heat sinks release the cooling capacity in a temperature gradient to maximize efficiency. The performance of the TMS is verified in a harsh flight profile. The selection of an appropriate return location and the storage of low-temperature fuel can enhance the efficiency of the fuel heat sink. An effective means of improving the vapor compression subsystem's efficiency is increasing the withstand temperature of the electronics. The introduction of LNG extends mission time by more than three times with minor fuel penalties. The potential for utilizing turbines to enhance LNG cooling efficiency is explored.

Optimal component activation in multi-attempt missions with common shock process

Abundant research efforts were devoted to modeling and optimizing mission systems operating in random shock environments. The existing models assumed that different components are exposed to independent shock processes. However, in many real-world applications (e.g., virtual machines in cloud computing, drones deployed in the same mission), multiple operating components may be simultaneously impacted by common shock processes during the mission, causing them to deteriorate and even crash. This paper contributes by modeling a multi-attempt mission system with heterogeneous components characterized by different performance, shock resistance and cost. Each component may start performing the mission at different times and a common shock process can negatively affect all operating components. Different activation schedules of system components may lead to dramatically different mission success probabilities and expected component losses, contributing to the expected mission losses (EML). We formulate and solve a new optimal component activation schedule (CAS) problem to minimize the EML. The proposed model is demonstrated through a case study of an aerial vehicles delivery mission system. Influences of several key model parameters (shock rate, mission failure penalty, allowed mission time, and component performance) on the mission performance metrics and the optimal CAS solutions are also investigated using the case study.

Multidisciplinary Design Optimization of Active Debris Removal Mission via Electric Propulsion

A design optimization framework for an active orbital debris removal mission to minimize the life cycle cost and mission time is presented. The general concept of operations consists of spacecraft capable of deorbiting 22 identical high-priority debris from sun-synchronous orbit via continuous low thrust from electrostatic thrusters. This modular subsystem framework is proposed and investigated with a fractional factorial design of experiments approach as preliminary analysis in order to inform effects of design variables as well as identify the scope of possible design and output space. The single-objective optimization minimizes the life cycle cost of the mission through a heuristic-based genetic algorithm, resulting in a 4.12-year, $354 million mission using 5.34 kW xenon Hall thrusters. Pareto fronts generated by a multiobjective weighted-sum genetic algorithm are presented to highlight the cost and time objective space for both a nominal and expensive xenon price per kilogram to show design space fluctuations with xenon price volatility. High-power 8 kW xenon Hall thrusters are proven to be in closest proximity to the utopia of the multiobjective design space with a cost of $687 million and mission time of 1 year. High-power krypton Hall thrusters prove to offer a comparable alternative to xenon systems.

Pulsed Laser Links Simulation for Small Satellite Clock Model Estimation

The expansion of satellite constellation applications brings attention to the need for responsive, reliable satellite communication. For preflight technology assessment of missions, a simulation of two spacecraft in low Earth orbit has been created to estimate clock synchronization and precision orbit determination based on measured instrumentation performance. A novel MATLAB-based numerical simulator was developed to model spacecraft-to-spacecraft laser time-transfer and estimate the offset between the spacecraft clocks over time. This simulation includes timing errors associated with laser pulse detection, as well as non-Gaussian clock drift models. Two on-board clocks are modeled: a cesium-based chip-scale atomic clock and a rubidium-based miniature atomic clock. The positions and velocities of the spacecraft at a reference epoch and the constant coefficients of a polynomial clock model are estimated. Results compare the estimated clock model of a mission operation that only uses GPS measurements and one that uses both GPS and laser pulse time-of-flight measurements between spacecraft referenced to their on-board clocks. Including lasing measurements reduces the root-mean-square clock model error to approximately 80% of the RMS of the cases with only GPS measurements. This simulation tool can be used to optimize the lasing operations schedule based on mission timing performance objectives.

Reliability analysis of GAN based transmit modules for active array antenna of phased array radar

Reliability is one of the most important requirements in our day to day life considering consistency, availability and failure free performance of the product over it’s define mission time. As complexity of the system increases, design for reliable systems is a big challenge. The objective of the reliability prediction analysis is to evaluate the predicted reliability of the active transmit receive modules (TRMs) under specified operating conditions, and to demonstrate that the predicted reliability meets the requirements, also to identify any parts present in the design which leads to higher failure rates. The research shows reliability of generative adversarial network (GAN) based TRMs covering from design to finalization of components as early as practicable in today's short product lifecycles. Using the reliability prediction process, we describe a method for providing design engineers with reliability feedback on their decisions. Using a conventional reliability prediction model, the Telcordia (Bellcore) parts stress prediction model, and some standard rules of thumb, we describe an initial implementation of this technique. It provides systematic identification of likely modes of failure, possible effects of each failure, and the criticality of each failure with regard to reliability, system readiness, mission success, and demand for maintenance/logistic support.

Impact of the Coronavirus Pandemic on Patients Requiring Tracheal Intubation by Helicopter Emergency Medical Services: A Retrospective, Single-Center, Observational Study.

Background/Objectives: The impacts of the coronavirus disease 2019 (COVID-19) pandemic on patients using helicopter emergency medical services (HEMS) regarding tracheal intubation and patient management remain unclear. Thus, we aimed to investigate this matter in Japan. Methods: In this retrospective, observational study, we analyzed 2277 patients who utilized HEMS in Tochigi Prefecture during 2018-2022. We included only patients who required tracheal intubation. We categorized patients from February 2020 to January 2022 in the pandemic group and those from February 2018 to January 2020 in the control group. We compared the interval from arrival at the scene to leaving the scene (on-scene time) and secondary variables between the two groups. Results: A total of 278 eligible patients were divided into the pandemic group (n = 127) and the control group (n = 151). The on-scene time was lower during the pandemic than that before (25.64 ± 9.19 vs. 27.83 ± 8.74 min, p = 0.043). The percentage of patients using midazolam was lower (11.8% vs. 22.5%, p = 0.02) and that of patients using rocuronium bromide was higher (29.1% vs. 6.0%, p < 0.001) during the pandemic. In contrast, the type of intervention other than tracheal intubation and the type of transportation to the hospital did not differ between the groups. Conclusions: The COVID-19 pandemic was associated with changes in the mission time of and the frequency of certain drugs administered by the HEMS. However, the type of intervention and the type of transportation did not differ. Further research is needed on changes in patient prognosis and condition due to the effects of the COVID-19 pandemic.

Sensing technologies for the challenging Lunar environment

This study reviews major sensing technologies for the Lunar environment and its resources, as they have been developed since the times of Apollo missions. Selected technologies of sensors and instruments for the chemical, isotopic, and structural analysis of Lunar rocks and regoliths, as well as of the Lunar exosphere environment, are presented in a critical review towards an optimised and information-rich framework. Special focus is given on the activated Lunar regolith, and especially the Lunar dust, describing the development of Lunar simulants as the only accessible materials for experimentation and testing of the above technologies. New technologies are also highlighted, such as the development of the OxR microfluidic and spectroscopy integrated device, which, in its small scale aims to detect reactive oxygen species in the Lunar regolith, while in its larger format it is used to release oxygen gas from the Lunar dust and regolith, enabling astronaut respiration and fuel production on the Moon. It is finally suggested that miniaturisation of instruments and sensors, together with the standardisation of output information and characterisation protocols through holistic informational frameworks, will enhance the dynamic expansion and further integration and interoperation of sensors and devices, aiming to an efficient, safer, and resilient utilisation on the Moon and the establishment of sustainable settlements in the near future.

Autonomous construction of lunar infrastructure with in-situ boulders

Significant infrastructure is required to establish a long-term presence of humans on the lunar surface. In-situ resource utilization (ISRU) is a fundamental approach to ensure the viability of such construction. Here, we investigate the feasibility of constructing blast shields as one example of lunar infrastructure using unprocessed lunar boulders and an autonomous robotic excavator. First, we estimate the volume of unprocessed material required for the construction of blast shield segments. Secondly, we quantify the amount of available boulders in two exploration zones (located at the Shackleton-Henson Connecting Ridge and the Aristarchus Plateau pyroclastic deposit) using LRO NAC images and boulder size-frequency distribution laws. In addition, we showcase an alternative approach that relies on Diviner rock abundance data. Thirdly, we use a path planning algorithm to derive the distance, energy, and time required to collect local material and construct blast shield elements. Our results show that our construction method requires two orders of magnitudes less energy than alternative ISRU construction methods, while maintaining realistic mission time and payload capacity margins.

Enabling efficient satellite mission design with rule-based collision avoidance

The growing number of operational spacecraft in Earth's orbit entails an increasing operational effort for collision avoidance (COLA), particularly regarding the coordination of evasive measures. To reduce the associated workload, COLA operations should already be considered in the early planning phases of space missions. The Mission Analysis Software (MAS) is a web-based application developed within the ESA-funded CASCADE (Collision avoidance, satellite coordination assessment demonstration environment) project by OKAPI:Orbits and TU Darmstadt for this purpose. The software follows a data-driven approach to offer satellite operators, mission designers, service providers, agencies, and authorities two services: conjunction assessment and rule analysis. The conjunction assessment provides an estimation of the number and type of conjunctions to be expected on the targeted orbit and identifies frequently conjuncting parties for the current population of active satellites as well as for conceivable future scenarios. The rule analysis follows a rule-based approach to coordinate COLA between individual operators, allowing users to build custom hierarchical rule sets from pre-defined rule building blocks to achieve a desired split of effort between the conjunction parties. The MAS enables the assessment of the operational consequences for a chosen rule set, empowering users to reach bilateral agreements with identified frequently conjuncting parties to determine the obligation to take evasive measures for future conjunctions. The approach of the MAS allows for the pre-emptive reduction of the expected number of conjunctions enabling operators to optimize orbit parameters within their mission constraints as well as the automatization of COLA coordination during operations. Through this, the MAS optimizes propellant needs, mission time, and required workforce associated with COLA for space missions.This paper presents the MAS, showcasing the key features and use cases that have been developed closely with stakeholders and the European Space Agency. Furthermore, the data-based simulation approach of the MAS will be explained, covering the data sources and design choices for the conjunction detection and propagation module. The paper also presents the results of a preliminary rule analysis conducted for the population of active satellites in low Earth orbit as of April 2023. As an intermediate result of an on-going research activity involving the authoring entities, a major goal of this paper is to engage with satellite operators, mission designers, service providers, agencies, and authorities in order to tailor the results of the activity to their actual needs.

MODELING AND OPTIMIZATION OF A PCM-BASED OCEAN THERMAL ENERGY HARVESTER FOR POWERING UNCREWED UNDERWATER VEHICLES

Abstract As oceans cover over 70% of the planet's surface, they represent a large reservoir of resources that remained vastly untapped. Uncrewed Underwater Vehicles (UUVs) are becoming key technology for ocean exploration. Ocean thermal gradient is a permanent and reliable energy source that can be used to power UUVs using phase change material (PCM)-based thermal engines. When using PCM-based thermal engines to power UUVs, there are different energy conversion stages, thermal, hydraulic, kinetic, and electrical, dependent on a wide variety of parameters. Thus, optimization of the overall energy conversion is still a challenge for powering the increasing energy demanding UUVs for long missions. The goal of this study is to propose a PCM-based ocean thermal energy harvesting system for powering float type UUVs such as the Solo II float. This reduces the cost for battery replacement and expands the float's mission time. For this purpose, we developed a model consisting of hydraulic and electrical systems, designed to provide the electrical power needed by the UUV. The hydraulic and electrical systems are implemented using MATLAB-Simulink. The model developed can provide 13.66 kJ of electrical energy, which is more than 1.5 times the energy requirement per cycle for the SOLO II float.

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.

The Prolonged Path of Indigenization: A Study on German Protestant Missionary Ernst Faber’s Chinese Literary Works

Ernst Faber’s 34 years of literary missionary works reveal his commitment to refining his approach to indigenizing Christianity in China. Employing three linguistic and cultural adaptation strategies—translation and commentary of the Bible, examination and analysis of missionary practical outcomes in Western society, and the revision and reinterpretation of Chinese classics incorporating Christian insights—Faber adapted his methods gradually into China’s specific conditions, indicating a prolonged path of indigenization. Despite expressing appreciation for Chinese culture, a critical examination reveals the preservation of his cultural biases and an unwavering commitment to Christianity as a means of purifying and enriching the spirit of the Chinese people. Rooted in the political context of his time and confidence in European historical world missions, Faber’s indigenization strategy in his Chinese literary works represents an interplay of cultural adaptation and resistance.

A Spacecraft Onboard Autonomous Task Scheduling Method Based on Hierarchical Task Network-Timeline

To address the inherent challenges of deep space exploration, such as communication delays and the unpredictability of spacecraft environments, this study focuses on enhancing spacecraft adaptability and autonomy, which are essential for Autonomous Space Scientific Exploration. A pivotal aspect of this endeavor is the advancement of spacecraft task scheduling, which is integral to increasing spacecraft autonomy. Current research in this domain predominantly revolves around mission timing planning and is primarily executed from ground stations. However, these plans often lack the granularity required for direct implementation by spacecraft. In response, our study proposes an innovative approach to augment spacecraft autonomy, introducing a method that articulately describes mission objectives and resource information. We designed a novel hierarchical task network-timeline (HTN-T) algorithm, an amalgamation of the HTN scheduling method and the distinctive elements of existing research. This algorithm addresses time constraints through horizontal and vertical expansions, building upon the resolution of logical constraints found in conventional planning methods. Furthermore, it introduces a priority-based strategy for resolving resource conflicts in spacecraft tasks. This algorithm is substantiated through validation, including proof-of-principle demonstrations and assessments within a Space–ground Collaborative Management and Control System encompassing both ground and spacecraft operations. The findings indicate that our proposed algorithm achieves high rates of scheduling success and operational efficiency within a feasible timeframe, thus effectively navigating the complexities of autonomous spacecraft task scheduling.