Mission Cycle Research Articles

Modeling random warranty and replacement strategies for products with two modes of failure and mission cycles

Characteristics like mission cycle, failure number, and failure mode act as crucial metrics for evaluating the reliabilities of products subject to various failure modes. As a result, this study develops two distinct strategies to manage product reliabilities. The first strategy focuses on managing warranty-stage reliability and employs renewable-free replacements to enhance warranty appeal. Using either the criterion of “whichever occurs first” or “whichever occurs last”, this strategy is called a three-dimensional random warranty-first-or-last approach with renewable-free replacement. The second strategy involves various replacements, providing comprehensive management of post-warranty reliability. The first approach within this second type of strategy is called the bivariate random periodic replacement-first-with-corrective-replacement method. The proposed warranty can identify reliability heterogeneities, which serves as the basis for adapting the second approach within the second type of strategy. Time and cost factors are used to quantify the proposed strategies. Numerical analyses are carried out focusing on key parameters.

Modeling Renewable Warranties and Post-Warranty Replacements for Self-Announcing Failure Products Subject to Mission Cycles

Modeling Renewable Warranties and Post-Warranty Replacements for Self-Announcing Failure Products Subject to Mission Cycles

Low-thrust trajectory optimization of deep space exploration based on discrete pulse method

Deep space exploration is gradually becoming the hot mission of human space activities, and this kind of mission has the characteristics of a long mission cycle, complex space environment, high fuel demand, and difficult telemetry track and command, etc. It is the future trend to carry out deep space exploration activities using low-thrust propulsion systems, and the trajectory optimization of interplanetary missions is one of the significant difficulties. Considering the characteristics and difficulties of interplanetary missions, a method of transfer orbit preliminary design in the multi-body system is proposed in this paper. The simulation results illustrate that the transfer orbit obtained by the method in this paper can provide a reliable initial guess for the optimization of high-precision orbit and decrease convergence sensitivity. The research results can provide a significant reference for the implementation of deep space exploration missions in China in the future.

CORBES: Radiation belt survey with international small satellite constellation

The COnstellation of Radiation BElt Survey program (CORBES) is designed to deploy small satellites into a highly elliptic orbit for multi-point exploration of the Earth’s radiation belts. Its scientific objective is to achieve unprecedented high-time-resolution dynamics measurements within the regions of Earth’s outer radiation belts. The CORBES program initiative comprises satellites equipped with three types of payloads: the Magnetometer (MAG), the Search Coil Wave Detector (SCWD), and the High Energy Electron Detector (HEED). The energy interval of HEED is suggested as 0.1–4 MeV, logarithmically divided into 12 channels. To ensure extensive coverage of the outer radiation belts, a highly eccentric and inclined orbit is suggested, featuring a perigee of 280 km, an apogee of 7 Earth-Radius (Re), and an inclination of approximately 11°, resulting in an orbital period of approximately 13.5 h. Within a single orbital period, it takes roughly 10 h to traverse the outer radiation belts (3 Re to 7Re). All satellites are expected to operate within the same orbit, maintaining a spin-stabilized with sun-pointing spinning axis, and a spinning speed of approximately 8 RPM. Each satellite’s mass should not exceed 30 kg. For telecommand, either S-band or X-band will be utilized, while X-band is designated for data downlink. The satellites are scheduled for launch by one or two rockets, with the equipped upper stage placing them into the target orbit, and the attached dispenser releasing them individually according to the required separation sequence. Key aspects of the program include cross-calibration, radiation shielding, assembly integration and testing (AIT). Prior to launch, the cross-calibration is optional for the payloads. The payloads will be tested in the same environment to calibrate the technical specifications. Post-launch, in orbit cross-calibration becomes necessary to maintain data consistency and comparability. Specifically for HEED, this involves selecting electrons with the same energy range during the magnetospheric quiet period (Kp < 3), and comparing the observation results of different HEEDs under the same L,B conditions. A similar method applies to MAG and SCWD comparing observations during selected quiet period. Given that the satellites will operate within radiation belts characterized by high-energy protons at low altitudes and electrons at high altitudes, all on-board electronic components must meet fundamental requirements, including shielding geometry structure design, and thickness calculation to mitigate the Total Ionizing Dose Effect (TID) to a level of 200 krad [Si] over a one-year mission cycle. Lastly, system-level AIT before launch could be performed.

Dynamic predictive maintenance strategy for system remaining useful life prediction via deep learning ensemble method

In data-driven prognostics and health management (PHM), most studies focus only on prognostics performance but rarely consider maintenance decision problems. However, simple predictive maintenance decisions are not effective in dealing with the complex operating conditions faced in modern industrial systems. Thus, we propose a complete data-driven dynamic predictive maintenance strategy for system remaining useful life (RUL) prediction via deep learning ensemble method to solve this problem. This deep learning ensemble method is composed of a convolutional neural network (CNN) and a bidirectional long short-term memory network (Bi-LSTM), which aims to effectively predict the system RUL. Then, we consider a dynamic predictive maintenance strategy with uncertain system mission cycles based on the RUL predicted by deep learning ensemble method. Meanwhile, this dynamic predictive maintenance strategy includes order, stock, and maintenance decisions. In addition, the number of missions performed by the system and the reliability of the last performed mission are presented based on the mission cycle and the predicted RUL. Finally, experimental results from the NASA turbofan engine dataset C-MAPSS show the favorable performance of the proposed dynamic predictive maintenance strategy compared to the existing maintenance strategy.

Three-dimensional warranty and post-warranty maintenance of products with monitored mission cycles

Three-dimensional warranty and post-warranty maintenance of products with monitored mission cycles

Nezha-F: Design and Analysis of a Foldable and Self-Deployable HAUV

This letter introduces a small hybrid aerial underwater vehicle (HAUV), which we named Nezha-F, that can fly in the air, perform vertical profiling underwater, and vertically take off and land from both the water surface and ground. A foldable and self-deployable arm mechanism linked to and driven by a piston variable buoyancy system (PVBS) is proposed to reduce the excessive underwater drag caused by aerial structures. By having a compact size and successfully balanced aerial and underwater performance without adding excessive actuators, this design provides a feasible idea for the miniaturization of amphibious floats. The dynamic characteristics of the small PVBS are linear fitted, and modeled. The originally nonlinear actuator performance is linearized by the post-fitting mapping. Asymmetric dead zones of the actuator are removed by adding compensation to the algorithm. During a 10-day field test, the vehicle showed good aerial performance and underwater control effect. Several full mission cycle tests proved the vehicle's ability in semi-autonomous operation and robust domain crossing and verified the vehicle's endurance during each mission stage.

Study of a Random Warranty Model Maintaining Fairness and a Random Replacement Next Model Sustaining Post-Warranty Reliability

With the help of advanced digital technologies, product managers can use monitored mission cycles to sustain product reliability. In this study, a random warranty model and a random replacement next (RRN) model are designed to sustain the through-life reliability of the product with monitored mission cycles. The designed random warranty, called a two-stage two-dimensional free repair warranty (2DFRW), can be carried out to sustain the reliability of the product during the warranty stage. In this warranty, ‘whichever occurs first and last’ is used to distinguish the coverage ranges of the latter stage warranties, which is to maintain the warranty fairness by removing the inequity of the former stage warranty. The RRN can be performed to sustain post-warranty reliability, which defines that if the limited number of mission cycles is completed before a working time, then the product will be replaced at next mission cycle completion to extend remaining service life; otherwise, the product will be replaced at a working time. Under the case of the two-stage 2DFRW, the cost rate of the RRN is constructed based on the renewable reward theorem. By simplifying the parameters, some derivative models of the cost rate are presented. Numerical analysis is performed to explore characteristics.

Numerical simulation and performance analysis of the radiofrequency inductive cathode

The radiofrequency (RF) inductive cathode has great prospects in space missions with long mission cycles, large speed increments, and rapid response requirements as the main electron source and neutralizer in Hall thrusters and ion thrusters. This paper proposes a comprehensive multi-physics RF inductive cathode model in which the RF electromagnetic field, electrostatic field for extracting electrons, flow field, plasma transport and electrochemical reaction process are all accounted for. Each physical field mentioned above can form a closed partial differential equation. The two-dimensional finite element code COMSOL is used to solve the multi-physics model. With this model, the formation process of the anode spot is exhibited and demonstrates the non-bipolar flow theory in practice. The simulation results demonstrate that the current jump in the RF inductive cathode is caused by the anode spot. Furthermore, the influences of preset discharge parameters such as RF power, bias voltage and actuating gas flow as well as structural parameters like the coil structure, discharge chamber size and ion collector area, emission hole size, distance between the anode target and the emission hole etc on the cathode performance are investigated, and some important optimal parameters are proposed.

Lessons learned from the first 50 COVID-19 critical care transfer missions conducted by a civilian UK Helicopter Emergency Medical Service team

BackgroundThe COVID-19 pandemic has placed exceptional demand on Intensive Care Units, necessitating the critical care transfer of patients on a regional and national scale. Performing these transfers required specialist expertise and involved moving patients over significant distances. Air Ambulance Kent Surrey Sussex created a designated critical care transfer team and was one of the first civilian air ambulances in the United Kingdom to move ventilated COVID-19 patients by air. We describe the practical set up of such a service and the key lessons learned from the first 50 transfers.MethodsRetrospective review of air critical care transfer service set up and case review of first 50 transfers.ResultsWe describe key elements of the critical care transfer service, including coordination and activation; case interrogation; workforce; training; equipment; aircraft modifications; human factors and clinical governance. A total of 50 missions are described between 18 December 2020 and 1 February 2021. 94% of the transfer missions were conducted by road. The mean age of these patients was 58 years (29–83). 30 (60%) were male and 20 (40%) were female. The mean total mission cycle (time of referral until the time team declared free at receiving hospital) was 264 min (range 149–440 min). The mean time spent at the referring hospital prior to leaving for the receiving unit was 72 min (31–158). The mean transfer transit time between referring and receiving units was 72 min (9–182).ConclusionCritically ill COVID-19 patients have highly complex medical needs during transport. Critical care transfer of COVID-19-positive patients by civilian HEMS services, including air transfer, can be achieved safely with specific planning, protocols and precautions. Regional planning of COVID-19 critical care transfers is required to optimise the time available of critical care transfer teams.

Design Considerations of Low Bypass Ratio Mixed Flow Turbofan Engines with Large Power Extraction

The possibility of extracting large amounts of electrical power from turbofan engines is becoming increasingly desirable from an aircraft perspective. The power consumption of a future fighter aircraft is expected to be much higher than today’s fighter aircraft. Previous work in this area has concentrated on the study of power extraction for high bypass ratio engines. This motivates a thorough investigation of the potential and limitations with regards to performance of a low bypass ratio mixed flow turbofan engine. A low bypass ratio mixed flow turbofan engine was modeled, and key parts of a fighter mission were simulated. The investigation shows how power extraction from the high-pressure turbine affects performance of a military engine in different parts of a mission within the flight envelope. An important conclusion from the analysis is that large amounts of power can be extracted from the turbofan engine at high power settings without causing too much penalty on thrust and specific fuel consumption, if specific operating conditions are fulfilled. If the engine is operating (i) at, or near its maximum overall pressure ratio but (ii) further away from its maximum turbine inlet temperature limit, the detrimental effect of power extraction on engine thrust and thrust specific fuel consumption will be limited. On the other hand, if the engine is already operating at its maximum turbine inlet temperature, power extraction from the high-pressure shaft will result in a considerable thrust reduction. The results presented will support the analysis and interpretation of fighter mission optimization and cycle design for future fighter engines aimed for large power extraction. The results are also important with regards to aircraft design, or more specifically, in deciding on the best energy source for power consumers of the aircraft.

Long-Term Trends of P-Band Temporal Decorrelation Over a Tropical Dense Forest-Experimental Results for the BIOMASS Mission

Fostered by the upcoming BIOMASS mission, this article explores long-term trends of P-band temporal decorrelation over a tropical forest due to a time series of 617 days acquired during the TropiScat-2 experiment. The interest in this unique time series is twofold. First, it provides consistent statistics to monitor the yearly evolution of temporal coherences according to specific time scales of the BIOMASS tomographic and interferometric phases. Second, it provides key insights to explore new processing approaches with the combination of data from different orbit directions (ascending/descending) and different mission cycles separated by about seven months according to the current acquisition plan. For the first time, this study shows that 18-day coherences (corresponding to the time interval between the first and last acquisitions of the BIOMASS tomographic processing) can vary significantly according to rainy and dry seasons (medians from 0.3 to 0.9). The extension to time intervals of up to 90 days within both seasons and over two consecutive years puts forward the key role of the typical sporadic rainfalls occurring during dry periods in tropical rainforests, with a stronger impact on temporal coherence evolution compared to the more reproducible rainy seasons. Furthermore, outstanding values significantly above zero have been obtained for the 7- and 14-month coherences (medians of 0.35 and 0.2, respectively), opening the way to new methods of change detection. Overall, this study highlights the role of P-band temporal decorrelation not only as a disturbance factor for coherent applications but also as a relevant indicator of forest changes.

Improving the Fatigue of Newly Designed Mechanical System Subjected to Repeated Impact Loading

This paper develops parametric accelerated life testing (ALT) as a systematic reliability method to produce the reliability quantitative (RQ) specifications—mission cycle—for recognizing missing design defects in mechanical products as applying the accelerated load, expressed as the inverse of stress ratio, R. Parametric ALT is a way to enhance the prediction of fatigue failure for mechanical systems subjected to repeated impact loading. It incorporates: (1) A parametric ALT plan formed on the system BX lifetime, (2) a fatigue failure and design, (3) customized ALTs with design alternatives, and (4) an assessment of whether the last design(s) of the system fulfills the objective BX lifetime. A BX life concept with a generalized life-stress model and a sample size equation are suggested. A domestic refrigerator hinge kit system (HKS), which was a newly designed mechanical product, was used to illustrate the methodology. The HKS was subjected to repeated impact loading resulting in failure of the HKS in the field. To conduct ALTs, a force and momentum balance was utilized on the HKS. A straightforward impact loading of the HKS in closing the refrigerator door was examined. At the first ALT, the housing of the HKS failed. As an action plan, the hinge kit housing was modified by attaching inside supporting ribs to the HKS to provide sufficient mechanical strength against its loading. At the second ALT, the torsional shaft in the HKS made with austenitic ductile iron (18 wt% Ni) failed. The cracked torsional shaft for the 2nd ALTs came from its insufficient rounding, which failed due to repeated stress. As an action plan, to have sufficient material strength for the repetitive impact loads, the torsional shaft was reshaped to give it more rounding from R0.5 mm to R2.0 mm. After these modifications, there were no problems at the third ALT. The lifetime of the HKS in the domestic refrigerator was assured to be B1 life 10 years.

Achieving Robust and Efficient Consensus for Large-Scale Drone Swarm

Achieving consensus is a crucial problem for large scale drone swam to perform collaboration tasks. There are some critical issues for the consensus of large-scale drone swarms, such as limited-time convergence and high robustness against drone failure due to stringent requirements of mission cycle and hostile environment. Note that traditional consensus cannot guarantee limited-time convergence and a robust consensus against node failure. Existing finite-time consensus faces challenges of strict prerequisites and high complexity. Moreover, leaderless and leader-follower consensus adopts different models respectively. Toward these ends, a unified consensus model for both leaderless and leader-follower modes is proposed. It achieves limited-time convergence by using distributed energy minimization. A dynamic spanning tree algorithm is designed to ensure consensus under dynamic topology. Furthermore, a robust method against node failure is proposed by combining grey prediction, average consensus, and Molly-Reed criterion. Simulation results show that the proposed methods can be adopted in both leaderless and leader-follower situations with advantages of limited-time convergence and high robustness.

Sizing of hybrid electric propulsion system for retrofitting a mid-scale aircraft using non-dominated sorting genetic algorithm

The paper presents the sizing of a hybrid electric propulsion system for a prototype aircraft. The main contribution of the paper is to apply multi-objective optimization in the retrofit of a mid-scale aircraft and investigate the fuel economy of the hybrid aircraft for a particular mission cycle. Using the Non-dominated Sorting Genetic Algorithm (NSGA), the fuel consumptions for different flight durations are minimized, which represent the optimal trade-off between fuel consumption and flight duration. With no compromise on endurance and range, the maximum fuel reduction of the retrofitted hybrid aircraft reaches 17.6%, by comparison with the prototype aircraft. The retrofitted aircraft achieves better cruising and climbing performance with the sized hybrid propulsion system. The novelty of the study is the proposal of a new non-dominated sorting algorithm—Benchmark based Non-Dominated Sort (BNDS) for the NSGA. BNDS can reduce the number of comparisons and the time complexity of the non-dominated sorting process. A constraint handling approach is also integrated into the BNDS/NSGA to address performance and mission requirements.

Conceptual Moon imaging micro/nano-satellite design optimization under uncertainty

Low-cost Moon imaging micro/nano-satellites have been receiving much attention from the engineering community. The reliability-based robust design optimization (RBRDO) of these weight/size/power constrained satellites is crucial. In this study, the configuration of this conceptual design problem considering uncertainty is analyzed and the interdisciplinary relations are described. Discipline models including orbit, payload, propulsion, and communication are mainly discussed. A new RBRDO approach to lunar micro/nano-satellite system design is presented, involving dimension reduction, dynamic response surface, system decoupling, and multiobjective alliance search. The optimization goal includes payload cost-effective ratio and satellite mass, and five reliability constraints are considered including satellite installation volume and battery cycles. Through identifying a dominant active subspace for high-dimensional inputs, the in-loop uncertainty quantification is greatly accelerated by about two orders of magnitude. A smooth and uniformly distributed Pareto front is therefore obtained to provide beneficial Pareto-optimal solutions, which indicates that the orbit altitude gathers around 200 km and the mission cycle is nearly 2.4 years. An optimal trade-off design has the minimum satellite mass of 8.95 kg and smaller cost-effective ratio. Compared with the deterministic optimization, the RBRDO approach is preferable for designing Moon imaging micro/nano-satellites of high reliability and robustness.

Key Components of Modular Propulsion Systems for Next Generation Electric Vehicles

The objective of this paper is to provide an overview of emerging technologies for modular power converter architectures for electric vehicles. Nowadays, the most common electrical drive-train architecture exhibits one single inverter which is directly tied to the battery. As a consequence, only one high-voltage battery module can be applied and the dc-link voltage of the inverter and its apparent power rating is directly dependent on the available battery voltage. To overcome this restriction, modern power converter architectures with a higher degree of freedom have been proposed. These architectures exhibit modular dc-dc converters to allow different battery technologies to be linked to drive inverters operating independently from each other. To make this development feasible, new components and technologies are evolving which enhance the efficiency over mission cycles while ensuring further integration of the power-converter architectures. Wide-bandgap power semiconductors enable high switching frequencies and miniaturization of passive devices. Smart topology enhancements and control methods allow a significant loss reduction, in particular at light loads, resulting in a higher efficiency of the drive train over the entire driving cycle. Highly integrated bidirectional battery charger systems with intelligent charging strategies inhibit battery degradation and provide opportunities for grid stabilization. It is demonstrated how these technologies are realized and implemented to contribute to the development of future electric vehicles.

Illumination conditions at the lunar poles: Implications for future exploration

We produced 400 × 400 km Digital Terrain Models (DTMs) of the lunar poles from Lunar Orbiter Laser Altimeter (LOLA) ranging measurements. To achieve consistent, high-resolution DTMs of 20 m/pixel the individual ranging profiles were adjusted to remove small track-to-track offsets. We used these LOLA-DTMs to simulate illumination conditions at surface level for 50 × 50 km regions centered on the poles. Illumination was derived in one-hour increments from 01 January, 2017 to 01 January, 2037 to cover the lunar precessional cycle of 18.6 years and to determine illumination conditions over several future mission cycles. We identified three regions receiving high levels of illumination at each pole, e.g. the equator-facing crater rims of Hinshelwood, Peary and Whipple for the north pole and the rim of Shackleton crater, and two locations on a ridge between Shackleton and de Gerlache crater for the south pole. Their average illumination levels range from 69.5% to 82.9%, with the highest illumination levels found at the north pole on the rim of Whipple crater. A more detailed study was carried out for these sites as targets for a lander and/or rover equipped with solar arrays. For this purpose we assumed a lander with a structural height of two meters above the ground (height of the solar panels). Here average illumination levels range from 77.1% to 88.0%, with the maximum found at the ridge between Shackleton and de Gerlache crater on the south pole. Distances, sizes and slopes of nearby Permanently Shadowed Regions (PSRs) as a prime science target were also assessed in this case.

Decision support in a fieldable laboratory management during an epidemic outbreak of disease

Purpose The purpose of this paper is to analyze the decision-making process and provide a decision support framework for deployment of an on-site analytical capacity (a fieldable laboratory (FL)) to contain an expanding outbreak and protect public health. Design/methodology/approach The FL mission cycle consists of five successive interlinked phases with a set of operational functions (OFs) performed during the mission. The list of phases, OFs and their contents were iteratively developed during and after FL missions and validated with operational partners. Findings The well-defined structure of the FL domain appears as the best functional basis for tracking the decision-making process across the whole mission cycle. Description of all the FL elements and information flows addresses the major issue of interoperability of resources used by similar international capacities (inter-)acting as operational partners in global response to the crisis. Originality/value The work presents the first attempt in this field to systematically describe and chronologically organize the decisions taken by a FL manager and staff during all phases of the FL mission cycle. Definition of OFs with all the related information flows allows for comparison of procedures, their better planning and refining, validation of protocols, mutual training and operational improvement between FLs from different geographical, organizational and cultural origins.

Assessment of Sleep Disruption and Sleep Quality in Naval Special Warfare Operators.

Little is known about sleep in elite military populations who are exposed to higher operational demands, unpredictable training, deployment, and mission cycles. Twenty-nine Naval Special Warfare (NSW) Operators wore an actiwatch for an 8-day/7-night period for objective sleep assessment and completed a nightly sleep log. A total of 170 nights of actigraphically recorded sleep were collected. When comparing objectively versus subjectively recorded sleep parameter data, statistically significant differences were found. Compared with sleep log data, actigraphy data indicate NSW Operators took longer to fall asleep (an average of 25.82 minutes), spent more time awake after sleep onset (an average of 39.55 minutes), and demonstrated poorer sleep efficiency (83.88%) (ps < 0.05). Self-reported sleep quality during the study period was 6.47 (maximum score = 10). No relationships existed between the objectively derived sleep indices and the self-reported measure of sleep quality (rs = -0.29 to 0.09, all ps > 0.05). Strong inter-relationships existed among the subjectively derived sleep indices (e.g., between self-reported sleep quality and sleep efficiency; r = 0.61, p < 0.001). To our knowledge, this is the first study to objectively and subjectively quantify sleep among NSW Operators. These findings suggest sleep maintenance and sleep efficiency are impaired when compared to normative population data.