Mission Requirements Research Articles

Research on an optimization design method for a TBCC propulsion scheme

Abstract An optimization methodology for a TBCC propulsion schemes was established for hypersonic vehicles, focusing on the integration of aircraft and engine performance. Altitude-velocity characteristics of TBCC propulsion were obtained through engine performance calculations. By analyzing mission requirements, lift-drag characteristics, and flight constraints, the take-off thrust-weight ratio and wing load of the vehicle were optimized to meet the flight conditions. In addition, the fuel ratio was calculated. To determine the vehicle’s gross take-off weight and the engine’s take-off thrust, a model considering the weight of the vehicle and the turbine engine were used. The optimization process selects four thermodynamic cycle parameters for the turbine engine as the independent variables. An improved particle swarm optimization-back propagation neural network was used to establish the relationship between the four parameters and the gross take-off weight, aiming to minimize the vehicle’s weight. The results of the optimization process show that the total take-off weight of the optimized vehicle has decreased from 112363.41 kg to 102218.98 kg. The required uninstalled take-off thrust of TBCC has also been reduced from 162.86 kN to 147.49 kN, resulting in a decrease in mass flow from 156.50 kg/s to 133.30 kg/s.

Collaborative Task Allocation and Optimization Solution for Unmanned Aerial Vehicles in Search and Rescue

Earthquakes pose significant risks to national stability, endangering lives and causing substantial economic damage. This study tackles the urgent need for efficient post-earthquake relief in search and rescue (SAR) scenarios by proposing a multi-UAV cooperative rescue task allocation model. With consideration the unique requirements of post-earthquake rescue missions, the model aims to minimize the number of UAVs deployed, reduce rescue costs, and shorten the duration of rescue operations. We propose an innovative hybrid algorithm combining particle swarm optimization (PSO) and grey wolf optimizer (GWO), called the PSOGWO algorithm, to achieve the objectives of the model. This algorithm is enhanced by various strategies, including interval transformation, nonlinear convergence factor, individual update strategy, and dynamic weighting rules. A practical case study illustrates the use of our model and algorithm in reality and validates its effectiveness by comparing it to PSO and GWO. Moreover, a sensitivity analysis on UAV capacity highlights its impact on the overall rescue time and cost. The research results contribute to the advancement of vehicle-routing problem (VRP) models and algorithms for post-earthquake relief in SAR. Furthermore, it provides optimized relief distribution strategies for rescue decision-makers, thereby improving the efficiency and effectiveness of SAR operations.

Mission operations management of a regional coverage highly agile SAR satellite: Few key aspects

The regional coverage satellite constellations are in demand for fulfilling earth observation needs of specific user regions of interest as opposed to global coverage thus enhancing the revisit period for the area. In this paper, we present a few key mission aspects of the regional coverage constellation designed and operated by the Indian Space Research Organization (ISRO) in low earth orbit. ISRO developed three X-Band Synthetic Aperture Radar (SAR) Earth Observation satellites and placed them in three inclined orbit planes to enhance the Indian region's coverage. This is India's first inclined orbit constellation designed for remote sensing applications in low earth orbit. The satellites were built around a standard bus carrying a Synthetic Aperture Radar payload with a deployable Radial Rib Antenna (RRA). They were designed to achieve a high agility capability. As SAR sensors are capable of all-weather, day, and night imaging; thus, most suitable in inclined orbits where the illumination conditions vary continuously for imaging. Though the inclined orbits provide more revisit opportunities to the region of interest, their characteristics pose challenges in mission design and operations. Though the mission design and planning involved a host of elements, this paper brings out the details of a few key mission analysis elements, planning aspects and operations that were critical in the course of various mission phases. The mission analysis included mission-specific requirements like launch windows selection for the constellation and reference attitude generation specific to inclined orbit geometry. Mission planning had to take care of Radial Rib Antenna (RRA) deployment requirements which were very critical for the mission, apart from taking care of individual subsystem requirements. The SAR payload data product quality and targeting accuracy are very sensitive to the satellite image point range (vis-a-vis SAR operation data window). Extensive post-launch calibration activity was carried out to meet all these mission requirements and data product specifications. The challenge was in fixing the payload beam alignment and fixing the uncertainties in onboard and ground computations. The paper also describes the methods of fixing all possible error sources affecting the high-resolution SAR payload performance.

Conceptual design and configurations selection of S/H-UAVs based on Q-rung dual hesitant double layer FQFD

For the conceptual design phase of Unmanned Aerial Vehicles (UAVs), a process for conceptual design and configuration selection of Solar/Hydrogen powered UAVs (S/H-UAVs) is proposed. The design requirements of S/H-UAVs were analyzed firstly. The proposed process used Fuzzy Quality Function Deployment (FQFD) to establish logical and quantitative standards. Moreover, in order to appropriately describe the hesitancy of experts while making decision, it used Q-Rung Dual Hesitant Fuzzy Sets (QRDHFS) to score the correlationships. In addition, a decision-making framework is proposed to perform a logical selection of typical layouts based on defuzzification method and Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS). The present process has been applied for S/H-UAVs. The resulting set of design requirements consists of three categories: Mission Requirements (MRs), Engineering Characteristics (ECs) and Technical Indicators (TIs). Four typical layouts of S/H-UAVs were sorted and determined. The performance of four typical layouts were evaluated and the Strut-Braced Wing (SBW) with external hydrogen storage was selected as the best layout for S/H-UAVs.

Investigating the Applicability of Nested Secret Share for Drone Fleet Photo Storage

Military drones can be used for surveillance or spying on enemies. They, however, can be either destroyed or captured, therefore photos contained inside them can be lost or revealed to the attacker. A possible solution to solve such a problem is to adopt Secret Share (SS) techniques to split photos into several sections/chunks and distribute them among a fleet of drones. The advantages of using such a technique are two folds. Firstly, no single drone contains any photo in its entirety; thus even when a drone is captured, the attacker cannot discover any photos. Secondly, the storage requirements of drones can be simplified, and thus cheaper drones can be produced for such missions. In this scenario, a fleet of drones consists of t+r drones, where t (threshold) is the minimum number of drones required to reconstruct the photos, and r (redundancy) is the maximum number of lost drones the system can tolerate. The optimal configuration of t+r is a formidable task. This configuration is typically rigid and hard to modify in order to fit the requirements of specific missions. In this work, we addressed such an issue and proposed the adoption of a flexible Nested Secret Share (NSS) technique. In our experiments, we compared two of the major SS algorithms (Shamir's schema and the Redundant Residue Number System (RRNS)) with their Two-Level NSS (2NSS) variants to store/retrieve photos. Results showed that Redundant Residue Number System (RRNS) is more suitable for a drone fleet scenario.

3D Galileo Reference Antenna Pattern for Space Service Volume Applications.

There is an increasing demand for navigation capability for space vehicles. The exploitation of the so-called Space Service Volume (SSV), and hence the extension of the Global Navigation Satellite System (GNSS) from terrestrial to space users, is currently considered a fundamental step. Knowledge of the constellation antenna pattern, including the side lobe signals, is the main input for assessing the expected GNSS signal availability and navigation performance, especially for high orbits. The best way to define and share this information with the final GNSS user is still an open question. This paper proposes a novel methodology for the definition of a high-fidelity and easy-to-use statistical model to represent GNSS constellation antenna patterns. The reconstruction procedure, based on antenna characterization techniques and statistical learning, is presented here through its successful implementation for the "Galileo Reference Antenna Pattern (GRAP)" model, which has been proposed as the reference model for the Galileo programme. The GRAP represents the expected Equivalent Isotropic Radiated Power (EIRP) variation for the Galileo FOC satellites, and it is obtained by processing the measurements retrieved during the characterization campaign performed on the Galileo FOC antennas. The mathematical background of the model is analyzed in depth in order to better assess the GRAP with respect to different objectives such as improved resolution, smoothness and proper representation of the antenna pattern statistical distribution. The analysis confirms the enhanced GRAP properties and envisages the possibility of extending the approach to other GNSSs. The discussion is complemented by a preliminary use case characterization of the Galileo performance in SSV. The accessibility, a novel indicator, is defined in order to represent in a quick and compact manner, the expected Galileo SSV quality for different altitudes and target mission requirements. The SSV characterization is performed to demonstrate how simply and effectively the GRAP model can be inserted into user analysis. The work creates the basis for an improved capability for assessing Galileo-based navigation in SSV according to the current knowledge of the antenna pattern.

A Performance Evaluation Approach for Satellite Attitude Control System in Tracking Mode

The study of satellite performance evaluation can reveal the ability of satellite systems to fulfil corresponding tasks in the space environment, and provide information support for the resource allocation and mission scheduling of in-orbit satellites. In this paper, we took the satellite attitude control system in attitude tracking mode as the research object. In accordance with the system’s mission requirements, the control performance evaluation indicator set, characterized by a generalized grey number, is constructed to tackle the uncertainty and inadequacy of information contained in flight status data resulting from the complex space operating environment and sensor measurement noise. An improved principal component analysis method based on generalized grey number is proposed to solve the weight amplification caused by the correlation between performance indicators and realize the weight allocation of the indicators. Finally, the grey-target decision model is established to determine the weights of the performance indicators, and the performance evaluation model is established under the tracking mode. The feasibility of the grey-target decision-evaluation model based on the improved principal component is confirmed through comparative experiments.

Onboard autonomous mission generation method based on user preference

This paper presents a method for autonomous onboard mission generation of Earth observation imaging satellites based on user preferences. The paper develops a planning database to store the previous user mission requirements, and proposes a database updating algorithm to track the changes in user preferences. The paper also proposes a mission generation method based on the planning database, which predicts target priorities and imaging methods. Finally, a mission allocation strategy is used to assign newly generated missions to the appropriate satellites. Simulations results show that the proposed method can effectively improve the utilization of satellite resources and thereby obtain higher mission return.

Dynamic Modeling and Altitude Control for Flying Cars Based on Active Disturbance Rejection Control

Flying cars offer huge advantages due to their deformable structure, which can adapt to external environments and mission requirements. They represent a novel system that can realize vertical takeoff and landing. However, the structure of a flying car is complicated, placing higher requirements on modeling accuracy and control effectiveness. Thus, in this paper, a dynamic model of a flying car is proposed by combining a car body, motor, and propellers. Then, a double-loop controller based on active disturbance rejection control is proposed to accurately control its flight altitude. Utilizing the extended state observer, external wind and other disturbances are regarded as an extended state, which can be dynamically observed and compensated to significantly improve tracking accuracy. The effectiveness of the proposed controller is validated through detailed simulations and flight experiments. The proposed controller significantly improves control accuracy and disturbance rejection capability.

Concept and Feasibility Analysis of the Alba Cubesat Mission

AlbaSat is a 2-Unit CubeSat which is being developed by a student team at the University of Padova. The Alba project aims to design, build, test, launch, and operate the first student CubeSat of the University of Padova, featuring four different payloads. The first goal is to collect data regarding the debris environment in Low Earth Orbit, the second goal is the study of the satellite vibrations, the third one is about CubeSat attitude determination through laser ranging technology, and the fourth goal concerns satellite laser and quantum communication. The Alba CubeSat mission has been selected by the European Space Agency to join the Fly Your Satellite! Design Booster program in December 2022. This paper presents the feasibility study of the Alba CubeSat mission reproduced in the framework of the “Space Systems Laboratory” class of Master of Science in Aerospace Engineering at the University of Padova. In the beginning, a mission requirements definition was conducted. After that, the mission feasibility was considered, with preliminary requirements verification to assess the ability of the spacecraft to survive the space environment, including compliance with Debris Mitigation Guidelines, ground station visibility and minimum operative lifetime evaluation. The Alba mission sets a base for a better understanding of the space environment and its interaction with nanosatellites, and an improvement of the accuracy of debris models. Furthermore, this paper, describing the educational experience and the results achieved, will provide a useful example for future students’ studies on CubeSat mission design.

Analysis and modeling of the aerodynamic ceiling effect on small-scale propellers with tilted angles

Micro air vehicles with propellers have been widely used in military and civilian applications due to their high maneuverability and low cost. As the mission scenarios and requirements of rotorcrafts become more complex, proximity effects caused by confined environments, such as the ceiling effect cause significant interference to the performance and stability of rotors. Most researchers have analyzed this phenomenon by considering the ceiling effect in hover conditions. However, few scholars considered the tilt angle between the rotor and the ceiling, which is more likely to occur in real missions, such as the close inspection of bridges or large equipment, flight in narrow indoor environments, and flight near the ceiling for fully actuated multirotors. In this study, a CFD-based study is conducted to evaluate the ceiling effect for small-scale tilted propellers. The aerodynamic analysis was experimentally evaluated through a series of ground tests in a test bench designed for this research. The CFD results were validated by a mesh-independent study and experimental data comparison. The results show that in contrast to the phenomenon of reduced thrust when tilt angles exist between the rotors and ground, the existence of tilt angles between the propeller and the ceiling reduces the thrust-increasing effect of the ceiling when the dimensionless distance is greater than 0.6. When the distance gets smaller, the thrust-increasing effect increases when the tilt angle is greater than 10∘. In particular, when the distance is less than 0.3, the existence of tilt angles will increase the thrust-increasing effect of the ceiling. Additionally, a data-driven model has been proposed to predict the thrust with the distance to the ceiling and the angle inclination between the rotor and the ceiling. This model enables future rotorcrafts that require accurate models to operate in narrow environments.

The Data Compression Method and FPGA Implementation in the Mars Rover Subsurface-Penetrating Radar on the Tianwen-1 Mission

Since Mars is far away from Earth, the propagation delay between Mars and Earth is very large. To ensure the effective use of the link transmission bandwidth, China’s first Mars exploration mission has put forward a demand for data compression for all scientific payloads. The on-board mature algorithms for data compression are mainly focused on optical images and microwave imaging radar applications. No articles have been published on data compression methods that are applied to subsurface-penetrating radar. Based on the background of this application, this paper proposes a logarithmic lossy compression algorithm which can meet the mission requirements for high compression ratios of 4:1 and 2.5:1. Its compression error is less than that of the block adaptive quantization (BAQ) algorithm. The algorithm is not only easy to implement on field-programmable gate array (FPGA) platforms, but also offers simple ground decompression and fast imaging. The experimental results show that high compression ratios of 4:1 and 2.5:1 can be realized, even if the data in and between traces do not have a strong correlation. And its relative error is less than 2%, which is a new type of high-efficiency data compression method that can be implemented on-board to meet with the demand of subsurface penetrating radar.

End-to-end simulations to optimize imaging spectroscopy mission requirements for seven scientific applications

CNES is currently carrying out a Phase A study to assess the feasibility of a future hyperspectral imaging sensor (10 m spatial resolution) combined with a panchromatic camera (2.5 m spatial resolution). This mission focuses on both high spatial and spectral resolution requirements, as inherited from previous French studies such as HYPEX, HYPXIM, and BIODIVERSITY. To meet user requirements, cost, and instrument compactness constraints, CNES asked the French hyperspectral Mission Advisory Group (MAG), representing a broad French scientific community, to provide recommendations on spectral sampling, particularly in the Short Wave InfraRed (SWIR) for various applications.This paper presents the tests carried out with the aim of defining the optimal spectral sampling and spectral resolution in the SWIR domain for quantitative estimation of physical variables and classification purposes. The targeted applications are geosciences (mineralogy, soil moisture content), forestry (tree species classification, leaf functional traits), coastal and inland waters (bathymetry, water column, bottom classification in shallow water, coastal habitat classification), urban areas (land cover), industrial plumes (aerosols, methane and carbon dioxide), cryosphere (specific surface area, equivalent black carbon concentration), and atmosphere (water vapor, carbon dioxide and aerosols). All the products simulated in this exercise used the same CNES end-to-end processing chain, with realistic instrument parameters, enabling easy comparison between applications. 648 simulations were carried out with different spectral strategies, radiometric calibration performances and signal-to-noise Ratios (SNR): 24 instrument configurations × 25 datasets (22 images + 3 spectral libraries).The results show that spectral sampling up to 20 nm in the SWIR range is sufficient for most applications. However, 10 nm spectral sampling is recommended for applications based on specific absorption bands such as mineralogy, industrial plumes or atmospheric gases. In addition, a slight performance loss is generally observed when radiometric calibration accuracy decreases, with a few exceptions in bathymetry and in the cryosphere for which the observed performance is severely degraded. Finally, most applications can be achieved with a realistic SNR, with the exception of bathymetry, shallow water classification, as well as carbon dioxide and methane estimation, which require the optimistic SNR level tested. On the basis of these results, CNES is currently evaluating the best compromise for designing the future hyperspectral sensor to meet the objectives of priority applications.

Reliability analysis for a generalized sparse connection multi-state consecutive-k-out-of-n linear system

The utilization of binary states is a common practice in reliability analysis. However, in complex systems such as aviation, spaceflight, and watercraft, the prevalence of multi-state systems and units is more pronounced. Consequently, extensive research has been undertaken to explore reliability analysis with a focus on multi-state consecutive-k models across various disciplines. Notably, the concept of sparse connection has received considerable attention due to its relevance in practical applications like wireless communication, cloud computing networks, and oil pipeline systems. This paper aims to propose a generalized multi-state consecutive-k: G system model that incorporates sparse connection. Both the system and the units are allowed to be in one of the (M+1) possible states, wherein the order numbers 0,1,2,…,M indicate the performance measurement of the system or the units, i.e., 0 denotes the worst performance state while M denotes the best performance state. We classify the model into increasing, decreasing and non-monotonic consecutive-k systems corresponding to different mission requirements in practical applications. This paper utilizes the finite Markov chain imbedding (FMCI) method to derive explicit system state distributions for three types of multi-state consecutive-k-out-of-n: G systems. Subsequently, numerical examples are provided to demonstrate the proposed models and the corresponding results.

Fires in the deep: The luminosity distribution of early-time gamma-ray-burst afterglows in light of the Gamow Explorer sensitivity requirements

Gamma-ray bursts (GRBs) are ideal probes of the Universe at high redshift ($z$), pinpointing the locations of the earliest star-forming galaxies and providing bright backlights with simple featureless power-law spectra that can be used to spectrally fingerprint the intergalactic medium and host galaxy during the period of reionization. Future missions such as Gamow Explorer (hereafter )\ are being proposed to unlock this potential by increasing the rate of identification of high-$z$ ($z>5$) GRBs in order to rapidly trigger observations from $6-10$ m ground telescopes, the James Webb Space Telescope (JWST), and the upcoming Extremely Large Telescopes (ELTs). was proposed to the NASA 2021 Medium-Class Explorer (MIDEX) program as a fast-slewing satellite featuring a wide-field lobster-eye X-ray telescope (LEXT) to detect and localize GRBs with arcminute accuracy, and a narrow-field multi-channel photo-$z$ infrared telescope (PIRT) to measure their photometric redshifts for $>80<!PCT!>$ of the LEXT detections using the Lyman-alpha dropout technique. We use a large sample of observed GRB afterglows to derive the PIRT sensitivity requirement. We compiled a complete sample of GRB optical--near-infrared (optical--NIR) afterglows from 2008 to 2021, adding a total of 66 new afterglows to our earlier sample, including all known high-$z$ GRB afterglows. This sample is expanded with over 2837 unpublished data points for 40 of these GRBs. We performed full light-curve and spectral-energy-distribution analyses of these afterglows to derive their true luminosity at very early times. We compared the high-$z$ sample to the comparison sample at lower redshifts. For all the light curves, where possible, we determined the brightness at the time of the initial finding chart of at different high redshifts and in different NIR bands. This was validated using a theoretical approach to predicting the afterglow brightness. We then followed the evolution of the luminosity to predict requirements for ground- and space-based follow-up. Finally, we discuss the potential biases between known GRB afterglow samples and those to be detected by We find that the luminosity distribution of high-$z$ GRB afterglows is comparable to those at lower redshift, and we therefore are able to use the afterglows of lower-$z$ GRBs as proxies for those at high $z$. We find that a PIRT sensitivity of $15\ (21 mag AB) in a 500 s exposure simultaneously in five NIR bands within 1000s of the GRB trigger will meet the mission requirements. Depending on the $z$ and NIR band, we find that between 75<!PCT!> and 85<!PCT!> of all afterglows at $z>5$ will be recovered by at $5 detection significance, allowing the determination of a robust photo-$z$. As a check for possible observational biases and selection effects, we compared the results with those obtained through population-synthesis models, and find them to be consistent. and other high-$z$ GRB missions will be capable of using a relatively modest 0.3m onboard NIR photo-$z$ telescope to rapidly identify and report high-$z$ GRBs for further follow-up by larger facilities, opening a new window onto the era of reionization and the high-redshift Universe.

FloripaSat-2: An Open-Source Platform for CubeSats

This paper presents the FloripaSat-2 platform, an open-source service platform already on its second version, including, but not limited to, On-Board Data Handling (OBDH), Telemetry, Tracking and Command (TTC), and Electrical Power System (EPS) modules. The platform is conceived to be general-purpose, i.e., easily adaptable for missions with different payloads and requirements. In this context, an overview of the generic nanosatellite architecture, along with the ongoing missions in which it is being employed, is discussed, including the embedded systems, functionalities, and components. Also, the relevant source code is available in an online repository and can be used and expanded to different kinds of CubeSat missions. Finally, good practices regarding the development and a FlatSat proposal for faster testing of the subsystems are presented to aid engineers in testing and adapting the systems to their mission requirements.

Enhancement of multirotor UAV conceptual design through Machine Learning algorithms

Designing an efficient and optimized multirotor UAV requires laborious trade-off analyses, involving numerous design variables and mission requirement parameters, especially during the early conceptual design phase. The large number of unknown parameters, as well as the associated design effort often leads to non-optimal designs, for the sake of time efficiency. This work presents the implementation of a machine learning (ML) framework to assist and expedite the conceptual design phase of multirotor UAVs. The framework utilizes information from a comprehensive database of commercial lightweight multirotor UAVs. The database contains an extensive collection of crucial sizing parameters, performance metrics, and features associated with foldability and indoor guidance (e.g., obstacle avoidance sensors). These attributes specifically pertain to multirotor UAVs weighing less than 2kg, which exhibit diverse design and performance characteristics. The proposed ML framework employs multiple regression models (e.g. k-nearest neighbors regression, multi-layer perceptron regression) to predict the sizing parameters during a multirotor UAV’s conceptual design phase. This enables designers to make quick informed decisions, while also significantly reducing computational time and effort. Finally, the ML framework’s predictive capability is validated by comparing the predicted values with real-world data from an “unseen” test dataset.

Detail and structural design of a fixed-wing BWB UAV

The current study focuses on the development of a prototype BWB UAV for highway traffic monitoring by supporting a Cooperative Intelligent Transport System (C-ITS). This system allows the monitoring of traffic conditions at large roads and highways. Having determined the mission requirements and concluded the aerodynamic conceptual and preliminary design phases, high fidelity CFD simulations are performed, aiming to calculate the key aerodynamic and stability characteristics of the platform and to optimize its performance throughout the mission. More specifically, regarding the aerodynamic vehicle design, results concerning the calculation of stability derivatives, control surfaces sizing, trim analysis and flight envelope (V-n diagram) are presented, along with the respective methodologies. Considering the structural design of the aircraft, a combination of layout, FE simulations and parameterized design tools were employed, allowing the design and sizing of the skin and the internal structural parts. The parts are mainly made of composite and additively manufactured nylon materials. Coupled interaction loops are conducted among the aerodynamic and structural analyses to optimize the overall performance of the aerial vehicle, maximizing the aerodynamic efficiency, and reducing the structural weight. Finally, the study is concluded by the presentation of the manufactured prototype of the UAV, which satisfies all the structural, aerodynamic, stability and performance requirements for the established highway traffic monitoring mission.

3D printing in aerospace and defense: A review of technological breakthroughs and applications

The integration of 3D printing technology in the aerospace and defense sectors has heralded a paradigm shift in manufacturing processes, design capabilities, and operational efficiency. This review explores the transformative impact of 3D printing on these industries, focusing on breakthroughs and applications that have reshaped traditional methodologies. Technological advancements in additive manufacturing have facilitated the production of complex geometries and intricate components that were once deemed impractical or impossible. Aerospace engineers and defense manufacturers are now leveraging 3D printing to create lightweight, high-strength structures, optimizing the balance between performance and fuel efficiency. This has led to enhanced aircraft design and functionality, as well as the development of unmanned aerial vehicles with unprecedented capabilities. Moreover, the ability to rapidly prototype and iterate designs has significantly reduced the time-to-market for new aerospace and defense systems. The review delves into case studies showcasing how 3D printing has streamlined the development process, enabling quicker adaptation to evolving threats and technological advancements. In the defense sector, the customization potential of 3D printing has revolutionized the production of weapons and equipment. Tailoring components to specific mission requirements enhances the effectiveness of military operations while reducing costs associated with mass production. The review also highlights the role of 3D printing in the development of advanced sensors, communication devices, and protective gear for defense personnel. However, challenges such as material limitations, standardization, and certification processes persist. The review provides insights into ongoing research and development efforts addressing these challenges, aiming to further unlock the full potential of 3D printing in aerospace and defense. This review offers a comprehensive overview of the current state of 3D printing in aerospace and defense, emphasizing its transformative impact on manufacturing, design, and operational capabilities. As the technology continues to evolve, its integration is poised to shape the future landscape of these critical industries.

A framework for the design of fault-tolerant systems-of-systems

Context:Systems-of-Systems (SoS) increasingly permeate everyday life in various critical domains. Due to their dynamic nature, guaranteeing their fault tolerance is challenging. Fault-tolerant SoS must deal with behavioral changes in constituent systems, whether accidental or deliberate. Goal:This work proposes ReViTA, a framework to assist professionals in designing fault-tolerant SoS that can continue to provide their function even in the presence of disturbances, i.e., events that affect the ability of an SoS to fulfill its mission. Methods:By adopting ReViTA, fault tolerance can be achieved by reconfiguring an SoS architecture to meet the critical mission requirements. Results:We performed two studies to evaluate the ReViTA acceptance by professionals. In the former, we gathered perceptions and suggestions from 14 professionals through individual interviews. In the latter, we involved a group of four professionals who applied ReViTA to a real-world scenario. Conclusion:The results demonstrate that ReViTA can effectively support professionals in designing fault-tolerant SoS. Employing ReViTA also brings insights into costs and planning that are crucial for implementing fault-tolerance strategies. Using ReViTA facilitates a comprehensive understanding of conflicts and weaknesses in constituent systems and fosters collaboration between domain experts and decision-makers. Employing ReViTA also improves stakeholder communication and enhances resource utilization.