Search Results (2,327)

Unmanned aerial vehicles (UAVs) are increasingly expected to support both wireless communication and logistics missions, creating a need for integrated operation strategies that jointly manage data collection and physical item handling. This paper investigates a UAV system that simultaneously performs uplink communication with multiple ground nodes (GNs) while completing time-constrained item-pickup tasks. To enhance both throughput and fairness across GNs, we maximize the proportional fair spectral efficiency of GNs while ensuring that all items are collected within the required mission duration under payload and geographical constraints. The resulting formulation constitutes a mixed-integer nonconvex optimization problem involving binary pickup assignments, binary communication scheduling, and trajectory-dependent channel coupling, making direct global optimization intractable. To address this challenge, we develop an iterative convexification framework that integrates the successive convex approximation and the penalty convex–concave procedure within a block coordinate descent structure, enabling efficient joint optimization of trajectory, pickup timing/sequence, and GN scheduling. Simulation results validate that the proposed scheme dynamically shapes the UAV trajectory to improve channel conditions without violating the pickup deadline and compensates disadvantaged GNs through proportional fair scheduling. As a result, it consistently outperforms the baseline strategies under various system parameters. Full article

The expected rise in space operations challenges the European Air Traffic Management (ATM), as traditional static airspace segregation causes operational inefficiencies. To mitigate this, a new function within the European Network Manager Operations Centre (NMOC), supported by the novel Network Real-time Mission Monitoring (N-RMM) tool, and complemented by ad hoc Debris Response Areas (DRAs), are being developed. This paper introduces the safety assessment of this approach using the Expanded Safety Reference Material (E-SRM) methodology. By developing specialised Accident Incident Models (AIMs) for mid-air collisions with space debris, we quantify safety barrier efficiencies and define a Risk Classification Scheme (RCS). The results indicate that by developing dedicated AIMs for the proposed dynamic airspace-management concept, the derived safety criteria, under the stated assumptions, are compatible with the targeted safety thresholds. The potential reduction in segregated airspace volume and duration remains an expected operational benefit to be quantified in subsequent validation work. Full article

Cyanobacterial blooms in lakes and reservoirs pose significant environmental and public health risks. This paper presents an effective exploration strategy to detect them from Autonomous Surface Vehicles (ASVs) equipped with probes, whose sensing trajectories are optimized by an AI-based planner that considers the 3D spatial-temporal evolution of the cyanobacteria concentration obtained by a multiphysics model. The planner, simultaneously working on the AI decision-making and robotic domains, optimizes the surface displacement of the ASV and the depth of its probe by solving a constrained multi-objective optimization problem that minimizes the mission duration and trajectory length, maximizes the possibilities of the probe to overpass areas with high concentration of cyanobacteria, and satisfies operational constraints (such as ASV velocity or acceleration limits, and obstacle avoidance). The optimization is supported by two well-known versions of the Non-Sorted Generic Algorithm (NSGA-II and NSGA-III) and by encoding the trajectories with spline curves whose number of control points can be fixed, progressively increased, or freely manipulated by the algorithm. The performance of different configurations of the planner is tested against six scenarios obtained from different simulations of the multiphysics model (which couples water dynamics and temperature, light transmission, daily vertical migration of the cyanobacteria and their growth). The statistical analysis of the planner results determines that NSGA-III working with variable-length chromosomes and NSGA-II with the progressive increment of spline points as the best configurations for maximizing cyanobacteria detection, and minimizing mission duration and trajectory length. Full article

The rapid expansion of artificial intelligence and cloud computing is straining terrestrial data center infrastructure, motivating exploration of space-based data centers (SBDCs) as a scalable and energy-efficient alternative. While orbital platforms offer unique advantages, including continuous solar energy, radiative cooling, and global coverage, their practical deployment is constrained by unresolved reliability challenges across the mission lifecycle. This study presents a lifecycle-oriented reliability and risk assessment for SBDCs spanning launch, orbital operation, maintenance, and end-of-life phases, using a structured systems-level analysis of failure modes and operational dependencies. This paper focuses on compute-centric SBDC architectures, treating storage solely as a supporting resource. We identify and classify space-environment-specific risks, including launch-induced mechanical stress, radiation-driven degradation, thermal extremes, and single points of failure in power and communication subsystems. By integrating engineering constraints with economic considerations, we develop a unified risk-chain framework that shows how reliability limitations propagate from component design to system cost and operational viability. The analysis reveals a critical trade-off: achieving terrestrial-grade reliability in orbit requires substantial redundancy and radiation hardening, increasing mass and cost and reducing economic feasibility, whereas lower-reliability designs introduce operational and financial risks that challenge sustainability. These findings establish reliability as the central determinant of SBDC viability, providing an applied foundation for fault-tolerant, modular, and lifecycle-aware design strategies essential for transitioning orbital cloud infrastructure from concept to scalable reality. Full article

Unmanned Aircraft Systems (UAS) have seen a significant growth in civilian space over the past decade. The number one ranked challenge in UAS operations in Europe is regulatory obstacles such as the Specific Operations Risk Assessment (SORA) for 2023–2025. Existing approaches have focused on individual technical solutions (radio technologies, redundancy schemes, or cryptographic protections) or on high-level safety analysis, but have not integrated regulatory compliance, risk assessment, and repeatable systems models that directly support SORA artifact generation and rapid adaptation across BVLOS operational contexts. Thus, the current state-of-the-art apparatus lacks a systematic Model-Based Systems Engineering (MBSE) approach that can cater to Command and Control (C2) data-link design for Beyond Visual Line-of-Sight (BVLOS) missions. In this work, we propose an MBSE methodology designed to assist engineers in designing a C2 data link for BVLOS drone operations that complies with SORA regulations in the Netherlands and Europe. To validate the use of MBSE in a wide range of complex drone operations, we demonstrate how subtle modifications in the proposed engineering models can be made without any major overhaul of new SORA applications, and this is validate these changes through laboratory software tests and simulations. Full article

Technical debt (TD) poses a significant systemic risk in aerospace systems engineering, yet existing frameworks inadequately address debt irreversibility at hardware–software integration boundaries. Current detection approaches operate on structured code artifacts rather than the unstructured test and evaluation (T&E) documentation where integration debt often becomes visible. This paper presents the Technical Debt Management Framework (TDMF), a proof-of-concept architecture for identifying, quantifying, and prioritizing TD across the systems engineering lifecycle. The TDMF proposes an integrative architecture combining leading indicator (LI) monitoring with an AI detection module using large language model (LLM) analysis to surface debt indicators within unstructured aerospace documentation. The framework is grounded in a systematic review of 143 publications and illustrated through retrospective application to the Hubble Space Telescope and Mars Climate Orbiter failures, with an Evidence Traceability Matrix bounding historical claims against hindsight bias. An initial pilot evaluation of the ATLAS prototype—conducted on a single-program aerospace T&E documentation using GPT-4 with expert annotation—yielded a preliminary F1 score of 0.82 and an observed 45% reduction in median review time, providing initial evidence of computational feasibility within that scope. The framework is positioned as an early-stage design-science artifact at Technology Readiness Level 2–3. Prospective multi-program validation constitutes the required next study. This work contributes a proof-of-concept management architecture, a documented prompt engineering approach for TD classification, and a structured research agenda for empirical validation for TD classification in mission-critical systems engineering. Full article

As unmanned aerial vehicles (UAVs) are increasingly deployed in mission-critical domains such as military operations, infrastructure inspection, and disaster response, the threat of GPS and network spoofing attacks has emerged as a fundamental challenge to operational continuity. Existing intrusion detection systems based on threshold rules or shallow machine learning models are inherently limited in their ability to identify the latent onset of sophisticated, gradually intensifying spoofing campaigns—a gap that motivates the present work. This study proposes a deep learning-based early detection and network resilience prediction framework that employs Gated Recurrent Unit (GRU) and Long Short-Term Memory (LSTM) architectures operating on three spatio-temporal network features—Hop Count Spike Rate (HCS), Packet Drop Volatility (PDV), and Spatial Disconnect Density (SDD)—proposed in this study. To reflect realistic adversarial conditions, we design a Gradual Adaptive Attacker model in which the spoofing intensity escalates progressively across six operational phases, including a second-stage adaptive attack that modulates its gradient upon detecting initial countermeasures. Both models are trained on 1000 simulated runs using sliding-window time-series sequences and evaluated across 500 independent test runs with paired statistical testing. The GRU model achieves a mean ROC-AUC of 0.9915 (±0.0091) and a mean F1-Score of 0.9099 (±0.0462), outperforming LSTM across all metrics with statistical significance at p < 0.001 under both the paired t-test and the Wilcoxon signed-rank test. Critically, GRU detects spoofing onset with an average latency of 0.503 time steps—approximately 29.4% faster than LSTM (0.712 steps)—a difference confirmed as statistically significant (p < 0.001, Cohen’s d = 0.41). Network resilience simulations further demonstrate that integrating GRU-based autonomous evasion maintains a Connectivity Ratio (CR) above 80% even under severe attack phases, whereas passive networks experience total connectivity collapse (CR = 0%). These findings establish GRU as the superior architecture for real-time UAV edge deployment and affirm that the proposed pipeline extends beyond threat alerting to actively preserving mission continuity under adversarial spoofing conditions. Full article

While drones play important roles in areas such as communication and logistics delivery, they have certain limitations in emergency rescue scenarios due to their inability to carry passengers. Building on mature drone technologies such as autonomous flight and environmental perception, unmanned passenger Electric Vertical Take-off and Landing (eVTOL) aircraft are designed with a manned cabin, enabling them to operate without an onboard pilot while rapidly transporting injured people. Consequently, eVTOLs can play a significant role in emergency rescue that cargo-only drones cannot fulfill, as they are capable of rapidly reaching emergency scenes, effectively overcoming the delays caused by traditional ground traffic congestion. Despite their potential, eVTOLs still face several critical obstacles, including signal disruption, limited coverage of dispatching centers, mutual authentication among entities, and concerns related to security and privacy preservation. As a remedy, this paper presents a lightweight authentication protocol leveraging drone assistance to overcome these challenges for unmanned eVTOL emergency rescue. In scenarios where an unmanned eVTOL experiences signal blockage due to dense urban high-rise structures, neighboring drones can serve as a transmission relay to assist the unmanned eVTOL and the dispatch center (DC) in completing mutual authentication and session key negotiation, thereby enabling the unmanned eVTOL to safely complete its mission. To enhance security, physical unclonable functions (PUFs) are integrated into unmanned eVTOLs, drones, and the DC, safeguarding sensitive data against side-channel and physical capture attacks while preserving the confidentiality of unmanned eVTOL identities to mitigate privacy risks. Our protocol achieves provable security in the random oracle model while exhibiting strong resistance to various well-known attacks. Comparative analysis with the existing drone authentication and drone-assisted emergency rescue authentication protocols reveals that our protocol not only provides stronger security guarantees but also maintains a low computational overhead. Full article

A dusty thermal vacuum chamber (DTVAC) equipped with a regolith simulant bin is a key infrastructure to validate space equipment planned to operate in the future lunar missions. The proper setup of such infrastructure is challenging since the regolith simulant needs to be outgassed; otherwise, it might affect the validation process. This paper presents the results of experiments conducted in a dusty thermal vacuum chamber. The experiment was designed to verify if lunar regolith simulants prepared and placed in the bin may preserve atmospheric gases after the chamber depressurization process. Such hypotheses were defined after testing a drill in vacuum conditions, the performance of which was higher than expected. The obtained results show that the preparation and placement of regolith in the bin should be performed under vacuum conditions regardless of the external temperature. Full article

This paper presents the preliminary implementation of a web-based tool designed to support UAS operators in mission planning and risk assessment in compliance with the SORA 2.5 methodology. The system integrates risk maps for high-fidelity ground risk assessment and risk-aware path planning to identify minimum-risk flight corridors. The tool guides the operator through the evaluation phase of SORA, allowing the assessment of the iGRC, ARC, and SAIL within an intuitive workflow. A representative use case in an urban area of Turin illustrates how the application highlights the distribution of risk in the urban area and supports SORA-compliant decision-making. The results demonstrate the usefulness of the tool in improving risk awareness and supporting mission preparation. Full article

Over the past 50 years, researchers have produced a considerable body of work substantiating that gross domestic product (GDP) is not a measure of social welfare. In response, numerous measures, collectively known as Beyond GDP (BGDP) measures, have been developed to provide a more balanced assessment of the social, environmental, and economic impacts of economic activity on current and future generations. BGDP measures have gained the attention not only of academics, but also of government practitioners concerned with prevailing measures of national and regional progress that overrepresent narrow economic objectives and underrepresent sustainability objectives. Despite this widespread support for alternatives, few governments have made significant progress in implementing BGDP measures to inform public policy. Viewed through an operational lens, this study examines strategies used by two governments that have progressed in implementing BGDP measures. We analyze their strategies against five practical considerations: (1) alignment with mission, (2) fiscal and resources constraints, (3) communication and public messaging challenges, (4) challenges with political and public commitment, and (5) gaps in internal agency knowledge and training. These five considerations were identified as the five most prominent barriers to implementing BGDP measure based on a systematic review of the BGDP literature published over the past 50 years. We conclude that these two governments implemented actions that addressed key elements of these five barriers and succeeded in adopting BGDP measures. We conclude that others could emulate these successes to advance the broader adoption of BGDP measures. Full article

Autonomous underwater vehicles (AUVs) are widely employed in missions conducted near the seabed, including underwater inspection, seabed mapping, and marine resource exploration. During such operating conditions, the interaction between the AUV and the bottom wall can significantly influence the surrounding flow field and the hydrodynamic characteristics of the vehicle. In this study, a numerical investigation is carried out to examine the influence of near-bottom effects on the hydrodynamic performance of an AUV using a commercial Computational Fluid Dynamics (CFD) solver. The seabed is assumed as a flat wall, and two operating conditions are considered, including an open-water case and a near-bottom case with a clearance ratio of h/L_A = 1.93. The flow field is investigated through analyses of hydrodynamic force, pressure distribution, and wake structures. The results indicate that the wall bottom noticeably alters the pressure field and wake development around the AUV, leading to changes in total resistance and flow separation. The findings provide useful insights into the hydrodynamic mechanisms associated with near-bottom operation and offer valuable guidance for the design, control, and operation of AUVs performing missions in shallow or seabed-related missions. Full article

As human space missions become longer and more autonomous, robots are expected to assume broader responsibilities in inspection, maintenance, logistics, scientific support, and crew assistance. Among available robot forms, humanoid robotic astronauts are especially relevant because their anthropomorphic embodiment is compatible with human-centered habitats, tools, interfaces, and procedures. Their deployment in orbital and planetary environments, however, introduces challenges that differ from those of terrestrial humanoids, including floating-base dynamics, intermittent contact, whole-body coordination, constrained perception, and delayed supervision. This review contributes a mission-oriented and astronaut-centered synthesis of humanoid robotic astronauts, distinguishing itself from platform-by-platform or morphology-only surveys. It treats these systems as mission-compatible embodied agents whose feasibility depends on the coupling among mission context, morphology, contact behavior, perception, autonomy, and validation evidence. The primary goals are threefold: to classify representative platforms according to mission context, to synthesize the core technical foundations required for mission-compatible operation, and to identify cross-cutting deployment bottlenecks and benchmarking priorities for future development. Representative systems are organized into intravehicular assistance, extravehicular operations and on-orbit servicing, and surface exploration or transitional scenarios, showing how mission demands shape embodiment, mobility, manipulation, autonomy, and validation strategies. This review further summarizes recent progress in microgravity dynamics and contact mechanics, multimodal perception and scene understanding, whole-body motion planning and control, teleoperation and supervised autonomy, and evaluation and benchmarking methods. The analysis indicates that humanoid robotic astronauts are not simple extensions of terrestrial humanoids but astronaut-oriented embodied systems for mission-constrained environments. Three priorities are identified for future development: contact-rich whole-body intelligence under support transitions, delay-tolerant supervised autonomy with explicit authority handoff, and systematic benchmarking pipelines that connect simulation, ground analogs, short-duration microgravity tests, human-in-the-loop trials, and mission-context demonstrations. Full article

In the context of increasing water scarcity, the new paradigm in efficient water management relies on the digitalisation of water infrastructure to optimise resource use. One of the key factors in addressing the new challenges facing urban water cycle companies is the shortage of qualified technical staff. This context highlights the new training needs of technical personnel required by companies in the urban water cycle sector due to the increasing digitalisation of tools and the new technological requirements of jobs which are not yet sufficiently reflected in the existing training offer. Companies express their dissatisfaction with how poorly existing training programs meet their current needs. Vocational training has a fundamental role to play in providing high-quality, technically up-to-date training that is aligned with the needs of water management companies. This mission involves the adoption of innovative teaching strategies and methods and the development of innovative teaching resources. This paper presents the design of a bench-scale plant specifically designed as a teaching resource at a Spanish vocational training centre that offers intermediate-level training in water networks and treatment plants and advanced-level training in water management. The plant, occupying a footprint of 4 × 5 m, simulates a drinking water distribution network, from the intake to the distribution network via a pumping station with two pumps (1 + 1) of 0.75 kW each that provide a flow range of 4–12 m³/h with a range of 22–10 m water column and a regulating reservoir of 1 m³ located above the water network. The plant is equipped with sensors that allow operational data to be monitored: pressures, flow rates, consumption and levels, enabling multiple operational scenarios to be simulated: leaks, sectorisation, pressure and flow management, etc. Its design has focused on facilitating the acquisition by students of the skills and learning outcomes required in the curricula of the different professional modules that make up the aforementioned studies, through learning based on multidisciplinary collaborative projects. Full article

Mars climatology is a growing interest domain for planetary research and for operational missions. In the last three decades, Martian General Circulation Models have been developed to support the interpretation of spacecraft and telescopic observations and for the advancement of theoretical understanding of the climate. They have been designed to represent key processes, such as dust cycle, seasonal CO₂ condensation, and interaction between boundary layer and surface. At the same time, new observations from orbiters and landers have enhanced the diagnostics, but several uncertainties in the parameterization, especially in dust representation and turbulent mixing, require further improvements. This review represents a synthesis of the state of the art of existing global and regional models, comparing numerical and physical approaches, identifying the main challenges for the next years, with particular attention to the needs of operational missions and machine learning techniques. Full article