VOYCE-M1 (Voice-Oriented Yielding and Communication Experiment – Mars Mission 1) is an interplanetary technology demonstration satellite intended to validate autonomous, voice-based communication from Mars-distance environments under realistic deep-space constraints. The mission is centered on the concept of “voice as data,” treating human speech not merely as an audio signal but as a structured, time-delayed communication artifact that can be processed, prioritized, and transmitted autonomously across interplanetary distances. Operating at Earth–Mars ranges, VOYCE-M1 addresses key challenges including extreme signal latency, limited bandwidth, intermittent ground contact, and strict power availability. The spacecraft incorporates an AI-enabled communication system that performs onboard voice encoding, compression, noise filtering, and content management prior to store-and-forward transmission to Earth. This architecture allows voice messages to be generated, curated, and transmitted without continuous ground control, reflecting future human–robot interaction scenarios around Mars. The transmitted voice content may include predefined human messages, autonomous system-generated narration, or mission-status audio summaries, demonstrating both cultural and operational use cases of voice in deep space. In addition to voice transmission, VOYCE-M1 supports context imaging and symbolic messaging experiments to enhance mission validation and outreach. The mission is designed for operational resilience, enabling meaningful voice and data demonstrations during interplanetary cruise and Mars-proximal operations. VOYCE-M1 serves as a precursor to future Mars communication infrastructure, offering critical insights into AI-assisted autonomy, low-power interplanetary communications, and the role of human-centric voice interaction in sustained planetary exploration. This paper outlines mission and operational planning, technical overview, mass budget, payload systems, and satellite infrastructure.

Sea-based rocket launches have become a critical capability in aerospace engineering due to their operational flexibility and expanded safety zones. However, the interaction between high-temperature supersonic exhaust and the ocean surface poses severe challenges to the structural integrity of launch platforms. Unlike land-based launches, the marine environment presents a deformable boundary with complex phase-change dynamics. This study employs the Volume of Fluid (VOF) method coupled with the k-ω SST turbulence model to conduct a comprehensive numerical investigation of these multiphase interactions. Distinct from classical internal combustion instabilities, this research reveals an external "shock–vortex–thermal" coupling mechanism formed among exhaust shockwaves, shear layer vortices, and seawater vaporization. Simulation results demonstrate that under low launch altitude conditions, rapid expansion of high-pressure steam significantly alters the shock structure, generating strong reverse jets that impose extreme thermal and mechanical loads on the platform foundation. Based on flow field topological evolution patterns, critical safety boundaries are identified. Below this altitude threshold, coupled effects trigger hazardous splashing and pressure feedback; above it, interactions effectively decouple. The parametric analysis further reveals how varying launch altitudes influence the evolution of key flow features including shock standoff distance, steam plume geometry, and pressure distribution on the platform surface. These findings provide theoretical guidance for optimizing initial launch altitude to mitigate adverse jet effects, thereby ensuring structural safety and operational stability of offshore launch platforms.

This paper introduces a computationally efficient mission planning framework tailored for the Ludi Tance-4A (LT-4A), the world's first operational GEO SAR satellite. The LT-4A's unique figure-8 ground track and large-scale imaging capabilities present complex scheduling challenges. Conventional planning methods often rely on fixed maneuver durations, leading to inefficiencies due to the satellite's evolving orbital geometry.

To address this, we propose an Orbital-Window-Aware Hybrid Genetic Algorithm (OW-HGA) integrated with an adaptive maneuver time calculation method. The approach utilizes a two-phase optimization strategy. An offline preprocessing phase exploits geosynchronous periodicity to identify "Optimal Imaging Windows" (OIWs) and dynamically calculates maneuver times based on real-time attitude adjustments. This converts a complex continuous search into a discrete set of opportunities. Subsequently, an online Genetic Algorithm determines the optimal sequence for these OIWs using rapid database lookups rather than time-consuming orbital calculations.

A case study focusing on the Yangtze River Basin validates the proposed method. Comparative results demonstrate a 19.6% reduction in total mission time against greedy algorithms and a 42% reduction in solution variance compared to standard genetic algorithms. Most notably, the framework achieves a 17-fold improvement in computational efficiency. These findings confirm the algorithm’s suitability for real-time mission planning and dynamic replanning for next-generation space-based observation systems.

Despite advances in space medicine, astronauts currently lack tools to comprehensively monitor their health in microgravity. This study aimed to demonstrate the potential of multimodal monitoring technologies to track physiological changes in space. The AURORA-HFSM experiment investigates headward fluid shifts and cerebrovascular dynamics during short-term weightlessness.

Healthy volunteers underwent multimodal monitoring during a parabolic flight campaign on the Airbus A310 Zero-G. Measurements integrated ultrasound (US), near-infrared spectroscopy (NIRS), indocyanine green (ICG) impedance tracking, and inertial measurement units (IMU) for motion synchronization. Signals were recorded continuously during each parabola (~22 s microgravity) across three gravity phases: 1.8 g pull-up (baseline), 0 g microgravity, and 1 g recovery. Each flight included 31 parabolas in three blocks, with short intermissions, providing ~11 minutes of cumulative 0 g exposure. This protocol enabled characterization of venous and arterial flow, tissue oxygenation, and thoracic fluid redistribution.

The study will provide the first synchronized multimodal dataset quantifying jugular, cerebral, and thoracic fluid dynamics during parabolic flight. Correlations between US, NIRS, and ICG indices will inform ESA research on intracranial fluid redistribution and guide the design of compact astronaut health-monitoring systems for long-duration missions.

AURORA demonstrates a feasible, safe, and operationally robust platform for multimodal physiological monitoring in microgravity. Medically certified components, low-voltage operation, mechanical robustness, and redundant data acquisition ensure ESA compliance and minimal residual risk. Expected outcomes include novel integrated biomarkers of cerebral hemodynamics, improved diagnostic accuracy, and enhanced monitoring for spaceflight and clinical applications, establishing AURORA as a translational platform bridging space physiology and astronaut health monitoring.

Biomimetics has become an increasingly important approach in aerospace engineering, offering innovative design solutions inspired by the flight mechanisms of living organisms. Birds, insects, and bats demonstrate exceptional aerodynamic efficiency, maneuverability, and adaptability, which have motivated the development of bio-inspired aircraft and unmanned aerial vehicles (UAVs). This systematic review aims to synthesize and critically evaluate existing research on biomimetic principles derived from biological flight and their application to aircraft and UAV design. A systematic literature review was conducted following PRISMA guidelines, using major scientific databases to identify relevant peer-reviewed studies linking biological flight mechanisms with aerospace engineering applications. The selected studies were categorized according to biological sources of inspiration, including avian wing morphology and feather-based flow control, insect flapping-wing aerodynamics for micro-air vehicles, and bat-inspired flexible membrane wings. The results show that biomimetic approaches can significantly enhance aerodynamic performance, improve maneuverability, increase flight stability, and reduce energy consumption, particularly in UAV and small-scale aircraft applications. Despite these advantages, several challenges persist, such as material constraints, structural complexity, and difficulties in scaling biological mechanisms to full-size aircraft. This review highlights current trends and research gaps in biomimetic aerospace design and emphasizes the potential of biologically inspired flight principles to support the development of next-generation, efficient, and sustainable aircraft and UAV technologies.