Space exploration has entered a new era in which success is no longer defined by access to orbit, but by the capacity for humans to live, perform, and thrive in extreme environments. This editorial advances a human-centered framework that integrates physiological resilience, psychological stability, and social adaptability across pre-, in-, and post-mission phases. Drawing on emerging insights in exercise science, behavioral health, artificial intelligence, and interdisciplinary education, it argues that sustainable spaceflight requires coordinated systems rather than isolated interventions. Structured conditioning, real-time adaptive technologies, and comprehensive recovery models are positioned as essential countermeasures to microgravity-induced decline and psychosocial strain. Beyond astronaut health, the piece highlights the broader implications of SPACE studies as a unifying platform for research, education, and outreach, with translational benefits for healthcare, workforce resilience, and global collaboration. Advancing human capability in space is inseparable from improving life on Earth.
The year 2026 marks a noticeable shift in space exploration from access to sustainability, driven by recent advancements such as NASA’s Artemis missions. This introduction synthesizes four critical perspectives including thermophysical data, cryogenic system sustainability, cross-disciplinary integration, and human-centered design highlighted by Drs. Narayanan, Chung, Petersen, and Fu. These works redefine space as an interconnected system where accurate data enables reliable modeling, engineering ensures long-term operation, integration overcomes disciplinary silos, and human capability remains central. This issue positions space not merely as a destination, but as a designed environment requiring coordinated innovation to support continuous operations and human thriving beyond Earth.
In-space servicing, assembly, and manufacturing (ISAM) represents a fundamental shift in how space systems are designed, deployed, operated, sustained, and ultimately retired. ISAM’s success depends on cross-disciplinary integration rather than disciplinary optimization — progress emerges not from isolated expertise, but from disciplines that actively strengthen one another. This article highlights several ISAM-relevant domains, both traditional and emerging, and discusses that a multi-disciplinary framework spanning research, education, policy, and system design is essential to accelerate ISAM and shape the future space paradigm.
Cryogenic propellants such as liquid hydrogen (LH₂), liquid oxygen (LOX), and liquid methane (LCH₄) are critical to high-performance chemical and nuclear propulsion systems. However, their storage, transfer, and utilization in space environments are fundamentally constrained by heat ingress from external environment, phase-change boiloff loss, and complex two-phase flow dynamics under reduced gravity and microgravity. This paper outlines the importance of cryogenic thermal-fluid management (TFM), identifies the governing physical processes, and presents key system elements required for reliable long-duration propellant storage and transfer. Particular emphasis is placed on Zero-Boil-Off (ZBO) technologies, which are essential for enabling in-space refueling, propellant depots, and nuclear thermal propulsion missions.
Future space manufacturing, thermal management, and life-support technologies depend on reliable thermophysical property data. Quantities such as viscosity, surface tension, thermal conductivity, and diffusion coefficients determine the dynamics of fluids, heat transport, and materials processing under extreme extraterrestrial conditions. Terrestrial methods are often compromised by gravity-driven effects, container interactions, and limited access to interfacial or high-temperature data. Microgravity environments provide an avenue to circumvent these obstacles by enabling container-less processing, interfacial studies, and precise transport measurements. Establishing robust data repositories is essential for predictive models, optimized algorithms, and integration with machine learning. The result will be reduced risk, improved efficiency, and rapid progress in both terrestrial and space-based manufacturing.
