Innovations in Thermal Control and Management for Spacecraft

A special issue of Aerospace (ISSN 2226-4310). This special issue belongs to the section "Astronautics & Space Science".

Deadline for manuscript submissions: 30 September 2026 | Viewed by 1633

Editors


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Guest Editor
College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
Interests: space thermal control; phase change materials; spacecraft heat transfer; magnetohydrodynamics; thermal protection systems
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Guest Editor
School of Energy and Environment, Southeast University, Nanjing 210096, China
Interests: spacecraft thermal management; two-phase heat transfer; thermal system design; microgravity thermal phenomena

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Guest Editor
School of Astronautics, Beihang University, Beijing 100191, China
Interests: spacecraft thermal control; advanced heat pipes; space heat transfer; microgravity thermal physics; thermal system modeling and optimization

Special Issue Information

Dear Colleagues,

Effective thermal control is one of the most critical challenges for spacecraft, directly influencing system reliability, mission duration, and onboard equipment performance. With the rapid development of new-generation spacecraft, satellites, deep-space probes, and crewed missions, the demand for advanced thermal control technologies is steadily increasing. Traditional methods such as heat pipes, radiators, and phase change materials are evolving toward higher efficiency, lightweight integration, and adaptability to extreme space environments. Meanwhile, emerging approaches, including magnetohydrodynamic cooling, microchannel-based thermal management, and intelligent thermal regulation, are gaining attention.

This Special Issue aims to gather recent advances and innovations in spacecraft thermal control and management technologies. We welcome contributions covering theoretical models, numerical simulations, ground experiments, flight verifications, and multidisciplinary integration methods. Through this collection, we hope to provide a comprehensive view of the current progress and future perspectives in spacecraft thermal control research, fostering collaboration across academia, industry, and space agencies.

Dr. Guiping Zhu
Prof. Dr. Nan Xiang
Dr. Yi Huang
Guest Editors

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Keywords

  • spacecraft thermal control
  • heat pipes and loop heat pipes
  • phase change materials
  • microgravity heat transfer
  • thermal protection systems
  • two-phase flow and cooling
  • radiative heat transfer in space
  • magnetohydrodynamic thermal management
  • space environment simulation
  • thermal system optimization

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Published Papers (2 papers)

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Research

16 pages, 7767 KB  
Article
Particle Dynamics Study of Microstructural Evolution and Mechanical Response in Magnetorheological Fluids
by Pengfei Xiao, Guofang Mu, Chunping Zhou, Chong Deng, Yuheng Liu, Guiping Zhu and Yi Huang
Aerospace 2026, 13(7), 578; https://doi.org/10.3390/aerospace13070578 - 26 Jun 2026
Viewed by 330
Abstract
Magnetorheological fluids (MRFs) exhibit field-dependent mechanical properties that are governed by the evolution of their internal particle structures. In this work, a particle-dynamics-based numerical method is used to investigate the microstructure formation and shear response of monodisperse and bidisperse MRFs at volume fractions [...] Read more.
Magnetorheological fluids (MRFs) exhibit field-dependent mechanical properties that are governed by the evolution of their internal particle structures. In this work, a particle-dynamics-based numerical method is used to investigate the microstructure formation and shear response of monodisperse and bidisperse MRFs at volume fractions of 22% and 33% under the same magnetic field and carrier-fluid viscosity. A mechanical model based on interparticle interactions is employed to describe particle motion and magnetic-field-induced chain assembly. To quantify the structural evolution during deformation, the average coordination number is introduced as a microstructural descriptor. The results show that bidisperse MRFs exhibit distinct chain formation mechanisms from monodisperse systems, particularly with decreasing particle size ratio and increasing concentration. Under steady shear, both systems display a fluctuating increase in stress, accompanied by structural rupture, migration and reorganization. However, concentration markedly affects the dominant evolution mode, while the incorporation of small particles in bidisperse systems weakens chain integrity, leading to stronger stress fluctuations and generally lower peak stress. These results provide insight into the coupling between microstructure evolution and mechanical response in MRFs. Full article
(This article belongs to the Special Issue Innovations in Thermal Control and Management for Spacecraft)
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22 pages, 2066 KB  
Article
A Two-Stage Framework for Microsatellite Thermal Mode Identification and Fault Detection via Clustering and Sequence Prediction
by Weijian Pang, Jun Zhou, Jingwen Xu and Xinian Zhi
Aerospace 2026, 13(6), 544; https://doi.org/10.3390/aerospace13060544 - 11 Jun 2026
Viewed by 482
Abstract
Microsatellites operate in highly dynamic thermal environments due to severe physical constraints, making temperature telemetry a critical onboard health indicator. Conventional threshold-based monitoring fails to distinguish normal operational mode transitions from genuine faults, causing excessive false alarms. To address this, we propose a [...] Read more.
Microsatellites operate in highly dynamic thermal environments due to severe physical constraints, making temperature telemetry a critical onboard health indicator. Conventional threshold-based monitoring fails to distinguish normal operational mode transitions from genuine faults, causing excessive false alarms. To address this, we propose a two-stage framework integrating unsupervised thermal mode discovery with mode-specific deep learning prediction. Raw temperature telemetry is downsampled and segmented into orbital cycles. Unsupervised clustering identifies two nominal thermal regimes and four canonical fault-type libraries (step, spike, drift, and noise), each corresponding to distinct in-orbit failure mechanisms. For each nominal mode, a Convolutional Neural Network–Long Short-Term Memory (CNN-LSTM) is trained on 7-day historical windows to forecast 3-day temperature evolution. Post-downlink, incoming cycle mode is inferred via nearest-neighbor DTW classification; anomalies are flagged when prediction residuals exceed mode-adaptive thresholds. Validation on Macau Science Satellite-1B (MSS-1B, COSPAR 2023-069-B, NORAD 56732) in-orbit telemetry from a 41° inclination low-Earth orbit—where solar illumination dominates external thermal loading and internal heat from the data-communication module and scientific payload constitutes the primary internal thermal source—shows the method reduces anomaly flags by 96.6% and improves prediction mean absolute error by 51.3% compared to a non-classified global baseline under nominal operating conditions, correctly detecting a known operational transient while suppressing spurious alarms. A synthetic fault injection experiment with four anomaly types and five baseline methods further confirms the framework’s detection capability, achieving an overall F1 score of 0.725 vs. 0.258 for the global baseline—a 2.8× improvement driven primarily by a 4× precision gain. Sensitivity analysis reveals that the two-stage advantage is most pronounced for low-magnitude and short-duration faults, where mode-specific context is essential. This work advances microsatellite autonomous health management by providing reliable anomaly detection with quantified fault detection performance. Full article
(This article belongs to the Special Issue Innovations in Thermal Control and Management for Spacecraft)
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