Spacecraft Thermal Design Research Articles

Application and optimization of residual connection neural network in spacecraft thermal design

In thermal analysis modeling, the finite element method (FEM) is commonly used; however, it incurs high computational costs and complicates the global optimization of thermal parameters. To address these challenges, developing simplified surrogate models is crucial for enhancing analysis efficiency. Yet, constructing such models demands exceptional predictive accuracy, making conventional parameter adjustment methods inadequate for design needs. This paper introduces a novel Residual connection Neural Network model, called Res-NN, designed to approximate the CMOS finite element model. By employing residual connections, the Res-NN model significantly reduces fitting errors between networks, achieving a predictive accuracy of 94.6 %, which is 6.6 % higher than that of comparable Multi-Layer Perceptron (MLP) models. Moreover, Res-NN is over 100 times faster than traditional FEM in prediction speed, effectively circumventing the difficulties associated with parameter adjustments. To optimize the temperature fluctuations of the CMOS model, we utilized the Res-NN model as an iterative object within an optimization algorithm. Through experimental comparisons, we identified the PSO algorithm as the most effective option. The PSO optimization results demonstrated a chip temperature difference of 0.045 °C, with a simulation error of only 0.0649 °C, meeting design specifications and achieving a 61.7 % reduction in temperature variance compared to traditional thermal design method. This validates the superiority of the entire optimization process.

Efficient Uncertainty Analysis of External Heat Flux of Solar Radiation with External Heat Flux Expansion for Spacecraft Thermal Design

Designing spacecraft involves a careful equilibrium to avoid overengineering or underdesigning, which underscores the importance of employing thermal uncertainty analysis. A key part of this analysis is modeling thermal conditions, but this is often a computationally heavy process. This is largely because ray-tracing calculations require determining the external heat flux of solar radiation across different operating conditions. Ray emission varies across conditions, which can lead to inefficient resource use in uncertainty calculations. Our study aims to address this by introducing a new approach to calculating the external heat flux of solar radiation that is better suited for uncertainty analysis than previous approaches. Our formula only requires ray tracing to be performed for one condition rather than for every condition. The other conditions are handled by simple matrix budgeting, negating the need for complicated ray tracing. In the aforementioned analytical procedure, certain matrices demonstrate sparsity properties. By exploiting this characteristic, optimization computations can be executed by utilizing sparse matrix algorithms. We tested this new formula, which we call the external heat flux expansion (EHFE) formula, on a specific spacecraft and compared the results with those obtained using the traditional method. Our findings suggest that the EHFE formula is ideal for calculating uncertainty. It significantly improves computational efficiency while maintaining accuracy. The formula is also user-adjustable, allowing the accuracy of uncertainty calculation results of the external heat flux of solar radiation to be fine-tuned by changing the value of the cutoff factor. This work establishes an essential theoretical framework pivotal to addressing inherent uncertainties in the thermal design of upcoming deep-space exploration spacecraft, solar observatory satellites, and space solar power stations.

Theoretical analysis on thermal grease dry-out degradation in space environment

Silicone thermal grease can reduce the contact thermal resistance of thermal interfaces and has been widely used as a thermal interface material in the thermal design of spacecraft. Silicone thermal grease gradually degrades owing to the dry-out of silicone oil during a long service period and breaks the validity of the thermal interface and induces thermal overload in a spacecraft. In this study, a mechanism-based prediction method for the silicone thermal grease loss in a space environment is proposed. The prediction of long-term thermal grease loss is realised by evaluating the variation in its effective thermal conductivity. In the prediction method, an improved multi-component thermal conductivity model was established to determine the thermal conductivity of thermal grease with multiple filler sizes and a high filler volume fraction. Then, the silicone oil loss induced by complex penetration, crawl, and volatilisation were evaluated with an equivalent capillary model and a volatilisation model. The behaviour of the silicone oil loss, the primary cause of dry-out degradation, was clarified. The variation in the effective thermal conductivity of thermal grease under different contact angles, operating temperatures, and connection surface dimensions was investigated. The results show that the dominant factor gradually changes from capillary loss to volatilisation loss during dry-out degradation. The effective thermal conductivity decreased faster at higher operating temperatures, and the effective thermal conductivity decreased slower with an increase in the contact angle and connection interface dimensions. The present work provides insights for the design of silicone thermal greases for space utilization.

Static and dynamic characteristics of post-buckling of porous functionally graded pipes under thermal shock

The study of thermal post-buckling characteristics of functionally graded pipelines is of great significance for promoting the application of functionally graded materials in spacecraft thermal protection design and marine pipelines. In this study, the static buckling of functionally graded pipes with porosity and the pseudo-linear vibration near the first buckling position of post-buckling are studied. Based on the modified power-law distribution, it is assumed that the material properties of porous FGM pipes change continuously and smoothly along the radial direction. For porosity, it generally occurs in the manufacturing process of functionally graded materials, so the classical Voigt model is selected to describe the material properties of functionally graded material pipelines with pores. Based on Hamilton principle, the nonlinear control equations and corresponding boundary conditions of the pipeline are derived. Firstly, the Routh-Hurwitz criterion is used to discuss the influence of temperature and porosity volume fraction on the critical flow velocity of instability, and then the post-buckling structure of the pipeline and the dynamic characteristics of post-buckling are discussed. The numerical results discussed the influence of important parameters such as power law index, porosity volume fraction and temperature on the buckling and post-buckling behaviors of the system.

About the application of simplified mathematical models complex at the initial stage of the interplanetary spacecraft thermal design

About the application of simplified mathematical models complex at the initial stage of the interplanetary spacecraft thermal design

Intelligent sensitivity analysis framework based on machine learning for spacecraft thermal design

The variance-based method of global sensitivity analysis (GSA) has been widely applied in spacecraft thermal design, which is typically calculated using Monte Carlo estimations. However, such estimations require a large number of samples to ensure sufficient accuracy, which makes GSA expensive to perform when modeling is difficult. Moreover, multimodal or highly skewed output distributions may result in the use of variance as an uncertain agent that generates contradictory results. Therefore, an intelligent density-based GSA framework based on machine learning and multi-fidelity metamodels called IDGSA-3M is proposed. An intelligent batch processing system based on a real-time data interaction between MATLAB and NX/TMG was designed that uses many cheap low-fidelity sample points to reduce the cost of model evaluation while using a small number of expensive high-fidelity sample points to maintain high accuracy, thus achieving trade-offs between high accuracy and low computational cost. A radial basis function (RBF) neural network based on an improved mind evolutionary algorithm was applied to approximate the multi-fidelity metamodel of a spacecraft thermophysical model calculated using a batch processing system, which had a computational speed that was 1000+ times faster than that of the traditional thermophysical model and a high computational accuracy of 99%+. The output distributions of the RBF were then characterized by its cumulative distribution functions to obtain density-based sensitivity indices. Both the theoretical and experimental results of GSA for the thermal design parameters of the extreme ultraviolet radiation detector on the space-based Lyman-Alpha Solar Telescope, developed in China, demonstrated that the convergence rate of IDGSA-3M can be improved up to 10-fold for a fixed convergence level in comparison with two other GSA methods, thereby verifying its superiority.

Establishment and Practical Results Report of the Spacecraft Thermal-Design Hands-on Training Program for General Public

Establishment and Practical Results Report of the Spacecraft Thermal-Design Hands-on Training Program for General Public

Research on High Temperature Protection Technology of Infrared Temperature Measuring Equipment in Space Environment

With the increasing complexity of spacecraft structure and thermal design, it is more difficult to implement surface temperature measurement technology, and the temperature measurement area tends to diverse. Therefore, there is an increasing demand for the application of non-contact temperature measurement technology in spacecraft thermal test. This paper takes the application of infrared temperature measuring equipment in vacuum and high temperature environment as the research object, designs the thermal protection scheme and device of the equipment, and simulates and analyses the thermal protection of infrared temperature measuring equipment based on node network method. Through physical test, the device can effectively realize the thermal protection of equipment in vacuum and high temperature environment, and ensure that the equipment is in the normal working temperature range and its temperature measurement algorithm model is not affected, the accuracy of temperature measurement is better than ±2°C, which meets the use requirements in spacecraft thermal test.

Intelligent Optimization Strategy Based on Statistical Machine Learning for Spacecraft Thermal Design

The thermal design of spacecraft becomes increasingly complicated as various advanced technologies are continuously introduced to the spacecraft. Determining and optimizing the uncertainties of a spacecraft thermal control system through global sensitivity analysis has long been an essential task for thermal engineers. It is a difficult task that relies heavily on engineering experience and is a time-intensive, trial-and-error endeavor that may not even lead to global optimization. Hence, an intelligent optimization strategy based on statistical machine learning for spacecraft thermal design, called IOSML, is proposed. An intelligent batch processing system (IBPS) based on MATLAB, Python, and NX/TMG real-time data interaction is designed. The IBPS uses a surrogate model to reduce the computational cost of global sensitivity analysis while using a detailed thermal mathematical model to maintain accuracy. We combine a Bayesian inference framework with a neural network surrogate spacecraft-thermophysical model that is 100× faster than numerical solvers. This article first reports on a density-based global sensitivity analysis that evaluates the effect of design parameters on the temperature difference between the complementary metal- oxide-semiconductor and cold screen of the Lehman Alpha Solar Space Telescope detector. From 42 design parameters, the most sensitive four are selected for optimization, and the temperature difference and the boundary temperature are used as the objective function. Adopting IOSML, under no supervision, four design parameters are optimized through the IBPS, and the effectiveness of the algorithm is verified by comparison with traditional methods. Additionally, IOSML is versatile and can be used in various complex engineering applications to provide guidance for the better selection of appropriate parameters and optimization.

Uncertainty calculation for spacecraft thermal models using a generalized SEA method

Uncertainty calculation in spacecraft thermal control and design is generally performed using two methods: Statistical Error Analysis (SEA) and Monte Carlo Simulation (MCS). These two methods present differences both in accuracy and in time of execution. Both features are compared in this paper, and the sources of possible divergence between their results are identified. Having these sources of divergence in mind, a new methodology has been developed. In it, temperature uncertainty is obtained as a linear combination of the probability density functions including non-linear effects due to independent variation of each parameter. In order to compare the new method with the previous ones, all three have been applied to a practical case: the EPD-STEP particle detector onboard ESA's Solar Orbiter mission. In this example this new method is proved to be comparable to SEA in terms of computing time and to MCS in terms of accuracy.

Thermal analysis of space debris for infrared-based active debris removal

In space, visual-based relative navigation systems suffer from dynamic illumination conditions of the target (eclipse conditions, solar glare, etc.) where most of these issues are addressed by advanced mission planning techniques. However, such planning would not be always feasible or even if it is, it would not be straightforward for active debris removal missions. On the other hand, using an infrared-based system would overcome this problem, if a guideline to predict infrared signature of space debris based on the target thermal profile could be provided for algorithm design and testing. Spacecraft thermal design is unique to every platform. This means every active debris removal target will have a different infrared signature, which changes over time not just only due to orbital dynamics but also due to its thermal surface coatings. In order to provide a space debris infrared signature guideline for most of the possible active debris removal targets, we introduce an innovative grouping system for thermal surface coatings based on their behaviour in space environment. Through the use of this grouping system, we propose a space debris infrared signature estimation method, which was extensively verified by our simulations and experiments. During our verifications, we have also discovered very important problem so-called ‘signature ambiguity’ that is unique to infrared-based active debris removal systems, which we have also discussed in our work.

Thermal Design of Spacecraft and Thermophysical Properties

Thermal Design of Spacecraft and Thermophysical Properties

G1900103 定常加熱を受ける部材結合部の接触熱抵抗に関する研究

A spacecraft thermal design is performed to satisfy severe demands for allowable temperature and thermal deformations in the spacecraft. The key to the effective thermal design is to build accurate thermal mathematical model for the spacecraft, which can predict temperature variations of the spacecraft on orbit. One of the difficulties in building the accurate model is to identify the characteristics of the thermal contact resistance in joints. In this study, we experimentally study the influence of the contact shapes and the contact pressures in joints on contact thermal resistance of the combination region. We contact two members at each tips under contact loads. We set four different shape types and conduct thermal tests with various contact loads to examine the characteristics of the contact thermal resistance in the different contact conditions. The experimental results indicate that the contact thermal resistance tends to reduce in accordance with the increase of the contact load.

Analysis of Orbital Thermal Environment for Inclined-LEO Small Satellite

Spacecraft thermal design is a process of energy management in which environmental heating plays a major role. This paper is aimed at modeling and analysis of the orbital thermal environment by considering the external heat radiation, for the inclined-LEO cubed satellite with 3-axis stabilized (to Earth state).The result indicates that the analytical model simplifies the analysis of orbital thermal environment and the absolute value of angle on inclined orbit can vary from 0 to a maximum which equals to the sum of orbit inclination and the maximum declination of the sun. Finally, for the inclined-LEO small satellite, the extreme thermal case should fully take account of the point of.

Degradation of thermal control materials under a simulated radiative space environment

A spacecraft with a passive thermal control system utilizes various thermal control materials to maintain temperatures within safe operating limits. Materials used for spacecraft applications are exposed to harsh space environments such as ultraviolet (UV) and particle (electron, proton) irradiation and atomic oxygen (AO), undergo physical damage and thermal degradation, which must be considered for spacecraft thermal design optimization and cost effectiveness. This paper describes the effect of synergistic radiation on some of the important thermal control materials to verify the assumptions of beginning-of-life (BOL) and end-of-life (EOL) properties. Studies on the degradation in the optical properties (solar absorptance and infrared emittance) of some important thermal control materials exposed to simulated radiative geostationary space environment are discussed. The current studies are purely related to the influence of radiation on the degradation of the materials; other environmental aspects (e.g., thermal cycling) are not discussed. The thermal control materials investigated herein include different kind of second-surface mirrors, white anodizing, white paints, black paints, multilayer insulation materials, varnish coated aluminized polyimide, germanium coated polyimide, polyether ether ketone (PEEK) and poly tetra fluoro ethylene (PTFE). For this purpose, a test in the constant vacuum was performed reproducing a three year radiative space environment exposure, including ultraviolet and charged particle effects on North/South panels of a geostationary three-axis stabilized spacecraft. Reflectance spectra were measured in situ in the solar range (250–2500nm) and the corresponding solar absorptance values were calculated. The test methodology and the degradations of the materials are discussed. The most important degradations among the low solar absorptance materials were found in the white paints whereas the rigid optical solar reflectors remained quite stable. Among the high solar absorptance elements, as such the change in the solar absorptance was very low, in particular the germanium coated polyimide was found highly stable.

Advanced Conductive Composite Materials for Spacecraft Application

In this study, thermal responses of advanced fiber/epoxy matrix composite materials are considered for spacecraft thermal design. These thermal responses are important, because the localized thermal behavior from applied heat loads can induce thermal stresses, which can lead to functional failure of the spacecraft system. Since most of polymer matrices exhibit relatively poor thermal conductivity, the composite materials have been widely considered only for structural application and little for thermal application. However, recently pitch-based high performance carbon fiber becomes available and this fiber shows high thermal conductivity. Because of this combination of low CTE and high thermal conductivity, continuous carbon fiber composites make them suitable for thermal management of spacecraft. The advanced composite material is composed of a continuous high modulus pitch based fiber (YS90A) and DGEBA epoxy resin(RS3232). It was demonstrated that advanced composite material satisfied thermal requirement for a lightweight thermal radiator for heat rejection of communication satellite.

Thermal diffusivity measurement of BMS 10-102 thermal insulation material in a vacuum condition using a cyclic heating method

With the many different types of spacecraft missions, insulation techniques are required to advance spacecraft thermal design. In order to create a reliable thermal design system, it is essential to characterize materials and basic properties accurately. In this paper, the cyclic heating method is used to measure the thermal diffusivity for a high-temperature porous material as an insulation material for a spacecraft. To verify this method, the thermal diffusivities of alumina (Al 2O 3) and polystyrene foam were measured at 47.5 °C (320.5 K) and 25.3 °C (298.3 K), respectively, in atmospheric conditions. The thermal diffusivity of the porous insulation material (BMS 10-102) was found to be 2.53 × 10 −7 m 2/s at room temperature under atmospheric conditions. The thermal diffusivity of this porous insulation material was 8.88 × 10 −8 m 2/s at room temperature under vacuum condition. The thermal diffusivities of porous insulation material under vacuum were reduced by 64.9% compared to the thermal diffusivities under the atmospheric condition. This difference is considered to be an effect of air in holes.

Spacecraft thermal design with the Generalized Extremal Optimization Algorithm

This article describes an application of the Generalized Extremal Optimization (GEO) algorithm to the inverse design of a spacecraft thermal control system. GEO is a recently proposed global search meta-heuristic (Sousa, F.L. and Ramos, F.M., 2002, Function optimization using extremal dynamics. In: Proceedings of the 4th International Conference on Inverse Problems in Engineering (cd-rom), Rio de Janeiro, Brazil.; Sousa, F.L., Ramos, F.M., Paglione, P. and Girardi, R.M., 2003, New stochastic algorithm for design optimization. AIAA Journal, 41(9), 1808–1818.; Sousa, F.L., Ramos, F.M., Galski, R.L. and Muraoka, I., 2005, Chapter III. In: L.N. De Castro and F.J. Von Zuben (Eds) Generalized Extremal Optimization: A New Meta-heuristic Inspired by a Model of Natural Evolution, Accepted for publication in Recent Developments in Biologically Inspired Computing (Hershey, PA: Idea Group Inc.).) based on a model of natural evolution (Bak, P. and Sneppen, K., 1993, Punctuated equilibrium and criticality in a simple model of evolution. Physical Review Letters, 71(24), 4083–4086), and specially devised to be used in complex optimization problems (Sousa, F.L., Vlassov, V. and Ramos, F.M., 2002, Heat pipe design through generalized extremal optimization. In: Proceedings of the IX Brazilian Congress of Engineering and Thermal Sciences – ENCIT 2002, Caxambu, MG, Brazil.). GEO is easy to implement, has only one free parameter to adjust, does not make use of derivatives and can be applied to constrained or unconstrained problems, and to non-convex or even disjoint design spaces with any combination of continuous, discrete, or integer variables. The application reported here concerns the optimum design of a simplified configuration of the Brazilian Multi-mission Platform (in Portuguese, Plataforma Multi-missão, PMM) thermal control subsystem, comprising five radiators and one battery heater. The PMM is a multi-purpose space platform to be used in different types of missions such as Earth observation, scientific, or meteorological data collecting. The design procedure is tackled as a multiobjective optimization problem, considering two critical cases, operational hot case (HC) and cold case (CC). The results indicate the existence of non-intuitive, new and more efficient design solutions.

Stochastic Spacecraft Thermal Design Optimization with Low Computational Cost

Covers advancements in spacecraft and tactical and strategic missile systems, including subsystem design and application, mission design and analysis, materials and structures, developments in space sciences, space processing and manufacturing, space operations, and applications of space technologies to other fields.

Thermophysical Properties of High-Thermal-Conductivity Graphite Sheets for Spacecraft Thermal Design

Thermophysical properties of a new material-a graphite sheet, which has characteristics of high thermal conductivity, anisotropy, lightweight and flexibility-have been measured in order to apply this sheet to a spacecraft thermal control material. The following measurements were performed: 1) The thermal diffusivities in the in-plane and out-of-plane directions were measured over the temperature range from 100 to 350 K using a laser heating ac calorimetric method. 2) The specific heat and the total hemispherical emittance were measured over the temperature range from 173 to 375 K using a transient calorimetric method. 3) The solar absorptance was measured using a spectroscopic method for angles of incidence ranging from 5 to 60 deg. Additionally, the thermal conductivities and the specific thermal conductivities were calculated using the measured results, and the high potential of this graphite sheet as a material for spacecraft thermal control was confirmed.