Advancements in satellite technologies are increasing the power density of electronics and payloads. When the power consumption increases within a limited volume, waste heat generation also increases and this necessitates a proper and efficient thermal management system. Mostly, micro and nanosatellites use passive thermal control methods because of the low cost, no additional power requirement, ease of implementation, and better thermal performance. Passive methods lack the ability to meet certain thermal requirements on larger and smaller satellite platforms.
This study explores the capability of Thermal Desktop to map temperatures from a thermal model to a Nastran model to evalautate thermal stress and distortion
A study of the mechanical systems contributing to the design and performance of a picosatellite’s mission in low-Earth orbit (LEO) was performed through design and analysis. The unique architecture of this satellite stems from a form factor established by the internationally recognized CubeSat Program. This CubeSat-Plus architecture limits the satellite’s size to be no larger than a 10 x 10 x 15 cm cube with an overall mass not exceeding 2 kg.
This paper provides an overview of the non-grey radiation modeling capabilities of Cullimore and Ring’s Thermal Desktop® Version 4.8 SindaWorks software. The non-grey radiation analysis theory implemented by Sindaworks and the methodology used by the software are outlined.
This paper summarizes the thermal math model correlation effort for the Fast Affordable Science and Technology SATellite (FASTSAT-HSV01), which was designed, built and tested by NASA's Marshall Space Flight Center (MSFC) and multiple partners. The satellite launched in November 2010 on a Minotaur IV rocket from the Kodiak Launch Complex in Kodiak, Alaska. It carried three Earth science experiments and two technology demonstrations into a low Earth circular orbit with an inclination of 72° and an altitude of 650 kilometers.
This paper describes readily available techniques for automating the search for worst-case (e.g., “hot case”, “cold case”) design scenarios using only modest computational resources. These methods not only streamline a repetitive yet crucial task, they usually produce better results.
The problems with prior approaches are summarized, then the improvements are demonstrated via a simplified example that is analyzed using various approaches. Finally, areas for further automation are outlined, including attacking the entire design problem at a higher-level.
Modeling to predict the condition of cryogenic propellants in an upper stage of a launch vehicle is necessary for mission planning and successful execution. Traditionally, this effort was performed using custom, in-house proprietary codes, limiting accessibility and application. Phenomena responsible for influencing the thermodynamic state of the propellant have been characterized as distinct events whose sequence defines a mission. These events include thermal stratification, passive thermal control roll (rotation), slosh, and engine firing.