Maya Heat Transfer Technologies Ltd.

Published purpose

Maya HTT proposes an innovative machine learning technique that will provide more reliable thermal simulation models for investigating spacecraft operational scenarios and allow for the creation of a database of optical property changes that occur with exposure to the space environment. This innovation will improve the correlation of thermal model predictions with spacecraft in-flight temperatures. The technique will build on data from computer thermal simulation models, developed during spacecraft development to predict on-orbit temperatures, which are used to ensure that the spacecraft components will operate within an acceptable temperature range during all phases of the mission. Using in-flight data from telemetry to determine changes to the optical properties of the external surfaces with machine learning algorithms will enhance the accuracy of the future predictions and provide more reliable simulation models.