Developing computational models to predict remnant lifetime in composites for space applications

In the low Earth orbit (LEO) environment, advanced composite materials have been considered as innovative alternatives to metal materials because of their desirable high strength-to-weight ratio and excellent thermal properties. However, the LEO environment is a harsh one and exposure to atomic oxygen (AO) is a constant threat to polymeric materials because the highly reactive oxygen atoms react with the polymer's surface, eroding the materials by forming volatile oxides which are removed from the surface.

The wider application of composite materials in space is limited. The cost of deploying materials in space is high and the ability to predict their lifetime in LEO is limited. Therefore, there is a growing demand to develop computational models that help predict the remnant lifetime of composites in LEO as this is an important step towards understanding currently used materials and developing the next generation of replacements.

This project aims to develop a series of computational models that predict the remnant lifetime of composite materials that are designed for space applications. Initial work will focus on the use of the Monte Carlo model, which predicts the surface roughness and erosion depth after defined periods of AO exposure. Kapton H samples will initially be used since they have well-known properties and their degradation in LEO is well understood. This study will aid the development of a reliable predictive model that can be used to predict AO erosion for other types of polymer materials.

Initially, the LEO environment will be simulated using a radio-frequency (RF) plasma chamber facility to generate energetic oxygen ions to erode the surfaces of samples. The RF plasma chamber replicates LEO erosion yield well, but is less effective in reproducing the surface effects observed in composites after LEO exposure. Therefore, it will be important to understand the nature of the plasma produced and mass spectrometry will determine the degree of oxygen dissociation and plasma emission spectra.

Atomic force microscopy (AFM) and laser profiling techniques will be used to determine the surface roughness before and after AO exposure, and these data will be used as input data for the Monte Carlo simulation, while the surface roughness after exposure will be compared with simulation results. Spectral analysis (e.g. optical photothermal infrared, OPT-IR, spectroscopy) will be used to ascertain the chemical nature of the species on the surface of the laminates before and after exposure to determine the mechanisms of degradation.


The Monte Carlo model can predict the effects of AO erosion on materials, potentially reducing the need for costly and time-consuming space flight experiments. In the later stages of the project, the integrated predictive models will be able to predict the sample's mechanical and thermal properties after AO exposure.

The study highlights differences between ground-based plasma asher tests and actual LEO conditions, particularly in surface roughness development. These findings can lead to improvements in ground-based testing methodologies. However, the method is material agnostic and might be applied more widely to other composites in equally demanding exposure environments.

With reliable Monte Carlo model development, the physical parameters can be modified to represent other types of polymer materials, expanding its applicability to a broader range of space materials.

Comparison of simulation with experimental results reveals that while a plasma asher can simulate mass loss similar to LEO conditions, it may not accurately replicate surface roughness changes, highlighting a need for improved ground-based testing methods.

The research combines materials science, plasma physics, space engineering, and computational modelling, demonstrating a novel interdisciplinary approach to studying space environment effects on materials.