Micro-to-meso scale high temperature response of ablative systems for atmospheric reentry

Foster, Collin W.

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https://hdl.handle.net/2142/127158 Copy

Description

Title

Micro-to-meso scale high temperature response of ablative systems for atmospheric reentry

Author(s)

Foster, Collin W.

Issue Date

2024-11-25

Director of Research (if dissertation) or Advisor (if thesis)

Panerai, Francesco

Doctoral Committee Chair(s)

Panerai, Francesco

Committee Member(s)

• Roberts, Scott A
• Stephani, Kelly
• Elliot, Gregory S
• Geubelle, Philippe

Department of Study

Aerospace Engineering

Discipline

Aerospace Engineering

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• Phenolic resin
• Pyrolysis
• X-ray Micro-computed tomography
• Material modeling
• Charring ablator

Abstract

Understanding the ablative response of thermal protection systems (TPS) in hypersonic environments is critical for both space exploration and national defense. Ablation begins with pyrolysis, and a critical mechanism to insulating the spacecraft that originates from the decomposition of the phenolic resin, the matrix phase for many contemporary ablative composite systems. How the micro-scale morphology evolves during pyrolysis can have direct implications on the TPS's ability to withstand the combined chemical, mechanical, and thermal loads. As such, this work aims to develop methodologies and tools to resolve the microstructural behavior of phenolic resin and other ablative systems during pyrolysis with a variety of ground-testing methods. An established tool for extracting these relevant geometries at sub-micron resolution from the 3-D anisotropic materials is X-ray micro-computed tomography (μ-CT). High thermal loading must be captured in situ μ-CT in order to accurately characterize material response for both the resin phase and full TPS with synchrotron radiation. This examination includes tracking the growth of porous networks, volumetric changes, and the development of open and closed porosities as the phenolic resin was heated to 1000°C with a lamp-furnace system. The ability to observe these changes closer-to-real-time under controlled conditions provides unprecedented insight into the material's performance and degradation mechanisms. Subsequent chapters extend this in situ methodology to other TPS materials, such as room temperature vulcanizing (RTV) silicone and super-light ablators (SLA). For RTV, significant differences in porosity formation and morphology were revealed under various heating rates, highlighting the material's response to thermal stress. In the case of SLA, machine learning techniques, particularly generative adversarial networks (GAN), were employed to enhance the resolution and segmentation of low-resolution μ-CT scans. This approach not only improved the quality of the data but also allowed for a more detailed analysis of the material's microstructural changes during pyrolysis. Also examined was the morphological evolution of phenolic resin under more relevant combined thermomechanical loading. The mechanical integrity of phenolic resin leading up to peak pyrolysis (400°C) was observed on the micro-scale with in situ μ-CT, recording the decrease in strength as temperature caused the previously observed porous networks to populate. Next, isolated phenolic resin and Phenolic Impregnated Carbon Ablator's (PICA) response was recorded under more representative heat flux conditions with the Plasmatron-X (inductively coupled plasma torch) and the Solar Furnace (radiative solar). In the Plasmatron-X, samples were subjected to heat fluxes ranging from 20 to 160 W/cm² in both nitrogen and air environments, while the Solar Furnace tests exposed samples to complimentary radiative heat fluxes between 20 and 50 W/cm². The resulting data, included optical emission spectroscopy, surface pyrometry, infrared imaging, SEM, Raman spectroscopy, and μ-CT offered comprehensive insights into the materials' performance under extreme conditions and draws connections between the microstructural evolution and the mode of heating. Together with multi-scale physics models and high-performance clusters, tomographic data enables numerical predictions on emerging TPS technologies. Of particular interest to high-fidelity predictions is resolving the individual fibers on the micro-scale, and the intertwined tows and resin phase of the meso-scale. Resolution of these regions of interest with μ-CT can be matched with relevant experimental property data on the micro-scale to infer predictions on scaled systems of similar materials. The large quantities data captured were segmented using state-of-the-art convolutional neural networks, and volumetrically meshed for multi-physics simulations and evaluated for effective properties. This strategy was employed for developing improved analytical geometries from the real μ-CT. By understanding the microstructural behavior of these materials, they can be optimized their properties for specific applications, ensuring greater reliability and safety in both space missions and terrestrial applications.

Graduation Semester

2024-12

Type of Resource

Thesis

Handle URL

https://hdl.handle.net/2142/127158

Copyright and License Information

Copyright 2024 Collin Foster

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