Accelerated Processing with Geometry-Specific Pyrolysis Heating Profiles for Production of C-C Hot Structures

The highest-risk processing step in manufacturing C-CAT’s ACC material is the initial carbonization cycle, during which a C/Ph composite preform is carbonized to produce a low-density C/C part to be subsequently densified using a Polymer Infiltration and Pyrolysis (PIP) process. Though the carbonization steps of the PIP densification cycles also present a risk, it is during the initial cycle that the most mass loss, dimensional change, and loss in strengths is experienced by the part, maximizing the potential for the generation of interlaminar stresses which exceed the in-process interlaminar strengths. To mitigate these risks, the current practice is to apply a standard, very conservative heating profile for all parts, with significant implications to lead times, throughput, and location of bottlenecks within the manufacturing process, particularly for production programs. C-CAT currently supports three production programs in the fields of hypersonics and space access: aeroshells for the Lockheed Martin AGM-183a, nozzle extensions for the Aerojet Rocketdyne RL-10C liquid rocket engine (LRE), and nozzle extensions for the Virgin Orbit NewtonFour LRE. All three, as well as potential future programs, could potentially benefit significantly in cost, schedule, and delivery rates with an ability to optimize heating profiles based on part geometry. In recent years, C-CAT has collaborated with Materials Research & Design, Inc. (MR&D) to support MR&D’s development of computational tools designed to predict the behavior of phenolic-derived carbon-carbon (C/C) materials during manufacturing. The current iteration of the model is complete, and has been verified and validated extensively. However, it cannot yet be confidently used in tailoring temperature profiles to part geometry, as too much uncertainty exists in the in-process strengths and other in-process material properties for it to be used without the potential of unintentionally dramatically increasing scrap rates. The effort outlined in this proposal would generate the data necessary to be able to optimize heating profiles to accelerate processing and potentially increase throughput, while also providing a means for estimating and minimizing scrap given the measured processing and material variability.