An LJDRNN-based efficient energy intensity prediction in carbon fiber composite material manufacturing process

An LJDRNN-based efficient energy intensity prediction in carbon fiber composite material manufacturing process

Carbon Fibers (CFs) are usually derived from a polyacrylonitrile precursor during composite fiber production. Due to high-temperature needs, the CF composite manufacturing process is considerably energy-consuming and costly. Hence, energy intensity prediction is required. Energy intensity is predict...

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Bibliographic Details
Main Authors: Rangaswamy Nikhil, Karthikeyan A G, Prabhu Loganathan, Tabrej Khan, Tamer A Sebaey
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:Materials Research Express
Subjects:
carbon fiber composite material
limit jordan deep recurrent neural network (LJDRNN)
linear interpolated honey badger optimization (LIHBO)
energy intensity
manufacturing process
Online Access:https://doi.org/10.1088/2053-1591/ada732
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https://doi.org/10.1088/2053-1591/ada732

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