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Applied Sciences
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Advances in Carbon Fiber Reinforced Plastics
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Advances in Carbon Fiber Reinforced Plastics

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Materials Science and Engineering".

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 3215

Special Issue Editors

Prof. Dr. Fuji Wang

E-Mail Website
Guest Editor
School of Mechanical Engineering, Dalian University of Technology, Dalian 116024, China
Interests: high-performance metal additive manufacturing; composite additive manufacturing; material–structure–function integrated manufacturing; space additive manufacturing
Special Issues, Collections and Topics in MDPI journals
Dr. Rao Fu

E-Mail Website
Guest Editor
Key Laboratory of High-Performance Manufacturing for Advanced Composite Materials, Liaoning Province, School of Mechanical Engineering, Dalian University of Technology, Dalian 116024, China
Interests: CFRP machining; CFRP and metal stack machining

Special Issue Information

Dear Colleagues,

Carbon-fiber-reinforced plastic composites (CFRPs) feature extraordinary mechanical and physical properties, such as high specific strength, high specific modulus, corrosion resistance, etc. They have thus been widely employed as key components in the aerospace, transportation, and energy industries to pursue weight reduction and performance enhancement in high-end equipment. High-performance manufacturing and assembly of these CFRP components are primarily needed to meet the requirements of high bearing capacity, extremely complex and harsh environments, as well as long service life. However, the special material compositions and structural characteristics of CFRPs have made them hard to form, hard to cut, and hard to join. Defects frequently occur in their forming (such as curing, molding, 3D printing, etc.), machining (drilling, milling, turning, etc.), and joining (mechanical connection, bonding connection, welding connection, etc.) processes, which are the challenging issues in both academic and industrial fields.

Topics covered by this Special Issue include, but are not limited to, the following:

  • Curing control method and technology for CFRPs and their stack;
  • 3D printing trajectory planning and defect control technology for CFRPs;
  • 3D printing performance prediction for CFRPs;
  • Mechanical-thermal behavior of machining CFRPs and their stack;
  • Low-defect cutting tool and processing method for CFRPs and their stack;
  • Mechanical-thermal behavior of direct-heat joining of CFRPs and their stack;
  • Joining performance prediction of CFRPs and their stack.

Prof. Dr. Fuji Wang
Dr. Rao Fu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • carbon-fiber-reinforced plastics composites (CFRPs)
  • forming
  • machining
  • joining
  • CFRP stack
  • mechanical-thermal behavior
  • performance prediction
  • defect

Published Papers (2 papers)

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Research

14 pages, 8288 KiB  
Article
Off-Axis Tension Behaviour of Unidirectional PEEK/AS4 Thermoplastic Composites
by Yifan Ma, Yazhi Li and Lu Liu
Appl. Sci. 2023, 13(6), 3476; https://doi.org/10.3390/app13063476 - 09 Mar 2023
Cited by 3 | Viewed by 1654
Abstract
An experimental method for non-standard off-axis tension tests of unidirectional composites is developed. A new oblique end-tab is designed to eliminate stress concentration and in-plane bending moment induced by off-axis tension loading. Finite element analysis and experiments on Polyetheretherketone (PEEK)/AS4 unidirectional thermoplastic composites [...] Read more.
An experimental method for non-standard off-axis tension tests of unidirectional composites is developed. A new oblique end-tab is designed to eliminate stress concentration and in-plane bending moment induced by off-axis tension loading. Finite element analysis and experiments on Polyetheretherketone (PEEK)/AS4 unidirectional thermoplastic composites (CFRTP) were conducted to evaluate the effectiveness of the proposed testing method. Simulation and test results demonstrate that the use of oblique end-tabs eradicates stress concentration and bending movements. The digital image correlation (DIC) method was used to help investigate the full-field tension/shear coupling deformation response of the off-axis specimen. Test results show significant nonlinear behaviour and inhomogeneous strain distribution under tension/shear combined stresses. A fractographic study was carried out to study the damage mechanisms under a tension/shear combined stress state. Specimens with 30°, 45° and 60° off-axis angles, fail in tension/shear mixed failure mode. Fracture surface morphology indicates that matrix plastic deformation and ductile drawing under tension/shear coupled stress state induced the nonlinear stress-strain response. Full article
(This article belongs to the Special Issue Advances in Carbon Fiber Reinforced Plastics)
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12 pages, 3107 KiB  
Article
In-Process Tool Condition Forecasting of Drilling CFRP/Ti Stacks Based on ResNet and LSTM Network
by Zhenxi Jiang, Fuji Wang, Debiao Zeng, Shaowei Zhu and Rao Fu
Appl. Sci. 2023, 13(3), 1881; https://doi.org/10.3390/app13031881 - 01 Feb 2023
Cited by 3 | Viewed by 1216
Abstract
Tool condition forecasting (TCF) is a key technology for continuous drilling of CFRP/Ti stacks, as the tool wear is always rapid and severe, which may further induce unexpected drilling quality issues. However, for drilling CFRP/Ti stacks, the cutting spindle power and vibration signals [...] Read more.
Tool condition forecasting (TCF) is a key technology for continuous drilling of CFRP/Ti stacks, as the tool wear is always rapid and severe, which may further induce unexpected drilling quality issues. However, for drilling CFRP/Ti stacks, the cutting spindle power and vibration signals change are complex, influenced by many factors due to the different materials properties. The TCF for drilling CFRP/Ti stacks remains challenging, as the sensitive features are difficult to extract, which decide the accuracy and robustness. Aiming to monitor and forecast tool wear of drilling CFRP/Ti stacks, an in-process TCF method based on residual neural network (ResNet) and long short-term memory (LSTM) network has been proposed in this paper. Using the cutting spindle power and vibration signals preprocessed by the proposed method, the LSTM network with the ResNet-based model integrated can forecast tool-wear values of the next drilling holes. A case study demonstrated the effectiveness of TCF, where the results using raw measured signals and preprocessed datasets are tested for comparison. The mean absolute error (MAE) using raw signals is 45.01 μm, which is 2.20 times bigger than that using preprocess signals. With the proposed method, the data preprocessing for drilling CFRP/Ti stacks can improve the tool-wear forecasting accuracy to MAE 20.43μm level, which meets the demand for online TCF. Full article
(This article belongs to the Special Issue Advances in Carbon Fiber Reinforced Plastics)
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