Drilling-induced damage and thermal–mechanical response of graphene nanoplatelet–modified CFRP composites under high-speed conditions

High-speed drilling of carbon fiber reinforced polymer (CFRP) laminates often faces challenges which compromise structural integrity. The novelty of this research lies in combining experimental investigation, statistical modeling, global sensitivity analysis, and evolutionary optimization to simultaneously evaluate different output results. Drilling experiments were conducted to investigate the effects of spindle speed, feed rate, tool diameter, and graphene nanoplatelet content on machining responses. The incorporation of 0.25 wt% graphene nanoplatelets improved thermal conductivity and heat dissipation during drilling, which contributed to reducing machining-induced damage. Response surface methodology was employed to develop predictive models, and the developed models showed statistically significant relationships (p < 0.05). Sobol sensitivity analysis was performed to quantify the relative influence of drilling parameters on each response. The results indicated that feed rate was the most influential parameter affecting thrust force (36.1%), peel-up delamination (62.4%), while spindle speed was the most influential parameter on push-down delamination (55.4%). In contrast, drilling temperature was primarily governed by spindle speed, contributing approximately 65.0% to its variation. Multi-Objective Particle Swarm Optimization (MOPSO) was subsequently applied to determine optimal combinations that simultaneously minimize all the results. Experimental validation under optimized conditions demonstrated good agreement with model predictions by 1.3% to 14.8% deviation. The findings demonstrate that graphene nanoplatelet reinforcement combined with data-driven multi-objective optimization significantly improves the machinability of CFRP laminates and reduces drilling-induced damage, providing a practical framework for enhancing hole quality and process reliability in industrial machining of advanced composite structures, particularly in aerospace and high-performance engineering applications.

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Publication Details

Journal
Journal of Composite Materials
Published
2026-04-11
DOI
https://doi.org/10.1177/00219983261442038
Primary Topic
Advanced machining processes and optimization
Type
article
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article

Drilling-induced damage and thermal–mechanical response of graphene nanoplatelet–modified CFRP composites under high-speed conditions

Mohammad Baraheni, Majid Takallu Bighash, Vahid Tahmasbi
Journal of Composite Materials
Advanced machining processes and optimization
article

Drilling-induced damage and thermal–mechanical response of graphene nanoplatelet–modified CFRP composites under high-speed conditions

Mohammad Baraheni, Majid Takallu Bighash, Vahid Tahmasbi
article en

Abstract

High-speed drilling of carbon fiber reinforced polymer (CFRP) laminates often faces challenges which compromise structural integrity. The novelty of this research lies in combining experimental investigation, statistical modeling, global sensitivity analysis, and evolutionary optimization to simultaneously evaluate different output results. Drilling experiments were conducted to investigate the effects of spindle speed, feed rate, tool diameter, and graphene nanoplatelet content on machining responses. The incorporation of 0.25 wt% graphene nanoplatelets improved thermal conductivity and heat dissipation during drilling, which contributed to reducing machining-induced damage. Response surface methodology was employed to develop predictive models, and the developed models showed statistically significant relationships (p < 0.05). Sobol sensitivity analysis was performed to quantify the relative influence of drilling parameters on each response. The results indicated that feed rate was the most influential parameter affecting thrust force (36.1%), peel-up delamination (62.4%), while spindle speed was the most influential parameter on push-down delamination (55.4%). In contrast, drilling temperature was primarily governed by spindle speed, contributing approximately 65.0% to its variation. Multi-Objective Particle Swarm Optimization (MOPSO) was subsequently applied to determine optimal combinations that simultaneously minimize all the results. Experimental validation under optimized conditions demonstrated good agreement with model predictions by 1.3% to 14.8% deviation. The findings demonstrate that graphene nanoplatelet reinforcement combined with data-driven multi-objective optimization significantly improves the machinability of CFRP laminates and reduces drilling-induced damage, providing a practical framework for enhancing hole quality and process reliability in industrial machining of advanced composite structures, particularly in aerospace and high-performance engineering applications.

Journal of Composite Materials
Arak University of Technology (IR)
Openalex Percentile: Top 18%
Advanced machining processes and optimization
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