Effect of drilling process parameters on bearing strength of glass fiber/aluminum mesh reinforced epoxy composites

In this study, neat glass (NG) fiber and hybrid GF/Al‐wire mesh composites with two different aluminum configurations (AG: with Al in the outer surface, and GA [Glass fiber/Al‐mesh]: with Al in the core) were fabricated using hand‐layup technique and then drilled via an abrasive water jet (AWJ) machine. The impact of the drilling parameters on the hole qualities; delamination , kerf angle (), and circularity error () of the holes were studied. Using Taguchi L9 orthogonal array, drilling operations were conducted. The following AWJ drilling parameters were chosen; water pressure (P), stand‐off distance (S), and traverse speed (V) with three levels each. A single‐objective optimization using Taguchi method was performed to minimize the drilling responses for the least outcome. In addition, gray relational analysis (GRA) was used as a multi‐decision technique. Analysis of variance (ANOVA) was carried out to identify the impacts of AWJ drilling parameters. The results indicated that for AG specimen, was reduced by 5.3%–10.96% and its by 10.4%–29.65%. GA had the lowest kerf angle. The most effective parameters on delamination for NG, AG, and GA were P, followed by S and V. Validation tests showed small variations between experimental and predicted values.Highlights A new GF/Al Wire Mesh Reinforced Epoxy Hybrid Composites were manufactured. AWJ drilling of the manufactured Composites was conducted. Hole quality was improved by adding Al to the outer layers (AG specimen). AWJ parameters were Controlled and optimized to reduce , , and . Process optimization was performed by single and multi‐objective optimization.

Section: Resultsmentioning

confidence: 99%

Section: Confirmation Tests and Confidence Intervals For Responsesmentioning

confidence: 99%

mentioning

confidence: 99%

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Hole quality evaluation for abrasive water jet drilling of GF/Al mesh reinforced epoxy hybrid composites

Seif,

Fathy,

Megahed

2023

“…2 In real-world scenarios, the pattern of stress variation is frequently irregular and difficult to predict, as observed in the case of stresses induced by vibrations. Seif et al 3 investigated the drilling effects on the bearing strength of a composite material comprised of epoxy reinforced with glass and aluminum mesh. They specifically analyzed how delamination influences the bearing strength of the specimen.…”

Section: Introductionmentioning

confidence: 99%

“…The model accurately captured the evolution of damage in woven glass-epoxy composite laminates under various fatigue loadings, as demonstrated by its ability to predict the fatigue life of the composites. Researchers utilized a variety of techniques, including, that is, Taghuchi, 3,21 ANOVA, 22 neural network, 23,24 Weibull 25,26 to optimize geometric and material parameters. Among all the techniques, the Weibull distribution function has established itself as a valuable and adaptable tool for evaluating the dependability of composite structures and describing their material properties.…”

Section: Introductionmentioning

confidence: 99%

Effect of nano‐silica on fatigue behavior of glass fiber‐reinforced epoxy composite laminates: A Weibull distribution approach

Gupta,

Singh,

Saini

2023

The aim of this study is to assess the impact of nano‐silica in glass fiber‐reinforced epoxy composite (GFEC) subjected to static and fatigue loading. Laminates were prepared in compression molding machine followed by the tensile test and tension‐tension fatigue testing at five different stress levels (from 50% to 90% of ultimate tensile strength). The addition of 3 wt% of nano‐silica with epoxy improved the tensile and fatigue strength as compared to neat GFEC. Scanning electron microscope (SEM) images of the fractured specimen showed the damage pattern which indicates that neat GFEC laminate exhibited damage patterns characterized by fiber breakage and matrix cracking. On the other hand, the modified GFEC with nano‐silica showed damage patterns including fiber pullout accompanied by fiber breakage and matrix cracking. During cyclic loading, the stress–strain hysteresis loop shows a reduced slope, indicating a decrease in the dynamic modulus of the specimen. This reduction in slope signifies a loss of stiffness during cyclic loading, particularly at high‐stress levels. The highest dynamic modulus at high‐stress levels indicates a rapid progression of severe damage and a shorter fatigue life. On the other hand, at low‐stress levels, the lower magnitude of dynamic modulus suggests a moderate damage progression and a longer fatigue life.Highlights Effect of nano‐silica in GFEC under static and fatigue loading conditions. GFEC with 3 wt% of nano‐silica shows improved tensile and fatigue strength. Examination of damage patterns through SEM analysis of the fractured surface. Depiction of the failure modes using damage pattern under fatigue loading. Comparison of fatigue life and dynamic modulus for neat and modified GFEC.

Optimization of AWJ parameters for improved material removal and hole geometry in drilling of Glass Fiber/Aluminum mesh epoxy hybrid composites

Seif,

Fathy,

El Aal

et al. 2024

Self Cite

This study explores the application of abrasive waterjet drilling (AWJD) for varied patterns of GF/Al mesh hybrid composites (neat glass NG, AG: Al in the exterior surface, and GA: Al in the center). Key parameters such as jet pressure (P), standoff distance (S), and traverse speed (V) are systematically varied, influencing material removal rate (MRR), hole taper ratio (), and roundness error (). Employing a Taguchi approach with an L9 design. It was indicated that the optimal conditions for maximum MRR are (P: 150 MPa, S: 2 mm, and V: 900 mm/min). V and S are the main influential parameters on and . Gray relational analysis (GRA) is employed for simultaneous optimization, enhancing drilling performance. The optimal parameters P of 150 MPa, S of 2 mm, and V of 300 mm/min are determined. Validation trials confirm the effectiveness of the determined parameters. A robust multiple regression equation is formulated, providing a predictive model that aligns closely with experimental observations.Highlights The hybrid composites were drilled via a nontraditional process. The attributes of the hole geometry and the material removal impacts were studied. Operation parameters were optimized to improve MRR, , and . A multiple regression model and a confirmation test were performed and validated.