Optimization of strength properties of bamboo mesoparticles reinforced polyamide 6 using Box–Behnken approach DOI
Abeer Adel Salih, Rozli Zulkifli,

Che Husna Azhari

et al.

Plastics Rubber and Composites Macromolecular Engineering, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 29, 2024

Bamboo mesoparticles were used as a viable alternative reinforcement in matrix polymers to produce eco-friendly products, and the for cheaper processing methods comparable mechanical properties nanoparticle. The main factors that influence behavior of natural composites are fiber size, loading, chemical treatment. This study optimized blending parameters bamboo mesoparticle/polyamide 6 through response surface methodology based on Box–Behnken design. predicted strength values these function independent variables obtained from analysis variance statistical approach. results showed alkali concentration significantly quadratic model terms. was determine maximum strength, it closely agreement with experimental finding value R 2 = 0.9385. optimum conditions tensile identified size 1 µm, NaOH wt.%, loading 18 wt.%. flexural particle 13 0.46 µm.

Language: Английский

Artificial Intelligence‐Driven Prediction and Optimization of Tensile and Impact Strength in Natural Fiber/Aluminum Oxide Polymer Nanocomposites DOI Creative Commons
Jothi Arunachalam Solairaju, R. Saravanan,

Nashwan Adnan Othman

et al.

Engineering Reports, Journal Year: 2025, Volume and Issue: 7(4)

Published: April 1, 2025

ABSTRACT This study investigates the mechanical properties of hybrid composites reinforced with jute, kenaf, and glass fibers, incorporating Aluminum Oxide (Al 2 O 3 ) as a nanoparticle filler. The effects three key parameters—fiber orientation, fiber sequence, weight percentage Al on—the tensile impact strength were examined. Three levels for each factor considered: orientation (0°, 45°, 90°), sequence (1, 2, layers), varying content (3%, 4%, 5%). response surface methodology (RSM) was employed to optimize parameters, providing insights into interactions between these factors their influence on composite's performance. Additionally, artificial neural networks (ANN) used prediction modeling. outcome presented that ANN model outpaced RSM in terms accuracy, higher correlation predicted experimental values. optimal parameters achieving highest determined, at 90°, 3, 5%. demonstrates effectiveness predicting laminated composite highlights significant role reinforcement enhancing

Language: Английский

Citations

1
Mechanical Assessment for Enhancing Hybrid Composite Performance through Silane Treatment Using RSM and ANN DOI Creative Commons

S. Jothi Arunachalam,

R. Saravanan,

T. Sathish

et al.

Results in Engineering, Journal Year: 2024, Volume and Issue: 24, P. 103309 - 103309

Published: Nov. 5, 2024

Language: Английский

Citations

5
Advanced Optimization of Alkalinization Processes for Date Palm Fibers Using Response Surface Methodology with Taguchi Design (L16) DOI Creative Commons
Mohamed Fnides, Salah Amroune, Ahmed Belaadi

et al.

Journal of Natural Fibers, Journal Year: 2025, Volume and Issue: 22(1)

Published: Feb. 15, 2025

Language: Английский

Citations

0
Quality Evaluation and Predictive Analysis of Drilled Holes in Jute/Palm/Polyester Hybrid Bio-Composites Using CMM and ANN Techniques DOI Creative Commons
Salah Amroune, Abdelmalek Elhadi, Mohamed Slamani

et al.

Journal of Natural Fibers, Journal Year: 2025, Volume and Issue: 22(1)

Published: April 26, 2025

Language: Английский

Citations

0
Enhancing the Mechanical Characteristics of Eco-Friendly Composite Materials: Taguchi and RSM Optimization DOI Creative Commons
Khalissa Saada, Salah Amroune, Ahmed Belaadi

et al.

Journal of Natural Fibers, Journal Year: 2024, Volume and Issue: 21(1)

Published: Nov. 18, 2024

Green composites consisting of renewable or biodegradable materials are becoming more popular as environmental awareness global waste issues grows. Among them, natural made polymers have proven to work exceptionally well because their high strength, rapid breakdown after disposal, and simplicity in processing using standard techniques. In particular, competitive mechanical performances been demonstrated by green having a polymer matrix reinforced with sisal, luffa, maize fibers at different fiber percentages 10%, 15%, 25%. The tensile characteristics these optimized this study the application Taguchi response surface methodology. By assessing such section size, content, type simultaneously, attempts produce optimal biocomposite qualities, which then experimentally tested. Tensile tests show considerable gains: containing 15% corn showed 21.04% increase strength. Similarly, all notable improvements Young's modulus, showing 22.77%, 31.77%, 20.25% increases, respectively.

Language: Английский

Citations

3
Optimization of strength properties of bamboo mesoparticles reinforced polyamide 6 using Box–Behnken approach DOI
Abeer Adel Salih, Rozli Zulkifli,

Che Husna Azhari

et al.

Plastics Rubber and Composites Macromolecular Engineering, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 29, 2024

Bamboo mesoparticles were used as a viable alternative reinforcement in matrix polymers to produce eco-friendly products, and the for cheaper processing methods comparable mechanical properties nanoparticle. The main factors that influence behavior of natural composites are fiber size, loading, chemical treatment. This study optimized blending parameters bamboo mesoparticle/polyamide 6 through response surface methodology based on Box–Behnken design. predicted strength values these function independent variables obtained from analysis variance statistical approach. results showed alkali concentration significantly quadratic model terms. was determine maximum strength, it closely agreement with experimental finding value R 2 = 0.9385. optimum conditions tensile identified size 1 µm, NaOH wt.%, loading 18 wt.%. flexural particle 13 0.46 µm.

Language: Английский

Citations

0