
Journal of Engineering Research, Journal Year: 2024, Volume and Issue: unknown
Published: Oct. 1, 2024
Language: Английский
Journal of Engineering Research, Journal Year: 2024, Volume and Issue: unknown
Published: Oct. 1, 2024
Language: Английский
Ain Shams Engineering Journal, Journal Year: 2024, Volume and Issue: 16(1), P. 103206 - 103206
Published: Dec. 7, 2024
Language: Английский
Citations
10Biochemistry and Biophysics Reports, Journal Year: 2025, Volume and Issue: 41, P. 101912 - 101912
Published: Jan. 1, 2025
Language: Английский
Citations
2International Journal of Hydrogen Energy, Journal Year: 2025, Volume and Issue: 114, P. 337 - 351
Published: March 1, 2025
Language: Английский
Citations
1AIP Advances, Journal Year: 2025, Volume and Issue: 15(4)
Published: April 1, 2025
This study introduces a novel approach for predicting the mechanical properties of 3D-printed polylactic acid wood composites using gene expression programming (GEP) and artificial neural networks (ANN) modeling methods. Addressing challenge determining optimal process parameters in fused deposition natural fiber composites, experiments were designed Taguchi’s L27 orthogonal array. Five key analyzed: layer thickness (100–300 μm), printing speed (40–90 mm/s), raster angle (0°–90°), infill density (35%–95%), nozzle temperature (200–220 °C). ANOVA results identified as most influential factor, contributing 38.36% 26% to tensile compressive strengths, respectively. Subsequently, comparative statistical analysis evaluated predictive accuracy GEP ANN. The model exhibited superior performance, achieving validation errors between 0.04% 0.82%, outperforming ANN (0.34%–5.31%). These findings provide robust framework enhancing performance sustainable enabling more efficient reliable production processes additive manufacturing.
Language: Английский
Citations
1Alexandria Engineering Journal, Journal Year: 2025, Volume and Issue: 118, P. 325 - 336
Published: Jan. 23, 2025
Language: Английский
Citations
0Journal of Materials Research and Technology, Journal Year: 2025, Volume and Issue: 35, P. 2736 - 2754
Published: Jan. 31, 2025
Language: Английский
Citations
0Alexandria Engineering Journal, Journal Year: 2025, Volume and Issue: 121, P. 38 - 52
Published: Feb. 25, 2025
Language: Английский
Citations
0Results in Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 104467 - 104467
Published: Feb. 1, 2025
Language: Английский
Citations
0Water Air & Soil Pollution, Journal Year: 2025, Volume and Issue: 236(4)
Published: March 11, 2025
Language: Английский
Citations
0AIP Advances, Journal Year: 2025, Volume and Issue: 15(3)
Published: March 1, 2025
In recent years, sustainability has evolved profoundly and garnered significant global attention, establishing itself as a pivotal topic in contemporary research. line with this development, the present review thoroughly examines existing studies on machining processes employing minimum quantity lubrication (MQL). The growing imperative for sustainable practices driven researchers to reassess alternative techniques within operations. Although conventional lubri-cooling agents continue be widely used engineering alloys, an expanding body of research demonstrates that incorporation vegetable oils, nanofluids, nanoplatelets into MQL systems can yield superior performance compared traditional methods. presents overview developments advancements related technology provides rigorous analysis oils nanofluids metalworking fluids. This study also eco-friendly approaches flood serves meaningful resource move toward greener solutions.
Language: Английский
Citations
0