Predicting natural aging effects on fatigue life of CFRP–aluminum adhesive joints using machine learning and accelerated aging data

Journal of Adhesion Science and Technology, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 22

Published: Feb. 3, 2025

Language: Английский

---

Experimental investigation on hole bearing behavior and failure mechanism of double‐lap hybrid composite/titanium bolted joints

Polymer Composites, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 18, 2025

Abstract In this paper, a new co‐curing process for hybrid titanium alloy foils into composite laminates was put forward. Meanwhile several pull‐out specimens were tested to obtained the bonding response between and composites. And size of in double‐lap composite/titanium bolted joints designed according response. Then these fabricated tested. The test results revealed that hole bearing responses significantly better than specimens. Moreover, strengths with 33% content more 40% higher composites degree strength enhancement exceeded weight gain specimen. Meanwhile, damage morphologies characterized. It could be found edge length had significant effect on failure form joints, area affected by reduced increasing appropriately. structure within joint will provide reference improving strength. Highlights A created. Hole are Increasing can effectively reduce zone.

Language: Английский

---

Assessment of geometric parameters on the tensile behavior of hybrid (rivet‐adhesive) aluminum‐composite joints

Polymer Composites, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 17, 2025

Abstract The hybrid adhesive‐rivet joints offer very good behavior in bonding. This bond is then reinforced by a rivet, adding significant mechanical strength and preventing separation under stress. In this research, composite‐aluminum, (adhesive‐rivet) were investigated. Two types of composites used research: unidirectional woven fiber types. Hybrid made two distinct types: single double rivet joints. Various simple (rivet adhesive) joint with one or rivets are investigated effect them on various composite substrate study advances knowledge demonstrating how combining adhesive reinforcements optimizes energy absorption composite‐aluminum structures. It was observed that specimens Al–glass plastic (GFRP) 45‐degree angle (Al–CU—45) have the lowest than 0° 90° UD angles (Al–CU—0 90) tensile for GFRP (Al–CW) better composites. Two‐rivet 0°/90° fibers exhibited 30% higher load capacity ±45° fibers, while also absorbing 20% more compared to single‐rivet maximum fracture force specimen orientation has improved 42.8% orientation. Finally, fractography done macroscopic microscopic investigation surface samples done. scanning electron microscopy images shows detailed view surfaces fracture. Highlights Adhesive joints: outperformed 45° strength. Fracture force: Al–CU‐0° showed highest Displacement: Al–CU‐45° had failure displacement. Energy absorption: excelled both SEM: 0/90° fewer cracks, weaker matrices.

Language: Английский

---

LLM-Mambaformer: Integrating Mamba and Transformer for Crystalline Solids Properties Prediction

Materials Today Communications, Journal Year: 2025, Volume and Issue: unknown, P. 112029 - 112029

Published: Feb. 1, 2025

Language: Английский

---

Prediction of weight change of glass fiber reinforced polymer matrix composites with SiC nanoparticles after artificial aging by artificial neural network-based model

Journal of Materials Science, Journal Year: 2025, Volume and Issue: unknown

Published: March 9, 2025

Language: Английский

---

Integrating machine learning and digital twin for strength prediction of CFRP/aluminum adhesive joints under hygrothermal conditions

Polymer Composites, Journal Year: 2025, Volume and Issue: unknown

Published: April 15, 2025

Abstract This study investigates the application of machine learning models integrated with a digital twin (DT) framework to predict and correlate performance carbon fibre‐reinforced polymer‐to‐aluminum adhesive joints subjected hygrothermal aging. By combining experimental methods techniques, research aims bridge gap between effects natural accelerated aging on joints. The were manufactured then left age naturally for period one 3 years. For aging, conditions four 50 days. Three‐point bending tests utilized evaluate To periods using data, five algorithms used: support vector regression (SVR), artificial neural network (ANN), linear regression, random forest (RF) XGBoost. scanning electron microscopy (SEM) analyses showed that moisture absorption caused substantial change in surface morphology aluminum adherends, including increased roughness crystalline formations. results indicated XGBoost has provided almost perfect predictions since MSE values equal 0 observed at all iterations, highlighting its accuracy reliability. In contrast, SVR demonstrated much lower accuracy, clear differences their predictions. integration approaches turns out be most efficient method real‐time adaptation model as well accurate prediction, enhancing durability reliability composite structures. Highlights Strength prediction by Machine twin. SEM revealed moisture‐induced changes morphology. high accuracy.

Language: Английский

---

Mechanical properties and adhesive parameter optimization of CFRP-Al bonded structures in hygrothermal environments

Journal of Adhesion Science and Technology, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 37

Published: April 27, 2025

Language: Английский

---

Machine learning-driven digital twin for strength prediction of dissimilar adhesive joints under environmental aging

Journal of Composite Materials, Journal Year: 2025, Volume and Issue: unknown

Published: May 13, 2025

This study investigates the integration of machine learning (ML) models with a digital twin (DT) framework to predict performance CFRP-to-aluminum adhesive joints under hygrothermal aging. The were aged naturally for one three years and subjected accelerated aging conditions four 50 days. Three-point bending tests conducted evaluate joint performance. Five algorithms employed correlate natural periods data. results demonstrated that XGBoost achieved near-perfect prediction accuracy across all rounds real-time updates, indicating exceptional adaptability reliability. In contrast, such as SVR linear regression exhibited limited adaptability, higher error margins less consistent predictions. These findings underscore importance selecting flexible robust dynamic environments where adaptation is critical. proved be powerful approach model accurate prediction, ultimately enhancing durability reliability composite structures.

Language: Английский

---

Artificial intelligence technology in materials selection, device engineering and parameter optimisation for triboelectric nanogenerator

Materials Today Communications, Journal Year: 2025, Volume and Issue: unknown, P. 112553 - 112553

Published: April 1, 2025

Language: Английский

---

Characterization of the cyclic hygroscopic aging behavior of balsa wood core bio‐composite sandwich structures with preexisting defects in laminate skins

Polymer Composites, Journal Year: 2025, Volume and Issue: unknown

Published: May 14, 2025

Abstract Aimed at the decarbonization of marine structures under harsh humid environments, present study explores cyclic hygroscopic aging behavior balsa wood core bio‐composite sandwich with manufacturing defects in Glass‐Fiber Reinforced‐Polymer (GFRP) skins. Both experimental investigations and analytical predictions are presented. Two distinct protocols were proposed to realize complete‐cycle incomplete‐cycle absorption conditions moisture, characterize moisture diffusion mechanisms due non‐Fickian effects. The Dual Fickian model was found be effective predicting kinetics during cycles, while demonstrated superior fit desorption processes. Furthermore, maximum content 13.80% after 33 days reveals that an 18 mm diameter hole skin GFRP‐balsa could result a considerable water uptake, which cannot neglected. However, it can fully dried 35 °C within 3 days. It indicates possess notable repairability. Additionally, significant impact initial cycle on coefficients subsequent resorption cycles highlighted investigate long‐term effects exposure properties structures. Highlights Multiple performed replicate harsh, environments. employed behavior. Dual‐Fickian proven predict mechanisms. Balsa good candidate rapid repair capabilities. Effect first rates ignored.

Language: Английский

---