Related references
Note: Only part of the references are listed.Mechanical behavior and failure mechanisms of CFRP and Titanium tubular adhesive lap joints at extreme temperatures
Isaiah Kaiser et al.
COMPOSITE STRUCTURES (2022)
Stochastic integrated machine learning based multiscale approach for the prediction of the thermal conductivity in carbon nanotube reinforced polymeric composites
Bokai Liu et al.
COMPOSITES SCIENCE AND TECHNOLOGY (2022)
Failure classification of porous additively manufactured parts using Deep Learning
Kyle L. Johnson et al.
COMPUTATIONAL MATERIALS SCIENCE (2022)
Application of Soft Computing Techniques to Predict the Strength of Geopolymer Composites
Qichen Wang et al.
POLYMERS (2022)
Bio-inspired patterned adhesive single-lap joints for CFRP and titanium
Isaiah Kaiser et al.
COMPOSITES PART B-ENGINEERING (2021)
Failure analysis of composite-to-titanium single lap adhesive joints subjected to tensile loading
Tianchun Zou et al.
ENGINEERING FAILURE ANALYSIS (2021)
Delamination detection in composite plates using random forests
Dao Kun Lim et al.
COMPOSITE STRUCTURES (2021)
A parametric study of adhesive bonded joints with composite material using black-box and grey-box machine learning methods: Deep neuron networks and genetic programming
Zewen Gu et al.
COMPOSITES PART B-ENGINEERING (2021)
Damage and strength analysis of Carbon Fiber Reinforced Polymer and Titanium tubular-lap joint using hybrid adhesive design
Isaiah Kaiser et al.
INTERNATIONAL JOURNAL OF ADHESION AND ADHESIVES (2020)
Analyzing single-lap joints bonded with a brittle adhesive by an elastic meshless method
I. J. Sanchez-Arce et al.
1ST VIRTUAL EUROPEAN CONFERENCE ON FRACTURE - VECF1 (2020)
Failure analysis of GFRP single lap joints tailored with a combination of tough epoxy and hyperelastic adhesives
D. V. Srinivasan et al.
COMPOSITES PART B-ENGINEERING (2020)
Failure analysis of AA8011-pultruded GFRP adhesively bonded similar and dissimilar joints
Nithin Simha Reddy et al.
INTERNATIONAL JOURNAL OF ADHESION AND ADHESIVES (2019)
Single and dual adhesive bond strength analysis of single lap joint between dissimilar adherends
R. Jairaja et al.
INTERNATIONAL JOURNAL OF ADHESION AND ADHESIVES (2019)
Review on techniques to improve the strength of adhesive joints with composite adherends
X. Shang et al.
COMPOSITES PART B-ENGINEERING (2019)
Experimental and numerical investigations of adhesively bonded CFRP single-lap joints subjected to tensile loads
Ligang Sun et al.
INTERNATIONAL JOURNAL OF ADHESION AND ADHESIVES (2019)
An experimental investigation on the failure loads of the mono and bi-adhesive joints
Ozkan Oz et al.
JOURNAL OF ADHESION SCIENCE AND TECHNOLOGY (2017)
Damage analysis of composite-aluminium adhesively-bonded single-lap joints
T. E. A. Ribeiro et al.
COMPOSITE STRUCTURES (2016)
Failure load prediction of adhesively bonded pultruded composites using artificial neural network
H. Ersen Balcioglu et al.
JOURNAL OF COMPOSITE MATERIALS (2016)
Failure load prediction of single lap adhesive joints using artificial neural networks
Erdi Tosun et al.
ALEXANDRIA ENGINEERING JOURNAL (2016)
Experimental study of adhesively bonded CFRP joints subjected to tensile loads
Jianfeng Li et al.
INTERNATIONAL JOURNAL OF ADHESION AND ADHESIVES (2015)
Neural network approach for damaged area location prediction of a composite plate using electromechanical impedance technique
S. Na et al.
COMPOSITES SCIENCE AND TECHNOLOGY (2013)
Application of artificial neural networks to predict the bond strength of FRP-to-concrete joints
Mohammed A. Mashrei et al.
CONSTRUCTION AND BUILDING MATERIALS (2013)
Modelling adhesive joints with cohesive zone models: effect of the cohesive law shape of the adhesive layer
R. D. S. G. Campilho et al.
INTERNATIONAL JOURNAL OF ADHESION AND ADHESIVES (2013)
Effect of adhesive thickness, adhesive type and scarf angle on the mechanical properties of scarf adhesive joints
Lijuan Liao et al.
INTERNATIONAL JOURNAL OF SOLIDS AND STRUCTURES (2013)
Time series forecasting using a weighted cross-validation evolutionary artificial neural network ensemble
Juan Peralta Donate et al.
NEUROCOMPUTING (2013)
Parametric study of adhesive joints with composites
J. A. B. P. Neto et al.
INTERNATIONAL JOURNAL OF ADHESION AND ADHESIVES (2012)
Variable Importance Assessment in Regression: Linear Regression versus Random Forest
Ulrike Groemping
AMERICAN STATISTICIAN (2009)
Effect of material, geometry, surface treatment and environment on the shear strength of single lap joints
Lucas. F. M. da Silva et al.
INTERNATIONAL JOURNAL OF ADHESION AND ADHESIVES (2009)
Estimation of composite damage model parameters using spectral finite element and neural network
AK Garg et al.
COMPOSITES SCIENCE AND TECHNOLOGY (2004)
Neural network design for engineering applications
MY Rafiq et al.
COMPUTERS & STRUCTURES (2001)