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Design and Analysis of Composites Proceedings of the American Society for Composites 39th Technical Conference, Volume 1 /

This book presents the proceedings of the American Society for Composites 39th Technical Conference. This volume, the first of six volumes, is a concise collection of cutting-edge research focusing on Artificial Intelligence (AI), Machine Learning (ML), Uncertainty Quantification (UQ), architected c...

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Bibliografiske detaljer
Institution som forfatter: SpringerLink (Online service)
Andre forfattere: Zobeiry, Navid (Editor), Liu, Xin (Editor)
Format: Electronisk eBog
Sprog:engelsk
Udgivet: Cham : Springer Nature Switzerland : Imprint: Springer, 2025.
Udgivelse:1st ed. 2025.
Serier:Proceedings of the American Society for Composites Annual Technical Conferences,
Fag:
Civil engineering.
Mechanics, Applied.
Materials science.
Civil Engineering.
Engineering Mechanics.
Materials Science.
Online adgang:https://doi.org/10.1007/978-3-032-01730-7
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Indholdsfortegnelse:
  • Part 1: AI and ML in Composites
  • Chapter 1: A Machine Learning Approach for Predicting Bending After Impact Strength and Failure Modes in Hybrid (CFRP/GFRP) Sandwich Composites
  • Chapter 2: Deep Learning Models for Automatic Image Segmentation of Low Velocity Impact Damage in CFRP Composites
  • Chapter 3: Developing Continuum Damage Model Tensors for Ceramic Matrix Composites Using Genetic Programming Based Symbolic Regression
  • Chapter 4: Development of Data-Driven Surrogate Models for Rapid Simulation of Fibre Reinforced Composites in Progressive Fracture Tests
  • Chapter 5: Discerning Microstructure of CMC Minicomposites from Micro-CT Imaging Data Using Machine Learning
  • Chapter 6: Failure Prediction of Fiber-Reinforced Polymer Composite Materials Using Data-Driven Modeling
  • Chapter 7: Image-Based RKPM for Accessing Failure Mechanisms in Composite Materials
  • Chapter 8: Implementing Machine Learning Methodologies to Characterize Hidden Damages in Composite Plates Through Lamb Waves
  • Chapter 9: Integrated Process and Failure Analysis in Composites Using Multi-Fidelity Simulations and Machine Learning
  • Chapter 10: Using Neural Network to Improve Failure Predictions
  • Part 2: Architected Composites
  • Chapter 11: Additive Manufacturing of Wood Nanocomposites Using Natural Fibers
  • Chapter 12: Composite Core Designs for Freeform Structures
  • Chapter 13: Development of Auxetic Composite Materials for Improved Impact Properties
  • Chapter 14: Failure Mechanism and Energy Absorption Characteristics of Auxetic Pyrolytic Carbon Reinforcements Embedded in Different Matrix Materials
  • Chapter 15: Improving Composite Tailorability Through Architected Nacre Tablets
  • Chapter 16: Interlaminar Shear Strength of Carbon/Epoxy Laminates Containing Magnetically Aligned Nickel-Coated, Diazotized Carbon Nanotubes
  • Part 3: Design and Manufacturing
  • Chapter 17: 3D Printing of Woven Carbon Fiber Composites via a Stereolithography-Inspired Technique with Consolidation
  • Chapter 18: Abrasive Friction Drilling in Fiber Reinforced Thermosetting Polymer Composites
  • Chapter 19: Effect of Fiber Angle on the Radial Stress in Hybrid Aluminum/Composite Tubes
  • Chapter 20: Efficient Manufacturing of Carbon Fiber Reinforced EPON-Based Epoxy Resin Composites via Hot Press-Triggered Frontal Polymerization
  • Chapter 21: Evaluation of Alumina Particle Reinforced Aluminum Matrix Composites Fabricated by Accumulative Roll Bonding Method
  • Chapter 22: Optimal Design of Viscoelastic Laminated Sandwich Composite Structures Considering Thermally-Induced Deformation of Composite Skins Using Lamination Parameters
  • Chapter 23: Optimized Design Workflow for Patient-Customized Composite Orthotics
  • Chapter 24: Stack Drilling of Carbon Fiber Reinforced Polymer Laminate and Metals Stacks Using Friction Flow Drilling
  • Part 4: ICME
  • Chapter 25: Molecular Dynamics Investigation of Bonding Structure and Property Relationships at the Interface Between Cellulose Nanocrystals and Glass Fibers
  • Part 5: Uncertainty Quantification
  • Chapter 26: Bayesian Calibration and Uncertainty Quantification of Cohesive Zone Parameters at an Adhesively Bonded Textile and Fabric Interface
  • Chapter 27: Efficient Design of Laminate Composites Using Ensemble Kalman Inversion Method
  • Chapter 28: Reliability-Based Design and Certification of Hybrid Composites
  • Chapter 29: Uncertainty Quantification in Advanced Aerospace Composite Manufacturing Through Stochastic Finite Element Analysis and Probabilistic Machine Learning.

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