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Advances in computational mechanics and applications [electronic resource] : OES 2023 / Dimitrios Pavlou, Hojjat Adeli, José A. F. O. Correia, Nicholas Fantuzzi, Georgios C. Georgiou, Knut Erik Giljarhus, Yanyan Sha, editors.

This book publishes the work presented at the 1st Olympiad in Engineering Science (OES 2023), an international congress and contest aiming to disseminate and evaluate the recent advances in Engineering Science. The book covers diverse domains of engineering. From Machine Learning applications in Thr...

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Bibliographic Details
Online Access: Full Text (via Springer)
Corporate Author: Olympiad in Engineering Science (Conference) Olympia, Greece)
Other Authors: Pavlou, Dimitrios G., Adeli, Hojjat, 1950-, Correia, José A. F. O., 1984-, Fantuzzi, Nicholas, Georgiou, Georgios C., Giljarhus, Knut Erik, Sha, Yanyan
Other title:OES 2023
Format: Electronic Conference Proceeding eBook
Language:English
Published: Cham : Springer, 2024.
Series:Structural integrity (Series) ; v. 29.
Subjects:
Engineering > Congresses.
Table of Contents:
  • Intro
  • Preface
  • Contents
  • Machine Learning
  • A Combined Machine Learning and Computational Methodology for Optimum Thrust Bearings' Behavior in Mixed Lubrication Regime
  • 1 Introduction
  • 2 Theory
  • 2.1 Lubrication Model
  • 2.2 Viscosity Model
  • 2.3 Numerical Analysis
  • 2.4 Machine Learning Techniques
  • 3 Results and Discussion
  • 4 Conclusions
  • References
  • Limited-Data-Driven Machine Learning in Structural Health Diagnosis
  • 1 Introduction
  • 2 Vision-Based Damage Recognition Using Few Images
  • 3 Correlation Pattern Recognition Based Condition Assessment
  • 4 Vision-Based Structural Seismic Assessment for Buildings
  • 5 Conclusions
  • References
  • A Numerical Study on the Early-Stage Performance of 3D Composite PLA/316L Scaffolds in Tissue Engineering
  • 1 Introduction
  • 2 Scaffold Design
  • 3 Numerical Modeling
  • 3.1 Boundary Element Method (BEM)
  • 3.2 Physics-Informed Neural Networks (PINNs)
  • 3.3 Element-Based Finite Volume Method (EbFVM)
  • 4 Numerical Results
  • 4.1 Computational Structural Mechanics (CSM) Analysis
  • 4.2 Computational Fluid Dynamics (CFD) Analysis
  • 4.3 Mechanoregulatory Model for the Early-Stage Cell Differentiation
  • 5 Conclusions
  • References
  • Ensembled Multi-classification Generative Adversarial Network for Condition Monitoring in Streaming Data with Emerging New Classes
  • 1 Introduction
  • 2 Methodology
  • 2.1 Notations
  • 2.2 Basic Structure of the Proposed MC-GAN
  • 2.3 History-State Ensemble (HSE)
  • 2.4 The Proposed SENC Framework
  • 3 Experimental Validation
  • 3.1 Dataset Description
  • 3.2 Results and Discussion
  • 4 Conclusion
  • References
  • Ultrasonic-Based Stress Identification of a Reinforced Concrete Beam via USR-Net
  • 1 Introduction
  • 2 USR-Net
  • 2.1 Overview
  • 2.2 STF and STA
  • 2.3 Feature Extractor with Residual Blocks and Classifier
  • 3 Experiment
  • 3.1 Experiment Design
  • 3.2 Experiment Materials and Instruments
  • 4 Result and Discussion
  • 4.1 Experimental Result
  • 4.2 Discussion
  • 5 Conclusion
  • References
  • Determination of the Presence or Absence of Defect for Laser Ultrasonic Visualization Testing Using Transfer Learning
  • 1 Introduction
  • 2 LUVT Setup
  • 3 FDTD Simulation for Ultrasonic Wave Propagation
  • 3.1 FDTD Formulation for 2-D Elastodynamics
  • 3.2 Learning Data Created by FDTD
  • 4 CNN and Transfer Learning
  • 5 CNN Results
  • 5.1 Scattered Wave Detection Using CNN
  • 5.2 Automatic Defect Detection Using CNN
  • 5.3 Automatic Defect Detection Using CNN with VGG16 Architecture
  • 6 Conclusion
  • References
  • Development of Nanomodified Graphene Concrete Using Machine Learning Methods
  • 1 Introduction
  • 2 Experimental Section
  • 2.1 GO Synthesis
  • 2.2 Preparation of Cementitious Composite Test Specimens
  • 3 Results and Discussion
  • 3.1 X-ray Diffraction Analysis (XRD)
  • 3.2 X-ray Photoelectron Spectroscopy (XPS)
  • 3.3 Fourier-Transform Infrared Spectroscopy (FTIR)
  • 3.4 Raman Spectroscopy

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