Computational and Experimental Simulations in Engineering : Proceedings of ICCES 2023--Volume 2

• Autore: Li Shaofan
• Pubblicazione: Cham : , : Springer International Publishing AG, , 2024; ©2024
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (1435 pages)
• Nota di contenuto: Intro -- Preface -- Contents -- 1 A Peridynamic Micro-Scale Model for Predicting Mechanical Properties of Graphene -- 1.1 Introduction -- 1.2 Interaction -- 1.3 PeriDynamics -- 1.4 Unit Cell -- 1.5 Results and Discussion -- 1.6 Conclusion -- References -- 2 Three-Dimensional Temperature Field Prediction in Double-Wall Cooling Structure Using Deep Learning Method -- 2.1 Introduction -- 2.2 Methodology -- 2.2.1 Numerical Simulation for DWCS Unit -- 2.2.2 Dataset Building -- 2.2.3 Deep Learning Algorithm -- 2.3 Experiment and Results -- 2.3.1 Model Evaluation -- 2.4 Conclusion -- References -- 3 A Neural Network-Based Method for Solving the Mass Flow Related Forward and Inverse Problems of Laminate Cooling Structures -- 3.1 Introduction -- 3.2 Dataset Preparation -- 3.2.1 Geometries, and Computational Setups -- 3.2.2 Flow Data for Training -- 3.3 Methodology -- 3.3.1 Network Architecture for Solving Forward Problems -- 3.3.2 Network Architecture for Solving Inverse Problems -- 3.4 Results and Discussion -- 3.4.1 Forward Problem -- 3.4.2 Inverse Problem -- 3.5 Conclusion -- References -- 4 Experimental Research of Ultra High Performance Concrete in Supersized Rectangle Pipe Jacking Project -- 4.1 Introduction -- 4.2 Background -- 4.2.1 Project Review -- 4.2.2 Design of an Assembled Tube -- 4.2.3 Connection Method -- 4.3 Mechanical Performance -- 4.3.1 Test Scheme -- 4.3.2 Results -- 4.4 Waterproofing Performance -- 4.4.1 Laboratory Test -- 4.4.2 Prototype Test -- 4.4.3 Improved Waterproofing Design -- 4.5 Conclusion -- References -- 5 Mechanical Performance and Experimental Research on Plug-in Fast Connector of Shield Tunnel -- 5.1 Introduction -- 5.2 Background -- 5.2.1 Project Overview -- 5.2.2 Plug-in Fast Connector -- 5.3 Tensile Test Scheme -- 5.3.1 Specimen Design -- 5.3.2 Apparatus -- 5.3.3 Monitoring Scheme -- 5.4 Shearing-Test Scheme. ; 5.4.1 Introduction of Scheme -- 5.4.2 Specimen Design -- 5.4.3 Apparatus and Loading Scheme -- 5.5 Results -- 5.5.1 Tensile Test -- 5.5.2 Shearing Test -- 5.6 Conclusion -- References -- 6 The Advancement of Knowledge Graphs in Cybersecurity: A Comprehensive Overview -- 6.1 Introduction -- 6.2 Background Knowledge -- 6.2.1 Knowledge Graph -- 6.2.2 Cybersecurity Knowledge Graph -- 6.3 Cybersecurity Knowledge Graph Dataset -- 6.3.1 Generalized Dataset of Cybersecurity Knowledge Graph -- 6.3.2 Cybersecurity Knowledge Graph Professional Type Dataset -- 6.4 Cybersecurity Knowledge Graph Construction Techniques -- 6.4.1 Technical Architecture of CyberSecurity Knowledge Graph -- 6.4.2 Network Security Domain Ontology Modeling -- 6.4.3 Knowledge Extraction for CyberSecurity Knowledge Graph -- 6.4.4 CyberSecurity Knowledge Graph Reasoning -- 6.5 Application Scenarios of Network Security Knowledge Graph -- 6.5.1 CyberSecurity Knowledge Graph Defense Class Application Scenarios -- 6.5.2 CyberSecurity Knowledge Graph Attack Class Application Scenarios -- 6.5.3 CyberSecurity Knowledge Graph Optimization Class Application Scenarios -- 6.6 Challenges and Future Trends -- 6.6.1 Challenges to the Cybersecurity Knowledge Graph -- 6.6.2 Future Trends of Knowledge Graph in Cybersecurity -- 6.7 Conclusion -- References -- 7 Active Disturbance Rejection Control of Hypersonic Vehicle Based on Q-Learning Algorithm -- 7.1 Introduction -- 7.2 Pitch Channel Dynamics Model of Hypersonic Vehicles -- 7.3 ADRC Controller Design for the Pitch Channel of Hypersonic Vehicle -- 7.3.1 Pitch Channel State Equation -- 7.3.2 Design of ADRC Controller -- 7.4 Q-Learning Algorithm for Attitude Controller Parameter Tuning -- 7.4.1 Q-Learning Theory -- 7.4.2 The Design Process of Q-learning Algorithm -- 7.4.3 Design of Q-Algorithm Behavior and State -- 7.5 Simulation Test -- 7.6 Conclusion. ; References -- 8 Deformation and Crack Monitoring of RC Beams Based on Computer Vision -- 8.1 Introduction -- 8.2 Image Acquisition -- 8.2.1 Experimental Specimens -- 8.2.2 Cameras Set-Up -- 8.3 Method and Result -- 8.3.1 Mid-Span Deflection Extraction -- 8.3.2 Crack Detection on Sequential Images -- 8.3.3 Crack Characteristic Parameters Extraction -- 8.4 Conclusion -- References -- 9 Numerical Simulation of Enhancing the Solar-Thermal Conversion and Storage Performance for Expanded Perlite/Paraffin Wax Composites by Introducing Expanded Graphite and Carbon Nanotubes -- 9.1 Introduction -- 9.2 Material and Characterization -- 9.2.1 Materials -- 9.2.2 Preparation of Composites -- 9.2.3 Characterization -- 9.2.4 Morphologies and Microstructure -- 9.2.5 Thermal Properties of PW and Composites -- 9.2.6 The Solar Absorptance of PW and Composites -- 9.3 Numerical Model -- 9.3.1 Physical Model -- 9.3.2 Governing Equations -- 9.3.3 Boundary Conditions -- 9.3.4 Numerical Approach and Module Validation -- 9.3.5 Grid and Time Steps Independence Verification -- 9.4 Results and Discussion -- 9.4.1 Heat Storage and Release -- 9.4.2 Solar-Thermal Conversion and Storage Process -- 9.5 Conclusion -- References -- 10 Effect of Natural Fracture Clusters on Hydraulic Fracture Propagation in Fractured Reservoirs: A Numerical Simulation Study -- 10.1 Introduction -- 10.2 Governing Equations -- 10.2.1 Rock Deformation and Fluid Flow Equations -- 10.2.2 Fracture Tip Initiation and Propagation Control Equation -- 10.2.3 Fluid Flow Equation in the Fracture -- 10.3 Numerical Simulation Method Validation and Model Building -- 10.3.1 Numerical Simulation Method Validation -- 10.3.2 Model Building -- 10.4 Simulation Results -- 10.4.1 Fracture Propagation Morphology and Injection Pressure Response Characteristics. ; 10.4.2 Influence of Horizontal Stress Difference on Hydraulic Fracture Propagation -- 10.4.3 Influence of Natural Fracture Angle on Hydraulic Fracture Propagation -- 10.4.4 Influence of Injection Rate and Fracturing Fluid Viscosity on Hydraulic Fracture Propagation -- 10.5 Discussion -- 10.6 Conclusions -- References -- 11 Molecular Dynamics Investigations of Hydrogen-Enriched Natural Gas Permeation in Polyethylene -- 11.1 Introduction -- 11.2 Molecular Dynamics Model -- 11.3 Molecular Dynamics Simulation Process -- 11.3.1 Simulation of Dissolution/Sorption Process -- 11.3.2 Simulation of Diffusion Process -- 11.3.3 Simulation of Permeation Process -- 11.4 Analysis of Simulation Results -- 11.4.1 Study of Gas Dissolution -- 11.4.2 Study of Gas Diffusion -- 11.4.3 Permeation Characteristics -- 11.5 Conclusions -- References -- 12 Estimation of Hourly Solar Radiation in Australia Using Machine Learning Models -- 12.1 Introduction -- 12.2 Study Site and Data Collection -- 12.3 Machine Learning Models and Statistical Indicators -- 12.3.1 RF -- 12.3.2 SVM -- 12.3.3 Statistical Indicators -- 12.4 Results and Discussion -- 12.5 Conclusion -- References -- 13 Theoretical Calculation and Parametric Study of Floating and Sinking Process of the Steel Tube with a Large Diameter -- 13.1 Introduction -- 13.2 Floating and Sinking Process of Steel Guard Cylinder -- 13.3 Establishment of Equilibrium Equation -- 13.4 Analysis and Discussion -- 13.4.1 The Relationship Between the Immersion Depth of the Protection Cylinder and the Depth of the Liquid Level in the Barrel -- 13.4.2 Relation Between Water Inlet Speed and Rotational Speed -- 13.4.3 Relation Between Water Inlet Area and Rotational Speed and Time -- 13.5 Conclusion -- References -- 14 A Stable Method for Multi-component Gas Darcy Flow in Porous Media -- 14.1 Introduction -- 14.2 Mathematical Model. ; 14.3 Proposed Method -- 14.4 Stability Verification -- 14.5 Case Study -- 14.5.1 Parameters of the Simulation -- 14.5.2 Case for a Single Well Gas Injection -- 14.5.3 Case for Multiple Wells Gas Injection -- 14.6 Conclusion -- References -- 15 Optimal Control of Vehicle Queue Following Based on Wireless Communication -- 15.1 Introduction -- 15.2 Problem Formulation and System Modeling -- 15.3 Vehicle Longitudinal Dynamics Model -- 15.4 Car Following Distance Optimization and Nonlinear Control -- 15.4.1 Follow Distance Optimization -- 15.4.2 Nonlinear Tracking Control Based on Optimal Following Distance -- 15.5 Simulation Studies -- 15.6 Conclusion -- References -- 16 Fatigue Crack Quantification Model for Metallic Structures Based on Strain Monitoring -- 16.1 Introduction -- 16.2 Model Development -- 16.3 Application Examples of the Model -- 16.4 Conclusion -- References -- 17 A Study of a Confucius Culture Learning Environment Based on a 3D Metaverse -- 17.1 Introduction -- 17.2 Metaverse -- 17.3 Based on HMD Interaction Technology -- 17.4 Experimental Platform -- 17.5 Experimental Method -- 17.5.1 Abbreviations and Acronyms -- 17.5.2 Building the Virtual Learning Environment -- 17.5.3 Conducting Experience and Analysis -- 17.6 Experiment Results -- 17.7 Conclusion -- References -- 18 Optimization on Aerodynamic Performances of Pantograph Combined with Sample Infill Criterion -- 18.1 Introduction -- 18.2 Kriging Model and Sample Infill Criterion -- 18.2.1 Kriging Model -- 18.2.2 Sample Selections in Pareto Front and Hybrid Infill Criterion -- 18.3 Kriging Model and Sample Infill Criterion -- 18.3.1 Single-Objective Function Branin -- 18.3.2 Multi-objective Function Poloni -- 18.4 Optimization on the Pantograph -- 18.5 Conclusion -- References -- 19 Measuring Fire Spread Rate with Digital Image Processing Method -- 19.1 Introduction. ; 19.2 Flame Image Acquisition and Spatial Correction.
• Titolo autorizzato: Computational and Experimental Simulations in Engineering
• ISBN: 3-031-42987-7
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910767549403321
• Lo trovi qui: Univ. Federico II
• Serie: Mechanisms and Machine Science Series