Advanced Intelligent Pipeline Management Technology / / edited by Huai Su [and three others]

• Pubblicazione: Singapore : , : Springer, , [2023]; ©2023
• Edizione: First edition.
• Descrizione fisica: 1 online resource (199 pages)
• Disciplina: 405
• Soggetto topico: Pipelines
• Persona (resp. second.): SuHuai
• Nota di bibliografia: Includes bibliographical references.
• Nota di contenuto: Intro -- Acknowledgments -- Contents -- 1 Overview for Pipeline Scheduling -- 1.1 Pipeline Scheduling Content -- 1.1.1 Gas Pipeline Network -- 1.1.2 Oil Pipeline Network -- 1.2 Research Status -- 1.2.1 Optimization Model of Pipeline Network Scheduling -- 1.2.2 Solution Algorithms -- 1.3 Conclusion -- 1.3.1 General Situation -- 1.3.2 Future Development Directions -- References -- 2 Advanced Modeling and Algorithm for Pipeline Scheduling -- 2.1 Modeling Methods -- 2.1.1 Mathematical Programming -- 2.1.2 Generalized Disjunctive Programming (GDP) -- 2.1.3 Resource Task Network (RTN) -- 2.2 Solution Algorithms -- 2.2.1 Mathematical Programming -- 2.2.2 Heuristic Algorithm -- 2.2.3 Metaheuristic Algorithm -- 2.2.4 Dynamic Programming Algorithm -- 2.2.5 Data-Driven Algorithm -- 2.3 Conclusion -- References -- 3 Demand Side Management in Smart Pipeline Networks -- 3.1 Development of Demand Side Management -- 3.2 Methodology -- 3.2.1 Mathematical Models for Gas Networks -- 3.2.2 Pipeline Network Model -- 3.2.3 Analysis of Customer Demands -- 3.2.4 Operating Center Profit Model -- 3.2.5 Objective Functions -- 3.2.6 Intelligent Algorithm for Gas Pipeline System Management -- 3.2.7 Forecasting Model of Customer Demand -- 3.3 Case Study -- 3.4 Conclusion -- References -- 4 Life Cycle Analysis of Pipeline Networks -- 4.1 Environmental Impacts of Pipelines -- 4.2 Carbon Emission Stages of Pipeline Transport System -- 4.3 Life Cycle Analysis of Oil Pipelines -- 4.3.1 Infrastructure Construction -- 4.3.2 Pipe Operation -- 4.3.3 Fugitive Emissions -- 4.3.4 Recycle and Disposal -- 4.3.5 Impact on Soil Environment -- 4.4 Life Cycle Analysis of Gas Pipelines -- 4.4.1 Compressor Station -- 4.4.2 Maintenance -- 4.4.3 Leakage -- 4.5 Life Cycle Analysis of Pipeline Samples -- 4.5.1 Oil Pipelines -- 4.5.2 Gas Pipelines -- 4.6 Conclusion -- References. ; 5 Operation Condition Monitoring for Pipeline -- 5.1 Introduction -- 5.2 Methodology -- 5.2.1 Method for Detecting Changes in Operational States -- 5.2.2 Characteristic Representation -- 5.2.3 Operational State Recognition Method -- 5.3 Case Study -- 5.3.1 Operational State Detection -- 5.3.2 Recognition of Pipeline Operational State on Single Station -- 5.4 Conclusion -- References -- 6 Operation Condition Prediction for Pipeline -- 6.1 Introduction -- 6.2 Methodology -- 6.2.1 Autoencoder -- 6.2.2 Stacked Autoencoder -- 6.3 Data Cleaning -- 6.4 Case Study -- 6.5 Conclusion -- References -- 7 Intelligent Inspection for Pipeline System -- 7.1 Inspection of Oil and Gas Pipelines -- 7.2 Mathematical Model for UAV Path Planning -- 7.2.1 Preliminaries -- 7.2.2 Objective Function -- 7.2.3 Constraints -- 7.3 Two-Stage Solution Methodology -- 7.3.1 First-Stage Solution -- 7.3.2 Second-Stage Solution -- 7.4 Case Study -- 7.5 Conclusions -- References -- 8 Probabilistic Safety Analysis in Complex Pipeline Systems -- 8.1 Evaluation of Natural Gas Pipeline Networks for Supply Reliability -- 8.2 Mathematical Model for Reliability Evaluation -- 8.2.1 Evaluating the Likelihood of Unit Failure -- 8.2.2 Creation of a Stochastic Capacity Network Model -- 8.2.3 Establishment of the Methodology for Capacity Analysis -- 8.2.4 Supply Reliability Assessment of Natural Gas Pipeline Network -- 8.3 Case Study -- 8.4 Conclusions -- References -- 9 Risk Prewarning Method for Pipeline Systems -- 9.1 Risk Prewarning of Oil and Gas Pipelines -- 9.2 Methodology -- 9.2.1 Probabilistic Forecasting Model -- 9.2.2 Dynamic Model of IES -- 9.2.3 Modeling of System Functional States -- 9.2.4 Supply Reliability Analysis -- 9.3 Case Study -- 9.3.1 Data Description -- 9.3.2 Description of the IES Model -- 9.3.3 Results and Discussion -- 9.4 Conclusions -- References. ; 10 Fault Detection and Diagnose Method for Pressurization Devices -- 10.1 Safety of Oil and Gas Pipeline System -- 10.2 Description of the Mathematical Model -- 10.2.1 Modeling the Pipeline System -- 10.2.2 Supply Capacity Calculation -- 10.2.3 Probabilistic Model for Pipeline System -- 10.3 Maintenance Optimization Based on RL -- 10.3.1 Modeling the Maintenance Optimization Problem -- 10.3.2 DRL-Based Maintenance Management Framework -- 10.4 Validation for the Proposed Method -- 10.4.1 Parameters for Pipeline System -- 10.4.2 Results Analysis -- 10.5 Conclusion -- References -- 11 Intelligent Leakage Detection for Pipelines -- 11.1 Pipeline Leakage Detection -- 11.2 Intelligent Algorithm for Pipeline Leakage Detection -- 11.2.1 Description of the Generative Adversarial Networks -- 11.2.2 The Variants GANs -- 11.3 The Proposed GANs Intelligent Framework for Leakage Detection -- 11.4 Pipeline Leakage Experiments -- 11.4.1 Leakage Data Description -- 11.4.2 Evaluation Metrics -- 11.4.3 Pipeline Leakage Cases -- 11.5 Experimental Conclusion of Pipeline Leakage Detection -- References -- 12 Smart Emergency Management of Pipeline System -- 12.1 Emergency Management -- 12.2 Emergency Scheduling -- 12.3 Mathematical Method -- 12.3.1 Mathematical Model -- 12.3.2 Solving Method -- 12.3.3 Robust Optimization -- 12.4 Case Study -- 12.4.1 Basic Data -- 12.4.2 Case 1 -- 12.4.3 Case 2 -- 12.5 Conclusion -- References.
• Titolo autorizzato: Advanced Intelligent Pipeline Management Technology
• ISBN: 981-19-9899-X
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910770277103321
• Lo trovi qui: Univ. Federico II