This book explores the innovative use of small unmanned aircraft systems (sUAS)-commonly known as drones-for methane emissions monitoring (i.e., detection, localization, and quantification) by introducing smart sensing frameworks and digital twin technology.
This book explores the innovative use of small unmanned aircraft systems (sUAS)-commonly known as drones-for methane emissions monitoring (i.e., detection, localization, and quantification) by introducing smart sensing frameworks and digital twin technology.
Derek Hollenbeck earned his Ph.D. in Mechanical Engineering in 2023 at the University of California, Merced. His research interests are in digital twins, fluid mechanics, controls, fractional calculus, and cyber physical systems using small unmanned aerial systems with applications in methane leak detection and quantification. YangQuan Chen is a professor at the University of California Merced, US. His research interests include mechatronics for sustainability, digital twins, small multi-UAV, applied fractional calculus. His recent publication with CRC Press includes Fractional Calculus for Skeptics I: The Fractal Paradigm.
Inhaltsangabe
Section I: From Detection to Quantification: sUAS-based Methane Sensing Techniques 1. The Methane Sensing Problem 2. Emission Source Detection 3. Emission Source Localization 4. Emission Source Quantification 5. Case Studies: LDAQ with sUAS Section II: Embedding Smartness to the Emission Source Determination Problem Solutions 6. Digital Twin Framework 7. Case Studies: Digital Twins 8. Smart Sensing, Sensor Placement, and the Observability Gramian 9. Case Studies: Smart Sensing 10. Conclusions and Best Practices
Section I: From Detection to Quantification: sUAS-based Methane Sensing Techniques 1. The Methane Sensing Problem 2. Emission Source Detection 3. Emission Source Localization 4. Emission Source Quantification 5. Case Studies: LDAQ with sUAS Section II: Embedding Smartness to the Emission Source Determination Problem Solutions 6. Digital Twin Framework 7. Case Studies: Digital Twins 8. Smart Sensing, Sensor Placement, and the Observability Gramian 9. Case Studies: Smart Sensing 10. Conclusions and Best Practices
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