Schlagwort(e):
Geophysics-Technique.
;
Electronic books.
Materialart:
Online-Ressource
Seiten:
1 online resource (323 pages)
Ausgabe:
1st ed.
ISBN:
9781119723066
Serie:
Geophysical Monograph Series
URL:
https://ebookcentral.proquest.com/lib/geomar/detail.action?docID=6871315
DDC:
621.3678
Sprache:
Englisch
Anmerkung:
Cover -- Title Page -- Copyright Page -- Contents -- Chapter 1 Principles of Muography and Pioneering Works -- 1.1 INTRODUCTION -- 1.2 PRINCIPLEs OF MUOGRAPHY -- 1.2.1 Muon Energy Spectrum -- 1.2.2 Geomagnetic Effects in the Muon Flux -- 1.2.3 Altitudinal Atmospheric Effects in the Muon Flux -- 1.2.4 Seasonal Atmospheric Effect in the Muon Flux -- 1.2.5 Muon Flux Reduction through Matter -- 1.2.6 Muon Scattering -- 1.2.7 Background Events in Muography -- 1.2.8 Required Measurement Times -- 1.2.9 Muographically Averaged Densimetric Thickness and Muographically Averaged Geometric Thickness -- 1.2.10 Limitations of Muography and Potential Geological Targets -- 1.3 PIONEERING WORKS -- 1.3.1 Early Works -- 1.3.2 Magmatic Convection -- 1.3.3 Phreatic Explosions and Magmatic Eruptions -- 1.3.4 Plate Tectonics and Volcanism -- 1.3.5 Underground Water -- 1.4 CONCLUSIONS -- REFERENCES -- Part I Muographic Image Processing -- Chapter 2 Tomographic Imaging of Volcano Structures with Cosmic-Ray Muons -- 2.1 INTRODUCTION -- 2.2 LINEAR INVERSION -- 2.3 FILTERED BACK PROJECTION -- 2.4 PERFORMANCE ESTIMATION WITH A FORWARD MODELING SIMULATION -- 2.5 RESULTS -- 2.6 DISCUSSION -- 2.7 CONCLUSIONS -- ACKNOWLEDGEMENTS -- REFERENCES -- Chapter 3 Joint Inversion of Muography and Gravity Data for 3D Density Imaging of Volcanoes -- 3.1 INTRODUCTION -- 3.2 GRAVITY MEASUREMENTS -- 3.3 LINEAR JOINT INVERSION -- 3.4 MORE EXACT FORMULATION -- 3.5 DENSITY BIAS -- 3.6 REGULARIZATION PARAMETERS -- 3.7 DISCUSSION -- 3.8 SUMMARY -- REFERENCES -- Chapter 4 Machine Learning with Muographic Images as Input: An Application to Volcano Eruption Forecasting -- 4.1 INTRODUCTION -- 4.1.1 The Concept of Machine Learning -- 4.1.2 Volcano Eruption Forecasting With Machine Learning -- 4.2 MUOGRAPHIC OBSERVATION OF THE SAKURAJIMA VOLCANO.
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4.3 A CONCEPTUALIZATION OF VOLCANO ERUPTION FORECASTING WITH MUOGRAPHY -- 4.4 MUOGRAPHIC DATA PROCESSING WITH MACHINE LEARNING -- 4.4.1 Processing of Average Fluxes with Support Vector Machine -- 4.4.2 Processing of Average Fluxes with Neural Network -- 4.4.3 Muographic Image Processing With Convolutional Neural Network -- 4.5 DISCUSSION -- ACKNOWLEDGEMENTS -- REFERENCES -- Part II Muography for Volcanic Investigations -- Chapter 5 Observation of the Dynamics of Hydrothermal Activity in La Soufrière of Guadeloupe Volcano with Joint Muography, Gravimetry, Electrical Resistivity Tomography, Seismic and Temperature Monitoring -- 5.1 INTRODUCTION -- 5.2 MUOGRAPHY FOR VOLCANO APPLICATIONS -- 5.2.1 Field Implementation and Maintenance -- 5.2.2 Resolution in Density, Time, and Space -- 5.2.3 Perturbing Effects -- 5.3 STRUCTURAL IMAGING OF HYDROTHERMAL RESERVOIRS IN LA SOUFRIÈRE LAVA DOME WITH JOINT MUOGRAPHY, ERT, AND GRAVIMETRY -- 5.3.1 Muography -- 5.3.2 Electrical Resistivity Tomography (ERT) -- 5.3.3 Gravity Survey -- 5.4 FUNCTIONAL IMAGING OF SUDDEN HYDROTHERMAL EVENTS WITH JOINT MUOGRAPHY, SEISMIC NOISE, AND FUMAROLE TEMPERATURE -- 5.4.1 Temperature at Fumaroles -- 5.4.2 Seismic Noise Measurements -- 5.4.3 Muography Experiment -- 5.4.4 Dynamics of the Shallow Hydrothermal System -- 5.5 CONCLUSION -- ACKNOWLEDGEMENTS -- REFERENCES -- Chapter 6 Structure of the Shallow Supply System at Stromboli Volcano, Italy, through Integration of Muography, Digital Elevation Models, Seismicity, and Ground Deformation Data -- 6.1 INTRODUCTION -- 6.2 ERUPTIVE ACTIVITY, MORPHOLOGY OF THE SHALLOW FEEDER SYSTEM, AND ERUPTION DYNAMICS -- 6.3 DIFFERENT TECHNIQUES FOR THE CRATER ZONE STUDY -- 6.3.1 Muography Measurements -- 6.3.2 Estimation of Filling Volumes through DEMs Comparison -- 6.3.3 GBInSAR: Deformation of the Crater Zone and of the Sciara Del Fuoco.
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6.3.4 Seismic Data -- 6.4 DISCUSSION -- 6.5 CONCLUDING REMARKS -- ACKNOWLEDGEMENTS -- REFERENCES -- Chapter 7 Three Years of Muography at Mount Etna, Italy: Results and Interpretation -- 7.1 INTRODUCTION -- 7.2 THE MEV PROJECT -- 7.2.1 Design and Construction of the Muon Telescope -- 7.2.2 Front-End and Readout Electronics -- 7.2.3 Time-Of-Flight Module -- 7.3 DATA COLLECTION AND ANALYSIS -- 7.4 IMPROVEMENT OF BACKGROUND REJECTION -- 7.5 OBSERVATION OF THE COLLAPSE OF NORTHEAST CRATER OF ETNA -- 7.6 CONCLUSIONS -- REFERENCES -- Chapter 8 Muography of Magma Intrusion Beneath the Active Craters of Sakurajima Volcano, Japan -- 8.1 INTRODUCTION -- 8.1.1 Remote Sensing of Subsurface Volcanic Phenomena -- 8.1.2 Eruptive Activity of Sakurajima Volcano -- 8.1.3 The Sakurajima Muography Observatory -- 8.2 OBSERVATIONAL INSTRUMENT AND METHODS -- 8.2.1 The MWPC-based Muography Observation System -- 8.2.2 Data Collection -- 8.2.3 Track Reconstruction and Flux Calculation -- 8.2.4 Density Imaging -- 8.2.5 Systematic Effects -- 8.3 VOLCANOLOGICAL IMPLICATIONS -- 8.4 CONCLUSIONS -- ACKNOWLEDGEMENTS -- REFERENCES -- Chapter 9 Muography of the Volcanic Structure of the Summit of Vesuvius, Italy -- 9.1 INTRODUCTION -- 9.1.1 Morphology and Structure of the ``Gran Cono´´ of Vesuvius -- 9.1.2 Motivation for Application of Muography to Vesuvius -- 9.2 MUOGRAPHY EXPERIMENTS AT VESUVIUS -- 9.2.1 The MURAVES Laboratory at Vesuvius -- 9.2.2 The MURAVES Detector -- 9.3 EXPECTED RESULTS -- 9.3.1 Status of the Experiment -- 9.4 SUMMARY -- ACKNOWLEDGEMENTS -- REFERENCES -- Part III Muography for Environmental Applications -- Chapter 10 Water Resource Management: The Multi-Technique Approach of the Low Background Noise Underground Research Laboratory and its Muon Detection Projects -- 10.1 INTRODUCTION -- 10.1.1 Underground Water Resources: A Societal Challenge.
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10.1.2 Particular Interest of Karst Environment -- 10.2 The Low Background Noise Underground Research Laboratory -- 10.3 WATER MONITORING AT LSBB -- 10.3.1 Fontaine-de-Vaucluse -- 10.3.2 First Characterization -- 10.3.3 Ongoing and Future Research -- 10.4 DETECTION OF COSMIC RAYS AT LSBB -- 10.4.1 Cosmic Ray Characterization for Background Noise Reduction -- 10.4.2 Muons as Primary Source of Information -- 10.5 MUON SURVEY TOMOGRAPHY BASED ON MICROMEGAS DETECTORS FOR UNREACHABLE SITES TECHNOLOGY -- 10.5.1 Purpose -- 10.5.2 Working Principle -- 10.5.3 Technology Update -- 10.6 AN EXAMPLE OF MULTI-TECHNIQUE APPROACH: THE BUISSONNIÈRE EXPERIMENT -- 10.6.1 Introduction -- 10.6.2 Study Area -- 10.6.3 Muon Detector and Experiment -- 10.6.4 Preliminary Results and Interpretation -- 10.6.5 Conclusion and Future Outlook -- 10.7 CONCLUSIONS -- ACKNOWLEDGEMENTS -- REFERENCES -- Chapter 11 Exploration of Underground Cave Systems with Muography -- 11.1 UNDERGROUND CHALLENGE -- 11.2 LIGHTWEIGHT GASEOUS DETECTORS -- 11.3 DATA ACQUISITION SYSTEMS -- 11.4 REFERENCE AND ROCK DENSITY -- 11.5 CAVE MUOGRAPHY CAMPAIGNS IN HUNGARY -- 11.6 TOMOGRAPHY AND INVERSION -- 11.7 CONCLUSION -- ACKNOWLEDGEMENTS -- REFERENCES -- Chapter 12 Detection and 3D Reconstruction of Cavities Inside Mount Echia, Naples, Italy -- 12.1 INTRODUCTION -- 12.2 THE MUON DETECTORS -- 12.3 MUON TRANSMISSION IN TWO DIMENSIONS -- 12.4 3D RECONSTRUCTION OF THE HIDDEN CAVITY -- 12.5 HINTS FROM CONVENTIONAL METHODS -- 12.6 SUMMARY AND OUTLOOK -- ACKNOWLEDGEMENTS -- REFERENCES -- Chapter 13 Exploration of Hidden Topography Beneath Alpine Glaciers with Muography -- 13.1 INTRODUCTION -- 13.2 DETECTORS -- 13.2.1 Emulsion Films -- 13.2.2 Automated Readout Microscopes -- 13.3 DATA ANALYSIS -- 13.3.1 Muon Energy Spectrum -- 13.3.2 Muon Flux -- 13.3.3 Bedrock Shape Reconstruction.
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13.4 RECONSTRUCTED BEDROCK TOPOGRAPHY -- 13.5 CONCLUSIONS -- REFERENCES -- Chapter 14 Muography, a Key Technology for Monitoring Carbon Geostorage -- 14.1 INTRODUCTION -- 14.1.1 Carbon Capture and Storage -- 14.1.2 Test Site -- 14.2 CARBON GEOSTORAGE MODELING -- 14.3 MUON FLUX MODELING AND FORECASTS -- 14.3.1 Muon Energy Spectrum at the Surface of the Earth -- 14.3.2 Muon Transport Through Rock -- 14.3.3 Simulation Procedure -- 14.3.4 Detector Simulation -- 14.3.5 Simulation Results -- 14.4 INSTRUMENTATION -- 14.4.1 Detector Deployment and Testing -- 14.5 OUTLOOK FOR CARBON CAPTURE AND STORAGE (CCS) -- 14.5.1 Routes toward Carbon Storage -- 14.5.2 Political Levers -- 14.6 CONCLUSION -- ACKNOWLEDGEMENTS -- REFERENCES -- Chapter 15 Future Prospects of Muography for Geological Research and Geotechnical and Mining Engineering -- 15.1 INTRODUCTION -- 15.2 MUONS, TERMS, AND MUON DETECTORS -- 15.3 BASICS OF MUOGRAPHY AND WHY IT WORKS IN GEOSCIENCES AND ENGINEERING -- 15.4 CURRENT AND NEAR-FUTURE APPLICATIONS IN GEOLOGICAL RESEARCH AND ENGINEERING -- 15.4.1 Applications in Mineral Exploration -- 15.4.2 Applications in Geotechnical and Mining Engineering -- 15.5 IMPACT ON DRILLING AND GEOLOGICAL AND GEOTECHNICAL RESEARCH -- 15.6 CONCLUDING REMARKS AND FUTURE DIRECTIONS -- REFERENCES -- Chapter 16 Muon Tomography for Underground Resources -- 16.1 INTRODUCTION -- 16.2 GEOPHYSICAL CONSIDERATIONS -- 16.2.1 Modeling the Sea-Level Muon Spectrum -- 16.2.2 Muon Interactions in Rock -- 16.2.3 Tomography -- 16.3 CASE STUDIES -- 16.3.1 Myra Falls Zinc Mine -- 16.3.2 Pend Oreille Lead/Zine Mine -- 16.3.3 McArthur River Uranium Mine -- 16.3.4 Cliffs Nickel Mine -- 16.4 CONCLUSIONS -- REFERENCES -- Part IV Next Generation Muography -- Chapter 17 Development of Scintillator-Based Muon Detectors for Muography -- 17.1 INTRODUCTION.
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17.2 DETECTING MUONS: DIRECT AND INVERSE PROBLEM.
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