Inhalt

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   Abstract
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   Preface
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   Contents
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   List of figures
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   List of tables
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   I Data collection in hydraulic engineering
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  1 Introduction
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   1.1 The role of data
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   1.2 New challenges and developments
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   1.3 Aims and scope of this thesis
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  2 Classical methodology in hydraulic modeling
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  2.1 Laboratory models of free-surface flows
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   2.1.1 Introduction
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   2.1.2 Similitude
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   2.1.3 Froude's law
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   2.1.4 Open channels
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   2.1.5 Hydraulic structures
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  2.2 Classical flow depth and velocity sensors
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   2.2.1 General remarks
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   2.2.2 Flow depth sensors
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   2.2.3 Flow velocity sensors
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   2.3 Discussion
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   II Free-surface detection
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  3 Free-surface recognition by edge detection
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  3.1 Introduction to edge detection methods
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   3.1.1 General remarks
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   3.1.2 Principle of edge detection methods
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   3.1.3 2D kernels
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   3.1.4 Image preprocessing
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  3.2 Non-intrusive detection of air-water surface roughness in self-aerated chute flows
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   3.2.1 Introduction
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   3.2.2 Methodology
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   3.2.3 Non-intrusive detection of the air-water mixture surface
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   3.2.4 Ultrasonic sensor
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   3.2.5 Results
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   3.2.6 Surface wave frequencies
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   3.2.7 Conclusions
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  4 3D free-surface reconstruction
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  4.1 Introduction to depth cameras
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   4.1.1 General remarks
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   4.1.2 Time of flight
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   4.1.3 Structured light
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   4.1.4 Stereo vision
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  4.2 Turbulent free-surface monitoring with an RGB-D sensor: the hydraulic jump case
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   4.2.1 Introduction
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   4.2.2 Experimental setup
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   4.2.3 Results
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   4.2.4 Discussion
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   4.2.5 Conclusions
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  5 Discussion
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   5.1 Capacities and limitations of optical water depth measurements
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   5.2 Potential prototype applications
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   III Velocity determination
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  6 Particle (Bubble) Image Velocimetry
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   6.1 Introduction
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  6.2 Initial stage of two-dimensional dam-break waves: Laboratory vs. VOF
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   6.2.1 Introduction
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   6.2.2 Theoretical Background
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   6.2.3 Experimental setup and numerical model
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   6.2.4 Results and discussion
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   6.2.5 Conclusions
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  6.3 Non-intrusive measuring of air-water flow properties in self-aerated stepped spillway flow
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   6.3.1 Introduction
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   6.3.2 Methodology
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   6.3.3 Results
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   6.3.4 Summary and Outlook
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  6.4 Measuring void fraction and velocity fields of a stepped spillway for skimming flow using non-intrusive methods
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   6.4.1 Introduction
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   6.4.2 Experimental facility
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   6.4.3 Re-coding of the image processing procedure (IPP) for stepped spillways
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   6.4.4 Bubble image velocimetry for stepped spillways
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   6.4.5 Calibration routine for IPP and BIV
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   6.4.6 Validation
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   6.4.7 Results
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   6.4.8 Discussion
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   6.4.9 Conclusion
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  6.5 Improving BIV results through image preprocessing
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   6.5.1 Motivation
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   6.5.2 Methodology
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   6.5.3 Image processing techniques
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   6.5.4 Results
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   6.5.5 Conclusions
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  7 Optical Flow
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   7.1 Introduction
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   7.1.1 Lucas-Kanade method
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   7.1.2 Horn-Schunck method
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   7.1.3 Farnebäck method
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   7.1.4 Image pyramids
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  7.2 Application of the optical flow method to velocity determination in hydraulic structure models
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   7.2.1 Introduction
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   7.2.2 Methodology
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   7.2.3 Results
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   7.2.4 Wave breaking at artificial reef
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   7.2.5 Aerated stepped spillway flow
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   7.2.6 Conclusions
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  7.3 Optical flow estimation in aerated flows
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   7.3.1 Introduction
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   7.3.2 Experimental setup
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   7.3.3 Optical flow and image processing techniques
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   7.3.4 Results
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   7.3.5 Summary and conclusion
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  8 Discussion
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   8.1 Capacities and limitations of BIV and Optical Flow
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  8.2 Image processing techniques for velocity estimation in highly aerated flows: Bubble Image Velocimetry vs. Optical Flow
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   8.2.1 Introduction
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   8.2.2 Methodology
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   8.2.3 Imaging techniques
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   8.2.4 Results
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   8.2.5 Discussion and outlook
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   8.2.6 Summary and conclusions
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  8.3 Benchmarking with synthetic images
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   8.3.1 General remarks
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   8.3.2 Synthetic particle image generation
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   8.3.3 Stochastic particle displacement: simulating isotropic turbulence
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   8.3.4 Case studies
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   8.3.5 Processing
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   8.3.6 Results
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   8.3.7 Conclusions
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   IV Closure
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   9 Summary and conclusions
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   10 Future research needs
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   References