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Deformation Monitoring and Modeling Based on Lidar Data for Slope Stability Assessment Von Der Fakultät Für Georessourcen

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Deformation Monitoring and Modeling Based on Lidar Data for Slope Stability Assessment Von Der Fakultät Für Georessourcen Deformation monitoring and modeling based on LiDAR data for slope stability assessment Von der Fakultät für Georessourcen und Materialtechnik der Rheinisch -Westfälischen Technischen Hochschule Aachen zur Erlangung des akademischen Grades eines Doktors der Ingenieurwissenschaften genehmigte Dissertation vorgelegt von M.Sc. Hui Hu aus Zhejiang, China Berichter: Univ.-Prof. Dr.rer. nat. Dr.h.c. (USST) Rafig Azzam Univ.-Prof. Dr.-Ing. Herbert Klapperich Tag der mündlichen Prüfung: 29.Mai.2013 Diese Dissertation ist auf den Internetseiten der Hochschulbibliothek online verfügbar Abstract Time dependent deformation is a common process in soil slopes but never the less a challeng- ing task for stability assessment. Slope failure and the land subsidence originating not only from extensive constructions and mining but also due to geological processes are common problems, which adversely influence environment, human safety and economic development. In order to pursue an advanced methodology for management and mitigation of soil slope failure, such points as adequate monitoring technology, effective deformation recognition, re- liable numerical modeling, and precise slope stability analysis are important to be taken into account. Within this scope, terrestrial laser scanner (TLS) was adopted to collect high resolution point cloud data from a fresh cut high slope in sandy and clayey soils in an open pit mine. Therefore, four scanning campaigns have been conducted over a period of three months. A conversion tool to transfer a LiDAR data-based 3D geological model into a 3D geotechnical model for numerical simulation has been developed. Two sophisticated techniques, i.e. both maximum distance method and feature degree method, were proposed to recognize the slope displacement in mm resolution from the surface model. In an iterative process with numerous numerical forward simulations, presumed geotechnical parameters and resultant movements were investigated to find the suitable solutions of parameter combinations for the FE-model which enable to describe the observed deformation process. This allows to determine the factor of safety (FOS) for the slopes, through finite element slope stability analyses combined with automatic strength reduction technique, followed by time effect discussion which im- proves the reliability of determined FOS. i Kurzfassung Lockergesteinssedimente reagieren mit zeitabh¨angigenDeformationen, wenn sie durch Ein- schnitte entlastet werden. Diese Zeitabh¨angigheitstellt eine Herausforderung, wenn es um die stabilit¨atsbewertung geht. B¨oschungsbr¨uche und Bodensenkungen beispielsweise werden nicht nur durch tiefgreifende Bauvorhaben und Bergbauaktivit¨atenausgel¨ost,sondern auch durch geologische Setzungsprozesse. Sie stellen ein Problem dar, welches sich negativ auf die Umwelt, die Sicherheit des Menschen und die Okonomie¨ auswirkt. Mit der Ziel eine ad¨aquate Technik zur Bearbeitung und Schadensminderung von Versagensf¨allenin Lockergestein zu entwickeln, m¨ussenangemessene Uberwachungstechnologien,¨ wirksame Methoden zur Erken- nung von Deformationen, zuverl¨assigenumerische Modellierung und pr¨aziseHangstabilit¨ats- analysen kombiniert werden. In diesem Rahmen wurde terrestrisches Laserscanning (TLS) verwendet um multitemporale hochaufl¨osende,dreidimensionale Oberfl¨achendaten einer hohen, frisch geschnittenen Tage- baub¨oschung in sandig und tonigem Lockeregestein zu erhalten. Es wurden vier aufeinan- derfolgende Scanaufnahmen ¨uber einen Zeitraum von drei Monaten hinweg aufgenommen. Anschliessend wurde ein Programm erstellt, welches ein auf der Basis von TLS Daten er- stelltes geologisches Modell in ein geotechnisches Modell f¨urnumerische Simulationen trans- feriert. Dabei werden Methoden wie das maximale Entfernungsverfahren oder die Bestimmung des Ausmasses von geometrischen Kennzeichen verwendet, um aus den geologischen Modell B¨oschungsverformungen in mm Aufl¨osungzu erkennen. In einem iterativen Prozess werden durch gerichtete Optimierung die Kombination f¨urdie geotechnischen B¨oschungsparameter ermittelt, welche die beobachteten Verformungen in einem FE-Modell am besten beschreibt. So kann durch die Finite-Element Analysen mit automatischer Festigkeitsreduktion ein Sicher- heitsbeiwert f¨urdie zeitabh¨angigeB¨oschungsverformungen bestimmt werden. Dies erlaubt im Anschluss die Zuverl¨assigkeit des ermittelten Sicherheitsbeiwerts auch unter Ber¨ucksichtigung zeitabh¨angigerVerformungen zu bewerten. ii Acknowledgements My doctoral thesis at the Department of Engineering Geology and Hydrogeology, RWTH Aachen University, was prepared within the scope of the China State-Sponsored Post-graduate Study Abroad Program (2008640010), conducted with the great field support from Open Pit Hambach, RWE Power AG. Many thanks to the financial and field support. I would like to express my respects and gratitude to my first supervisor, Prof. Dr. Dr. h. c. Rafig Azzam, head of the Department of Engineering Geology and Hydrogeology (RWTH Aachen University, Germany), for the scientific illumination, great assistance and encourage- ment througout of this research and during my whole study period. His advice and discussion were provided to me to successfully complete this work, and his directions and encourage- ments lead me to clibming the peak of knowledge mountain. I would also like to thank Prof. Dr.-Ing. Herbert Klapperich, head of the Department of Soil Mechanics (Technische Universi- taet Bergakademie Freiberg, Germany), for co-supervising my thesis. And I am very grateful to Prof. Dr. rer. nat. Klaus Reicherter, head of the Department of Neotectonic and Natural Hazards (RWTH Aachen University, Germany), for chairing my dissertation defense. Many and special thanks go to Dr. Tomas M. Fernandez-Steeger for mentoring my doctoral study and providing a lot of meaningful discussions. I would also like to thank Dr. Christoph Neukum for many help during my study of this work. Many thanks go to all scientists and staff members at Department of Engineering Geology and Hydrogeology (RWTH Aachen University, Germany). In particular, I acknowledge my gratitude to Dr. Dieter Dahmen, Dr. Christian Karcher, and Mr. Werner Guder (Open Pit Hambach, RWE Power AG, Germany) for supporting me to be closely and directly acquainted with one of the biggest lignite open pit mine in the world. The discussions and suggestions from them are useful to complete this research. Many thanks also go to Mr. Peter Goellner and Mr. Tobias Meurer for the field survey at Open Pit Hambach (RWE Power AG, Germany). I would like to thank Mr. Yi Shengtu and Mr. Xun Wang for the great assist during the complex programming work. Last but not least, my deepest gratitude goes to my beloved parents and my wife for their endless, selfless support and encouragement during my study abroad. iii iv Contents List of Figures ix List of Tables xiii 1 Introduction 1 1.1 Motivation . .1 1.1.1 Deformation Monitoring in Open Pit Mine . .1 1.1.2 Slope Stability Analysis in Open Pit Mine . .2 1.2 Objectives . .3 1.3 Structure and Methodology . .4 2 State of the Art 7 2.1 Considerations in Open Pit Mine . .8 2.2 Monitoring Technology in Open Pit Mine . 11 2.2.1 GPS Technology . 12 2.2.2 InSAR Technology . 13 2.2.3 Wireless Sensor Networks . 14 2.2.4 Robotic Total Stations . 15 2.2.5 Underground Monitoring . 15 2.2.6 LiDAR Technology . 16 2.2.7 Discussions . 21 2.3 Slope Stability Analysis . 21 2.3.1 Limit Equilibrium Methods . 21 2.3.2 Plastic Limit Analysis . 24 2.3.3 Numerical Analysis Methods . 24 2.3.4 Discussions . 26 3 Overview of the Study Area and Field Investigation 31 3.1 Overview of the Study Area . 31 3.2 Production of Open Pit Hambach Mine . 32 3.3 Re-cultivation in Open Pit Hambach Mine . 33 3.4 Geological Settings . 34 3.4.1 Stratigraphy . 34 v CONTENTS 3.4.2 Lithology . 34 3.4.3 Tectonics . 35 3.5 Dewatering . 35 3.6 LiDAR Investigation . 36 4 Processing and Converting LiDAR Data 41 4.1 LiDAR Data Processing . 41 4.1.1 Introduction of PolyWorks . 42 4.1.2 LiDAR Data Pre-processing . 42 4.2 High-Resolution Body Model . 44 4.2.1 Introduction of Gocad . 44 4.2.2 Three-Dimensional Grid-Body Model . 44 4.3 Converting Body Model to Numerical Model . 45 4.3.1 Introduction of ABAQUS . 45 4.3.2 Two-Dimensional Model Conversion . 46 4.3.3 Three-Dimensional Model Conversion . 49 4.4 Case Study . 50 4.4.1 Two-Dimensional Slope Stability Analysis . 52 4.4.2 Three-Dimensional Slope Stability Analysis . 54 5 Deformation Analysis 59 5.1 Deformation Detection . 59 5.2 Multi-Temporal HRDEMs . 60 5.2.1 Global Coordinate System . 60 5.2.2 Description of Multi-Temporal Models . 63 5.3 Deformation Detection in Macro-View . 63 5.4 Deformation Detection in Micro-View . 66 5.4.1 Preparations . 67 5.4.2 Maximum Distance . 70 5.4.3 Feature Degree . 73 5.5 Deformation Analysis . 77 5.5.1 Change of Elevation of the Sixth Floor . 80 5.5.2 Deformation of Slope Surface . 80 5.5.3 Results and Discussions . 83 6 Numerical Simulations 89 6.1 Framework . 89 6.1.1 Methods of Back Analysis . 89 6.1.2 Mathematical Description of Deformation Back Analysis . 91 6.2 Evaluation of Geotechnical Parameters . 92 6.2.1 Description of the Monitored Slope . 92 vi CONTENTS 6.2.2 Initial Geo-stress . 93 6.2.3 Parametric Domain . 95 6.2.4 Pre-evaluation of Parameters . 99 6.3 Parameters Determination by BPNN . 102 6.3.1 Methodology of BPNN . 102 6.3.2 Samples Preparation . 104 6.3.3 Neural Networks Training and Testing . 107 6.3.4 Results and Discussions . 113 6.4 FEM Slope Stability Analysis . 115 6.4.1 3D Slope Numerical Model . ..
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