Call number:
S 99.0139(375)
In:
Wissenschaftliche Arbeiten der Fachrichtung Geodäsie und Geoinformatik der Leibniz Universität Hannover
Type of Medium:
Series available for loan
Pages:
xii, 141 Seiten
,
Illustrationen, Diagramme
ISSN:
0174-1454
Series Statement:
Wissenschaftliche Arbeiten der Fachrichtung Geodäsie und Geoinformatik der Universität Hannover Nr. 375
Language:
English
Note:
Contents
Abstract
Zusammenfassung
List of Figures
List of Tables
Abbreviation
Contents
1 Introduction
1.1 Motivation
1.2 Proposal and content
2 State of art in terrestrial laser scanning and finite element analysis
2.1 General surface measurements and TLS
2.1.1 Surface measurement
2.1.2 Geometric measurements with TLS and its technical fundamentals
2.2 FEA computations
2.2.1 FEA
2.2.2 FEA computation and the description of the boundary domain
2.3 TLS application in FEA
2.3.1 FEA parameter calibration with TLS
2.3.2 FEA geometric boundary modeling with TLS
2.3.3 Benefits of combination between TLS and FEA
3 Finite element analysis parametric geometric modeling and calibration based on terrestrial laser scanning
3.1 Fundamentals of polynomial and B-spline fitting
3.1.1 Polynomial fitting
3.1.2 B-spline fitting
3.2 Other parametric methods in fitting point clouds
3.3 Analysis and comparison between polynomial and B-spline approximations
3.4 Implementation of the calibration cases
3.5 Validation based on deformation analysis
3.5.1 General methods in deformation computation and analysis for TLS
3.5.2 Case implementation
4 Sequential calibration of finite element analysis results with terrestrial laser scanning reference based on deep learning
4.1 Employment of DL in FEA
4.1.1 Direct outputs corresponding to inputs by training neural networks
4.1.2 Material model
4.1.3 Other problems
4.1.4 Summary and analysis
4.2 DL sequential prediction and its potential in FEA
4.3 LSTM methods based on sequential prediction
4.3.1 Challenges and advanced variant models of LSTM
4.3.2 Effects of activation functions in convolutional LSTM
4.4 Sequential prediction and calibration of FEA results with a TLS reference based on convolutional LSTM
5 Conclusions and outlook
Contributions of authors
Paper 1
Paper 2
Paper 3
Paper 4
Bibliography
Curriculum Vitae
Acknowledgment
Location:
Lower compact magazine
Branch Library:
GFZ Library
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