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Table of contents
General Introduction
1.1 Ground-motion prediction equations (GMPE)
1.1.1 Intensity measures (IMs)
1.1.2 How GMPEs are derived
1.1.3 Comments on site effects in GMPEs
1.1.4 GMPE residuals
1.2 Ground-motion prediction for reference rock conditions
1.2.1 The essence of Host-to-Target-Adjustments (HTTA)
1.2.2 Limitations of HTTA
1.2.3 Recent alternatives and advances concerning scaling ratios:
1.3 Site response estimations
1.3.1 Physical background
1.3.2 One-dimensional theoretical estimates
1.3.3 Empirical estimates
1.4 Scope of the work
2.1 Introduction
2.2 Data and observations
2.2.1 Observations
2.2.2 Measurements of VS perturbations and Geostatistical model validation
2.2.3 The geostatistical model proposed
2.3 KiK-net data, empirical estimations, and site signature
2.4 Tuning the model before application:
2.4.1 Quarter wavelength approximation
2.4.2 Sensitivity analyses of key parameters
2.5 Discussions:
2.5.1 An additional constraint to select randomized profiles
2.5.2 Statistical impact for selected sites
2.6 Conclusions
3.1 Introduction
3.2 About Generalized Inversion Techniques
3.2.1 Overview
3.2.2 Methodologies and inversion schemes involved in the benchmark
3.3 The datasets considered
3.4 Generalized inversions on synthetic and real data
3.4.1 Sanity check using a synthetic dataset
3.4.2 The two phases and the reference conditions
3.4.3 Results for the sparse regional dataset, the French Alps
3.4.4 Results for a dense regional dataset, the Central Italy dataset
3.5 Uncertainties associated with GIT results
3.5.1 Strategy for inter-method uncertainties characterization
3.5.2 Quantification of uncertainties
3.5.3 Possible origins of variability: regional Variations
3.6 Exploring the impact of the dataset size
3.7 Summary and conclusions
3.8 Perspectives
4.1 Introduction
4.2 KiK-net dataset adopted
4.2.1 Automated Onset detection
4.2.2 Selection of Ground Motion Recordings
4.2.3 Attenuation regionalization of Japan
4.3 Site response estimations
4.3.1 Empirical
4.3.2 Theoretical
4.3.3 Scales of the estimated functions
4.4 Spectral inversion techniques application
4.4.1 Highlights on the inversion method
4.4.2 Non-parametric attenuation:
4.5 Source and site separation with GIT
4.5.1 Reference site choice
4.5.2 Source results
4.5.3 Site results and some case studies
4.6 Discussions
4.6.1 Revising the 1D classification with absolute terms
4.6.2 Mean comparisons of relative and absolute site responses
4.6.3 Site response estimations using GIT
4.7 Conclusions
5.1 Introduction
5.2 KiK-net dataset explored
5.3 Deconvolution approach
5.4 GMPE functional form and first results
5.4.1 Fd scaling
5.4.2 Fm scaling
5.4.3 Fs scaling
5.4.4 Residuals check
5.5 Results
5.5.1 Model scaling
5.5.2 Variability analysis between SURF1D GMPEs
5.5.3 Variability analysis on SURFALL GMPEs
5.6 Discussions
5.6.1 Results in terms of rock to hard rock scaling
5.6.2 Comparison of amplification factors from recent GMPEs
5.7 Conclusions and perspectives
5.8 Acknowledgments
5.9 Supplements
References
