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Autor: Francesco Mulargia
ISBN-13: 9781402017780
Einband: Buch
Seiten: 338
Gewicht: 594 g
Format: 240x160x19 mm
Sprache: Englisch

Earthquake Science and Seismic Risk Reduction

Vol.32, NATO Science Series IV Earth and Environmental Sciences
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1 Modeling earthquakes.- 1.1 Phenomenology.- 1.1.1 The lack of a coherent phenomenology.- 1.2 Retrospective selection bias.- 1.2.1 Using statistics to find the 'truth'.- 1.2.2 Hypothesis testing.- 1.2.3 Data mining and fishing expeditions.- 1.2.4 Post hoc correction of optimal retrospective selections.- 1.2.5 The safest antidote to false discoveries: forward vahdation.- 1.3 Model building.- 1.3.1 Choosing among models.- 1.3.2 Deterministic, complex and stochastic cases.- 1.3.3 Complex systems.- 1.4 Prediction.- 1.4.1 Definitions of prediction.- 1.5 References.- 2 The classical view of earthquakes.- 2.1 A geologist's view of earthquakes.- 2.1.1 Geology, geomorphology and earthquakes.- 2.1.2 Paleontology and earthquakes.- 2.1.3 Petrology and earthquakes.- 2.1.4 Applied geology and seismic hazard.- 2.2 Seismology and geodesy.- 2.2.1 Introduction.- 2.2.2 Inversion for the Centroid and Moment Tensor (CMT).- 2.2.3 Geodetic constraints.- 2.2.4 Space-time history of faulting and physical implications.- 2.3 Scaling laws for earthquakes.- 2.3.1 The Gutenberg-Richter law.- 2.3.2 Empirical roots of the Gutenberg-Richter law.- 2.3.3 Moment-frequency relation.- 2.4 The elastic rebound model and its successors.- 2.4.1 The time-and slip-predictable models.- 2.4.2 The seismic gap hypothesis.- 2.4.3 The characteristic earthquake model.- 2.5 Nucleation or not?.- 2.5.1 Is there any evidence for a nucleation phase?.- 2.5.2 Models of a hypothetical preparatory process.- 2.5.3 Theoretical models.- 2.6 What is an earthquake? Fracture, slip or both?.- 2.6.1 Laboratory-based hypotheses.- 2.6.2 Stick-slip friction.- 2.6.3 Fracture mechanics.- 2.6.4 Damage mechanics.- 2.7 Stress: the basic yet unknown quantity.- 2.7.1 Stress in the Earth's crust.- 2.8 Earthquake energy balance.- 2.8.1 Earthquake energy function.- 2.8.2 Earthquakes as a three stage process.- 2.8.3 The size of the earthquake.- 2.9 References.- 3 The Physics of complex systems: appHcations to earthquake.- 3.1 Phase transitions, criticality, and self-similarity.- 3.1.1 Subcriticality and supercriticality.- 3.1.2 Universality.- 3.2 Scale invariance: the analytical approach.- 3.3 Scale invariance: the geometrical approach.- 3.3.1 Measuring an object's fractal dimension.- 3.3.2 Multifractals.- 3.3.3 The empirical origin of fractahty.- 3.3.4 Deterministic low-dimensional chaos: hope for predictability?.- 3.4 Characterizing scale-invariant systems.- 3.4.1 Log-log plots.- 3.4.2 Wavelets.- 3.5 Modeling scale invariant systems.- 3.5.1 Percolation.- 3.5.2 Cellular automata.- 3.5.3 Earthquakes as SOC.- 3.6 The origin of power laws and fractality.- 3.6.1 Scale invariance: artifacts and reality.- 3.6.2 Do power laws always mean geometrical scale invariance?.- 3.6.3 General features of self-organizing cellular automata earth- quake models.- 3.7 Problems in applying CA models to earthquakes.- 3.8 Dynamical implications.- 3.8.1 Intermittent criticality.- 3.8.2 Power law evolution before failure - Voight's law.- 3.9 Statistical implications.- 3.10 Implications for predictability.- 3.11 References.- 4 Time-independent hazard.- 4.1 Seismic Hazard assessment and site effects evaluation at regional scale.- 4.1.1 Seismic hazard estimates.- 4.1.2 Site effects estimates: how precise schould they be?.- 4.1.3 Conclusions.- 4.2 USGS and partners: approaches to estimating earthquake probabilities.- 4.2.1 Basic principles.- 4.2.2 Earthquake recurrence rates for national and international seismic hazard maps.- 4.2.3 San Francisco Bay region.- 4.2.4 Earthquake likelihood models in Southern California.- 4.2.5 The New Madrid Seismic Zone.- 4.2.6 Foreshocks and aftershocks.- 4.2.7 Conclusions.- 4.3 References.- 5 Time-dependent hazard estimates and forecasts, and their uncertainties.- 5.1 USGS and partners: research on earthquake probabilities.- 5.1.1 Physics, recurrence, and probabilities.- 5.1.2 Earthquake triggering.- 5.1.3 Conclusions.- 5.2 Probabilistic forecasting of seismicity.- 5.2.1 Long-term seismic hazard est
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What is the first thing that ordinary people, for whom journalists are the proxy, ask when they meet a seismologist? It is certainly nothing technical like "What was the stress drop of the last earthquake in the Imperial Valley?" It is a sim ple question, which nevertheless summarizes the real demands that society has for seismology. This question is "Can you predict earthquakes?" Regrettably, notwithstanding the feeling of omnipotence induced by modem technology, the answer at present is the very opposite of "Yes, of course". The primary motivation for the question "Can you predict earthquakes?" is practical. No other natural phenomenon has the tremendous destructive power of a large earthquake, a power which is rivaled only by a large scale war. An earth quake in a highly industrialized region is capable of adversely affecting the econ omy of the whole world for several years. But another motivation is cognitive. The aim of science is 'understanding' nature, and one of the best ways to show that we understand a phenomenon is the ability to make accurate predictions.
Autor: Francesco Mulargia
ISBN-13:: 9781402017780
ISBN: 1402017782
Verlag: Springer Netherlands, Springer, Berlin
Gewicht: 594g
Seiten: 338
Sprache: Englisch
Sonstiges: Buch, 240x160x19 mm