EARLI - Détection de signaux sismiques précoces en utilisant l'intelligence artificielle - ERC 2021
Detection od Early seismic signal using ARtificial Intelligence
Com2SiCa - COMprendre et SImuler les COMportements humains sur des territoires en situation de CAtastrophe
Understanding and Simulating Human Behaviors in Areas affected by Disasters
FAULTS R GEMS - Les propriétés des failles : vers une modélisation générique réaliste des tremblements de terre et une simulation des risques
Properties of FAULTS, a key to Realistic Generic Earthquake Modeling and hazard Simulation
INPOP et la recherche de la planète P9
Looking for P9 planet
E-POST -La déformation postsismique précoce
the Early POSTseismic Deformation
REMAKE - Risque sismique en Équateur : prévention, anticipation et connaissance des tremblements de terre
Seismic Risk in Ecuador: Mitigation, Anticipation and Knowledge of Earthquakes
While the past forty years have been affected by a significant increase in the number of disasters, they have also proved the intricacy of the events when numerous causes mingled together (physical, biological, technological and human causes). Those trends should not reverse over the coming years, for numerous risk factors remain: climate change, geopolitical strains, risks associated with technological development and the needs of human societies, population growth and poverty, environment degradation and urban pressure, etc. (URD, 2010). Modern societies, whatever their stages of development, are still inadequately prepared to cope with the intricacy and suddenness of disaster events, and become resilient. Populations often do not know how they should react or take action to protect themselves against a threat or danger (CEPRI, 2013). If some behaviors prove to be appropriate, some other ones, unfortunately more numerous (Boyd, 1981; ISI, 2012), turn out to be inappropriate (stunning, escape towards the danger zone, etc.) or clearly insane (curiosity, goods protection, etc.), as compared to the behaviors expected by the operational stakeholders (Quarantelli, 2008) and that are recommended in prevention tools. This partial misconception is not confined solely to populations and policy-makers; it also relates to the difficulties encountered by the research community in identifying the range of behavior patterns actually triggered in the face of a disaster (Crocq, 1994), their sequence, dynamics, and interdependence (Provitolo et al. 2015).
Decades of research on earthquakes have yielded meager prospects for earthquake predictability: we cannot predict the time, location and magnitude of a forthcoming earthquake with sufficient accuracy for immediate societal value. Therefore, the best we can do is to mitigate their impact by anticipating the most “destructive properties” of the largest earthquakes to come: longest extent of rupture zones, largest magnitudes, amplitudes of displacements, accelerations of the ground. This topic has motivated many studies in last decades. Yet, despite these efforts, major discrepancies still remain between available model outputs and natural earthquake behaviors. Here we argue that an important source of discrepancy is related to the incomplete integration of actual geometrical and mechanical properties of earthquake causative faults in existing rupture models.
To explain the unusual distribution of Kuiper Belt objects, several authors have advocated the existence of a super-Earth planet in the outer solar system.
It has recently been proposed that a 10 M⊕ object with an orbit of 700 AU semi major axis and 0.6 eccentricity can explain the observed distribution of Kuiper Belt objects around Sedna. Here A. Fienga, J. Laskar and their teams use the INPOP planetary ephemerides model as a sensor for testing for an additional body in the solar system.
We test the possibility of adding the proposed planet without increasing the residuals of the planetary ephemerides, fitted over the whole INPOP planetary data sample. We demonstrate that the presence of such an object is not compatible with the most sensitive data set, the Cassini radio ranging data, if its true anomaly is in the intervals [−130°:−100°] or [−65°:85°]. Moreover, we find that the addition of this object can reduce the Cassini residuals, with a most probable position given by a true anomaly v=117.8°(+11°/-10°).
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