Observations of Site Amplification and Liquefaction in the Jun 23, 2001, Southern Peru Earthquake

The Mw 8.4 Southern Peru Earthquake of June 23, 2001 caused extensive damage in a widespread area in southern Peru and northern Chile, including several important population centers. Damage in some of these cities was correlated with local soil conditions and topography, suggesting the influence of local site amplification effects in damage distributions. The earthquake caused numerous instances of other types of geotechnical related ground failures, including liquefaction and lateral spreads in river valleys, seismic compression of highway fills, and slope failures. This work focuses on case histories documenting site amplification and liquefaction in the Southern Peru earthquake. Among the liquefaction events observed in this earthquake, the liquefaction of a heap-leach pad is the first reported failure of its type in a seismic event

Propuesta de demanda sísmica continua para códigos: Alejándonos de VS30

En este artículo se discuten las falencias de un sistema de diseño sísmico basado en una clasificación discreta de la amplificación de sitio. Se muestra que el promedio de velocidades de onda de corte en los primeros 30 metros es un buen estimador de la amplificación de sitio pero no para todos los periodos espectrales. Es interesante notar que para periodos bajos, la amplificación está mejor correlacionada con promedios de velocidad de onda de corte más superficiales, es decir, con menos información obtenemos mejores resultados. Finalmente, se presenta una propuesta preliminar para utilizar distintos promedios de velocidad de onda de corte en la amplificación de sito. Esta metodología evita que para dos sitios con ligeras diferencias, puedan considerarse demandas significativamente diferentes, con efectos deseables en seguridad y economí

Developing a model for the prediction of ground motions due to earthquakes in the Groningen gas field

AbstractMajor efforts are being undertaken to quantify seismic hazard and risk due to production-induced earthquakes in the Groningen gas field as the basis for rational decision-making about mitigation measures. An essential element is a model to estimate surface ground motions expected at any location for each earthquake originating within the gas reservoir. Taking advantage of the excellent geological and geophysical characterisation of the field and a growing database of ground-motion recordings, models have been developed for predicting response spectral accelerations, peak ground velocity and ground-motion durations for a wide range of magnitudes. The models reflect the unique source and travel path characteristics of the Groningen earthquakes, and account for the inevitable uncertainty in extrapolating from the small observed magnitudes to potential larger events. The predictions of ground-motion amplitudes include the effects of nonlinear site response of the relatively soft near-surface deposits throughout the field.</jats:p

Characterisation of ground motion recording stations in the Groningen gas field

The seismic hazard and risk analysis for the onshore Groningen gas field requires information about local soil properties, in particular shear-wave velocity (VS). A fieldwork campaign was conducted at 18 surface accelerograph stations of the monitoring network. The subsurface in the region consists of unconsolidated sediments and is heterogeneous in composition and properties. A range of different methods was applied to acquire in situ VS values to a target depth of at least 30 m. The techniques include seismic cone penetration tests (SCPT) with varying source offsets, multichannel analysis of surface waves (MASW) on Rayleigh waves with different processing approaches, microtremor array, cross-hole tomography and suspension P-S logging. The offset SCPT, cross-hole tomography and common midpoint cross-correlation (CMPcc) processing of MASW data all revealed lateral variations on length scales of several to tens of metres in this geological setting. SCPTs resulted in very detailed VS profiles with depth, but represent point measurements in a heterogeneous environment. The MASW results represent VS information on a larger spatial scale and smooth some of the heterogeneity encountered at the sites. The combination of MASW and SCPT proved to be a powerful and cost-effective approach in determining representative VS profiles at the accelerograph station sites. The measured VS profiles correspond well with the modelled profiles and they significantly enhance the ground motion model derivation. The similarity between the theoretical transfer function from the VS profile and the observed amplification from vertical array stations is also excellent

Ground-motion prediction models for induced earthquakes in the Groningen gas field, the Netherlands

Small-magnitude earthquakes induced by gas production in the Groningen field in the Netherlands have prompted the development of seismic risk models that serve both to estimate the impact of these events and to explore the efficacy of different risk mitigation strategies. A core element of the risk modelling is ground-motion prediction models (GMPM) derived from an extensive database of recordings obtained from a dense network of accelerographs installed in the field. For the verification of damage claims, an empirical GMPM for peak ground velocity (PGV) has been developed, which predicts horizontal PGV as a function of local magnitude, ML; hypocentral distance, Rhyp; and the time-averaged shear-wave velocity over the upper 30 m, VS30. For modelling the risk due to potential induced and triggered earthquakes of larger magnitude, a GMPM for response spectral accelerations has been developed from regressions on the outputs from finite-rupture simulations of motions at a deeply buried rock horizon. The GMPM for rock motions is coupled with a zonation map defining frequency-dependent non-linear amplification factors to obtain estimates of surface motions in the region of thick deposits of soft soils. The GMPM for spectral accelerations is formulated within a logic-tree framework to capture the epistemic uncertainty associated with extrapolation from recordings of events of ML ≤ 3.6 to much larger magnitudes

Ground-motion prediction models for induced earthquakes in the Groningen gas field, the Netherlands

Small-magnitude earthquakes induced by gas production in the Groningen field in the Netherlands have prompted the development of seismic risk models that serve both to estimate the impact of these events and to explore the efficacy of different risk mitigation strategies. A core element of the risk modelling is ground-motion prediction models (GMPM) derived from an extensive database of recordings obtained from a dense network of accelerographs installed in the field. For the verification of damage claims, an empirical GMPM for peak ground velocity (PGV) has been developed, which predicts horizontal PGV as a function of local magnitude, ML; hypocentral distance, Rhyp; and the time-averaged shear-wave velocity over the upper 30 m, VS30. For modelling the risk due to potential induced and triggered earthquakes of larger magnitude, a GMPM for response spectral accelerations has been developed from regressions on the outputs from finite-rupture simulations of motions at a deeply buried rock horizon. The GMPM for rock motions is coupled with a zonation map defining frequency-dependent non-linear amplification factors to obtain estimates of surface motions in the region of thick deposits of soft soils. The GMPM for spectral accelerations is formulated within a logic-tree framework to capture the epistemic uncertainty associated with extrapolation from recordings of events of ML ≤ 3.6 to much larger magnitudes

Event generators for high-energy physics experiments

We provide an overview of the status of Monte-Carlo event generators for high-energy particle physics. Guided by the experimental needs and requirements, we highlight areas of active development, and opportunities for future improvements. Particular emphasis is given to physics models and algorithms that are employed across a variety of experiments. These common themes in event generator development lead to a more comprehensive understanding of physics at the highest energies and intensities, and allow models to be tested against a wealth of data that have been accumulated over the past decades. A cohesive approach to event generator development will allow these models to be further improved and systematic uncertainties to be reduced, directly contributing to future experimental success. Event generators are part of a much larger ecosystem of computational tools. They typically involve a number of unknown model parameters that must be tuned to experimental data, while maintaining the integrity of the underlying physics models. Making both these data, and the analyses with which they have been obtained accessible to future users is an essential aspect of open science and data preservation. It ensures the consistency of physics models across a variety of experiments

Event generators for high-energy physics experiments

We provide an overview of the status of Monte-Carlo event generators for high-energy particle physics. Guided by the experimental needs and requirements, we highlight areas of active development, and opportunities for future improvements. Particular emphasis is given to physics models and algorithms that are employed across a variety of experiments. These common themes in event generator development lead to a more comprehensive understanding of physics at the highest energies and intensities, and allow models to be tested against a wealth of data that have been accumulated over the past decades. A cohesive approach to event generator development will allow these models to be further improved and systematic uncertainties to be reduced, directly contributing to future experimental success. Event generators are part of a much larger ecosystem of computational tools. They typically involve a number of unknown model parameters that must be tuned to experimental data, while maintaining the integrity of the underlying physics models. Making both these data, and the analyses with which they have been obtained accessible to future users is an essential aspect of open science and data preservation. It ensures the consistency of physics models across a variety of experiments