Executive summary: The physical properties of rocks and minerals, particularly their density and elasticity, control the velocitywith which they transmit seismic waves. The acoustic impedance, which is the product of density and seismic velocity, is a useful property to characterize different lithologies. Available data indicates that there are strong contrasts in acoustic impedance between common types of rock and, most importantly, between common rocks and ore minerals. These differences provide a basis for relating passive seismic tomographic models with models based on geological and previously acquired geophysical data.
PACIFIC develops mineral exploration techniques that have a relatively low impact on the environment. This document is an assessment of this impact, but also of the environmental footprint of all activities related to the project. PACIFIC environmental footprint is still significant because of plane travels linked to transnational meetings. Learn more about it by reading the following document.
Executive summary: One of the PACIFIC’s goals is to support the European Innovation Partnership (EIP) on Raw Materials with its aim to translate its mission into concrete actions. To do so, PACIFIC will collaborate closely with the existing, recently finished or future H2020 projects funded under the same or similar topics.
This document includes a concrete plan for clustering with these projects, aiming to facilitate planning of joint online and physical events, sharing results and exchanging on the difficulties encountered.
The clustering plan is divided in three main sections:
This clustering plan will be considered as a living document to be reviewed in each General Assembly meeting to monitor the progress made in its implementation and allow for regular updates to take into account the evolving European context and prioritisation.
Understanding Seismic Waves Generated by Train Traffic via Modeling: Implications for Seismic Imaging and Monitoring.
Trains are now recognized as powerful sources for seismic interferometry based on noise correlation, but the optimal use of these signals still requires a better understanding of their source mechanisms. Here, we present a simple approach for modeling train‐generated signals inspired by early work in the engineering community, assuming that seismic waves are emitted by sleepers regularly spaced along the railway and excited by passing train wheels. Our modeling reproduces well seismological observations of tremor‐like emergent signals and of their harmonic spectra. We illustrate how these spectra are modulated by wheel spacing, and how their high‐frequency content is controlled by the distribution of axle loads over the rail, which mainly depends on ground stiffness beneath the railway. This is summarized as a simple rule of thumb that predicts the frequency bands in which most of train‐radiated energy is expected, as a function of train speed and of axle distance within bogies. Furthermore, we identify two end‐member mechanisms—single stationary source versus single moving load—that explain two types of documented observations, characterized by different spectral signatures related to train speed and either wagon length or sleeper spacing. In view of using train‐generated signals for seismic applications, an important conclusion is that the frequency content of the signals is dominated by high‐frequency harmonics and not by fundamental modes of vibrations. Consequently, most train traffic worldwide is expected to generate signals with a significant high‐frequency content, in particular in the case of trains traveling at variable speeds that produce truly broadband signals. Proposing a framework for predicting train‐generated seismic wavefields over meters to kilometers distance from railways, this work paves the way for high‐resolution passive seismic imaging and monitoring at different scales with applications to near‐surface surveys (aquifers, civil engineering), natural resources exploration, and natural hazard studies (landslides, earthquakes, and volcanoes).
The accepted version and the supplementary material can be downloaded as a compressed file from this webpage.
The link to the published version is provided below as well.
Download PACIFIC poster presented at the American Geophysical Union (AGU) in Washington DC (10-14 December 2018)
https://www.pacific-h2020.eu/wp-content/uploads/PACIFIC-poster.pdf
Executive summary:
This report details the design and result of a computer-based behavioural experiment to gauge how the format of information provided to the public affects their understanding and perception of mining[1]related activities. The experiment was undertaken by the Economic and Social Research Institute (ESRI – third party to GSI) in fulfilment of Deliverable 6.2, as part of WP6 of PACIFIC (Social acceptance & perception of risk for mining activities).
The design of the experiment was informed by a previous evaluation of currently used mining-related communication materials (Deliverable 6.1), as well as the broader social science and psychology literature. Insights gained from the results will be used to inform the design of follow-on experiments and will be used to generate recommendations for future communications (Deliverable 6.3).
The PACIFIC symposium and Kallak Workshop will take place on 27-28 October 2021 at the Killian Amphitheater of the Earth Science Institute (ISTerre). ISTerre is located on the campus of the University of Grenoble-Alpes (UGA) in Saint-Martin d’Hères/Gières, France.
It is expected that participants will attend on site but please note that the PACIFIC final events can also be attended online. All participants are invited to register using the link to the dedicated registration platform (below, see URL section). The program and the logistic pack are also available from the registration platform.
Deadline to register: Monday 11th October 2021 at the latest
Sometimes noise is incredibly helpful.
By Rahul Rao, Popular Science (January 28, 2021)
For the full article, please visit How trains can help scientists study what's underground | Popular Science (popsci.com)
No recommendations