To understand the main properties of cement, a ubiquitous material, a sound description of its chemistry and mineralogy, including its reactivity in aggressive environments and its mechanical properties, is vital. In particular, the porosity distribution and associated sample carbonation, both of which affect cement's properties and durability, should be quantified accurately, and their kinetics and mechanisms of formation known both in detail and in situ. However, traditional methods of cement mineralogy analysis (e.g. chemical mapping) involve sample preparation (e.g. slicing) that can be destructive and/or expose cement to the atmosphere, leading to preparation artefacts (e.g. dehydration). In addition, the kinetics of mineralogical development during hydration, and associated porosity development, cannot be examined. To circumvent these issues, X-ray diffraction computed tomography (XRD-CT) has been used. This allowed the mineralogy of ternary blended cement composed of clinker, fly ash and blast furnace slag to be deciphered. Consistent with previous results obtained for both powdered samples and dilute systems, it was possible, using a consolidated cement paste (with a water-to-solid ratio akin to that used in civil engineering), to determine that the mineralogy consists of alite (only detected in the in situ hydration experiment), calcite, calcium silicate hydrates (C-S-H), ettringite, mullite, portlandite, and an amorphous fraction of unreacted slag and fly ash. Mineralogical evolution during the first hydration steps indicated fast ferrite reactivity. Insights were also gained into how the cement porosity evolves over time and into associated spatially and time-resolved carbonation mechanisms. It was observed that macroporosity developed in less than 30 h of hydration, with pore sizes reaching about 100-150 mm in width. Carbonation was not observed for this time scale, but was found to affect the first 100 mm of cement located around macropores in a sample cured for six months. Regarding this carbonation, the only mineral detected was calcite.

11Earthquake early warning systems (EEWSs) that rapidly trigger risk-reduction actions after a 12 potentially-damaging earthquake is detected are an attractive tool to reduce seismic losses. One 13 brake on their implementation in practice is the difficulty in setting the threshold required to trigger 14 pre-defined actions: set the level too high and the action is not triggered before potentially-15 damaging shaking occurs and set the level too low and the action is triggered too readily. Balancing 16 these conflicting requirements of an EEWS requires a consideration of the preferences of its 17 potential end users. In this article a framework to define these preferences, as part of a participatory 18 decision making procedure, is presented. An aspect of this framework is illustrated for a hypothetical 19 toll bridge in a seismically-active region, where the bridge owners wish to balance the risk to people 20 crossing the bridge with the loss of toll revenue and additional travel costs in case of bridge closure. 21Multi-Attribute Utility Theory (MAUT) is used to constrain the trigger threshold for four owners with 22 different preferences. We find that MAUT is an appealing and transparent way of aiding the 23 potentially controversial decision of what level of risk to accept in EEW. 24

12 pagesInternational audienceGeological storage of the greenhouse gas CO2 has the potential to be a widespread and effective option to mitigate climate change. As any industrial activity, CO2 storage may lead to adverse impact on human health and the environment in the case of unexpected leakage from the reservoir. These potential impacts should be considered in a risk assessment process. We present an approach to assess the impacts on human health in case of CO2 leakage emerging in the unsaturated zone under a building. We first focus on the migration of the CO2 in the unsaturated zone and the foundation through numerical simulation with sensitivity analysis. Our results show that the intrusion of CO2 into a building is substantially attenuated by the unsaturated zone and the foundation and may lead only under very specific conditions (very low ventilated parts of buildings, high flow rate and/or building situated very close to a leaking pathway) to hazardous CO2 indoor concentrations. We have then integrated the former results in a global toolbox that provides an efficient and easy-touse tool for decision support, which enables to assess the impacts on human health of CO2 leakage from the reservoir to a building

A wider exploitation of deep geothermal reservoir requires the development of Enhanced Geothermal System technology. In this context, drilling and stimulation of high-enthalpy geothermal wells raise technical challenges. Understanding and predicting the rock behavior near a deep geothermal wellbore are decisive to implement stimulation strategies to reach the couple temperature/flowrate target. Numerical modeling can contribute to enhanced stimulation processes thanks to a better understanding of impact of stress release, pressure changes and rock cooling in the near-wellbore area. In this paper, we use Discrete Element Method (code PFC2D, © Itasca Consulting Group), and more specifically bonded-particle model to capture the thermo-mechanical processes at metric scale. The application case corresponds to the beginning of thermal stimulation at Reykjanes in well RN-15/IDDP-2 (Iceland, IDDP-2 project and H2020 project DEEPEGS). A cold fluid is injected at a depth of 4.5 km where the rock temperature is above 430 °C and the well pressure is around 34 MPa. Since we have site-specific data and logging images after drilling, we attempt to link the simulations with the reality. The numerical results are confronted with incipient interpretation of logging images and with analytical solution to go towards validation of the modeling approach. Numerical results show breakouts and thermally and/or mechanically induced fractures consistent with the analytical solutions. Moreover, the sensitivity analysis on uncertain parameters yields important clues regarding some logging features as, for example, asymmetric damaging or caving.

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