Numerical Prediction of the Large-Scale in Situ PRACLAY Heater Test in the Boom Clay

2021 ◽  
Vol 54 (5) ◽  
pp. 2197-2218
Author(s):  
Guangjing Chen ◽  
Arnaud Dizier ◽  
Xiangling Li ◽  
Jan Verstricht ◽  
Xavier Sillen ◽  
...  
2009 ◽  
Vol 36 (4) ◽  
pp. 626-640 ◽  
Author(s):  
Bertrand François ◽  
Lyesse Laloui ◽  
Clément Laurent

2010 ◽  
Vol 98 (9-11) ◽  
Author(s):  
E. Martens ◽  
Norbert Maes ◽  
E. Weetjens ◽  
M. Van Gompel ◽  
L. Van Ravestyn

Author(s):  
Xiangling Li ◽  
Guangjing Chen ◽  
Jan Verstricht ◽  
Philippe Van Marcke ◽  
Ioannis Troullinos

In Belgium, the URL HADES was constructed in the Boom Clay formation at the Mol site to investigate the feasibility of geological disposal in a clay formation. Since 1995, the URL R&D programme has focused on large scale demonstration tests like the PRACLAY Heater and Seal tests. The main objective of the Heater Test is to demonstrate that the thermal load generated by the heat-emitting waste will not jeopardise the safety functions of the host rock. The primary objective of the Seal Test is to provide suitable hydraulic boundary conditions for the Heater Test. The Seal Test also provides an opportunity to investigate the in-situ behaviour of a bentonite-based EBS. The PRACLAY gallery was constructed in 2007 and the hydraulic seal was installed in 2010. The bentonite is hydrated both naturally and artificially. The swelling, total pressure and pore pressure of the bentonite are continuously measured and analysed by numerical simulations to get a better understanding of this hydration processes. The timing of switching on the heater depends on the progress of the bentonite hydration, as a sufficient seal swelling is needed to fulfill its role. A set of conditions to be met for the heater switch-on and its schedule will be given.


2018 ◽  
Vol 23 (suppl_1) ◽  
pp. e16-e16
Author(s):  
Ahmed Moussa ◽  
Audrey Larone-Juneau ◽  
Laura Fazilleau ◽  
Marie-Eve Rochon ◽  
Justine Giroux ◽  
...  

Abstract BACKGROUND Transitions to new healthcare environments can negatively impact patient care and threaten patient safety. Immersive in situ simulation conducted in newly constructed single family room (SFR) Neonatal Intensive Care Units (NICUs) prior to occupancy, has been shown to be effective in testing new environments and identifying latent safety threats (LSTs). These simulations overlay human factors to identify LSTs as new and existing process and systems are implemented in the new environment OBJECTIVES We aimed to demonstrate that large-scale, immersive, in situ simulation prior to the transition to a new SFR NICU improves: 1) systems readiness, 2) staff preparedness, 3) patient safety, 4) staff comfort with simulation, and 5) staff attitude towards culture change. DESIGN/METHODS Multidisciplinary teams of neonatal healthcare providers (HCP) and parents of former NICU patients participated in large-scale, immersive in-situ simulations conducted in the new NICU prior to occupancy. One eighth of the NICU was outfitted with equipment and mannequins and staff performed in their native roles. Multidisciplinary debriefings, which included parents, were conducted immediately after simulations to identify LSTs. Through an iterative process issues were resolved and additional simulations conducted. Debriefings were documented and debriefing transcripts transcribed and LSTs classified using qualitative methods. To assess systems readiness and staff preparedness for transition into the new NICU, HCPs completed surveys prior to transition, post-simulation and post-transition. Systems readiness and staff preparedness were rated on a 5-point Likert scale. Average survey responses were analyzed using dependent samples t-tests and repeated measures ANOVAs. RESULTS One hundred eight HCPs and 24 parents participated in six half-day simulation sessions. A total of 75 LSTs were identified and were categorized into eight themes: 1) work organization, 2) orientation and parent wayfinding, 3) communication devices/systems, 4) nursing and resuscitation equipment, 5) ergonomics, 6) parent comfort; 7) work processes, and 8) interdepartmental interactions. Prior to the transition to the new NICU, 76% of the LSTs were resolved. Survey response rate was 31%, 16%, 7% for baseline, post-simulation and post-move surveys, respectively. System readiness at baseline was 1.3/5,. Post-simulation systems readiness was 3.5/5 (p = 0.0001) and post-transition was 3.9/5 (p = 0.02). Staff preparedness at baseline was 1.4/5. Staff preparedness post-simulation was 3.3/5 (p = 0.006) and post-transition was 3.9/5 (p = 0.03). CONCLUSION Large-scale, immersive in situ simulation is a feasible and effective methodology for identifying LSTs, improving systems readiness and staff preparedness in a new SFR NICU prior to occupancy. However, to optimize patient safety, identified LSTs must be mitigated prior to occupancy. Coordinating large-scale simulations is worth the time and cost investment necessary to optimize systems and ensure patient safety prior to transition to a new SFR NICU.


2021 ◽  
Vol 13 (2) ◽  
pp. 228
Author(s):  
Jian Kang ◽  
Rui Jin ◽  
Xin Li ◽  
Yang Zhang

In recent decades, microwave remote sensing (RS) has been used to measure soil moisture (SM). Long-term and large-scale RS SM datasets derived from various microwave sensors have been used in environmental fields. Understanding the accuracies of RS SM products is essential for their proper applications. However, due to the mismatched spatial scale between the ground-based and RS observations, the truth at the pixel scale may not be accurately represented by ground-based observations, especially when the spatial density of in situ measurements is low. Because ground-based observations are often sparsely distributed, temporal upscaling was adopted to transform a few in situ measurements into SM values at a pixel scale of 1 km by introducing the temperature vegetation dryness index (TVDI) related to SM. The upscaled SM showed high consistency with in situ SM observations and could accurately capture rainfall events. The upscaled SM was considered as the reference data to evaluate RS SM products at different spatial scales. In regard to the validation results, in addition to the correlation coefficient (R) of the Soil Moisture Active Passive (SMAP) SM being slightly lower than that of the Climate Change Initiative (CCI) SM, SMAP had the best performance in terms of the root-mean-square error (RMSE), unbiased RMSE and bias, followed by the CCI. The Soil Moisture and Ocean Salinity (SMOS) products were in worse agreement with the upscaled SM and were inferior to the R value of the X-band SM of the Advanced Microwave Scanning Radiometer 2 (AMSR2). In conclusion, in the study area, the SMAP and CCI SM are more reliable, although both products were underestimated by 0.060 cm3 cm−3 and 0.077 cm3 cm−3, respectively. If the biases are corrected, then the improved SMAP with an RMSE of 0.043 cm3 cm−3 and the CCI with an RMSE of 0.039 cm3 cm−3 will hopefully reach the application requirement for an accuracy with an RMSE less than 0.040 cm3 cm−3.


2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Sungmin O. ◽  
Rene Orth

AbstractWhile soil moisture information is essential for a wide range of hydrologic and climate applications, spatially-continuous soil moisture data is only available from satellite observations or model simulations. Here we present a global, long-term dataset of soil moisture derived through machine learning trained with in-situ measurements, SoMo.ml. We train a Long Short-Term Memory (LSTM) model to extrapolate daily soil moisture dynamics in space and in time, based on in-situ data collected from more than 1,000 stations across the globe. SoMo.ml provides multi-layer soil moisture data (0–10 cm, 10–30 cm, and 30–50 cm) at 0.25° spatial and daily temporal resolution over the period 2000–2019. The performance of the resulting dataset is evaluated through cross validation and inter-comparison with existing soil moisture datasets. SoMo.ml performs especially well in terms of temporal dynamics, making it particularly useful for applications requiring time-varying soil moisture, such as anomaly detection and memory analyses. SoMo.ml complements the existing suite of modelled and satellite-based datasets given its distinct derivation, to support large-scale hydrological, meteorological, and ecological analyses.


2021 ◽  
Vol 13 (7) ◽  
pp. 1335
Author(s):  
Ronald Souza ◽  
Luciano Pezzi ◽  
Sebastiaan Swart ◽  
Fabrício Oliveira ◽  
Marcelo Santini

The Brazil–Malvinas Confluence (BMC) is one of the most dynamical regions of the global ocean. Its variability is dominated by the mesoscale, mainly expressed by the presence of meanders and eddies, which are understood to be local regulators of air-sea interaction processes. The objective of this work is to study the local modulation of air-sea interaction variables by the presence of either a warm (ED1) and a cold core (ED2) eddy, present in the BMC, during September to November 2013. The translation and lifespans of both eddies were determined using satellite-derived sea level anomaly (SLA) data. Time series of satellite-derived surface wind data, as well as these and other meteorological variables, retrieved from ERA5 reanalysis at the eddies’ successive positions in time, allowed us to investigate the temporal modulation of the lower atmosphere by the eddies’ presence along their translation and lifespan. The reanalysis data indicate a mean increase of 78% in sensible and 55% in latent heat fluxes along the warm eddy trajectory in comparison to the surrounding ocean of the study region. Over the cold core eddy, on the other hand, we noticed a mean reduction of 49% and 25% in sensible and latent heat fluxes, respectively, compared to the adjacent ocean. Additionally, a field campaign observed both eddies and the lower atmosphere from ship-borne observations before, during and after crossing both eddies in the study region during October 2013. The presence of the eddies was imprinted on several surface meteorological variables depending on the sea surface temperature (SST) in the eddy cores. In situ oceanographic and meteorological data, together with high frequency micrometeorological data, were also used here to demonstrate that the local, rather than the large scale forcing of the eddies on the atmosphere above, is, as expected, the principal driver of air-sea interaction when transient atmospheric systems are stable (not actively varying) in the study region. We also make use of the in situ data to show the differences (biases) between bulk heat flux estimates (used on atmospheric reanalysis products) and eddy covariance measurements (taken as “sea truth”) of both sensible and latent heat fluxes. The findings demonstrate the importance of short-term changes (minutes to hours) in both the atmosphere and the ocean in contributing to these biases. We conclude by emphasizing the importance of the mesoscale oceanographic structures in the BMC on impacting local air-sea heat fluxes and the marine atmospheric boundary layer stability, especially under large scale, high-pressure atmospheric conditions.


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