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Life sciences payload definition and integration study, task C and D. Volume 2: Payload definition, integration, and planning studies

The Life Sciences Payload Definition and Integration Study was composed of four major tasks. Tasks A and B, the laboratory definition phase, were the subject of prior NASA study. The laboratory definition phase included the establishment of research functions, equipment definitions, and conceptual baseline laboratory designs. These baseline laboratories were designated as Maxi-Nom, Mini-30, and Mini-7. The outputs of Tasks A and B were used by the NASA Life Sciences Payload Integration Team to establish guidelines for Tasks C and D, the laboratory integration phase of the study. A brief review of Tasks A and B is presented provide background continuity. The tasks C and D effort is the subject of this report. The Task C effort stressed the integration of the NASA selected laboratory designs with the shuttle sortie module. The Task D effort updated and developed costs that could be used by NASA for preliminary program planning.

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DECOVALEX-2019 (Task C Final Report)

The DECOVALEX Project is an on-going international research collaboration, established in 1992, to advance the understanding and modeling of coupled Thermal (T), Hydrological (H), Mechanical (M) and Chemical (C) processes in geological in geological systems. This document is the final report of Task C which was proposed and coordinated by the Japan Atomic Energy Agency (JAEA), presenting the technical definitions of the problems studied, approaches applied, achievements made and outstanding issues for future research. DECOVALEX-2019 Task C aims to develop modelling and prediction methods using numerical simulation based on the water-filling experiment to examine the post-driftclosure environment recovery processes. Three research teams, JAEA, Sandia National Laboratories in the United States (SNL), and the Technical University of Liberec in the Czech Republic (TUL) were challenged to simulate the observed environmental changes. The Task consisted of following three main steps. The simulation targets were the water pressure drawdown/recovery and the variation of water chemistry during the tunnel excavation and closure, as observed in the monitoring boreholes and the CTD.

58 GEOSCIENCES↗

DECOVALEX-2023: Task C Final Report

The Full-scale Emplacement (FE) heater experiment at the Mont Terri Underground Rock Laboratory (URL) was designed and conducted by Nagra to replicate an emplacement tunnel of Nagra’s reference repository design at 1:1 scale. Alongside testing the technical feasibility of constructing disposal tunnels, emplacing waste containers in the tunnels and then backfilling them, the main goals of the FE experiment are (1) to obtain a better understanding of the coupled effects of induced thermo-hydro-mechanical (THM) processes that may occur and (2) to validate existing coupled THM models (Müller et al., 2017). A key aspect of ensuring safety for repositories located in low-permeability rock involves minimizing any damage to the rock itself, thereby preserving its integrity and promoting a stable environment Amongst a number of processes that could damage the rock is the increase in pore pressure due to thermal loading caused by heat emitted from the waste. To reduce the potential damage of the rock, it is important to analyse the evolution of heat over time due to the heat load of the containers and assess possible consequences by coupled THM models. The aim of Task C of DECOVALEX-2023 was to build 3D numerical models of the FE experiment, focussing in particular on the heating induced pore pressure change in the Opalinus Clay. Data from a large number of sensors were available from the FE experiment for model comparison. These sensors measured temperature and relative humidity in the bentonite around the heaters, and temperature, pressure and displacement/strain in the surrounding Opalinus clay. Data were available from the start of excavation (April 2012) up to August 2020 for most sensors (more than 5 years from the start of heating in December 2014). To fulfil the overall aim of the task, the work was broken down into a number of steps, starting with simpler models to build confidence in each team’s approach and then moving to more complex models that better represent the FE experiment. Step 0 consisted of 2D benchmark models, gradually increasing the number of processes that are represented from thermal (T) only models in Step 0a, to coupled thermal hydraulic (TH) models in Step 0b with a representation of changing porosity, to coupled thermo-hydro-mechanical (THM) models in Step 0c, where porosity changes are calculated by the mechanical model. A detailed specification of processes, parameters, initial and boundary conditions was provided for this step, with the ambition that all teams would work towards close agreement in their model results, thus building confidence in the model implementations. vi It was not straightforward to achieve agreement between the teams, so additional steps (Step 0b2, 0b3, 0c2, 0c3) were added along with derivation of some analytical solutions against which the models could be compared. The reasons for the differences between teams were investigated and found to be caused primarily by different conceptual model assumptions (including temperature dependence of the thermal expansion of water), different model formulations (including porosity evolution) and differences in modelled domain sizes, boundary conditions and grid discretisation. This demonstrates that comparisons between multiple modelling teams and/or comparison with analytical results and experimental data are highly beneficial in providing an indication of uncertainty in model predictions. At the conclusion of Step 0, almost all teams had achieved a close agreement in model results and those that had not achieved an agreement knew the reason for this. Step 1 moved from 2D models to 3D models of the FE experiment without adding technical features like shotcrete or EDZ, and only considering the heating phase. Initially the 3D model was tightly specified to continue to build confidence in the model implementations (Step 1a). The results of Step 1a were compared to the data from the FE-experiment without the teams seeing the data. The teams were then provided with a sub-set of the data from the FE-experiment and invited to consider how best to use the large dataset for model comparison (Step 1b). Teams were then asked to use the data provided to calibrate their models, only changing material property values rather than adding features or processes to their models (Step 1c). In Step 1, teams were asked to only model the heating phase of the experiment, so pressure in the Opalinus Clay was reported as change in pressure since the initial conditions were specified rather than modelled. The change from 2D to 3D models was accompanied by an increase in the dispersion of results between the teams. Some of this was resolved during the task, but some remained and is potentially due to model discretisation. Calibration of parameters was useful in improving the fit of the models to the data but the remaining differences indicated that the models were missing features or processes. In Step 2, the teams were asked to update their models with additional features and processes as well as calibrating parameters to try and improve the fit of the models to the data. Teams were encouraged to represent ventilation of the open FE tunnel prior to backfilling with heaters and bentonite and in Step 2, the absolute pressure in the Opalinus Clay was compared between the teams. Teams took different approaches, but there was consideration of adding shotcrete and an EDZ into the model, representing stress change during excavation and different approaches to modelling ventilation of the FE tunnel. Overall, the documented results showed a very good agreement for temperature. The results for porewater pressure evolution showed a significant improvement for most teams compared to Step 1c with a good agreement to the measurements for several teams whereas some teams overpredicted the pressure increase and others overpredicted the drainage effect especially for the sensors close to the heater. Step 3 was an opportunity for teams to use the models developed in Step 1 and Step 2 to make predictions about the temperature and pressure changes that will be expected at the FE experiment over the next few years in light of the planned changes in thermal output of the heaters.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

International Collaboration Activities on Disposal in Argillite R&D: DECOVALEX19 Task C – Geochemical and Reactive Transport Modeling

International collaborations on nuclear waste disposal R&D are an integral part of the Spent Fuel Waste Science and Technology (SFWST) campaign within the DOE Fuel Cycle and Technology (FCT) program. These partnerships with international repository R&D programs provide key opportunities to participate in experiments developing laboratory/field data (underground research laboratories (URL)) of engineered barrier system (EBS) interactions (e.g., near-field) and characterization of transport phenomena in the host rock (e.g., far-field). The results of these experiments are used in the evaluation of coupled processes and their representation via state-of-the-art simulation approaches to evaluate repository performance. During the thermal heating period, increases in temperature from radionuclide decay in the spent fuel (SF) waste canisters will increase temperature in the surrounding EBS driving chemical and transport processes in the near- and far-field domains of the repository. URL heater-tests for extended periods of times (e.g., years) provide key information and data on thermal effects affecting engineered barriers in response to temperature and water saturation levels. Groundwater interactions with cementitious barriers are also important to in-drift chemistry and EBS performance during post-closure. Descriptions of the various URL experiments for various disposal design concepts according to the host country repository program and relevance to the US program is given elsewhere (Birkholzer et al.,2017;Jové Col& et al., 2016). The DECOVALEX-2019 Task C involves collaboration with the GREET (Groundwater REcovery Experiment in Tunnel) at the Mizunami URL, Japan ,which targets the development of monitoring methodologies of groundwater in granitic rock with applications to THMC simulations (Iwatsuki et al., 2005;Iwatsuki et al.,2015,2017). Some of the goals of GREET is to conduct a facility-scale geochemical characterization study of short- and long-term effects of tunnel excavation activities, impacts on groundwater flow and transport, and influences on groundwater chemistry (Iwatsuki et al.,2015). The data obtained from these URL activities is then used in the development and evaluation of THC models to support post-closure safety and performance assessments of the repository environment.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Life science payload definition and integration study, task C and D. Volume 3: Appendices

Research equipment requirements were based on the Mini-7 and Mini-30 laboratory concepts defined in Tasks A and B of the intial LSPD contract. Modified versions of these laboratories and the research equipment within them were to be used in three missions of Shuttle/Sortie Module. These were designated (1) the shared 7-day laboratory (a mission with the life sciences laboratory sharing the sortie module with another scientific laboratory), (2) the dedicated 7-day laboratory (full use of the sortie module), and (3) the dedicated 30-day laboratory (full sortie module use with a 30-day mission duration). In defining the research equipment requirements of these laboratories, the equipment was grouped according to its function, and equipment unit data packages were prepared.

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DECOVALEX2019 Task C: Results of Step 2 modeling

The work for Step 1 performed at Sandia National Laboratories and reported in Section 7 has been updated to incorporate new data and to conduct new simulations using a new larger base case domain. The new simulations also include statistical analysis for different fracture realizations. A sensitivity analysis was also conducted to the study of the effect of domain size. A much larger mesh was selected to minimize boundary effects. The DFN model was upscaled to the new base case domain and the much larger domain to generate relevant permeability and porosity fields for each case. The calculations updated for Step 2 are described in Section 12.1. New calculations have also been conducted to model the flooding of the CTD and the resulting pressure recovery. The modeling includes matching of pressure and chloride experimental data at the six observation locations in Well 12M133. The modeling was done for the 10 fracture realizations. The Step 2 recovery simulations are described in Section 12.2. The Step 2 work is summarized in Section 12.3.

42 ENGINEERING↗