Computational simulation of coupled poromechanical processes in deformable fractured and porous media.
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Results from the fully and biogeochemically coupled simulations in which CO 2 increases at a rate of 1 % yr –1 (1pctCO2) from its preindustrial value are analyzed to quantify the magnitude of carbon–concentration and carbon–climate feedback parameters which measure the response of ocean and terrestrial carbon pools to changes in atmospheric CO 2 concentration and the resulting change in global climate, respectively. The results are based on 11 comprehensive Earth system models from the most recent (sixth) Coupled Model Intercomparison Project (CMIP6) and compared with eight models from the fifth CMIP (CMIP5). The strength of the carbon–concentration feedback is of comparable magnitudes over land (mean ± standard deviation = 0.97 ± 0.40 PgC ppm –1 ) and ocean (0.79 ± 0.07 PgC ppm –1 ), while the carbon–climate feedback over land (–45.1 ± 50.6 PgC °C –1 ) is about 3 times larger than over ocean (–17.2 ± 5.0 PgC °C –1 ). The strength of both feedbacks is an order of magnitude more uncertain over land than over ocean as has been seen in existing studies. These values and their spread from 11 CMIP6 models have not changed significantly compared to CMIP5 models. The absolute values of feedback parameters are lower for land with models that include a representation of nitrogen cycle. The transient climate response to cumulative emissions (TCRE) from the 11 CMIP6 models considered here is 1.77 ± 0.37 °C EgC –1 and is similar to that found in CMIP5 models (1.63 ± 0.48 °C EgC –1 ) but with somewhat reduced model spread. The expressions for feedback parameters based on the fully and biogeochemically coupled configurations of the 1pctCO2 simulation are simplified when the small temperature change in the biogeochemically coupled simulation is ignored. Decomposition of the terms of these simplified expressions for the feedback parameters is used to gain insight into the reasons for differing responses among ocean and land carbon cycle models.
We simulate vibrational strong coupling (VSC) and vibrational ultrastrong coupling (V-USC) for liquid water with classical molecular dynamics simulations. When the cavity modes are resonantly coupled to the O–H stretch mode of liquid water, the infrared spectrum shows asymmetric Rabi splitting. The lower polariton (LP) may be suppressed or enhanced relative to the upper polariton (UP) depending on the frequency of the cavity mode. Furthermore, although the static properties and the translational diffusion of water are not changed under VSC or V-USC, we do find the modification of the orientational autocorrelation function of H 2 O molecules especially under V-USC, which could play a role in ground-state chemistry.
Abstract Bjerknes compensation (BJC) refers to the anticorrelation observed between atmospheric and oceanic heat transport (AHT/OHT) variability, particularly on decadal to longer time scales that may be important to the predictability of the climate system. This study investigates the spread in BJC across fully coupled simulations of phase 6 of the Coupled Model Intercomparison Project (CMIP6) and critical processes (particularly related to sea ice and clouds) that may contribute to that spread. BJC on decadal to longer time scales is confirmed across all the simulations evaluated, and it is strongest in the Northern Hemisphere (NH) between 60° and 70°N. At these latitudes, BJC appears to be primarily driven by the exchange of turbulent fluxes (sensible and latent) in the Greenland, Iceland, and Barents Seas. Metrics to break down how sea ice and clouds uniquely modify the radiative balance of the polar atmosphere during anomalous OHT events are presented. These metrics quantify the impacts of sea ice and clouds on surface and top of atmosphere (latent, sensible, longwave, and shortwave radiative) energy fluxes. Cloud responses tend to counter the clear sky impacts over the Marginal Ice Zone (MIZ). It is further shown that the degree of BJC present in a simulation at high latitudes is heavily influenced by the sensitivity of the sea ice to OHT, which is most influential over the MIZ. These results are qualitatively robust across models and explain the intermodel spread in NH BJC in the preindustrial control experiment.
Two existing particle-in-cell gyrokinetic codes, GEM for the core region and XGC for the edge region, have been successfully coupled with a spatial coupling scheme at the interface in a toroidal geometry. Additionally, a mapping technique is developed for transferring data between GEM's structured and XGC's unstructured meshes. Two examples of coupled simulations are presented to demonstrate the coupling scheme. The optimization of GEM for graphics processing unit is also presented.
Here, this study investigates the impacts of geomechanical and geochemical changes on carbon storage in a partially depleted oil reservoir, using results from four different coupled simulation models. Models were used to examine the relative importance of storage mechanisms, and how changing reservoir parameters might affect these mechanisms through time. The study uses data from a Morrowan sandstone reservoir in the Farnsworth Unit (FWU), Ochiltree County, Texas which is currently undergoing CO 2 enhanced oil recovery (EOR). Partially depleted oil reservoirs such as the FWU offer attractive carbon utilization and/or storage targets because of existing infrastructure and economic benefits from incremental oil recovery as well as tax credits. However, prediction of storage capacity or long-term fluid migration in these fields can be difficult because of the wide variation in formation fluids and operational histories that may have undergone. CO 2 injection can cause complex geomechanical and geochemical responses in a reservoir as a result of interplay between dynamic changes in pore pressure, reservoir temperature, fluid composition, and interactions between formation fluids, CO 2 , and reservoir rock. Thus, multiple coupled numerical simulation models must be developed and used to more precisely understand what CO 2 storage mechanisms are most significant, as well as the long-term fate of the stored CO 2 . Our study used results from hydrodynamic, coupled hydro-geomechanical, coupled hydro-geochemical, and coupled hydro-geomechanical-geochemical models to examine how changes in geomechanical and geochemical properties can impact the injectivity or storage capacity of CO 2 . Models simulated historical field operations and then forward-modeled a water-alternate-gas (WAG) operation for 20 years, followed by a 1000-year post-injection monitoring. The work demonstrates that in this specific reservoir, geomechanical impacts appear to be more significant than any geochemical processes, which showed minimal impact on reservoir properties. Furthermore, these simulation scenarios corroborated other studies showing more than 90% of CO 2 injected are being stored and will remain stored in the reservoir. The study was able to draw on a rich set of data from this currently operational project for the work. Because the Morrow is a widespread oil-bearing reservoir in the midcontinent of the United States and is fairly typical of many sandstone reservoirs elsewhere, the study has significance beyond the boundaries of our field area.
Safety assessment of geological nuclear waste repositories is essential for the permanent disposal of spent nuclear fuels and high-level radioactive waste. The long-term integrity of the host rock as well as the engineered barrier system (e.g., bentonite buffer) surrounding nuclear waste canisters is of particular importance as decay heat from nuclear waste canisters, which will last over thousands of years, significantly disturbs the thermo-hydromechanical (THM) state of the repository. In this study, THM coupled simulations were carried out to investigate the effect of time-dependent deformation (i.e., creep) of shale on the long-term integrity of a generic subsurface nuclear waste repository. The Norton-Bailey creep model, which is also known as the Lemaitre-Menzel-Schreiner model, was employed to simulate the power-law type creep that is observed in shales. The TOUGH-FLAC simulator was employed for the THM coupled modeling of the repository. The objective of this study is to assess the effect of creep in different shales (i.e., high creep shale vs. low creep shale) on long-term stress and permeability changes in the repository. Results show potential advantages of constructing repositories in the high creep shale, as deviatoric stress levels in the formation decreased to zero in 100 years since the emplacement of nuclear waste canisters and the permeability also decreased to the undamaged, intrinsic levels in 10,000 years. Also, mean effective stress levels in the bentonite buffer increased by 100% in the high creep shale case relative to the low creep shale case at 10,000 years due to creep-induced contraction of the nuclear waste disposal tunnel. However, in earlier periods (e.g., 1000 years), the stress levels in the bentonite buffer were twice smaller in the high creep shale case than in the low creep shale case, which shows a tradeoff between the intermediate- (~1000 years) and long-term (>10,000 years) compaction levels in the bentonite buffer depending on the creep characteristics of the host shale.
Abstract Coupling between mesoscale models and large‐eddy simulation (LES) models is increasingly used to more realistically represent the wide range of scales of atmospheric motions affecting boundary layer winds and turbulence that need to be simulated accurately for applications such as wind energy. However, such mesoscale‐to‐microscale coupled modeling frameworks are potentially affected by a large number of uncertain closure parameters. Here, we investigate the sensitivity associated with six closure parameters related to a 1.5‐order subgrid‐scale turbulence closure for an ensemble of mesoscale‐coupled LES. The simulations are performed using the Weather Research and Forecasting model nested from horizontal resolutions of greater than a kilometer down to tens of meters. Closure parameters are varied to generate perturbed parameter ensembles for two case studies of highly sheared, convective boundary layers observed in the Columbia Basin of Oregon and Washington during the Second Wind Forecast Improvement Project. Machine learning algorithms are used to explore the sensitivity of LES predictions, considering the effects of the perturbed physical parameters alongside categorical factors such as the case study identity, measurement location, and LES resolution. For the conditions we examine, a single parameter, the eddy viscosity coefficient, is the dominant source of parametric sensitivity and its importance is comparable to the categorical factors for several of the simulation response variables we examine.
This paper presents the Parallel Coupler for Multimodel Simulations (PCMS), a new GPU accelerated generalized coupling framework for coupling simulation codes on leadership class supercomputers. PCMS includes distributed control and field mapping methods for up to five dimensions. For field mapping PCMS can utilize discretization and field information to accommodate physics constraints. PCMS is demonstrated with a coupling of the gyrokinetic microturbulence code XGC with a Monte Carlo neutral transport code DEGAS2 and with a 5D distribution function coupling of an energetic particle transport code (GNET) to a gyrokinetic microturbulence code (GTC). Weak scaling is also demonstrated on up to 2,080 GPUs of Frontier with a weak scaling efficiency of 85%.
The understanding and prediction of silicon carbide (SiC) material evolution exposed to SOL plasma conditions is of prime interest because SiC represents a promising main chamber wall plasma-facing material for next-step fusion devices (low hydrogenic diffusion, good mechanical and thermal properties under neutron irradiation). Gross and net Si erosion rates from SiC surfaces in contact with a well-diagnosed L-mode plasma in the DIII-D tokamak have been simulated and the surface concentrations of impurities have been tracked as a function of time. Coupled simulation of surface model and impurity transport demonstrates amorphization of crystalline SiC exposed to L-mode plasma due to the accumulation of displacement damages under ion irradiation. This affects the lifetime of SiC plasma facing components. Surface evolution is tightly coupled to impurity transport in the plasma and therefore needs to be integrated with impurity transport simulations to effectively predict Si erosion rates and sub-surface concentrations as a function of time. The simulation workflow couples a semi-analytical surface model to the impurity transport code GITR. The surface model is a homogeneous mixed-material model that tracks physical & chemical sputtering and reflection of impurities. Gross erosion is primarily influenced by the background plasma parameters and redeposition patterns are mainly influenced by the prompt redeposition due to the gyro-orbits of impurity ions. Although crystalline form of SiC is preferable for fusion wall applications because of resistance to neutron irradiation, this work indicates that crystalline SiC will undergo amorphization under D plasma contact with implications of higher sputtering and fuel retention. These results direct us to explore the effects of amorphization on crystalline SiC and further the physics basis of SiC usage as first wall material for fusion environments.
Background detector rates in the Electron Ion Collider depend in part on the pressure in the interaction region. Materials choice, synchrotron radiation induced desorption, conditioning time and pumping configuration all affect the pressure in the system. Simulations of the region using Synrad and Molflow+ coupled simulation codes will be presented for various configruations and conditioning times.
Abstract. The spatial heterogeneity related to complex topography in California demands high-resolution (< 5 km) modeling, but global convection-permitting climate models are computationally too expensive to run multi-decadal simulations. We developed a 3.25 km California climate modeling framework by leveraging regional mesh refinement (CARRM) using the U.S. Department of Energy (DOE)'s global Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM) version 0. Four 5-year time periods (2015–2020, 2029–2034, 2044–2049, and 2094–2099) were simulated by nudging CARRM outside California to 1° coupled simulation of E3SMv1 under the Shared Socioeconomic Pathways (SSP)5-8.5 future scenario. The 3.25 km grid spacing adds considerable value to the prediction of the California climate changes, including more realistic high temperatures in the Central Valley and much improved spatial distributions of precipitation and snowpack in the Sierra Nevada and coastal stratocumulus. Under the SSP5-8.5 scenario, CARRM simulation predicts widespread warming of 6–10 °C over most of California, a 38 % increase in statewide average 30 d winter–spring precipitation, a near-complete loss of the alpine snowpack, and a sharp reduction in shortwave cloud radiative forcing associated with marine stratocumulus by the end of the 21st century. We note a climatological wet precipitation bias for the CARRM and discuss possible reasons. We conclude that SCREAM RRM is a technically feasible and scientifically valid tool for climate simulations in regions of interest, providing an excellent bridge to global convection-permitting simulations.
The objective of this project is to develop the coupled system of PROTEUS/ANSYS for simulating a heat pipe cooled micro reactor. As an initial effort, while figuring out controlling ANSYS Mechanical with Workbench, the coupled system of PROTEUS/FLUENT in the CORBA environment were tried to demonstrate the coupled simulation for a transient problem of a heat pipe cooled micro reactor. Finally, the coupled system of PROTEUS/ANSYS was constructed using APDL commands in the CORBA environment, instead of ANSYS Workbench, since we found that ANSYS with the current version of Workbench Python scripting did not provide capabilities necessary for simulating a transient problem.
The development of reference standard problems based on prototypical reactor designs is of particular importance to verify the adequacy of computer codes and evaluation models for specific reactor types. To support the multiphysics coupled simulation of molten-salt-fueled reactor (MSR) using SAM and Griffin computer codes for safety and licensing analysis, much efforts have been put into enhancing code capabilities and developing reference models for the MSR primary loop in SAM. In this work, a previously developed Molten Salt Reactor Experiment (MSRE) primary loop model was updated to include a two-dimensional (2-D) core region and external core components in one-dimension (1-D) or zero-dimension (0-D). To ensure accurate feedback calculation in multi-physics simulations, the delayed neutron precursor tracking model and solid graphite model were added in the SAM model. In addition, the 2-D and 1-D domains are tightly coupled using the recently developed single-solve approach in SAM. The updated model has been tested under both steady-state and transient scenarios to demonstrate its potential for the multi-physics simulation of MSRE with coupled SAM and Griffin.
In this chapter, multiphysics coupling simulations of nuclear reactor systems are reviewed. On the one hand, the mainstream methods of multiphysics coupling are demonstrated. The fundamental theory and coupling scheme of operator splitting methods, Jacobian-free Newton–Krylov methods, and approximate block Newton methods are summarized and presented. On the other hand, some significant works on neutronic and thermal-hydraulic codes coupling, and large research project, including NURESAFE European project, Multiphysics Object-Oriented Simulation Environment plan, and Consortium for the Advanced Simulation of Light Water Reactors project, are reviewed. This chapter helps the readers have a better understanding on the worldwide current status of multiphysics coupling research.