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DOE OSTI2021

How Equivalent Are Equivalent Porous Media?

Abstract Geoenergy and geoengineering applications usually involve fluid injection into and production from fractured media. Accounting for fractures is important because of the strong poromechanical coupling that ties pore pressure changes and deformation. A possible approach to the problem uses equivalent porous media to reduce the computational cost and model complexity instead of explicitly including fractures in the models. We investigate the validity of this simplification by comparing these two approaches. Simulation results show that pore pressure distribution significantly differs between the two approaches even when both are calibrated to predict identical values at the injection and production wells. Additionally, changes in fracture stability are not well captured with the equivalent porous medium. We conclude that explicitly accounting for fractures in numerical models may be necessary under some circumstances to perform reliable coupled thermohydromechanical simulations, which could be used in conjunction with other tools for induced seismicity forecasting.

58 GEOSCIENCES↗

DOE OSTI2020

Evaluation of semi-empirical soot models for nonpremixed flames with increased stoichiometric mixture fraction and strain

Due to the size and complexity of industrial-scale systems and computing limitations, semi-empirical soot models are often employed in CFD simulations rather than computationally-expensive detailed models. Many of these models were developed for specific applications with unique characteristic timescales and/or validated only under fuel-air combustion conditions. Hence, their use in different contexts, such as oxy-combustion, could lead to inaccurate predictions. In this study, twelve semi-empirical models (1-step or 2-step) are evaluated on their ability to respond to changes in stoichiometric mixture fraction (Z st ) and strain in a series of ethylene counterflow flames which span the experimental sooting-to-non-sooting (yellow to blue) transition. A unique approach of plotting soot formation rate in normalized, local equivalence ratio space is introduced to aid in the analysis. Results show that no existing model is able to predict a blue flame when Z st is increased beyond the experimentally-measured sooting limit. Many models give the counter-intuitive result of increasing peak and/or integrated soot volume fraction (svf) as Z st increased, contrary to experimental observations. Two models are able to successfully predict a blue flame upon increase of strain to the sooting limit value. For two-step models, the strong dependence of growth rate on surface area results in high sensitivity of svf to changing flame boundary conditions, but with mixed accuracy. There is still a significant need for a robust semi-empirical model which can accurately predict soot fraction in systems with oxygen-enrichment or variable strain.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

SO(3)-invariance of informed-graph-based deep neural network for anisotropic elastoplastic materials

This work examines the frame-invariance (and the lack thereof) exhibited in simulated anisotropic elasto-plastic responses generated from supervised machine learning of classical multi-layer and informed-graph-based neural networks, and proposes different remedies to fix this drawback. The inherent hierarchical relations among physical quantities and state variables in an elasto-plasticity model are first represented as informed, directed graphs, where three variations of the graph are tested. While feed-forward neural networks are used to train path-independent constitutive relations (e.g., elasticity), recurrent neural networks are used to replicate responses that depends on the deformation history, i.e. or path dependent. In dealing with the objectivity deficiency, we use the spectral form to represent tensors and, subsequently, three metrics, the Euclidean distance between the Euler Angles, the distance from the identity matrix, and geodesic on the unit sphere in Lie algebra, can be employed to constitute objective functions for the supervised machine learning. In this, the aim is to minimize the measured distance between the true and the predicted 3D rotation entities. Following this, we conduct numerical experiments on how these metrics, which are theoretically equivalent, may lead to differences in the efficiency of the supervised machine learning as well as the accuracy and robustness of the resultant models. Neural network models trained with tensors represented in component form for a given Cartesian coordinate system are used as a benchmark. Our numerical tests show that, even given the same amount of information and data, the quality of the anisotropic elasto-plasticity model is highly sensitive to the way tensors are represented and measured. The results reveal that using a loss function based on geodesic on the unit sphere in Lie algebra together with an informed, directed graph yield significantly more accurate rotation prediction than the other tested approaches.

42 ENGINEERING↗

DOE OSTI2024

Relating flow resistance to equivalent roughness

Describing flow resistance using the physical properties of an underlying surface is a recalcitrant problem in overland flow models. If discharge measurements are available, an equivalent roughness (e.g., Manning’s n) can be calibrated to represent the effects of surface properties within the domain with a single numerical value. Alternatively, the flow resistance can be estimated from discharge and velocity measured at a point, typically a runoff plot outlet. However, such experimental estimates are often inconsistent with the equivalent roughness determined from calibration to discharge, even if both derive from the same dataset. For example, if Manning’s equation is used to parameterize flow resistance, the Manning’s n obtained by calibrating a model to discharge differs from the value of n calculated from measured flow and velocity at the hillslope outlet. Here, this discrepancy is resolved by deriving a correction factor relating experimentally-determined flow resistance to the equivalent roughness. The derived correction factor is tested for four commonly-used resistance formulations using 129 rainfall simulator experiments. The correction factor is necessary to reproduce measured velocities, and yields minor improvements in discharge prediction. Plain Language Summary: Accurate runoff prediction is needed for land and water management in dryland regions, where sporadic and limited rainfall necessitate efficient water use and drought mitigation strategies. The skill of runoff models is known to be hindered by out ability to estimate flow resistance, which is the quantity that describes how energy is lost from flowing water to the underlying surface. Typically, models represent flow resistance with an equivalent roughness, e.g., Manning’s n, that is adjusted until the model can reproduce available discharge observations at watershed scale. However, the flow resistance measured in plot-scale experiments (1–10 m) often exceeds equivalent roughness coefficients by a factor of 10. This means that the direct use of plot-scale experimental data to parameterize runoff models could cause errors in discharge and runoff velocity predictions. Here, we resolve these differences by deriving an analytic correction factor that relates flow resistance to the equivalent roughness required for models to reproduce experimental velocity and discharge data. This correction factor is tested using rainfall simulator data from 129 experiments performed in the US Southwest covering a wide range of precipitation intensities, soil textures and vegetation types. Use of the correction factor substantially improves model prediction of flow velocity, which is needed for reproducing the timing of flood events and the estimation of erosion.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Insulation or Irradiance: Exploring Why Bifacial Photovoltaics Run Hot

Bifacial photovoltaics are predicted to become the dominant device architecture over the next couple of years, but their thermal performance is not yet well understood. In this study, we model the thermal effects of different backside lamination materials on the performance of bifacial PERC cells. Glass-glass laminated cells were found to operate hotter than equivalent glass-polymer backsheet packed cells. This was solely due to the increased absorption of rear side incident light.

bifacial↗

DOE OSTI2024

Medium-Range Structural Order as the Driver of Activated Dynamics and Complexity Reduction in Glass-Forming Liquids

Here, we analyze in depth the Elastically Collective Nonlinear Langevin Equation theory of activated dynamics in metastable liquids to establish that the predicted inter-relationships between the alpha relaxation time, local cage and collective elastic barriers, dynamic localization length, and shear modulus are causally related within the theory to the medium range order (MRO) static correlation length. The latter grows exponentially with density for metastable hard sphere fluids and as a nonuniversal inverse power law with temperature for supercooled liquids under isobaric conditions. The physical origin of predicted connections between the alpha time and other metrics of cage order and the thermodynamic inverse dimensionless compressibility is fully established. It is discovered that although kinetic constraints from the real space first coordination shell are important for the alpha time, they are of secondary importance compared to the consequences of the more universal MRO correlations in both the modestly and deeply metastable regimes. This understanding sheds new light on the theoretical basis for, and prior successes of, the predictive mapping of chemically complex thermal liquids to effective hard sphere fluids based on matching their dimensionless compressibilities, a scheme we call “complexity reduction”. In essence, the latter is equivalent to the physical requirement that the thermal liquid MRO correlation equals that of its effective hard sphere analog. The mapping alone is shown to provide a remarkable level of quantitative predictive power for the glass transition temperature T g of 21 molecular and polymer liquids. Predictions for the chemically specific absolute magnitude and growth with cooling of the MRO correlation length are obtained and lie in the window of 2–6 nm at T g . Dynamic heterogeneity, elastic facilitation, and beyond pair structure issues are briefly discussed. Future opportunities to theoretically analyze the equilibrated deep glass regime are outlined.

cancer↗

DOE OSTI2020

A novel sector mass spectrograph design for high-order coded aperture Mass Spectrometry with stigmatic aberration correction

Previous works experimentally demonstrated that the application of spatially-coded apertures to simple sector mass spectrographs can result in increased signal intensity while maintaining spectral resolution comparable to that of a conventional slit aperture.[Chen, E.X., et al.: J Am Soc Mass Spectr. 26, 1633 (2015)][Russell, Z.E., et al.: J Am Soc Mass Spectr. 26, 248 (2015)] This spatial coding technique was later applied to a double-focusing Mattauch-Herzog mass spectrograph, and shown to be generally compatible with the architecture.[Russell, Z.E., et al.: J Am Soc Mass Spectr. 27, 1 (2016)] However, the achieved signal gain was limited by the spatial size of the electric sector gap. In this work, we introduce a modified version of the Mattauch-Herzog mass spectrograph with a wide-gap electric sector that is enabled by a novel, segmented-electrode approach, and show via simulation that this modified architecture alone (without aperture coding) achieves a 1.8x improvement in mass resolving power compared to a conventional Mattauch-Herzog spectrograph of equivalent size. Further, simulation of an aperture-coded version of the instrument supports a predicted signal strength increase of 50x with minimal loss of aperture clarity on the sensor due to the increased open area of the high-order coded aperture which can be passed.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Trehalose Degradation by Cellvibrio japonicus Exhibits No Functional Redundancy and Is Solely Dependent on the Tre37A Enzyme

The α-diglucoside trehalose has historically been known as a component of the bacterial stress response, though it more recently has been studied for its relevance in human gut health and biotechnology development. The utilization of trehalose as a nutrient source by bacteria relies on carbohydrate-active enzymes, specifically those of the glycoside hydrolase family 37 (GH37), to degrade the disaccharide into substituent glucose moieties for entry into metabolism. Environmental bacteria using oligosaccharides for nutrients often possess multiple carbohydrate-active enzymes predicted to have the same biochemical activity and therefore are thought to be functionally redundant. In this study, we characterized trehalose degradation by the biotechnologically important saprophytic bacterium Cellvibrio japonicus This bacterium possesses two predicted α-α-trehalase genes, tre37A and tre37B, and our investigation using mutational analysis found that only the former is essential for trehalose utilization by C. japonicus Heterologous expression experiments found that only the expression of the C. japonicus tre37A gene in an Escherichia coli treA mutant strain allowed for full utilization of trehalose. Biochemical characterization of C. japonicus GH37 activity determined that the tre37A gene product is solely responsible for cleaving trehalose and is an acidic α-α-trehalase. Bioinformatic and mutational analyses indicate that Tre37A directly cleaves trehalose to glucose in the periplasm, as C. japonicus does not possess a phosphotransferase system. This study facilitates the development of a comprehensive metabolic model for α-linked disaccharides in C. japonicus and more broadly expands our understanding of the strategies that saprophytic bacteria employ to capture diverse carbohydrates from the environment. The metabolism of trehalose is becoming increasingly important due to the inclusion of this α-diglucoside in a number of foods and its prevalence in the environment. Bacteria able to utilize trehalose in the human gut possess a competitive advantage, as do saprophytic microbes in terrestrial environments. While the biochemical mechanism of trehalose degradation is well understood, what is less clear is how bacteria acquire this metabolite from the environment. The significance of this report is that by using the model saprophyte Cellvibrio japonicus, we were able to functionally characterize the two predicted trehalase enzymes that the bacterium possesses and determined that the two enzymes are not equivalent and are not functionally redundant. Here, the results and approaches used to understand the complex physiology of α-diglucoside metabolism from this study can be applied broadly to other polysaccharide-degrading bacteria.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Hybrid Particle Method for Computational Shock Physics

A long-standing area of research for Eulerian shock wave physics codes has been the treatment of strength and damage for materials. Here we present a method that will aid in the analysis of strength and failure in shock physics applications where excessive diffusion of critical variables can occur and control the solution outcome. Eulerian methods excel for large deformation simulations in general but are inaccurate in capturing structural behavior. Lagrangian methods provide better structural response, but finite element meshes can become tangled. Therefore, a technique for merging Lagrangian and Eulerian treatments of material response, within a single numerical framework, was implemented in the Multiple Component computational shock physics hydrocode. The capability is a Lagrangian/Eulerian Particle Method (LEPM) that uses particles to interface a Lagrangian treatment of material strength with a more traditional Eulerian treatment of the Equation of State (EOS). Lagrangian numerical methods avoid the advection diffusion found in Eulerian methods, which typically strongly affects strength constitutive law internal variables, such as equivalent plastic strain, porosity and/or damage. The Lagrangian capability enhances existing capabilities and permits accurate predictions of high rate, large deformation and/or shock of mechanical structures.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Simulation Tools for Characterizing Stress Distribution in Laser Welded Dissimilar Joints

This project focuses on developing a thermo-metallurgical-mechanical modeling method to accurately predict the microstructural evolution and residual stress in laser welding between dissimilar metals, such as HSLA steel and high carbon equivalent (CE) gear steel. The method leverages a comprehensive material database to model the temperature and rate dependent phase transformations, along with their associated effects on material properties, such as thermal expansion and flow stress, throughout the welding process. A key innovation is the incorporation of phase transformation and phase-specific properties, which enhances the accuracy of residual stress predictions. The mixture material in the fusion zone due to the dissimilar metals will also be addressed in the numerical model. This is especially critical in scenarios involving phase transformations in the fusion zone and heat-affected zone (HAZ), where the phase changes can induce substantial residual stress variations. The material database has been generated using JMatPro. The modeling approach is implemented through a custom User Material (UMAT) subroutine, executed with the commercial finite element software Abaqus.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Simulation Tools for Characterizing Stress Distribution in Laser Welded Dissimilar Joints

36 MATERIALS SCIENCE↗

DOE OSTI2022

Reassessing energy deposition for the ITER 5 MA vertical displacement event with an improved DINA model

The beryllium (Be) main chamber wall interaction during a 5 MA/1.8 T upward, unmitigated VDE scenario, first analysed in [J. Coburn et al., Phys. Scr. T171 (2020) 014076] for ITER, has been re-evaluated using the latest energy deposition analysis software. Updates to the DINA disruption model are summarized, including an improved numerical convergence for the 0D power balance, limitations on the safety factor within the plasma core, and the choice to maintain a constant plasma +halo poloidal cross-section. Such updates result in a broad halo region and higher radiated power fractions compared to previous models. The new scenario lasts for ~75 ms and deposits ~29 MJ of energy, with the radial distribution of parallel heat flux q‖(r)resembling an exponential falloff with an effective λ_q=75-198 mm. A maximum halo width w_h of 0.52 m at the outboard midplane is observed. SMITER field line tracing and energy deposition simulations calculate a q_{⊥,max} of ~83 MW/m^2 on the upper first wall panels (FWP). Heat transfer calculations with the MEMOS-U code show that the FWP surface temperature reaches ~1000 K, well below the Be melt threshold. Variations of this 5 MA scenario with Be im-purity densities from 0 to 3∙10^19 m^-3 also remain below the melt threshold despite differences in energy deposition and duration. These results are in contrast to the early study which predicted melt damage to the first wall [J. Coburn et al., Phys. Scr. T171 (2020) 014076], and emphasize the importance of accurate models for the halo width w_h and the heat flux distribution q‖(r)within that halo width. The 2020 halo model in DINA has been compared with halo current experiments on COMPASS, JET, and Alcator C-Mod, and the preliminary results build confidence in the broad halo width predictions. Results for the 5 MA VDE are compared with those for a 15 MA equivalent, generated using the new DINA model. At the higher current, significant melting of the upper FWP is to be expected.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Photolysis Controls Atmospheric Budgets of Biogenic Secondary Organic Aerosol

Secondary organic aerosol (SOA) accounts for a large fraction of tropospheric particulate matter. While SOA production rates and mechanisms have been extensively investigated, loss pathways remain uncertain. Most large-scale chemistry and transport models account for mechanical deposition of SOA, but not chemical losses, such as photolysis. There is also a paucity of laboratory measurements of SOA photolysis, which limits how well photolytic losses can be modeled. Here we show, through a combined experimental and modeling approach, that photolytic loss of SOA mass significantly alters SOA budget predictions. Using environmental chamber experiments, we find that SOA produced from several biogenic volatile organic compounds (VOCs) undergoes photolysis-induced mass loss at rates between 0 and 2.2% ± 0.4% of nitrogen dioxide (NO 2 ) photolysis, equivalent to average atmospheric lifetimes as short as 10 hours. We incorporate our photolysis rates into a regional chemical transport model to test the sensitivity of predicted SOA mass concentrations to photolytic losses. The addition of photolysis at rates consistent with our experimental conditions causes a ~50% reduction in biogenic SOA loadings over the Amazon, indicating that photolysis exerts a substantial control over the atmospheric SOA lifetime, with a likely dependence upon SOA molecular composition and thus production mechanisms.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Porous Flow Modeling of Axial Gas Redistribution in Fragmented LWR Fuel Rods using MOOSE

Understanding how gas axially redistributes within fragmented fuel pellets is crucial for predicting the behavior of Light Water Reactor (LWR) fuel rods, particularly during transient and accidental scenarios. The time scale of this phenomenon plays a fundamental role in determining the progression and hazard of a Loss Of Coolant Accident (LOCA), especially when high burn-up fuel in a severe state of fragmentation is involved. Here, this study presents a Computational Fluid Dynamics (CFD) model developed within the Multiphysics Object-Oriented Simulation Environment (MOOSE) to predict the time-scale of plenum depressurization in Light-Water Reactor (LWR) fuel rods driven by axial gas transport through fragmented pellets. The model examines the effects of incorporating non-linearities in the friction term by comparing the results with experimental data. The experiment employed surrogate fuel rods containing pellets subjected to mechanical and/or thermal loadings to simulate various severity of cracking, and aimed at studying the influence of fuel conditions on axial gas redistribution. The results of this analysis indicate that under certain flow regime conditions - determined by the value of an equivalent Reynolds number - accounting for the non-linear friction term in Navier-Stokes equations guarantees better predictions for the time-scale of plenum depressurization. Also, the model enabled the simulation of the pressure decay by assigning distinct permeability values to each pellet instead of a single uniform value. Multiple simulations were run across all possible pellet position combinations, having each pellet assigned with values of permeability extracted from the experimental data. This allows to quantify the impact of the considering various non-uniform distributions of permeability on the dynamics of axial gas redistribution. The present work findings enhance the understanding of axial gas transport, and provide valuable insights for the integration of a model for predicting the axial gas redistribution during a LOCA scenario into the BISON fuel performance code.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Dynamic Earthquake Triggering in Southern California in High Resolution: Intensity, Time Decay, and Regional Variability

Abstract Earthquake triggering by seismic waves has been recognized as a phenomenon for nearly 30 years. However, our ability to study dynamic triggering has been limited by our ability to capture the triggering stresses accurately and record the resultant earthquakes. Here we use full waveforms from a dense seismic network and a modern, high‐resolution seismic catalog to measure triggering in Southern California from 2008 to 2017 based on interevent time ratios. We find that the fractional seismicity rate change, which we term triggering intensity or triggerability, as a function of peak strain change for the period of ∼20 s due to distant earthquakes is monotonically increasing and compatible with earlier measurements made with a disjoint data set from 1984 to 2008. A triggering strain of 1 microstrain is equivalent to the local productivity generated by an M 1.8 earthquakes. This result implies that a prediction of seismicity rate changes can be made based on recorded ground shaking using the same formalism as currently used for aftershock prediction. For a teleseismic event, this small level of triggering occurs throughout the region and thus aggregates to a regional effect. We find that the triggering rate decays after the triggerer follows an Omori‐Utsu law, but at a much slower rate than a typical aftershock sequence. The slow decay rate suggests that an ancillary process such as creep or fluid flow must be part of dynamic triggering. The prevalence of triggering in areas of creep or fluid involvement reinforces this inference. A triggering cascade of secondary earthquakes is insufficient to explain the data.

Miyazawa, Masatoshi↗

DOE OSTI2020

Three-dimensional microstructure-explicit and void-explicit mesoscale simulations of detonation of HMX at millimeter sample size scale

Fully three-dimensional (3D) microstructure-explicit and void-explicit mesoscale simulations of the shock-to-detonation (SDT) process of pressed granular HMX (octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine) are performed. The overall size scale of the models is up to 3 × 3 × 15 mm3, with ∼30 000 grains and 206 265 voids. The models account for the heterogeneous material microstructure, constituent distribution, constituent morphology, and voids. Loading conditions considered involve piston velocities in the range of 600–1200 m/s or pressures in the range of 4–8 GPa. The focus is on analyzing the SDT process and the effects of microstructure and voids on the run-to-detonation distance (RDD). Companion two-dimensional (2D) simulations are also carried out to assess the differences between 2D and 3D. Statistically equivalent microstructure sample sets (SEMSSs) are generated and used for both 2D and 3D, allowing the prediction of the statistical and probabilistic Pop plots (PPs). The predictions are in general agreement with trends in available experimental data in the literature. It is found that both the microstructure (heterogeneous grain size, morphology, and size distribution) and voids significantly affect the RDD and the PPs. These effects are systematically delineated and quantified via the use of SEMSSs with different combinations of attributes. A recently developed probabilistic formulation for the PPs is used to characterize the results, allowing uncertainties in the relations between the shock pressure and RDD arising from material heterogeneities to be quantified. The probabilistic formulation is further used to quantify the confidence levels in the ranked order of influences of different combinations of microstructure and voids on the PPs.

Miller, Christopher (ORCID:0000000206844381)↗

DOE OSTI2023

Code Benchmark of the HTTF Pressurized Conduction Cooldown Test Using SAM

The High Temperature Test Facility (HTTF) at Oregon State University is an integral system test facility to simulate postulated reactor transients of prismatic high-temperature gas-cooled reactors(HTGRs). A series of test campaigns was launched, providing abundant test data that could be used to benchmark reactor system analysis codes like the System Analysis Module (SAM). In this study, a SAM model of the facility is developed based on the two-dimensional (2D) ring model approach. All components including the ceramic matrix, graphite heaters, helium coolant channels, core barrel, upcomer, pressure vessel, and reactor cavity cooling system are modeled as concentric cylindrical rings. The model is used to simulate one of the benchmark problems-Pressurized Conduction Cooldown (PCC)-within the scope of the Organisation for Economic Co-operation and Development Nuclear Energy Agency International HTTF Benchmark. The simulations consist of two parts. In the first part, operating and boundary conditions as well as thermophysical properties of materials are specified for the benchmark problem. In this work, results from the first part will be used in code-to-code comparison. In the second part, the SAM model is used to simulate Test PG-27, which is the first PCC test carried out in the HTTF, with only two of the ten heater banks activated. The results in the second part are used for code-to-data comparison. Because the helium coolant flow rate is not measured in this facility, it is estimated using the input power and inlet/outlet coolant temperatures. Additionally, radial heat flow in the ceramic blocks is complicated by hundreds of cylindrical coolant channels and heater rods embedded in them. As such, it is necessary to deduce an effective thermal conductivity for the ceramic to analyze the core thermal behavior. SAM predictions of the helium coolant and ceramic temperatures are compared with test data measured in three equivalent sectors. Overall, the SAM results agree reasonably well with test data within the variation of data among the three sectors, which demonstrates SAM's capability in capturing transient effects in HTGR using the simplified 2D ring model.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

Effect of the Addition of a Low Equivalent Stress Mechanism to the Analysis of Geomechanical Behavior of the SPR West Hackberry Site

Sandia National Laboratories has long used the Munson-Dawson (M-D) model to predict the geomechanical behavior of salt caverns used to store oil at the Strategic Petroleum Reserve (SPR). Salt creep causes storage caverns to deform inward, thus losing volume. This loss of volume affects the salt above and around the caverns, puts stresses and strains on borehole casings, and creates surface subsidence which affects surface infrastructure. Therefore, accurate evaluation of salt creep behavior drives decisions about cavern operations. Parameters for the M-D model are typically fit against laboratory creep tests, but nearly all historic creep tests have been performed at equivalent stresses of 8 MPa or higher. Creep rates at lower equivalent stresses are very slow, such that tests take months or years to run, and the tests are sensitive to small temperature perturbations (<0.1°C). A recent collaboration between US and German researchers, recently characterized the creep behavior at low equivalent (deviatoric) stresses (<8 MPa) of salt from the Waste Isolation Pilot Plant. In addition, the M-D model was recently extended to include a low stress creep “mechanism”. This paper details new simulations of SPR caverns that use this extended M-D model, called the M-D Viscoplastic model. The results show that the inclusion of low stress creep significantly alters the prediction of steady-state cavern closure behavior and indicate that low stress creep is the dominant displacement mechanism at the dome scale. The implications for evaluating cavern and well integrity are demonstrated by investigating three phenomena: the extent of stress changes around the cavern; the predicted vertical strains applied to wellbore casings; and the evaluation of oscillating stress changes around the cavern due to oil sale cycles and their potential effect on salt fatigue.

58 GEOSCIENCES↗