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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

High-resolution hourly surrogate modeling framework for physics-based large-scale building stock modeling

Surrogate modeling can play a key role in reducing high computational burdens for large-scale physics-based modeling and uncertainty quantification. With the rapid development of large-scale building stock energy modeling, surrogate modeling has also begun to be widely applied in this field; however, most existing surrogate models lack hourly time resolution for regional-scale modeling, which is essential for understanding building demand profiles and grid impacts. Further, there is generally a lack of necessary data and feature engineering frameworks specific to building modeling for efficiently managing large datasets and complex computations. Furthermore, this paper proposes a modeling framework for large-scale (city-/region-scale), high-resolution, high-fidelity surrogate building stock energy models. Our developed framework consists of six modules: (1) building stock energy modeling (ComStock TM and ResStock TM ), (2) data engineering for large simulation data, (3) high performance computing workflow, (4) feature engineering, (5) machine learning model development, and (6) model performance evaluation. Two case studies apply the developed framework in both residential and commercial building stock analysis to demonstrate its computational efficiency and surrogate modeling accuracies. Results show that surrogate models, when efficiently trained using the HPC workflow module, reach a high level of modeling accuracy for two case studies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Aggregation bias and its drivers in large‐scale flood loss estimation: A Massachusetts case study

Abstract Large‐scale estimations of flood losses are often based on spatially aggregated inputs. This makes risk assessments vulnerable to aggregation bias, a well‐studied, sometimes substantial outcome in analyses that model fine‐grained spatial phenomena at coarse spatial units. To evaluate this potential in the context of large‐scale flood risk assessments, we use data from a high‐resolution flood hazard model and structure inventory for over 1.3 million properties in Massachusetts and examine how prominent data aggregation approaches affect the magnitude and spatial distribution of flood loss estimates. All considered aggregation approaches rely on aggregate structure inventories but differ in whether flood hazard is also aggregated. We find that aggregating only structure inventories slightly underestimates overall losses (−10% bias), and when flood hazard data is spatially aggregated to even relatively small spatial units (census block), statewide aggregation bias can reach +366%. All aggregation‐based procedures fail to capture the spatial covariation of inputs distributions in the upper tails that disproportionately generate total expected losses. Our findings are robust to several key assumptions, add important context to published risk assessments and highlight opportunities to improve flood loss estimation uncertainty quantification.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

The Rise of US Photovoltaics: An Exploration of Land Use Density Trends in Large‐Scale Solar Facility Attributes, 2012–2021

An energy transition is underway in the United States; renewable energy generation is now on par with coal and nuclear generation. The number of large-scale solar photovoltaic facilities increased approximately tenfold between 2012 and 2021, with an associated 25-fold increase in cumulative installed capacity. With ambitious decarbonization and renewable energy deployment goals at both the federal and state levels, deployments of large-scale solar photovoltaic facilities will continue apace. This growth is likely to be complex with ripples of impacts felt throughout different aspects of society, and thus accurate solar land use metrics allowing more accurate predictions are of value to policymakers, planners, and other stakeholders in the future photovoltaic build-out. In this paper, we leverage data from the newly released US Large-Scale Solar Photovoltaic Database to examine recent trends in large-scale solar photovoltaic land use. We analyze the relationships between solar array capacity density (W/acre) and a range of facility attributes to better understand the future land requirements of solar capacity expansion over the coming years. Installed capacity was the single strongest determinant of solar array area. However, we found substantial variation in capacity density across facility attributes, including mount type, latitude, urbanicity, time, and prior land use.

14 SOLAR ENERGY↗
DOE OSTI2022

Assessing the Effectiveness of Large-Scale Environmental Restoration: Challenges and Opportunities

A recent National Academies consensus report addresses monitoring and assessment of cumulative effects of large-scale and multiple restoration projects within the context of long-term environmental change. Fines and penalties from the Deepwater Horizon oil spill in the Gulf of Mexico (GoM) have supported hundreds of restoration projects at spatial scales not often possible in the past. Here, in this paper, the report committee members and staff provide personal reflections from our time working on the study. We found that gaps in data collection, issues with data accessibility, and a lack of synthesis and analysis are hindering the ability to answer a basic question: What are the impacts of these many restoration efforts on improving ecosystem health and productivity in the GoM at the regional and Gulf wide scale? Restoration efforts are occurring in environments where many trends are changing and exhibiting higher variability than in the past, suggesting that previously successful restoration practices may no longer be adequate to compensate for the effects of environmental changes and variability. Our proposed approach to these challenges includes employing emerging monitoring technologies; using conceptual models; devising an adaptive management framework; rethinking restoration outcome goals; assessing cumulative effects; and undertaking rigorous synthesis and analysis of existing information on long-term environmental trends and restoration efforts. Restoration scientists and practitioners working in the GoM have an unprecedented opportunity to demonstrate large-scale environmental recovery if advances in monitoring, synthesis, assessment, and action are taken quickly. We are cautiously optimistic that, with mid-course adjustments, continued progress toward large-scale environmental recovery is possible.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Constraints on the Correlation of IceCube Neutrinos with a Tracer of Nearby Large-scale Structure

The IceCube Neutrino Observatory has observed extragalactic astrophysical neutrinos with an apparently isotropic distribution. Only a small fraction of the observed astrophysical neutrinos can be explained by known sources. Neutrino production is thought to occur in energetic environments that are ultimately powered by the gravitational collapse of dense regions of the large-scale mass distribution in the universe. Whatever their identity, neutrino sources likely trace this large-scale mass distribution. The clustering of neutrinos with a tracer of the large-scale structure may provide insight into the distribution of neutrino sources with respect to redshift and the identity of neutrino sources. We implement a two-point angular cross correlation of the Northern sky track events with an infrared galaxy catalog derived from the Wide-field Infrared Survey Explorer (WISE) and Two Micron All Sky Survey (2MASS) source catalogs, which trace the nearby large-scale structure. No statistically significant correlation is found between the neutrinos and this infrared galaxy catalog. We find that ≤54% of the diffuse muon neutrino flux can be attributed to sources correlated with the galaxy catalog with 90% confidence. Additionally, when assuming that the neutrino source comoving density evolves following a power law in redshift, dN s /dV ∝ (1 + z) k , we find that sources with negative evolution, in particular k < −1.75, are disfavored at the 90% confidence level.

Abbasi, R. [Loyola University, Chicago, IL (United↗
DOE OSTI2023

Large-Scale Inference of Multivariate Regression for Heavy-Tailed and Asymmetric Data

Large-scale multivariate regression is a fundamental statistical tool with a wide range of applications. Here, this study considers the problem of simultaneously testing a large number of general linear hypotheses, encompassing covariate-effect analysis, analysis of variance, and model comparisons. The challenge that accompanies a large number of tests is the ubiquitous presence of heavy-tailed and/or highly skewed measurement noise, which is the main reason for the failure of conventional least squares-based methods. For large-scale multivariate regression, we develop a set of robust inference methods to explore data features such as heavy tailedness and skewness, which are not visible to least squares methods. The new testing procedure is based on the data-adaptive Huber regression and a new covariance estimator of regression estimates. Under mild conditions, we show that our methods produce consistent estimates of the false discovery proportion. Extensive numerical experiments and an empirical study on quantitative linguistics demonstrate the advantage of the proposed method over many state-of-the-art methods when the data are generated from heavy-tailed and/or skewed distributions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Large-scale atomistic model construction of subbituminous and bituminous coals for solvent extraction simulations with reactive molecular dynamics

Large-scale atomistic models for complex polycyclic aromatic hydrocarbon systems help understand the chemical properties and behaviors of complex feedstocks such as coal or petroleum. However, the development and utilization of large-scale models remain limited due to the difficulty in achieving the varied structural characteristics necessary to capture stochastic nature of these feedstocks. Here we demonstrate a systematic workflow to construct stochastic molecular systems from a broad analytical suite: high-resolution transmission electron microscopy (HRTEM), carbon-13 nuclear magnetic resonance spectroscopy ( 13 C NMR), laser desorption ionization mass spectroscopy (LDI-MS), and elemental analysis. We present a model construction and analysis utility of a new Python-based module. We selected one subbituminous and three high-volatile bituminous coals to construct large-scale models (~40,000 atoms). The constructed models were utilized to examine the affinity for solvent extraction (naphthalene or tetralin) and the effect of structural properties (e.g., aromatic cluster size, functional groups, and cross-linking) in reactive molecular dynamics simulations. Complex chemical reactions were monitored with bond order transitions, intermediates formation, and mass distributions. Reactive molecular dynamics simulations suggest a plausible chemical extraction process and products for the complex fossil feedstocks. The results indicated that radical formations with bond breaking of bridging oxygens and carbons were required at high temperatures to facilitate hydrogeneration and extraction of gas molecules from radical-free molecules. We observed that aliphatic chains of tetralin were easily decomposed and combined with radicals to form small size of molecules with aryl bonding, mainly increasing molecules in the 500–1000 Da, while naphthalene had little impact on chemical extraction process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

The role of chromatin state in intron retention: A case study in leveraging large scale deep learning models

Complex deep learning models trained on very large datasets have become key enabling tools for current research in natural language processing and computer vision. By providing pre-trained models that can be fine-tuned for specific applications, they enable researchers to create accurate models with minimal effort and computational resources. Large scale genomics deep learning models come in two flavors: the first are large language models of DNA sequences trained in a self-supervised fashion, similar to the corresponding natural language models; the second are supervised learning models that leverage large scale genomics datasets from ENCODE and other sources. We argue that these models are the equivalent of foundation models in natural language processing in their utility, as they encode within them chromatin state in its different aspects, providing useful representations that allow quick deployment of accurate models of gene regulation. We demonstrate this premise by leveraging the recently created Sei model to develop simple, interpretable models of intron retention, and demonstrate their advantage over models based on the DNA language model DNABERT-2. Our work also demonstrates the impact of chromatin state on the regulation of intron retention. Using representations learned by Sei, our model is able to discover the involvement of transcription factors and chromatin marks in regulating intron retention, providing better accuracy than a recently published custom model developed for this purpose.

Biochemistry & Molecular Biology↗
DOE OSTI2020

The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: Large-scale structure catalogues for cosmological analysis

ABSTRACT We present large-scale structure catalogues from the completed extended Baryon Oscillation Spectroscopic Survey (eBOSS). Derived from Sloan Digital Sky Survey (SDSS) IV Data Release 16 (DR16), these catalogues provide the data samples, corrected for observational systematics, and random positions sampling the survey selection function. Combined, they allow large-scale clustering measurements suitable for testing cosmological models. We describe the methods used to create these catalogues for the eBOSS DR16 Luminous Red Galaxy (LRG) and Quasar samples. The quasar catalogue contains 343 708 redshifts with 0.8 < z < 2.2 over 4808 deg2. We combine 174 816 eBOSS LRG redshifts over 4242 deg2 in the redshift interval 0.6 < z < 1.0 with SDSS-III BOSS LRGs in the same redshift range to produce a combined sample of 377 458 galaxy redshifts distributed over 9493 deg2. Improved algorithms for estimating redshifts allow that 98 per cent of LRG observations result in a successful redshift, with less than one per cent catastrophic failures (Δz > 1000 km s−1). For quasars, these rates are 95 and 2 per cent (with Δz > 3000 km s−1). We apply corrections for trends between the number densities of our samples and the properties of the imaging and spectroscopic data. For example, the quasar catalogue obtains a χ2/DoF = 776/10 for a null test against imaging depth before corrections and a χ2/DoF= 6/8 after. The catalogues, combined with careful consideration of the details of their construction found here-in, allow companion papers to present cosmological results with negligible impact from observational systematic uncertainties.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Understanding collective human movement dynamics during large-scale events using big geosocial data analytics

Conventional approaches for modeling human mobility pattern often focus on human activity and movement dynamics in their regular daily lives and cannot capture changes in human movement dynamics in response to large-scale events. With the rapid advancement of information and communication technologies, many researchers have adopted alternative data sources (e.g., cell phone records, GPS trajectory data) from private data vendors to study human movement dynamics in response to large-scale natural or societal events. Big geosocial data such as georeferenced tweets are publicly available and dynamically evolving as real-world events are happening, making it more likely to capture the real-time sentiments and responses of populations. However, precisely-geolocated geosocial data is scarce and biased toward urban population centers. In this research, we developed a big geosocial data analytical framework for extracting human movement dynamics in response to large-scale events from publicly available georeferenced tweets. The framework includes a two-stage data collection module that collects data in a more targeted fashion in order to mitigate the data scarcity issue of georeferenced tweets; in addition, a variable bandwidth kernel density estimation(VB-KDE) approach was adopted to fuse georeference information at different spatial scales, further augmenting the signals of human movement dynamics contained in georeferenced tweets. To correct for the sampling bias of georeferenced tweets, we adjusted the number of tweets for different spatial units (e.g., county, state) by population. To demonstrate the performance of the proposed analytic framework, we chose an astronomical event that occurred nationwide across the United States, i.e., the 2017 Great American Eclipse, as an example event and studied the human movement dynamics in response to this event. Finally, this analytic framework can easily be applied to other types of large-scale events such as hurricanes or earthquakes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Locating the missing large-scale emission in the jet of M87* with short EHT baselines

In very-long baseline interferometric arrays, nearly co-located stations probe the largest scales and typically cannot resolve the observed source. In the absence of a large-scale structure, closure phases constructed with these stations are zero and, since they are independent of station-based errors, they can be used to probe data issues. Here, we show how these trivial closure phases become nonzero with a brightness distribution on smaller scales than their short baseline would suggest. When applied to sources that are made up of a bright compact and large-scale diffuse component, the trivial closure phases directly measure the centroid relative to the compact source and higher-order image moments. We present a technique to measure these image moments with minimal model assumptions and validate it on synthetic Event Horizon Telescope (EHT) data. We then apply this technique to 2017 and 2018 EHT observations of M87* and find a weak preference for extended emission in the direction of the large-scale jet. We also apply it to 2021 EHT data and measure the source centroid about 1 mas northwest of the compact ring, which is consistent with the jet observed at lower frequencies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Learning local equivariant representations for large-scale atomistic dynamics

Abstract A simultaneously accurate and computationally efficient parametrization of the potential energy surface of molecules and materials is a long-standing goal in the natural sciences. While atom-centered message passing neural networks (MPNNs) have shown remarkable accuracy, their information propagation has limited the accessible length-scales. Local methods, conversely, scale to large simulations but have suffered from inferior accuracy. This work introduces Allegro, a strictly local equivariant deep neural network interatomic potential architecture that simultaneously exhibits excellent accuracy and scalability. Allegro represents a many-body potential using iterated tensor products of learned equivariant representations without atom-centered message passing. Allegro obtains improvements over state-of-the-art methods on QM9 and revMD17. A single tensor product layer outperforms existing deep MPNNs and transformers on QM9. Furthermore, Allegro displays remarkable generalization to out-of-distribution data. Molecular simulations using Allegro recover structural and kinetic properties of an amorphous electrolyte in excellent agreement with ab-initio simulations. Finally, we demonstrate parallelization with a simulation of 100 million atoms.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Predicting large-scale pool fire dynamics using an unsteady flamelet- and large-eddy simulation-based model suite

A low-Mach, unstructured, large-eddy-simulation-based, unsteady flamelet approach with a generalized heat loss combustion methodology (including soot generation and consumption mechanisms) is deployed to support a large-scale, quiescent, 5-m JP-8 pool fire validation study. The quiescent pool fire validation study deploys solution sensitivity procedures, i.e., the effect of mesh and time step refinement on capturing key fire dynamics such as fingering and puffing, as mesh resolutions approach O(1) cm. A novel design-order, discrete-ordinate-method discretization methodology is established by use of an analytical thermal/participating media radiation solution on both low-order hexahedral and tetrahedral mesh topologies in addition to quadratic hexahedral elements. Here, the coupling between heat losses and the flamelet thermochemical state is achieved by augmenting the unsteady flamelet equation set with a heat loss source term. Soot and radiation source terms are determined using flamelet approaches for the full range of heat losses experienced in fire applications including radiative extinction. The proposed modeling and simulation paradigm are validated using pool surface radiative heat flux, maximum centerline temperature location, and puffing frequency data, all of which are predicted within 10% accuracy. Simulations demonstrate that under-resolved meshes predict an overly conservative radiative heat flux magnitude with improved comparisons as compared to a previously deployed hybrid Reynolds-averaged Navier–Stokes/eddy dissipation concept-based methodology.

42 ENGINEERING↗
DOE OSTI2024

Bubble Mass Transport Measurement in the Large-Scale Test Loops at Oak Ridge National Laboratory

Molten salts are complex fluids that incorporate multi-phase behavior depending on the chemistry and the physical properties of the entrained components. These components include the carrier salt, the actinide fuel, and fission, activation, and corrosion products, the concentrations of which depends on the burnup history of the salt. Radionuclide transport from the salt into the cover gas / off-gas system depends on volatility as predicted by thermochemistry, but data from the Molten Salt Reactor Experiment (MSRE) conducted in the late 1960s suggest that bubble formation and transport are also important. Anomalously high fractions of noble metals were found in the off-gas system and were attributed to transportation with parent salt aerosols and their association with rising noble gas bubbles. The prediction of such phenomena requires coupled neutronic, thermal hydraulic, and chemical equilibrium calculations, the framework of which is being developed within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program supported by the US Department of Energy (DOE) Office of Nuclear Energy (NE). However, separate effects tests and models of experiments using tools such as SAM and Thermochimica can guide model developers through important processes. Conversely, model development guides the choice of experiments and systems to provide data that are relevant for validation. This report describes several experiments that tracked gas transport in molten salts, ranging from small-scale systems to large-scale loops. Gas transportation in a molten salt, LiCl-KCl, has been studied using the shadowgraph technique. Sensors such as residual gas analysis, Raman spectroscopy, and laser-induced breakdown spectroscopy have been tested for off-gas measurements. These data were used to interpret how the gases move through the upstream salt / cover gas and the interface between them. Differential pressure measurements were able to detect individual gas bubbles as they popped at the liquid–gas interface. Salt aerosols were collected on a cascade impactor. Their formation was also observed directly via the shadowgraph method, and most of these aerosols were launched ballistically into the cover gas. Fine mists could also be observed. Convection currents through the salt were visualized and can be used to calculate the thermophysical properties of the salt itself. The apparatuses described in this report and in a previous work (McFarlane et al. 2023) have been commissioned and are available for use in making further measurements of salt/surrogate fission product behavior. Novel approaches using neutron imaging are planned for the study of fluoride salts, which cannot be contained in quartz, so shadowgraph visualization is not available. Bubble transport in convective flow and in a slow-moving salt column are planned. The mobile laser-induced breakdown spectroscopy (LIBS) system is available for several applications, including iodine capture in a molten hydroxide scrubber, H2 transport though molten salts to complement Raman analysis, and online tracking of salt aerosol generation, transport, and deposition. This report summarizes the findings from FY24 and the plans for FY25. The work completes milestone M2AT-24OR0702013 of the DOE-NE Advanced Reactor Technology, Molten Salt Reactor Campaign, DOE-NE-5.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Cold ion beam in a storage ring as a platform for large-scale quantum computers and simulators: Challenges and directions for research and development

The purpose of this paper is to evaluate the possibility of constructing a large-scale storage-ring-type ion-trap system capable of storing, cooling, and controlling a large number of ions as a platform for scalable quantum computing (QC) and quantum simulations. In such a trap, the ions form a crystalline beam moving along a circular path with a constant velocity determined by the frequency and intensity of the cooling lasers. In this paper, we consider a large leap forward in terms of the number of ions that serve as qubits in QC, from fewer than 100 available in state of the art linear ion-trap devices today to an order of 10 5 crystallized ions in the storage-ring setup. This new trap design unifies two different concepts: the storage rings of charged particles and the linear ion traps used for QC and mass spectrometry. In this paper, we use the language of particle accelerators to discuss the ion state and dynamics. We outline the differences between the above concepts, analyze challenges of the large ring with a revolving chain of ions, and propose goals for the research and development required to enable future quantum computers with 1000 times more qubits than available today. The challenge of creating such a large-scale quantum system while maintaining the necessary coherence of the qubits and the high fidelity of quantum logic operations is significant. Performing analog quantum simulations may be an achievable initial goal for such a device. Quantum calculations and simulations of complex quantum systems will move forward both the fundamental science and the applied research. Nuclear and particle physics, many-body quantum systems, lattice gauge theories, and nuclear structure calculations are just a few examples in which a large-scale quantum simulation system will become a very powerful tool to move forward our understanding of nature.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Large-scale Hydrogen Storage – Risk Assessment Seattle City Light and Port of Seattle [Abstract]

This CRADA presents the strategy that Pacific Northwest National Laboratory (PNNL) and Sandia National Laboratories (SNL) will take to support Seattle City Light (SCL), and the Port of Seattle (Port) in performing a risk assessment of large-scale hydrogen storage. Risk assessment is often used to ensure that adequate measures are taken to protect workers and the public, the environment, infrastructure, and assets. A detailed risk assessment can also be used to direct funding and upgrades, to specific components and sub-systems in order to mitigate risks to the larger system. In this way risk assessments are often employed as a part of a larger risk management strategy, with the goal of minimizing the occurrence of hazards and to identify means to limit their consequences. Risk assessment is often used to engage and inform regulators, and to communicate how specific regulations are being met. However, it is important to note that the proposed work is not intended for SCL and the Port to use in order to gain regulatory acceptance for their proposed activities. The work performed as a part of this effort will be a preliminary risk assessment for early-stage component and system designs and should be considered research and development (R&D). As such, the proposed work will be performed to a quality level and design maturity consistent with R&D and is not considered appropriate for final safety analysis and regulatory compliance purposes. Previous and on-going work at SCL and the Port demonstrated the utility of deploying hydrogen systems at the Port. The deployment of hydrogen at the Port is a part of a larger vision of using hydrogen to address a range of issues for SCL and the Port. These include large-scale fueling of MD/HD vehicles, cargo-handling equipment (CHE), and harbor vessels to reduce emissions; support of adjacent LD vehicles; support of critical port operations during extreme events (i.e., resiliency); deferral of more capital- and time-intensive electrical distribution system upgrades while still supporting evolving port operations and decarbonization efforts; facilitating electrification by establishing energy storage as a grid resource, starting at strategic port locations; creation of a flexible market resource that can be used by SCL to generate revenue via arbitrage; support of planned future maritime operations that involve heavy use of hydrogen for ocean-going vessels; and future end-use applications involving natural gas pipeline hydrogen injection. Ultimately, the success of these activities is underpinned by the deployed storage capacity. Large-scale deployment of hydrogen systems will require hydrogen storage at a scale that has not been demonstrated. In addition, the ideal location for such multi-use systems is near the end user which will often necessitate deploying into urban and/or industrial areas. A detailed risk assessment using the Port as a test case is necessary to ensure the deployment of large-scale hydrogen is successful. Many technologies have been proposed for hydrogen storage; however, these technologies need to be analyzed as they apply to an actual site. The physical infrastructure and hydrogen use cases for the Port will be analyzed, and a risk assessment for compressed hydrogen, liquified hydrogen, and Liquid Organic Hydrogen Carrier (LOHC) storage will be performed. These risk assessments will be useful for understanding how each of these technologies would perform in terms of facility and public safety. The operating states of the proposed hydrogen systems at the Port will be analyzed and incorporated into the storage risk assessment. Scalability will also be analyzed to understand how future port uses would affect the overall risk assessment. Finally, using the risk assessment as a tool to inform engagement and to gain stakeholder acceptance will be explored.

08 HYDROGEN↗
DOE OSTI2025

A comparative analysis of numerical approaches for the description of gas flow in clay-based repository systems: From a laboratory to a large-scale gas injection test

There is nowadays a consensus among many countries that geological disposal is a favourable solution for the long-term management. Although different host formations and different barrier systems are under consideration around the world, clay-based materials form an important component for waste isolation in most national programmes. Hence, a good comprehension of the effect of gas flow on the hydro-mechanical behaviour of clay-based soils is essential, both at laboratory and field scale. Task B under the international cooperative project DECOVALEX-2023 has recently shown that, after some enhancement, models can be employed to reproduce laboratory scale tests, even with different sample geometries 37 . However, further work is required to understand whether they can be applied to simulate a large-scale experiment. Up-scaling of models for the advective transport of gas through clay-based low permeable material presents a number of problems related to the difficulty in obtaining consistent hydrogeological parameters and constitutive relationships at both laboratory and field scale. Based on a unique dataset from a large-scale gas injection test (Lasgit) performed at the Äspö Hard Rock Laboratory (Sweden), Task B within DECOVALEX-2023 has explored the refinement of these numerical strategies applied to the simulation of gas flow. Work performed within the task reveals that codes do not need to be substantially modified from the laboratory models to reproduce full-scale tests: indeed, model parameters calibrated and validated at laboratory scale have been applied to predict field scale gas flow at Lasgit, including peak gas pressure and injected cumulative gas volume. By means of (1) the introduction of interfaces between blocks to reflect the experimental configuration and the (2) adjustment of some parameters (e.g., higher permeability), the updated models are able to represent most of the key features observed in the experimental data, even at a large scale.

Tamayo-Mas, E↗
DOE OSTI2022

Energy balance and Alfvén Mach numbers in compressible magnetohydrodynamic turbulence with a large-scale magnetic field

Energy equipartition is a powerful theoretical tool for understanding astrophysical plasmas. It is invoked, for example, to measure magnetic fields in the interstellar medium (ISM), as evidence for small-scale turbulent dynamo action, and, in general, to estimate the energy budget of star-forming molecular clouds. Here, in this study, we motivate and explore the role of the volume-averaged root-mean-squared (rms) magnetic coupling term between the turbulent, δB , and large-scale, B 0 , fields, $\langle$(δB·B 0 ) 2 $\rangle$$_{V}^{1/2}$. By considering the second moments of the energy balance equations we show that the rms coupling term is in energy equipartition with the volume-averaged turbulent kinetic energy for turbulence with a sub-Alfvénic large-scale field. Under the assumption of exact energy equipartition between these terms, we derive relations for the magnetic and coupling term fluctuations, which provide excellent, parameter-free agreement with time-averaged data from 280 numerical simulations of compressible magnetohydrodynamic (MHD) turbulence. Furthermore, we explore the relation between the turbulent mean field and total Alfvén Mach numbers, and demonstrate that sub-Alfvénic turbulence can only be developed through a strong, large-scale magnetic field, which supports an extremely super-Alfvénic turbulent magnetic field. This means that the magnetic field fluctuations are significantly subdominant to the velocity fluctuations in the sub-Alfvénic large-scale field regime. Throughout our study, we broadly discuss the implications for observations of magnetic fields and understanding the dynamics in the magnetized ISM.

79 ASTRONOMY AND ASTROPHYSICS↗