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At least 667 records · Page 37

Automatic Volume Balancing for Online Refueling in Molten Salt Reactor Simulations with SCALE

This work introduces recently implemented capabilities in the SCALE code system’s TRITON reactor physics sequence that improve molten salt reactor (MSR) modeling: (1) a volume balancing option, which automatically balances the volumes of the fed material with a corresponding material removal to maintain fixed mixture volumes in the neutron transport model and accurate densities, and (2) continuous feed from mixtures, which enables users to define material feed streams directly from salt mixture definitions rather than individual nuclides. The new capabilities were demonstrated via SCALE/TRITON simulations of two representative MSR concepts. Simulations of the 180 MWth molten chloride fast reactor—a system with a fixed fuel salt volume in the reactor core—applied continuous refueling with fresh fuel salt. The results confirm approximately constant reactivity when the new volume balancing capability is used. Additionally, excellent agreement with a manual feed-and-drain method for volume balancing further verified the new implementation. Simulations of the 400 MWth EIRENE reactor, an integral MSR in which the salt volume may grow over time within the reactor core, demonstrated the capability to represent growing salt volume within the TRITON depletion calculation. Compared with reference solutions, the results show consistent trends in reactivity and isotopic evolution, confirming that these new user-friendly capabilities provide accurate, physically consistent approaches for modeling MSRs in SCALE.

Elzohery, Rabab [ORNL] (ORCID:0000000160043633)↗

Getting a THUMP from a WIMP

Producing an acceptable thermal relic abundance of dark matter with masses >> 10 2 TeV is a challenge. We propose a novel mechanism where GeV-scale states establish a tiny thermal relic abundance for dark matter, which is later promoted to ultra massive status by a very light scalar. We refer to this dark matter as a THermal Ultra Massive Particle (THUMP). Direct detection of THUMPs can be naturally expected due to large scattering cross sections mediated by low mass states that couple THUMPs to the Standard Model. Our model generically leads to signals for the associated GeV-scale states at accelerator experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Predicting octane number from microscale flame dynamics

The standard method for measuring the octane number of fuels requires large sample volumes (~1L) and access to a Cooperative Fuel Research (CFR) engine. This method reliably quantifies the knock resistance of fuels in spark ignition engines, however the large sample volume requirement prevents testing of new experimental fuels (often produced in quantities of just ~1 mL), and the large equipment size impedes mobile, decentralized testing of remote fuel supplies. When direct measurements of octane number are impractical, other methods are needed. Micro flow reactors have shown promise in measuring ignition characteristics that are sensitive to octane number, and they are compact and operate on small volumes (~1 mL). This study uses simulations to demonstrate that measurements of the unsteady flame dynamics in a micro flow reactor can provide valuable data for accurate octane number predictions. Simulations of the flow reactor are used to obtain ignition characteristics for over 200 ethanol-toluene primary reference fuels (ETPRF) and 21 biofuel blends. A feed forward neural network is trained using the micro flow reactor ignition characteristics, fuel properties, and known research octane number (RON) and motor octane number (MON) for the ETPRF fuels. Here, the neural network is able to predict the RON and MON of the biofuel blends to within 2 octane number on average. Prediction results are compared to other methods available in the literature. Additional neural network models are trained that show improved prediction accuracy as additional fuel training data becomes available.

02 PETROLEUM↗

Numerical study of the effect of the shape of the phase diagram on the eutectic freezing temperature

To evaluate the reliability of metal-carbon eutectic systems as fixed points for the next generation of high-temperature standards the effect of thermodynamic properties related to the shape of eutectic phase diagram on the freezing temperature is investigated within the context of the numerical multi-phase-field model. The partition coefficient and liquidus slopes of the two solids involved in the eutectic reaction are varied deliberately and independently. The difference between the eutectic temperature and the freezing temperature is determined in dependence of the solid/liquid (s/l) interface shape and concentration. Where appropriate reference is made to the Jackson-Hunt analytical theory. It is shown that there are mainly two typical conditions to decrease the undercooling: 1) a small liquidus slope and 2) the associated difference between the eutectic composition and the liquid composition during solidification.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

On the applicability of the standard kinetic theory to the study of nanoplasmas

Kinetic theory applies to systems with a large number of particles, while nanoplasma generated by the interaction of ultra–short laser pulses with atomic clusters are systems composed by a relatively small number (10{sup 2} ÷ 10{sup 4}) of electrons and ions. In the paper, the applicability of the kinetic theory for studying nanoplasmas is discussed. In particular, two typical phenomena are investigated: the collisionless expansion of electrons in a spherical nanoplasma with immobile ions and the formation of shock shells during Coulomb explosions. The analysis, which is carried out comparing ensemble averages obtained by solving the exact equations of motion with reference solutions of the Vlasov-Poisson model, shows that for the dynamics of the electrons the error of the usually employed models is of the order of few percents (but the standard deviation in a single experiment can be of the order of 10%). Instead, special care must be taken in the study of shock formation, as the discrete structure of the electric charge can destroy or strongly modify the phenomenon.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Communication: Orientational self-ordering of spin-labeled cholesterol analogs in lipid bilayers in diluted conditions

Lipid-cholesterol interactions are responsible for different properties of biological membranes including those determining formation in the membrane of spatial inhomogeneities (lipid rafts). To get new information on these interactions, electron spin echo (ESE) spectroscopy, which is a pulsed version of electron paramagnetic resonance (EPR), was applied to study 3β-doxyl-5α-cholestane (DCh), a spin-labeled analog of cholesterol, in phospholipid bilayer consisted of equimolecular mixture of 1,2-dipalmitoyl-sn-glycero-3-phosphocholine and 1,2-dioleoyl-sn-glycero-3-phosphocholine. DCh concentration in the bilayer was between 0.1 mol.% and 4 mol.%. For comparison, a reference system containing a spin-labeled 5-doxyl-stearic acid (5-DSA) instead of DCh was studied as well. The effects of “instantaneous diffusion” in ESE decay and in echo-detected (ED) EPR spectra were explored for both systems. The reference system showed good agreement with the theoretical prediction for the model of spin labels of randomly distributed orientations, but the DCh system demonstrated remarkably smaller effects. The results were explained by assuming that neighboring DCh molecules are oriented in a correlative way. However, this correlation does not imply the formation of clusters of cholesterol molecules, because conventional continuous wave EPR spectra did not show the typical broadening due to aggregation of spin labels and the observed ESE decay was not faster than in the reference system. So the obtained data evidence that cholesterol molecules at low concentrations in biological membranes can interact via large distances of several nanometers which results in their orientational self-ordering.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

IRMA

IRMA (In)elastic Representation of Materials As S(α,β) evaluations IRMA turns one phonon model into three outputs that usually require three separate tool chains: an evaluated nuclear-data file, predicted neutron-scattering spectra, and scattering kernels for Monte Carlo transport. The three outputs draw on a single, consistent description of the material, so the evaluation, the spectroscopy that can validate it, and the transport that uses it always agree about the physics. Nuclear data. IRMA writes ENDF-6 File 7 thermal scattering evaluations on automatically constructed (α, β) grids. This part reimplements and generalizes NJOY's LEAPR: the classic kernels reproduce freshly generated NJOY2016 tapes digit for digit and published reference tapes to about 1e-4, and the generalized paths add the exact coherent one-phonon term, anisotropic Debye-Waller tensors, coherent elastic for arbitrary crystals, and a per-species partition for polyatomic materials. The tapes feed NJOY, AMPX, FUDGE, and every transport code downstream of them. Neutron spectroscopy. The irma.spectra forward model projects the same physics onto an instrument's kinematics and resolution: INS spectra for VISION and generic indirect geometries, and 2-D S(Q,E) powder maps for direct-geometry spectrometers, from a phonopy model or straight from a phonon DOS. It can be used to predict a proposed measurement before beam time; in analysis, it supplies the calculated single-scattering counterpart of a measured spectrum, from the same material description the evaluation was built from. Monte Carlo transport. The irma.ncrystal exporter writes per-temperature scattering kernels for the companion NCrystal plugin, so McStas, OpenMC, and other NCrystal-aware codes sample the same physics. The exported kernels carry the per-site anisotropic Debye-Waller tensors, keeping directional coherent-elastic physics that NCrystal's standard scalar treatment does not represent. With the same physics inside a transport code, an entire beamline becomes a virtual experiment: IRMA's end-to-end validation ran a custom McStas implementation of the ARCS spectrometer, assembled from the existing McVine and McStas models, against measured data. From a bare crystal structure. The irma mlip front end builds the phonon model itself: a structure file and a choice of potential are enough. Nine pretrained machine-learned interatomic potentials are supported, on a laptop CPU, with no first-principles calculation; an approximate phonon model for a new material costs minutes, not a DFT campaign, and the build emits prefilled inputs for all three outputs. The result is a good starting point rather than a finished evaluation: survey-quality physics with every parameter exposed for review. A converged atomistic calculation enters the same way, as a phonopy model, when higher fidelity is needed.

Ramic, Kemal [Oak Ridge National Laboratory (ORNL)↗

Integrated Computational Study of Radiation Damage Effects in Grade 92 Steel and Alloy 709

Radiation resistance of austenitic alloy 709 (named as A709) and ferritic-martensitic steel Grade 92 (G92) were investigated in this project using 316H and Grade 91 (G91) as references, respectively. In the meantime, a model 709 (M709) alloy (Fe-20Cr-24Ni) was prepared to study the matrix response to irradiation. Samples machined from the tab section of three creep-ruptured A709 samples, i.e., 17,106 h at 600 °C, 12,014 h at 650 °C, and 16,448 h at 700 °C, were included in this work to evaluate radiation effect on the long-term “thermally aged” samples. Primarily Fe 2+ ion irradiation was conducted at 350, 600 and 670 °C for up to 75 displacements per atom (dpa), together with a few proton irradiation experiments at 380–670 °C for up to 1.5 dpa. Additionally, four neutron-irradiated NF709 samples (3.22–8 dpa at ~430–469 °C) were examined. The samples were examined by transmission electron microscopy (TEM), scanning electron microscopy (SEM) and energy dispersive x-ray spectroscopy (EDS) for microstructures and nanoindentation for radiation-hardening. Unlike the negligible hardening after irradiation at 670 °C, irradiation to nominal 2.5–50 dpa at 350 °C resulted in radiation-hardening of 13.5±5.4 % for A709, which was comparable to that of 13.4±6.2 % for M709 and moderately lower than that of 20.1±5.6 % for 316H. The radiation-hardening induced by the same irradiation condition to the “thermally aged” samples was comparable to A709, which were hardened by 15.0±8.2 %, 13.5±6.0 %, and 10.1±6.1 % for the 600, 650, and 700 °C aged samples, respectively. The radiation-hardening of A709 is significantly lower than that (~94±9 %) of neutron-irradiated NF709 to 8 dpa at ~430 °C.

36 MATERIALS SCIENCE↗

Integrated Computational Study of Radiation Damage Effects in Grade 92 Steel and Alloy 709

Radiation resistance of austenitic alloy 709 (named as A709) and ferritic-martensitic steel Grade 92 (G92) were investigated in this project using 316H and Grade 91 (G91) as references, respectively. In the meantime, a model 709 (M709) alloy (Fe-20Cr-24Ni) was prepared to study the matrix response to irradiation. Samples machined from the tab section of three creep-ruptured A709 samples, i.e., 17,106 h at 600 °C, 12,014 h at 650 °C, and 16,448 h at 700 °C, were included in this work to evaluate radiation effect on the long-term “thermally aged” samples. Primarily Fe 2+ ion irradiation was conducted at 350, 600 and 670 °C for up to 75 displacements per atom (dpa), together with a few proton irradiation experiments at 380–670 °C for up to 1.5 dpa. Additionally, four neutron-irradiated NF709 samples (3.22–8 dpa at ~430–469 °C) were examined. The samples were examined by transmission electron microscopy (TEM), scanning electron microscopy (SEM) and energy dispersive x-ray spectroscopy (EDS) for microstructures and nanoindentation for radiation-hardening

36 MATERIALS SCIENCE↗

Muon to Positron Conversion

Lepton-flavor violation (LFV) has been discovered in the neutrino sector by neutrino oscillation experiments. The minimal extension of the Standard Model (SM) to include neutrino masses allows LFV in the charged sector (CLFV) at the loop level, but at rates that are too small to be experimentally observed. Lepton-number violation (LNV) is explicitly forbidden even in the minimally extended SM, so the observation of an LNV process would be unambiguous evidence of physics beyond the SM. The search for the LNV and CLFV process μ−+N(A,Z)→e++N′(A,Z−2) (referred to as μ−→e+) complements 0νββ decay searches, and is sensitive to potential flavor effects in the neutrino mass-generation mechanism. A theoretical motivation for μ−→e+ is presented along with a review of the status of past μ−→e+ experiments and future prospects. Special attention is paid to an uncertain and potentially dominant background for these searches, namely, radiative muon capture (RMC). The RMC high energy photon spectrum is theoretically understudied and existing measurements insufficiently constrain this portion of the spectrum, leading to potentially significant impacts on current and future μ−→e+ work.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Optical and Near-infrared Spectra of σ Orionis Isolated Planetary-mass Objects

We have obtained low-resolution optical (0.7–0.98 μ m) and near-infrared (1.11–1.34 μ m and 0.8–2.5 μ m) spectra of 12 isolated planetary-mass candidates ( J = 18.2–19.9 mag) of the 3 Myr σ Orionis star cluster with the aim of determining the spectroscopic properties of very young, substellar dwarfs and assembling a complete cluster mass function. We have classified our targets by visual comparison with high- and low-gravity standards and by measuring newly defined spectroscopic indices. We derived L0–L4.5 and M9–L2.5 using high- and low-gravity standards, respectively. Our targets reveal clear signposts of youth, thus corroborating their cluster membership and planetary masses (6–13 M {sub Jup}). These observations complete the σ Orionis mass function by spectroscopically confirming the planetary-mass domain to a confidence level of ∼75%. The comparison of our spectra with BT-Settl solar metallicity model atmospheres yields a temperature scale of 2350–1800 K and a low surface gravity of log g ≈ 4.0 [cm s{sup −2}], as would be expected for young planetary-mass objects. We discuss the properties of the cluster’s least-massive population as a function of spectral type. We have also obtained the first optical spectrum of S Ori 70, a T dwarf in the direction of σ Orionis. Our data provide reference optical and near-infrared spectra of very young L dwarfs and a mass function that may be used as templates for future studies of low-mass substellar objects and exoplanets. The extrapolation of the σ Orionis mass function to the solar neighborhood may indicate that isolated planetary-mass objects with temperatures of ∼200–300 K and masses in the interval 6–13 M {sub Jup} may be as numerous as very low-mass stars.

79 ASTRONOMY AND ASTROPHYSICS↗

5D quantum dynamics of the H{sub 2}@SWNT system: Quantitative study of the rotational-translational coupling

The dynamics of the dihydrogen molecule when confined in carbon nanotubes with different chiralities and diameters are studied by using a 5 dimensional model considering the most relevant degrees of freedom of the system. The nuclear eigenstates are calculated for an (8,0) and a (5,0) carbon nanotubes by the State-Average Multiconfigurational Time-dependent Hartree, and then studied using qualitative tools (mapping of the total wave functions onto given subspaces) and more rigorous analysis (different kinds of overlaps with reference functions). The qualitative analysis is seen to fail due to a strong coupling between the internal and translational degrees of freedom. Using more accurate tools allows us to gain a deeper insight into the behaviour of confined species.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Adaptive multiconfigurational wave functions

A method is suggested to build simple multiconfigurational wave functions specified uniquely by an energy cutoff Λ. These are constructed from a model space containing determinants with energy relative to that of the most stable determinant no greater than Λ. The resulting Λ-CI wave function is adaptive, being able to represent both single-reference and multireference electronic states. We also consider a more compact wave function parameterization (Λ+SD-CI), which is based on a small Λ-CI reference and adds a selection of all the singly and doubly excited determinants generated from it. We report two heuristic algorithms to build Λ-CI wave functions. The first is based on an approximate prescreening of the full configuration interaction space, while the second performs a breadth-first search coupled with pruning. The Λ-CI and Λ+SD-CI approaches are used to compute the dissociation curve of N{sub 2} and the potential energy curves for the first three singlet states of C{sub 2}. Special attention is paid to the issue of energy discontinuities caused by changes in the size of the Λ-CI wave function along the potential energy curve. This problem is shown to be solvable by smoothing the matrix elements of the Hamiltonian. Our last example, involving the Cu{sub 2}O{sub 2}{sup 2+} core, illustrates an alternative use of the Λ-CI method: as a tool to both estimate the multireference character of a wave function and to create a compact model space to be used in subsequent high-level multireference coupled cluster computations.

74 ATOMIC AND MOLECULAR PHYSICS↗

Development of Defenses against False Data Injection Attacks for Nuclear Power Plants

With the recent successful attempts against the digital control systems of critical infrastructures, there is a need to develop new defense strategies that recognize two important realities, 1) state- sponsored attackers can rely on a number of techniques including espionage, social engineering, and brute force techniques, etc. to gain access to the raw data used to control system behavior, 2) attackers can falsify operational data in manners that do not trigger conventional outlier/anomaly detection techniques in order to go undetected, which is referred to as false data injection attacks. Therefore, there is a strong need to explore another class of defense measures, referred to as physical process defense, serving as a new line of defense in the event existing defenses relying on information protection measures are breached. This physical process defenses utilize the physics and engineering models of the system to build unique signatures for genuine system behavior. If successful, the signatures would be able to detect attacks that falsify the operational data and render them harmless before they can inflict physical damage on the system. This report is focused on exploring the feasibility of physical process defenses for nuclear reactors, and their associated functional requirements to maximize their resiliency against state-sponsored, or equivalent, attackers.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Best Practice for the Commercial Deployment of Carbon Dioxide Geologic Storage: Adaptive Management Approach

The Plains CO 2 Reduction (PCOR) Partnership is one of seven regional partnerships formed as part of the U.S. Department of Energy’s National Energy Technology Laboratory Regional Carbon Sequestration Partnerships (RCSP) Initiative. The RCSP Initiative is focused on the safe and long-term storage of CO 2 to support the commercial deployment of carbon capture and storage (CCS). To that end, the PCOR Partnership has spent over 10 years developing, testing, and validating the best methods and technologies to conduct the geologic storage of CO 2 (hereafter referred to as CO 2 storage). Through this effort, the PCOR Partnership has formalized an adaptive management approach (AMA) for the commercial development of CO 2 storage projects. The use of this approach, which draws upon the collective experience and lessons learned from the PCOR Partnership, represents best practice for advancing CO 2 storage projects toward commercial deployment. At the heart of the AMA are four technical elements necessary for any successful CO 2 storage project: 1) site characterization; 2) modeling and simulation; 3) risk assessment; and 4) monitoring, verification, and accounting (MVA). Each of these elements plays a key role in gathering and assessing site-specific data that provide a fundamental understanding of the storage complex and its performance. While each of the four technical elements can provide useful data independently, integrating them through the AMA yields a streamlined, fit-for-purpose strategy for the commercial deployment of CO 2 storage. Key to this integration and resulting best practice are feedback loops that allow the results of each element to serve as inputs to the others. Each iteration of the AMA creates an improved understanding of the storage complex and thus more targeted and efficient applications of the technical elements. For the purpose of establishing an adaptive management framework, hard lines have been drawn between the technical elements of the AMA. However, in practice, the rapid and seamless interaction between the elements can blur these lines. For example, to aid in the analysis and interpretation of site characterization data, a static geocellular model is often required. While this model development is part of the technical element, modeling and simulation, it is an integral part of the site characterization effort. Likewise, much of the monitoring data collected as part of the MVA technical element can be used to inform site characterization. This back-and-forth flow of data and use of models between the technical elements continues throughout the project.

54 ENVIRONMENTAL SCIENCES↗

Understanding the Formation of Complex Phases: The Case of FeSi 2

One of the fundamental goals of materials science is to understand and predict the formation of complex phases. In this study, FeSi 2 is considered as an illustration of complex phase formation. Although Fe and Si both crystallize with a simple structure, namely, body-centered cubic (bcc A2) and diamond (A4) structures, respectively, it is rather intriguing to note the existence of two complex structures in the Si-rich part of the phase diagram around FeSi 2 : α-FeSi 2 at high temperatures (HT) with a slight iron-deficient structure and β-FeSi2 (also referred to as Fe 3 Si 7 ) at low temperatures (LT). We re-analyze the geometry of these two phases and rely on approximant phases that make the relationship between these two phases simple. To complete the analysis, we also introduce a surrogate of the C16 phase that is observed in FeGe 2 . We clearly identify the relationship that exists between these three approximant phases, corroborated by a ground-state analysis of the Ising model for describing ordering that takes place between the transition metal element and the “vacancies”. This work is further supported by ab initio electronic structure calculations based on density functional theory in order to investigate properties and transformation paths. Finally, extension to other alloys, including an entire class of alloys, is discussed.

36 MATERIALS SCIENCE↗

Global Geo-processed Data of Aquifer Properties by 0.5° Grid, Country and Water Basins

This repository of global hydrogeologic datasets contains aquifer properties on 0.5° scale, including depth to groundwater (Fan et al., 2013), aquifer thickness (de Graaf et al., 2015), WHYMap aquifer classes (Richts et al., 2011), porosity and permeability (Gleeson et al., 2014), digitized and geo-processed from their respective sources. Globally gridded aquifer properties could be used independently to estimate global groundwater availability or used as critical inputs to the superwell model to simulate groundwater extraction and provide estimates of pumped volumes and unit costs under user-specific scenarios. Key resources related to this data are: Niazi, H., Ferencz, S., Graham, N., Yoon, J., Wild, T., Hejazi, M., Watson, D., & Vernon, C. (2024; In-prep). Long-term Hydro-economic Assessment Tool for Evaluating Global Groundwater Cost and Supply: Superwell v1. Geoscientific Model Development. superwell model repository which uses this data to simulate groundwater extraction and provides estimates of the global extractable volumes and unit-costs ($/km3) of accessible groundwater production under user-specified extraction scenarios. Repository Overview Main output: aquifer_properties.csv contains all processed outputs, including aquifer properties like porosity, permeability, aquifer thickness, and depth to groundwater. shapefiles.zip: contains all digitized GIS databases and shapefile for all aquifer properties prep_inputs.R: R script that processes the shapefiles to produce the aquifer_properties file plot_inputs.R: R script for plotting the maps and conducting preliminary analysis on the available groundwater volume basin_to_country_mapping.csv, basin_country_region_mapping.csv and continent_county_mapping.csv provide the mapping between continents, 32 energy-economic macro regions, countries, and water basins for post-processing aquifer_properties.csv Maps: Each map visualizes the spatial distribution of one of the aquifer properties across the globe map_in_Porosity.png map_in_Permeability.png map_in_Aquifer_thickness.png map_in_Depth_to_water.png map_in_Grid_area_km.png map_in_WHYClass.png Sample inputs sample_inputs.py: this script samples inputs from the aquifer_properties dataset, ensuring the sampled and original inputs maintain the same distributions sampled_data_100.csv contains 100 sampled data points and sampled_data_100.png compares their distributions Dataset Overview The main outputs are consolidated in a comprehensive aquifer_properties.csv file and include the following fields: GridCellID: Unique identifier for each (roughly 0.5°) grid cell Continent: Continent name Country: Country name GCAM_basin_ID: Identifier for GCAM hydrologic basin Basin_long_name: Full name of the basin WHYClass: Hydrogeologic classification based on WHYMap aquifer classes (Richts et al., 2011) Porosity: Soil porosity (%) (Gleeson et al., 2014) Permeability: Soil permeability (in square meters; Gleeson et al., 2014) Aquifer_thickness: Thickness of the aquifer (in meters; de Graaf et al., 2015) Depth_to_water: Depth to groundwater (in meters; Fan et al., 2013) Grid_area: Area of the grid cell (in square meters) Key References The datasets are digitized versions of global hydrogeologic properties from the following key literature sources: Depth to Groundwater: Fan, Y., Li, H., & Miguez-Macho, G. (2013). Global Patterns of Groundwater Table Depth. Science, 339(6122), 940-943. https://doi.org/10.1126/science.1229881 Aquifer Thickness: de Graaf, I. E. M., Sutanudjaja, E. H., van Beek, L. P. H., & Bierkens, M. F. P. (2015). A high-resolution global-scale groundwater model. Hydrol. Earth Syst. Sci., 19(2), 823-837. https://doi.org/10.5194/hess-19-823-2015 Porosity and Permeability: Gleeson, T., Moosdorf, N., Hartmann, J., & van Beek, L. P. H. (2014). A glimpse beneath earth's surface: GLobal HYdrogeology MaPS (GLHYMPS) of permeability and porosity. Geophysical Research Letters, 41(11), 3891-3898. https://doi.org/10.1002/2014GL059856 Aquifer classes: Richts, A., Struckmeier, W. F., & Zaepke, M. (2011). WHYMAP and the Groundwater Resources Map of the World 1:25,000,000. In J. A. A. Jones (Ed.), Sustaining Groundwater Resources: A Critical Element in the Global Water Crisis (pp. 159-173). Springer Netherlands. https://doi.org/10.1007/978-90-481-3426-7_10 Cite as Niazi, H., Watson, D., Hejazi, M., Yonkofski, C., Ferencz, S., Vernon, C., Graham, N., Wild, T., & Yoon, J. (2024). Global Geo-processed Data of Aquifer Properties by 0.5° Grid, Country and Water Basins. MSD-LIVE Data Repository. https://doi.org/10.57931/2307831 Contact Reach out to Hassan Niazi or open an issue in superwell repository for questions or suggestions.

aquifer thickness↗

Global Geo-processed Data of Aquifer Properties by 0.5° Grid, Country and Water Basins

This repository of global hydrogeologic datasets contains aquifer properties on 0.5° scale, including depth to groundwater (Fan et al., 2013), aquifer thickness (de Graaf et al., 2015), WHYMap aquifer classes (Richts et al., 2011), recharge (Döll and Fiedler, 2008; Gleeson et al., 2016), lakes (Messager et al., 2016), porosity and permeability (Gleeson et al., 2014), digitized and geo-processed from their respective sources. Globally gridded aquifer properties could be used independently to estimate global groundwater availability or used as critical inputs to the superwell model to simulate groundwater extraction and provide estimates of pumped volumes and unit costs under user-specific scenarios. Key resources related to this data are: Niazi, H., Ferencz, S. B., Graham, N. T., Yoon, J., Wild, T. B., Hejazi, M., Watson, D. J., & Vernon, C. R. (2025). Long-term hydro-economic analysis tool for evaluating global groundwater cost and supply: Superwell v1.1. Geoscientific Model Development, 18(5), 1737-1767. https://doi.org/10.5194/gmd-18-1737-2025 superwell model repository which uses this data to simulate groundwater extraction and provides estimates of the global extractable volumes and unit-costs ($/km3) of accessible groundwater production under user-specified extraction scenarios. Repository Overview Main output: aquifer_properties_rec.csv contains all processed outputs, including aquifer properties like porosity, permeability, recharge, lake areas, aquifer thickness, and depth to groundwater. shapefiles.zip: contains all digitized GIS databases and shapefile for all aquifer properties prep_inputs.R and prep_inputs_recharge_lakes.R: R scripts that process the shapefiles to produce the aquifer_properties_rec.csv file plot_inputs.R: R script for plotting the maps and conducting preliminary analysis on the available groundwater volume basin_to_country_mapping.csv, basin_country_region_mapping.csv and continent_county_mapping.csv provide the mapping between continents, 32 energy-economic macro regions, countries, and water basins for post-processing aquifer_properties_rec.csv Maps: Each map visualizes the spatial distribution of one of the aquifer properties across the globe map_in_Porosity.png map_in_Permeability.png map_in_Aquifer_thickness.png map_in_Depth_to_water.png map_in_Recharge.png map_in_Grid_area_km.png map_in_Lake_area_km.png map_in_WHYClass.png Sample inputs sample_inputs.py: this script samples inputs from the aquifer_properties_rec dataset, ensuring the sampled and original inputs maintain the same distributions sampled_data_100.csv contains 100 sampled data points and sampled_data_100.png compares their distributions Dataset Overview The main outputs are consolidated in a comprehensive aquifer_properties_rec.csv file and include the following fields: GridCellID: Unique identifier for each (roughly 0.5°) grid cell Continent: Continent name Country: Country name GCAM_basin_ID: Identifier for GCAM hydrologic basin Basin_long_name: Full name of the basin WHYClass: Hydrogeologic classification based on WHYMap aquifer classes (Richts et al., 2011) Porosity: Soil porosity (%) (Gleeson et al., 2014) Permeability: Soil permeability (in square meters; Gleeson et al., 2014) Aquifer_thickness: Thickness of the aquifer (in meters; de Graaf et al., 2015) Depth_to_water: Depth to groundwater (in meters; Fan et al., 2013) Recharge: long-term annual averaged recharge rates (in m/yr; Döll and Fiedler, 2008; Gleeson et al., 2016) Grid_area: Area of the grid cell (in square meters) Lakes_area: Area of inland lakes (in square meters; Messager et al., 2016) Key References The datasets are digitized versions of global hydrogeologic properties from the following key literature sources: Depth to Groundwater: Fan, Y., Li, H., & Miguez-Macho, G. (2013). Global Patterns of Groundwater Table Depth. Science, 339(6122), 940-943. https://doi.org/10.1126/science.1229881 Aquifer Thickness: de Graaf, I. E. M., Sutanudjaja, E. H., van Beek, L. P. H., & Bierkens, M. F. P. (2015). A high-resolution global-scale groundwater model. Hydrol. Earth Syst. Sci., 19(2), 823-837. https://doi.org/10.5194/hess-19-823-2015 Porosity and Permeability: Gleeson, T., Moosdorf, N., Hartmann, J., & van Beek, L. P. H. (2014). A glimpse beneath earth's surface: GLobal HYdrogeology MaPS (GLHYMPS) of permeability and porosity. Geophysical Research Letters, 41(11), 3891-3898. https://doi.org/10.1002/2014GL059856 Aquifer classes: Richts, A., Struckmeier, W. F., & Zaepke, M. (2011). WHYMAP and the Groundwater Resources Map of the World 1:25,000,000. In J. A. A. Jones (Ed.), Sustaining Groundwater Resources: A Critical Element in the Global Water Crisis (pp. 159-173). Springer Netherlands. https://doi.org/10.1007/978-90-481-3426-7_10 Recharge: Döll, P., & Fiedler, K. (2008). Global-scale modeling of groundwater recharge. Hydrol. Earth Syst. Sci., 12(3), 863-885. https://doi.org/10.5194/hess-12-863-2008; Gleeson, T., Befus, K. M., Jasechko, S., Luijendijk, E., & Cardenas, M. B. (2016). The global volume and distribution of modern groundwater. Nature Geoscience, 9(2), 161-167. https://doi.org/10.1038/ngeo2590 Inland Lakes: Messager, M. L., Lehner, B., Grill, G., Nedeva, I., & Schmitt, O. (2016). Estimating the volume and age of water stored in global lakes using a geo-statistical approach. Nature Communications, 7(1), 13603. https://doi.org/10.1038/ncomms13603 Cite as Niazi, H., Watson, D., Hejazi, M., Yonkofski, C., Ferencz, S., Vernon, C., Graham, N., Wild, T., & Yoon, J. (2024). Global Geo-processed Data of Aquifer Properties by 0.5° Grid, Country and Water Basins. MultiSector Dynamics-Living, Intuitive, Value-adding, Environment. https://doi.org/10.57931/2484226 Contact Reach out to Hassan Niazi or open an issue in the superwell repository for questions or suggestions.

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