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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Soot and PAH formation in high pressure spray pyrolysis of gasoline and diesel fuels

Time-resolved soot and PAH formation from gasoline and diesel spray pyrolysis are visualized and quantified using diffuse back illumination (DBI) and laser induced fluorescence (LIF) at 355 nm, respectively, in a constant-volume vessel at 60 bar from 1400 to 1700 K for up to 30 ms. The delay, maximum formation rate, and yield of soot and PAHs are compared across fuels and temperatures and correlated with the yield sooting indices on either the mass or mole basis. The delays generally decrease with increasing temperature, and the formation rates of both PAHs and soot generally increase with temperature. The apparent PAH-LIF yield may decrease with temperature due to PAH growth and conversion into larger species, signal trapping, and thermal quneching. Soot yield generally increases with temperature. The mass-based YSI correlates reasonably well with soot delay, but YSI does not correlate well with soot yield. Here, the mass-based YSI is a more appropriate predictor of sooting propensity than the mole-based YSI.

42 ENGINEERING↗
DOE OSTI2018

Small-Angle Neutron Scattering Reveals Energy Landscape for Rhodopsin Photoactivation

Here, knowledge of the activation principles for G-protein-coupled receptors (GPCRs) is critical to development of new pharmaceuticals. Rhodopsin is the archetype for the largest GPCR family, yet the changes in protein dynamics that trigger signaling are not fully understood. Here we show that rhodopsin can be investigated by small-angle neutron scattering (SANS) in fully protiated detergent micelles under contrast matching to resolve light-induced changes in the protein structure. In SANS studies of membrane proteins, the zwitterionic detergent [(cholamidopropyl)dimethylammonio]-propanesulfonate (CHAPS) is advantageous because of the low contrast difference between the hydrophobic core and hydrophilic head groups as compared with alkyl glycoside detergents. Combining SANS results with quasielastic neutron scattering reveals how changes in volumetric protein shape are coupled (slaved) to the aqueous solvent. Upon light exposure, rhodopsin is swollen by the penetration of water into the protein core, allowing interactions with effector proteins in the visual signaling mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Performance and Emission Investigations of Jatropha and Karanja Biodiesels in a Single-Cylinder Compression-Ignition Engine Using Endoscopic Imaging

Biofuels produced from non-edible sources that are cultivated on marginal lands represent a viable source of renewable and carbon-neutral energy. In this context, biodiesel obtained from Jatropha and Karanja oil seeds have received significant interest, especially in South Asian subcontinent. Both of these fuels are produced from non-edible plant seeds with high oil content, which can be grown on marginal lands. In this research, we have investigated the performance and emission characteristics of Jatropha and Karanja methyl esters (biodiesel) and their blends with diesel. Another objective is to examine the effect of long-term storage on biodiesel’s oxidative stability. The biodiesels were produced at Indian Institute of Technology Kanpur, (IIT Kanpur), India, and the engine experiments were performed in a single cylinder, 4-stroke, compression ignition engine at Argonne National Laboratory (ANL), Chicago. An endoscope was used to visualize in-cylinder combustion events and examine the soot distribution. The effects of fuel and start of injection (SOI) on engine performance and emissions were investigated. Results indicated that ignition delay was shorter with biodiesel. Consequently the cylinder pressure and premixed heat release were higher for diesel compared to biodiesel. Engine performance data for biodiesel (J100, K100) and biodiesel blends (J30, K30) showed an increase in break thermal efficiency (BTE) (10.9%, 7.6% for biodiesel and blend, respectively), BSFC (13.1% and 5.6%), and NOx emission (9.8% and 12.9%), and a reduction in BSHC (8.64% and 12.9%), and BSCO (15.56% and 4.0%). The soot analysis from optical images qualitatively showed that biodiesel and blends produced less soot compared to diesel. The temperature profiles obtained from optical imaging further supported higher NOx in biodiesels and their blends compared to diesel. Additionally, the data indicated that retarding the injection timing leads to higher BSFC, but lower flame temperatures and NOx levels along with higher soot formation for all test fuels. The physicochemical properties such as fatty acid profile, cetane number, and oxygen content in biodiesels support the observed combustion and emission characteristics of the fuels tested in this study. Finally, the effect of long-term storage is found to increase the glycerol content, acid value and cetane number of the two biodiesels, indicating some oxidation of unsaturated fatty acids in the fuels.

09 BIOMASS FUELS↗
DOE OSTI2020

The ARM Data-oriented Metrics and Diagnostics Package for Climate Models - A New Tool for Evaluating Climate Models with Field Data

The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program User Facility produces ground-based long-term continuous unique measurements for atmospheric state, precipitation, turbulent fluxes, radiation, aerosol, cloud and the land surface, which are collected at multiple sites. These comprehensive datasets have been widely used to calibrate climate models and are proven to be invaluable for climate model development and improvement. This article introduces an evaluation package to facilitate the use of ground-based ARM measurements in climate model evaluation. The ARM data-oriented metrics and diagnostics package (ARM-DIAGS) includes both ARM observational datasets and a Python-based analysis toolkit for computation and visualization. The observational datasets are compiled from multiple ARM data products and specifically tailored for use in climate model evaluation. In addition, ARM-DIAGS also includes simulation data from models participating the Coupled Model Inter-comparison Project (CMIP), which will allow climate-modeling groups to compare a new, candidate version of their model to existing CMIP models. The analysis toolkit is designed to make the metrics and diagnostics quickly available to the model developers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Effect of X-ray Irradiation and Carnauba Wax Coating on Quality of Lime (Citrus latifolia Tan.) Fruit

The quality of Persian (Tahiti) lime (Citrus latifoliaTan.) fruit was determined following coating with carnauba wax and X-ray irradiation at doses suitable for disinfestation of quarantine pests. Fruit with or without carnauba wax coating were treated with irradiation doses of 0, 150, 300, or 450 Gy, and stored for 14 days at 13 °C and 6 days at 20 °C to simulate commercial transportation and marketing conditions from Hawaii to the continental United States. The fruit color, weight loss, total soluble solids (TSS) content, and titratable acidity (TA) were analyzed at 7, 14, and 14 + 6 days post irradiation. Wax coating significantly delayed fruit peel discoloration, and reduced fruit weight loss by more than 7% compared with the unwaxed controls. Irradiation did not affectΔEof the peel for coated fruit at day 14 + 6. Irradiation with or without coating did not affectΔEof flesh color, weight loss, TSS content, or TA. Wax coating combined with irradiation treatment of limes at doses ≤450 Gy ensured marketable visual quality and chemical composition while providing quarantine security.

Agriculture↗
DOE OSTI2021

Resilience of Interdependent Water and Power Systems: A Literature Review and Conceptual Modeling Framework

As increasing pressures of population growth and climate change arise, water and power systems (WPS) are becoming increasingly interdependent. This interdependency has resulted in an increased potential for cascading failures, whereby the service interruption of one system can propagate to interdependent ones. This paper makes four contributions. First, we present an extensive literature review in the field of integrated water and power resilience, leveraging both institutional and technical literature research landscapes. We compare various modeling approaches used to model interdependent WPS and discuss the different metrics and definitions that are typically employed to quantify and define resilience. Relevant challenges and gaps related to modeling tools and metrics are also discussed, and appropriate recommendations are made. Second, the paper presents a visualization prototype for interdependent WPS to showcase water and power system interdependencies and reveal co-managed resilience strategies that can be used to improve resilience under different types of common threats. Third, we provide a conceptual decision support framework that simultaneously optimizes a portfolio of co-managed resilience strategies in the face of multiple, uncertain threats and addresses WPS interdependencies. Finally, we present future trends regarding digitalization, integrated planning, collaborative governance, and equity needs for building more resilient WPS.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Evaluation of Geologic Carbon Storage Resource Estimates (SREs) of Cambrian Ordovician Units within the CarbonSAFE Prefeasibility Study Region Subtasks 4.2 and 4.3 – Topical Report

This report by the Indiana Geological & Water Survey (IGWS) assessed the storage resource estimate (SRE) of Cambrian-Ordovician stratigraphic units located within the CarbonSAFE prefeasibility area within the Illinois Basin. A comprehensive data set of wireline logs and petrophysical information was used. These data include core analysis for porosity and permeability, and existing well data including location and stratigraphic information. This report includes storage resource estimates (SREs) for four potential storage reservoirs (Upper Ordovician Trenton Limestone/Black River Group, Middle Ordovician St. Peter Sandstone, Lower Ordovician and Upper Cambrian Knox Supergroup, including a separate assessment for the lower Knox Potosi Dolomite. The resultant SREs volumes are displayed using georeferenced maps and boxplots. The latter allow for comparing data statistics (mean values and variability) between five methods employed for the SRE calculations. Differences observed in SRE results from the five methods are mainly attributable to differences in the data used for porosity in each method. ArcMap 10.5.1 software was used to portray SREs to help visualize spatial variance of estimates for each methodology, and more importantly, to highlight those areas having the greatest total storage potential estimates.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2016

Automated selection of the optimal cardiac phase for single-beat coronary CT angiography reconstruction

Purpose: Reconstructing a low-motion cardiac phase is expected to improve coronary artery visualization in coronary computed tomography angiography (CCTA) exams. This study developed an automated algorithm for selecting the optimal cardiac phase for CCTA reconstruction. The algorithm uses prospectively gated, single-beat, multiphase data made possible by wide cone-beam imaging. The proposed algorithm differs from previous approaches because the optimal phase is identified based on vessel image quality (IQ) directly, compared to previous approaches that included motion estimation and interphase processing. Because there is no processing of interphase information, the algorithm can be applied to any sampling of image phases, making it suited for prospectively gated studies where only a subset of phases are available. Methods: An automated algorithm was developed to select the optimal phase based on quantitative IQ metrics. For each reconstructed slice at each reconstructed phase, an image quality metric was calculated based on measures of circularity and edge strength of through-plane vessels. The image quality metric was aggregated across slices, while a metric of vessel-location consistency was used to ignore slices that did not contain through-plane vessels. The algorithm performance was evaluated using two observer studies. Fourteen single-beat cardiac CT exams (Revolution CT, GE Healthcare, Chalfont St. Giles, UK) reconstructed at 2% intervals were evaluated for best systolic (1), diastolic (6), or systolic and diastolic phases (7) by three readers and the algorithm. Pairwise inter-reader and reader-algorithm agreement was evaluated using the mean absolute difference (MAD) and concordance correlation coefficient (CCC) between the reader and algorithm-selected phases. A reader-consensus best phase was determined and compared to the algorithm selected phase. In cases where the algorithm and consensus best phases differed by more than 2%, IQ was scored by three readers using a five point Likert scale. Results: There was no statistically significant difference between inter-reader and reader-algorithm agreement for either MAD or CCC metrics (p > 0.1). The algorithm phase was within 2% of the consensus phase in 15/21 of cases. The average absolute difference between consensus and algorithm best phases was 2.29% ± 2.47%, with a maximum difference of 8%. Average image quality scores for the algorithm chosen best phase were 4.01 ± 0.65 overall, 3.33 ± 1.27 for right coronary artery (RCA), 4.50 ± 0.35 for left anterior descending (LAD) artery, and 4.50 ± 0.35 for left circumflex artery (LCX). Average image quality scores for the consensus best phase were 4.11 ± 0.54 overall, 3.44 ± 1.03 for RCA, 4.39 ± 0.39 for LAD, and 4.50 ± 0.18 for LCX. There was no statistically significant difference (p > 0.1) between the image quality scores of the algorithm phase and the consensus phase. Conclusions: The proposed algorithm was statistically equivalent to a reader in selecting an optimal cardiac phase for CCTA exams. When reader and algorithm phases differed by >2%, image quality as rated by blinded readers was statistically equivalent. By detecting the optimal phase for CCTA reconstruction, the proposed algorithm is expected to improve coronary artery visualization in CCTA exams.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

Heavy-Duty Vehicle Port Drayage Drive Cycle Characterization and Development

In an effort to better understand the operational requirements of port drayage vehicles and their potential for adoption of advanced technologies, National Renewable Energy Laboratory (NREL) researchers collected over 36,000 miles of in-use duty cycle data from 30 Class 8 drayage trucks operating at the Port of Long Beach and Port of Los Angeles in Southern California. These data include 1-Hz global positioning system location and SAE J1939 high-speed controller area network information. Researchers processed the data through NREL's Drive-Cycle Rapid Investigation, Visualization, and Evaluation tool to examine vehicle kinematic and dynamic patterns across the spectrum of operations. Using the k-medoids clustering method, a repeatable and quantitative process for multi-mode drive cycle segmentation, the analysis led to the creation of multiple drive cycles representing four distinct modes of operation that can be used independently or in combination. These drive cycles are statistically representative of real-world operation of port drayage vehicles. When combined with modeling and simulation tools, these representative test cycles allow advanced vehicle or systems developers to efficiently and accurately evaluate vehicle technology performance requirements to reduce cost and development time while ultimately leading to the commercialization of advanced technologies that meet the performance requirements of the port drayage vocation. The drive cycles, which are suitable for chassis dynamometer testing, were compared to several existing test cycles. This paper presents the clustering methodology, accompanying results of the port drayage duty cycle analysis and custom drive cycle creation.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Nanoscale Antiferromagnetic Domain Imaging using Full-Field Resonant X-ray Magnetic Diffraction Microscopy

The physical properties of magnetic materials frequently depend not only on the microscopic spin and electronic structures, but also on the structures of mesoscopic length scales that emerge, for instance, from domain formations, or chemical and/or electronic phase separations. However, experimental access to such mesoscopic structures is currently limited, especially for antiferromagnets with net zero magnetization. Here, full-field microscopy and resonant magnetic X-ray diffraction are combined to visualize antiferromagnetic (AF) domains of the spin–orbit Mott insulator Sr 2 IrO 4 with area over ≈0.1 mm 2 and with spatial resolution as high as ≈150 nm. With the unprecedented wide field of views and high spatial resolution, an intertwining of two AF domains on a length comparable to the measured average AF domain wall width of 545 nm is revealed. This mesoscopic structure comprises a substantial portion of the sample surface, and thus can result in a macroscopic response unexpected from its microscopic magnetic structure. In particular, the symmetry analysis presented in this work shows that the inversion symmetry, which is preserved by the microscopic AF order, becomes ill-defined at the mesoscopic length scale. We report this result underscores the importance of this novel technique for a thorough understanding of the physical properties of antiferromagnets.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Defining and applying an electricity demand flexibility benchmarking metrics framework for grid-interactive efficient commercial buildings

Building demand flexibility (DF) research has recently gained attention. To unlock building DF as a predictable grid resource, we must establish a quantitative understanding of the resource size, performance variability, and predictability based on large empirical datasets. Researchers have proposed various sets of theoretical metrics to measure this performance. Some metrics have been applied to simulation results, but most fall short of exploring the complexities in real building applications. There are practical metrics used in individual demand response field studies but they alone cannot fulfil the job of DF benchmarking across a diverse group of buildings. The electrical grid's geographically diverse and changing nature presents challenges to comparing building DF performance measured under different conditions (i.e., benchmarking DF). To address this challenge, a novel DF benchmarking framework focused on load shedding and shifting is presented; the foundation is a set of simple, proven single-event metrics with attributes describing event conditions. These enable benchmarking and visualization in different dimensions for identifying trends that represent how these attributes influence DF. To test its feasibility and scalability, the DF framework was applied to two case studies of 11 office buildings and 121 big-box retail buildings with demand response participation data. Furthermore, these examples provided a pathway for using both building level benchmarking and aggregation to extract insights into building DF about magnitude, consistency, and influential factors. Potential applications of the framework and real-world values have been identified for grid and building stakeholders.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Hierarchical Superhydrophobic Surfaces with Micropatterned Nanowire Arrays for High-Efficiency Jumping Droplet Condensation

Self-propelled droplet jumping on nanostructured superhydrophobic surfaces is of interest for a variety of industrial applications including self-cleaning, water harvesting, power generation, and thermal management systems. However, the uncontrolled nucleation-induced Wenzel state of condensed droplets at large surface subcooling (high heat flux) leads to the formation of unwanted large pinned droplets, which results in the flooding phenomenon and greatly degrades the heat transfer performance. In this work, we present a novel strategy to manipulate droplet behaviors during the process from the droplet nucleation to growth and departure through a combination of spatially controlling initial nucleation for mobile droplets by closely spaced nanowires and promoting the spontaneous outward movement of droplets for rapid removal using micropatterned nanowire arrays. Through the optical visualization experiments and heat transfer tests, we demonstrate greatly improved condensation heat transfer characteristics on the hierarchical superhydrophobic surface including the higher density of microdroplets, smaller droplet departure radius, 133% wider range of surface subcooling for droplet jumping, and 37% enhancement in critical heat flux for jumping droplet condensation, compared to the-state-of-art jumping droplet condensation on nanostructured superhydrophobic surfaces. The excellent water repellency of such hierarchical superhydrophobic surfaces can be promising for many potential applications, such as anti-icing, antifogging, water desalination, and phase-change heat transfer.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Molecular reorganization in bulk bottlebrush polymers: direct observation via nanoscale imaging

Bottlebrush polymers are important for a variety of applications ranging from drug delivery to electronics. The functional flexibility of the branched sidechains has unique assembly properties when compared to linear block polymer systems. However, reports of direct observation of molecular reorganization have been sparse. This information is necessary to enhance the understanding of the structure–property relationships in these systems and yield a rational design approach for novel polymeric materials. In this work, we report direct visualization of bottlebrush molecular organization and the formation of nematic-type ordering in an amorphous polymer bottlebrush system, captured with plasma etching and helium ion microscopy. By observing the unperturbed structure of this material at high resolution and quantifying image features, we were able to qualitatively link experimental results with structures predicted by coarse-grained molecular dynamics simulations. Here, the direct visualization and computation workflow developed in this work can be applied to a broad variety of polymers with different architectures, linking imaging results with other, independent channels of information for better understanding and control of these classes of materials.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Analysis of 440 GeV proton beam–matter interaction experiments at the High Radiation Materials test facility at CERN

In a previous paper [Schmidt et al., Phys. Plasmas 21, 080701 (2014)], we presented the first results on beam–matter interaction experiments that were carried out at the High Radiation Materials test facility at CERN. In these experiments, extended cylindrical targets of solid copper were irradiated with beam of 440 GeV protons delivered by the Super Proton Synchrotron (SPS). The beam comprised of a large number of high intensity proton bunches, each bunch having a length of 0.5 ns with a 50 ns gap between two neighboring bunches, while the length of this entire bunch train was about 7 μs. These experiments established the existence of the hydrodynamic tunneling phenomenon the first time. Detailed numerical simulations of these experiments were also carried out which were reported in detail in another paper [Tahir et al., Phys. Rev. E 90, 063112 (2014)]. Excellent agreement was found between the experimental measurements and the simulation results that validate our previous simulations done using the Large Hadron Collider (LHC) beam of 7 TeV protons [Tahir et al., Phys. Rev. Spec. Top.--Accel. Beams 15, 051003 (2012)]. According to these simulations, the range of the full LHC proton beam and the hadronic shower can be increased by more than an order of magnitude due to the hydrodynamic tunneling, compared to that of a single proton. This effect is of considerable importance for the design of machine protection system for hadron accelerators such as SPS, LHC, and Future Circular Collider. Recently, using metal cutting technology, the targets used in these experiments have been dissected into finer pieces for visual and microscopic inspection in order to establish the precise penetration depth of the protons and the corresponding hadronic shower. This, we believe will be helpful in studying the very important phenomenon of hydrodynamic tunneling in a more quantitative manner. The details of this experimental work together with a comparison with the numerical simulations are presented in this paper.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Multiscale Solar Water Heating (MSWH) v1.0

The main purpose of the software is to model energy use for individual and community scale solar water heating projects in California. Usage The user provides a climate zone for a project, an occupancy for each household and whether any of the occupants stay at home during the day. The software can then load a set of example California specific hourly domestic hot water end-use load profiles from a database, size and locate the systems. The user can now simulate the hourly system performance over a period of one representative year, visualize and explore the simulation results using time-series plots for temperature profiles, heat and power rates, or look at annual summaries. Similarly the user can model individual household solar water heating projects and base case conventional gas tank water heater systems, such that the results can be compared between the individual, community and base case systems. This functionality is readily available through a Jupyter notebook and a Django web framework, depending on what level of detail the user would like to access. Features - Python module to calculate solar irradiation on a tilted surface - Python module with simplified component models for Converter (solar collectors, electric resistance heater, gas burner, photovoltaic panels, heat pump), Storage (solar thermal tank, heat pump thermal tank, conventional gas tank water heater), and Distribution (distribution and solar pump, piping losses) components - Python module with preconfigured system simulation models for: base case gas tank water heaters, solar thermal water heaters (solar collector feeding a storage tank, with a tankeless gas water heater backup in a new installation cases and a base case gas tank water heater in a retrofit case) and solar electric water heaters (heat pump storage tank with an electric resistance backup) - Database with component performance parameters, California specific weather data and domestic hot water end-use load profiles - Django web framework to configure project, parametrize components and run simulation from a web browser The package contains functional and unit tests and it is structured so that it can be extended with further technologies, applications and locations.

Grahovac, Milica↗
DOE OSTI2024

Foldy: An open-source web application for interactive protein structure analysis

Foldy is a cloud-based application that allows non-computational biologists to easily utilize advanced AI-based structural biology tools, including AlphaFold and DiffDock. With many deployment options, it can be employed by individuals, labs, universities, and companies in the cloud without requiring hardware resources, but it can also be configured to utilize locally available computers. Foldy enables scientists to predict the structure of proteins and complexes up to 6000 amino acids with AlphaFold, visualize Pfam annotations, and dock ligands with AutoDock Vina and DiffDock. In our manuscript, we detail Foldy’s interface design, deployment strategies, and optimization for various user scenarios. We demonstrate its application through case studies including rational enzyme design and analyzing proteins with domains of unknown function. Furthermore, we compare Foldy’s interface and management capabilities with other open and closed source tools in the field, illustrating its practicality in managing complex data and computation tasks. Our manuscript underlines the benefits of Foldy as a day-to-day tool for life science researchers, and shows how Foldy can make modern tools more accessible and efficient.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

The Importance of Scientific Visualization on Novel Hardware

Innovation in HPC hardware and adoption of heterogeneous systems has led to a variety of unique programming models. This has led to a challenge for scientific visualization software (and indeed all HPC software) to take full advantage of recent generations of supercomputing. Edge computing, where hardware is specialized for the needs of the particular application, exacerbates the problem. VTK-m has had many successes on this front by providing device-agnostic algorithms that compare favorably to implementations written to specific devices as shown in Table 1. However, VTK-m has focused mostly on GPU and traditional CPU multicore technology. There are numerous processor technologies, both existing and potential future, that are not being addressed by current R&D efforts.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

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↗