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At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

High-Quality Revision of the Israeli Seismic Bulletin

Seismic bulletins, with trustworthy phase picks, origin times, and source locations are key for regional seismic studies, such as travel-time (TT) tomography, attenuation tomography, and anisotropy studies. To lay the groundwork for such studies in Israel, we revised the seismic bulletin of Israel and the surrounding area and obtained a trustworthy TT data set. From the earthquake and explosion bulletins of the Geophysical Institute of Israel, we compiled a starting data set of about 123,000 earthquakes and explosions that occurred during the past 40 yr. After screening out the poorly recorded events, we were left with a data set of ~38,000 well-recorded events. We then revised the remaining data set in two consecutive steps. In the first, we reviewed and updated station metadata, including changes in station metadata parameters over time. In the second step, we jointly relocated a list of selected seismic events, using the Bayesian hierarchical location software package (BayesLoc) of Myers et al. (2007) that performs joint relocation of multiple events. We observed striking dissimilarities between the spatial distributions of the newly relocated catalog and the initial locations. Although the depth distribution of the starting catalog is trimodal with peaks at 0, 5, and 10 km, the distribution in this study is unimodal, with a broad peak between 7.5 and 12.5 km. By differencing the observed arrival times and the origin times obtained through relocation with BayesLoc, we obtained a revised TT database that consists of 261,336 Pg, 132,876 Pn, 114,816 Sg, and 60,394 Sn arrivals, from a set of 30,458 jointly relocated seismic sources. In this work, we compared prerevision and postrevision TTs as a function of epicentral distance and concluded that the revised data set contains far fewer outliers and inconsistencies than the original data set. The revised TT data set may be used for seismic studies, such as TT tomography, attenuation tomography, and anisotropy studies.

58 GEOSCIENCES↗
DOE OSTI2024

Leveraging Afterglow in Scintillation-based x-ray detectors for spacetime-resolved computed tomography for accelerated acquisition and high-speed event capture

Afterglow in x-ray imaging for high-speed radiography is a constraint that limits imaging systems to low-light/fast decay screens which create poor data. Current approaches focus purely on using low-light yield screens with fast decay to avoid multiple exposure pileup due to afterglow. The goal of this work is to develop a statistical estimation approach to leverage afterglow to improve image quality thus allowing for higher quality imaging components to be used. This will allow for bright screens will slow decay to be used, and then a post-processing step applies the statistical estimation to separate each frame with superior signal compared to low-light/fast decay screens.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

The Evolution of LiNi 0.5 Mn 0.3 Co 0.2 O 2 Particle Damage from Fast Charging in Optimized, Full Li-Ion Cells

Fast charging batteries are critical to the widespread adoption of electric vehicles to compete with refueling times of combustion-based vehicles. In the near term, adapting current commercial battery technologies to perform better under fast charging conditions through engineering optimizations will greatly expedite the process while exploratory fast-charging electrode materials are being pursued. To do so, the degradation modes in optimized Li-ion batteries need to be completely explored to understand fast charging limits while maintaining a high energy density and a long cycle life. While lithium plating on graphite still remains a challenge, cathode degradation also plays a key role in battery performance. In this work, we used nano- and micro-X-ray computed tomography to characterize the mechanical degradation of LiNi 0.5 Mn 0.3 Co 0.2 O 2 (NMC532) in optimized Li-ion batteries cycled at three rates, 1C, 6C, and 9C, and at different stages of cycle life, 225 and 600 cycles. We report despite using a conservative upper voltage cutoff limit aimed to minimize extensive cathode degradation, higher charging rates and increased cycling caused the polycrystalline NMC532 particles to fracture and pulverize, which likely drives cathode capacity fade and contributes to the decrease in overall cell performance.

25 ENERGY STORAGE↗
DOE OSTI2021

SGD-Net: Efficient Model-Based Deep Learning with Theoretical Guarantees

Deep unfolding networks have recently gained popularity for solving imaging inverse problems. However, the computational and memory complexity of data-consistency layers within traditional deep unfolding networks scales with the number of measurements, limiting their applicability to large-scale imaging inverse problems. We propose SGD-Net as a new methodology for improving the efficiency of deep unfolding through stochastic approximations of the data-consistency layers. Our theoretical analysis shows that SGD-Net can be trained to approximate batch deep unfolding networks to an arbitrary precision. Our simulations on intensity diffraction tomography and sparse-view computed tomography show that SGD-Net can match the performance of the traditional batch network at a fraction of training and testing complexity.Deep unfolding networks have recently gained popularity for solving imaging inverse problems. However, the computational and memory complexity of data-consistency layers within traditional deep unfolding networks scales with the number of measurements, limiting their applicability to large-scale imaging inverse problems. We propose SGD-Net as a new methodology for improving the efficiency of deep unfolding through stochastic approximations of the data-consistency layers. Our theoretical analysis shows that SGD-Net can be trained to approximate batch deep unfolding networks to an arbitrary precision. Our simulations on intensity diffraction tomography and sparse-view computed tomography show that SGD-Net can match the performance of the traditional batch network at a fraction of training and testing complexity.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

NDE of titanium alloy MMC rings for gas turbine engines

Progress in the processing and fabrication of metal matrix composites (MMC's) requires appropriate mechanical and nondestructive testing methods. These methods are needed to characterize properties, assess integrity, and predict the life of engine components such as compressor rotors, blades, and vanes. Capabilities and limitations of several state-of-the-art nondestructive evaluation (NDE) technologies are investigated for characterizing titanium MMC rings for gas turbine engines. The use of NDE technologies such as x-ray computed tomography, radiography, and ultrasonics in identifying fabrication-related problems that caused defects in components is examined. Acousto-ultrasonics was explored to assess degradation of material mechanical properties by using stress wave factor and ultrasonic velocity measurements before and after the burst testing of the rings.

Baaklini, George Y.↗
DOE OSTI2022

X-ray Computed Tomography as a Metrology Technique for the Analysis of Additively Manufactured Material

X-ray computed tomography (X-ray CT) is an analytical technique used in materials science to non-destructively characterize features in a variety materials like polymer, metals, composites, and explosives. It also has the capability of imaging additively manufacture, machine and assembled parts. The non-destructive imaging allows for the analysis of features (voids and cracks), which give a fundamental understanding of the material characteristics. Additionally, X-ray CT can obtain accurate measurements of dimensional and topographic variations due to different stimuli and assess the accuracy of material production. This study focuses on parts manufactured via metal additive manufacturing (AM). Although AM produces parts faster and easier, the printing process can produce defects (pores and surface roughness) that undermine the part’s mechanical properties and performance. The analysis of 3D printed objects has an asset in that the material has an STL file from which the item was printed, which is not available in many manufactured materials (i.e., foams) due to stochastic structures. For this study, the print accuracy of four additively manufactured cylinders will be assessed via X-ray CTto approximate the surface roughness and visualize any major morphological changes to assess the dimensional accuracy of complex additively manufactured parts. It was concluded that using X-ray CT to measure surface roughness was affective because reasonable surface roughness values were measured. Additionally, itwas determined that small-scale features can be produced via additive manufacturing with strong dimensional accuracy so long as the features are highly complex with sharp grooves.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Development of a silicon carbide ceramic based counter-flow heat exchanger by binder jetting and liquid silicon infiltration for concentrating solar power

A silicon carbide ceramic counter-flow heat exchanger with integrated headers was printed by binder jetting additive manufacturing process. Multiple phenolic binder infiltration cycles (3 or 5) followed by pyrolysis were conducted to increase the net carbon content of the printed SiC specimens. Subsequently, to attain full densification, silicon melt infiltration was used. The microstructure and mechanical properties were comprehensively characterized on the densified material. The chemical compositions and visual distribution of the various regions in the specimens were determined via scanning electron microscopy, while X-ray diffraction and synchrotron µ-computed tomography were used to provide a quantitative assessment of the volume fractions of the identified phase regions. Microhardness measurements showed dependence on the local microstructure. The fracture strength of the material was correlated with the specimen density and agreed with the reported values in the literature. High-temperature exposure at 750 °C for up to 200h did not degrade the strength for the specimens with three phenolic-binder infiltrations; however, the strengths degraded for ones with five phenolic-binder infiltrations. The associated fracture toughnesses of the specimens were ~3.4 MPam 1/2 at room temperature and 750°C, and the thermal conductivities varied from >150 W/mK at room temperature to ~45 W/mK at 750°C. Hence, this study validated the use of the binder-jetting printed SiC ceramic materials for high-temperature heat exchanges. Lastly, we also present in this work the first successful fabrication of a binder-jetting printed one-piece dense SiC ceramic heat exchanger body with unblocked channels that can be used for the flow of heat transfer fluids.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Highly Reversible Plating/Stripping of Porous Zinc Anodes for Multivalent Zinc Batteries

Zinc continues to garner immense interest due to its versatility as an anode material in several configurations utilizing either alkaline or mild-pH electrolytes. Current research on using mild-pH electrolytes has improved the rechargeability aspect of Zn-based batteries since Zn2+ is solely utilized for plating/stripping of Zn. Several studies have incorporated Zn metal foils, yet, dramatic improvements can be achieved by expressing Zn as a porous structure. Herein, we use a quasi-pulsed electrodeposition process to prepare a conformal Zn coating onto 3D porous copper foam. By tuning the electrodeposition parameters, we achieved an optimal Zn coating that undergoes reversible plating/stripping when tested in symmetric Zn cells, which supported a low overpotential of ~60 mV for up to 100 cycles. We further investigated changes in the surface morphology by studying the Zn surface of both foil and 3D structure using scanning electron microscopy and X-ray micro-computed tomography. Both techniques showed that the Zn foil undergoes dramatic alterations at the surface, which results in inhomogeneous deposition of Zn, whereas the 3D form exhibited minimal changes. Lastly, we paired both Zn foil and 3D Zn with vanadium oxide and demonstrated that the porous structure supports high rate capability and high specific capacity.

25 ENERGY STORAGE↗
DOE OSTI2020

The potential role of organics in new particle formation and initial growth in the remote tropical upper troposphere

Abstract. Global observations and model studies indicate that new particle formation (NPF) in the upper troposphere (UT) and subsequent particles supply 40 %–60 % of cloud condensation nuclei (CCN) in the lower troposphere, thus affecting the Earth's radiative budget. There are several plausible nucleation mechanisms and precursor species in this atmospheric region, which, in the absence of observational constraints, lead to uncertainties in modeled aerosols. In particular, the type of nucleation mechanism and concentrations of nucleation precursors, in part, determine the spatial distribution of new particles and resulting spatial distribution of CCN from this source. Although substantial advances in understanding NPF have been made in recent years, NPF processes in the UT in pristine marine regions are still poorly understood and are inadequately represented in global models. Here, we evaluate commonly used and state-of-the-art NPF schemes in a Lagrangian box model to assess which schemes and precursor concentrations best reproduce detailed in situ observations. Using measurements of aerosol size distributions (0.003 < Dp < 4.8 µm) in the remote marine troposphere between ∼0.18 and 13 km altitude obtained during the NASA Atmospheric Tomography (ATom) mission, we show that high concentrations of newly formed particles in the tropical UT over both the Atlantic and Pacific oceans are associated with outflow regions of deep convective clouds. We focus analysis on observations over the remote Pacific Ocean, which is a region less perturbed by continental emissions than the Atlantic. Comparing aerosol size distribution measurements over the remote Pacific with box model simulations for 32 cases shows that none of the NPF schemes most commonly used in global models, including binary nucleation of sulfuric acid and water (neutral and ion-assisted) and ternary involving sulfuric acid, water, and ammonia, are consistent with observations, regardless of precursor concentrations. Through sensitivity studies, we find that the nucleation scheme among those tested that is able to explain most consistently (21 of 32 cases) the observed size distributions is that of Riccobono et al. (2014), which involves both organic species and sulfuric acid. The method of Dunne et al. (2016), involving charged sulfuric acid–water–ammonia nucleation, when coupled with organic growth of the nucleated particles, was most consistent with the observations for 5 of 32 cases. Similarly, the neutral sulfuric acid–water–ammonia method of Napari (2002), when scaled with a tuning factor and with organic growth added, was most consistent for 6 of 32 cases. We find that to best reproduce both nucleation and growth rates, the mixing ratios of gas-phase organic precursors generally need to be at least twice that of SO2, a proxy for dimethyl sulfide (DMS). Unfortunately, we have no information on the nature of oxidized organic species that participated in NPF in this region. Global models rarely include organic-driven nucleation and growth pathways in UT conditions where globally significant NPF takes place, which may result in poor estimates of NPF and CCN abundance and contribute to uncertainties in aerosol–cloud–radiation effects. Furthermore, our results indicate that the organic aerosol precursor vapors may be important in the tropical UT above marine regions, a finding that should guide future observational efforts.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2000

Thermographic Imaging of Defects in Anisotropic Composites

Composite materials are of increasing interest to the aerospace industry as a result of their weight versus performance characteristics. One of the disadvantages of composites is the high cost of fabrication and post inspection with conventional ultrasonic scanning systems. The high cost of inspection is driven by the need for scanning systems which can follow large curve surfaces. Additionally, either large water tanks or water squirters are required to couple the ultrasonics into the part. Thermographic techniques offer significant advantages over conventional ultrasonics by not requiring physical coupling between the part and sensor. The thermographic system can easily inspect large curved surface without requiring a surface following scanner. However, implementation of Thermal Nondestructive Evaluations (TNDE) for flaw detection in composite materials and structures requires determining its limit. Advanced algorithms have been developed to enable locating and sizing defects in carbon fiber reinforced plastic (CFRP). Thermal Tomography is a very promising method for visualizing the size and location of defects in materials such as CFRP. However, further investigations are required to determine its capabilities for inspection of thick composites. In present work we have studied influence of the anisotropy on the reconstructed image of a defect generated by an inversion technique. The composite material is considered as homogeneous with macro properties: thermal conductivity K, specific heat c, and density rho. The simulation process involves two sequential steps: solving the three dimensional transient heat diffusion equation for a sample with a defect, then estimating the defect location and size from the surface spatial and temporal thermal distributions (inverse problem), calculated from the simulations.

Plotnikov, Y. A.↗
NASA NTRSDate not supplied

Flash Thermal Diffusivity Measurements and Inspection of Additively Manufactured Ti-6Al-4V Specimens with Varying Process Parameters

Flash thermal diffusivity measurements were obtained on additively manufactured Ti-6Al-4V disk shaped specimens with various process parameters. For additively manufactured metal parts, processing parameters such as laser power and scanning speed are critical to ensure the desired microstructure. For this study, the laser powder bed fusion process parameters were changed at various angular sections on a 21 mm diameter and 3.0 mm thick disk. The measurement of thermal diffusivity was performed by fitting a 1-dimensional thermal model to the data pixel by pixel to produce an inspection image. The image revealed the detection of defects such as lack of fusion porosity and areas of aggregated porosity. The thermal diffusivity imagery was compared to immersion scan ultrasonic and X-ray computed tomography (CT) measurements for validation. Based on these results, additional samples were investigated using a single side thermal inspection technique to detect lack of fusion porosity and near surface voids.

thermal nondestructive evaluation↗
NASA NTRS2023

Flash Thermal Diffusivity Measurements and Inspection of Additively Manufactured Ti-6Al-4V Specimens with Varying Process Parameters

Flash thermal diffusivity measurements were obtained on additively manufactured Ti-6Al-4V disk shaped specimens with various process parameters. For additively manufactured metal parts, processing parameters such as laser power and scanning speed are critical to ensure the desired microstructure. For this study, the laser powder bed fusion process parameters were changed at various angular sections on a 21 mm diameter and 3.0 mm thick disk. The measurement of thermal diffusivity was performed by fitting a 1-dimensional thermal model to the data pixel by pixel to produce an inspection image. The image revealed the detection of defects such as lack of fusion porosity and areas of aggregated porosity. The thermal diffusivity imagery was compared to immersion scan ultrasonic and X-ray computed tomography (CT) measurements for validation. Based on these results, additional samples were investigated using a single side thermal inspection technique to detect lack of fusion porosity and near surface voids.

thermal nondestructive evaluation↗
DOE OSTI2023

System and method for identifying objects of interest in images based on likelihood map decluttering

An automatic threat recognition system and method is disclosed for scanning the x-ray CT image of an article to identify the objects of interest (OOIs) contained within the article, which are otherwise not always quickly apparent or discernable to an individual. The system uses a computer to receive information from two-dimensional (2D) image slices from a reconstructed computed tomography (CT) scan image and to produce a plurality of voxels for each slice of the 2D image. The computer analyzes the voxels to create a likelihood map (LM) representing likelihoods that voxels making up the CT image are associated with a material of interest (MOI). The computer further analyzes the LM to construct neighborhoods of voxels within the LM, and classifies each voxel neighborhood based on its features, thereby decluttering the LM to facilitate the process of connecting voxels of a like MOI together to form segments. The computer classifies each candidate segment based on its features, thereby identifying those segments that correspond to objects of interest.

Paglieroni, David W.↗
DOE OSTI2023

Shadow Distillation: Quantum Error Mitigation with Classical Shadows for Near-Term Quantum Processors

Mitigating errors in quantum information processing devices is especially important in the absence of fault tolerance. An effective method in suppressing state-preparation errors is using multiple copies to distill the ideal component from a noisy quantum state. Here, we use classical shadows and randomized measurements to circumvent the need for coherent access to multiple copies at an exponential cost. We study the scaling of resources using numerical simulations and find that the overhead is still favorable compared to full state tomography. We optimize measurement resources under realistic experimental constraints and apply our method to an experiment preparing a Greenberger-Horne-Zeilinger state with trapped ions. In addition to improving stabilizer measurements, the analysis of the improved results reveals the nature of errors affecting the experiment. Hence, our results provide a directly applicable method for mitigating errors in near-term quantum computers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Low-Temperature Annealing of Nanoscale Defects in Polycrystalline Graphite

Polycrystalline graphite contains multi-scale defects, which are difficult to anneal thermally because of the extremely high temperatures involved in the manufacturing process. In this study, we demonstrate annealing of nuclear graphite NBG-18 at temperatures below 28 °C, exploiting the electron wind force, a non-thermal stimulus. High current density pulses were passed through the specimens with a very low-duty cycle so that the electron momentum could mobilize the defects without heating the specimen. The effectiveness of this technique is presented with a significant decrease in electrical resistivity, defect counts from X-ray computed tomography, Raman spectroscopy, and nanoindentation-based mechanical characterization. Such multi-modal evidence highlights the feasibility of nanoscale defect control at temperatures about two orders of magnitude below the graphitization temperature.

Liu, Gongyuan↗
DOE OSTI2026

Tomography of Atomic Nuclei

We carry out continuum quantum Monte Carlo calculations of the quantum-mechanical Wigner distribution functions of selected nuclei, up to $^{16}$O. These distributions provide a form of quantum tomography of the spatial and momentum structure of the system. They also help identify the location of high-momentum regions in atomic nuclei and provide insight into the onset of alpha clustering. Besides their intrinsic interest, these distributions will be useful for neutrino event generators, as they correlate the positions and momenta of nucleons in the initial target state. To facilitate their application, we address the need to store them compactly by developing an accurate Gaussian Process emulator that automatically preserves their normalization.

Rocco, Noemi [Valencia U., IFIC; Fermilab]↗
DOE OSTI2024

Enhancing Mechanical Properties of Carbon–Silicon Steel through Two–Stage Quenching and Partitioning with Bainitic Transformation: Ultimate Tensile Strength of 1875 MPa and Total Elongation of 8.03%

To achieve the desired microstructural properties, the ongoing development and innovation in new structural steels require novel thermal processing. This study aims to improve the mechanical properties of a commercial spring carbon–silicon steel by tailoring its microstructure through a process involving quenching and partitioning (Q&P) followed by bainitic transformation. A two–stage Q&P process is proposed to generate a nanoscale dispersion of stable retained austenite and carbides within the tempered martensite and bainite microstructure. The resulting tensile properties demonstrate a yield strength of 1280 MPa, an ultimate tensile strength of 1875 MPa, and a total elongation of 8.03%. These values surpass those of conventional spring 9254 steel, highlighting the effectiveness of the thermal treatment design. Microstructure analysis reveals the presence of tempered martensite, bainite sheaves, nanoscale carbides, and aggregates of retained austenite. Moreover, the resulting body–centered cubic matrix exhibits minimal lattice tetragonality of ≈1.0051, coupled with stable retained austenite featuring a carbon concentration of ≈3.42 ± 0.5 wt%, resulting in outstanding strength–ductility properties. In conclusion, these findings indicate that the proposed two–stage Q&P process, followed by bainitic transformation, significantly enhances the mechanical properties of carbon–silicon steels, making it a promising candidate for high–performance spring applications.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Soil Water Retention and Hydraulic Conductivity Data and Model at Snodgrass Mountain in East River Watershed, Colorado 2020-2025

This data package includes soil water retention and hydraulic conductivity data and model fitting results from measurements of ex-situ soil samples and in-situ soil sensors at Snodgrass Mountain. Soil water retention curves (SWRC) characterize soil water content as a function of soil water potential. SWRC depends on soil texture and pore structure and can be used to describe the constraints on biogeochemical processes in terms of soil water availability. In this data package, the sample identification follows the format SG-X-Y, where SG refers to Snodgrass Mountain, X is the location identifier, and Y is the depth identifier at the same X (shallow Y=1). Specifically, SG-EHS is associated with ecohydrology sites under the East-Taylor Watershed Community Observatory Sites directory, and SG-ERTn (upslope n=1) are points along the Snodgrass electrical resistivity tomography transect not associated with the existing site names in the directory. The sample and location information can be found in metadata.csv. Sampling and Measurements Each sample falls into one of the three sampling methods – (1) intact cores, (2) repacked samples, or (3) soil sensors – and one of the two measurement methods – (a) laboratory or (b) in-situ. Both intact cores and repacked samples were measured using the laboratory methods, which include measurements of soil water potential (HYPROP & WP4C, METER), saturated (KSAT, METER) and unsaturated hydraulic conductivity (HYPROP). The in-situ method uses a pair of co-located soil sensors to measure volumetric water content (TEROS12, METER) and soil water potential (TEROS21, METER), and the hydraulic conductivity was not measured. In comparison, the laboratory methods progress from full saturation to dry conditions, and the in-situ method includes both dry-to-wet and wet-to-dry cycles. The sampling and measurement methods for each sample can be found in metadata.csv, and more information about the measurements is detailed in the Methods section below. Models Retention and hydraulic conductivity data were fitted with four van-Genuchten-type models (specified by “model_name” column in the files): (1) traditional constrained van Genuchten model (“vG_constrained”), (2) traditional unconstrained van Genuchten model (“vG_unconstrained”), (3) PDI-variant of the constrained van Genuchten model (“vG_constrained_PDI”), and (4) PDI-variant of the unconstrained van Genuchten model (“vG_unconstrained_PDI”). The difference between the constrained (1: n) and the unconstrained (2: n, m) van Genuchten models is the number of pore-size distribution parameters in the model equations, giving the unconstrained model more degrees of freedom when fitting the data. Between the traditional and the PDI-variant models, model fitting differs the most at the dry end of the measurements. The traditional models allow infinite suction at the residual water content (water content does not drop below residual water content), and the PDI-variant models enforce a soil water potential value of pF=6.8 (~ -630 MPa) at oven-dryness (water content reaches 0). The inclusion of the van-Genuchten-type models is due to their common application. If other retention models are required, users can access the data in data.csv for further data fitting. More information about the models can be found in the Methods section below. Fitting Tasks The model fitting can be categorized into three levels of tasks (specified by “fitting_task” column in the files). Level 1 (“fit_retention”) only includes retention data fitting (the only level available for the in-situ method). Level 2 (“fit_retention_conductivity”) includes both retention and hydraulic conductivity data fitting, and the saturated hydraulic conductivity (Ks, a parameter of the hydraulic conductivity functions) is fixed by the measurements from KSAT. Level 3 (“fit_retention_conductivity_Ks”) also includes both retention and hydraulic conductivity data fitting, but Ks is a fitted parameter without the constraints from KSAT measurements. Among the same retention models (e.g. vG_constrained models of the same sample), level 1 should produce the best retention data fitting. Level 2 should have the highest misfit of the retention and hydraulic conductivity data, because the retention and hydraulic conductivity functions share common model parameters, and the unsaturated hydraulic conductivity (HYPROP) data fitting is subject to Ks measured independently by KSAT. Level 3 should have mid-level misfits of the retention and hydraulic conductivity data. While level 3 fits the hydraulic conductivity data better than level 2, the fitted Ks value might be unreasonable due to the lack of constraints at the wet end of the measurements. General recommendation when using this data package: (1) Choice of sampling methods: Intact cores and in-situ soil sensors could be prioritized because these sampling methods are less destructive. While the repacked samples were packed to the target bulk density (estimated post-sampling, when sample volume was known), these samples had altered pore structures. Nevertheless, intact cores might suffer from sample gaps that would lead to overestimation of Ks (sample gaps can be inferred from the “soil_sample_volume” column in metadata.csv when the value is < 249). In-situ method also has higher uncertainty in characterizing the wet end of the SWRC because of sensor limitations and the difficulty in reaching full saturation under natural conditions. (2) Choice of fitting tasks: When only retention data is needed, level 1 (“fit_retention”) should be prioritized. When both retention and hydraulic conductivity data are needed, level 2 (“fit_retention_conductivity”) could be prioritized. (3) Choice of models: This could depend on what the downstream models call for. If no specific model is required, model misfit could be used as a ranking criterion. Model misfit values in terms of RMSE can be found in model_parameters.csv. The following files are included in this data package: (1) metadata.csv – This file includes the general information of each sample, including location (description, geocoordinates, elevation), sampling and measurements details (method, depth, time or period, volume, instruments), and soil physical properties (bulk density, saturated hydraulic conductivity, only applicable to physical soil samples). (2) data.csv – This file includes soil water potential, volumetric water content, and unsaturated hydraulic conductivity data of each sample. Column “instrument” specifies the instrument (HYPROP, WP4C, or TEROS) used to perform the measurements. (3) model_fit.csv – This file includes soil water potential, volumetric water content, and unsaturated hydraulic conductivity fitted from the four models and three fitting tasks. Column “model_name” specifies the retention model used, and “fitting_task” specifies the level of data fitting. Missing values indicate that the variable does not apply to that fitting task. (4) model_parameters.csv – This file includes the fitted model parameters, model misfits, and conventional water content thresholds (field capacity and wilting point) from the four models and three fitting tasks. Column “model_name” specifies the retention model used, and “fitting_task” specifies the level of data fitting. Missing values indicate that the parameter does not apply to that model and/or that fitting task. (5) data_Ks.csv – This file includes the saturated hydraulic conductivity measurements from KSAT. (6) /figure/*.png – This folder includes three quick visualizations of the data, retention model fitting results and misfits, and hydraulic conductivity model fitting results, misfits, and parameters. The model fitting results are separated by samples and fitting tasks and colored by models. Zoom-in required. (7) /hyprop/*.bdhx – This folder includes proprietary hyprop files that require the free Labros SoilView-Analysis (METER) to open. Users can explore data fitting using other retention models (i.e. Brooks-Corey, Fredlund-Xing, Kosugi, bimodal models). Be aware that Ks value is pre-entered under “Fitting tab, Conductivity functions parameters” for level 2 fitting. If the value is lost, please refer to metadata.csv under “Ks” column. (8) Six file-level metadata that summarize file, header, column, and variable information of all files. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

EARTH SCIENCE > LAND SURFACE > SOILS↗