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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Application of a new hybrid particle swarm optimization-mixed kernels function-based support vector machine model for reservoir porosity prediction: A case study in Jacksonburg-Stringtown oil field, West Virginia, USA

Porosity is a fundamental property that characterizes the storage capability of fluid and gas-bearing formations in a reservoir. An accurate porosity value can be measured from core samples in the laboratory; however, core analysis is expensive and time consuming. Well-log data can be used to calculate porosity, but the availability of log suites is often limited in mature fields. Therefore, robust porosity prediction requires integration of core-measured porosity with available well-log suites to control for changes in lithology and fluid content. A support vector machine (SVM) model with mixed kernel function (MKF) is used to construct the relationship between limited conventional well-log suites and sparse core data. Porosity is the desired output, and two conventional well-log responses (gamma ray [GR] and bulk density) and three well-log-derived parameters (the slope of GR, the slope of density, and [Formula: see text]) are input parameters. A global stochastic searching algorithm, particle swarm optimization (PSO), is applied to improve the efficiency of locating the appropriate values of five control parameters in MKF-SVM model. The results of SVM with different traditional kernel functions were compared, and the MKF-SVM model provided an improvement over the traditional SVM model. To confirm the advantage of the hybrid PSO-MKF-SVM model, the results from three models: (1) radial basis function (RBF)-based least-squares SVM, (2) multilayer perceptron artificial neural network (ANN), and (3) RBF ANN, are compared with the result of the hybrid PSO-MKF-SVM model. The results indicate that the hybrid PSO-MKF-SVM model improves porosity prediction with the highest correlation coefficient ([Formula: see text] of 0.9560), the highest coefficient of determination ([Formula: see text] of 0.9140), the lowest root-mean-square error (1.6505), average absolute error value (1.4050), and maximum absolute error (2.717).

Geochemistry & Geophysics↗
DOE OSTI2020

Forest Structural Complexity and Biomass Predict First-Year Carbon Cycling Responses to Disturbance

The pre-disturbance vegetation characteristics that predict carbon (C) cycling responses to disturbance are not well known. To address this gap, we initiated the Forest Resilience Threshold Experiment, a manipulative study in which more than 3600 trees were stem girdled to achieve replicated factorial combinations of four levels (control, 45, 65, and 85% gross defoliation) of disturbance severity and two disturbance types (targeting upper or lower canopy strata). Applying a standardized stability framework in which initial C cycling resistance to disturbance was calculated as the first-year natural log response ratio of disturbance and control treatments, we investigated to what extent pre-disturbance levels of species diversity, aboveground woody biomass, leaf area index, and canopy rugosity—a measure of structural complexity—predict the initial responses of subcanopy light-saturated leaf CO 2 assimilation (A sat ), aboveground wood NPP (ANPP w ), and soil respiration (R s ) to phloem-disrupting disturbance. In the year following stem girdling, we found that above-ground C cycling processes, A sat and ANPP w , were highly resistant to increases in disturbance severity, while Rs resistance declined as severity increased. Disturbance type had no effect on first-year resistance. Pre-disturbance aboveground woody biomass, and canopy rugosity were positive predictors of ANPP w resistance and, conversely, negatively related to R s resistance. Subcanopy A sat resistance was not related to pre-disturbance vegetation characteristics. Stability of C uptake processes along with R s declines suggest the net C sink was sustained in the initial months following disturbance. Therefore, we conclude that biomass and complexity are significant, but not universal, predictors of initial C cycling resistance to disturbance. Moreover, our findings highlight the utility of standardized stability measures when comparing functional responses to disturbance.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Coupling of an atmospheric pressure microplasma ionization source with an Orbitrap Fusion Lumos Tribrid 1M mass analyzer for ultra-high resolution isotopic analysis of uranium

The coupling of a combined atomic and molecular (CAM) ionization source, the liquid sampling-atmospheric pressure glow discharge (LS-APGD) microplasma to an Orbitrap Fusion Lumos Tribrid 1M mass spectrometer is described as a significant step towards the elimination of isobaric interferences in elemental/isotopic mass spectrometry. The developed setup permits broadband, elemental mass spectra to be easily acquired at a mass resolution (m/Δm) of 500 000. A new ion source housing and integrated control system provide enhanced stability and sensitivity of the microplasma ion source in comparison to the previous designs. Detailed evaluation of the ion sampling parameters provided insight into differences with other Orbitrap platforms leading to a 5-fold increase in resolution in elemental/isotopic analysis. The roles of data acquisition/ion processing parameters were evaluated with regards to the precision and accuracy of 235 U/ 238 U isotope ratios. Significantly, the precision of those measurements improves as a function of pre-set mass resolution up to a value of 1 000 000, where a precision of 0.086% RSD is obtained for uranium concentrations of 100 ng mL− 1 . Analytical response curves (log–log), acquired for the two uranium isotopes at a resolution of 120 000 were linear (R 2 = 0.9969) over more than 5 orders of magnitude, with limits of detection of 1 pg mL −1 for U. Based on 60 μL injection volumes, this represents a mass of 70 fg 235 U. These figures of merit satisfy International Target Values (ITVs) for Measurement Uncertainties in Safeguarding Nuclear Materials set by the International Atomic Energy Agency (IAEA). Ultimately, and totally unique from beam-type instruments, the move to the higher-resolution Orbitrap platform provides all of the benefits of high mass resolution, with no penalties in sensitivity, precision, or dynamic range for uranium analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Particle Collisions and Negative Nonlocal Response of Ballistic Electrons

An electric field that builds in the direction against current, known as negative nonlocal resistance, arises naturally in viscous flows and is thus often taken as a telltale of this regime. Here, we predict negative resistance for the ballistic regime, wherein the ee collision mean free path is greater than the length scale at which the system is being probed. Therefore, negative resistance alone does not provide strong evidence for the occurrence of the hydrodynamic regime; it must thus be demoted from the rank of irrefutable evidence to that of a mere forerunner. Furthermore, we find that negative response is log enhanced in the ballistic regime by the physics related to the seminal Dorfman-Cohen log divergence due to memory effects in the kinetics of dilute gases. The ballistic regime therefore offers a unique setting for exploring these interesting effects due to electron interactions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Utah FORGE: Rock Properties

This is an Excel spreadsheet that contains rock properties from several wells in the Utah FORGE study area. This includes a map of the wells. Data is described in the Final Topical Report included in the resources below.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Deep Learning-Assisted Real-Time Forward Modeling of Electromagnetic Logging in Complex Formations

Higher dimensional (i.e., 2-D and 3-D) modeling is indispensable to correctly evaluate the responses of electromagnetic logging tools in complex formation environments. However, limited by the high computational cost of rigorous modeling such as finite difference method and the finite element method, the real-time applications in the well logging industry primarily rely on the 1-D forward solver, which would result in erroneous formation evaluation for complex scenarios. As a result, aiming at realizing fast modeling for electromagnetic logging tools in complex formations, this paper proposes a general framework assisted by deep neural networks (DNNs). The framework consists of three modules: earth model classification, parameter extraction, and surrogate construction. Separate DNNs are trained and tested for different modules. The accuracy and efficiency of the DNN assisted fast modeling are validated by several experiments. Here, this study finds that the fast modeling assisted by DNNs is able to calculate the tool responses and reconstruct the subsurface formations in real-time.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Comparing capacity coefficient and dual task assessment of visual multitasking workload

Capacity coefficient analysis could offer a theoretically grounded alternative approach to subjective measures and dual task assessment of cognitive workload. Workload capacity or workload efficiency is a human information processing modeling construct defined as the amount of information that can be processed by the visual cognitive system given a specified of amount of time. In this paper, I explore the relationship between capacity coefficient analysis of workload efficiency and dual task response time measures. To capture multitasking performance, I examine how the relatively simple assumptions underlying the capacity construct generalize beyond the single visual decision making tasks. The fundamental tools for measuring workload efficiency are the integrated hazard and reverse hazard functions of response times, which are defined by log transforms of the response time distribution. These functions are used in the capacity coefficient analysis to provide a functional assessment of the amount of work completed by the cognitive system over the entire range of response times. For the study of visual multitasking, capacity coefficient analysis enables a comparison of visual information throughput as the number of tasks increases from one to two to any number of simultaneous tasks. I illustrate the use of capacity coefficients for visual multitasking on sample data from dynamic multitasking in the modified Multi-attribute Task Battery.

capacity coefficient↗
DOE OSTI2022

Improving magnitude and phase comparison metrics for frequency response functions using cross-correlation and log-frequency shifting

This paper provides a new method for matching dominant features of Frequency Response Functions (FRFs). In particular, this paper proposes a slicing and shifting method where the key features (in this case, resonant amplitudes) of a baseline FRF are compared with a similar FRF using cross-correlation and a Log-Frequency Shift (LFS). Here, the goal is to provide an alternative to classic point-to-point methods for FRF comparison and instead to match the dominant features of two FRFs in a way similar to visual inspection. This enables existing FRF comparison metrics to then be applied with greater fidelity. Additionally, this paper introduces the Phase Similarity Metric (PSM) for comparing phases of two FRFs and illustrates the improvement of using LFS for phase comparisons as well. This paper uses a cantilever beam experiment in multiple configurations to provide a benchmark case for FRF comparison improvements.

42 ENGINEERING↗
DOE OSTI2016

A method to improve the sensitivity of neutron porosity measurement based on D-T source

Compensated porosity logging tool utilizing deuterium-tritium (D-T) source shows a lower sensitivity to the variation of formation porosity compared with that adopting Am-Be source. In order to improve the sensitivity, the factors of an infinite homogeneous formation influencing slowing-down length and the near to far counts ratio are analyzed in this paper. Then Monte Carlo simulation method is used to build well logging models to study the responses of a neutron porosity logging tool to hydrogen index and formation density. It shows that in addition to hydrogen index, the variation of the density also has a great impact on slowing-down length and the ratio which reduces the response sensitivity to porosity. A new model depicts the relationship between the count ratio and porosity is proposed. Finally, when the model is used to process the measured ratio, the ratio shows improved dynamic range and sensitivity to porosity compared with the values without processing.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

The Effect of Brine on the Electrical Properties of Methane Hydrate

Gas hydrates possess lower electrical conductivity (inverse of resistivity) than either seawater or ice, but higher than clastic silts and sands, such that electromagnetic methods can be employed to help identify their natural formation in marine and permafrost environments. Controlled laboratory studies offer a means to isolate and quantify the effects of changing individual components within gas-hydrate-bearing systems, in turn yielding insight into the behavior of natural systems. Here we investigate the electrical properties of polycrystalline methane hydrate with ≥25% gas-filled porosity and in mixture with brine. Initially, pure methane hydrate was synthesized from H2O ice and CH4 gas while undergoing electrical impedance measurement, then partially dissociated to assess the effects of pure pore water accumulation on electrical conductivity. Methane hydrate + brine mixtures were then formed by either adding NaCl (0.25–2.5 wt %) to high-purity ice or by using frozen seawater as a reactant. Conductivity was obtained from impedance measurements made in situ throughout synthesis while temperature cycled between +15 °C and -25 °C. Several possible conduction mechanisms were subsequently determined using equivalent circuit modeling. Samples with low NaCl concentration show a doping/impurity effect and a log linear conductivity response as a function of temperature. For higher salt content samples, conductivity increases exponentially with temperature and the log linear relationship no longer holds; instead, we observe phase changes within the samples that follow NaCl–H 2 O–CH 4 phase equilibrium predictions. Final samples were quenched in liquid nitrogen and imaged by cryogenic scanning electron microscopy (cryo-SEM) to assess grain-scale characteristics.

58 GEOSCIENCES↗
DOE OSTI2016

Molecular mobility in glassy dispersions

Dielectric spectroscopy was used to characterize the structural relaxation in pharmaceutical dispersions containing nifedipine (NIF) and either poly(vinyl) pyrrolidone (PVP) or hydroxypropyl methylcellulose acetate succinate (HPMCAS). The shape of the dielectric response (permittivity versus log time) curve was observed to be independent of temperature. Thus, for the pure NIF as well as the dispersions, the validity of the time-temperature superposition principle was established. Furthermore, though the shape of the full dielectric response varied with polymer concentration, the regime related to the α- or structural relaxation was found to superimpose for the dispersions, though not with the response of the NIF itself. Hence, there is a limited time-temperature-concentration superposition for these systems as well. Therefore, in this polymer concentration range, calculation of long relaxation times in these glass-forming systems becomes possible. We found that strong drug-polymer hydrogen bonding interactions improved the physical stability (i.e., delayed crystallization) by reducing the molecular mobility. The strength of hydrogen bonding, structural relaxation time, and crystallization followed the order: NIF$-$PV P>NIF$-$HPMCAS>NIF. With an increase in polymer concentration, the relaxation times were longer indicating a decrease in molecular mobility. The temperature dependence of relaxation time, in other words fragility, was independent of polymer concentration. This is the first application of the superposition principle to characterize structural relaxation in glassy pharmaceutical dispersions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

HFTS-2 (Final Report)

This report delves into the research program, identified tasks, various studies, observations, results, and conclusions under the Hydraulic Fracturing Test Site (HFTS-2) project. This test site is located in Loving County close to the Texas, New Mexico border. The program targeted the Wolfcamp formation in Delaware Basin. The aim of the project was to improve our understanding of hydraulic fracturing processes to not only optimize unconventional resource development in US Basins but to minimize environmental footprint as well. Various new diagnostic technologies were demonstrated at this site, including distributed acoustic microseismic, high resolution strain using Rayleigh frequency band (DSS-RFS), and in-fill proppant logging tool. Significant conclusions from this study include: 1) lateral and vertical fracture growth mapping as well as proppant transport behavior, 2) Use of DSS-RFS as a diagnostic tool to understand cluster level behavior, 3) Validation of proppant log, both at core scale as well as in-fill well implementation, and 4) New modeling tools to map far-field strain response using distributed strain sensing data. Specifically, far-field fracture distribution is influenced by linear fracture corridors defined by the stress-state as well as clustering behavior influenced by spatio-temporal effects. Depletion impacts on new stimulation was demonstrated and technically quantified. Significant vertical fracture height growth was observed. However, our understanding is limited by available gauge data availability. Numerical strain modeling techniques have been developed and demonstrated to help understand observed strain response behavior. Finally, proppant log has been further validated as a useful tool to map propped zones within the SRV. It has also shown very strong correlation with observed drawdown behavior at this test site. This report will detail many of these studies as well as technical results and conclusions from said studies. These include general subsurface characterization work, completion designs as implemented, studies looking at fracture geometry, high resolution microseismic study including source mechanisms, advanced DSS-RFS studies including drainage characterization, core characterization results, proppant analysis (core and in-fill child well), geochemistry, etc.

02 PETROLEUM↗
DOE OSTI2019

Path of Disposal for Hazardous and Non-hazardous Waste from Cradle to Grave

Hazardous waste is a threat to human health and the environment and must be managed and disposed of properly. A Solid Waste is defined as any material (solid, liquid, containerized gas) which has been discarded, abandoned (no longer needed), or recycled. The Resource Conservation Recovery Act (RCRA) is a law that creates the framework for the proper management of solid waste. Under RCRA, EPA has developed a program which ensures hazardous waste is managed safely from the moment it is generated to its final disposal (cradle-to-grave)2. To educate about how waste is handled at the Savannah River Research Campus (SRRC) under RCRA, the path it takes from point of generation (cradle) to disposal (grave), and the responsibilities of every person involved in the process. Researcher or other laboratory personnel that generates waste as a result of their work Responsibilities: - Fill out inventory log sheet and corresponding container sheet which includes the constituents of the waste; - Properly label waste container with SAA/WSA ID no., generator's name, what it is, the hazards, and date; - Place waste in designated waste storage area. Laboratory Custodian Responsibilities: - Ensures waste is handled and stored properly; - Ensures inventory is updated; - Ensures all container sheets are completed; - Ensures only authorized personal have access to waste storage areas. Environmental Compliance Authority Responsibilities: - Develops waste procedures; - Provide waste training; - Inspects for improperly handled waste; - Establishes or closes waste storage areas as needed; - Determines if waste can be recycled; - Determines if waste is RCRA hazardous: Is it U or P listed? - Unused commercial chemical products; Is it F listed - Spent solvents; Is it characteristic? - Flammable/Oxidizer, Corrosive, Reactive, Toxic; - Weighs waste to ensure laboratory has not exceeded its monthly or total storage limits; - Maintains waste records; - Determines how waste should be disposed: Trash - Nonhazardous solids; Drain - Nonhazardous Liquids; Labpack; - Prepares waste for shipment with Vendor and Department of Transportation (DOT) personnel. Packages, Transports, and Treats Hazardous Waste Responsibilities: - Must be EPA permitted and approved by the Department of Energy - Picks up hazardous waste for transport to a treatment, storage or disposal facility depending on waste disposal requirements - Must meet all Department of Transportation regulations for transporting hazardous waste - Dispose of waste according to RCRA regulations. Due to the potential risks to human health and the environment, waste must be handled safely through the chain of possession from cradle to grave. To ensure proper handling, there are many safety checks as required by RCRA and DOT regulations. This includes proper labeling, inventory, and characterization to ensure all hazards are known, inspections by the Custodian, ECA, and the state regulator (SCDHEC), and transportation verifications and manifesting. One of the best ways to reduce the risks that waste presents is to minimize or eliminate the creation of waste. This can be accomplished through source reduction which includes: Inventory control, material substitution, process modification, improved housekeeping, and preventative maintenance and recycling.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Salmonella Inactivation During Extrusion of an Oat Flour Model Food

Abstract Little research exists on Salmonella inactivation during extrusion processing, yet many outbreaks associated with low water activity foods since 2006 were linked to extruded foods. The aim of this research was to study Salmonella inactivation during extrusion of a model cereal product. Oat flour was inoculated with Salmonella enterica serovar Agona, an outbreak strain isolated from puffed cereals, and processed using a single‐screw extruder at a feed rate of 75 kg/h and a screw speed of 500 rpm. Extrudate samples were collected from the barrel outlet in sterile bags and immediately cooled in an ice–water bath. Populations were determined using standard plate count methods or a modified most probable number when populations were low. Reductions in population were determined and analyzed using a general linear model. The regression model obtained for the response surface tested was Log ( N R / N O ) = 20.50 + 0.82 T − 141.16a w – 0.0039 T 2 + 87.91 a w 2 ( R 2 = 0.69). The model showed significant ( p < 0.05) linear and quadratic effects of a w and temperature and enabled an assessment of critical control parameters. Reductions of 0.67 ± 0.14 to 7.34 ± 0.02 log CFU/g were observed over ranges of a w (0.72 to 0.96) and temperature (65 to 100 °C) tested. Processing conditions above 82 °C and 0.89 a w achieved on average greater than a 5‐log reduction of Salmonella . Results indicate that extrusion is an effective means for reducing Salmonella as most processes commonly employed to produce cereals and other low water activity foods exceed these parameters. Thus, contamination of an extruded food product would most likely occur postprocessing as a result of environmental contamination or through the addition of coatings and flavorings.

Anderson, Nathan M.↗
DOE OSTI2023

Topological enhancement of nonlinear transport in unconventional point-node semimetals

The topological singularity of the Bloch states close to the Fermi level significantly enhances nonlinear electric responses in topological semimetals. Here, we systematically characterize this enhancement for a large class of topological nodal-point fermions, including those with linear, linear-quadratic, and quadratic dispersions. Specifically, we determine the leading power-law dependence of the nonlinear response functions on the chemical potential μ defined relative to the nodal point. We identify two characteristics that qualitatively improve nonlinear transports compared to those of conventional Dirac and Weyl fermions. First, the type-II (overtilted) spectrum leads to the log μ enhancement of nonlinear response functions having zero scaling dimension with respect to μ, which is not seen in a type-I (moderately or not tilted) spectrum. Second, the anisotropic linear-quadratic dispersion increases the power of small-μ divergence for the nonlinear response tensors along the linearly dispersing direction. Furthermore, our work reveals new experimental signatures of unconventional nodal points in topological semimetals as well as provides a guiding principle for giant nonlinear electric responses.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Reservoir response to thermal and high-pressure well stimulation efforts at Raft River, Idaho

An injection stimulation test begun at the Raft River geothermal reservoir in June, 2013 has produced a wealth of data describing well and reservoir response via high-resolution temperature logging and distributed temperature sensing, seismic monitoring, periodic borehole televiewer logging, periodic stepped flow rate tests and tracer injections before and after stimulation efforts. One of the primary measures of response to the stimulation is the relationship between fluid pressure and flow rate, short-term during forced flow rate changes and the long-term change in injectivity. In this paper we examine that hydraulic response using standard pumping test analysis methods, largely because pressure response to the stimulation was not detected, or measurable, in other wells. Analysis of stepped rate flow tests supports the inference from other data that a large fracture, with a radial extent of one to several meters, intersects the well in the target reservoir, suggests that the flow regime is radial to a distance of only several meters and demonstrates that the pressure build-up cone reaches an effective constant head at that distance. The well’s longer term hydraulic response demonstrated continually increasing injectivity but at a dramatically faster rate later from ~2 years out and continuing to the present. The net change in injectivity is significantly greater than observed in other longterm injectivity monitoring studies, with an approximately 150–fold increase occurring over ~2.5 years. While gradually increasing injectivity is a likely consequence of slow migration of a cooling front, and consequent dilation of fractures, the steady, ongoing, rate of increase is contrary to what would be expected in a radial or linear flow regime, where the cooling front would slow with time. As a result, occasional step-like changes in injectivity, immediately following high-flow rate tests suggest that hydro shearing during high-pressure testing altered the near-well permeability structure.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Gaussian Kernel Methods for Seismic Fragility and Risk Assessment of Mid-Rise Buildings

Seismic fragility functions can be evaluated using the cloud analysis method with linear regression which makes three fundamental assumptions about the relation between structural response and seismic intensity: log-linear median relationship, constant standard deviation, and Gaussian distributed errors. While cloud analysis with linear regression is a popular method, the degree to which these individual and compounded assumptions affect the fragility and the risk of mid-rise buildings needs to be systematically studied. This paper conducts such a study considering three building archetypes that make up a bulk of the building stock: RC moment frame, steel moment frame, and wood shear wall. Gaussian kernel methods are employed to capture the data-driven variations in the median structural response and standard deviation and the distributions of residuals with the intensity level. With reference to the Gaussian kernels approach, it is found that while the linear regression assumptions may not affect the fragility functions of lower damage states, this conclusion does not hold for the higher damage states (such as the Complete state). In addition, the effects of linear regression assumptions on the seismic risk are evaluated. For predicting the demand hazard, it is found that the linear regression assumptions can impact the computed risk for larger structural response values. However, for predicting the loss hazard with downtime as the decision variable, linear regression can be considered adequate for all practical purposes.

58 GEOSCIENCES↗