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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 1,495 records · Page 83
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

RODeO (Revenue Operation and Device Optimization Model) [SWR 20-67]

The Revenue, Operation, and Device Optimization (RODeO) model explores optimal system design and operation considering different levels of grid integration, equipment cost, operating limitations, financing, and credits and incentives. RODeO is a price-taker model formulated as a mixed-integer linear programming (MILP) model in the GAMS modeling platform. The objective is to maximizes the net revenue for a collection of equipment at a given site. The equipment includes generators (e.g., gas turbine, steam turbine, solar, wind, hydro, fuel cells, etc.), storage systems (batteries, pumped hydro, gas-fired compressed air energy storage, long-duration systems, hydrogen), and flexible loads (e.g., electric vehicles, electrolyzers, flexible building loads). The input data required by RODeO can be classified into three bins: 1) utility service data, which refers to retail utility rate information (meter cost, energy and demand charges), 2) electricity market data, which include energy and reserve prices, 3) other inputs, which refer to additional electrical demand, product output demand, technological assumptions, financial properties, and operational parameters.

Guerra Fernandez, Omar Jose↗
DOE OSTI2022

The dataset of in-situ measurements of chemically and radiatively important atmospheric gases from the AGAGE and affiliated stations (2022R1)

In the ALE/GAGE/AGAGE global network program, continuous high frequency gas chromatographic measurements of four biogenic/anthropogenic gases (methane, CH4; nitrous oxide, N2O; hydrogen, H2; and carbon monoxide, CO) and several anthropogenic gases that contribute to stratospheric ozone destruction and/or to the greenhouse effect have been carried out at five globally distributed sites for several years. The program, which began in 1978, is divided into three parts associated with three changes in instrumentation: the Atmospheric Lifetime Experiment (ALE), which used Hewlett Packard HP5840 gas chromatographs; the Global Atmospheric Gases Experiment (GAGE), which used HP5880 gas chromatographs; and the present Advanced GAGE (AGAGE). AGAGE uses two types of instruments: a gas chromatograph with multiple detectors (GC-MD), and a gas chromatograph with mass spectrometric analysis (GC-MS). Beginning in January 2004, an improved cryogenic preconcentration system (Medusa) replaced the absorption-desorption module in the GC-MS systems at Mace Head and Cape Grim; this provided improved capability to measure a broader range of volatile perfluorocarbons with high global warming potentials. The Medusa GC-MS systems were subsequently used at other AGAGE stations (Trinidad Head, Barbados, American Samoa, Zeppelin, Jungfraujoch, and Goan) after the initial setup at Mace Head and Cape Grim. More information may be found at the AGAGE home page: https://agage.mit.edu/instruments. Data from the AGAGE and affiliated stations (total of 9 sites) between August 1993 and March 2021 are provided in “Agage_gcmd_gcms_data_2022_05_26_tar.gz” (compressed tar file). The metadata file has information on each station and currently released species. The standard scales used in archived species are listed in "AGAGE_scale_2022_v1.pdf". Additional information can be found on the AGAGE website (https://agage.mit.edu).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

United States Industrial Sector Energy End Use Analysis

The United States Department of Energy’s (DOE) Energy Information Administration (EIA) conducts the Manufacturing Energy Consumption Survey (MECS) to provide detailed data on energy consumption in the manufacturing sector. The survey is a sample of approximately 15,000 manufacturing establishments selected from the Economic Census - Manufacturing Sector. MECS provides statistics on the consumption of energy by end uses (e.g., boilers, process, electric drives, etc.) disaggregated by North American Industry Classification System (NAICS) categories. The manufacturing sector (NAICS Sector 31-33) consists of all manufacturing establishments in the 50 States and the District of Columbia. According to the NAICS, the manufacturing sector comprises establishments engaged in the mechanical, physical, or chemical transformation of materials, substances, or components into new products. The establishments are physical facilities such as plants, factories, or mills. For many of the sectors in the MECS datasets, information is missing because the reported energy use is less than 0.5 units or BTUs, or is withheld to avoid disclosing data for individual establishments, or is withheld because the standard error is greater than 50%. We infer what the missing information likely are using several approximations techniques. First, much of the missing data can be easily calculated by adding or subtracting other values reported by MECS. If this is not possible (e.g. two data are missing), we look at historic MECS reports to help identify the breakdown of energy use in the past and assume it remained the same for the current MECS. Lastly, if historic data is also missing, we assume that 3 digit NAICS classifications predict energy use in their 4, 5, or 6 digit NAICS sub-classifications, or vice versa. Along with addressing data gaps, end use energy is disaggregated beyond the specified MECS allocations using additional industry specific energy consumption data. The result is a completed table of energy end use by sector with mechanical drives broken down by pumps, fans, compressed air, and drives.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

Numerical Simulations of Cratering Effects in Adobe

This paper outlines a new simplified approach to developing a material model for adobe. The approach is to fit the equation of state (EOS) using a Mie-Gruneisen (MGR) analytical model with a P-Alpha compaction law, and to fit the pressure-dependent yield surface with the Geological Yield Surface (GEO) modeled in CTH using well characterized adobe. By identifying key parameters that governed material response, this simplified modeling approach aimed to increase the understanding of the shock compaction and compression behavior of adobe. The new simplified model for adobe represented in this paper replicated the features of past experimental penetration data. At low velocities the penetration behavior of steel spheres into adobe is captured by Stokes law, where the drag coefficient is inversely proportional to the Reynolds number. Each inherently different adobe material investigated had a separate linear region with the slope equal to the inverse of the coefficient of drag multiplied by impact velocity. A transition region following the Stokes region was identified in each adobe material, where the penetration depth was constant with increasing impact velocity. This penetration depth limit was shown to be dependent upon the yield strength of the adobe and inversely proportional to the initial density. Finally, examining the sensitivity of the penetration depth to the key model parameters, the material model for adobe was adjusted to provide the best fit to the experimental penetration data. In addition, a simplified water content, or initial saturation of the adobe, was introduced as another relevant parameter to characterize the response. Using this simple material model for adobe, validated with experimental penetration data, the response of adobe targets to hypervelocity impact of a variety of projectile types can be reliably predicted.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Electrochemical Compression for Ammonia Storage and Refrigeration System (Phase 2)

In this project, we studied the performance of the ammonia EC compressor under a variety of different conditions. We replicated preliminary data and using a small cell with 5 cm 2 of active area. We demonstrated the operation of larger cells with 100 cm 2 of active area. Further, we used a commercially available hydrogen EC compressor stack to analyze the scaled-up compressor performance. While previous experiments examined only the transient EC compressor performance, we developed test facilities that allowed the compressor to reach steady state.

25 ENERGY STORAGE↗
DOE OSTI2024

Vegetation Warming Experiment: Landscape-scale digital camera imagery for vegetation phenology, Utqiagvik (Barrow), Alaska, 2019

Images captured using a StarDot NetCam SC phenocamera looking east from the top of the Barrow Environmental Observatory (BEO) Sled Shed, Utqiagvik, Alaska. The camera was installed to remotely monitor plant phenology and operation of the Brookhaven National Laboratory (BNL) TEST group's ZPW (Zero Power Warming) chambers during the growing season of 2019. Images were captured from early spring (4 April) through to mid fall (30 October). Snowmelt, vegetation growth and senescence, and snow accumulation were captured. Images were uploaded to the BNL FTP server every hour, then from 2019-06-27 to 2019-10-02 images were recorded every 10 minutes, then at hourly intervals until the end of data collection on 2019-10-30. Files were renamed with the date and time of the image. jpg images have been compressed in *.tar.gz format (5.6 GB). Closer fields of view (northeasterly) were also captured using 4 Wingscapes TimelapseCam cameras mounted on a mast on the sled shed. These cameras were operated from 2019-06-23 to 2019-09-25, with images recorded every 30 minutes from 9:00 to 16:30 Alaska daylight time (AKDT, UTC-8). Individual jpg images have been compressed in zip format for each camera and also presented as mp4 timelapse movies.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Big Sky Regional Carbon Sequestration Partnership (Phase III Final Scientific/Technical Report)

The Big Sky Carbon Sequestration Partnership (BSCSP) pursued a Phase III demonstration project at Kevin Dome in north central Montana. Kevin Dome covers approximately 700 square miles and is a naturally occurring CO 2 reservoir that is flanked by oil and gas fields. The carbon dioxide (CO 2 ) is in the upper Devonian Duperow (carbonate) formation and does not reach the spill point of the dome; therefore, the dome has potential as a CO 2 sequestration reservoir, a CO 2 supply, or as both if anthropogenic sources and enhanced oil recovery (EOR) operations are associated with the dome. Kevin Dome could potentially act as a buffer to continue accepting anthropogenic CO 2 when EOR flooding operations are interrupted or completed. The project objective was to produce one million tonnes of CO 2 from the gas cap of Kevin Dome, pipe it laterally, inject, and re-store it in the brine leg of the same formation to test the hub / buffer storage concept. This was to be accomplished by drilling up to five production wells, building a short pipeline and compression facilities, and drilling an injection well and several monitoring wells. BSCSP commenced outreach and site characterization activities including acquiring baseline data for near-surface insurance monitoring, acquiring 3-dimensional, 9-component surface seismic over the project area, drilling two test wells (one in the production area and one in the injection area), coring key intervals, and performing comprehensive logging. Well tests of those wells revealed two barriers to the project. The production (Danielson 33-17) well was perforated in multiple zones but failed to produce any significant CO 2 . This was despite being drilled in the near vicinity of a historic well that had produced 3700 MCF per day in a drill stem test. Modeling indicated that this was likely due to a phase change during production causing a temperature drop resulting in hydrate and/or water ice formation that clogged the formation. Tests of the injection zone (Wallewein 22-1) well indicated total dissolved solids (TDS) slightly below the EPA required 10,000 parts per million (ppm) for a Class VI underground injection control permit. While the project was initiated before Class VI rules were promulgated, and this was an experimental project (seemingly qualified for a Class V permit), the Environmental Protection Agency (EPA) indicated that injection would require a Class VI permit. The low salinity result was unexpected as contours plotted based on regional formation water quality data indicated an expected TDS above 20,000 ppm, and wells between the recharge zone and the Wallewein well tested above 10,000 ppm. Faced with the inability to obtain an injection permit, the demonstration project could not proceed. However, the project had generated valuable samples and data on a large natural analog including 32 sq. mi. of 3-D, 9-C seismic, 430 ft. of carbonate core covering seven different depositional environments taken from areas with, and without the presence of CO 2 , 30 ft. of core of two caprocks, a tight carbonate and an anhydrite, a full set of modern logs on both wells, and well tests. DOE decided to re-scope the project around completing studies utilizing this data. This report covers both the initial scope and the re-scope (Task / Section numbers preceded with an R). While the report covers a wide range of project activities, highlights of this work include: Development of a geostatic model using neural nets to match well logs to facies and using multi-waveform seismic to inform reservoir heterogeneity; Unique mechanical testing of permeability – stress relationship in two caprock materials; Development of full waveform inversion to generate a high resolution velocity model; Model development for dual permeability (fracture and matrix) systems to better account for matrix-matrix interactions; Joint seismic wave inversion (including the first quadr-joint inversion) exhibiting better imaging of a challenging reservoir zone in stiff rock; Core flow and core flood results on a reactive carbonate; and Innovative laboratory measurements of seismic response of fractured core as a function of fluid fill.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Development of Separate Sensible and Latent Cooling System Using Electrochemical Compressor

Separate sensible and latent cooling systems offer superior energy efficiency performance compared to conventional vapor compression air conditioning systems. In this paper we describe an innovative non-vapor compression system that uses electrochemical compressor (ECC) to pump hydrogen between 2-metal hydride reservoirs to provide the sensible cooling effect. The heat rejected during this process is used to regenerate the ionic liquid (IL) used for desiccant dehumidification. The overall system design is illustrated. The Xergy version 4C electrochemical compressor, while not designed as a high pressure system, develops in excess of 2 MPa (300 psia) and pressure ratios > 30. The projected base efficiency improvement of the electrochemical compressor is expected to be ~ 20% with higher efficiency when in low capacity mode due to being throttleable to lower capacity with improved efficiency. The IL was tailored to maximize the absorption/desorption rate of water vapor at moderate regeneration temperature. This IL, namely, [EMIm].OAc, is a hydrophilic IL with a working concentration range of 28.98% when operating between 25 75 C. The ECC metal hydride system is expected to show superior performance to typical vapor compression systems. As such, the combined efficiency gains from the use of ECC and separate and sensible cooling would offer significant potential savings to existing vapor compression cooling technology. A high efficiency Window Air Conditioner system is described based on this novel configuration. The system s schematic is provided. Models compared well with actual operating data obtained by running the prototype system. Finally, a model of an LiCl desiccant system in conjunction with the ECC-based metal hydride heat exchangers is provided.

Electrochemical Compression↗
DOE OSTI2012

Fermi-LAT Observation of Supernova Remnant S147

We present an analysis of gamma-ray data obtained with the Large Area Telescope (LAT) onboard the Fermi Gamma-ray Space Telescope in the region around SNR S147 (G180.0-1.7). A spatially extended gamma-ray source detected in an energy range of 0.2-10 GeV is found to coincide with SNR S147. We confirm its spatial extension at >5{sigma} confidence level. The gamma-ray flux is (3.8 {+-} 0.6) x 10{sup -8} photons cm{sup -2} s{sup -1}, corresponding to a luminosity of 1.3 x 10{sup 34} (d/1.3 kpc){sup 2} erg s{sup -1} in this energy range. The gamma-ray emission exhibits a possible spatial correlation with prominent H{alpha} filaments of S147. There is no indication that the gamma-ray emission comes from the associated pulsar PSR J0538+2817. The gamma-ray spectrum integrated over the remnant is likely dominated by the decay of neutral {pi} mesons produced through the proton-proton collisions in the filaments. Reacceleration of pre-existing CRs and subsequent adiabatic compression in the filaments is sufficient to provide the required energy density of high-energy protons.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

X-Ray Diffraction and Electron Microscopy Studies of the Size Effects on Pressure-Induced Phase Transitions in CdS Nanocrystals

In recent years, investigations of the phase transition behavior of semiconducting nanoparticles under high pressure has attracted increasing attention due to their potential applications in sensors, electronics, and optics. However, current understanding of how the size of nanoparticles influences this pressure-dependent property is somewhat lacking. In particular, phase behaviors of semiconducting CdS nanoparticles under high pressure have not been extensively reported. Therefore, in this work, CdS nanoparticles of different sizes are used as a model system to investigate particle size effects on high-pressure-induced phase transition behaviors. In particular, 7.5, 10.6, and 39.7 nm spherical CdS nanoparticles are synthesized and subjected to controlled high pressures up to 15 GPa in a diamond anvil cell. Analysis of all three nanoparticles using in-situ synchrotron wide-angle X-ray scattering (WAXS) data shows that phase transitions from wurtzite to rocksalt occur at higher pressures than for bulk material. Bulk modulus calculations not only show that the wurtzite CdS nanomaterial is more compressible than rocksalt, but also that the compressibility of CdS nanoparticles depends on their particle size. Furthermore, sintering of spherical nanoparticles into nanorods was observed for the 7.5 nm CdS nanoparticles. Our results provide new insights into the fundamental properties of nanoparticles under high pressure that will inform designs of new nanomaterial structures for emerging applications.

Meng, Lingyao↗
DOE OSTI2022

Data-driven model for divertor plasma detachment prediction

We present a fast and accurate data-driven surrogate model for divertor plasma detachment prediction leveraging the latent feature space concept in machine learning research. Our approach involves constructing and training two neural networks: an autoencoder that finds a proper latent space representation (LSR) of plasma state by compressing the multi-modal diagnostic measurements and a forward model using multi-layer perception (MLP) that projects a set of plasma control parameters to its corresponding LSR. By combining the forward model and the decoder network from autoencoder, this new data-driven surrogate model is able to predict a consistent set of diagnostic measurements based on a few plasma control parameters. In order to ensure that the crucial detachment physics is correctly captured, highly efficient 1D UEDGE model is used to generate training and validation data in this study. The benchmark between the data-driven surrogate model and UEDGE simulations shows that our surrogate model is capable of providing accurate detachment prediction (usually within a few per cent relative error margin) but with at least four orders of magnitude speed-up, indicating that performance-wise, it has the potential to facilitate integrated tokamak design and plasma control. Comparing with the widely used two-point model and/or two-point model formatting, the new data-driven model features additional detachment front prediction and can be easily extended to incorporate richer physics. This study demonstrates that the complicated divertor and scrape-off-layer plasma state has a low-dimensional representation in latent space. Understanding plasma dynamics in latent space and utilising this knowledge could open a new path for plasma control in magnetic fusion energy research.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Experimental shock Hugoniot and melt boundary temperatures of aluminum

Aluminum is a ubiquitous component in dynamic compression, pulsed power, and other high energy density physics studies. Its high-pressure behavior and phase diagram are extensively studied standards in shockwave physics. While theoretical calculations and multiphase equations of state have been benchmarked to velocity measurements of loading and unloading waves, pressure and density under shock, and other mechanical data, experimental temperature data under these conditions have not been reported. We conducted a series of experiments shocking and releasing aluminum 6061 and 1100 samples into lithium fluoride windows. We measured temperature at the sample–window interface under steady compression and subsequent isentropic release. These results allow us to constrain the temperature of the solid Hugoniot and the boundary between the liquid and face-centered cubic solid phases.

Hartsfield, Thomas Murray [Sandia National Laborat↗
DOE OSTI2013

Specific features of the structure of the Z-pinch emitting region formed during the implosion of a foam-wire load at the ANGARA-5-1 facility

Results are presented from experimental studies of the structure of the compressed plasma of a Z-pinch produced during the implosion of a foam-wire load at the current of up to 3 MA. The foam-wire load consisted of two nested cylindrical cascades, one of which was a solid or hollow cylinder made of low-density agar-agar foam, while the other was a wire array. The wall thickness of a hollow foam cylinder was 100-200 {mu}m. The images of the pinch and its spectrum obtained with the help of multiframe X-ray cameras and a grazing incidence spectrograph with a spatial resolution were analyzed. Data on the spatial structure of the emitting regions and the soft X-ray (SXR) spectrum of the Z-pinch in the final stage of compression of a foam-wire load were obtained. The implosion modes characterized by the formation of hot regions during implosion of such loads were revealed. The characteristic scale lengths of the hot regions were determined. It is shown that the energy distribution of SXR photons in the energy range from 80 eV to 1 keV forms the spatial structure of Z-pinch images recorded during the implosion of foam-wire loads. It is revealed that the spectral density of SXR emission in the photon energy range of 300-600 eV from hot Z-pinch regions exceeds the spectral density of radiation from the neighboring Z-pinch regions by more than one order of magnitude. Groups of lines related to the absorption and emission of radiation by atoms and multicharged ions of carbon and oxygen in the outer foam cascade of a foam-wire load were recorded for the first time by analyzing the spatial distribution of the SXR spectra of multicharged ions of the Z-pinch. The groups of absorption lines of ions (C III, O III, O IV, and O VI) corresponding to absorption of SXR photons in the Z-pinch of a tungsten wire array, which served as the inner cascade of a foam-wire load, were identified. The plasma electron temperature measured from the charge composition of carbon and oxygen ions in the outer agar-agar foam cascade was 10-40 eV. During the implosion of foam-wire loads at currents of up to 3 MA, SXR pulses (h{nu} > 100 eV) with a duration of 10 ns and peak power of 3 TW were detected. It is shown that the temporal profile of single-peak and double-peak SXR pulses can be controlled by varying the parameters of the outer and inner cascades of the foam-wire load.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Bayesian learning with Gaussian processes for low-dimensional representations of time-dependent nonlinear systems

This work presents a data-driven method for learning low-dimensional time-dependent physics-based surrogate models whose predictions are endowed with uncertainty estimates. We use the operator inference approach to model reduction that poses the problem of learning low-dimensional model terms as a regression of state space data and corresponding time derivatives by minimizing the residual of reduced system equations. Standard operator inference models perform well with accurate training data that are dense in time, but producing stable and accurate models when the state data are noisy and/or sparse in time remains a challenge. Another challenge is the lack of uncertainty estimation for the predictions from the operator inference models. Our approach addresses these challenges by incorporating Gaussian process surrogates into the operator inference framework to (1) probabilistically describe uncertainties in the state predictions and (2) procure analytical time derivative estimates with quantified uncertainties. The formulation leads to a generalized least-squares regression and, ultimately, reduced-order models that are described probabilistically with a closed-form expression for the posterior distribution of the operators. The resulting probabilistic surrogate model propagates uncertainties from the observed state data to reduced-order predictions. Furthermore, we demonstrate the method is effective for constructing low-dimensional models of two nonlinear partial differential equations representing a compressible flow and a nonlinear diffusion–reaction process, as well as for estimating the parameters of a low-dimensional system of nonlinear ordinary differential equations representing compartmental models in epidemiology.

Data-driven model reduction↗
DOE OSTI2023

Closed Loop Geothermal Working Group: GeoCLUSTER App, Subsurface Simulation Results, and Publications

To better understand the heat production, electricity generation performance, and economic viability of closed-loop geothermal systems in hot-dry rock, the Closed-Loop Geothermal Working Group -- a consortium of several national labs and academic institutions has tabulated time-dependent numerical solutions and levelized cost results of two popular closed-loop heat exchanger designs (u-tube and co-axial). The heat exchanger designs were evaluated for two working fluids (water and supercritical CO2) while varying seven continuous independent parameters of interest (mass flow rate, vertical depth, horizontal extent, borehole diameter, formation gradient, formation conductivity, and injection temperature). The corresponding numerical solutions (approximately 1.2 million per heat exchanger design) are stored as multi-dimensional HDF5 datasets and can be queried at off-grid points using multi-dimensional linear interpolation. A Python script was developed to query this database and estimate time-dependent electricity generation using an organic Rankine cycle (for water) or direct turbine expansion cycle (for CO2) and perform a cost assessment. This document aims to give an overview of the HDF5 database file and highlights how to read, visualize, and query quantities of interest (e.g., levelized cost of electricity, levelized cost of heat) using the accompanying Python scripts. Details regarding the capital, operation, and maintenance and levelized cost calculation using the techno-economic analysis script are provided. This data submission will contain results from the Closed Loop Geothermal Working Group study that are within the public domain, including publications, simulation results, databases, and computer codes. GeoCLUSTER is a Python-based web application created using Dash, an open-source framework built on top of Flask that streamlines the building of data dashboards. GeoCLUSTER provides users with a collection of interactive methods for streamlining the exploration and visualization of an HDF5 dataset. The GeoCluster app and database are contained in the compressed file geocluster_vx.zip, where the "x" refers to the version number. For example, geocluster_v1.zip is Version 1 of the app. This zip file also contains installation instructions. **To use the GeoCLUSTER app in the cloud, click the link to "GeoCLUSTER on AWS" in the Resources section below. To use the GeoCLUSTER app locally, download the geocluster_vx.zip to your computer and uncompress this file. When uncompressed this file comprises two directories and the geocluster_installation.pdf file. The geo-data app contains the HDF5 database in condensed format, and the GeoCLUSTER directory contains the GeoCLUSTER app in the subdirectory dash_app, as app.py. The geocluster_installation.pdf file provides instructions on installing Python, the needed Python modules, and then executing the app.

15 GEOTHERMAL ENERGY↗
DOE OSTI2018

Effect of Plane Strain Compression and Subsequent Recrystallization Annealing on Microstructures and Phase Transformation of NiTiFe Shape Memory Alloy

The effect of plane strain compression and subsequent recrystallization annealing on microstructures and phase transformation of NiTiFe shape memory alloy (SMA) is investigated. Inhomogeneous plastic deformation at various deformation degrees occurs in NiTiFe SMA during plane strain compression. Nanocrystalline phase and amorphous phase increase as the deformation degree increases. B2 austenite, B19′ martensite, nanocrystalline and amorphous phases coexist in the NiTiFe samples subjected to large plastic strain. The static recrystallization mechanisms depend on the microstructures of the deformed NiTiFe samples. The static recrystallization mechanisms deal with nucleation and growth of the recrystallized grains, growth of nanocrystalline phase and crystallization of amorphous phase. Grain size, subgrain boundaries, geometrically necessary dislocation density and Schmid factor are captured on the basis of electron backscattered diffraction data. The process of recrystallization annealing cannot eliminate the deformation texture completely. The slip direction [110] is the most favorable slip direction in the recrystallized NiTiFe sample. Plane strain compression along with subsequent recrystallization annealing changes the phase transformation path of as-rolled NiTiFe SMA, and it results in the decreasing martensite transformation start temperature. The three annealed NiTiFe samples exhibit the similar phase transformation behavior since complete recrystallization annealing leads to the similar microstructures.

36 MATERIALS SCIENCE↗
DOE OSTI2026

An analysis of alcohol compression ignition strategies on different engine platforms

Strategies that enable ignition of the low cetane alcohol fuels (methanol and ethanol) include intake heating (direct or via hot residual trapping), increased compression ratio (CR), multi-injection strategies, ignition enhancers, and active prechambers. The literature consistently shows alcohol compression ignition (CI) is more efficient than diesel at high loads irrespective of ignition strategy but shows contradictory results at low loads. To understand this, this work combines data from four different engine platforms ranging from a displaced volume of 0.4 to 2.1 L/cyl. using different alcohol CI ignition strategies. Using modeling to support experimental analysis, alcohol-specific efficiency penalties are highlighted to inform alcohol combustion system development. The alcohols’ lower energy density means more fuel must be injected near top dead center to achieve a given load, increasing the relative penalty of sensible/latent heating. Pilot injections help reduce this penalty. Intake heating incurs both a heat transfer penalty and a thermodynamic penalty due to a reduced ratio of specific heats during compression. A strategy that combines elevated CR, large pilot injections, and ignition enhancers can avoid this penalty. Alternatively, a prechamber strategy can achieve this without changing the CR, nor needing ignition enhancers in the fuel. At low loads, diesel burns in a partially premixed mode characterized by high burn rates and low heat losses, reducing alcohol-specific combustion benefits. Alcohol CI on the light-duty platform showed abnormally high heat transfer over diesel compared to other platforms, favoring a more premixed/partially premixed strategy despite a combustion efficiency tradeoff.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Estimation of the orientation of stress in the Earth’s crust without earthquake or borehole data

Abstract Mechanical stress acting in the Earth’s crust is a fundamental property that is important for a wide range of scientific and engineering applications. The orientation of maximum horizontal compressive stress can be estimated by inverting earthquake source mechanisms and measured directly from borehole-based measurements, but large regions of the continents have few or no observations. Here we present an approach to determine the orientation of maximum horizontal compressive stress by measuring stress-induced anisotropy of nonlinear susceptibility, which is the derivative of elastic modulus with respect to strain. Laboratory and Earth experiments show that nonlinear susceptibility is azimuthally dependent in an anisotropic stress field and is maximum in the orientation of maximum horizontal compressive stress. We observe this behavior in the Earth—in Oklahoma and New Mexico, U.S.A, where maximum nonlinear susceptibility coincides with the orientation of maximum horizontal compressive stress measured using traditional methods. Our measurements use empirical Green’s functions and solid-earth tides and can be applied at different temporal and spatial scales.

58 GEOSCIENCES↗