SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
This dataset consists of Baker Hughes Pressure-Temperature gauge readings on fiber optics in Utah FORGE Well 16B(78)-32. This gauge is at a measured depth of 7,056.67 feet. The true vertical depth can be determined from the well survey data, which is linked below. The data consists of time series pressure-temperature data and plots from March 26th - April 20th 2024.
This dataset contains raw and processed zero resistance ammetry (ZRA) measurements collected from wetland sediments at Old Woman Creek, a freshwater estuary on Lake Erie, Ohio, USA, between June and November 2022. Measurements were obtained using a vertically deployed electrode array positioned at multiple depths within the sediment profile to capture electrochemical gradients associated with microbial activity and sediment geochemistry. The raw dataset consists of parsed instrument log files containing timestamps, electrode pair identifiers, and measured electrical potential (mV). The processed dataset includes standardized and quality-controlled values with instrument saturation limits removed and timestamps converted to ISO 8601 format. Electrode line identifiers were mapped to physical depths, enabling interpretation of depth-resolved electrochemical gradients. Instrument saturation values (−2048, −2047, 2047, and 2048 mV) were identified as measurement limits and excluded from quantitative analyses. All data parsing, processing, and quality control steps are documented in an accompanying R Markdown script, ensuring full reproducibility from raw instrument logs to final datasets.
The Hermiston, Oregon Basalt CarbonSAFE Phase II project (HERO CarbonSAFE) seeks to accelerate the deployment of commercial carbon dioxide (CO2) storage projects in basaltic rocks. Basalt CO2 storage has several advantages to conventional saline storage reservoirs including 1. The potential for rapid mineralization of CO2, 2. Associated decreases in pressure and CO2 migration risks, 3. Reduced long-term monitoring requirements with respect to plume tracking, 4. Widespread geographic distribution and, 5. Large storage potential due to thickness, porosity, and CO2 interactions with basalt. And for locations such as the Pacific Northwest, Hawaii, Iceland, India and Japan, basalts may offer the only economically feasible option for local CO2 storage. However, there are limited field-scale assessments of CO2 storage in basalt, and current carbon capture utilization and storage (CCUS) permitting and regulatory frameworks were developed for conventional saline reservoirs. HERO CarbonSAFE is designed to address research gaps and uncertainties associated with basalt storage. Specifically, the project will assess the feasibility of CO2 injection in the deep layered basalts, long-term storage (mineralization), practical approaches for large-scale implementation (50+ million metric tons of CO2 over 30 years), lithology-specific risks, and the technoeconomic potential for CO2 storage in basalts. The HERO CarbonSAFE project will assess feasibility of developing a commercial-scale (50+ million metric tons of CO2) geological storage complex within the Columbia River Basalt Group (CRBG), a layered continental flood basalt complex that underlies Calpine’s natural gas-fired Hermiston Power Project (HPP) in Hermiston, OR (Figure 1). Under this 2-year CarbonSAFE Phase II project, the HERO team will conduct a data acquisition campaign that includes drilling a stratigraphic well to a total depth of ~1,500 m into the thick layered basalts proximal to HPP. A comprehensive well logging and hydrologic testing program will be augmented with new core collected from flow zones and sealing units, and comprehensive laboratory testing to help refine the kinetic rates of mineralization. The newly acquired information will be integrated with existing data from regional wells to correlate basalt injection zone properties to develop storage hub/commercial-scale models. Using these models, the project team will evaluate injection scenarios to define the technical and economic potential for storing a minimum of 50 million metric tons of CO2 over a 30-year period, along with a robust sensitivity analysis on key parameters governing reservoir viability for sustainable injection over a commercial project lifetime. Specific technical objectives of HERO are: (1) assessing the reservoir response of a series of stacked layered reservoir flowtop sequences occurring in this area of the CRBG to commercial-scale injection volumes; (2) extending prior efforts by the project team to characterize the deep layered basalts encountered in regional studies, to leverage prior investments by U.S. Department of Energy’s (DOE) Carbon Storage program; (3) leveraging DOE’s mineralization characterization efforts to advance model parametrization for commercial scale injection of CO2 in basalts; (4) conducting risk assessments associated with scaling up to commercial storage hub injection goals, while validating DOE’s National Risk Assessment Partnership (NRAP) tools, to identify potential constraints that would prevent the CRBG from serving as a commercial-scale storage complex; (5) developing mitigation plans to address identified risks; (6) developing a commercial-scale injection and monitoring, verification and accounting (MVA) strategy; (7) utilizing computational models to define and minimize, if possible, the Area of Review (AoR) under Class VI regulations; and (8) developing a robust CO2 management strategy for CRBG that also considers a regional source/sink approach that is responsive to stakeholder needs and industrial demand. Specific institutional objectives are: (1) identifying and developing plans to mitigate the nontechnical challenges associated with the build-out of a commercial-scale storage complex within the CRBG with integrated CO2 sources; (2) implementing the community outreach plan; (3) conducting regulatory research, including a survey of issues related to pore space ownership, MVA and long-term assurance of mineralization-based storage, to support an eventual application for a UIC Class VI permit; (4) advancing the project’s plan for CO2 liability management; and (5) continuing to refine and update the project’s economic model. The final objective is the preparation of a comprehensive Site Characterization Plan that draws upon the technical and institutional feasibility assessments to prepare the project for future commercialization efforts.
Sodium-cooled fast reactors (SFR), which use high temperature fluid near ambient pressure as coolant, are one of the most promising types of GEN IV reactors. One of the unique challenges of SFR operation is purification of high temperature liquid sodium with a cold trap to prevent corrosion and obstructing small orifices. We have developed a deep learning long short-term memory (LSTM) autoencoder for continuous monitoring of a cold trap and detection of operational anomaly. Transient data were obtained from the Mechanisms Engineering Test Loop (METL) liquid sodium facility at Argonne National Laboratory. The cold trap purification at METL is monitored with 31 variables, which are sensors measuring fluid temperatures, pressures and flow rates, and controller signals. Loss-of-coolant type anomaly in the cold trap operation was generated by temporarily choking one of the blowers, which resulted in temperature and flow rate spikes. The input layer of the autoencoder consisted of all the variables involved in monitoring the cold trap. The LSTM autoencoder was trained on the data corresponding to cold trap startup and normal operation regime, with the loss function calculated as the mean absolute error (MAE). The loss during training was determined to follow log-normal density distribution. During monitoring, we investigated a performance of the LSTM autoencoder for different loss threshold values, set at a progressively increasing number of standard deviations from the mean. The anomaly signal in the data was gradually attenuated, while preserving the noise of the original time series, so that the signal-to-noise ratio (SNR) averaged across all sensors decreased below unity. Results demonstrate detection of anomalies with sensor-averaged SNR < 1.
M dwarf stars are excellent candidates around which to search for exoplanets, including temperate, Earth-sized planets. To evaluate the photochemistry of the planetary atmosphere, it is essential to characterize the UV spectral energy distribution of the planet’s host star. This wavelength regime is important because molecules in the planetary atmosphere such as oxygen and ozone have highly wavelength-dependent absorption cross sections that peak in the UV (900–3200 Å). We seek to provide a broadly applicable method of estimating the UV emission of an M dwarf, without direct UV data, by identifying a relationship between noncontemporaneous optical and UV observations. Our work uses the largest sample of M dwarf star far- and near-UV observations yet assembled. We evaluate three commonly observed optical chromospheric activity indices—Hα equivalent widths and log{sub 10} L Hα /L bol , and the Mount Wilson Ca ii H&K S and R HK ' indices—using optical spectra from the HARPS, UVES, and HIRES archives and new HIRES spectra. Archival and new Hubble Space Telescope COS and STIS spectra are used to measure line fluxes for the brightest chromospheric and transition region emission lines between 1200 and 2800 Å. Our results show a correlation between UV emission-line luminosity normalized to the stellar bolometric luminosity and Ca ii R HK ' with standard deviations of 0.31–0.61 dex (factors of ~2–4) about the best-fit lines. We also find correlations between normalized UV line luminosity and Hα log 10 L Hα /L bol and the S index. These relationships allow one to estimate the average UV emission from M0 to M9 dwarfs when UV data are not available.
M dwarf stars are excellent candidates around which to search for exoplanets, including temperate, Earth-sized planets. To evaluate the photochemistry of the planetary atmosphere, it is essential to characterize the UV spectral energy distribution of the planet's host star. This wavelength regime is important because molecules in the planetary atmosphere such as oxygen and ozone have highly wavelength-dependent absorption cross sections that peak in the UV (900–3200 Å). We seek to provide a broadly applicable method of estimating the UV emission of an M dwarf, without direct UV data, by identifying a relationship between noncontemporaneous optical and UV observations. Our work uses the largest sample of M dwarf star far- and near-UV observations yet assembled. We evaluate three commonly observed optical chromospheric activity indices—Hα equivalent widths and log(10) L(Hα)/L(bol), and the Mount Wilson Ca ii H&K S and R'(HK) indices—using optical spectra from the HARPS, UVES, and HIRES archives and new HIRES spectra. Archival and new Hubble Space Telescope COS and STIS spectra are used to measure line fluxes for the brightest chromospheric and transition region emission lines between 1200 and 2800 Å. Our results show a correlation between UV emission-line luminosity normalized to the stellar bolometric luminosity and Ca ii R'(HK) with standard deviations of 0.31–0.61 dex (factors of ∼2–4) about the best-fit lines. We also find correlations between normalized UV line luminosity and Hα log(10) L(Hα)/L(bol) and the S index. These relationships allow one to estimate the average UV emission from M0 to M9 dwarfs when UV data are not available.
A TIME-HONORED system of recording medical histories and the data obtained on physical and laboratory examination has been that of writing the information on record sheets that go into a folder for each patient. In order to have information which would be more readily retrieved, 'a program was initiated in 1952 by the U. S. Naval School of Aviation Medicine in connection with their "Care of the Flyer" study to place this information on machine record cards. In 1958, a machine record card method was developed for recording medical data in connection with the astronaut selection program. Machine record cards were also developed by the Aero Medical Laboratory, Wright-Patterson AFB, Ohio, and the Aviation Medical Acceleration Laboratory, Naval Air Development Center, Johnsville, Pennsylvania, for use in connection with a variety of tests including acceleration stress.1 Therefore, a variety of systems resulted in which data of a medical nature could easily be recalled. During the NASA, Ames Research Center centrifuge studies/'S the pilot subjects were interviewed after each centrifuge run, or series of runs, and subjective information was recorded in a log book by the usual history taking methods referred to above. After the methods Were reviewed, it' was recognized that a card system would be very useful in recording data from our pilots after they had been exposed to acceleration stress. Since the acceleration stress cards already developed did not meet our requirements, it was decided a different card was needed.
Personal thermoregulatory systems which provide chest cooling are used in the industrial and aerospace environments to alleviate thermal stress. However, little information is available regarding the physiologic and circulatory changes produced by routine operation of these systems. The objectives of this study were to compare the effectiveness of two passive cooling vests, and to measure the body temperature and circulatory changes produced by each cooling vest configuration. A Life Enhancement Technologies, (LET) ice vest garment and a Steele, Inc. vest were used to cool the chest region of 11 male subjects (25 to 55 yr) in this study. Calf, forearm and finger blood flows were measured using a tetrapolar impedance rheograph. The subjects, seated in an upright position at normal room temperature (approximately 21 C) were tested for 60 min. with the cooling system operating at its maximum cooling capacity. Blood flows were recorded continuously using a computer data acquisition system with a sampling frequency of 250 Hz. Oral, right and left ear temperatures and cooling system parameters were logged manually every 5 min. Arm, leg, chest and rectal temperatures; heart rate; respiration; and an activity index were recorded continuously on a U.F.I., Inc. Biolog ambulatory monitor. No significant differences were found in either the oral or ear temperature responses to the two vests. However, the rectal and mean skin temperatures at the end of the cooling period were both significantly lower (P less than 0.05), approximately 0.2 and 1.9 C, respectively for the LET vest than for the Steele garment. These data show that different vest configurations may produce different thermal responses in healthy male subjects which should be considered in the use of these cooling garments.
Radiation portal monitors (RPMs) are widely used at border security checkpoints to detect the presence of radioactive materials in people, vehicles, and cargo. Typically, RPM detection systems consist of two pillars equipped with gamma and neutron detectors. To improve detection efficiency, RPMs employ techniques such as a limited energy window, dynamic alarm thresholds, and lead shielding. However, without continuous monitoring of background radiation, signal interpretation can be compromised, because environmental factors and mechanical failures can cause fluctuations. Here, we introduce a daily file format that logs gamma background and neutron background radiation levels continuously over a 24 h period; this format is different from traditional formats that record data only when the RPM is active or occupied. The approach enables RPM operators and analysts to (1) identify and diagnose malfunctioning components, (2) adjust system settings to account for dynamic environmental factors, and (3) use the recorded data to characterize outer space phenomena. Continuous background reporting is essential for identifying issues such as faulty connections, voltage divider failures, and errors in background updates. Continuous background reporting also enables the detection of external influences, including nearby X-ray scanners, temperature fluctuations, rainfall, cosmic radiation, and lunar phase changes. These data files are designed to be easily evaluated and parsed using common tools, and a quick review by an expert is often sufficient for problem diagnosis. We anticipate that continuous background radiation monitoring and these new strategies will significantly improve the accuracy and reliability of RPM systems, reducing the rate of false alarms and enhancing overall system performance.
In this paper, we have developed a methodology to estimate the spatiotemporal distribution of radiation air dose rates around the Fukushima Daiichi Nuclear Power Plant (FDNPP). In our exploratory data analysis, we found that (1) the temporal evolution of dose rates is composed of a log-linear decay trend and fluctuations of air dose rates that are spatially correlated among adjacent monitoring posts; and (2) the slope of the log-linear environmental decay trend can be represented as a function of the apparent initial dose rates, coordinate position, land-use type, and soil type. From these observations, we first estimated the log-linear decay trend at each location based on these predictors, using the random forest method. We then developed a modified Kalman filter coupled with a Gaussian process model to estimate the dose-rate time series at a given location and time. We applied this method to the Fukushima evacuation zone (as of March 2017), which included 17 monitoring post locations (with monitoring datasets collected between 2014 and 2018) and generated a time series of dose-rate maps. Our results show that this approach allows us to produce accurate spatial and temporal predictions of radiation dose-rate maps using limited spatiotemporal measurements.
We forward-model mass-weighted stellar ages (MWAs) and quiescent fractions (f Q ) in projected phase space (PPS), using data from the Sloan Digital Sky Survey, to jointly constrain an infall quenching model for galaxies in log (M vir /M ⊙ ) > 14 galaxy clusters at z ∼ 0. We find the average deviation in MWA from the MWA–M⋆ relation depends on position in PPS, with a maximum difference between the inner cluster and infalling interloper galaxies of ∼1 Gyr. Our model employs infall information from N-body simulations and stochastic star-formation histories from the universemachine model. We find total quenching times of t Q = 3.7 ± 0.4 Gyr and t Q = 4.0 ± 0.2 Gyr after first pericentre, for 9 < log (M ⋆ /M ⊙ ) < 10 and 10 < log (M ⋆ /M ⊙ ) < 10.5 galaxies, respectively. By using MWAs, we break the degeneracy in time of quenching onset and time-scale of star formation rate (SFR) decline. We find that time of quenching onset relative to pericentre is $t_{\mathrm{delay}}=3.5^{+0.6}_{-0.9}$ Gyr and $t_{\mathrm{delay}}=-0.3^{+0.8}_{-1.0}$ Gyr for 9 < log (M ⋆ /M ⊙ ) < 10 and 10 < log (M ⋆ /M ⊙ ) < 10.5 galaxies, respectively, and exponential SFR suppression time-scales are τenv ≤ 1.0 Gyr for 9 < log (M ⋆ /M ⊙ ) < 10 galaxies and τenv ∼ 2.3 Gyr for 10 < log (M ⋆ /M ⊙ ) < 10.5 galaxies. Stochastic star formation histories remove the need for rapid infall quenching to maintain the bimodality in the SFR of cluster galaxies; the depth of the green valley prefers quenching onsets close to first pericentre and a longer quenching envelope, in slight tension with the MWA-driven results. Taken together these results suggest that quenching begins close to, or just after pericentre, but the time-scale for quenching to be fully complete is much longer and therefore ram-pressure stripping is not complete on first pericentric passage.
Code to organize, prepare, and segment multi-scan, larger-than-memory, volumetric dataset. Deep learning segmentation uses pytorch-lightning for code organization, logging and metrics, and multi-GPU parallelization of training and prediction. Also uses moani for volumetric data augmentation and model implementation (currently U-Net++). Training can be done slice-by-slice with 2D models trained on 2D patches either aligned with or perpendicular to the electrode plane, or with 3D models on 3D patches. Sparse labels can be used to minimize required hand-labeling -- less than 0.1% of the entire dataset was labeled. Also includes code for data preparation (alignment/cropping/patching).
This report analyzes experimental data from Test Plans TP 08-02, TP 12-02, and TP 20-01 to add new log K values and Pitzer interaction parameters for Fe, Pb, Mg, Nd and B reactions to the WIPP geochemical thermodynamic database, data0.fm 1.
This dataset contains daily csv files summarizing data from 10-min wind statistics from Doppler lidar at the BARG site for the WFIP3 event log. See https://a2e.energy.gov/ds/wfip3/bloc.lidar.10min.z01.c1/summary
Observations of the Crab nebula are described, which were made under the OAO 2/NASA guest-investigator program with WEP stellar photometers. The 10 foot-diameter focal plane diaphragm was ample enough to accept the 4 ft X 6 ft image. The logarithm of the integrated relative intensity per wavelength interval, corrected for sky background, and the rms error, from 11 passbands in the range 4250 to 1380 A, are given. No correction was given for polarization of light. The data were converted to logarithm of the flux density per frequency interval and plotted on scales of log nu (Hz) and of reciprocal microns with two adjustments.
The framework in which minimum-commitment analyses of creep-rupture data can be implemented is outlined. The approach is termed the focal point convergence method (FPCM) because the basic parameter A, also known as stability factor, is geometrically the (imaginary) focal point of convergence of all isothermals when extended to the very long or very short times necessary for such convergence to occur. The method can be implemented either by manual-graphical analysis or by computer code. The method is illustrated in detail for the nickel-base alloy Astroloy, as well as for steels, other nickel-base alloys, and aluminum alloys. The minimum-commitment concept is extended to the analysis of creep-rupture data where each isothermal is generated by an oblique translation of the 'master curve' when plotted on log rupture time and log stress axes. The oblique translation method uses the same types of functions in the FPCM. Approaches for treating multiheats on the basis of the FPCM are discussed in detail.
To examine chemical transformation within stagnant air masses and the atmospheric processes acting upon such air masses, the United States EPA sponsored a study in the summer of 1980 in the northeastern region of the country. Ten research aircraft and several mobile and stationary surface monitoring platforms participated in an intensive measurement program between 16 July and 15 August 1980. Pollutants of interest included SO2, NO, NO(x), HC, O3, sulfate, nitrate, and aerosols in general. This paper summarizes the activities of these research aircraft. Three aircraft and one helicopter logged a total of 353 flight hours during 100 missions in the program. The flight patterns and data collected for each mission are documented. This summary will allow scientists who are interested in this data base to identify subsets of the data for model development.
The purpose of this study is to use airborne imaging spectrometer data to discriminate hydrothermal alteration mineral assemblages associated with silver and gold mineralization at Virginia City, NV. The data is corrected for vertical striping and sample gradients, and converted to flat-field logarithmic residuals. Log residual spectra from areas known to be altered are compared to field spectra for kaolinitic, illitic, sericitic, and propylitic alteration types. The areal distributions of these alteration types are estimated using a spectral matching technique. Both visual examination of spectra and the matching techniques are effective in distinguishing kaolinitic, illitic, and propylitic alteration types from each other. However, illitic and sericitic alteration cannot be separated using these techniques because the spectra of illite and sericite are very similar. A principal components analysis of 14 channels in the 2.14-2.38 micron wavelength region is also successful in discriminating and mapping illitic, kaolinitic, and propylitic alteration types.