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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

EGS Collab Experiment 1: Core Logs

Core logs from the EGS Collab project Experiment 1 for the stimulation (Injection) well (E1-I), the Production well (E1-P), and monitoring wells (E1-OT, E1-OB, E1-PST, E1-PSB, E1-PDT, and E1-PDB) on the 4850 Level of SURF (the Sanford Underground Research Facility), single PDF file, 5-ft run intervals. In the monitoring well IDs, "O" indicates that the well is orthogonal to the anticipated fracture plane, "P" indicates that the well is parallel to the anticipated fracture plane, "S" indicates a shallow well, "D" indicates a deep well, "T" refers to top, and "B" refers to bottom. Logs include: experiment number; borehole ID; depth interval; run number; final packed core box number; scribe line (yes/no; red-on-right convention); logging dates; logger initials; as well as sketches of core foliation, folding, and fracturing with additional details and notes on other features of interest.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Utah FORGE: Updated FMI Fracture Log from Well 16A(78)-32

This dataset consists of an Excel spreadsheet detailing the fracture picks from a reinterpretation of the formation micro-imaging (FMI) log from Utah FORGE well 16A(78)-32. The provided information details fracture location, geometry, and type. Also included here is a link to the original raw and processed FMI logs, as well as other data from the 2021 well logging.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Utah FORGE: Well 56-32 Drilling Data and Logs

This dataset consists of drilling data (Pason data spreadsheets, daily reports, days v. depth, mud logs), Schlumberger logs (FMI, shear anisotropy analysis, memory, sonic, array induction/spectral density/dual spaced neutron/gamma ray/caliper, spectral GR/temperature, and Gardner density correlation), and an end of well report (EOWR) for Utah FORGE well 56-32. This is a vertical well that will be used for seismic monitoring. It was drilled between February 7th and February 21st 2021 to a depth of 9,145 feet. More information about this well can be found at: https://utahforge.com/2021/02/09/drilling-progress-of-well-56-32/ (linked below)

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

LogPath: Log data based energy consumption analysis enabling electric vehicle path optimization

Vehicle navigation and path optimization require a more meticulous approach when it deals with EVs (electric vehicles) and SDVs (software-defined vehicles), due to lengthy charging times and the lack of charging infrastructure. Long-distance freight EV trucking needs path guidance with accurate energy consumption estimates to prevent charging-related failures. We developed a novel energy consumption estimation approach that only uses battery log data to extract major vehicle parameters to increase EV navigation accuracy without additional sensors. This is enabled by extracting multiple drive modes from the log data for analysis. The system provides 1) routes, 2) charge locations, 3) charging times, and 4) optimal vehicle speeds that guarantee the shortest travel time. Here we successfully validated the system using log data collected from an EV and Tesla's Supercharging map in the US and compared it with the commercially available navigation system, Tesla's trip planner, whose capabilities solely include charging time and routing.

EV (Electric vehicles) navigation↗
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 OSTI2016

Remote Geophysical Logging at the Hanford Single-Shell Tank Farms: Maintaining Efficiency and Reducing Personnel Hazards - 16190

Vadose zone characterization around groups of underground waste storage tanks (known as tank farms) at the US DOE Hanford Site in Washington State is conducted to assess the presence and extent of manmade gamma-ray emitting radionuclides. Boreholes around the tanks are characterized using a high-resolution spectral gamma logging system (SGLS). In the past, logging operations required workers to remain inside the tank farm boundary during data acquisition. This approach was effective; however, personnel were at risk of exposure to potential radiological hazards, chemical hazards, and/or vapor releases that can be associated with the tank farm environment. Limitations associated with this work environment necessitated a new approach in order to decrease the amount of time personnel spent in the farm without affecting work productivity and efficiency. In order to accomplish this, a new remote logging cable support (RLCS) was developed and implemented which effectively removed workers from the hazards associated with the tank farm environment. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

Glass Buttes Well 52-33 Core Log

Core log from Glass Buttes Well 52-33, drilled by Geodrill Rig 6 in 2014 to a depth of 3000 feet. Logged at 500 ft intervals.

15 GEOTHERMAL ENERGY↗
DOE OSTI2018

Utah FORGE: Stress Logging Data

This spreadsheet consist of data and graphs from deep well 58-32 stress testing from 6900 - 7500 ft depth. Measured stress data were used to correct logging predictions of in situ stress. Stress plots shows pore pressure (measured during the injection testing), the total vertical in situ stress (determined from the density logging) and the total maximum and minimum horizontal stresses. The horizontal stresses were determined from the DSI (Dipole Sonic Imager) and corrected to match the direct measurements.

15 GEOTHERMAL ENERGY↗
DOE OSTI2015

Near-equipartition jets with log-parabola electron energy distribution and the blazar spectral-index diagrams

Fermi-LAT analyses show that the γ-ray photon spectral indices Γ{sub γ} of a large sample of blazars correlate with the νF{sub ν} peak synchrotron frequency ν{sub s} according to the relation Γ{sub γ}=d−klog ν{sub s}. The same function, with different constants d and k, also describes the relationship between Γ{sub γ} and peak Compton frequency ν{sub C}. This behavior is derived analytically using an equipartition blazar model with a log-parabola description of the electron energy distribution (EED). In the Thomson regime, k=k{sub EC}=3b/4 for external Compton (EC) processes and k=k{sub SSC}=9b/16 for synchrotron self-Compton (SSC) processes, where b is the log-parabola width parameter of the EED. The BL Lac object Mrk 501 is fit with a synchrotron/SSC model given by the log-parabola EED, and is best fit away from equipartition. Corrections are made to the spectral-index diagrams for a low-energy power-law EED and departures from equipartition, as constrained by absolute jet power. Analytic expressions are compared with numerical values derived from self-Compton and EC scattered γ-ray spectra from Lyα broad-line region and IR target photons. The Γ{sub γ} versus ν{sub s} behavior in the model depends strongly on b, with progressively and predictably weaker dependences on γ-ray detection range, variability time, and isotropic γ-ray luminosity. Implications for blazar unification and blazars as ultra-high energy cosmic-ray sources are discussed. Arguments by Ghisellini et al. that the jet power exceeds the accretion luminosity depend on the doubtful assumption that we are viewing at the Doppler angle.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Generating log-normal mock catalog of galaxies in redshift space

We present a public code to generate a mock galaxy catalog in redshift space assuming a log-normal probability density function (PDF) of galaxy and matter density fields. We draw galaxies by Poisson-sampling the log-normal field, and calculate the velocity field from the linearised continuity equation of matter fields, assuming zero vorticity. This procedure yields a PDF of the pairwise velocity fields that is qualitatively similar to that of N-body simulations. We check fidelity of the catalog, showing that the measured two-point correlation function and power spectrum in real space agree with the input precisely. We find that a linear bias relation in the power spectrum does not guarantee a linear bias relation in the density contrasts, leading to a cross-correlation coefficient of matter and galaxies deviating from unity on small scales. We also find that linearising the Jacobian of the real-to-redshift space mapping provides a poor model for the two-point statistics in redshift space. That is, non-linear redshift-space distortion is dominated by non-linearity in the Jacobian. The power spectrum in redshift space shows a damping on small scales that is qualitatively similar to that of the well-known Fingers-of-God (FoG) effect due to random velocities, except that the log-normal mock does not include random velocities. This damping is a consequence of non-linearity in the Jacobian, and thus attributing the damping of the power spectrum solely to FoG, as commonly done in the literature, is misleading.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

A Zoom-in Analysis of I/O Logs to Detect Root Causes of I/O Performance Bottlenecks

Scientific applications frequently spend a large fraction of their execution time in reading and writing data on parallel file systems. Identifying these I/O performance bottlenecks and attributing root causes are critical steps toward devising optimization strategies. Several existing studies analyze I/O logs of a set of benchmarks or applications that were run with controlled behaviors. However, there is still a lack of general approach that systematically identifies I/O performance bottlenecks for applications running "in the wild" on production systems. In this study, we have developed an analysis approach of "zooming in" from platform-wide to application-wide to job-level I/O logs for identifying I/O bottlenecks in arbitrary scientific applications. We analyze the logs collected on a Cray XC40 system in production over a two-month period. This study results in several insights for application developers to use in optimizing I/O behavior.

Wang, Teng↗
DOE OSTI2015

NMR Logging to Estimate Hydraulic Conductivity in Unconsolidated Aquifers

Abstract Nuclear magnetic resonance ( NMR ) logging provides a new means of estimating the hydraulic conductivity ( K ) of unconsolidated aquifers. The estimation of K from the measured NMR parameters can be performed using the Schlumberger‐Doll Research ( SDR ) equation, which is based on the Kozeny–Carman equation and initially developed for obtaining permeability from NMR logging in petroleum reservoirs. The SDR equation includes empirically determined constants. Decades of research for petroleum applications have resulted in standard values for these constants that can provide accurate estimates of permeability in consolidated formations. The question we asked: Can standard values for the constants be defined for hydrogeologic applications that would yield accurate estimates of K in unconsolidated aquifers? Working at 10 locations at three field sites in Kansas and Washington, USA, we acquired NMR and K data using direct‐push methods over a 10‐ to 20‐m depth interval in the shallow subsurface. Analysis of pairs of NMR and K data revealed that we could dramatically improve K estimates by replacing the standard petroleum constants with new constants, optimal for estimating K in the unconsolidated materials at the field sites. Most significant was the finding that there was little change in the SDR constants between sites. This suggests that we can define a new set of constants that can be used to obtain high resolution, cost‐effective estimates of K from NMR logging in unconsolidated aquifers. This significant result has the potential to change dramatically the approach to determining K for hydrogeologic applications.

Knight, Rosemary↗
DOE OSTI2014

SU-E-T-261: Plan Quality Assurance of VMAT Using Fluence Images Reconstituted From Log-Files

Purpose: A successful VMAT plan delivery includes precise modulations of dose rate, gantry rotational and multi-leaf collimator (MLC) shapes. One of the main problem in the plan quality assurance is dosimetric errors associated with leaf-positional errors are difficult to analyze because they vary with MU delivered and leaf number. In this study, we calculated integrated fluence error image (IFEI) from log-files and evaluated plan quality in the area of all and individual MLC leaves scanned. Methods: The log-file reported the expected and actual position for inner 20 MLC leaves and the dose fraction every 0.25 seconds during prostate VMAT on Elekta Synergy. These data were imported to in-house software that developed to calculate expected and actual fluence images from the difference of opposing leaf trajectories and dose fraction at each time. The IFEI was obtained by adding all of the absolute value of the difference between expected and actual fluence images corresponding. Results: In the area all MLC leaves scanned in the IFEI, the average and root mean square (rms) were 2.5 and 3.6 MU, the area of errors below 10, 5 and 3 MU were 98.5, 86.7 and 68.1 %, the 95 % of area was covered with less than error of 7.1 MU. In the area individual MLC leaves scanned in the IFEI, the average and rms value were 2.1 – 3.0 and 3.1 – 4.0 MU, the area of errors below 10, 5 and 3 MU were 97.6 – 99.5, 81.7 – 89.5 and 51.2 – 72.8 %, the 95 % of area was covered with less than error of 6.6 – 8.2 MU. Conclusion: The analysis of the IFEI reconstituted from log-file was provided detailed information about the delivery in the area of all and individual MLC leaves scanned.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-C-BRF-04: Delivered 4D Dose Calculation for Lung-VMAT Patients Using In- Treatment CBCT and LINAC Log Data

Purpose: To verify the delivered four-dimensional (4D) dose distribution for the lung VMAT using in-treatment 4D cone-beam CT (CBCT) and LINAC log data. Methods: Three patients for lung stereotactic radiotherapy (SRT) were treated by single-arc volumetric modulated arc therapy (VMAT) created by SmartArc in Pinnacle v9.2 (Philips, USA).Kilovoltage (kV) projection images were acquired during VMAT delivery using the x-ray volumetric imager, XVI (Elekta, UK). LINAC log data were also recorded via iCom interface (Elekta, UK). Subsequently, the iCom data format was converted to Pinnacle data format, thereby allowing Pinnacle to read actual MLC positions, jaw positions, gantry angles and MUs. These parameters were categorized into four groups according to patient's respiratory phase. The patient respiratory phase was determined from kV-projection images by in-house phase recognizing software. By exporting these data back to Pinnacle, in-treatment dose distributions for each respiratory phase were obtained by combining calculated dose having a particular phase. The 4D CBCT were reconstructed by in-house program. The density in the structures on the CBCT was overridden by the average density in the corresponding structures on the planning CT for the dose calculation. The dose indexes, such as maximum, minimum, mean dose in the target were compared among the plan, in-treatment 3D calculation, and in-treatment 4D calculation. Results: The day-to-day variation of the delivered dose was observed for all three patients. The maximum difference was 5.9% for the minimum dose in the target. Difference for the mean dose was found to be small (1.1% at maximum). Conclusion: We have obtained in-treatment dose distribution for each of the different respiratory phases using in-treatment 4D CBCT and LINAC log data during lung VMAT delivery. Our result indicate a small but significant dose difference between the 3D and 4D calculations for the case of large target traveling.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-158: Catching Errors with Trajectory Log Files

Purpose: To present our single institution experience on catching errors with trajectory log file analysis. The reported causes of failures, probability of occurrences (O), severity of effects (S), and the probability of the failures to be undetected (D) could be added to guidelines of FMEA analysis. Methods: From March 2013 to March 2014, 19569 patient treatment fields/arcs were analyzed. This work includes checking all 131 treatment delivery parameters for all patients, all treatment sites and all treatment delivery fractions. TrueBeam trajectory log files for all treatment field types as well as all imaging types were accessed, read in every 20ms, and every control point (total of 37 million parameters) compared to the physician approved plan in the planning system. Results: Couch angle outlier occurrence: N= 327, range = −1.7 −1.2 deg; gantry angle outlier occurrence: N =59, range = 0.09 – 5.61 deg, collimator angle outlier occurrence: N = 13, range = −0.2 – 0.2 deg. VMAT cases have slightly larger variations in mechanical parameters. MLC: 3D single control point fields have a maximum deviation of 0.04 mm, 39 step and shoot IMRT cases have MLC −0.3 – 0.5 mm deviations, all (1286) VMAT cases have −0.9 – 0.7 mm deviations. Two possible serious errors were found: 1) A 4 cm isocenter shift for the PA beam of an AP-PA pair, under-dosing a portion of PTV by 25%. 2) Delivery with MLC leaves abutted behind the jaws as opposed to the midline as planned, leading to a under-dosing of a small volume of the PTV by 25%, by just the boost plan. Due to their error origin, neither of these errors could have been detected by pre-treatment verification. Conclusion: Performing Trajectory Log file analysis could catch typically undetected errors to avoid potentially adverse incidents.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-G-BRB-04: Automated Output Factor Measurements Using Continuous Data Logging for Linac Commissioning

Purpose: Linac commissioning is a time consuming and labor intensive process, the streamline of which is highly desirable. In particular, manual measurement of output factors for a variety of field sizes and energy greatly hinders the commissioning efficiency. In this study, automated measurement of output factors was demonstrated as ‘one-click’ using data logging of an electrometer. Methods: Beams to be measured were created in the recording and verifying (R&V) system and configured for continuous delivery. An electrometer with an automatic data logging feature enabled continuous data collection for all fields without human intervention. The electrometer saved data into a spreadsheet every 0.5 seconds. A Matlab program was developed to analyze the excel data to monitor and check the data quality. Results: For each photon energy, output factors were measured for five configurations, including open field and four wedges. Each configuration includes 72 fields sizes, ranging from 4×4 to 20×30 cm{sup 2}. Using automation, it took 50 minutes to complete the measurement of 72 field sizes, in contrast to 80 minutes when using the manual approach. The automation avoided the necessity of redundant Linac status checks between fields as in the manual approach. In fact, the only limiting factor in such automation is Linac overheating. The data collection beams in the R&V system are reusable, and the simplified process is less error-prone. In addition, our Matlab program extracted the output factors faithfully from data logging, and the discrepancy between the automatic and manual measurement is within ±0.3%. For two separate automated measurements 30 days apart, consistency check shows a discrepancy within ±1% for 6MV photon with a 60 degree wedge. Conclusion: Automated output factor measurements can save time by 40% when compared with conventional manual approach. This work laid ground for further improvement for the automation of Linac commissioning.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Design and implementation of I/O performance prediction scheme on HPC systems through large-scale log analysis

Abstract Large-scale high performance computing (HPC) systems typically consist of many thousands of CPUs and storage units used by hundreds to thousands of users simultaneously. Applications from large numbers of users have diverse characteristics, such as varying computation, communication, memory, and I/O intensity. A good understanding of the performance characteristics of each user application is important for job scheduling and resource provisioning. Among these performance characteristics, I/O performance is becoming increasingly important as data sizes rapidly increase and large-scale applications, such as simulation and model training, are widely adopted. However, predicting I/O performance is difficult because I/O systems are shared among all users and involve many layers of software and hardware stack, including the application, network interconnect, operating system, file system, and storage devices. Furthermore, updates to these layers and changes in system management policy can significantly alter the I/O behavior of applications and the entire system. To improve the prediction of the I/O performance on HPC systems, we propose integrating information from several different system logs and developing a regression-based approach to predict the I/O performance. Our proposed scheme can dynamically select the most relevant features from the log entries using various feature selection algorithms and scoring functions, and can automatically select the regression algorithm with the best accuracy for the prediction task. The evaluation results show that our proposed scheme can predict the write performance with up to 90% prediction accuracy and the read performance with up to 99% prediction accuracy using the real logs from the Cori supercomputer system at NERSC.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

On coincident loop transient electromagnetic induction logging

Coincident loop transient induction wireline logging is examined as the borehole analog of the well-known land and airborne time-domain electromagnetic (EM) method. The concept of whole-space late-time apparent resistivity is modified from the half-space version commonly used in land and airborne geophysics and applied to the coincident loop voltages produced from various formation, borehole, and invasion models. Given typical tool diameters, off-time measurements with such an instrument must be made on the order of nanoseconds to microseconds — much more rapidly than for surface methods. Departure curves of the apparent resistivity for thin beds, calculated using an algorithm developed to model the transient response of a loop in a multilayered earth, indicate that the depth of investigation scales with the bed thickness. Modeled resistivity logs are comparable in accuracy and resolution with standard frequency-domain focused induction logs. However, if measurement times are longer than a few microseconds, the thicknesses of conductors can be overestimated, whereas resistors are underestimated. Thin-bed resolution characteristics are explained by visualizing snapshots of the EM fields in the formation, where a conductor traps the electric field while two current maxima are produced in the shoulder beds surrounding a resistor. Radial profiling is studied using a concentric cylinder earth model. Results found that true formation resistivity can be determined in the presence of either oil- or water-based mud, although in the latter case, measurements must be taken several orders of magnitude later in time. Lastly, the ability to determine true formation resistivity is governed by the degree that the EM field heals after being distorted by borehole fluid and invasion, a process visualized and particularly evident in the case of conductive water-based mud.

58 GEOSCIENCES↗