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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Liquid Nitrogen Yule Log

Is the standard 'log burning in fireplace' video just not setting the right atmosphere? Would you rather that the atmosphere be set using the actual atmosphere? If so, you can now relax to the sights and sounds of liquid nitrogen as it merrily boils away atop a 1/2" thick block of room temperature aluminum. No true scientist would dare to delight their guests with anything less! For those who are super into this, an extended cut is available: https://youtu.be/qn1RX12zEp8 Special thanks to freepic.com for the snowflake designs! (Handdrawn Snowflakes II)

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Downhole MCA for High-Resolution Spectral Gamma Logging for Characterization of Radiological Contaminants - 16321

A downhole data system for spectral gamma ray detectors has been developed and deployed in boreholes at the US DOE Hanford Site in southeastern Washington State. This system consists of a digital multichannel analyzer, power supply, and high-voltage power supply located in the borehole probe. Communication up the cable to a computer at the surface is digital, meaning that issues related to analog pulse transmission over the logging cable are eliminated. This system can support either scintillator or solid-state detectors. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

IoT in Radiology: Using Raspberry Pi to Automatically Log Telephone Calls in the Reading Room

The work environment for medical imaging such as distractions, ergonomics, distance, temperature, humidity, and lighting conditions generates a paucity of data and is difficult to analyze. The emergence of Internet of Things (IoT) with decreasing cost of single-board computers like Raspberry Pi makes creating customized hardware to collect data from the clinical environment within the reach of a clinical imaging informaticist. This article will walk the reader through a series of basic project using a variety sensors and devices in conjunction with a Pi to gather data, culminating in a complex example designed to automatically detect and log telephone calls.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Log-Correlated Large-Deviation Statistics Governing Huygens Fronts in Turbulence

Analyses have disagreed on whether the velocity u T of bulk advancement of a Huygens front in turbulence vanishes or remains finite in the limit of vanishing local front propagation speed u 0 . Here, a connection to the large-deviation statistics of log-correlated random processes enables a definitive determination of the correct small- u 0 asymptotics. This result reconciles several theoretical and phenomenological perspectives with the conclusion that u T remains finite for vanishing u 0 , which implies a propagation anomaly akin to the energy-dissipation anomaly in the limit of vanishing viscosity. Various leading-order structural properties such as a novel u 0 dependence of a bulk length scale associated with front geometry are predicted in this limit. As a result, the analysis involves a formal analogy to random advection of diffusive scalars.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
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 OSTI2026

Source-Resolved Inversion of Elemental Carbon Emissions in California Using Log-Space Bayesian Inference

Elemental carbon (EC), operationally quantified by thermal-optical analysis, is widely used as a proxy for black carbon (BC) relevant to short-term climate forcing and public health. Current EC emission inventories remain highly uncertain, with persistent discrepancies between bottom-up and top-down estimates. In this study, we develop a source-resolved, log-space Bayesian inversion framework applied to estimate California’s statewide EC emissions in 2019. By integrating surface EC measurements from the EPA’s Air Quality System network with high-resolution source contributions simulated by a chemical transport model, we identify a one-third underestimation in the existing statewide EC inventory, requiring an increase of the total from a prior of 8.58 [5.49–13.75] Gg year–1 to a posterior estimate of 12.78 [10.71–15.37] Gg year–1. This discrepancy is primarily driven by substantial underestimations in the power and industrial and off-road mobile sectors. Furthermore, population-weighted exposure analysis reveals a marked sectoral divergence between emission mass and health burden: off-road mobile sources dominate both emissions and exposure, accounting for 31% of statewide exposure, while residential wood combustion contributes 26% of total exposure despite comprising only 19% of total emissions, due to its source proximity to population. These findings underscore the need to update sector-specific EC speciation profiles and demonstrate that mitigation strategies targeting off-road mobile sources and residential wood combustion are critical for reducing EC-related health impacts in California.

Zhang, Jie↗
DOE OSTI2024

Radiological Source Term Estimation and Isotopic Identification with Parallel Log Domain Particle Filters

This paper presents a parallel log-domain particle filtering algorithm combined with gamma spectrum unfolding to perform localization, identification, and evaluation of multiple point sources of various isotopes in an environment with attenuating obstacles. The method uses sets of precomputed attenuation kernels that map the attenuation characteristics of the environment. These kernels are specific to the energy level of a photopeak of interest. The spectral measurements are deconvolved into count measurements of each photopeak. These count measurements are fed into a set of parallel particle filters using attenuation kernels computed for that photopeak’s energy level. The individual regularized particle filters perform all likelihood calculations in the logarithmic domain to mitigate the effects of particle degeneracy. The output of each particle filter is combined to estimate which isotopes are present as well as their positions and strengths. The performance of the algorithm is characterized in a lab-scale environment using a mobile robot equipped with a gamma ray spectrometer in the presence of up to three different radioactive isotopes simultaneously. The sources were localized to within 10 cm, and their strengths were estimated within 10% of their true values. Furthermore, the isotopes were all correctly identified, and no spurious sources were reported.

42 ENGINEERING↗
DOE OSTI2021

Geostatistical Mapping of Salinity Conditioned on Borehole Logs, Montebello Oil Field, California

We present a geostatistics-based stochastic salinity estimation framework for the Montebello Oil Field that capitalizes on available total dissolved solids (TDS) data from groundwater samples as well as electrical resistivity (ER) data from borehole logging. Data from TDS samples (n = 4924) was coded into an indicator framework based on falling below four selected thresholds (500, 1000, 3000, and 10,000 mg/L). Collocated TDS-ER data from the surrounding groundwater basin were then employed to produce a kernel density estimator to establish conditional probabilities for ER data (n = 8 boreholes) falling below the selected TDS thresholds within the Montebello Oil Field area. Directional variograms were estimated from these indicator coded data, and 500 TDS realizations from conditional indicator simulation were generated for the subsurface region above the Montebello Oil Field reservoir. Simulations were summarized as 3D maps of median TDS, most likely salinity class, and probability for exceeding each of the specified TDS thresholds. Results suggested TDS was below 500 mg/L in most of the study area, with a trend toward higher values (500 to 1000 mg/L) to the southwest; consistent with the average regional groundwater flow direction. Discrete localized zones of TDS greater than 1000 mg/L were observed, with one of these zones in the greater than 10,000 mg/L range; however, these areas were not prevalent. The probabilistic approach used here is adaptable and is readily modified to include additional data and types and can be employed in time-lapse salinity modeling through Bayesian updating.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Inverse Design of Two-Dimensional Airfoils Using Conditional Generative Models and Surrogate Log-Likelihoods

Abstract This paper shows how to use conditional generative models in two-dimensional (2D) airfoil optimization to probabilistically predict good initialization points within the vicinity of the optima given the input boundary conditions, thus warm starting and accelerating further optimization. We accommodate the possibility of multiple optimal designs corresponding to the same input boundary condition and take this inversion ambiguity into account when designing our prediction framework. To this end, we first employ the conditional formulation of our previous work BézierGAN–Conditional BézierGAN (CBGAN)—as a baseline, then introduce its sibling conditional entropic BézierGAN (CEBGAN), which is based on optimal transport regularized with entropy. Compared with CBGAN, CEBGAN overcomes mode collapse plaguing conventional GANs, improves the average lift-drag (Cl/Cd) efficiency of airfoil predictions from 80.8% of the optimal value to 95.8%, and meanwhile accelerates the training process by 30.7%. Furthermore, we investigate the unique ability of CEBGAN to produce a log-likelihood lower bound that may help select generated samples of higher performance (e.g., aerodynamic performance). In addition, we provide insights into the performance differences between these two models with low-dimensional toy problems and visualizations. These results and the probabilistic formulation of this inverse problem justify the extension of our GAN-based inverse design paradigm to other inverse design problems or broader inverse problems.

Engineering↗
DOE OSTI2016

SU-F-T-233: Evaluation of Treatment Delivery Parameters Using High Resolution ELEKTA Log Files

Purpose: As modern linacs have become more technologically advanced with the implementation of IGRT and IMRT with HDMLCs, a requirement for more elaborate tracking techniques to monitor components’ integrity is paramount. ElektaLog files are generated every 40 milliseconds, which can be analyzed to track subtle changes and provide another aspect of quality assurance. This allows for constant monitoring of fraction consistency in addition to machine reliability. With this in mind, it was the aim of the study to evaluate if ElektaLog files can be utilized for linac consistency QA. Methods: ElektaLogs were reviewed for 16 IMRT patient plans with >16 fractions. Logs were analyzed by creating fluence maps from recorded values of MLC locations, jaw locations, and dose per unit time. Fluence maps were then utilized to calculate a 2D gamma index with a 2%–2mm criteria for each fraction. ElektaLogs were also used to analyze positional errors for MLC leaves and jaws, which were used to compute an overall error for the MLC banks, Y-jaws, and X-jaws by taking the root-meansquare value of the individual recorded errors during treatment. Additionally, beam on time was calculated using the number of ElektaLog file entries within the file. Results: The average 2D gamma for all 16 patient plans was found to be 98.0±2.0%. Recorded gamma index values showed an acceptable correlation between fractions. Average RMS values for MLC leaves and the jaws resulted in a leaf variation of roughly 0.3±0.08 mm and jaw variation of about 0.15±0.04 mm, both of which fall within clinical tolerances. Conclusion: The use of ElektaLog files for day-to-day evaluation of linac integrity and patient QA can be utilized to allow for reliable analysis of system accuracy and performance.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

LLUDA (Low-cost Logging for Ubiquitous Decarbonization and Analysis) [SWR-24-131]

This repository features an Arduino-based GPS logger, called LLUDA, which uses the Adafruit Ultimate GPS FeatherWing with the Adafruit Feather M0 Adalogger, designed to capture and log GPS data in CSV format onto an SD card (embedded inside the Feather M0 Adalogger). The FeatherWing is powered through the vehicle's auxiliary power (from cigarette lighter) socket via a micro USB cable. The data it collects can be used to analyze vehicle operations and support vehicle modeling applications, helping to assess the potential for electrification.

Fakhimi, Setayesh [National Renewable Energy Labor↗
DOE OSTI2018

A Comparative Life-Cycle Assessment of Briquetting Logging Residues and Lumber Manufacturing Coproducts in Western United States

Abstract. Timber harvest activities in the western United States have resulted in large volumes of low- to no-value logging (forest) residues. Alternatives to pile-and-burning are needed to best utilize this material and to mitigate the resultant environmental impacts. Briquetting (densifying) forest residues near-woods is one such option and is the focus of this study. This study presents a cradle-to-grave life-cycle assessment (LCA) performed to evaluate the overall environmental impacts associated with briquetting post-harvest forest residues and dry sawmill residues (sawdust) in the Pacific Northwest (PNW) region of the United States. Environmental impacts resulting from the two briquette production systems were compared with firewood and propane production, which are common residential heating sources in rural areas of the PNW, on a per 1 MJ of useful energy for domestic heating. In the briquetted post-harvest forest residue system, the feedstock preparation stage had the largest share in global warming (GW) impact, mainly resulting from the drying process (69.5%), followed by transportation. Valorization of post-harvest forest residues, in combination with a briquetter, to produce a bioenergy carrier was revealed to be advantageous in smog, acidification, and eutrophication impact categories, with considerable environmental benefits from avoided pile-and-burn emissions. With all scenarios investigated, briquette production from post-harvest forest residues with high dryer efficiency showed lowest GW impact compared to briquetting sawmill residues and firewood supply chain. For a scenario analysis, LCA showed that using a diesel generator to support the forest residue briquetter operation resulted in 45% higher GW impact compared to use of a wood-gas-powered generator. Keywords: Bioenergy, Biomass densification, Briquette, Forest residues, Life-cycle assessment, Sawdust.

Agriculture↗
DOE OSTI2021

TEAMER - AquaHarmonics High Fidelity WEC Sim PTO and Control Model Validation, Test Logs and Results

Collaborative effort between AquaHarmonics, Sandia National Laboratories (SNL), and the National Renewable Energy Laboratory (NREL) to revise and validate Aquaharmonics' full wave to wire model, allowing for reduced uncertainty and increased understanding of design requirements of a utility scale wave energy converter (WEC). SNL and NREL in collaboration with AquaHarmonics, will set up and run WEC Simulator (WEC-Sim) models of the AquaHarmonics WEC, building off past model developments for inclusion of custom PTO (power take-off) dynamics. The intent is to review, update, and verify or validate a new WEC-Sim model against wave tank experimental data. Furthermore, the WEC-Sim model will be coupled to an energy storage system model to better understand the wave-to-wire functionality. This data set is described in the "Test Log" excel file. Please refer to that document for details on each specific test date/time, constraint parameters and model hardware setup details. Sim model can be found in the associated MHKDR link below.

16 TIDAL AND WAVE POWER↗
DOE OSTI2026

Drone Flight Data Logs

This dataset represents the open-air tests for the drones when testing different flight scenarios. For some flights we created and tested with a set of onboard sensors. For others we used the native logs for the drones. We recorded relevant conditions for each of the flights to examine environmental issues and weight impacts. We also looked at segmentations of flights to investigate the energy used in each type of flight.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Electricity Baseline 2022 Background Data and Log File

The ElectricityLCI v2 Python package (https://github.com/USEPA/ElectricityLCI/tree/v2.0) was used to generate the 2022 electricity baseline: a regionalized life cycle inventory model of U.S. electricity generation, consumption, and distribution using standardized facility and generation data. ElectricityLCI implements a local data store for downloading and accessing public data on an individual's computer. The data store follows the folder definition provided by USEPA's esupy Python package (https://github.com/USEPA/esupy), which utilized the appdirs Python dependency (https://pypi.org/project/appdirs/). This submission includes the background data used to generate the 2022 electricity baseline inventory. Each zip archive stores the source files as found in their data stores. Sub-folders in each of the data stores are archived separately. For example, stewi.zip contains the JSON files, while stewi.facility.zip is the 'facility' sub-folder of stewi data store that stores the parquet files. To reproduce the data store, extract each zip file and drag-and-drop sub-folders in to their appropriate root folders to recreate the data stores, then copy the root folders to your data store folder (as returned by running the following on the command line: `python -c "import appdirs; print(appdirs.user_data_dir())"`). The main five data stores include: 'electricitylci', 'facilitymatcher', 'fedelemflowlist', 'stewi', and 'stewicombo'. The log file generated by the 2022 model run is also included, which contains the statements at the DEBUG level and above.

Electricity; LCA; data inventory↗
DOE OSTI2025

Electricity Baseline 2021 Background Data and Log File

The ElectricityLCI v2 Python package (https://github.com/USEPA/ElectricityLCI/tree/v2.0) was used to generate the 2021 electricity baseline: a regionalized life cycle inventory model of U.S. electricity generation, consumption, and distribution using standardized facility and generation data. ElectricityLCI implements a local data store for downloading and accessing public data on an individual's computer. The data store follows the folder definition provided by USEPA's esupy Python package (https://github.com/USEPA/esupy), which utilizes the appdirs Python dependency (https://pypi.org/project/appdirs/). An overview of the ElectricityLCI data stores may be found on the README (https://github.com/USEPA/ElectricityLCI/blob/v2.0/README.md#data-store). This submission includes the background data used to generate the 2021 electricity baseline inventory. Each zip archive stores the source files as found in their data stores. Sub-folders in each of the data stores are archived separately. For example, stewi.zip contains the JSON files, while stewi.facility.zip is the 'facility' sub-folder of stewi data store that stores the parquet files. To reproduce the data store, extract each zip file and drag-and-drop sub-folders in to their appropriate root folders to recreate the data stores, then copy the root folders to your data store folder (as returned by running the following on the command line: python -c "import appdirs; print(appdirs.user_data_dir())"). The main five data stores include: 'electricitylci', 'facilitymatcher', 'fedelemflowlist', 'stewi', and 'stewicombo'. The log file generated by the 2021 model run is also included, which contains the statements at the DEBUG level and above.

Electricity; LCA; LCI; Life Cycle; data inventory↗
DOE OSTI2025

Electricity Baseline 2020 Background Data and Log File

The ElectricityLCI v2 Python package (https://github.com/USEPA/ElectricityLCI/tree/v2.0) was used to generate the 2020 electricity baseline: a regionalized life cycle inventory model of U.S. electricity generation, consumption, and distribution using standardized facility and generation data. ElectricityLCI implements a local data store for downloading and accessing public data on an individual's computer. The data store follows the folder definition provided by USEPA's esupy Python package (https://github.com/USEPA/esupy), which utilizes the appdirs Python dependency (https://pypi.org/project/appdirs/). An overview of the ElectricityLCI data stores may be found on the README (https://github.com/USEPA/ElectricityLCI/blob/v2.0/README.md#data-store). This submission includes the background data used to generate the 2020 electricity baseline inventory. Each zip archive stores the source files as found in their data stores. Sub-folders in each of the data stores are archived separately. For example, stewi.zip contains the JSON files, while stewi.facility.zip is the 'facility' sub-folder of stewi data store that stores the parquet files. To reproduce the data store, extract each zip file and drag-and-drop sub-folders in to their appropriate root folders to recreate the data stores, then copy the root folders to your data store folder (as returned by running the following on the command line: python -c "import appdirs; print(appdirs.user_data_dir())"). The main five data stores include: 'electricitylci', 'facilitymatcher', 'fedelemflowlist', 'stewi', and 'stewicombo'. The log file generated by the 2020 model run is also included, which contains the statements at the DEBUG level and above.

Electricity; LCA; LCI; Life Cycle; data inventory↗
DOE OSTI2022

Novel Proppant Logging Technique for Infill Drilling of Unconventional Shale Wells

Summary During the development of an unconventional play, wells are drilled and completed in batches, and depending on the development plans, current and expected energy market trends, as well as other developmental considerations, new wells are drilled and hydraulically fractured later near existing producing laterals. This creates challenges in terms of optimizing resource recovery and reducing interwell communication. A novel approach is proposed that utilizes systematic composite sampling and analysis of drilling mud returns to look for and quantitatively identify sand particles. The workflow involves cleaning, drying, and segregation of samples into sizes of interest to us (size distribution of pumped proppant in offset parent wells). These samples are imaged at a very high resolution and analyzed for grains using characteristic optical imaging properties to classify proppant sand particles using computer vision algorithms. Further analysis, such as elemental compositional analysis, is used to validate the results from the imaging workflow. We present a case study from the Permian Basin, where a new child well was used as a test case to prove this technology at the Hydraulic Fracturing Test Site (HFTS-2) in Delaware Basin. We introduce new proppant parameters that help identify sustained proppant zones vs. localized propped fractures. We have used additional diagnostics and data collected at the test site to validate observations from the proppant log and have successfully interpreted significantly propped vs. unpropped zones. A key finding from this test has been the significant proppant transport distances observed away from parent wells. Observable proppant was found at a lateral distance of approximately 425 m for one set of parent wells and more than 915 m for another set of parent wells. While a major limitation of this technique is the sampling rate, given adequate sampling, the proposed technology represents a systematic and one-of-a-kind interpretation of spatial proppant distribution while drilling infill wells. It provides us with unique opportunities to better understand the current state of the reservoir being targeted, including zones that are likely highly drained relative to others, and how the planned hydraulic fracturing of child wells can be improved.

Energy & Fuels↗