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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Quantifying Methane Leak Emissions by Fused Airborne Imaging Spectroscopy with in Situ Surface Mobile and Airborne Observations of a California Producing Oil Field

Methane (CH4) emission budgets remain uncertain and are projected to grow as oil and gas production from short-lived wells increases and their subsequent transport through aging gas distribution networks. Orders-of-magnitude variations in temporal, spatial, and emission scales present a key challenge to leak detection and quantification. Also, the probability distributions for large and stochastic, leaky systems such as geological reservoirs (by natural migration-seeps) and petroleum production from those reservoirs remain largely unknown, needed to address current approach limitations. The scale of many petroleum systems favors remote sensing, but the sensitivity of such systems often precludes detection of weak emissions. Consequently, an accurate evaluation requires that the relative contribution from the emission "tails" of small leaks also be quantified, which is best carried out using high-sensitivity in situ methods. Fusion of remote sensing and in situ approaches leverages complementary capabilities to address these limitations. We show results from mobile surface (AMOG) and airborne in situ (AJAX) and thermal-infrared (TIR) hyperspectral imaging spectroscopy (Mako) data applied to a producing oil field in the California Central Valley near Bakersfield. AMOG is an automobile-based mobile lab that measures 13 trace gases, aerosol size distributions and vertical profiles, 3D winds and other meteorology, and atmospheric column measurements by solar spectroscopy at highway speeds. AJAX measures 5 trace gases and 3D winds at ~140 m/s. Mako is a broad-area TIR imaging spectrometer that can discriminate multiple gases present in each pixel acquired. In situ-derived, total field emissions were 31±16 Gg/yr CH4. This was compared with Mako-derived emissions from all plumes identified across the study site. We found that super-emitters were not the dominant emissions mode and the spatial pattern of plume locations from production infrastructure was correlated to geological structures.

Leifer, Ira↗
DOE OSTI2025

Accurate and Fast Anomaly Detection in Additive Composite-Based Manufacturing using Thermal Cameras

Today, large-scale additive manufacturing with plastics and composite materials requires continuous monitoring by experienced staff to prevent, detect and correct anomalous events affecting the performance of the printed part. We address the complexity of this demanding task by designing a camera-based anomaly detection system utilizing probabilistic principal component analysis (PPCA). This is a machine learning technique is trained with thermal images collected during normal operation of the large-scale printer (Cincinnati BAAM). This technique is advantageous for practical applications as there is no need to artificially introduce anomalous conditions into model training. During deployment, we challenge this model by introducing deliberate variations of the extruder speed. We reduce extrusion speed to a lower level, between 70 and 95% of the nominal value to collected test images. Our results show that images are easily identified as anomalous for extruder speeds at or below 85% of the nominal speed, meaning that an anomalous reduction of the material deposition rate can be detected within seconds of its onset. We show that our results are robust to (a) camera-to-camera variability and (b) print-to-print variability.

Pike, John [ORNL]↗
NASA NTRS1993

An optical processor for zero-crossing edge detection

An optical processor for zero-crossing edge detection is presented, which consists of two defocused imaging systems to perform the Gaussian convolutions and a VLSI, ferroelectric liquid crystal spatial light modulator (SLM) to determine the zero-crossings. The zero-crossing SLM is a 32 x 32 array of pixels located on 100 microns centers. Each pixels contains a phototransistor, an auto-scaling amplifier, a zero-crossing detection circuit, and a liquid crystal modulating pad. Electrical and optical characteristics of the zero-crossing SLM are presented along with experimental results of the system.

Jared, David A.↗
NASA NTRS1982

Vertical flows of supergranular and mesogranular scale observed on the sun with OSO 8

A program of observations was carried out in order to study the penetration of supergranular flows over a broad range of heights in the solar atmosphere. Steady Doppler velocities are determined from observations of a Si II spectral line using the Ultraviolet Spectrometer on the Orbiting Solar Observatory 8 (OSO 8) satellite and Fe I and Mg I lines with the diode-array instrument on the vacuum telescope at Sacramento Peak Observatory (SPO). The heights of formation of these spectral lines span about 1400 km or nearly 11 density scale heights from the photosphere to the middle chromosphere. Steady vertical flows on spatial scales typical of supergranulation and mesogranulation have been detected in the middle chromosphere with OSO 8. The patterns of intensity and steady velocity of granular scale are reproducible in successive data sets. The patterns appear to evolve slowly over the 9 hr period spanned by six orbits.

November, L. J.↗
DOE OSTI2014

Molecular-scale investigations of structures and surface charge distribution of surfactant aggregates by three-dimensional force mapping

Surface charges on nanoscale structures in liquids, such as biomolecules and nano-micelles, play an essentially important role in their structural stability as well as their chemical activities. These structures interact with each other through electric double layers (EDLs) formed by the counter ions in electrolyte solution. Although static-mode atomic force microscopy (AFM) including colloidal-probe AFM is a powerful technique for surface charge density measurements and EDL analysis on a submicron scale in liquids, precise surface charge density analysis with single-nanometer resolution has not been made because of its limitation of the resolution and the detection sensitivity. Here we demonstrate molecular-scale surface charge measurements of self-assembled micellar structures, molecular hemicylinders of sodium dodecyl sulfate (SDS), by three-dimensional (3D) force mapping based on frequency modulation AFM. The SDS hemicylindrical structures with a diameter of 4.8 nm on a graphite surface were clearly imaged. We have succeeded in visualizing 3D EDL forces on the SDS hemicylinder surfaces and obtaining the molecular-scale charge density for the first time. The results showed that the surface charge on the trench regions between the hemicylinders was much smaller than that on the hemicylinder tops. The method can be applied to a wide variety of local charge distribution studies, such as spatial charge variation on a single protein molecule.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A deep learning model for automatic analysis of cavities in irradiated materials

Transmission electron microscopy (TEM) is a commonly used technique in materials science for defect investigation. Quantitative analysis of defects is important for understanding the properties of a material, but manual analysis of TEM micrographs can be time-consuming and prone to error, especially when the defects have irregular shapes rather than spherical shapes. Many existing methods or deep learning models do not handle a wide range of sizes for the same object type within a single image. In this work, we present a framework that enables users to train an instance segmentation model called Mask R- CNN on any microstructure dataset, perform multi-detection on the same image at different scales, and obtain properties (e.g., size, area) of the objects based on the desired shape (e.g., circle, ellipse, rectangle). Additionally, we have developed a parallel detection module that uses multiple GPUs to increase the efficiency of the object detection process. We demonstrate the capabilities of our framework using a set of TEM images of cavities with different shapes, size distributions, and background contrasts. Finally, we show that the performance of our model in terms of density, size, and swelling of the cavities is comparable to the human average and that our model achieves the highest recall value compared to existing methods due to the use of image multi-rescaling.

36 MATERIALS SCIENCE↗
DOE OSTI2021

New Laboratory and Astrophysical Probes of Physics Beyond the Standard Model (Final Technical Report)

The first of these directions centers on new ideas in dark matter detection. As experimental scrutiny narrows the window for new physics at the weak scale, it has become apparent that the solution to the dark matter mystery may not reside there. Theoretical developments such as the hidden sector/valley paradigm have, at the same time, shown that compelling theories of dark matter reside below the weak scale. Searching for dark matter at lower mass scales requires looking beyond the current paradigm of dark matter direct detection based on nuclear recoils. It is the goal of this project to provide new ideas to guide the experimental program looking for light dark matter. I am actively proposing ideas for detecting dark matter as light as a meV, well beyond the current focus of GeV-TeV scale dark matter. Some of the ideas I have proposed, such as superconducting, superfluid, and polar material targets, are actively being developed into experiments. My group will provide the relevant calculations to determine dark matter reach, providing crucial input to experiment on which targets should be developed. We will also provide an effective field theory framework to understand which types of experiments are most sensitive to each interaction type. The second of these directions is on probes of dark matter substructure as a mean to constrain, or observe, models of dark matter. The standard ΛCDM paradigm assumes that the dark matter density perturbations are adiabatic, scale invariant, and produced during inflation. However, many standard models of dark matter will produce modifications of this prediction, such as axion models with symmetry broken below the inflationary scale. Remarkably, we have limited direct measurements of the dark matter clumpiness at mass scales below dwarf galaxies. This allows for the possibility of observing modifications from vanilla ΛCDM due to particle dynamics. In many cases, simulations of dark matter structure in the presence of non-scale invariant fluctu- ations are understudied or completely lacking. I plan to develop both theoretical predictions for small scale structure in models with additional matter power on small scales, as well as observa- tional probes of small scale halos or clumps. One idea I have been recently focused on is pulsar timing, though my group will pursue a variety of lensing and astrometric probes. Lastly, the most risky direction involves spacetime fluctuations from quantum gravity. I showed that if one assumes that metric fluctuations in the Minkowski vacuum, at a surface separating a region in and out of causal contact (which we call a “horizon”), are determined by standard thermodynamic considerations at horizon, these metric fluctuations are large enough to observe in an interferometer with similar sensitivity to LIGO. In a follow-up paper we showed that these assumption holds for the vacuum in AdS/CFT. In future work, I plan to connect this work to recent soft graviton results, to frame this work in a concrete Randall-Sundrum model, and to work out concrete phenomenological predictions from the model. This work unquestionably takes a less trodden path, and works well as part of a well-rounded portfolio of less and more risky ideas. Particle physics is currently at a juncture which requires bold exploration of qualitatively new directions. This proposal outlines some of my plans over the coming years in these directions, leaving room also for surprises.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2003

WMAP Detection of Early Reionization

The Wilkinson Microwave Anisotropy Probe (WMAP) has mapped the full sky in Stokes I, Q, and U parameters at frequencies 23, 33, 41, 61, and 94 GHz. We detect correlations between the temperature and polarization maps significant at more than 10 standard deviations. The correlations are inconsistent with instrument noise and are significantly larger than the upper limits established for potential systenatic errors. The correlations are present in all WMAP frequency bands with similar amplitude from 23 to 94 GHz, and are consistent with a superposition of a CMB signal with a weak foreground. The fitted CMB component is robust against different data combinations and fitting techniques. On small angular scales the WMAP data show the temperature-polarization correlation expected from adiabatic density perturbations. The data for $\ell > 20$ agree well with the signal predicted solely from the temperature power spectra, with no additional free parameters. The existence of correlations on super-horizon scales provides significant support for inflationary cosmologies. We detect excess power on large angular scales compared to predictions based on the temperature power spectra alone. The excess power is well described by reionization at redshift $11 < z < 30$ at 95\% confidence. A model-independent fit to reionization optical depth yields results consistent with the best-fit $\Lambda$CDM model, with best fit value $\tau = 0.17 \pm 0.04$ at 68\% confidence, including systematic and foreground uncertainties. This value is larger than expected given the detection of a Gunn-Peterson trough in the absorption spectra of distant quasars, and implies that the universe has a complex ionization history. I will discuss the WMAP data and its implications for reionization in the early universe.

Kogut, A.↗
NASA NTRS1979

Aether drift and the isotropy of the universe: a measurement of anisotropies in the primordial black-body radiation

This experiment detected and mapped large-angular-scale anisotropies in the 3 K primordial black-body radiation with a sensitivity of 2x.0001k and an angular resolution of about 10 degs. It measured the motion of the Earth with respect to the distant matter of the Universe (Aether Drift), and probed the homogeneity and isotropy of the Universe (the Cosmological Principle). The experiment used two Dicke radiometers, one at 33 GHz to detect the cosmic anisotropy, and one at 54 GHz to detect anisotropies in the residual oxygen above the detectors. The system was installed in the NASA-Ames Earth Survey Aircraft (U-2), and operated successfully in a series of flights.

Muller, R. A.↗
DOE OSTI2024

Continuous thermostat setpoint monitoring and correction (Thermostat setpoint correction) v1.0

The Continuous Thermostat Setpoint Monitoring and Correction software is a set of fault detection and correction algorithms that can be implemented in thermostats with two-way OpenAPIs. It is written in the Python language. The algorithms aim to detect the most common and impactful efficiency problems associated with thermostat setpoints - overly aggressive heating or cooling setpoints, incorrect schedules/setbacks, and overly narrow deadbands. These algorithms can automatically detect faults, and implement associated corrective actions to bring the system back to a state of efficient operation. The algorithms can run remotely in the cloud, and directly implemented by connected thermostat manufacturers, or by third party service providers. The software enables a lightweight cost-effective energy management strategy for HVAC systems. The solution is specially viable for small and medium sized commercial buildings, where a full scale building automation system and fault detection and diagnostic tools are often unavailable.

Granderson, Jessica↗
DOE OSTI2025

Different methods of estimating riverbed sediment grain size diverge at the basin scale

Introduction: The distribution of sediment grain size in streams and rivers is often quantified by the median grain size (D50), a key metric for understanding and predicting hydrologic and biogeochemical function of streams and rivers. Manual D50 measurements are time-consuming and ignore larger grains, while approaches to model D50 based on catchment characteristics may over-generalize and miss site-scale heterogeneity. Machine learning-enabled object detection methods like You Only Look Once (YOLO) provides an alternative that enables estimation of D50 that is faster than manual measurements and more site-specific than predictions based on catchment characteristics. Methods: To understand the potential role of object detection methods for improving understanding of D50, we compared D50 estimates made manually, predicted from catchment characteristics, and using a YOLO-enabled approach across the Yakima River Basin. Results: We found distinct differences between methods for D50 averages and variability, and relationships between D50 estimates and basin characteristics. Discussion: We discuss the advantages and limitations of object detection methods versus current methods, and explore potential future directions to combine D50 methods to better estimate spatiotemporal variation of D50, and improve incorporation into basin-scale models.

grain size distribution↗
DOE OSTI2022

Integrated Pest Management (IPM) for Early Detection Algal Crop Protection. Final Report

During large-scale, outdoor algal biomass growth, production strain(s) are subject to attack by pathogens, predators, and non-productive competitors, compromising the biomass yield. The project team at UCSD developed and demonstrated the effectiveness of Volatile Organic Compound, VOC, analysis via mass spectrometry (MS) as an early detection system for the presence of production algal ponds infection. The MS detection can then trigger high-resolution melt analysis (HRMA) and enhanced quantitative PCR (qPCR) to identify predatory or pathogenic species precisely. This study gathered the foundational data informing how wholly automated systems monitor the health of production ponds. By detecting the presence of low molecular weight VOCs in the air space above ponds, the instrument was able to mimic “sniffing” the health of the algae pond. This early warning system will be free growers from time-consuming and costly regular surveillance of ponds with the current techniques, such as qPCR and flow-cam assays, which are slower, less sensitive, and not easily fully automated, resulting in increased production efficiency through the reduction of crop loss. This project demonstrated that Chemical Ionization Mass Spectrometry, CIMS, could serve as a real-time monitor of ponds health tracking up to 100 different VOCs simultaneously for continuous periods up to 60 days without interruption, signaling infection within an algal crop 24 to 36 hours prior to techniques such as qPCR and microscopy. While mass spectrometry is an expensive tool, this simple VOC sampling system proved not only to be sensitive and robust but could to multiplexed to monitor several ponds, lowering the overall cost serially. This technology demonstrated a reduction in biomass production cost by approximately 50% compared to growers not employing any detection methodology.

09 BIOMASS FUELS↗
NASA NTRS2022

ALMA Observations of Molecular Complexity in the Large Magellanic Cloud: The N105 Star-Forming Region

The Large Magellanic Cloud (LMC) is the nearest laboratory for detailed studies on the formation and survival of complex organic molecules (COMs), including biologically important ones, in lowmetallicity environments—typical for earlier cosmological epochs. We report the results of 1.2 mm continuum and molecular line observations of three fields in the star-forming region N105 with the Atacama Large Millimeter/submillimeter Array (ALMA). N105 lies at the western edge of the LMC bar with on-going star formation traced by H2O, OH, and CH3OH masers, ultracompact Hii regions, and young stellar objects. Based on the spectral line modeling, we estimated rotational temperatures, column densities, and fractional molecular abundances for twelve 1.2 mm continuum sources. We identified sources with a range of chemical make-ups, including two bona fide hot cores and four hot core candidates. The CH3OH emission is widespread and associated with all the continuum sources. COMs CH3CN and CH3OCH3 are detected toward two hot cores in N105 together with smaller molecules typically found in Galactic hot cores (e.g., SO2, SO, and HNCO) with the molecular abundances roughly scaling with metallicity. We report a tentative detection of the astrobiologically relevant formamide molecule (NH2CHO) toward one of the hot cores; if confirmed, this would be the first detection of NH2CHO in an extragalactic sub-solar metallicity environment. We suggest that metallicity inhomogeneities resulting from the tidal interactions between the LMC and the Small Magellanic Cloud (SMC) might have led to the observed large variations in COM abundances in LMC hot cores.

Marta Sewilo↗
DOE OSTI2022

Cross-scale sensing of field-level crop residue cover: Integrating field photos, airborne hyperspectral imaging, and satellite data

Conservation tillage practices can bring benefits to agricultural sustainability. Accurate spatial and temporal resolved information of field-scale crop residue cover, which reflects tillage intensity, is highly valuable for evaluating the outcomes of government conservation programs and voluntary ecosystem service markets, as well as facilitating agroecosystem modeling to quantify cropland biogeochemical processes. Remote sensing has the potential to cost-effectively detect crop residue cover, however, existing regional-scale studies were limited by insufficient ground truth data, scale mismatch between coarse satellite pixels and ground data, and the lack of key spectral data for detecting crop residues. Therefore, this study developed an innovative cross-sensing framework to integrate proximal sensing, airborne hyperspectral imaging, and satellite Earth Observation through deep learning to quantify field-level crop residue cover fractions at the regional scale. Specifically, we have collected intensive ground orthographic photos and conducted airborne hyperspectral surveys at corn and soybean fields of Champaign and nearby counties in Illinois, the heartland of the U.S. Corn Belt. Through semi-automatic labeling aided by ResNet-50 and superpixel image segmentation, we obtained 6719 records of ground residue fractions. With these ground data, we developed the 1-dimensional convolution neural network (CNN) model using airborne hyperspectral reflectance, which has 0.5m spatial resolution and 3–5 nm spectral resolution from 400 to 2400 nm, to predict residue fractions. By applying the CNN model to airborne pixels, we augmented “ground truth” data of crop residues and further combined them with Harmonized Landsat and Sentinel-2 (HLS) satellite data to quantify regional residue fractions at 30 m resolution. Results show that airborne hyperspectral imagery with CNN can accurately detect residue fractions (R 2 = 0.82, relative RMSE = 11.73%) to effectively generate quasi “ground truth” data to support satellite upscaling to all fields. With independent ground data for testing, we found that the ground-airborne-satellite integrative framework achieved better predictions in estimating crop residue cover (R 2 = 0.67, relative RMSE = 17.53%) than the conventional ground-satellite upscaling (R 2 = 0.22, relative RMSE = 32.09%). Here we also found that the shortwave infrared wavelengths, particularly 2100–2300 nm, are vital for predicting crop residue cover. Sentinel-2 and Landsat-8 data have a comparable capability to track residue fractions due to similar shortwave infrared wavelengths. This study highlights the high accuracy of hyperspectral imaging to detect agroecosystem tillage management practices and the advantages of cross-scale sensing to cost-effectively integrate multi-source data to quantify field-level agroecosystem variables across scales.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Simulating the X-ARAPUCA, DUNE&#x27;s next generation light sensors

The word arapuca refers to a bird trap built by the indigenous peoples of Brazil. On the other hand, our ARAPUCA is a photon trap for Noble Gases' scintillation light and it is the sensitive element upon which DUNE's whole photon detection system is based on. Here we present a glimpse of our state-of-the-art simulation of such device, the ArapucaSim, highlighting its philosophy and main components. As an application, we present here one of the studies being carried out, on the effects of light reflections inside the light guide and how affects the overall photon detection efficiency. Based on these results, we are able to not only acquire a better understanding of the device but also impose limits on the quality of the mechanical polishing of such surfaces. The ArapucaSim was developed with two main goals in mind: to assist in R&D by allowing short turnout times between new ideas and experimental tests, and to bridge the gap between high-precision time-consuming hardware simulations and the full-scale models for DUNE's Photon Detection System. This research also led to the development new algorithms for simulating wavelength shifting/scintillation processes and dichroic filters, which will be properly described in future publications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2004

Fire Detection Organizing Questions

Verified models of fire precursor transport in low and partial gravity: a. Development of models for large-scale transport in reduced gravity. b. Validated CFD simulations of transport of fire precursors. c. Evaluation of the effect of scale on transport and reduced gravity fires. Advanced fire detection system for gaseous and particulate pre-fire and fire signaturesa: a. Quantification of pre-fire pyrolysis products in microgravity. b. Suite of gas and particulate sensors. c. Reduced gravity evaluation of candidate detector technologies. d. Reduced gravity verification of advanced fire detection system. e. Validated database of fire and pre-fire signatures in low and partial gravity.

Source record↗
NASA NTRS2003

WMAP Detection of Early Reionization

The Wilkinson Microwave Anisotropy Probe (WMAP) has mapped the full sky in Stokes I, Q, and U parameters at frequencies 23, 33, 41, 61, and 94 GHz. We detect correlations between the temperature and polarization maps significant at more than 10 standard deviations. The correlations are inconsistent with instrument noise and are significantly larger than the upper limits established for potential systematic errors. The correlations are present in all WMAP frequency bands with similar amplitude from 23 to 94 GHz, and are consistent with a superposition of a CMB signal with a weak foreground. The fitted CMB component is robust against different data combinations and fitting techniques. On small angular scales the WMAP data show the temperature-polarization correlation expected from adiabatic density perturbations. The data for $\ell > 20$ agree well with the signal predicted solely from the temperature power spectra, with no additional free parameters. The existence of correlations on super-horizon scales provides significant support for inflationary cosmologies. We detect excess power on large angular scales compared to predictions based on the temperature power spectra alone. The excess power is well described by reionization at redshift $11 < z < 30$ at 95\% confidence. A model-independent fit to reionization optical depth yields results consistent with the best-fit $\Lambda$CDM model, with best fit value $\tau = 0.17 \pm 0.04$ at 68\% confidence, including systematic and foreground uncertainties. This trough in the absorption spectra of distant quasars, and implies that the universe has a complex ionization history. I will discuss the WMAP data and its implications for reionization in the early universe.

Kogut, A.↗