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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

TOLERANCES OF CRAB DISPERSION AT THE INTERACTION POINT IN THE HADRON STORAGE RING OF THE ELECTRON-ION COLLIDER

The Electron Ion Collider (EIC) presently under construction at Brookhaven National Laboratory will collide polarized high energy electron beams with hadron beams with luminosities up to 10^34 cm^?2 s^?1 in the center mass energy range of 20-140 GeV. Due to the detector solenoid in the interaction region, the design horizontal crabbing angle will be coupled to the vertical plane if uncompensated. In this article, we study the tolerances of crab dispersion at the interaction point in the EIC Hadron Storage Ring (HSR). Both strong-strong and weak-strong simulations are used. We found that there is a tight tolerance of vertical crabbing angle at the interaction point in the HSR.

Luo, Y.↗
DOE OSTI2023

Interpretation of Fracture Initiation Points by In-Well Low-Frequency Distributed Acoustic Sensing in Horizontal Wells

Summary Low-frequency distributed acoustic sensing (LF-DAS) exploits the optical phase shift of Rayleigh backscatter in fiber-optic cables to obtain distributed measurements of changes in strain and temperature. Fiber-optic cables are often installed for multistage hydraulic fracture diagnostics in horizontal wells. LF-DAS in an untreated well provides far-field strain measurements, while offset wells are hydraulically fractured. Such a configuration is called crosswell LF-DAS sensing. Crosswell LF-DAS measurements have proved useful in diagnosing fracture hits, fracture azimuth, planarity, cluster efficiency, fracture propagation rates, and the dynamic distance to the fracture front. In contrast, in-well LF-DAS is conducted on the actively fractured well. Due to cool fracture fluid being injected at high injection rates, the strain component of the LF-DAS response is largely obscured by temperature changes. In permanent fiber-optic cable installations, distributed temperature sensing (DTS) is often conducted simultaneously with LF-DAS. An opportunity exists to decouple the temperature and strain components of LF-DAS sensors to observe strain changes on in-well LF-DAS. The LF-DAS response is modeled as linearly dependent on strain and temperature changes. Theoretical LF-DAS temperature and strain sensitivity coefficients are derived based on the changes to the index of refraction and length of the fiber. Using the DTS measurements, temperature changes are computed, smoothed, filtered, and compared to the LF-DAS response. Crossplots of the in-well LF-DAS measurements and temperature changes from DTS measurements far from the actively fractured region are used to validate the theoretical sensitivity coefficients. Uncertainty in the temperature component of the LF-DAS response is quantified. The difficulty in corresponding the different spatial and temporal resolutions of the DTS and LF-DAS measurements is overcome by comparing the responses over a moving temporal and spatial window. If the LF-DAS response at the center of the window agrees with the DTS response within uncertainty, the measurement is filtered out. After filtering, the remaining nonzero in-well LF-DAS measurements are due to changes in strain. The data are then visualized in waterfall plots. The results indicate that the theoretical and observed strain and temperature coefficients agree within 10%. After the temperature component of the in-well LF-DAS response is extracted, the remaining nonzero measurements are located primarily within the actively treated region. Locations with peaks in the strain response are interpreted to indicate fracture initiation points. These fracture initiation points are compared with in-well DTS and high-frequency DAS noise measurements across multiple stages to better understand fracture initiation along the horizontal well.

Engineering↗
DOE OSTI2023

Literature Review and Experimental Observations of the Effects of Salinity, Hardness, Lithology, and ATBS Content on HPAM Polymer Retention for the Milne Point Polymer Flood

Summary At the Milne Point polymer flood (North Slope of Alaska), polymer retention is dominated by the clay, illite. Illite, and kaolinite cause no delay in polymer propagation in Milne Point core material, but they reduce the effective polymer concentration and viscosity by a significant amount (e.g., 30%), thus reducing the efficiency of oil displacement until the full injected polymer concentration is regained [which requires several pore volumes (PVs) of throughput]. This work demonstrates that polymer retention on illite is not sensitive to monovalent ion concentration, but it increases significantly with increased divalent cation concentration. The incorporation of a small percentage of acrylamido tertiary butyl sulfonic acid (ATBS) monomers into hydrolyzed polyacrylamide (HPAM) polymers is shown to dramatically reduce retention. The results are discussed in context with previous literature reports. Bridging adsorption was proposed as a viable mechanism to explain our results. Interestingly, an extensive literature review reveals that polymer retention (on sands and sandstones) is typically only modestly sensitive to the presence of oil. Extensive examination of the literature on inaccessible pore volume (IAPV) suggests the parameter was commonly substantially overestimated, especially in rock/sand more permeable than 500 md (which comprises the vast majority of existing field polymer floods).

Engineering↗
DOE OSTI2023

EPiC-GAN: Equivariant point cloud generation for particle jets

With the vast data-collecting capabilities of current and future high-energy collider experiments, there is an increasing demand for computationally efficient simulations. Generative machine learning models enable fast event generation, yet so far these approaches are largely constrained to fixed data structures and rigid detector geometries. In this paper, we introduce EPiC-GAN - equivariant point cloud generative adversarial network - which can produce point clouds of variable multiplicity. This flexible framework is based on deep sets and is well suited for simulating sprays of particles called jets. The generator and discriminator utilize multiple EPiC layers with an interpretable global latent vector. Crucially, the EPiC layers do not rely on pairwise information sharing between particles, which leads to a significant speed-up over graph- and transformer-based approaches with more complex relation diagrams. We demonstrate that EPiC-GAN scales well to large particle multiplicities and achieves high generation fidelity on benchmark jet generation tasks.

Buhmann, Erik↗
DOE OSTI2020

2019 Results for Avian Monitoring at the Technical Area 36 Minie Site, Technical Area 39 Point 6, and Technical Area 16 Burn Ground at the Los Alamos National Laboratory

Los Alamos National Laboratory biologists in the Environmental Compliance and Protection Division at Los Alamos National Laboratory (LANL) initiated a multi-year program in 2013 to monitor avifauna (birds) at two open detonation sites and one open burn site on LANL property. Monitoring results from these efforts were compared among years to monitor trends. The objectives of this study were to 1) determine whether LANL operations impact bird species richness, diversity, or abundance 2) evaluate trends in species abundance by feeding guild, and 3) examine occupancy and nest success of secondary-cavity nesting birds using nestboxes. LANL biologists completed the seventh year of this effort in 2019. Three bird point count surveys were completed at each of the treatment sites at the Technical Area (TA) 36 Minie site, the TA-39 point 6, and the TA-16 burn ground between May and July 2019. A total of 853 birds representing 53 species were recorded at the three treatment sites and compared to their associated controls. Occupancy and nest success data from nestboxes at treatment sites were compared with the overall avian nestbox monitoring network. In 2019 the species richness and diversity at the treatment sites were not statistically different from their associated controls. Rarefaction and extrapolation plots for all years through 2018 suggest that over time the species diversity was statistically different between treatments and controls, although the diversity was higher at the treatment sites than the control sites. Avian abundance showed more variability but treatment and controls were trending together year to year. The mean number of granivores, insectivores, and omnivores varies from year to year, but there is not a significant trend at any of the treatment sites. The dominant feeding guild at the treatment sites continues to be insectivores. The overall results from 2019 continue to indicate that operations at the three treatment sites are not negatively affecting bird populations. This long-term monitoring will continue to monitor for any changes over time.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Exceptional Points in Novel Multiscale Quantum-Nanoplasmonic Materials for Enhanced Sensing and Other Applications

Lossy quantum systems can display fascinating behaviors around singularities known as exceptional points in their complex eigenvalue spaces. Interest in these systems was ignited over two decades ago when Carl Bender and Stefan Boettcher—a LANL Director’s Postdoctoral Fellow at the time—pointed out that many features of conventional lossless quantum systems, such as real operator eigenvalues, could be recovered in lossy systems exhibiting parity- and time-reversal (ΡΤ) symmetry.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Material point generation from an STL file

In this short note we describe a method for generating material points from a file in the stere olithography (STL) format commonly used in computer aided design (CAD), 3-D printing, and computer aided manufacturing applications. In this file format the surface of an object is described by triangles in three-dimensional space. The coordinates of the triangle vertexes are provided in the file. In this note we assume that the object of interest is inside of the enclosing set of triangles. Similar methods can also be used to generate material points outside of the enclosing triangles.

42 ENGINEERING↗
DOE OSTI2023

2022 Results for Avian Monitoring of Inorganic Elements and Organic Chemical Concentrations in Passerine Eggs and Nestlings Collected from Technical Area 16 Burn Grounds, Technical Area 36 Minie, and Technical Area 39 Point 6 at Los Alamos National Laboratory

In 2022, nonviable avian eggs and one nestling were opportunistically collected at Los Alamos National Laboratory (LANL) near open detonation sites located at Technical Area (TA) 16 burn grounds, TA-36 Minie, and TA-39 Point 6. Samples were evaluated for inorganic elements (mostly metals) or per- and polyfluoroalkyl substances (PFAS). Three western bluebird (Sialia mexicana) egg samples were collected from TA-16 burn grounds. One deceased mountain bluebird (Sialia currucoides) nestling sample was collected from TA-36 Minie. One ash-throated flycatcher (Myiarchus cinerascens) egg sample was collected from TA-39 Point 6. Concentrations of inorganic elements (i.e., mostly metals) observed in this study were compared with the regional statistical reference level (RSRL), which is the upper-level bounds of background concentrations (mean + three standard deviations = 99% confidence interval). Several inorganic elements were not detected in avian eggs. All of the inorganic elements that were detected were below the RSRL and the lowest observable adverse effect level (LOAEL), when available. No PFAS compounds were detected in the mountain bluebird nestling sample collected from TA-36, and the majority of PFAS compounds were not detected in the western bluebird egg sample from TA-16. These data suggest that inorganic element and PFAS concentrations in eggs and nestlings are not of ecological concern. More data are needed to make a robust assessment and to evaluate trends over time.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

TOLERANCES OF CRAB DISPERSION AT THE INTERACTION POINT IN THE HADRON STORAGE RING OF THE ELECTRON-ION COLLIDER

The Electron Ion Collider (EIC) presently under construction at Brookhaven National Laboratory will collide polarized high energy electron beams with hadron beams with luminosities up to 10^34 cm^?2 s^?1 in the center mass energy range of 20-140 GeV. Due to the detector solenoid in the interaction region, the design horizontal crabbing angle will be coupled to the vertical plane if uncompensated. In this article, we study the tolerances of crab dispersion at the interaction point in the EIC Hadron Storage Ring (HSR). Both strong-strong and weak-strong simulations are used. We found that there is a tight tolerance of vertical crabbing angle at the interaction point in the HSR.

Luo, Y.↗
DOE OSTI2024

Theoretical Studies of Polar Systems near Ferroelectrics Quantum Critical Points (Final Report)

The PI has studied emergent quantum phases near polar quantum critical points. A first challenge was to develop a theoretical description of the observation that many polar materials undergo classical first-order transitions while displaying quantum criticality. The possibility of novel metallic states near polar quantum critical points was then studied; identification and characterization of a non-Fermi liquid phase was made in a multiband system. In dilute quantum critical polar metals, electronic coupling to polar energy fluctuations was shown to result in attractive electron-electron interactions and to superconductivity. A spin-phonon resonance measurement in applied magnetic field was proposed to determine the magnitude of spin-orbit mediated electron-phonon coupling; furthermore in the polar phase new field-induced phonon collective modes were identified with specific signatures for experiment. In order to keep current, the PI has also worked on other types of strongly correlated problems. With experimental groups, she has developed phenomenologies to identify and explain observed dynamical critical behaviors. The PI has studied the interplay of topology, fractionalization and deconfinement in a minimalist spin model. An emergent phase transition in a 1 + 1 frustrated spin nanotube has also been identified and characterized. The PI has also begun exploring criticality out of equilibrium, characterizing rich dynamical phases associated with photoinduced polar transitions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

An Intermediate Level Trigger Supernova Pointing Trigger for DUNE Using In-Storage AI

We propose a near-data approach to reduce the buffered supernova data on the DUNE DAQ front-end computers using ML techniques. Based on simulations, we are able to reduce the data by 5 orders of magnitude to 0(100)MB which can then be transferred quickly over ethernet to a single server that executes a full reconstruction and pointing analysis to determine the SN direction. The entire process of reducing the data and executing reconstruction and pointing analysis pipeline takes less time than that required to transfer all the data back to Fermilab before performing more processing to determine the direction of the supernova, which was the baseline plan for DUNE.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Prong Segmentation using Point Set Transformers in Multiple View Neutrino Detectors

NOvA is a long-baseline neutrino experiment studying neutrino oscillations by detecting neutrinos from the NuMI beam at Fermilab. Its physics analysis relies on accurate prong segmentation, which involves matching each hit to its source particle and identifying the particle type. This task has commonly been addressed using a combination of traditional clustering algorithms and convolutional neural networks (CNNs). However, NOvA’s detector design presents data as two sparse and decoupled 2D images (XZ and YZ views) rather than a native 3D representation, posing a significant challenge for traditional CNN-based models. In this talk, we propose a novel neural network based on the Point Set Transformer. By treating detector hits as sparse point clouds and implementing a cross-view attention mechanism, our model enables efficient information mixing between both views. Evaluated on NOvA simulated data, our model achieves superior accuracy while requiring significantly fewer computational resources compared to other models. Furthermore, the model demonstrates great performance when applied to Liquid Argon Time Projection Chamber (LArTPC) data, which shows its potential as a universal prong segmentation algorithm for multiple view neutrino detectors.

Liu, Jiaxi [UC, Irvine]↗
DOE OSTI2025

Automated segmentation and analysis of point clouds of pier foundations using Pier Inspection and Evaluation Report (PIER)

Pier foundations are commonly used in locations with unstable soil or where other types of foundations are unsuitable or cost prohibitive. A pier foundation consists of vertical columns to support the structure and elevate it above the ground. Common materials for pier foundations include masonry, concrete, timber, and steel. The methods for accurate placement of pier foundations have remained relatively unchanged for decades. For simple installations, construction chalk lines are used to layout the locations of piers to ensure accurate placement and elevation. For more complex installations, surveying instruments operated by trained professionals are employed to accurately locate piers and assess correct elevation before construction. After installation, another survey may need to be performed to assess the quality of the as-built foundation. However, with the advent of terrestrial laser scanners (TLS), the means now exist for contractors to conduct their own assessments of as-built foundations. The major barrier preventing contractors from performing their own assessments of as-built foundation quality is the segmentation and analysis of point cloud data, a skill that often requires a trained user. The objective of this research is to develop a software tool (PIER: Pier Inspection and Evaluation Report) to enable automated segmentation and analysis of point clouds of pier foundations. In this paper, the automated segmentation and analysis algorithms are detailed. A mockup lay out of pier foundations was built using concrete masonry units, and the algorithms were tested to evaluate performance. Limitations of the current algorithms and future research direction are discussed.

Turki, Amine [ORNL]↗
DOE OSTI2025

P2P: Point Cloud to Panel Layout Optimization

Building envelope retrofits, despite their benefits on enhancing energy efficiency, progress slowly due to high operating costs. Overclad panelized systems present an attractive solution to make retrofits affordable and easy to install. However, several stages of the retrofit process remain disconnected, suboptimal, and require significant human intervention. This study aims to bridge the gap between digital twin generation and overclad panel installation by automating the design of an optimal panel layout directly from a building envelope point cloud. In this end-to-end approach, the dimensional twin is generated by segmenting the facade point cloud. The facade then undergoes a three-step process to generate an optimized panel layout for integration with automated placement systems.

Philips, Nisha Deborah [ORNL]↗
DOE OSTI2026

Characterization of the Polarization Beam Response of SPT-3G Using Point Sources

Precise measurements of cosmic microwave background (CMB) polarization require rigorous control of instrumental systematics. For the South Pole Telescope's third-generation camera (SPT-3G), which observes in three bands centered near 95, 150, and 220 GHz, accurate beam characterization is critical for interpreting the polarized mm-wave sky. We present direct measurements of SPT-3G's polarized beam response from observations of 100 bright extragalactic point sources. Previous SPT-3G power spectrum analyses introduced a phenomenological parameter, $β_{\rm pol}$, to describe the polarization preserved in beam sidelobes, and found evidence for significant depolarization from the requirement of inter-frequency polarization power spectrum consistency. Our direct measurements yield $β_{\rm pol}=0.89\pm0.10$ at 95 GHz, $1.08\pm0.10$ at 150 GHz, and $0.90\pm0.22$ at 220 GHz, indicating minimal sidelobe depolarization. We validate these results with systematic tests of posterior sampling versus bootstrap resampling, real-space versus Fourier-space analysis, temperature-to-polarization leakage handling, covariance determination, and source selection. Compared to values inferred from previous cosmological analyses, our results differ by an effective $1.3σ$. This apparent discrepancy is model dependent, because the point source analysis derives much of its $β_{\rm pol}$ constraining power from higher multipoles than the power spectrum analysis. These measurements therefore admit three explanations for the frequency-dependent residuals observed in the power spectrum analysis: a statistical fluctuation, the need for more sophisticated polarized beam models, or systematics other than beam depolarization.

de Haan, T. [KEK, Tsukuba]↗
DOE OSTI2025

Comparison of spatial dynamics and point kinetics approaches in multiphysics modeling of the molten salt reactor experiment

In this work, we present validation test results of fully coupled neutronics and thermal-hydraulics models of the Molten Salt Reactor Experiment (MSRE) against experimental data of the zero power pump transients and the natural circulation tests at low power. To capture the strong coupling between neutronics and thermal-hydraulics due to fuel circulation, and to account for the delayed neutron precursor (DNP) distribution, the porous media thermal-hydraulics solver Pronghorn was fully coupled to the spatial neutron dynamics code Griffin, which solves the neutron diffusion equation, and to the 0-D point kinetics solver Squirrel, using a 2-D homogenized representation of the MSRE. The validation test results show very good agreement with experimental data for both point kinetics and spatial dynamics simulations, capturing the strong feedback effect and DNP losses in the MSRE. The 0-D code Squirrel accurately predicted the time-dependent behavior in the MSRE given the steady-state spatial dynamics solution of Griffin.

42 - ENGINEERING↗
DOE OSTI2021

Review of Dew Point Evaporative Cooling Technology for Air Conditioning Applications

Indirect evaporative cooling has the potential to significantly improve the natural environment. It follows from a significant reduction in electricity consumption in the hot period, and hence lower operating costs for cooling systems. This paper presents the current state of knowledge and research directions on dew point indirect evaporative cooling. It was found that researchers focus on the development of dew point indirect evaporative coolers (DPIEC) by improving its design, geometry, water distribution, and new porous materials implementation. To evaluate the performance of new types of DPIEC, different methods are used by the scientists. Finally, optimized devices are studied in terms of their performance in different systems, like hybrid and desiccant systems, considering different climate conditions. Potential directions of development of evaporative technologies were indicated, such as increasing the coefficient of performance of solid desiccant evaporative cooling systems, developing novel geometry, and efficient water distribution, including development of porous materials.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Detecting Quantum Critical Points of Correlated Systems by Quantum Convolutional Neural Network Using Data from Variational Quantum Eigensolver

Machine learning has been applied to a wide variety of models, from classical statistical mechanics to quantum strongly correlated systems, for classifying phase transitions. The recently proposed quantum convolutional neural network (QCNN) provides a new framework for using quantum circuits instead of classical neural networks as the backbone of classification methods. We present the results from training the QCNN by the wavefunctions of the variational quantum eigensolver for the one-dimensional transverse field Ising model (TFIM). We demonstrate that the QCNN identifies wavefunctions corresponding to the paramagnetic and ferromagnetic phases of the TFIM with reasonable accuracy. The QCNN can be trained to predict the corresponding ‘phase’ of wavefunctions around the putative quantum critical point even though it is trained by wavefunctions far away. The paper provides a basis for exploiting the QCNN to identify the quantum critical point.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗