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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 1,657 records · Page 92
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Preliminary Target Selection for the DESI Quasar (QSO) Sample

The DESI survey will measure large-scale structure using quasars as direct tracers of dark matter in the redshift range 0.9 < z < 2.1 and using quasar Lyα forests at z > 2.1. In this work, we present two methods to select candidate quasars for DESI based on imaging in three optical (g, r, z) and two infrared (W1, W2) bands. The first method uses traditional color cuts and the second utilizes a machine-learning algorithm.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Preliminary Target Selection for the DESI Emission Line Galaxy (ELG) Sample

DESI will precisely constrain cosmic expansion and the growth of structure by collecting ~35 million redshifts across ~80% of cosmic history and one third of the sky to study Baryon Acoustic Oscillations (BAO) and Redshift Space Distortions (RSD). In this work, we present a preliminary target selection for an Emission Line Galaxy (ELG) sample, which will comprise about half of all DESI tracers. The selection consists of a g-band magnitude cut and a (g – r) versus (r – z) color box, which we validate using HSC/PDR2 photometric redshifts and DEEP2 spectroscopy. The ELG target density should be ~2400 deg –2 , with ~65% of ELG redshifts reliably within a redshift range of 0.6 < z < 1.6. ELG targeting for DESI will be finalized during a "Survey Validation" phase.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Cabin Thermal Management Analysis for SuperTruck II Next-Generation Hybrid Electric Truck Design

In this article, we present a multistage, coupled thermal management simulation approach, informed by physical testing where available, to aid design decisions for PACCAR's SuperTruck II hybrid truck cabin concept. Focus areas include cabin insulation, battery sizing, and sleeper curtain position, as well as heating, ventilating, and air-conditioning (HVAC) component and accessory configurations, to maintain or improve thermal comfort while saving energy. The authors analyzed weather data and determined the national vehicle miles traveled weighted temperature and solar conditions for long-haul trucks. Example weather day profiles were selected to approximate the 5th and 95th percentile weighted conditions. A daylong drive cycle was developed to impose appropriate external wind conditions during rest and driving periods. Using the National Renewable Energy Laboratory's vehicle HVAC modeling and simulation tool VTCab, HVAC load design trade-off studies for the new truck geometry concept were completed. Parameters analyzed included effects of paint color, insulation, glass transmissivity, and curtain location. Simulation results helped with early design material selections for efficient cabin climate control. A detailed three-dimensional computer-aided engineering (CAE), computational fluid dynamics (CFD), radiation, and human physiology co-simulation, referred to in this article as CAE Thermal-CFD, was used to evaluate thermal comfort and energy impacts of diffuser configurations and air supply settings in driving and hoteling modes. Analysis revealed that it is more difficult to heat the cabin in hoteling mode during the winter than to cool the space in the summer. This seasonal load profile drives the requirement of additional energy storage for heating comfort. To determine the battery capacity requirement, multiday HVAC operation drive cycle simulations were then completed, showing that a 15-kWh battery would be required for HVAC operation during hoteling. Results helped reduce cabin thermal loads, determine component sizing requirements, and improve occupant comfort to save fuel and contribute to the economic viability of the hybrid system.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Validation of the DESI DR2 Ly$\alpha$ BAO analysis using synthetic datasets

The second data release (DR2) of the Dark Energy Spectroscopic Instrument (DESI), containing data from the first three years of observations, doubles the number of Lyman-$\alpha$ (Ly$\alpha$) forest spectra in DR1 and it provides the largest dataset of its kind. To ensure a robust validation of the Baryonic Acoustic Oscillation (BAO) analysis using Ly$\alpha$ forests, we have made significant updates compared to DR1 to both the mocks and the analysis framework used in the validation. In particular, we present CoLoRe-QL, a new set of Ly$\alpha$ mocks that use a quasi-linear input power spectrum to incorporate the non-linear broadening of the BAO peak. We have also increased the number of realisations used in the validation to 400, compared to the 150 realisations used in DR1. Finally, we present a detailed study of the impact of quasar redshift errors on the BAO measurement, and we compare different strategies to mask Damped Lyman-$\alpha$ Absorbers (DLAs) in our spectra. The BAO measurement from the Ly$\alpha$ dataset of DESI DR2 is presented in a companion publication.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Evaluation of cloud height, optical thickness, and phase retrievals from the CHROMA algorithm applied to Sentinel-3 OLCI data

We previously developed the Cloud Height Retrieval from O 2 Molecular Absorption (CHROMA) algorithm for the Ocean Color Instrument (OCI) on the new NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission. Here, we apply CHROMA to observations from the Ocean Land Colour Instrument (OLCI) to guide expectations for PACE, as it will take some time to obtain large-scale validation data for OCI. We use cloud top height (CTH), phase, and (for liquid clouds) cloud optical thickness (COT) data from the ground-based Atmospheric Radiation Measurement (ARM) network to evaluate the OLCI retrievals. We found that OLCI and Moderate Resolution Imaging Spectroradiometer (MODIS) CTH compare similarly well to the ARM reference. OLCI has a tendency to underestimate CTH as CTH increases, and algorithm assumptions about cloud geometric thickness may contribute to this. ARM COT from multifilter shadowband radiometers (MFRSR) and Sun photometers are well-correlated with one another, albeit with a roughly 30 % offset on average; OLCI and MODIS COT agree more closely with the MFRSR data. OLCI retrieval uncertainty estimates show skill at telling low-uncertainty cases from high-uncertainty ones, although CTH uncertainties are underestimated. Additionally, we compare the OLCI data to satellite retrievals based on thermal infrared measurements from MODIS and Sea and Land Surface Temperature Radiometer (SLSTR) data. Differences are broadly consistent with physical expectations based on the A-band vs. thermal techniques, although one key challenge in such aggregated comparisons is different cloud masking sensitivities and algorithm failure rates meaning additional sampling differences are introduced. We conclude by discussing the transition to and possible enhancements for PACE OCI.

Sayer, Andrew M. [Univ. of Maryland Baltimore Coun↗
DOE OSTI2022

Spatial heterogeneity effects on land surface modeling of water and energy partitioning

Abstract. Understanding the influence of land surface heterogeneity on surface water and energy fluxes is crucial for modeling earth system variability and change. This study investigates the effects of four dominant heterogeneity sources on land surface modeling, including atmospheric forcing (ATM), soil properties (SOIL), land use and land cover (LULC), and topography (TOPO). Our analysis focused on their impacts on the partitioning of precipitation (P) into evapotranspiration (ET) and runoff (R), partitioning of net radiation into sensible heat and latent heat, and corresponding water and energy fluxes. An initial set of 16 experiments were performed over the continental US (CONUS) using the E3SM land model (ELMv1) with different combinations of heterogeneous and homogeneous datasets. The Sobol' total and first-order sensitivity indices were utilized to quantify the relative importance of the four heterogeneity sources. Sobol' total sensitivity index measures the total heterogeneity effects induced by a given heterogeneity source, consisting of the contribution from its own heterogeneity (i.e., the first-order index) and its interactions with other heterogeneity sources. ATM and LULC are the most dominant heterogeneity sources in determining spatial variability of water and energy partitioning, mainly contributed by their own heterogeneity and slightly contributed by their interactions with other heterogeneity sources. Their heterogeneity effects are complementary, both spatially and temporally. The overall impacts of SOIL and TOPO are negligible, except TOPO dominates the spatial variability of R/P across the transitional climate zone between the arid western and humid eastern CONUS. Accounting for more heterogeneity sources improves the simulated spatial variability of water and energy fluxes when compared with ERA5-Land reanalysis dataset. An additional set of 13 experiments identified the most critical components within each heterogeneity source, which are precipitation, temperature, and longwave radiation for ATM, soil texture, and soil color for SOIL and maximum fractional saturated area parameter for TOPO.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

TRACER-MAP_2022_absorption_coefficient

Absorption coefficient for PM2.5 measured by the Tri-color Absorption Photometer averaged every 2 minutes for July-August 2022. The location of the measurement is indicated by latitude and longitude coordinates; TRACER-MAP included time at the AMF site in La Porte and additional sites around Houston. Three wavelengths are reported: 365, 520 and 640 nm. The AAE is also reported using the three wavelengths. The data is reported as 2 minute averages.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A Pedagogical Discussion of Quarkyonic Matter and Its Implication for Neutron Stars

This paper is a brief pedagogical review of the ideas that motivate the concept of Quarkyonic Matter. If N c is the number of quark colors, baryonic matter at very high density and low temperature remains confining to density scales of the order of N$3/2\atop{c}$ Λ$3\atop{QCD}$ that is parametrically larger than that of the QCD scale Λ$3\atop{QCD}$. This implies that a description of nuclear matter will involve both quark and confined degrees of freedom. I argue that the equation of state of Quarkyonic Matter should be very hard, and the sound velocity should rise very rapidly from its small value at nuclear matter densities to a value of the order of 1 at a few times nuclear matter density.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Instanton Effects in Euclidean vacuum, Real Time Production, and in the Light-front Wave Functions

Nontrivial topological structures of non-Abelian gauge fields were discovered in the 1970s. Instanton solutions, describing vacuum tunneling through topological barriers, have fermionic zero modes which are at the origin of ‘t Hooft effective Lagrangian. In the 1980s, instanton ensembles have been used to explain chiral symmetry breaking. In the 1990s, a large set of numerical simulations were performed deriving Euclidean correlation functions. The special role of scalar diquarks in nucleons and color superconductivity in dense quark matter has been elucidated. In these lectures, we discuss further developments of physics related to gauge topology. We show that the instanton–anti-instanton “streamline” configurations describe “sphaleron transitions” in high-energy collisions, which result in production of hadronic clusters with nontrivial topological/chiral charges. (They are not yet observed, but discussions of dedicated experiments at the LHC and RHIC are ongoing.) Another new direction is instanton effects in hadronic spectroscopy, both in the rest frame and on the light front. We will discuss their role in central and spin-dependent potentials, form factors and antiquark nuclear “sea”. Finally, we summarize the advances in the semiclassical theory of deconfinement, and chiral phase transitions at finite temperature, in QCD, and in some of its “deformed” versions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

QCD–Gravity Double Copy in Regge Asymptotics: From \(2\rightarrow n\) Amplitudes to Radiation in Shockwave Collisions

This paper discusses multi-particle production in QCD and in gravity at ultrarelativistic energies, their double-copy relations, and strong parallels in emergent shockwave dynamics. Dispersive techniques are applied to derive the BFKL equation for multi-gluon production in Regge asymptotics. Identical methods apply in gravity and are captured by a gravitational Lipatov equation. The building blocks in both cases are Lipatov vertices and reggeized propagators satisfying double-copy relations; in gravity, Weinberg’s soft theorem is recovered as a limit of the Lipatov framework. BFKL evolution in QCD generates wee parton states of maximal occupancy characterized by an emergent semi-hard saturation scale. Renormalization group equations in the Color Glass Condensate (CGC) EFT describe wee parton correlations and their rapidity evolution. A shockwave picture of deeply inelastic scattering and hadron–hadron collisions follows, with multi-particle production described by Cutkosky’s rules in strong time-dependent fields. Gluon radiation in the CGC EFT has a double copy in gravitational shockwave collisions, with a similar correspondence applicable between gluon and graviton shockwave propagators. Possible extensions of this semi-classical double copy are outlined for computing multi-particle production in gravitational shockwave collisions, self-force and tidal contributions, and classical and quantum noise in the focusing of geodesics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Bayesian Inference of the Fluctuating Proton Shape in DIS and Hadronic Collisions

We determine the likelihood distribution for the model parameters describing the event-by-event fluctuating proton geometry at small $x$ by performing a Bayesian analysis within the Color Glass Condensate framework. The exclusive J/ψ production data from HERA is found to constrain the model parameters well, and we demonstrate that complementary constraints can be obtained from simulations of Pb+Pb collisions at the LHC.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Collectivity in Ultra-peripheral Heavy-ion and \(e+A\) Collisions

We review recent theoretical progress in describing collective effects in photon+nucleus collisions. The approaches considered range from the color glass condensate, where correlations are encoded in the initial state, to hydrodynamic frameworks, where a strong final-state response to the initial geometry of the collision is the key ingredient to generate momentum-space correlations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Recycling of PET by Dissolution-Purification-Recovery (DPR) Process Using Bioderived Solvent

Polyethylene terephthalate (PET) waste continues to accumulate at staggering rates, with the majority still routed to landfills due to limitations in current recycling methods. While mechanical recycling is widely implemented, it struggles to effectively remove colorants, additives, and harmful contaminants - resulting in discolored, degraded materials with limited reuse potential. In this presentation, we demonstrate a scalable dissolution-purification-recovery (DPR) process designed to selectively reclaim high-purity PET from post-consumer bottle flake. The method utilizes a food grade bio-based solvent for targeted PET dissolution, followed by activated carbon treatment for impurity removal and antisolvent-induced precipitation for polymer recovery. The resulting recycled PET exhibits complete decolorization, significantly reduced metal contamination, and minimal loss in molecular weight. These performance metrics indicate strong suitability for remanufacturing into new bottles, offering a circular alternative to traditional mechanical recycling pathways.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

RTN-099: Photometric Transformation Relations for the LSST Data Preview 1

This technical note provides photometric transformation relations between the Vera C. Rubin Observatory's LSSTCam and LSSTComCam systems and other photometric systems. These transformations are derived using both synthetic and empirical data and are intended to support calibration and comparison across survey systems. We present both polynomial equations and lookup-table-based methods, depending on the available data and desired accuracy. The transformations are generally valid for stars with typical spectral energy distributions (SEDs), and caution should be used when applying them to objects with strong emission lines or atypical colors.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

RTN-125: Photometric Transformation Relations for the LSST Data Preview 2

This technical note provides photometric transformation relations between the NSF-DOE Vera C. Rubin Observatory's Data Preview 2 (DP2) and other photometric systems. These transformations are derived using both synthetic and empirical data and are intended to support calibration and comparison across survey systems. We present both polynomial equations and lookup-table-based methods, depending on the available data and desired accuracy. The transformations are generally valid for stars with typical spectral energy distributions (SEDs), and caution should be used when applying them to objects with strong emission lines or atypical colors.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Data augmentation for disruption prediction via robust surrogate models

The goal of this work is to generate large statistically representative datasets to train machine learning models for disruption prediction provided by data from few existing discharges. Such a comprehensive training database is important to achieve satisfying and reliable prediction results in artificial neural network classifiers. Here, we aim for a robust augmentation of the training database for multivariate time series data using Student-t process regression. We apply Student-t process regression in a state space formulation via Bayesian filtering to tackle challenges imposed by outliers and noise in the training data set and to reduce the computational complexity. Thus, the method can also be used if the time resolution is high. We use an uncorrelated model for each dimension and impose correlations afterwards via coloring transformations. We demonstrate the efficacy of our approach on plasma diagnostics data of three different disruption classes from the DIII-D tokamak. To evaluate if the distribution of the generated data is similar to the training data, we additionally perform statistical analyses using methods from time series analysis, descriptive statistics, and classic machine learning clustering algorithms.

97 MATHEMATICS AND COMPUTING↗