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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 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The Completed SDSS-IV Extended Baryon Oscillation Spectroscopic Survey: N-body Mock Challenge for Galaxy Clustering Measurements

We develop a series of N-body data challenges, functional to the final analysis of the extended Baryon Oscillation Spectroscopic Survey (eBOSS) Data Release 16 (DR16) galaxy sample. The challenges are primarily based on high-fidelity catalogues constructed from the Outer Rim simulation - a large box size realization (3h(-1) Gpc) characterized by an unprecedented combination of volume and mass resolution, down to 1.85 x 10(9) h(-1)M(circle dot). We generate synthetic galaxy mocks by populating Outer Rim haloes with a variety of halo occupation distribution (HOD) schemes of increasing complexity, spanning different redshift intervals. We then assess the performance of three complementary redshift space distortion (RSD) models in configuration and Fourier space, adopted for the analysis of the complete DR16 eBOSS sample of Luminous Red Galaxies (LRG5). We find all the methods mutually consistent, with comparable systematic errors on the Alcock-Paczynski parameters and the growth of structure, and robust to different HOD prescriptions - thus validating the robustness of the models and the pipelines used for the baryon acoustic oscillation (BAO) and full shape clustering analysis. In particular, all the techniques are able to recover and alpha(11) to within 0.9 per cent, and f sigma(8) to within 1.5 per cent. As a by-product of our work, we are also able to gain interesting insights on the galaxy-halo connection. Our study is relevant for the final eBOSS DR16 'consensus cosmology', as the systematic error budget is informed by testing the results of analyses against these high-resolution mocks. In addition, it is also useful for future large-volume surveys, since similar mock-making techniques and systematic corrections can be readily extended to model for instance the Dark Energy Spectroscopic Instrument (DESI) galaxy sample.

cosmology: theory, large-scale structure of Univer↗
DOE OSTI2022

Nitrogen Metabolism in Pseudomonas putida : Functional Analysis Using Random Barcode Transposon Sequencing

Pseudomonas putida KT2440 has long been studied for its diverse and robust metabolisms, yet many genes and proteins imparting these growth capacities remain uncharacterized. Using pooled mutant fitness assays, we identified genes and proteins involved in the assimilation of 52 different nitrogen containing compounds. To assay amino acid biosynthesis, 19 amino acid drop-out conditions were also tested. From these 71 conditions, significant fitness phenotypes were elicited in 672 different genes including 100 transcriptional regulators and 112 transport-related proteins. We divide these conditions into 6 classes, and propose assimilatory pathways for the compounds based on this wealth of genetic data. To complement these data, we characterize the substrate range of three promiscuous aminotransferases relevant to metabolic engineering efforts in vitro. So we examine the specificity of five transcriptional regulators, explaining some fitness data results and exploring their potential to be developed into useful synthetic biology tools. In addition, we use manifold learning to create an interactive visualization tool for interpreting our BarSeq data, which will improve the accessibility and utility of this work to other researchers.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Robust Infrasound Detection via Deep Learning (RIDDL)

RIDDL is a suite of software tools that enable AI/ML analysis of infrasound data. Methods and capabilities include construction, evaluation, and application of models for infrasound signal analysis, construction of synthetic data useful for construction and evaluation, as well as various other advanced data science tools enabling infrasound signal detection and categorization as well as downstream analysis methods such as localization and characterization of detected sources.

Blom, Philip↗
DOE OSTI2021

Characterizing the magnetic fields of nearby molecular clouds using submillimeter polarization observations

Of all the factors that influence star formation, magnetic fields are perhaps the least well understood. The goal of this paper is to characterize the 3D magnetic field properties of nearby molecular clouds through various methods of statistically analysing maps of polarized dust emission. Our study focuses on nine clouds, with data taken from the Planck Sky Survey as well as data from the Balloon-borne Large Aperture Submillimeter Telescope for Polarimetry observations of Vela C. We compare the distributions of polarization fraction (p), dispersion in polarization angles ($\mathcal {S}$), and hydrogen column density (N H ) for each of our targeted clouds. To broaden the scope of our analysis, we compare the distributions of our clouds’ polarization observables with measurements from synthetic polarization maps generated from numerical simulations. We also use the distribution of polarization fraction measurements to estimate the inclination angle of each cloud’s cloud-scale magnetic field. We obtain a range of inclination angles associated with our clouds, varying from 16° to 69°. We establish inverse correlations between p and both $\mathcal {S}$ and NH in almost every cloud, but we are unable to establish a statistically robust $\mathcal {S}$ versus NH trend. By comparing the results of these different statistical analysis techniques, we are able to propose a more comprehensive view of each cloud’s 3D magnetic field properties. These detailed cloud analyses will be useful in the continued studies of cloud-scale magnetic fields and the ways in which they affect star formation within these molecular clouds.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Heavy neutrinos with dynamic jet vetoes: multilepton searches at $\sqrt{s}=14$, 27, and 100 TeV

Heavy neutrinos (N) remain one of most promising explanations for the ori-gin of neutrinos’ tiny masses and large mixing angles. In light of broad advances in un-derstanding and modeling of hadron collisions at large momentum transfers, we revisit the long-standard search strategy for heavy N decaying to multiple charged leptons (ℓ), pp → NℓX → 3ℓνX. For electroweak and TeV-scale N, we propose a qualitatively new collider analysis premised on a dynamic jet veto and discriminating, on an event-by-event basis, according to the relative amount of hadronic and leptonic activity. We report that the sensitivity to heavy neutrinos at the CERN Large Hadron Collider (LHC) can be improved by roughly an order of magnitude at both $\mathcal{L}$ = 300 fb-1 and 3 ab-1. At s√=14 TeV with $\mathcal{L}$ = 3 ab -1 , we find active-sterile mixing as small as |V ℓN | 2 = 10 -2 (10 -3 ) [5 × 10 -4 ] can be probed at 95% CL for heavy Dirac neutrinos masses $m$ N ≲ 1200 (300) [200] GeV, well beyond the present |V ℓN | 2 ≲ 10 -3 - 10 -1 constraints for such heavy states set by indirect searches and precision measurements. The improvement holds also for Majorana N, and is largely independent of whether charged lepton flavor is conserved or violated. The analysis, built almost entirely from inclusive, transverse observables, is designed to be robust across increasing collider energies, and hence serves as a basis for searches at future colliders: with $\mathcal{L}$ = 15ab -1 at $\sqrt{s}$ = 27 TeV,onecanprobemixingbelow |V ℓN | 2 = 10 -2 (10 -3 )[2 × 10 -4 ] for m N ≲ 3500 (700) [200] GeV. At a hypothetical 100 TeV pp collider with $\mathcal{L}$ = 30 ab -1 , one can probe mixing down to 9 × 10 -5 for m N ≲ 200 GeV, below 10 -3 for m N ≲ 4 TeV, and below 10 -2 for m N ≲ 15 TeV. We anticipate these results can be further improved with detector-specific tuning and application of multi-variant / machines learning techniques. To facilitate such investigations, we make publicly available Monte Carlo libraries needed for the precision computations/simulations used in our study.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Bringing solar to agriculture: An interdisciplinary design and analysis of a Concord grape agrivoltaic system

Agrivoltaics presents an opportunity to integrate solar photovoltaics (PV) with agricultural production, but crop-specific challenges and operational constraints remain underexplored. This study develops and evaluates a Concord grape agrivoltaic system in the Lake Erie American Viticulture Area, where vineyards face economic pressures and land use conflicts with solar development. Starting with vertical, tracking, and overhead PV systems, we model photosynthetic photon flux density (PPFD) reduction in grapevines and power generation losses from shading using the Agrivoltaic Radiation Tool (ART). Based on these results, which indicate 0.47 % annual grapevine PPFD loss for vertical designs, 1.6 % for tracking, and up to 25 % for the overhead systems, the vertical and tracking designs are selected for further computational fluid dynamics (CFD) analysis to evaluate airflow interactions. CFD results show that vertical panels do not significantly impact airflow through the grapevine canopy, and that tracking systems in horizontal position may enhance airflow compared to a vine-only scenario. Considering operational constraints for tracking systems, the vertical design is selected for an economic evaluation to reveal key financial outcomes for solar developers (14-year payback period) and growers ($408 reduction in financial losses per acre annually). A sensitivity analysis quantifies uncertainty in power generation (±8.8 %) and PPFD (±5.0 %), ensuring model robustness across different vineyard conditions. Furthermore, these findings provide quantitative evidence for the feasibility of Concord grape agrivoltaics, demonstrating a synergistic opportunity for dual-use solar while preserving cultural heritage in grape-growing regions.

14 SOLAR ENERGY↗
DOE OSTI2014

Efficient solution of the simplified P N equations

We show new solver strategies for the multigroup SPN equations for nuclear reactor analysis. By forming the complete matrix over space, moments, and energy a robust set of solution strategies may be applied. Moreover, power iteration, shifted power iteration, Rayleigh quotient iteration, Arnoldi's method, and a generalized Davidson method, each using algebraic and physics-based multigrid preconditioners, have been compared on C5G7 MOX test problem as well as an operational PWR model. These results show that the most ecient approach is the generalized Davidson method, that is 30-40 times faster than traditional power iteration and 6-10 times faster than Arnoldi's method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Development of a U-19Pu-10Zr fuel performance benchmark case based on the IFR-1 experiment

Metallic nuclear fuels are subject to research and development for use in advanced reactors. Robust, accurate metallic fuel performance models are important for the design, safety analysis, and licensing of these reactors. However, metallic fuel performance models require additional development; they are not as mature as UO 2 fuel performance models. A benchmark case based on the IFR-1 experiment was developed to better gauge the accuracy of existing models, identify models for high-priority development, and potentially quantify any future improvements made by further model development.This work collected publicly available information on the IFR-1 experiment and used it to develop the benchmark case. Fuel behavior during the IFR-1 irradiation was simulated by using the fuel performance code BISON, and the predicted results were compared with postirradiation examination data from the IFR-1 experiment. Furthermore, a sensitivity study and tuning studies were performed as a preliminary investigation into the causes of inaccurate temperature and dimensional change predictions.The benchmark predicted reasonably accurate values for the burnup and fission gas release. There was error in the predicted temperatures, which could be explained by uncertainty in the input parameters and legacy temperatures. BISON over-predicted dimensional changes in the fuel and cladding. The sensitivity study showed that the dimensional changes were most sensitive to the fuel swelling anisotropy and the cladding void swelling model. Future benchmark and model development should focus on cladding swelling behaviors to improve dimensional change predictions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Detection of sub-500-μm cracks in multicrystalline silicon wafer using edge-illuminated dark-field imaging to enable thin solar cell manufacturing

High capital expenditures associated with manufacturing thin silicon wafers make it difficult for the industry to scale up and prevent novel technologies from entering the market. Thin wafers fail largely due to breakage during solar cell processing and handling. One of the root causes for breakage is sub-mm edge cracks in the silicon wafer, and these cracks cannot be reliably detected by most commercially-available crack detection tools. In this work, we first investigate the correlation between wafer thickness and critical crack length, and explain the importance of detecting sub-500-μm edge cracks as the wafer thickness is reduced. Secondly, we extend our previous work of micro-crack detection to demonstrate an edge illumination technique using a near-infrared laser to image edge cracks less than 500 μm in length in multicrystalline silicon. Thirdly, we investigate two fundamental edge illumination mechanisms based on dark-field imaging; namely, direct and vicinal illumination. We will then compare these methods to a state-of-the-art rear illumination method. The advantages and disadvantages of both illumination methods are presented and provide an in-depth analysis of light-crack interaction. In particular, we find that the robustness of vicinal illumination is due to diffuse reflectance. The diffuse reflectance has less dependence on crack configurations, while direct illumination has more dependence on the crack configurations because it utilizes specular reflectance. Our results show that our proposed prototype can detect sub-mm edge cracks in multicrystalline silicon wafers, which is an important step in enabling thin silicon wafer manufacturing.

14 SOLAR ENERGY↗
DOE OSTI2018

The Phase Evolution and Degradation Modes of $ R\overline{3}$ m Li x Ni 1-y-z Co y Al z O 2 Electrodes Cycled Near Complete Delithiation

We report that the practical utilization of energy densities near the theoretical limit for $ R\overline{3}m$ layered oxide positive electrode materials is dependent on the stability of the electrochemical performance of these materials at or near full delithiation. In order to develop new chemistries and novel approaches towards the improvement of the electrochemical performance of these materials at such high states of charge, a robust understanding of the failure mechanisms limiting current materials is necessary. Thorough analysis of Li x Co 1-y Al y O 2 and Li x Ni 1-y Al y O 2 as well as Li x Ni 0.8 Co 0.2 O 2 and Li x Ni 0.8 Co 0.15 Al 0.05 O 2 (1 ≥ x ≥ 0 and 0.2 ≥ y ≥ 0) enabled the identification of key relationships between the transition metal chemistry of the electrode, its structural stability, and cycling characteristics at or near complete delithiation (4.75 V). Extensive characterization of these materials was achieved by a multitude of physical and electrochemical techniques to investigate the relative importance of surface vs. bulk phenomena. Here, the resulting insights derived from these analyses highlight the importance of the intrinsic structural and mechanical stability of the electrode when highly delithiated and establish guidelines for identifying positive electrode materials with improved high state of charge performance. Lastly, particularly important is the contrasting electrochemical impact of Al substitution into LiCoO 2 - and LiNiO 2 -based materials, which is shown to likely arise from the enhanced propensity for Al ions to migrate to the tetrahedral site in Co-rich compounds at high states of delithiation.

25 ENERGY STORAGE↗
DOE OSTI2016

Chaos control of the micro-electro-mechanical resonator by using adaptive dynamic surface technology with extended state observer

This paper addresses chaos control of the micro-electro- mechanical resonator by using adaptive dynamic surface technology with extended state observer. To reveal the mechanism of the micro- electro-mechanical resonator, the phase diagrams and corresponding time histories are given to research the nonlinear dynamics and chaotic behavior, and Homoclinic and heteroclinic chaos which relate closely with the appearance of chaos are presented based on the potential function. To eliminate the effect of chaos, an adaptive dynamic surface control scheme with extended state observer is designed to convert random motion into regular motion without precise system model parameters and measured variables. Putting tracking differentiator into chaos controller solves the ‘explosion of complexity’ of backstepping and poor precision of the first-order filters. Meanwhile, to obtain high performance, a neural network with adaptive law is employed to approximate unknown nonlinear function in the process of controller design. The boundedness of all the signals of the closed-loop system is proved in theoretical analysis. Finally, numerical simulations are executed and extensive results illustrate effectiveness and robustness of the proposed scheme.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Comparative study of the superconductivity in the Holstein and optical Su-Schrieffer-Heeger models

Theoretical studies suggest that Su-Schrieffer-Heeger-like electron-phonon (e-ph) interactions can mediate high-temperature bipolaronic superconductivity that is robust against repulsive electron-electron interactions. Here we present a comparative analysis of the pairing and competing charge/bond correlations in the two-dimensional Holstein and optical Su-Schrieffer-Heeger (SSH) models using numerically exact determinant quantum Monte Carlo. We find that the SSH interactions support light bipolarons and strong superconducting correlations out to relatively large values of the e-ph coupling λ and densities near half-filling, while the Holstein interaction does not due to the formation of heavy bipolarons and competing charge-density-wave order. We further find that the Holstein and SSH models have comparable pairing correlations in the weak coupling limit for carrier concentrations < n > <<1, where competing orders and polaronic effects are absent. These results support the proposal that SSH (bi)polarons can support superconductivity to larger values of λ in comparison to the Holstein polaron, but that the resulting T c gains are small in the weak coupling limit. We also find that the SSH model's pairing correlations are suppressed after including a weak on-site Hubbard repulsion. Furthermore, these results have important implications for identifying and engineering bipolaronic superconductivity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

How analytic choices can affect the extraction of electromagnetic form factors from elastic electron scattering cross section data

Scientists often try to incorporate prior knowledge into their regression algorithms, such as a particular analytic behavior or a known value at a kinematic endpoint. Unfortunately, there is often no unique way to make use of this prior knowledge, and thus, different analytic choices can lead to very different regression results from the same set of data. In this paper, to illustrate this point in the context of the proton electromagnetic form factors, we use the Mainz elastic data with its 1422 cross section points and 31 normalization parameters. Starting with a complex unbound non-linear regression, we will show how the addition of a single theory-motivated constraint removes an oscillation from the magnetic form factor and shifts the extracted proton charge radius. We then repeat both regressions using the same algorithm, but with a rebinned version of the Mainz dataset. These examples illustrate how analytic choices, such as the function that is being used or even the binning of the data, can dramatically affect the results of a complex regression. These results also demonstrate why it is critical when using regression algorithms to have either a physical model in mind or a firm mathematical basis

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

Searching for Dark Matter Annihilation from Milky Way Dwarf Spheroidal Galaxies with Six Years of Fermi Large Area Telescope Data

The dwarf spheroidal satellite galaxies (dSphs) of the Milky Way are some of the most dark matter (DM) dominated objects known. We report on γ-ray observations of Milky Way dSphs based on six years of Fermi Large Area Telescope data processed with the new Pass8 event-level analysis. None of the dSphs are significantly detected in γ rays, and we present upper limits on the DM annihilation cross section from a combined analysis of 15 dSphs. These constraints are among the strongest and most robust to date and lie below the canonical thermal relic cross section for DM of mass ≲100 GeV annihilating via quark and τ-lepton channels.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Hierarchical Speed Planner for Automated Vehicles: A Framework for Lagrangian Variable Speed Limit in Mixed-Autonomy Traffic

Here, this article presents a novel hierarchical speed planning framework for variable speed limits in mixed-autonomy traffic environments, leveraging server-side macroscopic control and vehicle-side microscopic execution. The framework integrates real-time traffic state estimation (TSE) and reinforcement learning (RL)-based control to mitigate congestion and improve traffic flow. A TSE enhancement module combines macroscopic data from sources like INRIX with high-resolution observations from connected autonomous vehicles (CAVs), enabling predictive modeling to address latency and noise. The target speed design module employs kernel smoothing and a buffer zone strategy to optimize traffic density and flow around bottlenecks. The proposed system was validated in the largest open-road test to date with 100 CAVs, demonstrating an overall 8% traffic density decrease, with a specific decrease of 7% upstream, 10% downstream, and a 52% decrease during the congestion formation phase at bottlenecks.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Frequency Response Improvement in a Standalone Small Hydropower Plant Using Battery Storage

This paper proposes a control architecture for frequency, current, and voltage control that facilitates using battery storage to improve the response of standalone small hydropower plants. The frequency controller uses rate-of-change of frequency and frequency-Watt-based generations to produce active power commands. The distinctive feature of the controller design is that it nicely integrates response to frequency change with constraints on frequency and state of battery to enable power injections. The current and voltage control scheme allows incorporating the frequency controller. The distinctive feature of this controller is that it incorporates a bounded integral control strategy that guarantees stability. Results on the stability of the hydropower plant with proposed scheme are presented and robust ways to choose the controller gains are investigated via root locus analysis. In conclusion, simulations performed show that: the hydropower plant response is significantly improved with battery storage using the proposed scheme; the load carrying capability of the hydropower plant is significantly improved with battery storage; the proposed scheme has the capability to recharge the battery; and the proposed control scheme gives improved performance.

13 HYDRO ENERGY↗
DOE OSTI2020

Surge-Energy and Overvoltage Ruggedness of P-Gate GaN HEMTs

An essential ruggedness of power devices is the capability of safely withstanding the surge energy. The surge ruggedness of the GaN high-electron-mobility transistor (HEMT), a power transistor with no or minimal avalanche capability, has not been fully understood. This article unveils the comprehensive physics associated with the surge-energy withstand process and the failure mechanisms of p-gate GaN HEMTs. Two commercial p-gate GaN HEMTs with Ohmic- and Schottky-type gate contacts are studied. Two circuits are developed to study the device surge ruggedness: an unclamped inductive switching circuit is first used to identify the withstand dynamics and failure mechanisms, and a clamped inductive switching circuit with a controllable parasitic inductance is then designed to mimic the surge energy in converter-like switching events. The p-gate GaN HEMT is found to withstand the surge energy through a resonant energy transfer between the device capacitance and the load/parasitic inductance rather than a resistive energy dissipation as occurred in the avalanche. If the device resonant voltage goes below zero, the device reversely turns on and the inductor is discharged. The device failure occurs at the transient of peak resonant voltage and is limited by the device overvoltage capability rather than the surge energy, dV/dt , or overvoltage duration. Almost no energy is dissipated in the resonant withstand process and the device failure is dominated by an electric field rather than a thermal runaway. Furthermore, these results provide critical understandings on the ruggedness of GaN HEMTs and important references for their qualifications and applications.

42 ENGINEERING↗
DOE OSTI2023

Accelerating the development of a sustainable bioenergy portfolio through stable isotopes

Bioenergy could help limit global warming to 2°C above pre-industrial levels while supplying almost a fourth of the world's renewable energy needs by 2050. However, the deployment of bioenergy raises concerns that adoption at meaningful scales may lead to unintended negative environmental consequences. Meanwhile, the full consolidation of a bioenergy industry is currently challenged by a sufficient, resilient, and resource-efficient biomass supply and an effective conversion process. Here, we provide a comprehensive analysis of how stable isotope approaches have accelerated the development of a robust bioeconomy by advancing knowledge about environmental sustainability, feedstock development, and biological conversion. We show that advances in stable isotope research have generated crucial information to (1) gain mechanistic insight into the potential of bioenergy crops to mitigate climate change as well as their impact on water and nutrient cycling; (2) develop high-yielding, resilient feedstocks that produce high-value bioproducts in planta; and (3) engineer microbes to enhance feedstock conversion to bioenergy products. Further, we highlight knowledge gaps that could benefit from future research facilitated by stable isotope approaches. We conclude that advances in mechanistic knowledge and innovations within the field of stable isotopes in cross-disciplinary research actions will greatly contribute to breaking down the barriers to establishing a robust bioeconomy.

59 BASIC BIOLOGICAL SCIENCES↗