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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A space-time tracking algorithm for high occupancy events at future colliders

We propose to explore the potential advantages of a newclass of tracking algorithms loosely inspired by the Hough transformconcept and where we include the time of arrival of each hit as anadditional coordinate to be treated in the same way as a spatialcoordinate. A remarkable property of this algorithm is that theexecution time is proportional to the total number of hits to beprocessed, making it particularly attractive for high occupancysituations expected at future colliders. The particular structureof the algorithm also lends itself naturally to parallel hardwareimplementations which, combined to its intrinsic flexibility, shouldprovide a powerful tool for triggering at future colliders. To probethe effectiveness of the algorithm, we apply it to a quasi-realisticsimulated environment of a possible future muon collider experimentand report the performance.

Casarsa, Massimo [INFN, Trieste; Royal Inst. Tech.↗
DOE OSTI2021

Bioverse: A Simulation Framework to Assess the Statistical Power of Future Biosignature Surveys

Next-generation space observatories will conduct the first systematic surveys of terrestrial exoplanet atmospheres and search for evidence of life beyond Earth. While in-depth observations of the nearest habitable worlds may yield enticing results, there are fundamental questions about planetary habitability and evolution that can only be answered through population-level studies of dozens to hundreds of terrestrial planets. To determine the requirements for next-generation observatories to address these questions, we have developed Bioverse. Bioverse combines existing knowledge of exoplanet statistics with a survey simulation and hypothesis testing framework to determine whether proposed space-based direct imaging and transit-spectroscopy surveys will be capable of detecting various hypothetical statistical relationships between the properties of terrestrial exoplanets. Following a description of the code, we apply Bioverse to determine whether an ambitious direct imaging or transit survey would be able to determine the extent of the circumstellar habitable zone and study the evolution of Earth-like planets. Given recent evidence that Earth-sized habitable zone planets are likely much rarer than previously believed, we find that space missions with large search volumes will be necessary to study the population of terrestrial and habitable worlds. Moving forward, Bioverse provides a methodology for performing trade studies of future observatory concepts to maximize their ability to address population-level questions, including and beyond the specific examples explored here.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

DarkNESS: developing a skipper-CCD instrument to search for Dark Matter from Low Earth Orbit

The DarkNESS (Dark Matter Nano-satellite Equipped with Skipper Sensors) mission aims to deploy a skipper-CCD CubeSat Observatory to search for dark matter (DM) from Low Earth Orbit. This mission will employ novel skipper-CCDs to investigate O(keV) X-rays from decaying DM, as well as electron recoils from strongly-interacting sub-GeV DM. The DarkNESS mission will be the first space deployment of skipper-CCDs, and the DarkNESS team is developing a skipper-CCD instrument that is compatible with the CubeSat platform. DarkNESS has recently progressed from laboratory validation to a Critical Design Review (CDR) phase, with a launch opportunity anticipated in late 2025. The implementation of the DarkNESS skipper-CCD payload on the CubeSat platform will pave the way for future demonstrators of space-based imagers for X-ray and single-electron counting applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Recent 238 Pu Production Activities at Idaho National Laboratory

The Plutonium-238 ( 238 Pu) Production program at Idaho National Laboratory (INL) is actively qualifying irradiation targets containing 237 Np for the Advanced Test Reactor (ATR) to produce 238 Pu for future National Aeronautics and Space Administration missions. INL qualified and loaded seven targets in the ATR’s south flux trap for cycle 169A, which occurred in Spring 2021. The irradiation qualification program has expanded to additional ATR irradiation positions after two baseline production targets in three positions validated significant production of 238 Pu. The validation model was followed by the PFS-1 experimental test in the ATR Critical Facility that verified 238 Pu production cross sections. This paper outlines the progress and status of the 238 Pu production program at INL. The qualification effort, safety analysis, hardware status, and future activities for qualification of an updated target design for use in the ATR are discussed.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2021

Constraints and variation in food web link-species space

Predicting food web structure in future climates is a pressing goal of ecology. These predictions may be impossible without a solid understanding of the factors that structure current food webs. Here, the most fundamental aspect of food web structure—the relationship between the number of links and species—is still poorly understood. Some species interactions may be physically or physiologically ‘forbidden'—like consumption by non-consumer species—with possible consequences for food web structure. We show that accounting for these ‘forbidden interactions' constrains the feasible link-species space, in tight agreement with empirical data. Rather than following one particular scaling relationship, food webs are distributed throughout this space according to shared biotic and abiotic features. Our study provides new insights into the long-standing question of which factors determine this fundamental aspect of food web structure.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Hierarchical Inference with Bayesian Neural Networks: An Application to Strong Gravitational Lensing

In the past few years, approximate Bayesian Neural Networks (BNNs) have demonstrated the ability to produce statistically consistent posteriors on a wide range of inference problems at unprecedented speed and scale. However, any disconnect between training sets and the distribution of real-world objects can introduce bias when BNNs are applied to data. This is a common challenge in astrophysics and cosmology, where the unknown distribution of objects in our universe is often the science goal. In this work, we incorporate BNNs with flexible posterior parameterizations into a hierarchical inference framework that allows for the reconstruction of population hyperparameters and removes the bias introduced by the training distribution. We focus on the challenge of producing posterior PDFs for strong gravitational lens mass model parameters given Hubble Space Telescope–quality single-filter, lens-subtracted, synthetic imaging data. We show that the posterior PDFs are sufficiently accurate (statistically consistent with the truth) across a wide variety of power-law elliptical lens mass distributions. We then apply our approach to test data sets whose lens parameters are drawn from distributions that are drastically different from the training set. We show that our hierarchical inference framework mitigates the bias introduced by an unrepresentative training set's interim prior. Simultaneously, we can precisely reconstruct the population hyperparameters governing our test distributions. Our full pipeline, from training to hierarchical inference on thousands of lenses, can be run in a day. The framework presented here will allow us to efficiently exploit the full constraining power of future ground- and space-based surveys (https://github.com/swagnercarena/ovejero).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

In-Flight Gain Monitoring of SPIDER’s Transition-Edge Sensor Arrays

We report experiments deploying large arrays of transition-edge sensors (TESs) often require a robust method to monitor gain variations with minimal loss of observing time. We propose a sensitive and non-intrusive method for monitoring variations in TES responsivity using small square waves applied to the TES bias. We construct an estimator for a TES’s small-signal power response from its electrical response that is exact in the limit of strong electrothermal feedback. We discuss the application and validation of this method using flight data from SPIDER, a balloon-borne telescope that observes the polarization of the cosmic microwave background with more than 2000 TESs. This method may prove useful for future balloon- and space-based instruments, where observing time and ground control bandwidth are limited.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Hybrid metal additive/subtractive machine tools and applications

Additive manufacturing creates parts by depositing a preform, typically layer by layer. Subtractive manufacturing involves removing material from a preform to create parts. Hybrid machine tools combine both additive and subtractive processes in the same workspace. They can be used to create parts that meet functional tolerance and surface finish requirements, or to create features that are difficult to produce using additive or subtractive processes alone. Here, this paper describes hybrid metal additive/subtractive machine tools. It covers design considerations, sensors and controls, process management, programming and software, and the impact on the design space. It also identifies future research challenges.

42 ENGINEERING↗
DOE OSTI2026

High-Performance Near-Infrared Quantum Emission from Color Centers in hBN

Color centers hosted in hexagonal boron nitride (hBN) have emerged as a highly promising platform for single-photon emission and spin-photon technologies relevant to quantum communication and quantum networking. As a wide bandgap van der Waals material, hBN can host optically active quantum defects across a broad spectral range. Here, we demonstrate a simple and scalable oxygen-plasma process that reproducibly creates single quantum emitters in hBN with blinking-free zero-phonon lines (ZPLs) spanning near-infrared (NIR) from 700 up to 971 nm. These emitters combine MHz-level brightness, single-photon purity up to 99.9%, and ultranarrow cryogenic line widths down to 2.7 GHz under quasi-resonant excitation, placing them in a particularly attractive regime for quantum photonics. Photostability measurements further reveal resistance to photobleaching, subnanometer spectral stability over long time scales, and near-shot-noise-limited intensity fluctuations. Analysis of the phonon sidebands shows weak vibronic coupling and ZPL-dominated emission, with Debye–Waller factors approaching 50%. Control experiments together with elemental mapping support oxygen incorporation as a necessary ingredient in activating the NIR emitter population, while first-principles calculations identify O N V N and O N V N H as the leading defect candidates. These results establish a high-performance NIR quantum-emitter platform in hBN for free-space quantum networking and future integrated quantum-photonic architectures.

2D materials↗
DOE OSTI2020

Automated detector simulation and reconstruction parametrization using machine learning

Rapidly applying the effects of detector response to physics objects (e.g. electrons, muons, showers of particles) is essential in high energy physics. Presently available tools for the transformation from truth-level physics objects to reconstructed detector-level physics objects involve manually defining resolution functions. These resolution functions are typically derived in bins of variables that are correlated with the resolution (e.g. pseudorapidity and transverse momentum). This process is time consuming, requires manual updates when detector conditions change, and can miss important correlations. Machine learning offers a way to automate the process of building these truth-to-reconstructed object transformations and can capture complex correlation for any given set of input variables. Such machine learning algorithms, with sufficient optimization, could have a wide range of applications: improving phenomenological studies by using a better detector representation, allowing for more efficient production of Geant4 simulation by only simulating events within an interesting part of phase space, and studies on future experimental sensitivity to new physics.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Graph reinforcement learning for exploring model spaces beyond the standard model

We present a methodology for performing scans of beyond the standard model (BSM) parameter spaces with reinforcement learning. We identify a novel procedure using graph neural networks that is capable of exploring spaces of models without the user specifying a fixed particle content, allowing broad classes of BSM models to be explored—in theory, the technique is applicable to nearly any model space with a prespecified gauge group. We provide a generic procedure by which a suitable graph grammar can be developed for any BSM model that features user-specified symmetry groups and a finite number of different possible particle species, the use of which is applicable to a variety of machine learning tasks over the actions of BSM theories beyond our particular reinforcement learning use case. As a proof of concept, we construct the graph grammar for theories with vectorlike leptons that may or may not be charged under a dark U ( 1 ) group, inspired by portal matter extensions of the sub-GeV vector portal/kinetic mixing simplified dark matter models. We then use this graph grammar to create a reinforcement learning environment tasked with creating models with these vectorlike leptons that are consistent with a list of a variety of precision observables. The reinforcement learning agent succeeds in developing models that can address the observed muon anomalous magnetic moment discrepancy while remaining consistent with flavor violation and electroweak precision observables, including both constructions that have previously been studied as well as new models that have not, to our knowledge, previously been identified. By inspecting the resulting ensembles of models that the agent produces and experimenting with different configurations for our reinforcement learning environment and graph grammar, we also infer various lessons about the development of these environments that can be transferable to reinforcement learning scans of more complicated model spaces and comment on future directions for the development of this technique into a more mature tool. Published by the American Physical Society 2025

Wojcik, George N.↗
DOE OSTI2024

Advancing South American Water and Climate Science Through Multi-Decadal Convection-Permitting Modeling

The South America Affinity Group (SAAG) was established in early 2019 by the National Center for Atmospheric Research (NCAR) Water Systems Program as a community effort focused on improving hydroclimate science over South America. SAAG supports large research efforts such as the ANDEX Regional Hydroclimate Program as well as individual research groups. The group started with a dozen members and quickly grew to over 100 participants from more than ten countries. For the past four years, the SAAG has been meeting online every two weeks and has organized sessions at international conferences such as the American Geophysical Union Fall Meeting and the Convection-Permitting Climate Workshop. At the core of the SAAG effort are two multi-decadal convection permitting (CP) model simulations with 4-km grid spacing for historical and future climates over the South American continent. Additionally, a major observational data collection effort has been undertaken, including in-situ station data from South American meteorological and water services, gridded products, satellite-based observations, and field campaign data. In conclusion, this article discusses the research needs and scientific goals that drive this community of scientists with diverse backgrounds and interests.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

High-Performance/-Precision/-Z(HPPZ) Scintillator Grids via Advanced Electrochemistry. Phase I – Project # 20210572MFR- Mid year review [Slides]

Scintillation grids with improved imaging resolution in time and space, are required for future mission needs at various facilities (pRad user station, LANSCE, DARHT, Scorpius etc). Current technologies use inorganic crystal scintillators, which are positioned within a high-Z scintillator septa. Dense and high-Z materials are optimal for gamma-ray detection making them promising candidates for development of high -performance/-precision/-Z (HPPZ) scintillator grids. The current resolution of standard chemical etching and fabrication processes of high-Z materials is very low, leading to undesired undercutting and ultimately reducing crystal performance efficiency. Goals are to: Perform initial feasibility studies with the aim of producing complex parts for applications with difficult-to-process high-Z material; Use of pulse and pulse-reverse electrochemical methods on additive approaches to produce high-precision Au and Re scintillator grids at a small scale; and, Follow up in Phase II with the delivery of a large-scale scintillator grid of the best material candidate with unprecedented properties for LANL needs determined in Phase I.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Numerical Codes for the DESC-LSST Analysis Pipeline: Core Cosmology Library Standard Modules and Beyond wCDM Modules (Final Technical Report)

The overall objective of the project is to investigate and develop specific software modules and analysis components for the software pipeline of LSST Dark Energy Science Collaboration (DESC). Following the key projects of DESC Science Roadmap (SRM), we will write and test computer codes for the Core Cosmology Library (CCL) in order to complete its modules, functionalities, and interface to work with the analysis pipelines from the five science probes of DESC (parts of SRM deliverables CX4.2TJP, CX6.2CS). We will also code modules for CCL to test models beyond w-Cold-Dark-Matter (wCDM) and modification to gravity (MG). Interfaces for MG models will also be developed for the TJPCOSMO software which is the main pipeline of the Theory and Joint Probe (TJP) working group (deliverable TJP2.3). In order to use the full power of LSST data to constrain MG models, we will also work on constraints from nonlinear regime by running and analyzing MG N-Body simulations using a Parameterized-Post-Friedmann framework into the Gadget-2 simulation package (deliverable TJP2.2). Preliminary results for the simulations were obtained in the past. In collaboration with other DESC groups, we plan to make these simulations feedable to cosmic emulators that are practical for likelihood analyzes (deliverable TJP2.2, parts of CX6.2CS). We will also modify and integrate our current codes for consistency tests between data sets and probes into the pipeline (parts of deliverables CX8.2TJP, TJP2.3). We understand that other groups will contribute to some of these objectives but our team will focus and collaborate with others on the particular part of testing MG and models beyond wCDM and refine the DESC pipeline for this purpose. PI has been coordinating his work with the TJP and CS working groups and the DESC management team. PI is a full member of DESC since June 2013. He and his students have been contributing to LSST-DESC activities and work including TJP telecons, collaboration meetings, hack-weeks, and workshops. PI chaired or co-chaired sessions at collaboration meetings and hack-weeks about testing gravity and models beyond wCDM using LSST. He is coordinating the TJP2 projects for testing models beyond wCDM including the writing of DESC-research-note, development of code for pipeline, and N-Body simulations for MG and beyond wCDM models testable with LSST analyses. As stressed in the DESC white paper, SRM, and P5 report, one of the important questions in understanding cosmic acceleration and dark energy is to be able to distinguish whether the acceleration is due to a dark energy component in the universe or a modification to gravity. Answering these questions will have a significant impact on the question of cosmic acceleration and dark energy. The methods that we will use include analytical work, numerical code, and N-Body simulations. A first approach that that we will use consists of using growth rate parameters that enter the perturbed dynamics equations. These parameters take distinctive values for distinct gravity theories and have potential to distinguish between Dark Energy and Modified Gravity. The second method is to look for inconsistencies in Dark Energy parameter spaces using specific combinations of cosmological data sets. Our investigation addresses the Dark Energy problem that is relevant to the mission of the HEP program to understand how our universe works at its most fundamental level. It will allow us to make progress on the HEP mission to explore the nature of Dark Energy and the basic nature of space and time using future surveys such as LSST. The investigation supports the DOE HEP program Cosmic Frontier as it will contribute to the study and understanding of dark energy and fundamental properties of the universe. The investigation contributes directly to LSST-DESC key projects and their deliverables as described in the Science Road-map document to build analysis pipeline and to test dark energy and beyond wCDM models using LSST.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Hybrid Distributed Wind and Battery Energy Storage Systems

This document is a literature review of battery coupled distributed wind applications, including but not limited to fully DC-based power systems, the conceptual value of co-located wind and storage assets, and black start capabilities. This report will serves as a baseline reference document for MIRACL hybrids system research and to identify opportunities for future research in this space.

17 WIND ENERGY↗
DOE OSTI2022

Ontario International Airport Fleet Electrification Blueprint: Zero-Emission Vehicle Technology Assessment for Energy Optimization [Slides]

Ontario International Airport Authority (OIAA)'s Electric Vehicle (EV) Blueprint project presentation focuses on the possibilities for fleet electrification, including medium heavy duty charging and hydrogen refueling and their associated planning, infrastructure, operation, and maintenance options. This report includes detailed list of available electric ground support equipment (GSE), description of NREL tools for EV infrastructure design and optimization, and analyses of the current fleet and the potential grid impacts of electrification. Key recommendations are made in regard to simulation-based and in-depth system analyses to identify optimal charging infrastructure and long-term grid stability, and to ensure that the selected station architecture will provide enough space and capacity for future expansion and resiliency.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Searching for dark radiation at the LHC

There is an interesting connection between early universe cosmology and searches for long-lived particles (LLPs) at the LHC. Light particles can be produced via freeze-in and act as dark radiation, contributing to the effective number of relativistic species $N_\text{eff}$. The parameter space of interest for future CMB missions points to LLP decay lengths in the mm to cm range. These decay lengths lie at the boundary between prompt and displaced signatures at the LHC and can be comprehensively explored only by combining searches for both. We consider a model where the LLP decays into a charged lepton and a (nearly) massless invisible particle. By reinterpreting searches for promptly decaying sleptons and for displaced leptons at both ATLAS and CMS we can then directly compare LHC exclusions with cosmological observables. Our results show how in this model the target value of CMB-S4 is already excluded by current LHC searches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗