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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Projected changes in cross-equatorial northerly surges and their hydrological impacts in the near future

Recent decades have witnessed unprecedented extreme precipitation and catastrophic flooding in some of the most populated regions in Southeast Asia during boreal winter. These extreme events are often influenced by the cross-equatorial northerly surge (CENS), characterized by a strengthening of northerly moist monsoon winds south of the equator in the western Maritime Continent. However, the potential future changes in CENS and its hydrological impacts remain underexplored. Here, using an ensemble of high-resolution climate model simulations (CMIP6 HighResMIP), we show that the regional impacts of CENS on the intensity and frequency of extreme precipitation events are projected to significantly increase in the near future (2030–2050), particularly over the adjacent coastal regions of southern Indonesia and northwestern Australia. More specifically, the risk of CENS-related extreme precipitation is projected to increase by up to 39 ± 1.2% relative to the seasonal probability, despite no apparent changes in the CENS characteristics in the near future. Such stronger impact is attributed to the enhanced moistening efficiency and moist static instability due to a more humid and warmer environment, which leads to more intense CENS convection. Our results suggest the need for effective monitoring and disaster managements to respond to the increasing severity of such events in the near future.

Climate sciences↗
DOE OSTI2024

Updates to the ATLAS Data Carousel Project

The High Luminosity upgrade to the LHC (HL-LHC) is expected to deliver scientific data at the multi-exabyte scale. In order to address this unprecedented data storage challenge, the ATLAS experiment launched the Data Carousel project in 2018. Data Carousel is a tape-driven workflow whereby bulk production campaigns with input data resident on tape are executed by staging and promptly processing a sliding window to disk buffer such that only a small fraction of inputs are pinned on disk at any one time. Data Carousel is now in production for ATLAS in Run3. In this paper, we provide updates on recent Data Carousel R&D projects, including data-on-demand and tape smart writing. Data-on-demand removes from disk data that has not been accessed for a predefined period, when users request them, they will be either staged from tape or recreated by following the original production steps. Tape smart writing employs intelligent algorithms for file placement on tape in order to retrieve data back more efficiently, which is our long term strategy to achieve optimal tape usage in Data Carousel.

42 ENGINEERING↗
DOE OSTI2026

Project 8 apparatus for cyclotron radiation emission spectroscopy with 83m Kr and tritium

Cyclotron Radiation Emission Spectroscopy (CRES) is a novel technique for the precise measurement of relativistic electron energy. This technique is being employed by the Project 8 collaboration for measuring a high-precision tritium beta decay spectrum to perform a frequency-based measurement of the neutrino mass. In this work, we describe the Project 8 Phase II apparatus, used for the detection of the CRES signal from the conversion electrons of 83m Kr and the first CRES measurement of the beta-decay spectrum of molecular tritium.

Neutrino detectors↗
DOE OSTI2024

Localization of infrasonic sources via Bayesian back projection

SUMMARY A Bayesian framework is investigated for event-specific localization of infrasonic sources using back projection ray tracing. Direction-of-arrival information from array-based detection analysis is used to initialize a back projection ray path originating from the detecting array location and quantifying propagation characteristics from hypothetical source locations. The Fisher statistic, computed from the array’s beam coherence, is mapped into uncertainty in the launch angles of the ray path. Auxiliary parameters previously introduced for solving the Transport equation to compute geometric spreading along ray paths are used to map uncertainty in the ray launch angles into spatial and temporal uncertainties in the ray path. An atmospheric ensemble approach is applied to account for atmospheric uncertainty, and the relation between uncertainties in the atmospheric state and confidence in estimated localization are evaluated using several ensembles with specified variances. The method is evaluated using a synthetic event in the western United States constructed via forward propagation simulations as well as a single-station, multi-arrival detection from a surface explosion in the western United States. Localization results using this event-specific approach are more accurate and exhibit improved precision than existing Bayesian localization methods that leverage generalized, pre-computed propagation statistics.

58 GEOSCIENCES↗
DOE OSTI2024

Predicted range expansion of Prostephanus truncatus (Coleoptera: Bostrichidae) under projected climate change scenarios

Abstract The larger grain borer (Prostephanus truncatus [Horn] [Coleoptera: Bostrichidae]) is a wood-boring insect native to Central America and adapted to stored maize and cassava. It was accidentally introduced to Tanzania and became a pest across central Africa. Unlike many grain pests, P. truncatus populations can establish and move within forests. Consequently, novel infestations can occur without human influence. The objectives of our study were to (i) develop an updated current suitability projection for P. truncatus, (ii) assess its potential future distribution under different climate change scenarios, and (iii) identify climate variables that best inform the model. We used WALLACE and MaxEnt to predict potential global distribution by incorporating bioclimatic variables and occurrence records. Future models were projected for 2050 and 2070 with Representative Concentration Pathways (RCPs) 2.6 (low change) and 8.5 (high change). Distribution was most limited by high precipitation and cold temperatures. Globally, highly suitable areas (> 75%) primarily occurred along coastal and equatorial regions with novel areas in northern South America, India, southeastern Asia, Indonesia, and the Philippines, totaling 7% under current conditions. Highly suitable areas at RCPs 2.6 and 8.5 are estimated to increase to 12% and 15%, respectively, by 2050 and increase to 19% in 2070 under RCP 8.5. Centroids of highly suitable areas show distribution centers moving more inshore and away from the equator. Notably, the result is a range expansion, not a shift. Results can be used to decrease biosecurity risks through more spatially explicit and timely surveillance programs for targeting the exclusion of this pest.

Entomology↗
DOE OSTI2024

Systematic study of projection biases in the weak lensing analysis of cosmic shear and the combination of galaxy clustering and galaxy-galaxy lensing

This paper presents the results of a systematic study of projection biases in the weak lensing analysis of cosmic shear and the combination of galaxy clustering and galaxy-galaxy lensing using data collected during the first year of running the Dark Energy Survey experiment. The study uses Lambda cold dark matter ( Λ CDM ) as the cosmological model and two-point correlation functions for the weak lensing (WL) analysis. The results in this paper show that, independent of the WL analysis, projection biases of more than 1 σ exist and are a function of the position of the true values of the parameters h , n s , Ω b , and Ω ν h 2 with respect to their prior probabilities. For cosmic shear, and the combination of galaxy clustering and galaxy-galaxy lensing, this study shows that the coverage probability of the 68.27% credible intervals ranges from as high as 93% to as low as 16% and that these credible intervals are inflated, on average, by 29% for cosmic shear and 20% for the combination of galaxy clustering and galaxy-galaxy lensing. The results of the study also show that, in six out of nine tested cases, the reduction in error bars obtained by transforming credible intervals into confidence intervals is equivalent to an increase in the amount of data by a factor of 3.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Partial-wave projection of relativistic three-body amplitudes

We derive the integral equations for partial-wave projected three-body scattering amplitudes, starting from the integral equations for three-body amplitudes developed for lattice QCD analyses. The results, which hold for generic three-body systems of spinless particles, build upon the recently derived partial-wave projected one-particle exchange, a primary component of the relativistic framework proven to satisfy 𝑆 matrix unitarity. We derive simplified expressions for factorizable short-distance interactions, 𝒦 3 , in two equivalent formalisms—one symmetric under particle interchange and one asymmetric. For the asymmetric case, we offer parametrizations useful for amplitude analysis. Finally, we examine toy models for 3⁢𝜋 systems at unphysically heavy pion masses with total isospins 0, 1, and 2.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Denoising of imaginary time response functions with Hankel projections

Imaginary-time response functions of finite-temperature quantum systems are often obtained with methods that exhibit stochastic or systematic errors. Reducing these errors comes at a large computational cost—in quantum Monte Carlo simulations, the reduction of noise by a factor of two incurs a simulation cost of a factor of four. In this paper, we relate certain imaginary-time response functions to an inner product on the space of linear operators on Fock space. We then show that data with noise typically does not respect the positive definiteness of its associated Gramian. The Gramian has the structure of a Hankel matrix. As a method for denoising noisy data, we introduce an alternating projection algorithm that finds the closest positive definite Hankel matrix consistent with noisy data. We test our methodology at the example of fermion Green's functions for continuous-time quantum Monte Carlo data and show remarkable improvements of the error, reducing noise by a factor of up to 20 in practical examples. We argue that Hankel projections should be used whenever finite-temperature imaginary-time data of response functions with errors is analyzed, be it in the context of quantum Monte Carlo, quantum computing, or in approximate semianalytic methodologies. Published by the American Physical Society 2024

Yu, Yang (ORCID:0000000186178878)↗
DOE OSTI2024

Experiments and Project-Based Enhancements for STEM Learning

Motivating K-12 students to pursue careers in science, technology, engineering, and mathematics (STEM) is an effort that requires consistent engagement. Throughout the K-12 student timeline, STEM educators need to continuously pivot their teaching and update their educational materials to motivate the next generation of students. Once students begin their undergraduate education, university professors need to encourage them to consider pursuing graduate studies to ensure that a qualified future workforce can be developed for research and teaching. In this paper, we present our work on developing STEM materials for K-12 student engagement. Our K-12 materials target the grid integration of hydrogen assets that are suitable to engage students in the classroom. Our undergraduate materials target hands-on projects and collaboration with industry to connect classroom learning with real-world applications and needs in renewable energy. Our work leverages available open-source models and tools to create projects for undergraduate students and motivate their interest in pursuing research topics in graduate-level education.

ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

An integrated integral projection model ( IPM 2 ) to disentangle size‐structured harvest and natural mortality

Abstract Body size is one of the most important traits governing individual‐level demographic rates and modulating population‐level processes. Multiple size‐dependent demographic rates can simultaneously change population structure, so distinguishing their individual contributions to overall population dynamics remains a challenge. Disentangling size‐dependent harvest rates from other demographic rates is critical for assessing the impact of removal on populations of invasive species. Inference about invasive populations can be difficult, however, as observations are often collected opportunistically as part of removal programs, rather than experimentally designed. Yet accurate inference is essential for understanding the feasibility of population suppression and optimising management decisions. We develop an integrated integral projection model (IPM 2 ) that leverages the strengths of the integrated population model and integral projection model to enable inference about complex, size‐structured demographic rates from imperfect observations. We apply the IPM 2 in the context of invasive European green crab ( Carcinus maenas ), a species for which individual body size strongly regulates both the observation‐generating process and latent, population dynamics. The IPM 2 facilitates the distinct estimation of green crab size‐structured harvest and natural mortality rates, parameters for which no explicit data is collected and that are unidentifiable in component datasets of the integrated population model. The model represents how the green crab population changes over time, providing the first estimates of size‐structured abundance of this high‐priority species. By forecasting the stable size distribution and equilibrium population size under varying removal efforts, we demonstrate that extremely high levels of removal effort can reduce the equilibrium green crab population size. Yet these high mortality rates also shift the stable size distribution and increase the equilibrium abundance of smaller crabs, since size‐selective removal alters intraspecific interactions. The ecological outcome of this shift in size structure will be variable, as green crab size modulates only some of its interactions with other species. These results highlight the value of the IPM 2 framework for inferring complex population dynamics with information needs that outpace information in individual observational datasets, providing a path forward for accurate assessment of conservation programs.

Keller, Abigail G. [Department of Environment Scie↗
DOE OSTI2025

Laser system design and critical technologies for the NSF OPAL project

The three-year NSF OPAL project is completing the preliminary design of a 2 x 25-PW all-optical parametric chirped-pulse amplification (OPCPA) system capable of delivering 500-J, 20-fs pulses. The design includes two Alpha beamlines that can be co-timed and pointed into two experimental areas for high-intensity research in several configurations. Additionally, a more flexible 2-PW Beta beam can be used in place of one Alpha beam to allow a wider range of focusing geometries and synchronized electron-beam generation for diverse experimental applications. Here, building on the development of the mid-scale MTW-OPAL prototype system, the NSF OPAL project also focuses on advancing essential technologies, such as large-grating fabrication techniques and actively-cooled disk amplifiers.

42 ENGINEERING↗
DOE OSTI2024

Demonstration of neutron identification in neutrino interactions in the MicroBooNE liquid argon time projection chamber

A significant challenge in measurements of neutrino oscillations is reconstructing the incoming neutrino energies. While modern fully-active tracking calorimeters such as liquid argon time projection chambers in principle allow the measurement of all final state particles above some detection threshold, undetected neutrons remain a considerable source of missing energy with little to no data constraining their production rates and kinematics. We present the first demonstration of tagging neutrino-induced neutrons in liquid argon time projection chambers using secondary protons emitted from neutron-argon interactions in the MicroBooNE detector. We describe the method developed to identify neutrino-induced neutrons and demonstrate its performance using neutrons produced in muon-neutrino charged current interactions. The method is validated using a small subset of MicroBooNE’s total dataset. The selection yields a sample with 60% of selected tracks corresponding to neutron-induced secondary protons. At this purity, the integrated efficiency is 8.4% for neutrons that produce a detectable proton.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Downscaled Daily 1 km Climate Data (NEX-GDDP-CMIP6) for Southeast Texas. Full ensemble of downscaled CMIP6 climate projections at 1 km daily resolution.

For the SETx-UIFL, the daily NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP-CMIP6) dataset climate projections were downscaled from approximately 27 km to 1 km. The SETx dataset provides very high-resolution climate data for the historical period (1950–2014) and future scenarios derived from CMIP6 global models under the four Tier 1 Shared Socioeconomic Pathways (SSPs 1.26, 2.45, 3.70, and 5.85), developed for the IPCC Sixth Assessment Report. A subset of ten NEX-GDDP-CMIP6 models was selected to represent a balance of model families, climate sensitivities, and availability across scenarios, ensuring a diverse and reliable ensemble for regional analysis. Selected models: BCC-CSM2-MR, CESM2, CMCC-ESM2, CNRM-ESM2-1, EC-Earth3, FGOALS-g3, GFDL-CM4, MPI-ESM1-2-HR, MRI-ESM2-0, NorESM2-MM. Daily variables downscaled include tasmax, tasmin, tas, pr, hurs, huss, rsds, rlds, and sfcWind.

Persad, Geeta↗
DOE OSTI2024

AMReX and pyAMReX: Looking beyond the exascale computing project

AMReX is a software framework for the development of block-structured mesh applications with adaptive mesh refinement (AMR). AMReX was initially developed and supported by the AMReX Co-Design Center as part of the U.S. DOE Exascale Computing Project (ECP), and is continuing to grow post-ECP. In addition to adding new functionality and performance improvements to the core AMReX framework, we have also developed a Python binding, pyAMReX, that provides a bridge between AMReX-based application codes and the data science ecosystem. pyAMReX provides zero-copy application GPU data access for AI/ML, in situ analysis and application coupling, and enables rapid, massively parallel prototyping. In this paper we review the overall functionality of AMReX and pyAMReX, focusing on new developments, new functionality, and optimizations of key operations. We also summarize capabilities of ECP projects that used AMReX and provide an overview of new, non-ECP applications.

Myers, Andrew↗
DOE OSTI2025

Artificial Intelligence-Enhanced CMIP6 Climate Projections Across the Conterminous United States

This dataset comprises high-resolution climate projections at 1/24 degree grid (~4km) over the conterminous United States (CONUS) based on ten Global Climate Models (GCMs) that are part of the Coupled Models Intercomparison Project phase 6 (CMIP6). The CMIP6 GCMs are downscaled using two artificial intelligence (AI) techniques, primarily based on the computer vision approach called super-resolution. We train two separate networks: super-resolution convolutional neural network (SRCNN) and super-resolution generative adversarial network (SRGAN). The networks are trained using Daymet observations, originally available at a 1 km resolution. For training purposes, the Daymet data is interpolated to 1/24 degree (~4km), 0.25 degree and 1 degree, which serve as high, intermediate and low-resolution inputs respectively. For each of the SRCNN and SRGAN network, we use a two-step resolution enhancement, the first step generates 4x refinement from 1 degree to 0.25 degree and the second step generates 6x refinement from 0.25 degree to 1/24 degree (~4km). We downscale daily scale precipitation, maximum temperature and minimum temperature for the six CMIP6 GCMs for 1980 to 2019 in the historical period and 2020 to 2059 in the near-term future under the shared socioeconomic pathway 585 and 245 (SSP585 and SSP245) emission scenarios. We also perform double bias-correction with Daymet observations using a quantile mapping approach, first for GCMs prior to making predictions at 1 degree grid and second after making final predictions at ~4km.

13 HYDRO ENERGY↗
DOE OSTI2024

Utah FORGE Project 3-2417: Meteorological Data During 2024 Stimulation

This preliminary data archive includes meteorological data recorded at the Utah FORGE facility over the period of time including the 16A/16B stimulation activities, largely March/April/May of 2024. This information may prove useful for understanding seismic and other instrumentation response during monitoring. The bulk of relevant stimulation activities occurred between March 25th and April 28th, 2024 and the included files span this period. All sensors were installed at the 78-16 pad and hence reflect weather state at the site. This dataset was acquired by the FOGMORE R&D project (Fiber Optic MOnitoring for Reservoir Evolution), Utah FORGE R&D Project 3-2417.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Utah FORGE Project 3-2417: Meteorological Data During 2023 Completion/Circulation

This preliminary data archive includes meteorological data recorded at the Utah FORGE facility over the period of time including the completion/cementing of well 78-16B and the initial 2023 circulation test, largely occurring in June/July/August of 2023. This information may prove useful for understanding seismic and other instrumentation responses during these activities. The meteorological station was installed June 23rd, 2023 during drilling; the circulation test occurred in mid July of 2023 (July 4-19). The included files span this period. All sensors were installed at the 16 pad and hence reflect weather state at the site. This dataset was acquired by the FOGMORE R&D project (Fiber Optic MOnitoring for Reservoir Evolution), Utah FORGE R&D Project 3-2417.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Utah FORGE Project 3-2417: DAS Microseismic Event Catalog from the 16A/16B Circulation Test, 2023

This preliminary data archive includes the relocated microseismic event catalog, 1D velocity model, and methods report from DAS acquisition conducted during the Well 16A and 16B circulation test (July 19th and 20th, 2023) at Utah FORGE. The methods report describes all processing steps, including real-time event detection, hierarchical clustering, joint velocity/hypocenter inversion, and relocation. The resulting work is accepted and will be presented at IMAGE 2024. This dataset was acquired by the FOGMORE R&D project (Fiber Optic MOnitoring for Reservoir Evolution), Utah FORGE R&D Project 3-2417.

15 GEOTHERMAL ENERGY↗