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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Neutron Characterization of 3D Printed Gas Turbine Alloy With Internal Cooling Structure

The objective of this research work is to investigate the residual strains induced by the presence of a exit hole and internal hollow geometry present in a 3D printed IN718 similar to that seen in a gas turbine blade. The specimens were manufactured with an internal hollow structure that ended with an exit hole, and fabricated by direct metal laser sintering additive manufacturing technique. Using this technique, metal powder was melted by a laser source and rapidly cooled to form the part layer by layer. Rapid heating and cooling generate large thermal gradients and residual stresses in the 3D printed material. To be aligned with industry standards, specimens were heat-treated to relieve most of the residual stresses as well as to investigate whether IN718 still preserved a nonhomogeneous stress state after the thermal treatment. Roughness and microstructure analysis was performed to understand the heat-treated sample properties. To investigate the volumetric residual strain, the neutron diffraction technique was used with a definite neutron wavelength. Bragg’s law was used to determine lattice spacing. Interplanar lattice spacing and stress-free state lattice spacings were measured to calculate the strains. Residual strains were measured in the x and y direction to understand the impact of the presence of a exit hole and internal hollow geometry. The results of volumetric residual strain in the x and y directions showed no significant variations in the distribution of the strain due to the presence of a hollow structure as well as the exit hole. Overall, no significant stress concentration was observed in the heat treated sample. Sample geometry, instrumentation for neutron diffraction, and material properties are discussed in detail in this paper.

Raju, Nandhini↗
DOE OSTI2020

Status on 12 C + 12 C fusion at deep subbarrier energies: impact of resonances on astrophysical S * factors

Since the discovery of molecular resonances in 12 C + 12 C in the early sixties a great deal of research work has been undertaken to study α-clustering and resonant effects of the fusion process at sub-Coulomb barrier energies. The modified astrophysical S* factors of 12 C + 12 C fusion have been extracted from direct fusion measurements at deep sub-barrier energies near the Gamow window. They were also obtained by the indirect Trojan horse method (THM). A comparison of direct measurements and the THM, which elucidates problems in the analysis of the THM, is discussed in this Letter to the Editor.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

ASAP: Automatic Synthesis of Area-Efficient and Precision-Aware CGRAs

Coarse-grained reconfigurable accelerators (CGRAs) are a promising accelerator design choice that strikes a balance between performance and adaptability to different computing patterns across various applications domains. Designing a CGRA for a specific application domain involves enormous software/hardware engineering effort. Recent research works explore loop transformations, functional unit types, network topology, and memory size to identify optimal CGRA designs given a set of kernels from a specific application do- main. Unfortunately, the impact of functional units with different precision support has rarely been investigated. To address this gap, we propose ASAP – a hardware/software co-design framework that automatically identifies and synthesizes optimal precision-aware CGRA for a set of applications of interest. Our evaluation shows that ASAP generates specialized designs 3.2×, 4.21×, and 5.8× more efficient (in terms of performance per unit of energy or area) than non-specialized homogeneous CGRAs, for the scientific computing, embedded, and edge machine learning domains, respectively, with limited accuracy loss. Moreover, ASAP provides more efficient designs than other state-of-the-art synthesis frameworks for specialized CGRAs.

artificial intelligence↗
DOE OSTI2025

Accuracy-Based Annotation Quality Score (ABAQS) v1.0

Assessing genome annotation quality is crucial for downstream analyses, but current methods are inadequate for eukaryotes. We present Accuracy-Based Annotation Quality Score (ABAQS), a novel, minimal-data-driven method that comprehensively assesses annotation quality. ABAQS evaluates multiple factors, including genome completeness, gene model validity, and protein profile accuracy, outperforming other metrics like BUSCO and PSAURON. We applied ABAQS to over 2500 eukaryotic genomes and showed its robustness and effectiveness in evaluating genome annotation quality, making it a valuable tool for researchers working with genomic data. ABAQS reveals significant variation in annotation quality and highlights the importance of filtering in improving annotation quality and accuracy.

Haridas, Sajeet [Lawrence Berkeley National Labora↗
DOE OSTI2026

pypolymix

SAND2026-16700O Pypolymix builds stochastic surrogate models using a lightweight Python library. Researchers working with large-scale scientific models can use it to enhance optimization and uncertainty quantification studies. Pypolymix enables the efficient construction of surrogate models and improves analysis and performance of complex simulations. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

SciDAC↗
DOE OSTI2023

Scoping review of Culex mosquito life history trait heterogeneity in response to temperature

Abstract Background Mosquitoes in the genus Culex are primary vectors in the US for West Nile virus (WNV) and other arboviruses. Climatic drivers such as temperature have differential effects on species-specific changes in mosquito range, distribution, and abundance, posing challenges for population modeling, disease forecasting, and subsequent public health decisions. Understanding these differences in underlying biological dynamics is crucial in the face of climate change. Methods We collected empirical data on thermal response for immature development rate, egg viability, oviposition, survival to adulthood, and adult lifespan for Culex pipiens, Cx. quinquefasciatus, Cx. tarsalis , and Cx. restuans from existing literature according to the PRISMA scoping review guidelines. Results We observed linear relationships with temperature for development rate and lifespan, and nonlinear relationships for survival and egg viability, with underlying variation between species. Optimal ranges and critical minima and maxima also appeared varied. To illustrate how model output can change with experimental input data from individual Culex species, we applied a modified equation for temperature-dependent mosquito type reproduction number for endemic spread of WNV among mosquitoes and observed different effects. Conclusions Current models often input theoretical parameters estimated from a single vector species; we show the need to implement the real-world heterogeneity in thermal response between species and present a useful data resource for researchers working toward that goal. Graphical Abstract

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Computational Analysis of Water Film Thickness During Rain Events for Assessing Hydroplaning Risk, Part 1: Nearly Smooth Road Surfaces

In the research work reported here, both two- and three-dimensional computational fluid dynamics (CFD) analysis was used to investigate modern road geometries that were not frequently encountered in the latter half of the 20th century but are much more common today. The relation of newer road geometries to the water film thickness that develops on travel lanes was a major focus of this work.

42 ENGINEERING↗
DOE OSTI2020

Macro-physical Properties of Shallow Cumulus from Integrated ARM Observations (Final Report)

Fair-weather shallow cumuli (ShCu) play an important role in many climate-related processes. Irregular geometry of ShCu and their strong temporal and spatial variability make it challenging to observe ShCu holistically and to represent them correctly in climate models. To improve ShCu parameterizations, information on both vertically and horizontally resolved cloud properties is required. Commonly, the vertically resolved cloud properties are provided by zenith pointing lidar-radar observations with a very narrow field of view (FOV). Thus, these “pencil-beam” properties may not be representative of a larger surrounding area. Limited number of areal-averaged cloud properties, such as fractional sky cover (FSC), are offered typically by wide-FOV observations. The main goal of our project was to integrate advantages of the narrow-FOV (vertical structure of clouds) and wide-FOV (spatial arrangement of clouds) observations for an improved characterization of single-layer ShCu observed at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site for an 18-yr period (2000-2017). There are four major accomplishments of our project, First, an updated operational cloud classification for days with ShCu has been suggested and evaluated through a detailed comparison with the manually curated records. Our classification extends successfully the latest ARM cloud type Value Added Product (VAP) based on the Active Remote Sensing of Clouds (ARSCL) cloud product by incorporating both cloud fraction (CF) provided by narrow-FOV ceilometer data and FSC from wide-FOV images offered by a Total Sky Imager (TSI). Moreover, our classification allows one to identify impact of instrumentation changes at the SGP site, namely the transition to KAZRARSCL with the updated cloud radar, on the identification of periods with single-layer ShCu. Second, a new approach that resolves cloud area distributions for a given region (up to 4x4 km 2 ) has been suggested and cloud equivalent diameters (CEDs) have been estimated for the first time. These estimations have been performed over a wide range of cloud sizes (about 0.01–3.5 km) with high temporal resolution (30s) using wide-FOV TSI images and cloud base height (CBH) provided by complementary narrow-FOV lidar measurements. Our simple and computationally inexpensive approach offers a previously unavailable dataset for process studies in the convective boundary layer and evaluation of ShCu parameterizations in cloud-resolving models. Third, a long-term integrated record of ShCu macrophysical properties has been developed. The developed record represents the longest available compilation of events with ShCu and includes (i) a novel visualization of the spatial variability in cloud cover both along- and across-wind directions, (ii) updated estimates of narrow-FOV CF and wide-FOV FSC, (iii) updated narrow-FOV CBH, and (iv) complementary data, such as wind speed and direction from the 915-MHz Radar Wind Profiler (RWP) data. The developed record has been used successfully to assess conventional observational estimates of cloud cover and their sensitivity to the following two factors: (i) instrument-dependent cloud detection and data merging criteria and (ii) FOV configuration. Fourth, co-variability of the ShCu macrophysical properties and environmental parameters has been analyzed for a 3-yr period (2016-2018). Our initial analysis includes diurnal changes of FSCs obtained for clouds with small, moderate and large CEDs and several environmental parameters, such as lifted condensation level (LCL) and mixed layer height (zi). Preliminary results of our analysis suggest that the horizontal extent of ShCu is controlled substantially by the sign and magnitude of difference between these two parameters (zi-LCL): the CED tends to grow with increase of this difference (zi exceeds LCL). We have initiated relationships between the ShCu and key atmospheric parameters that control both the development and evolution of ShCu using our new data product, which combines effectively the advantages of narrow-FOV data offered by zenith pointing cloud radars and lidars and wide-FOV TSI images. While the latest instrumentation at the ARM sites may address these challenging relationships in the future, we believe that the historical ARM data at the SGP site has not yet been fully utilized. Overall, our data product can be used by researchers working on a wide range of climate-related projects. These projects may include (i) a comprehensive evaluation of outputs from the Large-Eddy Simulation (LES) and single-column models for their future improvement, (ii) the representativeness of “short-period” results obtained from the previous model and observational studies and (iii) the planning of future field campaigns with focus on improved understanding of the diurnal cycle of cumulus convection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Formation of Aerosol Nanoparticles by Gas-Phase Hydrolysis Reaction of Uranium Hexafluoride

The aerosol physics of uranyl particle formation has been addressed in this research using advanced aerosol instrumentation and an aerosol dynamics model. Based on the research works, we conclude that the formation and growth of aerosol particles by gas-phase UF6 hydrolysis strongly depends on the availability of water molecules in our reactor conditions. The total number concentration of the UO 2 F 2 particulate material that could be produced in the hydrolysis reaction is also regulated primarily by the availability of water molecule concentration. The higher the water molecule concentration, the higher the number and the larger the size of UO 2 F 2 aerosol particles that could be produced in a reactor custom-built at ORNL. Although the aerosol reactor was enabling the study of particle formation kinetics, the instrumentation was still insufficient in characterizing the chemical composition of the produced particles as well as the time-dependent evolution of the particulate species. The temporal evolution could impact the eventual fate of the particles upon release to the environment (i.e., the physio-chemical transformation, transport, and removal). On uranyl particle formation kinetics, we found that the growth rates of aerosol particles appeared to approach a single number in the range of 0.05 ± 0.03 - 0.08 ± 0.04 nm/s, statistically, as the ω value becomes smaller than 1. The size of primary particles from the UF6 hydrolysis at water-deprived condition was estimated to be 3.6 ± 0.4 nm; the higher the availability of water molecules, the larger the primary particles. The ability to precisely control the availability of water molecules in the reaction could lead to the production of nearly monodispersed aerosol particles. In other words, the result suggests that one can precisely manipulate the size of UO 2 F 2 aerosol particles by controlling the water vapor availability and interaction of water molecules with U F6 in the reaction. This finding has significant implications in the engineering manufacturing of fuel powder materials and possibly to future development and deployment of an environmental sampling apparatus.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

UA'(1): The search for low-mass dark matter in liquid xenon / Infrared Light for Liquid Xenon TPCs

Liquid xenon-based time projection chambers are used in a variety of applications spanning from the search for dark matter or signals from coherent neutrino-nucleus scattering, to detectors used in medicine and for nuclear non-proliferation. Extending the useful energy range of these detectors down to lower energies will prove extremely useful for such applications. However, various sources of single- and few-electron backgrounds limit the utility of experiments such as LZ and XENONnT to searches of lighter dark matter articles in the MeV mass range. These same backgrounds also limit their utility to measure signals from coherent neutrino-nucleus scattering of solar boron-8 neutrinos and Galactic supernovae. This research worked on multiple mitigation strategies to reduce these backgrounds, through improved xenon purity, infrared irradiation, and an improved theoretical understanding. Multiple dedicated liquid xenon setups were built to execute those tests, and data was successfully taken. Liquid xenon purity was shown to have an important impact, but infrared irradiation did not reduce these backgrounds.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

A Hardware and Software Co-design Framework for Energy Efficient Neuromorphic Systems

Neuromorphic systems can be realized by a variety of algorithms and architectures. A common understanding is that spiking neuromorphic designs, which encode information into spatio-temporal spiking events, are both a biologically-accurate and efficient way of processing information. However, representing the information through timing relationships induces sophisticated circuit designs in traditional CMOS-based implementations. In recent years, high-capacity resistive memory (RRAM, aka, memristor) has demonstrated great potential in mimicking synaptic behaviors. Several RRAM-based spiking neuromorphic designs exist, most of which focus on rate coding schemes. These designs simplify circuit implementations of neuron models and explore challenges such as unsatisfactory speed, resolution, and performance. As an alternative, we will explore temporal coding spiking neuromorphic systems that encode information as the relative timing of neuron activations (spikes), which have been proven to be more adaptive and energy-efficient. Developing a neuromorphic system for spiking neural network (SNN) inference and online training, however, faces some major technical challenges: (1) It lacks circuit implementation support for temporal-coding SNN to achieve satisfying power efficiency and accuracy; (2) Although existing research works have investigated memristive synapse and neuron designs for spike-timing-dependent plasticity, the non-ideal conditions in implementation, such as device variations and signal degradation, degrade online learning accuracy of large scale systems; and (3) Non-optimized, inter-layer data traffic in SNNs, leads to unnecessary data communication costs. In this project, we plan to address these challenges by a hardware and software co-design framework that incorporates solutions at the circuit, architecture, and algorithm levels. At the circuit-level, we will elaborate on the in-situ SNN processing element designs for supporting both inference and online training modes. Variation-aware schemes will be studied to improve reliability. At the architecture level, we propose a pipelined, asynchronous architecture to retain the timing resolution of spikes. At the algorithm level, we will investigate an innovative SNN training algorithm for enabling activation sparsification and reducing unnecessary data communication costs. This neuromorphic system will provide an effective solution to real-life energy-constrained applications and significantly contribute to the exploration of next-generation high-performance computing systems under the DOE context.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

EQSIM and RAJA: Enabling Exascale Predictions of Earthquake Effects on Critical Infrastructure

Nearly 120 years ago, the great “San Francisco” earthquake of 1906 provided a stark and sobering view of the havoc that can be caused by the sudden and violent movement of Earth’s tectonic plates. According to USGS, the rupture along the San Andreas fault extended 296 miles (447 kilometers) and shook so violently that the motion could be felt as far north as Oregon and east into Nevada. The estimated 7.9-magnitude quake and subsequent fires decimated the major metropolis and surrounding areas: buildings turned to ruins, hundreds of thousands of people left homeless, and a death toll exceeding 3,000. Today, as evidenced by the catastrophic 7.8-magnitude earthquake that struck Turkey in February of 2023, large earthquakes still present a significant potential danger to life and economic security as researchers work to develop ways to better understand earthquake phenomena and quantify associated risks.

42 ENGINEERING↗
DOE OSTI2024

Physics-Informed Learning Machines for Multiscale and Multiphysics Problems (PHILMS) (Technical Report)

The research work at University of California Santa Barbara (UCSB) resulted in several new developments in the areas of scientific machine learning, numerical analysis, and practical methods for data-driven modeling, prediction, reductions, and simulation. Many of the projects were carried out in collaboration with members of the national laboratories at Sandia National Laboratories (SNL), Pacific Northwestern National Laboratories (PNNL), and other institutions. Results included developing new scientific machine learning methods, related theory and mathematical frameworks for analysis and training, data-driven numerical solvers, and related tools and software for scientific computation. During the support period, over 16+ papers were submitted for publication, and 4 open-source software packages were developed and released (available at http://atzberger.org/). In addition, 7+ students and 2 post-docs were mentored in collaboration with the laboratory staff for future careers in academia, government labs, and industry.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Overview on Transactive Energy—Advantages and Challenges for Weak Power Grids

This document lists some challenges that researchers face when implementing transactive energy in weak power grids. These challenges often include high voltage fluctuations, limited generation, high line loadability, and unbalanced grids. The operation of transactive energy, as well as optimization techniques, are also considered, highlighting the performance and functionalities depending on power grid characteristics and market topology. Some of the most used optimization techniques for market clearing, considering the characteristics and topology, are presented as part of the research work. In addition, this paper compares different market topologies and highlights their advantages and challenges. Furthermore, this paper contains a brief description of the interoperability frameworks applied to a smart grid. As a result, it was determined that interoperability is necessary for the proper functioning of the grid. Moreover, all methods were found to be effective for their purpose from the user’s point of view as each technique has different characteristics relevant to the user and the grid. It was concluded that it is convenient to combine the optimization techniques to consider different constraints in the market clearing.

14 SOLAR ENERGY↗
DOE OSTI2024

Void-Engineered Metamaterial Delay Line with Built-In Impedance Matching for Ultrasonic Applications

Metamaterials exhibit unique ultrasonic properties that are not always achievable with traditional materials. However, the structures and geometries needed to achieve such properties are often complex and difficult to obtain using common fabrication techniques. In the present research work, we report a novel metamaterial acoustic delay line with built-in impedance matching that is fabricated using a common 3D printer. Delay lines are commonly used in ultrasonic inspection when signals need to be separated in time for improved sensitivity. However, if the impedance of the delay line is not perfectly matched with those of both the sensor and the target medium, a strong standing wave develops in the delay line, leading to a lower energy transmission. The presented metamaterial delay line was designed to match the acoustic impedance at both the sensor and target medium interfaces. This was achieved by introducing graded engineered voids with different densities at both ends of the delay line. The measured impedances of the designed metamaterial samples show a good match with the theoretical predictions. The experimental test results with concrete samples show that the acoustic energy transmission is increased by 120% and the standing wave in the delay line is reduced by over a factor of 2 compared to a commercial delay line.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Heliostat Consortium: Gap Analysis on Wind Load for Achieving a Fully Competitive Heliostat Industry

The Heliostat Consortium (HelioCon) Wind Load Subtask was initiated with the aim of bringing research work pertaining to wind load measurement, characterization, and prediction taking place across several tasks, including Advanced Manufacturing, Components and Controls, and Field Deployment. The cross-cutting wind load subtopic in the HelioCon roadmap report [1] highlighted standardized methods and tools that are needed for a more detailed understanding of the static and dynamic loads on a heliostat. This will enable cost reduction of wind-dependent heliostat components to avoid unnecessarily conservative, overly constrained designs and increase field efficiency/reliability, to reduce the risk of component failures due to high-wind events (>15 m/s). Gaps related to heliostat wind load include site characterization for wind measurements, critical load cases for heliostat design, turbulence impacts on heliostat tracking error, testing of heliostat array configurations, understanding spatial variation of maximum loads across the solar field, and heliostat field layout and operating strategies. The recommended highest-priority pathway as first steps taken by HelioCon to address these gaps are to develop site characterization guidelines for heliostat design and field load measurements.

Emes, Matthew (ORCID:0000000341474387)↗