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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Functional characterization of Autographa californica multiple nucleopolyhedrovirus gp16 (ac130)

To investigate the function of Autographa californica multiple nucleopolyhedrovirus (AcMNPV) gp16, multiple gp16-knockout and repair mutants were constructed and characterized. No obvious difference in productivity of budded virus, DNA synthesis, late gene expression and morphogenesis was observed between gp16-knockout and repair viruses, but gp16 deletion resulted in six hours of lengthening in ST{sub 50} to the third instar Spodoptera exigua larvae in bioassays. GP16 was fractionated mainly in the light membrane fraction, by subcellular fractionation. A GP16-EGFP fusion protein was predominantly localized close around the nuclear membrane in infected cells, being coincident with formation of the vesicles associated with the nuclear membrane, which hosted nucleocapsids released from the nucleus. These data suggest that gp16 is not required for viral replication, but may be involved in membrane trafficking associated with the envelopment/de-envelopment of budded viruses when they cross over the nuclear membrane and pass through cytoplasm. - Highlights: • gp16 knockout and repair mutants of AcMNPV were constructed and characterized. • AcMNPV gp16 is not essential to virus replication. • Deletion of gp16 resulted in time lengthening to kill S. exigua larvae. • GP16 was localized close around the nuclear membrane of infected cells. • GP16 was fractionated in the light membrane fraction in subcellular fractionation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Automated nuclear cloud feature extraction from film

Chemical, biological, radiological, nuclear, and explosives incidents require rapid detection and characterization for appropriate response. For a nuclear detonation, visible-light cameras may be used to locate the cloud and characterize fallout deposition when coupled with numerical models. Films from the United States’ nuclear testing era compose the only sizeable collection of imagery depicting high-yield detonations. These films offer unique insights into characteristics of flows involving scales that are difficult to replicate experimentally, and they are a valuable source of data for the validation of models for nuclear fallout transport, either as part of emergency response or forensic activities. In this work, we implement modern computer vision and machine learning techniques to identify and track the cloud automatically and subsequently determine the time dependence of some of its features. We trained a ResNet-18 image classifier on hundreds of images to categorize nuclear cloud morphology. Each category or cloud regime is determined by early cloud evolution and is associated to constitutive properties of the flow, such as distribution of vorticity. Next, we identified keypoint features using the KAZE algorithm and tracked these keypoints in the images, allowing us to determine the dimensions and velocities of the cloud across film frames. These measurements converted to real-world units provide valuable experimental data that can be used in the development and validation of nuclear cloud models. We compared the results of this method against manual cloud rise measurements from two different films. In one, our automated method accelerated the feature extraction process without sacrificing measurement accuracy.

Khristy, Joel [ORNL] (ORCID:0000000209963060)↗
DOE OSTI2026

Uncertainty quantification of fireball features extracted from nuclear test films using computer vision

Films from the US’s historic nuclear testing era comprise the only extensive collection of imagery depicting high-yield detonations. These films offer unique insights into the characteristics of flows occurring on scales that are difficult to replicate experimentally, and they are a valuable source of data for the validation of models used to describe nuclear detonations. In recent work, we implemented modern computer vision and machine learning techniques to extract features of the fireball following nuclear detonation. With a training dataset of fireball films, we fine-tuned a You Only Look Once 11 (YOLO11) model to detect and track the fireball. Applied to a video, the outer bounding box produced in each frame by YOLO11 is used as an input prompt to Meta’s Segment Anything Model 2 (SAM2), which is shown to accurately predict the boundary of the fireball over time with high resolution. These state-of-the-art computer vision foundation models exhibit impressive visual accuracy in their results but lack an output of values that robustly quantify uncertainty in scientific applications. In this paper, we develop procedures for uncertainty quantification of extracted fireball features. We outline the application of a parallel attention mechanism to calculate uncertainty ranges that complement and better pose model validation data. This higher quality fireball validation data may serve to improve prognostic models describing nuclear detonations in support of nuclear forensic and emergency response activities.

Khristy, Joel [ORNL] (ORCID:0000000209963060)↗
DOE OSTI2020

ESGF Future Architecture Report (V.1.1)

This document reports the findings of the Earth System Grid Federation Future Architecture Face-to-Face Meeting held in the UK 5-7 November 2019, attended by technical representatives from the ESGF partner organisations. ESGF is an International federated archive that provides access to Earth science data. It is fundamentally a distributed file management system with its main function being data dissemination through the provision of services for efficient replication and search. It has been in operation for over ten years and has undergone continuous improvements and enhancements over this time span. The Future Architecture is a major review of the software system including a fundamental reassessment of its requirements with a view to develop a new overall system architecture. This has been initiated in the light of challenges around the maintenance of the existing software legacy and a changing technology landscape and practices in the communities it serves. The work is being carried out under the oversight of the ESGF Executive Committee1,2 and is coordinated activity between ESGF and the European IS-ENES3 project.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Early Lab scientists had questions, Plastic Man gave them answers

He was a willing subject in countless scientific experiments, a superstar of health physics, as well as a favorite photo prop -- and not just around Halloween time. He was Plastic Man. Beginning in the mid-1950s, the Lab (then called Los Alamos Scientific Laboratory) often relied on several life-sized synthetic test subjects to avoid experimenting on people. In the early days of the Laboratory, not much was known about how different radioisotopes interacted with the human body and how much it absorbed from different radiation sources. Answering queries like these is where Plastic Man came in. For example, during the 1950s and 1960s, the Lab was tasked with developing nuclear rockets for space exploration under the Rover Program. One of the concerns was how astronauts might be affected when exposed to radiation from these rocket engines. So, the Lab’s health group set up an experiment in which Plastic Man was placed in close proximity to an experimental Rover nuclear rocket engine. Running experiments like this using Plastic Man kept humans safer. How life-like was he? There were actually two variations of Plastic Man. Both had hard plastic exteriors, but one of the models encased a real human skeleton. They also had movable joints and simulated organs, such as a liver, a spleen, kidneys, lungs and a thyroid. Although Plastic Man in its entirety was used in experiments, much of the data collected were from research conducted inside on these replicated organs. In time, technology advanced and Plastic Man was able to retire from the Lab. He found a new home in 1964 as a display at the Laboratory’s science museum, and is sometimes displayed today in the Bradbury Science Museum in downtown Los Alamos.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2017

Can We Practically Bring Physics-based Modeling Into Operational Analytics Tools?

We present that analytics software is increasingly used to improve and maintain operational efficiency in commercial buildings. Energy managers, owners, and operators are using a diversity of commercial offerings often referred to as Energy Information Systems, Fault Detection and Diagnostic (FDD) systems, or more broadly Energy Management and Information Systems, to cost-effectively enable savings on the order of ten to twenty percent. Most of these systems use data from meters and sensors, with rule-based and/or data-driven models to characterize system and building behavior. In contrast, physics-based modeling uses first-principles and engineering models (e.g., efficiency curves) to characterize system and building behavior. Historically, these physics-based approaches have been used in the design phase of the building life cycle or in retrofit analyses. Researchers have begun exploring the benefits of integrating physics-based models with operational data analytics tools, bridging the gap between design and operations. In this paper, we detail the development and operator use of a software tool that uses hybrid data-driven and physics-based approaches to cooling plant FDD and optimization. Specifically, we describe the system architecture, models, and FDD and optimization algorithms; advantages and disadvantages with respect to purely data-driven approaches; and practical implications for scaling and replicating these techniques. Finally, we conclude with an evaluation of the future potential for such tools and future research opportunities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Improved Neutron Lifetime Measurement with UCN$\tau$

In this work, we report an improved measurement of the free neutron lifetime $\tau_n$ using the UCN$\tau$ apparatus at the Los Alamos Neutron Science Center. We count a total of approximately 38×10 6 surviving ultracold neutrons (UCNs) after storing in UCN$\tau$’s magnetogravitational trap over two data acquisition campaigns in 2017 and 2018. We extract $\tau$ n from three blinded, independent analyses by both pairing long and short storage time runs to find a set of replicate $\tau$ n measurements and by performing a global likelihood fit to all data while self-consistently incorporating the β-decay lifetime. Both techniques achieve consistent results and find a value $\tau$ n =877.75±0.28 stat +0.22/–0.16 syst s. With this sensitivity, neutron lifetime experiments now directly address the impact of recent refinements in our understanding of the standard model for neutron decay.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Omics-Lethal Human Viruses, West Nile Experiment WDC011

The purpose of this experiment was to evaluate the host response to wild-type West Nile virus (WNVMT) and mutant (WNVE218A) virus infection. Sample data was obtained from primary mouse myeloid dendritic cells for mRNA expression analysis. See Experiment WDC010 (GSE74628) for corresponding independent biological replicate study. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Transcriptomics dataset downloads have a direct relationship to a primary sample submission corresponding to a specific West Nile virus infection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Omics-Lethal Human Viruses, West Nile Experiment WGCN002

The purpose of this experiment was to evaluate the host response to wild-type West Nile virus infectious clone (WNV-NY99 clone 382) and mutant (WNVE218A) virus infection. Sample data was obtained from mouse granule cell neurons for mRNA and miRNA expression analysis. See Experiment WGCN003 for corresponding independent biological replicate study. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Transcriptomics dataset downloads have a direct relationship to a primary sample submission corresponding to a specific West Nile virus infection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Omics-Lethal Human Viruses, West Nile Experiment WGCN003

The purpose of this experiment was to evaluate the host response to wild-type West Nile virus infectious clone (WNV-NY99 clone 382) and mutant (WNVE218A) virus infection. Sample data was obtained from mouse granule cell neurons for mRNA and miRNA expression analysis. See Experiment WGCN002 for corresponding independent biological replicate study. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Transcriptomics dataset downloads have a direct relationship to a primary sample submission corresponding to a specific West Nile virus infection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Reproducibility of Differential Proteomic Technologies in CPTAC Fractionated Xenografts

The NCI Clinical Proteomic Tumor Analysis Consortium (CPTAC) employed a pair of reference xenograft proteomes for initial platform validation and ongoing quality control of its data collection for The Cancer Genome Atlas (TCGA) tumors. These two xenografts, representing basal and luminal-B human breast cancer, were fractionated and analyzed on six mass spectrometers in a total of 46 replicates divided between iTRAQ and label-free technologies, spanning a total of 1095 LC-MS/MS experiments. These data represent a unique opportunity to evaluate the stability of proteomic differentiation by mass spectrometry over many months of time for individual instruments or across instruments running dissimilar workflows. We evaluated iTRAQ reporter ions, label-free spectral counts, and label-free extracted ion chromatograms as strategies for data interpretation. From these assessments we found that differential genes from a single replicate were confirmed by other replicates on the same instrument from 61-93% of the time. When comparing across different instruments and quantitative technologies, differential genes were reproduced by other data sets from 67-99% of the time. Projecting gene differences to biological pathways and networks increased the similarities. These overlaps send an encouraging message about the maturity of technologies for proteomic differentiation.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2017

Evaluation of a Class of Simple and Effective Uncertainty Methods for Sparse Samples of Random Variables and Functions

When very few samples of a random quantity are available from a source distribution of unknown shape, it is usually not possible to accurately infer the exact distribution from which the data samples come. Under-estimation of important quantities such as response variance and failure probabilities can result. For many engineering purposes, including design and risk analysis, we attempt to avoid under-estimation with a strategy to conservatively estimate (bound) these types of quantities -- without being overly conservative -- when only a few samples of a random quantity are available from model predictions or replicate experiments. This report examines a class of related sparse-data uncertainty representation and inference approaches that are relatively simple, inexpensive, and effective. Tradeoffs between the methods' conservatism, reliability, and risk versus number of data samples (cost) are quantified with multi-attribute metrics use d to assess method performance for conservative estimation of two representative quantities: central 95% of response; and 10 -4 probability of exceeding a response threshold in a tail of the distribution. Each method's performance is characterized with 10,000 random trials on a large number of diverse and challenging distributions. The best method and number of samples to use in a given circumstance depends on the uncertainty quantity to be estimated, the PDF character, and the desired reliability of bounding the true value. On the basis of this large data base and study, a strategy is proposed for selecting the method and number of samples for attaining reasonable credibility levels in bounding these types of quantities when sparse samples of random variables or functions are available from experiments or simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Omics-Lethal Human Viruses, West Nile Experiment WDC010

The purpose of this experiment was to evaluate the host response to wild-type West Nile virus (WNVMT) and mutant (WNVE218A) virus infection. Sample data was obtained from primary mouse myeloid dendritic cells for mRNA and proteomics expression analysis. See Experiment WDC011 (GSE75222) for corresponding independent biological replicate study. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Leveraging unique high-resolution Omics capabilities for proteomics and transcriptomics, each dataset download has a direct relationship to a primary sample submission corresponding to a specific West Nile virus infection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Increasing the Reproducibility and Replicability of Supervised AI/ML in the Earth Systems Science by Leveraging Social Science Methods

Artificial intelligence (AI) and machine learning (ML) pose a challenge for achieving science that is both reproducible and replicable. The challenge is compounded in supervised models that depend on manually labeled training data, as they introduce additional decision-making and processes that require thorough documentation and reporting. We address these limitations by providing an approach to hand labeling training data for supervised ML that integrates quantitative content analysis (QCA)—a method from social science research. The QCA approach provides a rigorous and well-documented hand labeling procedure to improve the replicability and reproducibility of supervised ML applications in Earth systems science (ESS), as well as the ability to evaluate them. Specifically, the approach requires (a) the articulation and documentation of the exact decision-making process used for assigning hand labels in a “codebook” and (b) an empirical evaluation of the reliability” of the hand labelers. In this paper, we outline the contributions of QCA to the field, along with an overview of the general approach. We then provide a case study to further demonstrate how this framework has and can be applied when developing supervised ML models for applications in ESS. With this approach, we provide an actionable path forward for addressing ethical considerations and goals outlined by recent AGU work on ML ethics in ESS.

58 GEOSCIENCES↗
DOE OSTI2024

Quantifying the Influence of Size, Shape, and Density of Microplastics on Their Transport Modes: A Modeling Approach

Microplastics (MPs) pose significant risks to marine ecosystems and human health, necessitating accurate predictions of their distributions in aquatic environments for effective risk mitigation. However, understanding MP transport dynamics is challenging because of the inadequate representation of MP characteristics such as size, shape, and density in numerical models. Further, the accuracy of the MP vertical profiles in existing models has not been thoroughly validated. Thus, we developed an MP transport model within the Finite Volume Community Ocean Model framework (FVCOM-MP) by integrating MP characteristics. We validated FVCOM-MP against experimental and analytical data, focusing on various MP transport modes and transitions. FVCOM-MP successfully replicates MP profiles in different transport modes, including the bedload, surface-load, suspended-load, and mixed-load modes. Additionally, we introduce phase diagrams for classifying MP transport modes based on particle characteristics, enhancing our understanding of MP dynamics in aquatic systems. The transport modes for a number of real-world MP particles, including fishing line, plastic bag/bottle fragments, synthetic fibers, tire wear particles, polyvinyl chloride and expanded polystyrene pellets, were analyzed with these phase diagrams.

Microplastic transport, Settling velocity, Rising ↗
DOE OSTI2024

Evaluation and Intercomparison of Small Uncrewed Aircraft Systems Used for Atmospheric Research

Abstract Small uncrewed aircraft systems (sUAS) are regularly being used to conduct atmospheric research and are starting to be used as a data source for informing weather models through data assimilation. However, only a limited number of studies have been conducted to evaluate the performance of these systems and assess their ability to replicate measurements from more traditional sensors such as radiosondes and towers. In the current work, we use data collected in central Oklahoma over a 2-week period to offer insight into the performance of five different sUAS platforms and associated sensors in measuring key weather data. This includes data from three rotary-wing and two fixed-wing sUAS and included two commercially available systems and three university-developed research systems. Flight data were compared to regular radiosondes launched at the flight location, tower observations, and intercompared with data from other sUAS platforms. All platforms were shown to measure atmospheric state with reasonable accuracy, though there were some consistent biases detected for individual platforms. This information can be used to inform future studies using these platforms and is currently being used to provide estimated error covariances as required in support of assimilation of sUAS data into weather forecasting systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Advanced wind turbine control development using field test analysis for generator overspeed mitigation

Abstract Turbulent and gusty wind conditions can cause generator overspeed peaks to exceed a threshold that then lead to wind turbine shutdowns, which then decrease the energy production of the wind turbines. We derive so‐called “gust measures” that predict when generator overspeed peaks may occur. These gust measures are then used to develop advanced controllers to mitigate generator overspeed peaks so that wind turbines can operate more robustly in difficult wind conditions without exceeding generator overspeed thresholds that would lead to turbine shutdown events. The advanced controllers are demonstrated in nonlinear aeroelastic simulations using the open‐source wind turbine simulation tool OpenFAST. To increase the realism of the simulations, they are run using field‐replicated wind conditions and a wind turbine model based on data from an experimental field campaign on a downscaled demonstrator of a novel extreme‐scale, two‐bladed, downwind rotor design.

17 WIND ENERGY↗
DOE OSTI2021

Small Animal IMRT Using 3D-Printed Compensators

Preclinical radiation replicating clinical intensity modulated radiation therapy (IMRT) techniques can provide data translatable to clinical practice. For this work, treatment plans were created for oxygen-guided dose-painting in small animals using inverse-planned IMRT. Spatially varying beam intensities were achieved using 3-dimensional (3D)-printed compensators.

3D PRINTING↗