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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Deep Active Learning for Solvability Prediction in Power Systems

Traditional methods for solvability region analysis can only have inner approximations with inconclusive conservatism and handle limited types of power flow models. In this letter, we propose a deep active learning framework for solvability prediction in power systems. Compared with passive learning where the training is performed after all instances are labeled, active learning selects most informative instances to be labeled and therefore significantly reduces the size of the labeled dataset for training. In the active learning framework, the acquisition functions, which correspond to different sampling strategies, are defined in terms of the on-the-fly posterior probability from the classifier. First, the IEEE 39-bus system is employed to validate the proposed framework, where a two-dimensional case is illustrated to visualize the effectiveness of the sampling method followed by the high-dimensional numerical experiments. Then, the Northeast Power Coordinating Council (NPCC) 140-bus system is used to validate the performance on large-scale power systems.

42 ENGINEERING↗
DOE OSTI2022

Fabrication of Arrays of Topological Solitons in Patterned Chiral Liquid Crystals for Real-Time Observation of Morphogenesis

Topological solitons have knotted continuous field configurations embedded in a uniform background, and occur in cosmology, biology, and electromagnetism. However, real-time observation of their morphogenesis and dynamics is still challenging because their size and timescale are enormously large or tiny. Liquid crystal (LC) structures are promising candidates for a model-system to study the morphogenesis of topological solitons, enabling direct visualization due to the proper size and timescale. We report a new way is found to rationalize the real-time observation of the generation and transformation of topological solitons using cholesteric LCs confined in patterned substrates. The experimental demonstration shows the topologically protected structures arise via the transformation of topological defects. Numerical modeling based on minimization of free energy closely reconstructs the experimental findings. The fundamental insights obtained from the direct observations pose new theoretical challenges in understanding the morphogenesis of different types of topological solitons within a broad range of scales.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Visualization of specific collagen-producing cells by Col1-GFP transgenic mice revealed novel type I collagen-producing cells other than fibroblasts in systemic organs/tissues

Highlights: • A new reporter mouse was generated to label type I collagen-producing cells. • Type I collagen-producing cells were specifically labeled in this reporter mouse. • Podocytes and Leydig cells showed the ability to produce type I collagen. Type I collagen is one of the most abundant proteins in mammals and plays important roles in maintaining the integrity of many tissues. Although fibroblasts are the main source of type I collagen, other cells also produce it; however, these cells are not well-defined owing to the lack of a specific marker. A transgenic (Tg) mouse line has been generated in which type I collagen-producing cells are labeled with enhanced green fluorescent protein (EGFP), which enables the monitoring of these cells without requiring an additional cell marker. This Tg mouse line has since been widely used to study type I collagen-producing cells and fibrosis; one study revealed that podocytes, which were not previously considered to produce type I collagen, expressed EGFP. This raises a question regarding the specificity of EGFP expression in this Tg mouse line. To exclude the possibility of non-specific EGFP expression in the existing Tg mouse line and specifically monitor type I collagen-producing cells, we generated a new Tg mouse line and histologically confirmed the specificity of EGFP expression throughout the body. Moreover, we explored type I collagen-producing cells other than fibroblasts and revealed for the first time that Leydig cells have the ability to produce type I collagen. Because of its highly specific and physiologically accurate expression, our new Tg mouse line will help to accurately elucidate not only type I collagen-producing cells in normal tissues but also the potential cells in fibrotic tissues, providing new insights into the pathology of fibrosis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Simulation of Helium Flow Visualization Apparatus for Studies of Blanket Cooling in Fusion Reactors

Flow visualization is essential to understanding helium cooling performance. This article investigates helium flow visualization in an apparatus to support the design of the blanket first wall for a fusion reactor. Helium’s safety advantages make it an attractive coolant, but effective cooling and flow visualization remain challenging. Sophisticated simulations are conducted in different test sections to address three key areas in the design of a test apparatus and cooling channel enhancements: the influence of viewing glass windows on flow patterns, the impact of increased heating, and the effectiveness of cooling structures like baffles. Viewing glass windows introduce flow recirculation region bifurcation and flow asymmetry, affecting flow patterns and necessitating careful analysis in future experiments. Increased heating results in helium flow detachment from the heated surface, leading to hot spots. Cooling structures, particularly baffles, prove effective in maintaining consistent attachment to the heated surface, improving the heat transfer performance. Further, this study also examines a tunable parameter in the turbulence model, highlighting the importance of accurate model tuning for future fusion reactor cooling designs. With an imminent helium flow visualization facility, these simulations will be used to optimize cooling structures on the heated wall to improve flow attachment and heat transfer efficiency. This work serves as a first investigation of the helium flow visualization apparatus for blanket cooling enhancement in fusion reactor design.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Leading in Los Angeles: Demonstrating scalable emerging energy efficient technologies for integrated façade, lighting, and plug loads INTER System FLEXLAB Test Report

This report is a part of the California Energy Commission (Energy Commission) EPIC study Leading in Los Angeles: Demonstrating scalable emerging energy efficient technologies for integrated façade, lighting, and HVAC. The set of technologies are called the Integrated Technologies for Energy-efficient Retrofits (INTER) and are comprised of automated shading products and LED lighting systems with networked luminaire-level sensors and controls. In addition, the project will include control modifications and assessments of HVAC savings. This document includes the test plan and test results for the FLEXLAB® testing of the shading and lighting INTER system and related energy use impact. The test plan describes the test objectives and features, test cases, schedule, and measurements. The test results cover system performance in the lab; including lighting and HVAC energy, visual comfort, and thermal comfort.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Remote Sensor Design for Visual Recognition with Convolutional Neural Networks

While deep learning technologies for computer vision have developed rapidly since 2012, modeling of remote sensing systems has remained focused around human vision. In particular, remote sensing systems are usually constructed to optimize sensing cost-quality trade-offs with respect to human image interpretability. While some recent studies have explored remote sensing system design as a function of simple computer vision algorithm performance, there has been little work relating this design to the state-of-the-art in computer vision: deep learning with convolutional neural networks. We develop experimental systems to conduct this analysis, showing results with modern deep learning algorithms and recent overhead image data. Our results are compared to standard image quality measurements based on human visual perception, and we conclude not only that machine and human interpretability differ significantly, but that computer vision performance is largely self-consistent across a range of disparate conditions. This repository contains all the code required to replicate the results of our research paper, and the corresponding docker environment in which that code can be executed. All code is written in Python3 and utilizes the PyTorch library (v1.0) for neural network model training and evaluation. Jupyter notebooks are used to visualize images transformed with our code, in addition to plotting experimental results. We also include the specific parameter files used to execute our experiments, with the intent that these experiments can be replicated.

Zelinski, michaelE.↗
DOE OSTI2020

Hidden fluid mechanics: Learning velocity and pressure fields from flow visualizations

For centuries, flow visualization has been the art of making fluid motion visible in physical and biological systems. Although such flow patterns can be, in principle, described by the Navier-Stokes equations, extracting the velocity and pressure fields directly from the images is challenging. We addressed this problem by developing hidden fluid mechanics (HFM), a physics-informed deep-learning framework capable of encoding the Navier-Stokes equations into the neural networks while being agnostic to the geometry or the initial and boundary conditions. We demonstrate HFM for several physical and biomedical problems by extracting quantitative information for which direct measurements may not be possible.

Raissi, Maziar↗
DOE OSTI2026

What Is the Agent Doing? Visualizing Agentic AI Querying Workflows

We explore how visualizations can help users understand what an AI agent is doing as it builds and runs queries over data. As part of the LinkQ system, a natural language interface for querying knowledge graphs with a large language model (LLM), we designed two complementary views: A State Diagram that shows where the agent is within a larger workflow, and a Live Action Display that gives real-time updates about the agent's current task. In a study with 14 practitioners, we found that these visuals helped participants build stronger mental models of the agent's behavior while also increasing their confidence in the system. However, we also observed that users sometimes trusted incorrect outputs simply because the agent appeared to be doing the "right" thing. Our findings point to both the value and risk of visualizing agent behavior in interactive AI systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

An Overview of the Circular Economy Lifecycle Assessment and VIsualization (CELAVI) Framework

A circular economy emphasizes the efficient use of all resources (e.g., materials, land, water). Despite anticipated overall benefits to society, the transition to a circular economy is likely to create regional differences in impacts. Current tools are unable to fully evaluate these potential externalities, which will be important for informing research prioritization and regional decision making. This presentation will review and contrast nine current impact assessment methods and describe their granularity, scope, data requirements, and capabilities within the context of identifying regional and sectoral transfers of impacts that could result from transitioning to a circular economy for energy systems. The review of current approaches highlights the need for a new hybrid circularity assessment framework that leverages multiple methods. We describe one such approach: the Circular Economy Lifecycle Assessment and VIsualization (CELAVI) framework. CELAVI uses system dynamics to model material flows for multiple circular economy pathways, network theory to track the spatial and sectoral flow of functional units across a graph, and discrete event simulation to to step through time and evaluate lifecycle assessment data at each time step. The framework is designed to be flexible and scalable enough to accommodate multiple energy materials and multiple energy technologies. CELAVI's hybridization of multiple existing methods yields additional capabilities, which may help answer questions about how flows between the technosphere and ecosphere may evolve if the circularity of energy systems is modified.

circular economy↗
DOE OSTI2025

Leveraging public AI tools to explore systems biology resources in mathematical modeling

Predictive mathematical modeling is an essential part of systems biology and is interconnected with information management. Systems biology information is often stored in specialized formats to facilitate data storage and analysis. These formats are not designed for easy human readability and thus require specialized software to visualize and interpret results. Therefore, comprehending modeling and underlying networks and pathways is contingent on mastering systems biology tools, which is particularly challenging for users with no or little background in data science or system biology. To address this challenge, we investigated the usage of public Artificial Intelligence (AI) tools in exploring systems biology resources in mathematical modeling. We tested public AI’s understanding of mathematics in models, related systems biology data, and the complexity of model structures. Our approach can enhance the accessibility of systems biology for non-system biologists and help them understand systems biology without a deep learning curve.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Simultaneous imaging and diffraction in the dynamic diamond anvil cell

The ability to visualize a sample undergoing a pressure-induced phase transition allows for the determination of kinetic parameters, such as the nucleation and growth rates of the high-pressure phase. For samples that are opaque to visible light (such as metallic systems), it is necessary to rely on x-ray imaging methods for sample visualization. Here, we present an experimental platform developed at beamline P02.2 at the PETRA III synchrotron radiation source, which is capable of performing simultaneous x-ray imaging and diffraction of samples that are dynamically compressed in piezo-driven diamond anvil cells. This setup utilizes a partially coherent monochromatic x-ray beam to perform lensless phase contrast imaging, which can be carried out using either a parallel- or focused-beam configuration. The capabilities of this platform are illustrated by experiments on dynamically compressed Ga and Ar. Melting and solidification were identified based on the observation of solid/liquid phase boundaries in the x-ray images and corresponding changes in the x-ray diffraction patterns collected during the transition, with significant edge enhancement observed in the x-ray images collected using the focused-beam. These results highlight the suitability of this technique for a variety of purposes, including melt curve determination.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Implementing Neural Adaptive Filtering in Engineered Detection Systems

The retina plays an important role in animal vision --- namely to pre-process visual information before sending it to the brain. The goal of this LDRD was to develop models of motion-sensitive retinal cells for the purpose of developing retinal-inspired algorithms to be applied to real-world data specific to Sandia's national security missions. We specifically focus on detection of small, dim moving targets amidst varying types of clutter or distractor signals. We compare a classic motion-sensitive model, the Hassenstein-Reichardt model, to a model of the OMS (object motion- sensitive) cell, and find that the Reichardt model performs better under continuous clutter (e.g. white noise) but is very sensitive to particular stimulus conditions (e.g. target velocity). We also demonstrate that lateral inhibition, a ubiquitous characteristic of neural circuitry, can effect target-size tuning, improving detection specifically of small targets.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Pool boiling on metal-foam enhanced tube bundle: heat transfer characteristics and flow visualization

A flooded evaporator configuration is common in large central air conditioning or process cooling systems. It is basically a shell and tube heat exchanger, in which a secondary fluid (brine or water) circulates inside the tube bundle and is cooled by the vaporization of the refrigerant on the outside surface of the tubes. The enhanced pool boiling process enables the compact design of flooded evaporators, which substantially reduces the refrigerant charge. High-porosity metal foam, with a large surface-area-to-volume ratio, could provide an extended heat transfer area and a high-density of nucleation sites. This study experimentally investigated the pool boiling heat transfer and flow characteristics on metal-foam enhanced tube bundles. The enhanced bundle consists of four aluminum tubes with aluminum foam brazed around the outer surface, which are horizontally mounted in a staggered arrangement. The results showed that the metal-foam enhanced tube bundles improved the heat transfer coefficient by 100-160% with a lower wall temperature difference of 1-10°C, compared to the baseline. In addition, the tube pitch played a significant role in determining the pool boiling behavior of the tube bundles.

Yang, Cheng-Min↗
DOE OSTI2026

Symmetrizing relativistic three-body partial wave amplitudes

S matrix principles and symmetries impose constraints on three-particle scattering amplitudes, which can be formulated as a class of integral equations for their partial wave projections. However, these amplitudes are typically expressed in an asymmetric basis, where one of the initial and final state particles is singled out, and all quantum numbers are defined relative to this spectator. In this work, we show how to construct symmetric partial wave amplitudes, which have been symmetrized over all possible spectator combinations, using their asymmetric counterparts and sets of recoupling coefficients. We derive these recoupling coefficients for arbitrary angular momentum and isospin for arbitrary systems of spinless particles with SU(2) flavor symmetry. We propose a simple intensity observable suitable for visualizing the structure of three-body dynamics in Dalitz distributions. Finally, we provide some numerical examples of Dalitz distributions relevant for future lattice QCD calculations of 3⁢𝜋 systems and provide numerical evidence that the symmetrization procedure is consistent with expected symmetries of Dalitz plots.

Lattice QCD↗
DOE OSTI2019

A review of smart building sensing system for better indoor environment control

Here this paper aims to provide a systemic review of how indoor sensors influence in managing optimal energy saving, thermal comfort, visual comfort, and indoor air quality in the built environment. The optimal management of energy saving and occupant comfort plays a vital role in the built environment because the occupant's productivity and health are highly influenced by indoor environmental quality. In order to do this, there must be a functional sensing system that connects the environment variables (e.g., temperature) with building environmental control systems such as the heating, ventilation, and air-conditioning system. This paper starts with an overview of the importance of energy saving and occupant comfort in the built environment. It then discusses sensors and their importance in the built environment and reviews the different types of sensors, which explains them in terms of how they influence the indoor built environment and occupant productivity. The paper further explores the application of sensors in the built environment and analyzes this in terms of energy saving, thermal comfort, visual comfort, and indoor air quality. Following this, the data analysis is discussed in terms of data, information, and knowledge accrued from the sensors. Lastly, the paper discusses the future challenges for the improvement of building indoor environmental quality and energy saving by the application of sensors.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

H-Canyon Ventilation System Exhaust Tunnel Inspection at the Savannah River Site - 18052

The Department of Energy (DOE) H-Canyon Facility at the Savannah River Site (SRS) is operated by Savannah River Nuclear Solutions (SRNS). The Facility Structural Integrity Program (SIP) performs periodic visual inspections to confirm the component is capable of performing its safety function. This Program provides the process to document the conditions of safety related structural systems and components, their damage mechanisms, and recommend repairs if required before there is impact on the safety envelope. The H-Canyon Exhaust Tunnel is part of the H-Canyon Exhaust Ventilation System and is periodically inspected under the Structural Integrity Program. The Tunnel performs a Safety Class passive design feature function that is available 100% of the time. The Tunnel directs Canyon process air from the Canyon to the Sand Filter System. The radiological and chemical airborne activity coupled with the physical configuration of the tunnel precludes a manned entry into the tunnel. Tunnel inspections have been performed using cameras on a stick, referred to as pole cameras prior to CY2003. Since CY2003, five camera equipped crawlers have been used with varying levels of inspection success. With each successive crawler inspection, expectations have increased to perform tasks beyond visual examinations. The 2017 crawler performed the visual inspection but also included improvements on crawler performance, such as testing the use of wireless capability and remediation of crawler travel route, to the addition of stationary cameras and lighting at key locations. The latest 2017 crawler successfully traveled the entire length of the tunnel between the Canyon and Sand Filter System for the second time since development, thus providing key visual data for the integrity program [2]. In addition, several access ports were installed in 2017 following the removal of concrete core samples that allow for new visual inspection of the Canyon Crossover tunnel, thus providing information for an area that was generally inaccessible for monitoring. Planning for the 2019 crawler inspection is underway with the expectations to improve upon inspection cameras and also introduce mapping technologies such as LIDAR. The challenge to obtain meaningful data from the remote inspections of a 60+ year operating Canyon Exhaust tunnel continues to be a complex endeavor requiring close coordination of multiple organizations, adherence to Conduct of Operations, Radiological Safety, Worker Safety, etc. principles as well as alignment with Facility Safety Basis requirements. This paper discusses the continuing improvements in inspection techniques and the challenges associated these inspections. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Ferroelectric quantum Hall phase revealed by visualizing Landau level wave function interference

States with spontaneously broken symmetry can form due to Coulomb interactions in electronic systems with multiple internal degrees of freedom. Materials with several degenerate regions in the Brillouin zone-called valleys-offer a rich setting for the emergence of such states, which have potential electronic and optical applications. To date, identification of these broken-symmetry phases has mostly relied on macroscopic transport or optical properties. Here we demonstrate a direct approach by visualizing the wavefunctions of bismuth surface states with a scanning tunnelling microscope. Strong spin-orbit coupling on the surface of bismuth leads to six degenerate, teardrop-shaped, hole valleys. Our spectroscopic measurements reveal that exchange interactions fully lift this degeneracy at high magnetic field, and we are able to determine the nature of the valley ordering by imaging the broken-symmetry Landau level wavefunctions. The spatial features of singly degenerate Landau level wavefunctions near isolated defects contain unique signatures of interference between spin-textured valleys, which identify the electronic ground state as a quantum Hall ferroelectric. As a result, our observations confirm the recent prediction that interactions in strongly anisotropic valley systems favour the occupation of a single valley, giving rise to emergent ferroelectricity in the surface state of bismuth.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

ARMADA. I. Triple Companions Detected in B-type Binaries α Del and ν Gem

Ground-based optical long-baseline interferometry has the power to measure the orbits of close binary systems at ∼10 μas precision. This precision makes it possible to detect “wobbles” in the binary motion due to the gravitational pull from additional short-period companions. We started the ARrangement for Micro-Arcsecond Differential Astrometry (ARMADA) survey with the Michigan Infra-Red Combiner (MIRC)/MIRC-X instrument at the Center for High Angular Resoloution Astronomy (CHARA) array for the purpose of detecting giant planets and stellar companions orbiting individual stars in binary systems. We describe our observations for the survey, and introduce the wavelength calibration scheme that delivers precision at the tens of microarcseconds level for <02 binaries. We test our instrument performance on a known triple system, κ Peg, and show that our survey is delivering a factor of 10 better precision than previous similar surveys. We present astrometric detections of tertiary components to two B-type binaries: a 30 day companion to α Del, and a 50 day companion to ν Gem. We also collected radial velocity data for α Del with the Tennessee State University Automated Spectroscopic Telescope at Fairborn Observatory. We are able to measure the orbits and masses of all three components in these systems. We find that the previously published radial velocity orbit for the inner pair of ν Gem is not consistent with our visual orbit. The precision achieved for these orbits suggests that our ARMADA survey will be successful at discovering new compact triple systems to A/B-type binary systems, leading to better statistics of hierarchical system architectures and formation history.

47 OTHER INSTRUMENTATION↗