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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Operando visualization of porous metal additive manufacturing with foaming agents through high-speed x-ray imaging

Porous metals find extensive applications in soundproofing, filtration, catalysis, and energy-absorbing structures, thanks to their unique internal pore structure and high specific strength. In recent years, there has been an increasing interest in fabricating porous metals using additive manufacturing (AM), leveraging its unique advantages, including improved design freedom, spatial material control, and cost-effective small-batch production. In this study, we conducted pioneering operando visualization of AM porous metal using a laser powder bed fusion (L-PBF) setup combined with a high-speed synchrotron x-ray imaging system. Single track printing experiments using Ti6Al4V (Ti64) combined with titanium hydride (TiH 2 ) and sodium carbonate (Na 2 CO 3 ) as foaming agents, with varying mixing ratios were performed under different processing conditions. Here. the results elucidate the dynamic development of porosity formation. The average pore size is significantly influenced by the particle size of foaming agents when pore coalescence is absent. For all foaming agent content tested in the current study, the number of pores is found to be more sensitive to changes in laser power than in laser scanning speed. Increasing linear energy density (increasing laser power or reducing laser scanning speed) promotes the foaming agent activation thereby porosity formation. However, high linear energy density skews pore distribution towards the surface despite forming deeper melt pools. In addition, the impact of additional factors including foaming agent's laser absorptivity and decomposition kinetics with respect to AM time scales should be carefully considered to avoid ineffective activation of foaming agents during the AM of porous metals.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Atomic Resolution Structural and Chemical Imaging Revealing the Sequential Migration of Ni, Co, and Mn upon the Battery Cycling of Layered Cathode

Layered lithium transition metal oxides (LTMO) are promising candidate cathode materials for next generation high energy density lithium ion battery. The challenge for using this category of cathode is the capacity and voltage fading, which is believed to be associated with the layered structure disordering, a process that is initiated from the surface or solid-electrolyte interface and facilitated by transition metal (TM) reduction and oxygen vacancy formation. However, the atomic level dynamic mechanism of such a layered structure disordering is still not fully clear. In this work, utilizing atomic resolution electron energy loss spectroscopy (EELS), we map, for the first time at atomic scale, the spatial evolution of Ni, Co and Mn in a cycled LiNi1/3M1/3Co1/3O2 layered cathode. In combination with atomic level structural imaging, we discovered the direct correlation of TM ions migration behavior with lattice disordering, featuring the residing of TM ions in the tetrahedral site and a sequential migration of Ni, Co, and Mn upon the increased lattice disordering of the layered structure. This work highlights that Ni ions, though acting as the dominant redox species in many LTMO, are labile to migrate to cause lattice disordering upon battery cycling; while the Mn ions are more stable as compared with Ni and Co and can act as pillar to stabilize layered structure. Direct visualization of the behavior of TM ions during the battery cycling provides insight for designing of cathode with structural stability and correspondingly a superior performance.

annular bright field image↗
DOE OSTI2017

Atomic-resolution imaging of electrically induced oxygen vacancy migration and phase transformation in SrCoO 2.5-σ

Oxygen ion transport is the key issue in redox processes. Visualizing the process of oxygen ion migration with atomic resolution is highly desirable for designing novel devices such as oxidation catalysts, oxygen permeation membranes, and solid oxide fuel cells. We show the process of electrically induced oxygen migration and subsequent reconstructive structural transformation in a SrCoO 2.5-σ film by scanning transmission electron microscopy. We find that the extraction of oxygen from every second SrO layer occurs gradually under an electrical bias; beyond a critical voltage, the brownmillerite units collapse abruptly and evolve into a periodic nano-twined phase with a high c/a ratio and distorted tetrahedra. These results show that oxygen vacancy rows are not only natural oxygen diffusion channels, but also preferred sites for the induced oxygen vacancies. These direct experimental results of oxygen migration may provide a common mechanism for the electrically induced structural evolution of oxides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Comparison of Planar and Tubular Flow Field Plates for Proton Exchange Membrane Fuel Cells (PEMFCs) through Simulation

Proton exchange membrane fuel cells are excellent clean energy alternatives to current non-renewable energy sources. Bipolar plates are a key component of these fuel cells and directly responsible for their performance. Traditional bipolar plates are created in a planar form, but recent research has revealed a novel tubular design that performs similarly to conventional plates. Here, this study compares traditional planar designs with tubular ones. The finite element ANSYS software was used to determine and visualize velocity and pressure distributions of fluid flow through the bipolar plate channels.

25 ENERGY STORAGE↗
DOE OSTI2019

Integrated Modeling and Simulation Capability For Full Scale Multi-Physics Simulation and Visualization of Microreactor Concept

Microreactors are small mobile transportable nuclear reactors with thermal power less than 20 MWt that are designed to meet the needs of remote areas, military installations, emergency operations, and disaster relief zones. These reactor are concepts that are intended to be factory-manufacturable, easily transportable, and will allow for semi- or full-autonomous operation. To assist with development of microreactors, modeling and experimentation need to be performed with verification and validation to gain confidence in the models and tools. The objective of this study is apply advanced modeling and simulation capabilities being developed by the DOE Office of Nuclear Energy Nuclear Energy Advanced Modeling and Simulation (NEAMS) program to perform integrated modeling and simulation capability for multiphysics simulation of the microreactor concepts. This activity will provide an opportunity to exercise the codes to provide both gain experience and to provide feedback to the developers.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

CSRI Summer Proceedings 2021

The Computer Science Research Institute (CSRI) brings university faculty and students to Sandia National Laboratories for focused collaborative research on Department of Energy (DOE) computer and computational science problems. The institute provides an opportunity for university researches to learn about problems in computer and computational science at DOE laboratories, and help transfer results of their research to programs at the labs. Some specific CSRI research interest areas are: scalable solvers, optimization, algebraic preconditioners, graph-based, discrete, and combinatorial algorithms, uncertainty estimation, validation and verification methods, mesh generation, dynamic load-balancing, virus and other malicious-code defense, visualization, scalable cluster computers, beyond Moore’s Law computing, exascale computing tools and application design, reduced order and multiscale modeling, parallel input/output, and theoretical computer science. The CSRI Summer Program is organized by CSRI and includes a weekly seminar series and the publication of a summer proceedings.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

CSRI Summer Proceedings 2021

The Computer Science Research Institute (CSRI) brings university faculty and students to Sandia National Laboratories for focused collaborative research on Department of Energy (DOE) computer and computational science problems. The institute provides an opportunity for university researches to learn about problems in computer and computational science at DOE laboratories, and help transfer results of their research to programs at the labs. Some specific CSRI research interest areas are: scalable solvers, optimization, algebraic preconditioners, graph-based, discrete, and combinatorial algorithms, uncertainty estimation, validation and verification methods, mesh generation, dynamic load-balancing, virus and other malicious-code defense, visualization, scalable cluster computers, beyond Moore’s Law computing, exascale computing tools and application design, reduced order and multiscale modeling, parallel input/output, and theoretical computer science. The CSRI Summer Program is organized by CSRI and includes a weekly seminar series and the publication of a summer proceedings.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

GridCoPilot for Thermal Events: An LLM-Based Platform for Power Grid Reliability Analysis

Large Language Models show promise for translating natural language into database queries, but deploying such systems in safety-critical domains requires high reliability. We present an application of GridCoPilot to thermal event analysis (heatwaves and coldwaves) that affect power grid reliability. Our approach uses a LangChain SQL Agent to translate natural language queries into auditable SQL statements, with deterministic visualization routines that parse the structured query results. We introduce structural framing as a design principle, we integrate a NERC-region-level event library with county-level meteorology and decompose the combined data into three relational tables (event metadata, county-level event details, and a county-to-NERC subregion mapping), using prompt-guided joins to direct the model toward correct multi-table queries. For two core analytical patterns (identifying worst events by region and by region-year), the system achieved 100% SQL accuracy across all 16 NERC subregions and both event types (64 queries total). These results validate the approach for target use cases, though performance on diverse natural language formulations requires further investigation. We discuss design trade-offs, failure modes including JSON output truncation, and pathways for extending this approach to other hazard domains.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Visual, Optical and Replica Inspections: Surface Preparation of 650 MHz NB Cavity for PIP-II Linac

Surface preparation of niobium superconducting RF cavities is a critical step for achieving good RF performance under the superconducting state. Surface defect, roughness, and contamination affect the accelerating gradient and quality factor of the cavities. We report surface inspection methods used to control the surface processing of 650 MHz cavities designated for the pre-production and prototype cryomodules for PIP-II linac. The cavity surface was routinely inspected visually, with an optical camera, and by microscopic scanning of surface replicas. This article covers details on the surface inspection methods and surface polishing process used to repair the surface.

43 PARTICLE ACCELERATORS↗
DOE OSTI2015

Robot for Investigations and Assessments of Nuclear Areas

RIANA is a remote controlled Robot dedicated for Investigations and Assessments of Nuclear Areas. The development of RIANA is motivated by the need to have at disposal a proven robot, tested in hot cells; a robot capable of remotely investigate and characterise the inside of nuclear facilities in order to collect efficiently all the required data in the shortest possible time. It is based on a wireless medium sized remote carrier that may carry a wide variety of interchangeable modules, sensors and tools. It is easily customised to match specific requirements and quickly configured depending on the mission and the operator's preferences. RIANA integrates localisation and navigation systems. The robot will be able to generate / update a 2D map of its surrounding and exploring areas. The position of the robot is given accurately on the map. Furthermore, the robot will be able to autonomously calculate, define and follow a trajectory between 2 points taking into account its environment and obstacles. The robot is configurable to manage obstacles and restrict access to forbidden areas. RIANA allows an advanced control of modules, sensors and tools; all collected data (radiological and measured data) are displayed in real time in different format (chart, on the generated map...) and stored in a single place so that may be exported in a convenient format for data processing. This modular design gives RIANA the flexibility to perform multiple investigation missions where humans cannot work such as: visual inspections, dynamic localization and 2D mapping, characterizations and nuclear measurements of floor and walls, non destructive testing, samples collection: solid and liquid. The benefits of using RIANA are: - reducing the personnel exposures by limiting the manual intervention time, - minimizing the time and reducing the cost of investigation operations, - providing critical inputs to set up and optimize cleanup and dismantling operations. (authors)

42 ENGINEERING↗
DOE OSTI2018

A Virtual Reality Visualization Tool for Neuron Tracing

Tracing neurons in large-scale microscopy data is crucial to establishing a wiring diagram of the brain, which is needed to understand how neural circuits in the brain process information and generate behavior. Automatic techniques often fail for large and complex datasets, and connectomics researchers may spend weeks or months manually tracing neurons using 2D image stacks. We present a design study of a new virtual reality (VR) system, developed in collaboration with trained neuroanatomists, to trace neurons in microscope scans of the visual cortex of primates. We hypothesize that using consumer-grade VR technology to interact with neurons directly in 3D will help neuroscientists better resolve complex cases and enable them to trace neurons faster and with less physical and mental strain. We discuss both the design process and technical challenges in developing an interactive system to navigate and manipulate terabyte-sized image volumes in VR. Using a number of different datasets, we demonstrate that, compared to widely used commercial software, consumer-grade VR presents a promising alternative for scientists.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

WE-D-BRD-01: New Linac Designs for MR-Guided Therapy Systems

The advantages that make MR highly desirable for in-room treatment guidance, i.e. soft-tissue visualization and physiological assessment of healthy/tumor tissues, are largely recognized in the research community. However, the MR absorption in practical clinical workflows is still hindered by lack of sufficient technological infrastructure. Recent advances have been made towards filling that gap such as the development of integrated therapy systems relying on an MR scanner and a radiation source (linac, Co-60) and/or brachytherapy. The session is intended to present new efforts and methods aimed at facilitating the adoption of MR guidance for treatment delivery. Specifically, the discussion will focus on a) linac designs for reduced footprint and seamless integration with MR/linac systems, b) tracking coils for brachytherapy applications, and c) procedures for the commissioning and monitoring of MR and MR/linac performance. Learning Objectives: Understand limitations and proposed solutions for linac designs and associated integration with MR/linac systems; Understand current issues with MR-guided brachytherapy procedures Understand the issues and needs for new MR commissioning and QC. License agreement with Modus Medical Devices to develop a phantom for the quantification of MR image distortions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Probabilistic Deliverability Assessment of Distributed Energy Resources via Scenario-Based AC Optimal Power Flow

As electric grids decarbonize and distributed energy resources (DERs) become increasingly prevalent, interconnection assessments must evolve to reflect operational variability and control flexibility. This paper highlights key modeling limitations observed in practice and reviews approaches for modeling uncertainty. It then introduces a Probabilistic Deliverability Assessment (PDA) framework designed to complement and extend existing procedures. The framework integrates scenario-based AC optimal power flow (AC OPF), corrective dispatch, and optional multi-temporal constraints. Together, these form a structured methodology for quantifying DER utilization, deliverability, and reliability under uncertainty in load, generation, and topology. Outputs include interpretable metrics with confidence intervals that inform siting decisions and evaluate compliance with reliability thresholds across sampled operating conditions. A case study on Puerto Rico’s publicly available bulk power system model demonstrates the framework’s application using minimal input data, consistent with current interconnection practice. Across staged fossil generation retirements, the PDA identifies high-value DER sites and regions requiring additional reactive power support. Results are presented through mean dispatch signals, reliability metrics, and geospatial visualizations, demonstrating how the framework provides transparent, data-driven siting recommendations. The framework’s modular design supports incremental adoption within existing workflows, encouraging broader use of AC OPF in interconnection and planning contexts.

14 SOLAR ENERGY↗
DOE OSTI2020

In situ multimodal imaging for nanoscale visualization of tribofilm formation

A third of the energy from fuel combustion in passenger car gasoline engines is lost due to friction. Carefully designed engine lubricants can recover some of these losses by reducing friction and wear by forming a nanometer-scale chemico-physico tribofilm between surfaces. Accordingly, attention has focused on developing oil formulations that form low-friction tribofilms. However, analyses of resultant tribofilms are typically conducted after tribo-tests with conventional characterization tools and do not offer insights into tribofilm formation and evolution, precluding information critical to tuning tribofilm properties. In this work, we developed a unique multimodal methodology based on Atomic Force Microscopy (AFM) with local probe heating for in situ tribological studies that activates friction modifiers and simultaneously captures the evolution of friction and surface roughness, with nanometer resolution. As a platform to demonstrate the ability of this methodology to visualize dynamics of tribofilm formation in situ, we apply it to molybdenum-based friction modifiers to distinguish key factors in their functionality and correlate nanoscale AFM and Friction Force Microscopy data to bench tribo-tests used in the industry. To decode the formation mechanisms observed in situ and underlying chemistry of tribofilms, we performed ab initio Molecular Dynamics (AIMD) simulations at comparable conditions. AIMD simulations confirmed both nanoscale and bench tribo-test results and showed deviations in molecular organization in tribofilms that are formed from different molybdenum-based friction modifiers that corroborates with surface functionality. With this innovative methodology, we demonstrate proof-of-principle in situ formation of molybdenum-based tribofilms directly on steel surfaces that could be applied generally to studying tribofilm formation.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Database development and exploration of process–microstructure relationships using variational autoencoders

The paper demonstrates graphical representation of a large database containing process–microstructure relationships using an unsupervised machine learning algorithm. Correlating microstructural features to processing is an essential first step to answer the difficult problem of process sequence design. Here, a large database of 346,200 orientation distribution functions resulting from a variety of process sequences is constructed, where each sequence comprises up to four stages of tension, compression and rolling along different directions in various permutations. This open-source database is constructed for collaborative development of process design algorithms. The paper demonstrates a novel application of the large database: graphical representation of texture–process relationships. A variational autoencoder is used to reduce the entire database to a two dimensional latent space where variations in processes and properties can be visualized. Using proximity analysis in this latent space, we can quickly unearth multiple process solutions to the problem of texture or property design.

36 MATERIALS SCIENCE↗
DOE OSTI2017

CDS Re Mix

CDS (Change Detection Systems) is a mechanism for rapid visual analysis using complex image alignment algorithms. CDS is controlled with a simple interface that has been designed for use for anyone that can operate a digital camera. A challenge of complex industrial systems like nuclear power plants is to accurately identify changes in systems, structures and components that may critically impact the operation of the facility. CDS can provide a means of early intervention before the issues evolve into safety and production challenges.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

A Visual Analytic Platform for Interactive Validation of Human Mobility Simulations

Human mobility insights guide domain experts in an array of decisions, including critical infrastructure design, disaster response, epidemic modeling, national security, and policy making. Due to the inherent noise and privacy concerns in real-world individual-level mobility data, it is often preferred to leverage simulators that generate synthetic mobility data instead. However, it is critical to inspect and validate the output of such simulators to ensure the synthetic data is aligned with the characteristics of the population and the area of interest known to domain experts. While there exist many quantitative approaches for validating synthetic data, we argue it is also important to also validate such data qualitatively to capture aspects that are known to domain experts but difficult to quantify. In this work, we demonstrate a visual analytic platform that empowers domain experts to interact with their simulation outputs along spatial and temporal dimensions. By augmenting automated techniques and human skills, our visual analytic platform is a step towards interactive capabilities for model steering and quality control of mobility simulators.

Monadjemi, Shayan↗