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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Ability to Simulate Absorption and Melt Pool Dynamics for Laser Melting of Bare Aluminum Plate: Results and Insights from the 2022 Asynchronous AM-Bench Challenge

The 2022 Asynchronous AM-Bench challenge was designed to test the ability of simulations to accurately predict laser power absorption as well as various melt pool behaviors (width, depth, and solidification) during laser melting of solid metal during stationary and scanned laser illumination. In this challenge, participants were asked to predict a series of experimental outcomes. Experimental data were obtained from a series of experiments performed at the Advanced Photon Source at Argonne National Laboratories in 2019. These experiments combined integrating sphere radiometry with high-speed X-ray imaging, allowing for the simultaneous recording of absolute laser power absorption and two-dimensional, projected images of the melt pool. All challenge problems were based on experiments using bare aluminum solid metal. Participants were provided with pertinent experimental information like laser power, scan speed, laser spot size, and material composition. Additionally, participants were given absorptance and X-ray imaging data from stationary and scanned laser experiments on solid Ti–6Al–4V that could be used for testing their models before attempting challenge problems. In total, this challenge received 56 submissions from eight different research groups for eight individual challenge problems. The data for this challenge, and associated information, are available for download from the NIST Public Data Repository. This paper summarizes the results from the 2022 Asynchronous AM-Bench challenge as well as discusses the lessons learned to help inform future challenges.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Flattening of the tokamak current profile by a fast magnetic reconnection with implications for the solar corona

During tokamak disruptions, the profile of the net parallel current is observed to flatten on a time scale that is so fast that it must be due to a fast magnetic reconnection. After a fast magnetic reconnection has broken magnetic surfaces, a single magnetic field line covers an entire volume and not just a magnetic surface. The current profile, given by K ≡ μ 0 j | | / B , relaxes to a constant within that volume by Alfven waves propagating along the chaotic magnetic field lines. The time scale for this relaxation determines the commonly observed disruption phenomena of a current spike and a sudden drop in the plasma internal inductance. An efficient method for studying this relaxation is derived, which allows a better understanding of the information encoded in the current spike and the associated sudden drop in the plasma internal inductance. Implications for coronal heating are also discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1989

Finite solid representation of robot manipulation in three-dimensional geometric reasoning

Intelligence robotic system design involves sensor allocation and sensor data fusion. In the field of geometric reasoning, a fast and effective representation method is needed to determine the physical dimensions of the manipulator as well as the motion environment in sufficient detail. Due to the capability of current sensor technology, the integrity of the sensor information is location dependent and point-wise, line-wise and plane-wise in nature. In order to maneuver the robot by reasoning the environment, there is a minimum requirement of prior information for integrating the allocated sensor feedback. Some new theoretical developments of how to associate the number and the locations of the sensors with three-dimensional geometry of the robot and the motion environment is presented. The related collision avoidance problem (CAP) will be addressed as well.

Chen, Alexander Y. K.↗
NASA NTRS1992

Thermal and range fusion for a planetary rover

This paper describes how fusion between thermal and range imaging allows us to discriminate different types of materials in outdoor scenes. First, we analyze how pure vision segmentation algorithms applied to thermal images allow discriminating materials such as rock and sand. Second, we show how combining thermal and range information allows us to better discriminate rocks from sand. Third, as an application, we examine how an autonomous legged robot can use these techniques to explore other planets.

Caillas, Claude↗
NASA NTRS2002

Software for Partly Automated Recognition of Targets

The Feature Analyst is a computer program for assisted (partially automated) recognition of targets in images. This program was developed to accelerate the processing of high-resolution satellite image data for incorporation into geographic information systems (GIS). This program creates an advanced user interface that embeds proprietary machine-learning algorithms in commercial image-processing and GIS software. A human analyst provides samples of target features from multiple sets of data, then the software develops a data-fusion model that automatically extracts the remaining features from selected sets of data. The program thus leverages the natural ability of humans to recognize objects in complex scenes, without requiring the user to explain the human visual recognition process by means of lengthy software. Two major subprograms are the reactive agent and the thinking agent. The reactive agent strives to quickly learn the user's tendencies while the user is selecting targets and to increase the user's productivity by immediately suggesting the next set of pixels that the user may wish to select. The thinking agent utilizes all available resources, taking as much time as needed, to produce the most accurate autonomous feature-extraction model possible.

Opitz, David↗
NASA NTRS2003

Software for Partly Automated Recognition of Targets

The Feature Analyst is a computer program for assisted (partially automated) recognition of targets in images. This program was developed to accelerate the processing of high-resolution satellite image data for incorporation into geographic information systems (GIS). This program creates an advanced user interface that embeds proprietary machine-learning algorithms in commercial image-processing and GIS software. A human analyst provides samples of target features from multiple sets of data, then the software develops a data-fusion model that automatically extracts the remaining features from selected sets of data. The program thus leverages the natural ability of humans to recognize objects in complex scenes, without requiring the user to explain the human visual recognition process by means of lengthy software. Two major subprograms are the reactive agent and the thinking agent. The reactive agent strives to quickly learn the user s tendencies while the user is selecting targets and to increase the user s productivity by immediately suggesting the next set of pixels that the user may wish to select. The thinking agent utilizes all available resources, taking as much time as needed, to produce the most accurate autonomous feature-extraction model possible.

Opitz, David↗
DOE OSTI2024

Challenging Common Assumptions of Thick-Wall Chamber Dynamics in Inertial Fusion Systems using MOOSE

As an increasing number of companies look toward commercial Inertial Fusion Energy (IFE) designs, there is a pressing need to understand the physics of thick-wall chamber gas dynamics. The thick liquid wall approach implements a renewable wall to mitigate the fusion target emissions, thereby reducing the radiation damage rate and significantly extending the lifetime of chamber structures, leading to increased plant availability and reduced waste streams in comparison to dry wall chamber designs. It is necessary, however, to assess the critical performance and safety aspects of these systems. For example, it is crucial to predict (1) where the mass ablated from the liquid walls will vent, which determines the placement of condensing surfaces; (2) debris propagation up the beam lines, which provides essential information for design and protection requirements; (3) peak pressures and impulse on chamber walls, which affect chamber structural design; and (4) momentum transfer to the liquid jets, which constrains the shape and positioning of the jets. In turn, the chamber design and its liquid walls affect shielding requirements, material activation, and tritium fuel cycle. Currently available simulation tools, however, are unable to accurately capture key thick-wall chamber dynamics. Significant assumptions are often made to simplify the system and reduce computational cost and modeling capability needs, but the impact of these assumptions on simulation predictions has not been evaluated. For example, no three-dimensional simulations can be found in the open literature to evaluate gas venting and momentum transfer to the jets with simulations using two-dimensional domains to represent complex three-dimensional geometries. Moreover, limited studies have been dedicated to jet breakup due to both turbulence and neutron heating, and no studies have been found that evaluate how jet breakup can impact shock-jet interaction. Furthermore, effects of radiative heat transfer have rarely been included for the hydrodynamic phase of shock propagation, and integration of proper equations of state in shock dynamics codes has been mostly exploratory. In this study, we use the flexible, high-fidelity Multiphysics Object-Oriented Simulation Environment (MOOSE) to model these complex phenomena and inform design and safety studies. Capabilities to model thick-wall chamber gas dynamics are being developed, and the impact of the assumptions listed above (i.e., two-dimensional vs three-dimensional, absence of jet breakout, no radiative heat transfer, and ideal gas behavior) are being quantified.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

A two-stage optical fusion framework for wildfire severity mapping across the conterminous United States

Accurate wildfire severity mapping (WSM) is essential for post-fire recovery planning, erosion risk assessment, ecosystem monitoring, and disaster risk reduction. Although Landsat and Sentinel optical imagery have been widely used for burn severity assessment, the added value of fusing multiple optical sensors has not been sufficiently quantified across diverse fire events, particularly since the launch of Landsat-9. This study evaluates whether multisensor optical fusion improves wildfire severity mapping relative to single-sensor baselines using Sentinel-2, Landsat-8, and Landsat-9 imagery across 40 wildfire events in the conterminous United States. We tested a two-stage fusion framework that combines feature-level fusion with pixel-level dimensionality reduction. First, feature-level fused datasets were created through early fusion by combining standardized post-fire bands from each sensor into a single predictor stack. Both raw reflectance bands and pairwise spectral transforms were retained to capture within- and cross-sensor spectral interactions. Second, Linear Discriminant Analysis was applied to both single-sensor and fused datasets to produce comparable low-dimensional feature spaces. Six machine-learning classifiers were then used to benchmark model performance with repeated spatially buffered train–test splits. Results show that Landsat-9 was the strongest single-sensor baseline. Among the fusion strategies, Sentinel-2 + Landsat-9 produced the most consistent improvement and reduced performance variability. Landscape-condition analysis further showed that this fusion was most beneficial in shrubland-dominated and high-terrain fires, where it achieved the highest overall mean accuracy and the fewest failures. In contrast, its benefits were less reliable in evergreen forests, mixed vegetation, and low- to moderate-elevation terrain. In operational settings, the Sentinel-2 + Landsat-9 configuration offers a practical solution for post-fire recovery planning, erosion-risk assessment, watershed management, and ecological monitoring when field observations are available and timely satellite-based information is needed.

Landsat↗
DOE OSTI2022

Analysis of limited coverage effects on areal density measurements in inertial confinement fusion implosions

Accurate diagnosis of areal density ($\textit{ρR}$) is critical for the inference of performance metrics in inertial confinement fusion implosions. One potential source of error in this diagnosis is the existence of low mode perturbations in the imploding target, which lead to asymmetries in the inference of the $\textit{ρR}$ from different lines of sight. Here, the error accrued as a result of limited coverage of the sphere due to a finite number of detectors is quantified, and the development of a forward scatter measurement from the OMEGA neutron time-of-flight detectors is motivated. In this work, a method by which the 1D-equivalent 4 π-averaged $\langleρR\rangle$ can be reconstructed, if accurate mode information can be diagnosed by other means, is validated.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Visualization and analysis of coupling between plasmas self-organization and plasma-induced fluid circulation in 1 atm DC glows with liquid anode

The physical processes prevailing when plasma contacts liquid water are poorly understood; however, it is this very interaction that is the basis of new, exciting technologies for water purification, the treatment of cancer and disease and the production of new, high value chemical products. A chief impediment to widespread application of plasmas for the aforementioned applications is scale up and cost. Here we investigate plasma induced flows which facilitate transport of reactivity from the plasma to liquid water at rates much faster than diffusion. We find that this plasma induced motion varies depending on whether or not the plasma is self organized. The insight from this work paves the way to a better understanding of transport and ultimately informing plasma treatment technologies on how to best optimize the rate at which processes such as plasma based water purification occurs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Turbulence characteristics and flow dynamics impacts on the H-mode transition in favourable magnetic geometry with lower power threshold

We report the L-H transition power threshold (P LH ) in favourable magnetic geometry (ion ∇B drift pointing towards X-point) is much lower than in the unfavourable magnetic geometry (ion ∇B drift pointing away from X-point) on multiple tokamaks. In a systematic experiment on DIII-D, the ion ∇B drift direction was changed continuously from the unfavourable to favourable configuration during plasma discharges. During such process, the input neutral beam power was kept constant at a value that was above P LH for favourable configuration, but lower than P LH for unfavourable configuration. Toroidal field and plasma current were also kept constant and there was little change in the edge electron density ne and electron temperature T e profiles. The density fluctuation amplitude was reduced approaching the transition, while a large increase of turbulence Reynolds stress and flow shear were simultaneously observed. The turbulence decorrelation rate was found to increase as the ion ∇B drift direction was moving towards the favourable configuration, but the flow shear also increased and exceeded the turbulence decorrelation rate. These measurements demonstrate an important correlation between turbulence and turbulence-driven flow and a lowering of PLH, provide insights into the underlying physics behind the hidden parameters and inform a more complete physics-based model of the L-H transition power threshold.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

On residual stress analysis and microstructural evolution for stainless steel type 304 spent nuclear fuel canisters weld joint: Numerical and experimental studies

Chloride-induced stress corrosion cracking (CISCC) in the weldments of austenitic stainless steel canisters is one of the primary safety concerns during the dry storage of used nuclear fuel at Independent Spent Fuel Storage Installations in coastal areas. In order to evaluate the CISCC behavior in the canister, a 3D sequentially coupled thermo-mechanical finite element model was built to simulate the residual stresses induced by two intersecting longitudinal and circumferential multi-pass welds in austenitic stainless steel mockup canister. Weld-induced residual stresses from simulation were in good agreement with the experimental measurement results by deep-hole drilling and contour methods. Through-wall high tensile axial and hoop stresses were observed in both the fusion zone and heat affected zone (HAZ) in the longitudinal and circumferential weld, respectively. On the other hand, the microstructure within the weldments of 304 stainless steel mockup was characterized using optical microscopy, scanning electron microscopy, electron back-scattered diffraction and energy dispersive X-ray spectroscopy methods. A few amount of MnS inclusions in both the base metal and HAZ, and a lot of (Mn,Si) x O y inclusions in the fusion zone were found. Meanwhile, there is some α'-martensite in the base metal, while the martensite was reversed in the HAZ. In the fusion zone, there is a lot of δ-ferrite. The martensite reversion phenomenon was also verified by the combination of Feritscope test and thermal simulation, which could predict a martensite reversion temperature as 400C°. The welding residual stresses and microstructure analysis results could offer the instructive information for the prediction of CISCC behavior of the spent nuclear fuel canisters.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A theoretical study on quasifission and fusion–fission processes in heavy-ion collisions

Despite recent advances and focus on rigorous uncertainty quantification for microscopic models of quantum many-body systems, the uncertainty on the dynamics of those systems has been underexplored. To address this, we have used time-dependent Hartree-Fock to examine the model uncertainty for a collection of low-energy, heavy-ion fusion reactions. Fusion reactions at near-barrier energies represent a rich test-bed for the dynamics of quantum many-body systems owing to the complex interplay of collective excitation, transfer, and static effects that determine the fusion probability of a given system. The model uncertainty is sizable for many of the systems studied and the primary contribution arises from static properties that are ill-constrained, such as the neutron radius of neutron-rich nuclei. These large uncertainties motivate the use of information from reactions to better constrain existing models and to infer static properties from reaction data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Influence of Process Parameter and Build Rate Variations on Defect Formation in Laser Powder Bed Fusion SS316L

Laser powder bed fusion (LPBF) is an additive manufacturing process that has gained interest for its material fabrication due to multiple advantages, such as the ability to print parts with small feature sizes, good mechanical properties, reduced material waste, etc. However, variations in the key process parameters in LPBF may result in the instantiation of porosity defects and variation in build rate. Particularly, volumetric energy density (VED) is a variable that encapsulates a number of those parameters and represents the amount of energy input from the laser source to the feedstock. VED has been traditionally used to inform the quality of the printed part but different values of VED are presented as optimal values for certain material systems. An optimal VED value can be maintained by changing the key process parameters so that various combinations yield a constant value. In this study, an optimal constant VED value is maintained while printing SS316L with variable key processing parameters. Porosity analysis is performed using optical microscopy, as well as X-ray computed tomography, to reveal the volume density and distribution of those pores. Two primary defect categories are identified, namely lack of fusion and porosity induced by balling defects. The findings indicate that, even at optimal VED, variations in process parameters can significantly influence defect type, underscoring the sensitivity of defect formation to the variation of these parameters. Furthermore, a minor change in the build rate, driven by adjustments in process parameters, was found to influence defect categories. These findings emphasize that fine tuning the process parameters and build rate is essential to minimize defects. Finally, fiducial marks have been identified as a source of unintentional porosity defects. These results enable the refinement of process parameters, ultimately optimizing LPBF to achieve enhanced material density and expedite the printing.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Nanowire implosion under laser amplified spontaneous emission pedestal irradiation

Nanowire array targets exhibit high optical absorption when interacting with short, intense laser pulses. This leads to an increased yield in the production of accelerated particles for a variety of applications. However, these interactions are sensitive to the laser prepulse and could be significantly affected. Here, we show that an array of aligned nanowires is imploded when irradiated by an Amplified Spontaneous Emission pedestal of a 1 PW laser with an intensity on the order of 10 11 W cm –2 . Using radiation hydrodynamics simulations, we demonstrate that the electron density profile is radially compressed at the tip by the rocket-like propulsion of the ablated plasma. The mass density compression increases up to 2.9x when a more dense nanowire array is used. This is due to the ablation pressure from the neighboring nanowires. These findings offer valuable information for selecting an appropriate target design for experiments aimed at enhancing production of accelerated particles.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Digital Twin Enabling Technologies for Online Condition Monitoring of Nuclear Power Plant Components

Online condition monitoring is an area of active research that may enable improved scheduling, maintenance, and safety of nuclear power plant components, reducing unnecessary derate while simultaneously improving operational capacity. Digital twins are one avenue to conduct online condition monitoring and are currently being explored by national laboratories and universities alike. Digital twins for online condition monitoring are, in essence, state concurrent models that emulate a physical process which predicts a parameter and compares it against a measured value. However, digital twins may also provide additional insights by combining and interpreting various sources of information. These insights may be used for preventative maintenance scheduling optimization or early fault detection and are projected to be valuable for meeting requirements under 10 CFR 50.55a. However, digital twin technologies are still under significant development; quantifying model uncertainties, improving unique fault identification, and multimodal sensor fusion are some areas under investigation. Therefore, in this work, we discuss and review the various enabling technologies, in the form of advanced sensors, instrumentation, and modelling methods, that may be used to implement and enhance digital twins for online condition monitoring. A potential use case for pump-motors is presented to demonstrate how these various pieces of enabling digital twin technologies may integrated together for online condition monitoring. Challenges and opportunities associated with the pump-motor digital twin enabling technologies are also identified and discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Digital-Twin-Enabling Technologies for Online Condition Monitoring of Nuclear Power Plant Components

Online condition monitoring is an area of active research that may enable improved scheduling, maintenance, and safety of nuclear power plant components, reducing unnecessary derates while simultaneously improving operational capacity. Digital twins are one avenue to conduct online condition monitoring and are currently being explored by national laboratories and universities alike. Digital twins for online condition monitoring are, in essence, state concurrent models that emulate a physical process which predicts a parameter and compares it against a measured value. However, digital twins may also provide additional insights by combining and interpreting various sources of information. These insights may be used for preventative maintenance scheduling optimization or early fault detection and are projected to be valuable for meeting requirements under 10 CFR 50.55a. However, digital twin technologies are still under significant development; quantifying model uncertainties, improving unique fault identification, and multimodal sensor fusion are some areas under investigation. Therefore, in this work, we discuss and review the various enabling technologies, in the form of advanced sensors, instrumentation, and modelling methods, that may be used to implement and enhance digital twins for online condition monitoring. A potential use case for pump-motors is presented to demonstrate how these various pieces of enabling digital twin technologies may integrated together for online condition monitoring. Challenges and opportunities associated with the pump-motor digital twin enabling technologies are also identified and discussed.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Self-consistent modeling of tokamak edge plasma transport with lithium sources

Magnetic confinement fusion devices require effective heat and particle exhaust solutions on the divertor plates to operate sustainably, especially under reactor-relevant conditions. Liquid lithium divertors have been proposed to address two major challenges: control of excessive heat flux to plasma-facing components through vapor shielding and minimization of core plasma contamination from impurities. The National Spherical Torus Experiment-Upgrade (NSTX-U) will explore lithium as a divertor material due to its potential to meet both objectives. We present a self-consistent coupling framework between the plasma boundary transport code UEDGE and the lithium wall transport code Wall–Li to evaluate the feasibility and operational limits of lithium-based divertors. The model aims to optimize lithium sourcing levels to prevent core plasma contamination via fuel dilution while ensuring divertor protection through vapor shielding. This integrated framework, applicable to any tokamak with lithium sources, dynamically adjusts lithium sourcing based on local plasma conditions and surface temperature. The coupled model is tested using NSTX-like geometry and plasma conditions to assess its performance and reliability. Wall–Li calculates lithium fluxes from plasma-facing components, incorporating physical sputtering, thermally enhanced sputtering, and evaporation driven by surface temperature and ion flux. These fluxes are reintroduced into UEDGE as neutral lithium atoms, enabling simulation of their transport and distribution within the plasma. UEDGE computes plasma and neutral transport, surface heat flux, and iteratively feeds this information back to Wall–Li. A small time step is employed to ensure numerical stability and convergence, enabling accurate simulations over typical tokamak discharge durations. This integrated modeling approach provides a robust tool for identifying operational regimes that balance effective lithium sourcing with minimal core plasma contamination, offering critical insights for optimizing lithium-based divertor systems in current and future fusion devices.

Magnetic confinement fusion↗