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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Status, Challenges, and Plans for Consistent Modeling and Evaluation of Fission Data: Nubar, PFNS, and FPY [Slides]

This presentation discusses the importance of consistent evaluations for fission observables. Currently, prompt fission quantities (e.g., neutron multiplicity, neutron energy spectrum, and fission product yields) are evaluated independently of one another, either with separate models or data-only/non-model evaluations (few – if any – shared model inputs) and inconsistencies can arise in evaluated data (e.g. NSE 190, 258 (2018)). They have found that consistent, model-based evaluations lead to more physical constraints on free parameters in the model, more robust predictions for other observables and other isotopes, that there are correlations between the uncertainties on different observables, and that uncertainties can be propagated to unmeasured quantities. They are working on developing models to the point where fission observables are calculated at the quality needed for an evaluation. They are striving to consistently calculate fission observables, such as $\bar{v}$, PFNS, and FPY, to a quality suitable for an evaluation. Current evaluations for fission observables use separate models for each observable (with minimal shared input) or are purely data driven. LANL models, such as the Monte Carlo CGMF and deterministic BeoH, have different strengths; the similar fission fragment initial conditions and decay models leads to consistency between the two codes (FPY can be connected to $\bar{v}$ and PFNS, even when calculated by different codes). Work is underway by Lovell to optimize the models and Neudecker is working to perform detailed uncertainty quantification. The PFNS, in particular, presents a significant challenge.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Recent Developments in the R-Matrix Code SAMMY [Slides]

This presentation covers recent developments in the R-Matrix Code SAMMY. The presentation starts with a discussion around SAMMY releases. Secondly it provides updates in the program flow. The presentation concludes with goals and achievements in the modernization efforts.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Proton Beam Dynamics in Bare IOTA with Intense Space-Charge

We are commissioning a 2.5~MeV proton beam for the Integrable Optics Test Accelerator at Fermilab, allowing experiments in the strong space-charge regime with incoherent betatron tune shifts nearing 0.5. Accurate modelling of space-charge dynamics is vital for understanding planned experiments. We compare anticipated emittance growth and beam loss in the bare IOTA configuration using transverse space-charge models in Xsuite, PyORBIT, and MAD-X simulation codes. Our findings reveal agreement within 30\% in core phase-space density predictions up to 100~synchrotron periods at moderate beam currents, while tail distributions and beam loss show significant differences.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Malware analysis and recovery

A system and method detects malware by processing notifications from an intrusion detection system and baseline snapshots from an image capture utility. The image capture utility constructs an image of the suspected malware intrusion and links the suspected malware intrusion to the baseline snapshots. The system and method propagates the image of the suspected malware intrusion across multiple networks before it distinguishes malicious code, device state, and files from benign code, device state, and files. Some systems and methods include a malware recovery system that executes machine learning instructions and heuristics to revert a client and/or a remote server to one or more baseline snapshots.

Smith, Jared M.↗
DOE OSTI2024

Developing Platinum-Group-Metal-Free Catalysts for Oxygen Reduction Reaction in Acid: Beyond the Single Metal Site

This project is to develop M (x) -N-C catalysts with dense multiple metal center (MMC) sites to meet the DOE 2025 activity target of 0.044 mA/cm 2 at 0.9 V IR-free ., as well as other goals such as durability. We have made important contributions to both catalyst development and fundamental understandings of the active sites in M-N-C catalysts in this project. We successfully made M (x) -N-C catalysts with some multiple metal center (MMC) sites by combining ionothermal carbonization with chemical vapor deposition (CVD). These catalysts, however, are not as active as the most active single-atom Fe-N-C catalysts made by the similar CVD process, owing likely to the low site density and the presence of inorganic Fe species such as iron carbides and nanoparticles. The most significant accomplishments we achieved in this project are: (1) we unraveled the formation pathway of Fe-N 4 sites during pyrolysis step-by-step and identified the trans-metalation mechanism, in collaboration with Deborah Myers and her colleagues at Argonne National Laboratory (ANL); (2) inspired by this finding, we pioneered the CVD synthesis of M-N-C catalysts (M = Mn, Fe, and Co), in which the Fe-N-C catalyst by CVD demonstrated an ORR activity of 33 mA/cm 2 at 0.9 V in H 2 -O 2 proton exchange membrane fuel cells (PEMFCs), very close to the ultimate goal of 35 mA/cm 2 of our project. This catalyst is the first Fe-N-C catalyst that contains only D1 sites without the D2 sites; whereas D1 and D2 sites have been always identified by Mossbauer in previous Fe-N-C catalysts. This finding helps to understand what the D1 and D2 sites are and their roles in catalyzing the ORR. (3) by improving the mass transport of the carbon matrix prior to the CVD process, the revised Fe-N-C catalyst made by CVD delivered a maximum power density of 0.53 W/cm 2 in H 2 -air PEMFCs. The improvement strategy was partly inspired by the computational modeling work by Adam Weber from LBNL, the Co-PI of this project, by developing, coding, and exercising a continuum level model of transport phenomena within a PGM-free catalyst layer. The model demonstrated that local resistances combined with limited site density of the PGM-free catalyst can result in limiting currents and poor polarization performance. The model also gave design guidance for impact of ECSA and overall catalyst-layer thickness. However, both Fe-N-C and Co-N-C catalysts developed by CVD showed poor durability in PEMFCS, in comparison with the traditional M-N-C catalysts synthesized via regular pyrolysis process. Consequently, we did not achieve the proposed durability targets. Despite so, we believe the FeNC-CVD catalysts with the poor durability and D1 sites only provides an excellent platform to understand the degradation mechanism of Fe-N-C in PEMFCs, the most important challenge in the development of M-N-C catalysts.

08 HYDROGEN↗
DOE OSTI2020

Review of the first charged-particle transport coefficient comparison workshop

We present the results of the first Charged-Particle Transport Coefficient Code Comparison Workshop, which was held in Albuquerque, NM October 4–6, 2016. In this first workshop, scientists from eight institutions and four countries gathered to compare calculations of transport coefficients including thermal and electrical conduction, electron–ion coupling, inter-ion diffusion, ion viscosity, and charged particle stopping powers. In this paper, we give general background on Coulomb coupling and computational expense, review where some transport coefficients appear in hydrodynamic equations, and present the submitted data. Large variations are found when either the relevant Coulomb coupling parameter is large or computational expense causes difficulties. Understanding the general accuracy and uncertainty associated with such transport coefficients is important for quantifying errors in hydrodynamic simulations of inertial confinement fusion and high-energy density experiments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Machine learning for photovoltaic single axis tracker fault detection and classification

More than 81% of the annual capacity of utility-scale photovoltaic (PV) power plants in the U.S. use single-axis trackers (SATs) due to SATs delivering 4% in capacity factor on average over fixed-array systems. However, SATs are subject to faults, such as software misconfigurations and mechanical failures, resulting in suboptimal tracking. If left undetected, the overall power yield of the PV power plant is reduced significantly. Minimizing downtime and ensuring efficient operation of SATs requires robust detection and diagnosis mechanisms for SAT faults. We present a machine learning framework for implementing real-time SAT fault detection and classification. Our implementation of the proposed framework reliably identifies measurements taken from a test PV system undergoing emulated SAT faults relative to state-of-the-art algorithms and produces nearly zero false positives on our testing days. Code and data are available at https://pvpmc.sandia.gov/tools.

Fault classification↗
DOE OSTI2022

Corrosion of 316H stainless steel in flowing FLiNaK salt

In this report type 316H stainless steel samples were exposed to flowing FLiNaK salt for 1000 h in a monometallic thermal convection loop (TCL) with a maximum temperature of 650 °C and a minimum of 540 °C. Samples in the hottest part of the TCL lost mass, with a maximum mass loss of 1.4 mg/cm 2 , while samples in the coldest parts of the TCL gained mass, with a maximum mass gain of 1.0 mg/cm 2 . Analysis of the samples that gained mass showed an Fe-rich layer on the sample surfaces, indicating that Fe, not Cr, was the primary deposition product in the TCL. Cr loss was apparent to a depth of ~5 µm in the hot leg. Post-exposure analysis of the salt showed major increases in the Cr, Fe, and Mn contents. The TCL was modeled using the TRANSFORM code. Modeled values matched the experimental temperature measurements showing that TRANSFORM is capable of accurately simulating the TCL conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2024

To Exascale and Beyond—The Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM), a Performance Portable Global Atmosphere Model for Cloud-Resolving Scales

The new generation of heterogeneous CPU/GPU computer systems offer much greater computational performance but are not yet widely used for climate modeling. One reason for this is that traditional climate models were written before GPUs were available and would require an extensive overhaul to run on these new machines. In addition, even conventional “high–resolution” simulations don't currently provide enough parallel work to keep GPUs busy, so the benefits of such overhaul would be limited for the types of simulations climate scientists are accustomed to. The vision of the Simple Cloud-Resolving Energy Exascale Earth System (E3SM) Atmosphere Model (SCREAM) project is to create a global atmospheric model with the architecture to efficiently use GPUs and horizontal resolution sufficient to fully take advantage of GPU parallelism. After 5 years of model development, SCREAM is finally ready for use. In this paper, we describe the design of this new code, its performance on both CPU and heterogeneous machines, and its ability to simulate real-world climate via a set of four 40 day simulations covering all 4 seasons of the year.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Disentangling multiple scattering with deep learning: application to strain mapping from electron diffraction patterns

Abstract A fast, robust pipeline for strain mapping of crystalline materials is important for many technological applications. Scanning electron nanodiffraction allows us to calculate strain maps with high accuracy and spatial resolutions, but this technique is limited when the electron beam undergoes multiple scattering. Deep-learning methods have the potential to invert these complex signals, but require a large number of training examples. We implement a Fourier space, complex-valued deep-neural network, FCU-Net, to invert highly nonlinear electron diffraction patterns into the corresponding quantitative structure factor images. FCU-Net was trained using over 200,000 unique simulated dynamical diffraction patterns from different combinations of crystal structures, orientations, thicknesses, and microscope parameters, which are augmented with experimental artifacts. We evaluated FCU-Net against simulated and experimental datasets, where it substantially outperforms conventional analysis methods. Our code, models, and training library are open-source and may be adapted to different diffraction measurement problems.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Statistical data analysis of x-ray spectroscopy data enabled by neural network accelerated Bayesian inference

Bayesian inference applied to x-ray spectroscopy data analysis enables uncertainty quantification necessary to rigorously test theoretical models. However, when comparing to data, detailed atomic physics and radiation transfer calculations of x-ray emission from non-uniform plasma conditions are typically too slow to be performed in line with statistical sampling methods, such as Markov Chain Monte Carlo sampling. Furthermore, differences in transition energies and x-ray opacities often make direct comparisons between simulated and measured spectra unreliable. Here, we present a spectral decomposition method that allows for corrections to line positions and bound–bound opacities to best fit experimental data, with the goal of providing quantitative feedback to improve the underlying theoretical models and guide future experiments. In this work, we use a neural network (NN) surrogate model to replace spectral calculations of isobaric hot-spots created in Kr-doped implosions at the National Ignition Facility. The NN was trained on calculations of x-ray spectra using an isobaric hot-spot model post-processed with Cretin, a multi-species atomic kinetics and radiation code. The speedup provided by the NN model to generate x-ray emission spectra enables statistical analysis of parameterized models with sufficient detail to accurately represent the physical system and extract the plasma parameters of interest.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

MHD-induced beta limits in the Large Helical Device

Using the extended-magnetohydrodynamics code, M3D-C1, we perform a systematic numerical study of the effect of externally applied heating on the achievable plasma beta in a ten field-period heliotron. Heat sources of varying intensity are applied to a vacuum magnetic field that is representative of the standard configuration of the Large Helical Device, with R 0 = 3.66 m, where R 0 is the radial position of the magnetic axis in vacuum. As the system is driven to a state that is unstable to low-n magnetohydrodynamic (MHD) modes, nonlinear mode interactions lead to the formation of chaotic magnetic fields. With sufficiently strong heating, a collapse of the electron temperature profile is observed. This demonstrates the necessity of simulating the self-consistent evolution of plasma profiles, without imposing assumptions on the structure of the magnetic field, to accurately determine transport properties in stellarator plasmas. It also highlights the value of these advanced simulation capabilities for accelerating the development of high-performance stellarator operating scenarios.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Progress in modelling fast-ion D-alpha spectra and neutral particle analyzer fluxes using FIDASIM

FIDASIM is a code that models signals produced by charge-exchange reactions between neutrals and ions (both fast and thermal) in magnetically confined plasmas. With the ion distribution function as input, the code predicts the efflux to a neutral particle analyzer diagnostic and the photon radiance of Balmer-alpha light to a fast-ion D α diagnostic, in addition to many other related quantities. A new, parallelized version of the Monte Carlo code FIDASIM has been developed in Fortran90 that is substantially faster than the original interactive data language version. Modified algorithms include more accurate treatments of the time dependent collisional-radiative equations that describe neutral energy levels, of the cloud of ‘halo’ neutrals that surround the injected neutral beam, and of finite Larmor radius effects. Enhanced physics capabilities include modelling ‘passive’ signals from cold edge neutrals, the ability to treat general three-dimensional magnetic confinement configurations, and calculations of diagnostic-specific weight functions that enable tomographic reconstructions of the fast-ion distribution function. Neutral beam attenuation, beam emission, and fast-ion birth profiles are also modelled. Finally, the new algorithms have been successfully validated against experimental data and new features have been tested through benchmarks between two independently developed versions of the code.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Generation of meter-scale hydrogen plasmas and efficient, pump-depletion-limited wakefield excitation using 10 GeV electron bunches

High repetition rates and efficient energy transfer to the accelerating beam are important for a future linear collider based on the beam-driven plasma wakefield acceleration scheme (PWFA-LC). This paper reports the first results from the Plasma Wakefield Acceleration Collaboration (E300) that are beginning to address both of these issues using the recently commissioned FACET-II facility at SLAC national accelerator laboratory. Here we have generated meter-scale hydrogen plasmas using time-structured 10 GeV electron bunches from FACET-II, which hold the promise of dramatically increasing the repetition rate of PWFA by rapidly replenishing the gas between each shot compared to the hitherto used lithium plasmas that operate at 1–10 Hz. Furthermore, we have excited wakes in such plasmas that are suitable for high gradient particle acceleration with high drive-bunch to wake energy transfer efficiency- a first step in achieving a high overall energy transfer efficiency. We have done this by using time-structured electron drive bunches that typically have one or more ultra-high current (> 30 kA) femtosecond spike(s) superimposed on a longer (~0.4 ps) lower current (< 10 kA) bunch structure. The first spike effectively field-ionizes the gas and produces a meter-scale (30–160 cm) plasma, whereas the subsequent beam charge creates a wake. The length and amplitude of the wake depends on the longitudinal current profile of the bunch and plasma density. We find that the onset of pump depletion, when some of the drive beam electrons are nearly fully depleted of their energy, occurs for hydrogen pressure ≥ 1.5Torr. We also show that some electrons in the rear of the bunch can gain several GeV energies from the wake. These results are reproduced by particle-in-cell simulations using the QPAD code. At a pressure of ~2Torr, simulation results and experimental data show that the beam transfers about 60% of its energy to the wake.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Advantages and Limits of Metagenomic Assembly and Binning of a Giant Virus

ABSTRACT Giant viruses have large genomes, often within the size range of cellular organisms. This distinguishes them from most other viruses and demands additional effort for the successful recovery of their genomes from environmental sequence data. Here, we tested the performance of genome-resolved metagenomics on a recently isolated giant virus, Fadolivirus, by spiking it into an environmental sample from which two other giant viruses were isolated. At high spike-in levels, metagenome assembly and binning led to the successful genomic recovery of Fadolivirus from the sample. A complementary survey of the major capsid protein indicated the presence of other giant viruses in the sample matrix but did not detect the two isolated from this sample. Our results indicate that genome-resolved metagenomics is a valid approach for the recovery of near-complete giant virus genomes given that sufficient clonal particles are present. However, our data also underline that a vast majority of giant viruses remain currently undetected, even in an era of terabase-scale metagenomics. IMPORTANCE The discovery of large and giant nucleocytoplasmic large DNA viruses (NCLDV) with genomes in the megabase range and equipped with a wide variety of features typically associated with cellular organisms was one of the most unexpected, intriguing, and spectacular breakthroughs in virology. Recent studies suggest that these viruses are highly abundant in the oceans, freshwater, and soil, impact the biology and ecology of their eukaryotic hosts, and ultimately affect global nutrient cycles. Genome-resolved metagenomics is becoming an increasingly popular tool to assess the diversity and coding potential of giant viruses, but this approach is currently lacking validation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

HVAC System Performance for Energy Codes (Technical Brief)

The prescriptive path is likely the most widely used approach for commercial code compliance in the United States. Though easy to implement, the prescriptive approach does not discriminate between high-performing and poorly performing heating, ventilation, air conditioning (HVAC) system configurations that are both minimally compliant. To meet aggressive energy and carbon reduction goals, energy codes will need to transition from prescriptive to performance-based approaches, a transition that is riddled with several challenges. HVAC System Performance is a discipline performance path and provides a simpler solution to HVAC system evaluation compared to whole building performance, while keeping tradeoffs limited to specific building systems. The Total System Performance Ratio (TSPR) is a metric for evaluation of overall system efficiency instead of individual component efficiency, a solution that could also eventually facilitate the transition to a 100% performance-based code structure. TSPR is a ratio that compares the annual heating and cooling load of a building to the annual energy consumed by the building’s HVAC system. A web-based calculation tool has been developed for determining a building’s TSPR. Already incorporated into the 2018 Washington State Energy Code, this approach has also been evaluated by the ASHRAE Standard 90.1 Project Committee and has the potential to provide a comprehensive performance-based approach for HVAC system evaluation and analysis

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Development of Plant Reload Optimization Framework Capabilities for Core Design and Fuel Performance Analysis

The United States (U.S.) nuclear industry faces a challenge in maintaining required levels of safety while ensuring economic competitiveness to stay in business. Safety remains a key parameter for all aspects of light water reactor (LWR) nuclear power plant (NPP) operations. Safety can become more economical by using a risk-informed ecosystem, such as the one being developed by the Risk-Informed Systems Analysis (RISA) Pathway under the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program. The LWRS Program promotes a wide range of research and development activities with the goal of maximizing both the safety and economic efficiency of NPPs through improved scientific understanding, especially given many plants are now considering second license renewals. The RISA Pathway has two main goals: (1) deploy methodologies and technologies that better represent safety margins and cost and safety factors and (2) develop advanced applications that enable cost-effective plant operation. The Plant Reload Optimization Platform development project aims to build a reactor core design tool that includes reactor safety and fuel performance analyses, and also uses artificial intelligence to support optimization of core design solutions. This report summarizes Fiscal Year 2022 (FY-22) activity in platform capability developments in RAVEN. This platform performs simulations using industry codes for core design (i.e., PARCS) and fuel performance (i.e., TRANSURANUS) which will allow expansion of the capabilities to include advanced fuel designs such as accident-tolerant fuel (ATF)s with high burnup.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗